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The impact of an asymmetric allocation of power on the digitalization strategy of port logistics

Janosch Brinker and Hans-Dietrich Haasis

A chapter in Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability, 2020, pp 457-484 from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management

Abstract: Purpose: The objective of this paper is to investigate the impact of the asymmetric allocation of power on the digitalisation strategy in port logistics. To reach this pur-pose this paper combines the term of asymmetric power to the concept of bargaining power, supply chain leadership theory, and the trends of digitalisation in port logistics. Methodology: A systematic literature review on the asymmetric allocation of power is used to synthesize the current state of the art in this field of research, by selecting journals in supply chain management, logistics and operation research. This review establishes a theoretical framework while combining the concept of digitalisation in port logistics and the research about the allocation of power. Findings: While this paper provides an overview of the research of marketing channels, bargaining power, supply chain leadership theory, and information asymmetry in SCM, it also develops a definition for the asymmetric of power. Linked to the classification of relations within a port, conclusions are drawn about the influence of power on digitization in that port. Originality: During the last decades the importance of ports has transformed from traditional regional gateways to key-factors in the supply chain and logistics activities. While the influence of globalisation and digitalisation increases, digitalisation becomes one of the central strategic terms for port logistics. Based on these trends the strategic decisions within the port are getting penetratively influenced by the relationships within the supply chain.

Keywords: Logistics; Industry 4.0; Supply Chain Management; Sustainability; City Logistics; Maritime Logistics; Data Science (search for similar items in EconPapers)
Date: 2020
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