A Meta-Analysis of Logistics Customer Service

By Leuschner, Rudolf; Charvet, Francois et al. | Journal of Supply Chain Management, January 2013 | Go to article overview

A Meta-Analysis of Logistics Customer Service


Leuschner, Rudolf, Charvet, Francois, Rogers, Dale S., Journal of Supply Chain Management


INTRODUCTION

Logistics customer service has received considerable attention in the literature for several decades (La Londe and Zinszer, 1976). Companies use their logistics network to deliver products to their customers, and therefore, it can significantly impact firm performance. As such, logistics customer service is the output of a firm's logistics system. It is a measurement of the "Seven Rs" and as a consequence creates customer satisfaction (Bienstock, Mentzer & Bird, 1997; Mentzer, Flint 81 Huh, 2001; Mentzer, Gomez & Krapfel, 1989). They describe a company's ability to deliver the right product in the right amount at the right place at the right time for the right customer in the right condition at the right price (Coyle, Bardi & Langley, 2002; Stock & Lambert, 2001). The implication is that a significant part of the value of a product is created by logistics customer service, a concept that is also supported by the Service-Dominant Logic of Marketing (Vargo & Lusch, 2004). A traditional view of logistics is focused on the creation of time and place utilities (Perreault & Russ, 1976). The service that is provided to the customer through logistics has been defined as a component of or a substitute for logistics value (Langley & Holcomb, 1992). Firms can use logistics customer service as a differentiating element to compete more effectively in the marketplace (Yazdanparast, Manuj & Swartz, 2010).

The importance attached to logistics customer service is reflected in the prominent role played by this stream of research within the supply chain management field (e.g., Georgi, Darkow & Kotzab, 2010). While most of the literature found on this topic is in logistics (e.g., Daugherty, Stank & Ellinger, 1998; Mentzer et al., 1989; Novack, Rinehart & Langley, 1994), researchers in other fields have studied this subject as well. Logistics customer service has been directly linked to the marketing mix, where it is conceptualized as a large part of the place component (e.g., Innis & Londe, 1994; Sterling & Lambert, 1987). Operations management scholars consider delivery performance as one of the key capabilities that can determine a firm's success (e.g., Swink, Narasimhan & Wang, 2007; Ward, McCreery, Ritzman & Sharma, 1998).

The importance of this topic has been stated before. Establishing the link between logistics customer service and overall firm performance has been portrayed as one of the logistics discipline's most important challenges (Bowersox, 1999). Whereas some regard the logistics function as a cost center that contributes primarily to the firm's bottom line in the areas of cost and asset reductions (Andraski & Novack, 1996; Novack et al., 1994; Novack, Rinehart & Langley, 1996), a considerable stream of literature has provided evidence that logistics customer service creates value and can lead to a competitive advantage (e.g., Daugherty et al., 1998; Davis-Sramek, Mentzer & Stank, 2008; Innis & Londe, 1994; Stock & Lambert, 1992). This prior evidence, however, is based on single studies that were performed in specific industries, on specific products and at one point in time, and this is not generalizable. Only with generalizable evidence that superior logistics performance produces desirable business outcomes, such as increased customer satisfaction and better financial performance, can the notion that logistics only contributes cost and asset reductions be addressed in a more holistic manner.

Despite this strong interest and the resulting body of literature, only a few integrative reviews can be found on the topic (e.g., Mentzer et al., 1989; Yazdanparast et al., 2010), all of which were qualitative in nature. While such studies are important and valuable, their main drawback is that they are inherently biased because the researchers have the challenge of objectively tying together several studies. …

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