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common for retailers and wholesalers to be given slotting and stocking ... Innovative firms have sought more efficient ways to satisfy business requirements.8 ... enhancements in the profitability, market share, and customer service levels.14 .... Annual corporation sales per respondent ranged from $2 million to $8 billion with.


Abstract Results of a recent survey of logistics managers of firms associated with food processing and manufacturing are reported. Based upon the managers’ perceptions regarding the implementation of interfirm coordination processes such as communications, information technology, partnering, and performance monitoring, the research finds that firms demonstrating higher levels of these processes experienced improvements in critical logistics performance areas.

About the Authors: Theodore P. Stank is Assistant Professor of Logistics and Supply Chain Management at Michigan State University. He received his Ph.D. in Marketing and Distribution at The University of Georgia. Michael R. Crum is Professor of Transportation and Logistics at Iowa State University. He received his DBA in Transportation Management at Indiana University. Miren Arango is Senior Forecast Analyst at Tone’s. She received her MBA at Iowa State University.


BENEFITS OF INTERFIRM COORDINATION IN FOOD INDUSTRY SUPPLY CHAINS INTRODUCTION Six years after the Kurt, Salmon, and Associates1 report exposed the waste associated with traditional grocery supply chain operations and introduced the benefits associated with the principles of Efficient Consumer Response (ECR), demonstrable instances of true coordination among vendors, channel intermediaries, and retailers are few and far between. Recent reports suggest that traditional supply processes, characterized by forward deployment of large inventory stockpiles dictated by anticipatory forecasts of consumer demand, have actually increased since 1992.2 Mounting evidence from academic researchers and business practitioners, however, supports the contentions of the benefits of the integrated supply chain management processes extolled in ECR. Supply chain management extends a firm’s capabilities by coordinating operations to encompass source, make, and delivery processes in collaboration with channel partners and suppliers. Coordination of sourcing, production, and logistical activities coupled with interfirm cooperation engendered in a supply chain perspective shifts channel arrangements from loosely linked groups of businesses to coordinated enterprises focused on efficiency improvement and increased competitiveness through lead-time reduction.3 The new organization is capable of rapidly responding to market by eliminating redundant activities and reducing response time through seamless flows of information, supply materials, and finished goods. Coordinated operations enable higher levels of service provision and reduced overall cost, two goals that are mutually exclusive in traditional operating systems. The objective of this research is to investigate the relationship between interfirm supply chain coordination and performance on key logistical elements. The food industry was selected for the study because of its leadership in ECR and other supply chain management initiatives.4


The small contribution margins and perishable nature of many of its products make efficient supply chain management extremely important for food companies. Suppliers of food products were surveyed to determine the extent and nature of coordination with key customers and the suppliers’ performance on logistics cost and customer service.

The results should enable

academicians and practitioners to understand better the performance implications of supply chain processes. In the following sections, interfirm supply chain coordination processes examined in this paper are defined and relevant findings from previous research are reviewed. Research hypotheses are introduced and details are provided regarding the sample, measures, and methodology used. Results are presented, followed by a discussion of the conclusions and implications drawn from the research findings. BACKGROUND AND RESEARCH HYPOTHESES In traditional grocery channel operations, vendors’ sales are fully supported in terms of inventory deployment. Inventory levels are typically based on anticipatory demand forecasts tempered with knowledge concerning promotional campaigns planned to stimulate demand. It is common for retailers and wholesalers to be given slotting and stocking allowances to allocate sufficient warehouse and retail shelf space to carry the forecasted inventory. Retailers are reluctant to change a system in which vendors essentially finance forward-deployed inventory and encourage large inventory stockpiles through promotional activities.5 The appropriate levels of source, make, and deliver activities necessary to support anticipatory supply chain management are extremely difficult to predict. The entire process is driven by forecasts that are based on limited information beyond knowledge regarding sales penetration needed to ensure financial success. While predictive ability can be improved using


multiple market testing methods, such forecasts are subject to market volatility and competitive action.6 Operational effort to support anticipatory management requires significant capacity to buffer forecast variance. Fragmented supply chain operations, particularly in the food industry, are often characterized by forward buying spurred by uncoordinated promotional activity. This leads to increased demand and lead-time variance that raises requirements for anticipatory capacity. The resulting increase in overall cost and reduction in ability to respond to changing market patterns make high service levels and low system cost mutually exclusive goals.7 Innovative firms have sought more efficient ways to satisfy business requirements.8 Closer coordination of activities within and among firms throughout the supply chain creates flexible operating systems characterized by coordinated source, make, and deliver operations that drastically cut raw material to consumer cycle times, enabling the firm to respond to actual market needs rather than anticipate demand with inventory. Coordinated planning and control of marketing and promotions, distribution, manufacturing, and raw materials/sub-component procurement characterize intrafirm integration. Externally, an emphasis on communications, information exchange, partnering, and performance monitoring integrates individual firm processes with source, make, and deliver activities of suppliers and customers.9 The process is presented in Figure 1. Integrated supply chain management has been linked to performance improvement in customer service areas such as order cycle time reductions and increases in ontime delivery of shipments, as well as indicators of cost performance, i.e., decreased expedited shipments of freight and routing and scheduling improvements.10




Internet/Intranet and Conventional EDI U



Supplier Certification and Coordination


Material and Service Supplier Integration

Integrated Internal Operations

Distributive Integration

RELATIONAL CONTEXT Supplier Relationships

Internal Facilitation and Integration




Collaborative Forecasting and Joint Planning



Channel Relationships


INFORMATION FLOW CASH FLOW Adapted from Bowersox, Donald J. “Integrated Supply Chain Management: A Strategic Imperative,” Annual Conference Proceedings of the Council of Logistics Management, 1997: 181-189.

Communications among participating firms provides the glue that holds the supply chain together.11 Managers at successful companies realize that sharing knowledge and exchanging critical information with trading partners can enhance operating performance and support business relationships.12 Ready availability of information positions firms to be able to respond to customer needs and to leverage the information to create significant competitive advantage.13


The complex nature of logistics requires substantial information support. Logistics information support has been credited with producing significant cost reductions and enhancements in the profitability, market share, and customer service levels.14 Information facilitates managing activities both within and outside a firm.15 Internal interactions between functional areas can be coordinated more easily because of information availability. Information availability also yields service enhancements and thus improves external relationships with supply chain.16 Attitudes have changed and freer information exchange is more common today than in the past. Too frequently, however, a reluctance to share proprietary company information still exists. Without adequate communications, supply chain members are forced into a trade-off between effectiveness and efficiency that compromises performance.17 For example, uncertainty typically results in holding excess inventory within the supply chain “just in case.” This can be avoided if cross-firm activities can be more closely coordinated.18 Sharing information such as advance shipment notification, production scheduling, and design requirements enables supply chain members to cope better with a volatile environment.19 Rather than hoarding and releasing information only to solve problems, firms must be willing to share information concerning plans and best practices with their supply chain affiliates to prevent problems and meet or exceed customer.20 Strong information linkages are essential to support inter-organizational communications. While these linkages could take any number of forms, the focus must be placed on providing access to timely, accurate information. Electronic Data Interchange (EDI) is commonly used to achieve such information exchange. When EDI implementation is cost prohibitive or unavailable, the Internet may offer an economically feasible way to exchange information.21 Both EDI and the Internet allow businesses to quantify sales, define requirements, and trigger production and inventory replenishment twenty-four hours a day, seven days a week. Rather than


relying upon sales forecasts, inventory replenishments are driven by precise sales information regarding specific stock items in the market.22 Computer systems and information technology provide data for improving managerial decision-making through effective resource management and organizational alignment. Developing tailored information systems that enable supply chain firms to meet customers’ needs is crucial. This requires determining specifically what types of information must be exchanged, how often, in what format, etc. If performance is truly to be enhanced, the new philosophy of information sharing must impact resource allocations. Adequate resources must be committed to technology and information systems in order to facilitate the actual transfer of information between trading partners.23 Many firms have discovered that heightened coordination and information flow can be achieved by strengthening their relationships with product and service suppliers and customers rather than relying on short-term, single-transaction arrangements or producing the activity inhouse.24 Strengthened supply chain relationships allow firms to maintain greater control over external activities without the investment commitment associated with vertical integration. Additionally, customer value is enhanced through access to external expertise.25 Partnering relationships among supply chain members differ from transactional relationships along several key dimensions. Most importantly, they extend over time and focus on developing trust and cooperative planning between trading partners to enhance future collaboration. Other key aspects of partnering include the level of assistance partners provide each other beyond minimally acceptable levels; the flexibility partners demonstrate in reaction to unforeseen requests; and mutual commitment to improvements that benefit the partnership in general.26 While not all partnerships prove successful, the benefit potential is significant and thus has attracted many firms interested in long-term involvement with supply chain.27 Benefits


generally result from the synergy gained through shared expertise and resources, exchange of information, mutual planning and support, and joint problem solving fostered by win/win, mutually committed trading partners. Such situations have allowed firms to increase the value provided to end-use.28 Failed partnerships often result from commitment imbalances between partners, inaccurate or insufficient communications and information exchange, disagreement on baseline costs used to assess future performance, and confusion regarding specific responsibility for key aspects of exchange.29 Once the infrastructure for enhanced supply chain information and product flow is in place, sophisticated performance measurement systems are required to manage integrated supply chains.30 Performance measurement should monitor both the effectiveness and efficiency of members in accomplishing supply chain goals.31 Good measurement systems also assist continuous process improvement by allowing managers to focus on eliminating the causes of process variations. Performance feedback allows firms to use information to prevent problems or correct them in a timely manner.32 Preferred performance monitoring systems consist of both internal and external performance measures. Internal measures should monitor the costs and service levels of several different specific logistics functional areas, including warehousing, order processing, inbound and outbound transportation, and inventory. Internal accounting methods such as activity-based costing allow managers to understand the links between performance levels of specific activities and the demands they place on a firm’s resources, identifying opportunities for taking costs out of the supply chain.33 Additionally, managers should compare internal processes to external standards benchmarked from leading “target” firms. External performance measurement should enable firms to monitor the activities of supply chain members as well as assess the degree to which the supply chain is creating value and satisfying customers.34


Research Hypotheses The preceding discussion of the literature on interfirm supply chain processes identified four characteristics or constructs of interfirm coordination that are believed to be positively related to logistics performance: communication, information exchange, partnering, and performance monitoring.

That is, higher levels of coordination are expected to result in

improved logistics cost and customer service performance. One objective of this study is to determine empirically whether this is, in fact, true from the suppliers’ perspective.


relationship between interfirm coordination and the suppliers’ performance on nine key logistics cost and service measures will be investigated.

This is more formally stated in the first

hypothesis: H1: Interfirm supply chain coordination processes, characterized by effective communication, information exchange, partnering, and performance monitoring, will be related to improvements in absolute performance in delivery service. Specifically, strong interfirm coordination will be related to absolute performance improvements in the following areas: a. Inventory levels b. Transportation costs c. Warehousing costs d. Ordering costs e. Stockouts f. Order cycle time g. Order cycle variance h. On-time deliveries i. Unacceptable deliveries Whereas the first hypothesis considers the firm’s performance in an absolute sense, the authors also hypothesize that interfirm coordination will be positively related to the supplier’s customer service performance relative to that of the supplier’s competitors. As noted in the previous section, firms are interested not only in their absolute performance but also in how they compare to their key competitors. Thus, performance monitoring includes assessments of and comparisons with other organizations. The authors believe that a competitive advantage of


improved interfirm coordination from the supplier’s perspective is improved knowledge of what the suppliers’ competitors are doing. This knowledge is prerequisite to improving one’s service in a relative sense. Thus, the authors hypothesize that interfirm coordination will be positively related to the supplier’s delivery service relative to that of the suppliers’ competitors. This is more formally stated in the second hypothesis: H2: Interfirm supply chain coordination processes, characterized by effective communication, information exchange, partnering, and performance monitoring, will be related to improvements in performance in delivery service relative to competitors. Specifically, strong interfirm coordination will be related to relative performance improvements in the following areas: a. On-time delivery b. Product availability c. Customer satisfaction d. Transaction processes e. Order cycle time f. Flexibility g. Assessing customer needs

RESEARCH METHODOLOGY The research design used to empirically test the hypotheses is presented next. First, the sample design and development of measures are presented, followed by the procedures used to analyze the data. Sample Design A survey instrument was developed based on variables used in previous studies to measure the relevant relationship constructs and performance attributes. The instrument was targeted to food suppliers because of their focus on improving supply chain performance. A sample of food industry firms was generated from three sources: (1) The Council of Logistics Management (CLM) membership roster, (2) The American Society of Transportation and Logistics (AST&L) membership roster, and (3) Quick’s Annual Directory and Buyer’s Guide for Frozen Foods. The six-page survey instrument was mailed to every listed firm that was believed


to be a food supplier and for which the listed contact person was at the level of manager or above. The firm personnel who were sent the survey instrument were generally upper level managers or executives, and thus presumed to be knowledgeable about both the level of interfirm coordination and the firms’ logistics performance. The most frequent professional titles of the sampled individuals were President (27%), Vice President (17%), General Manager (11%), Corporate Manager or Director (19%), and Manager (26%). In total, surveys were mailed to145 different food companies. Thirteen (13) surveys were returned as undeliverable. Subsequent to the mailing, an attempt was made to telephone the sample firms to encourage them to respond. Forty-seven (47) usable responses were received for an effective overall response rate of 35.6% (i.e., 47/132). Respondents were asked to provide demographic information relating to their individual companies. Annual corporation sales per respondent ranged from $2 million to $8 billion with an average of slightly over $1.1 billion. The number of personnel employed by each respondent location ranged from 4 to 6000 with an average of 543. Most respondents were employed by firms involved in food manufacturing. In general, these firms do not engage in much outsourcing of order processing, packaging or inventory control/management, though about 18% of their total warehousing cost is paid to third-party providers. Thus, the respondents’ perceptions of cost and service performance related to these activities may be interpreted as reflecting their firms’ performance and not attributed to nor obscured by the use of third-party logistics partners. Additionally, the respondent firms appear to be focused on logistics performance as almost 30% indicated they have implemented a formal benchmarking program, 40% have implemented a formal re-engineering program, and nearly 50% have implemented a formal TQM program. Table 1 summarizes the characteristics of the respondent firms.


TABLE 1 Sample Description •Annual sales (frequencies)

$1 - 50 million: 12 firms $51 – 100 million: 2 firms $101 – 500 million: 8 firms $501 million – 1 billion: 3 firms greater than $1 billion: 9 firms (11 firms did not respond to this question)

•Number of full-time employees (frequencies)

1 – 150: 22 firms 151 – 300: 5 firms 301 – 500: 3 firms 501 – 1000: 6 firms greater than 1000: 5 firms (6 firms did not respond to this question)

•Firm type (frequency) Food Manufacturing Food Merchandising (Retail/Wholesale) Food Services Provider Other Food-related Firm

40 firms 1 firm 3 firms 3 firms

•Number of firms that have implemented a formal benchmarking program: Yes -- 14 firms No -- 32 firms •Number of firms that have implemented a formal re-engineering program: Yes -- 19 firms No -- 26 firms •Number of firms that have implemented a formal TQM program: Yes -- 23 firms No -- 24 firms •Mean percent of total costs in specific logistics functions outsourced/paid to third party providers (variables report the independent percentage of total costs spent on specific logistics functions that are outsourced to third party providers ): Customer order entry/processing 4.8% Finished goods warehousing/DC management 17.9% Finished goods packaging 6.2% Finished goods inventory control/management 8.2% Development of Measures Measurement items used to represent interfirm communications (COMM) and partnering (PART) were constructed from measures validated in previous research on related topics. Items comprising information technology/EDI (EDI) and performance monitoring (PERF) are based in


the logistics literature but were developed by the authors.35 In each case, operational definitions and contexts were found that closely matched the intent of the current research. All measures were structured as seven point scales of bipolar opposites. Items comprising the predictor variable scales were submitted to purification procedures. Scales were purified by running factor analyses and dropping complex variables that loaded highly on two or more dimensions.36 Coefficient alphas were utilized to determine the overall reliability of the scales. Table 2 contains a listing of the constructs and the final items used to measure them, and the coefficient alphas for each scale. The lowest alpha for summed scales in this study was 0.7273. The current research examines the linkage between interfirm supply chain coordination and performance outcomes. Despite continued research on the performance implications of business processes, no consensus exists as to a universal performance definition. Similarly, no agreement regarding what factors constitute the best measure of performance has been reached.37 While performance has often been evaluated by analyzing information reporting performance outcomes, such indicators may not be appropriate and/or relevant when the object of analysis is the performance of specific business activities or processes such as logistics. Outcome-based measures often fail to account for perceptual behavior-based factors such as customer service or product sales support.38 Perceptual measures can provide valuable supplemental information such as indicating the causes of poor performance highlighted by outcome-based measures.39


TABLE 2 Measurement Scales for Predictor Variables

Communication (COMM): An 11-item scale measuring the degree to which respondents communicate with key customers: always (1) to never (7). •Our firm informs customers of special promotions in advance. •Our firm shares pricing changes with our customers. •Our firm shares information on our new products (e.g., stocking instructions) with our customers. •Our firm shares information on discontinued products (e.g., removal dates) with our customers. •Our firm notifies our customers in advance of shipment (delivery) problems. •Our firm and our customers keep each other informed about events or changes that may affect the other party. •Our firm notifies our customers of fluctuations in production that could affect product availability. •Our firm solicits customer input for planning logistics strategy. •Exchange of information between our firm and our customer takes place as needed, and not according to a prespecified agreement. •In the course of our business dealings, our firm and our customers will provide proprietary information if it can help the other party. •In our relationship with our customers, any information that might help the other party will be provided to them. Reliability (coefficient alpha): .8283 Information Technology/EDI: A 5-item scale measuring the degree to which respondents communicate with key customers using EDI: always (1) to never (7). •Our customers provide us with demand forecasts using EDI. •Our customers provide point-of-sale demand information to us using EDI. •We provide shipment tracking information on outbound shipments to our customers using EDI. •We provide product availability information (e.g., production schedules or inventory levels) to our customers using EDI. •Our customers place their orders via EDI. Reliability (coefficient alpha): .7825


TABLE 2--continued Measurement Scales for Predictor Variables Partnering (PARTNER): A 7-item scale rating agreement with statements related to aspects of interfirm relationships with key customers: strongly agree (1) to strongly disagree (7). •When we are selected by a customer, we expect to have a long-term relationship with them. •Our firm and our customers are committed to improvements that may benefit the relationship as a whole, and not only the individual parties. •Our firm and our customers do not mind owing each other favors. •Problems that arise in the course of our relationship with our customers are treated by the parties as a joint rather than individual responsibility. •We are generally satisfied with the level of cooperation between our firm and our customers. •In our relationship with our customers, both parties expect to be able to make adjustments in the ongoing relationship to cope with changing circumstances. •When some unexpected situation arises, our firm and customers would rather work out a new deal than hold each other to the original terms. Reliability (coefficient alpha): .7273 Performance Monitoring (PERF): A 10-item scale rating agreement with statements related to monitoring of logistics performance outputs: strongly agree (1) to strongly disagree (7). •Our firm has clear definitions of what functions each channel member performs in the distribution process. •We are able to trace cause and effect activities for our logistics costs. •We are able to identify the costs that drive our logistics activities. •We are able to measure the interaction between the costs that drive the logistics activities. •We are able to measure the value of different logistics service levels for different customers. •We are able to measure the profitability/contribution of different logistics service levels for different customers. •We are able to determine whether our firm is able to provide the different logistics service levels needed or required by our different customers. •We are able to monitor cost and identify our most profitable customers by product. •Our firm is able to monitor the success of our various partnerships with different channel members. •Our firm is able to provide our customers with services tailored to their needs. Reliability (coefficient alpha): .9378

The complex nature of the subject warrants the use of multiple indicators of performance. Outcome-based logistics performance measures such as order fill rate or percentage of on-time deliveries capture certain performance dimensions, but the information may be considered proprietary and, therefore, hard to collect. Behavior-based measures such as self-reports of order cycle time reductions or lead-time variability are helpful in evaluating the quality of service


rendered, but their usefulness may be limited by self-report bias and comparability problems. A combination of outcome-based and behavior-based measures captures many performance dimensions and forms the basis for the selection of measures used in our analysis.40 A set of measures was selected to achieve a multidimensional representation of logistical performance. Respondents’ perceptions of firm performance were evaluated in both absolute (i.e., general measures of productivity and performance) and relative terms (i.e., firms’ performance relative to key competitors). Performance measures were adapted from The Logistics Handbook,41, and they were structured as seven-point scales of agreement with statements regarding the firm’s absolute and relative performance on specific logistics activities (1 = strongly agree, 7 = strongly disagree). Table 3 provides a summary of the performance measures used in the study. Tests of Hypotheses Main effects of interfirm relationship dimensions on logistics performance were estimated using regression analyses. Evaluations of the results of hypothesis testing were based upon the overall robustness and fit of the regressions models and the direction and significance of individual parameters. ANALYSIS AND RESULTS A set of measures was selected to achieve a multidimensional representation of interfirm relationships--communication, information technology/EDI, partnering, and performance measurement. The items chosen were based upon measures validated in past research. Each multiitem variable was constructed as a mean score of individual scale measures.


TABLE 3 Dependent Variables, Performance Outputs

Absolute Performance: Variables rated agreement with statements related to ABSOLUTE performance on specific logistics activities: strongly agree (1) to strongly disagree (7). •On a constant sales volume/dollar basis, my firm’s average finished goods (e.g., outbound) inventory has been decreasing. •Per-unit transportation cost for finished goods has been decreasing. •Our firm has seen a decrease in warehousing costs. •Our firm has experienced a decrease in ordering cost. •Our firm has achieved a decrease in stockouts per year. •Our firm has achieved a decrease in total order cycle time for our customers. •Our firm has achieved a decrease in the variability of the order cycle time for our customers. •Our firm has experienced an increase in the percentage of on-time deliveries of shipments to customers. •Our firm has achieved a decrease in the percentage of unacceptable deliveries to customers (e.g., deliveries that are defective, not up to specification, etc.) Relative Performance: Variables rated agreement with statements related to performance on specific logistics activities RELATIVE to competitors: strongly agree (1) to strongly disagree (7). •Our firm’s ability to deliver orders on time is among the best. •Our product availability to meet customer demand is among the best. •Customer satisfaction with our firm’s overall logistics performance is among the best. •Our firm’s effectiveness and efficiency in the transaction processes (e.g., order processing, inquiry handling, etc.) is among the best. •Our firm’s order cycle time is among the best. •Our flexibility to meet customers’ requirements is among the best. •Our ability to assess customer logistics requirements is among the worst in the industry.

Table 4 provides descriptive statistics for the variables. For most variables, the mean value agreed closely with the median, which suggests that skewness was low. Means for most predictor variable scales and independent performance measures were below the neutral value (4), which indicates that most respondents scored high on the relational traits and performance measures. Significantly, the mean for information technology/EDI was above 4.0, which indicates that on average most respondent firms do not frequently communicate demand,


product availability, and shipment data to their customers via EDI. Of the performance variables, only decreased transportation and warehousing cost had means greater than 4.0, that is, respondents disagreed with statements related to their firm’s achievement of transportation and warehousing cost decreases. TABLE 4 Descriptive Statistics Variable

Mean Median

Std. Dev.

















Inv. Level Decrease




Transport Cost Decrease




Warehouse Cost Decrease




Ordering Cost Decrease




Stockout Decrease




Order Cycle Time Decrease




Cycle Time Variance Dec.




% On-Time Delivery Inc.




% Unacceptable Del. Dec.




Best % On-Time Delivery




Best Availability




Best Customer Satisfaction




Best Transaction Processes




Best Order Cycle Time




Best Flexiblility




Best Assess of Cust Needs




Note: COMM and EDI are scales measuring the degree to which respondents communicate with key customers and use EDI (1 = always and 7 = never). All others are scales or single variables rating agreement with statements related to relevant subject areas (1 = strongly agree, 7 = strongly disagree).


Table 5 reports regression results supporting three of the nine hypotheses that associate dimensions of interfirm relationships with absolute logistics performance measures. Significant and positive beta coefficients, as well as highly significant fit statistics and explained variance (ranging from 17.6% to 28.7%), were found for the hypothesized relationships between relational dimensions and decreased inventory levels, decreased order cycle time, and decreased order cycle variance. Information technology/EDI had significant explanatory power in each of these three models, while performance monitoring was a significant predictor variable and had the largest standardized beta weight for both decreased order cycle time and variance. Communication was significant only for decreased inventory levels and partnering only for decreased order cycle time. Analysis also supported four of the seven hypotheses linking interfirm relationships and relative performance measures. Significant and positive beta coefficients, as well as highly significant fit statistics and explained variance (ranging from 13.8% to 27.2%), were found for the hypothesized relationships between relational dimensions and flexibility in meeting customer needs, assessment of customer needs, customer satisfaction, and product availability. Performance monitoring had significant explanatory power for three of the firms’ relative performance measures--product availability, customer satisfaction, and assessment of customer need. Communication was significant for flexibility and assessment of customer need, while partnering was significant only for customer satisfaction and information technology/EDI only for flexibility. Results of the regression analyses for the relative performance measures are shown in Table 6.


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