International Journal of Physical Distribution & Logistics Management

Richey, Robert Glenn; Morgan, Tyler R.; Lindsey-Hall, Kristina; Adams, Frank G.

2016 International Journal of Physical Distribution & Logistics Management

doi: 10.1108/IJPDLM-05-2016-0134

PurposeJournals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data.Design/methodology/approachA native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach.FindingsThis study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research.Research limitations/implicationsThis study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research.Practical implicationsSupply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships.Originality/valueThere is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.

Wichmann, Barbara K.; Kaufmann, Lutz

2016 International Journal of Physical Distribution & Logistics Management

doi: 10.1108/IJPDLM-05-2015-0122

PurposeThe purpose of this paper is to investigate when and how to best use social network analysis (SNA) in the supply chain management (SCM) discipline. In doing so, the study identifies SCM phenomena that have been examined from a social network perspective (SNA approach) in the SCM literature and highlights additional SCM phenomena that would be worth investigating using social network research. Then, the study critically investigates the application of SNA as a methodology (SNA method), with the goal of assessing and mitigating methodological risks in future studies.Design/methodology/approachThis study carries out a systematic literature review of articles published in 11 top-tier SCM journals over a 20-year period.FindingsFirst, while social network research has gained momentum especially since 2010, scholars are not yet entirely aware of the many possibilities the SNA approach offers to the SCM field. Second, expanded possibilities also hold for the development of SNA as a method.Originality/valueThe paper guides future SCM research by investigating when SNA is the right approach to use and how SNA as a method should be performed. Theoretically richer and practically more relevant research should result.

Xu, Yun; Liu, Jiafen; Wu, Jing; Luo, Chuan

2016 International Journal of Physical Distribution & Logistics Management

doi: 10.1108/IJPDLM-10-2015-0255

PurposeThe purpose of this paper is to examine how use of industry standards and community socialization contribute to the operational, strategic and environmental performances of supply chain partners.Design/methodology/approachSurvey data were collected from 216 firms in China that have implemented RosettaNet standards. Structural equation modeling was used to test the hypotheses forming the research model.FindingsThe empirical analysis suggests that use of industry standards and community socialization is central to achieving greater supply chain performances. The results show that the use of industry standards and community socialization enhance inter-organizational knowledge sharing and trust, which eventually improve performances of supply chain partners.Originality/valueThe study makes several contributions to the literature. First, it highlights the importance of standards consortia, which not only develop and promote industry standards, but also improve community socialization. Second, the research examines how use of industry standards could influence the operational, strategic and environmental performances of supply chains, and thus fills the research gap in related literature. Third, this paper explores how industry standards can be used as boundary objects to span organizational boundaries and enable greater supply chain partnerships.

Larsen, Samuel Brüning; Jacobsen, Peter

2016 International Journal of Physical Distribution & Logistics Management

doi: 10.1108/IJPDLM-03-2015-0054

PurposeWhen original equipment manufacturers (OEMs) examine whether to implement a reverse supply chain (RSC) for their products, oftentimes the motive is cost savings or regulatory compliance. However, a frequently overlooked but equally important benefit is the possibility for creating new revenue. The purpose of this paper is to examine which revenue streams the RSC enables for OEMs to utilize and how these streams are utilized in industrial practice.Design/methodology/approachFirst, the paper identifies the RSC-enabled revenue streams that are available to OEMs using a literature-based conceptual modeling approach. Second, using a set of eight cases the paper explores these streams’ utilization pattern and develops a set of propositions that explain the pattern.FindingsResults show a set of 12 distinct RSC-enabled revenue streams within three categories: new revenue through sales of used items, new revenue through sales of recovered items, and new revenue through added sales of virgin products. Six of these 12 streams are utilized in industrial practice. Among the propositions that explain the utilization pattern are the degree of component customization, product life-cycle longevity, and the value gap between used and recovered products.Originality/valueWhile extant literature concerning the relation between the RSC and the firm’s revenue is scarce, this paper contributes to the understanding of RSCs’ revenue generation potential and thus to the stream of literature that views the RSC as a value creator rather than a costly nuisance. Furthermore, the paper provides managers with a broad view of how their firm’s RSC can increase revenue from existing markets as well as create revenue from new markets.