Investigating the Tourism Development Strategy 4.0: An Integration of Data Mining and Digital Technology

2.1 Tourism 4.0

Tourism 4.0 integrates all stakeholders, from local communities, tourists, tourism service providers, and the government [36]. Tourism 4.0 represents a new phase of tourism development following E-tourism and M-tourism, also known as Smart Tourism [37, 38]. As a relatively new concept, the implementation of Tourism 4.0 varies across countries. However, in general, Tourism 4.0 can be defined as adapting the tourism sector to the principles of Industry 4.0 to create a smarter system (smart tourism), providing convenience, and enhancing the tourist experience (see Figure 1) [37, 39, 40].

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Figure 1. Concept of Tourism 4.0 [36]

2.2 Inclusive green economy in the tourism sector

The concept of an inclusive green economy plays a crucial role in encouraging innovation, particularly in renewable energy and sustainable technologies, thereby balancing economic development and environmental sustainability [9, 41]. This approach helps preserve natural ecosystems and provides economic benefits to local communities [34, 42]. An inclusive green economy in Indonesia is implemented to support environmental sustainability and encourage sustainable tourism practices [43].

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Figure 2. Inclusive green economy scheme [44]

This approach is crucial, especially in regional tourism destinations consumption, because it can involve local communities and promote environmentally friendly activities, enabling equitable, simultaneous economic and social benefits. An inclusive green economy is also seen as capable of addressing systemic issues within the economic system, thereby simultaneously achieving sustainable development goals in social, economic, and environmental spheres. Figure 2 presents the strategy for realizing an Inclusive Green Economy, encompassing three principal dimensions. First, the economic aspect encompasses efficient resource allocation, job creation and maintenance, stimulating innovation and the adoption of green technologies that benefit vulnerable groups, and diversification to strengthen local and national economic resilience.

Second, the social aspect encompasses improving health and well-being, maintaining justice, and building social capital to enhance community resilience. Third, the environmental aspect emphasizes optimizing productivity and natural resource utilization, reducing pollution and disaster risk, and investing in conservation and ecosystem restoration to ensure sustainability. Inclusiveness in this economy refers to increasing per capita income by providing equal access to the benefits of economic growth for all levels of society.

While previous literature has extensively explored Smart Tourism and Tourism 4.0 primarily as mechanisms for enhancing visitor experiences and optimizing destination operations [12-14, 37-40], most studies approach digital transformation from an isolated technological perspective. Furthermore, although the importance of sustainable development and the Inclusive Green Economy is well recognized for balancing economic growth with environmental sustainability and community empowerment [9, 32-34, 41-44], a significant gap persists in current research. Few past studies have developed a comprehensive matrix that explicitly bridges Tourism 4.0 digital interventions with the specific tri-dimensional pillars of an Inclusive Green Economy: economic, social, and environmental. This study addresses this gap by presenting a novel framework that directly maps tailored digital strategies, such as AR and digital tour packages, to these three core sustainability dimensions [45-49].

4.1 Respondent characteristics

The results of this study indicate that the number of tourists by gender is 43 men and 57 women. Respondents’ tourism expenditure is illustrated in Figure 3.

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Figure 3. Tourist data based on travel expenditure (monthly)

Figure 3 shows that tourists have a special travel budget, spending less than IDR 500,000 per month. There are 47 respondents, followed by those with an income of IDR 500,000 - IDR 1,000,000 (30) and those with an income of IDR 1,000,000 - IDR 2,000,000 (8). In comparison, as many as 15 respondents who travel have monthly expenses exceeding IDR 2,000,000. This data shows that the average respondent does not prepare a large budget and prioritize travel needs.

4.2 Accessibility

Accessibility is an important component of the tourism experience because it influences travel convenience, visitor satisfaction, and destination attractiveness. The distribution of respondents' perceptions is presented in Table 1.

Table 1. Road conditions and accessibility

Table 1 presents respondents' perceptions of road conditions and accessibility to the tourist destination. The findings indicate that most respondents evaluated the accessibility positively. Specifically, 42 respondents (42%) rated the road conditions and accessibility as good, while 41 respondents (41%) considered them fairly good. In addition, 14 respondents (14%) perceived the accessibility as very good. Collectively, these three categories account for 97% of all responses, demonstrating that most visitors experienced generally satisfactory access to the tourist destination. Only 3 respondents (3%) rated the road conditions and accessibility as poor, indicating that accessibility issues affected a relatively small proportion of visitors.

The distance between the main road and the tourist destination is an important factor in accessibility, as it affects visitors' travel convenience and overall experience. Table 2 presents respondents' perceptions of the distance from the main road to the tourist destination.

Table 2. Distance from the main road to the tourist destination

Table 2 shows that 56 (56%) respondents perceived the tourist destination as far from the main road. Meanwhile, 33 respondents (33%) considered the distance to be near, while 12 respondents (12%) considered it very far. These results suggest that many visitors need to travel a considerable distance beyond the main road before reaching their destination. The relatively high proportion of respondents reporting that the destination is far or very far indicates that distance remains a potential challenge for tourists. Longer travel distances may increase transportation costs, travel time, and visitor fatigue, particularly for tourists who rely on public transportation or travel with families and elderly companions.

4.3 Amenities

The availability of amenities is a key factor influencing tourists' overall satisfaction and destination competitiveness. Among these amenities, the prices of food, beverages, souvenirs, and other tourism-related goods and services play an important role in shaping visitors' perceptions of value. Table 3 presents respondents' perceptions of prices at the tourist destination.

Table 3. Prices of goods and services at the tourist destination

Table 3 shows that most respondents (70%) perceived the prices of goods and services at the tourist destination as expensive. In contrast, 23 respondents (23%) considered the prices affordable, while only 2 respondents (2%) rated them as very expensive. Additionally, only 1 respondent (1%) perceived the prices as very affordable, whereas 4 respondents (4%) indicated that they did not know, possibly because they did not purchase any products or services during their visit. The dominance of responses indicating that prices are high suggests that the cost of tourism-related products and services may be a concern for many visitors. Higher prices can reduce tourists' purchasing intentions, shorten their stay, and negatively affect overall satisfaction, particularly among domestic tourists and budget-conscious travelers.

Cleanliness and maintenance are essential components of tourism amenities because they directly influence visitor comfort, satisfaction, and the overall image of a destination. Well-maintained tourist attractions contribute to a positive visitor experience and encourage repeat visits. Table 4 presents respondents' perceptions of the cleanliness and maintenance of the tourist destination.

Table 4. Cleanliness and maintenance

Table 4 displays that respondents generally evaluated the cleanliness and maintenance of the tourist destination positively. Nearly half of the respondents, 47 or (47%), rated cleanliness and maintenance as good, while 40 respondents (40%) rated them as fairly good. Furthermore, 12 respondents (12%) perceived the conditions as very good. Collectively, these responses account for 99% of all respondents, indicating a high level of satisfaction with the destination's cleanliness and maintenance. Only 1 respondent (1%) rated cleanliness and maintenance as poor, suggesting minimal dissatisfaction with environmental conditions. Although this proportion is very small, it highlights the importance of continuous maintenance and environmental management to ensure consistently high service standards.

4.4 Facilities

Facilities are a fundamental component of tourism development because they support visitors' comfort, convenience, and overall travel experience. The availability of adequate facilities, such as rest areas, parking spaces, public toilets, places of worship, information centers, and food outlets, can significantly influence tourist satisfaction and destination competitiveness. Table 5 presents respondents' perceptions of the adequacy of facilities at the tourist destination.

Table 5. Perceived adequacy of facilities

Table 5 shows that most respondents viewed the available facilities positively. A total of 77 respondents (77%) stated that the facilities were adequate, while 6 respondents (6%) considered them very adequate. Together, these responses account for 83% of all respondents, suggesting that the existing facilities generally meet visitors' expectations and support their tourism activities. In contrast, 17 respondents (17%) perceived the facilities as inadequate, indicating that a notable proportion of visitors still experienced deficiencies during their visit. These concerns may relate to the availability, condition, accessibility, or capacity of tourism facilities, particularly during peak visitor periods.

Service quality is an important aspect of tourism management because it influences visitor satisfaction, destination image, and tourists' intentions to revisit and recommend a destination. Effective management services include responsive staff, efficient administration, visitor assistance, and the overall organization of tourism activities. Table 6 presents respondents' perceptions of the quality of management services at the tourist destination.

Table 6. Perceived quality of management services

Table 6 shows that respondents generally evaluated the management services positively. Most respondents (58%) rated service quality as good, while 33 respondents (33%) rated it as fairly good. In addition, 7 respondents (7%) perceived the services as very good. Together, these responses represent 98% of all respondents, indicating a high level of satisfaction with the management of the tourist destination. Only 2 respondents (2%) rated the management services as poor, suggesting that negative experiences with service delivery were relatively uncommon. Nevertheless, these responses indicate that opportunities remain for improving consistency in service quality and visitor engagement.

4.5 Digital technology

Digital technology has become an integral component of the tourism industry, supporting information access, travel planning, destination promotion, online reservations, navigation, and communication. The growing adoption of digital platforms has transformed the way tourists search for information and experience destinations. Table 7 presents respondents' perceptions of the importance of digital technology in tourism.

Table 7. Importance of digital technology in tourism

Table 7 shows that all respondents recognized the importance of digital technology in tourism. A total of 53 respondents (53%) considered digital technology important, while the remaining 47 respondents (47%) perceived it as very important. Notably, no respondents indicated that digital technology was unimportant, reflecting a unanimous acknowledgment of its significant role in contemporary tourism activities.

4.6 Data mining with the K-means clustering method

Data mining analysis aims to identify potential tourist attractions in regional destinations, enabling stakeholders to develop effective strategies. This mapping helps increase the efficiency of marketing strategies, making them more targeted and enabling tourist destinations to utilize their various resources more effectively [58, 59]. Although the survey utilized ordinal response categories, these variables were transformed into 1-to-5 numerical scales and treated as interval data. This transformation, standard in social science research, allows for the calculation of cluster centroids and the application of Euclidean Distance as the similarity measure.

The clustering analysis was conducted using the K-Means algorithm in RStudio to identify groups of respondents with similar perceptions regarding tourism destination development. The optimal number of clusters was determined using the Silhouette Method. As shown in Figure 4, the highest average silhouette width was obtained at k = 3, indicating that three clusters provided the most appropriate grouping structure for the dataset.

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Figure 4. Determination of the optimal number of clusters using the silhouette method

Table 8. Measurement and coding scheme used in data mining and clustering analysis

On the basis of the silhouette analysis, the optimal number of clusters was determined to be three (k = 3). The clustering analysis was conducted using responses from 100 tourists collected across ten tourism destinations. Although individual tourists served as the primary unit of analysis, their collective responses were aggregated to evaluate and formulate development strategies for destination-level infrastructure and digital technologies. The variable used in the clustering analysis was transformed into numerical scores based on the coding scheme presented in Table 8. Most variables were measured using ordinal response categories representing respondents’ perceptions of accessibility, amenities, facilities, and digital technology.

Since the variables were transformed into comparable numerical scales and primarily represented ordered respondent perceptions, Euclidean Distance was employed as the similarity measure in the K-means clustering process. This approach is commonly applied in exploration tourism and social science research to identify groups with similar response patterns. The K-means analysis grouped the 100 respondents into three clusters: 48, 17, and 35, respectively. The distribution of respondents across the resulting clusters is illustrated in Figure 5.

Figure 5 illustrates the distribution of respondents across three clusters based on similarities in their assessments of the analyzed variables. The average values of the analyzed variables within each cluster were used to identify cluster characteristics and primary development issues. Based on these findings, development implications were formulated using the Inclusive Green Economy framework, encompassing economic and environmental dimensions. Rather than merely categorizing destination characteristics, the core conceptual output of this study is presented in Tables 9, 10, and 11, which collectively establish a novel framework for destination management by directly translating these cluster insights into actionable economic, social, and environmental strategies.

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Figure 5. Cluster of tourist plot

Ultimately, Tables 9, 10, and 11 represent the core conceptual output of this study: a destination management framework that moves beyond traditional clustering by prescribing tailored Tourism 4.0 solutions for specific economic, social, and environmental challenges. The clustering results indicate that each respondent group exhibits distinct perceptions regarding tourism facilities, technology use, and destination management. These differences suggest that tourism development priorities vary across clusters and therefore require tailored development strategies rather than a uniform policy approach.

Table 9. Result of clustering and development implications based on an inclusive green economy

Table 10. Potential Tourist Objects and Attractions (TOAs) digital tour package strategy

Table 11. Tourist Objects and Attractions (TOA)’s developing digital tour package strategy

Rather than relying solely on visual separation, an exploratory outlier analysis was conducted based on distance metrics. A total of 22 observations were identified as outliers, formally defined as data points whose Euclidean distance from their assigned cluster centroid exceeded the 90th percentile of the overall distance distribution. These points were further analyzed to explore distinctive destination characteristics.

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Figure 6. Cluster of tourist plot (re-analyzed)

Figure 6 shows an explanatory analysis of observations visually separated from the main cluster concentration in the cluster plot. A total of 22 observations were identified and further analyzed to explore distinctive characteristics that may not be fully represented within the three primary clusters. This additional analysis highlighted several differentiating indicators, including tourism destinations, distance, amenity price, and perceived destination shortcomings.

While the primary cluster analysis identified general development patterns, an additional exploratory analysis was conducted on observations visually located outside the main cluster in the cluster plot. These observations provide additional insights into destinations that exhibit unique characteristics and may require more specific development strategies. The summary of these characteristics, key issues, and development implications is presented in Table 12.

Table 12. Distinctive destination characteristics and development implications

4.7 Mapping of potential tourist attractions

On the basis of the clustering analysis, the TOAs identified as potential tourist attractions in this study are those in cluster 3 and a new cluster formed from outliers. This is because these clusters already have attractions widely known to tourists, good accessibility, and supporting facilities. Meanwhile, cluster 1 faces significant accessibility constraints, underscoring the need for infrastructure development to further enhance the potential of these tourist destinations. Meanwhile, cluster 2 can develop with improved facilities and more effective promotional strategies. Based on these results (in Table 13), it can be concluded that of the 10 tourist attractions in this regional tourism destination, the mapping of objects based on their potential and development is as follows:

Table 13. Potential Tourist Objects and Attractions (TOA) and developing TOA

4.8 Digital technology development strategy in Tourism 4.0

The proposed digital strategies are derived directly from the empirical cluster characteristics. For instance, destinations in cluster 1, which face significant physical accessibility constraints, can leverage VR to provide alternative remote access and stimulate initial interest. Conversely, destinations in cluster 2 and the outlier group, which boast good physical accessibility but require enhanced diversification of attractions, are better suited for AR to overlay digital experiences onto existing physical attractions. Finally, digital tour packages and integrated apps address the widespread need for transparent pricing and integrated stakeholder communication identified across cluster 3.

In line with the results of interviews with stakeholders in regional tourism destinations, it is planned to create an application in the next few years that will provide more inclusive, integrated information, ranging from village tourist attractions to other data that many people can access. The application of technological innovation is expected to help become one of the solutions. This is also in line with the results of the tourist questionnaire, which stated that the promotional media considered effective for tourism marketing is the use of digital, namely through social/electronic media (77%), followed by sales promotions 17%, through print media 11%, and 5% with other means such as through word of mouth (see Figure 7).

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Figure 7. Tourist plot cluster

In relation to this, several development strategies that can be implemented by using digital technology in this regional TOA are:

4.8.1 Virtual tour

This virtual tour system can be web-based and accessed via mobile devices. This virtual tour is hoped to improve effective solutions for promotion, accessibility, education, and tourism management [45-47]. Virtual tours are one of the most promising and effective ways to achieve these goals [48]. Virtual tours can help prevent various tourism businesses from being completely shut down during the crisis by creating new business models and offering various opportunities to various organisations in the tourism sector [49, 60]. This is especially true for TOAs that are still developing or have limited access. Based on this, several tourist attractions have implemented virtual tours as a form of tourism marketing, including Cibodas Botanical Gardens and Kota Bunga (in Figure 8). Other TOAs can also adapt this program to accelerate the development of tourist attractions and increase the number of direct and digital visits.

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Figure 8. Virtual tour of Cibodas botanical gardens

4.8.2 Tour packages

A digital-based tourism package strategy, combined with an inclusive green economy concept, can help TOA maximize tourism potential and accelerate the development of more inclusive emerging tourist attractions.

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Figure 9. Regional Tourist Objects and Attractions (TOA)

TOAs in this category (Figure 9) have a strong appeal and already have a relatively robust infrastructure. Therefore, they can focus on enhancing tourism experience with digital technology.

The TOA in this category (see Table 10) has limited facilities and attractions. Therefore, they can focus on digital promotion and on enhancing their tourist appeal through interactive, sustainable technology.

4.8.3 Digital support

Tourist attractions can develop digital payment strategies through mobile payment for entrance tickets. This cashless mobile payment strategy can be implemented using smartphones and e-wallets. From an inclusive green economy perspective (environmental aspects), this strategy will reduce paper waste (going paperless). Furthermore, digital maps can be accessed by scanning QR codes, reducing the paper waste associated with conventional maps or brochures (see Table 6). Previous studies demonstrated that the use of mobile-based applications in various fields [61-63], including education and monitoring, has significantly simplified transactions and increased user satisfaction [64]. Therefore, ticket payments at tourist attractions can be made using NFC, QR codes, artificial intelligence, and IoT. This aims to help tourists book and pay for tickets. Furthermore, the use of QR codes in ticket validation has been proven to speed up the tourist entry process and enhance transaction data security.

The authors would like to express our sincere gratitude to the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia, particularly the Directorate General of Higher Education, Research, and Technology (DRTPM), for supporting this research through the Higher Education Excellence Basic Research Grant (Regular Fundamental Research Scheme 2025), under Grant No. 125/C3/DT.05.00/PL/2025 and Agreement No. 7928/LL4/PG/2025. The authors also thank the reviewers for their constructive comments and suggestions.