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Tourist confidence plays an important role in people’s decision-making, including decisions related to consuming tourism products. However, little research has explored this concept in depth to provide proper guidance on its operation and measurement. This paper aims to explore the concept of tourist confidence, develop and test a measurement and test the effects of tourist confidence on people’s travel intentions at different periods of time.

This study used repeated cross-sectional data and collected responses from three waves of national surveys of U.S. residents in 2021.

The results revealed three underlying dimensions of tourist confidence: (1) confidence in tourism/hospitality service providers, (2) self-confidence in tourist competency and (3) confidence in travel safety. The validity and reliability of the instrument were deemed satisfactory. The results also indicate the positive associations between tourist confidence and people’s travel decisions.

This study developed a measurement that is specific to the domain of tourist confidence. The findings of this paper reveal the multidimensional nature of tourist confidence. When translated into practice, the findings of this study can help practitioners understand how to effectively enhance tourist confidence in challenging, difficult and uncertain times.

Confidence intervals play a crucial role in economics and finance, providing a credible range of values for an unknown parameter along with a corresponding level of certainty. Their applications encompass economic forecasting, market research, financial forecasting, econometric analysis, policy analysis, financial reporting, investment decision-making, credit risk assessment and consumer confidence surveys. Signal-to-noise ratio (SNR) finds applications in economics and finance across various domains such as economic forecasting, financial modeling, market analysis and risk assessment. A high SNR indicates a robust and dependable signal, simplifying the process of making well-informed decisions. On the other hand, a low SNR indicates a weak signal that could be obscured by noise, so decision-making procedures need to take this into serious consideration. This research focuses on the development of confidence intervals for functions derived from the SNR and explores their application in the fields of economics and finance.

The construction of the confidence intervals involved the application of various methodologies. For the SNR, confidence intervals were formed using the generalized confidence interval (GCI), large sample and Bayesian approaches. The difference between SNRs was estimated through the GCI, large sample, method of variance estimates recovery (MOVER), parametric bootstrap and Bayesian approaches. Additionally, confidence intervals for the common SNR were constructed using the GCI, adjusted MOVER, computational and Bayesian approaches. The performance of these confidence intervals was assessed using coverage probability and average length, evaluated through Monte Carlo simulation.

The GCI approach demonstrated superior performance over other approaches in terms of both coverage probability and average length for the SNR and the difference between SNRs. Hence, employing the GCI approach is advised for constructing confidence intervals for these parameters. As for the common SNR, the Bayesian approach exhibited the shortest average length. Consequently, the Bayesian approach is recommended for constructing confidence intervals for the common SNR.

This research presents confidence intervals for functions of the SNR to assess SNR estimation in the fields of economics and finance.

Wine marketers realise that to increase the overall size of the wine consuming population they must make wine more approachable and easier to understand. As it now stands, many consumers lack confidence in their ability to select a wine for either their own consumption or to share with others. Therefore, understanding the role played by consumer self‐confidence is especially relevant to marketers of wine, and the need to accurately measure the construct is important to scholarly research. Recently, the development of a scale to measure consumer self‐confidence has appeared in the consumer behaviour literature (Bearden, Hardesty and Rose, 2001). This study first adapts this consumer self‐confidence scale for use in wine‐related research. Next, the impact of six distinct dimensions of consumer self‐confidence on three different wine purchase situations is demonstrated. Results show the scale has the potential to inform both researchers and marketers about consumers' self‐confidence related to wine purchases.

This chapter investigates the nature of tax preparers’ confidence, as well as how the introduction of a tax decision support system (TDSS) affects tax preparers’ confidence levels. Psychological theories of confidence (e.g., Einhorn & Hogarth, 1978) are drawn upon to develop predictions regarding the role of process (ex ante) and outcome (ex post) confidence in tax return preparation. An experimental methodology is used with 114 inexperienced and experienced participants who prepare an individual income tax return manually or with tax preparation software (a TDSS). Less-experienced tax preparers have lower levels of ex-ante confidence and are more likely to be overconfident in the accuracy of their performance. Furthermore, when examining only the participants who made errors in their tax return preparation task, those that prepare the return with the TDSS are significantly more likely to be overconfident in their performance. These results support the predictions of Noga and Arnold (2002) and suggest that inexperienced users’ over-reliance on a TDSS (Masselli, Ricketts, Arnold, & Sutton, 2002) may be due to individuals’ overconfidence in the accuracy of their performance with the software.

On September 15, 2008, Lehman Brothers filed for bankruptcy and nearly caused a meltdown of the financial system. This article looks at the situation before Lehman went bankrupt and how this event came to trigger a financial panic during the fall of 2008 and early 2009. Two key ideas inform the analysis. The first is that what triggers financial panics are typically hidden losses. The second is that confidence plays a key role in financial panics and that confidence can be conceptualized as a belief that action can be based on proxy signs, rather than on direct information about the situation itself.

This study examined early childhood special education preservice teachers' perceived knowledge and confidence, as well as actual knowledge of functional assessment-based interventions pre- and postuniversity course participation. A quasi-experimental two-group pre- and posttest design was applied to examine (1) initial differences between two groups (by assigned instructor) in preservice teachers' perceived knowledge, perceived confidence, and actual knowledge, (2) growth over time on these three measures, and (3) their concluding performance following course completion. Results indicated mean score differences between groups at the start of the functional assessment-based intervention course instruction. Large magnitude effects were found for both groups when comparing pre- to posttest scores of preservice teachers' ratings of their perceived knowledge and confidence, as well as a measure of actual content knowledge. Posttest scores showed preservice teachers ended the experience with similar levels of actual knowledge, regardless of group membership. Findings indicate preservice teachers may benefit from a preparation course with applied practice to develop knowledge and confidence for using functional assessment-based interventions, a promising practice (What Works Clearinghouse, 2016), to support students with challenging behaviors. Limitations and future directions are presented.

Organizations desire more accurate cost systems as competition increases, and consequently increase cost system complexity, as cost systems with greater complexity are potentially more accurate than simpler systems. However, even complex systems are prone to impactful inaccuracies, for example, due to design or calculation issues, that can adversely affect decision-making and firm performance. The authors investigate whether and the extent to which cost system complexity and competition decrease managers’ attribution of cost-system-driven adverse firm effects to the cost system. The authors find greater cost system complexity (by inspiring greater confidence in the cost system) and higher competition (by providing a plausible external cause) decrease managers’ attribution of cost-system-driven adverse firm effects to the cost system. With both greater cost system complexity and higher competition, managers observing signals of material cost inaccuracies are potentially the least likely to attribute cost-system-driven adverse firm effects to the cost system.

In this chapter we demonstrate the construction of inverse test confidence intervals for the turning-points in estimated nonlinear relationships by the use of the marginal or first derivative function. First, we outline the inverse test confidence interval approach. Then we examine the relationship between the traditional confidence intervals based on the Wald test for the turning-points for a cubic, a quartic, and fractional polynomials estimated via regression analysis and the inverse test intervals. We show that the confidence interval plots of the marginal function can be used to estimate confidence intervals for the turning-points that are equivalent to the inverse test. We also provide a method for the interpretation of the confidence intervals for the second derivative function to draw inferences for the characteristics of the turning-point.

This method is applied to the examination of the turning-points found when estimating a quartic and a fractional polynomial from data used for the estimation of an Environmental Kuznets Curve. The Stata do files used to generate these examples are listed in Appendix A along with the data.

Business graduates’ enterprising capability augments their work readiness, transforming them into professionals capable of driving successful outcomes. At the core lie self-confidence and negotiating competence. However, embedding enterprise education and developing assessments to evidence learning is challenging. This study aims to offer a blueprint for establishing enterprise learning in the classroom and investigating the effectiveness of cultivating negotiating competence and self-confidence.

Modelled on Kolb’s experiential learning cycle, students engage in in-class and real-life negotiations, assessing self-confidence using a scale founded in Bandura’s self-efficacy theory. Open-ended reflections are also submitted. Quantitative data is analysed through multiple linear regression, while quantitative and qualitative data triangulation substantiates enterprise learning in negotiating competence and self-confidence.

Students’ reflections show that low self-confidence poses an initial barrier in negotiations, overcome with successive engagements. Quantitative analysis uncovers response-shift biases, with female and male students overestimating initial self-confidence levels. The gender and difference score type interaction reveals a more pronounced bias among female students starting from a lower baseline than male students, implying a more substantial self-confidence improvement for female students. These findings challenge traditional assumptions about gender differences in negotiations and emphasize the need for nuanced perspectives.

Enterprising capability is pivotal for business professionals. This study highlights the advancement of negotiating competence and self-confidence. It contributes uniquely to the development of enterprise education pedagogy. Focusing on nuanced gender differences challenges prevailing assumptions, providing a perspective to the discourse on negotiating competence and self-confidence in management training.