Herding Behavior Research Articles

Retracted: Herding Behavior in China’s Stock Market under the Background of Implementation of the SHKSC Policy

Retracted: Herding Behavior in China’s Stock Market under the Background of Implementation of the SHKSC Policy

Transcritical bifurcation and Neimark-Sacker bifurcation of a discrete predator-prey model with herd behaviour and square root functional response

Transcritical bifurcation and Neimark-Sacker bifurcation of a discrete predator-prey model with herd behaviour and square root functional response

Intelligent electric vehicle charging optimization and horse herd-inspired power generation for enhanced energy management

This article focuses on optimizing electric vehicle charging in distribution networks, emphasizing technical and economic considerations. Unlike traditional methods, the proposed intelligent approach tailors each EV's charging based on specific daily trip energy requirements. Vehicle owners provide trip data to the charge management system, enabling precise charging calculations considering factors such as energy tariffs, distribution network limits, and charging levels. The paper introduces the horse herd optimization algorithm, inspired by horse herd behavior, offering advantages like reduced computational time and improved convergence in maximizing power generation, especially under shading conditions. The comparative analysis of smart EV charging under normal and fast conditions, considering various constraints and load response programs, demonstrates the proposed method's effectiveness. Numerical results reveal a 46.02 % average load reduction and a 20.53 % peak load decrease with a Load Response Program. Charging costs are optimized, with Case 2 exhibiting a 2.61 % cost reduction compared to Case 3. The study delves into charging frequencies, discharge frequencies, total unsupplied energy, and unloaded energy for each case, providing crucial insights into algorithmic performance. The horse herd optimization algorithm-based approach proves superior, offering a promising solution for efficient and cost-effective electric vehicle charging in distribution networks. Furthermore, graphical representations illustrate the algorithm's impact on charging power, energy allocation, power passing through distribution posts, and megavolt-ampere flow through network lines. These numerical and graphical analyses provide a comprehensive understanding of the horse herd optimization algorithm capabilities, emphasizing its potential to optimize power distribution, reduce costs, and enhance the resilience of residential distribution networks.

Impact of Influencer Trustworthiness and Financial Literacy on Herding Behavior with Risk Perception Mediating Variables of Indonesian Millennial Investors

The ease of investment resulted in soaring number of millennial investors in Indonesia. Most investors in Indonesia are a beginner and do not know how to invest properly. Ignorance of investment encourages investors to find information and looking for role model then commonly leads to herding behaviour. This habit contradicts with traditional finance theory where investors supposed to invest rationally and avoid risk. This study will further explore the relationship between trustworthiness of financial influencers and financial literacy on herding behaviours with risk perception as mediating variables in millennial investors in Indonesia. Based on path analysis resulting the variable significantly influence each other directly or indirectly through mediating variable. Direct effect of trustworthiness financial influencer positively related with the herding behaviour, but the financial literacy negatively related with the herding behaviour. Indirectly Financial literacy level increased to increase risk perception and trustworthiness financial influencer vice versa. The decrease of risk perception leads millennial investor to herd and the increase of risk perception make investor more careful to make investment. There are still 33% of other factors influenced outside this study, for example gender, age, income, occupation and many other. Prior study has not examined the impact of a millennial follower’s trust on influencers to herding behaviours using risk perception as a mediating variable.

Understanding consumer herding behavior in online purchases and its implications for online retailers and marketers

Herding behavior refers to the imitation of the behavior of the masses. The primary purpose of this study is to determine how herding affects digital purchases. It is an under-researched area in the marketing and consumer behavior context. First, one needs to understand the circumstances under which one is likely to herd. Second, it is yet to be understood how the effect of observing others' buying behavior transmits into herding. Third, there needs to be a better understanding of the role of price in one's tendency to herd. An online experiment with 541 participants was conducted using a 3 (consumer ratings/sales volume/control) × 2 (high involvement product/low involvement product) between-subjects design. LED TV was selected as a high-involvement product and ball pen pack was selected as a low-involvement product. This research study combined three theories to propose a holistic herding model. It used the social impact theory to capture its persuasive impact, the information adoption model to analyze the acceptance of herding information, and the cue utilization theory to assess the inference from herding information in consumer decision-making. Results indicated significant negative moderating effects of perceived price and product knowledge and the positive moderating effect of perceived uncertainty between the relationship of herding cues (star rating and the number of products sold) and herding behavior. In addition, the mediating results of perceived information usefulness and perceived quality were also significant. This herding model provides a holistic view of the herding process beyond limiting it to an attempt to follow others blindly. Therefore, this study has both theoretical as well as managerial implications.

The digital economy and markup: Based on herd behavior and peer effect

The relationship between digital economy and signal information on firms‘ markup has been overlooked and not well explained, especially in the emerging economies. When there is information asymmetry or too much information, the export decisions of firms are not completed independently, but the result of the comprehensive trade-off of the export signals issued by the 'neighbors'. This paper discusses the impact of the development of digital economy on the markup of export firms by distinguishing two perspectives of export signal, namely herd behavior and peer effect. We find that the digital economy has a positive impact on firm markup. There is substitution effect in digital economy and export signals, and digital economy acts price bonus by influencing export signals. The growing popularity of market signals could offset some of the advantages of the digital economy on export markup for companies. In addition, our paper finds that foreign-owned firms, large-scale firms, highly competitive industries and non-digital economy industries adjust their markups more significantly when they were affected by export signals.

Bayesian Decision Dynamics in Social Systems: The Influence of External Principals on Herd Behavior

Bayesian Decision Dynamics in Social Systems: The Influence of External Principals on Herd Behavior

DeFi era: the behavioral intentions toward cryptocurrency in Lebanon

PurposeThis paper examines the factors which impact the behavioral intentions toward cryptocurrency based on signaling theory.Design/methodology/approachData were collected through online questionnaire, and responses from 223 individuals in Lebanon were analyzed through SEM technique using Amos 24.FindingsThe outcomes portrayed the positive effect of perceived benefits and trust in cryptocurrency on behavioral intentions toward cryptocurrency; while not supporting the hypothesized influence of herd behavior and regulatory support.Originality/valueThis paper is among the first studies to adopt Signaling Theory (ST) in the cryptocurrency behavioral intentions research. Moreover, it is of the initial efforts in Lebanon and Middle East in evaluating behavioral intentions to use cryptocurrency, and it provide insights for future researchers, crypto project owners, crypto investors and crypto trading platforms.

Herding Behavior in The Asean Stock Market During The Covid-19 Pandemic

This study aims to detect indications of herding behavior that occurred in the ASEAN capital market throughout the COVID-19 pandemic. The research spanned from December 31, 2019, to June 30, 2021, encompassing the duration of the COVID-19 pandemic. This research used panel regression and rolling window regression methods on the dependent variable of Cross-Sectional Absolute Deviation (CSAD) to detect indications of herding behavior. This research also employed daily stock return data for all companies on several stock exchanges in five ASEAN countries. The panel regression model was then utilized in the analysis. The panel regression results demonstrated the absence of herding behavior on the stock exchanges in ASEAN. This was evident as the Rm2 coefficient consistently revealed a significant positive sign throughout the entire observation period. However, upon rechecking through rolling window regression, it was uncovered that, at some times, herding did occur on the ASEAN stock exchange during the COVID-19 pandemic. Furthermore, the government’s policy response by limiting short selling could reduce herding on the stock market. Simultaneously, the government’s policy response to the COVID-19 epidemic, proxied by the Stringency Index, apparently heightened investor anxiety and promoted herding behavior. Lastly, the heightened levels of anxiety and volatility experienced during the pandemic (variable IVI) led to a rise in herd behavior among the stock markets of ASEAN countries.

Detecting deception in computer-mediated communication: the role of popularity information across media types

PurposeWith the widespread use of online communications, users are extremely vulnerable to a myriad of deception attempts. This study aims to extend the literature on deception in computer-mediated communication by investigating whether the manner in which popularity information (PI) is presented and media richness affects users’ judgments.Design/methodology/approachThis study developed a randomized, within and 2 × 3 between-subject experimental design. This study analyzed the main effects of PI and media richness on the imitation magnitude of veracity judges and the effect of the interaction between PI and media richness on the imitation magnitude of veracity judges.FindingsThe manner in which PI is presented to people affects their tendency to imitate others. Media richness also has a main effect; text-only messages resulted in greater imitation magnitude than those viewed in full audiovisual format. The findings showed an interaction effect between PI and media richness.Originality/valueThe findings of this study contribute to the information systems literature by introducing the notion of herd behavior to judgments of truthfulness and deception. Also, the medium over which PI was presented significantly impacted the magnitude of imitation tendency: PI delivered through text-only medium led to a greater extent of imitation than when delivered in full audiovisual format. This suggests that media richness alters the degree of imitating others’ decisions such that the leaner the medium, the greater the expected extent of imitation.

Herding and retail investors’ decisions: A review literature

The main purpose of this paper is to review the existing literature of herding behavior and its relationship with retail investors’ decisions as well as its impact too to understand trend in the literature and some aspects relate to herd behavior. Herding occurs when individuals surrender their decision to a group and neglect their own beliefs to replicate others’ thoughts, feelings and actions. The study employed Prisma framework to review literature. It relied on intensive databases and sources such as Google scholar, Emerald, Elsevier, Springer, Research gate and Scopus. Literature studies have revealed tremendous empirical investigations about the impact of herding on retail investors’ decisions in the developed and developing countries. However, those studies have been filled the gap in the literature which relate to the relationship between herding and retail investors’ decision. This study aims to fill this gap by reviewing the literature on the relationship between herding and retail investors’ decision to figure out the trend of herd behavior. Therefore, the highlighting and reviewing of herding and its impact on retail investors decision might enrich the literature and assist researchers to determine gap in the field as well as determine new area need to be investigated.

Behavioural Economics: “Herd Behavior”

Behavioural Economics: “Herd Behavior”

Market memory, advance reaction, and retail investor herding

The arrival of new information, in conjunction with investor cognitive biases, has commonly been acknowledged as the main cause of herding behavior. However, whether past market information embedded in market memory influences investor herding has been less explored. We utilize tick-level trading data from the Chinese stock market to examine the impact of the market memory formed of stocks' exceptional performance during their initial trading days on the future herding behavior of retail investors. The empirical results show that the market memory of newly listed stocks is positively correlated with retail investor herding one year later at the appearance of a market-wide upward trend. We also propose an advance reaction channel in which retail investors tend to pay early attention to and preemptively invest in stocks with deep market memory due to their limited attention and the availability heuristic, leading to further herding due to confirmation bias. Our findings show that market information, if not fully incorporated into current stock prices through investor trading, can be partly stored in market memory. When activated by specific market conditions, market memory can be recalled and affect investor behavior and subsequent price dynamics. Our findings provide additional evidence to challenge the efficient market hypothesis (EMH) from the perspective of behavioral finance.

Evolutionary mechanism of green product certification behavior in cement enterprises: A perspective of herd behavior

While the United Nations advocates for sustainable production and consumption, the implementation of green product certification for cement enterprises is still in its infancy. This study focuses on understanding the evolution mechanism of cement enterprises adopting green product certification, and identifying the factors that influence this evolution involving cement enterprises, certification bodies, and the government. Based on herd behavior, a tripartite evolutionary game model is developed, leading to several conclusions. (1) When cement enterprises, certification bodies, and the government participate in green product certification, five evolutionarily stable strategies emerge in the evolutionary game system. (2) Key factors influencing participation in green product certification include the rent-seeking preference of cement enterprises, the transportation distance of cement products, the intensity of government regulation, and the success rate of regulation. (3) The rent-seeking preferences of cement enterprises have varying impacts on the rent-seeking behavior of certification bodies and the subsidy behavior of the government. (4) The transportation distances of cement products also have diverse effects on the rent-seeking behavior of certification bodies and the green product certification behavior of cement enterprises. This research offers valuable insights for governments in establishing and enhancing policies related to building material products.

A Micro-Level Evidence of how Investor and Manager Herding Behavior Influence the Firm Financial Performance

Using the investor-herding index (IHRB) and manager-herding index (MHRB), the emergence of investors’ and managers’ herding behavior at the corporate-level and its potential impact on firm financial performance (FFP) is analyzed in the entire study. The study utilizes the micro-level data of 296 listed firms of Pakistan stock exchange (PSX) from 2013 to 2017. Empirical findings show that the investors’ and managers’ herding significantly affect FFP. The results are robust under alternative measurements of FFP. This study has a unique contribution to the literature on behavioral finance by addressing the astonishingly overlooked phenomena of firm-level biases and their potential impact on FFP. For prospective investor’s decision, the findings are significant in such way that the market index is irrelevant than the firm-level financial evidence. Explicitly, the study concludes that positive herding behavior is elucidated by the bullish trend and inverse herding behavior of investors with respective to firm value leads toward bearish trend of stock market index. The likelihood of market crash may become more stringent in circumstances once managers and investors interactively exhibit negative herding behavior. Thus, the study offers useful policy and strategy implications for the associated stakeholders to the device the policies accordingly. JEL Code: D9, D21, D91, G11.

Sector-Wise Herd Behaviour in the Indian Stock Market during COVID-19

The article examines the herd behaviour at sector level in the National Stock Exchange of India. The novel objective of the paper is to analyse the presence of herd behaviour during the whole, pre- and post-coronavirus disease 2019 (COVID-19) pandemic outbreak period. The popular model proposed by Chang et al. (2000) has been deployed to examine herd formation in each sector. Five major sectors namely auto, bank, fast moving consumer goods, information technology and pharma have been considered along with NIFTY50 consisting daily closing prices of 106 companies comprising 58 from five sectoral indices and 48 from NIFTY50 for the period from 2011 to 2021 considering 1 January 2011–29 January 2020 as before COVID-19 outbreak period and 30 January 2020–31 December 2021 as after COVID-19 outbreak period. Results revealed significant evidence of anti-herd behaviour before COVID19 outbreak. At the same time, significant evidence of the existence of herd behaviour in FMCG, auto and pharma sectors have been detected after the outbreak of COVID-19 pandemic which assumes that investors tend to imitate the investment decisions of other market participants during such adverse macro events around the globe. The study tried to enhance the knowledge of investors to develop their trading strategies in the volatile market conditions by investing vigilantly and keeping such phenomenon in concern.

Determinants of Source Credibility in Terms of Herd Behaviour and the Anchoring Effect: The Case of Instagram Influencers

The objective of this paper is to explore the effects of herding and anchoring effects, two behavioural economics concepts, on perceived source credibility, which is commonly utilized in marketing research. These cognitive shortcuts that shape consumers’ decisions reduce their perceived risk or help them make decisions under uncertainty. The literature contains a limited amount of research on the topic that addresses source credibility in terms of behavioural economics. Within this framework, the study is anticipated to enhance the body of literature through its chosen topic and methodology. When reviewing research undertaken within the marketing domain, the experimental design method has been used in very few studies. In this context, in the experimental designs created within the scope of the study, various scenarios were designed on the basis of follower number (high/low) to evaluate the impact of herd behaviour on the credibility of the source and on the substance of news about the influencer (positive/negative) to measure the anchoring effect. After the participants were shown one of the scenarios, they were given questionnaires with statements about source credibility to answer, and how the perception of source credibility differs according to herd behaviour and the anchoring effect was investigated. Instagram influencers were used in the experimental designs created in the study because Instagram application is increasingly preferred over other social media platforms, is more effective in terms of marketing communication, is increasingly included in the marketing strategies of businesses and is preferred by the young population. Within the framework of this research, data were gathered via an online survey administered to a total of 727 students enrolled in various departments across universities in Turkey. These data were subjected to one-way ANOVA via the SPSS program. Research findings indicate that herding behaviour significantly affects the perceptions of the source credibility, expertise, and attractiveness of social media influencers. Furthermore, anchoring significantly affects the source credibility perceptions and expertise, trustworthiness, and attractiveness subdimensions. However, in scenarios where the number of followers and anchors are identical, a statistically significant difference was not found in the perception of source credibility in relation to the gender of the influencer.

Сентимент и стадное поведение частных инвесторов: кластерный анализ российского фондового рынка

In this paper, the sentiment of private investors and the divergence of opinions of users of online investment platforms are analyzed as factors in the emergence of herd behavior on the stock market in different clusters. This clusters are formed on the basis of stock exchange information on shares of Russian issuers. The relevance of the study lies in determining the significance of consensus periods and their impact on the behavior of different groups of investors on the Russian stock market depending on different levels of risk taking by investors. Based on the Russian stock market data for the period from 2019 to 2023, 66 discussed Russian stocks were analyzed. To conduct sentiment analysis, an algorithm was applied to collect and automatically classify textual data using machine learning methods. As proxies for private investor sentiment, metrics of logarithmic sentiment and market-wide divergence of opinions on the stocks under discussion were constructed. The testing of the research hypotheses was based on the implementation of clustering and quantile regression analysis methods. As a result, the significant role of divergence of opinions of Internet users in the formation of herd behavior of private investors on shares with lower average return and risk level was determined. It was also found that asset clustering helps to determine the opposite behavior of investors on stocks with higher volatility level. Consensus of opinions in the market is a signal to deviate from the general market trend. Finally, the test of the hypothesis about the significant influence of investor sentiment did not provide sufficient evidence that this kind of sentiment is important for determining herd behavior in the market.

COVID-19 effect on the herding behaviour in the Indian stock market.

COVID-19 effect on the herding behaviour in the Indian stock market.

COVID-19 effect on the herding behaviour in the Indian stock market

COVID-19 effect on the herding behaviour in the Indian stock market