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This study aims to investigate the influence of perceived luxuriousness on consumers’ revisit intentions via the mediating effects of positive and negative emotions based on the Stimulus-Organism-Response (SOR) model. In this context, “luxuriousness” specifically refers to the richness of furnishings, including the visual allure of aesthetic design and the surrounding cues.

A quantitative approach using a survey method is employed to analyse the collected 289 data from consumers of bubble tea. Partial least squares structural equation modelling is chosen as the main analytical approach to examine the research model.

The results showed that perceived luxuriousness has a significant positive influence on positive emotion and a significant negative influence on negative emotion. Furthermore, positive emotion positively affects revisit intentions, whereas negative emotion negatively affects revisit intentions. Positive emotion mediates the relationship between perceived luxuriousness and revisit intentions, but negative emotion does not.

In terms of theoretical contributions, this study contributes to the SOR model by exploring the influence of perceived luxuriousness on revisit intentions via the mediating effects of emotions in the bubble tea context, which has not been previously examined by past studies. In terms of managerial implications, this study provides insights into how to leverage the element of luxury to encourage consumers to revisit bubble tea stores.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This study aims to establish the factors affecting the financial investment decision-making of an investor, with specific reference to investors’ emotions and how various events such as festivals, the pandemic and sports matches affect their investors’ investment decision-making. The authors further intend to understand the role of these investor emotions in creating stock market anomalies.

Twenty-nine semistructured exploratory interviews with fund managers from the top 10 asset management companies in India, who deal with individual investors regularly, were taken. The interviews were conducted to identify and describe the underlying ideas and sentiments that influence an individual’s investment behavior.

Although risk and return are the primary motivators of investment decisions, fund managers’ daily interactions with individual investors are affected by unpredictability and technical ambiguity, and investing is an inherently emotionally arousing process, according to the findings of the in-depth interviews.

To the best of the authors’ knowledge, this study is one of the first studies in Indian market to report the views of financial professionals about the emotional aspect of investors in making an investment decision. With most of the research conducted using quantitative methods, the current study brings in the perspective of financial professionals using primary data.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

This study aims to merge the world’s proven ways of housing finance, including musharakah mutanaqisah, housing cooperatives and real estate crowdfunding, to present an alternative housing unaffordability solution based on the Islamic finance principle. It is intended to reduce the burden of funding for both sides (consumers and developers) and create win–win chances for all stakeholders, including intermediaries. By moving away from debt financing and merging the features of crowdfunding and cooperative, it is hopeful that the burden of home ownership will no longer be the case.

This paper presents the opinions of potential Chinese homebuyers (minority Muslims and most non-Muslims) and a few industry experts toward the proposed model via a mixed research method.

According to the findings, the majority of respondents agreed with the proposed paradigm. Just concerned that China’s lack of community culture and trust could pose a major threat to implementation. However, this paper argues that Chinese local governments may perform pilot testing in places where Islamic culture is prevalent. Their unique community culture and fundamental understanding of Shariah law may affect the viability of the proposed model.

The proposed model would increase the applicability of Islamic finance as a way of protecting the social order of communities in the spirit of upholding justice and fairness. A new type of housing loan based on musharakah mutanaqisah may squeeze out the real estate bubble and provide stakeholders with a multidimensional investment channel. In particular, the study identifies the impact of Chinese Islamic financing on government and cultural needs. It presents possible challenges for implementing the proposed model in reality and helps bridge the gap between theory and practice.

Cryptocurrency arose, and grew in popularity, following the financial crisis of 2008 built upon a promise of decentralizing money and payments. An examination of the history of money and banking in the United States demonstrates that stable money benefits from strict controls and commitments by a centralized government through chartering restrictions and a broad safety net, rather than decentralization. In addition, financial crises happen when the government allows money creation to occur outside of official channels. The US central bank is then forced into a policy of supporting a range of money-like assets in order to maintain a grip on monetary policy and some semblance of financial stability.

In addition, this chapter argues that cryptocurrency as a form of shadow money shares many of the problematic attributes of both the privately issued bank notes that created instability during the “free banking” era and the “shadow banking” activities that contributed to the 2008 crisis. In this sense, rather than being a novel and disruptive idea, cryptocurrency replicates many of the systemically destabilizing aspects of privately issued money and money-like instruments.

This chapter proposes that, rather than allowing a new, digital “free banking” era to emerge, there are better alternatives. Specifically, it argues that the Federal Reserve (Fed) should use its tools to improve public payment systems, enact robust utility-like regulations for private digital currencies and limit the likelihood of bubbles using prudential measures.

The paper's purpose is to investigate the effects of digital finance on the risk of stock price crashes and the underlying transmission mechanisms, and to provide suggestions to inhibit the stock crash risk (CR).

This paper selects all companies that were listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2011 to 2020. It then uses the two-way fixed effect model and the intermediary effect model to verify such effects.

The overall outcomes demonstrate such a result that the CR of listed companies in China can be significantly reduced by the development of digital finance, and the overall transparency of business financial information and the equity pledge of controlling shareholders are the two underlying transmission mechanisms that digital finance can cause effects on the CR of stocks.

The main limitations are that there may exist some problems in the method for evaluating the CR of stocks. And there may be a problem of endogeneity caused by the empirical model cannot control all correlation variables.

This paper would provide policy implications, for different roles, to inhibit the stock CR and to make the development of the economy more stabilize.

Digital finance can promote economic development while restraining financial risks at the same time. Therefore, although this study is based on the relevant data from China, it can also provide a reference for other economies with different basic conditions from China, to promote the overall development of the world economy.

The current academic research on digital finance or stock price CR has been relatively sufficient, but there are few papers that combined both. By combining digital finance with stock CR, this paper researches the influence of digital finance on the CR of stocks through empirical analysis. So, this paper would provide new research ideas and evidence for potential influence factors of the CR of stocks, fill the gap in this research field and provide certain help for subsequent scholars to conduct relevant research.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.