Hendrik Reefke’s research while affiliated with Cranfield School of Management and other places

Purpose Autonomous vehicle (AV) adoption has both positive and negative impacts on supply chain social sustainability (SCSS). This paper explores and evaluates the actions that organisations take to address the social impacts of adopting AVs and develops a model for SCSS in this context. Design/methodology/approach This study implemented a Delphi study conducted over three iterative rounds to gather and evaluate the actions that organisations take to address social impacts when adopting AVs in supply chains. The panel consisted of 39 experts from industry and academia. The Delphi findings are validated and extended through 14 follow-up expert interviews. Findings Our findings identify eight categories of actions used to address the social impacts of adopting AVs in the supply chain. These are discussed in relation to established SCSS indicator categories and an additional category, “reputation” is introduced. The categories are also aligned to the technology adoption process to understand how social sustainability implications can be mitigated as AV adoption matures. Practical implications Practitioners benefit from prescriptive frameworks which provide actions addressing the social sustainability implications of AV adoption. These can be applied either from a social sustainability indicator or innovation adoption process perspective. Originality/value This study builds on the diffusion of innovation (DOI) theory to propose a refined innovation process model for socially sustainable adoption of AVs. This customised model aligns the new action categories with the established stages of the innovation adoption process, uniquely illustrating how to manage the social sustainability impacts of AV adoption as part of the technology adoption process. Identified social supply chain indicator categories are also aligned with the actions for an alternative perspective.

Purpose This paper aims to seek answers to the question: What are the relevant factors that allow not-for-profit innovation networks to successfully transition new technologies from proof-of-concept to commercialisation? Design/methodology/approach This question is examined using the knowledge-based view and network orchestration theory. Data are collected from 35 interviews with managers and engineers working within seven centres that comprise the High Value Manufacturing Catapult (HVMC). These centres constitute a not-for-profit innovation network where suppliers, customers and competitors collaborate to help transition new technologies across the “Valley of Death” (the gap between establishing a proof of concept and commercialisation). Findings Network orchestration theory suggests that a hub firm facilitates the exchange of knowledge amongst network members (knowledge mobility), to enable these members to profit from innovation (innovation appropriability). The hub firm ensures positive network growth, and also allows for the entry and exit of network members (network stability). This study of not-for-profit innovation networks suggests the role of a network orchestrator is to help ensure that intellectual property becomes a public resource that enhances the productivity of the domestic economy. The authors observed how network stability was achieved by the HVMC's seven centres employing a loosely-coupled hybrid network configuration. This configuration however ensured that new technology development teams, comprised of suppliers, customers and competitors, remained tightly-coupled to enable co-development of innovative technologies. Matching internal technical and sectoral expertise with complementary experience from network members allowed knowledge to flow across organisational boundaries and throughout the network. Matrix organisational structures and distributed decision-making authority created opportunities for knowledge integration to occur. Actively moving individuals and teams between centres also helped to diffuse knowledge to network members, while regular meetings between senior management ensured network coordination and removed resource redundancies. Originality/value The study contributes to knowledge-based theory by moving beyond existing understanding of knowledge integration in firms, and identified how knowledge is exchanged and aggregated within not-for-profit innovation networks. The findings contribute to network orchestration theory by challenging the notion that network orchestrators should enact and enforce appropriability regimes (patents, licences, copyrights) to allow members to profit from innovations. Instead, the authors find that not-for-profit innovation networks can overcome the frictions that appropriability regimes often create when exchanging knowledge during new technology development. This is achieved by pre-defining the terms of network membership/partnership and setting out clear pathways for innovation scaling, which embodies newly generated intellectual property as a public resource. The findings inform a framework that is useful for policy makers, academics and managers interested in using not-for-profit networks to transition new technologies across the Valley of Death.

This paper studies micro-fulfilment centres (MFCs) as a response to rising e-grocery sales and customer expectations from decreased delivery time and cost requests. MFC is a business solution that allows orders to be picked and packed in a hyper-local facility. The study’s aim is to provide an overview of this subject from two research questions: i) how MFCs affect the last-mile delivery challenges? and ii) what design decisions are critical in building MFCs? While we evaluate the advantages and disadvantages of centralised versus decentralised warehousing strategies in the first question, we discuss the critical decisions in designing MFCs in the second question. In that, we discuss location and technology selection decisions as well as other warehousing design criteria. Further, this study provides future research directions at the end of this study. KeywordsE-commerceMicro-fulfilment centreSustainabilityLast-mile deliveryUrban distribution centre

This chapter follows Chap. 4 with tactical decisions. Based on strategic decisions, tactical decisions have a medium-term effect on warehouse operations. These decisions are easier to adjust during the implementation stage compared to strategic-level decisions, but they should not (and generally cannot) be changed in the short term.

This chapter will present strategic-level decisions for mobile robot automation in warehouses, which involve comprehensive, long-term business decisions such as the layout of the warehouse and the type of mobile robots. These decisions are generally taken before the installation stage of mobile robot systems, and they are rather difficult to alter during the implementation. The effects of these decisions occur in the long run, which might be years.

This chapter provides details on the systematic literature review methodology followed to produce the state-of-the-art mobile robot automation. It explains the application process, inclusion/exclusion/quality criteria, and other analysis details for the pool of peer-reviewed papers. This chapter is necessary for the reproducibility and replicability of the literature review. Although at the time the book is written, the review is recent, as time passes, the reader may wish to identify papers that are published after the book, and they can follow the methodology explained in this chapter for that purpose.

This final chapter concludes the book, highlighting the key aspects of the new knowledge presented across the preceding chapters, providing recommendations for practitioners, and acknowledging the limitations of the work.

This chapter provides definitions of ten mobile robot systems incorporating suitable case examples. It evaluates these systems using a multi-criteria rating approach, where the criteria are also identified through the literature review. The chapter also provides justifications for these criteria when selecting a mobile robot automation system. Then, ten mobile robot systems are rated on a three-point scale in each criterion, where the higher the score, the better the performance in the given criterion. To provide guided examples, the rationale for this multi-criteria selection support is further explained with the ‘Equal Weight’ approach and the ‘Full Consistency Method’ (FUCOM) which uses supply chain experts’ judgements on each criterion.

This chapter synthesises Chaps. 4–6 to provide a conceptual framework of managerial decisions at every level to aid warehouse managers in choosing and implementing mobile robot systems. It provides focus areas for each decision and the questions the decisions should answer. It also addresses concepts that have not formally affected the managerial decision framework yet are eligible for further attention. It provides a discussion on change management and a critique of algorithms that may be deployed to manage robots’ behaviour in the warehouse.

The tactical decisions provide a boundary for the operational decisions to be taken when running the warehouse on a day-to-day basis. Operational-level decisions could be altered in the short term. Their effect on the warehouse operations could be observed within the same month or even within the same day as they directly affect operations. Thus, warehouse managers can experiment (without jeopardising the ongoing operations) with their decisions to optimise the operational focus areas.