The purpose of this paper is to provide an overview of the current state of research and the key aspects and implications of the relationships between Information and Digital Technologies (IDT) of Industry 4.0 and Lean Supply Chain Management (LSCM), with the identification of the lines of research developed and an analysis of the main findings. A Systematic Literature Review methodology has been used for the identification, selection, and evaluation of the published research. A set of 78 papers deduced from the most relevant scientific databases, including Web of Science, Scopus, and ABI/Inform, from 1996 to December 2019, has been analyzed and synthesized. The analysis and evaluation of these papers has enabled a new classification of the literature to be offered that identifies four lines of research based on the Life Cycle of Technology: obsolete IDT in LSCM; mature IDT in LSCM; emerging IDT in LSCM; and an Information Systems and IDT general approach in LSCM. The paper goes on to discuss the gaps found in the literature and proposes new opportunities and challenges for future research. A series of implications are presented intended to be useful from not only an academic point-of-view but also from a management focus, including recommendations for industrial managers and policymakers.
1 March 2019 in Computers & Industrial Engineering
It is widely argued that to be competitive, a company not only needs to focus on internal aspects but on the entire supply chain. Lean supply chain management has become a means of enhancing competitiveness by improving efficiency and increasing flexibility at all stages of the supply chain. This research develops and validates a lean supply chain management measurement instrument. A two-phase approach is used for scale development and refinement. In the first phase, a literature review is conducted to identify definitions of lean supply chain management and agile supply chain management and their corresponding measurement items. In the second phase, the lean supply chain management measurement instrument is validated using survey data based on scales developed in the first phase by 59 scholars with experience in lean management and/or supply chain management. The results provide a structured and comprehensive measure of lean supply chain management indicating that there are two differentiated dimensions in the measurement instrument: one related to the operational aspects of lean supply chain strategy implementation and the second related to lean supply chain planning.
8 October 2018 in International Journal of Production Research
Cloud Computing are innovative technologies that are being applied in the main business functions in the supply chain. This study aims to reveal the determinant factors (drivers and a relevant outcome) of the level of use or assimilation of Cloud Computing in the supply chain. In order to test three hypotheses we conducted an empirical study in 484 companies from sectors in an intermediate position in the supply chain. The data gathering method consisted of a telephone survey using a computerised system (CATI). We used structural equation modelling (SEM) to test the hypotheses. The empirical study reveals that Advanced Manufacturing Technologies pursuing the internal efficiency of the supply chain (Intra-organisational IT) and IT for capabilities in e-business/e-commerce seeking external connection of the supply chain with other companies (Inter-organisational IT) are drivers of Cloud Computing assimilation. Furthermore, supply chain integration is one of the major consequences of Cloud Computing assimilation in the supply chain.
28 July 2020 in International Journal of Production Research
This article examines how the research into Lean Supply Chain Management (LSCM) has evolved over the period 1996–2018 with the identification of the main issues explored and future trends. A performance bibliometric analysis has been conducted through a study of published documents, citations, journal impact factor, h-index, most cited papers and authors, and data on the geographic distribution of publications. More relevantly, a science mapping analysis has been performed with SciMAT bibliometric analysis software using co-word networks in a longitudinal overview. The large number of studies of LSCM published has enabled a conceptual evolution map to be constructed of the way that this research has developed. The results have enabled us to identify four thematic areas in the LSCM field: Methods, Key factors, Internal efficiency, and Performance.