Search results

The purpose of this paper is to develop a typology of heuristics in business relationships. We distinguish between four categories: (1) general heuristics used in the context of a business relationship but that may also (and are often) used in other contexts; (2) relational context heuristics that are typically used in a relational context; (3) relational information heuristics that rely on relational information and (4) genuine relational heuristics that use relational information and are applied in relational contexts.

We draw on existing literature on heuristics and business relationships to inform our conceptual paper.

We apply this typology and discuss specific heuristics that fall under the different categories of our typology. These include word-of-mouth, tit-for-tat, imitation, friendliness, recognition and trust.

We contribute to the heuristics literature by providing a novel typology of heuristics in business relationships. Emphasizing the interdependence between heuristics and business relationships, we identify genuine relational heuristics that capture the bidirectional relationships between business relationships and heuristics. Second, we contribute to the business relationships literature by providing a conceptual framework for understanding the types of heuristics managers use in business relationships and by discussing examples of specific heuristics and how they are applied in relational contexts.

We contribute to practice by providing a simple framework for making sense out of the “universe” of heuristics for business relationships.

Our paper provides a novel typology for understanding heuristics in business relationships.

In competitive environments, explicitly seeking institutional changes to adopt a new technology, rather than exploiting current resources, can harm more than help organizations’ efforts to achieve their performance goals. However, institutionally embedded organizations often respond to the introduction of industry disruptive technology in counterproductive ways. This paper aims to study the paradox of embedded agency in competitive environments and explore the diffusion of new occupations associated with data analytics.

This study uses the context of the Major League Baseball where the digital platform, PITCHf/x, implemented during 2006 and 2007 seasons facilitated the professional baseball clubs to create occupations for data analytics.

This study found that long-term low performance of organizations resulted in creating occupations for a new technology and deploying professionals to them and the public media’s negative tenor mediated the relationship between the signal of institutional inefficiency and such a boundary work in a competitive environment.

This research enriches our understanding of the early disperse of a new occupation in the times of the emergence of digital platform by exploring the temporal attributes of organizational performance and the role of public media as the antecedents to embedded agency.

With 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.

This 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.

The 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.

The 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.

This study aims to investigate the impact of financial and behavioural factors on investment decisions in the cryptocurrency market within the Gulf Cooperation Council (GCC).

The study uses the cross-sectional absolute deviation methodology developed by Chang et al. (2000) to determine the existence of herding behaviour during extreme conditions in the cryptocurrency market of four GCC countries: Bahrain, Saudi Arabia, Kuwait and UAE. In addition, a questionnaire survey was distributed to 322 investors from the GCC cryptocurrency markets to gather data on their investment decisions.

The study finds that the herding theory, prospect theory and heuristics theory account for 16.5% of the variance in investors' choices in the GCC cryptocurrency market. The regression analysis results show no multicollinearity problems, and a high F-statistic indicates the general model's acceptability in the results.

The study's findings suggest that behavioural and financial factors play a significant role in investors' choices in the GCC cryptocurrency market. The study's results can be used by investors to better understand the impact of these factors on their investment decisions and to develop more effective investment strategies. In addition, the study's findings can be used by policymakers to develop regulations that consider the impact of behavioural and financial factors on the GCC cryptocurrency market.

This study adds to the body of literature in two different ways. Initially, motivated by earlier research examining the impact of behaviour finance factors on investment decisions, the authors look at how the behaviour finance factors affect investment decisions of the GCC cryptocurrency market. To extend most of these studies, this study uses a regime-switching model that accounts for two different market states. Second, by considering the recent crisis and more recent periods involving more cryptocurrencies, the authors have contributed to several studies examining the impact of behavioural financial factors on investment decisions in cryptocurrency markets. In fact, very few studies have examined the impact of behavioural finance on cryptocurrency markets. Therefore, to the best of the authors’ knowledge, this study is the first of its kind to investigate how behavioural finance factors influence investment decisions in the GCC cryptocurrency market. This allows to better illuminate the factors driving herd behaviour in the GCC cryptocurrency market.

Organization theory seeks to explain how people coordinate their behaviors to achieve common objectives, but it has offered little insight into how organizations emerge from such coordination. Fully understanding entities requires knowing their origins. The purpose of this paper is to draw attention to and to suggest an approach for fortifying a foundational weakness in organization theory: pre-organization theory.

To develop pre-organization theory, this paper employs an evolutionary approach that integrates three theories. This paper first employs memetics to articulate a unit of selection, the i-memeplex, and next introduces inducement-contribution theory to tailor the i-memeplex to pre-organization, yielding a founder’s mental map for exchanges of inducements and contributions. It then applies generalized Darwinism to complete its evolutionary theory of pre-organization.

Memetics, inducement-contribution theory, and generalized Darwinism can be integrated to create a promising theoretical solution, but further investigation is needed to assess the empirical and practical value of pre-organization theory.

This paper contributes to organization theory by (1) explicating a foundational weakness in organization theory – its lack of pre-organization theory – and (2) integrating a novel set of theories to develop an evolutionary theory of pre-organization.

This empirical study uses herd behavior model to explore the role of anchor investors in ensuring fundraising success and overfunding of crowdfunded ventures.

Qualitative comparative analysis (QCA) is applied to find the configurational patterns describing how anchor investors' information disclosure leads to successful financing and overfunding.

Even when the anchor investor's resume is not detailed or the anchor investor has little experience in entrepreneurial investment, success or overfunding can be achieved, provided the anchor investor is a corporation rather than an individual. For individual anchor investors, a detailed resume matters. Overfunding can be achieved even when an individual anchor investor makes a small relative investment, if this small relative investment is compensated for by a detailed resume. Experience in entrepreneurial investment is crucial when individual anchor investors have few previous investments. Regardless of the anchor investor's identity, investment in absolute terms is crucial for crowdfunding success when experience in entrepreneurial investment is low. Such experience must be extensive if the anchor investor's resume is not detailed.

Both entrepreneurs and crowdfunding platforms can benefit from the findings in relation to the design of campaigns that use anchor investors' informational cues to achieve success and overfunding.

The study examines the importance of anchor investors' information disclosure in digital crowdfunding environments, differentiating between individual and corporate anchor investors.

本實證研究使用羊群行為模型, 去探究錨定投資者在確保眾籌活動可達成功籌資以及過多籌資方面所扮演的角色。

研究人員以定性比較分析法、去找出描述錨定投資者的資訊公佈如何帶來成功融資和過多籌資的配置模式。

研究結果顯示、只要錨定投資者不是個人、而是一間公司, 則即使他們的履歷不詳盡, 又或他們對企業投資的經驗淺薄, 也無礙籌資或過多籌資的成功完成。如錨定投資者為個人, 則詳盡的履歷會影響甚鉅。即使個人錨定投資者相對而言參與少量的投資, 但若這少量的投資給他們詳盡的履歷所彌補的話, 則過多籌資仍可成功達到。若個別錨定投資者原有的投資量不多的話, 則企業投資的經驗至為重要。不管錨定投資者的身份是什麼, 若他們對企業投資所持的經驗淺薄, 則按絕對值計算的投資額對眾籌能否成功至為重要。若錨定投資者的履歷不詳盡, 則這種經驗必須是豐富廣泛的。

本研究區分了個人錨定投資者與公司錨定投資者兩者對眾籌的影響, 就此而研究在數碼的眾籌環境裡, 錨定投資者信息公佈的重要性。

研究結果可幫助企業家和群眾募資平台去設計可使用錨定投資者的資訊提示來達至成功眾籌和過多籌資的活動。

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

This study combines different perspectives on herding, viewing it as a social network heuristic in comparison to other heuristics. The purpose is to use the heuristic view of herding as found in early literature and test it on grounds of efficiency and payoff, in essence, combining the heuristic and rational agent view of herding. The simulated double auction setting includes agents embedded in a social network, allowing for an examination of herding alongside rational behaviour and imperfect signals.

In each round of the simulation, levels of homophily, density and fractions of types of agents is set and agents are allowed to follow their respective heuristics under those conditions. Characteristics of the social network, such as the size, levels of different homophilies, density and fractions of different types of agents are varied randomly to gauge their effect on the performance of herders vis-à-vis others and the overall market efficiency through simulation based approach. The data used for the study has been developed in Python and linear models are estimated using R.

Herding decreases total surplus in private value double auctions, but herders are not worse off than other agents and perform equally in common value auctions. Further, herders and random offerers reduce payoffs of other agents as well, and herding effects the surplus per transaction and not the quantum.

This study explores herding as a strategic behaviour coexisting with rationality and other strategies in specific circumstances. It presents intriguing findings on the impact of herding on individual outcomes and market efficiency, raising new avenues for future research. Implication to research includes a dent on the “sieve” argument of markets rooting out irrationality and from it, a policy implication that follows is the need for corrective measures as markets cannot self-correct this, given herders do not perform worse than others.

The study links the phenomenon of herding to the dynamics of social networks and heuristic-based learning mechanisms that sets apart this research from the majority of existing literature, which predominantly conceptualizes herding as an outcome derived from a perfect Bayesian Equilibrium and a rational learning process.

Financial professionals are increasingly important in the Indian financial system. Our study examines the association between the Big Five personality traits and Indian financial professionals' behavioral biases when making investment decisions.

After testing our questionnaire's reliability and validity, we used it to obtain the sample responses. We used multiple regression analysis and other statistical tools to identify the relationships between the Big Five personality traits and behavioral biases.

Our findings reveal a high level of extraversion and conscientiousness, a moderate level of agreeableness and openness and a low neuroticism level among financial professionals. The results show a significant association between neuroticism, extraversion, openness and all behavioral biases except anchoring bias. The neuroticism trait has a statistically significant relationship with all behavioral biases examined, whereas agreeableness and conscientiousness traits lack a significant association with behavioral biases. The openness trait is associated with many emotional biases and cognitive heuristics, while the extraversion trait has a significantly positive relationship with availability bias.

Future researchers could analyze primary (survey) and secondary investor data from brokerage houses. Using a larger sample could provide more generalizable findings. Researchers could also consider other aspects of investment decision-making using various asset classes. Understanding financial professionals' personality traits and behavioral biases could help them develop strategies to suit client needs.

This study provides the first comprehensive examination of the association between personality traits and behavioral biases of Indian financial professionals.

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.