Barriers and Opportunities In Cyber Risk And Compliance Management For Data-Driven Supply Chains

Purpose In spite of growing research interest in cyber security, inter-firm based cyber risk studies are rare. Therefore, this study aims to investigate cyber risk management in supply chain contexts. Design/methodology/approach Adapting a systematic literature review process, papers from interdisciplinary areas published between 1990 and 2017 were selected. Different typologies, developed for conducting descriptive and thematic analysis, were established using data mining techniques to conduct a comprehensive, replicable and transparent review. Findings The review identifies multiple future research directions for cyber security/resilience in supply chains. A conceptual model is developed, which indicates a strong link between information technology, organisational and supply chain security systems. The human/behavioural elements within cyber security risk are found to be critical; however, behavioural risks have attracted less attention because of a perceived bias towards technical (data, application and network) risks. There is a need for raising risk awareness, standardised policies, collaborative strategies and empirical models for creating supply chain cyber-resilience. Research limitations/implications Different types of cyber risks and their points of penetration, propagation levels, consequences and mitigation measures are identified. The conceptual model developed in this study drives an agenda for future research on supply chain cyber security/resilience. Practical implications A multi-perspective, systematic study provides a holistic guide for practitioners in understanding cyber-physical systems. The cyber risk challenges and the mitigation strategies identified support supply chain managers in making informed decisions. Originality/value To the best of the authors’ knowledge, this is the first systematic literature review on managing cyber risks in supply chains. The review defines supply chain cyber risk and develops a conceptual model for supply chain cyber security systems and an agenda for future studies.

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Leveraging Digital Approaches for Transparency in Sustainable Supply Chains: A Conceptual Paper

Sustainability ◽

10.3390/su12156129 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6129

Author(s):

Frank Ebinger ◽

Bramwel Omondi

Keyword(s):

Supply Chain ◽

Supply Chains ◽

Data Driven ◽

Sustainable Supply Chain ◽

Current Application ◽

Chain Management ◽

Sustainable Supply Chains ◽

Conceptual Paper ◽

And Control ◽

Trial Phase

With the growing global interdependence of companies, their scope of responsibility for the environmental, social, and human rights impacts associated with their activities is also growing. In this context, companies are increasingly held accountable for social and ecological issues that lie within the sphere of action of their suppliers and sub-suppliers. They are thus faced with the challenge of meeting these demands for transparency, traceability, and compliance with standards in their Supply Chains (SCs). Based on the theoretical framework of Sustainable Supply Chain Transparency (SSCT) in Sustainable Supply Chain Management (SSCM), this conceptual article aims at initiating the discussion on digitalization in SSCM. Therefore, a heuristical research framework, based on relevant fields in the management of sustainability oriented transparency (governance, cooperation and partner selection, traceability/tracking, and strategic and operational risk assessment) is developed. In relation to these fields, consequently, data-driven digital approaches are identified to which potentials for SSCT and control can be attributed. This initial analysis of existing digital approaches already shows that the market is developing dynamically, but is driven more by individual initiatives. In many cases, the approaches used so far are still in the trial phase or offer only limited solutions. Therefore, this paper contributes by giving an overview of the current application of the digitalization approaches in SSCM pinning our discussion on SSCT dimensions.

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Data-driven productivity improvement in machinery supply chains

International Journal of Mechatronics and Manufacturing Systems ◽

10.1504/ijmms.2019.103483 ◽

2019 ◽

Vol 12 (3/4) ◽

pp. 255

Author(s):

Rafael Lorenz ◽

Torbjørn H. Netland ◽

Philip Roh ◽

Valentin Holzwarth ◽

Andreas Kunz ◽

...

Keyword(s):

Supply Chains ◽

Data Driven ◽

Productivity Improvement

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Data-driven supply chains, manufacturing capability and customer satisfaction

Production Planning & Control ◽

10.1080/09537287.2017.1336788 ◽

2017 ◽

Vol 28 (11-12) ◽

pp. 906-918 ◽

Cited By ~ 24

Author(s):

Roberto Chavez ◽

Wantao Yu ◽

Mark A. Jacobs ◽

Mengying Feng

Keyword(s):

Customer Satisfaction ◽

Supply Chains ◽

Data Driven ◽

Manufacturing Capability

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Incentivizing Environmental Improvements in Supply Chains through Data-Driven Governance

California Management Review ◽

10.1177/00081256211049827 ◽

2021 ◽

pp. 000812562110498

Author(s):

Dara O’Rourke ◽

Niklas Lollo

Keyword(s):

Supply Chains ◽

Global Value Chains ◽

Data Driven ◽

Value Chains ◽

Environmental Measurement ◽

Measurement Systems ◽

Environmental Improvements ◽

Governance Systems ◽

New Strategy

The Sustainable Apparel Coalition’s Facility Environmental Module (FEM) is one of the world’s most advanced “data-driven governance” initiatives. The FEM represents an important new strategy in the governance of Global Value Chains. This article reports on a multi-year study to evaluate how firms have implemented the FEM, and whether and under what conditions it leads to improvements in factory performance. It finds that while the FEM represents an important step in improving environmental measurement systems, the program currently acts like a “scale without a diet.” Companies are now better able to measure performance, but many have not implemented the mechanisms needed to motivate systematic improvements. This article offers recommendations for how to strengthen data-driven governance systems and explores their implications for managers.

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Data-driven and adaptive leadership contributing to sustainability: global agri-food supply chains connected with emerging markets

International Journal of Production Economics ◽

10.1016/j.ijpe.2015.11.013 ◽

2016 ◽

Vol 181 ◽

pp. 392-401 ◽

Cited By ~ 36

Author(s):

Pervaiz Akhtar ◽

Ying Kei Tse ◽

Zaheer Khan ◽

Rekha Rao-Nicholson

Keyword(s):

Emerging Markets ◽

Supply Chains ◽

Food Supply ◽

Adaptive Leadership ◽

Data Driven ◽

Food Supply Chains

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Taxonomy of organizational alignment: implications for data-driven sustainable performance of firms and supply chains

Journal of Enterprise Information Management ◽

10.1108/jeim-02-2020-0046 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Jose Celso Contador ◽

Walter Cardoso ◽

Jose Luiz Contador ◽

Mauro de Mesquita Spinola

Keyword(s):

Supply Chains ◽

Strategic Alignment ◽

Structure Alignment ◽

Data Driven ◽

Content Type ◽

Sustainable Performance ◽

Strategic Value ◽

Strategy Alignment ◽

Alignment Structure ◽

Definition Of

PurposeThe purpose of this paper is to identify, characterize, classify and conceptualize different perspectives on strategic alignment still in use, propose a taxonomy and definitions that allow understanding the various coexisting concepts, as well as investigate the implications of strategic alignment for data-driven sustainable performance of firms and supply chains.Design/methodology/approachBibliographic review was used.FindingsThe taxonomy proposes two classes of strategic alignment: (1) Align – more rigorous types of alignment: structure alignment, strategic congruence and strategy alignment; (2) Fit – less rigorous types of alignment: contingency strategic adjustment, strategic coalignment and strategic consistency. Companies are accumulating large amounts of data, which relevance varies widely. The strategic alignment can define criteria to select only the data that have strategic value, which restricts the amount of data to be analyzed. Each of the six types of strategic alignment is appropriate for a given situation in companies and/or supply chains.Research limitations/implicationsThe limitations stem from the exclusive use of the taxonomy of strategic alignment, without considering the most diverse perspectives of strategy.Practical implicationsDecision makers will be able to identify more objectively which classes of data should be explored in each situation.Social implicationsTheoretical implications – The taxonomy proposal and the definition of each of the strategic alignment perspectives solve generalized misunderstandings resulting from the lack of a clear delimitation between the perspectives and the conceptual divergence between authors, who use them as equivalent or synonymous.Originality/valueFrom 1961 to 2019, no paper was found proposing taxonomy, typology, systematization, ranking, distribution or classification of strategic alignment. The strategic alignment can define criteria to select, within the large amount of data accumulated by the company, only those that have strategic value, what restricts the quantity of data to be analyzed and facilitates the decision of the leaders.

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