Michael S. Garver

Best practices in identifying customer-driven improvement opportunities

Abstract This article makes a significant contribution to the literature by modifying traditional performance–importance analysis and by expanding customer-driven improvement models. The model significantly advances theory, addressing many important research issues and gaps. It is extremely useful to practitioners, providing a guide for identifying continuous and breakthrough improvement opportunities.

Measuring the importance of attributes in logistics research

Purpose – Traditional methods of capturing and determining logistics attribute importance have serious research limitations. The purpose of this paper is to introduce maximum difference (MD) scaling as a new research methodology that will improve validity in measuring logistics attribute importance, overcoming many of the limitations associated with traditional methods. In addition, this new research method will allow logistics researchers to identify meaningful need‐based segments, an important goal of logistics research.Design/methodology/approach – This paper provides an overview of MD scaling along with important research advantages, limitations, and practical applications. Additionally, a detailed research process is put forth so that this technique can be implemented by logistics researchers. Finally, an application of this technique is presented to illustrate the research method.Findings – The importance of truck driver satisfaction attributes was analyzed using bivariate correlation analysis as we...

Modelling choice in logistics: a managerial guide and application

Purpose – Much of the research conducted in logistics/SCM has focused on satisfaction/retention of customers. This has left a critical gap for managers: before customers can be satisfied and ultimately retained, a purchase choice of logistics services has to occur. To date, very little research has addressed how logistics customers make purchase choice decisions about logistics services. The purpose of this paper, using logistics research methods, is to introduce adaptive choice modelling (ACM) to address this gap and put forth a research method that is useful for academic researchers and logistics/SCM managers.Design/methodology/approach – This paper provides an overview of ACM, along with a discussion of its important research advantages, limitations, and practical applications. Additionally, an empirical demonstration of this research technique is provided to illustrate how academic researchers and logistics managers can use ACM to better understand the decision‐making process of customers when selecti...

Segmentation Analysis of the Volunteering Preferences of University Students

The purpose of this article is to explore how universities can increase volunteering among their students. To accomplish this objective, conjoint anlaysis was undertaken to determine the different underlying needs and preferences that drive the volunteering behavior of students. From this data, four need‐based segments are identified and discussed. Strategies are then formulated to meet the needs and preferences of each segment as a means to increase volunteering on campuses.

Listening to Customers

While most practitioners are familiar with traditional customer satisfaction surveys, research findings suggest that best practice companies use multiple tools to bring the voice of the customer inside the organization. The purpose of this study is to examine how best practice companies use various tools to listen to customers. The primary contribution of this article is in discussing a variety of different customer listening tools used by practitioners, along with introducing new customer listening tools to the literature. Furthermore, this article puts forth a framework that captures essential characteristics of each tool, depicting when their use is most appropriate. Finally, this article depicts how customer listening tools are linked together and synthesized into a customer performance model.

Owner operators: employing a segmentation approach to improve retention

Purpose – Owner operators are an important group of truck drivers, yet have been the subject of very little academic research. Specifically, no research has explored retention issues among owner operators. Thus, this paper aims to employ a segmentation approach to owner operator retention, examining important independent variables that include: pay and compensation, top management support, time at home, and safety.Design/methodology/approach – Data were collected from a large truckload (TL) carrier. The drivers surveyed were irregular route long‐haul drivers. A total of 239 responses were obtained, for a response rate of 74.6 per cent. Latent class regression (LCR), a technique new to logistics and supply chain management (SCM) research, was utilized for data analysis.Findings – The results show there are four different need‐based driver segments, which means that specific driver retention programs must be developed for each segment.Research limitations/implications – The major limitation of this paper is...

Conjoint Analysis of Study Abroad Preferences: Key Attributes, Segments and Implications for Increasing Student Participation

ABSTRACT An adaptive conjoint analysis was performed on the study abroad preferences of a sample of undergraduate college students. The results indicate that trip location, cost, and time spent abroad are the three most important determinants of student preference for different study abroad trip scenarios. The analysis also uncovered four different study abroad need-based segments. In order to increase study abroad participation rates it is recommended that universities determine which of these segments they want to target, and then develop a set of study abroad offerings and communication strategies custom designed to address the particular needs of each targeted segment. Recommendations on how to market to each segment are provided.

Subscription Supply Chains: The Ultimate Collaborative Paradigm

Supply chain practitioners have made great strides in forming collaborative partnerships, yet the end consumer is often left out of these plans. Being an important member of the supply chain, we propose that supply chains need to get closer to the end consumer ‐ forming collaborative relationships that center around demand planning. Developing subscription relationships with end consumers will lead to increased planning time, which will result in dramatic cost reductions and superior consumer value and satisfaction through lower costs, increased convenience, and improved availability of supply. Being a new and unique strategy, not all consumers will adopt subscription supply chains. However, we argue that some consumer segments will receive tremendous value and satisfaction purchasing certain types of products and services through subscriptions. Tremendous opportunities await those supply chains who target the right consumers, marketing the right products and services through a subscription supply chain.

Best Practice Customer Value and Satisfaction Cultures

To use customer value and satisfaction data effectively, the company culture must embrace, support, and encourage customer value and satisfaction initiatives. The purpose of this article is to discuss the nature of a customer value and satisfaction culture and to model how best practice companies transform their cultures. The research results make a contribution to the literature by revealing unique insights into the nature of a customer value and satisfaction culture and by offering practitioners a model of how to manage such a culture.

Improving the house of quality with maximum difference scaling

Purpose – The purpose of this paper is to put forth maximum difference scaling to more accurately identify importance scores for customer requirements, which will also allow need‐based segments to be recognized and utilized within the QFD process.Design/methodology/approach – An overview of research methods to explore customer requirements are discussed, followed by survey data analysis of customer requirements which compares and contrasts stated importance ratings to maximum difference scaling results.Findings – The results from this study suggest that maximum difference scaling offers some advantages compared to traditional stated importance ratings, as well as other traditional methods for determining importance ratings. Providing significantly more discriminating power among customer requirements, maximum difference scaling allows researchers to have a more accurate and valid view of the relative importance of customer requirements as well as the ability to form need‐based segments.Research limitation...