Editorial: How to deal with the human factor in supply chain management?

Hoberg, Kai; Thornton, La Donna; Wieland, Andreas

doi:10.1108/ijpdlm-10-2019-0311

Cited by 10 publications

(7 citation statements)

References 25 publications

(29 reference statements)

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“…Potentially with greater scope, big data applications for cross-industry supply chain processes in the circular economy are worth exploring (Tseng et al 2018). Third, the role of human dealing with big data in supply chains need to be better understood (Hoberg, Thornton, and Wieland 2020). While many decisions have the potential for automation, humans will continue to perform many tasks in interaction with the systems and will be ultimately responsible for the decision-making process.…”

Section: Resultsmentioning

confidence: 99%

Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector

Viet

Behdani

Bloemhof-Ruwaard

et al. 2020

International Journal of Production Research

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While many supply chain decisions could take advantage of big data, firms struggle with investments into supply chain analytics since they are not able to assess the application areas and benefits of these initiatives. In this paper, we provide a multi-level perspective to assess the value of supply chain data. We develop a framework that highlights the connections between data characteristics and supply chain decisions with different time horizons (i.e. short-or long-term) as well as different supply chain levels (i.e. individual-firm level or supply-chain level). As data gets more complex in one or more of the 4 V dimensions (i.e. volume, variety, velocity, veracity), firms must assess how to best take advantage of the opportunities offered. We use the Dutch floriculture sector as a case study for our framework in which we highlight four data analytics applications to improve logistics processes. In the applications, we demonstrate how the data is used to support the decisions at different time horizons and supply-chain levels. We find that each of the big data's Vs is required differently according to the decisions' characteristics. Based on the findings, applications in other industries and promising directions for future research are discussed.

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Section: Resultsmentioning

confidence: 99%

Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector

Viet

Behdani

Bloemhof-Ruwaard

et al. 2020

International Journal of Production Research

Self Cite

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“…For research on SPSM from an individual view, being one of the first studies on the nature of SPSM competences for individual purchasing professionals, this paper adds the sustainability perspective, focusing on both the social and environmental aspects of sustainability, to complement existing research on individual PSM and SCM competences (Flöthmann et al 2018;Giunipero et al 2006;Giunipero and Pearcy 2000;Hoberg et al 2020;Hohenstein et al 2014). Besides a mere adding of SPSM competences to existing framework proposals, the nature of the SPSM competences that resulted from this study may drive a discussion in the academic field as to how SPSM competences are related to a future competence profile for PSM professionals.…”

Section: Discussionmentioning

confidence: 99%

A sustainable sourcing competence model for purchasing and supply management professionals

2022

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In order to implement sustainability standards in practice, capabilities are needed at the organizational level as well as at the individual level. The presented sustainable purchasing and supply management (SPSM) competence model is based on the combination of a systematic literature review (SLR) and a Delphi study. The competence model outlines specific SPSM competences which are divided into functional-oriented, cognition-oriented, social-oriented and meta-oriented competence clusters. We also discuss their applicability during typical purchasing and supply management processes. Each of the 26 competences is presented with a short definition as well as exemplary behaviors. For research on SPSM from an organizational point of view, the analysis of the relevance of competences with regard to purchasing process stages offers a conceptual basis for bringing sustainability into overall PSM models, instead of positioning sustainability as an ‘add-on’ activity, which risks the potential of sustainability issues becoming marginalized. The resulting SPSM competence model can serve as a basis for improving teaching and training in both higher education and professional training contexts. In practice, it can also serve to aid the selection of new employees, evaluate employee performance, create development plans or build HR systems.

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“…Autonomizing such processes will have direct implications for the workforce and raise various questions that have not yet been adequately investigated. Several authors already highlighted the significance of the human factor in the introduction of AI systems (Dora et al, 2022;Dwivedi et al, 2021;Hoberg et al, 2020;Klumpp and Ruiner, 2022). However, most current research focuses on the technical implementation of specific UCs, as demonstrated in the literature reviews by Pournader et al (2021), Riahi et al (2021) and Toorajipour et al (2021).…”

Section: Managerial and Societal Implicationsmentioning

confidence: 99%

“…Autonomizing such processes will have direct implications for the workforce and raise various questions that have not yet been adequately investigated. Several authors already highlighted the significance of the human factor in the introduction of AI systems (Dora et al, 2022;Dwivedi et al, 2021;Hoberg et al, 2020;Klumpp and Ruiner, 2022) In highly digitalized and partially autonomous supply chains, the competence profiles of logistics managers will need to change. It is currently unclear to what extent systems can run autonomously or when employees will need to intervene in systems whose decision-making processes can only be understood to a limited extent.…”

Section: Managerial and Societal Implicationsmentioning

confidence: 99%

“…It is currently unclear to what extent systems can run autonomously or when employees will need to intervene in systems whose decision-making processes can only be understood to a limited extent. Consequently, Hoberg et al (2020) point out that, despite technological advancements, it is unlikely that human decision-making will ever be completely eliminated. For the supply chains of the future, Hoberg et al (2020) favor a combination of the unique capabilities of human decision-makers with AI-based guidance to enable complex problem-solving.…”

Section: Managerial and Societal Implicationsmentioning

confidence: 99%

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The impact of multiagent systems on autonomous production and supply chain networks: use cases, barriers and contributions to logistics network resilience

Nitsche

Brands

Treiblmaier

et al. 2023

SCM

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Purpose Academics and practitioners have long acknowledged the potential of multiagent systems (MAS) to automate and autonomize decision-making in logistics and supply chain networks. Despite the manifold promises of MAS, industry adoption is lagging behind, and the exact benefits of these systems remain unclear. This study aims to fill this knowledge gap by analyzing 11 specific MAS use cases, highlighting their benefits, clarifying how they can help enhance logistics network resilience and identifying existing barriers. Design/methodology/approach A three-stage Delphi study was conducted with 18 industry experts. In the first round, these experts identified 11 use cases of MAS and their potential benefits, as well as any barriers that could hinder their adoption. In the second round, they assessed the identified use cases with regard to their potential to enhance logistics network resilience and improve organizational productivity. Furthermore, they estimated the complexity of MAS implementation. In the third round, the experts reassessed their evaluations in light of the evaluations of the other study participants. Findings This study proposes 11 specific MAS use cases and illustrates their potential for increasing logistics network resilience and enhancing organizational performance due to autonomous decision-making in informational processes. Furthermore, this study discusses important barriers for MAS, such as lack of standardization, insufficient technological maturity, soaring costs, complex change management and a lack of existing use cases. From a theoretical perspective, it is shown how MAS can contribute to resilience research in supply chain management. Practical implications The identification and assessment of diverse MAS use cases informs managers about the potential of this technology and the barriers that need to be overcome. Originality/value This study fills a gap in the literature by providing a thorough and up-to-date assessment of the potential of MAS for logistics and supply chain management. To the best of the authors’ knowledge, this is the first study to investigate the relevance of MAS for logistics network resilience using the Delphi method.

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Editorial: How to deal with the human factor in supply chain management?

Cited by 10 publications

References 25 publications

Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector

Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector

A sustainable sourcing competence model for purchasing and supply management professionals

The impact of multiagent systems on autonomous production and supply chain networks: use cases, barriers and contributions to logistics network resilience

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