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Knowledge of consumer behavior is important to a corporation's accomplishment. Organizations may change for the better deal with the promotion mix, product administration, and buyer interaction by knowing how the buyer performs and what motivates him. Selecting the influencing elements for consumers is frequently exceedingly challenging to accurately detect because they are inside forces. The COVID-19 pandemic's wide-scale spread has significantly altered peoples' daily lives and purchasing patterns. The Indian government implemented several steps across the nation to limit the fatal disease to slow the spread of COVID-19. Following its initial breakout in China in early 2020, the novel coronavirus pandemic rapidly developed all over the globe, giving an unfavorable influence on the global financial system and industries. During the COVID-19 pandemic, the authors seek to uncover changes in consumer behavior when purchasing everyday items including food, medications, clothing, footwear, and technology. To understand how the current pandemic conditions compare to the aforementioned shock events, we carried out a comprehensive review of the literature with a focus on the presentation of panic buying and pack mentality behavioral patterns and changes to voluntary consumer spending as defined by Maslow's hierarchy of needs.

India has a distinct family hierarchy and a vertical collectivistic culture. Indian traditional cultural norms discourage young adults from having romantic or sexual relationships before marriage. Romantic liaisons and marriages are fiercely opposed outside the caste and social network. Despite this cultural practice, research in the last decade demonstrated that more young adults in India engage in premarital romantic relationships and prefer a marriage of choice. However, they strongly wish their parents to approve of their partner and arrange their marriage. This increasing trend of love-cum-arranged marriages could be considered how Indian culture adapts to the demands of modernization strongly impelled by globalization. This chapter discusses the dynamics of change in the romantic and marital agency among young adults in India. First, the authors provide a brief historical introduction to the Indian marital system. Then, the authors discuss the changing cultural dimensions that promote marital choice and independence in partner selection (e.g., filial piety). Further, the authors provide an overview of the trends in premarital romantic relationships in India. In addition, the authors discuss the distress and conflict in Indian families due to the increasing premarital romantic and sexual relationships among Indian youth, as evidenced by eloped marriages, forced marriages, and honor killings.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

Introduction: India has the 15th-largest domestic natural gas consumption (NGC), critical to sustainable economic growth. Promoting natural gas will have a crucial impact on production in all industries.

Purpose: This research gives an overview of NGC and gross domestic product (GDP) in India from 1990 to 2021 and investigates the association and nature of causality between NGC and GDP in India.

Methodology: For the years 1990 through 2021, we used annual statistics from the NGC and the GDP of India. Both research variables data have been taken from the World Bank Indicator.

Findings: There is no causality and correlation between natural gas and GDP in India.

Practical Implications: Based on the research, the Government of India can create different policies for substituting natural gas for other energy sources to have a healthier impact on a sustainable environment in the short and long term. In the future, researchers can work on environmental degradation and GDP.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

The management of consumer privacy has become a critical concern for organizations in the age of artificial intelligence–powered marketing. The impact of data on the market environment has brought both benefits and challenges, with marketers gaining valuable insights but also raising privacy concerns. As artificial intelligence–powered marketing advances, consumer vulnerability increases due to the sensitivity of collected data. This vulnerability leads some consumers to resort to falsifying information, posing a significant threat to the digital economy. Privacy empowerment and customer control play a vital role in addressing these challenges. This chapter explores the influencing factors and ethical considerations surrounding data falsification. It also discusses strategies to mitigate perceived vulnerability through privacy controls and explores the consequences of data breaches and customer vulnerability. The chapter further emphasizes the need for organizations to balance benefits, risks, and customer trust while harnessing the value of customer data. An ethical framework for data privacy marketing audits is proposed to help organizations assess their data practices responsibly and competitively. By integrating personal data protection strategies within an ethical framework, organizations can protect consumer privacy, enhance customer trust, and maintain their competitive edge in the market.

This study aims at investigating the effect of corporate social responsibility (CSR) and corporate social irresponsibility (CSI) on corporate financial performance (CFP) in firms headquartered in developed versus emerging countries. Drawing upon stakeholder and legitimacy perspectives, the authors argue that the CSR/CSI–CFP relationship differs depending on the home-countries’ level of economic development as this reflects their different sensitivity to sustainability. Indeed, as emerging economies are normally characterized by weaker regulations, they are likely to place lower pressures on companies for superior CSR practices. Therefore, the authors expect the effect of CSR on CFP to be more positive for firms headquartered in advanced than in emerging countries. At the same time, the authors propose a more negative relationship between CSI and CFP for firms headquartered in developed countries due to the higher overall sustainability expectations required to gain legitimacy. The empirical analyses, run on a sample of 1,971 publicly listed firms between 2010 and 2020 from developed and emerging economies, support the expectations, thus confirming that country-specific contextual factors do play a role in shaping both the positive and the negative impact of CSR and CSI on CFP, and that the reactions of stakeholders to responsible and irresponsible behavior are stronger when their sensitivity to sustainability is higher.

Nuclear energy investments contribute significantly to the energy independence of countries. This situation helps countries to develop both economically and socially. Therefore, countries need to develop strategies to increase their nuclear energy investments. However, radioactive waste generated in nuclear reactors is one of the most important disadvantages of this type of energy. Due to this situation, the wastes generated must be disposed of effectively for nuclear energy investments to be effective. In this study, it is aimed to create optimal strategies for the effective waste managements generated in nuclear power plants. Within this framework, four different balanced scorecard perspectives are considered as the criteria. In the analysis process, Analytical Hierarchy Process (AHP) methodology is taken into consideration. It is identified that learning and development is the most critical factor for the effective radioactive waste management created in nuclear power plants. On the other side, internal factors are the second most important criterion in this framework. Hence, it is understood that nuclear energy investors should give priority to the technological development for effective waste management in nuclear power plants. With the help of these technological improvements, the wastes can be disposed more successfully. As a result, environmental sustainability can be provided much easily.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.