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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 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.

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.

This study aims to evaluate the short-term impact of brokerage analysts’ recommendations on abnormal returns using a sample selected from the S&P BSE 100 in the Indian context. The efficient market hypothesis, specifically, its semi-strong form, is tested for “Buy” stock recommendations published in the electronic version of Business Standard. The crucial issue is, are there any abnormal returns that can be earned following a recommendation? If so, how quickly do prices incorporate the information value of these recommendations? It tests the impact of analyst recommendations on average abnormal returns (AARs) and standardized abnormal returns (SRs) to determine their statistical significance.

Using a sample of stock recommendations published in the e-version of Business Standard, the event study methodology is used to determine whether AARs and SRs are significantly different from zero for the duration of the event window by using several significance tests.

The findings indicate a marginal opportunity for profit in the short term, restricted to the event day. However, the effect does not persist, i.e. the market is efficient in its semi-strong form implying that investors cannot consistently earn abnormal returns by following analysts’ recommendations. Post the event date, the market reaction to analyst recommendations becomes positive, however, insignificant until the ninth day after the recommendation providing support to the underreaction hypothesis given by Shliefer (2000) and post-recommendation price drift documented by Womack (1996). The study contributes by using different statistical tests to determine the significance of returns.

There are important implications for traders, investors and portfolio managers. The speed with which market prices incorporate publicly available information is useful in formulating trading strategies. However, stock characteristics such as market capitalization, volatility and level of analyst coverage need to be incorporated while making investment decisions.

The study contributes by using different statistical tests to determine the significance of returns.

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.