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The purpose of this paper is to analyze the dynamics of budgetary biasing in the context of public hospitals.

The study applies theories of accounting and budgeting behaviors in the specific institutional context of health care systems. Based on the theoretical framework, data from interviews with hospital budget officers were analyzed using qualitative content analysis.

A typology of biases is provided. It proved to be useful and highlighted the central empirical assumptions and preliminary results of biasing dynamics.

Understanding the logic of budgeting actors and the drivers of bias may help explain why bias so often appears in health care budgeting. It further contributes to understanding whether the bias is functional or dysfunctional.

The concepts of budgetary bias are rarely used in the context of health care budgeting, so the study fills a gap in research knowledge.

While some studies have found that cognitive biases are detrimental to entrepreneurial performance, others have conjectured that cognitive biases may stimulate entrepreneurial action. This study uses a typology of availability and representative heuristics to examine how two patterns of biases affect entrepreneurial performance. Drawing on ideas from cognitive science, this study predicts that various levels of biases in each pattern stimulate entrepreneurial behavior and performance.

A profile-deviation approach was employed to analyze data from 253 entrepreneurs and zero-truncated Poisson regression and the zero-truncated negative binomial regression to test hypotheses.

This study finds some positive associations between a particular level of cognitive biases in each of the two patterns and entrepreneurial behavior and performance. Results show that the patterns of biases often stimulate and never hurt entrepreneurial behavior and performance. The opposite holds for a lack of cognitive biases, which hurts and never stimulates entrepreneurial behavior and performance.

This study examines patterns of cognitive biases of entrepreneurs instead of single biases. The study broadens the perspective on the heuristics and cognitive biases of entrepreneurs by examining patterns of biases emanating from the availability and the representativeness heuristic that make a difference for entrepreneurial behavior and performance. The study also brings the “great rationality debate” closer to the entrepreneurship field by showing that a normative rule based on statistics and probability theory does not benefit entrepreneurial behavior and performance.

Unicorn companies, such as Facebook, Uber, and Airbnb, significantly impact our economies. This happens although they had a dramatic initial start – at least in terms of financial performance – that would have let any other “conventional” business close. In other words, Unicorns challenge the start-ups’ problems traditionally associated with early failure (liability of newness). This paper aims to understand what helps Unicorn firms initially survive despite huge losses.

By adopting a behavioral lens, this historical case study article focuses on key strategic decisions regarding the famous social media Unicorn Snapchat from 2011 to 2022. The case combines secondary data and a thematic analysis of Snapchat founders’ and investors’ interviews/comments to identify the behavioral antecedents leading to Snapchat’s honeymoon.

Snapchat network effect triggered cognitive biases of Snapchat founders’ and investors’ decisions, leading them to provide initial assets (i.e. beliefs/goodwill, trust, financial resources and psychological commitment) to the nascent Unicorn. Therefore, the network effect and biases resulted in significant antecedents for Snapchat’s honeymoon.

The authors propose a general, theoretical framework advancing the possible impact of biases on Unicorns’ initial survival. The authors argue that some biases of the Unicorns’ founders and investors can positively support a honeymoon period for these new ventures. This is one of the first case studies drawing on a behavioral approach in general and on biases in particular to investigate the liability of newness in the Unicorns’ context.

The growth of own label brands of products offered by supermarket chains is changing the “rules of the game” when managing fast moving consumer good products. A lot is written on the development of these brands and the consumers' behaviour in regions where their use is widely spread, but not in other markets. This paper compared the importance of choice criteria when purchasing own label and national brands and the perceived characteristics of the products carrying store and manufacturer brands in two regions of the European Union where the development of own label brands is at a different stage, Greece and Scotland. The results indicate that own label and manufacturer brands have an overall different positioning; Greeks are less familiar with own label products and assess them somewhat differently than the Scots, while several own label related attributes may be good predictors of the loyalty to the supermarket.

There is strong excitement during Ponzi schemes and financial bubble periods. This emotion causes investors to turn to “unknown and new investment instruments”. This study, the factors that made “unknown and new investment instruments” preferable to “known and experienced investment instruments” were investigated.

It was taken into account unconscious like phantasy, emotional like emotional intelligence, both affective and cognitive like financial literacy and subjective beliefs like trust and overconfidence. In addition, risk preferences were measured with four different risk variables. In this context, data were collected by online survey method between November 2020 and May 2021 with convenience sampling. First, the data were collected from 832 participants in the pilot study. Additional data were also collected using convenience sampling and online surveys, and a total of 1,692 participants were obtained. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 25 and AMOS 24.

As a result of the analyses made, the variables that lead investors to choose “unknown and new investment instruments” were determined as risky investment intention, phantasy, risk taking/risk avoidance, confidence, risk tolerance and subjective financial literacy. Trust and risk perception have a very weak effect on preferences. However, no effect of emotional intelligence and objective financial literacy was detected. In addition, a moderately positive and significant relationship was found between objective and subjective financial literacy. Subjective financial literacy was found to have a strong and significant relationship with emotional intelligence, confidence, trust, risky investment intention and phantasy.

This study investigates the factors underlying individuals' investment preferences from a broad perspective. We think that this study is unique in this structure and wide variables. We believe that the findings obtained in this manner are unique to both academics and practitioners. We also believe that the findings of the study will make an important contribution to understanding participation behavior in various Ponzi schemes and financial bubbles.

The purpose of this paper is to apply Connolly’s (2003) concept of agonistic respect to develop a typology of agonistic/antagonistic discourses on Twitter. To develop the typology, this study examines 2,236 Tweets containing the hashtag #guncontrol and uses NodeXL (Smith et al., 2010) to create a network map from which the 75 most influential accounts are derived. Using constant-comparative analysis (Glaser and Strauss, 1967), the authors identify seven categories of discourse style based on Connoly’s (2001) notion of ressentiment and “good faith presentations” of opposing arguments: furtive/secretive, cravenly opportunistic, willfully ignorant, irrational sentimental, misunderstanding/misguided, contingently wrong and reciprocal inquiry. The typology provides a useful and unique way to operationalize agonistic democratic theory and serves as the possible basis for training a machine learning classifier to detect antagonistic discourses on social media platforms.

To determine the level of agonism on Twitter, the authors examine tweets that employed the hashtag #guncontrol on March 12, 2018, one month after the shooting at the Marjory Stoneman Douglass High School in Parkland, Florida on February 14. The authors used the NodeXL excel add-on to collect and map 2,236 tweets. Using grounded theory/constant-comparative analysis (Glaser and Strauss, 1967), the authors develop a typology of seven types of discourses ordered from most antagonistic to most agonistic using Connolly’s (1993) concept of agonistic respect.

After examining the top 75 most shared tweets and using constant-comparative analysis to look for patterns of similarity and dissimilarity, the authors identified seven different ways in which individuals present their opponents’ value positions on Twitter on the issue of gun control. The authors were guided by agonistic theory in the authors’ inquiry. The authors looked at how Twitter users expressed their opponent’s faith/value positions, how pluralistic the discourse space was in the comment threads and how much the “talk” was likely to elicit ressentiment from adversaries.

Because the authors intended to engage in theory building, the authors limited the analysis to a selected number of tweets on one particularly salient topic, on one day. The intent of this was to allow for a close reading of the tweets in that specific network for the purposes of creating a useful typology that can be applied to a broader range of cases/issues/platforms.

The authors hope that typology could serve as a potential starting point for Twitter to think about how it could design its algorithms toward agonistic talk. The typology could be used as a classification scheme to differentiate agonistic from antagonistic threads. An algorithm could be trained to spot threads overwhelmingly populated by antagonistic discourse and instructed to insert posts from other threads that represent agonistic responses like “contingently wrong” or “reciprocal inquiry.” While generous presentations or deeper, more nuanced presentations of the opponent’s value position are not a panacea, they could serve to change the orientation by which users engage with policy issues.

Social media platforms like Twitter have up to now been left alone to make markets and establish profitability off of public sphere conversations. The result has been a lack of attention to how discourse on these platforms affects users mental well-being, community health and democratic viability. Recently, Twitter’s CEO has indicated a need to rethink the ways in which it promotes “healthy discourse.” The utilitarian presumption that, left to our own devices, we will trial and error our way to the collective good does not account for the importance of others in refining one’s preferences, arguments and world views. Without an “other” to vet ideas and lead us toward becoming wiser, we are left with a Wyly antagonism that moves discourse further and further away from agonistic respect and toward antagonistic virtual struggle. Platforms that allow antagonistic talk that breeds ressentiment run the risk of irrevocably damaging democracy through poisoning its public sphere.

This paper is unique in providing a typology/framework for thinking about the types of “political talk” that exists on Twitter. By using agonistic political theory as a framework, the authors are able to establish some guiding principles for “good political talk” that acknowledges the incommensurability of value positions on issues like gun control. The typology’s emphasis on agonistic respect, ressentiment and generosity in the presentation of alternative value positions provides a starting point from which to map and catalog discourse on Twitter more generally and offers a normative model for changing algorithmic design.

Bystander intervention mitigates the negative impact of bias incidents in the workplace. However, intervention tends to be viewed as binary: intervention occurred or it did not. Consequently, research has focused on conditions under which witnesses of bias incidents choose to intervene, and less is known about how witnesses may intervene. This paper elucidates the intervention behavior choices available to witnesses of bias incidents and develops a bystander intervention behavior (BIB) scale.

To develop the scale, the authors used the three-phased act frequency methodology. In phase I, the authors surveyed faculty who had both witnessed a bias incident and seen someone intervene to address it. The authors asked these faculties to list the observed bystander intervention behaviors they had personally observed. In Phase II, different survey respondents and subject matter experts assessed the prototypicality of each of the behaviors in relation to the concept of bystander intervention. In phase III, the authors tested the validity and reliability of the resulting 18-item scale and assessed the ability of bystander intervention behavior to mitigate the negative impact of bias incidents on the academic workplace.

The BIB scale consists of two theoretically derived, empirically validated and reliable dimensions; it can be used as a summary score to evaluate the extent to which colleagues intervene indirectly and directly when a bias incident occurs in the academic workplace.

This scale is valuable in advancing efforts to mitigate the negative effect of bias in the workplace and training colleagues to intervene in various ways when bias occurs.

Although the impact of human capital on productivity has long been discussed in prior studies, empirical evidence for African firms remains limited. The existing few studies have focussed on one type of human capital in isolation and failed to explore the distinct role of different types of human capital on productivity. The aim of this study is to examine the extent to which various typologies of human capital – schooling, on-the-job training (OJT) and slack time –, both in isolation and as a combination, contribute to the productivity of African firms.

To this end, a cross-sectional firm-level data set from 13 African countries was used. To unravel the casual relationship, propensity score matching (PSM) and multinomial endogenous switching treatment regression (MESTR) techniques were employed.

Results indicate that all typologies of human capital – schooling, slack time and OJT – have a significant and positive impact on firms' productivity. The findings of the study further point out that the highest payoff, in terms of increased productivity, is achieved when various typologies of human capital are used in combination, rather than in isolation, in the production process.

The policy implications are that productivity of African firms can be improved by increasing the general level of schooling; encouraging firm-sponsored OJT; and giving employees time to develop new ideas.

The present study provides important insights into the distinct role of different types of human capital on productivity. In addition, it provides empirical evidence for a region where empirical evidence is scant.

Social media rumor combating is a global concern in academia and industry. Existing studies lack a clear definition and overall conceptual framework of users' rumor-combating behaviors. Therefore, this study attempts to empirically derive a typology of rumor-combating behaviors of social media users.

A three-phase typology development approach is adopted, including content analysis, multidimensional scaling (MDS), interpreting and labeling. Qualitative and quantitative data collection and analysis methods are employed.

The elicited 40 rumor-combating behaviors vary along two dimensions: high versus low difficulty of realization, and low versus high cognitive load. Based on the two dimensions, the 40 behaviors are further divided into four categories: rumor-questioning behavior, rumor-debunking behavior, proactive-appealing behavior, and literacy enhancement behavior.

This typology will serve as reference for social media platforms and governments to further explore the interventions to encourage social media users to counter rumor spreading based on various situations and different characteristics of rumor-combating behaviors.

This study provides a typology of rumor-combating behaviors from a novel perspective of user participation. The typology delves into the conceptual connotations and basic forms of rumor combating, allowing for a comprehensive understanding of the complete spectrum of users' rumor-combating behaviors. Furthermore, the typology identifies the similarities and the differences between various rumor-combating behaviors, thus providing implications and directions for future research on rumor-combating behaviors.