Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor

Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor Shatrajit Goswami, Sandip Chakraborty, Yashwant Singh Rawal, Debasish Batabyal, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8617507/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Char Dham, the four sacred abodes of Lord Vishnu, hold profound religious and mythological significance, attracting millions of Hindu pilgrims across the Indian subcontinent. Despite its spiritual prominence, the Jagannath Temple in Puri has recorded a substantial number of negative visitor reviews from September 2016 to May 2022. This study aims to analyze and interpret the critical feedback from TripAdvisor, focusing exclusively on poor and terrible ratings to identify service gaps and enhance the quality of pilgrimage experiences. Out of 2,842 available reviews, only the most negative ones were considered to develop a Temple Administrative Quality (TAQ) model based on user-generated content (UGC). The model, designed for all four Char Dham sites, places special emphasis on Jagannath Temple, which reported the highest number of negative reviews over the past decade. The study integrates extensive literature reviews, official temple website analyses, and TripAdvisor UGC to construct the TAQ model. Its accuracy, precision, and sensitivity were tested using a confusion matrix. Findings underscore the need for differentiated pilgrimage tourism planning, recognizing distinctions among domestic and international tourists, pilgrims and leisure travelers, and spiritual versus cultural visitors. Notably, spiritual devotion often outweighs service shortcomings, fostering a tolerant attitude among pilgrims. JEL Classification: L83, M10, L15 Trip Advisor Temple Service Quality User Generated Content Pilgrimage Figures Figure 1 Introduction There exists a direct relationship between tourism development and economic development upliftment. It is empirically found that the cities with a higher potentiality of tourism development register a higher level of socio-economic development too (Parrilla-González,2021; Gong and Zhong, 2021 ). Many studies emphasized on authentic experience and perceived benefits as yardstick of support for new and retained visitors (Hung Lee et al., 2021 ; Chung et al., 2018 ; Taheri et al., 2018 ). While identifying indicators towards model building for sustainable pilgrimage in cultural destinations, Lozano-Oyola et al. ( 2012 ) focused on the sustainability approach and identification and selection of indicators that help tourism managers to assess the condition of a tourist site, and to identify and analyze issues that require addressing to upgrade the level of destination sustainability. However, they strongly recommend a realistic guide to establish how to understand and interpret information and how to compile it for decision-making. The importance of sustainable development transcends even well-established mass tourism destinations engaged in intensive pilgrimages with environmentally unsound practices and a disregard for sustainable principles. The ongoing restructuring of traditional destinations introduces a more intricate landscape, where sustainability emerges as an unavoidable and integral benchmark. It is not only a critical factor for maintaining competitiveness in the tourism industry but also responds to an increasing societal demand for responsible and ethical practices. In this evolving context, the concept of sustainability is fundamental, serving as a guiding principle that destinations must embrace for both their continued success and societal responsibility. (RebolloandBaidal,2003). With this changing pace of threats and challenges, pilgrim sites have to offer next-generation pilgrimage with a more human and sustainable orientation. Since time immemorial, Kashi is famous for intensive pilgrimage. This intensive pilgrimage has both the worst- and the best cases: worst because uncontrollable crowding occurs; best because there is mutuality between hosts and visitors as all are worshippers (Bleie,2003). Bleie ( 2003 ) also illustrates incipient blurred boundaries between pilgrimage and tourism, recognizes the increasing diversity of both tourism and sacred journeying, identified differences and similarities between modes of travel of recreation and pilgrimage, and incorporated economic and environmental risks assessment for the destination. Pilgrimage is sheerly unmatched by other types of tourism as it mainly focuses on religious belief and faith. In the promotion of any pilgrimage site mythological occurrence and history is critical. Interconnection between tourism and pilgrimage produces positive changes and in the case of Hindu pilgrimage, this is very important to imbibe new enthusiasm without seeing the god for real (Aukland,2017). As pilgrimage sites are frequently visited by people of all ages, and income groups, travel agents or tour operators need to provide pilgrimage packages as per the specific tradition and religious beliefs. Customized pilgrim packages with all the necessary information about the destination on the travel website of a travel provider will certainly have a positive influence on the tourists and enhance the trust (Khareetal.,2020). Othergroupsoftourismexpertsthinkthatthepilgrimagetraditionshouldbeconsidered from the tourism circumstances and distance between the pilgrim destination and tourist location matters. Pilgrims become tourist pilgrims when the destination of the pilgrimage is more distant from their home (Cohen, 1992 ; Kim et al., 2020 ). Recently, the idea of pilgrimage has been changing, and the concept of pilgrims and religious tourists is switching day by day. Pilgrimage does not complete with the arrival of pilgrims at the destination rather it stretches till further return home and away (Béres, 2018 ). A further method of approach to the study is founded upon user-generated content (UGC) that is highly utilized by tourism and hospitality services consumers both as a source of information needed for decision making as well as mean of sharing. Consumer accounts that are online are viewed as likely to have latest and credible information that is detail and purpose-oriented (GretzelandYoo,2008). Reviews shared on social media such as Trip Advisor can have profound effects on every stage of the travel decision-making process (Choe et al., 2017 ; Zeng and Gerritsen, 2014 ). Such comments and reviews can greatly help service providers and destination managers to better know travel patterns, expectations, feelings, destinations, image perceptions, and satisfiers dissatisfies that can affect tourist behaviors and intentions. Most of the research on consumer feedback primarily explores the usage of social media among tourists (Gursoyet al., 2021 ). Users of social media not only use the content available on social media websites but also generate and provide content through posting and commenting (Choe et al., 2017 ). As the topic of online reviews, comments, etc. Review of literature Pilgrimage Attractions Mak Twain describes “Jagannath as kindest of Gods.” Puri, located in the eastern state of Odisha, India, is a city of great religious and cultural significance, primarily because of the Jagannath Temple. The Jagannath Temple is one of the most important pilgrimage destinations for Hindus, and it holds a special place in the hearts of devotees. The Jagannath Temple is the main attraction in Puri and is dedicated to Lord Jagannath, a form of Lord Krishna. The temple is renowned for its towering spire and unique architecture. It is an important center of worship and is one of the Char Dham pilgrimage sites for Hindus. The annual Rath Yatra or Chariot Festival is one of the most famous festivals in Puri and is celebrated with great fervor. During this festival, the idols of Lord Jagannath, his brother Balabhadra, and sister Subhadra are placed on elaborately decorated chariots and pulled through the streets by thousands of devotees. It is believed that participating in this festival or even witnessing it can grant spiritual blessings. In conclusion, Puri and the Jagannath Temple hold immense religious, cultural, and historical importance in India. Pilgrims and tourists visit Puri not only for their spiritual journey but also to experience the rich traditions and festivities associated with this sacred place. Later, the place became a confluence of many world religions for centuries, with Hinduism predominating and co-existing with Jainism, Buddhism, and Islam. Kutlutürk ( 2013 ) has demonstrated why and how this place is accorded a holy place while Gogate ( 2020 ) explains the demolition, relocation, and reconstruction of this pilgrim center for the centuries. This great heritage is culturally associated and comparative, representing various ways by different agents of tourism promotion (Bandyopadhyay et al., 2008 ), deciding on public and private sector participation. Therefore, as an icon of Vishnuism in Hinduism, Puri promotes not only the destination itself but the several thousand-year-old heritage routes that attract tourists and pilgrims to relatively other lesser-known place also (Moulin and Boniface, 2010). UGC (User-Generated Content) and its role in the pilgrimage tourism experience With the advent and increasing use of the World Wide Web, consumers’ interests are anew focal point, specifically in tourism and hospitality services in which consumers or tourists rust more websites with reviews than professional guides, travel agencies, and even blogs (Akehurst,2009). User-generated content (UGC) has emerged as a critical data source for analyzing tourism mobility patterns, influencing travel decisions, and forecasting tourism demand. The integration of UGC with big data and physical footprint analytics allows for the creation of temporal effects in vacation mobility through static-network scanning and spatial interaction models at an accumulative level. The reviews and digital content provided by tourists serve as a form of digital word-of-mouth (WOM), significantly impacting trip choices (Gretzel, 2006 ; Jin et al., 2018 ). This digital WOM is instrumental in shaping travel perceptions, destination selection, and tourism behaviors, offering valuable insights for both researchers and industry stakeholders. The utilization of online reviews in tourism demand forecasting has demonstrated substantial improvements in predictive accuracy. Traditional models of tourism demand forecasting are often limited by data availability and frequency. However, by employing high-frequency online review data in time-series models, tourism forecasting models achieve superior predictive performance (Hu et al., 2022 ). This advancement enhances destination management strategies by allowing real-time adjustments based on evolving traveler sentiments and behaviors. Digital literacy studies further enrich the understanding of UGC's role in tourism. Research into online materials has facilitated a 'digital turn' in literacy studies, which has evolved in response to new linguistic and communicative practices. Digital literacies, as described by Lankshear and Knobel ( 2011 ) and Coiro et al. ( 2008 ), differ from traditional literacy studies in that they emphasize the unique textual, interactive, and participatory nature of online communication (Jin et al., 2018 ). This framework provides an essential lens through which to examine the effectiveness of UGC in tourism research. Contemporary studies on UGC primarily explore its applications in service quality assessment, destination image and reputation management, tourist experience analysis, and behavioral trends (Lu & Stepchenkova, 2014 ). However, leveraging UGC for tourism research presents challenges. User motivations for contributing reviews are varied and often unspecified, and only a fraction of tourists actively generate content (Jiang et al., 2010 ; Yoo & Gretzel, 2009 ). Additionally, the credibility and reliability of user-generated content vary significantly across platforms, affecting its utility for comprehensive tourism analysis (Cox et al., 2009 ). A deductive-inductive approach is suitable for analyzing UGC, particularly in assessing the tourism experiences of historically significant circuits, such as the Char Dham pilgrimage in India. For instance, a focus on Kashi Vishwanath Temple, identified through high volumes of negative reviews, highlights the need for precise data extraction, interpretation, and contextual analysis. However, manual transcription of such reviews is time-intensive and costly, necessitating automated web harvesting techniques. While automation streamlines data collection, it remains a controversial approach due to ethical and methodological concerns (Jennings & Yates, 2008 ; Vanweland & Royakkers, 2004; Batabyal et al., 2023 ). Johnson et al. ( 2012 ) emphasize that analyzing UGC requires either extensive manual efforts or automated extraction, each with its respective limitations. Further research by Han et al. ( 2018 ) highlights the potential of web-based UGC samples in constructing hypothetical models that explain direct and indirect effects of tourism-related issues. By leveraging user-generated knowledge, researchers can enhance predictive capabilities and develop targeted interventions to improve tourism experiences. As digital platforms continue to shape consumer behaviors, the strategic utilization of UGC remains pivotal in advancing tourism research, policy-making, and destination management. In beyond couple of years, numerous stages for online surveys in the travel industry area, like Trip Advisor, Desolate Planet, and Google Guides, have become more common in examination and work, prompting the multiplication of concentrates on web-based audits, and featuring the utilization of new scientific advances. Components of pilgrimage destination experience of tourists According to Cooper et al. ( 1993 ), a tourist destination comprises four fundamental components: attractions, accessibility, amenities, and ancillary services. These elements serve as the cornerstone of tourism development, ensuring a comprehensive and fulfilling experience for travelers. Expanding on this framework, Jauhari ( 2010 ), Gamboa ( 2021 ), and Skinner and Soomers ( 2019 ) emphasize additional dimensions of tourism services and development, such as the integration of internet facilities, self-check-in kiosks, and immersive light and sound experiences. Furthermore, they highlight the significant impact of niche tourism on cultural heritage, stakeholders, and community participation, all of which contribute to an enriched cultural, transformational, and spiritual visitor experience. Pilgrimage tourism, in particular, necessitates proficient management due to the vast number of tourists motivated by religious beliefs (Kreiner, 2018). Effective pilgrimage tourism management ensures a secure and comfortable experience by providing essential services, including food, accommodation, and infrastructural support. Additionally, proper management mitigates the adverse effects of mass tourism on sacred sites, as excessive tourism can lead to environmental and cultural degradation (Prihantoro et al., 2019 ). Given that pilgrimage destinations often hold immense heritage value (Giovine & Fuentes, 2016), their preservation is critical in fostering national and shared cultural identities. Consequently, service quality assessment emerges as a vital tool for evaluating consumer experience and satisfaction, often employing multidimensional methodologies (Pakurar et al., 2019). Authenticity is a crucial aspect of grand festivals and pilgrimage tourism, significantly shaping tourists' emotional experiences and engagement (Lee et al., 2015 , 2021). Authentic experiences contribute to perceived benefits and influence active participation in tourism development. Several models have been proposed for assessing service quality within the tourism sector. Gronroos ( 1982 , 1984 ) introduced a service quality model that differentiates between technical and functional quality. However, Rust and Oliver ( 1994 ) expanded this model by incorporating the service environment as a third dimension. Despite their conceptual significance, these models have not undergone extensive empirical testing, and support in the literature remains limited. While some service quality frameworks demonstrate strong validity in specific service industries, they often lack broad applicability and generalization (Oh & Kim, 2017). To address these limitations, Ramya and Kowsalya (2019) developed and empirically tested a multidimensional model of M-S-QUAL for mobile service quality. Their study, involving 578 Internet respondents, assessed service quality through validity, reliability, exploratory factor analysis, and confirmatory factor analysis, thereby contributing valuable insights for future research. Industry-specific service quality measurement models have also emerged in various sectors, such as mobile healthcare (Ghotbabadi et al., 2015 ) and low-cost airlines (Barnes, 2017). More recently, Batabyal et al. ( 2023 ) introduced the concept of temple service quality (TSQ) measurement, underscoring the need for sector-specific service quality assessment within religious tourism. In the digital era, pilgrims increasingly rely on online platforms to share experiences and consult reviews before planning their journeys. Online Travel Agencies (OTAs) such as TripAdvisor provide a repository of user-generated content that influences pilgrimage planning. The analysis of TripAdvisor reviews reveals a shift in tourists’ perspectives, transitioning from a 'dark tourist gaze' to an 'environmental gaze' and a 'cultural gaze'—a phenomenon shaped by strategic governmental interventions aimed at post-war reconciliation (Park et al., 2016 ; Samarathunga et al., 2020 ). Again, Husemann and Eckhardt ( 2018 ) observed that many pilgrims engage in online forums to seek advice on preparations, attire, and other logistical concerns. Cugini (2021) further asserts that modern tourists, akin to pilgrims, seek spiritual enrichment when visiting sacred sites. While spiritual motivation is not a prerequisite for spiritual experience, the ambiance of the destination, interactions with local communities, and site-specific activities significantly influence the depth of spiritual engagement. As pilgrimage tourism continues to evolve, future research should explore innovative service quality models that encompass both traditional and modern dimensions of pilgrimage experiences, ensuring sustainable development and enriched visitor satisfaction. Objectives and Research Question: Char Dham or four holy temples of the lord Vishnu represents one of the oldest extant pilgrim circuits and part of the great religious heritage in South Asia. For compelling and quality experiences the opinions of tourists are often analyzed and interpreted for enhancing the administrative and managerial quality of services. Temple administrative equality has a positive relationship with tourist satisfaction that influences future behavior intentions (Canny, 2013 ). From the field visits and direct and indirect observations, it is found that different service failures are very common and the quality of temple administrative services is to be improved in most of the temples. Following is Table 1 showing the review performance for all the holy temples representing mythological and religious Char Dham of the god Vishnu respectively. Table 1 Ranking of Responses Retrieved from the Trip Advisor from September, 2016 to May, 2022 Char Dham Total Responses for 'excellent' Rank (% of Total Responses) Responses for 'Terrible' Rank (% of Total Responses) Badri Nath 480 396 1 2 4 Dwarka 1131 751 2 8 3 Jagannath 2771 1632 4 65 1 Rameswaram 1695 1112 3 12 2 Source: Trip Advisor Reviews, September2016 to July 2022 Jagannath temple is found to have been lacking most whereas Badrinath is the best performing one among all four abodes of the god Vishnu in India. Now, the question is “do these maximum negative reviews exhibit a true picture of this destination?” This study further investigates the reviews and user-generated contents (UGC) and proposes a hypothetical model of temple administrative quality (TAQ) for future sustainable pilgrimage in this circuit incorporating three other major pilgrim centers in the sub-continent. Therefore, the research question in the study is whether temple administrative qualities are responsible for future pilgrimages (Ghimireetal.,2022) in Jagannath temple and similar other temples in the circuit or a pre-occupied spiritual belief and faith have a significant contribution, often exhibited the compromising attitude and minimizing negative perceptions. Methodology Research site The study explores the online reviews posted by the tourist decadal time frame from September 2011 to July 2021 who visited the Jagannath temple, Puri. A total of 2848 reviews are found over this specified period and 157 ‘poor and terrible’ reviews are finally chosen. Jagannath temple is chosen as a research site because it is one of the epicenters of Hinduism and associated mythology. However, at present, government authorities, temple or shrine trusts etc. have identified certain common areas of management and operation. Following are the areas of services retrieved from the official/ related temple or shrine websites in Table 2 . Accommodation facility; Pony services; Heli services; Bus services; Registered Tour Operators Research Design Parasuraman et al. ( 1985 ), gave a more detailed model of service quality assessment, which has the maximum number of dimensions, namely 10 dimensions, including Tangibles, Reliability, Responsiveness, Understanding the customers, Access, Communication, Credibility, Security, Competence, and Courtesy. This huge model was later advanced into the commonly known SERVQUAL, by Parasuraman et al. ( 1988 ), which merged the dimensions on a five-dimensional basis, that is, Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The SERVQUAL scale has now come to be accepted widely across the world by academics, researchers, and practitioners by virtue of its applications in diverse fields and countries (Butt and Run, 2010 ; Farooq et al., 2018 ; Lee-Ross, 2008 ). Good practical implications recognize SERVQUAL itself as a service quality measurement scale able to measure customer perception about that quality service (Parasuraman et al., 1994 ). The present study extends the SERVQUAL model (Parasuraman et al., 1985 ) and essentially addresses the introduction of Temple Administrative Qualities (TAQ) for intensive pilgrim sites of the Asian subcontinent. The ratings of online reviews play a major role in customer patronage, whereas official ratings are going down. Current-day customers are increasingly becoming aware of the ratings posted by other online customers through sites Trip Advisor, Google Reviews, and Yelp. The slightest changes in the online review ratings are being worked upon by business houses, for any change in rating, however small, could affect the business (Nalley et al., 2019 ; Ghimire et al., 2021 ). Review platforms need to develop new review/framing processes that, in conjunction with emotional sentiments, can better distinguish between helpful and unhelpful reviews with marketers encouraging that readers of the review share this kind of review with others (Huang et al.,2020). In the travel and tourism sector, several online review portals, such as Trip Advisor, Lonely Planet, and Google Maps, have lived on in actual practice and research into the past few years (Sun et al., 2019 ). Though, each of the platforms has its features, yet the philosophy of the review platforms is starkly similar: these enable users to submit reviews while letting users score their experiences on a scale (Taecharungroj and Mathayomchan, 2019 ). Orea-Giner's team in 2022 employed text mining in its study to examine the emotions and sentiments of customers regarding the implementation of robots in hotels, drawing from the ratings that they gave in reviews on Trip Advisor. The Trip Advisor platform is the biggest place to assist traveling, where more than a billion reviews and feedback from 8 million businessmen and tourists go into assisting someone in making a decision to visit a particular city place or destination. Trip Advisor became a prominent review platform in the tourism sector for both tourists and researchers alike (Taecharungroj and Mathayomchan, 2019 ). Therefore, Trip Advisor was selected as a case for the study in the present work. The main purpose of this study is to investigate whether temple service qualities are responsible for future pilgrimages in Puri Jagannath and similar other temples in the circuit or whether a pre-occupied spiritual belief and faith have a significant contribution, often exhibiting a compromising attitude and minimizing negative perceptions using the UGC and to offer insight for understanding the factors that can affect the pilgrimage tourist’s evaluation of travel experience in a site. To achieve this goal, the review comments posted to the largest social media platform i.e., the trip pilgrimage or religious experience for determining the dimensions of attractions and services advisor (O’Connor, 2010 ), have been analyzed within the scope of similar websites as their UGC source (Bamberger and Phillips, 1991 ). This study adopted a mixed approach since this approach is one of the correct methods for understanding (Taecharungroj and Mathayomchan,2019). A significant number of studies used customer review from Trip Advisor and other individual feelings and ideas (Creswell et al., 2003) keeping in view the positive and negative emotions (Huangetal.,2020; RenandHong,2019; Orea-Gineretal., 2022 ). Data Collection and Analysis: Abowitz and Toole ( 2010 ) pointed out that there is no single way of collecting data since all methods have strengths and weaknesses and therefore recommended a mixed-methods approach in terms of feedback, reliability, and causal inference. The critical feedback regarding interpretations of the researcher and suggested offers of their reflections enhances the quality and trustworthiness of an analysis and justifies the model as an empowerment position endorsing participants as co-owners of the results (Fassinger and Morrow. 2013). Khareetal. ( 2020 ) investigated the competitive advantage of websites over apps particularly in branding and CRM opportunities and identified network benefits, interactivity, and pilgrimage package information to be influential factors triggering trust and customer reviews in keeping relationships with the website. Laer and Izberk-Bilgin ( 2018 ) emphasize the rambunctious characteristics of online reviews of tourists in pilgrimage sites on TripAdvisor and how tourists articulate the spiritual and material dimensions of pilgrimage experiences. They looked at how pilgrims integrate analytical discursive features into expressing the material side of their consumption experience while review ratings are seen to only deliberate the spiritual side of their consumption engagement. All the temple service qualities are thus postulated as reasonably good and positively recognized by the majority of the pilgrims. However, there is a growing marketisation of spirituality (McAlexander et al., 2014 ) and even spiritual experiences are considered 'rateable' and 'reviewable' online today (Laer and Izberk-Bilgin, 2018 ). Pilgrimage for spiritual enlightenment has been shown to be a remarkable consumption experience (Husemann et al., 2016 ). On the other hand, Santana et al. (2019) adopted an interpretive approach while making use of the multi-sited ethnographic methodologies of "following the thing" and "following the people," tracing the pathways of tourists and objects during a pilgrimage with implications for the understanding of the past as it utilizes the spiritual and liquid/solid engagement to sacred objects. It has also been maintained that India continues to be an ethnically diverse nation where Hinduism precedes and dominates all other religions/ethnicities (Bandyopadhyay et al., 2008 ) with an overall pluralistic and secular religious disposition since its very independence. Data analysis in the study considers a decadal time frame from September 2011 to July2021 and is subject to the availability of tourists’ reviews on Trip Advisor. A total of 1670reviews are found over this specified time period and 1379 are finally chosen. From these total usable reviews, 129 pilgrims mention their occasional visit whereas 1250 reviews were non-occasional. The average of the coefficient of variations of the temple administrative qualities (TAQ) for tourists or pilgrims visiting usually during the non-occasions is 35.2976, compare to the occasional movement with 30.26704 respectively, indicating more consistency in opinion. On the other hand, the average coefficient of variations of the temple administrative qualities (TEMP SERVQUAL) for the 984 Hindu tourists was 41.7, whereas the same was 38.4 for the non-Hindu visitors indicating more consistency in their opinion. Tourist distribution From Tables 3 and 4, it can be depicted that most of the reviews about Puri Jagannath temple on TripAdvisor were from countries like the UK, South Africa, the USA, Australia, and Bangladesh. Whereas, few reviews were from other countries like Germany, Nepal, France, and the rest of the world. Researchers also collected reviews of national tourists visiting the Puri Jagannath temple. Their views were from Maharashtra, Delhi, Uttar Pradesh, Karnataka, Tamil Nadu, West Bengal, Telangana, Gujarat, Panjab, Madhya Pradesh, Bihar, etc. A total of 1379 relevant reviews were used in the current study of which 984 reviews were of Hindus and 395 reviews were from non-Hindus respectively. Table 3 Foreign tourist distribution Country Percentage United States of America 22.19 Bangladesh 20.29 United Kingdom 9.98 Australia 5.96 Canada 4.48 Sri Lanka 2.87 Nepal 2.19 Germany 2.01 Rest of the world 26.27 All the usable reviews are carefully studied for conceptualizing the negative and positive aspects of services and relevant points are taken into note, viz. understanding the sources of bias, judgement calls, subjectivity, and inductive approach for developing theory (Guzzoetal.,1987). Considering the technical and conceptual limitations, such as biasness, communication barriers, related accuracy, web harvesting, etc. reviews have been studied by the experts only. This study’s scale reliability coefficient is found 0.7894 for all the usable reviews. Reviews of the residents, hotels or other facilities and religious descriptions have been excluded from this study. Reviews have been tabulated with four fundamental options in the confusion matrix viz. True Negative (TP), False Positive (FP), True Positive (TN), and False Negative (FN) respectively. In this study, True Negative (TN) and False Positive (FP)are two confusions in the matrix. True negative (TN)implies tourists are positive, patient, and graceful about destination service qualities though it is not. False positive (FP), on the other hand, is when tourists are negative and informed about perpetual chaos and conflict but gains a positive experience with all services. The number of service quality issues in this study is dependent on actual temple visits and study of respective websites of all major temples and shrines already focusing on relevant points of service delivery, convenient customer access and service failure respectively (as referred to Table 2 ). Many studies scrutinized the impacts of service quality (SQ) on customer satisfaction (CS), attitudinal loyalty (AL), and purchase intention (PI) although SQ may also have an impact on other important variables such as word of mouth, trust, price premium, market share, and profits (Carrillat et al., 2009 ; Zeithaml, 2000 ). This study is in line with the extension of such trends and practices along with the studies for mobile healthcare, hairdresser, etc. (Pollack, 2009 ; Akter et al., 2010 ) with varying service recognition and failure. Based on services and activities offered by most of the Indian temples (as referred to in Table 2 ), cleanliness, beggars and trespassers handling, security/documentation, services by priests’ shopkeepers’ human discrimination, temple hospitality, activities crowd handling, local transportation and street animals handling are the classifiers comprising of temple service quality (TSQ). As stated in Fig. 2, all usable 1379 reviews are read and marked 1, 2, 3, and 4 respectively for true-negative (TN), false-positive (FP), true-positive (TP), and false-negative (FN) cases comprising an imbalanced dataset. To mitigate or stop such tyranny imbalance, the degree of class imbalance and the complication of the concept have been taken care of to check bias in policy decisions (Kulkarnietal., 2020 ). The user generated content (UGC) based service quality models are not new. Han et al. ( 2018 ) shows how to appeal tourists’ intrinsic interest via media channels making their choice, style, and delivery of certain messages a key issue for tourism marketers and management. They explained how the social media turned into an important and acknowledged channel for tourism information, with user-generated content (UGC) being more trusted than official channels, yet there is hardly any knowledge about its potential role. Results and discussion There are several other factors in each classifier mentioned in Fig. 1 . The confusion matrix is composed of nine classifiers and each one has several interrelated points contributing to overall temple services. Table 6 Results of confusion matrix towards temple administrative quality (TAQ) model Measures Cleanliness Beggars & Trespassers Handling Security Documentation Services by Priests & Shopkeepers Human Discrimination Temple Hospitality Activities Crowd Handling Local Transport Street Animal Handling Sensitivity 0.6522 0.6957 0.60000 0.7059 0.6481 0.7870 0.60000 0.4421 0.2308 0.5455 Specificity 0.1667 0.6000 0.5238 0.3966 0.2727 0.8947 0.5238 0.0069 0.2949 0.2830 Precision 0.6522 0.8000 0.6667 0.6316 0.6364 0.7391 0.6667 0.0103 0.2308 0.6122 Negative Predictive Value 0.1667 0.4615 0.4521 0.4792 0.2830 0.9173 0.4521 0.3457 0.2949 0.2308 False Positive Rate 0.8333 0.4000 0.4762 0.6034 0.7273 0.1053 0.4762 0.9931 0.7059 0.7170 False Discovery Rate 0.3478 0.2000 0.3333 0.3684 0.3636 0.2609 0.3333 0.9897 0.7692 0.3878 False Negative Rate 0.3478 0.3043 0.4000 0.2941 0.3519 0.2130 0.4000 0.5579 0.7692 0.4545 Accuracy 0.5092 0.667 0.5706 0.5804 0.5215 0.8651 0.5706 0.0168 0.2638 0.4601 FI Score 0.6522 0.7442 0.6316 0.6667 0.6422 0.7623 0.6316 0.0200 0.2308 0.5769 Matt Hews Correlation Coefficient -0.1812 0.2781 0.1212 0.1065 -0.0799 0.6690 0.1212 -0.5957 -0.4751 -0.1641 Here, the confusion matrix with the above nine classifiers raises a confusion from true negative (TN)to false positive (FP). Basically, Fig. 1 discloses four important measures, viz. sensitivity, specificity, F1 score and Mathew’s correlation coefficient respectively. This model is a pioneer to ascertain a TAQ model through user-generated contents (UGC) for sustainable pilgrimage and its practices in 4 Hindu pilgrim centers belonging to the several thousand years old mythologies of the sacred radiant of pillars in Indian Subcontinent. Indian sub-continent-specific Hindu temple site-oriented TAQ model is the first of its kindexploringmanyconvenientpilgrims’accessandpointofsalesforactual(ritualistic/general) service delivery. This model reorients a new service blueprint for ritualistic and non- ritualistic or general service delivery in any Hindu pilgrim site in the Indian Sub-continent. Towards the fitness of the TAQ model, all the technical and conceptual issues were found important and F1 scores were found highly acceptable. Though the model was technically accepted, yet the assertion of exploring and improving service quality was rejected and rather exhibited a scope for the materiality-spirituality continuum for future research. For the cleanliness, the value of the sensitivity is point 0.97 and values of respective other classifiers are more than 0.9, except activities. Sensitivity of the pilgrims are found very high and they are satisfied with cleanliness, beggars and trespassers handling, security/documentation, services by priests’ shopkeepers’ human discrimination, temple hospitality, activities crowd handling, local transportation, and street animals handling. Only there is a certain problem in the activities as pilgrims are unable to take important decision which of the activities to opt. From the specificity, most of the values of respective classifiers are more than 0.80, i.e., whatever observations are coming from literature review are specific. From the precision, it is also found that the confidence level of the pilgrims is very high, i.e., they are more confident while writing an opinion on TripAdvisor. F1 score (i.e., the geometric mean of precision and sensitivity) is also very high and close to 1. Therefore, a robust relationship exists between the inter-class and inter-class groups. Conclusion and Implications The aim of this paper was to explore if maximum negative reviews exhibit a true picture of Puri Jagannath temple and whether temple service qualities are responsible for future pilgrimages in Puri Jagannath and similar other temples in the circuit or a pre-occupied spiritual belief and faith have a significant contribution, often exhibit compromising attitude, and minimize negative perceptions. This study adopted a mix approach. Based on the total reviews received from the tripadvisors.com, the reviews and user generated contents (UGC) are investigated through an extension of SERVQUAL model (Parasuramanetal.,1985), known as Temple administrative qualities (TAQ) for intensive pilgrim sites of the Asian Subcontinent. Towards the fitness of the temple administrative quality (TAQ) model, all the technical and conceptual issues are important. The accuracy, sensitivity, precision, and F1 scores are highly acceptable in the study. Though the model is technically accepted, yet the assertion of exploring and improving service quality is rejected and exhibits a scope for materiality-spirituality continuum with appropriate point of balance. Therefore, an immense possibility of promoting Puri, Jagannath as an epicenter for alternative creative tourism destination for spiritual learning is emerging for various interest groups locally and globally. Instead of offering more temple facilities and services, future pilgrimage tourism planning may be oriented to a sheer difference between domestic and international tourists, pilgrims and accompanied tourists, spiritual and cultural tourists, etc. The spiritual belief and faith supersede commonly visible service failures and exhibit a compromising attitude of the pilgrims and accompanied tourists as indicated in previous studies (Medhekar and Haque, 2012 ; Yanata, 2021 , Ray et al. 2012 ). Future pilgrimage is considered as a healing process from a past occurrence or pain in which the pilgrims can communicate to the gods in a temple, church, or mosque that has a significant effect on their life (Warfieldetal.,2014). Limitations and Future Research: Though this study has conducted a complete enumeration, it is confined to the reviews and contents of the TripAdvisor’s only and exhibits a future scope for comparability in model fitting (Richards, 2021 ). This study does not differentiate the perceptions and attitudes of domestic pilgrims from their foreign counterparts. Based on reviews and user-generated content, specifically for foreign tourists, maybe with other portals of OTAs (Online Travel Agents), research can be conducted for destination image and identity in the future. Furthermore, this is only an indication of much more research along different pilgrim. Circuits in India that possess the same mythological and religious values, e.g., 51 Shakti-Peeths, 8 Vinayak temples, etc. It also finds out new scope for comparing many reviews already available on the websites of OTAs. Declarations Author Contribution Our original research manuscript entitled “Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor” for consideration for publication in SN Business & Economics.This study proposes and empirically evaluates the Temple Administrative Quality (TAQ) Model within the context of the Char Dham pilgrimage circuit, a globally significant religious tourism destination in the Indian subcontinent. Drawing on User-Generated Content (UGC) extracted from TripAdvisor reviews, the research offers a data-driven assessment of pilgrims’ and visitors’ perceptions of temple administration, service efficiency, infrastructure management, crowd control, and experiential quality.The novelty of the study lies in its integration of digital tourism analytics with religious and spiritual destination management, an area that remains underexplored in business and economics literature. By applying qualitative and quantitative UGC analysis, the paper contributes to emerging discussions on service quality measurement, public administration effectiveness, destination governance, and sustainable religious tourism management. The findings offer practical insights for policymakers, temple management authorities, and tourism administrators seeking to enhance service delivery and visitor satisfaction in high-density pilgrimage destinations.This manuscript is original, has not been published previously, and is not under consideration for publication elsewhere. All authors have approved the manuscript and agree with its submission to SN Business & Economics. Ethical standards have been duly observed, and no conflict of interest exists. References Abowitz, D. A., & Toole, T. M. (2010). Mixed method research: Fundamental issues of design, validity and reliability in construction research. Journal of Construction Engineering and Management, 136 (1), 1–24. Akehurst, G. (2009). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8617507","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602169575,"identity":"f1431e3d-9734-4cdb-95a5-44e8a2d810ea","order_by":0,"name":"Shatrajit Goswami","email":"","orcid":"","institution":"Institute of Advanced Education and Research","correspondingAuthor":false,"prefix":"","firstName":"Shatrajit","middleName":"","lastName":"Goswami","suffix":""},{"id":602169576,"identity":"2afcbca2-8b7f-4e38-8982-e58bad33d662","order_by":1,"name":"Sandip Chakraborty","email":"","orcid":"","institution":"Amity University","correspondingAuthor":false,"prefix":"","firstName":"Sandip","middleName":"","lastName":"Chakraborty","suffix":""},{"id":602169577,"identity":"320d8eb1-e241-4759-b019-8190e1e30486","order_by":2,"name":"Yashwant Singh Rawal","email":"","orcid":"","institution":"Amity University","correspondingAuthor":false,"prefix":"","firstName":"Yashwant","middleName":"Singh","lastName":"Rawal","suffix":""},{"id":602169578,"identity":"2f10a86c-fc4d-4a10-a3b3-d0cd16105243","order_by":3,"name":"Debasish Batabyal","email":"","orcid":"","institution":"Amity University","correspondingAuthor":false,"prefix":"","firstName":"Debasish","middleName":"","lastName":"Batabyal","suffix":""},{"id":602169579,"identity":"713eb59e-80d2-4851-8671-fcb6f96eacfd","order_by":4,"name":"Nilanjan Ray","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYDCCA0CcUMDAwNgA4cuBBR8Q1GIA12JgDBZMIKSFwQDONUgEa8Wnhe/2AbYHDwzs8pjbzx7d+DXnT/r8sMMPgbbYyek2YNcieS6B3SDBILmYsScv7bbsNoPcjbfTDIBako3NDmDXYnCGgU0iwYA5sbEhx+y2JEjL7ASQlgOJ2/BrqU9s7H8D1pJuODv9AzFaDic2zsgxu/lxm0GCvHQOflskzzC2AbUcB2oB2sK4zdhwg3ROwQGg73D6he8M8zHJHxXViRv7gbb83CYnLz87ffOHDxV2cri0wOPQEEgx84CcClZpgEs5EpAH6f4BYjQQoXoUjIJRMApGFAAAEJFmPnm+9rUAAAAASUVORK5CYII=","orcid":"","institution":"JIS University","correspondingAuthor":true,"prefix":"","firstName":"Nilanjan","middleName":"","lastName":"Ray","suffix":""}],"badges":[],"createdAt":"2026-01-16 11:06:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8617507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8617507/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104248927,"identity":"00f5c916-c779-4120-9dfe-e753f09ce054","added_by":"auto","created_at":"2026-03-09 15:52:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":742402,"visible":true,"origin":"","legend":"\u003cp\u003eTemple administrative quality (TAQ) model (see online version for colors)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource\u003c/em\u003e: TripAdvisor’s reviews for Puri Jagannath temple\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8617507/v1/3292b58045bb96df15a32fac.png"},{"id":107480349,"identity":"93980e4d-1d4e-4661-8840-3a1aa60a9831","added_by":"auto","created_at":"2026-04-22 02:08:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1443802,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8617507/v1/1f56a079-4a50-404d-b22f-263684f6c07f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThere exists a direct relationship between tourism development and economic development upliftment. It is empirically found that the cities with a higher potentiality of tourism development register a higher level of socio-economic development too (Parrilla-Gonz\u0026aacute;lez,2021; Gong and Zhong, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Many studies emphasized on authentic experience and perceived benefits as yardstick of support for new and retained visitors (Hung Lee et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chung et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Taheri et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While identifying indicators towards model building for sustainable pilgrimage in cultural destinations, Lozano-Oyola et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) focused on the sustainability approach and identification and selection of indicators that help tourism managers to assess the condition of a tourist site, and to identify and analyze issues that require addressing to upgrade the level of destination sustainability. However, they strongly recommend a realistic guide to establish how to understand and interpret information and how to compile it for decision-making. The importance of sustainable development transcends even well-established mass tourism destinations engaged in intensive pilgrimages with environmentally unsound practices and a disregard for sustainable principles. The ongoing restructuring of traditional destinations introduces a more intricate landscape, where sustainability emerges as an unavoidable and integral benchmark. It is not only a critical factor for maintaining competitiveness in the tourism industry but also responds to an increasing societal demand for responsible and ethical practices. In this evolving context, the concept of sustainability is fundamental, serving as a guiding principle that destinations must embrace for both their continued success and societal responsibility. (RebolloandBaidal,2003). With this changing pace of threats and challenges, pilgrim sites have to offer next-generation pilgrimage with a more human and sustainable orientation.\u003c/p\u003e \u003cp\u003eSince time immemorial, Kashi is famous for intensive pilgrimage. This intensive pilgrimage has both the worst- and the best cases: worst because uncontrollable crowding occurs; best because there is mutuality between hosts and visitors as all are worshippers (Bleie,2003). Bleie (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) also illustrates incipient blurred boundaries between pilgrimage and tourism, recognizes the increasing diversity of both tourism and sacred journeying, identified differences and similarities between modes of travel of recreation and pilgrimage, and incorporated economic and environmental risks assessment for the destination. Pilgrimage is sheerly unmatched by other types of tourism as it mainly focuses on religious belief and faith. In the promotion of any pilgrimage site mythological occurrence and history is critical. Interconnection between tourism and pilgrimage produces positive changes and in the case of Hindu pilgrimage, this is very important to imbibe new enthusiasm without seeing the god for real (Aukland,2017). As pilgrimage sites are frequently visited by people of all ages, and income groups, travel agents or tour operators need to provide pilgrimage packages as per the specific tradition and religious beliefs. Customized pilgrim packages with all the necessary information about the destination on the travel website of a travel provider will certainly have a positive influence on the tourists and enhance the trust (Khareetal.,2020).\u003c/p\u003e \u003cp\u003eOthergroupsoftourismexpertsthinkthatthepilgrimagetraditionshouldbeconsidered from the tourism circumstances and distance between the pilgrim destination and tourist location matters.\u003c/p\u003e \u003cp\u003ePilgrims become tourist pilgrims when the destination of the pilgrimage is more distant from their home (Cohen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Recently, the idea of pilgrimage has been changing, and the concept of pilgrims and religious tourists is switching day by day. Pilgrimage does not complete with the arrival of pilgrims at the destination rather it stretches till further return home and away (B\u0026eacute;res, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA further method of approach to the study is founded upon user-generated content (UGC) that is highly utilized by tourism and hospitality services consumers both as a source of information needed for decision making as well as mean of sharing. Consumer accounts that are online are viewed as likely to have latest and credible information that is detail and purpose-oriented (GretzelandYoo,2008). Reviews shared on social media such as Trip Advisor can have profound effects on every stage of the travel decision-making process (Choe et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zeng and Gerritsen, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Such comments and reviews can greatly help service providers and destination managers to better know travel patterns, expectations, feelings, destinations, image perceptions, and satisfiers dissatisfies that can affect tourist behaviors and intentions. Most of the research on consumer feedback primarily explores the usage of social media among tourists (Gursoyet al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Users of social media not only use the content available on social media websites but also generate and provide content through posting and commenting (Choe et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As the topic of online reviews, comments, etc.\u003c/p\u003e"},{"header":"Review of literature","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePilgrimage Attractions\u003c/h2\u003e \u003cp\u003eMak Twain describes \u0026ldquo;Jagannath as kindest of Gods.\u0026rdquo; Puri, located in the eastern state of Odisha, India, is a city of great religious and cultural significance, primarily because of the Jagannath Temple. The Jagannath Temple is one of the most important pilgrimage destinations for Hindus, and it holds a special place in the hearts of devotees. The Jagannath Temple is the main attraction in Puri and is dedicated to Lord Jagannath, a form of Lord Krishna. The temple is renowned for its towering spire and unique architecture. It is an important center of worship and is one of the Char Dham pilgrimage sites for Hindus. The annual Rath Yatra or Chariot Festival is one of the most famous festivals in Puri and is celebrated with great fervor. During this festival, the idols of Lord Jagannath, his brother Balabhadra, and sister Subhadra are placed on elaborately decorated chariots and pulled through the streets by thousands of devotees. It is believed that participating in this festival or even witnessing it can grant spiritual blessings. In conclusion, Puri and the Jagannath Temple hold immense religious, cultural, and historical importance in India. Pilgrims and tourists visit Puri not only for their spiritual journey but also to experience the rich traditions and festivities associated with this sacred place.\u003c/p\u003e \u003cp\u003eLater, the place became a confluence of many world religions for centuries, with Hinduism predominating and co-existing with Jainism, Buddhism, and Islam. Kutlut\u0026uuml;rk (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) has demonstrated why and how this place is accorded a holy place while Gogate (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) explains the demolition, relocation, and reconstruction of this pilgrim center for the centuries. This great heritage is culturally associated and comparative, representing various ways by different agents of tourism promotion (Bandyopadhyay et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), deciding on public and private sector participation. Therefore, as an icon of Vishnuism in Hinduism, Puri promotes not only the destination itself but the several thousand-year-old heritage routes that attract tourists and pilgrims to relatively other lesser-known place also (Moulin and Boniface, 2010).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eUGC (User-Generated Content) and its role in the pilgrimage tourism experience\u003c/h3\u003e\n\u003cp\u003eWith the advent and increasing use of the World Wide Web, consumers\u0026rsquo; interests are anew focal point, specifically in tourism and hospitality services in which consumers or tourists rust more websites with reviews than professional guides, travel agencies, and even blogs (Akehurst,2009).\u003c/p\u003e \u003cp\u003eUser-generated content (UGC) has emerged as a critical data source for analyzing tourism mobility patterns, influencing travel decisions, and forecasting tourism demand. The integration of UGC with big data and physical footprint analytics allows for the creation of temporal effects in vacation mobility through static-network scanning and spatial interaction models at an accumulative level. The reviews and digital content provided by tourists serve as a form of digital word-of-mouth (WOM), significantly impacting trip choices (Gretzel, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This digital WOM is instrumental in shaping travel perceptions, destination selection, and tourism behaviors, offering valuable insights for both researchers and industry stakeholders. The utilization of online reviews in tourism demand forecasting has demonstrated substantial improvements in predictive accuracy. Traditional models of tourism demand forecasting are often limited by data availability and frequency. However, by employing high-frequency online review data in time-series models, tourism forecasting models achieve superior predictive performance (Hu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This advancement enhances destination management strategies by allowing real-time adjustments based on evolving traveler sentiments and behaviors.\u003c/p\u003e \u003cp\u003eDigital literacy studies further enrich the understanding of UGC's role in tourism. Research into online materials has facilitated a 'digital turn' in literacy studies, which has evolved in response to new linguistic and communicative practices. Digital literacies, as described by Lankshear and Knobel (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Coiro et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), differ from traditional literacy studies in that they emphasize the unique textual, interactive, and participatory nature of online communication (Jin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This framework provides an essential lens through which to examine the effectiveness of UGC in tourism research.\u003c/p\u003e \u003cp\u003eContemporary studies on UGC primarily explore its applications in service quality assessment, destination image and reputation management, tourist experience analysis, and behavioral trends (Lu \u0026amp; Stepchenkova, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, leveraging UGC for tourism research presents challenges. User motivations for contributing reviews are varied and often unspecified, and only a fraction of tourists actively generate content (Jiang et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Yoo \u0026amp; Gretzel, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Additionally, the credibility and reliability of user-generated content vary significantly across platforms, affecting its utility for comprehensive tourism analysis (Cox et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A deductive-inductive approach is suitable for analyzing UGC, particularly in assessing the tourism experiences of historically significant circuits, such as the Char Dham pilgrimage in India. For instance, a focus on Kashi Vishwanath Temple, identified through high volumes of negative reviews, highlights the need for precise data extraction, interpretation, and contextual analysis. However, manual transcription of such reviews is time-intensive and costly, necessitating automated web harvesting techniques. While automation streamlines data collection, it remains a controversial approach due to ethical and methodological concerns (Jennings \u0026amp; Yates, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Vanweland \u0026amp; Royakkers, 2004; Batabyal et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Johnson et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) emphasize that analyzing UGC requires either extensive manual efforts or automated extraction, each with its respective limitations.\u003c/p\u003e \u003cp\u003eFurther research by Han et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) highlights the potential of web-based UGC samples in constructing hypothetical models that explain direct and indirect effects of tourism-related issues. By leveraging user-generated knowledge, researchers can enhance predictive capabilities and develop targeted interventions to improve tourism experiences. As digital platforms continue to shape consumer behaviors, the strategic utilization of UGC remains pivotal in advancing tourism research, policy-making, and destination management.\u003c/p\u003e \u003cp\u003eIn beyond couple of years, numerous stages for online surveys in the travel industry area, like Trip Advisor, Desolate Planet, and Google Guides, have become more common in examination and work, prompting the multiplication of concentrates on web-based audits, and featuring the utilization of new scientific advances.\u003c/p\u003e\n\u003ch3\u003eComponents of pilgrimage destination experience of tourists\u003c/h3\u003e\n\u003cp\u003eAccording to Cooper et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), a tourist destination comprises four fundamental components: attractions, accessibility, amenities, and ancillary services. These elements serve as the cornerstone of tourism development, ensuring a comprehensive and fulfilling experience for travelers. Expanding on this framework, Jauhari (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), Gamboa (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Skinner and Soomers (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) emphasize additional dimensions of tourism services and development, such as the integration of internet facilities, self-check-in kiosks, and immersive light and sound experiences. Furthermore, they highlight the significant impact of niche tourism on cultural heritage, stakeholders, and community participation, all of which contribute to an enriched cultural, transformational, and spiritual visitor experience.\u003c/p\u003e \u003cp\u003ePilgrimage tourism, in particular, necessitates proficient management due to the vast number of tourists motivated by religious beliefs (Kreiner, 2018). Effective pilgrimage tourism management ensures a secure and comfortable experience by providing essential services, including food, accommodation, and infrastructural support. Additionally, proper management mitigates the adverse effects of mass tourism on sacred sites, as excessive tourism can lead to environmental and cultural degradation (Prihantoro et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Given that pilgrimage destinations often hold immense heritage value (Giovine \u0026amp; Fuentes, 2016), their preservation is critical in fostering national and shared cultural identities. Consequently, service quality assessment emerges as a vital tool for evaluating consumer experience and satisfaction, often employing multidimensional methodologies (Pakurar et al., 2019).\u003c/p\u003e \u003cp\u003eAuthenticity is a crucial aspect of grand festivals and pilgrimage tourism, significantly shaping tourists' emotional experiences and engagement (Lee et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, 2021). Authentic experiences contribute to perceived benefits and influence active participation in tourism development. Several models have been proposed for assessing service quality within the tourism sector. Gronroos (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1982\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) introduced a service quality model that differentiates between technical and functional quality. However, Rust and Oliver (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) expanded this model by incorporating the service environment as a third dimension. Despite their conceptual significance, these models have not undergone extensive empirical testing, and support in the literature remains limited. While some service quality frameworks demonstrate strong validity in specific service industries, they often lack broad applicability and generalization (Oh \u0026amp; Kim, 2017). To address these limitations, Ramya and Kowsalya (2019) developed and empirically tested a multidimensional model of M-S-QUAL for mobile service quality. Their study, involving 578 Internet respondents, assessed service quality through validity, reliability, exploratory factor analysis, and confirmatory factor analysis, thereby contributing valuable insights for future research. Industry-specific service quality measurement models have also emerged in various sectors, such as mobile healthcare (Ghotbabadi et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and low-cost airlines (Barnes, 2017). More recently, Batabyal et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) introduced the concept of temple service quality (TSQ) measurement, underscoring the need for sector-specific service quality assessment within religious tourism.\u003c/p\u003e \u003cp\u003eIn the digital era, pilgrims increasingly rely on online platforms to share experiences and consult reviews before planning their journeys. Online Travel Agencies (OTAs) such as TripAdvisor provide a repository of user-generated content that influences pilgrimage planning. The analysis of TripAdvisor reviews reveals a shift in tourists\u0026rsquo; perspectives, transitioning from a 'dark tourist gaze' to an 'environmental gaze' and a 'cultural gaze'\u0026mdash;a phenomenon shaped by strategic governmental interventions aimed at post-war reconciliation (Park et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Samarathunga et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Again, Husemann and Eckhardt (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) observed that many pilgrims engage in online forums to seek advice on preparations, attire, and other logistical concerns. Cugini (2021) further asserts that modern tourists, akin to pilgrims, seek spiritual enrichment when visiting sacred sites. While spiritual motivation is not a prerequisite for spiritual experience, the ambiance of the destination, interactions with local communities, and site-specific activities significantly influence the depth of spiritual engagement. As pilgrimage tourism continues to evolve, future research should explore innovative service quality models that encompass both traditional and modern dimensions of pilgrimage experiences, ensuring sustainable development and enriched visitor satisfaction.\u003c/p\u003e\n\u003ch3\u003eObjectives and Research Question:\u003c/h3\u003e\n\u003cp\u003eChar Dham or four holy temples of the lord \u003cem\u003eVishnu\u003c/em\u003e represents one of the oldest extant pilgrim circuits and part of the great religious heritage in South Asia. For compelling and quality experiences the opinions of tourists are often analyzed and interpreted for enhancing the administrative and managerial quality of services. Temple administrative equality has a positive relationship with tourist satisfaction that influences future behavior intentions (Canny, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). From the field visits and direct and indirect observations, it is found that different service failures are very common and the quality of temple administrative services is to be improved in most of the temples. Following is Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showing the review performance for all the holy temples representing mythological and religious Char Dham of the god Vishnu respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRanking of Responses Retrieved from the Trip Advisor from September, 2016 to May, 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChar Dham\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResponses for 'excellent'\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRank (% of Total Responses)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResponses for 'Terrible'\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRank (% of Total Responses)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBadri Nath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDwarka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJagannath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRameswaram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSource: Trip Advisor Reviews, September2016 to July 2022\u003c/p\u003e \u003cp\u003eJagannath temple is found to have been lacking most whereas Badrinath is the best performing one among all four abodes of the god Vishnu in India. Now, the question is \u0026ldquo;do these maximum negative reviews exhibit a true picture of this destination?\u0026rdquo; This study further investigates the reviews and user-generated contents (UGC) and proposes a hypothetical model of temple administrative quality (TAQ) for future sustainable pilgrimage in this circuit incorporating three other major pilgrim centers in the sub-continent. Therefore, the research question in the study is whether temple administrative qualities are responsible for future pilgrimages (Ghimireetal.,2022) in Jagannath temple and similar other temples in the circuit or a pre-occupied spiritual belief and faith have a significant contribution, often exhibited the compromising attitude and minimizing negative perceptions.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eResearch site\u003c/h2\u003e\n \u003cp\u003eThe study explores the online reviews posted by the tourist decadal time frame from September 2011 to July 2021 who visited the Jagannath temple, Puri. A total of 2848 reviews are found over this specified period and 157 \u0026lsquo;poor and terrible\u0026rsquo; reviews are finally chosen. Jagannath temple is chosen as a research site because it is one of the epicenters of Hinduism and associated mythology. However, at present, government authorities, temple or shrine trusts etc. have identified certain common areas of management and operation. Following are the areas of services retrieved from the official/ related temple or shrine websites in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Accommodation facility; Pony services; Heli services; Bus services; Registered Tour Operators\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eResearch Design\u003c/h3\u003e\n\u003cp\u003eParasuraman et al. (\u003cspan class=\"CitationRef\"\u003e1985\u003c/span\u003e), gave a more detailed model of service quality assessment, which has the maximum number of dimensions, namely 10 dimensions, including Tangibles, Reliability, Responsiveness, Understanding the customers, Access, Communication, Credibility, Security, Competence, and Courtesy. This huge model was later advanced into the commonly known SERVQUAL, by Parasuraman et al. (\u003cspan class=\"CitationRef\"\u003e1988\u003c/span\u003e), which merged the dimensions on a five-dimensional basis, that is, Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The SERVQUAL scale has now come to be accepted widely across the world by academics, researchers, and practitioners by virtue of its applications in diverse fields and countries (Butt and Run, \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Farooq et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lee-Ross, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). Good practical implications recognize SERVQUAL itself as a service quality measurement scale able to measure customer perception about that quality service (Parasuraman et al., \u003cspan class=\"CitationRef\"\u003e1994\u003c/span\u003e). The present study extends the SERVQUAL model (Parasuraman et al., \u003cspan class=\"CitationRef\"\u003e1985\u003c/span\u003e) and essentially addresses the introduction of Temple Administrative Qualities (TAQ) for intensive pilgrim sites of the Asian subcontinent.\u003c/p\u003e\n\u003cp\u003eThe ratings of online reviews play a major role in customer patronage, whereas official ratings are going down. Current-day customers are increasingly becoming aware of the ratings posted by other online customers through sites Trip Advisor, Google Reviews, and Yelp.\u003c/p\u003e\n\u003cp\u003eThe slightest changes in the online review ratings are being worked upon by business houses, for any change in rating, however small, could affect the business (Nalley et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ghimire et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Review platforms need to develop new review/framing processes that, in conjunction with emotional sentiments, can better distinguish between helpful and unhelpful reviews with marketers encouraging that readers of the review share this kind of review with others (Huang et al.,2020). In the travel and tourism sector, several online review portals, such as Trip Advisor, Lonely Planet, and Google Maps, have lived on in actual practice and research into the past few years (Sun et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Though, each of the platforms has its features, yet the philosophy of the review platforms is starkly similar: these enable users to submit reviews while letting users score their experiences on a scale (Taecharungroj and Mathayomchan, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Orea-Giner\u0026apos;s team in 2022 employed text mining in its study to examine the emotions and sentiments of customers regarding the implementation of robots in hotels, drawing from the ratings that they gave in reviews on Trip Advisor. The Trip Advisor platform is the biggest place to assist traveling, where more than a billion reviews and feedback from 8 million businessmen and tourists go into assisting someone in making a decision to visit a particular city place or destination. Trip Advisor became a prominent review platform in the tourism sector for both tourists and researchers alike (Taecharungroj and Mathayomchan, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, Trip Advisor was selected as a case for the study in the present work.\u003c/p\u003e\n\u003cp\u003eThe main purpose of this study is to investigate whether temple service qualities are responsible for future pilgrimages in Puri Jagannath and similar other temples in the circuit or whether a pre-occupied spiritual belief and faith have a significant contribution, often exhibiting a compromising attitude and minimizing negative perceptions using the UGC and to offer insight for understanding the factors that can affect the pilgrimage tourist\u0026rsquo;s evaluation of travel experience in a site. To achieve this goal, the review comments posted to the largest social media platform i.e., the trip pilgrimage or religious experience for determining the dimensions of attractions and services advisor (O\u0026rsquo;Connor, \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e), have been analyzed within the scope of similar websites as their UGC source (Bamberger and Phillips, \u003cspan class=\"CitationRef\"\u003e1991\u003c/span\u003e). This study adopted a mixed approach since this approach is one of the correct methods for understanding (Taecharungroj and Mathayomchan,2019). A significant number of studies used customer review from Trip Advisor and other individual feelings and ideas (Creswell et al., 2003) keeping in view the positive and negative emotions (Huangetal.,2020; RenandHong,2019; Orea-Gineretal., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eData Collection and Analysis:\u003c/h3\u003e\n\u003cp\u003eAbowitz and Toole (\u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e) pointed out that there is no single way of collecting data since all methods have strengths and weaknesses and therefore recommended a mixed-methods approach in terms of feedback, reliability, and causal inference. The critical feedback regarding interpretations of the researcher and suggested offers of their reflections enhances the quality and trustworthiness of an analysis and justifies the model as an empowerment position endorsing participants as co-owners of the results (Fassinger and Morrow. 2013).\u003c/p\u003e\n\u003cp\u003eKhareetal. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) investigated the competitive advantage of websites over apps particularly in branding and CRM opportunities and identified network benefits, interactivity, and pilgrimage package information to be influential factors triggering trust and customer reviews in keeping relationships with the website. Laer and Izberk-Bilgin (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) emphasize the rambunctious characteristics of online reviews of tourists in pilgrimage sites on TripAdvisor and how tourists articulate the spiritual and material dimensions of pilgrimage experiences. They looked at how pilgrims integrate analytical discursive features into expressing the material side of their consumption experience while review ratings are seen to only deliberate the spiritual side of their consumption engagement. All the temple service qualities are thus postulated as reasonably good and positively recognized by the majority of the pilgrims.\u003c/p\u003e\n\u003cp\u003eHowever, there is a growing marketisation of spirituality (McAlexander et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) and even spiritual experiences are considered \u0026apos;rateable\u0026apos; and \u0026apos;reviewable\u0026apos; online today (Laer and Izberk-Bilgin, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Pilgrimage for spiritual enlightenment has been shown to be a remarkable consumption experience (Husemann et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). On the other hand, Santana et al. (2019) adopted an interpretive approach while making use of the multi-sited ethnographic methodologies of \u0026quot;following the thing\u0026quot; and \u0026quot;following the people,\u0026quot; tracing the pathways of tourists and objects during a pilgrimage with implications for the understanding of the past as it utilizes the spiritual and liquid/solid engagement to sacred objects.\u003c/p\u003e\n\u003cp\u003eIt has also been maintained that India continues to be an ethnically diverse nation where Hinduism precedes and dominates all other religions/ethnicities (Bandyopadhyay et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e) with an overall pluralistic and secular religious disposition since its very independence.\u003c/p\u003e\n\u003cp\u003eData analysis in the study considers a decadal time frame from September 2011 to July2021 and is subject to the availability of tourists\u0026rsquo; reviews on Trip Advisor. A total of 1670reviews are found over this specified time period and 1379 are finally chosen. From these total usable reviews, 129 pilgrims mention their occasional visit whereas 1250 reviews were non-occasional. The average of the coefficient of variations of the temple administrative qualities (TAQ) for tourists or pilgrims visiting usually during the non-occasions is 35.2976, compare to the occasional movement with 30.26704 respectively, indicating more consistency in opinion. On the other hand, the average coefficient of variations of the temple administrative qualities (TEMP SERVQUAL) for the 984 Hindu tourists was 41.7, whereas the same was 38.4 for the non-Hindu visitors indicating more consistency in their opinion.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eTourist distribution\u003c/h2\u003e\n \u003cp\u003eFrom Tables \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eand 4, it can be depicted that most of the reviews about Puri Jagannath temple on TripAdvisor were from countries like the UK, South Africa, the USA, Australia, and Bangladesh. Whereas, few reviews were from other countries like Germany, Nepal, France, and the rest of the world. Researchers also collected reviews of national tourists visiting the Puri Jagannath temple. Their views were from Maharashtra, Delhi, Uttar Pradesh, Karnataka, Tamil Nadu, West Bengal, Telangana, Gujarat, Panjab, Madhya Pradesh, Bihar, etc. A total of 1379 relevant reviews were used in the current study of which 984 reviews were of Hindus and 395 reviews were from non-Hindus respectively.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eForeign tourist distribution\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCountry\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePercentage\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnited States of America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnited Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAustralia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSri Lanka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNepal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermany\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRest of the world\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cp\u003eAll the usable reviews are carefully studied for conceptualizing the negative and positive aspects of services and relevant points are taken into note, viz. understanding the sources of bias, judgement calls, subjectivity, and inductive approach for developing theory (Guzzoetal.,1987). Considering the technical and conceptual limitations, such as biasness, communication barriers, related accuracy, web harvesting, etc. reviews have been studied by the experts only.\u003c/p\u003e\n \u003cp\u003eThis study\u0026rsquo;s scale reliability coefficient is found 0.7894 for all the usable reviews. Reviews of the residents, hotels or other facilities and religious descriptions have been excluded from this study. Reviews have been tabulated with four fundamental options in the confusion matrix viz. True Negative (TP), False Positive (FP), True Positive (TN), and False Negative (FN) respectively. In this study, True Negative (TN) and False Positive (FP)are two confusions in the matrix.\u003c/p\u003e\n \u003cp\u003eTrue negative (TN)implies tourists are positive, patient, and graceful about destination service qualities though it is not. False positive (FP), on the other hand, is when tourists are negative and informed about perpetual chaos and conflict but gains a positive experience with all services.\u003c/p\u003e\n \u003cp\u003eThe number of service quality issues in this study is dependent on actual temple visits and study of respective websites of all major temples and shrines already focusing on relevant points of service delivery, convenient customer access and service failure respectively (as referred to Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eMany studies scrutinized the impacts of service quality (SQ) on customer satisfaction (CS), attitudinal loyalty (AL), and purchase intention (PI) although SQ may also have an impact on other important variables such as word of mouth, trust, price premium, market share, and profits (Carrillat et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zeithaml, \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e). This study is in line with the extension of such trends and practices along with the studies for mobile healthcare, hairdresser, etc. (Pollack, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Akter et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e) with varying service recognition and failure.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003cp\u003eBased on services and activities offered by most of the Indian temples (as referred to in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), cleanliness, beggars and trespassers handling, security/documentation, services by priests\u0026rsquo; shopkeepers\u0026rsquo; human discrimination, temple hospitality, activities crowd handling, local transportation and street animals handling are the classifiers comprising of temple service quality (TSQ). As stated in Fig. 2, all usable 1379 reviews are read and marked 1, 2, 3, and 4 respectively for true-negative (TN), false-positive (FP), true-positive (TP), and false-negative (FN) cases comprising an imbalanced dataset. To mitigate or stop such tyranny imbalance, the degree of class imbalance and the complication of the concept have been taken care of to check bias in policy decisions (Kulkarnietal., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe user generated content (UGC) based service quality models are not new. Han et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) shows how to appeal tourists\u0026rsquo; intrinsic interest via media channels making their choice, style, and delivery of certain messages a key issue for tourism marketers and management. They explained how the social media turned into an important and acknowledged channel for tourism information, with user-generated content (UGC) being more trusted than official channels, yet there is hardly any knowledge about its potential role.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cp\u003eThere are several other factors in each classifier mentioned in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The confusion matrix is composed of nine classifiers and each one has several interrelated points contributing to overall temple services.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of confusion matrix towards temple administrative quality (TAQ) model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMeasures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCleanliness\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBeggars \u0026amp; Trespassers Handling\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSecurity Documentation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eServices by Priests \u0026amp; Shopkeepers\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHuman Discrimination\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTemple Hospitality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eActivities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrowd Handling\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocal Transport\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStreet Animal Handling\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5455\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2830\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrecision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative Predictive Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse Positive Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse Discovery Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3878\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse Negative Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4545\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFI Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5769\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMatt Hews Correlation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.1812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.0799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.5957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.4751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.1641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHere, the confusion matrix with the above nine classifiers raises a confusion from true negative (TN)to false positive (FP). Basically, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e discloses four important measures, viz. sensitivity, specificity, F1 score and Mathew\u0026rsquo;s correlation coefficient respectively.\u003c/p\u003e\n\u003cp\u003eThis model is a pioneer to ascertain a TAQ model through user-generated contents (UGC) for sustainable pilgrimage and its practices in 4 Hindu pilgrim centers belonging to the several thousand years old mythologies of the sacred radiant of pillars in Indian Subcontinent. Indian sub-continent-specific Hindu temple site-oriented TAQ model is the first of its kindexploringmanyconvenientpilgrims\u0026rsquo;accessandpointofsalesforactual(ritualistic/general) service delivery. This model reorients a new service blueprint for ritualistic and non- ritualistic or general service delivery in any Hindu pilgrim site in the Indian Sub-continent. Towards the fitness of the TAQ model, all the technical and conceptual issues were found important and F1 scores were found highly acceptable. Though the model was technically accepted, yet the assertion of exploring and improving service quality was rejected and rather exhibited a scope for the materiality-spirituality continuum for future research.\u003c/p\u003e\n\u003cp\u003eFor the cleanliness, the value of the sensitivity is point 0.97 and values of respective other classifiers are more than 0.9, except activities. Sensitivity of the pilgrims are found very high and they are satisfied with cleanliness, beggars and trespassers handling, security/documentation, services by priests\u0026rsquo; shopkeepers\u0026rsquo; human discrimination, temple hospitality, activities crowd handling, local transportation, and street animals handling. Only there is a certain problem in the activities as pilgrims are unable to take important decision which of the activities to opt. From the specificity, most of the values of respective classifiers are more than 0.80, i.e., whatever observations are coming from literature review are specific. From the precision, it is also found that the confidence level of the pilgrims is very high, i.e., they are more confident while writing an opinion on TripAdvisor. F1 score (i.e., the geometric mean of precision and sensitivity) is also very high and close to 1. Therefore, a robust relationship exists between the inter-class and inter-class groups.\u003c/p\u003e"},{"header":"Conclusion and Implications","content":"\u003cp\u003eThe aim of this paper was to explore if maximum negative reviews exhibit a true picture of Puri Jagannath temple and whether temple service qualities are responsible for future pilgrimages in Puri Jagannath and similar other temples in the circuit or a pre-occupied spiritual belief and faith have a significant contribution, often exhibit compromising attitude, and minimize negative perceptions. This study adopted a mix approach. Based on the total reviews received from the tripadvisors.com, the reviews and user generated contents (UGC) are investigated through an extension of SERVQUAL model (Parasuramanetal.,1985), known as Temple administrative qualities (TAQ) for intensive pilgrim sites of the Asian Subcontinent.\u003c/p\u003e\u003cp\u003eTowards the fitness of the temple administrative quality (TAQ) model, all the technical and conceptual issues are important. The accuracy, sensitivity, precision, and F1 scores are highly acceptable in the study. Though the model is technically accepted, yet the assertion of exploring and improving service quality is rejected and exhibits a scope for materiality-spirituality continuum with appropriate point of balance. Therefore, an immense possibility of promoting Puri, Jagannath as an epicenter for alternative creative tourism destination for spiritual learning is emerging for various interest groups locally and globally.\u003c/p\u003e\u003cp\u003eInstead of offering more temple facilities and services, future pilgrimage tourism planning may be oriented to a sheer difference between domestic and international tourists, pilgrims and accompanied tourists, spiritual and cultural tourists, etc. The spiritual belief and faith supersede commonly visible service failures and exhibit a compromising attitude of the pilgrims and accompanied tourists as indicated in previous studies (Medhekar and Haque, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Yanata, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e, Ray et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). Future pilgrimage is considered as a healing process from a past occurrence or pain in which the pilgrims can communicate to the gods in a temple, church, or mosque that has a significant effect on their life (Warfieldetal.,2014).\u003c/p\u003e\u003ch2\u003eLimitations and Future Research:\u003c/h2\u003e\u003cp\u003eThough this study has conducted a complete enumeration, it is confined to the reviews and contents of the TripAdvisor’s only and exhibits a future scope for comparability in model fitting (Richards, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). This study does not differentiate the perceptions and attitudes of domestic pilgrims from their foreign counterparts. Based on reviews and user-generated content, specifically for foreign tourists, maybe with other portals of OTAs (Online Travel Agents), research can be conducted for destination image and identity in the future. Furthermore, this is only an indication of much more research along different pilgrim.\u003c/p\u003e\u003cp\u003eCircuits in India that possess the same mythological and religious values, e.g., 51 Shakti-Peeths, 8 Vinayak temples, etc. It also finds out new scope for comparing many reviews already available on the websites of OTAs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eOur original research manuscript entitled \u0026ldquo;Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor\u0026rdquo; for consideration for publication in SN Business \u0026amp; Economics.This study proposes and empirically evaluates the Temple Administrative Quality (TAQ) Model within the context of the Char Dham pilgrimage circuit, a globally significant religious tourism destination in the Indian subcontinent. Drawing on User-Generated Content (UGC) extracted from TripAdvisor reviews, the research offers a data-driven assessment of pilgrims\u0026rsquo; and visitors\u0026rsquo; perceptions of temple administration, service efficiency, infrastructure management, crowd control, and experiential quality.The novelty of the study lies in its integration of digital tourism analytics with religious and spiritual destination management, an area that remains underexplored in business and economics literature. By applying qualitative and quantitative UGC analysis, the paper contributes to emerging discussions on service quality measurement, public administration effectiveness, destination governance, and sustainable religious tourism management. The findings offer practical insights for policymakers, temple management authorities, and tourism administrators seeking to enhance service delivery and visitor satisfaction in high-density pilgrimage destinations.This manuscript is original, has not been published previously, and is not under consideration for publication elsewhere. All authors have approved the manuscript and agree with its submission to SN Business \u0026amp; Economics. Ethical standards have been duly observed, and no conflict of interest exists.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbowitz, D. A., \u0026amp; Toole, T. M. (2010). Mixed method research: Fundamental issues of design, validity and reliability in construction research. \u003cem\u003eJournal of Construction Engineering and Management, 136\u003c/em\u003e(1), 1\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eAkehurst, G. (2009). User-generated content: The use of blogs for tourism organizations and tourism consumers. \u003cem\u003eService Business, 3\u003c/em\u003e, 51\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eAkter, S., D\u0026rsquo;Ambra, J., \u0026amp; Ray, P. (2010). Service quality of mHealth platforms: Development and validation of a hierarchical model using PLS. \u003cem\u003eElectronic Markets, 20\u003c/em\u003e(3), 209\u0026ndash;227. https://doi.org/10.1007/s12525-010-0043-x\u003c/li\u003e\n\u003cli\u003eAnthony, G. D. (2019). If you are not Indian, don\u0026rsquo;t even think about Kasi Viswanath. It does not matter\u0026hellip; Om Namah Shivaya! [Comment on the review \u0026ldquo;TripAdvisor\u0026rdquo;]. \u003cem\u003eTripAdvisor\u003c/em\u003e. Retrieved from https://www.tripadvisor.in/Attraction_Review-g297685-d320084-Reviews\u003c/li\u003e\n\u003cli\u003eAshworth, G. (1994). From history to heritage - from heritage to identity: In search of concepts and models. In G. J. 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A review. \u003cem\u003eTourism Management Perspectives, 10\u003c/em\u003e, 27\u0026ndash;36. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Trip Advisor, Temple Service Quality, User Generated Content, Pilgrimage","lastPublishedDoi":"10.21203/rs.3.rs-8617507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8617507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Char Dham, the four sacred abodes of Lord Vishnu, hold profound religious and mythological significance, attracting millions of Hindu pilgrims across the Indian subcontinent. Despite its spiritual prominence, the Jagannath Temple in Puri has recorded a substantial number of negative visitor reviews from September 2016 to May 2022. This study aims to analyze and interpret the critical feedback from TripAdvisor, focusing exclusively on poor and terrible ratings to identify service gaps and enhance the quality of pilgrimage experiences. Out of 2,842 available reviews, only the most negative ones were considered to develop a Temple Administrative Quality (TAQ) model based on user-generated content (UGC). The model, designed for all four Char Dham sites, places special emphasis on Jagannath Temple, which reported the highest number of negative reviews over the past decade. The study integrates extensive literature reviews, official temple website analyses, and TripAdvisor UGC to construct the TAQ model. Its accuracy, precision, and sensitivity were tested using a confusion matrix. Findings underscore the need for differentiated pilgrimage tourism planning, recognizing distinctions among domestic and international tourists, pilgrims and leisure travelers, and spiritual versus cultural visitors. Notably, spiritual devotion often outweighs service shortcomings, fostering a tolerant attitude among pilgrims.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eJEL Classification: \u003c/em\u003eL83, M10, L15\u003c/p\u003e","manuscriptTitle":"Evaluating the Temple Administrative Quality (TAQ) Model for Char Dham in the Indian Subcontinent: A User-Generated Content (UGC) Analysis from TripAdvisor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-09 15:52:21","doi":"10.21203/rs.3.rs-8617507/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b05e0417-d46a-4a50-880d-80b3724768b8","owner":[],"postedDate":"March 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T11:11:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-09 15:52:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8617507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8617507","identity":"rs-8617507","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}