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1 – 2 of 2Ekrem Tufan, Merve Aycan and Bahattin Hamarat
Introduction: When people need to take decisions, being economic decisions or otherwise, their decisions tend to rely on information the brain has already processed, and this…
Abstract
Introduction: When people need to take decisions, being economic decisions or otherwise, their decisions tend to rely on information the brain has already processed, and this includes the resources that the person has already invested. This is called sunk cost bias in the behavioural economics literature. On the other hand, mental practices could lead to the mental accounting bias, where people allocate a different value to a fixed amount of money, depending on circumstances.
Purpose: In this chapter, both biases mental accounting and sunk cost are investigated for the tourism industry in Turkey.
Methodology: The topic is researched through scenario-based questions and the Chi-square Automatic Interaction Detector (CHAID) method is applied.
Findings: As a result, it could be reported that people, regardless of gender, fall into sunk cost and mental accounting biases in decisions relating to their vacations. Mental accounting biases can be primarily explained using the scenario questions posed rather than gender, education, and income while sunk cost bias is explained by status, ‘being s university student’ and ‘income level’.
Practical implications: Rapid price changes in the tourism industry can disturb consumers who are mental accounting and sunk cost biased. So, they can change their holiday preferences or be dissatisfied with it and give negative feedback.
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Konstantinos Koronios, Lazaros Ntasis and Panos Dimitropoulos
This study aims to explore spectators' awareness of and attitudes toward sponsoring firms as well as to propose a model predicting their purchase and word-of-mouth (WOM…
Abstract
Purpose
This study aims to explore spectators' awareness of and attitudes toward sponsoring firms as well as to propose a model predicting their purchase and word-of-mouth (WOM) intentions toward the sponsors of a major sporting event during a pandemic crisis.
Design/methodology/approach
A quantitative method was used to collect the data, with 1,259 questionnaires being effectively collected and analyzed using SPSS and AMOS. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), path analysis and structural equation modeling (SEM) were used to analyze the data.
Findings
Factors such as sports involvement, sincerity, social media use, beliefs about sponsorship, sponsor's image, Covid-19 beliefs and emotions, awareness of and attitude toward sponsors were found to significantly predict spectators' purchase and WOM intentions.
Originality/value
The results support the structural equation model, providing a multidisciplinary conceptual framework that highlights the significance of comprehending the role of significant factors in sponsorship efficiency during the Covid-19 crisis. The proposed framework adds to the knowledge corpus of this field.
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