Linking customer experience, satisfaction, and loyalty to brand power and performance in international hotels

  • Received November 20, 2021;
    Accepted July 20, 2022;
    Published August 4, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.18(3).2022.06
  • Article Info
    Volume 18 2022, Issue #3, pp. 59-71
  • TO CITE АНОТАЦІЯ
  • Cited by
    6 articles
  • 793 Views
  • 490 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The COVID-19 pandemic has had a significant influence on decreasing hotel consumption levels. To survive and compete in the market, hotels must be able to maintain their brand power and performance. This study aims to determine the relationship between customer experience, customer satisfaction, and customer loyalty toward brand power and brand performance in the hotel industry. The focus is on the importance of the role of the three consumer constructs on brand value. The paper uses a descriptive research design and a quantitative approach where data is collected by distributing online questionnaires to respondents through Google Forms. The selected population is tourists who have stayed in 4-5 star international hotels in Indonesia, with a sample size of 240 respondents. The collected data is then processed using SmartPLS v.3.3.3 to examine the results of the outer and inner models. The results show that from the customer’s perspective, customer experience has an impact on customer satisfaction, which influences customer loyalty. In addition, customer loyalty is a factor that affects brand value, including brand power and performance. Therefore, customer loyalty is a strong predictor of brand value in the hospitality and tourism industry. By strengthening this sphere, a company will have great resources and opportunities to build brand power and brand performance.

view full abstract hide full abstract
    • Figure 1. Research model
    • Figure A1. Outer model
    • Table 1. Characteristics of respondents
    • Table 2. Constructs and measuring items
    • Table 3. VIF values
    • Table 4. R-Squares and predictive relevance
    • Table 5. Model fit
    • Table 6. Hypothesis testing
    • Table A1. Construct reliability and validity
    • Table A2. Discriminant validity – HTMT
    • Table A3. Inner VIF
    • Conceptualization
      Evo Sampetua Hariandja, Fellicia Vincent
    • Formal Analysis
      Evo Sampetua Hariandja, Fellicia Vincent
    • Funding acquisition
      Evo Sampetua Hariandja
    • Investigation
      Evo Sampetua Hariandja, Fellicia Vincent
    • Methodology
      Evo Sampetua Hariandja, Fellicia Vincent
    • Resources
      Evo Sampetua Hariandja
    • Software
      Evo Sampetua Hariandja, Fellicia Vincent
    • Supervision
      Evo Sampetua Hariandja
    • Validation
      Evo Sampetua Hariandja, Fellicia Vincent
    • Writing – original draft
      Evo Sampetua Hariandja, Fellicia Vincent
    • Writing – review & editing
      Evo Sampetua Hariandja, Fellicia Vincent
    • Data curation
      Fellicia Vincent
    • Project administration
      Fellicia Vincent
    • Visualization
      Fellicia Vincent