Christopher A. Boone

Postponement: an evolving supply chain concept

Purpose – The purpose of this paper is to assess and document the progress of postponement research, identify current gaps, and provide direction for future research efforts.Design/methodology/approach – Postponement literature published from 1999 to 2006 was reviewed.Findings – The review revealed a significant increase in the number of postponement research efforts, many of which at least partially addressed past challenges noted in previous research. Several opportunities to continue addressing these past challenges were identified. Future researchers are challenged to validate new postponement concepts and extend postponement research beyond its manufacturing context. Other challenges call for the continued assessment of the relationship between postponement and uncertainty and the investigation into the slow rate of postponement adoption among practitioners.Research limitations/implications – This effort is not an exhaustive review of all postponement research. This review does not consider unpublish...

Suggested reporting guidelines for structural equation modeling in supply chain management research

Purpose – Structural equation modeling (SEM) is a data analysis method of choice for many empirical supply chain management (SCM) researchers. As the statistical technique has evolved, so have its applications and reporting guidelines. Consequently, there has been a lack of standardized reporting across the SCM literature. The purpose of this paper is to provide a basis for standardizing reporting conventions. Design/methodology/approach – This paper presents a review of recent SEM methods literature. In addition, the authors content analyze articles from International Journal of Logistics Management, International Journal of Physical Distribution and Logistics Management, and Journal of Business Logistics that contained either covariance-based or partial least square structural equation models. Using the aforementioned literature review and content analysis, the authors compare and contrast what is currently reported in extant supply chain literature with suggested reporting protocols in the methods lite...

Big data and predictive analytics for supply chain sustainability

Big data/predictive analytics (BDPA) impacts financial/strategic performance in SCM.We suggest that BDPA can also be used to enhance and enable sustainable SCM.We review extant theories that can inform research in this area.A theory-based research agenda is proposed. Big data and predictive analytics (BDPA) tools and methodologies are leveraged by businesses in many ways to improve operational and strategic capabilities, and ultimately, to positively impact corporate financial performance. BDPA has become crucial for managing supply chain functions, where data intensive processes can be vastly improved through its effective use. BDPA has also become a competitive necessity for the management of supply chains, with practitioners and scholars focused almost entirely on how BDPA is used to increase economic measures of performance. There is limited understanding, however, as to how BDPA can impact other aspects of the triple bottom-line, namely environmental and social sustainability outcomes. Indeed, this area is in immediate need of attention from scholars in many fields including industrial engineering, supply chain management, information systems, business analytics, as well as other business and engineering disciplines. The purpose of this article is to motivate such research by proposing an agenda based in well-established theory. This article reviews eight theories that can be used by researchers to examine and clarify the nature of BDPAs impact on supply chain sustainability, and presents research questions based upon this review. Scholars can leverage this article as the basis for future research activity, and practitioners can use this article as a means to understand how company-wide BDPA initiatives might impact measures of supply chain sustainability.

Supply chain management technology: a review of empirical literature and research agenda

The interest in Supply Chain Management (SCM) related technologies continues to garner interest from a variety of research disciplines. However, the varied disciplines and perspectives from which SCM Technology (SCMT) research arises complicates the efforts of those seeking to develop a comprehensive understanding of the subject. This effort provides a multidisciplinary review of the extant literature and assesses the progress of SCMT research. Using a rigorous content analysis-based approach, multiple reviewers identified and categorised 82 empirical SCMT-related articles appearing in highly rated journals from one of three research fields: Operations Management (OM), logistics and Information Systems (IS). Each of the identified articles was categorised according to the methodology, stage of theoretical development and research focus. The progress of SCMT research within each of these areas is discussed and opportunities for the continued development and extension of the body of knowledge are presented.

Investigating logistics service quality in omni-channel retailing

The purpose of this paper is to investigate the impact of logistics service quality (LSQ) on consumer satisfaction and loyalty in an omni-channel retail environment.,An empirical, survey-based approach is used to collect data from consumers about experiences with two different omni-channel retail scenarios: buy-online-pickup-in-store (BOPS), and buy-in-store-ship-direct (BSSD). Participants responded to questions regarding the LSQ, consumer satisfaction, and consumer loyalty relative to their actual experience in one of these situations.,Results suggest that omni-channel consumers are truly unique, and all three dimensions of LSQ (condition, availability, and timeliness) are distinct in their impact on satisfaction and loyalty. Results suggest that in the BOPS sample, consumer satisfaction partially mediates the relationship between condition and loyalty and fully mediates the relationship between timeliness and loyalty. In the BSSD model, consumer satisfaction partially mediates the relationship between timeliness and consumer loyalty.,This research studies LSQ in two different omni-channel scenarios; additional research is needed to explore other omni-channel scenarios and extend the findings to be more generalizable.,Managers should recognize that for omni-channel consumers, timeliness is the essential driver of satisfaction and loyalty. Retailers need to account for this reality and dedicate substantial resources to meet delivery requirements in a timely manner. Logistics service providers need to emphasize speed and reliability of their delivery processes for omni-channel consumers.,This research is the first attempt at conceptualizing LSQ in an omni-channel supply chain, and testing the impact of LSQ on consumer satisfaction and loyalty.