Data and Predictive Analytics Use for Logistics and Supply Chain Management

Purpose The 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/approach The 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. Findings Findings 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 implications This 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/value The 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

Investigating the Effects of Daily Inventory Record Inaccuracy in Multichannel Retailing

Inventory record inaccuracy (IRI) challenges multichannel retailers in fulfilling both brick-and-mortar and direct channel demands from their distribution centers. The nature and damaging effects of IRI largely go unnoticed because retailers assume daily IRI remains stable over time within the replenishment cycle. While research shows that a high level of IRI is damaging, in reality the level of IRI can change every day. We posit that daily IRI variation increases the uncertainty in the system to negatively affect inventory and service levels. Our research uses data collected daily from a multichannel retailer to ground a discrete-event simulation experiment. Going beyond testing just the level of IRI, we evaluate daily IRI variation\u27s impact on operating performance. What we find in our empirical data challenges extant assumptions regarding the characteristics of IRI. In addition, our simulation results reveal that daily IRI variation has a paradoxical effect: it increases inventory levels while also decreasing service levels. Moreover, we also reveal that brick-and-mortar and direct channels are impacted differently. Our findings show that assumptions and practices that ignore daily IRI variation need revising. For managers, we demonstrate how periods of multiday counting help assess their daily IRI variation and indicate what the causes may be

Customer use of virtual channels in multichannel services: does type of activity matter?

Many firms have recently adopted virtual channels, based most notably on the Internet and the phone, to complement the delivery of services to their customers by their existing physical facilities. The success of such multichannel (MC) strategies relies on the alignment of service design decisions—namely those concerning the allocation of service activities to virtual channels—with customers’ MC behavior. Although prior studies have looked at the intensity with which customers use virtual channels, they have not addressed virtual channel use for different types of service activities. In our study, we investigate whether customers’ use of virtual channels for MC services varies with the type of service activities they engage in, and if so, in what way. In doing so, we address two objectives. First, we investigate the impact of accessibility to the physical channel on the degree of use of virtual channels (Internet and phone, aggregated) for different types of activities. Second, we look at channel preferences (Internet vs. phone) for different types of activities when customers do resort to virtual channels to conduct activities. To address our objectives, we develop and test hypotheses regarding customers’ use of virtual channels based on the match between activity attributes (complexity and volume)and channel attributes (access efficiency, interface efficiency, interface richness). Using data from a MC bank, we find that the impact of accessibility to physical channels (specifically, customer distance) on customers’ use of virtual channels, as well as the relative use of Internet versus phone, depend on the type of activities. [Submitted: February 26, 2013. Revised: January 23, 2014. Accepted: January 30, 2014.]info:eu-repo/semantics/publishedVersio