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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 students will be able to understand the diversity and inclusivity in the recruitment process and different sources of recruitment from the context of school’s managed by the government (state schools); execute job analysis thereby clearly mentioning objectives and performance metrics for the post of principal in the government (state schools); align the succession planning efforts with the organization’s strategic objectives and long-term vision; and evaluate the role of a leader involving integrity, fairness, transparency and accountability and applying ethical principles in decision-making and actions.

The case study exhibits the dilemma faced by a principal Mrs Veena Gandhi in the year 2020–2022 when manpower shortage was the major challenge being faced by the government-run schools in New Delhi NCR. She inculcated inventiveness and practicality in the teaching of elementary education in Nigam Pratibha Vidyalaya. The school’s philosophy was based on creating a learning environment for students so that they could express them, learn and memorize concepts, and had joyful learning. The school managed 50% of the teaching staff, as most of the teachers were promoted to Sarvodaya Vidyalaya run by the department of education in New Delhi. Whereas other teachers were not recruited for the same position which created a demand and supply gap among teaching staff. Now she was going to be retired in January 2023 and was facing a dilemma about her next successor, who could carry forward the philosophies of value-based teaching. She wanted to have such a successor who could carry forward the legacy of the school, but as the school was government-run and the appointment was seniority-wise complete freedom was not in her hands to choose the next principal. By keeping in mind the constraints of authority and entitlement after retirement, she wanted to have the best person for the job who would understand and implement the art integration in teaching and learning.

The case study further engaged the students of BBA in their HR class in reviewing the recruitment and selection strategies in general and succession planning in particular with class discussion. It also targets teaching job analysis concepts to them. Furthermore, it helps them to understand value-based prepositions from the point of view of leaders and comprehend how decisions impact organizational philosophies and culture.

Teaching notes are available for educators only.

CSS6: Human resource management.

COVID entered the world in 2019 as a pandemic and the intensity of this health crisis is only increasing in several regions. Therefore, it is critical to study and detect the public's frame of mind, government and economists' perception regarding the COVID crisis, as well as the primary worries that the public has expressed, and how this evolves over time. Responsive measures towards COVID-19 from the Indian economy have been explored as a key objective. Moreover, efforts have been made to explore recovery in India through economists and policymakers. Data have been explored through online interviews of key economists which were published in leading newspapers and covered through media channels such as NDTV, CNBC, etc. Moreover, various newspapers and reports were explored to understand government initiatives to address COVID-19 in India. The study's findings show how essential economic recovery from the second wave is in India, and how it may be achieved by strong fiscal and monetary policies, as well as specific attention to impoverished households, small and micro-businesses and increased employment. The short-term focus of the developing economic strategy must be on giving crisis relief to the most unprotected segments of society since long-term system stimulation is impossible.

This study examines how intellectual capital (IC) drives firm performance via the lens of dynamic capabilities (DCs). Drawing on resource-based view (RBV) and dynamic capability view (DCV), the authors elaborate the mediating role of learning, integration and reconfiguration DC in the Indian banking context.

A sample of 358 top- and middle-level managers from the Indian banking sector was administered with structured questionnaires for data collection. Structural equation modeling (SEM) and Sobel test were used to analyze the data and test the hypothesized mediating effect.

The findings reveal that learning and integration DCs are key mediators in IC and banks' performance relationships in an emerging economy context. In contrast, the analysis revealed partial mediating role of reconfiguration DC. Furthermore, the learning DC has been identified as the primary mediating mechanism for transforming bank's IC into performance benefits.

This study provides an important implication for the IC and DC link by empirically developing and validating a model in the Indian banking sector and making a several contributions to the related literature. This sector needs to incorporate and strengthen their IC and DCs to attain enhanced performance in today's dynamic environment. Bank managers can use these findings to bring their knowledge-related activities to channelize specific DCs to transform banks' IC when seeking to improve overall performance. Theoretically, this study extends previous research by outlining a set of organizational elements that tend to influence firm performances with the help of IC, learning, integration and reconfigurations DCs.

Although several studies have investigated the links between IC, DC and firm performance, studies on emerging economies are scarce. This study is one of the most in-depth investigations of the relationship between IC, learning, integration and reconfiguration DCs and firm performance in an integrated framework, with a particular focus on the banking sector of an emerging economy.

Task conflict and relationship conflict are common in organizations. This paper aims to present a unique case of the use of the targeted conflict-resolution technique. The revival of positive group dynamics is aptly shown.

This descriptive case study is developed as a practice insight to showcase how a peculiar case of misunderstanding is resolved in the most unconventional way through the intervention of a mediator who unearths the real cause of contention. The mediator works through logic and emotion to remove negativity. Narration, a necessary component of the case study approach, peeps into the research subject involving flashbacks, flash forward, backstories and foreshadowing. The mediator uses reframing as a tool very efficiently, encouraging the people in conflict to understand the nothingness in their cold war and eventually prompting them to collaborate and compromise.

The shifts in communication dynamics post-mediator’s intervention are subtle and full of wisdom, encouraging introspection and constructive interaction, eventually bridging the differences. The possibility of achieving a state of homeostasis in the future magnifies. The belief in the power of affirmation and manifestation is validated. The heavy, difficult, hardened negativity loses ground and gets transformed.

Conversation/prayers at the deepest level in several meetings are the communication tools that have immense social relevance in the Indian context.

A unique combination of intermediation encompassing written communication and energy transformation is adopted to resolve ongoing conflict by stroking the positive psychology of the partakers. To some, the method may appear to have a spiritual connotation.

As fitness apps have integrated gamification elements into their design to transform exercise into a compelling and competitive experience, this study draws on the expectation confirmation model (ECM) and self-determination theory (SDT) to propose a comprehensive framework for sustained usage by satisfying the psychological needs of users.

A longitudinal study design is utilized where data from 598 fitness app users were gathered over two distinct phases separated by 24 weeks, where data were analyzed using structural equation modeling.

The findings until phase 1 depict that motivational affordances significantly affect mastery, autonomy and relatedness, which in turn exert a significant influence on flow. Identification and compliance have a more pronounced effect in phase 2 compared to stage 1 of the analysis.

Individuals are more prone to being swayed by fellow members of their social group who share an affiliation with fitness apps, leading them to sustain their usage of fitness apps. These insights can potentially guide app developers and marketers in formulating strategies based on modifiable factors to foster sustained growth for gamified fitness apps.

This study takes a novel stance by employing social impact theory (SIT) in a longitudinal setting to reveal how users react to identification and compliance effects during initial and post-adoption usage of gamified fitness apps.

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.

Achieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.

An integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.

The results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.

A new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.

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).

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.