Riswanto Aura Lydia, Kim Seieun, Kim Hak-Seon
Department of Global Business, Kyungsung University, Busan 48434, Republic of Korea.
School of Hospitality & Tourism Management, Kyungsung University, Busan 48434, Republic of Korea.
Behav Sci (Basel). 2023 Nov 13;13(11):923. doi: 10.3390/bs13110923.
Tourism to Indian heritage destinations has been on the rise due to the increasing demand for heritage tourism. Increasing customer satisfaction and promoting Indian culture require tourism businesses to understand factors influencing tourists' experiences and behavior towards these destinations. Therefore, this study analyzes four popular heritage tourist destinations in India by using online reviews collected from Google Travel. Data are refined, processed, and visualized using the R programming language and UCINET 6.0. Furthermore, we explore the fundamental framework and interconnections among these characteristics through the utilization of exploratory factor analysis and linear regression analysis with the assistance of the SPSS software package. Based on customer reviews obtained from Google Reviews, an analysis was conducted on 6618 reviews of four heritage tourism destinations in India. From the top 60 words, four clusters of words were created, including "Physical characteristic", "Cultural and historical link", "atmosphere", and "area". Through explanatory factor analysis and linear regression analysis, we found that Physical characteristic, Cultural and historical link, atmosphere, and area all play a significant role in customer satisfaction. This study provides heritage destination managers and Indian government with insights into which attributes impact customer satisfaction the most and offers valuable marketing insights. As a result of this study, we are able to gain a greater understanding of the Indian heritage tourism market, and in doing so, we provide businesses with implications on how to enhance customer service.
由于对文化遗产旅游的需求不断增加，前往印度文化遗产目的地的旅游业一直在上升。提高客户满意度和推广印度文化要求旅游企业了解影响游客对这些目的地的体验和行为的因素。因此，本研究通过使用从谷歌旅游收集的在线评论，分析了印度四个受欢迎的文化遗产旅游目的地。使用R编程语言和UCINET 6.0对数据进行提炼、处理和可视化。此外，我们借助SPSS软件包，通过探索性因素分析和线性回归分析，探索了这些特征之间的基本框架和相互联系。基于从谷歌评论获得的客户评论，对印度四个文化遗产旅游目的地的6618条评论进行了分析。从前60个单词中，创建了四个词簇，包括“物理特征”、“文化和历史联系”、“氛围”和“区域”。通过解释性因素分析和线性回归分析，我们发现物理特征、文化和历史联系、氛围和区域在客户满意度方面都发挥着重要作用。本研究为文化遗产目的地管理者和印度政府提供了哪些属性对客户满意度影响最大的见解，并提供了有价值的营销见解。作为这项研究的结果，我们能够更好地了解印度文化遗产旅游市场，并在此过程中为企业提供如何提升客户服务的启示。
