misrc working paper series linking is-user partnerships to...

MISRC Working Paper Series

WP 99-01

Linking IS-User Partnerships to IS Performance: A Socio-Cognitive Perspective

Mani R. Subramani

Carlson School of Management, University of Minnesota,321, 19th Ave S. Minneapolis, MN 55455

(612) 624-3522, (612)-626-1316 (fax)[email protected]

John C. Henderson

Boston University, 595 Commonwealth Ave, Boston, MA 02215(617) 353-6142, (617) 353-1695 (fax)

email: [email protected]

Jay Cooprider

Bentley College, Waltham, MA(617) 891-2952 (617) 891-2949 (fax)

email: [email protected]

February 1999

Comments are welcome

Linking IS-User Partnerships… 2


Author Biographies

Mani R. Subramani is an Asst. Professor in the IDS Department at the University of Minnesota at

Minneapolis, MN.

John C. Henderson is a Professor and the Department Chair of the IS Department at Boston

University, Boston, MA.

Jay G. Cooprider is an Associate Professor at Bentley College, Waltham, MA.

Acknowledgements

We wish to thank the Systems Research Center at Boston University for support in carrying out this

research and the organizations participating in the research effort that chose to remain anonymous

for their assistance in collecting the data. The first author also wishes to thank Gordon Davis, N.

Venkatraman, Stephanie Watts and Weidong Xia for their helpful comments and Mark Bergen for

his encouraging persistence that helped bring closure to the final draft!



Abstract

The notion that effective relationships between groups improve coordination, cooperation and

consequently performance has considerable appeal in a broad range of contexts. In particular,

partnerships are suggested as critical organizational mechanisms enabling information systems groups

and their clients within organizations to utilize existing information technology investments already

in place and to tap the potential offered by information technologies. This paper proposes a

theoretical model drawing from socio-cognitive theory, highlighting a convergence in perspectives

on key issues between the groups as the central mechanism underlying partnerships. Data from a

survey of managers on both sides of 95 IS-User relationships in multiple firms provides support for

the model and the hypothesized relationship between convergence in perspectives and the

performance of IS groups. In particular, the results suggest that a convergent assessment of the

perspectives of IS groups by Users significantly enhances the performance of IS groups.

Keywords: IS-User Partnerships, IS-Line Partnerships, Social Cognition Theory, IS Performance

ISRL Classification Codes: EI0203 (IS Performance) , Information Services Organization (EG)


Introduction

As organizations increasingly re-evaluate the traditional logic of establishing hierarchical control

mechanisms to achieve coordination between sub-units, the alternative of creating flexible,

cooperative lateral working relationships between interdependent departments has considerable

appeal. Studies of relationships between IS groups who provide IT products and services and their

clients, often termed the 'Line' groups suggest that cooperative arrangements such as partnerships

between IS and User groups significantly enhance outcomes on a variety of dimensions (Henderson

1990, Lasher, Ives and Jarvenpaa 1991). The flexibility and adaptability of such mutually regulated

mechanisms are advantageous in contexts such as that faced by IS providers and clients in

organizations where participants can discover and fashion efficient ways of using and deploying

information technologies during ongoing task execution. Such IS-User partnerships are critical

components of organizational efforts to effectively exploit the potential of information

technologies (Broadbent and Weill 1993, Weill 1992). An understanding of phenomena underlying

IS-User partnerships is clearly imperative for IS research and practice.

The bulk of prior research studies on inter-firm and intra-firm partnerships in general, provides case

based evidence or conceptual frameworks on issues such as vulnerability and risks from

partnerships and articulate the nature of management processes in specific instances that led to

outcomes observed (Johnston and Lawrence 1988, Konsynski and McFarlan 1990, Lasher, Ives and

Jarvenpaa 1991). Examinations of IS-User partnerships are similarly focussed on providing rich,

contextual descriptions of the phenomenon, identifying common themes and proposing intuitive

models to guide action and further research (Henderson 1990, Lacity, Wilcocks and Feeny 1995).

However, few studies have attempted to provide a theoretical understanding of cooperative IS-User

relationships. Consequently, while the anecdotal evidence of both the characteristics and the utility


of partnerships is compelling, this is not matched by an understanding of fundamental processes

underlying the establishment and management of partnerships and their links to performance in

such relationships. In this paper, we move towards rectifying this shortcoming by drawing on

cognitive theory, specifically the socio-cognitive models of group functioning and argue that the

creation of a consensual view on key issues between members of the IS and User groups is the

central feature of cooperative relationships. We also propose that the extent of consensual

understanding is positively related to outcomes such as the performance of IS providers. We

examine the support for these hypotheses in data collected in a survey of 680 IS and User managers

in 95 IS-User relationships in 7 large firms.

In the sections that follow, we briefly review the literature on partnerships and propose the socio-

cognitive model of convergence of perspectives in partnerships. The operationalization of

constructs and the description of the field study of IS-User relationships follow hypotheses relating

convergence in perspectives to performance. We conclude by discussing the implications and

avenues for further research.

What are Partnerships?

Research in multiple disciplines highlights partnerships as patterns of interaction between independent actors

who share common objectives (Anderson and Narus 1990, Lasher, Ives and Jarvenpaa 1991). The term

partnership has been defined as "working relationship that reflects a long-term commitment, a

sense of mutual cooperation, shared risk and benefits, and other qualities consistent with concepts

and theories of participatory decision making" (Henderson 1990, page 8). Partnerships between the

IS group and business units are considered critical relationship-specific assets that allow firms to

derive competitive advantages through information technologies. The ability to derive benefits from

investments in IT in the face of the rapid pace of change in underlying technologies and the


considerable complexity of implementing them in organizations hinges largely on the effectiveness

of the linkages between information technology providers and the functional areas of the business

(Rockart, Earl and Ross 1996, Reich and Benbasat 1996). A field study of coordination mechanisms

in organizations successful in consistently leveraging their IT investments revealed that partnerships

between business and IS managers were vital to their successes with information technologies

(Clark, Cavanaugh, Brown and Sambamurthy 1997). One approach to address the issue is the

building of effective interpersonal relationships between the CIO and the CEO of the firm (Feeny,

Edwards and Simpson 1992). Another approach is the establishment of multiple linkages across

the boundaries of the two groups to foster a broader mutual understanding of IT concerns by

business unit personnel and of business unit concerns by IT personnel (Henderson 1990, Weill

1992).

Despite the allure of the well publicized benefits of IS-User partnerships, they are often difficult to

establish, sustain and manage. The complexity of such efforts in the IS-user context are

compounded by the ambiguity surrounding the causal model underlying partnerships and the

consequent lack of clarity of roles required of IS and User personnel in such relationships (Brown,

MacLean and Straub 1996). A better understanding of factors underlying partnerships and the

nature of their influence on performance are therefore essential to inform both research and

practice in the management of information systems in organizations.

The Socio-Cognitive Model of Information Processing

Evidence on cooperative relationships highlights that development of a mutual understanding between

members of interacting groups as central to enabling effective patterns of coordinated action. In

developing a model of inter-group partnerships, we consequently draw on the theoretical

mechanism of convergence suggested by the socio-cognitive model of managerial information


processing and organizational action (Ginsberg 1994, Walsh, Henderson and Deighton 1993, Weick

and Roberts 1993).

Cognitive structures that are shared by individuals in a group, such as the knowledge and shared

experiences, the assumptions about the environment and expectations from other players are the

central constructs in socio-cognitive theories. Cognitive structures are considered the basic elements

of the common frame of reference and sensemaking apparatus associated with group membership.

The similarity of cognitive structures among group members is viewed as the outcome of social

processes involving communication and interpersonal interactions within a group. In general, the

socio-cognitive model is a theoretical view suggesting that shared cognitive structures that are

generated and maintained through social processes in groups are responsible for shaping outcomes

through their powerful influence on information seeking, problem diagnosis, issue interpretation

and decision making.

These shared cognitive structures are variously termed frames (Goffman 1974), cognitive maps

(Ginsberg 1994), mental models (Ginsberg and Venkatraman 1994) and thought worlds (Dougherty

1992). A large body of literature has examined the role of shared cognitive structures in enabling

the consistent interpretations of stimuli and events in organizational groups and allowing effective

role behavior (see Carley 1977 for a detailed review).

Researchers in management strategy and organizational behavior have examined the influence of

cognitive structures shared by participants on phenomena at both the organizational and

institutional levels. For instance, Ginsberg (1990, 1994) suggests that the belief systems shared by

top management teams determines the corporate strategy of the firm. The reasoning underlying

the link is that the characteristics of managerial belief systems influence the interpretation of the

environment as well as the subset of firm resources that receive emphasis in organizational strategy


formulation. Dutton and Duncan (1987) empirically demonstrate that managers' belief structures

are linked to their assessments of forces impelling change and subsequently to organizational

responses to change stimuli. Porac, Thomas and Baden-Fuller (1989) relate the commonality of

perspectives among industry participants to the competitive structure of the Scottish knitwear

industry. Similarly, Reger and Huff (1993) highlight the importance of managerial perceptions in

defining strategic groups in the banking industry. They argue that the cognitive structures of

managers about the competitive environment significantly influence the nature of action by each

organization and thereby influence industry evolution.

The socio-cognitive perspective is a particularly appropriate lens to examine phenomena related to

information systems in organizations for several reasons. Firstly, information systems have many of

the features ascribed to equivoques (Weick 1990): contexts of IS design and use generally require

individuals and groups to resolve the considerable ambiguity that surrounds inputs, outputs and

underlying processes. These features are similar to those present in contexts where artefacts are

created from relatively novel technologies, the background knowledge and assumptions of

individuals and groups and habitual modes of interpretation significantly influence sensemaking and

action formulation (Garud and Rappa 1994). Further, information systems involve not only the

creation of invisible analogs of formerly visible and sentient work processes but also have

considerable implications for the task design as well as the social system where systems are

introduced. System conception and implementation therefore requires participants to engage in

abstract reasoning and the consideration of the context significantly altered by technology, actions

that are influenced significantly by alternative mental models of the technology, the task and the

context (Goodman and Sproull 1989, Ginsberg and Venkatraman 1992). Secondly, the inherently

open-ended and flexible nature of software often obscures differences in the mental models


underlying the design of software providing similar functionality, not all of which are, however,

equivalent in terms of their implications for users (Silver 1990). The character of the final software

artifact delivered to users is therefore influenced by the many individual choices made by systems

designers from multiple alternatives available at different stages of design (Orlikowski 1992). The

shared cognitive structures manifested in the perspectives held by information systems designers

about users and the assumptions about the role of technology in the organization, are consequently

key factors directly influencing outcomes. Thirdly, the usage of information systems and nature of

their incorporation into work processes are significantly shaped by the structure of IS and User

relationships (Beath and Orlikowski 1994) as well as social factors such as the interpersonal

interactions between developers and users, the interpretation of the organizational motivations for

technology introduction and the attitudes formed by the socio-political contextual surrounding the

change (Hirscheim and Klein 1989).

In IS research, socio-cognitive theory has been used examine phenomena pertaining to information

systems design, implementation and use of the technologies in organizations. Orlikowski and Gash

(1994) propose the concept of technological frames: interpretations of information technology by

organizational participants. They argue that the outcomes of technology introduction and use are

linked to the congruence of the technology frames of users and developers. They suggest that frame

congruence reflects the sharing of understanding of different aspects of the technology between

designers and users and that congruence aids the realization of the benefits of technology

introduction in the organization. Conversely, a lack of congruence in the frames is considered to be

detrimental: "the incongruence of frames provides an interesting explanation of the difficulties and

unanticipated outcomes associated with the technology implementation" (Orilowski and Gash 1994,

page 175). A convergence in understanding on key issues between providers and users is linked to


innovativeness in the use of the technology (Lind and Zmud 1992) and performance of IS

providers (Nelson and Cooprider 1997).

A Socio-Cognitive perspective on IS-User Relationships

In line with the notion of convergence highlighted by Lind and Zmud (1992), we suggest that IS-

User relationships may be characterized in terms of the level of convergence in perspectives on key

aspects of the relationship. We view intergroup relationships, those approaching the commonly

construed notions of partnership, as characterized by each group realistically interpreting and

accurately taking the perspectives of the partner. Such a convergence in perspectives, we argue, is

central to cooperation and the favorable outcomes attributed to partnerships.

We suggest that our approach emphasizing the importance of the comprehension of the

perspectives of each group by the other is particularly appropriate in the context of IS-User

relationships where the ability to accurately make sense of the other group's world-view is very

important. IS-User relationships involve considerable collaborative action by the two groups that

inherently have differences arising out of differences in their functional specializations. Information

systems designers tend to focus on the technical aspects of their design, often neglecting the

implications of these design choices for users. Many system design failures have their roots in

inappropriate choices by systems designers that introduced characteristics that made them

unacceptable in the social system (Hirscheim and Kling 1989). Perspective Convergence: the

understanding of designers' perspectives by users and vice versa, would enable the groups to

explore alternatives that satisfy the requirements of both technical and social design perspectives,

improving outcomes for both groups. Perspective Convergence we argue is central to perspective

taking in intergroup interactions: the ability of a group to visualize issues from the standpoint of

another group, a feature central to effective communication (Boland and Tenkasi 1995).


When each group clearly understands the perspective of the other group on issues that influence

action in intergroup interactions, the partners can accurately interpret and anticipate each other's

actions and evolve advantageous patterns of resource combinations through adaptive coordination

(Lounaama and March 1993). As each group works to achieve both their individual and joint goals

in the interaction, the mental models that one group has of the other significantly influence the

effectiveness of communication, the nature of negotiation, bargaining and conflict resolution

processes that occur between the groups. This is particularly critical in IS-User relationships

involving the design and support of systems to support knowledgework (Boland and Tenkasi 1995).

For instance, the ability of customers to take advantages of the IS provider’s capabilities is aided by

the customers' understanding of the knowledge and experiences that the IS providers possess. In

such instances, customers are likely to be able to express their problems in a manner that the IS

group can effectively address. Similarly, the IS provider's understanding of the users' perspective of

their task environment would improve the ability of providers to craft solutions that fit with their

customers views of the task and further, anticipate problems customers may encounter in using

them. The appreciation of the perspective of the other group in an interaction enhances the ability

of the one group to truly understand the motivations and reasoning underlying the actions of the

other group. This not only encourages meaningful dialogue to achieve mutually acceptable

resolutions to differences but also creates the context for more innovative uses of information

technologies (Boland and Tenkasi 1995).

Overall, drawing on the socio-cognitive perspective, we view partnerships between interacting

groups as the bridging of the frames of reference of the two groups in a manner that enables each

group to effectively comprehend the perspective of the other group. This suggests an alternative

framing of working relationships between IS and User groups: as mechanism to facilitate the realistic


assessment of perspectives between groups on key issues influencing action. Analogous to the notion of a shared

understanding conveyed by the notion of covergence (Lind and Zmud 1992), we use the term

perspective convergence to refer to the understanding of the perspectives of one group by the other.

Clearly, relationships charcterized by greater perspective convergence are likely to be more effective than

those with lower levels of perspective convergence.

This is analogous to the views expressed in the socio-technical paradigm that information systems

designers need to effectively appreciate the task and the social environment as perceived by the

users (Bostrom and Hienen 1977). This is also consistent with the implications of research that has

highlighted the multiple perspectives inherent in issues related to IT interventions (Orlikowski 1991,

Orlikowski and Gash 1994). These authors' persuasive arguments about the far-reaching

implications of the differences in perspectives on information technologies endorse our arguments

for a need to focus on the extent to which each group understands the views of the other group.

Such an understanding of the other groups' perspectives is also recognized in other contexts of

cooperation (Andersen and Weitz 1992, Gulati, Khanna and Nohria 1994).

We emphasize that this approach is distinct from an expectation that the perspectives of the two

interacting groups, even in the ideal case, be identical. Studies of mental models of managers

emphasize that the perspectives are very significantly influenced by the role responsibilities of the

group that they belong to (Hodgkinson and Johnson 1994). Differences in views on multi-faceted

phenomena such as information technology are natural and founded on genuinely different views

of organizational reality confronting groups in different roles. In IS-User relationships, IS

personnel such as systems analysts in systems conceptualization and design roles and users draw on

different bases of knowledge and past experience, leading to different framing of organizational

phenomena.. In organizational contexts marked by changes in organizational processes with the


application of information technologies, systematic differences in the views of IS and user groups

may arise from many sources. These include the differing levels of experience with the technology

and the task, variances in the organizational visibility for the roles before and after technology

mediation, differing views on the outcomes of technology implementation and the implications for

the technology mediation for the groups concerned (Hirscheim and Kling 1989). For instance,

Orlikowski and Gash (1994) narrate an episode where " a technologist amused his colleagues by

recounting a hands-on computer demonstration where a user picked the mouse up and tried to use

it by pointing it at the screen as if it were a remote-control device. Such stereotypical views of users

are not uncommon in IS departments." (page 191). This account hints at the wide disparity in

experience with and expectations of technology between technologists and users. However, we

believe effective relationship are marked by technologists and users developing a realistic

understanding of the way the other group views key issues: a realistic perception of one group's views by

the other rather than a coincidence of perspectives of the two groups.

The notion of perspective convergence in a dyadic setting incorporates two distinct phenomena. For

instance, in the context of an IS group serving a specific user group, one type of convergence is the

extent to which the extent to which the IS group is successful in perspective taking with respect to

Perspective Takingby IS group

(ISUS) IS Group

Perspective Takingby User group

(USIS)User Group

Key IS Issues in Relationship -Perspective of IS (ISIS)

Figure 1a: Convergence on IS PerspectivesIS Gap = ISIS – USIS

Key User Issues in Relationship- Perspective of Users (USUS)

Figure1b: Convergence on User PerspectivesUser Gap = USUS - ISUS


the User group, in a sense, reflecting the extent of the IS group comprehension of the perspective of the User

group. The other type of convergence is the extent to which the User group is successful in

perspective taking, reflecting the extent of User group comprehension of the perspective of the IS group. We

suggest that, each of these is likely to have different implications for management of the

relationship and likely to have differentially influence outcomes in the relationship. These are

illustrated in figures 1a and 1b.

Using the notation USUS and ISIS to represent the User and IS groups' perspectives on specific issues

in the relationship and ISUS and USIS for the IS's and User groups’ perspective taking with respect to

the partner, we define gaps or a lack of perspective convergence as:

User gap = (USUS-ISUS), i.e. the difference between the User group’s views on issues

affecting the relationship and the IS group’s assessment of the User group's perspectives.

IS gap = (ISIS-USIS), i.e. the difference between IS group’s views on issues affecting the

relationship and the User group’s assessment of the IS group's perspectives.

The User gap is the discrepancy between User group views and the IS group’s perspective taking with

respect to the Users. When there is a high level of convergence, there would minimal differences

between the Line's perspectives (USUS) and IS group’s view of the User group's perspectives (ISUS).

The User gap in such a relationship would consequently be small. Analogously, the IS gap is the

discrepancy between the perspective of IS groups and the User group’s perspective taking with respect

to the IS group.

A high level of convergence is indicated by minimal discrepancies in perspectives and small IS and

User gaps. Where the level of convergence is low, the perspectives of the IS group (ISIS) and the IS


group's perspective as perceived by clients (USIS) are likely to be quite divergent, a situation

indicated by a high IS gap1.

Qualitative data collected from observations of boundary spanners at the IS-User interface provides

support for our approach to examine IS-User relationships in terms of the convergence in

perspectives between the groups. The evidence suggests that effective IS-user relationships are

characterized by the sensitivity of participants to the views of partner groups and high performing

managers at the interface are acutely sensitive to the socio-political processes required to achieve a

convergence in perspectives. Managers at the interface of these groups are seen working to establish

convergence through coalition building and mechanisms that create greater transparency of the

actions, intentions and priorities of one group to the other (Subramani, Iacono and Henderson

1995). For instance, unless the IS has a clear perception of the Line's business priorities and the

future plans, it is likely that the IS personnel would fail to recognize opportunities to leverage

emerging technology to meet client needs, focusing instead on other areas that might be of lesser

significance to users.

Perspective Convergence in IS-User Relationships

Drawing from the partnership model (Henderson 1990), we focus on perspective convergence in

the IS-User context on the six factors comprising the model: Mutual benefits, Commitment,

Predisposition, Shared knowledge, Distinctive competencies and Organizational linkages (See

Appendix-1 for a brief description of the model). These factors in the model are suggested as the

most salient in influencing effective action and enabling effective coordinated action by IS and User

groups. Viewed in terms of gaps, the IS and User gaps e.g. in Distinctive Competencies:

1 Here on, we continue our discussion of convergence in terms of gaps. Gaps are inversely related to the extent of


a) User gap in Distinctive Competencies is the difference between:

- the User group’s assessments of the level of skills and experience that their own group possesses and brings to

the relationship (USUS) and

- the IS group’s assessments of the level of skills and experience that the User group possesses and brings to

the relationship (ISUS)

A high level of convergence is indicated by a small 'User gap'.

b) Similarly, IS gap in Distinctive Competencies is the difference between:

- the IS group’s assessments of the level of skills and experiences that their own group possesses and brings to

the relationship (ISIS) and

convergence and, in our experience, the concepts are more readily communicated when expressed in terms of gaps.

Convergence(IS Gap)

IS SharedKnowledge

IS DistinctiveCapabilities

IS OrgLinkages

IS MutualBenefits

IS Commit-ments

IS Predis-position

Partnership Factors(IS)

IS SharedKnowledge

IS DistinctiveCapabilities

IS OrgLinkages

IS MutualBenefits

IS Commit-ments

IS Predis-position

User View of ISPartnership Factors

PartnershipOutcomes

Convergence(User Gap)

User SharedKnowledge

Us DistinctiveCapabilities

User OrgLinkages

User MutualBenefits

Us Commit-ments

User Predis-position

Partnership Factors(User)

User SharedKnowledge

Us DistinctiveCapabilities

User OrgLinkages

User MutualBenefits

Us Commit-ments

User Predis-position

IS View of UserPartnership Factors


- the User group’s assessments of the level of skills and experiences that the IS group possesses and brings to

the relationship (USIS)

A high level of convergence is indicated by a small 'IS gap'.

The notion inherent in the partnership model is that parties take an overall view of their

relationship and that is a composite of their perceptions of the individual factors in the model (See

Figure 2). Our arguments suggest that an overall convergence in perspectives (where the gaps are

small), across all individual factors involved would enable the IS groups to engage in superior

perspective taking related to the Users and serve them more effectively, leading us to the

hypotheses that:

H1a: The overall level of convergence between IS and User perspectives across all partnership factors is positively

related to IS Performance.

Or analogously, stated in terms of gaps:

H1b: The overall level of gaps in convergence between IS and User perspectives across all partnership factors is

inversely related to IS Performance

The Partnership Model implicitly suggests that the six dimensions are co-equal in their influence on

the strength of IS-User relationships. An interesting question is whether any of the individual

factors of partnership is particularly influential in determining outcomes such as performance. If

this is the case, we would expect convergence on of the six dimensions to be directly related to

performance and gaps (in any direction - positive or negative) between IS and User groups to

adversely impact IS performance, leading us to the following hypotheses:

H2: The level of convergence on each of the dimensions of the Partnership Model is positively related to IS

Performance.

Expressed in terms of gaps:


H2’: The IS and the Line gaps on each of the dimensions of the Partnership Model are inversely related to IS

Performance.

We expand the hypothesis for each of the six factors of partnership in the model:

H2’a: The IS and the Line gaps on Mutual Benefits are inversely related to IS Performance.

H2’b: The IS and the Line gaps in Commitment are inversely related to IS Performance.

H2’c: The IS and the Line gaps in Predisposition are inversely related to IS Performance.

H2’d: The IS and the Line gaps in Shared Knowledge are inversely related to IS Performance.

H2’e: The IS and the Line gaps in Distinctive Capabilities are inversely related to IS Performance.

H2’f: The IS and the Line gaps in Organizational Linkage are inversely related to IS Performance.

Study

Data to examine the hypotheses were collected in a field survey of IS-User relationships. The

instruments to measure the constructs were constructed from the rich qualitative data collected in

executive interviews in the first phase of the project (Henderson 1990).

Sampling: A field study of 132 relationships between the IS and User groups was conducted in a

convenience sample of seven large organizations in the pharmaceutical, insurance, oil & gas,

consumer goods, computer manufacturing, insurance and automotive industries in USA. The

organizations in the study were associated with a research center in a large East Coast university and

agreed to cooperate with the researchers, permitting access to IS and user managers for the survey.

The sample was restricted to this set of organizations because of the difficulty in eliciting

organizational participation as the study design imposed considerable demands on the managerial

time: the study description indicated that upto 10 managers: 3 IS managers, 3 User managers and 2

senior executives would be required to spend about 30-45 minutes each to fill out surveys.


The survey method was chosen to extend our understanding of partnerships and enhance

generalizability of the findings and build upon the rich descriptions in prior accounts (Johnston and

Lawrence 1988) highlighting unique particulars of partnerships.

The level of analysis in this study is the IS-User relationship. While all organizations agreeing to

participate were covered in the survey, the choice of IS-User relationships within each organization

included the survey was determined by three criteria:

a) That user departments obtain IT products and services solely from the in-house IS department.

b) That the relationships deliver well defined product/services to users and be managed through a

formal management structure

c) That the relationship have a history of interaction of at least 3 years

Data were collected using the key informants method (Philips and Bagozzi 1986) from both sides of

IS-User relationships: from managers of IS groups and managers of user groups who could report

reliably on the perspective of their own organizational units in the relationship. Multiple informants

provided data on the perspectives of the group that they belonged to (e.g. the perspectives of the IS

group in their interactions with users).

Survey Administration: In each of the firms surveyed, the senior manager championing the study

appointed a coordinator who us helped identify IS-User relationships that met the criteria for

inclusion in our sample. The coordinators also identified individual managers to be surveyed within

each of the IS and User groups involved in each of the relationships. Surveys were mailed to 423 IS

managers and 426 managers in User groups. Performance assessment surveys were mailed to 262

senior divisional level managers responsible for user groups and the VP or the equivalent senior

manager heading the IS function. To avoid common methods bias, care was taken to ensure that


the managers providing performance assessments were distinct from those who had been mailed

the partnership instrument.

Measures

Partnership Measures: Items to measure the dimensions of the partnership model were created based

on interviews with IS managers and User managers. These were then extensively field tested and

further refined in personal administrations to multiple managers to address the possibility of

inaccurate responses due to ambiguous item construction and biases from specific sequencing of

questions. Two versions of the partnership instrument were created, one for IS groups and the

other for User groups. Each of these was a two-part survey eliciting assessments of:

a) Partnership factors from the perspective of their own group

b) Partnership factors from the perspective of the partner

A third instrument to ascertain the level of IS performance was created for mailing to senior

managers in participating organizations. Items in all surveys were worded in a manner that allowed

customization of questions to refer to the specific IS group and the specific User group in

organizations being studied. A detailed description of the procedures followed for item

construction and the psychometric tests performed for instrument validation is provided in

Cooprider (1990).

The items used to measure the constructs in the study are provided in Appendix -2.

IS Performance: One of the important motivations underlying the establishment of IS-User

partnerships in firms is the improvement of IS performance (Henderson 1990). We consequently

focussed on IS performance as the key outcome variable and measured this in the study. This

decision was reinforced by field interviews that suggested that IS performance metrics often directly


incorporated the level of benefits provided to users. Thus, IS performance provides a measure of

outcomes both to the IS group as well as indirectly outcomes for the User group.

Consistent with the model of IS performance (Cooprider and Henderson 1989), we conceptualized

IS Performance as comprising two dimensions: Operational performance and Service performance.

Operational performance refers to the efficiency of the group in the usage of resources while service

performance refers to the ability of the IS providers to anticipate and be responsive to the needs of

the client. These two dimensions represent the conflicting choices: acting to optimize resource

usage and acting to customize offerings for customers often required of IS groups (Cooprider and

Henderson 1989).

Data Analysis, Results

Response: Overall, 671 responses on IS-User relationships were received from 346 IS managers

and 334 User managers. The 346 responses from IS managers pertained to 125 IS-User

relationships, the 334 responses from Users pertained to 123 relationships. IS performance

assessments were received from 168 senior managers on IS performance in 119 relationships. Every

IS-user relationship included in the analysis combined data from three sources: a) assessment of

partnership factors by IS managers b) assessment of partnership factors by User managers and c)

the assessment of IS performance by senior managers. Relationships that were not complete in all

these respects were dropped from further consideration. The final dataset created for the analysis

included 95 relationships for which we had complete information from all three sources, the

analyses reported here are based on this set. In 56 of the 95 relationships, all of the three

assessments: IS side perspectives, User perspectives and IS performance are based on information

provided by multiple informants.


Table 1: Details of survey mailing and response# SurveysDistributed

# ResponsesReceived

ResponseRate

# RelationshipsRepresented

IS Perspective 423 346 82 % 125User Perspective 426 334 79 % 123Performance 262 170 65% 119

Sample and Informant Characteristics: The average size of the IS groups in the sample was 160

persons, the average size of the user groups was about 740. On average, IS informants had spent

13 years in the firm and were involved in interactions with the specific user group for about 3.5

years. User informants had spent an average of 17 years in the firm and had been in the current

user group for about five years. The senior managers who provided the assessments of IS

performance had, in general, a tenure in the organization of over 20 years. The Cronbach's alphas

for the constructs measured are provided in Table 2. The values suggest adequate levels of

reliability and internal consistency as they are all above 0.6 except for User Commitment, which is

0.59. The means and standard deviations of the partnership factors as viewed by the IS and the

User groups are presented in Table 4.

Table 2: Measurement Properties of IndicatorsPartnership Dimension Cronbach's α

IS Perspectives (n=95)Cronbach's α

User Perspectives (n=95)#

ItemsOwn

GroupOn

Users#

ItemsOwn

GroupOn ISGroup

Mutual Benefits 4 0.83 0.81 4 0.77 0.86

Commitment 2 0.65 0.63 2 0.59 0.74

Predisposition 3 0.70 0.84 3 0.74 0.88

Shared Knowledge 2 0.82 0.81 2 0.85 0.84

Distinctive Competencies 2 0.63 0.63 2 0.64 0.71

Organizational Linkages 4 0.85 0.82 4 0.84 0.87

Operational Performance* 3 0.78

Service Performance * 3 0.85

Note: Assessments of Partnership factors were provided by members of I/S and User groups while Performanceassessments were provided by senior managers managing the groups


Table 3: Descriptive Statistics of Partnership Factors (n=95)Partnership Dimension IS Perspectives

Means (sd)

User Perspectives

Means (sd)

Gaps in Perspectives

Means (sd)

Construct Perspectiveof ownGroup

(I1)

Perspectiveof Partner

(I2)

Perspectiveof ownGroup(U1)

Perspectiveof Partner

(U2)

ISGap(I1-U2)

User Gap(U1-I2)

Mutual Benefits 4.23 (0.86) 4.30 (0.85) 4.30 (0.82) 4.02 (0.95) 0.22 (0.82) -0.04 (0.86)

Commitment 4.60 (0.93) 3.48 (0.80) 3.60 (0.81) 3.83 (1.03) 0.77 (1.18) 0.13 (0.98)

Predisposition 4.71 (0.91) 4.89 (0.88) 4.86 (0.74) 4.17 (1.09) 0.54 (0.94) -0.03 (0.91)

Shared Knowledge 4.30 (0.92) 3.83 (1.03) 4.16 (1.03) 4.06 (1.04) 0.25 (1.08) 0.32 (1.03)

Distinctive Competencies 4.92 (0.88) 4.83 (0.82) 5.18 (0.71) 4.55 (0.97) 0.37 (1.02) 0.35 (0.90)

Organizational Linkages 3.91 (0.93) 4.31 (0.92) 4.14 (0.93) 4.11 (0.99) -0.19 (0.97) -0.17 (0.99)

Overall Partnership 4.45 (0.76) 4.28 (0.76) 4.37 (0.69) 4.12 (0.91) 0.33 (0.84) 0.09 (0.73)

Table 4: Descriptive Statistics for IS performance (n=95)Mean (SD) Correlation

Service Performance 4.57 (0.93)

Operational Performance 4.50 (0.96)

0.59, p<.01

Analyses, Results

Before proceeding to verify our research hypotheses, we considered alternative hypotheses that

differences in IS performance may be attributed to contextual factors in the relationships,

procedure suggested by Bock (1975). We ran a series of regressions of IS performance on variables

that may potentially influence IS performance such as the size of the IS and User groups, the

technical complexity of the IS products and services, the level of risk and uncertainty characterizing

IS products/services and the stability of the requirements of the User groups. Of this set of

potential explanatory variables of IS performance, only complexity of IS products and services was

significantly (and inversely) related to performance, a relationship recognized in prior research

(Ellis, Watson and Moody 1992). We therefore included product/service complexity as a control


variable in our analyses. In effect, by controlling for complexity, we perform a conservative test of

the influence of IS and User gaps on IS performance.

As our hypotheses relate only to the effect of the magnitude of gaps rather than the direction of the

differences, we calculated the absolute values of gaps in perception at the level of each of the six factors

of Partnership e.g. Shared Knowledge, Predisposition etc for each IS-User relationship. We

calculated the overall gaps in Partnership as the average of the gaps on all six factors. The

descriptive statistics for the IS and Line gaps on each of the partnership factors are provided in

Table 8.

Association of Partnership Gaps and Performance

To ascertain the strength and direction of the association between the magnitude of the gaps and IS

performance, we performed multiple regression analyses with the absolute value of the IS and User

gaps in partnership as the independent variables and performance as the dependent variable. We

included Product/Service Complexity as a control variable in all the analyses. Separate regressions

were run for Operational Performance and Service Performance.

Table 5 presents the results of the two regression analyses with the overall IS Gap and overall User

Gap (average of the values of gaps in the six partnership factors) as the predictors; Service

performance and Operational performance as the dependent variables. Technical complexity of the

task was included as a control variable in both the analyses. 2.

The results indicate that the values of the IS Gap and of the User Gap are significantly related to

both Service performance F(3,91)=4.9, p<.01 and to Operational performance, F(3,91)=4.2, p<.01.

2 Introducing an interaction term in the equations, we found that the coefficient of the interaction of the two gaps toperformance was non-significant. We also explored the likelihood that the relationship of gaps to performance wasnon-linear. We re-analyzed the data with second order terms corresponding to both IS gap and User gap introduced


The adjusted R2 of 0.11 and 0.09 indicate that these variables explain 11 percent and 9 percent of

the variance in Service performance and Operational performance respectively. The values of the regression

coefficients of IS gap (-0.36, t=-2.67, p<.01) and of User gap (-0.23, t=-1.77, p<0.05,) in the

equation relating them to IS Service performance are negative and significant. Similarly, the

coefficients of IS gap and User gap in the regression relating them to IS Operational performance (-

0.45, -0.30 respectively) are negative and significant as well (t=-3.32, p<.01, t=-2.14, p<.05).

These results suggests support for an inverse relationship between gaps and performance: that

lower levels of performance are observed in dyads with larger IS Gaps and User gaps. The results

therefore provide support for Hypothesis 1a and 1b, that IS performance is inversely related to IS

and User gaps.

While IS gap and User gap are both inversely related to Operational as well as Service performance of

IS groups, the relative magnitudes of individual coefficients in both equations indicates that IS gaps

(lack of congruence between IS perspective and those perceived by Users) are more strongly (and

inversely) related to IS performance than User gaps.

Table 5: Association of IS and User Gaps with IS performanceDependent Variable Predictors and

ControlStandardized Beta

(t value)R2 (adjusted)

F statistic:(df 3,91)IS Service Performance IS, User Gaps,

Complexity0.114.9**

IS Gap (-)0.36(-)2.67**

User Gap (-)0.23(-)1.77*

Complexity (-)0.28(-).2.78**

IS Operational Performance IS, User Gaps,Complexity

0.094.2**

IS Gap (-)0.45(-)3.32**

User Gap (-)0.30(-)2.14*

into the regression. The coefficients of the second order factors were non-significant, lending support to the firstorder relationship proposed between gaps and performance.


Complexity (-)0.14(-)1.38

Note: **: p<.01, *:p<.05 in one sided t tests

Association of Gaps in Partnership factors to IS Performance

To examine the influence of gaps on individual partnership factors on performance, we performed

multiple regressions with IS and User gaps in partnership factors as the independent variables and

Service performance and Operational performance as the dependent variables. As before, Technical

complexity was included as a control variable in each regression equation. Performing multiple

significance tests within a single sample (12 in our case, one test each for gaps on the six dimension

of partnership on the two dependent variables) increases the error rate across the entire study. As

suggested by Bock (1975), we used the Bonferroni correction and employed p<0.005 as the

significance level for each individual test to control the overall level of significance of each

individual test to p<0.05. In effect, this correction yields a very conservative test for the influence

of each factor. In each instance, we performed one-sided tests since the hypotheses propose an a-

priori directionality of effects. The results of the analyses are provided in Table 6.

Table 6: Regression Results: Influence of Gaps on IS PerformanceGaps inPartnershipDimensions

Service Performance (Dependent Variable) Operational Performance(Dependent Variable)

R2 adj. Overall F(df 3,91)

Beta, tstatistic forUser Gap

Beta, tstatistic forIS Gap

R2 adj. Overall F(df 3,91)

Beta, tstatistic forUser Gap

Beta, tstatistic forIS Gap

Gap in MutualBenefits

0.15 6.77*** -0.26(-2.187)*

-0.38(-3.37)***

0.07 3.45* -0.19(-1.53)

-0.35(-3.51)***

Gap inCommitment

0.049 2.61 0.10(0.09)

-0.86(-0.79)

0.03 1.82 -0.05(-0.43)

-0.22(-1.97)

Gap inPredisposition

0.08 3.66* -0.15(-1.29)

-0.23(-1.91)

0.05 2.75* -0.24(-1.96)

-0.30(-2.98)***

Gap in SharedKnowledge

0.05 2.64 0.05(0.40)

-0.06(-0.51)

0.01 1.30 -0.5(-0.42)

-0.18(-1.50)

Gap in DistinctiveCompetencies

0.15 6.60*** -0.18(-1.63)

-0.37(-3.45)***

0.09 4.14** -0.24(-2.12)

-0.35(-3.19)***

Gap in OrgLinkages

0.09 4.57*** -0.12(-0.96)

-0.38(-2.81)***

0.05 2.63 -0.21(-1.61)

-0.27(-2.08)*

Note: 1)Complexity was included as a control variable in all the analyses. 2) ***: p<.005, **: p<.01, *p<.05 in one sided t tests


Focussing on the overall F statistic that reflects the strength of the relationships of gaps in

individual partnership factors to IS Service performance, we find that the links between gaps in

Mutual Benefits, gaps in Distinctive Competencies and gaps in Organizational Linkages to IS

Service performance pass the conservative test of significance at p<0.005. The data suggest that, of

the six factors of the partnership model, these are the three that are the most significantly

associated with Service performance.

None of the F statistics relating gaps in partnership factors to IS Operational performance are

significant at the 0.005 level.

An examination of the individual coefficients of User gap and IS gap where the overall relationship

to IS Service Performance is significant, reveals that coefficients of IS gaps in each of these factors

is negative and significant. The coefficients of User gaps in each of these factors do not achieve

significance.

While the overall F statistics of the association between IS Operational performance and gaps in

Distinctive Competencies and gaps in Mutual Benefits are significant at the 0.01 and the 0.05 levels

respectively and are suggestive of their inverse relationship to performance, the evidence is tenuous

as they do not meet the stronger criteria for association when multiple comparisons are performed.

In general, the t statistics for the coefficients of the IS gap and User gap for most dimensions are

negative (all except two of the 24 coefficients), reflecting the inverse relationship between the size

of gaps on these dimensions and performance. The relationship is significant at the conservative

0.005 level in the case of only three dimensions: IS gaps in Mutual Benefits IS gap in Distinctive

competencies and IS gaps in Organizational linkages.

The results thus provide only partial support for Hypothesis 2.


Discussions and Conclusions

Overall, this study highlights the utility of the socio-cognitive model in examining intergroup

relationships in organizations, particularly those between IS providers and their clients. This

research contributes to the conceptualization and operationalization of perceptual congruence in

terms of IS gaps and User Gaps, lending clarity to a model of how the perception of the views of

each group by the partner in partnership relationships may influence outcomes.

The results, in general, reflect the importance of achieving a match between the perspectives of IS

providers and their clients: a lack of convergence is negatively associated with IS performance. In

particular, IS gaps: a lack of convergence of User perspectives on IS perspectives emerges as the

most salient aspect influencing performance. This essentially suggests that influencing user groups’

perceptions of their IS providers is a powerful tool to improve IS performance.

Advancing the understanding of the factors in the relationship on which convergence influences IS

performance, the data suggest that efforts to achieve convergence can focus fruitfully upon the

factors identified in the partnership model, particularly the nature of benefits to the IS group, the

distinctive resources contributed by IS groups and the organizational linkages between the IS group

and users.

Some of these results run counter to current conventional wisdom on improving IS performance.

The assumption implicit in most efforts to enhance IS performance in organizations is that the

delivery of IS performance is improved by a greater understanding of client perspectives by IS

groups. While IS gap and User gap are both related to IS performance, our findings suggest that IS

gaps have a stronger influence and are more closely related to IS performance than User gaps. This

reinforces the idea that developing ‘intelligent’ and understanding customers is a powerful means to

impact performance, a notion recognized in the IS service quality literature (Pitt, Watson, Kavan


1995) where perceptions of service attributes by users is a key construct related to IS service quality.

Recalling that IS gaps arise from differences in the perception of the IS by User groups, this

suggests in effect that achieving a realistic assessment of IS perspectives by Users is a powerful lever

to influence IS performance. Further, the results suggest that users' comprehension of the

structure of IS benefits in the relationship, the distinctive competencies contributed by the IS group

and the nature of social, informational and process linkages by which the IS group are able to

influence users are important in influencing IS performance.

Material from subsequent interviews with IS managers and users to understand the results of our

study provide some clues related to the link observed between Users' understanding of IS

perspectives and IS performance. In one instance, we found that a greater understanding by Users

of the profile of the processing workload of their IS provider enhanced IS performance by allowing

User managers to work within the constraints on IS capacity without affecting the outcomes to

themselves. The case involved a large centralized HR function located in the East coast of a

Fortune 500 firm whose IT services were provided by a central IS group. One of the major

services provided by the IS group involved an I/O intensive and CPU intensive report generation

application that was run every day at noon on its central server in Raleigh to provide an updated

report on employee turnover available online for access by 2PM. This major application stretched

IS processing resources during the period that the group was handling the increasing volume from

West Coast offices, requiring the IS group to consider making a budget request to upgrade

processing capacity. However, when the managers of the user group were approached by the

Relationship Manager, the person managing the interface between the groups, who explained to

them the processing constraints faced by the IS, the group readily agreed to have the report

generation application moved from its regularly scheduled mid-day slot to off-peak hours later in


the day. The Relationship Manager learnt that the User group had specified a mid-day deadline on

the processing only as a precaution to ensure that the statistics would be available to brief senior

managers the following morning: the user group requirements were met as long as the report

generation was completed before the end of the working day3. This accommodation helped the IS

group tremendously as it allowed them to provide high response times for online transactions

during peak times while utilizing capacity during off-peak times for the HR application. This is one

instance of how an understanding of IS perspectives, particularly that of the structure of IS benefits

by User personnel leads to improved IS performance.

We encountered another instance of the productive outcomes from an understanding of the IS

providers' perspective in a large firm during the design of an application to provide standard HR

services (such as changing 401K payroll deductions) to employees online. In the course of

interactions, the user group learnt that the IS group's internal procedures to evaluate the quality of

the project members' performance strongly emphasized the creation of highly secure systems.

Further, the IS group had instituted a policy of penalizing both the development and operations

groups responsible for systems that were considered insufficiently secure. To the user group, this

provided the causal logic for what they believed to be overly elaborate security measures that the IS

group was suggesting for the applications. This led to a meeting being convened by managers of

the user group with the IS group in which senior personnel from both groups discussed the security

concerns anticipated by the IS group in great detail, jointly assessing not only the severity of the risk

but also the probability of the occurrence of each type of incident. The consequent exchange of

information on patterns of anticipated system use and the HR group's understanding of the target

3 For a more detailed account of the activities of relationship managers: organizational roles devised to achieve theconvergence of perspectives between IS and User groups, see Subramani, Iacono and Henderson (1995) and Iacono,Subramani and Henderson (1995).


audience allowed the IS group to redefine the system specifications with the appropriate levels of

security. The final set of security measures adopted was a more practical subset of the original

proposal by the IS group resulting in a scaling down of cost and complexity of the design while

meeting the security standards of the IS group. This subset avoided large costs related to preventing

egregious behavior (such as malicious hacking by insiders in the HR group) and relied instead on a

closely monitored security process tracking the modification of sensitive information. This re-

specification, engendered by the users' understanding of the IS group's application development

processes and the development effort and costs for different alternatives enabled significant cost

savings as well as faster application development: both of which were key factors influencing IS

performance.

The results of this study support the propositions based on socio-cognitive theory that gaps in

perception are negatively related to performance and that convergence in perspectives between

interacting groups is desirable. However, it is also feasible for members of groups to converge on

views that might not be reflective of reality or might be a distortion of reality. A convergence in

such instances is in fact quite counterproductive and can often lead to adverse consequences. In IT

mediated IS-User interactions for applications development, groupthink, the phenomenon

characterized by group members feeling pressured to achieve consensus prevents a consideration of

divergent perspectives that might lead to more desirable outcomes (Kettelhut 1993). The negative

outcomes of convergence between IS and User group are also observed in re-engineering projects,

where widely held non-critical attitudes towards existing organizational features often hinder the

elimination of structural deficiencies (Kiely 1995). We therefore sound a note of caution that

efforts to minimize perceptual gaps in IS-user relationships need to be sensitive to this possibility.

This is a real threat in the context of IS-User relationships as mental models incorporating distorted


views of reality, when shared, can be disastrous as this may lead groups to ignore or underplay the

value and applicability of new technologies that radically disrupt convents and standard operating

procedures or the established status quo.

This study provides an empirical test of the partnership model (Henderson 1990), extending our

understanding of the nature of factors important in establishing effective relationships between IS

groups and their users. The results, while demonstrating the utility of the model suggest ways in

which the model may be refined further.

We believe that the results also have implications for the design of IS curricula in business schools.

There has been considerable emphasis on the incorporation of content relating to the various

organizational functions in IS curricula so that graduates can effective members of IS organizations

(Lee, Trauth and Farwell 1995). The results of our study suggest this emphasis on providing an

understanding of functional organizations in IS graduate programs needs to be matched by an

emphasis on providing an understanding of IS management issues in functional business curricula

such as marketing and operations. This understanding of IS perspectives will train students to be

effective managers who can effectively leverage organizational resources invested in information

technologies most effectively. While this is an emerging view expressed by educators concerned

about the content of core MBA curricula (Silver, Markus, Beath 1995), our study provides evidence

for the validity of their conceptual arguments.

This study also has implications for the design of organizational incentive mechanisms. We believe

that the result of this study may be generalizable to the use of organizational services provided by

the IS group that are infrastructural in nature such as electronic commerce services, human resource

services etc. Our results suggest that it might be productive to design incentive mechanisms that

encourage the comprehension of service providers' perspectives so that the groups may be


intelligent consumers, allowing service providers to enhance performance, achieving the larger goal

of effective organizational resource utilization. This is clearly an issue of considerable importance to

IS researchers and practitioners and warrants further examination.

We would like to emphasize that these generalizability of these results may be limited because they

are based on the examination of phenomena in large firms where users groups exclusively used the

services of in-house IS service providers. The applicability to domains where a large proportion of

services are outsourced is an empirical question that bears further research. While this study

focussed specifically on the factors identified as being important in the partnership model

(Henderson 1990), more work is needed to inform our understanding of the key issues on which

convergence between IS and their client groups is important and the influence of social processes

and organizational context on the IS-User interface. Further, this study, consistent with the

reference theory, focussed exclusively on the absolute magnitude of the gaps in perception between

groups and their influence on outcomes. Such an approach is consequently not sensitive to the

magnitude and direction of the gaps. For instance, by focussing on the absolute magnitudes of

gaps, this study treats the effect of an over-estimation of the Organizational Linkages of the IS

group by the User group as identical to the influence of an under-estimation of the Organizational

Linkages by the same magnitude. We believe that a finer articulation of the differences examining

the influence of the directionality of gaps is likely to yield further insights on the phenomenon.

Finally, we also echo the call for more action research by other authors such as Markus and

Benjamin (1996), Iacono, Subramani and Henderson (1995) to articulate micro-behaviors, based on

actual observations of managerial action at the IS-User interface that would enhance our

understanding of dynamics leading to the outcomes of interaction of these groups.


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Appendix-1

A Model of IS-User Partnerships

The partnership model (Henderson 1990) characterizes partnerships between IS and User groups in

as six factors that are clustered in two dimensions - Partnership in Context (PIC) and Partnership in

Action (PIA). PIC comprises the factors that provide the motivation for sustaining the

relationship: responses to the basic question that Henderson put to executives from both sides of

IS and User interactions: “Why are you in this relationship”. Henderson argues that the factors

comprising PIC create the context for action that is the touchstone that needs to be addressed in

the relationship by both groups. PIC encompasses a range of issues consistently emphasized in the

literature on trust and cooperative action (Smith, Carroll and Ashford 1995). PIA, comprises factors

that create the ability of groups to influence each other on an ongoing basis and reflects the ability

of each group to influence action and participate effectively in the relationship. The PIA dimension

captures the responses to the question: “What are you doing on a day to day basis to manage this

relationship?”. This dimension incorporates the social political component of intergroup action

important for performance in a wide range of contexts (Seely Brown and Duguid 1991).

The partnership models suggests three factors underlying both PIC and PIA. The factors

constituting the contextual dimension (PIC) are mutual benefits derived from the relationship, the

formal and informal commitments to the relationship and the predisposition: the attitudes towards

cooperation between the groups. The factors constituting the action dimension (PIA) are shared

knowledge: the extent of knowledge about the other group's environment, the distinctive competencies

that create the dependence on the resources of the other partner and organizational linkage, the task

related, social and informational linkages between the groups. The factors of the model and the

typical issues involved in each of them are in Table 1.


Table 7 : The Partnership Model (Henderson 1990)Factors determining Partnership Typical Issues

Mutual Benefits from relationship * Financial Benefits

* Risk Sharing

* Increased Innovation

* Increased Quality of Work Life

Commitment to relationship * Nature of formal agreements

* Extent of Shared Goals

* Organizational Incentives to cooperate

Predisposition * Trust

* Track record of partner

* Attitudes towards Cooperation

Shared Knowledge Knowledge of partner's:

* Task environment

* Decision environment

* Social environment

Dependence on Distinctive

Competencies and Resources

* Dependence on partner's personnel, skills and physical assets

* Extent of training and preparation required to work effectively in the relationship

Organizational Linkages * Creation of joint management processes for planning, performance review etc.

* Joint involvement in operational processes e.g. rescheduling batch jobs, enhancing data security

* Information exchange

* Social linkages


Appendix -2 4

IS Performance Measures

Scale: 7 point Likert Scale anchored (from 1 to 7) on :Non Existent, Very Weak, Weak, About Average, Strong, Very Strong, Extremely Strong

Operational PerformanceIn general, the job satisfaction of the [IS organization] personnel is:In general, the financial contribution (e.g. return on assets, profitability, etc.) of the [IS organization] is:In general, the flexibility of the [IS organization] is:

Service PerformanceIn general, the contribution that the [IS organization] has made to the accomplishments of the [User

organization]’s strategic goals is..In general, the ability of the [IS organization] to react quickly to the [User organization]’s changing business

needs is..In general, the extent to which the work produced for the [User organization] by the [IS organization] is

innovative or creative is:

Technical Complexity

Scale: 7 point Likert ScaleTechnically Very Simple, Mixed Technically Very Complex.

In general, the work done by the IS organization for the User organization is:

Factors of IS-User PartnershipsScale: 7 Point Likert Scale

Mutual BenefitsThe level of non-financial benefits (such as improved job satisfaction or quality of work life) that the

[User/functional organization] receives from its relationship with the [I/S organization] is:The degree to which the [User/functional organization] is able to reduce its risk level in achieving its goals

because of its relationship with the [I/S organization] is:The extent to which the [User/functional organization] uses technology in more innovative ways because of

its relationship with the [I/S organization] is:The degree to which the [User/functional organization] is proactive in initiating new uses and applications of

information technologies is:CommitmentThe degree to which the [User/functional organization] supports the goals of the [I/S organization] is:The degree to which the incentive system of the [User/functional organization] supports the goals of the [I/S

4Note: The material in brackets in each question was customized in surveys to refer to the specific IS and Userorganizations e.g. In general, the ability of the IT Support Group to react quickly to the Marketing Research Group's changing businessneeds is..


organization] is:

PredispositionThe willingness of the [User/functional organization] to involve key [I/S organization] people in their

planning activities is:The reputation of the [User/functional organization] for meeting its commitments to the [I/S organization]

is:The degree to which the [I/S organization] trusts the [User/functional organization] is:Shared KnowledgeThe level of understanding of the [User/functional organization] for the work environment (problems, tasks,

roles, etc.) of the [I/S organization] is:The level of appreciation that the [User/functional organization] has for the accomplishments of the [I/S

organization] is:Distinctive Competencies and ResourcesThe extent to which the [User/functional organization] depends on the resources of the [I/S organization]

(such as people, skills, technology, etc.) to accomplish its goals is:The extent to which the [User/functional organization] has invested specific resources (such as people,

technology, special training, etc.) in order to work more effectively with the [I/S organization] is:Organizational LinkagesThe extent to which the [User/function organization] receives information about the planning processes of

the [I/S organization] is:The extent to which [User/function organization] personnel have close relationships with key I/S planners or

strategists is:The extent to which [User/function organization] personnel have close relationships with those involved in

the day-to-day activities of the [I/S organization] is:The extent to which [User/function organization] personnel monitor and review the activities of the [I/S

organization] is:


Table 8: Descriptive Statistics and Zero Order CorrelationsMean SD LMUTBG LCOMMG LPREDG LSHRKG LDISTG LORGLG IMUTBG ICOMMG IPREDG ISHRKG

LMUTBG -.101 .9967 1.000LCOMMG .094 1.0920 .506 1.000LPREDG -.091 .8907 .446 .445 1.000LSHRKG .203 1.0184 .577 .564 .541 1.000LDISTG .256 .9746 .552 .421 .532 .568 1.000

LORGLG -.231 .9661 .606 .512 .388 .591 .539 1.000IMUTBG .309 .9603 -.536 -.461 -.291 -.551 -.466 -.627 1.000

ICOMMG .791 1.1568 -.346 -.371 -.294 -.331 -.338 -.529 .568 1.000IPREDG .599 1.0261 -.573 -.427 -.544 -.606 -.491 -.663 .622 .662 1.000ISHRKG .367 1.0877 -.478 -.319 -.314 -.546 -.412 -.516 .639 .674 .680 1.000IDISTG -.117 .9671 -.431 -.324 -.292 -.494 -.443 -.598 .729 .604 .666 .693

IORGLG .427 1.0525 -.495 -.391 -.371 -.538 -.359 -.618 .676 .596 .650 .650IS Complex 2.887 1.0723 -.289 -.241 -.073 -.133 -.178 -.067 .073 .066 .098 .125** Correlation is significant at the 0.01 level (2-tailed).* Correlation is significant at the 0.05 level (2-tailed).

a Listwise N=95

Note on Nomenclature: Lmutbg refers to Line gaps while Imutbg refers to IS Gaps

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