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Purpose: This study investigates the influence of inflation and oil price fluctuations on stock prices and returns. A thorough bibliometric analysis of research articles published in the last 22 years has been conducted to achieve this objective.

Need for the Study: Inflation and oil prices are critical macroeconomic variables that significantly impact the economy, including the stock market. It is crucial for investors and policymakers to understand the complex relationship between these economic variables and the stock market.

Methodology: The study employed a bibliometric analysis to identify the most influential authors, institutions, and research themes related to the impact of inflation and oil prices on stock prices.

Findings: The study identified that the fluctuations of the stock market are significantly influenced by both inflation and oil prices. This relationship has been extensively studied in the literature, with several key research themes identified. These themes include the effects of inflation and oil prices on various sectors and industries, the role played by monetary and fiscal policy, and the impact of international trade and global economic conditions.

Practical Implications: The insights that have emerged have significant implications for investors and policymakers. It highlights the need for risk management strategies and mitigation of macroeconomic factors’ impact on stock prices.

This article aims to explain how organizations create and integrate medical knowledge to develop AI-based medical solutions. The study resulted from a discussion on value co-production with digital technologies and the capabilities needed for it.

The study explores the case of value co-production with the digitalization of traditional medical stethoscopes. It considers integrated resources to create AI-based medical solutions, actors engaged in co-production and activities related mainly to knowledge embodiment.

This article presents operand and operant resources integration when AI is implemented in innovative medical solutions. Furthermore, it shows which activities are undertaken for value co-production and what roles actors from various fields play in resource integration.

Our article discusses the integration of knowledge and the role of knowledge embodiment among resource integration in value co-production when working on AI.

The purpose of this study is to increase the resilience capacity of residential health-care professionals to achieve intrapreneurial development in workers. Through training based on the development of emotional competencies and the application of mindfulness techniques, the aim is for the individual to become aware of his or her role, learn to manage emotions and reduce feelings of distress and anxiety.

The proposed programme has a duration of eight weeks. Every four days of training, mindfulness sessions are integrated, and at the beginning and end of the working day, 10 min are spent with superiors to give feedback on what happened during the day and the setting of new objectives. A control group is also established where they do not undergo such training. After the delivery of the programme, the results obtained after the application of the methodology to a sample of 91 residential health-care professionals are presented. By means of a validated resilience questionnaire composed of 25 items, the aim is to measure the resilience capacity of the participants before and after training and to observe the impact of the programme.

The results of this study show that the training has led to an improvement in the overall resilience capacity by 3.93% and has been able to reduce the existing gap between those over 45 years of age and younger people, although the age-related variable still represents a significant difference.

This study provides an innovative way of fostering entrepreneurship. While participants work on resilience management through mindfulness techniques, organisational commitment is achieved.

Demand planning (DP) is a key element of supply chain management (SCM) and is widely regarded as an important catalyst for improving supply chain performance. Regarding the availability of technology to process large amounts of data, artificial intelligence (AI) has received increasing attention in the DP literature in recent years, but there are no reviews of studies on the application of AI in supply chain DP. Given the importance and value of this research area, we aimed to review the current body of knowledge on the application of AI in DP to improve SCM performance.

Using a systematic literature review approach, we identified 141 peer-reviewed articles and conducted content analysis to examine the body of knowledge on AI in DP in the academic literature published from 2012 to 2023.

We found that AI in DP is still in its early stages of development. The literature is dominated by modelling studies. We identified three knowledge clusters for AI in DP: AI tools and techniques, AI applications for supply chain functions and the impact of AI on digital SCM. The three knowledge domains are conceptualised in a framework to demonstrate how AI can be deployed in DP to improve SCM performance. However, challenges remain. We identify gaps in the literature that make suggestions for further research in this area.

This study makes a theoretical contribution by identifying the key elements in applying AI in DP for SCM. The proposed conceptual framework can be used to help guide further empirical research and can help companies to implement AI in DP.

This paper intends to contribute to the evolving understanding of Indian adolescents as consumers by examining their unique relationships with food brands, focusing specifically on brand love. It further investigates the key drivers that cultivate brand love among adolescents and explores the resulting outcomes of brand love.

About 37 in-depth interviews, including three exercises, were conducted with adolescents aged 11–16. The first and second exercises used projective techniques to explore respondents’ culture-bound love relationships with their favorite brands. Using the laddering technique, the third exercise investigated the critical drivers of respondents’ brand love.

The study reveals that adolescents derive value through attribute-benefit-value linkages from the consumption experience, leading to brand love. The customer value–brand love dynamics result in adolescents’ customer engagement behavior. Additionally, Indian adolescent customers seek brand consumption as a medium to instate their social identity and achieve hedonic pleasure from the experience. The study highlights the role of socialization and attitudinal autonomy in shaping adolescent–brand interactions.

The study could be relevant for both academicians and practitioners as they unveil the consumer psychology of contemporary adolescents in emerging countries like India and how similar or different they are from adult consumers. Also, there are very few adolescent–brand relationship studies in the past that have been deliberated in the context of food brands. Brand managers may design their product development and communication appeals around higher levels of abstraction in the attribute-benefit-value linkages discovered by this study.

This research investigates the complex relationship between economic policy uncertainty (EPU), energy consumption and institutional factors in the Gulf region. The purpose of this study is to examine how institutional factors moderate the impact of EPU on energy consumption in Gulf countries.

This paper uses the dynamic panel autoregressive distributed lag (PARDL) method, over a period stretching from 1996 to 2021 in the Gulf countries.

The results show that, only in the long term, EPU has a positive and significant impact on energy consumption, suggesting that increased EPU leads to increased energy use. Furthermore, this study found that, only in the long term, government effectiveness and regulatory quality have positive and significant effect on energy consumption. Accordingly, the two institutional factors play a moderating role in the EPU−energy consumption nexus.

This study highlights the importance of considering the time dimension when formulating energy and economic policies in Gulf countries. Policymakers should take into consideration the nature of these relationships to make informed decisions that promote energy efficiency and economic stability in the region.

To the best of the authors’ knowledge, this is the first study examining the relationship between EPU and energy consumption in the Gulf countries while incorporating the role of institutional factors as potential mediators.

Automated social media messaging tactics can undermine trust in health institutions and public health advice. As such, we examine automated software programs (ASPs) and social bots in the Twitter anti-vaccine discourse before and after the release of COVID-19 vaccines.

We compare two Twitter datasets comprising user accounts and associated English-language tweets featuring the keywords “#antivaxx” or “anti-vaxx.” The first dataset, from 2018 (pre-COVID vaccine), includes 3,154 user accounts and 6,380 tweets. The second comprises 327,067 accounts and 545,268 tweets published during the 12 months following December 1, 2020 (post-COVID vaccine). Using Information Laundering Theory (ILT), the datasets were examined manually and through user analytics and machine learning to identify activity, visibility, verification status, vaccine position, and ASP or bot technology use.

The post-COVID vaccine dataset showed an increase in highly probable bot accounts (31.09%) and anti-vaccine accounts. However, both datasets were dominated by pro-vaccine accounts; most highly active (59%) and highly visible (50%) accounts classified as probable bots were pro-vaccine.

This research is the first to compare bot behaviors in the “#antivaxx” discourse before and after the release of COVID-19 vaccines. The prevalence of mostly benevolent probable bot accounts suggests a potential overstatement of the threat posed by anti-vaccine accounts using ASPs or bot technologies. By highlighting bots as intermediaries that disseminate both pro- and anti-vaccine content, we extend ILT by identifying a benevolent variant and offering insights into bots as “pathways” to generating mainstream information.

This paper aims to investigate the extent of transgender (TG) inclusivity in workplaces, particularly comparing developed and developing economies. It seeks to address the social stigma faced by TG individuals in Asian economies, notably focusing on India. Through qualitative studies, the research identifies barriers hindering TG employment and proposes a theoretical framework to guide organizations in creating TG-inclusive work environments. The research intends to provide insights that enhance the experiences of TG employees while promoting diversity and inclusion in organizations.

This research comprises two qualitative studies aimed at first identifying barriers to TG employment through the lens of human resources (HR) professionals and then suggesting a theoretical framework to organizations for overcoming these barriers to achieve a TG-inclusive workplace. Thematic analysis, using Atlas.Ti software, and the interpretive structural modelling technique were used to synthesize a conceptual framework.

This study's outcomes highlight a substantial gap in achieving truly TG-inclusive workplaces, particularly in economies with prevalent social stigma like India. The findings show that traditional means may not be enough for building a TG-inclusive workplace, and organizations need to go the extra mile by promoting positive deviance and TG-centric corporate social responsibility initiatives to achieve results.

The results of this study provide insights for organizations seeking to improve the experiences of their TG employees and promote diversity and inclusion in the workplace. The incorporation of HR professionals' insights offers a practical perspective, and the conceptual framework proposed for organizations to overcome TG employment barriers is a novel contribution.

This study aims to examine the impact of non-fungible tokens (NFTs’) characteristics on Chinese consumers’ purchase intention towards luxury fashion physical products. It also investigates the mediating role of perceived hedonic value and moderating role of perceived NFT–physical product fit during the buying process.

A conceptual model combining Stimuli–Organism–Response Model and Theory of Consumption Value was established. A purposive sampling method was adopted to collect data from luxury fashion consumers aged 21–41 who lived in four Tier 1 cities in China. Structural equation modelling and SmartPLS 4.0 were utilized to analyse the 304 valid questionnaires collected.

The study’s findings indicate that luxury fashion NFTs with four characteristics (NFT scarcity, NFT exclusivity, NFT design aesthetic and NFT novelty) affect Chinese consumers’ purchase intention towards luxury fashion physical products positively, with perceived hedonic value mediating these relationships. Further, perceived NFT–physical product fit moderates the relationship between perceived hedonic value and purchase intention.

This study bridges a gap in investigating the interplay between NFTs as intangible collectibles and tangible products, by stressing the significant role played by NFTs in influencing the purchase intention of luxury fashion products. This paper contributes to an understanding of consumers’ psychological responses and behaviours towards NFTs, providing a new perspective in the study of luxury fashion NFTs in the context of marketing strategy and consumption.

Measuring and understanding the dynamics of democracy as well as democratic attitudes of people have become a big challenge for every democratic state. The study proposes the investigation of middle-class peoples’ attitudes towards democracy in Pakistan.

The study employs a deductive approach based on cross-sectional data from Pakistan’s middle-class people. The researchers use a survey questionnaire through a convenience sampling technique. Finally, the study utilizes 1854 samples to conclude the findings.

The evidence confirms that trust in public institutions and political engagement positively and significantly impact peoples’ democratic attitudes. In addition, the investigation witnessed the preference for democracy also supports understanding middle-class peoples’ democratic attitudes.

The study would provide an endorsement for politicians of Pakistan to perceive the inclination of middle-class people towards democracy. The study would guide the researchers and policymakers and intellectualize the middle-class peoples’ opinions and attitudes. Moreover the study would support reflecting the public confidence in decision making and ability to deliver. Finally the study findings would contribute to the literature of political science and democracy to understand democratic attitudes mainly focusing on middle-class populations.

This study empirically confirms the Pakistani middle-class peoples’ attitudes towards democracy.