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A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of their trace such as stay points, revisit locations and meeting points is important. More trained staffs and tools are required under the traditional system of contact tracing. At the time of the spiralling patient count, the time-bound tracing of primary and secondary contacts may not be possible, and there are chances of human errors as well. In this context, the purpose of this paper is to propose an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations.

Pandemic situations push the world into existential crises. In this context, this paper proposes an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. By exploring the daily mobility and activities of the general public, the system identifies multiple levels of contacts with respect to an infected person and extracts semantic information by considering vital factors that can induce virus spread. It grades different geographic locations according to a measure called weightage of participation so that vulnerable locations can be easily identified. This paper gives directions on the advantages of using spatio-temporal aggregate queries for extracting general characteristics of social mobility. The system also facilitates room for the generation of various information by combing through the medical reports of the patients.

It is identified that context of movement is important; hence, the existing SemTraClus algorithm is modified by accounting for four important factors such as stay point, contact presence, stay time of primary contacts and waypoint severity. The priority level can be reconfigured according to the interest of authority. This approach reduces the overwhelming task of contact tracing. Different functionalities provided by the system are also explained. As the real data set is not available, experiments are conducted with similar data and results are shown for different types of journeys in different geographical locations. The proposed method efficiently handles computational movement and activity analysis by incorporating various relevant semantics of trajectories. The incorporation of cluster-based aggregate queries in the model do away with the computational headache of processing the entire mobility data.

As the trajectory of patients is not available, the authors have used the standard data sets for experimentation, which serve the purpose.

This paper proposes a framework infrastructure that allows the emergency response team to grab multiple information based on the tracked mobility details of a patient and facilitates room for various activities for the mitigation of pandemics such as the prediction of hotspots, identification of stay locations and suggestion of possible locations of primary and secondary contacts, creation of clusters of hotspots and identification of nearby medical assistance. The system provides an efficient way of activity analysis by computing the mobility of people and identifying features of geographical locations where people travelled. While formulating the framework, the authors have reviewed many different implementation plans and protocols and arrived at the conclusion that the core strategy followed is more or less the same. For the sake of a reference model, the Indian scenario is adopted for defining the concepts.

Technology is the lifeline for the logistics industry, and it has been immensely disrupted by the emerging blockchain technology. This paper has two main objectives. The first is to explore how the current blockchain technology can be implemented in the logistics industry with the aim of improving logistic services amongst the network of logistics service providers (LSPs). The second is to propose the development of a blockchain model for the small and medium logistics service supply chain.

A prototype blockchain-based logistics system has been created and tested in a case study with a real logistics company. The primary technologies for developing a blockchain model on the Hyperledger platform as well as how the system is designed based on the logistics service flow are explained.

The study has resulted in the successful implementation of the proposed prototype blockchain-based logistics system. In particular, the case company has managed to fully utilise the developed tracking and tracing system. Whilst utilising the prototype, the participants have been able to fulfil their responsibilities in an effective manner. The performance of LSPs has improved following the World Bank Logistics Performance Index (LPI) criteria.

This paper contributes to current research in the application of blockchain technologies in the domain of logistics and the supply chain to progress LSPs towards Logistics 4.0. The current frameworks for Logistics 4.0 and how blockchain as a disruptive technology revolutionises logistic services are reviewed. In addition, this paper highlights the benefits of blockchain technology that LSPs can leverage to further improve their performance based on the LPI criteria.

To explore how motivational interviewing (MI) training might benefit the practice of COVID-19 contact tracers.

Following co-production of a MI training package, with a United Kingdom (UK) track and trace organisation, training was delivered virtually to 101 volunteer participants involved in contact tracing. Data were captured via an online survey, incorporating questions from recognised measures of occupational self-efficacy and workplace wellbeing, prior to the training. Open data fields were used to gather feedback about participants' reasons for attending, and views about the training afterwards.

Although the contact tracers reported high occupational self-efficacy and workplace wellbeing, both quantitative and qualitative data suggested participants saw practitioner value and utility in MI.

The sample was self-selecting and typically involved contact tracers from UK local authorities. The study did not measure impact on compliance with self-isolation guidance and/or providing details of contacts, and larger-scale research would be needed to establish this. This was not a pre-post-test evaluation study, and measures of occupational self-efficacy and workplace wellbeing were gathered to give insight into the sample and to test the feasibility of using this survey for a future large-scale study. The research was conducted during the height of the pandemic. While UK COVID-19 contact tracing services have since been reduced, there are potential implications for infection control more generally.

MI is potentially a useful approach for enhancing contact tracing practice. However, implementation factors should be carefully considered, to ensure effective and sustainable practice.

Improved practice in contact tracing could have potential benefits in infection control, through improving compliance with central guidance, although this requires more widespread investigation.

This is the first empirical study to investigate how MI training could benefit COVID-19 contact tracing practice.

This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns in these networks.

The paper is based on a single case study of a technological start-up, providing tracking, tracing and other information services to MLN members using internet-based software. An interorganizational theory perspective informs the case study to unveil the resource integration for value cocreation in the network.

The start-up holds multiple resource interaction roles and the start-up’s involvement enables the creation of new knowledge resources, which facilitate new revenue streams and manage resource dependencies. Hence, the findings indicate that the start-up changes value cocreation patterns in the network by reconfiguring and integrating existing resources so that the service is customized for various customers, including shippers and freight forwarders.

The results provide insights about how technological start-ups can unlock resources within MLNs.

The study extends previous studies on resource roles in business networks and shows how start-ups can perform multiple roles simultaneously within these networks. In addition, the study contributes to the literature by studying information and knowledge as resources configured in different ways in a unique network setting.

This paper aims to present an emergent framework that proposes the strategic importance of supply chain (SC) traceability beyond the traditional role in supporting product safety, recalls and sustainability initiatives.

A grounded theory (GT) approach with 22 in-depth interviews with managers from 10 countries/territories and 3 different echelons of the food SC is employed to arrive at the strategic traceability framework and framework's propositions.

The framework suggests that traceability can sometimes help expose and modify firms' core and non-core SC capabilities and provide an opportunity to align them better with SC strategies. This alignment may require a complementary execution of human coordination and the adoption of technological traceability components.

The research suggests that firms may be able to extract greater value from the firms' traceability investments. While traceability continues to serve the key purposes of preventing and mitigating the risks of recalls, this can sometimes illuminate sustained business growth opportunities.

The study extends traceability beyond a means to meet the requirements of product safety, recalls and sustainability. Rather, this study establishes traceability's role in exposing and aligning firms' capabilities for business gain and not merely recall risk mitigation. This reframing of the premise for traceability can invigorate both research and practice on the subject of traceability.

This study aims to investigate the various systems in logistics industry of Pakistan through the lens of the World Bank's logistics performance indicators (LPI) and understand their impact on the China–Pakistan economic corridor (CPEC) that is a vital part of China's belt and road initiative (BRI).

In this study thematic analysis was performed on twenty-three semi-structured interviews with experts in Pakistan's logistics and supply chain sector to gain an in-depth insight into the logistics performance relative to CPEC.

A performance gap exists in the logistics systems in Pakistan, both for hard and soft infrastructure. The significant challenges are the inefficiencies of the government, minimal use of information and computing technology (ICT), and an incapable workforce. It is essential to be cognizant of the ground realities and amendments required in the existing policies and practices in light of the challenges faced and best practices adopted by developed and developing countries with good standing in logistics performance. This study will guide policymakers and practitioners for hard and soft logistics infrastructure improvement, which may benefit economic corridors in general and CPEC in particular.

This study contributes to the existing literature by highlighting the role of ICT in improving both soft and hard logistics infrastructure, which can lead to significant development of economic corridors. The study makes use of a case study of the CPEC to demonstrate the lack of ICT can hamper the growth of an economic corridor despite billions of dollars of investment in the hard infrastructure development projects.

This study aims to explore the critical application areas of radio frequency identification (RFID) technology for sustainable buildings.

The quantitative research approach was adopted through a structured questionnaire administered to relevant stakeholders of construction projects. The data collected were analysed with the exploratory factor analysis, relative importance index (RII) and fuzzy synthetic evaluation (FSE).

The study’s results have categorised the crucial areas of application where construction industry stakeholders should focus their attention. These areas are divided into four categories: management technologies, production technologies, sensing technologies and monitoring technologies. The findings from the FSE indicate that monitoring technologies represent the most significant category, whereas management technologies rank as the least significant. Moreover, the RII analysis highlights that tools management stands out as the most important application of RFID, while dispute resolution emerges as the least significant RFID application.

The study establishes the core areas of RFID application and their benefits to sustainable buildings. Consequently, it helps stakeholders (consultants, clients and contractors) to examine the RFID application areas and make informed decision on sustainable construction. Furthermore, it provides systematic proof that can aid the implementation of RFID in developing countries.

The study provides an insight into the possible application areas and benefits of RFID technology in the construction industry of developing countries. It also developed a conceptual frame for the critical application areas of RFID technology in the construction industry of developing countries.

Product counterfeiting has been ubiquitously observed in various segments of the supply chain. The intrinsic values of brands create more opportunities for counterfeiting. The damaging reputation of such brands leaves them to deal with the fallouts of counterfeits. Hence, such companies address them mainly through legal action, price and quality strategy. However, consumer characteristics and the random distribution of counterfeit products to the consumer types affect the effectiveness of a counter strategy. This paper aims to generate insights on how to leverage digital technology to curb counterfeit entities with consideration of consumer characteristics and the random distribution of counterfeits to them.

The authors used game theory and vertical differentiation model to understand and encounter deceptive counterfeiting of brand products. The study understands the economic relationship between a brand product manufacturer and consumer types based on their awareness. Further, the authors have considered different cases in the model to gain useful insights.

The results reveal that when the consumers are proactive, informed and value-conscious brand product manufacturers take digital technology counterstrategy to earn the maximum revenue. Hence, this analysis highlights that the effectiveness of a counterstrategy critically depends on the consumer characteristics, whether they are proactive, informed or unaware.

The study outlines that brand product manufacturers must emphasize on the digital supply chain, product redesign and product tracking facility to empower informed and value-conscious and proactive consumers. Moreover, the government should take steps to create awareness among uninformed consumers via information campaigns.

This paper incorporates the role of consumers and brand product manufacturers to understand and address the deceptive counterfeiting issue.

In the aftermath of disasters, humanitarian actors need to coordinate their activities based on accurate information about the disaster site, its surrounding environment, the victims and survivors and the supply of and demand for relief supplies. In this study, the authors examine the characteristics of radio frequency identification (RFID) technology and those of disaster relief operations to achieve information visibility and actor coordination for effective and efficient humanitarian relief operations.

Building on the contingent resource-based view (CRBV), the authors present a model of task-technology fit (TTF) that explains how the use of RFID can improve visibility and coordination. Survey data were collected from humanitarian practitioners in India, and partial least squares (PLS) analysis was used to analyze the model.

The characteristics of both RFID technology and disaster relief operations significantly influence TTF, and TTF predicts RFID usage in disaster relief operations, providing visibility and coordination. TTF is also a mediator between the characteristics of RFID technology and disaster relief operations and between visibility and coordination.

The many recent humanitarian disasters have demonstrated the critical importance of effective and efficient humanitarian supply chain and logistics strategies and operations in assisting disaster-affected populations. The active and appropriate use of technology, including RFID, can help make disaster response more effective and efficient.

Humanitarian actors value RFID technology because of its ability to improve the visibility and coordination of relief operations. This study brings a new perspective to the benefits of RFID technology and sheds light on its antecedents. The study thus expands the understanding of technology in humanitarian operations.

Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC.

To examine the behavioural intention of employees in the retail SC, the research uses three theories – the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis.

This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector.

This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only.

This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC.