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This study delves into the nuanced implications of short-sale constraints on stock prices within the context of stock market efficiency. While existing research has explored this relationship, inconsistencies persist in their findings. The purpose of this study is to conduct a comprehensive review of literature to elucidate the reasons behind these disparities.

A systematic review of existing theoretical and empirical studies was conducted following the PRISMA method. The analysis centered on discerning the factors contributing to the divergence in projected stock prices due to these constraints. Key areas explored included assumptions related to expectations homogeneity, revisions, information uncertainty, trading motivations and fluctuations in supply and demand of risky assets.

The review uncovered multifaceted reasons for the disparities in findings regarding the influence of short-sale constraints on stock prices. Variations in assumptions related to market expectations, coupled with fluctuations in perceived information uncertainty and trading motivations, were identified as pivotal factors contributing to differing projections. Empirical evidence disparities stemmed from the use of proxies for short-sale constraints, varied sample periods, market structure nuances, regulatory changes and the presence of option trading.

This study emphasizes the significance of not oversimplifying the impact of short-sale constraints on stock prices. It highlights the need to understand these effects within the broader context of market structure and methodological considerations. By delineating the intricate interplay of factors affecting stock prices under short-sale constraints, this review provides a nuanced perspective, contributing to a more comprehensive understanding in the field.

A stylized fact in finance literature is the belief in positive relationship between ex ante return and risk. Hence, a rational investor, by utility preference axiom can only consider committing fund in asset which promises commensurate higher return for higher risk. Questions have been asked as to whether this holds true across securities, sectors and markets. Empirical evidence appears less convincing, especially in developing markets. Accordingly, the author investigates the nature of reward for taking risk in the Nigerian Capital Market within the context of individual assets and markets.

The author employed ex post design to collect weekly stock prices of firms listed on the Premium Board of Nigerian Stock Exchange for period 2014–2022 to attempt to answer research questions. Data were analyzed using a unique M Vec TGarch-in-Mean model considered to be robust in handling many assets, and hence portfolio management.

The study found that idea of risk-expected return trade-off is perhaps more general than as depicted by traditional finance literature. The regression revealed that conditional variance and covariance risks reveal minimal or no differences in sign and sizes of coefficients. However, standard errors were also found to be large suggesting somewhat inconclusive evidence of existence of defined incentive structure for taking additional risk in the market.

In terms of choice of methodology and outcomes, this research adds substantial value to body of knowledge. The adapted multivariate model used in this paper is a rare approach especially for management of portfolios in developing markets. Remarkably, the research found empirical evidence that positive risk-expected return trade-off, as known in mainstream literature, is not supported especially using a typical developing country data.

The objective of this paper is to investigate the direction of the causal relationship between dividend policy (DP) and earnings management (EM).

This research utilizes the panel data analysis to investigate the causal relationship between EM and DP. It provides empirical insights based on a sample of 280 French nonfinancial companies listed on the CAC All-Tradable index during the period of 2008–2015. The study initiates with a Granger causality examination on the unbalanced panel data and employs a dynamic panel approach with the generalized method of moments (GMM). It further estimates the empirical models simultaneously using the three-stage least squares (3SLS) method and the iterative triple least squares (iterative 3SLS) method.

The estimation of our various empirical models confirms the presence of a bidirectional causal relationship between DP and EM.

Our study highlights the prevalence of EM in the French context, particularly within DP. It underscores the need for regulatory bodies, the Ministry of Finance, external auditors and stock exchange organizers to prioritize governance mechanisms for improving the quality of financial information disclosed by companies.

This research is, to the best of our knowledge, the first is to extensively investigate the reciprocal causal relationship between DP and EM in France. Previous studies have not placed a significant emphasis on exploring this bidirectional link between these two variables.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

The purpose of this paper is to investigate the effect of family control on the association between related party transactions (RPTs) and different forms of accrual-based earnings management (AEM) and real earnings management (REM), analyzing the effect of board characteristics on the possible association.

This paper studies a sample of Italian non-financial listed firms over the 2014–2019 period, by GLS regression models, controlling for the fixed effects of the company's sector of operation and the year.

Results indicate a different association between RPTs and earnings management (EM) in family and non-family firms. They point out that family firms use RPTs in association with downward AEM and REM perpetrated by abnormal discretionary expenses as well as a substitute of REM via abnormal production costs. For non-family firms, findings indicate only a substitution effect between RPTs and AEM. Furthermore, CEO duality, board gender diversity and the presence of the family on the board positively moderate the association between RPTs and, respectively, REM implemented through sales manipulations, downward AEM and upward AEM.

This study suggests that the socioemotional wealth (SEW) differently affects the relationship between RPTs and EM, according to the form of the latter. It also points out family firms' heterogeneity in earnings manipulations, by providing evidence of the moderating role of board characteristics on the association between RPTs and the various forms of EM.

The current research takes a closer look at the investment intention of Generation Z and its relation to investing in a speculative market. The study applies the theory of planned behaviour (TPB) to understand the dominant factors leading to Generation Z investment decisions in speculative markets. The main objective is to identify whether these decisions are learnt decisions or herd behaviours.

Structural equation modelling is used to evaluate the research model, and examine the mediation effect of financial literacy using bootstrapping in AMOS software. Information was gathered from 271 students studying at the University of Technology and Applied Sciences. The questionnaire used for the survey was adapted from previous related studies examining the TPB.

The findings show financial literacy and behavioural outcome (attitude) are key components associated with investment intention. Motivation to comply (subjective norm) affects the intention to invest if mediated by financial literacy. The subjective norm has no bearing on the intention to invest in a speculative market. This implies social peers have no bearing on their intention to invest unless mediated by financial literacy.

The main limitation of the study is that the group from which the sample is drawn consists of all students at a state-funded university who receive stipends. This limits the applicability of related findings. Furthermore, the variables have dynamic properties, which implies their impacts may vary over time.

Generation Z comprises a large number of small investors who can make a significant difference to the overall economic trends of the country. The digital world, which is time- and space-infinite, is shaping the next generation. It is only possible to reach and sway their opinions by conducting extensive behavioural science research.

Academic institutions ought to be viewed as a resource for conducting additional in-depth research on a variety of subjects to assist and shape the current generation for a better future.

Although the TPB has been used by many researchers to explore the behavioural intention of Generation Z, very few have used financial literacy as a perceived behaviour control to study its direct and indirect effects on behaviour intention.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

Trade relations between China and the USA have been marked by conflict, especially since China’s membership in the World Trade Organization (WTO). These conflicts have been analyzed from a variety of perspectives, including the loss of jobs in the USA due to Chinese imports, competition in high technology sectors and the balance of trade. Conceptual frameworks have employed models of domestic differences as well as models of international power distribution. Among domestic differences examined are the existence of state-owned enterprises in China compared to the domination of the USA economy by private firms, the large role of the Communist Party in China and the influence of labor and environmental and labor groups in the USA. Power distribution theories focus on the systemic effects of the distribution of power on trade openness and on the pattern of intra-bloc versus between-bloc trade. This paper aims to examine the role of macroeconomic policy factors in China and the USA, in particular, the role of national patterns of savings, investment and consumption (both private and government). The paper concludes that insofar as the balance of trade is an important component of the trade conflict, domestic macroeconomic factors continue to be important. The resolution of the conflict will have to take into account the respective macroeconomic policies of China and the USA.

The design is an analytic case study of US–China trade relations with a particular focus on the balance of trade. The conceptual framework employed involves an analysis of macroeconomic policy categories, especially the overall pattern of savings (household, firm and government), investment and consumption. Process tracing over time since China's membership in the WTO is carried out with an eye toward the relationship between the balance of trade and macroeconomic policy.

The main findings are that there is a strong relation between the respective macroeconomic policies of the USA and China and their trade relations. The domestic political economy of the USA encourages consumption and a low rate of savings. The opposite is true of China where household income is low by design and national savings are high. China depends on the USA to consume what is not consumed domestically. The USA depends on Chinese imports for additional consumption encouraged by its low rate of savings. The two economies are locked in a mutual dependence.

Key research implications are that there should be more focus on domestic macroeconomic policies since these are the root causes of the trade imbalance. This is not to say that trade frictions centering on jobs, subsidies and competition in high technology are unimportant. However, without the resolution of differences in the management of macroeconomic policies, trade conflicts between the USA and China will continue.

Practical implications are huge, in some ways much more important than the academic implications. Macroeconomic policy differences in savings, investment, government spending, taxation and infrastructure are important. Furthermore, there are available tools in both China and the USA to manage the macroeconomy, particularly, monetary and fiscal policy.

One implication of this paper is that satisfaction or dissatisfaction of workers is dependent on income distribution which in turn affects trade. Treatment of people in different socioeconomic categories, such as the elderly, the young, and those at working age are a function of macroeconomic policies.

Many people have written about macroeconomics. It is a conventional subfield of economics. The originality of this paper lies in its advocacy of a shift of focus and attention and in the argument that traditional macroeconomics is related to trade. Despite its importance, macroeconomics has not been the center of attention for most political scientists, though economists have made it more central.

The purpose of this study is to investigate the moderating effect of board gender diversity on the relationship between sustainability reporting (SR) and earnings management (EM) in the East Africa Community (EAC).

The study analyzed a sample of 71 publicly traded companies from 2011 to 2021.

The study finds that both SR and board gender diversity have a negative and significant effect on EM and that board gender diversity moderates the relationship between SR and EM.

The findings suggest that boards should support the adoption of SR and increase female representation as a practical way to reduce EM. Policymakers should also implement appropriate measures, such as imposing mandatory SR and gender quotas on corporate boards, to address EM.

This research adds to the limited knowledge of SR and EM in the EAC and also fills a gap in the existing literature by investigating the influence of board gender diversity on the link between SR and EM.

This paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.

The study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.

The use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.

Integrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.