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Through the “Going Digital Initiative,” the Ghanaian government has introduced policies that aim at improving the information and communication technology (ICT) infrastructure of the country. These ICT policies have benefited numerous sectors of the Ghanaian economy. In logistics management, ICT has impacted drone medical delivery in the healthcare and maritime sectors. However, the importance of ICT is not realized in the motorcycle goods transport (MGT) industry, regardless of its popularity and high economic dependency. Second, all research on motorcycles is focused on diverse social concerns, and no study has attempted to analyze ICT implementation for MGT operations. This is a significant gap in logistics management. Hence, the study aimed to investigate the impact of ICT on Ghana's MGT industry empirically.

The study adopts a two-phase data collection approach to collect the data. The authors use partial least square structural equation modeling to analyze the study's measurement and structural assessment model.

ICT positively impacts MGT and the drivers considered. The drivers positively influence MGT. The study further analyzes novel results on the relationships between the drivers and their mediating roles in enhancing MGT performance.

The study's originality is the extension of ICT adoption and usage in MGT. The lack of literature on the importance of ICT for MGT services makes this study the primary source of literature, and the relationships investigated are unique as the research area is unexplored.

The global food industry is faced with the dilemma of finding a balance between food wastage and food shortage. Approximately one-third of food produced globally goes to waste, while about 800 million people suffer from undernourishment. Given this context, the purpose of this study is to investigate the unresolved challenges related to enhancing transparency associated with products of high perishability and low shelf life.

The authors conducted 25 interviews with global agri-food supply chains (AFSCs) experts to ask what impedes the progress of the current technologies, such as blockchain, to enable transparency and traceability (T&T) in AFSCs.

The findings indicate barriers at the individual, firm and supply chain levels. Based on these barriers, the authors propose an interconnected framework to explain technologically-driven T&T and guide on barrier removal from AFSCs. The authors conclude that by applying technology (i.e. blockchain) the authors can resolve the tension of supporting T&T in AFSCs. This can enable the efficient and transparent tracking of goods, reduction of food waste and loss, as well as promotion of the use of recyclable packaging and further sustainable practices and materials, all of which are aligned with a range of UN Sustainable Development Goals (2, 8, 10 and 12). Moreover, the authors see that some factors are interrelated. Based on these factors, the authors build an interconnected framework to guide on barrier removal from AFSCs. Managers in AFSC would find the findings especially relevant.

Drawing on industrial network theory and signalling theory, the authors propose an interconnected framework for explaining barriers (challenges) and potential solutions (opportunities) to T&T in AFSCs. This framework is developed by examining the interconnections of barriers at micro, meso and macro levels and applying signalling theory to explain how solutions address these barriers. The specific contributions of this study are: the list of barriers that impede the implementation of technological solutions for T&T in AFSCs; and a three-stage framework that explains how to remove the barriers for T&T. The study is limited by the focus on blockchain, which calls for future research once the next decentralised technology becomes available.

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.

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.

An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin system using Internet of things (IoT) sensors is generated. The sensors detect the level of waste in the dustbin. The data collected by the IoT sensor is stored in the blockchain. Here, an adaptive deep Markov random field (ADMRF) method is implemented to determine the weight of the wastes. The performance of the ADMRF is boosted by optimizing its parameters with the help of the improved corona virus herd immunity optimization algorithm (ICVHIOA). Here, the main objective of the developed ADMRF-based waste weight prediction is to minimize the root mean square error (RMSE) and mean absolute error (MAE) rate at the time of testing. If the weight of the bins is more than 80%, then an alert message will be sent to the waste collector directly. Optimal route selection is carried out using the developed ICVHIOA for efficient collection of wastes from the smart bin. Here, the main objectives of the optimal route selection are to reduce the distance and time to minimize the operational cost and the environmental impacts. The collected waste is then considered for recycling. The performance of the implemented IoT and blockchain-based smart dustbin is evaluated by comparing it with other existing smart dustbins for e-waste management.

The developed e-waste management system is used to collect the waste and to avoid certain diseases caused by the dumped waste. Disposal and recycling of the e-waste is necessary to decrease pollution and to manufacture new products from the waste.

The RMSE of the implemented framework was 33.65% better than convolutional neural network (CNN), 27.12% increased than recurrent neural network (RNN), 22.27% advanced than Resnet and 9.99% superior to long short-term memory (LSTM).

The proposed E-waste management system has given an enhanced performance rate in weight prediction and also in optimal route selection when compared with other conventional methods.

Tracing audience preferences via audience analytics software has become a vital strategy for many news organizations to ensure their competitiveness in media markets. Extant research also confirms the growing presence of these tools in digital news work in recent years across many local and international news media. However, little is understood about the analytics-driven tensions emerging among journalists and media managers. This paper aims to address this gap by drawing on the labor process theory, which critically analyzes labor and workplace transformations under capitalism.

The present study employs an interview-based qualitative methodology to deeply understand the factors at the base of the emerging tensions between news workers and managers brought about by audience metrics tools.

Results show how some perceptions, activities and contextual triggers related to analytics could make relationships between workers and managers problematic. The pressures felt by some journalists stemmed from the way their media managers introduced, interpreted, communicated and applied analytics in the workplace, which were not tied to the quality and learning goals related to journalists’ aspirations. As our evidence suggests, the analytics-induced tensions among news workers were rather an outcome of managerial deficits than of systematic plans to exploit journalists.

By identifying the nature of fundamental analytics-driven tensions in newsrooms, this paper contributes to our understanding of how media managers can embrace more effective approaches toward audience analytics, workforce and organizational performance.

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.

Although technologies such as blockchain (BCT) hold great potential to improve global food supply chains (GFSCs), our understanding of BCT use in GFSCs remains limited. The purpose of this study is to broaden BCT discussions by exploring its benefits and challenges across the entire GFSC.

Qualitative interviews with 23 industry experts were used to identify and comprehend the nuanced issues with BCT application in GFSCs.

The study identifies 21 perceived benefits and challenges with BCT use in GFSCs, including the benefit of broader data incentives beyond BCT use and the challenge of reluctance to assume dominant roles among the GFSC actors.

While prior studies mostly focused on BCT use for traceability and food safety in the GFSC midstream, this study extends the scope to include upstream and midstream actors. It highlights socio-economic benefits for traditionally disadvantaged farmers in the upstream and normative challenges to its adoption in the GFSC midstream and downstream. It also identifies three paradoxes emerging with BCT use in the GFSCs including the paradoxes of food technology, transparency and de-centralization.

The COVID-19 pandemic has affected around 216 countries and territories worldwide and more than 2000 cities in India, alone. The smart cities mission (SCM) in India started in 2015 and 100 smart cities were selected to be initiated with a total project cost of INR 2031.72 billion. Smart city strategies play an important role in implementing the measures adopted by the government such as the issuance of social distancing regulations and other COVID-19 mitigation strategies. However, there is no research reported on the role of smart cities strategies in managing the COVID-19 outbreak in developing countries.

This paper aims to address the research gap in smart cities, technology and healthcare management through a review of the literature and primary data collected using semi-structured interviews.

Each city is unique and has different challenges, the study revealed six key findings on how smart cities in India managed the COVID-19 outbreak. They used: Integrated Command and Control Centres, Artificial Intelligence and Innovative Application-based Solutions, Smart Waste Management Solutions, Smart Healthcare Management, Smart Data Management and Smart Surveillance.

This paper contributes to informing policymakers of key lessons learnt from the management of COVID-19 in developing countries like India from a smart cities’ perspective. This paper draws on the six Cs for the implications directed to leaders and decision-makers to rethink and act on COVID-19. The six Cs are: Crisis management leadership, Credible communication, Collaboration, Creative governance, Capturing knowledge and Capacity building.

The purpose of this study is to increase awareness of current supply chain (SC) security-related issues by providing an extensive analysis of existing SC security solutions and their limitations. The security of SCs has received increasing attention from researchers, due to the emerging risks associated with their distributed nature. The increase in risk in SCs comes from threats that are inherently similar regardless of the type of SC, thus, requiring similar defence mechanisms. Being able to identify the types of threats will help developers to build effective defences.

In this work, we provide an analysis of the threats, possible attacks and traceability solutions for SCs, and highlight outstanding problems. Through a comprehensive literature review (2015–2021), we analysed various SC security solutions, focussing on tracking solutions. In particular, we focus on three types of SCs: digital, food and pharmaceutical that are considered prime targets for cyberattacks. We introduce a systematic categorization of threats and discuss emerging solutions for prevention and mitigation.

Our study shows that the current traceability solutions for SC systems do not offer a broadened security analysis and fail to provide extensive protection against cyberattacks. Furthermore, global SCs face common challenges, as there are still unresolved issues, especially those related to the increasing SC complexity and interconnectivity, where cyberattacks are spread across suppliers.

This is the first time that a systematic categorization of general threats for SC is made based on an existing threat model for hardware SC.