Search results

Community events are significant for building community identity and cohesion. During 2020–2021, events largely halted due to coronavirus disease 2019 (COVID-19) and many communities lacked the capacity to recover their events quickly, in comparison to larger more well-resourced events. The study aims to understand and learn from the experiences of Scottish community event practitioners' during the disruption and recovery period for their events.

A targeted qualitative questionnaire elicited open-ended responses from people involved in the management and operation of community events in Scotland. Focus groups were also conducted with relevant practitioners to further elicit data.

Four key themes emerged as follows: (1) COVID-19 fractured stakeholder networks and impacted the ability of community events to operate. Practices adapted to incorporate virtual events. (2) Events were considered as important for place-building and wider collective community benefits. This was brought more into focus for practitioners as a result of the pandemic. (3) Local authorities were variable in the level and support they gave community events. (4) Some positive changes were enforced through COVID-19, such as collaboration between small event collectives that can build resilience for community events in the future.

The research provides an analysis of community events, which are often small-scale, diverse, local, unique to destinations and under-researched compared to large events. It particularly builds understanding of their resilience to sectoral disruption, through the lens of recovery from the COVID-19 pandemic, an extraordinary disruptive event. This paper provides practical strategies for community actors and local authorities to improve event delivery and leverage community events as place-builders.

Building on both the uncanny valley and construal level theories, the analyses detailed in this paper aims to address customers’ explicit and implicit attitudes toward various service robots, categorized by the degree of their human-like appearance, namely, mechanoids (low human-likeness), humanoids (medium human-likeness) and realistic robots (high human-likeness).

The analyses reflect a mixed-method approach, across three studies. A qualitative study uses focus groups to identify consensual attitudes. An experiment measures self-reported, explicit attitudes toward the three categories of robots. Another experiment explores customers’ implicit attitudes (unconscious and unintentional) toward robots, using three implicit association tests.

Customers express both positive and negative attitudes toward service robots. The realistic robots lead to both explicit and implicit negative attitudes, suggesting that customers tend to reject these robots in frontline service settings. Robots with lower human-likeness levels generate relatively more positive attitudes and are accepted to nearly the same extent as human employees in hospitality and tourism contexts.

Because customers reject, both consciously and unconsciously, very human-like robots in service encounters, managers should leverage this key finding, along with the more detailed results, to inform their strategic introduction of robots into hospitality frontline service settings.

The combined qualitative and quantitative studies specify and clarify customers’ implicit and explicit attitudes toward robots with different levels of human-likeness, in the real-world setting of hospitality and tourism services. Such insights can inform continued research into the effects of these service innovations.

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 paper describes how financial professionals' behavioral biases influence their financial forecast and decision-making process. Most of the earlier studies are focused on well-developed financial markets, and little is researched about financial professionals, such as institutional investors, portfolio managers, investment advisors, financial analysts, etc., in emerging markets.

An expert-validated questionnaire measure four prominent behavioral biases and Indian financial professionals' rational decision-making process. The final sample consists of 274 valid responses using the purposive sampling technique. IBM SPSS and AMOS structural equation modeling (SEM) software are used to build measurement and structural models, multivariate analysis including regression, factor analysis, etc.

The results provide empirical insights into the relationship between behavioral biases and the decision-making process. The results suggest that the structural path model closely fits the sample data. The presence of behavioral biases indicates that financial professionals' forecasting and decision-making is not always rational but bounded rational or irrational due to these factors. Furthermore, these biases (except overconfidence bias) have a markedly significant and positive relationship with irrational decision-making.

It is critical to eradicate these psychological errors, but awareness and attentiveness toward behavioral biases may help financial professionals to make informed decisions. Investors can improve their portfolio decisions and investments by recognizing their judgment errors and focusing on specific investment strategies to mitigate the impact of these biases. It is necessary to incorporate behavioral insights while developing training techniques for financial professionals. Rules of thumb, visual tools, financial coaching and implementing social-cultural elements in training programs enable financial professionals to develop simple, engaging, appealing and customized approaches for their clients.

This novel study is the first of this kind of research that examines the relationship between financial professionals' behavioral biases and rational decision-making process. This study significantly and remarkably provides insights into irrationality in financial professionals' decision-making.

This qualitative study focused on how girls' high school coaches in the United States Southwest thought about Latina teens' participation in school sports. Semi-structured interviews with coaches (4 women, 11 men) indicated they continue to rely on cultural (deficit) discourses implicating girls' families and culture when discussing Latina teens' sports participation. Coaches suggested that Latina teens' parents do not see the value of sports for girls, do not view sports as a pathway to college, are not involved or interested in their daughters' participation for cultural reasons, and are overly productive. These conceptualizations shape coaches' recruitment and pedagogical strategies within school sports contexts. More critical reflections could aid coaches and schools in developing more adaptive school contexts and strategies to better meet the needs of Latina teens and their families.

This paper aims to investigate the risk of corruption in several countries based on the cultural dimensions of Hofstede and institutional quality (IQ).

Data was collected from the Corruption Perception Index, Hofstede index and Worldwide Governance Indicators in 92 countries. Structural equation modeling based on partial least squares was used to test the proposed model.

The findings support the fraud triangle theory, which states that high transparency of individualist cultural attitudes and institutional control mechanisms reduces the opportunities for fraud to occur. From this research, it is also concluded that culture is a factor that tends to be constant and difficult to change.

Research limitations include: First, it is limited to the number of samples, where the number of samples depends on the availability of data. However, only 92 countries intersect and have complete information. Second, this study only uses individualism from the Hofstede cultural dimension to see the risk of corruption.

The result of this study implicates the policymakers in government agencies to increase IQ to reduce the risk of corruption.

This is a preliminary study that discusses national culture (NC) and corruption, as well as the effect of the mediating variable, namely, the IQ. By including IQ, the authors hope that the impact of the effects of NC on corruption risk can be clarified.