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PurposeThe purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology's post-adoption phases in retail supply chain (RSC) organizations.Design/methodology/approachThe authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC.FindingsFindings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations.Practical implicationsThis study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place.Originality/valueThe literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the "how" and bring a social perspective into a technology-centric area.

PurposeThis study follows the tenets of the resource dependence theory (RDT) to investigate the effects of four dimensions of industry-level environmental uncertainty – munificence, dynamism, complexity and innovative intensity – on a shipper's cross-buying (i.e. outsourcing across multiple service categories) in logistics outsourcing arrangements.Design/methodology/approachNegative binomial regression was used to test the hypotheses with a sample of US manufacturers. Measures were developed through information acquired from a proprietary database of 3PL companies obtained through Armstrong and Associates, Inc. and publicly available industry measures from the US Manufacturing Census and Compustat.FindingsThe findings indicate that individual dimensions of environmental uncertainty exhibit distinct influences on shippers' cross-buying in their logistics outsourcing arrangements. Specifically, the growth and initial innovative intensity of shippers' industries lead to an increased number of logistics service categories outsourced to 3PLs, while industry dynamism and exceptionally high innovative intensity drive the opposite effect.Practical implicationsThese findings provide valuable guidance to 3PLs with respect to decisions related to the acquisition of specialized transportation, storage, information systems and personnel assets to serve specific industries. The findings highlight industry conditions that are more likely to lead shippers to outsource across a wider array of logistics service categories and, as a result, potentially yield higher customer retention and profit margins.Originality/valueWhile extant 3PL literature posits that shippers' individual strategic orientations and capabilities impact their outsourcing strategy, this study contributes to the literature by providing a theoretical-based empirical examination of the industry-level influencers of such behavior.

PurposeSupply chain (SC) professionals are increasingly working alongside business partners of diverse backgrounds, which has been argued to engender both innovation and creativity but also found as potentially detrimental to SC relationships and performance. To reconcile these views, this study explores two mechanisms – supplementary (similarity) and complementary fits – at the surface (observable traits) and deep (unobservable characteristics) levels and their impact on a focal firm representative's perception of a SC partner's trustworthiness.Design/methodology/approachModel was tested using survey data from 285 managers involved in interorganizational SC relationships.FindingsResults indicate that a focal firm representative's perception of supplementary and complementary fits with a SC partner positively impacts their perception of the partner's trustworthiness. However, the effects of similarity at both surface and deep levels and complementarity weaken each other.Practical implicationsUnderstanding the mechanisms of diversity in SC relationships is crucial for fostering trustworthiness and achieving organizational objectives. Firms should evaluate both supplementary and complementary fits when hiring or assigning roles. Embracing a complementary fit not only promotes diversity but also mitigates the negative impact of similarity bias, ultimately strengthening trustworthiness within the organization's SC ecosystem.Originality/valueBy simultaneously examining individual and combined effects of two unique mechanisms of supplementarity and complementarity at the surface and deep levels, this study sheds light on inconsistent findings of the effects of diversity in the SCM literature.

Purpose– The accurate measurement of demand variability amplification across different nodes in the supply chain, or "bullwhip effect," is critical for firms to achieve more efficient inventory, production, and ordering planning processes. Building on recent analytical research that suggests that data aggregation tends to mask the bullwhip effect in the retail industry, the purpose of this paper is to empirically investigate whether different patterns of data aggregation influence its measurement.Design/methodology/approach– Utilizing weekly, product-level order and sales data from three product categories of a consumer packaged goods manufacturer, the study uses hierarchical linear modeling to empirically test the effects of data aggregation on different measures of bullwhip.Findings– The authors findings lend strong support to the masking effect of aggregating sales and order data along product-location and temporal dimensions, as well as the dampening effect of seasonality on the measurement of the bullwhip effect.Research limitations/implications– These findings indicate that inconsistencies found in the literature may be due to measurement aggregation and statistical techniques, both of which should be applied with care by academics and practitioners in order to preserve the fidelity of their analyses.Originality/value– Using product-weekly level data that cover both seasonal and non-seasonal demand, this study is the first, to the author's knowledge, to systematically aggregate data up to category and monthly levels to empirically examine the impact of data aggregation and seasonality on bullwhip measurement.

PurposeDespite the important role that suppliers have in enhancing the environmental performance of a buyer firm, previous research has not investigated the individual-level motivations of supplier employees (representatives) in supplier-to-supplier environmental knowledge sharing. Thus, we use insights from the coopetition literature to examine how buyer firms can encourage supplier-to-supplier environmental knowledge sharing with the aim of improving the buyer's environmental performance.Design/methodology/approachWe empirically test our model using an online vignette-based experiment administered to supply chain managers. We contextualized our results using insights from interviews with senior managers representing firms operating in a broad array of industries.FindingsWe find that a supplier representative's personal environmental values influence their commitment to an environmental consortium with a rival firm, and they are subsequently willing to share proprietary environmental knowledge. In turn, these relationships are moderated by situational factors including competitive intensity and buyer power.Originality/valueThe study of coopetition is an emerging stream of research in operations management. Our findings improve the understanding on how a focal actor within a buyer–supplier coopetitive network can promote environmental knowledge sharing behavior.