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There has been significant interest in the classification of exchange rate regimes in order to investigate a wide range of hypotheses. Studies of the effects of exchange rate regimes on crises and other aspects of economic performance can have important implications for policy choices. The paper provides a guide to the major new large data sets that classify exchange rate regimes and to critically analyze important methodological issues.

The study surveys and critiques the literature and provides theoretical analysis of major issues involved in classifying exchange rate regimes.

The study finds that all of the new data sets have problems but some have more problems than others and several of them are substantial improvements on what was previously available. It is also shown that the best ways to classify depend on the issue being addressed and that for detailed studies variants of measures using the concept of exchange market pressure are the most promising. Directions for future research are also discussed.

The paper makes researchers aware of the new data sets that are available and discusses their strengths and weaknesses. It also presents original analysis of several of the major conceptual issues involved in classifying exchange rate regimes.

The purpose of this paper is to highlight the method of field work supervision in BSW and MSW programmes offered through open and distance learning (ODL) at the Indira Gandhi National Open University (IGNOU). The key argument of the paper will focus on the fact that despite various challenges, field work supervision through ODL provides lot of scope and flexibility to students, generating a cadre of trained social work professionals.

The paper adopts a case study approach in presenting the various methods employed for field work supervision by the University. This section will highlight the achievements in terms of developing indigenous theory course and the best practices adopted by IGNOU to train social work professionals through adequate and timely supervision in the ODL mode.

Field work supervision in the ODL mode poses many challenges, especially when compared to that in the conventional universities. Some of these include irregular meeting of supervisor and student, inability of students to meet supervisor due to several reasons like remote location, poor economic background, lack of leave for working professionals, etc.

There is a need for developing a mechanism to regularly orient field work supervisors in supervising students in the ODL mode. It is recommended that regular field work practicum workshops be conducted for supervisors and students. Viva for field work could be made mandatory at different regional centres. Field work supervision could be enhanced through the use of technology, namely, Skype, e-mail, WhatsApp, etc.

The paper describes the various nuances of field work supervision through ODL system. It is an original work and is of great value in understanding the challenges and difficulties encountered by learners and academic counsellors throughout the process of supervision. The paper highlights important recommendations by the stakeholders themselves in mitigating the challenges faced during field work supervision through ODL.

The purpose of this paper is to investigate the practices that start-ups in emerging economies can implement to design circular economy business models and how they can create and capture value from a circular economy business model.

The paper adopts a qualitative case method approach with semi-structured interviews with start-up founder promoters, its employees, its beneficiaries and its customers, conducted in two local Indian start-ups engaged in the manufacture of products and providing services that promote adoption of circular economy principles.

Analysis of the two business models reveals common patterns in building value proposition. The findings suggest that start-up ventures adopt an iterative approach to produce reusable and interlinked products and co-create with customers, vendors and local communities. They adopt mechanisms that can create, deliver and capture value while maintaining economic viability, and thus contribute towards micro- and macro-level benefits.

This study maximizes the depth of the phenomenon under investigation by leveraging case study methodology. Future research opportunities could be found in quantitative studies to increase the generalizability of the findings of this paper.

The paper presents a theoretical model linking the circular business model design and deployment mechanisms that can be used by start-up entrepreneurs desirous of embracing circular economy principles and thus contribute towards environmental, economic and developmental goals in emerging economies.

To accelerate the transition of adoption of circularity principles in emerging markets, start-up ventures could adopt circular business models that contribute towards achieving positive behavioural change. This can be achieved by integrating with different stakeholders in the value network such that they play a vital role in the process of value creation and delivery and benefit from the value captured.

An interdisciplinary approach that integrates the research streams of circular economy, and business model design has been pursued to identify the design and deployment mechanisms adopted in the circular business models of start-ups in real-world emerging economies’ context.

The purpose of this study is to identify the critical success factors (CSFs) of corporate social responsibility (CSR) in the post-COVID-19 period and to identify the cause–effect relationships amongst those CSFs.

The success factors impacting CSR activities are identified based on inputs from 14 experts in the CSR domain. Thereafter, authors use a statistical approach to identify CSFs with inputs from useable respondents. Finally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to understand the causal relationship between different CSFs.

Using the DEMATEL method, the authors developed an analytical model showing cause–effect aspects of the CSFs and identified seven factors which firms need to emphasize more to execute better CSR activities in the post-COVID-19 period.

The authors asked 14 experts for their inputs, but more experts could have made identifying success factors more comprehensive. In this study, the DEMATEL method found seven CSFs that improve CSR activities in the post-COVID-19 period. Another identification process could have enriched the study. The findings of this study cannot be generalized since this study is based on the inputs of employees from India only.

This proposed analytical model is effective in determining the complex interactions among all impacting CSFs. Firms' CSR managers and policy makers can use the proposed model, especially in the post-COVID-19 period.

The proposed model provides a precise and most accurate analysis for CSFs impacting CSR activities in the post-COVID-19 period. It also provides a unique opportunity for the competent authorities at firms to understand the interaction of different impacting CSFs and takes necessary actions. No other exhaustive analytical model is available in this context.

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.