PurposeThe purpose of this paper is to develop a more precise conceptual understanding of the interplay between food product traceability and supply network integration.Design/methodology/approachA resource‐based network approach was used to create a framework with empirical evidence from a fresh strawberry product case.FindingsA conceptual model describes product traceability as interacting with different organizational and informational resources.Research limitations/implicationsThis is a preliminary model that substantiates a cross‐functional approach teamwork‐based to developing product traceability.Originality/valueThe study shows developing food product traceability as a complex undertaking dependent on information connectivity including a technical aspect of supply chain integration, and different forms of knowledge, an organizational aspect of supply chain integration.

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Purpose – The paper aims to explore the effects of geographic proximity among firms in value networks on service provision and service exchange. Design/methodology/approach – A case study of the offshore supply vessel shipbuilding and shipping cluster in the North-Western Møre region of Norway with focus on the new ship contracting process. Findings – The case study reveals how service provision and service exchange are facilitated by geographical proximity among firms. Research limitations/implications – Study findings should be validated in further research, and the effects of other forms of proximity (cultural, social, cognitive and institutional) on co-creation of value also need to be considered. Considering the role of operant resources in developing competence in clusters and wider value networks offers interesting opportunities for further research. Originality/value – This study proposes an alternative view of co-creation of value in value networks and responds to calls for research on how value network attributes affect aspects of co-creation of value: service provision and service exchange. The study contributes to more knowledge on the systemic nature of value creation in value networks.

Purpose This study aims to consider the developing of strategic use of big data in association with long-linked physical goods supply focusing on risk management. Design/methodology/approach Analysis is grounded on a case study of organizing the import of machine parts from Shanghai, China, to Norway. An analytical framework is developed through a literature review on long linked supply chains, big data and risk management. Findings Analysis reveals that big data use in this scenario encompasses mainly around handling risks associated with transformations in the supply chain, a data-driven approach. Complexity is founded in transformation – the flows of goods and information. Supply chain dynamics represent an important source for data acquisition for big data analytics. Research limitations/implications The qualitative nature of the study limits the aim of generalization. An alternative view of big data as process is discussed and proposed, adapted to supply chain management and industrial marketing functionality. Originality/value This is the first part in an ongoing research project aimed at developing a research approach to study information technology use in the inherently complex setting and scope of a long linked supply network. This scope of investigation enhances big data associated with operations dynamics providing foundation for future research on how to use big data to mitigate risk in long linked supply chains.

The future of logistics shipping bases will be to seek efficient flows of materials to meet the needs of business partners. Supply chain and operations managers of supply bases will need to integrate technologies that allow for greater automation, digitalization, flexibility and improved communications among stakeholders. The technologies that are likely to boost integration will consist of a plethora of Industrial Internet-of-Things (IIoT) technologies that may include Wireless Sensor Network (WSN) technologies and could be applied for improved monitoring of healthy and safe industrial workplaces for workers. However, little is known regarding how WSN technologies can be implemented on a larger scale and its implications when integrated on standard logistics and operations of industrial workplaces such as a shipping base. The WSN sensor units represent an integrating resource that are capable of monitoring air temperature, humidity and levels of carbon dioxide (CO2) and other gasses and of disseminating this information to different actors in the production system. Air quality factors play a critical role in the perceived levels of workers' comfort and in reported medical health. The low cost of wireless sensor network (WSN) technologies offer potential for continuous, autonomous and importantly networked assessment of industrial workplace air quality that may have implications for operations management and quality of production. This paper initially presents a case study that monitors air quality that is collected with WSN technologies from two workshops carried out by a large on-shore logistics base that supports offshore petroleum logistics. The case study demonstrates a monitoring and visualization approach for facilitating BD in decision making for health and safety in the shipping industry. However, with the advancement in IIoT technologies and the emergence of smart sensing and actuating devices, it is possible to form a digital closed-loop system that we argue is essential for managers to link together information about air quality with supply chain and operations management decisions. We propose that central to effective decision making is the data analytics approach and visualization of what is potentially, big data (BD) in monitoring the air quality in industrial workplaces. We discuss how WSN technologies can be integrated into the logistics management and operations of the shipping base. Through an analytical discussion of BD we explore how to extend the potential application of IIoT and Visual Analytics to facilitate a smart workplace for the Industry 4.0 era.

Purpose The purpose of this paper is to reveal the interdependencies involved and how interaction takes place in the context of a project organization as a network of academic and business actors. Design/methodology/approach This study focuses on relationships between business and academia and applies a single case research strategy. Data are collected through a series of theoretically sampled in-depth interviews including company observations. The single case study provides a rich narrative of the network structure and processes involved in establishing, implementing and completing a research project in Poland. The Industrial Marketing and Purchasing Group network approach focusing on resource combinations that emerge in a network structure characterized by interdependency and integration is applied to analyze interaction in this project-organized network. Findings Change in interdependencies, interaction and integration are analyzed individually, and in conclusion in relation to each other. While supply chain management literature postulates that integration is a management goal, a driver of successful business, this study points out that integration is an outcome of interaction in a context of changing interdependencies. This means that managerial focus should rather be driven to understanding the nature of network interdependencies, their path of change and how interaction is carried out in this emergent context. Originality/value The study aims to help better understand the potential for research project cooperation by explaining how businesses and research units can cooperate through an understanding that integration is a complex phenomenon, focusing on how management may better support services production through careful consideration of that integration is developed through considerations of interdependencies as context of interaction in the varied business cultures a project network comprises. Project management is more a learning process than a planning process.

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The Covid-19 pandemic that began in the city of Wuhan in China has caused a huge number of deaths worldwide. Countries have introduced spatial restrictions on movement and social distancing in response to the rapid rate of SARS-Cov-2 transmission among its populations. Research originality lies in the taken global perspective revealing indication of significant relationships between changes in mobility and the number of Covid-19 cases. The study uncovers a time offset between the two applied databases, Google Mobility and John Hopkins University, influencing correlations between mobility and pandemic development. Analyses reveals a link between the introduction of lockdown and the number of new Covid-19 cases. Types of mobility with the most significant impact on the development of the pandemic are “retail and recreation areas", "transit stations", "workplaces" "groceries and pharmacies”. The difference in the correlation between the lockdown introduced and the number of SARS-COV-2 cases is 81%, when using a 14-day weighted average compared to the 7-day average. Moreover, the study reveals a strong geographical diversity in human mobility and its impact on the number of new Covid-19 cases.