This paper introduces a method of analyzing large text data in the context of an Actor-Network Theory based study. A case is used to illustrate conditions under which using an analytical technique from another philosophy seems particularly apt. A tool commonly used in Grounded Theory was applied in a manner aimed at facilitating a search for potential actors and their interactions and for evidence of specific translations of the innovation in the case used.

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The increase in e-commerce and omnichannel commerce is having a significant impact on the supply chain sector and its warehouses. Fluctuations in demand and priorities, the requirement for value-added service, government regulations and other factors put pressure on the operational decision makers on the warehouse floor and the systems that support them. The increasing complexity of daily warehouse operations means that decision support systems will need to become more sophisticated and intelligent to assist decision makers in real-time. The aim of this literature review is to investigate how decision support in warehousing and distribution operations is examined in the research literature. The objective of this review is to understand how this decision support research can assist operational decision makers to manage and complete the daily volume of work through the warehouse. Fifty-one articles were obtained by the literature search. Articles were categorized by type of warehouse, decision support target, operational task and problem type, research article methodology, architecture and technology. Decision support is examined in almost all areas of warehousing operations with the use of a variety of methods and technologies within the research literature. Most “daily warehouse operational” decision support deals with expertise transfer and reacting to real-time events. This paper highlights the lack of research into human–machine collaboration in adaptive decision support systems to assist warehouse operational decision makers.

Warehouses are being impacted by increasing e-commerce and omni-channel commerce. The design of current WMSs (Warehouse Management Systems) may not be suitable to this mode of operation. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment, resulting in disruptions. Standard operational process is paramount to warehouse operational control but may preclude a dynamic response to real-time operational constraints. The growth of IoT (Internet of Things) sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents the design and development stage of a design science methodology of an intelligent agent framework for basic warehouse management systems. This framework is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework.

Purpose With the advent of new technologies, the integration of blockchain-enabled food supply chain (FSC) implementations is on the rise. Considering the multilateral, comprehensive and complex nature of the whole blockchain-enabled FSC implementation process, understanding knowledge management (KM) practices will add value. Prior literature shows that only a few studies have focused on this topic. As such, this study aims to identify and establish key KM enablers for blockchain-enabled FSC implementations. Design/methodology/approach This study conducted a qualitative research approach. By conducting 22 in-depth interviews with experienced blockchain implementation experts in FSC contexts, this study provides interesting insights for academics and practitioners. Findings The results of the analysis highlighted eight critical KM enablers that directly influence blockchain-enabled FSC implementations. They include external enablers (i.e. regulation and market competition) as well as internal enablers (i.e. people – organizational learning, strategy and leadership, culture, information technology, organizational infrastructure, processes and activities). Originality/value This study is one of the few studies that identify KM enablers for blockchain-enabled FSC implementations. Considering the novelty of decentralized blockchain implementations in FSC and its importance in transforming silo-based knowledge exchange to a decentralized operational structure, this study attempts to identify factors that increase the efficiency of blockchain implementations in FSC contexts.