ISLI 2003 - Semantic Scholar

Knowledge Management Practices in the Context of Supply Chain Integration: The Canadian Experience Alain Halley Associate Professor, HEC Montréal [email protected]

Martin Beaulieu Research Professional, CHAINE Research Group, HEC Montréal [email protected]

Knowledge can be a strategic resource for any organization. Today, it is considered the cornerstone for the development of core competencies that will generate competitive advantages. This knowledge is not found exclusively within organizations, but may be shared through business relationships developed within the supply chain through the interconnection of value-added activities among business partners. This article seeks to study the relationship between supply chain and knowledge management practices. The results of a study of 163 Quebec (Canada) manufacturing companies (almost 90% of which are small- and medium- sized enterprises) confirmed our hypothesis that the deployment of integrated supply chain management practices with both upstream and downstream partners is associated with more effective knowledge management processes. Although this relationship is not linear, a more comprehensive, integrated vision of the supply chain–both upstream and downstream–leads to an awareness of the value of the knowledge exchanged. This awareness also results in the implementation of measures to protect knowledge deemed to be strategic.

In an environment characterized by multiple upheavals, companies must rely on their knowledge and not their products to remain competitive (Hamel, 2001). Moreover, this knowledge may be found outside the company (Dyer and Singh, 1998; Zack, 2003). It may therefore be shared through business relationships developed within the supply chain (Gold et al., 2001; Mak and Ramaprasad, 2003). This situation raises various management challenges and highlights the need to rely on judicious business relationships to maintain the competitiveness of the company and, at the same time, to carry out a thorough analysis of the knowledge exchanged to prevent its devaluation. To date, studies of knowledge management have often maintained an intra-organizational perspective. Moreover, studies seeking to

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understand the processes of knowledge management within an inter-organizational context have focused mainly on very precise relational contexts, such as that of the strategic alliance, where one finds a high level of inter-firm cooperation. In daily life, the supply chain represents diverse levels of integration, opening new prospects for expanding the rather limited existing research results (Frohlich and Westbrook, 2001). With this in mind, a research program financed by the FQRSC (Fonds québécois de la recherche sur la société et la culture) was set up to study knowledge management within the specific context of supply chain management. To achieve these research goals, a questionnaire was developed and administered to 2,000 manufacturing companies in the province of Quebec (Canada).

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This article presents the initial results of this data collection. More specifically, the research objective was to study the relationship between supply chain management practices and the knowledge management processes deployed by respondents.

Literature Review This section will first review the various study-related concepts leading to the development of the research model. These include resource-based view, organizational learning, knowledge management, and supply chain management. Resource-based view and knowledge Resource-based view is a research trend stipulating that organizations develop core competencies that will give them a competitive advantage (Sanchez and Heene, 1997). These competencies are based on a combination of various resources. Theoretical developments tend to show that these resources take the form of more-or-less structured knowledge (Sanchez, 1997). On the one hand, structured or explicit knowledge takes the form of tangible assets, such as plant and information systems and equipment. Tacit knowledge, on the other hand, includes employee know-how, reputation, and culture (Spekman et al., 2002) and is often based on human expertise. Figure 1 illustrates the link between the resources and knowledge underlying the development of competencies, including the distinctive competencies directly contributing to the development and maintenance of a competitive advantage.

During the 1980s, this theory was the subject of a vast amount of literature (Huber, 1991). Despite this abundance of literature, there is still confusion, particularly regarding the terms learning organization, organizational learning, and knowledge management (Loermans, 2002; Ortenblad, 2001). The term learning organization refers to a type of organization that has deliberately implemented a series of learning processes (Ortenblad, 2001). The concept of organizational learning includes both individual and collective learning processes (Ortenblad, 2001; Wang and Ahmed, 2003). In recent years, these concepts seem to have been eclipsed by that of knowledge management, which adopts a more operational perspective based on tools and systems (Newell et al., 2001). Loermans (2002) defines the concept of knowledge management as a set of practices for creating, acquiring, capturing, sharing, and using knowledge. However, before being able to exploit knowledge fully, there are intermediate steps to master, because knowledge is a complex blend of data and information (Bohn, 1994). Knowledge management and the supply chain Knowledge is not necessarily specific to an organization; it may be located outside the company (Dyer and Singh, 1998; Spekman et

al., 2002; Wang and Ahmed, 2003) or exchanged through relationships developed within the supply chain (Gold et al., 2001; Mak and Ramaprasad, 2003). Indeed, the sharing of data, information, and knowledge among members of a supply chain is critical to its success (Romano, 2003). Overall, the successful integration of a supply chain requires the careful linking of internal processes with external suppliers and customers (Frohlich and Westbrook, 2001); this is why it becomes necessary to speak about coordination mechanisms. These mechanisms may take various forms: electronic linkages, personnel flows, use of common systems (e.g., CAD) or reports, manuals, project teams, and written or oral channels of communication (Chai et al., 2003; Halley, 1999; Halley and Beaulieu, 2001). Research synthesis Various studies—some exclusively theoretical—integrate the concepts of knowledge management (organizational learning), competence development, and supply chain management (Arlbjorn and Halldorsson, 2002; Dyer and Singh, 1998; Olavarrieta and Ellinger, 1997; Simatupang et al., 2002). In this regard, Morash et al. (1996) identify a significant relationship between logistical competencies and a firm’s performance, but they offer little information about the

Figure 1

Resource-based View Framework

Organizational learning and knowledge management As the organization thus becomes a warehouse of knowledge, it is natural to associate this concept with that of organizational learning, which seeks to employ various management practices to realize the full potential of this knowledge (Helleloid and Simonin, 1994).

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resources needed to develop such competencies. From an inter-organizational perspective, knowledge management (or organizational learning) has given rise to studies of specific cases involving very close cooperation between two organizations: strategic alliances or technological cooperation (Anand and Khanna, 2000; Combs and Ketchen, 1999; Khanna et al., 1998; Simonin, 1997; Tidd and Izumimoto, 2002). These studies mainly target a single type of relationship whereas supply chain management involves various levels of coordination among network stakeholders (Spekman et al., 1998). The study by Tatikonda and Stock (2002) integrates the concepts of knowledge and the supply chain in the case of technology transfer. This context seems too restrictive, however, because according to Zack (2003), knowledge management should not be limited to technological perspectives. Burkink (2002) deals with knowledge management in the distribution network, which occurs only in the downstream portion of the supply chain. More recently, Belzowski et al. (2003) studied knowledge management, but only in the automobile industry. The results of this study indicate that respondents recognize the importance of sharing knowledge but that the means to do so are not always deployed on a large scale.

Research Model With this in mind, a research model linking four major variables has been developed (figure 2). In this article, particular attention will be paid to the relationship between supply chain management practices and knowledge management practices. This research program postulates that the integration of the supply chain, which facilitates greater mastery of core competencies, is based on knowledge management practices (the diversity of knowledge exchanged, the frequency of exchanges, and the more intensive use of various exchange mechanisms). Because this study is concerned with exchanges among parties in the supply chain, it will look specifically at practices related to the acquisition, capture, and sharing of knowledge. As noted by Spekman et al. (2002), overly close relationships between business partners may result in the expropriation of trade secrets. The deployment of measures to protect knowledge of strategic importance should also be a component of knowledge management. Finally, supply chain management practices will be defined according to the degree of connection of the

respondents’ value-added activities with their suppliers and customers (Frohlich and Westrook, 2001). Within the framework of this article, we will test the following hypotheses: H1: Integrated supply chain management practices are associated with effective knowledge management processes. H1.1: Integrated supply chain management practices are associated with greater diversity of knowledge exchanged. H1.2: Integrated supply chain management practices are associated with higher frequency of exchanges between partners. H1.3: Integrated supply chain management practices are associated with greater diversity of knowledge exchange mechanisms. H1.4: Integrated supply chain management practices are associated with the deployment of a greater number of knowledge protection measures.

Data Collection and Respondent Profile Based on the research model, a questionnaire was developed covering all the dimensions of this study. Table 1 presents the four parts of the questionnaire as well as the works that inspired the

Figure 2

Research Model

This study thus reconciles two basic elements affecting the competitiveness of organizations: knowledge management and supply chain management. An analysis of the literature reveals that the number of studies establishing links between these two concepts is limited and they address the question from only a limited perspective. By integrating these two concepts, new perspectives on supply chain management open up because their integration is not restricted to linking the flow of information with the flow of material; it also includes the overlapping of knowledge by the business partners (Spekman et al., 2002).

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Table 1

Major Parameters of the Questionnaire

questions and indicators. Readers may note that the contents of Part II will not be discussed in this article. Appendix 1 shows the study variables of the questionnaire that will be analyzed here. The questionnaire was pretested with four respondents. These respondents work for large industrial companies (electronics, pharmaceuticals, aerospace, and transport) and are experienced in questionnaire design. They made a few suggestions on how to clarify questions and the wording of answers and suggested additional responses. The questionnaire was then administered to 2,000 manufacturing companies (mainly secondary and tertiary processing) with more than 20 employees that were located in the province of Quebec (Canada). This sample choice enabled us to collect data from companies of different sizes–a not-insignificant consideration given that studies by Halley and Guilhon (1997) and Arend and Wisner (2005) reveal that major corporations adopt different logistical behaviours with small- and medium-sized businesses. In addition, ignoring small- and medium-sized businesses in logistical studies is less and less appropriate because these companies are an important vector of economic growth in many countries (Julien, 1993) as well as being key players in the logistic chains of major contract givers in various sectors of activity (e.g., automotive, aerospace, and apparel).

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The questionnaires were mailed out along with self-addressed, stamped return envelopes. An initial mailing was carried out in mid-April 2003 with a follow-up mailing four weeks later. In all, 41 questionnaires did not reach their addresses, leaving us with a total population of 1,959 respondents; 163 completed questionnaires were returned to us, for a participation rate of 8.3%. The length of the questionnaire as well as the fact that it was sent mainly to small- and medium-sized businesses may explain this low response rate. Indeed, Dennis (2003) and Greer et al. (2000) postulate that small- and medium-sized businesses are less willing to complete questionnaires. Non-response bias is always a threat to survey. One common test for non-response bias is to compare the date of early and late respondents. Comparisons were made between pairs of respondents of various sizes: the first 30 respondents with the last 30, the first 40 with the last 40, the first 50 with the last 50, the first 60 with the last 60, and, finally, the first half of the sample with the last half. This division was based on the assumption that the final respondents tend to have a similar behaviour to that of the nonrespondents. An analysis of variance (ANOVA) was carried out to compare the averages of the level of supply chain integration. With the exception of a single comparison, the behaviours within the studied pairs were similar. The only difference observed may be attributed to the very different

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behaviour of a single respondent among the first 30 to 40 respondents. This sample seems statistically representative of this population. This test was employed previously by Zsidisin and Ellram (2003).

Data Analysis Respondents represent various sectors of activity, including the following five in particular: metal manufacturing (25.8%), wood and furniture (16.0%), electric and electronic (10.4%), food and beverage (8.6%), and printing (7.4%). Almost 63% of respondents reported sales ranging between $2 and $20 million and 70% of those employ between 20 and 99 employees (44.8% between 20 and 49 employees and 25.2% between 50 and 99 employees). The collected data was entered into an Excel spreadsheet. This database was then transferred to the SPSS program and run through a univariate analysis of all dimensions of the study, a factorial analysis (AFC), an analysis of reliability, and a directed classification. The initial analyses aimed to assess the explanatory nature of the variables and their degree of overlapping. The directed classification focused on part IV of the questionnaire, which aims to classify the relational practices in the upstream and downstream supply chain of the companies in this population sample. For the purposes of this classification, questions 4.1 and 4.2 were used. These questions measure the


Table 2

Results of the Reliability Test

Results above 0.6000 are reliable, with the closer the score to 1.0000, the higher the degree of reliability (Cohen et al., 2003).

deployment of supply chain management practices upstream and downstream (question 4.1 includes 13 statements and question 4.2 includes 14 statements). The correlation analysis reveals that there is no colinearity or redundancy between these statements. In order to form these various clusters, composite indexes for each of the two questions were created. The Cronbach Alpha for the 13 statements in question 4.1 was 0.6851 and 0.7655 for the 14 statements in question 4.2. A Cronbach Alpha greater than 0.6000 generally indicates a reliable construct. In fact, the closer the result is to 1.000, the greater the reliability (Cohen et al, 2003). The

results consistently meet this criterion. The reliability test (Cronbach Alpha) confirmed the strength of the chosen scale (Table 2). Based on these two analyses, two composite indexes integrating all the statements in question 4.1 (customers) and then all the statements in question 4.2 (suppliers) were formulated. This directed classification gave us four clusters of respondents. To confirm this result, an undirected classification using SAS software was carried out. This software was used because it allows the construction of an algorithm that determines the optimal number of clusters, whereas a version of the SPSS

Figure 3

Positioning of the Four Clusters in the Undirected Classification

software was required to first determine this number. The SAS system also identified four clusters. According to Hansen and Jaumard (1997), the basis of a cluster analysis exercise is to obtain subsets that are internally homogeneous and clearly separated from one another. Figure 2 presents a diagram created by the SAS software that displays the results of the undirected classification. The circumference of the circles shows that the respondents composing these clusters are relatively homogeneous and the distance between the circles confirms that the clusters are distinct from each other. Based on this classification, a statistical analysis using a paired t-test was carried out to determine whether the various clusters of respondents adopted different behaviours with regard to the exchange of knowledge with the various stakeholders in their supply chain. Table 3 presents some general characteristics of each of these groups.

Presentation of Results Tables 4 and 5 present the principal supply chain management practices deployed by each cluster to manage relationships with suppliers and customers. These tables summarize the behaviour of each cluster. The analysis of these results leads us to define the first cluster, composed of 20 companies, as balanced integrated. These companies assume full responsibility for the design and

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Table 3

General Characteristics of the Clusters (Average)

i 1 = 0 to $499,999; 2 = $500,000 to $1,999,999; 3 =$2,000,000 to 19,999,999; 4 = $20,000,000 to $49,999,999; 5 = $50,000,000 and up ii 1 = 20-49, 2 = 50-99, 3 = 100-199, 4 = 200-499, 5 = 500-999, 6 = 1,000 and up iii 1 = 0-49, 2 = 50-99, 3 = 100-199, 4 = 200-499, 5 = 500-999, 6 = 1,000 and up

Table 4

Predominant Supply Chain Management Practices with Suppliers by Cluster of Respondents

Table 5

Predominant Supply Chain Management Practices with Clients by Cluster of Respondents

assembly activities of a larger number of customers than do the three other clusters. These 20 companies also entrust more responsibility for design and assembly to a significant number of suppliers. The supply chain of these respondents is thus characterized by a great overlap of responsibilities with many stakeholders both upstream and downstream. At the same time, a form of mistrust is established with the suppliers, because the companies in this cluster regard the majority of their suppliers as potential competitors. This mistrust is confirmed by the development of practices aimed at decreasing their dependence on

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their suppliers, shown, example, by the search alternative sources of supply.

for for

The second cluster, which includes 49 respondents, is called the upstream integrated cluster. The companies in this cluster adopt an overall unbalanced behaviour in that the integration of their supply chain seems more complete with their suppliers than with their customers. The companies in this group carry out design and assembly activities for their customers but to a lesser extent than those in cluster 1. In addition, these companies entrust a majority of their suppliers with design activities for their products, but to

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a lesser extent than cluster 1. With these suppliers, the respondents adopt a more defensive attitude than those in cluster 1 and the relationship is usually limited to the terms of the contract. The companies in this cluster also consider many suppliers as potential competitors, leading them to seek alternative supply sources, as do their counterparts in cluster 1. The third, or downstream integrated cluster, is composed of 42 companies. These firms also have an unbalanced strategy, because responsibilities are more integrated with their customers than with their suppliers. These


Table 6

Average of the Four Clusters for the Knowledge Management Practices

Table 7

Information Most Often Exchanged with Business Partners

Scale from 1 to 5: 1 = none of your suppliers (or clients) to 5 = all of your suppliers (or clients)

respondents carry out design and assembly activities for their customers (to a lesser extent than do companies in cluster 1). In terms of their relationships with suppliers, they adopt a behaviour similar to that of cluster 2. Relying both on the sharing of responsibilities for design and on relationships limited to the clauses in their contracts, these companies

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constantly seek to diversify their supplier base. They are distinguished, however, from clusters 1 and 2 by a greater sharing of opinions and advice with their customers. For example, they do not hesitate to ask the opinions of their customers or to establish shared objectives with their suppliers for the development of new products.

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The final cluster of firms, called the defensive integrated cluster, consists of 52 companies. These companies adopt the most distant overall attitude with both their suppliers and their customers. These respondents entrust their suppliers with assembly activities and accept their suggestions, at the same time freely exchanging opinions and advice. They


Table 8

The Information Exchanged Most Frequently

Scale from 0 to 6: 0 = never, 1 = once a year, 2 = once a quarter, 3 = once a month, 4 = once a week, 5 = once a day, and 6 = in real time

nevertheless maintain a defensive attitude with their suppliers and ensure their relationships with them are limited to the terms of their contract. They also seek to diversify their sources of supply. These analyses show no significant variation with regard to the average number of employees, sales figures, number of customers, or number of suppliers. The implementation of a consistent supply chain management policy is thus related to a company’s orientation and not to a natural evolution in the historical development of a firm. This classification sought to determine if the four clusters adopted different knowledge management practices. This concept encompasses four major dimensions: exchange mechanisms used, the frequency of exchanges, diversity of knowledge exchanged, and protective measures. For each of these dimensions, composite indexes were created, composed of the average of the answers for each statement characterizing a dimension (each statement is presented in Appendix 1). Table 6 presents the averages obtained by each cluster of respondents for each block of answers. The first observable result is a decline in the averages from cluster 1 to cluster 4 for many statements in this table. Based on these results, many readers could question the real difference among the behaviours for each of these four clusters. To confirm that these differences are in fact significant, a paired t-test was carried out, comparing the averages for the various respondent clusters.

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Appendix 2 provides a synthesis of these results. It confirms that cluster 1 has a behaviour that is statistically different from that of the three other clusters for every dimension of knowledge management. These results were also clarified by further analysis. For example, with regard to information-exchange mechanisms deployed with suppliers and customers, the four clusters favour four measures: frequent telephone contact, joint work teams, in-house staff devoted to follow-up, and electronic data exchange. Overall, these measures are deployed with a greater number of clients (Table 7). Production planning, delivery schedules, quality tests, delivery routes, and technical drawings are the information most frequently exchanged by the four clusters, and this information is exchanged a little more frequently than once a month (Table 8). This information may be considered explicit knowledge because it requires no specific skills to be processed. In addition, this information is related to a more operational perspective (results of quality tests, delivery routes, and schedules). This confirms the prior observation regarding a certain generalization of more distant supply chain management practices (see Tables 4 and 5). Moreover, these similarities hide a deep discrepancy with regard to frequency. For example, in the case of production planning, cluster 1 respondents exchange information more than once a day whereas the three other clusters may exchange it just a few times a month.

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Discussion The model (Figure 2) sought to study the relationship between supply chain management practices and the various aspects of knowledge management. The primary hypothesis of this study was that expanded supply chain management practices are associated with more effective knowledge management practices. These subhypotheses referred to the aspects of knowledge management studied within the supply chain (diversity of knowledge exchanged, frequency of knowledge exchanged, exchange mechanisms used, and protective measures implemented). These results (Table 6) demonstrate that companies in Cluster 1, those that adopt integrated supply chain management practices, are the ones making the most intensive and wide-scale use of the various knowledge management practices. Similarly, Cluster 4 includes companies that adopt the most distant supply chain management practices and are least likely to employ knowledge management practices. The hypotheses in this research were confirmed because the knowledge management practices that contribute directly to the greater integration of the supply chain specifically involve the acquisition, capture, sharing, and protection of knowledge. Figure 4 synthesizes these observations. The supply chain management axis of the graph indicates the degree of connection between the value-added activities of the various partners. The knowledge management axis,


noted by Dyer and Singh (1998) as well as Simonin (1997), the sharing of knowledge should result in learning that improves the organization’s performance. At this stage of research, the internal processes learning how the shared knowledge is developed have not yet been studied. Additional studies in this area will therefore be necessary.

Figure 4

Supply Chain and Knowledge Management

inspired by the work of Bohn (1994), indicates the scope and effectiveness of knowledge management. Bohn (1994) affirms that there are eight stages to mastering production activities, beginning with complete ignorance about the functioning of processes and their effects and ending with full understanding, when all problems can be anticipated and prevented. Naturally, there are intermediary stages, including awareness and process characterization. An adaptation of this scale gives us two extremes: the ignorance stage, when there is no deliberate attempt to manage knowledge, and the stage of complete knowledge, when the company is aware of the value of knowledge and its effects. In other words, distant, isolated supply chain management practices result in the limited sharing of knowledge, including low-frequency, personalized communication mechanisms or explicit knowledge exchanges. At the other end of the scale, greater integration of the supply chain results in increased understanding of activities and the effects of knowledge management practices. This figure is consistent with the results of this study, which show a

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close relationship between the degree of integration of the supply chain and knowledge management practices. This relationship is not linear, however. Cluster 4, the defensive integrated group, includes companies that deploy the most distant supply chain management practices and also the least comprehensive knowledge management practices. Moreover, companies in the downstream and upstream integrated groups have more extensive supply chain management practices but not significantly different knowledge management activities. These three groups of companies have surpassed the stage of ignorance because they have implemented more structured knowledge-sharing activities supporting more detailed and more frequent exchanges. Although this article was not prepared to affirm that the balanced integrated group has reached the stage of complete knowledge, this group’s implementation of knowledge protection measures reveals that these respondents are aware of the value of knowledge. However, some readers might question whether these companies exploit the full potential of that knowledge. As

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Despite this observation, these results indicate that there is a supply chain integration threshold resulting in a different approach to knowledge management between partners. This threshold is characterized by the greater integration of value-added activities with both clients and suppliers. Moreover, this study has not targeted a specific form of structure characterizing supply chain integration. The studies of Simonin (1997) and Anand and Khanna (2000) characterize these integration thresholds in the form of formal alliances between partners, and this research recommends the greater integration of activities and processes throughout the length of the supply chain.

Conclusion The relevance of this study relates to the fact that very little of the work previously done on knowledge management has adopted an inter-organizational perspective (Parise and Henderson, 2001). In addition, similar studies on the subject have addressed only a single type of business relationship, whereas the reality of the supply chain is more complex because it integrates a diversity of relationships, some of which are more unstable (Nissen, 2001) than those of a strategic alliance. Moreover, the existing empirical studies on the subject have often targeted a single sector of activity, whereas this study includes manufacturing organizations in different sectors of activity and in both the upstream and downstream segments of the supply chain. This study also includes companies of various sizes, allowing us to collect data


about knowledge management from smalland mediumsized enterprises, segments often neglected in studies of organizational learning and knowledge management (Chaston et al., 2001). The most significant result of this study is the idea that the integration of the supply chain seems to proceed by levels. Companies that have reached the level of overlapping value-added activities with a significant number of customers and suppliers also share more knowledge. The fact that this sharing occurs both upstream and downstream in the supply chain appears to be significant. Greater overlapping of value-added activities both upstream and downstream results in greater awareness of the value of the knowledge exchanged and the development of adapted processes that contribute to its further development. In addition, this integration is not incompatible with a more distant attitude with certain partners in the supply chain. Indeed, the highly integrated first cluster deploys different strategies that aim to preserve its power relationship: the search for alternative sources of supply and internal knowledge-protection measures.

relationship affect the management of knowledge within a supply chain? What is the impact of the integration of the supply chain on the development of organizational competencies? In the medium term, this research program will extend its investigation to other regions of Canada as well as to other countries (the United States and France) once this project has received a research grant. An international perspective could offer new comparisons by highlighting sectors of activity or the national origin of companies as factors explaining the behaviour of companies with regard to managing the supply chain.

Arend, Richard J., and Joel D. Wisner. (2005). “Small Business and Supply Chain Management: Is There a Fit?” Journal of Business Venturing, 20(3), 403436. Arlbjorn, Jan Stendoft, and Arni Halldorsson. (2002). “Logistics Knowledge Creation: Reflections on Content, Context and Processes.” International Journal of Physical Distribution & Logistics Management, 32(1), 22-40.

Bidault, Francis, Charles Despres, and Christina Butler. (1998). “New Product Development and Early Supplier Involvement (ESI): The Drivers of ESI Adoption.” International Journal of Technology Management, 15(1-2), 49-69. Bohn, Roger E. (1994). “Measuring and Managing Technological Knowledge.” Sloan Management Review, 36(1), 61-73. Burkink, Tim. (2002). “Cooperative and Voluntary Wholesale Groups: Channel Coordination and Interfirm Knowledge Transfer.” Supply Chain Management, 7(2), 60-70. Chai, Kah-Hin, Mike Gregory, and Yongjiang Shi. (2003). “Bridging Islands of Knowledge: A Framework of Knowledge-Sharing Mechanisms.” International Journal of Technology Management, 25(8), 706-731. Chaston, Ian, Beryl Badger, and Eugene Sadler-Smith. (2001). “Organizational Learning: An Empirical Assessment of Process in Small U.K. Manufacturing Firms.” Journal of Small Business Management, 39(2), 139-151.

Although the results of this research are still factual, the completion of the portrait is pursuing two objectives. In the short term, this research program naturally plans to finish processing the data, enabling us to integrate two other variables into the model: the power relationship and the distinctive competencies mastered. These analyses could suggest answers to questions such as the following: How does a power


Anand, Bharat N., and Tarun Khanna. (2000). “Do Firms Learn to Create Value? The Case of Alliances.” Strategic Management Journal, 21(3), 295-315.

Belzowski, Bruce M., Michael S. Flynn, Barbara C. Richardson, and Maitreya Kathleen Sims. (2003). “Harnessing Knowledge: The Next Challenge to Interfirm Cooperation in the North American Auto Industry.” International Journal of Automotive Technology and Management, 3(1/2), 9-29.

This study has limits, however: the size of its sample as well as the lack of a precise analysis of nonrespondents, the fact that the sample is composed only of companies in the province of Quebec, and certain conceptual choices related to the definition of the supply chain all limit the potential for generalization.

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About the authors Alain Halley is associate professor of Purchasing, Logistics, and Operations Management in the Department of Production and Operations Management at HEC Montréal. He has published in numerous logistics and operations journals and conference proceedings. He has also published in journals such as the International Journal of Physical Distribution & Logistics Management and The Journal of Supply Chain Management. His research interests include outsourcing and networking, supply chain integration and competencies, e-commerce, and transportation. Martin Beaulieu is a research professional and former member of the CHAINE Research Group at HEC Montréal. His research interests lie in the field of healthcare logistics, supply chain management, reverse logistics, and operational strategy. He has published in journals such as the International Journal of Operations & Production Management, Supply Chain Management: An International Journal, and the Journal of Purchasing and Supply Management.

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Appendix 1 Part III—Communication and the Exchange of Information with Your Partners

3.1 Specify the frequency with which the following information is exchanged with your suppliers and clients (both when you receive this information from your partners and when you share data concerning your company with them). For each statement, circle the number that corresponds most closely to the situation in your company.

3.2 Specify with which players (clients or suppliers) you share or receive the following information. For each statement, circle the number that corresponds most closely to the situation in your company.

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3.3 The following statements refer to the communication and exchange mechanisms used to share information with your business partners. For each statement, circle the number that corresponds most closely to the situation in your company.

3.4 The following statements refer to measures designed to protect information deemed to be strategic by your company. For each statement, circle the number that corresponds most closely to the situation in your company.

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Part IV—Questionnaire on the Nature of Relationships within the Supply Chain

4.1 For each of the following statements, circle the number corresponding most closely to the frequency of use of the following logistics practices with your company’s customers.

4.2 For each of the following statements, circle the number corresponding most closely to the frequency of use of the following logistics practices with your company’s suppliers.

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Appendix 2 RESULTS OF PAIRED T-TEST

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