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This study aims to provide a scientific framework for the selection of suitable substation technology in an electrical power distribution network.

The present paper focuses on adopting an integrated multi-criteria decision-making approach using the Delphi method, analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The AHP is used to ascertain the criteria weights, and the TOPSIS is used for choosing the most fitting technology among choices of air-insulated substation, gas-insulated substation (GIS) and hybrid substation, to guarantee educated and supported choice.

The results reveal that the GIS is the most preferred technology by area experts, considering all the criteria and their relative preferences.

The current research has implications for public and private organizations responsible for the management of electricity in India, particularly the distribution system as the choice of substations is an essential component that has a strong impact on the smooth functioning and performance of the energy distribution in the country. The implementation of the chosen technology not only reduces economic losses but also contributes to the reduction of power outages, minimization of energy losses and improvement of the reliability, security, stability and quality of supply of the electrical networks.

The study explores the impact of substation technology installation in terms of its economic and environmental challenges. It emphasizes the need for proper installation checks to avoid long-term environmental hazards. Further, it reports that the economic benefits should not come at the cost of ecological degradation.

The present study is the first to provide a decision support framework for the selection of substation technologies using the hybrid AHP-TOPSIS approach. It also provides a cost–benefit analysis with short-term and long-term horizons. It further pinpoints the environmental issues with the installation of substation technology.

Mobile-based payment is increasing exponentially but in the developing country like India, consumers’ perception is highly positive in daily cash transaction. The purpose of this research is to identify and examine the important challenges for mobile wallet (m-wallet) implementation in India. In the wake of COVID-19, one of the transmission mechanisms of this virus has been the coins and paper money passed between a buyer and a seller. As such m-wallet considered as a convenience of payment has become a necessity in light of the pandemic.

The authors explored 19 unique sets of challenges selected from the literature and collected data from 14 experts from private sector, multinational corporations and mixed private and public partnership who have significant knowledge and experience of mobile payment implementation and use in their respective organisations. Also, the authors have used Interpretive Structural Modelling (ISM) methodology in developing a hierarchal model for the identified challenges. The authors implemented Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis to classify the identified challenges.

The ISM-based framework is divided into nine different hierarchical levels. “Lack of strong regulatory compliance (Ch6)” has been recognised as the most important challenge, which inhibited the mobile wallet implementation, whereas “Perception of customers about the value of using mobile wallets (Ch11)” is the most dependent critical challenge. There are seven hierarchical layers in between the top and the bottom level with the varied number of challenges based on their driving and dependence power.

This is the first research to the best of our knowledge that has not only comprehensively reviewed the m-wallet literature but also employed a unique ISM-MICMAC-based approach to develop a framework of challenges for the m-wallet implementation.

This paper aims to examine if Malaysian public listed companies have expressed any specific sentiment(s) when publishing their financial performance during the COVID-19 pandemic.

The disclosed sentiments contained in the management discussion and analysis section of the companies’ annual reports were extracted by means of computer-automated textual analysis through the linguistic inquiry and word counts and the Loughran–McDonald Financial Sentiment Dictionary. Next, a correlation analysis was conducted. Finally, a qualitative content analysis (QCA) was conducted to confirm these sentiments.

The analysis shows that companies adopted various tones of sentiments when communicating with their stakeholders. Most companies used negative sentiments to voice their concerns about how the COVID-19 pandemic has impacted upon their business operations. Only a few companies reflected positive sentiments, whilst those that experienced operating losses also expressed uncertainty.

This study may assist either the regulators or accounting bodies to introduce a reporting framework that public companies can adopt during natural hazards. It also provides useful insights to (potential) investors to enable them to better understand the business landscape. For future research, the same study could be conducted on more countries so that their experiences can be used to better understand the business phenomenon from a global perspective.

This study is one of few studies to adopt automated textual analysis and QCA to examine the exhibited sentiments when public companies reported their financial performance during the COVID-19 pandemic.

This paper aims to provide an in-depth awareness into the research on customised training programme for the indigenous population in India. The central aim is to conduct a systematic review on the available studies to explore its crucial themes interweaving with skill development.

This study uses systematic review method, for which the author uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, SPIDER tool and Mendeley to identify relevant articles from 2011 to 2022.

Results show that the customised training programme is useful for the first-generation population to upgrade their skills. It aids in improving scalability, supports job creation and facilitates in mitigating low level of training exposure by meeting the local needs. However, poor approachability on customised training, its oversimplification and lack of research dents the critical insights and prospects.

The novelty of this paper lies on retrieving the essential indicators of customised training from previous studies by systematic review tools. It can aid academicians, educators, local administration and policymakers to understand its benefits for indigenous population to fill the policy gaps.