Structural equation modeling of affective commitment through Thainess customer-centric service for boutique hotel
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2023
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2566
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eng
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338 leaves
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b216688
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Thanasit Suksutdhi (2023). Structural equation modeling of affective commitment through Thainess customer-centric service for boutique hotel . Retrieved from: https://repository.nida.ac.th/handle/662723737/6696.
Title
Structural equation modeling of affective commitment through Thainess customer-centric service for boutique hotel
Alternative Title(s)
รูปแบบเชิงสาเหตุของความผูกพันทางจิตใจผ่านการบริการลูกค้าเป็นศูนย์กลางอย่างความเป็นไทยสำหรับโรงแรมบูติก
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Abstract
The customer-centric service plays a crucial role to enhance customer satisfaction in many service organizations currently. Especially, the service experience creation can invade the emotion and feelings of customers more deeply and expect them to revisit the hotel again. Thainess tends to place a great focus on the spiritual side of humans and the serving of guests naturally from the heart. Thus, this study aims to investigate the effect of the Thainess customer-centric service on perceived service value, customer experience, customer satisfaction, and affective commitment. To develop and test a structural equation model and analyze the direct and indirect effects of all five components based on the perspective of boutique hotel guests during the COVID-19 pandemic. The data was collected by using questionnaires from 528 samplings of boutique hotel guests in Thailand via an online survey via Google form. Descriptive statistics and path analysis were applied. The researcher employed both descriptive statistics and inferential statistics by using structural equation modeling (SEM). Exploratory Factor Analysis (EFA) with principal component and varimax rotation was employed to test the dimensionality of all 91 question items. In this study, second-order CFA (Confirmatory Factor Analysis) was applied to examine the four constructs, Thainess customer-centric service (TCCS), perceived service value (PSV), customer satisfaction (CS), and affective commitment (AC), which were conceptually and empirically specified as a higher-order factor, while the customer experience (CE) was examined through the first-order CFA application. To improve a model fit, 45 items were removed for further analysis due to the low standardized factor loadings and high correlation measurement error through the review of modification indices. Therefore, the remaining 46 indicators were used to measure the structural equation modeling of affective commitment through Thainess customer-centric service for boutique hotels. A further detailed examination is carried out by looking at the standardized residual covariance of each item and modification indices. After measurement, the number of paths was taken to enhance the validity of the collected data. The fit indices were tested for SEM and found that X2/Df = 0.966, GFI = 0.941, CFI = 1.000, NFI = 0.964, TLI = 1.002, RFI = 0.952, RMSEA = 0.000, and RMR = 0.024, all of them passed the criteria.
The results found that the model is consistent with empirical material in statistical significance. It can confirm that three significant factors affect affective commitment directly which are 1) Thainess customer-centric service, 2) perceived service value, and 3) customer satisfaction, while customer experience indirectly affects affective commitment. Moreover, the Thainess customer-centric service has an indirect significant affected affective commitment through perceived service value, customer experience, and customer satisfaction respectively.
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Description
เอกสารฉบับเต็มระบุปีไม่ตรงกับปีการศึกษาที่จบ (A Dissertation Submitted in Partial
Fulfillment of the Requirements for the Degree of Doctor of Philosophy (Integrated Tourism and Hospitality Management) The Graduate School of Tourism Management National Institute of Development Administration 2023)