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The volatile nature of foreign portfolio flows, especially flows into debt market, has large implications on financial and macroeconomic stability in recipient countries. It is necessary to identify the main drivers of portfolio investments in bond market of developing economies to design effective policies to enhance resilience of the economy and help in managing capital flow volatility. The determinants of foreign portfolio investment to Indian equity market have been examined in literature, but flows to bond market remain unexplored. Thus, the purpose of this paper is to identify the possible determinants of foreign portfolio flows to Indian bond market both in the short and in the long run.

This study carries out a time series analysis by deploying autoregressive distributed lag (ARDL) approach to cointegration of monthly data of the period from January 2002 to December 2016 for the Indian economy. A mix of pull and push factors has been analysed in this study. Domestic growth, domestic stock market performance, interest rate differential, exchange rate, volatility in exchange rate, stock market returns in other emerging economies, foreign output growth and dummy variables to trace the external developments such as global financial crisis and unconventional monetary policies of advanced economies have been used as explanatory variables.

The dominant pull factor such as interest rate differential explains the dynamics of flows in Indian bond market. The relationship between capital movements and interest rate differentials is the most accepted paradigm in international finance (Haynes, 1988). Among other domestic factors are stock market performance, volatility in exchange rates and domestic growth rates which are found to be significant drivers of foreign portfolio bond flows to India. The study also confirmed that global conditions could induce a fast outflow of capital from India.

The study concludes that both domestic factors and external factors are equally important in determining the foreign portfolio investments in the Indian debt market.

The empirical analysis conducted in this study suggests that direct and indirect measures can be taken to increase and stabilise foreign investments in the Indian bond market. Direct policy measures refer to those tools which are under the ambit of policymakers. Indirect measures comprise those tools that are not under the direct control of the fiscal and monetary authorities but require coordinated efforts of the government and private sector. In this context, strengthening of not only financial and economic but also administrative institutions will be necessary. Creditworthiness and policy credibility should be improved to address erratic foreign portfolio investment in debt market of India.

This study is an original research study. This study adds to the existing literature and is expected to guide policymakers on the specific aspect of the management of capital flows as it gets affected by changes in monetary and fiscal policies.

The purpose of this study is to examine the continuance intentions of working professionals to pursue e-learning courses as a path for career advancement. The primary objective of this study is to ascertain the predictors of continued intentions of working professionals to pursue e-learning courses and examine if this is a trend in career development.

Perceived usefulness of e-learning, motivation and satisfaction are independent variables which are examined using a regression model as potential determinants of continued intentions to use various e-learning platforms. Data from 240 working professionals in different sectors was collected. In addition, satisfaction, motivation and perceived usefulness among the male and female respondents are compared using ANOVA.

The findings showed that motivation, satisfaction and perceived usefulness of e-learning are significant predictors and have a strong influence on the continued intentions of working professionals to pursue e-learning courses. In addition, the results showed that motivation levels while pursuing e-learning and satisfaction derived from them were higher for female professionals.

This study identifies the antecedents of the continued intentions of working professionals to pursue e-learning courses on the path of career advancement. The outcome of the study can be used by educators and e-content creators to make e-learning more engaging. Corporates can also use the results of this study to identify initiatives that can encourage the pursuit of e-learning.

This study provides an important insight exploring the antecedents of continued intentions of working professionals to pursue e-learning courses as a path of career advancement. The research contributes significantly to the understanding thought process of working professionals towards their careers.

The purpose of the study is to analyze a sample of 528 published papers over the past 11 years by conducting a bibliometric analysis. The study also aims to provide a consolidated overview of the existing literature on “gaming addiction” and presents the status of research with future directions for researchers who wish to explore and contribute to this rapidly evolving field. The descriptive statistics have been conducted through citation and co-citation analysis.

For the bibliometric analysis, the documents were retrieved from the Scopus database with the help of the Scopus analyzer while the VOS viewer1.6.16 software was used to analyze citations, co-authorship, etc. The literature search strategy was applied across various databases and the articles published between 2010 and December 2021 giving a total of 1,219 articles across all disciplines. Finally, 528 articles were shortlisted through the query restricted to subject areas, namely, business management, psychology, social science and multidisciplinary areas.

IGA has also been recognized by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, as one of the disorders; hence, this certainly calls for focussed efforts to understand the same and control further damage. The number of articles devoted to the study of “gaming addiction” has increased rapidly in recent years. Moreover, this study identifies some of the most influential articles in this area. Finally, this paper highlights the new trends and discusses the future research associated with gaming addiction.

This study focusses on gaming addiction and its trends, related to researchers and country-wise contributions. This is one of the few studies to review the literature on gaming addiction by using citation and co-citation analysis. The main findings of this paper will help academicians and practitioners to improve the body of knowledge on the topic and provide an overview of promising future research avenues.

Internet gaming is a newly emerging area and studies related to gaming addiction are very recent. To the best of the authors’ knowledge, this study is a unique and comprehensive overview of the leading works done in this area.

The primary objective of the study is to discover the most prominent criteria and sub-criteria among environmental issues, social dimensions and corporate governance factors that may impact individual equity investors' investment decisions.

The present study collected data from 438 individual equity investors from the North Indian region. To achieve the objectives of the study, a fuzzy analytic hierarchy process (Fuzzy AHP) was applied. The key considerations of the study were environmental, social and governance (ESG) factors.

The governance criterion was discovered to be the most significant factor influencing individual equity investors' investment decisions among the three ESG factors, followed by environmental criteria, while social criteria were shown to be the least influential.

The present study solely looked at ESG issues as drivers of stock investors' investment decisions. In the current world, however, many other factors, including behavioral biases, accounting information, ownership structure and fundamental analysis, can have a substantial influence on investors' investment decisions.

The study's findings widen the theoretical contribution in the field of responsible investment by asserting how ESG factors influence investors' investment decisions in the equity market. From a practical standpoint, this study applies to retail and institutional investors, portfolio managers, financial advisors, market regulators, corporations and society at large.

To the best of authors knowledge, no attempt has been made to prioritize the ESG issues that impact the investment decisions of individual equity investors. Ergo, this study contributes to the existing literature on socially responsible investment.

Achieving sustainable development in terms of people, prosperity and partnership is the main aspect in any country’s plan for development. This sustainable development has to be achieved in three major dimensions, that is, economic, social and environmental in an integrated, balanced and systematic way. The same is highlighted in the United Nations’ (UN) vision for sustainable development by 2030. The purpose of this study is to identify the critical barriers of urban sustainability and gender equality with reference to Indian context, to suggest the strategies to achieve sustainable development in the referred area and to evaluate the relationship between them.

The major contribution of this study lies in the development of a contextual relationship model from the various identified critical barriers in Indian context, using interpretive structural modeling with MICMAC analysis.

Of the 17 goals given by UN, considering the Indian context, the goals of building resilient infrastructure, promoting inclusive and sustainable industrialization and fostering innovation; promoting sustained and inclusive economic growth along with full and productive employment and decent work for all; and gender equality and empowering women at all levels seem to be the major challenges and the same are selected in this study for further analysis. To understand the major challenges in these areas and also to find the way forward, the study has set following three major objectives: to identify the critical barriers of urban sustainability and gender equality with reference to Indian context; to suggest the strategies to achieve sustainable development in the referred area; and to evaluate the relationship between them.

Considering the highly volatile and complex demand requirements, this approach may help to enable the government to tackle issues/challenges related to both urban sustainability and gender inequality on priority basis and in a holistic manner to achieve the goals of sustainable development, thereby improving the quality of life.

The concepts of showrooming and webrooming have been well researched but majorly from the marketing/economic perspectives. The present study explores the socio-psychological motivations and different types of satisfaction derived from “cross-shopping” behaviour namely, showrooming and webrooming in a developing nation.

The study is exploratory and is conducted using an interpretive approach. The researchers conducted 52 in-depth interviews and the collected data were subjected to open and axial coding to generate the conceptual model.

The findings indicate various motivations of cross-shopping such a habit and the joy of discovery while novel aspects of satisfaction emerge such as process satisfaction and social satisfaction. The findings also revealed contextual moderators of the cross-shopping process.

The present study contributes to the domain of cross shopping behaviour by illustrating the social motivators behind the same and novel satisfaction outcomes because of the cross-shopping process.

The present study has multiple implications that would enable managers to effectively utilize cross shopping behaviour such understanding of satisfaction beyond those derived from the product only.

This is one of the first studies to investigate consumer behaviour related to cross shopping based on psycho-social dimensions.

This article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.

20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.

The study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.

This study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.

This study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.

The purpose of this research is to develop a building information modelling (BIM)-enabled sustainable design process model that identifies critical decisions actions in the design process along with the information and level of detail that facilitate an informed and timely decision. Building performance analysis is usually performed after the design and construction documents are produced, resulting in lost opportunities.

A number of research methods have been adopted; these include extensive literature review and 11 in-depth exploratory interviews with industry practitioners (sustainable building design experts, early BIM adopters).

Project delivery methods have a significant effect on the sustainable outcome of buildings. The development of a structured process can assist sustainable design practice among building professionals. Learning from implemented projects, that have utilised BIM processes, facilitates the scope of creating this process and advises future projects to prevent failures. Process mapping is essential to streamline the process, support key project processes and help the design team manage their own responsibilities and deliverables required by them.

The identification of the gap and the need for a structured process for sustainable building design for BIM execution is discussed. The synergies that exist between BIM, building performance modelling, Building Research Establishment’s Environmental Assessment Method assessment and the Royal Institute of British Architects Plan of Work are shown. The effect that project delivery has on sustainable design outcome has been established. A coordinated collaborative design process model is presented based on the findings from interviewing early adopters.

In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI’s influence on supply chain risk mitigation (SCRM).

This study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses.

This study’s findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence.

This study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

This paper aims to illustrate the scope and challenges of using computer-aided content analysis in international marketing with the aim to capture consumer sentiments about COVID-19 from multi-lingual tweets.

The study is based on some 35 million original COVID-19-related tweets. The study methodology illustrates the use of supervised machine learning and artificial neural network techniques to conduct extensive information extraction.

The authors identified more than two million tweets from six countries and categorized them into PESTEL (i.e. Political, Economic, Social, Technological, Environmental and Legal) dimensions. The extracted consumer sentiments and associated emotions show substantial differences across countries. Our analyses highlight opportunities and challenges inherent in using multi-lingual online sentiment analysis in international marketing. Based on these insights, several future research directions are proposed.

First, the authors contribute to methodology development in international marketing by providing a “use-case” for computer-aided text mining in a multi-lingual context. Second, the authors add to the knowledge on differences in COVID-19-related consumer sentiments in different countries. Third, the authors provide avenues for future research on the analysis of unstructured multi-media posts.