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The study attempts to examine the effect of the COVID-19 pandemic on the economic growth and public debt of the Indian economy. The authors also attempt to make quarterly projections of economic growth and external debt (ED) for the next five years. The objective is to understand how much time the economy takes to recover and at what pace. Consequently, this study elucidates the composition of debt after the crisis in the next five years.

To predict India's gross domestic product (GDP) and ED for the next five years, the authors used an auto-regressive integrated moving average (ARIMA) model. This model was built under a Box–Jenkins methodology (Box and Jenkins, 1976) and was subjected to an augmented Dickey–Fuller (ADF) test to check the stationarity of the data. The methodology includes three main steps to estimate and forecast the model: identification, estimation, and diagnostic and forecasting.

The study finds that the outbreak of the COVID-19 pandemic has significant implications for economic growth and public debt. The economy faced contraction in the first quarter of the year 2020 due to the suspension of economic activities and still struggling with the negative values of GDP. The forecasting results reveal that ED will continue to grow to meet the increasing health expenditure needs, and GDP will also bounce back slowly after the end of the year 2021. It has been noticed that the recurrent crisis derails the developing economies from the path of sustainable development to a prolonged economic slump with mounting public debt.

The study examines the impact of the COVID-19 pandemic on economic growth and public debt with particular reference to India. To the best of the authors’ knowledge, this is the first time the quarterly projections for GDP and ED have been made after the COVID-19 crisis.

The study aims to examine the influence of Unified Theory of Acceptance and Use of Technology (UTAUT) and anthropomorphic design cues in determining the level of satisfaction among banking chatbot users. It also tests the moderating impact of the localization of content on the relationship. The study also encompasses expectation confirmation, elucidating the significance of perceived trust in maintaining intention.

The study conducted a comprehensive online survey, collecting 667 questionnaires from users of conversational chatbots in both public and private sector banks. We analyse the data using Partial Least Squares Structural Equation Modelling and fuzzy-set Qualitative Comparative Analysis.

Performance and effort expectancy, perceived interestingness of interaction and perceived empathy were identified as significant indicators, whereas facilitating conditions, social influence and perceived intelligence were not significant in explaining satisfaction. Perceived trust was a significant mediator, while localization was a significant moderator in all the cases except social influence and satisfaction.

To improve perceived intelligence and empathy, tech developers should focus on improving the chatbot’s ability to maintain contextual understanding within a conversation where it can remember and reference previous interactions. Future studies might explore the development of banking chatbots that incorporate advanced levels of anthropomorphic characteristics, whether visual or intuitive.

The work is unique in that it integrates UTATUT, anthropomorphism and expectation confirmation model in the context of conversational banking chatbots, which is not achievable in a single theory-based model. The study also underlined the necessity of localizing chatbot content, recommending that banks engage localized native speakers to help with chatbot training and content creation, where specialists can fine-tune the conversational features.

The purpose of the study is twofold. First, it aims to analyse the impact of green human resource management (GHRM) on green employee creativity. Second, it further explores the mediating role of personal moral norms between GHRM and green employee creativity.

Through multi-source and multi-level analysis, data was collected from 46 managers and 315 employees to investigate the role of personal moral norms in GHRM and green employee creativity. For data analysis, multi-level structural equation modelling was applied using Mplus software version 8.6.

Positive and significant effects were observed between GHRM, personal moral norms and green employee creativity. However, personal moral norms partially mediated the relationship between GHRM and green employee creativity.

The study is first in itself to explore the interplay between the variables in a multi-level manner. The present study aims at addressing the urgent call by the United Nations regarding Sustainable Development Goals (SDGs) for three key SDGs, focussing on decent work and economic growth (SDG 8), boosting industry, innovation and infrastructure (SDG 9) and supporting climate action (SDG 12).

The purpose of this paper is to determine the relationship between employee empowerment (structural empowerment [SE] and psychological empowerment [PE]), employee commitment (EC) and organizational citizenship behavior (OCB) within the unique context of a learning organization in the Indian retail sector.

The investigation was conducted using a survey-based questionnaire approach. Data were gathered from 222 frontline employees working in different retail stores in India. The researcher used AMOS 22.0 version and SPSS 22.0 version for the data analysis.

This study concluded that SE and PE have a positive and significant influence on OCB and EC. In addition, EC is a mediator between employee empowerment (SE and PE) and OCB.

This research is built on cross-sectional data with a limited sample size, that is, 222 sample size. This study also offers some practical insights to managers of retail stores.

To the best of authors’ knowledge, this study is the first to empirically investigate the mediating role of EC between SE and OCB. By focusing on the interplay of these variables within a learning organization, this study sheds light on the mechanisms driving employee behavior and organizational dynamics in this rapidly evolving retail sector.

The Indian government’s launch of Digital India initiative is critical to achieving a sustainable future by leveraging digital capabilities to promote social justice, economic prosperity and environmental stewardship. There are a lot of factors affecting digital India’s transformation to achieve sustainable development goals. This study aims to identify, examine and develop an empirical model estimating the relationship among enablers affecting and enhancing digital India’s transformation toward sustainability.

Following a thorough review of the literature, 10 key enablers were identified and analyzed using the total interpretive structural model (TISM). This novel approach has been adopted to analyze the hierarchical linkage between identified Enablers. Further Matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis technique is used to evaluate the driving and dependence power among enablers.

Findings show that the government’s supportive policy is the strategic enabler with the highest driving power, positioned at the bottom of the model. The government must support digital empowerment initiatives to ensure all individuals have access to the information they require to make proper decisions regarding their lives. This study examines the literature to generalize the findings to focus on the motivator of digital India transformation to achieve sustainable development goals.

This study suggests that TISM and MICMAC-based hierarchical models help practitioners, managers and other stakeholders to focus more on strategic factors to enhance the performance aspects of digital transformation. Government, business and academic cooperation promotes a comprehensive approach to environmental sustainability by stimulating innovation and digital approach implementation.

In addition, it offers novel insights into the enablers, such as how the identified enablers interact with one another depending on the drive and dependency power to achieve the goals of digital India’s transformation to achieve sustainable development goals.