Search results

The transition from centralized thermal power plants to distributed renewable energy sources complicates the balance between power supply and load demand in electrical networks. Energy storage systems (ESS) offer a viable solution to this challenge. This research aims to analyze the factors influencing the implementation of ESS in the Indian smart grid.

To analyze the factors affecting ESS deployment in the grid, the SAP-LAP framework (situation-actor-process and learning-action-performance) integrated with e-IRP (efficient-interpretive ranking process) was used. The variables of SAP-LAP elements were selected from expert opinion and a literature review. Here, e-IRP was utilized to prioritize elements of SAP-LAP (actors in terms of processes and actions in terms of performance).

This analysis prioritized five stakeholders in the Indian power industry for energy storage implementation: government agencies/policymakers, ESS technology developers/manufacturers, private players, research and development/academic institutions, and contractors. Furthermore, the study prioritized the necessary actions that these stakeholders must take.

The study’s findings help identify actors and manage different actions in implementing grid energy storage integration. Ranking these variables would help develop a strategic roadmap for ESS deployment and decisions about adopting new concepts.

It is one of the first attempts to analyze factors influencing ESS implementation in the power grid. Here, qualitative and quantitative methodologies are used to identify and prioritize various aspects of ESS implementation. As a result, the stakeholder can grasp the concept much more quickly.

Companies are adopting innovative methods for responsiveness and efficiency in the public transport sector. The implementation of air-taxi services (ATS) in the transport sector is a move in this direction. Air taxis have a two-pronged advantage as they can reduce travel times by avoiding traffic congestion and have the potential to reduce carbon footprint compared to traditional modes of public transportation. Many companies worldwide are developing and testing ATS for practical applications. However, many factors may play a significant role in adopting ATS in the transport sector. This paper attempts to unearth such critical success factors (CSFs) and establish the interrelationships between these factors.

Fifteen CSFs were identified by systematically reviewing the literature and taking experts' input. An integrated multi-criteria decision-making (MCDM) technique, Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (DEMATEL-ANP [DANP]) was used to envisage the causal relationships between the identified CSF.

The results reveal that Govt Regulations (GOR), Skilled Workforce (SKF) and Conductive Research Environment (CRE) are the most influential factors that impact the adoption of ATS in the transport sector.

The research implications of these findings will help practitioners and policymakers effectively implement ATS in the public transportation sector.

This is the first kind of study that identifies and explores the different CSFs for ATS implementation in public transportation. The CSFs are evaluated with the help of a framework built with inputs from logistics experts. The study recognizes the CSFs for ATS implementation and provides a foundation for future research and smooth adoption of ATS.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

Building a robust cold chain logistics system boosts the company’s profits in various ways. Any cold chain logistics company needs well-organised and efficient management of cold chain logistics to produce high-quality products, ensure that the product reaches the customer without any changes to the quality, and do so promptly. This paper aims to identify factors influencing cold chain logistics performance design. These factors are further helpful in analysing the behaviour intentions of stakeholders on increasing the cold chain logistic performance.

The authors conducted a thorough literature review to identify the variables that affect the performance of the cold chain logistics design. The factors were identified using exploratory factor analysis and empirically analysed using confirmatory factor analysis. The study also used structural equation modelling (SEM) to examine cold chain logistics performance determinants. Data was collected from 380 respondents working in the cold chain.

This study selected the factors influencing CCL performance, including five main factors and 22 sub-factors. Distribution, warehouse inventory storage, quality, demand, and technology affect the CCL’s performance. The results confirmed the theoretical model and proved that the factors significantly positively impact CCL performance.

Future studies should focus on actual case studies to confirm the usefulness of the parameters found, examine how they affect performance growth, provide important insights into how to improve overall business performance and assist in identifying crucial research hotspots.

The study provides insight into issues regarding performance development in cold chain logistics for various stakeholders associated with the cold chain logistics industry, including practical managers, academics, and consultants. It also argues in favour of giving problems with CCL performance a higher priority. Policymakers interested in the service sector, like the Indian Department of Commerce and MSMEs, make up a modest additional audience for this work.

Indian meat industry can be organised by implementing this methodology. This work benefits the government to get more transparent transaction and data digitalisation, which comes into account of GST.

There is a lack of significant quantitative literature suggesting modification strategies for factors affecting processed meat and chicken products in storage and transportation levels in India. Thus, this work tried to fill this gap and add the food chain logistics literature that helps practitioners and scholars enhance the food supply chain in developing countries.The framework developed for this study is where its originality lies. A detailed examination of cold chain logistics is included in the paper.

Education for sustainability has become the mechanism for creating a pool of graduates who can understand, appreciate, practice and support the achievement of Sustainable Development Goals (SDGs). In a world with diverse cultures, demographics, political ideologies, etc. faster progress towards sustainable development needs increased use of digital technologies. Integration of digital technologies like artificial intelligence (AI), metaverse, visualisation techniques, cloud computing, Internet of Things (IoT), open data repositories, geographic information system (GIS), etc. with classroom teaching can build awareness, skills, attitudes and values among students in the journey towards sustainable development and scale up the efforts towards the goals.

In this chapter, the authors have tried to bring out a list of digital technologies and the way in which they can be used in classroom teaching to ensure education for sustainability. It may be noticed that there are watertight compartments between those who know the SDGs and those with proficiency in technology. What is also needed is integration between both silos for mapping the digital technologies with the appropriate SDGs. The teachers in the higher education system need more exposure to understand and implement this integration.

Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.

This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.

Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.

Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.

This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.

This study aims to focus on exploring the role of fear of missing out (FOMO) in the technology adoption context, whereby the bottom-of-the-pyramid (BOP) segment was studied to explore the factors responsible for the development of behavioural intentions (BI) to use unified payments interface (UPI), a disruptive technological phenomenon in the mobile payment systems field.

A mixed-method research approach involving both qualitative and quantitative methods was used. Initially, qualitative data obtained through interviews with UPI’s BOP users were subjected to thematic analysis, leading to the identification of eight factors and the construction of a conceptual model. Subsequently, 354 responses were gathered, and empirical analysis was conducted using structural equation modelling in AMOS 23.0.

Eight factors, including personal and social benefits, perceived security risk, socio-cultural influences, governmental influence, usability, psychological inertia, perceived value (PV) and FOMO, were discovered. The quantitative examination confirmed the validity of the conceptual model in the BOP context, explaining 51% of the variance in BI. FOMO and PV emerged as robust indicators of UPI adoption, with PV significantly regulating the impact of FOMO.

To the best of the author’s knowledge, this study is one of the first to explore what drives BOP users in an emerging economy to adopt UPI. The conceptual model it presents contributes to the advancement of technology adoption literature by incorporating FOMO alongside newly identified BOP-specific factors.

Made-in-India tyres are rapidly integrating into global supply chains due to a globally coordinated regulatory environment and aspiring for value creation and contribution to circularity. However, it is not clear what are the constituent components of emerging technologies like blockchain that can facilitate value creation and how they are associated. Therefore, this study intends to explore the elements of blockchain technology and how they create value to bring circularity to a tyre supply chain.

This study employed a survey-based quantitative methodology to test the theoretical framework of blockchain-enabled circular supply chains using non-parametric regression analysis. A total of 307 responses from India-based supply chain professionals’ data were collected from September 2022 to January 2023 to perform non-parametric regression analysis.

The results indicated that blockchain could improve visibility and accessibility by having value-creation capabilities of data collection, monitoring, processing and analysis to facilitate the circular tyre supply chain which focuses on recycling, reusing, reducing and rethinking initiatives. Further, accessibility contributes more than visibility to creating value toward a blockchain-enabled tyre circular supply chain.

First, this study employs a grounded theory-driven approach in identifying and testing a framework through hierarchical regression. This study identifies the role of blockchain technology in unfolding visibility and accessibility towards value creation, enhancing circularity in the supply chains in complex and critical industries such as tyres in India and across the globe.