Modeling and analysis of customer journey enablers: A case study of religious pilgrimage

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Customer journey theory has been discussed in service and management-related fields, but in the context of tourism, there is a lack of research on customer journeys and their enablers. Such research work is challenging, mainly because the customer journey involves the subjectivity of customers' experience and is influenced by multiple factors. Therefore, this study proposes a deduction analysis of an interpretive structural model (ISM) to construct a correlation analysis of customer journey enablers by collecting data on tourists’ actual experiences of pilgrimage. The importance of customer journey enablers is evaluated through the analytic network process (ANP), and the characteristics of the driving power and dependence power of the enablers are classified. This research analyzes the content of religious pilgrimages, establishes 12 enablers for customer journeys, such as “quality of life”, “local security”, “social stability”, and “local friendship”, and develops four customer journey paths through ISM. The important differences in journey path enablers are analyzed by the ANP and cross-impact matrix multiplication (MICMAC) under the influence of different ISM-level contents of each customer journey path. It is hoped that the discussion of the enablers of customer journey paths in religious pilgrimages can enhance tourists' understanding of religious pilgrimages and provide a management framework for tourism departments to help tourists enjoy the experience of local religion, humanities, and the natural environment.