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The influence of security practices is increasingly common in the supply chain management and logistics literature. However, an under-researched area exists within the logistics service provider (LSP) selection process. The purpose of this paper is to introduce a security capability into the LSP selection process. Specifically, this research seeks to understand partner willingness to compensate and collaborate with service providers that possess a security capability.

Adaptive choice modeling is adopted to assess the influence of a security capability in the LSP selection process. This study represents the first use of this method in supply chain management and logistics research. Cluster analysis is also performed to uncover specific buyer segments along with traditional regression-based significance testing and counting analysis.

The findings indicate that security can have an important influence on the LSP selection process. In particular, the findings note a willingness to pay for a security capability in LSP selection. Applying segmentation techniques to the findings, three LSP buying segments are determined, each placing different importance and value on LSP capabilities.

This research notes an ongoing provider deficiency in security offerings. Partner firms sometimes maintain a cost focus, but others show a willingness to pay higher prices for access to partners with a security capability. Key practitioner findings include the need to include security with other traditional selection variables. The study walks the researcher and manager through the development of segments based on LSP capabilities.

This manuscript investigates logistic service provider selection. The authors detail an advanced form of conjoint analysis, adaptive conjoint modeling, for first time consideration. Additionally, this is the first study to integrate security into the LSP selection process. This is also the first study to identify a willingness to pay for a security capability.

Driver turnover has plagued the truckload industry in the USA since deregulation in 1980. Turnover in truck load firms averages above 100 percent in good economic times and over 40 percent in bad ones, costing the industry billions of dollars. This research sought a best‐fit regression model to show how a firm might control its own turnover.

The paper distributed a survey questionnaire to 800 truck drivers at a large US truckload motor carrier. The questionnaire included over 50 items with a seven‐point Likert‐type scale from strongly agree to strongly disagree. The paper analyzed 309 usable responses using regression analysis with scaled scores on aspects of a driver's job. The dependent variable was intent to quit (ITQ).

Research on truck driver turnover has focused on driver attitudes as determinants of ITQ, looking at drivers' attitudes that might lead to higher ITQ and higher turnover. In this research, drivers' attitudes toward top management and dispatchers did not influence ITQ, a surprising result that raises questions and suggests a new direction for research.

This research was conducted in only one firm. Its results may not generalize to all trucking firms, especially not to smaller firms. The method used, however, does generalize. Other firms may use this same approach to identify the causes of turnover in their organizations.

This research demonstrated a method for researching the causes of driver turnover that are practical and accessible to firms of all sizes.

This research was conducted in only one firm. Its results may not generalize to all trucking firms, especially not to smaller firms. The method used, however, does generalize. Other firms may use this same approach to identify the causes of turnover in their organizations.

The results of this research suggest that the relationship between drivers and the firm have changed, probably because of the extensive use of new technology. The methods used here will help large trucking firms allocate resources for driver management and retention. They may also help smaller firms understand the implications of investment in sophisticated technology.

The events of September 11, 2001 heightened the awareness of supply chain professionals to the threat of man‐made disasters on the security of supply chains. According to institutional theory, the environment in which an organization operates creates pressures (normative, coercive, and mimetic) to adopt “institutionalized” norms and practices in order to be perceived as “legitimate.” Using an institutional theory perspective, this paper identifies and explores the environmental drivers that motivate firms to engage in supply chain security (SCS) practices to thwart man‐made supply chain disasters.

Qualitative research in the form of 19 depth interviews with mid‐to‐high level supply chain management professionals is conducted.

The findings of the qualitative research indicate that four primary drivers of SCS exist: government, customers, competitors, and society. Implications and suggestions for future research are provided.

The qualitative findings call for future empirical testing.

Practitioners will benefit from the research presented here by better understanding what environmental factors are causing improved security measures in the supply chain.

This paper investigates drivers of SCS, an issue that is currently having an impact on supply chain operations worldwide. This is the first SCS study to investigate the reason behind why supply chains are implementing security strategies.

Career shifts and talent shortages in supply chain management (SCM) are evident at most occupation levels and need further attention and understanding. The purpose of this paper is to present factors that shape SCM career expectations, choices, and satisfaction and to advance career theory and research that is currently absent in SCM literature.

This study administered open‐ended surveys to individuals educated and working in SCM to elicit the satisfaction and dissatisfaction that professionals derive from various aspects of their SCM careers. Resulting data were content analyzed and categorized into major themes representing career satisfiers (likes) and dissatisfiers (dislikes).

This exploratory study found evidence of traditional career components and the presences of objective and subjective components that transcend organizational boundaries. The results indicate an emergence of the boundaryless career concept in SCM, as the SCM career appears less dependent on a single employer. From the data emerged six major career satisfiers and seven major career dissatisfiers. Challenge is the most satisfying aspect of a SCM career. Challenge, however, may have limits, as the most dissatisfying aspect of a SCM career is the overload that can overwhelm a SCM professional in his or her career.

Career satisfaction can be readily measured and categorized to explain SCM career expectations and choices that may lead to positive or negative work outcomes. Supply chain managers could utilize the information to understand employee perceptions and behaviors that may influence performance and to contend with disruptive career shifts and looming talent shortages in SCM.

This paper introduces contemporary career theory concepts and is a first of its kind in the field that explores attitudes and perceptions toward careers in SCM, as it focuses on career satisfiers and dissatisfiers described by SCM professionals.

The purpose of this paper is to present a newly developed scale useful for measuring supply chain security culture (SCSC), defined as the overall organizational philosophy that creates supply chain security as a priority among its employees through embracing and projecting norms and values to support secure activities and to be vigilant with security efforts.

The approach to developing a scale for SCSC follows the steps presented by Churchill. This includes conducting steps such as: generating items, establishing face and content validity, conducting a pretest to refine items, and validating the scale through an additional data collection so reliability, convergent, discriminant, and predictive validity can be evaluated.

The process yielded a unidimensional, five‐item scale with strong psychometric properties. Through empirical verification, this scale is shown to exhibit high levels of reliability and validity.

Organizational culture has been a construct of interest in social science research for many years. The new phenomenon of supply chain security has been recently introduced to academics and practitioners. Thus, the presented scale has applications for theory and practice. Limitations of the study include allowing one error term to correlate in the SCSC scale and the resiliency scale, a somewhat low response rate, and no ability to test for common method variance bias.

Practitioners will find the presented scale useful in gauging the culture of their respective organizations in terms of supply chain security. A security focused culture is important for organizations to protect their supply chain.

The paper provides a useful measurement tool for use in future research addressing the social aspects of security management within the supply chain context.

This paper seeks to present a framework depicting the development of information power‐based relationships between firms, and to describe the effect of information power on long‐term relationships between supply chain partners.

This conceptual paper combines literature from the field of information sciences regarding information integration with literature addressing traditional power relationships to develop a set of propositions describing how interfirm relationships evolve.

The conceptual framework introduced indicates that information can be utilized as a coercive and non‐coercive power base in supply chain relationships.

The need for information may result in a firm utilizing either coercive or non‐coercive power as a means of obtaining it. This research provides interesting findings about the use of information, as a power base, and its role in interfirm relationships.

This paper combines literature from various fields to develop a needed conceptual model of information power roles within supply chain relationships.

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.

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.

The importance of truck driver satisfaction attributes was analyzed using bivariate correlation analysis as well as MD scaling analysis. The two sets of results are compared and contrasted. The resulting rank order of attributes is very different and MD scaling results are shown to possess important advantages. As a result of this analysis, MD scaling analysis allows for meaningful, need‐based segmentation analysis, resulting in two unique need‐based driver segments.

From a practitioner viewpoint, knowing which attributes are most important will help in investing scarce resources to improve decision making and raise a firm's ROI. Although a number of relevant applications exist, the most important may include examining: the importance of customer service attributes; the importance of logistics service quality attributes; and the importance of customer satisfaction attributes.

MD scaling is a relatively new research technique, a technique that has yet to be utilized or even explored in existing logistics and supply chain literature. Yet, evidence is mounting in other fields that suggest this technique has many important and unique advantages. This paper is the first overview, discussion, and application of this technique for logistics and supply chain management and creates a strong foundation for implementing MD scaling in future logistics and supply chain management research.

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.

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 selecting logistics services.

In order to demonstrate this research technique, a research project was designed and implemented that analyzed the choice process of consumers selecting parcel carriers to ship a textbook. The results show that price, speed of delivery, and tracking are the three most important variables in the selection decision. The results also show that consumers are not homogeneous, but can be divided into five distinct need‐based segments. Recognizing and understanding the nature of these segments should help managers better meet the needs of parcel shippers.

The main research limitation with this study is that it is based on a convenience sample; thus future research will need to replicate this study to confirm the research findings. However, the ultimate purpose of the study is to present a new research method and discuss how to apply this method, so that logistics/SCM practitioners and academic researchers can better understand customers of logistics/SCM services. Thus, while the nature of the sample is a limitation, it should be viewed in this context.

While conjoint analysis has existed for decades, this technique has rarely been implemented by logistics/SCM researchers and practitioners. Instead, logistics/SCM researchers and practitioners have focused more on retention methods and have virtually ignored modelling the actual purchase choice of logistics/SCM services. New advancements in conjoint analysis, specifically the ACM approach, have many important and unique advantages and applications for logistics/SCM researchers and practitioners. ACM has not been used in a logistics/SCM context.

Supply chain security (SCS), as a component of an organization's overall supply chain risk management strategy, has become a critical factor for businesses and government agencies since September 11, 2001, yet little empirical research supports policy or practice for the field. Therefore, this paper develops and presents a categorization of SCS based on existing research. This categorization of supply chain literature can help academics and practitioners to better understand SCS and also helps to identify a research agenda. Setting a research agenda for SCS will help academic and practitioner research focus on critical issues surrounding SCS.

The researchers thoroughly reviewed the literature on SCS, including academic publications, white papers, and practitioner periodicals. The literature was then categorized according to the approach to SCS and the practical implications of this categorization are presented. In addition, this categorization was used to identify research gaps.

This analysis found that SCS needs more attention from the academic community. Like earlier assessments of this literature, this analysis found it to be mainly normative, with little research based on primary data. This paper categorizes the literature into four approaches to SCS: intraorganizational, interorganizational, a combination of intraorganizational and interorganizational, and ignore. This study develops a focused agenda for future, primary, empirical research on SCS.

The sources of data for this literature review are secondary. The review sets a research agenda and calls for future empirical testing.

Practitioners will benefit from the framework presented here by better understanding approaches to SCS. This comprehensive review discusses the characteristics of SCS in great depth. As other researchers follow the research agenda, practitioners will benefit from the empirical findings and theory building.

This paper summarizes the literature on SCS to date, a topic that has grown in importance, yet received little attention from academics. This is the first comprehensive literature review of SCS. It includes a categorization of four possible approaches to SCS. It also distinguishes SCS from supply chain risk, while also recognizing their relationship. It identifies key issues in SCS research and calls for future research.

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.

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.

The results show there are four different need‐based driver segments, which means that specific driver retention programs must be developed for each segment.

The major limitation of this paper is that an attitudinal measure (intent to stay) was used to assess turnover instead of actual behavior. Additionally, only one demographic variable was collected. Implications of this paper include demonstrating the existence of unique segments within the same sample; the specification of the major attitudinal drivers for each segment; and the need to further study a largely neglected but very important group in the supply chain.

From a practitioner viewpoint, knowing that different groups of owner operators exist will help in developing programs to improve driver retention. Specific recommended actions for each segment are presented. These results will help managers with the retention of owner operators.

Owner operators are an important group when it comes to making the global supply chain function smoothly and efficiently. Yet, little research in logistics and SCM address this group. Driver turnover continues to plague the TL industry and understanding owner operators, and their segments, is critical to improve driver retention, cost structure, and profitability. Also, to determine if segments of this under‐researched group exist, LCR was deployed.