the interrelationships between organizational
TRANSCRIPT
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LSU Historical Dissertations and Theses Graduate School
1983
The Interrelationships Between OrganizationalCommunication, Organizational Climate, and JobSatisfaction in a Local Government Agency.William Chambliss Sharbrough IIILouisiana State University and Agricultural & Mechanical College
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Sharbrough, William Chambliss, III
THE INTERRELATIONSHIPS BETWEEN ORGANIZATIONAL COMMUNICATION, ORGANIZATIONAL CLIMATE, AND JOB SATISFACTION IN A LOCAL GOVERNM ENT AGENCY
The Louisiana State University and Agricultural and Mechanical Col. Ph.D. 1983
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THE INTERRELATIONSHIPS BETWEEN ORGANIZATIONAL COMMUNICATION, ORGANIZATIONAL CLIMATE, AND JOB SATISFACTION
IN A LOCAL GOVERNMENT AGENCY
A Dissertation
Submitted to the Graduate Faculty of the Louisiana State University and
Agricultural and Mechanical College in partial fulfillment of the
requirements for the degree of Doctor of Philosophy
in
The Department of Management
by ■William Chambliss Sharbrough III
B.S., Mississippi State University, 1972 M.B. A., Mississippi State University, 1975
May 19, 1983
PREFACE
This dissertation is essentially the result of a search for know
ledge about one of the most pervasive aspects of human life - communica
tion. In particular, this has been an effort to gain additional know
ledge about how communication in organizations relates to the concepts
of organizational climate and job satisfaction. This researcher's
journey in the quest for this additional knowledge has been long and
sometimes tedious, but in the end, it all seems worthwhile. Like all
planned learning experiences, I've not only learned about the subject of
this dissertation, but I've also learned much about human behavior, and
myself as well. With this as a background, the beginning of this
journey did not really begin in Baton Rouge, Louisiana, or Louisville,
Kentucky, but, to steal a line from one of my favorite movies, it began
in a place "...long ago, and far away." These next few pages attempt to
describe some of the important events and people I've encountered on
this journey.
This journey has been much more than just a quest for knowledge on
a particular subject. It has also been a quest for knowledge about
life. This journey has taken me from its beginning as a "small town
Mississippi boy" to its current shopping place, someone about to com
plete a Ph.D. The road has been long and winding. As I've wandered
down "life's highway" I haven't always known where I was going or what
the result of getting there would be. Many people deserve much more
than the thanks and recognition I can give for their support and under
standing as I've traveled this winding road.
First and foremost, I had the good fortune to be brought into the
world and reared under the loving guidance of my parents, Mr. and Mrs.
W. C. Sharbrough, Jr., of Holly Bluff, Mississippi. They imprinted me
with their strong moral values and gave me a healthy dose of protestant
work ethic. (Sometimes I'm not sure if the dose was as effective as it
should have been.) They always stood by me, allowing me the freedom to
fail as well as succeed in all the things I attempted. It was their
guidance and financial support that gave me the courage and self-
confidence to leave my home town and to grow into the person I've become.
The sometimes almost worshipful respect of my younger brother, Sam,
should not go unrecognized. We've had differences, as brothers will,
but we've learned from them and both are better people for the experi
ences we've shared.
After my parents, the next most important influence in my life and
career has been my partner and best friend in all I've achieved in the
academic world and as a father. We've come a long way down this road
together since that sunny, Spring day when we met at a college baseball
game. By now you should know that I am talking about my wife, Dana'.
Whenever I lost my confidence and direction she has had enough confi
dence in me to put up with me til I found my way, whatever that turned
out to be. We've been together for many miles in this journey: from
Starkville to Calhoun City, back to Starkville, on to Baton Rouge, and
now to Louisville. Surely the day we were married, she had no idea she
iii
would end up as the wife of a college professor. Later though, at leastl
she knew what I was getting us into, having been brought up the daughter
of a professor. No one could have worked harder and deserves more
thanks and recognition than Dana. She put up with me and put me through
seven years of graduate courses and four years of working on this
dissertation. She has also brought twin rays of sunshine into our lives
at the same time by having our twin sons. She should be getting a medal
as I finally walk up on that graduate platform. Is there such a thing
as a Put Hubby Through degree with highest honors? She surely deserves
one. Dana's love and support have gotten me through even the darkest of
times and I can never thank her enough for the part she’s played.
Most of my success is owed to my wife and parents, but my in-laws
have surely helped. Their support and encouragement has always been
there when I needed it. Also, they deserve credit for not panicking
when they found out I was taking their daughter on with me to a Ph.D.
program. After all, they knew too well what was involved. Kim, my
brother-in-law, has been a great friend and has provided a sense of
humor that has lightened my load many times during this journey toward
my degree.
But what of the academic path? How did the small-town boy who
thought he wanted to be an engineer, then a plant manager, then a young
executive, and finally a college professor end up where he did? My high
school and grammar school teachers surely had a hand in getting me this
far on my journey. The good, basic education they provided has been one
of my strong points and they deserve thanks for their efforts. I only
hope I have lived up to their expectations.
I suspect some thanks should go to those courses in a college
catalog that are never taught. I went into the M.B.A. program intent on
being a production manager, but the courses I wanted were not taught for
lack of staff. Instead, I ended up in Thad Green's Survey of Management
Topics class and his influence pushed me not only into the behavioral
area, but toward an interest in research as well. Paul Pietri deserves
a special place in my journey for stimulating my interest in communica
tion. He not only provided guidance in choosing a doctoral program, but
also wrote the most glowing recommendation I've ever seen. It was
difficult to live up to my advance billing at L.S.U.
When Dr. Pietri had guided me through his part of my journey into
higher education, he turned me over to a mentor who has become one of
the most important people in my life. His guidance and support have
been immeasurable. I am honored to have become one of "Lesikar's
students" in the area of business and organizational communication.
That places me in exclusive company, .fQr many of Dr. Lesikar's students
have achieved outstanding careers. He has helped me through many trying
times. Whenever I thought the walls were falling in and I would never
finish the program, a call to Dr. Lesikar would immediately brighten my
spirits and give me the resolve to keep pushing down the road. Dr.
Lesikar has always done more than required to help me out. First, after
retiring from L.S.U., he has remained as chairman of my graduate commit
tee. Then we broke new ground together by conducting an oral general
v
exam over the phone. He is willing to talk anytime, and to come toi
Baton Rouge from Texas when 1 need him. I’ll never he able to pay the
debt I owe you, Dr. Lesikar. I only hope I can continue to live up to
your expectations.
In this tale of travels down the "academic highway," I've come to
another important happening and group of people who deserve my thanks.
First, there is Dr. Jerry Wallin, who has so ably served as acting
chairman of my committee. Not just anyone could have done the kind of
job Dr. Wallin has done in guiding me toward completion of this final
task from its beginning to its end. Dr. 0. Jeff Harris has also stayed
the course and been willing to help in any way possible. To professors
Hair and Smeltzer goes a special thanks for joining the dissertation
process with it already in motion. They have provided support that
helped me when I was confused, and comments that have made this a better
dissertation. Professor Grimes, for coming on board in the last month,
also deserves recognition.
Then there are the friends and colleagues at the University of
Louisville who have contributed so greatly toward the end result of this
process. Mike Carrell stands out as the person who has helped the most
and deserves the most recognition. He was responsible for my coming to
Louisville in the first place. It was his contacts in local government
that made this project possible from its beginning. His support and
encouragement as the chairman of my department have been instrumental in
my completing this research effort. Most of all, Mike deserves recogni-
tion for being one of the best friends I've ever had. John Vahaly also
stands out. His "Dissertation in Progress" sign on my door spurred me
on down the road toward its end.
Sarah Hill deserves a special thank you for the long hours and
yeoman-like job she did in typing this work. Bob Gaines, my graduate
assistant, also deserves recognition for chasing down the odd article in
the library quickly and efficiently.
Many people have had a part in this dissertation and in guiding my
path along this journey. Two that did not provide the reason I started
this journey through academia, but are one of the most important reasons
I am completing it are my sons, Matthew and Geoffrey. Sons, your
arrival a little over two years ago probably slowed the journey down,
but you are worth it. I never thought being a father could be so much
fun; or provide such a responsibility to move on to another path in
life.
To all those numerous people who have shared a part in this journey
and have gone unmentioned, thank you. To the students that I may have
neglected in this last two weeks in the rush to get this work to Baton
Rouge on time, I apologize. As I've stated, many people have helped me
with this dissertation. They've done a good job, first motivating me to
work, and then providing the support to see it through. I feel that I
must get these people off the hook though, by saying that in the end,
the responsibility for the quality of this work is mine. Any errors or
omissions are my responsibility alone. At the same time, surely God's
help has been here when I needed Him, providing me with the strength tot
keep at it when I was ready to give up. His help is there for others as
well.
William C. Sharbrough III
TABLE OF CONTENTS
Page
PREFACE 11TABLE OF CONTENTS ixLIST OF TABLES xilABSTRACT xiii
CHAPTER I. ORIENTATION TO THE STUDY..................... 1Purpose of the Study................... 5Hypotheses to be Tested................. 11Justification for the Study............. 13Scope of the Study..................... 15Possible Limitations to the Study....... 15A Preview to the Findings............... 18
CHAPTER II. REVIEW OF THE PERTINENT LITERATURE............ 20Reviews of Organizational Communication. . . 20Reviews of Organizational Climate......... 21Reviews of Job Satisfaction............... 21Reviews of Interrelationships............. 23
Organizational Communication/Organizational ClimateRela t ionship..................... 24
Organizational Communication/JobSatisfaction Relationship .......... 31
Organizational Communication/Organizational Climate/JobSatisfaction Relationship .......... 37
Summary of the Literature............... 39
CHAPTER III. METHODOLOGY UTILIZED......................... 43Design of the Sample................... 43Instruments Utilized in Data Collection. . . 45
Communication Instrument........... 45Organizational Climate Instrument . . . 46Job Satisfaction Instrument .......... 47
Techniques of Data Analysis Utilized . . . . 50
CHAPTER IV. STATISTICAL ANALYSIS......................... 54Analysis of Hypothesis I ........ . . . . . 54Analysis of Hypothesis II............... 59
ix
Page
Analysis of Hypothesis I I I ................ 60Canonical Function I............ 62Canonical Function II .......... 64Redundancy Analysis .................. 66
Summary of Hypothesis III.................. 66Analysis of Hypothesis IV................... 68
Canonical Function 1............ 68Canonical Function II . ...... 70Redundancy Analysis ................... 71
Summary of Hypothesis I V ................... 71Analysis of Relationship of Demographics
to Climate, Communication, andSatisfaction ........................... 73
Demographics vs- OrganizationalClimate Relationship................ 74
Demographics vs. OrganizationalCommunication Relationship....... 75
Demographics vs. Job SatisfactionRelationship..................... 80
Summary of Analysis of Data............. 85
CHAPTER V. CONCLUSIONS AND RECOMMENDATIONS FORFURTHER STUDY ............................... 88
Organizational Climate Job SatisfactionRelationship ........................... 88
Organizational Communication Organizational Climate Relationship......... 91
Organizational Communication JobSatisfaction Relationship............. 97
Final Summary of Relationships.......... 101Further Limitations to the Study .......... 103Suggestions for Further Research .......... 104
BIBLIOGRAPHY .................................................. 109
APPENDICES
Appendix A ORGANIZATIONAL COMMUNICATION INSTRUMENT. . . 118Appendix B ORGANIZATIONAL CLIMATE INSTRUMENT.........124Appendix C JOB SATISFACTION INSTRUMENT...............128Appendix D COMPLETE QUESTIONNAIRE WITH COVER LETTER . . 132Appendix E SUMMARY OF DEMOGRAPHIC DATA...............145Appendix F COMPUTATION OF MINIMUM SAMPLE SIZE ........ 163Appendix G MEANS, STANDARD DEVIATIONS AND RELIABILITIES
OF THE VARIABLES AS REPORTED BY MUCHINSKY. 165Appendix H CANONICAL ANALYSIS COMPUTER PROGRAM OF
COMMUNICATION/CLIMATE/SATISFACTION RELATIONSHIP ........................... 167
x
Page
Appendix I CANONICAL ANALYSIS COMPUTER PROGRAM OFDEMOGRAPHICS/COMMUNICATION/CLIMATE/SATISFACTION RELATIONSHIP................... 182
Appendix J SCORING SHEETS AND NORMS FOR THE JOBDESCRIPTIVE INDEX...........................200
Appendix K PERMISSION LETTERS......................... 208
V I T A ........................................................... 213
APPROVAL FORMS ............................................... 215
xi
LIST OF TABLES
TABLE PAGE
I WORKING DEFINITIONS OF COMMUNICATION VARIABLES. . 48
II WORKING DEFINITIONS OF CLIMATE VARIABLES.... 49
III WORKING DEFINITIONS OF SATISFACTION VARIABLES . . 50
IV MEANS AND STANDARD DEVIATIONS OF VARIABLES. . . . 55
V CANONICAL ANALYSIS OF ORGANIZATIONAL CLIMATE/JOB SATISFACTION RELATIONSHIP......... 56
VI REDUNDANCY INDEX FOR ORGANIZATIONAL CLIMATE/JOB SATISFACTION CANONICAL ANALYSIS... 61
VII CANONICAL ANALYSIS OF ORGANIZATIONAL COMMUNICATION/ORGANIZATIONAL CLIMATE RELATIONSHIP........ 63
VIII REDUNDANCY INDEX FOR ORGANIZATIONAL COMMUNICATION/ORGANIZATIONAL CLIMATE CANONICAL ANALYSIS. . 67
IX CANONICAL ANALYSIS OF ORGANIZATIONAL COMMUNICATION JOB SATISFACTION RELATIONSHIP . . . . 69
X REDUNDANCY INDEX FOR ORGANIZATIONAL COMMUNICATION/JOB SATISFACTION CANONICAL ANALYSIS........ 72
XI SUMMARY OF DEMOGRAPHIC VARIABLES................ 75
XII CANONICAL ANALYSIS OF DEMOGRAPHIC DATA/ORGANIZATIONAL COMMUNICATION RELATIONSHIP . . . 76
XIII REDUNDANCY INDEX FOR DEMOGRAPHIC DATA/ORGANIZATIONAL COMMUNICATION CANONICALANALYSIS..................................... 79
XIV CANONICAL ANALYSIS OF DEMOGRAPHIC DATA/JOBSATISFACTION RELATIONSHIP.................. 81
XV REDUNDANCY INDEX FOR DEMOGRAPHIC DATA/JOBSATISFACTION CANONICAL ANALYSIS .............. 83
ABSTRACT
The interrelationships between three multivariate concepts: Organi
zational communication, organizational climate, and job satisfaction
were studied in a local government agency. Demographic data were also
studied as they, as a group, relate to the three multivariate concepts.
Questionnaires were collected from 175 of the 220 employees. Canon
ical analysis was utilized to analyze the respondents' perceptions of
the three concepts and to determine their relationships to the demo
graphic data set.
Organizational climate significantly correlated (p<0.001) with job
satisfaction. Only very small, but significant (p<0.01} redundancy was
found between the two concepts.
Organizational communication and organizational climate were signif
icantly correlated (p<0.001). Redundancy analysis indicated that small
to moderate redundancies are shared between the concepts for the sample
under study.
Organizational communication and job satisfaction also exhibited
significant correlation (p<0.001). Redundancy analysis indicated that
communication explains a small but significant (p^O.OS) amount of the
variance in job satisfaction. However, job satisfaction did not explain
a significant amount of the variance in the communication variable set.
xiii
For each of the canonical analyses studied, some of the values of
the loadings on the components possessed positive signs while others
possessed negative signs. Thus, the direction of the relationships
between the three concepts remains unclear.
Canonical analysis of demographic data and each of the three multi
variate concepts was undertaken to determine whether the demographic
makeup of the sample was affecting the relationships between the con
cepts. No significant relationship was found between demographics and
organizational climate at the p<0.05 level. Canonical correlations be
tween the demographic data set and the communication data set were sig
nificant beyond p<0.01. Redundancy analysis indicated that demographics
did not explain a significant amount of the variance in communication
(p f0.05). The reverse relationship was significant at p<0.01, thus
clouding the question of the importance of demographics in explaining
variance in the communication set. Canonical analysis of the demo
graphic/satisfaction relationship was also significant (p<0.01). Redun
dancies yielded similar mixed findings as in the demographics/communica
tion relationship.
Conclusions from the analysis were drawn. Limitations to the use
fulness of the findings were discussed. Finally, suggestions for
further research were made.
xiv
THE INTERRELATIONSHIPS BETWEEN ORGANIZATIONAL COMMUNICATION,ORGANIZATIONAL CLIMATE, AND JOB SATISFACTION
IN A LOCAL GOVERNMENT AGENCY
CHAPTER I
ORIENTATION TO THE STUDY
Communication— A Necessary Component of Organizations
One of the basic building blocks in the study of organizations is
that communication is necessary for the existence and functioning of
organizations. One author has stated that communication "... is vital
to the functioning of organizations... [and] we could go so far as to
say that organizations exist through communication."^ Smith, et.al., in
discussing the importance of communication in organizational behavior
have stated that communication is:
... (1) the primary means by which organizations select,control, and coordinate the activities of human and material resources internally, and (2) the primary means by which organizations respond and ^dapt to the external environment within which they function.
Little Research Has Been Undertaken
To some degree, this emphasis on communication has been carried
into the current literature dealing with humans and their interactions
Lesikar, Business Communication: Theory and Application, p. 4,2Smith, et.al., "Organizational Behavior: An Approach to Human
Communication," pp. 269-70.
2
3in organizational settings. However, as noted by Porter and Roberts in
their 1976 review of the pertinent literature, students of organizational
theory and behavior have offered little direct help in the search for
ways to view organizational communication. Specific discussions of
communication appear relatively infrequently in the literature of
organizational theory and behavior.
One of the reasons for this lack of research could be the elusive
ness of the communication variable. Organizational communication is a
dynamic and pervasive phenomenon that continues to be difficult to
measure. Communication is manifested in such organizational topics as
organizational climate, job satisfaction, control, leadership, moti
vation, roles and role behavior, formal and informal organization
structure, authority, etc. Thus, communication is rarely treated as a
separate variable in the study of these topics. Porter and Roberts have
pointed out that although the major schools of organization theory have
considered communication at least indirectly, an integration of these
various thoughts is generally lacking and is "... probably a necessary
prerequisite to the development of viable theories concerned with
organizational communication."^
When present trends in organizations towards larger size, increased
technology, etc., are considered, one conclusion becomes obvious:
today's organization requires communication performance at an unprece
dented level of excellence. It is not surprising that the effectiveness
3Porter and Roberts, "Communication in Organizations," pp. 1553-99.
4Ibid, pp. 1558.
^Haney, Communication and Organizational Behavior, p. 3.
3
of an organization in attaining its goals seems so closely tied to the
functioning of the system of organizational communication. At the same
time, increasing complexity within organizations is making excellence in
communication even more difficult to attain. One cross-cultural study^
sampled managers from companies in Japan, Great Britain, and the United
States. Seventy-four percent of those sampled listed breakdowns in
communication as the greatest stumbling block to corporate excellence.
It is clear that advances must be made in the study and understanding of
organizational communication.
Increased Knowledge of Communication is Necessary
Although the need for increased expertise in communication is
evident, organizational communication is still in its infancy as an7applied behavioral science. In 1965, Guetzkow posed two questions that
do much toward explaining the slow growth of the field:
Do we find in communication in organizations an area of study in which there is special richness in contingent, interactive effects? Or is it merely that a clarifying perspective— which would make the pieces fall more simply into the whole— remains hidden?8
Since Guetzkow1s statements, studies of communication in organiza
tions have increased. Research in the field is being conducted by
scholars from the many disciplines concerned with the way people commun-9icate within organizations. This broad interest in communication
^Blake and Mouton, Corporate Excellence Through Grid Organization Development, p. 4,
^Greenbaum, "The Audit of Organizational Communication," p. 739.gGuetzkow, "Communication in Organizations," p. 569.9Smith, et.al., Op.cit., p. 270.
4
serves as a two-edged sword. The growth in research provides a wide
theoretical base for studying communication. However, the varying
interests make a clear-cut definition of the concept and what it involves
very difficult to determine.^ The boundaries of the field are becoming
even more vague.^ It seems that Guetzkow's questions can both be
answered "yes." The clarifying perspective remains hidden, and those
contingent, interactive effects of organizational communication have
just begun to be studied.
Even when considering the organization itself as a boundary, an12added difficulty becomes defining the area under consideration. Dance
found some 95 definitions of the concept of communication in his review
of the literature in 1970. As noted by Roberts, et.al., in 1976, almost
all definitions of the terms "communication" and "organizational communi
cation" have the ideas of information exchange and transfer of meaning
in common. Beyond this, there is little similarity among the various 13definitions. A confounding factor in trying to understand the organi
zational communication concept is that:
What are good communication practices in a small office may be neither possible nor desirable in a large retail organization with hundreds of outlets, and of course, the converse is true.The demands on individu^ communicators and communication systems are situational.
10_Loc. cit.^Sereno and Mortenson, Foundations of Communication Theory, p. 2. 12Dance, "The 'concept' of Communication," pp. 201-210.13Roberts, et.al., "Organizational Theory and Organizational
Communication: A Communication Failure?" p. 501.14Sanborn, "Communication in Business: An Overview," p. 4.
5
Further, Roberts, et.al. , have mentioned that communication operates
differently at different levels of organizational analysis. These
authors have identified three levels of analysis of organizational
communication: the interpersonal level; within-organizational; and
organizational-environmental. The behavioral variables that affect
communication will change as the level of analysis changes.^
Difficulties notwithstanding, communication seems to be the glue
that ties organizations together. The study of the relationship between
communication and various organizational processes should have high
payoffs in terms of understanding organizational behavior. Also, as
noted by Roberts, et.al., the relationship between organizational
communication and the quality of organizational life appears to have
important implications.^
It is this area of identifying and studying communication variables
and their effect on the quality of organizational life that this current
research effort focuses. Specifically, the interrelationships between
organizational communication, organizational climate, and job satisfac
tion are studied.
PURPOSE OF THE STUDY
A Statement of the Problem
This research seeks additional knowledge concerning how organiza
tional communication, organizational climate and job satisfaction are
related. Although no attempt is made to determine causality, the
^Roberts, et.al, Op■ cit. , p. 514.
16Ibid., p. 520.
6
underlying thought is to identify which communication variables are
related to organizational climate and/or job satisfaction. Also,
additional information on the relationship between organizational
climate and job satisfaction is explored. Specifically, the idea that
communication may serve as a moderator between organizational climate
and job satisfaction is studied.
Variables To Be Considered
The first step toward hypothesizing relationships between the
variables associated with each of the relevant concepts is the identif
ication of these variables. The fruits of previous research by many
authors are utilized to tentatively identify these variables. One
should remember that the focus of this research is on the total organi
zational (within organization) level. Only those variables which have
been considered relevant at this level of analysis in previous research
are studied.
Communication Variables
Roberts and O'Reilly, in a review of the literature concerning the
communication variables frequently Investigated, identify seven broad
communication variables. In addition, these researchers identify three
respondent-oriented variables which have been repeatedly shown to
influence individual communication in organizations.
The communication variables include: 1) directionality of infor
mation flow; 2) accuracy and distortion of information; 3) mode of
information transfer; 4) gatekeeping of information; 5) information
overload; 6) satisfaction with communication; and 7) desire for inter
action with others. The three respondent-oriented variables include:
7
1) trust in superior; 2) perceived influence of superior; and 3) mobility17aspirations of the respondent.
In a follow-up of their research, Roberts and O'Reilly have expanded
the list of communication variables to include summarization, expansion
and withholding of information, information underload, and openness of 18communication. With these additions, this list of 15 variables
appears to be quite comprehensive.
Organizational Climate Variables
Organizational climate, which has been studied by a wide variety of
researchers and research methods, refers to a set of attributes of a
particular organization and/or its subsystems, that may be perceived
from the way that organization and/or its subsystems interact with its19members and their environment. Several themes are Implied in this
definition of climate: first, employee responses sought are perceptual
and typically descriptive of the organization rather than evaluative;
also, the level of analysis involves attributes of the organization and20its subsystems rather than the individual. Thus, climate is measured
through perceptual measures at the within-organization level of analysis
referred to earlier.
^Roberts and O'Reilly, "Measuring Organizational Communication," p. 321.
18Roberts and O'Reilly, "Assessing Communication in Organization,"p. 1.
19Hellriegel and Slocum, "Organizational Climate: Measures,Research, and Contingencies," p. 255-6.
20Op. cit., p. 256.
8
The dimensions or variables that make up the concept of climate21have been stated in many different forms. Campbell, et.al., in a
comparative analysis of climate instruments suggest at least six common
dimensions: autonomy, structure, rewards, consideration, warmth, and22support. Muchinsky, in several articles concerning climate has
utilized a six variable construct also, but has arranged the variables
in a slightly different manner. The variables used by Muchinsky
include: interpersonal milieu, standards, affective tone toward
management/organization, organizational structure and procedures,
responsibility, and organizational identification. There appears to be
considerable overlap between the six common dimensions of Campbell,
et.al. and those utilized by Muchinsky in his research.
Job Satisfaction Variables
Job satisfaction has been defined as the positive or negative
aspects of the attitudes of an individual toward his or her job or some23aspect of his or her job. A slightly more specific definition has
21 Campbell, et.al., Managerial Behavior, Performance, and Effectiveness.
22Muchinsky, "An Assessment of the Litwin and Stringer Organizational Climate Questionnaire: An Empirical and Theoretical Extension ofthe Sims and LaFollete Study," pp. 371-92.
___________, "The Interrelationships of Organizational Communicationand Organizational Climate," pp. 370-4.
___________, "Organizational Communication: Relationships toOrganizational Climate and Job Satisfaction," pp. 592-607
23Gibson, et.al., Organizations: Structure, Processes, Behavior,p. 449.
9
been set out by Locke, who states that job satisfaction is "...a
pleasurable or positive emotional state resulting from the appraisal of25one's job or job experience.” This definition leaves out the negative
side of job satisfaction; seemingly, one can infer that dissatisfaction
with a job is not necessarily the opposite of satisfaction. This2 6thought follows from Herzberg's Motivation-Hygiene theory, but is not
necessarily at odds with the first definition above.
It should be noted that a controversy continues regarding whether
or not job satisfaction and organizational climate are redundant con- 27cepts. Most research shows that the two concepts are at least highly 28related. The concept of job satisfaction embraces many of the same
variables as the organizational climate concept. However it views these
variables differently by evoking evaluative responses about work and the
organization.
Job satisfaction is one of the most widely studied concepts of
organizational behavior, as noted earlier. At the same time, the
ability to interpret and generalize many of the empirical relationships
found in the literature remains unclear. Among the factors contributing
to this problem is a great diversity of "personalized measurement
9 /Locke, "The Nature and Causes of Job Satisfaction," pp. 1293-1349.
25Ibid., p. 1300.26Herzberg, et.al., The Motivation to Work.27LaFollete and Sims, "Is Satisfaction Redundant with
Organizational Climate?" pp. 257-78.28Downey, et.al., "Organizational Climate and Job Satisfaction; A
Comparative Analysis," pp. 233-248.
10
29instruments," which has led to a lack of standardization of variablesinstudied. The most widely used instrument, the Job Descriptive Index,
has been used in only 99 of the 346 studies (28.6% of the total) which31were reported between 1973 and 1978 by O’Connor, et,al.
The Job Descriptive Index (JDI) has the greatest acceptance by
students of organizational behavior because of its continued reliability. 32Vroom has described the JDI as one of the most carefully developed
scales measuring job satisfaction. Since publication of Vroom's state
ment, several instruments have been developed that are reported to have33 3 Agreater reliability and/or validity than the JDI. ’ Yet, the JDI
remains one of the most widely used measures of job satisfaction.
The JDI divides the concept of job satisfaction into five components
or variables. These include: a) satisfaction with work; b) satisfaction
with supervision; c) satisfaction with pay; d) satisfaction with
promotions; and, e) satisfaction with co-workers.
29O'Connor, et.al., "The Measurement of Job Satisfaction: CurrentPractices and Future Considerations," p. 18,
30Smith, Kendall and Hulin, The Measurement of Satisfaction in Work and Retirement.
31O'Connor, et.al., Op. cit., pp. 18-19.32Vroom, Work and Motivation.33Gillet and Schwab, "Convergent and Discriminant Validities of
Corresponding Job Descriptive Index and Minnesota Satisfaction Questionnaire Scales," pp. 313-317.
3 4Dunham, et.al., "Validation of the Index of Organizational Reactions with the JDI, the MSQ, and Faces Scales," pp. 420-432.
11
HYPOTHESES TO BE TESTED
Previous research has concluded that organizational climate and job
satisfaction are highly correlated (if not redundant) concepts. This
study should not only serve to further corroborate this finding, but
also provide a more precise description of the relationship between
organizational climate and job satisfaction. Thus, the initial hy
pothesis is:
HYPOTHESIS I:
Organizational climate has a strongly positive, significant relationship to job satisfaction.
Canonical analysis allows the calculation of a measure of the variance
shown between two multivariate concepts. Specifically, the amount of
redundancy between these two concepts, and its statistical significance
may be tested. The amount of variance in the organizational climate
variables that is explained by the variance in the job satisfaction
concept, and vice versa, may be determined. The practical significance
of this measure is that it essentially determines the amount of overlap
or redundancy between the variables under study. This leads to a second
hypothesis.
HYPOTHESIS II:
Organizational climate and job satisfaction are significantly different concepts; i.e., they are comprised of significantly different variables and explain little of the variance in each other.
Further, it is the contention of this study that the character of
the system of communication in an organization is significantly related
to the organizational climate and/or job satisfaction of an organization.
More specifically, the communication variables under study should be
12
correlated with variables associated with both climate and satisfaction.
These relationships are stated in the following two general hypotheses:
HYPOTHESIS III:
Organizational communication has a strongly positive, significant relationship to organizational climate.
HYPOTHESIS IV:
Organizational communication has a strongly positive, significant relationship to Job satisfaction.
Certain of the communication variables under study should have
significantly strong relationships with organizational climate, based on35findings of research mentioned previously. These variables include
trust, influence, accuracy, directionality (up, down, and lateral) and
satisfaction with communication. The gatekeeping, overload, written and
other modality variables have not been found to have significant rela
tionships to any of the climate variables. The previously reported
research, however, was also a case study of one organization, so it may
not be unreasonable to find additional communication variables related
to organizational climate in this study.
Likewise, certain of the communication dimensions should have sign
ificant correlations with job satisfaction. Trust, influence, desire
for interaction, accuracy, directionality-lateral, and satisfaction with
communication should all be related to the facets of job satisfaction.36In the previous case study, the dimensions of communication overload
and written modality were not significantly related to job satisfaction.
^^Muchinsky, Ibid., p. 597. 36Loc. cit.
13
Organizational communication, as viewed in the above hypotheses,
appears to serve as a moderating variable in the relationship between
organizational climate and job satisfaction. The overall hypothesized
relationships among the concepts under study may be graphically modeled
as shown in Figure 1, with organizational communication moderating the
relationship between organizational climate and job satisfaction.
Figure 1
A Model of the Organizational Climate-Organizational
Communication-Job Satisfaction Relationship
C Organizational Communication J
/ \
\/ \JL X(Organizational^, f Job "N
Climate J ~*\. Satisfaction J
JUSTIFICATION FOR THE STUDY
The hypothesized relationships will add to the understanding of
organizational communication and its relationship to both organizational
climate and job satisfaction. Also, additional insight into the organi
zational climate-job satisfaction relationship may be uncovered. This
understanding and insight could lead to more efficient organizations by
giving direction to efforts to improve levels of communication, organi
zational climate and job satisfaction in organizations that may be
unclear with current knowledge.
14
Previous studies (explained in detail in the following chapter)
have investigated the relationships between the various dimensions of
communication and the dimensions of either or both organizational
climate and job satisfaction. This study proposes going one step
further by assessing the relationships among these three complex, multi-
variable constructs by utilizing composite dimensions of each construct
rather than just the individual dimensions of each construct. A broader,
more powerful statistical technique (canonical correlation analysis)
than has been previously reported is used to accomplish the assessment.
Previous studies have utilized simple, global measures (consisting of
one to two questions) of satisfaction with communication and global job
satisfaction measures to investigate relationships between the constructs
two at a time. Only one study by Muchinsky has reported the use of
instruments that measure the various dimensions of each of the constructs
under study, but that study does not utilize the statistical technique
of the present study. Thus, no empirical assessment of the overall
relationships among the three constructs has been reported.
An additional justification for this study is the unique view of
the relationship between organizational climate and job satisfaction
that will be provided. The redundancy measure associated with the
statistical technique utilized may shed additional light on the question
of whether climate and satisfaction are actually different concepts, or
just different ways of viewing the same organizational phenomena. This
work does not propose to be totally definitive on this issue, but does
intend to add additional information.
15
SCOPE OF THE STUDY
This research effort is a case study of a local government agency
in a Midwestern city with a population of approximately 300,000. The
research instruments (questionnaires) were distributed to all organi
zational levels of the agency in an effort to obtain a sample view
representative of the organization. The data gathered is limited to
perceptual responses concerning the three concepts under study and to
limited demographic information. Objective measures of the concepts,
such as absenteeism and turnover, interviews, physical measures of
communication, etc. were unavailable from the organization under study.
Analysis of the hypotheses presents several problems. The communi-
cation-climate-satisfaction relationships demand a multivariate analysis;
however, the statistical techniques employed tend to cloud simple*
relationships. Also, interpretation of the data utilizing multivariate
analyses (canonical correlation) does not lend itself well to classical37hypothesis testing. As noted in research by Penley and Alexander, the
degree to which the hypotheses are supported will depend on the ex post
facto analysis of the researcher.
POSSIBLE LIMITATIONS TO THE STUDY
The most obvious limitation to this study is the use of perceptual
data. By using the same methods to assess the three constructs; that
is, instruments that measure perceptions, the possibility of inflated
Penley and Alexander, "The Communication and Structure of Organizational Work. Groups," p. 334.
16
significances because of correlated method error, or response bias may
occur. The basic nature of the relationships between the concepts
should not be affected by the possibility of this problem. Utilizing
objective measures of the concepts would overcome this limitation and
provide better information about the relationships under study. However,
more objective means of measuring organizational communication, organi
zational climate, and job satisfaction are unavailable from the organi
zation under study.
A second limitation to the use of perceptual measures is the
question of an "inner vs. other" orientation of the respondents. That
is, are they responding to the instruments in a way that describes their
own perceptions; or conversely, are they responding as they feel they
should respond based on their feelings of others in their part of the
organization. There is little that can be done to overcome this poten
tial limitation.
Further, there may be a wide variety of variables not studied that
may moderate the relationships among the three concepts. A partial list
might include organizational growth, level of education of members of
the organization, age, sex, individual's expectations of the organiza
tion, etc. Although some of these variables may be measured through
gathering demographic data, others cannot be predicted or controlled.
A possibly serious limitation to the usefulness of the findings of
this study is the questionable ability to generalize the findings of a
study of a local government agency in the Midwest to all types of
organizations in other parts of the United States, or other countries.
This may be especially true because of the differences in reward
structure, management style, etc. that may occur as the organization
17
type changes from a governmental bureaucracy to other forms of organi
zation, especially into for-profit organizations. The usual caveats
about generalization apply; that is, one should be extremely careful in
generalizing these findings to other organizations, especially
organizations with different tasks, structures, etc.
A fifth limitation that may occur is the usual problems associated38with the administration of questionnaires. Specifically, problems
such as faked, incomplete, or poorly thought out responses, a lack of
understanding by respondents with little education, etc. may occur.
This limitation is minimized through guarantees of anonymity, explanation
of the purpose of the research to respondents, and direct administration
of the instruments during working hours.
An additional limitation involves the technique employed to measure
the relationships between the concepts (canonical analysis). Canonical
analysis, and other multivariate statistical methods, tends to obscure
simple relationships that may be determined through more traditional
techniques such as multiple regression. The nature of the loadings that
identify the importance of each of the components in explaining the
relationships with the other multivariate concepts are unstable and may
vary considerably from sample to sample. Canonical correlations repre
sent the product-moment correlations between two variates made up of
multiple variables. When the relationship between two concepts is
interpreted, one should remember that canonical roots represent the pro
portion of variance in each variate that is explained from the variate
38Williams, et.al., "On Administering Questionnaires in Organizational Settings."
18
of the other set, not from the variance extracted from the other set.
Thus, the variate does not account for all the explainable variance in
the variables in a set as in multiple regression. However, the
multivariate nature of the concepts under study demand that they be
studied through multivariate methods. Multivariate methods such as
canonical analysis do not lend themselves readily to classical
hypothesis testing. Multiple regression, on the other hand, fits well
with classical hypothesis testing. Because canonical analysis does not
fit classical hypothesis testing, the degree to which the hypotheses are
supported will depend on the analysis of the researcher.
A PREVIEW OF THE FINDINGS
Following this introductory chapter are four additional chapters.
The first is made up of a thorough review of the literature pertinent to
the constructs under study. This review is organized according to the
relationships between the constructs as presented in the management
literature. First, research concerning the relationship between organi
zational communication and organizational climate is reviewed. This is
followed by a review of the research concerning the organizational
communication/job satisfaction relationship. Finally, the research
which considers the relationships among all three constructs is reviewed
and summarized.
The third chapter introduces the methodology utilized in the study.
Sample selection and design is explained. Survey instruments used are
discussed in detail. To conclude the chapter, special emphasis is given
to an explanation of the techniques of analysis of the data used in this
study.
19
The next chapter develops the actual analysis of data. This
chapter is organized around the four basic hypotheses elaborated pre
viously, and discusses each in order. Both the canonical analysis and
significance of statistical results concerning each of the hypotheses
are discussed.
The final chapter of this study summarizes the findings and dis
cusses conclusions drawn from these findings by the researcher. Impli
cations for management and organizational behavior are pointed out.
Suggestions for future research are also elaborated.
CHAPTER II
REVIEW OF THE PERTINENT LITERATURE
The three major concepts studied in this research effort are
extremely broad. Studies concerning each of these concepts are numerous,
as noted previously. However, this review focuses on studies, articles,
etc. which are concerned with the interrelationships between organiza
tional communication, and either or both organizational climate and job
satisfaction. If the reader desires an indepth review of the literature
regarding each of the individual concepts under discussion, the following
reviews will prove very helpful.
Reviews of Organizational Communication
One of the earliest reviews of the organizational communication39literature covers through 1963 and was reported in 1965 by Guetzkow.
40 41This review was followed in 1967 by Thayer and also by McLeod. A
slightly different approach to the literature was reported by Roberts,42et.al., which discusses the question of whether there has been a
39Guetzkow, Op. cit.40Thayer, "Communication and Organization Theory."41McLeod, "The Contribution of Psychology to Human Communication
Theory."42Roberts, et.al., Op. cit.
20
21
communication failure between organizational communication and organiza-43tional theory. Porter and Roberts followed up in 1976 in a review
which focuses on empirical research in the field of organizational
communication in the ten years prior to publication of their review. In
the ensuing years, an updated review has not been published.
Reviews of Organizational Climate
Several comprehensive reviews of the organizational climate liter
ature have been undertaken. Organizational scholars have summarized and
integrated the theoretical and practical issues concerning organizational
climate in several articles. These include treatises by Hellreigel and44 45 46 47Slocum, James and Jones, Schneider, Campbell, et.al., and Payne
48and Pugh. One of the most recent reviews was published in 1978 by 49Woodman and King.
Reviews of Job Satisfaction
Similarly, there have been several comprehensive reviews of the job
satisfaction literature. Well over 4000 studies have been undertaken
43Porter and Roberts, Op. cit.44Hellreigel and Slocum, Op. cit.45James and Jones, "Organizational Climate: A Review of Theory and
Research," pp. 1096-1112.46Schneider, "Organization Climates: An Essay," pp. 447-479.47Campbell, et.al., Op. cit.48Payne and Pugh, "Organizational Structure and Climate,"
pp. 1125-1174.49Woodman and King, "Organizational Climate: Science on Folklore,"
pp. 816-61.
22
which relate job satisfaction to its hypothesized causes and effects.
A thorough review of the literature was reported in 1957 by Herzberg,51 52et.al. In 1963, Blauner surveyed several hundred job satisfaction
studies. Since that time, a comprehensive review has become53increasingly difficult. Locke, in 1976, pointed out that such a
review would not necessarily be desirable since "much of this literature
is trivial, repetitive, and inconclusive." At the same time, Locke/provides an historical overview of the concept and analyzes and
distinguishes job satisfaction from other concepts. Locke also
discusses the major process and content theories of job satisfaction.
He looks into the major causes and effects of satisfaction, and points
out major measurement problems. Summaries of literature on job
satisfaction can be found in several texts in organizational behavior as54 55 56well, such as Katz and Kahn, Luthans, etc.
■^0'Connor, et.al., Op. cit., p. 17.51Herzberg, et.al., Op. cit.52Blauner, "Extent of Satisfaction: A Review of General Research,"
pp. 80-81.53Locke, Op. cit.54Katz and Kahn, The Social Psychology of Organizations.55Luthans, Organizational Behavior.56Behling and Schriesheim, Organizational Behavior: Theory,
Research and Application.
23
Reviews of Interrelationships
Studies by Johannesson,"^ Downey, et .al,, LaFollette and Sims,^
and Friedlander and Marguiles^ have researched the relationships
between the dimensions of organizational climate and job satisfaction.
Johannesson^ concluded from his work that the two are redundant con-62cepts; but, on the other hand, LaFollette and Sims felt that the
63evidence did not warrant such a conclusion. Muchinsky sums up the
continuing controversy by saying that the two concepts may be closely
related yet still provide different sources of information. "That is,
climate provides descriptive information, often contaminated by satis-64faction, while satisfaction provides evaluative assessments." Thus,
although the debate is far from over, several researchers agree that
organizational climate and job satisfaction are related but are indeed
different concepts. Several authors have discussed the relationship
between communication and organizational climate; others have investi
gated the organizational communication-job satisfaction relationship. A
few authors have considered the interrelationship between organizational
^Johannesson, "Some Problems in the Measurement of Organizational Climate", pp. 118-145.
58Downey, et.al., Op. cit.59LaFollette and Sims, Op. cit.
^Friedlander and Marguiles, "Multiple Impacts of Organizational Climate and Individual Value Systems Upon Job Satisfaction." pp. 171-183.
61Johannesson, Op. cit.62LaFollette and Sims, Op. cit.f i *5Muchinsky, (1977-C), Op. cit., pp. 592-607.64 Ibid., p. 594.
24
communication and both climate and satisfaction. The following para
graphs present a summary of the research and writing in these areas.
Organizational Communication/Organizational Climate Relationship
Almost all studies of organizational climate treat communication at
least implicitly through such dimensions as openness, warmth and support,
etc. Some authors, however, have explicitly studied the effects of
communication on climate. It is these works which are the focus here.
Hall,88 in 1973, discussed communication problems in organizations.
He pointed out that many of the communication problems people name are
not actually communication problems, but symptoms of dysfunctions in the
"corporate climate." Hall further notes that the quality of relation
ships within an organization (i.e., climate) may dictate the level of
effectiveness of communication to a large degree.
Holland, et.al.,8 surveyed 384 engineers and scientists in a large
government research and development organization. The purpose was to
examine the relationship of two variables, the level of training in a
field, and the familiarity with the technology involved, to a decision
maker's choice of an information channel and source. Among their
findings, Holland, et.al., noted that ". . .Managers should attempt to
develop and maintain a 'warm* organizational climate that encourages68rather than hinders interpersonal communication." The authors found
^Campbell, et .al., Op. cit., pp. 389-91.
88Hall, "Communication Revisited," p. 56.
^Holland, et.al., "Information Channel/Source Selection as a Correlate of Technical Uncertainty in a Research and Development Organization," pp. 163-167.
68Ibid., p. 167.
25
some support for the basic hypothesis that as uncertainty increases,
individuals will prefer the "richer" channels and/or sources of informa
tion. That is, as uncertainty increases, organizational members will
prefer to utilize more informal, face-to-face communication. A positive
organizational climate, because of its increased trust, warmth, and
openness, etc., will encourage individuals to utilize more informal,
face-to-face communication channels in times of uncertainty. A negative
climate, on the other hand, with its relatively low trust, warmth and
openness, etc., will discourage the use of such channels. Thus, it
appears that a positive organizational climate fosters improved commun
ication by encouraging the use of more effective channels.69Long reports on the use of survey research in banks to improve
communication and increase performance. Findings from nine banks
indicate that banks with good communication (as judged by employees),
along with policies and practices which stimulate good communication,
show increases in financial performance over banks which do not promote,
or actually discourage good communication practices. It can be seen
that the author implies that banks with good climates will have good
communication and therefore, increased performance over banks with poor
organizational climates. Again, the relationship between organizational
communication and organizational climate is discussed. Specifically,
there is a positive relationship between organizational communication
and organizational climate, which has a positive impact on performance.
It should be noted that the sample size of the study is small (9 banks)
and performance is measured by having respondents state that they
69Long, "The Hawthorne Myth and Employee Communications," pp. 6-10.
26
perceive communication in their bank to be good, poor, or neutral.
Specific communication or climate variables are not reported.
Ireland, et.al. have investigated the relationship between
organizational climate and communication climate. The authors focus on
how six dimensions of organizational climate have an impact on communi
cation climate, which may be characterized as being either supportive or
defensive. A discussion of specific typologies of both organizational
and communication climates is presented. This discussion is followed by
an analysis of their perceived relationships. No empirical data are
presented.
The organizational climate dimensions discussed by Ireland, et.al.,71are drawn from the work of Litwin and Stringer as summarized by
72Campbell, et.al. The dimensions are explained in the following
sentences:
1. Structure: the employees' perception of the breadth and depthof organizational rules, constraints, and regulations.
2. Individual Responsibility: the employees' perception of thedegree of autonomy extended to them by the organization.
3. Rewards: the employees' perception of the adequacy and appropriateness of organizational rewards received for exhibiting desired performances.
4. Risk and risk taking: the employees' perception of the extentof risk and challenge offered within the work setting.
5. Warmth and support: the employees' perceptions of the fellowship and helpfulness pervading the work environment.
Ireland, et.al., "An Investigation of the Relationship Between Organizational Climate and Communication Climate," pp. 3-10.
^Litwin and Stringer, Motivation and Organizational Climate.72Campbell, et.al., "Environmental Variation and Managerial Effec
tiveness ."
27
6. Tolerance and conflict: the employees' confidence inability of the organization to accept differing opinions.
Litwin and Stringer have also suggested three basic types of
organizational climates, based on different combinations of the above
variables: 1) the power-motivated climate; 2) the affiliation-motivated74 75climate; and 3) the achievement-motivated climate. Ireland, et.al.,
indicate that these three types of organizational climate have an
influence on the development of the two identifiable communication
climates noted previously. The supportive communication climate facili
tates efficient and effective transmission of information. On the other
hand, defensive climates generally serve as impediments to successful
transmission of information in organizations. Supportive communication
climates are characterized by communication which: is descriptive
rather than evaluative; is oriented toward problem solving rather than
control; is spontaneous rather than of a calculated, strategic nature;
focuses on empathy rather than neutrality, equality rather than superi
ority, and decisions are considered as provisional or temporary rather
than certain or fixed. In summary, communication climate is thought to
have an intimate relationship with patterns of organizational success.
The feelings people have about where and with whom they work help define
the climate and the manner in which communication can be managed. Thus,
dimensions of the formal and informal organization (components of
organizational climate) will ultimately shape the overall communication
73Ireland, et.al., Op. cit., p. 4.74Hellreigel and Slocum, Management: A Contingency Approach,
p. 430.
^Ireland, et.al., Op. cit., p. 5.
28
climate of an organization. Ireland, et.al., thus indicate that in
this study at least, the organizational climate shapes the nature
of communication in the organization. It should be noted that this may
be a reciprocal relationship, with- the communication climate affecting
the organization climate as well.
A direct study of the interrelationships of dimensions or organiza
tional communication and organizational climate has been reported by
Muchinsky^ in his exploratory study of 695 employees of a large public
utility. Results of the study indicate that certain dimensions of
communication are highly related to organizational climate variables.
Muchinsky utilized the Roberts and O'Reilly Organizational Communi- 78cation Questionnaire and Form B of Litwin and Stringer's Organizational79Climate Questionnaire in a mail survey of the respondents. Because of
doubtful reliability and validity of the original nine a priori climate
variables, the original 50-item instrument was factor analyzed to yield
six derived dimensions of climate: Interpersonal Milieu; Standards;
Affective Tone Toward Management/Organization; Organizational Structure
and Procedures; Responsibility; and Organizational Identification. The
16 dimensions of organizational communication which were studied have
been listed previously.
^Muchinsky, (1977-A), Op. cit, pp. 370-374.78Roberts and O'Reilly, (1974), Op. cit.79Litwin and Stringer, Op. cit.
29
Of the 96 correlation coefficients reported, 46 were statistically
significant at the p. < .01 or < .001 level. Trust, Influence, Accuracy,
Directionality-Downward, Directionality-Lateral, and Satisfaction with
Communication were found to be significantly related to all or most of
the climate dimensions. Other communication dimensions, however, were
unrelated to any of the climate dimensions. These variables were
Gatekeeping, Overload, Written Modality, and Other Modality. A wide
array of correlations differing in sign and magnitude indicates that no
singular relationship between organizational communication and perceived
climate was discovered. At the same time, the authors note that the
relatively unreliable scale properties of the Gatekeeping and Overload
dimensions contributed to the lack of a significant relationship between
each of these variables and dimensions of organizational climate. Also,
the significance of some of the findings may have occurred because of,
at least in part, correlated method error; that is, employing the same80method to assess both of the concepts which may lead to response bias.
The author concludes that certain dimensions of organizational
communication are related to perceived organizational climate. In any
event, it is concluded that the need for further research to identify
parameters of the individual concepts is needed.
In order to measure the relationship between communication and81performance in organizations, O'Reilly and Roberts utilized both
objective and subjective measures of performance. These were compared
to dimensions of organizational communication to determine how they were
^Muchinsky, (1977-A), Op. cit., pp. 373-374.81O'Reilly and Roberts, "Communication and Performance in Organi
zations," pp. 375-379.
30
related in a sample and resample of three Navy aviation units. Objec
tive, goal-centered measures of performance (individual, overall
performance) were derived from supervisors' ratings for the time period
of the data collection, while perceptual measures of performance were
tapped by measuring six dimensions of organizational climate completed
by the subjects themselves. The assumption was that perceptual
measures would yield a better estimate of overall organizational health
and performance than simple objective performance ratings.
Thirty-six significant bivariate correlations between the 17
communication dimensions and the six climate dimensions were found. The
authors point out that several trends are apparent and document the
relationships among perceptions of communication and perceptions of
climate. The possibility of response bias caused by using two perceptual
instruments is pointed out, but findings are consistent with previous
research on performance. That is, the communication-organizational
climate relationships echo the findings of the correlations between
communication and objective measures of performance. In summary, it is
stated by the authors that both the quality of information, which
includes accuracy, expansion, and summarization, and the amount of
information transferred (includes amount passed, underload, overload,
and redundancy) are consistently related to perceptions of work group82functioning which are usually associated with high performance groups.
^ Ibid., p. 378.
31
From this review, it may be seen that there is evidence that there
is a relationship between organizational communication and organizational
climate. At least, it can be stated that there are significant rela
tionships among some of the dimensions of organizational communication
and some of the variables associated with organizational climate.
Although the variables studied vary from study to study, there is enough
overlap to allow the preceding evaluation. However, no researchers have
reported an empirical relationship between the two concepts when each is
considered as a whole. The greatest problem with the research efforts
reported above is the problem of response bias brought about by
utilizing several perceptual measures of the concepts under study. This
could be viewed as a serious problem, but in at least one study of the
six reported, the correlation between perceptual and objective measures
indicates that response bias has little effect on the usefulness of the
findings concerning the communication-climate relationship. However,
the other five articles do not address the issue of correlated method
error and/or response bias.
Organizational Communication/Job Satisfaction Relationship
The relationship between dimensions of organizational communication
and job satisfaction has gotten little recognition in the study of job
satisfaction. Only a few articles have treated this relationship and
then only incidentally while studying other aspects of job satisfaction.83In a case study of two organizations, Merryman and Shani report
on how job satisfaction and communication in a company that has experi
Merryman and Shani, "Growth and Satisfaction of Employees in Organizations," pp. 492-292.
32
enced recent growth differs from a similar company without recent
growth. The basic premise behind this research seems to be that uncon
trolled growth will lead to decreases in communication effectiveness,
which will lead to decreased job satisfaction. The researchers found
that the average employee satisfaction in the smaller company was
significantly higher than the average for the larger (growth) company.
They conclude that any company experiencing growth should take special
pains to ensure good communication.
In a study of role ambiguity and conflict as related to job atti-84tudes of salesmen, Futrell and Fortune found relationships that have
implications for the organizational communication/job satisfaction
relationship. Significant relationships (Pearson product-moment
correlations) were found among four dimensions of job satisfaction and
role ambiguity. Three significant relationships were noted among job
satisfaction dimensions and role conflict. The results of the study
indicate the importance of effective communication of the firm's goal
expectations, policies, procedures, etc. to salesmen. Salesmen in this
study who experienced low levels of role conflict and ambiguity perceived
that: (1) their organizational goals were clearly communicated to them;
(2) they were relatively more satisfied with pay, promotions, super
visor, and work; (3) and they tended to not want to leave the organi-- • 85 zation.
Futrell and Fortune, "Role Conflict and Role Ambiguity Related to Salesmen's Job Attitudes," pp. 133-134.
O CIbid., p. 133.
33
Downs and Hazen have reported a factor analytic study of com
munication satisfaction in organizations. The primary dimensions of
communication satisfaction as reported include: general organizational
perspective, organizational integration, personal feedback, relations
with supervisor, horizontal-informal communication, relations with
subordinates, media quality and communication climate. Correlations
between the facets of communication satisfaction and a global measure of
job satisfaction were calculated for four different organizations. The
researchers observed from the results that their communication satis
faction instrument was able to pick up widespread differences among
organizations. More importantly for the purpose of this research, the
communication satisfaction dimensions which are most highly correlated
with job satisfaction are Personal Feedback, Relations with Supervisor,8 7and Communication Climate.
88Swan and Futrell address the question, "Does clear communication
relate to job satisfaction and self-confidence among salespeople?" in
their article by the same name. Specifically, the study focuses on the
extent to which outcomes of the organizational communication process
relate to job satisfaction and job confidence among salespeople. One of
the hypotheses tested in the study is that salespeople who perceive
greater goal clarity will experience higher job satisfaction. Job
Downs and Hazen, "A Factor Analytic Study of Communication Satisfaction," pp. 63-73.
O7Ibid., p. 71.
Swan and Futrell, "Does Clear Communication Relate to Job Satisfaction and Self-Confidence Among Salespeople," pp. 39-52.
34
satisfaction is measured by the JDI, while the goal clarity measure
consists of items where the respondents rate their jobs using a five-
point agree-disagree scale. The researchers utilized canonical correla
tion analysis to determine the strength of the relationship between two
sets of variables, as well as an index of the degree to which each
variable in either set of variables is correlated with its set of
variables. In some cases, the canonical coefficients may be unstable
and "true" relationships between variables are difficult to determine.
To overcome both these potential problems, the researchers utilized
simple correlational analysis to indicate the possibility of meaningful
relationships between the pairs of variables.
Goal clarity was found to be significantly related to job satisfac
tion, as the three clarity dimensions explained 38.5% of the total
variance in job satisfaction, with a canonical correlation coefficient
of .596. Thus, these figures indicate a modest relationship between
goal clarity and job satisfaction. It seems that "Goal clarity has a
general effect on job satisfaction, and the greatest influence is in89satisfaction with supervision." Job satisfaction tended to increase
to the extent that a salesperson: knew how well he had performed as
judged by his superior; knew what results were expected of him; and
clearly understood the relative importance of job goals. The authors
indicate that the results of this study suggest that if sales supervisors
could clarify job accomplishments, standards, and priorities, then the
^Ibid., p. 46.
35
job satisfaction and job security of their sales people could be in- 90creased. The implications for the importance and strength of the
organizational communication/job satisfaction relationship appear
obvious, at least for sales management.
In a study of the communication correlates of employee morale,91Baird and Bradley correlated ten dimensions of communication content
and ten communication style dimensions with five dimensions of employee
morale which included a global measure of job satisfaction. The re
searchers compiled a 25-item questionnaire which was administered to 150
workers randomly selected from 20 departments of two medium-sized
organizations. The results were analyzed through Pearson product-moment
correlations of the communication and morale variables. Nine of the ten
communication content dimensions were correlated with job satisfaction
at the p. < .05 level, while seven of the communication style dimensions
were significantly correlated with job satisfaction. The significant
content dimensions include managerial communication which: solicits
input from employees; gives information; stresses happy relationships,
company goals, and conflict avoidance; allows unsupervised work; empha
sizes teamwork; encourages effort; and reinforces good performance.
Managerial communication styles which come on strong to subordinates, or
are quick to disagree, are negatively correlated with job satisfaction.
On the other hand, styles which show concern, ease in communicating,
^Ibid. , p. 51.91Baird and Bradley, "Communication Correlates of Employee Morale,"
pp. 47-56.
36
attentiveness to others, active communication, good listening and92friendliness are positively correlated with job satisfaction. Thus,
it can be concluded that improving the communication quality of
relations between superiors and subordinates should lead to improved
morale in general and improved job satisfaction in particular.93Churchill, et,al., included the frequency of communication as an
organizational climate variable in a study of organizational climate and
job satisfaction in the salesforce. Among others, one hypothesized
relationship tested was that the greater the frequency of communication
between a salesperson and his sales manager, the greater the salesper
son's overall job satisfaction. Using a stepwise regression procedure,
it was determined that the frequency of communication with sales managers
is significantly related to only two components of job satisfaction; pay
and satisfaction with customers. Thus, the hypothesis could not be
supported. This, according to the authors, suggests that the substance
of the contact between a salesperson and his supervisor is much more
critical to satisfaction than the frequency of contact. Also, sales
people are more likely to communicate with their supervisors when they
face difficult customers than when customer relationships are smooth.
Although communication and job satisfaction have been measured in
many different ways in the articles discussed above, some relationship
between organizational communication and job satisfaction seems to exist
across the studies. The various methodologies and samples have investi-
92Ibid., p. 51.93Churchill, et.al., "Organizational Climate and Job Satisfaction
in the Salesforce," pp. 323-332.
37
gated different- aspects of the two concepts. This has provided a wealth
of information about the existence of the relationship between organi
zational communication and job satisfaction but additional knowledge
would help to understand this relationship more completely. At the same
time, additional knowledge may have important implications for improving
the quality of organizational life.
Organizational Communication/Organizational Climate/Job Satisfaction Relationship
Only one research effort has been reported that studies the rela
tionship between organizational communication and both organizational94climate and job satisfaction. Muchinsky, in an exploratory study,
examined the relationships among measures of organizational communica
tion, organizational climate and job satisfaction. Six hundred ninety-
five employees of a large public utility returned questionnaires and
made up the sample studied.
The instruments utilized include: A) the Roberts and O'Reilly
Organizational Communication Questionnaire (36 items measuring 16
dimensions); B) Form B of the Litwin and Stringer Organizational Climate
Survey (50 items measuring 6 dimensions based on an earlier article by 95Muchinsky ) ; and C) the JDI (72 items measuring 5 dimensions of job
satisfaction).
Means, standard deviations and reliability indices were computed
for each of the 27 variables. Then, measures of correlation were
Muchinsky, "Organizational Communication: Relationships toOrganizational Climate and Job Satisfaction," pp. 592-607.
95Muchinsky, "An Assessment of the Litwin and Stringer Organization Climate Questionnaire: An Empirical and Theoretical Extension of theSims and LaFollette Study," pp. 371-392.
38
computed between the organizational communication and the job satisfac
tion and organizational climate variables, and between the organizational
climate and job satisfaction variables. Organizational climate and job
satisfaction were found to be significantly related, with 29 of the 30
correlations significant (p < .05 or less). Forty-seven percent of the
correlations between the 6 climate dimensions and the 16 communication
dimensions were found to be significant (p. < .01 or p. < .001). The
communication dimensions of trust, influence, accuracy, directionality-
downward, directionality—lateral, and satisfaction with communication
were significantly related to all or most of the dimensions of organiza
tional climate. On the other hand, gatekeeping, overload, written
modality, and other modality were not related to any of the climate
dimensions. The pattern of significant communication/job satisfaction
correlations is similar to the communication/climate correlations, with
47 percent being significant. Trust, influence, desire for interaction,
accuracy, directionality-lateral, and satisfaction with communication
were correlated significantly with most or all of the satisfaction
dimensions, while overload and written modality were not significantly96related to any of the satisfaction dimensions. One could infer from
this that job satisfaction is more closely related to the content of
communication than to its volume or mode of transmission. Basic statis
tics (means, standard deviations, and reliabilities) for the variables
included within each of these three areas of study as reported by
Muchinsky may be found in Appendix G.
^Muchinsky, (1977-C), Op. cit., p. 597.
39
Muchinsky points out that this investigation was undertaken at the
"individual" level of analysis, and that the term "Organizational" when
associated with communication should probably be labelled as individual
communication in organizations since no items dealing with communication
across departments and other organizational sub-units are included. At
the same time, the author summarizes the study by stating that the
findings indicate that certain dimensions of communication are related
to both perceived climate and job satisfaction.
The implications of these findings are potentially of great value
to practitioners and organizational scholars alike in studying and
understanding the workings of organizations.
Although no suggestions of causality are made by Muchinsky, the
correlations between the components of each of the constructs are clear.
Thus, any changes in the communication system of an organization, for
example should have a predictable effect on organizational climate
and/or job satisfaction. Of course, the inverse of this statement
should also hold. The end result then would be a greater understanding
of how the components that make up the system of organizational behavior
in an organization work together.
Summary of the Literature
The interrelationships among organizational communication, organiza
tional climate and job satisfaction have been discussed in the literature
from several different perspectives. The many different variables,
methodologies, and types of organizations reported make the ability to
generalize findings tenuous at best. Yet, there appears to be a general
agreement that these interrelationships not only exist, but are important
to both organizational functioning and the quality of work life.
40
The research concerned with the organizational communication/organi
zational climate relationship is made up almost entirely of correlational97 98 99studies utilizing perceptual data. Hall, Holland, et.al., Long,
Ireland, et.al.,*^ all seem to conclude that the organizational climate
affects the nature of organizational communication in organizations.
The perceptual climate factors of trust, openness, warmth, etc. are the
most important in the relationship. In particular, these authors can be
summarized by saying good or positive climates lead to effective organi
zational communication.
On the other hand, O'Reilly and Roberts^* have suggested the
reverse relationship, that organizational communication affects organi-102zational climate. Muchinsky's work indicates that the relationship
is significant and important, but makes no statements regarding the
direction of the relationship.
Long^^ and O'Reilly and Roberts*^ go one step further In their
research to tie communication and climate to organizational performance.
■^Hall, Op. cit.98Holland, et.al., Op. cit.99Long, Op. ext.
1 Ireland et.al. , Op. cit.
^^O'Reilly and Roberts, Op. cit 102Muchinsky, 1977-A, Op. cit.1 0 3 tLong, Op. cit.104 O'Reilly and Roberts, Op. cit.
41
These authors state that the nature of the relationship between organi
zational communication and organizational climate in an organization
will affect its performance.
There is greater agreement among the researchers who have studied
the organizational communication/job satisfaction relationship. Again,
a multitude of instruments, methodologies, and types of organizations
have been reported, yet most of the authors (Merryman and Shani,^^
Futrell and F or tu ne ,S wa n and Futrell,*^ and Baird and Bradley*^)
conclude that organizational communication systems and practices affect109the level of job satisfaction in organizations. Downs and Hazen, as
well as Churchill,note the significance of the interrelationship,
but do not draw conclusions concerning the direction of the relationship.
Muchinsky, has studied the interrelationships among each of the
three concepts under discussion. His conclusions are that these rela
tionships are both significant and important. He makes no statements
concerning causality and/or the direction of these relationships, but
feels that more research into the concepts and their interrelationships
is warranted. It is only through such further study that a greater
105Merryman and Shani, Op. cit.106„ ., . _ _Futrell and Fortune, Op. cit.
^^Swan and Futrell, Op. cit.108Baird and Bradley, Op. cit.109Downs and Hazen, Op. cit.
^^Churchill, Op. cit.
^^Muchinsky, (1977-C), Op. cit.
42
understanding of the interaction of these three important concepts can
be achieved. Additional study into
light on how these concepts interact
this complex relationship may shed
to affect behavior in organizations.
CHAPTER III
METHODOLOGY UTILIZED
Design of the Sample
The respondents that make up the sample for this study are employees
from a local government agency in a midwestern city of approximately
300,000. This agency has been in existence since 1975, and coordinates
the use of city, state, and federal funds pertaining to housing, economic
development, and community development programs of the city. Because of
its broad areas of responsibility, the agency carries out many programs
which cut across departmental and agency boundaries. The 1979-80 budget
for this department was in excess of 12 million dollars.
Questionnaires were passed out randomly to 175 of the 220 total
employees of the agency. The only restriction on the sample was to
attempt to cut across all organizational levels to obtain a representa
tive perception of communication, climate and satisfaction as a whole.
The demographic make up of the respondents who returned questionnaires
appears to be representative of the organization in that the mean
responses on the demographic questions at least intuitively fits the
range of individuals employed by the organization. The director of per
sonnel for the organization under study has also indicated that the
sample Is representative. A summary of thisinformation may be found in
Appendix E.
43
44
One hundred and sixty-two questionnaires were returned. Nine of
these were discarded because of a large number of non-responses to the
questions, leaving a total of 153 usable questionnaires (an 87,4 percent
return rate). The questionnaires were distributed during working hours
to insure acceptable return rates and to aid in explaining the purpose
of the study. Respondents were guaranteed anonymity and encouraged to
respond as they actually perceived their reactions to the various
questionnaire items. The sample more than adequately meets the size112requirements as set forth by Gildea and Rosenberg for communication
audits for the 95 percent confidence level. The formulae used to
determine an adequate sample are as follows:
(1) „ .zitrnaiO ,2d
n(2) n = - °no
1 + N
where:
n^ = Sample Size Coefficient
Z = Standard Deviation Coefficient for a given confidence level (Z = .96 at a 95% confidence level)
P = Probability of a given response (p = .5 represents the maximum possible error)
Q = 1 - p
d = Percent of errors in the data (.05 is accepted as reasonable)
N = Total population (Number of Employees)! , 11.3n = Sample size required.
112Gildea and Rosenberg, "Auditing Organizational Communications: Is There Life Beyond Print-Outs?" pp. 7-12.
1 1 3 r w a Ibid.
45
The minimum sample size for the 95 percent confidence level is 134.
The 153 usable questionnaires easily exceeds this minimum (See Appendix
F for computations).
The questionnaire as administered consists of four parts: questions
concerning demographics to be used in later research; the Roberts and
O'Reilly Communication instrument; Litwin and Stringer's Organizational
Climate instrument - Form B; and, the Job Descriptive Index. Discussion
of the three research instruments follows.
Instruments Utilized in Data Collection
Communication Instrument114In 1974, Roberts and O'Reilly reported development of a 36-item
questionnaire designed to measure 13 aspects of perceived communication
in organizations, along with three aspects of interpersonal relations
that are thought to influence organizational communication. The non
communication facets include: trust in superior (three items), perceived
influence of superior (three items), and mobility aspirations of the
respondent (two items). The communication facets are composed of:
desire for interaction (three items); directionality of information
flow-upward (three items), -downward (three items), and -lateral (three
items); perceived accuracy (three items); degree of summarization (three
items); gatekeeping (three items); overload (two items); satisfaction
with communication (one item); and modality-written, -face-to-face,
-telephone, -other (one item each).
114Roberts and O'Reilly, (1974-C), Op. cit.
46
Subsequently, this questionnaire was expanded to a 46-item version
including questions concerning redundancy (one item), information
underload (three items), deliberate withholding of information (three
items), and information expansion (three items). In conjunction, a
ten-item scale with increased validity to measure openness and accuracy
was developed. It is this 46-item communication questionnaire with
the ten items measuring openness and accuracy that is utilized in this
study. A copy of this instrument can be found in Appendix A.
Organizational Climate Instrument
Form B of Litwin and Stringer's Organizational Climate Question
naire^^ is utilized to study the dimensions of organizational climate.
This instrument consists of 50 items scored on a four-point Likert
format, measuring nine a priori dimensions of climate. However, because
of doubtful reliability and validity of these original s c a l e s , s i x
derived climate dimensions, based on a factor analytic study by 118Muchinsky are utilized. These dimensions are: interpersonal milieu;
standards, affective tone toward management/organization; organizational
structure and procedures; responsibility; and organizational identifi-
Roberts and O'Reilly, "Assessing Communication in Organizations," Op. cit.
116Litwin and Stringer, Op. cit., pp. 204-207.
^^Sims and LaFollette, "An Assessment of the Litwin and Stringer Organizational Climate Questionnaire," pp. 19-38.
118Muchinsky, "An Assessment of the Litwin and Stringer Organizational Climate Questionnaire: An Empirical and TheoreticalExtension of the Sims and LaFollette Study," Op. cit.
47
cation. These factors have increased reliability and validity compared
to the original nine a priori dimensions. A copy of this instrument can
be found in Appendix B.
Job Satisfaction Instrument119The JDI developed by Smith, et.al., is utilized to measure five
dimensions of job satisfaction. This instrument consists of 72 items
scored on a three-point scale measuring satisfaction with work, satis
faction with supervision, satisfaction with pay, satisfaction with
promotions, and satisfaction with co-workers. The JDI has been shown to
be a reliable and valid measure of the job satisfaction concept through120extensive research. This instrument can be located for review in
Appendix C, along with norms and scoring sheets found in Appendix J.
Tables I, II, and III, on the following pages, list the working
definitions of each of the variables included within each of the three
concepts under study. The means, standard deviations, and reliabilities121for each of these variables as reported in Muchinsky's previous study
may be found in Appendix G.
Demographic data of interest have also been collected. This infor
mation determined the general demographic characteristics of the sample.
See Appendix E for details, as noted previously. Also, a copy of the
questionnaire as it was handed out may be found in Appendix D.
119Smith, Kendall and Hulin, Op. cit.120Muchinsky, (1977-C), Op. cit.
121Ibid.
48
TABLE I
WORKING DEFINITIONS OF COMMUNICATION VARIABLES
ComputerAbbreviation Variable Working Definition
TRUST TRUST Perceived trust in superior
INFLUENC SUPERVISOR'S INFLUENCE Perceived influence of supervisorRespondent's aspiration for job mobility
MOBILITY MOBILITY ASPIRATIONS
INTERACT DESIRE FOR INTERACTION Respondent’s desire for interaction with others
DIRUP DIRECTIONALITY-UPWARD Perceived percentage of upward communication flow
DIRDOWN DIRECTIONALITY-DOWNWARD Perceived percentage of downward communication flow
DIRLATRL DIRECTIONALITY-LATERAL Perceived percentage of lateral communication flow
ACCORR ACCURACY-ORIGINAL perceived accuracy of communiMEASURE cation
SUMMARIZ MESSAGE SUMMARIZATION Perceived degree of message summarization
GATEKEEP GATEKEEPING Perceived degree to which messages are stopped from spreading further through the organization
COMMSAT SATISFACTION WITH Perceived overall satisfactionCOMMUNICATION with communication
OVERLOAD COMMUNICATION OVERLOAD Perceived degree to which too much information is received by the respondent
WITHHOLD WITHHOLDING OF MESSAGES Perceived degree to which messages are deliberately withheld from others
EXPAND MESSAGE EXPANSION Perceived degree to which messages are expanded
CHANGE MESSAGE CHANGE Perceived degree to which messages are actively changed as they are passed on
OPENNESS OPENNESS Perceived degree of interpersonal openness
ACCNEW ACCURACY-NEW MEASURE Perceived accuracy of communication (greater reliability than ACCORR)
49
TABLE II
WORKING DEFINITIONS OF CLIMATE VARIABLES
ComputerAbbreviation Variable Working Definition
INTERMIL INTERPERSONAL MILIEU Perceived interpersonal relations environment or atmosphere within the organization
STANDARD STANDARDS Perceived degree to which the organization has established exacting standards of quality and performance
TONETMGT AFFECTIVE TONE TOWARD MANAGEMENT/ORGANIZATION
Perception of Management; where "Management" represents organizational "higher-ups" and their image
STRUCTUR STRUCTURE AND PROCEDURES
Perceptions of procedures, red tape, and organizational structure
RESPONSI RESPONSIBILITY Perception of who has ultimate responsibility for "getting the job done" within the organization
ORGIDENT ORGANIZATIONALIDENTIFICATION
Perception of feelings of being a part of the organization— Involves feelings of organizational pride, loyalty and teamwork
Source: Muchinsky, "An Assessment of the Litwin and Stringer Organizational Climate Questionnaire: An Empirical and TheoreticalExtension of the Sims and LaFollette Study," Personnel Psychology, Vol. 29, (1976), p. 375-6.
50
TABLE III
WORKING DEFINITIONS OF SATISFACTION VARIABLES
Computer Abbreviations Variable Working Definitions
SATWRK SATISFACTION WITH WORK
Perceived satisfaction with the work itself; i.e., the nature of the respondent's job
SATPAY SATISFACTION WITH PAY
Perceived satisfaction with the level of pay in the respondent's job
SATPROMO SATISFACTION WITH PROMOTIONS
Perceived satisfaction with the respondent's opportunity for promotions within the organization
SATSUPER SATISFACTION WITH SUPERVISION
Perceived satisfaction with the method of supervision of the respondent
SATPEOPL SATISFACTION WITH PEOPLE
Perceived satisfaction with coworkers, peers, i.e., the people the respondents work with
Techniques of Data Analysis Utilized
Previous research of this nature has typically relied on correla
tions among the individual variables associated with each concept to
draw conclusions. Then, general statements like, "concept A appears to
be related to concept B on the basis of the significant correlations
among the variables" are used to express overall relationships. This
research effort attempts to go beyond this stage of analysis by utilizing
canonical correlation analysis, (e.g., Canonical Analysis) which is the
most generalized member of the family of multivariate statistical
techniques. Canonical analysis facilitates the study of interrela-
51
tionships among constructs that are best explained through multiple
variables. That is, while multiple regression predicts a single depen
dent variable from a set of multiple independent variables, canonical
analysis predicts multiple dependent variables from multiple independent
variables. The goal of canonical analysis is to determine the indepen
dent dimensions which relate one set of variables to another set of 122variables.
Canonical analysis is capable of measuring:
L) The strength of the relationship between two sets of variables through the canonical correlation coefficient, which is interpreted in the same vein as a simple correlation coefficient. Canonical correlation also produces a measure of the total amount of variation in the criterion variable explained by the predictor variable.
2) Canonical analysis also provides an index of the degree to which each variable within the set of predictor variables is related to its respective set. That is, the amount of contribution of a particular variable towards explaining the a^^n-t of variance explained by the composite variable .
By utilizing this technique, it is possible to develop a number of
independent canonical functions which will maximize the correlation
between the linear composite of sets of criterion and predictor vari
ables. Usually, the number of canonical functions is equal to the
number of variables in the smaller composite variable.
Like most statistical techniques, there are certain limitations to
the use of canonical analysis. These limitations include:
1) The canonical correlation reflects the variance shared by the linear composites of the sets of variables, and not the variance extracted from the variables;
122Hair, et.al., Multivariate Data Analysis, pp. 180-181,123Swan and Futrell, Op. cit.
52
2) Canonical weights derived in computing canonical functions are subject to a great deal of instability;
3) Canonical weights are derived to maximize the correlation between linear composites, not to maximize the variance extracted; and
4) It is difficult to identify meaningful relationships between the subsets of independent and dependent variables because precise statistics have not yet been developed to interpret canonical analysis and we must rejL^ on inadequate measures such as loadings or crossloadings.
However, a method has recently been developed to test the signif
icance of the "redundancy" of relationships measured through canonical
analysis. Redundancy is essentially a measure of the practical signif
icance of the canonical relationships between two sets of variables.
"This statistic Ry/x summarizes in a single value the proportion of
total variation in a set of criterion variables (Y) that may be explained125by shared variation with a set of predictor variables (X)." Thus,
2redundancy is also the average R for a set of predictor variables
(taken as a set) able to explain variation in each of the criterion
variables (taken one at a time). The test statistic for the significance
of redundancies is analogous to the F-test for regression analysis, and
fits F-distribution statistics. The test statistic for the significance
of redundancy is:
*Y/X (N-p-l)q1 ' R2 pq1 h / x
124Hair, et.al., Op. cit., p. 192.125Alpert, Peterson, and Martin, "Testing the Significance of
Canonical Correlations," pp. 118.
53
where df^ = pq and df^ = (N-p-l)q; N = subjects; p = number of "indepen-126dent" or predictor variables, q = number of "dependent" variables.
The organizational communication composite variable has been
arbitrarily utilized as the predictor variable in the canonical analysis
of both the organizational climate and job satisfaction composite
variables. Organizational climate is arbitrarily designated the predic
tor variable in the canonical analysis of climate and job satisfaction.
However, redundancy analysis will yield the percentage of variation in
either variable that can be explained by the other variable, making the
designation as predictor/criterion variable superfluous.
Thus, the statistical analysis of each of the hypotheses will 127determine the strength of the relationships between the concepts
under study. Further, the redundancy, or the ability of each of the
variables to explain the variance in the other variables, will provide
additional information about the concepts.
I26Ibid., pp. 117-119.127The "strength" of the relationships refers to the amount of
significant correlation between the concepts. Canonical correlations of 0.60 or greater will be considered strong relationships. Canonical correlation values of 0.30-0.59 will be considered moderate, while canonical correlations of less than 0.30 will be considered weak. These same divisions should be considered as applicable to redundancy measures as well.
CHAPTER IV
STATISTICAL ANALYSIS
After data collection was completed, statistical analysis was128undertaken. The Statistical Package for the Social Sciences was
utilized to analyze the data related to the four hypotheses. In parti
cular, the CANCORR subroutine was used to develop the canonical analysis
that tests the hypothesized relationships. "Compute" statements were
utilized to combine individual questions from the communication and
climate instruments into their composite variables. The satisfaction
variables were scored by hand according to directions from Smith,129et.al. (See Appendix J for scoring directions and norms). These
computations allowed the development of individual scores on each of the
variables from each of the respondents. Raw means for each of the
variables replaced missing responses. Adjusted means and standard devi
ations for each of the variables may be found in Table IV. The computer
program may be found in Appendix H.
Analysis of Hypothesis I
Hypothesis I concerns the relationship between organizational
climate and job satisfaction. It is hypothesized that these two
concepts have a strongly positive, significant relationship. Canonical
Nye, et.al., Statistical Package for the Social Sciences.129Smith, P.C., et.al., Op. cit.
54
55
TABLE IV
MEANS AND STANDARD DEVIATIONS OF VARIABLES
Number ofCOMMUNICATION VARIABLES Trust
Items
3
Range
3-21
Means*
8.5882
Std. Dev.’
4.1573Superior's Influence 2 2-14 6.9150 3.6544Mobility Aspirations 2 2-11 7.6601 1.3286Desire for Interaction 3 2-20 8.2092 4.1733Directionality-up 3 0-20 8.7843 4.2456
-down 3 0-14 5.6732 4.8134-lateral 3 0-21 7.9477 4.2717
Accuracy (original measure) 3 3-21 9.6078 3.3447Summarization 3 3-21 9.3529 3.8653Gatekeeping 3 2-21 10.4379 3.7554Communication Overload 2 2-13 7.3072 2.0075Satisfaction with Communication 1 1-7 3.7190 1.6680
Modality-written 1 0-7 2.1765 1.4378-Face-to-Face 1 0-7 3.4575 1.6099-Telephone 1 0-7 2.0980 1.2288
Communication Redundancy 1 1-7 4,1307 1.7833Communication Underload 2 2-14 8.0784 2.9144Communication Withholding 3 3-21 7.6993 4.3906Communication Expansion 3 3-21 9.8758 3.5268Change in Communication 3 3-21 8.8366 4.5573Openness 5 5-35 17.8431 7.4561Accuracy (New) 5 5-35 16.6471 6.7828CLIMATE VARIABLESInterpersonal Milieu 5 12.12-23.86 20.1868 1.5196Standards 3 3.71-13.27 8.7133 1.5897Affective Tone Toward
Management/Organization 17 16.74-35.45 24.5656 3.6463Structure and Procedures 10 22.26-35.54 29.3910 2.1764Responsibility 7 8.48-18.12 13.5972 1.5852Organizational Identification 5 12.71-24.86 20.6319 1.5308SATISFACTION VARIABLESSatisfaction with Work 18 6-54 31.3725 11.6585Satisfaction with Pay 9 0-48 19.1242 13.0532Satisfaction with Promotions 9 0-54 14.1699 14.8034Satisfaction with Supervision 18 0-54 41.1111 11.2329Satisfaction with People 18 0-54 34.7778 13.4376
* Means are adjusted by substituting raw mean values for blanks through SPSS "Recode" procedure
** N = 153 cases
functions based on the data were developed and are displayed in Table V.
The first canonical function is significant beyond the p <0.001 level
and is presented along with the corresponding canonical loadings for
each of the variables. The remaining canonical functions were not
significant at the p < 0.05 level, and are not reported in detail.
TABLE V
CANONICAL ANALYSIS OF ORGANIZATIONAL CLIMATE/JOB SATISFACTION RELATIONSHIP
Number EigenvalueCanonicalCorrelation
WilkesLambda
ChiSquare D.F. Significance
123
0.439410.051740.03004
0.662880.227460.17332
0.505990.902610.95186
99.4602114.959317.20296
302012
0.0000.7790.884
ClimateVariables L
Canvar1 i 7
INTERMILSTANDARDTONETMGTSTRUCTURRESP0NSIORGIDENT
- 0.38499 0.27255 0.80273
- 0.28740 0.50413
- 0.06580IL2
.1482
.0743
. 6444
.0826
.2541
.0043= 1.2079
SatisfactionVariables
SATWRKSATPAYSATPROMOSATSUPERSATPEOPL
- 0.52387 0.11627
- 0.41402- 0.15487- 0.24981
IL2
0.27440.01350.17140.02400.0624
= 0.5457
57
As noted above, the first canonical function is statistically
significant beyond the p < 0.001 level. Also, the first function has a
canonical correlation of 0.66288 and an eigenvalue or canonical root of
0.43941. The canonical correlation of 0.66288 indicates that there is
an important and significant relationship between the two sets of
variables, just as a simple correlation coefficient of 0.66 would
indicate an important relationship.
The canonical root, which is the square of the canonical correla
tion coefficient, indicates the amount of variation in the criterion set
(satisfaction) that is explained by the predictor set (climate). The
value of 0.43941 indicates that a moderate amount of the variance in job
satisfaction is shared with the organizational climate set.
The climate variables which have canonical loadings of a magnitude
of at least 0.30 may be interpreted as being important in explaining the130relationships between the variables. One can see from a review of
Table V that the climate variable of Affective Tone Toward Management/
Organization is the most important of the climate variables with a
canonical loading of 0,80273. Responsibility (L=0.50413) is a second
variable that is important in explaining the relationship between
organizational climate and job satisfaction. Interpersonal Milieu, with
a loading of -0.38499, is also important (negative signs are interpreted
just as in typical correlational analysis). The Standards, Structure,
and Organizational Identification variables appears to have little
effect on the relationship between climate and job satisfaction. Thus,
three of the six organizational climate variables are important in
130Hair, et.al., p. 191.
58
explaining the relationship between climate and job satisfaction. Two
of the three have positive signs, while one has a negative sign.
The most important satisfaction variable is Satisfaction with Work
with a loading of -0.52387. Satisfaction with Promotions is also
important in the relationship with climate, having a loading of
-0.41402. Satisfaction with People, Satisfaction with Fay, and
Satisfaction with Supervision have little, if any, effect on the
relationship between organizational climate and job satisfaction. Thus,
only two of the five variables that make up the job satisfaction concept
are important in explaining the relationship between climate and
satisfaction. Both of the satisfaction variables considered important
have negative signs.
Given the canonical correlation coefficient of 0.66288, and its
statistical significance (p < 0 .001), one can conclude that the concepts
of organizational climate and job satisfaction are significantly related
to one another. Therefore, Hypothesis I should be accepted. However,
it is difficult to determine if the relationship is positive as hypothe
sized, since important loadings on both concepts show positive and
negative signs. Three of the six climate variables are considered
important in explaining the variance in the satisfaction set (L>0.30).
One of these, Interpersonal Milieu has a negative relationship to the
variables in the job satisfaction set. The other two considered as
important, Affective Tone Toward Management/Organization and
Responsibility, have positive relationships with the job satisfaction
set.
59
On the other hand, both of the job satisfaction variables con
sidered as important to the relationship have negative signs and
relationships with the climate set. One can conclude that the negative-
negative relationship of one of the climate variables to the satisfac
tion variable set is actually a direct but negative relationship. That
is, the more negatively Interpersonal Milieu of this organization are
perceived by the respondents, the more negative will be levels of job
satisfaction associated with Satisfaction with Work and Satisfaction
with Promotions.
An inverse relationship exists between the climate variables
Affective Tone Toward Management/Organization and Responsibility and the
important job satisfaction variables. These directional differences
make it difficult, if not impossible, to determine the directionality of
the relationship between the concepts for the sample under study. In
fact, the relationship has both positive and negative aspects.
The significant canonical correlation coefficient of 0.66288
indicates that the concepts of organizational climate and job satisfac
tion are strongly and significantly correlated. As stated above,
however, the relationship has both positive and negative effects. Thus,
Hypothesis I can be only partially accepted.
Analysis of Hypothesis II
Hypothesis II considers the question of whether organizational
climate and job satisfaction are actually different or redundant con
cepts. As noted in Chapter 2, this question has led to an ongoing
controversy in the organizational behavior literature. The question is
addressed through redundancy analysis of the canonical correlation
discussed in the previous section of this chapter.
60
Redundancy analysis seeks to determine the amount of variance in
one set of variables that can be explained by another set of variables
in canonical analysis. If the degree of redundancy between organi
zational climate and job satisfaction were high, then one could conclude
that these are very similar, or possibly identical concepts, which
address the same organizational phenomena from different directions. On
the other hand, if the level of redundancy is relatively low, one could
conclude that these are different but related (given acceptance of
Hypothesis I) concepts. That is, the two concepts measure different but
related organizational phenomena.
Computation of redundancy indices for both the climate and satis
faction variable sets is located in Table VI. Only 8.85 percent of the
variation in the satisfaction set can be explained by the climate
variables. This percentage is significant beyond the p < 0.01 level.
Similarly, only 4.180 percent of the variation in the climate variable
set can be explained by the job satisfaction variable set (significant
at p < 0.05). Thus, there appears to be very little redundancy between
the two variable sets, although they are significantly correlated with
each other. One may conclude then, that given these low levels of
redundancy, job satisfaction and organizational climate should be
considered as different concepts that measure different organizational
phenomena for this sample at least. Hypothesis II should be accepted.
Analysis of Hypothesis III
Hypothesis III states that, "Organizational communication has a
strongly positive, significant relationship to organizational climate."
Again, canonical analysis is utilized to test the hypothesis. The first
61
TABLE VIr
REDUNDANCY INDEX FOR ORGANIZATIONAL CLIMATE/JOB SATISFACTION CANONICAL ANALYSIS
CanonicalFunction Root
VarianceExtracted Redundancy
Proportionof
Redundancy
.4394
0.43941
Dependent Set (Climate)
.2013
Independent Set (Satisfaction)
0.1092
.0885
,0480
100%
100%
Significance of Redundancy Index
Dependent Set
N = 153 P = 6 Q = 5
F = R2y 1x 1-R2y|x
F = 0.088471-0.08847
F = 2.3628
(N-P-l)QPQ
(153-6-1)5(5){6)
F.99(3Q,«) = 1.70
-2 iSince 2.3628 > 1.70, conclude R y|x is significant at the p < 0.01 level
Independent Set
N = 153 P = 5 Q = 6
F = R2x|y 1-R2y|x
F = 0.04801-0.0480
F = 1.48
(N-P-1)(Q)PQ
(153-5-1)6 (5)(6)
F.95(30*") = K46_2
Since 1.48 > 1.46, conclude R xjy is significant at the p < 0.05 level
62
two canonical functions are significant beyond p < 0.001 level and are
presented in Table VII. The first canonical function is derived:
...to have the highest intercorrelation possible between the two sets of variables. The second pair of canonical variates [is] derived so that they will exhibit the maximum amount of relationship between the two sets of variables which was not accounted for by the first pair of variates [and so on.]...Each of the pairs of variates is orthogonally indepeiju^nt of all other variates derived from the same set of data.
Canonical Function I
The canonical correlation coefficient of the first function is
0.70745 (p < 0.001). This value represents a significant relationship
between the organizational communication and organizational climate data
sets. The canonical root of 0.63593 indicates that 63.6 percent of the
variance within the two data sets is shared.
Only those variables with loadings of 0.30 or greater are inter
preted as being important in explaining the relationship between
communication and climate. The communication variables of Openness
(L=0.50919) and Satisfaction with Communication (L=0.36675) are
important to the relationship.
The climate variables of Organizational Identification (L=0.67591),
Responsibility (L=0.65006), and Affective Tone Toward Management/Organ
ization (L=0.59782) have a direct relationship to the communication set.
The negative signs of the climate variables, Interpersonal Milieu, with
a loading of -0.82934, and Structure and Procedures (L=-0.67463),
indicate an inverse relationship to the variables of the communication
set. The Standards variable is not interpreted as important in explain-
131Hair, et. al., Op. cit., p. 183.
63
TABLE VII
CANONICAL ANALYSIS OF ORGANIZATIONAL COMMUNICATION/ ORGANIZATIONAL CLIMATE RELATIONSHIP
Number EigenvalueCanonicalCorrelation
WilkesLambda
ChiSquare D.F. Signif icai
1 0.63593 0.79745 0.11189 301.15771 132 0.0002 0.39744 0.63043 0.30733 162.22499 105 0.0003 0.23092 0.48054 0.51005 92.57140 80 0.159
CommunicationVariables
CanvarL
Canvar II „ L L
TRUST 0.18431 .0340 - 0.22634 .0512INFLUENC 0.00498 .000025 0.56419 .3193MOBILITY 0.01466 .0002 - 0.07114 .0051INTERACT 0.04558 .0021 0.08619 .0074DIRUP - 0.13255 .0176 0.09326 .0087DIRDOWN - 0.20096 .0404 0.07238 .0052DIRLATRL 0.09875 .0098 0.29450 .0867ACCORR - 0.08431 .0071 - 0.29123 .0848SUMMARIZ - 0.10199 .0104 - 0.06905 .0048GATEKEEP - 0.11976 .0143 0.03072 .0009OVERLOAD - 0.05916 .0035 0.13358 .0178COMMSAT 0.36675 .1345 - 0.11539 .0133MODEWRIT 0.13432 .0180 - 0.28956 .0838MODEFTF 0.05308 .0028 - 0.51918. .2695MODETELE - 0.06760 .0046 - 0.46037 .2119REDUND 0.25113 .0631 - 0.22557 .0509UNDERLOD - 0.11971 .0143 - 0.40963 .1678WITHHOLD - 0.07073 .0050 - 0.32726 .1071EXPAND - 0.10319 .0106 0.00607 .000037CHANGE - 0.06602 .0044 - 0.02852 .0008OPENNESS 0.50919 .2593 - 0.00325 .000011ACCNEW - 0.14059 .0198 0.24043 .0578
EL2 = .6758 EL2 = 1.5541
INTERMIL - 0.82934 .6878 0.83518 .6975STANDARD 0.00015 -0- 0.33733 .1138TONETMGT 0.59782 .3574 0.07100 .0050STRUCTUR - 0.67463 .4551 - 0.85676 .7340RESPONSI 0.65006 .4226 - 0.22267 .0496ORGIDENT 0.67591 .4569 0.67280 .4527
2EL = 2.3798 EL2 = 2.0525
64
ing the relationship between the two variable sets for this sample.
Canonical Function II
The second function has a canonical correlation of 0.63043, again
indicating a relatively strong, significant relationship between organi
zational communication and organizational climate from the remaining
variance (p < 0.001). The canonical root of the second function is
0.39744. Because of the wide range in magnitude of loadings in the
second canonical function, only those loadings with values of 0.30 or132greater are considered interpretable. As noted by Hair, et.al., this
procedure facilitates interpretation and makes the findings more concep
tually manageable.
Influence of Superior (L=0.56419) is the only communication
variable positively related to the climate set. The other interpretable
communication variables are inversely related to the climate set. These
include: Modality— Face-to-Face (L=-0.51918), Modality— Telephone
(L=-0.46037), Underload (L=-0.40963), and Withholding of Information
(L=-0,32726). None of the other communication variables have loadings
large enough (L < 0.30) to be considered as important in explaining the
communication-climate relationship.
Interpersonal Milieu with a loading of 0.83518, Organizational
Identification with a loading of 0.67280, and Standards with a loading
of 0.33733 are the climate variables that are both interpretable as
important to the relationship and positively related to the
communication set. The climate variable of Structure, having a loading
of -0.85676, is inversely related to the variables in the communication
.set.
132 Ibid., p.191.
65
To reiterate, there is a significant relationship between the
variables in the organizational communication set and the climate set
for the sample under study. The question of the direction of this
relationship, however, is cloudy. In the first canonical function two
communication variables are considered important and are positively
related to three of the climate variables. These communication
variables are inversely related to two of the other important climate
variables. Thus, a slight majority of the relationships between the
variables are positive and direct.
In the second canonical function, a quite different situation
exists. Of the five communication variables considered important in
explaining the relationship to climate, only one is positive. Four of
the climate variables are considered important in explaining the rela
tionship to communication. Of these, three are positively related,
while one is inversely related to the communication set.
There are no communication variables common to the two significant
canonical functions, while two of the climate variables (Interpersonal
Milieu and Organizational Identification), are found in both functions.
The Interpersonal Milieu variable is inversely related to the communica
tion set in the first canonical function, and directly related in the
second. Organizational Identification is directly related to the
communication set in both functions. It should be noted that in total,
only seven of the twenty-two communication variables are considered
important in explaining the relationship to organizational climate.
Each of the climate variables, however, is considered important in
explaining the relationship to communication in one or the other or both
of the significant canonical functions.
66
Redundancy Analysis
There Is some tendency when using canonical roots as a measure of
the shared variance between two variable sets to overestimate the amount
of shared variation. Redundancy analysis has been developed to over
come this inherent bias. The redundancy index "provides a summary
measure of the ability of a set of predictor variables (taken as a set)
to explain variation in the criterion variables (taken one at a 133time)."
Thus, even though the first two canonical functions are highly
significant (p < 0.001), the redundancy indices given in Table VIII shed
additional light on the relationship between the variable sets. Only
4.76 percent of the variation in the organizational communication set is
explained by the canonical variate for the organizational climate set.
A little more encouraging is the 38.82 percent of the variance in the
organizational climate set that is explained by the canonical variate of
the organizational communication set. When considering the number of
variables in each set considered as important, these shared variation
figures (redundancies) are particularly interesting. Both redundancy
indices are significant at the p < 0.01 level.
Summary of Hypothesis III
Given the canonical correlations of the two significant canonical
functions and the corresponding redundancy analysis, one may conclude
that there is a statistically significant relationship between organiza
tional communication and organizational climate. Signs of the loadings
associated with the two functions cloud the question of whether the
133 Ibid., p. 193.
67
TABLE VIII
REDUNDANCY INDEX FOR ORGANIZATIONAL COMMUNICATION/ ORGANIZATIONAL CLIMATE CANONICAL ANALYSIS
CanonicalFunction Root
VarianceExtracted Redundancy
Proportionof
Dependent Set (Climate)
1 .635932 .39744
.0307
.0706
Independent Set (Communication)
.0195,0281.0476
.4094
.59091.0003
1 .635932 .39744
.3966
.3421.2522.1360.3882
.6496
.3503
.9999
Significance of Redundancy Index
Dependent Set F = R2y|x (N-P-l)(Q)
N = 153 P = 6 Q = 22
1-R2y|x
F = .0476
(P)(Q)
(153-6-l)(22)1-.0467 (22)(6)
1.2167
F ( co oo } ss.99 132, 130 1.00
_ 2Since 1.2167 > 1,00, conclude R y|x is significant beyond the
p < 0.01 level
Independent Set
N = 153 P = 22 Q = 6
F =
F =
R2x|y1-R2x|y
.38821-.3882
3.7493
(N-P-11(0) (P)(Q)
(153-22-1)(6) (6)(22)
I* ( OO 00 \ SS 1 00.99 130 132
Since 3.7493 > 1.00, conclude R x|y is significant beyond the p < 0.01level
68
relationship is positive or negative. It appears that the relationship
between organizational communication and organizational climate has both
positive and negative aspects. Thus, although the direction of the
relationship is unclear, a slight majority (9-7) of the important load
ings are positive. Thus, there is enough support to accept Hypothesis
III.
Analysis of Hypothesis IV
Hypothesis IV focuses on the relationship between organizational
communication and job satisfaction. It is hypothesized that this
relationship is a strongly positive and significant relationship.
Canonical analysis is again utilized to test Hypothesis IV. Only the
first two canonical functions are significant at or beyond the p <. 0..001
level and are presented in Table IX. Since the other canonical func
tions are not significant at the p < 0.01 level, only the first two
functions are presented in detail.
Canonical Function I
The first canonical function explaining the relationship between
organizational communication and job satisfaction has a canonical
correlation of 0.71837. This value indicates a significant relationship
between the two sets of variables. The canonical root of 0.51605
represents a 51.6 percent shared variance between communication and
satisfaction.
The communication variables of Satisfaction with Communication and
Openness, with canonical loadings of -0.57066 and -0.30886,
respectively, are the only variables with loadings of sufficient
magnitude to interpret as important to the relationship. These two
69
TABLE IX
CANONICAL ANALYSIS OF ORGANIZATIONAL COMMUNICATION/ JOB SATISFACTION RELATIONSHIP
Canonical Wilkes ChiNumber Eigenvalue Correlation Lambda Square D.F. Significance
1 0.51605 0.71837 0.18590 232.19341 110 0.0002 0.37520 0.61254 0.38413 132.03662 84 0.0013 0.19990 0.44710 0.61480 67.13171 60 0.246
CommunicationVariables
CanvarL 1 2 L
CanvarL 11 2 L
TRUST 0.00177 .000003 0.66363 .4404INFLUENC 0.1515 .0002 0.32691 .1069MOBILITY 0.14136 .0200 0.05465 .0030INTERACT - 0.18380 .0338 - 0.10177 .0104DIRUP - 0.15122 .0229 - 0.14922 .0223DIRDOWN - 0.01218 .0001 - 0.04975 .0025DTRLATRL - 0.04705 .0022 - 0.00609 .00004ACCORR - 0.03245 .0011 - 0.25561 .0653SUMMARIZ 0.02280 .0005 - 0.18253 .0333GATEKEEP 0.03172 .0010 - 0.23618 .0558OVERLOAD - 0.13189 .0174 0.29904 .0894COMMSAT - 0.57066 .3257 0.04784 .0023MODEWRIT - 0.15758 .0284 - 0.22978 .0528MODEFTF - 0.14613 .0214 - 0.04959 .0025MODETELE 0.00543 .00003 - 0.26014 .0677REDUND - 0.00303 .000009 0.09175 .0084UNDERLOD 0.12689 .0161 - 0.09834 .0097WITHHOLD 0.13204 .0174 - 0.06449 .0042EXPAND - 0.15825 .0250 - 0.01235 .0002CHANGE - 0.02494 .0006 0.10670 .0114OPENNESS - 0.30886 .0954 - 0.27270 .0744ACCNEW 0.03364 .0011 - 0.21006 .0441
IL2 - .6268 EL2 - 1.1068
SatisfactionVariables
SATWRK 0.35823 .1283 - 0.01169 .0001SATPAY - 0.01687 .0003 0.20263 .0411SATPROMO 0.25167 .0633 - 0.43660 .1906SATSUPER 0.18165 .0330 - 0.80347 .6456SATPEOPL 0.54076 .2924 0.83339 .6945
IL2 = .5173 EL2 = 1.5719
70
communication variables are inversely related to the job satisfaction
variables of Satisfaction with People (L=0.54076) and Satisfaction with
Work (L=0.35823).
Canonical Function II
The canonical correlation of the second function explaining the
communication-satisfaction relationship is 0.61254. This value again
points toward a significant relationship between communication and
satisfaction. The variance shared between the two variable sets is 37.5
percent, since the canonical root of this function is 0.37520.
Trust in Superior (L=0.66363) and Influence of Superior (L=0.32691)
are the most important of the communication variables. These two
variables indicate a direct relationship with job satisfaction.
Satisfaction with People, with a loading of 0.83339 is the most
important of the satisfaction variables in explaining the relationship
to organizational communication. Satisfaction with Supervision
(L=0.80347) and Satisfaction with Promotions (L=0.43660) are also
important to the relationship to communication.
Again, canonical analysis indicates a statistically significant
relationship (p < 0.001) between the two variable sets. Canonical
correlations of 0.71837 and 0.61254, respectively, indicate at least a
moderately strong relationship between organizational communication and
job satisfaction for the sample organization. Whether this relationship
may be characterized as positive or negative is uncertain, since
loadings of the variables considered important (L < 0.30) in explaining
the relationship of each variable set to the other exhibit both positive
and negative signs, although a majority (5-4) of the loadings are
positive.
71
A total of four communication variables are considered important in
explaining the relationship between the two concepts in this sample.
Two have positive values, while two (Openness counted in both functions)
have negative values.
Of the job satisfaction variables, only Satisfaction with Pay is
not considered as important in explaining the relationship between
satisfaction and communication. Satisfaction with People has a positive
value and is common to both functions. A total of five satisfaction
variables (one counted twice) are important in explaining the relation
ship to organizational communication. Positive signs are associated
with three and negative signs with two. Thus, the component variables
of the communication concept show both direct and inverse relationships
with the job satisfaction variable set (and vice versa), with the
majority being positive.
Redundancy Analysis
The two canonical functions above are highly significant
(p < 0.001), as noted previously. Redundancy indices for the canonical
analysis, as shown in Table X, indicate that 17.14 percent of the
variance in the job satisfaction variables is explained by the variance
in the communication set. This redundancy is significant at the p < 0.05
level.
Variance in the job satisfaction set explains only 3.36 percent of
the variation in the organizational communication variables. This
redundancy, however, is not significant at the p < 0.10 level.
Summary of Hypothesis IV
A significant relationship between organizational communication and
job satisfaction is indicated by the canonical correlation coefficients
72
TABLE X
REDUNDANCY INDEX FOR ORGANIZATIONAL COMMUNICATION/ JOB SATISFACTION CANONICAL ANALYSIS
CanonicalFunction Root
VarianceExtracted Redundancy
Proportionof
Redundancy
12
.51605,37520
Dependent Set (Job Satisfaction)
.1035
.3144
Independent Set (Organizational Communication)
.51605
.37520.0285.0503
.0534
.1180
.1714
.0147,0189.0336
.3116
.68861 .0 002
.4378
.56281.0006
Dependent Set
N = 153 P = 22 Q = 5
Significance of Redundancy Index
F = R2y|*
F =
1-R2y|x
.1714 1 - .1714
(N-P-l)(Q) PQ
(153-22-1)5 (22)(5)
1.226
9 5 ( 1 2 0 * "> 1 . 2 2
Since 1.2226 > 1.22, conclude R y|x is significant at the p < .05 level
Independent Set
N = 153 P = 5 Q = 22
F = .03361-.0336
1.023
(153-5-1)22 (22)(5)
f .90(12°- -> 1.17
_2Since 1.023 / 1.17, we conclude R x|y is not significant at the p < .10
level
73
of the two significant canonical functions. Redundancy Analysis,
however, indicates that although the communication set explains a
significant amount of the variance in job satisfaction, the opposite
relationship (Satisfaction-Comrounication) is not significant at the
p < 0.1 level. This diminishes the certainty with which the nature of
the relationship between the two concepts may be stated. Hypothesis IV
is partially, but not strongly, supported by the data from the sample.
The two concepts are significantly correlated, but the strength and
direction of the relationship is unclear. Hypothesis IV should be
partially accepted. This lack of total commitment indicates that
further information is necessary to determine the actual nature of the
relationship between communication and satisfaction.
Analysis of Relationship of Demographics to Climate, Communication, and Satisfaction
The unsuspected and surprising directions of the relationships of
several of the component variables of organizational communication,
organizational climate, and job satisfaction to each other are difficult
to explain. Further research may shed light on these relationships. As
an ex post facto attempt to begin this research, the relationship
between the demographic data gathered and each of the concepts under
study has been investigated.
To be specific, canonical analyses of the demographic data and data
from each of the concepts studied were conducted to determine If the
perceptions of the concepts are affected by the demographic make up of
the sample. This analysis is of a purely exploratory nature so no
hypotheses have been stated.
Ik
Eight variables are included in the data set that make up the
Demographic Profile. These variables include: Age, Sex and Marital
Status, Childhood Environment, Level of Education, Years in Present Job,
Years With Sample Organization, Salary Level, and Number of Employees
Supervised. Means, standard deviations, ranges and computer abbre
viations of these variables may be found in Table XI. The average
respondent may be characterized as being between 30-39 years of age,
unmarried, from an unban background, with some college education, having
worked in the same job for the sample organization for seven months to
two years, making between $10,000 and $15,000 annually, and supervising
from zero to five employees. Standard deviations for the variables
indicate that there may be considerable deviation from this "average"
employee.
Variables included in the communication, climate and satisfaction
variable sets are the same as used previously. Refer to Table IV for
summary data for each of the variables within each concept.
As noted, the technique of canonical analysis is utilized to study
the relationship between the demographic variables as a set and each of
the concepts studied previously. Analyses of the three relationships,
i.e., Demographics/Organizational Climate, Demographics/Organizational
Communication, and Demographics/Job Satisfaction are discussed in the
following pages.
Demographics Versus Organizational Climate Relationship
No canonical correlation for this relationship is statistically
significant at the p < 0.05 level. Thus, one may conclude that for this
sample, there is no significant relationship between perceptions of
organizational climate and the demographic variables.
75
TABLE XI
SUMMARY OF DEMOGRAPHIC VARIABLES
VariableComputer
Abbreviation MeanStandardDeviation
ScoringRange
Age ACE 4.9085 2.6392 1-11
Sex and Martial Status SEXMAR 2.4771 1.0329 1-4
Childhood Environment ENVT 1.3203 0.6753 1-3
Level of Education EDUC 4.1046 1.3580 1-6
Years in Present Job YRSPRSJO 3.1307 1.4267 1-6
Years with Sample Organization YRSCD 2.2353 1.9255 i-6
Salary Level SALARY 4.7190 1.8117 1-8
Employed Supervised SUPERVIS 1.5621 1.0689 1-5
because of this lack of a significant relationship, statistical data are
not presented here. Refer to Appendix I for details of the analysis.
Demographics Versus Organizational Communication Relationship
Two canonical functions are significant at the p < 0.01 level in
the analysis of the relationship between the demographic variable set
and the organizational communication concept. These functions and their
corresponding loadings are displayed in Table XII. The first
significant function has a canonical correlation of 0.64652 and an
eigenvalue or canonical root of 0.41798. Thus, there is a significant
relationship between the two variable sets, with 41.798 percent of the
variance in the dependent set (Climate) shared with the predictor set
(Demographics).
76
TABLE XII
CANONICAL ANALYSIS OF DEMOGRAPHIC DATA/ORGANIZATIONAL COMMUNICATION RELATIONSHIP
Number Eigenvalue
123
0.417980.302030.28160
Canonical Wilkes Correlation Lambda
0.646520.549570.53066
0.13765 0.23651 0.33885
ChiSquare
270.68457196.80350147.72057
D.F. Significance
176174120
0.0000.0040.044
CommunicationVariables
Canvar I Canvar II
TRUSTINFLUENCMOBILITYINTERACTDIRUPDIRDOWNLIRLATRLACCORRSUMMARIZGATEKEEPOVERLOADCOMMSATMODEWRITMODEFTFMODETELEREDUNDUNDERLODWITHHOLDEXPANDCHANGEOPENNESSACCNEW
DemographicVariables
0.15179 0.00791 0.03606 0.03890 0.21454 0.81163 0.07373 0.25655 0.13839 0.10951 0.10127 0.14272 0.00862 0.12622 0.12624 0.07629 0.07629 0.02654 0.12719 0.07507 0.39616 0.01275
0.0230 0.0001 0.0013 0.0015 0.0464 0.6587 0.0054 0.0658 0.0192 0.0120 0.0103 0.0200 0.0001 0.0159 0.0159 0.0188 0.0058 0.0007 0.0162 0.0056 0.1569 0.0002
EL2 = 1.0998
0.37011 0.56550 0.05683 0.18470 0.14550 0.05307 0.27704 0.19172 0.41050 0.07427 0.04772 0.35243 0.24117 0.32810 0.12458 0.15664 0.34099 0.08266 0.01507 0.08702 0.05906 0.20455
0.1370 0.3198 0.0032 0.0341 0.0212 0.0028 0.0768 0.0368 0.1685 0.0055 0.0023 0.1242 0.0582 0.1076 0.0181 0.0245 0.1163 0.0068 0.0002 0.0076 0.0035 0.0418
EL2 = I.2168
AGE - 0.27301 0.0745 - 0.11529SEXMAR 0.19036 0.0362 - 0.44374ENVT - 0.09196 0.0085 0.65957EDUC - 0.37954 0.1441 - 0.41598YRSPRSJO - 0.07603 0.0058 - 0.05986YRSCD 0.24841 0.0617 0.01609SALARY 0.42303 0.1790 - 0.25968SUPERVIS 0.76810 0.5900 0.42483
EL = 1.0998
0.01330.19690.43500.17300.00360.00030.06740.1805
EL2 = 1.0700
77
Three of the Demographic variables may be considered as important
in explaining the relationship to the communication set. These include
Education (L=-0.37954), Salary (L=0.42303), and Employees Supervised
(1=0.76810). On the other hand, only two of the 22 organizational
communication variables are important in explaining the relationship
with the demographic variable set. These are Directionality-Downward
(L=0.81163) and Openness (L=0.39616).
The second significant canonical function has a canonical corre
lation of 0.54947 and a canonical root of 0.3023. Because of the
significance level (p < 0.004), and correlation coefficient, these
figures indicate a moderately strong relationship between the variable
sets, and a shared variance of 30.23 percent.
Four of the demographic variables are considered important in
explaining the relationship to the communication variable set.
Childhood Environment, with a loading of 0.65957, Educational Level
(L=0.41598), and Employees Supervised (L=0.42483) are directly related
to the organizational communication data set. Sex and Marital Status
(L=0.44374) is inversely related to the organizational communication
variables.
Only six of the 22 organizational communication variables are
important in explaining the relationship to demographics. Two of these
variables, Influence (L=-0.56550), and Modality-Telephone (L=-0,32810),
have inverse relationships with the demographic data set. The other
four are directly related to the demographic data set. These include
Trust in Superior (1=0.37011), Summarization (L=0.41056), Satisfaction
with Communication (L=0.35243), and Underload, (L=0.34099).
78
As noted previously, the two canonical functions reported are
statistically significant (p < 0.004 or less). Redundancy indices, as
illustrated in Table XIII, indicate that 3.76 percent of the variance in
the organizational communication set is explained by the variance in the
demographic variables; however, this figure is not significant at
p < 0.05. The proportion of the variance in the demographic variable
set that is explained by the communication variables is 9.79 percent.
This redundancy, however, is significant at the p < 0.01 level.
Canonical correlation coefficients of the significant canonical
functions indicate a moderate to strong relationship between the
demographic variables and organizational communication for the sample
organization. Loadings on the variables in both functions indicate that
the relationship has both positive and negative aspects. The practical
implications of this relationship, however, become difficult to develop
when the results of the redundancy analysis are considered. The
variance in the communication set explained by the demographic variables
is not significant at the p <0.05 level. The variance in demographics
explained by communication is small but significant (p < 0.01), however,
confusing the issue of explained variance and usefulness of this
relationship. Essentially, a significant relationship exists as
indicated by the canonical analysis of the data. However, the lack of
complete evidence of a significant amount of variance in common between
the two concepts diminishes the certainty with which the nature of this
relationship may be stated. The demographic data set appears to have
only a slight effect on the variables associated with organizational
communication as measured by redundancy analysis.
79
TABLE XIII
REDUNDANCY INDEX FOR DEMOGRAPHIC DATA ORGANIZATIONAL COMMUNICATION CANONICAL ANALYSIS
CanonicalFunction Root
VarianceExtracted Redundancy
Proportionof
Redundancy
Dependent Set (Organizational Communication)
0.417980.30203
0.417980.30203
0.13750.2338
Independent Set (Demographics)
0.05000.0553
0.05750.04040.0979
0.02090.01670.0376
0.58730.41271.0000
0.55590.44411.0000
Significance of Redundancy Index
Dependent Set
N = 153 P = 22 Q = 8
F =
F =
R2y|x1-R2y|x
0.03761-0.0376
F = 0.2310
,(120, °° ) = 1.32
(N-P-l)QPQ
(153-22-1)(8) (22)(8)
,95 176,1040-2Since 0.2310 > 1.32, conclude R yjx is not significant at p < 0.05
Independent Set
N = 153 P = 8 Q = 22
F =
F =
R2x [ y 1-R2x|y
0.09791-0.0979
F = 1.9530
» ) = 1.32
(N-P-1)(Q)(P)(Q)
(153-8-1)(22) (8)(22)
F 95<120,176,3165
Since 1.953 > 1.32, conclude R2x|y is significant at p < 0.01
80
Demographics Versus Job Satisfaction Relationship
Two canonical functions investigating the relationship between the
demographic variable set and the job satisfaction variable set are
significant at the p < 0.01 level or beyond. No others are statisti
cally significant, so only the first two functions are reported in
detail. Statistics associated with these two significant canonical
functions may be found in Table XIV. The first function is significant
beyond p < 0.001 and has a canonical correlation of 0.47987. Only
23.027 percent of the total variance in the two variable sets is shared
(canonical root = 0.23027) in this function. The canonical correlation
of the second significant function (p < 0.01) is 0.44298. The canonical
root, or variance shared between the variable sets is 0.19624. Discus
sion of the variables within each set that are important In explaining
the relationship to the other set and redundancy analysis of those
relationships is reported below.
Three of the eight demographic variables have canonical loadings
that exceed 0.30 and are considered important in explaining the
relationship to the job satisfaction set. Level of Education
(L=-0.33044) and Years in Present Job (L=-0.52169) are inversely related
to the job satisfaction variable set. A positive relationship exists
between Salary Level, with a loading of 0.85055, and the job
satisfaction variable set.
Satisfaction with Work, with a loading of 0.78833 and Satisfaction
with Pay, with a loading of 0.60088, are both important to the relation
ship to the demographic data set. These two variables are directly
related to the predictor variable set (demographics). On the other
81
TABLE XIV
CANONICAL ANALYSIS OF DEMOGRAPHIC DATA/JOBSATISFACTION RELATIONSHIP
Canonical Wilkes ChiNumber Eigenvalue Correlation Lambda Square D.F. Significance
1 0.23027 0.47987 0.55130 86.34383 40 0.0012 0.19624 0.44298 0.71623 48.39428 28 0.0103 0.07135 0.26712 0.89109 16.71956 18 0.542
Demographic Canvar I Canvar HVariables L L2 L L
AGE 0.28727 0.0825 0.06738 0.0045SEXMAR - 0.27700 0.0767 0.44590 0.1988ENVT - 0.02520 0.0006 0.33805 0.1143EDUC - 0.33044 0.1092 - 0.36659 0.1344YRSPRSJO - 0.52169 0.2722 - 0.14472 0.0209YRSCD 0.27290 0.0745 - 0.25818 0.0667SALARY 0.85055 0.7234 - 0.44026 0.1938SUPERVIS 0.23285 0.0542 0.71769 0.5151
EL2 = 1.3934 EL2 = 0.1561VE = 0.1742 VE = 0.1561
SatisfactionVariables
SATWRK 0.78833 0.6215 0.57257 0.3278SATPAY 0.60088 0.3611 - 0.61088 0.3732SATPR0M0 - 0.14765 0.0218 0.45864 0.2104SATSUPER 0.11057 0.0122 0.68478 0.4689SATPEOPL - 0.32622 0.1064 0.01188 0.0001
XL2 = 1.1230 EL2 = 1.3804VE = 0.2246 VE 0.2761
hand, Satisfaction with People (L=-0.32622) is also important in
explaining the relationship between the job satisfaction and demographic
variable sets, but is inversely related to the predictor set.
82
In the second statistically significant function, five of the eight
demographic variables are considered important in explaining the rela
tionship to job satisfaction on the basis of their loadings (L < 0.30).
Three, Sex and Marital Status (L=0.44590), Childhood Environment,
(L=0.33805), and Number of Subordinates (L=0.71769), are directly and
positively related to the job satisfaction variable set. Education
Level (L=-0.36654) and Salary (L=-0.71769) have negative signs and are
inversely related to the job satisfaction set.
The job satisfaction, variables also show a mixed direction of
relationships to the demographic variable set. Four variables are
considered important in explaining the relationship to the demographic
variables. Two variables are positively related and two are negatively
related to the predictor variable set (Demographics). The satisfaction
variables that are directly related to the demographic set are Satis
faction with Work (L=0.57257) and Satisfaction with Promotions
(L=0.45864). The variables inversely related to the demographic
variable set are Satisfaction with Pay (L=-0.61088) and Satisfaction
with Supervision (L=-0.68478). Satisfaction with People, which has a
loading of (-0.01188) is not considered important in explaining the
relationship between the two variable sets. Canonical correlation
coefficients indicate that there is a moderate and significant
relationship between the demographic variables as a set and the job
satisfaction variable set. When considering both significant functions,
six of the eight demographic variables are important in explaining the
relationship to satisfaction. Two demographic variables are common to
both functions: Education (negative in both) and Salary (positive in I,
83
TABLE XV
REDUNDANCY INDEX FOR DEMOGRAPHIC DATA/JOB SATISFACTION CANONICAL ANALYSIS
ProportionCanonicalFunction Root
VarianceExtracted Redundancy
ofRedundancy
Dependent Set (Job Satisfaction)
12
0.23027 0.19624
0.17420.1561
Independent Set (Demographics)
0.04010.03060.0707
0.56720.43281.0000
12
0.230270.19624
0.22460.2761
0.05170.05420.1059
0.48830.51191.0002
Significance of Redundancy Index
Dependent Seto
F = R y |x (N--P-lXQ)
N = 153 1-R2y|x PQ
P = 8 Q = 5 F = 0.0707
1-0.0707
F = 1.3603
(153-8-l)(5) (8)(5)
F<95(40,715) = 1.39n
Since 1.3603 i 1.39, conclude R y|x is not significant at the p < 0.05 level
Independent Set
N = 153 P = 5 Q = 8
F = R2x|y 1-R2x|y
F = 0.10591-0.1059
F = 3.4810
(N-P-1)(Q) (P)(Q)
(153-5-1X8) (5)(8)
F (40,1176) = 1.39 40,1176
Since 3.4810 > 1.39, conclude R x|y is significant at the p < 0.01 level
84
negative in II). Similarly, Satisfaction with Work (positive in both)
and Satisfaction with Pay (positive in I, negative in II) are considered
as important in both functions in explaining the relationship to the
demographic data set. Each of the other three satisfaction variables is
considered important in one canonical function or the other. On the
basis of a sum of the signs of the loadings considered as important, the
overall relationship between the demographic data set and the job
satisfaction set may be considered positive by a slight majority of the
loadings (8-7),
Computation of redundancy indices, found in Table XV, indicates the
amount of variance in each of the data sets that may be explained by the
variance in the other. As discussed earlier, canonical analysis has a
tendency to have inflated shared variance figures (eigenvalues or
canonical roots) . Redundancy analysis has been developed to overcome
this problem. The variance in the job satisfaction set that is
explained by variance in the demographic set amounts to 7.07 percent.
However, this redundancy is not significant at the p < 0.05 level.
Conversely, the variance in the demographic variable set that is
explained by variance in the job satisfaction variables is significant
at the p < 0,01 level and amounts to 10.59 percent. Thus, the two
variable sets are significantly correlated, but the strength and
direction of this relationship remains unclear.
The relationship between the demographic data set and the job
satisfaction concept is similar to the relationship between demographics
and communication. The two variable sets are moderately to strongly
correlated on the basis of canonical correlations. The differing signs
of the loadings associated with each variable set make the direction of
85
this relationship unclear. Redundancy analysis further complicates the
usefulness of the relationship between the variable sets because only a
small and partially non-significant amount of variance in one variable
set is explained by the other set.
Summary of Analysis of Data
Analysis of the data discussed here indicates significant relation
ships between job satisfaction and organizational climate; organiza
tional communication and organizational climate; and organizational
communication and job satisfaction for the sample organization. Ex post
facto analysis of demographic data indicates there is the possibility
that the relationships stated above may also be moderated by the demo
graphic composition of the organization under study.
Hypothesis I, concerning the nature of the relationship between
organizational climate and job satisfaction, was accepted. It is con
cluded that these two concepts are significantly related. The direction
of the relationship includes both direct and inverse relationships,
however.
The acceptance of Hypothesis II leads to the conclusion that
organizational climate and job satisfaction are for practical purposes
different concepts. That is, they are correlated, but measure different
organizational phenomena. The low but significant redundancy levels
associated with each concept lead to this conclusion.
Hypothesis III has also been accepted. Thus, a significant rela
tionship between organizational communication and organizational climate
exists for the sample organization. The direction of this relationship
is mixed, having both direct and inverse components. Redundancy
86
analysis yields small to moderate amounts of variance in each concept
that may be explained by variance in the other.
Only partial acceptance of Hypothesis IV can be supported by data
analysis. There is a significant correlation between the concepts of
organizational communication and job satisfaction for the sample. As in
the previous hypotheses, the direction of this relationship is mixed.
Redundancy analysis, however, indicates that the variance in the com
munication set explained by variance in the satisfaction set is non
significant, It should be pointed out that a significant, although
small, amount of the variance in levels of job satisfaction in the
sample is explained by variance in the organizational communication
variables, but the reverse relationship does not hold.
Finally, ex post facto analysis of the effect of demographic
variables on the three concepts that are the main subject of this study
was undertaken.
Analysis indicates that for the sample, no significant relationship
between demographics and the climate variable set exists. There is a
moderate and significant relationship between demographics and the
communication concept as studied. However, redundancy analysis indi
cates that the variance in the communication set explained by the
demographic data set is not statistically significant and that the
actual strength of the relationship may be overstated.
Moderate to strong and significant correlations were also found
between the demographic variables and the job satisfaction concept. The
direction of this relationship is also mixed, however. The variance in
the satisfaction set that is explained by the variance in the
demographic variables is not significant as determined by redundancy
analysis. The reverse relationship is significant.
It should also be noted that the levels of variance explained in
each of the variable sets are small, even for significant redundancies
(less than 11 percent), and for practical purposes the effect of demo
graphic variables on the concepts studied should be considered negli
gible. To a great extent, the relationships explained in the four
hypotheses stand on their own, with little influence from the demo
graphic variables. Job satisfaction and organizational climate are
significantly related, but different concepts. Organizational commun
ication and organizational climate are significantly related, as are
communication and job satisfaction. The directions of these relation
ships are mixed, making interpretation of the nature and directions of
these relationships unclear.
CHAPTER V
CONCLUSIONS AND RECOMMENDATIONS FOR FURTHER STUDY
Organizational Climate— Job Satisfaction Relationship
As proposed by Hypothesis I, organizational climate and job satis
faction are significantly related concepts. This conclusion is reached
on the basis of the strength of the canonical correlation coefficient
(0.71847), which is significant beyond the p < 0.001 level. This rela
tionship was expected, given the majority of the literature noted in134Chapter II. In particular, the findings of LaFollete and Sims, and
135 136Muchinsky also led to this conclusion. Johannesson , however,
concluded that the two are redundant concepts.
The statistical techniques used to test Hypothesis I not only
measured the strength of the relationship between the two concepts, but
also provide information concerning the nature of the relationship
between organizational climate and job satisfaction. Canonical loadings
associated with each of the variables indicate the importance that
variable has in explaining the relationship to the other concept. The
reader should be cautioned though that one of the limitations of canon
ical analysis is the instability of loadings from sample to sample.
Further research to refine the canonical analysis technique Is needed to
overcome this limitation. Thus, since a different sample might achieve
very different loadings, any conclusions concerning the relationships
134Lafollete and Sims, Op. cit.133Muchinsky, (1977-B), Op. cit., 1977-B,136Johannesson, Op. cit.
88
89
between the two variable sets are specific to the sample, under study.
Any generalization to other groups may be tenuous at best. This fact may
help explain otherwise unsuspected loading values and relationships among
the variables within each of the data sets.
The results of the first canonical function, however, are both
statistically significant and relatively easily explainable. Greater
responsibility and a more positive affective tone toward management have
a negative effect on satisfaction with work and satisfaction with promo
tions. It appears that the more responsibility a person has on the job,
and the more closely he or she relates to management in the sample
organization, the more dissatisfied that person becomes with his or her
work and chances for promotion. This type of reaction appears to corre-137spond to feelings of inequity in that perceived increases in responsi
bility and more positive relations with management would typically be
associated with greater levels of job satisfaction rather than lesser
levels as seem to exist here. One could assume that the sample perceives
the reward system (dn terms of promotions) is unfair; and/or, that as a
group, the sample feels its capabilities are being underutilized.
Further research including objective measures of job satisfaction in the
sample organization would be necessary to validate this conclusion. As
stated earlier, this type of data was not available from the sample
organization. Similar research findings in other organizations would
surely be required to be able to generalize this relationship as it
exists here to other organizations.
Campbell and Pritchard, "Motivation Theory in Industrial and Organizational Psychology," pp. 104-110.
90
The climate variable of interpersonal milieu also is important in
explaining the organizational climate-job satisfaction relationship.
Values of canonical loadings indicate that a negative interpersonal
milieu is associated with low levels of satisfaction with work and
satisfaction with promotions. One possible explanation for this
relationship may be the concept of "locus of control," or the "inner vs.138other orientation." That is, the sample group may be composed of
individuals who see others as controlling their lives and destinies
rather than themselves. Respondents with this outlook on life and work
would possibly consider interpersonal relations in their jobs as very
important. A lack of these factors then, could lead to low levels of
satisfaction with their work. Further research into this area,
especially for organizations such as the one studied here may help to
determine whether the relationship between these climate and satisfaction
variables is sample specific or generalizable to other organizations.
In summary, the people/management aspects of climate have an overall
negative effect on the work/promotion aspects of job satisfaction. The
climate variables have little effect on satisfaction with people,
supervision, and pay. It may be possible that the relationship between139climate and satisfaction for this sample is that of a "dissatisfier"
type of relationship. That is, negative perceptions of these climate
variables leads not to decreased levels of job satisfaction, but rather
to increased dissatisfaction with the job. Further research with
other samples in different types of organizations must be undertaken to
138Rotter, "Beliefs, Social Attitudes and Behavior: A SocialLearning Analysis," pp. 335-50.
139Herzberg, et.al., Op. cit.
91
determine whether this conclusion is sample specific or is a general
conclusion that may be applied to many people and organizations.
Hypothesis II addresses the controversy over whether organizational
climate and job satisfaction are redundant concepts or are actually
different concepts measuring different organizational phenomena.140Johannesson has concluded that the concepts are redundant, while
141Muchinsky has concluded that the concepts are actually different
concepts. Analysis of redundancy indicates that very little of the
variance in either of the concepts may be explained by variance In the
other. Stated differently, in the organization under study, organiza
tional climate and job satisfaction are significantly different concepts.
In fact, in this sample, organizational climate explains only 8.85
percent of the variance in job satisfaction, while only 4.18 percent of
the variance in organizational climate is explained by job satisfaction.
These findings lead to the conclusion that although the two concepts are
significantly correlated, there is very little redundancy between the two
measures. That is, one may conclude that organizational climate and job
satisfaction are related but significantly different concepts that
measure different aspects of organizations.
Organizational Communication— Organizational Climate Relationship
Hypothesis III suggests that the concepts of organizational
communication and organizational climate are strongly and positively
related. As noted, this hypothesis is generally supported by the data.
Johannesson, Op. cit.
Muchinsky, Ibid.
92
Two different canonical functions are significant beyond the p < 0.001
level. The first function has a canonical correlation coefficient of
0.70745, while the second has a coefficient of 0.63043. Both of these
values indicate a strong relationship between two concepts.
Loadings on the variable sets in the first canonical function show
that the relationship between organizational communication and organiza
tional climate has both positive and negative aspects. The
communication variables that are most important to the relationship are
satisfaction with and openness of communication. These variables may be
considered as being summary measures of the perceptions of the
communication system of the organization under study. These two
variables have a positive relationship with the climate dimensions of
responsibility, organizational identification and affective tone toward
management/organization. On the other hand, these important communi
cation variables have a negative relationship to interpersonal milieu
and organizational structure and procedures variables. One may conclude
that the overall openness and satisfaction with communication in this
organization is associated with both positive perceptions of management
and the organization as a whole, and negative perceptions of the
interpersonal relationships and degree of structure in the organization.
This relationship appears in part contradictory. That is, in the
sample, communication factors are associated with positive perceptions
of the organization but negative perceptions of the people in the
organization and also the structure and procedures necessary for the
organization to function. This finding could be attributed to correlated
method error, also known as a "perception - perception" problem in this
case, since both criterion and predictor variables are measured using
93
perceptual responses. However, as noted in Chapter I, this should not
affect the basic nature of the relationships between the concepts. A
second explanation may lie in the "locus on control" issue raised in the
explanation of relationships covered under Hypothesis I. That is,
individuals in the sample may feel that "others" are exerting excessive
control over rewards, especially through peer group influence and
bureaucratic structures and procedures. Stated differently, the sample
as a group may feel that as relations between workers and their super
visors become more open and satisfying, those workers develop negative
perceptions of their peers and become more frustrated with the "red
tape" associated with bureaucratic organizations such as the one under
study. This conclusion is tentative at best, and only further research
in this and other organizations will determine the validity of this
explanation. Another explanation may be to write the contradiction off
to this sample. Also, possible differences in perceptions of communica
tion and climate in different departments may explain these findings.
Departmental differences were not controlled in an effort to insure
anonymity for the respondents. Because the organization is composed of
approximately 220 employees in several departments, any attempt to
identify respondents by departments would have compromised anonymity.
This would have risked reducing the return rate of the questionnaire and
reliability and significance of the study. (In meetings after the data
were collected, several members of the organization who were respondents
in this research project expressed reservations about completing the
relatively few demographic questions that were asked.)
Other factors not studied, such as objective measures of communi
cation, etc., may explain the nature of this relationship between
94
organizational communication and organizational climate. In particular,
organizational level could be moderating the communication-climate
relationship. To some extent, analysis of the relationship between the
demographic information gathered and the communication and climate
concepts addresses this question. Three of the demographic variables,
number of workers supervised, salary level, and possibly education may
be thought of as surrogate measures for organizational level. Canonical
analysis of the demographic variables indicates that there is no signi
ficant relationship between the demographic variables as a set,
including those associated with organizational level, and the
organizational climate variable set. These three demographic variables
are important in explaining the significant relationship between the
demographic variables as a set and the organizational communication
variable set (R= 0.64652, p < 0.001). Redundancy analysis of the
relationship between the two variable sets, however, indicates that the
variance the concepts explain in each other is small and nonsignificant.
These results indicate that any moderating effect of organizational
level as measured by these demographic variables is minimal within the
sample organization. A better explanation of the relationship between
the component variables of communication and climate may be determined
only through additional research in other organizations.
The second canonical function measuring the relationship between
organizational communication and organizational climate, as noted
previously, is indicative of a strong and significant relationship
between the concepts. Again, however, this relationship has both
negative and positive aspects. Greater perceived influence of superior,
less use of more informal modes of communication (face-to-face and
95
telephone), less communication underload and less withholding of
communication are associated with more positive interpersonal
relationships, greateridentification with the organization, higher
standards of performance, and a more negative perception of structure
and red tape associated with the organization. If one ignores the two
communication dimensions associated with modality, the relationship
between the two concepts is intuitively logical; i.e., when people are
provided with adequate information to do their jobs and have supervisors
that are influential, they have a positive perception of the people with
which they work, identify more easily with the organization and its
standards, but are more frustrated with structure and procedures. The
modality measures appear to contradict this relationship. Could this
finding be explained by a sample made up of people who prefer more
formal relationships and a greater degree of structure than is present
in the organization under study, or the inner vs. other locus of control
issue again? Or is this an anomaly of the data caused by differing
perceptions of the questions related to these dimensions of
organizational communication? The relationship is partially consistent
with the findings of Muchinsky, who in a similar study found similar
contradictory correlations between these two communication modality142dimensions and the dimensions of organizational climate. Muchinsky,
in his study of the relationship between organizational communication
and organizational climate in a state-wide public utility company
(telephone company), utilized simple correlational analysis to study
relationships between the components (variables) included in
142Ibid. p. 598.
96
communication and climate rather than canonical analysis. He did find
significant negative correlations between these two modality dimensions
and organization climate variables. Muchinsky was also unable to give a
rational explanation for the direction of this relationship. It is
possible then, that the modality aspect of the relationship between
organizational communication and organizational climate is peculiar to
this particular sample and also may not really reflect any consistent
relationship.
Redundancy analysis of the two variable sets adds additional
information about the relationship between communication and climate.
The climate set explains little (although a statistically significant
amount) of the variance in the communication set, only 4.76 percent.
The communication set, on the other hand, explains 38,82 percent of the
variance in organizational climate. This suggests that although in
canonical analysis predictor and criterion variable sets may be arbi- 143trarily defined, communication explains a much greater amount of the
variance in climate than the reverse relationship. Further, this
evidence suggests that changes in organizational communication practices
may have a direct impact on organizational climate because of their
significant correlations.
To summarize the findings concerning the relationship between
organizational communication and organizational climate, one may state
that certain of the organizational communication variables are highly
related to organizational climate while other variables seem to have
143Nie, et al., O p . cit., p. 517.
97
little impact on the relationship. This is consistent with the findings 144of Muchinsky. However, this study did not find the communication
variables of accuracy or directionality to be important, which contra
dicts Muchinsky's analysis. Satisfaction with communication and with
holding (gatekeeping) are in common in the two studies. Openness of
communication and underload are important in explaining the relationship
between the two variable sets in the present study, but were not
included in Muchinsky's efforts. Thus, on balance, Muchinsky's findings
regarding the relationship between communication and climate have been
corroborated, where 47 percent of the correlations between communication
and climate were significant. At the same time additional information
concerning how various aspects of the two concepts interact have been
added. Organizational communication and organizational climate are
highly correlated concepts. However, only certain aspects of these two
multivariate concepts are important in explaining the relationship.
Other variables have little effect on the relationship between
communication and climate in the organization under study.
Organizational Communication— Job Satisfaction Relationship
The relationship between organizational communication and job
satisfaction is the subject of Hypothesis IV. This hypothesis proposes
a strongly positive and significant relationship between the two con
cepts. Two canonical functions were found to be significant at or
beyond the p < 0.001 level, with canonical correlations of 0.71837 and
0.61254 respectively. These values suggest a strong and significant
relationship between the variable sets.
144Muchinsky, (1977-C^, Ibid., p. 597.
Analysis of loadings on the first canonical function and analysis
of redundancy creates some skepticism regarding acceptance of this
hypothesis. In this sample, lower levels of satisfaction with communi
cation and lower levels of openness are associated with higher levels of
satisfaction with work and satisfaction with people. It appears that
the more negatively organizational communication is perceived, the
greater are the levels of at least two components of job
satisfaction. This unusual relationship between organizational
communication and job satisfaction is at least similar to the findings
of an ongoing European study of organizational communication and job1A5satisfaction as reported by Goldhaber. In that study,
dissatisfaction with the job and organization actually increase as a
function of more open communication climate. It was reasoned that as
communication flow increases, employee expectations are raised
concerning participation in the decision-making process, and when those
expectations are not met, greater dissatisfaction results. The author
of the study is reported to conclude that the concepts of communication
and satisfaction may be related, but their relationship varies as a146function of demographic and organizational contingencies. This would
surely seem to be the case in this study. Communication and satisfac
tion are significantly correlated. The demographic variable set is
significantly correlated with the communication data set, as discussed
in Chapter IV. However, redundancy analysis indicates that little or no
significant variance in either variable set is explained by the other,
Goldhaber, Organizational Communication, p. 75.
99
diminishing the probability that demographic variables are responsible
for the stated relationship between communication satisfaction and
openness and the job satisfaction set. Is it possible that organiza
tional contingencies not studied, such as the bureaucratic structure as
compared to other structures, etc., may explain this relationship?
Further research will be required to answer this question. From another
viewpoint, as noted by Hair, et,al, one of the limitations of canonical
analysis is that, "It is difficult to identify meaningful relationships
between the subsets of independent and dependent variables... and we147must rely on inadequate measures such as loadings or cross-loadings."
This seems to be the case here as the direction of the relationship in
this function runs counter to any expectations as well as the majority
of thought and research. It is doubtful that poor communication can be
associated with increased levels of job satisfaction. Further analysis
with other organizations will be necessary to resolve this confusing
f inding.
The second canonical function is more easily interpretable, but
possesses some of the same confusing relationships among the component
variables as the previous canonical analyses. Trust in superior and
influence of superior are the most important of the communication
variables in explaining the relationship to job satisfaction in this
function. These variables have a positive impact on satisfaction.
Satisfaction with people is the most important of the satisfaction
variables, having a positive relationship to the communication variable
set.
147Hair, et a l ., Op.cit., p. 192.
100
One may conclude that high levels of trust and influence of super
iors are associated with high levels of the job satisfaction variable of
satisfaction with people (co-workers) for the sample organization. At
the same time, high levels of trust and influence of superiors are
associated with lower levels of the job satisfaction variables of
satisfaction with supervision and satisfaction with promotions.
This canonical function appears to illustrate a multiple relation
ship between communication and job satisfaction. Some communication
variables seem to have positive impacts on some aspects of job satis
faction and little or no impact on others. Satisfaction with work
itself and satisfaction with pay have little direct relation to the
concept of communication and not surprisingly, have little impact on the
data from this sample. These other components of job satisfaction which
focus on the task itself and specific rewards rather than communication
aspects of work may help to explain the lack of redundancy between the
concepts of organizational communication and job satisfaction. Redun
dancy analysis indicates that job satisfaction explains very little of
the variance in communication (3.36 percent), and in fact this relation
ship is not significant at the p < 0.10 level. Communication explains
only 17,14 percent of the variance in job satisfaction. This
relationship is less significant than the other reported redundancies,
being significant only at the p < 0.05 level. On the basis of these
values, one may conclude that the two concepts, although highly corre
lated, are very different concepts and have little real effect on each
other, with communication being relatively more important to explaining
variance in job satisfaction than the reverse relationship for the
101
sample under study. Because of the lack of clarity of the direction of
the relationships of each of the variable sets to each other and the
small and partially non-significant redundancies associated with
communication and satisfaction for the organization under study, it is
concluded that Hypothesis IV can be only partially supported.
Final Summary of Relationships
Several general statements may be developed from the conclusions
drawn here that impact organizational behavior, and to a certain extent,
organizational design. First, as expected, organizational climate and
job satisfaction are related concepts. At the same time, each does
little toward explaining variance in the other. Thus, the two concepts
are different and measure different organizational phenomena. This
finding may have the greatest significance of any included in this
research effort. The theoretical implication is that this study may at
least potentially provide an answer to the question of whether
organizational climate and job satisfaction are difference concepts.
The practical implication of this is that organizational efforts to
improve job satisfaction may have little direct effect on organizational
climate and vice versa, at least for this sample organization. There
may be indirect effects, however, as the changes affect the nature of
the communication system in the organization or possibly other
variables.
Secondly, as hypothesized, there is a direct correlation between
organizational communication and organizational climate. The communica
tion variable set explains a moderate, and statistically significant
portion of the variance in organizational climate, while only a small
102
but significant percentage of variation in communication is explained by
the organizational climate set. Focusing organizational efforts on
improving communication, especially openness, interpersonal relations
with superiors, and decreasing information withholding (or gatekeeping)
should have a positive impact on organizational climate. Put simply, in
this sample, providing employees with more and better communication
should lead to more positive organizational climate. At the same time,
efforts aimed at improving communication may be associated with
increased frustration with the red tape (structures and procedures)
associated with government bureaucracies such as the sample
organization. This may imply that efforts to improve communication
should be linked with organization redesign efforts to decrease red tape
if the maximum benefit is to be achieved from any efforts to improve
communication and organizational climate simultaneously, especially in
government organizations. Future research into this area may provide
factual backing for this idea of "linking communication practices and
organizational design efforts" for maximum effectiveness.
Thirdly, although job satisfaction and organizational communication
are highly correlated concepts, each explains little or no significant
variance in the other, at least for the sample organization. Can one
conclude that communication is such a small part of the job satisfaction
concept that it has only a limited impact on job satisfaction? Or can
one conclude that the nature of the Job Descriptive Index, used to
measure job satisfaction, does little to pick up the effects of communi
cation on job satisfaction? Two of the five job satisfaction scales
(satisfaction with pay and satisfaction with promotions) seem to have
little to do with communication, at least directly. Research in other
103
organizations with the same and other job satisfaction instruments is
needed to answer these questions.
In an effort to determine whether demographic factors moderate the
relationships between organizational communication, organizational
climate and job satisfaction, further canonical analyses were under
taken. For this sample, no significant relationship exists between the
demographic data set and organizational climate. The canonical corre
lation between the demographic data set and both organizational communi
cation and job satisfaction is significant. However, redundancy
analyses of these relationships indicate that little or no significant
variance is shared between the sets of concepts and the demographic
variables data set. Other demographic or personality variables not
studied here may play a role in affecting the relationships between
communication, climate, and satisfaction. The possibility of additional
variables having an important role in explaining these relationships
should be the subject of further research in this and other
organizations.
Further Limitations to the Study
Possible limitations to the findings that are inherent to the study
have been stated in Chapter I. These include response bias due to
correlated method error. The fact that the sample was selected to be
representative of the organization as a whole means that the data
concerning job satisfaction are contaminated by the effects of differing
organizational levels. Also, contact with respondents after data were
gathered indicated that some of the respondents were reluctant to
complete the demographic data. This reluctance may have spilled over
into data concerning each of the concepts as well if any of the
104
respondents' willingness to give answers to the questions that
accurately reflected their perceptions of the variables was affected.
Additionally, the limitations of canonical analysis have been pointed
out earlier. Further research concerning the technique itself,
interpretation of loadings, and its applicability to classical
hypothesis testing, etc. needs to be undertaken. Several other possible
limitations are evident in the questions for future research discussed
below.
Suggestions for Further Research
This research project has provided additional insight into the relation
ships between organizational communication, organizational climate, and
job satisfaction. The relationship between certain demographic vari
ables and these major concepts within the sample organization have also
been investigated. More questions have been raised than answered
though, in the effort to gain this added knowledge. As noted throughout
this chapter, further research in several areas will be required to
resolve these questions.
Does organizational climate act as a "dissatisfier" as defined by 148Herzberg, et al. in its relationship to job satisfaction? Is the
relationship between the two concepts specific to this sample only, or
can it be found in other organizations as well? Are there other vari
ables, especially demographic variables (organizational level,
professional status, department, etc.) and personality variables such as
locus of control, as well as structural variables that are moderating
Herzberg, et a l ., Op. cit.
105
the relationship between climate and satisfaction? For that matter,
just how important is the relationship between organizational climate
and job satisfaction anyway? In this sample, they are highly
correlated, but share low levels of redundancy.
Are there other variables related to communication that affect its
relationship to organizational climate? Can the question of the effect
of communication modality on organizational climate in the sample
organization be resolved through further research in other
organizations, especially in private sector as well as in other public
sector organizations. Again, are there moderating variables not studied
here that affect the communication-climate relationship? In particular,
is the relationship found here common to government bureaucracies, or to
other organizational types and structures as well? Does locus of
control of the respondents affect how they perceive both communication
and climate?
Further, do organizational communication and job satisfaction
always have such a small amount of variance explained by the other, or
is this finding a function of the organization itself, the instruments
used in the study, correlated method error, some moderating variables
not studied, etc.? As information about pay, performance etc., is
communicated throughout an organization, do feelings of fairness or
inequity affect the relationship between communication and job satis
faction? Would the relationships found for this organization also hold
up in private sector organizations where the reward and tenure system is
usually quite different from that of local government (civil service)
type organizations?
106
These questions can only be answered through additional research:
research in other types of organizations, possibly with other instru
ments that measure the three concepts differently and/or more objec
tively, and that possess greater internal reliabilities than the
instruments used in this study. Causal modeling of the relationships
may help to determine more effectively the nature of the interactions
among organizational communication, organizational climate, and job
satisfaction. Path analysis techniques and cross-lagged panel
correlation techniques may be helpful in providing additional
information about the relationships between the concepts studied here.
Other longitudinal studies may also shed additional light on these
relationships. Such research would add further evidence to support the
findings of this study and allow the conclusions to be more easily
generalized to other organizations, or establish a set of conditions
under which these findings apply to other organizations.
Analysis that is beyond the scope of the present effort may provide
other information that would be helpful to the management of the sample
organization and management scholars alike. The combinations of items
that make up the variables under study were chosen because of their149general reliability in the past. These reliabilities should be
checked for the sample organization as well. Differences that may exist
in the demographic makeup of the sample organizations, as well as
differences in structures and reward systems in the sample organization
from the public sector as compared to the organizations sampled
149Muchinsky, 1977-C, O p . cit., 596-603.
107
previously from the private sector may require that different dimensions
of the three concepts be utilized to yield a better explanation of the
relationships between the concepts. An additional factor analysis may
point out communication and climate variables that would be more
appropriate for the organization under study than the one used in this
and previous studies. Further analysis of the component variables
through regression analysis, etc., may also uncover additional
information about the effects of the components of the concepts on each
other.
Analysis of objective measures of communication flow and content as
well as objective measures of job satisfaction such as absenteeism and
turnover would help to overcome the limitation of correlated method
error in the analysis and may also yield additional information about
the relationships between communication, climate, and job satisfaction.
Only one or two significant canonical functions were developed from
analysis of each of the relationships. This occurs because the
canonical functions are composed of linear combinations of the variables
within each set that maximize the correlation between the predictor and
criterion sets. Additional linear functions that maximize the remaining
correlation are derived by the technique, subject to the constraint of
being independent from the preceding set (or sets) of linear composites,150as well as constraints of statistical significance. Thus, for the
sample, all the correlation between the concepts (given restrictions of
statistical significance) has been explained in one or two canonical
functions. The redundancies (shared variance) associated with the
^^Hair, et. al.. Op. cit., pp. 151-2.
103
relationships studied are moderate to low, and in some cases
non-significant. Is the implication of this finding, especially given
the strong and significant correlations, that the concepts are too
robust and have too many dimensions to be treated as a whole? Would
other multivariate statistical techniques that do not group the
composite variables of each concept provide a better representation of
the relationships between the composite variables of the concepts, and
the relationships between the concepts as a whole?
Undoubtedly, questions have been raised by this study, yet signifi
cant implications have turned up as well. The most significant of these
may be evidence that indicates that at least for this sample, that
organizational climate and job satisfaction are different concept that
measure different, though correlated, organizational phenomena.
Suggestions for directing efforts for improving organizational climate
by improving communication in organizations have been developed and
await testing in future research. Less positive organizational climate
is associated with lower levels of job satisfaction in this
organization. This finding may apply to other organizations as well. A
logical corrolary could be that more positive levels of organizational
climate would be associated with increased levels of job satisfaction.
Further, improvements in communication should be associated with
improvements in organizational climate and job satisfaction.If further
research concludes that the findings of this research effort may be
applied to other organizations, the results of the present study should
prove beneficial to many.
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Redding, W.C., and G.A. Sanborn, eds., Business and Industrial Communication, Harper and Row, New York, 1964.
Roberts, K.H,, and C.A. O’Reilly, III, "Assessing Communication in Organizations," unpublished paper, College of Business Administration, University of California at Berkeley, Berkeley, CA, 1974.
_______________________________ , "Failures in Upward Communication inOrganizations: Three Possible Culprits," Academy of ManagementJournal, Vol. 17, No. 2, (1974), pp. 205-15.
_______________________________ , "Measuring OrganizationalCommunication," Journal of Applied Psychology, Vol. 59, (1974), pp. 321-26.
, "Some Correlates of CommunicationRoles in Organizations," Academy of Management Journal, Vol. 22, No. 1, (1979), pp. 42-57.
_______________________________ , G.E. Bretton, and L.W. Porter,"Organizational Theory and Organizational Communication: ACommunication Failure?" Human Relations, vol. 27, No. 5, (1974), pp. 501-524.
Romoff, M,, "Employee Communications in the Federal Government:Assessing Needs, Interests, and Perceptions," The Canadian Business Review, Vol. 4, No. 1, (Winter, 1978), pp. 36-39.
116
Rotter, J. B., "Beliefs, Social Attitudes and Behavior: A SocialLearning Analysis," in Applications of a Social Learning Theory of Personality, J.B. Rotter, J.E. Chance, and E.J. Phares, Holt, Rinehart and Winston, New York, 1972, pp. 335-350.
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Sanborn, G.A., "Communication in Business: An Overview," in Businessand Industrial Communication, eds., W.C. Redding, and G.A. Sanborn, Harper and Row, New York, 1964, pp. 3-26.
Scanlan, B.K., "Determinants of Job Satisfaction and Productivity," Personnel Journal, (January, 1976), pp. 12-14.
Schneider, B., "The Perception of Organization Climate: The Customer'sView," Journal of Applied Psychology, Vol. 57, (1973), pp. 284-256.
_____________, "A Note on Johnston's 'A New Conceptualization of Sourceof Organizational Climate'," Administrative Science Quarterly, Vol. 21, No. 3, (September, 1976), pp. 502-4.
Sereno, K.K., and C.D. Mortensen, Foundations of Communication Theory, Harper and Row, New York, 1970.
Sims, H.P., and W.R. LaFollette, "An Assessment of the Litwin andStringer Organizational Climate Questionnaire," Personnel Psychology, Vol. 28, (1975), pp. 19-38.
Smith, P.C., L.M. Kendall, and C.L. Hulln, The Measurement ofSatisfaction in Work and Retirement, Rand McNally, Chicago, 1969.
Smith, R.L., G.M. Richetto, and J.P. Zima, "Organizational Behavior: AnApproach to Human Communication," in Approaches to Human Communication, eds., R.W. Budd and B.D. Ruben, Spartan Books, New York, 1972, pp. 269-289.
Steers, R.M., and L.W. Porter, eds., Motivation and Work Behavior, McGraw-Hill, New York, 1975.
____________, "Factors Affecting Job Attitudes in a Goal SettingEnvironment," Academy of Management Journal, Vol. 19, No. 1,(1976) , pp. 6-16.
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117
Swan, J.E., and C.M. Futrell, "Does Clear Communication Relate to Job Satisfaction and Self-Confidence Among Salespeople?" Journal of Business Communication, Vol. 15, No. 4, (Summer, 1978), pp. 38-52.
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Thorndike, R,, and D. Weiss, "A Study of the Stability of Canonical Correlations and Canonical Components," Educational and Psychological Measurement, Vol. 33, (1973), pp. 123-134.
Timm, P.R., "Worker Responses to Supervisory Communication Inequity: AnExploratory Study," Journal of Business Communication, Vol. 16, No. 1, (Fall, 1978), pp. 11-24.
Vroom, V.H., Work and Motivation, John Wiley and Son, New York, 1964.
Wilkins, P.L., and P.R. Timm, "Perceived Communication Inequity: ADeterminant of Job Dissatisfaction," Journal of Management, Vol. 4, No. 1, (Spring, 1978), pp. 107-109.
Williams, L.K., J.W. Seybolt, and C.C. Pinder, "On AdministeringQuestionnaires in Organizational Settings," Personnel Psychology, Vol. 28, (1975), pp. 93-103.
Woodman, R.W., and D.C. King, "Organizational Climate: Science orFolklore?" Academy of Management Review, Vol. 3, No. 4, (1978),pp. 816-26.
APPENDIX A
ORGANIZATIONAL COMMUNICATION INSTRUMENT
118
PLEASE NOTE:
Copyrighted materials in this document have not been filmed at the request of the author. They are available for consultation, however, in the author's university library.
These consist of pages:
119-144________________________________________________
202-207 : Scoring the Job D e s c r ip t iv e Index (JDI)
UniversityMicrofilms
International300 N Zeeb Rd., Ann Arbor, Ml 48106 (313) 761-4700
APPENDIX E
SUMMARY OF DEMOGRAPHIC DATA
145
Please fill in the following information so we can have a better idea of what kino of people work in the Department of Human Resources. Put a ( by the appropriate answer.
1. How old were you on your last birthday? 1_ less than 20 1J 35-39 10 55-5?21 20-2L 9 liO-liD t~ 60-6831 25-2? 8 85-ii? 5 65 and over30 30-33 12 50-53
2 did not answer2. Sex and Marital Status
28 female and Married 49 Male and Married46 Female and Hot Married 28 Male and Hot Married
2 did not answer 3- What type of environment did you grow up in?
107 Largely urban 13~ Undecided28 Largely rural 8 did not answer
k . Khat level of schooling have you completed? 0_ Grade school 45 Some college24 High scnool 41 College17 Trade or Business school 24 Graduate school
2 did not answer 5- How long have you been in your present job?
24 0 - 6 months 43 3 - 5 years23 7 months - 1 year 13 6 - 1 0 years3d 1 - 2 years 6_ More than 13 years
2 did not answer6. How long have you been with the Department of Human Resources?
27 0 - 6 months 31 3 - 5 years10 7 months - 1 year 9 6 - 1 0 years24 1 - 2 years 9 More than 10 years
43 did not answer7. What is your approximate annual salary level before taxes?
L $2)500 - 35,003 27 $10,031 - 312,503 6 317,501 - 323,06 $5,001 - $7,500 33 $12,501 - $15,000 1 "!' 320,031 or more34 37,531 - $10,000 ~£~6" $15,001 - $17,500 Tdid not answer
8. In your present position, do you supervise the work of other employees?104 No 7 Yes, 1 1 - 2 0 employees25 Yes, 1 - 5 employees 6 Yes, more than 20 employees
9_ Yes, 6 - 1 0 employees , 2 did not answer
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A P P E N D IX F
SAMPLE S IZ E COMPUTATION
163
SAMPLE SIZE COMPUTATION
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Therefore Sample Size is adequate for at least a 95% confidence level
APPENDIX G
MEANS, STANDARD DEVIATIONS, AND RELIABILITIES OF
THE VARIABLES AS REPORTED BY MUCHINSKY
.165
166
MEANS, STANDARD DEVIATIONS AND RELIABILITIES OFTHE VARIABLES AS REPORTED BY MUCHINSKY
Variables X SD Reliability*
Organizational CommunicationTrust 14.12 4.54 .83Influence 13.98 4.24 .69Mobility 9.71 4.07 .93Desire for Interaction 15.52 3.49 .63Accuracy 15.24 2.46 .54Summarization 15.34 3.49 .80Gatekeeping 12.61 3.64 .46Overload 5.59 2.73 .67Directionality— Upward 32.13** 19.21 .58
:— Downward 19.02** 28.76 .58— Lateral 48.85** 18.74 .76
Modality— Written 14.19** 11.89 (one item)— Face-to-Face 40.03** 18.16 If
— Telephone 43.35** 38.31 II
— Other 2.43** 3.40 fl
Satisfaction with Communication 4.83 1.30 Tl
Organizational ClimateInterpersonal Milieu 14.24 2.87 .75Standards 9.66 1.84 .54Affective Tone Toward Management/Organization 40.46 8.45 .91
Structure and Procedures 24.90 5.52 .82Responsibility 16.80 3.03 .56Organizational Identification 14.06 3.04 .82
Job SatisfactionSatisfaction with Work 33.54 10.53 .80Satisfaction with Supervision 37.43 12.10 .87Satisfaction with Pay 14.26 5.61 .77Satisfaction with Promotions 12.06 8.35 .88Satisfaction with Co-workers 39.38 11.36 .86
*Internal consistency reliability (Coefficient Alpha) for multi-itemscales
**Percentage of total communication
Source: Muchinsky, P.M., "Organizational Communication: Relationshipsto Organizational Climate and Job Satisfaction," Academy of Management Journal, Vol. 20, No, 4, p. 596.
APPENDIX H
CANONICAL ANALYSIS COMPUTER PROGRAM OF COMMUNICATION/
CLIMATE/SATISFACTION RELATIONSHIP
167
168
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( r ' ) * v A f t | f t « » 1 l l | + V A h | 7 » f | g * y A k | t , » u g + V A H i g * , ( ' 7 * W A I . p i l * | S t V i i | . ^ 5 * J , l t v A S r^ H » ( V J + V A k J | * , 1t M t » A h 4 3 * , | M * V A I - 3 o * , 1 5 + V A W 3 5 » . 2 | * i ( t , »- 3 t ' » . J h + V A | . O U * 1 Ll t l t V A H O l » . 0 7 t V A H y H , l o * v A k u 5 * , l o + V " k | * , u 5 * v A M t; * , ( i 5 - t v A k i a , l l « v A H ' ( » . l ( ’ + ' < A i ' 5 * , l ,i + ' < » t . n « I i j 7 t ' . t " / » . l l | t V A k l U A . | h + v A k l 5 * , l h » v A P ^ I | A , l i J + V A k ' l » , l i I * Y A l « J U * , ( J 0 t v A i . | l * , ) / *VAkl **,l|]tvAk|i*»,U + vAkc'3<,y5tvAhM/n,iJ0tVAH0t;*lCi +vtku/»,J * V A h O H t . l / ♦ Y A k t i g * t P i » Y A w i n * > mSTANOAkl)sV(Auj7*.7il»VA7>l,M*</i + vAtii9»,7Jt*Ak2|*tObtVAkit7*tlJ0*v«k?V* , 0 ' l t v A k J i i » . O 7 + v * k J p « , I 1 + v A i . h * - . ( m t v A H 1 f t * , 0 h t V A M j ; « - , i i 7 ' t v » « | k i , i j i i * V A h | q * - t f ' | t v « H ^ U * . , I J ( l < < A H ^ t , ( . < i i 3 i ( f A k P 6 t » , 1 5 * v A h i | » - , U 0 * v A - l i i * t l U t t f A U i ( | * “ . l j h t \ / A H i 5 * . ( t O + V » H i f t « . ( l > V t V A k U | n , 3 i j t v A t i O l » t < ? l l t v A w O i « , i H tv A k o 5 * - ( j 5 n v A k | ‘ 1 | O t v * k ( ' * . n . 4 + v A w i » , i i f t * v A k u * * , i u t v A h b « - . l o t v f k o * , l l U + V A k / * . | r ) + V A K l U * - . n i t k A k l 5 » . l l b + Y A H P u * - , l ) l t v A t . g < - . l l 9 » ^ t t M | ' i < - . n i t v A k i i * , i i i i + v B t , | ^ * , 6 n + v r t 5 J 3 » , ' i h t v A I < 1J 3 » , i i [ i t V A k u o * t | 5 t x A H a ^ . . | y * H i i ' i l * . 1 3 * v I w on * , | u * v A n u < * « t [ i < ; t v A i - 5 u * , ' ‘ 3t l N t I I ' < * I S V « M H * > i b « v A k i b * , 5 k + ^ A k l 7 » . f t S t v A f | H * . 0 O * V A l i l 0 » < J 5 * v A i . <' n * , 5 o + 7 A k p 5 A . u H * v i k | 7 H * . 3 b « v A P 3 i * . 5 ( i + v A n 3 3 * . 5 H * ^ A k l i i * . ' M * V A K i 5 » l 5 i ) t V A « 3 b » , b l i + W A t H I ( j * * . 3 i * 7 A | . I J | » , < ! £ * V A * < ,J i * , 0 < A + V A H l i b * , 5 i t » * A I . ( t | » , ^ ^ « V A k d 7 * , 3 5 + V A H ^ q * , ( ' l | * v A k ( i i . l « ( i | i t . A « i ( ' » , < ; / + V A K i / * . l 5 * I . A l . j n » . , l i S * v A I - 3 P « - v , / ' * v A k | * , r i f t f V A K £; , I j 7 + v A | , 3 » . P 5 + v A k U * , l o * > A W 5 * I ^ 3 ' f V * t . h * . < ' 3 * V « l - 7 * t l 7 ' * 1 A l . l l i » i ; i ; t V 4 f t t 5 » , ) | i + v A H d 4 * . p n t V A b ' l * , n f t * V A k | l ' * 1 U / t k A k l I * , | 5 * n i k l (; * , d ' * + v A « l 3 » - t u J * 7 A k d i " , l / l ' v i H U ( i » - , i i o t v A i < o < ' * . c ! u * * ' A k u 7 » , { : /♦ 0 A k 0 f t * . i O + l | f . « t l S * , 3 l l + ll A H 5 l ' * , M !S I W ' i L i y k b v A P i i ^ ' j V t u A h e * ' , v + v A k S * . 5 l * w A k i J * . b 7 t y A i . ^ t , u | t i pA i i b * , S f t * V « P 7 * | « 7 * v A i i | O . . H f > t v A " l 5 » . b 7 t v A k t ' » * , 3 d t ¥ f . B d | * , i ; ' t t v A H d 7 « , c , t * » v A r < < ; ‘7 * , | ( i t v A k 3 ^ * . | b « v A k 3 e ; * . < l 7 t V A H 3 7 * , ] b + v A k 3 t ‘ * , l i i t ¥ A n 3 ,» * * , l l i + ¥ A k b * , i ' M Y A P | b t , 3 ‘l * V A I < 1 7 * . ( ! t ' * V A >M b * , i / + * A k l k * , i l J » ¥ A * i ‘ U * 1 J 6 * » A > ' (' 5 * , d f t + ¥ A k £ . 0 * , ? d + v A i i i l * . 2 o * v n H j 3 » ( i ; t v t . l i J u * , 5 S + v A k i 5 * , i ? i ! t v a h . 4 f t * , i ? 3 k V « h ' i o » - . l l 4 V A k o t * . 1 3 * J A k ' I 3 * , 1 A t v A k n b * , i t H t K V . l u i v * ” l i ' t . n i j t w A H i 1 « , 1 $ + v A » | d < » , u ' 7 A V A k ( 3 * - , 0 3 + v A i . d 3 » u « t v A k O i i t - . l i » i i A k y d * , d k + V A l ' 0 ' 7 * , ( , i ; * v A k U r t *. 3 5 * v J k ' i k » . P B t v A H 5 i i * , 6 kh t S k L N S I S V 7 ‘ k 9 * . 3 3 + ¥ A k t ' J * . b | + v A K | i « , u ( , * l/ a i , i d * , l m l / A h l 3 * . 5 5 - * v A | - d 3 * , P l + i ' A ‘' 0 0 » , ^ | t v A k d l » . 0 f t 1 V A I . d 7 » . I / + ¥ A k d o » l i 9 * ¥ A K 4 b * . y 3 * ¥ A K 3 d * , u b * V A k 3 7 * . n u * - ¥ A ' < 3 i 4 * , ' i | t * A M 3 b » < i> 4 t ¥ ( i , M * t i / « v ' A t . l b * . u t * v i ' i ’ | 7 * i b * « A k i p » . i ' d » V A « l li * , l 5 * v A k d i i » . U | t v A k d b * i ( l ' i + v A i l i : b * . d 3 t ¥ A i - 3 1 * , i i i . t ¥ A k 3 4 * , i ) u * i i A k 3 o * , i i 3 + » A k 3 5 * . i 5 * ¥ A k 3 h * i d t “ ;. k O u « , n H t v A k O | * , i i 4 * i / A i . n 3 « , u 7 t v A k * 4 b * t l 5 + w A H i * # n f l t v A r t d * . , i 6 * V A k 3 * # k t7 + v A N j * . M b + v A H ,j * » * 0 3 + V A k o * , u u * ' ¥ A H 7 *
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APPENDIX I
CANONICAL ANALYSIS COMPUTER PROGRAM OF DEMOGRAPHICS/
COMMUNICATION/CLIMATE/SATISFACTION RELATIONSHIP
182
SPSS BATCH SYSTEM 0<l/0a/63 PACE 1S P S S FCR U S / 3 6 0 , V E R S I ON H, R E L E AS E 4 , 1 , FEBRUARY 1 , 1 4 8 /
CURRENT DOCUMENTATI ON FOR THE S P S S BATCH SYSTEM Cf l DER FROM M C C R A H - H I L L t S P S S , 2 h U E H , ( P R I N C I P A L l E x t ) ORDER FROM S P S S I N C , | S P S S S T A T I S T I C A L A I. CUR I T HHS
S P S S UPUATE 7 * 4 ( U S E N / S P S 3 . 2 N 0 FOR R E L , T , 8 , 4 ) NEYwURDSr THE S P S S I N C , N t t - S L E T I E RS P S S P O C « E T G U I D E , H t L E A S E 4S P S S I NTRODUCTORY G U l D E I B A S I C S T A T I S T I C S ANO O P E R A T I O N S S P S S P R I M E R ( H H 1 E F J NT RO TO S P S S )
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1 1 7 2 RECODE VALUES ♦ LAG VAR I ABL E S 5 « B 4 I F / C U mFUYE O P E R A T I O N S
C ANONI CAL C ORR E L AT I ON OF DEMOGRAP HI CS AND OTHER CONCE P TS CrjHDE VAGE S E X h a H ENVT EDUC Y R S P R S J O Yh S CD SALARY S U P E R V I S COH1 COm| A c n w 2 TU C OH5 7 VAH1 TO VARSO SATwRK SATPAY S A T P R Oh Q S AT S UP E R S A T P E C P LAGE AGE R ANGE / S E VHAR SEX AND MARI TAL ST A T U S / E N V T E N V I R U N M E N I / EDUC E DUCATI ON L E V E L / y R S P R S J C YEARS I N P RE S E NT J C H / Y R S C D VEAHS with CUmh D E v E L U P M E N T / S A L A P Y S a l a Ry / S u P E R v I S S U P E R V I S E OTh f R S / S A T h RK S A T I S F A C T I O N w i t h w O R K / S A I P A V S A T I S F A C T I O N w i t h p a y / S ATPROHQ S A T I S F A C T I O N w I T h P R O h C T I O N / S A T S U P E R S A T I S F A C T I O N wlTH S U P E R V l S I O N / S A T P E O P L S A T I S F A C T I O N w i t h P E O P L E /F I X E D < 5 X , F 2 , 0 , 6 5 F l , 0 / 5 x , 5 0 F l , 0 , 5 F 2 , 0 )
ACCORDI NG TO TOUR I NP UT F O R h a T , V A R I A B L E S ARE 1 0 BE READ AS FQL LOwS
v a r i a h l E FORMAT RECORD COLUMNS
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C A N Q M C A L CORRE L AT I ON OF DEHQGRa P h i c S AND OTHER CONCE P TS
F I L E c O h o e v ( C R E A T I O N DATE * U i l / O O Z e D
C O E F F I C I E N T S FOR CANONI CAL V A R I A B L E S OF t h e SECOND SET
CANVAR I CANVAR 2 CANVAR 3
TRUST - 0 , 1 5 1 7 9 0 . 1 7 0 1 1 0 , 1 7 b l 2I n FLUENC 0 , On 7 R 1 - 0 , 5 6 5 8 0 0 , 1 0 5 0 2
►‘ C H I L I T Y • 0 , 0 3 6 0 6 0 , 0 5 b B 3 0 , 3 6 5 2 1i n t e r a c t - 0 . 0 1 8 9 0 0 , 1 P 0 7 U 0 , 1 H 6 5 7D I FUP - 0 . 2 1 0 5 9 o , i a s S u • 0 , Oi t i iR 1Dl RCCRN 0 , 8 1 1 6 1 - 0 , 0 5 1 0 / 0 , 0 0 0 3 9C J R L 1 T R L • 0 , 0 7 1 7 } • 0 . 2 T 7 U R - 0 , 0 1 5 3 1AcCORR • 0 . Z 5 6 5 5 • 0 , I R 1 72 ' 0 , 2 7 7 6 7S U MHA R I Z 0 . 1 3 B 3 9 0 . 0 1 0 5 0 - 0 , 2 1 1 0 3G a TEk E EP 0 . 1 0 9 5 I • 0 . 0 7 U 2 7 - 0 , 0 5 1 6 0Cv ERLCAD • 0 , 1 0 1 2 7 0 , 0 0 7 7 2 - 0 , 2 2 6 0 0C 0 mm5AT • 0 , U 2 7 2 0 . 3 5 2 0 3 - 0 , 1 1 " 9 |
PCDE » f i I T - 0 , 0 0 8 6 2 0 , 2 0 | 17 - 0 , 5 0 6 7 bMCDEF TF 0 , 1 2 0 2 2 • 0 , 3 2 8 1 0 - 0 , 2 5 6 0 1
P CDET EL E 0 , 1 2 6 2 0 - 0 , 1 3 0 5 8 - 0 , 2 1 1 1 1r e u u n c • 0 , 1 3 6 9 9 - 0 , 1 5 6 6 " - 0 . 0 1 1 3 3Un OERLCD • 0 . 0 7 6 2 9 0 , 3 " 0 9 S 0 , 1 0 1 2 7
*■ 1 1 Hh c L D 0 . 0 2 b 5 0 0 , 0 6 2 6 6 0 , 2 2 3 7 0E > p a n d • 0 , 1 2 7 I R 0 . 0 1 5 0 / 0 , 2 2 6 7 9
Ch a n g e 0 , 0 7 5 0 7 - 0 , 0 6 7 U Z - 0 , 3 0 7 9 0
C P E n n e SS 0 , 3 9 6 1 6 - 0 . 0 5 9 0 6 - 0 , 2 5 6 1 3
ACCNE" • 0 . 0 1 2 7 5 0 , 2 0 0 5 5 - 0 , 2 5 0 2 3
C O E F F I C I E N T S FOR CANONI CAL VARI ABL E S OF THE F I R S T
CANVAR 1 CANVAR 2 CANVAR 3
AGE - 0 , 2 7 3 0 1 - 0 , 1 1 5 2 9 0 , 8 1 6 0 5SE » HAR 0 , 1 9 0 3 6 - 0 , o u j 7« 0 . 1 3 7 0 7E n v T • 0 . 0 9 1 9 6 0 , 6 5 9 5 / - 0 , 1 6 2 9 1EOUC * 0 , 3 7 9 5 0 - 0 , 0 ) 5 9 6 - 0 . 2 R O J 6
Y R 3 P R S J 0 - 0 . 0 7 6 0 3 - 0 , 0 5 9 8 6 0 , 2 2 0 6 "Y R SCO 0 , 2 0 6 0 1 0 , 0 1 6 0 9 - 0 , 1 5 0 0 3SALARY 0 . 0 2 3 0 3 - 0 , 2 5 9 6 6 - 0 . 3 2 0 1 0S u P E R V I S 0 . 7 6 8 1 0 0 , 0 2 0 8 3 O . O A b l O
oo/oa/ei PAGE I I
CANONI CAL CORRE L AT I ON OF P E HO g Ha P H I c 3 a n d OTHER C ONC E P T S
f i l e c u h d e v ( c r e a t i o n o a t e ■ u « / o <i / « i i
• • • • • • • ■ • » • • • * • C a n o n i c a l , c □ R r e
NUMBER EI GE NVAL UE c a n o n i c a l H L * 3C O R R E L A T I O N L A ^ b D A
1 0 . 2 3 0 2 7 O . o T R B T 0 , 5 5 i 3 o2 P , 1 8 6 2 « D , 0 U 2 8 8 O . T l t P J3 0 , 0 7 1 3 5 0 , 2 6 7 1 2 O . f i V l O R“ 0 , 0 2 6 6 8 0 , 1 8 3 3 3 0 , 8 5 8 5 65 0 . 0 1 U1 U 0 , 1 1 8 8 3 0 , 8 8 5 8 b
C C E F F l C I t N T 3 FOR C a n o n i c a l VA H I A U L E a o f t h e f i r s t 5ET
a g e3 E a h a rE n v TEP U CV P S P H S J OVR S C OS a l a r y
S u P E H V l J
CANVAR I
0 , 2 8 7 2 7 - 0 , 2 7 7 0 0 - 0 , 0 2 5 2 0 •0,JIORR • 0 , 5 2 1 6 8
0 , 2 7 2 8 0 0 . 8 5 0 5 5 0 , 2 3 2 8 5
C A NV A R i
0 , 0 6 7 3 8 0,88580 0 , 3 3 8 0 5
- 0 , 3 6 b 5 N • 0 ,10072 • 0 , 2 5 8 1 8- 0, « « n 26
0 , 7 1 7 8 ?
C O E F F I C I E N T S f o r C a n o n i c a l V A R I A B L E S fJF THE SECCNO SET
CANVAR 1 CANVAR 2
S i T n R"S a 1 P A V SiIPRC OS a TSL' PEH3 A T P E C P L
0 , 7 8 8 3 3 0 , 6 0 0 8 8
■ 0 , 1 0 7 6 5 0 , 1 1 0 5 7
> 0 , 3 2 6 2 2
0,61257 •0,61088 0 , <1586« •0,68078 -0,01188
0O/0U/B3 PALE 12
T 1 0 N .........................................REL AT E L I S ' 3
C H I - S O l i R E 0 , F , S I G N I F I C A N C E
B6 . 10 3 8 3 00 O . O n p0 8 , 3 8 0 5 8 2 8 0 . 0 1 01 6 , 7 1 8 5 6 18 0 , 5 u 2
5 , 9 6 5 8 7 10 0 , 8 1 62 , 0 6 5 0 0 u 0 . 7 2 8
CANONI CAL CORREL ATJ ON o r DEHQGRa P N I C S AND OTHER CONCE P TS
T R A N S P ' C t R E C l t l R E O . . 7 5 0 0 0 » T t SJJ iHANgPORt'ATlCNJ 222 «tcCDE VALUES ♦ LAG VARIABLES
1 2 0 0 I P / C C H P U T E O P E R A T I O N S
CPU T I N E H E O U I R E D . , o . 5 0 SECONUS
1 3 5 F I N I S H
n c r h i l f N n CF J G R .1 3 5 CONTROL CARDS WERE P R O C E S S E D .0 errors ne»E detected.
0 U / 0 U / A 3 PAGE 1 3 .
A P P E N D IX J
NORMS AND SCORING FORMS FOR
THE JO B D E S C R IP T IV E INDEX
TABLE 5.7Normative JDI Scores
Satisfaction with AH JDI Variables: Stratified by Sox
Male Female
Percenfi/e Work Pay Promotions Supervision Co-Workers Work Pay Promotions'Supervision Co-Workers Percentile
01 0Z 00 00 08 12 08 00 00 10 12 0105 15 04 00 18 21 16 05 00 20 20 0510 21 08 01 25 28 22 07 02 27 25 1015 25 12 04 30 33 25 11 04 31 30 1520 27 15 06 33 36 27 13 05 33 33 2025 30 18 08 35 38 29 16 07 35 36 2530 31 20 10 37 41 30 19 09 37 38 30
. 35 33 24 12 39 42 32 22 10 39 40 3540 35 26 14 41 44 34 23 U 40 42 40
•45 36 28 16 42 45 35 25 12 41 43 4550 38 30 18 44 46 37 28 14 42 44 5055 39 32 20 45 47 38 30 16 44 45 5560 40 34 24 45 48 39 32 17 45 46 6065 42 36 26 47 49 40 34 18 47 48 6570 43 39 30 48 50 41 36 21 47 49 7075 44 41 34 48 50 42 37 23 48 50 7580 45 42 36 50 51 44 40 ' 25 50 51 8085 47 46 41 51 52 45 42 30 51 52 8590 48 48 46 51 52 47 44 38 51 53 9095 50 50 50 52 54 49 48 47 53 53 9599 52 54 54 54 54 52 52 52 54 54 99
Number percolumn 1970 1961 1941 1949 1926 638 634 632 636 635
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APPENDIX K.
PERMISSION LETTERS
208
LOUISIANA. STATE UNIVERSITY Baton Rouge Campus
From: Comnlttee on Humans and Animals as Research Subjects.
To: Vice Chancellor for Advanced Studies and ResearchDavid Boyd Hall
/U n 'in -ii-Proposal of ~b~ Ii M I It Vl I h C ^ " 1 ? J ! j j j _ _ _ _ _ _ _ _
Principal Investigator 'Re:
Entitled A < \ \ A \ M t h e ^ V h l - v Y v d h i p r K r h u v - n{XiwwuH'wrr.i+.i.ci) Y. iiYr.rtj.--/, i .n.i-.n
Y . Y --r H 1 ;p r. tr/X\ | '.I H--.r-~.iV
This is to certify that a quorum of the Conmittee on Humans and Animals as Research Subjects reviewed the above proposal. The Committee evaluated the procedures of the proposal with appropriate guidelines established for activities supported by federal funds involving as subjects humans and/or animals.
Recomsendation of Committee
Comments:
A review of this proposal by the Committee will be accomplished at least on an annual basis and at more frequent Intervals depending on the element of risk.
Humans and Animals as Research Subjects
H A R V A R D U N I V E R S I T Y 210
G R A D U A T E SCHOOL OF BUSINESS ADM INISTRATION
GEORGE F. 'BAKER FOl'.XDATIO'X
DIVISION O F RESEARCH Soldiers FieldB o s t o n , M a s s a c h u s e t t s 0:163
29 May 1979
William C. Sharbrough 111 Louisiana State University Department of Management Baton Rouge, LA 70803
Dear Mr. Sharbrough:
Regarding your request for permission to quote from Litwin and Stringer's Motivation and Organizational Climate, request dated May 23, 1979:
The Division of Research no longer holds the rights to this book. The subsidiary rights were transferred to Harvard University Press. Therefore,I am forwarding your request to:
Ms. Susan Metzger, Permissions Editor Harvard University Press 79 Garden Street Cambridge, MA 02138
Ms. Metzger should be contacting you shortly regarding your request. If you have any further questions, please contact her directly. Thank you for your interest in our publications.
211
UNIVERSITY OF CALIFORNIA, BERKELEY
t v n u T * euvi* • orviNi • m m a m cc-u • ittemjiii • u k doco • u h nuncwo
y n u w i o r lUDNlli AD W IH lfT T L A T IO N I I K O I J T , C A U / M N U 9 4 7 * 0
Octob: r 2nd
Dear I” Sharbrough,
Enclose5. la the r,aterial yov. 'requested,I thin.-: scoring the ite.’is should be obvious.Just take the list of scales fro: here or the JAF article and you can see what items are in each scale.
The questionnaire has been used in a bank, in military units, intphysician’s assistant training program, and in e :ocsk± several mental health units. In addition the accuracy an:’ openness scales we developed have been used and validated in the Ul and in Puerto Rico, SmKTE The sample fcr the US includes all regional areas of a large distribution organisation.This questionnaire has also been used In a military sample, I believe.
Feel free to use the instrument. You can format it as you please and do your own reproduction. I really don't have any information relevant to the questionnaire that has not either been published or is due to be published in A'iT or Hu:an Ccmunication Research shortly.
Good luck with your study. I'd be interested in seeing the results,
karlene rob:- rts
212
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(Subiect t o C o n d i t io n * o n R e v e r t * S id e .) TOTAL AMOUNT 7 3 . ( 1 0
I HEREBY CERTIFY THAT THE M ERCH ANDISE A N D /O R SERVICE HAS BEEN RECEIVED A N D /O R RENDERED fiS INDICATED ABOVE A N D HEREBY AUTHO RIZE PAYMENT FOR MERCHANDISE O R SERVICE
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213
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VITA
William Chambliss Sharbrough III 1302 Tycoon Way Louisville, KY 40213
EDUCATION:
Date of Birth: August 25. 1950Vicksburg, MS
Wife: Dana Handy SharbroughChildren: Matthew, Geoffrey; age 2
1975-present Ph.D. Program, LOUISIANA STATE UNIVERSITY, Major:Management; Minor: Marketing. Commencement: May 19, 1983
1975
1972
1968
WORK EXPERIENCE
August, 197 9- present
September, 1975- May, 1979
January, 1974- August, 1975
July, 1973- January, 1974
January, 1973- June, 1973
M.B.A., MISSISSIPPI STATE UNIVERSITY, Major: Management
B.S., MISSISSIPPI STATE UNIVERSITY, Major: Industrial Tech.
Diploma, HOLLY BLUFF HIGH SCHOOL, Holly Bluff, MS
ASSISTANT PROFESSOR, Department of Management, School of Business, University of Louisville, Louisville, KY
GRADUATE TEACHING ASSISTANT, INSTRUCTOR, Department of Management, College of Business Administration, Louisiana State University, Baton Rouge, LA
GRADUATE RESEARCH ASSISTANT, Department of Management, College of Business and Industry, Mississippi State University, Mississippi State, MS
INDUSTRIAL ENGINEERING AIDE, Gulf State Manufacturers, Inc., Starkville, MS
BUYER'S REPRESENTATIVE, Kelwood Company, Inc., Calford Group, Boys Pants Division, Calhoun City, MS
PROFESSIONAL MEMBERSHIPS:
AWARDS:
Academy of Management Southern Management Association Southwest Division, Academy of Management American Business Communications Association Southwestern American Business Communications
Assoc iationSoutheastern American Business Communications
Association
SWFAD DISTINGUISHED PAPER AWARD, presented by Business Publications, Inc. and Richard D. Irwin, Inc., American Business Communications Association, Southwest Division, March, 1983.
EXAM INATION AND THESIS REPORT
Candidate:
Major Field:
Title of Thesis:
William C. Sharbrough, III
Business Administration
The Interrelationships between Organizational Communication, Organizational Climate, and Job Satisfaction in a local Government Agency.
Approved
Ch' M a jo r P ro fe sso r and
m L
C h a irm a n
D ean of the G ra d u a te
fr-nlLA-— .te fch o o l
EXAM INING COMMITTEE:
Date of Examination: