Data supply chain (DSC): research synthesis and future directions

Abstract

In the digital economy, the volume, variety and availability of data produced in myriad forms from a diversity of sources has become an important resource for competitive advantage, innovation opportunity as well as source of new management challenges. Building on the theoretical and empirical foundations of the traditional manufacturing Supply Chain (SC), which describes the flow of physical artefacts as raw materials through to consumption, we propose the Data Supply Chain (DSC) along which data are the primary artefact flowing. The purpose of this paper is to outline the characteristics and bring conceptual distinctiveness to the context around DSC as well as to explore the associated and emergent management challenges and innovation opportunities. To achieve this, we adopt the systematic review methodology drawing on the operations management and supply chain literature and, in particular, taking a framework synthetic approach which allows us to build the DSC concept from the preexisting SC template. We conclude the paper by developing a set of propositions and outlining an agenda for future research that the DSC concept implies.

Digital data and management accounting: why we need to rethink research methods

“…This is because digital data are "more evenly distributed across the span of collective existence of which they therefore offer a more continuous appraisal" (Rogers 2013: 4). Management scholars have pointed to the handling of big data and how analytical tools provided by data science can be adapted and altered to not only seek better answers to existing questions but also for posing new questions (George et al 2016;Kuo and Kusiak 2019;Mikalef et al 2018;Spanaki et al 2018;Tonidandel et al 2018). What may be derived from research using larger volumes of data that emerges faster than ever before and which is more varied in structure whilst also offering specific characteristics such as time-stamping and chronology, goes beyond what has been empirically available to us.…”

Knowledge Risks in Digital Supply Chains: A Literature Review

“…Information systems (IS) improved during the 1990s and demand information have already been shared along the SC at this time, in a controllable and manageable manner [10]. As it can be seen, data has been exchanged for decades, but data as a primary reason of interest within the SC is relatively new [11]. The digital transformation is seen as a process that induces digital technologies which, in further consequence, lead to disruptions [7].…”

“…Additionally, there is a security and privacy risk, which increases with the dependency on IT, e.g. [36], [24], [51], [11].…”

Access Control and Quality Attributes of Open Data: Applications and Techniques

“…Mostly, the data manufacturing analogy was focusing on data quality and the ways to ensure that we can trust the data we use in manufacturing processes. Recent studies in data quality research, apply the data manufacturing analogy, in order to explain the tailoring techniques and the potential of data marketplaces within the context of supply chain [12,30].…”