A comparative assessment of senior and logistics executives’ perceptions of logistics value
Novack, Robert A
Distribution was once referred to as the “dark continent” of business.1 This reference was a call to management to realize that distribution, or logistics, is one of the few remaining areas in business that can be used to gain a competitive advantage. Logistics academics and practitioners have attempted to convince upper management and other functional managers of the importance of logistics to the success of their organizations. The importance placed on logistics within the organization is partially based on senior management’s perceptions of the importance of the logistics function and processes. Measuring these perceptions can give insights into not only whether logistics is considered important to the organization, but also how logistics can play an important role in accomplishing organizational goals.
Previous research has presented results on logistics executives concerning their perceptions of whether and how logistics adds value.2 However, these attempts must be expanded to include the perceptions of others within the organization who have decision-making power and who have influence over the importance given to any one functional area. The purpose of this research is to present a comparative assessment of the logistics executive and senior executive perceptions of logistics value.
CONCEPTUALIZING THE DEVELOPMENT OF THE LOGISTICS VALUE PROCESS
Most research of customers has focused on the external customers of the firm. These customers can be classified as organizational customers in business-to-business transactions or as the ultimate consumer at the end of the logistics channel. However, the logistics executive has three groups of customers to satisfy. Exhibit 1 is a representation of these customer groups.
Zeithaml, Berry, and Parasuraman have identified five gaps between providers and customers of service that affect perceptions of service quality.3 These gaps have been identified in the appropriate locations in Exhibit 1. Gap 1 is the difference between customer expectations and management perceptions of customer expectations; Gap 2 is the difference between management perceptions of customer expectations and service quality specifications; Gap 3 is the difference between service quality specifications and the service actually delivered; Gap 4 is the difference between service delivery and what is communicated about the service to customers; and, Gap 5 is the difference between customer expectations and perceptions. This research will address a dimension of Gap I in this model-the perceptions of logistics executives and senior executives concerning the value of logistics service provided to the external customer.
Two of these customer groups are considered to be internal to the firm.4 First, logistics has functional customers, such as marketing and engineering, that require certain logistics services to accomplish storage or movement of materials and products under design or finished goods destined to external customers. Senior executives also are customers. They require effective performance of logistics processes to achieve organizational profit or revenue goals. The external customer obviously requires logistics services in order to receive the product in the right form, at the right time, at the right place, in the right quantity, with no damage, and at the right price. The impact that these logistics services have on each customer group cannot be separated. If logistics fails to meet the delivery requirements of manufacturing, production schedules might not be met, resulting in missed deliveries of finished product to external customers and potentially lost revenue for the supplying firm. What can be different, however, is how each customer group perceives the performance and importance of logistics. Therefore, value is created through the performance of logistics processes based on internal and external customer perceptions of the benefit received.5
Using a conceptual model of the logistics value process introduced by Novack, Rinehart, and Langley, this research investigates the comparative perceptions of logistics executives and their senior executives for an expanded understanding of these theoretical relationships. (See Exhibit 2.)6 The specific theoretical relationships and measures of the logistics functions, logistics quality, and the value created by logistics are presented in Exhibit 3 and are supported by previous research findings.7
The model in Exhibit 3 provides the underlying conceptual structure used for the development of the constructs analyzed in this research. Logistics functions (e.g., forecasting, purchasing, inventory management, transportation, warehousing, and logistics engineering and control) are combined in logistics processes to fulfill customer service requirements. Meeting customer specifications results in the creation of what has been called objective quality.8’9 Perceived quality is created when the receiver of the service recognizes that the firm has met predetermined specifications.10’1 1 When objective quality is consistent with perceived quality, value has been created for the customer.12
Examining perceptual similarities and differences between logistics executives and senior executives concerning logistics value is critical to the future of the logistics discipline. This importance centers on the reality that senior management perceptions affect the “political” positioning of logistics within firm, which affects resource allocation, which ultimately affects service offerings to external customers.
RESEARCH DESIGN AND METHODOLOGY
This research is designed to address the following research question:
Do logistics executives and their specific senior executive counterparts perceive the value of logistics differently?
To address this research question, an initial survey was mailed to logistics executives as part of research presented by Novack, Rinehart, and Langley.13 That study resulted in 66 usable responses for a 21% response rate. Of those 66 logistics executives, 22 identified their senior executive who would be willing to be the subject of a thirty-minute follow-up telephone interview concerning the same issues. This research question compares the responses of the 22 logistics executives and their senior executive counterpart. Eleven hypotheses were generated and tested from this research question. (See Exhibit 3.) Some basic demographics of the organizations and executives involved in this research are presented in Exhibit 4. The demographics for both the logistics executives and senior executives are the same for Industry, Type of Business, and Revenue, since both groups are from the same twenty-two firms. The largest group represented in the study was food and beverage manufactures, which had more than $1 billion in annual revenue. Sixty three percent of the logistics executive respondents held the title of vice president or higher and 86% of the senior executives were at the vice president level or higher. These titles, however, can be misleading since they do not necessarily reflect relative level of responsibility. Of the eight senior executives who had another functional area in their titles (other than logistics), two had responsibility for sales/marketing, four had manufacturing/operations, and two held responsibility for customer service and finance/customer relations.
The hypotheses developed were intended to measure the perceptions of logistics executives and senior executives concerning the value of logistics. Each hypothesis presented here will be tested using multiple regression analysis. The first 4 hypotheses were developed to test executives’ perceptions of the effect of logistics inputs on logistics productivity. These hypothesized relationships (as identified in Exhibit 3) are as follows:
Hla: Executives’ perceptions of the importance of inbound activities are related to their perceptions of the importance of logistics productivity.
Hlb: Executives’ perceptions of the importance of operations activities are related to their perceptions of the importance of logistics productivity.
Hlc: Executives’ perceptions of the importance of outbound activities are related to their perceptions of the importance of logistics productivity.
Hld: Executives’ perceptions of the importance of support activities are related to their perceptions of the importance of logistics productivity.
Four hypotheses were developed to test the executives’ perceptions of the effect of logistics inputs on the importance of logistics service performance. These hypotheses (as identified in Exhibit 3) are as follows:
Hle: Executives’ perceptions of the importance of inbound activities are related to their perceptions of the importance of logistics service performance.
Hlf: Executives’ perceptions of the importance of operations activities are related to their perceptions of the importance of logistics service performance.
Hlg: Executives’ perceptions of the importance of outbound activities are related to their perceptions of the importance of logistics service performance.
Hlh: Executives’ perceptions of the importance of support activities are related to their perceptions of the importance of logistics service performance.
Finally, three hypotheses were developed to test the effect of logistics productivity, logistics service performance, and the performance measurement system on customer reaction. These hypotheses (as identified in Exhibit 3) are as follows:
H2a: Executives’ perceptions of the importance of logistics productivity are related to their perceptions of customer reaction.
H2b: Executives’ perceptions of the importance of logistics service performance are related to their perceptions of customer reaction.
H2c: Executives’ perceptions of the importance of logistics service performance are related to their perceptions of customer reaction.
The telephone interview was conducted by the members of the research team that developed and conducted the initial survey of the logistics executives. The measures used in these telephone interviews assessed the construct relationships of the model in Exhibit 3, which were identical to those used on the mail survey directed to the logistics executives. To insure adequate interpretation of the scales used during the telephone interview, each senior executive was sent an advanced copy of the scales with some sample questions. Since this study turned into a nonrandom sample, the issue of nonresponse bias among the senior executives was not considered an issue.
The survey instrument and the telephone survey asked both the logistics executive and their senior management counterparts specific questions concerning their perceptions of the importance of logistics activities, logistics deliverables, and logistics value. Perception of importance for each section was measured using a 7-point Likert-type scale. Several items within each section were combined to create multiple item measures which were used to test the construct relationships in this research. A copy of the senior executive telephone template can be found in Appendix I on page 167. The exact survey questions used in the creation of the measures can be found in the Appendix to Novack, Rinehart, and Langley.14
RESULTS
The results shown in Exhibit 5 can be used to address the research question by comparing the responses for the logistics executives with their senior executive counterparts. For the sake of brevity, only the construct averages will be compared unless specific item differences are noticed. These findings show that the logistics executive group places less importance on inbound logistics than does the senior executive group. The expected result here might well be the opposite, with the logistics executive group placing more importance on the traditional logistics activities. There might be two reasons for this response. First, the logistics executive might have primary responsibility for outbound logistics with operations, while inbound logistics is controlled by purchasing and manufacturing. Therefore, logistics might not be as broadly integrated in this group as might be expected. Second, this finding might reveal that the senior executives actually do value logistics activities; whether they associate the activities with the concept of logistics is not known.
Exhibit 6 reveals several differences between the senior executives and the logistics executives. Product availability and order cycle time are more important, on a relative basis, to the logistics executives than they are to the senior executives. This is not a surprising result. This is especially true with order cycle time. One possible explanation for this is the fact that the logistics executive has direct interface with the external customers and, as such, is more aware of the importance the customer places on these logistics services.
Finally, Exhibit 7 contains the results for the two groups on the items in the logistics productivity, performance measurement, and customer reaction constructs. The fourth statement under logistics productivity has a higher agreement score for the senior executives than for the logistics executives. This might be related to the results found in Exhibit 6. The senior executive group might perceive product availability and order cycle time as less important because they do not see current service levels in these areas as providing a competitive advantage. As such, the senior executives are in high agreement that their firms are constantly trying to improve these services. On the other hand, the logistics executive groups might perceive their current service levels to be satisfactory and not in need of much improvement.
The next two sections will present a more thorough examination of the responses of the senior and logistics executives by presenting the regression results of the hypothesized relationships identified in this research.
Relationship Between Logistics Functions and Logistics Quality
Exhibit 8 contains the regression results for Hypotheses Hla through Hld (Exhibit II contains a summary of the regression results for all of the hypotheses.) These hypotheses represent the relationships between logistics inputs and logistics productivity as shown in Exhibit 3.
Hypothesis Hla addresses the effect of inbound logistics on productivity and takes the form:
PRODUCTIVITY = f(Sales Forecasting, Production Planning, Purchasing, Inbound Transportation) (1)
The null hypothesis can be accepted for both groups. This might be interpreted to mean that both groups agree that no significant relationship exists between logistics productivity and inbound logistics activities.
Hypotheses Hlb addresses the effect of operations activities on logistics productivity and takes the form: PRODUCTIVITY = f(Production, Packaging, Raw Materials Inventory, Finished Goods Plant Warehousing) (2)
The null hypothesis can be rejected for the logistics executives and accepted for the senior executives. The logistics executive group has production as a significant independent variable with a negative beta. This indicates a negative relationship between the perceived importance placed on production and logistics productivity. This agrees with previous research. A possible explanation might be that as a firm places more emphasis on the production activity, inventory levels might increase at plant sites and field warehouses, thereby decreasing logistics productivity. Only 4.5% of the logistics executives indicated having direct line control over the production activity, while 59.1% had no responsibility at all for the production activity. This lack of control by the logistics executives might also influence the perceived negative effect.
Hypothesis Hlc addresses the effect of outbound logistics on logistics productivity and takes the form:
PRODUCTIVITY = f(Finished Goods Inventory Management, Intracompany Transportation, Finished Goods Field Warehousing, Order Processing, Outbound Transportation) (3)
The null hypothesis can be accepted for both groups. Neither perceive that outbound logistics activities effect logistics productivity improvements. However, previous research has found a significant relationship for this hypothesis, with intracompany transportation and finished goods field warehousing being significant independent variables.15
Finally, Hypothesis Hld analyzes the effect of logistics support activities on logistics productivity and takes the form:
PRODUCTIVITY = f(Logistics Planning, Logistics Engineering, Logistics Control) (4)
As can be seen in Exhibit 8, the null hypothesis for both groups can be accepted. Previous research has also shown that this is significant for the logistics executives, with logistics engineering being a significant independent variable.l6
This research produced only one significant model with only one significant independent variable linking logistics activities with logistics productivity. That variable, production, was a perceived negative effect on logistics productivity and is not one that is under direct control of the logistics executive. This might imply that neither the logistics executives nor the senior executives perceive a positive influence of logistics activities on logistics productivity. Also, it appears that the logistics executives perceive those activities not under their control to have potential negative effects on logistics productivity. Consequently, both groups conclude that logistics is a difficult function (process) to control.
Exhibit 9 contains the regression results for Hypotheses Hle through Hlh, which analyze the effects of logistics activities on logistics service performance. These relationships can be seen in Exhibit 3.
Hypothesis Hle presents the relationship between inbound logistics activities on logistics service performance and takes the form:
SERVICE PERFORMANCE = f(Sales Forecasting, Production Planning, Purchasing, Inbound Transportation) (5)
The null hypothesis for both groups can be rejected. Both groups agree that inbound transportation is important to logistics service performance. Since a majority of the respondent organizations were manufacturing-based, it is easy to understand why inbound movements to plants would be important to internal customers (manufacturing) and to external customers. The senior executive, however, also perceived sales forecasting and purchasing to be significant independent variables. The reasoning behind these significant variables is the same as that used to rationalize the importance of inbound transportation. The question arises then as to why the logistics executives did not perceive the same variables to be significant as did their senior executive counterparts. One possible explanation is that the only inbound activity over which a majority of the logistics executive respondents (73%) have direct line control is inbound transportation. Only production planning comes close to this in direct line control (46%). So, in this case, control might have an influence over perceived importance. Since the senior executives conceptually have control over a wide range of activities, they will indicate that more will be important.
Hypothesis Hlf addresses the effect of operations activities on logistics service performance and takes the form:
SERVICE PERFORMANCE = f(Production, Packaging, Raw Materials Inventory, Finished Goods Plant Warehousing) (6)
The null hypothesis for both groups can be accepted as seen in Exhibit 9. This result is consistent with that found in previous research. If it is assumed that operations activities are consistent with “product attributes,” then logistics executives might feel this is something over which they have little control. As such, operations has little influence on service performance. For the senior executives, product quality might be considered to be a “given” in the marketplace, thus having little influence over logistics service performance. Hypothesis Hlg introduces the relationship between outbound activities and service performance and takes the form:
SERVICE PERFORMANCE = f(Finished Goods Inventory Management, Intracompany Transportation, Finished Goods Field Warehousing, Order Processing, Outbound Transportation) (7)
The null hypothesis for both groups can be accepted. This is consistent with previous research but surprising, since these activities come closest to the external customer. However, these executive groups might perceive that customers are about what is delivered in a way of service and not how it is delivered. This “what” aspect will be addressed in Hypothesis H2b.
Finally, Hypothesis Hlh addresses the effect of support activities on service performance and takes the form:
SERVICE PERFORMANCE = f(Logistics Planning, Logistics Engineering, Logistics Control) (8)
Again, the null hypothesis for both groups can be accepted. This is not consistent with previous research, where the relationship with the logistics engineering and logistics control independent variables was significant. Both groups were consistent in their perceptions of the effects of logistics activities on service performance, with inbound activities being the only ones that influence logistics service performance.
Relationship Between Logistics Quality and Value of Logistics Service
This section will present the regression results of Hypotheses H2a, H2b, and H2c. These hypotheses test the relationship between logistics productivity and customer reaction, logistics service performance and customer reaction, and performance measurement systems and customer reaction. These relationships can be seen in Exhibit 3. Customer reaction is a measure comprised of 4 statements concerning customer value perceptions by the logistics executive and the senior executive. The development of this measure can be found in Appendix 2. If value is created for the customer, then some type of reaction from the customer should occur, whether it be positive, negative, or neutral. These three hypotheses attempt to determine which of the three measures, if any, creates customer value from the perspectives of the logistics and senior executives. Exhibit 10 contains the regression results for these hypotheses.
Hypothesis H2a addresses the effect of logistics productivity on customer reaction and takes the form:
CUSTOMER REACTION = f(High Productivity, Low Cost, Productivity Through Quality, High Service) (9)
The null hypothesis for both groups can be accepted. Neither the logistics executive group nor the senior executive group believe that improving logistics productivity, or reducing logistics costs, is important to creating value for customers. This is consistent with previous research, which explained that cost reductions by the firm might not be passed on to the customer in the form of price reductions. Therefore, customers would not be sensitive to logistics cost reductions since they would not receive their benefits directly.
Hypothesis H2b examines the effect of logistics service performance on customer reaction and takes the form:
CUSTOMER REACTION = f(Product Availability; Order Cycle Time; Logistics System Flexibility, Malfunction and Recovery; Logistics System Information; Postsale Product Support) (10)
The null hypothesis for the logistics executives can be rejected and accepted for the senior executives. The result for the logistics executives is consistent with previous research, with product availability being a significant independent variable. This could mean that logistics executives perceive product availability elicits some type of reaction from customers. This could be a positive reaction for superior performance or a negative reaction for inferior performance. This result supports the previous notion that customers care about what service is performed, not how it is delivered. What is surprising is the lack of significance for this model for senior executives. This could be interpreted to mean that these senior executives do not perceive a relationship to exist between logistics service performance and customer reaction. This result, coupled with the insignificance of the results from Hypothesis H2a, could be interpreted to mean that these senior executives do not attribute any ability for logistics to elicit a reaction from customers, either through cost or service control.
Finally, Hypothesis H2c presents the results of the effects of logistics performance measurement on customer reaction and takes the form:
CUSTOMER REACTION = f(Measure, Dollars, Value) (II)
The null hypothesis can be rejected for the logistics executives and accepted for the senior executives. The results for the logistics executives are consistent with previous research with the model being significant and the item VALUE being significant. This can be interpreted to mean that the logistics executives believe that logistics adds value and will elicit some type of reaction from customers. However, the senior executives do not appear to believe that logistics adds value. Although these senior executives place importance on several logistics activities (Exhibit 5) and deliverables (Exhibit 6), they do not seem to believe that logistics provides a competitive advantage. This could also be interpreted to mean that they believe logistics to be important but also believe it to be a minimum requirement to compete in the market.
IMPLICATIONS, LIMITATIONS, AND CONCLUSIONS
The research question in this study attempted to address the differences and similarities of perceptions by logistics executives and their senior executives concerning logistics importance. The research question attempted to determine whether or not logistics executives and their senior executive counterparts share similar perceptions concerning the importance and value of logistics. The preliminary conclusion reached by this research is that they do not agree. Exhibit 11 presents a summary of the results of the 11 hypotheses tested to address this research question.
As can be seen in this exhibit, both groups agree on only one hypothesis test, i.e., that inbound logistics activities have a significant relationship with logistics service performance. Both groups agreed that 7 of the hypotheses generated no relationships but disagreed on the strength of the relationships on the remaining 3 hypotheses. Exhibit 12 is a summary of the similarities/differences between both groups concerning the significance of each of the ll hypotheses tested.
Although the groups agreed on the insignificance of 7 of the hypotheses tests, a detailed discussion of this is not warranted since insignificant results of tests on 2 groups do not necessarily mean that the groups are in agreement. As such, the discussion will focus on the 4 hypotheses that produced significant results for at least one of the groups.
Hypothesis Hla produced a disagreement between the two groups. Logistics executives indicated a negative relationship between production and logistics productivity, while senior executives indicated no significant relationship between any operations activity and logistics productivity. Respondent firms in this particular research question apparently are mostly manufacturing based (73%). As such, the focus of senior management is on manufacturing performance and the focus of logistics management is on reacting to manufacturing performance. Only 4.5% of these logistics executives said they had direct line control over manufacturing. This possibly explains the negative beta for production in the logistics executive model. Therefore, logistics executives focus on reacting to supplying production processes and managing the inventories and movement created by these processes. Upper management might also perceive the role of logistics to be subservient to that of production, or manufacturing, since it is likely that manufacturing comprises a higher total cost to the company than does logistics. An informal indicator of the relative importance of production to senior executives can be found in the importance ratings as shown in Exhibit 5. Although it is not statistically appropriate to average averages (because of potential different respondent sample sizes for each average and different standard deviations), it was felt that doing so for illustrative purposes would be acceptable. Also, respondent sample sizes for each item within each executive group were similar and the standard deviations for each item within each group are consistent. If it is assumed that a focus on manufacturing would also include a focus on those activities that would affect manufacturing performance, then sales forecasting, production planning, purchasing, and inbound transportation could be included in that focus. Averaging the importance scores for these 4 manufacturing support activities plus that for production for the senior executives results in a mean importance score of 5.32 for senior executives and 5.03 for logistics executives. Combining the importance scores for the remaining activities in this exhibit results in a mean importance score for senior executives of 5.15 and 5.03 for logistics executives. So, the senior executives appear to place a higher importance on production and its supporting activities than they do on the other logistics activities; logistics executives place equal importance on production and nonproduction related activities.
Both groups agree that inbound activities have an impact on logistics service performance (Hypothesis Hle). Logistics executives feel that inbound transportation is responsible for this relationship, while the senior executives also include sales forecasting and purchasing. This difference once again supports the notion that logistics executives place more importance on activities over which they have control. Only 9.1% of these logistics executives have direct line control over sales forecasting and only 27.3% have direct line control over purchasing. On the other hand, 72.7% have direct line control over inbound transportation. The senior executive group more than likely has responsibility over all of these inbound activities, thus generating the three significant independent variables. Once again, note the importance placed on manufacturing support activities by the senior executive group. It appears that this group evaluates its customer as being manufacturing, while the logistics executive group also includes the external customer in its realm of responsibility.
A previous examination of Exhibit 6 showed that both groups perceived product availability to be important. However, only the logistics group perceives it to be able to elicit a reaction from the customer (Hypothesis H2b). This could mean that the senior executive group is defining its customer group as being internal to production and defining product availability as product available at the end of the production line or in finished goods inventory. This could also mean that either the senior executive group does not consider product availability as important to the external customer or that product availability is a requirement by customers to just be in the market. Regardless of the reasoning, it is clear that the groups disagree on the ability of product availability to stimulate a customer reaction. In fact, the senior executive group did not indicate the ability of any logistics service to elicit a customer response. This will have implications on the senior executive group’s perception concerning the value added by logistics.
This last statement is tested in Hypothesis H2c. The groups disagree on this hypothesis. The logistics group perceives that logistics does add value to the firm’s output; the senior executive group does not. It appears, from preceding discussions, that logistics is considered a cost center by upper management, with emphasis placed on cost reductions. Logistics executives seem to perceive logistics as both a cost center and a revenue generator, i.e., able to elicit responses from customers with service. This highlights the internal focus of the senior executive group and the multiple customer focus of the logistics executive group. This might also imply that the senior executives in this group are not as close to the external customer as would be desired. The perception by the senior executives of logistics as a cost center is also compounded by the logistics executive group’s inability to quantify logistics value (items “MEASURE” and “DOLLARS” in Hypothesis H2c, Exhibit 10). Logistics executives have proven their competence at measuring logistics costs. However, their inability to quantify the impacts of service levels on revenue might lead the senior executive group to believe that what can be measured is what is managed. Future research needs to address the ability, or inability, of logistics service to impact the firm’s revenue and market share.
Apparent from this research is that the logistics executives and senior executives certainly have their differences of opinion concerning the importance of logistics to the external customer. If this is the result of the senior executive group’s lack of understanding of customer needs, then it is up to the logistics executive group to inform and educate senior executives of customer desires and promote logistics as a competitive weapon. If it is the result of logistics’ inability to prove to senior executives that there is a relationship between logistics service and customer reaction, then it is imperative that the logistics executives undertake research to begin this quantification process. Either way, a perceptual gap exists between the beliefs of both groups concerning logistics. Logistics executives need to be proactive within their own organizations to eliminate these perceptual differences.
Finally, it should be recognized that this study was conducted to assess similarities and differences in perceptions between logistics executives and their senior management counterparts. Because of the nature of the research, the need for self-selection of the senior management participants became important. However, the methodological result was the development of a nonrandom sample for analysis rather than a random sample from which statistical inferences can be made concerning the population studied. This certainly is a limitation of the study. However, the limited statistical generalizations should not mask the potential reality identified in the research, that is, senior executives perceive logistics importance differently than logistics executives. This finding can be important to the political positioning of logistics within the organization when considering future budgets and resource allocation. Therefore, this study highlights the importance of future research concerning senior management perceptions of logistics.
NOTES
1 Peter Drucker, “Physical Distribution: The Frontier of Modern Management,” reprinted in Donald J. Bowersox, Bernard J. LaLonde, and Edward W. Smykay, eds. Readings in Physical Distribution Management (Toronto: Macmillan, 1969), pp. 3-8.
2Robert A. Novack, Lloyd M. Rinehart, and C. John Langley, Jr., “An Internal Assessment of Logistics Value,” Journal of Business Logistics 15, no. 1 (1994): 113-152.
3 Valerie A. Zeithaml, Leonard L. Berry, and A. Parasuraman, “Communication and Control Processes in the Delivery of Service Quality,” Journal of Marketing 52 (April 1988): 35-48. 4Same reference as Note 3.
5Ruth N. Bolton and James H. Drew, “A Multistage Model of Customers’ Assessments of Service Quality and Value,” Journal of Consumer Research 17 (March 1991): 375-384. 6Same reference as Note 2. 7Same reference as Note 2.
8Morris B. Holbrook and Kim P. Corfman, “Quality and Value in the Consumption Experience: Phaldrus Rides Again,” Perceived Quality, J. Jacoby and J. Olson, eds. (Lexington, Mass.: Lexington Books, 1985).
9A. Parasuraman, Valerie A. Zeithaml, and Leonard L. Berry, “SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality,” Journal of Retailing 64, no. 1 (1988): 12-37.
10 Same reference as Note 8. 11 Same reference as Note 9. 12 Same reference as Note 2. 13 Same reference as Note 2. 14 Same reference as Note 2. 15 Same reference as Note 2. 16 Same reference as Note 2.
Robert A. Novack, associate professor of business logistics at The Pennsylvania State University, holds a B.S. and M.B.A. degrees from Penn State and a Ph.D. from the University of Tennessee with a major in business logistics and a minor in strategic management. He taught logistics and transportation courses at the University of Tennessee and the University of Cincinnati. His research has been published in a number of academic journals.
Lloyd M. Rinehart, associate professor of marketing and logistics at Michigan State University, holds a B.S. in marketing and an M.A. in business education from the University of Northern Colorado and a Ph.D. in marketing and logistics from the University of Tennessee. His current research interests include concept foundations for integrating materials and logistics management, integration of
marketing and logistics, and theoretical foundations and applications of negotiation processes in marketing and logistics.
C. John Langley is the J. H. “Red” Dove Distinguished Professor of Logistics and Transportation at the University of Tennessee. He holds B.S. (mathematics), M.B.A. (finance) and Ph.D. (business logistics) degrees from The Pennsylvania State University. He served as president of the Council of Logistics Management during 1990-1991, is a co-author of two texts on logistics management, and has published widely in the professional journals.
Copyright Council of Logistics Management 1996
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