Focusing on positive service encounters, this study examined the relationships among employee behaviors, customers' positive emotions, and subsequent customer behaviors. A comprehensive framework of positive service encounters and ten hypotheses were developed based on an in-depth literature review and an application of the theory of cognitive appraisal and the theory of positive emotions. The dissertation employed a survey design with measurements from previous research and collected data with Amazon Mechanical Turk. The target sample (N=299) was individuals that had a positive interaction with an employee at hotels over the last six months. The Structural Equation Modeling results suggested that employees' mutual understanding affects customer gratitude and employees' unsolicited behaviors and competence influence customer delight. Subsequently, customer gratitude has a positive relationship with customers' repurchase intentions and word-of-mouth. In addition, customer delight has a positive relationship with customer' repurchase intentions and positive word-of-mouth. However, the results of the study did not support that customer delight can be triggered by employees' authenticity and customer gratitude can be evoked by employees' customized service. In addition, the relationship between customer gratitude and customers' providing feedback was not established. This study provides valuable implications for the industry regarding generating favorable customer behaviors in positive service encounters. This research also offers a theoretical explanation of systematic relationships among five dimensions of employee behaviors, two customers' discrete emotions, and three customer behavioral intentions in positive service encounters.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5965 |
| Date | 01 January 2016 |
| Creators | Kageyama, Yoshimasa |
| Publisher | University of Central Florida |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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