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In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

While the literature has highlighted the impacts of COVID-19, there is limited evidence on the gendered determinants of the impact of COVID-19 among small-scale rural traders in developing and emerging economies.

Cross-border fish traders who had operated before and during the COVID-19 pandemic were interviewed in a survey conducted in Zambia and Malawi. Logistic regressions among male and female traders were employed to assess the gendered predictors.

Heterogeneous effects in geographical location, skills, and knowledge were reported among male cross-border traders. Effects of household structure and composition significantly influenced the impact of COVID-19 among female traders. Surprisingly, membership in trade associations was associated with the high impact of COVID-19.

Due to the COVID-19 pandemic and the migratory nature of cross-border fish traders, the population of cross-border fish traders at the time of the study was unknown and difficult to establish, cross-border fish traders (CBFT) at the landing sites and market areas were targeted for the survey without bias.

This paper addresses a gap in the literature on understanding gendered predictors of the impacts of COVID-19 among small-scale cross-border traders.

This study aims to analyze the effect the liberalization of industrial relations in Germany has had on trade unions’ influence on companies’ decisions. Particular attention is given to European measures of flexibilizing company law and how they affect industrial relations in Germany.

After presenting a theoretical basis regarding industrial relations and corporate governance, the paper then demonstrates, via a case study, the effects of the flexible European company law. It examines the strategic avoidance of trade union activity at SAP, a case that ended up before the European Court of Justice.

The flexibility of European company law allows companies to limit the influence of trade unions on company decisions. Limiting trade unions' internal participation weakens their position overall. Precautionary measures to protect employees’ rights help to reduce the dangers of this process.

The influence of European law brings a new perspective to the transformation of the German industrial relations model. The analysis of the strategy of using the legal type of the European company (Societas Europaea) to limit the internal activity of trade unions demonstrates the connection between institutional settings and corporate governance.

The purpose of this study is to explore the interplay between the selection of selling formats of remanufactured products for a third-party remanufacturer (TPR) and the quality decision of an original equipment manufacturer (OEM).

This study considers a remanufacturing supply chain, where the OEM sells new products through a platform retailer, but the products remanufactured by the TPR can be sold via a direct or indirect channel. The authors model a Stackelberg game and explore the optimal quality decision of the OEM and selling format choice of the TPR.

The OEM's optimal decision depends mainly on consumers' discounted utility coefficient and cost-scale factor of remanufactured products. A higher consumers' valuation of the remanufactured product will not result in a higher retail price, but may lead to an increase in new product's sales. Given the cost-scale factor, the TPR prefers to sell directly no matter what the value of consumers' discounted utility coefficient is. An all-win situation is achieved with selling directly when consumers' discounted utility coefficient is sufficiently large.

These results provide some support to the operational strategies of the OEM and TPR.

This study firstly endogenizes the quality decision and combines the selling format selection of the TPR and the quality decision of the OEM to explore the interplay between these two important decisions.

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 purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.

This study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.

Deploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.

This study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.

The Russian export flow is highly concentrated on few trading partners that results in its high vulnerability to external shock. Furthermore, the Russian–Ukraine conflict and corresponding western sanctions has enhanced the need of export markets diversification for Russia. Therefore, this study is a baseline attempt to explore determinants of export flow along with identifying potential export markets. This objective is realized by employing an augmented version of gravity model on export flow of Russian Federation to 108 trading partners from 2000 to 2020.

The augmented gravity model of export flow is estimated by using employing contemporary panel econometrics such as panel generalized ordinary least square estimation technique with cross-sectional weight along with heteroskedasticity consistent white coefficients is employed to explore impact of selected macroeconomic and policy variables. Furthermore, the sensitivity analysis is performed by using panel random effect along with the Driscoll–Kraay standard errors with pooled ordinary least squares (OLS) regression and random effect generalized least square (GLS) estimator techniques. The estimated result of panel GLS technique is subjected to in-sampled forecasting technique to explore potential export markets.

The findings show that an increase in the income of trading partners and enhancement of domestic production capacity has significant positive impact on Russian export flow, whereas geographic distance has a significant negative impact. Income of trading partners emerged as major determinant of export flow with high explanatory power. Among augmented variables, the real exchange rate reveals a significant positive impact of lower intensity, whereas binary variables for the common border, common history and preferential/free trade agreement show a significant positive impact. The finding of export potential reveals a high concentration of export with existence of large potential for exports across the globe. For instance, many developing countries in Asia, Africa and America reveal high potential for Russian exports.

The findings urge Russian Federation to diversify its export markets by targeting potential export markets. Many emerging developing countries are witnessing a high potential for Russian exports, therefore attempts should be taken to diversify toward them. The expansion of existing transportation facilities along with development of cargo trade can be important policy instrument to realize objective of export diversification.

This study is the first comprehensive analysis that employs augmented gravity model to explore potential export markets for Russian Federation by using panel data of 108 global trading partners from 2000 to 2020. This finding of this study provides a framework of export diversification toward potential markets across the globe.

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.

Based on the research of free trade agreements on alleviating service trade policy heterogeneity and its impact on manufacturing exports, this article aims to not only provide a basis for China's strategy of promoting regional economic integration, but also provide a policy reference for the manufacturing industry to expand the export market space.

This study uses the two principles of “answering” and “scoring” to quantify the indicators of service trade policy heterogeneity to test the relationship between heterogeneity of service trade policy, free trade agreement and manufacturing export.

According to empirical study, the export of Chinese manufacturing firms is severely hampered by the variety of service trade regulations, and the bigger the enterprise, the more hampered it is. In comparison to communications, transport and commerce, the financial industry's policy heterogeneity has a greater negative impact on certain industries. The major methods used to reduce the impact of service trade policy heterogeneity on manufacturing exports are product price increases and product quantity reductions. Also, by reducing the heterogeneity of service trade regulations and fostering industrial exports, the free trade agreement that China has signed can be quite successful. The open commitment in the area of national treatment, however, can reduce policy heterogeneity and advance manufacturing.

In the area of market access, the effect of export is superior to the open promise. Thus, in order to effectively support the stabilization of international trade, China should actively encourage the negotiation and signing of higher-quality and mutually beneficial free trade agreements.