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This chapter focuses on how alternative data can change the nature of financial forecasting through improved short-term forecasting techniques and decreased informativeness from longer term sources. Increased use of social media data leads the charge in transforming this transition. Alternative data are data not from standard financial statements or formal reports. This chapter looks at alternative data from new sources (e.g., social media, Internet of Things [IoT], and digital footprints) and alternative data from new collection methods like web scraping for textual analysis, image analysis, and vocal analysis). It first discusses standard data in financial forecasting. Next, this chapter examines alternative data in financial forecasting. Finally, it discusses alternative data used in studying finance more broadly.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

Financial technology (fintech) refers to using new technology to improve and automate the delivery and use of financial services. This chapter provides a brief introduction to fintech. It also includes the book's purpose, distinguishing features, intended audience, and structure. A synopsis of Chapters 2 through 23 is offered. The chapter concludes that fintech is constantly evolving and is reshaping finance. Fintechs offer a new paradigm of growth.

Crowdfunding is a rapidly growing phenomenon in theory and practice. A significant gap exists between theoretical literature and empirical evidence regarding the volumes of crowdfunding and the quality of firms that use crowdfunding.

This is one of the first articles that offers a theory of entrepreneurs' choice between debt, equity and crowdfunding (reward-based). It uses a game-theoretic model where information about the expected quality of products developed by entrepreneurs is asymmetric.

We argue that in most cases crowdfunding is at the end of pecking order. The payments in the form of pre-orders come before the project investment is made making the entrepreneur's profit independent of actual quality of the product creating a strong ground for cross-subsidies of low-quality entrepreneurs by high-quality entrepreneurs in a pooling equilibrium.

The paper is consistent with some well-known empirical phenomena on crowdfunding, e.g. relatively small volumes of crowdfunding vs traditional funding, low volumes of reward-based crowdfunding vs debt-based and equity-based crowdfunding and excess entry of low-quality firms to crowdfunding market. We further compare this approach with an approach based on asymmetric information about the cost of production/investment (as in Belleflamme et al. (2014) and some other papers) and argue that even though some predictions maybe close under some general assumptions both approaches lead to qualitatively different results.

Technology serves as a key catalyst in shaping society and the economy, significantly altering customer dynamics. Through a deep understanding of these evolving behaviors, a service can be tailored to address each customer's unique needs and personality. We introduce a strategy to integrate customer complaints with their personality traits, enabling responses that resonate with the customer’s unique personality.

We propose a strategy to incorporate customer complaints with their personality traits, enabling responses that reflect the customer’s unique personality. Our approach is twofold: firstly, we employ the customer complaints ontology (CCOntology) framework enforced with multi-class classification based on a machine learning algorithm, to classify complaints. Secondly, we leverage the personality measurement platform (PMP), powered by the big five personality model to predict customer’s personalities. We develop the framework for the Indonesian language by extracting tweets containing customer complaints directed towards Indonesia's three biggest e-commerce services.

By mapping customer complaints and their personality type, we can identify specific personality traits associated with customer dissatisfaction. Thus, personalizing how we offer the solution based on specific characteristics.

The research enriches the state-of-the-art personalizing service research based on captured customer behavior. Thus, our research fills the research gap in considering customer personalities. We provide comprehensive insights by aligning customer feedback with corresponding personality traits extracted from social media data. The result is a highly customized response mechanism attuned to individual customer preferences and requirements.

The purpose of this study is to examine the effect of polarisation on trust in government.

The authors use the ordered probit technique to model trust as a function of polarisation and various control variables. The authors apply the instrumental variables approach to address potential endogeneity in polarisation, using ethnic diversity as an instrument.

The results reveal that an increase in polarisation reduces trust in central government. However, trust in local government is non-responsive to this polarisation. The estimations controlled for government performance, and the authors found a positive association between government performance and trust in government, which, however, does not alter the relationship between polarisation and trust in government.

In ethnically polarised nations, policymakers should consider decentralisation measures. This can help sustain trust and development support, particularly in regions where citizens prioritise ethnicity over nationality.

The social implications of this research underscore the importance of promoting trust in government to foster social cohesion and stability, particularly in ethnically diverse societies.

The authors find that increased ethnic polarisation reduces trust in the central government, particularly among those prioritising their ethnicity over nationality. This adds a non-performance dimension to government trust literature, suggesting that policies focusing solely on performance may yield limited results. The research extends beyond central government trust to include local governments. Unlike central government, local government trust remains tied to performance attributes unaffected by polarisation. Hence, investing resources through local governments is a viable strategy for enhancing citizen support while mitigating polarisation’s adverse effects.

This review paper aims to explore and investigate the Quality 4.0 current knowledge, emerging areas, and trends available in the literature and provide insights for future research directions. The bibliometric analysis determines the most prominent journals, authors, countries, articles, and themes. The Citation and PageRank analysis identifies the most influential and prestigious articles. The author's keyword analysis identifies the research theme, patterns, and trends within a particular area of research.

This study utilised the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) declaration as a review protocol, and the data is retrieved accordingly. Therefore, 104 articles from Scopus and 28 from Web of Science were combined in R-Environment, and 25 duplicates were removed using RStudio. Finally, 107 papers were selected for further analysis. After the abstract level screening, the study reviewed 99 articles bibliographically published in peer-reviewed journals from prominent academic databases Scopus and WoS between 2011 to April 2023. We used the VOSviewer software tool for analysing bibliometric networks that allow the construction, visualisation, and exploration of maps based on any form of network data.

The review identified emerging themes: artificial intelligence, digitalization, sustainability, root cause analysis, topic modelling, and digital voice-of-customers. To establish the intellectual structure of the field and identify gaps, co-citation and content analysis were used. The content of 49 papers in the identified clusters was then carefully analysed. The four primary themes are the relationship of Quality 4.0 with Industry 4.0, the conceptualization of Quality 4.0, recommendations for the new Quality 4.0 model, and the impact of Quality 4.0. The findings provide an excellent foundation for future research in this field for policymakers, managers, practitioners, and academia.

This is the first systematic literature review-cum-bibliometric analysis on quality 4.0 that covers the field comprehensively. Based on the present review, the paper proposes six possible future research directions to investigate.

The current study examines a novel model that examines how the online and offline or general personality of the same person predicts social identification with the endorser in a message and their subsequent online behaviors (e.g. ad-skipping) on social media, both differentially and simultaneously.

Real-time ad-skipping behaviors were tracked and analyzed across three online experiments.

The results supported the model explicating the dual and simultaneous influence of offline and online personalities on ad-skipping behaviors. Specifically, in response to a skippable video ad, online and offline personalities respectively increase and decrease viewers’ identification with the endorser. Consequently, the higher or lower the identification, the lower or higher the rate of ad-skipping behaviors.

The current study will benefit from a larger set of real-world data (i.e. big data) to enhance the generalizability of the findings, supporting the model.

With the growing prevalence of the gap between online and offline self-identities driven by social media usage, this paper suggests that the ad message needs to address the dual influence of both online and offline identities on ad-skipping behaviors.

The current study tests a novel model that shows that the online and offline personalities of the same person concurrently influence one’s behavior on the Internet, rather than separately.

This study aims to investigate how gamification, namely, WeChat’s cultural gifting function, improves emotional involvement among three generations (Y, X and silver) in mobile payments. It draws attention to the beneficial effects of cultural components and digital intimacy on gamified mobile payment systems.

The data were collected from Y, X and silver generation in Dalian, China. The users were well equipped with the WeChat pay features and had experience. The PLS-SEM software was used to assess the data.

The findings show that consumer word of mouth and loyalty are positively impacted by perceived utility, fun, and enjoyment. Besides, gamification components like fun and playfulness have a favourable effect on how useful mobile payments are judged to be. It demonstrates how delighted and ecstatic users are with WeChat Hongbao. In addition, the positive moderation effect of intimacy on the hypothesised connections shows that all three generations are likely to accept gamified money features. These results provide a substantial contribution to our comprehension of gamification in the context of mobile payment services for all three generations.

The study is distinctive because it focuses on how China’s three generations use WeChat Pay for routine transactions. The framework confirms that the gamification elements improve user performance and encourage continued usage of mobile payment systems.

Este estudio investiga cómo la gamificación, específicamente la función de regalos culturales de WeChat, mejora la participación emocional entre tres generaciones (Y, X y plata) en los pagos móviles. Se presta atención a los efectos beneficiosos de los componentes culturales y la intimidad digital en los sistemas de pago móvil gamificados.

Los datos fueron recopilados de las generaciones Y, X y plata en Dalian, China. Los usuarios estaban familiarizados con las características de pago de WeChat y tenían experiencia. Se utilizó el software PLS-SEM para evaluar los datos.

Los resultados muestran que la reputación y la lealtad del consumidor son positivamente influenciadas por la utilidad percibida, la diversión y el disfrute. Los componentes de gamificación, como la diversión y la jugabilidad, tienen un efecto favorable en cómo se juzga la utilidad de los pagos móviles. Se demuestra cuán encantados están los usuarios con WeChat Hongbao. Además, la moderación positiva de la intimidad en las relaciones supuestas muestra que las tres generaciones tienen probabilidades de aceptar las características de dinero gamificado. Estos resultados contribuyen sustancialmente a nuestra comprensión de la gamificación en el contexto de los servicios de pago móvil para las tres generaciones.

El estudio es novedoso ya que se centra en cómo las tres generaciones de China utilizan WeChat Pay para transacciones rutinarias. El marco confirma que los elementos de gamificación mejoran el rendimiento del usuario y fomentan el uso continuado de los sistemas de pago móvil.

本研究探讨了游戏化, 即微信的文化赠送功能, 如何提高三代人（Y、X和银发族）在移动支付中的情感投入。它引起了人们对文化成分和数字亲密关系对游戏化移动支付系统的有益影响的注意。

数据来自中国大连市的Y、X和银发族用户。用户对微信支付功能非常熟悉, 并具有使用经验。采用PLS-SEM软件对数据进行评估。

结果表明, 消费者的口碑和忠诚度受到了感知效用、乐趣和享受的积极影响。乐趣和趣味等游戏化组件对移动支付的有用性评估产生了积极影响, 展示了用户对微信红包的喜悦和兴奋程度。此外, 亲密关系对假设连接的正向调节效应表明, 三代人都可能接受游戏化货币功能。这些结果为我们理解移动支付服务背景下游戏化对三代人的贡献提供了实质性的帮助。

该研究独特之处在于它着眼于中国三代人如何将微信支付用于日常交易。该框架证实了游戏化元素如何提高用户绩效并鼓励继续使用移动支付系统。