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This study aims to analyse whether investment in green and sustainable stocks provide some cushion during current precarious time. To compare the impact of COVID-19 on the volatility of sustainable and market-capitalisation-based stocks, daily returns from Greenex, Carbonex, Large-Cap, Mid-Cap and Small-Cap index have been analysed over a period of six years from 2015 to 2021.

At the outset, logarithmic return of all selected indices has been tested for possible unit root and heteroscedastic. On confirmation of stationarity and heteroscedasticity of data, auto-regressive conditional heteroscedastic models have been applied. Thereafter, volatility is modelled through best suitable model as suggested by Akaike and Schwarz information criterions.

The findings indicate the positive impact of COVID-19 on the volatility of the indices. Asymmetric power ARCH model indicates highest significant impact of COVID-19 over the volatility of Large-Cap index, whereas exponential GARCH model detected highest significant impact of COVID-19 over the volatility of Mid-Cap Index.

To the best of the authors’ knowledge, the present study is original in the sense that it aimed at comparing the possible impact of COVID-19 over sustainable and market-capitalisation-based indices.

The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both national and international agricultural organizations to promote CSAPs in India, adoption of these practices is low. This study aims to examine the elements that affect the likelihood and intensity of adoption of multiple CSAPs in Bihar, India.

The probability and intensity of adoption of CSAPs are analyzed using multivariate and ordered probit models, respectively.

The results show significant correlations between multiple CSAPs, indicating that their adoptions are interrelated, providing opportunities to exploit the complementarities. The results confirm that both the probability and intensity of adoption of CSAPs are affected by numerous factors, such as demographic characteristics, farm plot features, access to market, socio-economics, climate risks, access to extension services and training. Farmers who perceive high temperature as the major climate risk factor are more likely to adopt crop diversification and minimum tillage. Farmers are less likely to adopt site-specific nutrient management if faced with short winters; however, they are more likely to adopt minimum tillage in this case. Training on agricultural issues is found to have a positive impact on the likelihood and the intensity of CSAPs adoption.

The major policy recommendations coming from of our results are to strengthen local institutions (public extension services, etc.) and to provide more training on CSAPs.

By applying multivariate and ordered probit models, this paper provides some insights on the long-standing discussions on whether farmers adopt CSAPs in a piecemeal or in a composite way.

With a growing preference for active, authentic, and cultural experiences over traditional ones, creative tourism has garnered significant academic interest. This study offers a comprehensive review of creative tourism research, delineating its evolution, prominent contributors, pivotal areas, and prospective trajectories through a bibliometric analysis.

Employing a bibliometric analysis using the biblioshiny and VOSviewer software, this study systematically reviews 198 articles on creative tourism identified and retrieved from the Scopus database.

A notable increase in creative tourism research is witnessed in recent times, with Portugal and the Netherlands leading in publications and citations, respectively. This review also pinpoints key authors, countries, institutions, and journals shaping the field, and presents emerging themes such as authenticity and creative experience, culture and heritage, urban and rural contexts, and co-creation in creative tourism.

Identifying core research contributors (authors, countries, institutions, journals) and contributions (themes, topics) assists academics in seeking collaborations and shaping future research. Practitioners are advised to adapt these trends (authenticity, co-creation, sustainability) into their strategic planning to meet market demands.

This study offers a seminal review of creative tourism through a bibliometric analysis, a technique that leverages the power of technology (data, software) to engage in retrospection and projection—the hallmark of benchmarking studies across fields, including tourism. Noteworthily, this study provides a detailed summary of the field’s trajectory and significant trends, positioning itself as an essential reference for academic scholars, industry professionals, and policymakers with a keen interest in creative tourism.

The primary purpose of this paper is to examine how generative Artificial Intelligence (AI) such as ChatGPT may serve as a new context for management theories and concepts.

The paper presents the analyses of selected management theories on decision-making, knowledge management, customer service, human resource management and administrative tasks and explains what may change after generative AI adoption.

The paper indicates that some management theories and concepts need to be studied in the generative AI environment that may influence managerial work at the strategic, functional and administrative levels.

This paper is an opinion piece article and does not refer to empirical data. It formulates some conclusions to further empirical research studies.

The paper analyzes selected management theories in a new technological setting. The paper also provides information about the functions of generative AI that are useful in understanding and overcoming how new technology may change organizations and management.

This paper aims to examine the factors affecting the implementation of corporate social responsibility (CSR) sustainably in mobile operators in the kingdom of Bahrain.

The research relies on the existing literature as a secondary data source. The primary data was collected through questionnaires distributed to three leading mobile operators in the Kingdom of Bahrain. The research's population numbered 1,689, and the sample size was 313; the simple random sampling method was used for data collection with a response rate of 87.2% out of a total sample size of 273 respondents. In addition, the responses were analyzed using statistical package for the social sciences (SPSS) software version 24.0; specifically, Spearman's rank correlation was used to test the hypotheses. The research design was quantitative, so a nonparametric procedure was applied to test the hypotheses.

The research produced positive relationships between the independent variables (economic, legal, ethical, philanthropic and environmental responsibilities) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The research produced positive relationships between the independent variables (economic responsibility, legal responsibility, ethical responsibility, philanthropic responsibility and environmental responsibility) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The outcomes of the research mainly suggest that mobile operators assign employees who have been working with the company for more than 7 years to implement CSR; due to their engagement to implement CSR as a sustainable practice more than others with less than 3 years or 3-6 years in Bahrain mobile operators. Besides, the research provides a starting point by which other researchers could investigate CSR in other sectors in the Kingdom of Bahrain.

The research provided a framework for Bahrain mobile operators to assist them in enhancing the implementation of CSR in a sustainable manner, which are economic, legal, ethical, philanthropic and environmental responsibilities.

Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the wheat production season in India. This study aims to examine whether farmers learn from their past experiences of exposure to climate extremes and use the knowledge to better adapt to future climate extremes.

The authors used data collected from 184 farmers from Haryana over three consecutive wheat seasons from 2013-2014 to 2015-2016 and multivariate logit model to analyse the driver of the adoption of CAW as an ex ante climate risk mitigating strategies based on their learning and censored Tobit model to analyse the intensity of adoption of CAW as an ex ante climate risk mitigation strategy. Farmer’s knowledge and key barriers to the adoption of CAW were determined through focus group discussions.

The analysis shows that the majority of farmers who had applied CAW in the year 2014-2015 (a year with untimely excess rainfall during the wheat season) have continued to practice CAW and have increased the proportion of land area allocated to it. Many farmers shifted from CTW to CAW in 2015-2016.

While farmers now consider CAW as an ex ante measure to climate risks, a technology knowledge gap exists, which limits its adoption. Therefore, designing appropriate methods to communicate scientific evidence is crucial.

This paper uses three years panel data from 184 farm households in Haryana, India, together with focus groups discussions with farmers and interviews with key informants to assess if farmers learn adaptation to climate change from past climate extremes.

The authors examine the impacts of corporate announcements on stock returns during the pandemic stress.

The authors employ the event study methodology with the market model on a sample of 90 events (announcement and ex-date).

The authors find that all the corporate announcements do not impact the stock returns in a similar pattern. While the bonus announcement, ex-bonus and ex-split events led to positive significant abnormal returns on the event date, the rights issue and stock-split announcements failed to influence the stock returns. The findings suggest that before making such announcements, the corporates should wait until the market recovers because even the positively impacting events result in negative market responses during pandemic stress.

This study will guide the policymakers to stimulate share prices during such pandemics with the help of various corporate announcements. The investors will be assisted in understanding the stock market mechanism and making wise decisions before reacting to corporate actions during a pandemic or emergency period. While the policymakers are concerned with influencing the share prices, the investors are concerned with the composition of the risk-return parameters in their portfolio. This study will act as an essential investment tool for both.

To the best of the authors’ knowledge, the authors conduct the first-ever study to examine the impacts of corporate announcements during a pandemic stress period that significantly contributes to the literature. The authors examine the announcement effects in India and accurately anticipate that this study will be a pioneer in this field. This study also paves the way for future researches in this area.

The purpose of this paper is to research the impact of digitalization on employees' future competencies and the conditional role of human resource development (HRD) in the relationship between independent and dependent variables.

Empirical research covered 1209 enterprises from all of Slovakia, Poland and the Czech Republic. The research was conducted from 2019 to 2021. Using structural equation modeling (SEM), a theoretical model was tested and verified.

Confirmatory factor analysis has shown a good fit for the tested model. The purpose and character of our data showed a good alignment with the SEM partial least squares method, as the goal is to predict a construct. The model showed that employee-oriented digitalization positively affected the employees' future competencies, with no impact of customer-oriented digitalization treated as a control variable. Also, the moderating role of HRD has not been shown to be significant for the “digitalization – competencies” relationship.

Previous studies on the development of personnel competencies treated these competencies as antecedents of digital transformation and examined the formal role of HRD in building the competencies. The novelty of this study lies in exploring the pattern of interactions among the impact of an environment built by innovative technologies and HRD on the competencies of the future. Also, the research embedded in the environment of Poland, the Czech Republic and Slovakia has contributed to the complex understanding of the transition to digitalization, as this region has often been omitted in the field of human resource management (HRM) research focused on exploring digital transformation.

Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.