measuring internal supply chain...

Measuring Internal Supply Chain Integration

Chuda Basnet Department of Management Systems

The University of Waikato Private Bag 3105

Hamilton, New Zealand 3216 [email protected]

Abstract

Internal supply chain refers to the chain of activities within a company that concludes

with providing a product to the customer. This process involves multiple functions within

companies – sales, production, and distribution. It is obvious that these functions need to be

integrated in order to provide good customer service. However, there is no consensus yet on

how integration is to be defined and measured. This paper presents research that was

conducted with the goal of developing an instrument for the measurement of internal supply

chain integration. Scale items were identified from current literature and the resulting survey

instrument was sent out to a sample of New Zealand manufacturers. Statistical analysis was

conducted to validate the instrument. We also identified three dimensions of integration

labelled coordination, communication, and affective relationship. This paper makes a

contribution towards developing a consensus in the understanding and measurement of the

integration construct.

1. Introduction

Internal supply chain refers to the chain of activities or functions (see Figure 1) within a

company that concludes with providing a product to the customer. Integration of these

functions involves holistic performance of activities across departmental boundaries. A well-

integrated internal supply chain should result in excellent customer service and company

performance.

Figure 1. Internal supply chain integration

While there is no dispute about the benefits of a well-integrated internal supply chain, there is

little consensus on what constitutes integration and how to measure integration. Some authors

have envisaged integration as coordination of functional activities, others view integration as

communication. Instruments that researchers have employed to measure integration reflect

their own definitions.

In the research reported in this paper, we identified scale items to measure internal supply

chain integration from existing research and used a survey to purify and validate the scale.

We also identified three dimensions within the integration construct – communication,

coordination, and affective relationship. The contribution of this paper is the development of

this scale for the measurement of integration, validating the instrument against a criterion,

and the identification of the three dimensions of integration. To the best of our knowledge,

this kind of investigation has not been done before in this area.

Production Sales Distribution

The next section presents a literature review, which is followed by a statement of research

objective. Then we describe our research methodology. The statistical analysis of collected

data is detailed next. In the final section, we discuss our findings and make some concluding

comments. Unless indicated otherwise by the context, the word “integration” is used to mean

internal supply chain integration throughout this paper.

2. Literature review

The advent of the concept of supply chain management has put great emphasis on supply

chain integration. It is generally accepted that supply chain integration evolves in stages

(Stevens, 1989):

Functional integration, whose focus is intra-functional, followed by

Internal supply chain integration, whose focus is inter-functional, and

External supply chain integration whose focus is inter-firm.

Giménez (2004) supported this evolution in her exploratory study of supply chain integration.

Stank et al., (2001b) also supported the link between internal and external integration. Even

though the study of internal supply chain integration is new and not numerous (Giménez,

2004; Gimenez & Ventura, 2003; Pagell, 2004), there have been many earlier studies in the

area of inter-functional integration particularly in the context of new product development

and production-marketing interface (e.g. Calantone et al., 2002; Kahn, 1996; Kahn &

Mentzer, 1996; Mollenkopf et al., 2000; Stank et al., 1999).

Most of the studies on internal integration have sought to determine the performance benefits

of integration. Chen et al. (2007) found that “marketing-logistics collaborative activities”

lead to “firm-wide integration”, which leads to “performance”. Ellinger (2000) investigated

marketing – logistics collaboration and posited that “Evaluation and reward system”, “Cross-

functional collaboration”, “Effective inter-departmental relations” and “Distribution service

performance” were serially linked. This linkage was supported by a survey and regression

analysis. Gimenez & Ventura (2003) tested the effect of internal integration and external

integration on performance, using structural equations modelling and a survey. They found

that both had positive effect on performance. Kahn & Mentzer (1998) sought to separately

identify the benefits of communication and collaboration on performance in the context of

marketing’s integration with other departments. They found significant benefits for

collaboration, but not for communication. O'Leary-Kelly & Flores (2002) studied the effect

of mediating variables on the relationship between integration and performance using survey

and regression analysis. Swimming against the current, they found that the benefit of

production – marketing integration is not always worth the cost of such integration. The costs

of integration could only be justified by examining the internal and external environment

faced by a firm.

Another stream of research on internal integration is focused on the antecedents of internal

integration. . Calantone et al. (2002) used a survey and structural equations modelling to find

that marketing’s knowledge of manufacturing and manufacturing’s evaluation of marketing

communication both had positive relationships with marketing-manufacturing integration.

Hausman et al. (2002) proposed a model linking antecedents to manufacturing-marketing

integration, and integration to profits. They found through a survey that the strategic

importance of both departments positively related to integration, and integration related to

profits. This suggested that top management should strive to view both marketing and

manufacturing as key contributors to a firm’s competitive strategy in order to boost

integration (and profits). Pagell (2004) conducted case studies to determine the factors that

foster or inhibit internal (supply chain) integration in firms. His focus was on the integration

of production, logistics, and purchasing functions. He identified the constructs influencing

integration as structure, culture, facility layout, job rotation and cross-functional teams.

Mollenkopf et al. (2000) carried out a survey in New Zealand to verify their model that

linked antecedents to inter-functional integration. Regression analysis showed that including

integration in strategic plans helps in fostering integration. Cross - training helps too, but

rewards did not prove significant in this research.

As discussed above, significant amount of research has been conducted on the performance

benefits of integration, which by and large has shown that integration is beneficial for

customer service and a company’s bottom line. A complementary theme of research, which is

less voluminous, seeks to identify antecedents of integration. This stream of research has the

ultimate goal of normatively suggesting top management what it can do to foster integration.

Many such suggestions have been made including changing the culture, job rotation,

knowledge of each other, numeration schemes, top management attitude, etc.

Even as this research on integration continues, there is no clear consensus on the definition of

integration and on the measurement of integration. Researchers have posited various

dimensions within the construct of integration, such as: communication, interaction,

coordination, collaboration, harmony, adherence to the “integrated logistics” concept,

cooperation, interfacing, and consultation.

Table 1 is a compilation of definitions of integration found in the literature. There is a wide

divergence in how authors see integration. It appears that interaction or exchange of

information is seen as a minimum part of integration. Another element is the coordination of

activities, which involves the orchestration of inter-departmental activities. A third common

element is collaboration, which involves departments working jointly.

Table 1. Definitions of integration

Reference Context Definition of integration

Adler (1995) Production & Design Coordination of design manufacturing relationship. They did not provide a definition, but they considered only coordination.

Calantone et al. (2002)

Marketing–manufacturing in new product development

Cross functional harmony; cooperation and relationship quality.

Chen et al. (2007)

Firmwide Interaction and collaboration

Crittenden (1992)

Marketing / manufacturing

Communication

Daugherty et al. (1996)

Logistics/General Adherence to the “integrated logistics” concept

Ellinger et al. (1997)

Logistics/General Integration = close coordination and central programming

Ellinger et al. (2000)

Marketing/Logistics Integration = information interchange, consultation, collaboration

Giménez (2004) Wider supply chain Coordination, collaboration, and integration

Gimenez & Ventura (2003)

Internal (purchasing, manufacturing, sales and distribution) / External integration

Interaction

Gimenez & Ventura (2005)

Wider supply chain Interaction

Griffin & Hauser (1996)

Marketing/R&D Integration = communication & cooperation

Hausman et al. (2002)

Marketing/Manufacturing Marketing/Manufacturing interface harmony—the functions’ ability to work together

Hsu & Chen (2004)

Marketing/Manufacturing Interaction ‐ congruence

Kahn (1996) Marketing/Others (Product development)

Multi‐dimensional process that subsumes interaction and collaboration. Interaction = structural, formal, routine coordinated activities like meetings, calls, documents. Collaboration = Unstructured, affective, volitional, shared process of working together.

Kahn & Mentzer (1996)

Logistics function and other functions

A process of interdepartmental interaction and interdepartmental collaboration that brings departments together into a cohesive organization; interaction = communication, collaboration = work together.

Kahn & Marketing/Others Integration = interaction = information interchange; or, Integration =

Mentzer (1998) (Product development) collaboration = high degrees of shared values, mutual goals and collaborative behaviours; or integration = composite of both

Lunn (1997) General Teamwork

Mollenkopf et al. (2000)

Marketing/Logistics Integration = dissemination of information and coordination of activities

Murphy & Poist (1992)

Logistics / Marketing Integration = cooperation, used synonymously with coordination; but cooperation was not defined.

O'Leary‐Kelly & Flores (2002)

Marketing/Manufacturing the extent to which separate parties work together in a cooperative manner to arrive at mutually acceptable outcomes

Orsini & Karagozoglu (1988)

Marketing/Service Integration = coordination = interfacing

Pagell (2004) Production/Logistics/Purchasing

Integration is a process of interaction and collaboration in which manufacturing, purchasing and logistics work together in a cooperative manner to arrive at mutually acceptable outcomes for their organization.

Sawhney & Piper (2002)

Marketing/Manufacturing Integration = interface

Stank et al. (1999)

Marketing/Logistics integration = melding together disparate areas, achieved through information sharing or collaboration or both

Stank et al. (2001a)

SCM Linking internal activities to best support customer requirements at the total system cost

Swink & Song (2007)

Marketing/Manufacturing Coordination of timing and substance of functional strategies and development activities. Communication + Cooperation

Van Hoek & Mitchell (2006)

Interdepartmental Integration = Agreement on goals and objectives

The context of our research is internal supply chain – in particular the functions of

production, sales, and distribution. A basic requirement for integration would be that these

independent functions work together. This has been emphasised by many authors in Table 1.

In arriving at a consensus definition of integration, one should also consider that supply chain

integration is often justified on the basis that the entities of a supply chain should work

holistically, trying to optimise a common outcome rather than each entity optimising its own

well-being. Thus unity of purpose is essential for any definition of integration. We adopt a

simple minimal definition of integration for our research – working together for the benefit

of the company.

It is inevitable that as the definitions of integration are divergent, the scale items to measure

integration are also diverse. Table 2 presents scale items for measuring integration found in

the literature. The scale items reflect the concept of integration from the authors’ perspectives

and the context of integration considered by them. The variety of measures in the table

clearly makes the case that there is a need to work towards a consensus in the measurement

of the integration construct.

Table 2. Scale items for the measurement of integration

Scale item Included in this research? (Reason for exclusion)

Reference

Within my firm, employees from different functional areas are encouraged to share resources

Antecedent Chen et al. (2007)

My firm extensively utilizes cross-functional work teams for managing day-to-day operations

Yes Chen et al. (2007)

The orientation of my firm has shifted from managing functions to managing processes

Explanation Chen et al. (2007)

Mutual understanding of technical knowledge about NPD Different context Calantone et al. (2002)

Cooperation between MKT and MFG in NPD Different context Calantone et al. (2002)

Informally working together Summative Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Kahn & Mentzer (1998)

Sharing ideas, information, and/or resources Yes Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Gimenez & Ventura (2003 and 2005); Kahn & Mentzer (1998)

Working together as a team Summative Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Kahn & Mentzer (1998)

Conducting joint planning to anticipate and resolve operational problems

Yes Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Gimenez & Ventura (2003 and 2005)

Achieving goals collectively Summative Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Kahn & Mentzer (1998)

Developing a mutual understanding of responsibilities Yes Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Gimenez & Ventura (2003 and 2005); Kahn & Mentzer (1998)

Making joint decisions about ways to improve overall cost efficiency

Yes Chen et al. (2007); Ellinger (2000); Ellinger et al. (2000); Gimenez & Ventura (2003 and 2005)

Information Exchange through Exchange of reports Yes Ellinger et al. (2000)

Information Exchange through Exchange of memorandums Yes Ellinger et al. (2000)

Information Exchange through Exchange of fax materials Yes Ellinger et al. (2000)

Consultation through Committees / task forces Yes Ellinger et al. (2000)

Consultation through Phone conversations Yes Ellinger et al. (2000)

Consultation through Phone mail Yes Ellinger et al. (2000)

Consultation through Electronic mail Yes Ellinger et al. (2000)

Linkage between functions Explanation Giménez (2004)

Consideration of the effect of own actions on other functions Yes Giménez (2004)

Organisational structure (presence of a customer service department responsible for complete order fulfilment process)

Different context Giménez (2004)

How well marketing and manufacturing work together Summative Hausman et al. (2002)

Working closely with manufacturing often helps your department achieve its goals

Summative Kahn & Mentzer (1994)

Working closely with manufacturing often improves the quality of decisions made by your department

Summative Kahn & Mentzer (1994)

Your department strives to maintain a good working relationship with manufacturing

Yes Kahn & Mentzer (1994)

Interaction through: I. Meetings: (1) Meetings 2) Committees/Task Forces 3) Phone Conversations, 4) Phone Mail 5) Electronic Mail.


Interaction through Documented Information Exchange: 1) Exchange of forms 2) Exchange of reports 3) Exchange of memorandums 4) Exchange of FAX materials;


Share the same vision for the company Yes Kahn & Mentzer (1998)

Informal teamwork Yes Gimenez & Ventura (2003 (2005)

Established teamwork Yes Gimenez & Ventura (2003 (2005)

Joint establishment of objectives Yes Gimenez & Ventura (2003 (2005)

Information is communicated between marketing and logistics Yes Mollenkopf et al. (2000)

Information regarding customers is given to logistics people Yes Mollenkopf et al. (2000)

Information regarding products is given to logistics Yes Mollenkopf et al. (2000)

Information regarding warehousing / transportation is given to marketing

Yes Mollenkopf et al. (2000)

Marketing and logistics people don't discuss with each other the issues affecting marketing and logistics


Marketing and logistics don't coordinate their activities Yes Mollenkopf et al. (2000)

Marketing and logistics don't spend time discussing future customer needs


Level of cooperation Summative, Explanation

Murphy & Poist (1992)

Data integration among internal functions through information network

Antecedent Narasimhan & Kim (2002)

System-wide information system integration among internal functions


Real-time searching of the level of inventory Different context Narasimhan & Kim (2002)

Real-time searching of logistics-related operating data Different context Narasimhan & Kim (2002)

Data integration in production process Antecedent Narasimhan & Kim (2002)

Integrative inventory management Explanation Narasimhan & Kim (2002)

The construction of system-wide interaction system between production and sales


The utilization of periodic interdepartmental meetings among internal function

Yes Narasimhan & Kim (2002)

Extent of integration of decisions in product development Summative O'Leary-Kelly & Flores (2002)

Extent of integration of decisions in marketing/sales planning Summative O'Leary-Kelly & Flores (2002)

Extent of integration of decisions in process development Summative O'Leary-Kelly & Flores (2002)

Extent of integration of decisions in manufacturing planning Summative O'Leary-Kelly & Flores (2002)

In this business unit, it is easy to talk virtually with anyone you need to regardless of rank or position

Yes Parente et al. (2002)

In this business unit, I feel comfortable calling people in the manufacturing unit when the need arises.


Managers here discourage employees from discussing work-related Antecedent Parente et al. (2002)

matters with those who are not their immediate superiors or subordinates People in our sales department are quite accessible to those in the manufacturing units.


Managers in manufacturing can easily schedule meetings with sales personnel.


Salespeople can easily schedule meetings with manufacturing Yes Parente et al. (2002)

Most departments in this business unit get along well with each other.


When members from sales and the production units get together, tensions frequently runs high.


Employees from sales and the production units feel that the goals in their respective departments are in harmony with each other.

Summative Parente et al. (2002)

The objectives pursued by the sales department are incompatible with those of the manufacturing departments.


There is little / no sales/ production conflict in this business unit. Summative Parente et al. (2002)

Both functions share information. Yes Parente et al. (2002)

Both functions integrate strategy. Explanation Parente et al. (2002)

Both functions contribute to customer value. Summative, Explanation

Parente et al. (2002)

Operations consults marketing before making process changes Yes Sawhney & Piper (2002)

Marketing consults operations before accepting early delivery requests

Yes Sawhney & Piper (2002)

Marketing consults operations before accepting special feature requests

Yes Sawhney & Piper (2002)

Order entry system provides information on existing orders, their completion time and available capacity

Different context Sawhney & Piper (2002)

Numeric estimate of the time taken by marketing to pass order information to production

Different context Sawhney & Piper (2002)

My firm maintains an integrated database and access method to facilitate information sharing

Antecedent, Different context

Stank et al. (2001b)

My firm effectively shares operational information between departments

Yes Stank et al. (2001b)

My firm has adequate ability to share both standardised and customised information internally

Yes Stank et al. (2001b)

My firm provides objective feedback to employees regarding integrated logistics performance

Antecedent Stank et al. (2001b)

My firm's compensation, incentive, and reward systems encourage integration

Antecedent Stank et al. (2001b)

3. Research objective

This research is focused on the measurement of the integration construct, in the context of

internal supply chains. Our goal was to identify a parsimonious set of scale items from

previous literature that will capture the domain of this concept, as defined succinctly in the

above section – working together for the benefit of the company. Another goal was to explore

the structure of this construct, that is, to see if it makes sense to break this construct into

further dimensions.

4. Research methodology

The list of scale items in Table 2 was scrutinised with a view to severely reduce the number

of items in the scale, the ultimate goal being the development of a parsimonious measurement

instrument, at the same time capturing the domain of the construct. Items were excluded for

one or more of the following reasons (see Table 2):

Summative – Summative items were not suitable, since the goal was to capture the

domain of the construct

Antecedent – The item appears to be antecedent to integration

Different context – The item appears to apply to a different context other than internal

supply chain considered in this research

Explanation – Further explanations would be needed for use in a survey questionnaire

Many of the remaining items were similar in meaning. These similar items were reworded to

construct a single item. Two academics and two practitioners vetted the items for clarity. This

process led to the following 16 items for the measurement of integration. The items asked the

respondents to answer each of these questions with the preface: “In my company the

departments involved in production, sales and distribution of products ...”

Table 3. Scale items included in the instrument

Q1 Share ideas, information, and resources between them.

Q2 Conduct joint planning to anticipate and resolve supply chain problems.

Q3 Spend time developing a mutual understanding of responsibilities.

Q4 Strive to maintain a good working relationship with each other.

Q5 Interact with each other through meetings or phones or emails.

Q6 Interact with each other through the exchange of forms, reports, or documents.

Q7 Spend time discussing future customer needs.

Q8 Are quite accessible to each other.

Q9 Share the same vision for the company.

Q10 Establish joint objectives.

Q11 Get along well with each other.

Q12 Share information regarding own department with other departments.

Q13 Consult with each other before making decisions affecting other departments.

Q14 Work frequently in informal cross-departmental teams.

Q15 Understand the pressures and concerns of each other.

Q16 Synchronise their activities with each other.

Criterion

A criterion question was included in the survey, encompassing the definition of integration

adopted in this research.

Q17 (In my company the departments involved in production, sales and distribution of

products) work together for the benefit of the company.

A mail questionnaire and a postage-free return envelope were sent out to 999 manufacturing

firms in New Zealand in October 2010. These firms were identified through a commercial

database of businesses, KOMPASS, which is fairly comprehensive. The selected firms were

the largest in New Zealand with respect to number of employees, the rationale being that the

larger firms are likely to have distinct departments in their internal supply chain in need of

integration. After all, a firm with one employee can be assumed to be highly integrated!

The survey was sent out to either the general managers (or equivalent) or to the top executive

in production, sales, or distribution in order to ensure that the respondents were

knowledgeable about the state of integration in their company. All the items in the survey had

a 7-point Likert scale (1 = Strongly disagree, 4 = Neutral, 7 = Strongly agree).

The questionnaire was accompanied by a cover letter highlighting the objectives of the

research, assuring confidentiality, and promising a summary of the research report. A serial

number was included for follow-up. After a month, when the flow of responses had started to

dwindle, a reminder was sent with another copy of the questionnaire and a postage-free return

envelope. When the responses had stopped, there was a tally of 273 usable responses. This is

a response rate of 27%, which is quite high for this kind of survey.

The number of employees of the respondents is shown in Table 4. There is a clear

preponderance of larger firms within New Zealand, but by international standards, most of

our respondents are small to medium sized firms.

Table 4. Demographics of the sample

Number of employees Frequency

Up to 20 6 21-50 74 51-100 85 101-150 45 151-200 12 More than 200 50

The usable 273 responses were analysed using commercial SPSS software, as detailed in the

next section.

5. Analysis

Non-response bias

Even though our response rate was high, the question of non-response bias still arises. The

possibility exists that the firms who did not respond are different from the respondents, and

our sample does not represent the non-responders. Assuming that the late responders are

similar to the non-responders, we compared early responders with the late responders. The

first 25% of the sample was compared against the last 25% of the sample. The hypothesis

could not be rejected that the mean of each of the 17 item-responses was the same for the two

groups, using 2-tailed t-test at p = 0.05. The lowest p was 0.193. Similarly, a Pearson Chi

square test on an organisational characteristic (number of workers) rejected the null

hypothesis that there was an association between organisation size and tardiness in response

(p = 0.848). These tests give confidence that the non-response bias in our study is minimal.

Content validity

All the measures in this instrument were obtained from existing literature. In addition, two

academics and two practitioners reviewed the measures and suggested changes for clarity.

After data collection Pearson correlation coefficients between all the different measures were

examined (see Table 5). None of the correlations were found very high (highest = 0.715),

suggesting that there was no multi-collinearity. Item to sum-of-items correlations were also

high (0.523 to 0.787). This gives confidence that the items measure the same construct.

However, the correlation of Q6 with the criterion was particularly low (0.307). For this

reason, this item was dropped from further analysis. All the correlations reported in Table 5

were statistically significant at p = 0.001.

Table 5. Coorelation Matrix

Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 SUM

Q1

Q2 0.656

Q3 0.648 0.714

Q4 0.604 0.561 0.600

Q5 0.614 0.546 0.545 0.605

Q6 0.340 0.387 0.361 0.313 0.458

Q7 0.573 0.544 0.620 0.511 0.508 0.374

Q8 0.590 0.393 0.465 0.516 0.557 0.269 0.463

Q9 0.590 0.443 0.524 0.494 0.528 0.331 0.523 0.596

Q10 0.574 0.542 0.589 0.497 0.495 0.368 0.650 0.513 0.662

Q11 0.529 0.415 0.418 0.542 0.511 0.276 0.397 0.511 0.528 0.445

Q12 0.561 0.497 0.537 0.511 0.565 0.334 0.544 0.549 0.566 0.582 0.577

Q13 0.511 0.477 0.556 0.478 0.455 0.285 0.529 0.421 0.469 0.608 0.472 0.645

Q14 0.477 0.428 0.444 0.419 0.430 0.333 0.433 0.417 0.431 0.456 0.427 0.496 0.453

Q15 0.476 0.454 0.530 0.471 0.421 0.293 0.458 0.429 0.492 0.502 0.418 0.567 0.624 0.521

Q16 0.568 0.518 0.586 0.494 0.532 0.344 0.509 0.497 0.533 0.611 0.496 0.622 0.640 0.451 0.691

SUM 0.785 0.731 0.787 0.729 0.738 0.523 0.747 0.692 0.747 0.787 0.666 0.785 0.746 0.661 0.720 0.784

Criterion 0.650 0.535 0.569 0.558 0.553 0.307 0.546 0.570 0.697 0.629 0.536 0.585 0.580 0.440 0.629 0.684 0.771

Factor Analysis

Factor analysis was carried out on the data (after removing Q6) using the principal

components (PCA) method of extraction. The determinant of the correlation matrix was

calculated as 0.0000697, which is more than 0.00001, indicating that the correlation matrix is

suitable for factor analysis. The scree plot is shown in Figure 2, which shows an elbow at

component number 2. This justifies a single general factor, which has an eigenvalue of 8.309.

However, this factor explains only 55.39% of the total variance in the data. The scree plot also

has a less pronounced elbow at component number 4, which justifies three factors. The third

component is associated with an eigenvalue of 0.876, which is higher than 0.7, regarded

generally as the lowest acceptable value. The three-factor solution will also explain 67.55%

of the total variance. Thus SPSS was directed to find a three-factor solution, and to rotate the

vectors using the varimax procedure for interpretability.

Figure 2. Scree plot

Table 6 displays the rotated component matrix produced by SPSS. Factor loadings less

than 0.4 have been suppressed.

Table 6. Rotated component matrix

Integration measures Component 1 2 3

Q1 Share ideas, information, and resources between them.

0.634 0.503

Q2 Conduct joint planning to anticipate and resolve supply chain problems.

0.824

Q3 Spend time developing a mutual understanding of responsibilities.

0.775

Q4 Strive to maintain a good working relationship with each other.

0.579 0.510

Q5 Interact with each other through meetings or phones or emails.

0.508 0.607

Q7 Spend time discussing future customer needs. 0.401 0.619

Q8 Are quite accessible to each other. 0.759

Q9 Share the same vision for the company. 0.629

Q10 Establish joint objectives. 0.542 0.461

Q11 Get along well with each other. 0.746

Q12 Share information regarding own department with other departments.

0.596 0.513

Q13 Consult with each other before making decisions affecting other departments.

0.768

Q14 Work frequently in informal cross-departmental teams.

0.52

Q15 Understand the pressures and concerns of each other. 0.804

Q16 Synchronise their activities with each other. 0.732

Factor 1 loads heavily on Q13 (Consult with each other before making decisions affecting

other departments), Q15 (Understand the pressures and concerns of each other), and Q16

(Synchronise their activities with each other). This factor seems to capture the coordination

dimension of internal supply chain integration. Factor 2 loads heavily on Q1 (Share ideas,

information, and resources between them), Q2 (Conduct joint planning to anticipate and

resolve supply chain problems), and Q3 (Spend time developing a mutual understanding of

responsibilities). This factor seems to capture the communication dimension of internal

supply chain integration. The third factor loads heavily on Q8 (Are quite accessible to each

other), Q9 (Share the same vision for the company), and Q11 (Get along well with each

other). This factor appears to capture the affective relationship dimension of internal supply

chain integration.

Reliability

Sample size.

Sample size is an important factor in the reliability of factor analysis. A ratio of 10-15 cases

per variable is commonly suggested. With 16 items in our questionnaire, the number of cases

should be 160-240. This criterion is comfortably met by our sample size of 273. Another

measure of sampling adequacy is the Kaiser-Meyer-Olkin (KMO) statistic, which is

calculated by SPSS. The KMO statistics for our data is 0.949. This confirms that the data is

highly suitable for factor analysis. Still other measures for sampling adequacy are the

diagonal elements of the anti-image correlation matrix, which should be at least 0.5 for a

satisfactory factor analysis. The lowest diagonal element in the SPSS results is 0.922,

ensuring sampling adequacy.

Correlation matrix

Individual item-total and item – criterion correlations were checked as mentioned earlier to

ensure that the items belonged to the same construct. One item (Q6) was excluded on this

account. Another measure to ensure that the items are not independent, is the Barlett’s test of

sphericity, whose null hypothesis is that the correlation matrix is an identity matrix (no

correlation at all). SPSS results show that the set of our remaining variables pass Barlett’s test

at p < 0.001.

Degree of fit

The degree of fit of the hypothesised 3-factor model to the data can be assessed by the

reproduced correlations matrix. For a perfect fit, this matrix should be identical to the original

correlation matrix of the variables. The ideal value of the diagonal elements (the

communalities) is 1. With the exception of variable Q14, which has a communality of 0.449,

all of our variables have a communality of more than 0.6, the average communality being

0.676. This indicates a satisfactory fit. A good fit is also indicated when the residual

correlations (difference between the original correlations and the reproduced correlations) are

small. A commonly used criterion is to have less than 50% of the residuals less than 0.05 in

absolute value. SPSS output shows that for our three-factor solution, 68% of residuals have an

absolute value of less than 0.05.

Scale reliability

A common measure for testing whether the different items of the scale measure the same

construct is the Cronbach’s alpha. This measure for our scale of remaining 15 items and for

the three factors is given in Table 7 below.

Table 7. Cronbach’s alpha statistic

Scale Cronbach’s alpha 15 – item scale 0.940 Communications factor 0.900 Coordination factor 0.895 Affective relationship factor

0.858

All of these statistics are above the acceptable range of 0.7-0.8, indicating high scale

reliability.

Test-retest reliability

Test – retest reliability can only be ultimately tested by carrying out the data collection

exercise again. A split sample factor analysis can give an indication of the test-retest

reliability of factor analysis. Our survey respondents were asked whether company’s

production is mainly based on make-to-order or make-to-stock policies. There were 143

responses indicating mainly make-to-order production; 91 respondents indicated mainly

make-to-stock production (many respondents wrote “both”; some responses were missing).

We extracted three-factor models for both of these sub-samples. Table 8 shows the factor

loadings obtained, comparing the subsamples against the entire sample.

Table 8. Split sample factor analysis

Variable Coordination Communication Affective relationship

Entire sample

Make to order

Make to stock

Entire sample

Make to order

Make to stock

Entire sample

Make to order

Make to stock

Q1 0.535 0.634 0.614 0.582 0.503 0.566 Q2 0.824 0.793 0.799 Q3 0.449 0.775 0.777 0.757 Q4 0.579 0.527 0.679 0.510 0.526 0.422

Q5 0.508 0.470 0.577 0.607 0.594 0.552 Q7 0.401 0.581 0.619 0.785 0.406 Q8 0.410 0.759 0.825 0.534 Q9 0.431 0.629 0.637 0.560 Q10 0.542 0.646 0.461 0.686 Q11 0.746 0.699 0.831 Q12 0.596 0.464 0.667 0.513 0.641 0.406 Q13 0.768 0.712 0.810 Q14 0.520 0.517 0.460 0.487 Q15 0.804 0.850 0.746 Q16 0.732 0.679 0.843

Table 8 shows that the same three factors are obtained, even though factor loadings are a

bit different, particularly for those variables that load on more than one factor. The variables

in the core of the coordination dimension are Q13, Q15, and Q16. Similarly high loadings for

communication are on Q2 and Q3. High loadings for affective relationship are on Q8 and

Q11. It should be stated here that although the measures of sampling adequacy mentioned

earlier were satisfactory for both the subsamples, the sizes of the split samples are small,

particularly for the “make to stock” group.

Predictive validity

Even though as discussed above, each of the factors appear to measure a different dimension,

and the entire scale measures a common construct, this does not confirm that they measure

what one would understand as internal supply chain integration. We had included a criterion

question in our survey instrument (Q 17: Work together for the benefit of the company) to test

this. This criterion, in our opinion, is a summary measure for the latent variable of internal

supply chain integration. The correlation of the criterion with the item totals in the factors and

the entire scale is given in Table 9 below.

Table 9. Correlations of item totals with the criterion

Scale Correlation Coordination dimension 0.736 Communication dimension 0.712 Affective relationship dimension 0.750 Internal supply chain integration 0.778

All of the correlations are high. The correlations are all significant at the p = 0.01 level

(two tailed test). These correlations give us a great deal of confidence that the scales measure

dimensions of internal supply chain integration.

6. Discussion and conclusion

In this research our goal was to develop a parsimonious instrument for the measurement of

internal supply chain integration. Scale items were identified from relevant current research

literature. The number of items was greatly reduced through our scale refinement process; the

final 15 item instrument appears to capture the essence of integration – working together for

the benefit of the company. We offer this instrument as a measurement tool for integration – it

is parsimonious, it appears to capture the domain of the concept and to pass tests of reliability

and validity. To the best of our knowledge there has been no instrument so far which was

tested for predictive validity, thus assuring the instrument’s alignment with the definition of

integration.

Factor analysis indicates that the integration construct has three dimensions – coordination,

communication, and affective relationship. Many previous authors have focused on the first

two dimensions; in fact communication is the sole construct used by a large number of

authors. The communication dimension subsumes the common concept of information

exchange, consultation, and interaction as presented by many authors. Similarly the

coordination dimension covers the concepts of cooperation and synchronisation, The finding

of the affective relationship dimension is a bit of surprise in this research. The core items for

this factor are Q8 (Are quite accessible to each other), Q9 (Share the same vision for the

company), and Q11 (Get along well with each other), which clearly emphasises the affective

aspect of integration. Calantone et al. (2002) have presented a relationship construct, but they

see this construct as separate from the integration construct. Ellinger et al. (2000) envisage

integration having the components of collaboration, consultation, and information exchange.

Relationship is seen as a consequence of integration. Kahn & Mentzer (1998) and others have

posited that integration consist of two dimensions (communication or interaction, and

collaboration). This collaboration concept has some aspects of affective relationship

embedded in it. However, affective relationship as a separate factor of integration concept is

something new brought out by this research. It is hard to imagine supply chain functions

within a company working together to the highest extent without harmonious relationship

within these functions. Thus this dimension of integration is worthy of further studies.

We hope we have made a contribution here towards building a consensus among practitioners

and researchers in defining and measuring internal supply chain integration. For practitioners,

our measurement instrument offers a self-assessment tool for internal supply chain

integration.

Future work prompted by this research are: a confirmatory research on the instrument

presented here and on the dimensions of integration, further exploration of the domain of the

affective relationship dimension in integration, and an exploration of how the concept of

integration changes with its context.

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