Purpose Journals 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/approach A 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. Findings This 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/implications This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research. Practical implications Supply 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/value There 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.

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Supply chain management (SCM) plays a major role in creating (or destroying) shareholder value by influencing the three major drivers of firm financial performance: revenue, operating costs, and working capital. Yet, the relationship between SCM competency and firm financial performance is not well‐established. Drawing on the resource‐based view of the firm, this study assesses this relationship using Delphi‐style opinion data from AMR Research’s Supply Chain Top 25 rankings to assess SCM competency and Altman’s (1968)Z‐score statistic as the measure of financial success. The study findings show that firms recognized by industry experts for SCM competency have significantly higher Z‐scores than their close competitors and industry averages.

Purpose This research study aims to investigate consumer usage motivations for three of the top social media platforms today: Facebook, Twitter and Instagram. Additionally, through understanding various platform distinctions, firms can understand which social media platforms consumers prefer to use to co-create with brands online. Design/methodology/approach An exploratory qualitative study is first conducted to understand consumer motivations for using different social media platforms. The main study tests five hypotheses related to consumer usage intentions and social media co-creation behavior across three social media platforms. A survey is conducted with 1,050 social media users with a comparison of mean responses using multivariate analysis of covariance. Findings Results support significant differences between platforms in terms of use and co-creation behaviors. For informational purposes, consumers gravitate toward Twitter. For social purposes, Twitter and Instagram are preferred. Instagram is the primary platform for entertainment motivation as well as co-creating with brands via social media. Surprisingly, Facebook shows the lowest usage intentions and co-creation despite being the largest platform and network most widely used by marketers. Originality/value To the best of the authors’ knowledge, this is one of the first studies to take a multi-platform approach to understanding consumer social media use and co-creation with brands. The results highlight that marketing academics and practitioners must segment the various social media platforms as each offers unique value propositions to consumers.

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The relationship between supply chain management (SCM) competency and firm performance is not well established empirically. This is largely because proven metrics for quantifying the effects of SCM are scarce. Drawing on the strategic managerial concept of supply chain orientation as a source of competitive advantage, this paper aims to apply three independent sources of secondary data to examine the influence of SCM competency on two important firm performance metrics: customer satisfaction and shareholder value. Design/methodology/approach -SCM competency is assessed with data from the expert opinion element of Gartner Supply Chain Group's (formerly AMR Research) supply chain top 25 rankings; the American Customer Satisfaction Index (ACSI) database and the recently developed Economic Value Added (EVA) Momentum financial metric are utilized as outcome measures. Findings -Firms recognized by peers and experts for superior SCM competency exhibit higher levels of customer satisfaction and shareholder value than their respective industry averages. Research limitations/implications -Further evidence is required to prove causality does exist between these variables. Limitations associated with the use of secondary data restricted the number of top performer firms available for this analysis. Nevertheless, the strong correlations found between SCM competency and two critical firm performance metrics may help senior managers and managers from other functional areas to better understand potential advantages associated with developing greater SCM competency. Practical implications -The assessment of two metrics that differentiate top SCM performers from their industry competitors may also help SCM professionals to better convey the impact of SCM competency to non-supply chain managers and external participants in the supply chain whose support and cooperation are critical to the success of process improvement initiatives. Originality/value -In addition to the study findings, blending qualitative expert opinion, formal customer satisfaction and quantitative financial performance secondary data represents a relatively novel and informative method that responds to contentions that...