Search results

The coronavirus pandemic led to supply chain disruptions resulting in adverse economic impacts on global supply chains. Nationwide lockdowns in countries that play key roles in global manufacturing restricted freight movements through air, ocean, and land routes resulting in delivery delays, higher freight rates and congestion. At the same time, the pandemic has accelerated the growth of the e-commerce sector. Concern around infections has led to a surge in first-time online consumers for categories such as health and pharmaceuticals and fast-moving consumer goods. Companies have had to rethink their approaches to optimising warehouse locations and inventory to meet customer demand. From a freight perspective, the focus has shifted from a single-mode model towards multi-modal logistics to reduce costs and dependence on any one mode. This chapter will review recent developments, long term impacts and opportunities for growth in the context of this important sector and illustrate some of the key impacts of the pandemic using the example of the emerging economy in India. It concludes by synthesising key takeaways and reflecting on the future of the sector.

The success of e-retailers is intrinsically linked to the effectiveness of their logistics processes which, inevitably, involve third party service providers. As the most tangible representative of the e-retailers it is inevitable that customers expect the e-retailer to resolve delivery queries, including on social media platforms. The purpose of this paper is to investigate the effectiveness of e-retailers’ logistics-related customer service interactions on Twitter with a view towards identifying effective and ineffective social media customer service strategies.

The design and public nature of Twitter encourages organic conversations between e-retailers and customers as well as between customers and other customers. The methodology applied here accounts for this by collecting and analysing interactions within and as part of conversations, not as independent observations. In total, 203,349 tweets were collected from 22 of the most popular e-retailers. A random sample of 5,000 logistics-related conversations (16,998 tweets) is used for the analysis presented here and forms a foundation for future research.

Conversations are initiated by customers on the basis of 24 event triggers which can be categorised as occurring either before or after an order is delivered. These can be general queries or related to a specific order or delivery issue. The paper identifies a number of significant findings such as the extent to which e-retailers and logistics providers redirect customers to other channels to resolve queries, ignoring the implicit preference by customers to use Twitter to resolve their problem. Similarly, the lack of interactions between e-retailers and their logistics providers within the Twitter platform to help resolve customer queries results in ineffective customer service.

The study identifies the way in which e-retailers can substantially improve the effectiveness of the customer service they provide on Twitter by ensuring that customer queries can be resolved within the platform and by working with their logistics partners to do the same. This is critical since problems may be directed to the e-retailer or the logistics provider but both companies jointly suffer the consequences of poor customer service.

The study examines a hitherto underexplored aspect of retail logistics – the social media-based customer service activities of e-retailers. Methodologically, the study is rooted in the acknowledgement that interactions on Twitter form conversations and analyses should take this into account. This is a distinctly different approach from existing Twitter-related studies which conduct an automated sentiment analysis of tweets. This approach reveals a rich picture of interactions and, importantly, identifies where conversations between e-retailers begin, how they develop and how they conclude.

Transport and pandemics are interlinked given the ubiquitous nature of modern transport systems. The COVID-19 pandemic has provided much evidence for both virus contagion but also containment and how transport plays a role in both. As the world and its cities experienced lockdowns, there were travel restrictions, physical social distancing rules, transport systems shut down, changed operations, a re-opening with lower demands in some sectors (e.g., air transport and urban public transport services) and an increased demand in others (e.g., freight and home deliveries). These changes brought about a series of reactions at all levels, from governments and local authorities, operators of all transport modes but also personal and individual behaviour. This volume provides evidence on an array of transport and pandemic experiences through a collection of works from around the world, each chapter discussing a mode, a region and possible future outcomes. This introductory chapter provides the context for this volume with an overview of literature that looks at transport and pandemics, a timeline of events that marked the COVID-19 pandemic developments across different parts of the world, and finally an overview of the chapters in the volume. It concludes with some insights from the editors on the future of transport in a post-COVID world.

Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.

This paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.

The analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.

To the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.

The purpose of this study is to understand consumers in the emerging wine market of India to ensure the best services. To this end, factors were identified to describe Indian wine consumer behavior and further segments for consumers were created based on the factors identified.

The research design is descriptive in nature and based on primary data. Data was collected by a structured questionnaire from 232 respondents in five major cities of India (Mumbai, Delhi NCR, Bangalore, Pune and Hyderabad). The scale was mainly adopted from wine-related lifestyle approaches.

The principal component factor analysis resulted in six factors, namely, drinking ritual, consumption reason (social), consumption reason (mood, enjoyment and relaxation), consumption practice, consumption planning and quality. Cluster analysis resulted in a three-cluster solution. These clusters were named as cautious social drinker, loner regular drinker and highly engaged drinker based on the attributes possessed.

The segmentation of urban Indian wine consumers will be helpful for marketers to identity and describe the differences in attributes and behaviors, to create customized promotions to match the needs.

GiveIndia is an online donation platform that bridges the gap between the donors and credible Non-Governmental Organizations. The focus of GiveIndia has been on individual donations with a vision to create a culture of giving, where every Indian donates at least 2% of their income for the poor. In 2013, the Government of India introduced Corporate Social Responsibility Bill, which mandates corporates to invest at least 2% of their profits in CSR activities. At present, GiveIndia has not been seeking corporate, but now they find themselves at the right position to exploit this opportunity. Dhaval, the CEO faces a dilemma. Corporate donations could significantly increase his funding; however, it could also lead deviations from the mission to creating a giving culture. There were other problems to contend with, such as the question of investing in GiveIndia brand, how to pitch business reasons for philanthropy and employee compensation and retention issues.

This paper aims to introduce a new fault protection scheme for microgrid DC networks with ring buses.

It is well recognized that the protection scheme in a DC ring bus microgrid becomes very complicated due to the bidirectional power flow. To provide reliable protection, the differential current signal is decomposed into several basic modes using adaptive variational mode decomposition (VMD). In this method, the mode number and the penalty factor are chosen optimally by using arithmetic optimization algorithm, yielding satisfactory decomposition results than the conventional VMD. Weighted Kurtosis index is used as the measurement index to select the sensitive mode, which is used to evaluate the discrete Teager energy (DTE) that indicates the occurrence of DC faults. For localizing cable faults, the current signals from the two ends are used on a sample-to-sample basis to formulate the state space matrix, which is solved by using generalized least squares approach. The proposed protection method is validated in MATLAB/SIMULINK by considering various test cases.

DTE is used to detect pole-pole and pole-ground fault and other disturbances such as high-impedance faults and series arc faults with a reduced detection time (10 ms) compared to some existing techniques.

Verification of this method is performed considering various test cases in MATLAB/SIMULINK platform yielding fast detection timings and accurate fault location.