Formulating A Competitive Advantage Model for Tourism Destinations in Indonesia

Abstract

Indonesia has successfully increased its ranking to 40th place in the 2019 Travel & Tourism Competitiveness Index. While tourism has become the country's second largest foreign exchange contributor, there is no existing competitive advantage model for Indonesian tourist destinations. The purpose and novelty of this study is to develop and formulate a competitive advantage model for Indonesia's tourism industry. The model will be based on the supply-side perception analysis of competitiveness indicators from Bali and five designated super-priority destinations in Indonesia. This model is expected to become a guideline for policymakers to design an effective and focused strategy. Data were obtained from in-depth interviews with, and questionnaires given to, 62 qualified industry players from the public and private sectors. This data-driven approach builds a relationship between competitiveness indicators and competitive advantages using a combination of importance-performance analysis and confirmatory factor analysis, thereby leveraging these advantages to generate a strategic model to compete in the international tourism industry. This would also be the first study to use this method in defining the competitive advantage of a destination. Using structural equation modeling, the study found that there are 54 indicators representing twelve dimensions of competitive advantages with good fit criteria.

1. Introduction

The 2019 Indonesian Economic Report issued by Bank Indonesia stated that tourism has become the second largest contributor of foreign exchanges (Bank Indonesia, 2020). The Travel & Tourism Competitiveness Index (TTCI) produced by the WEF revealed the ranking of Indonesian tourism industry had increased significantly from 81^st in 2010 to 42^nd in 2017 and 40^th in 2019 (WEF, 2019). From the four indexes, Indonesia succeeded significantly in two indexes, the Natural & Cultural Resources and Travel & Tourism Policy Enabling Conditions. Two other indexes, the Infrastructure and Enabling Environment, still need major improvements, especially when compared to neighboring countries like Singapore, Malaysia and Thailand. Fitch also reported that tourism infrastructure is less developed particularly outside of main destinations and the country is vulnerable to natural disasters and terrorist attacks (Fitch Solutions, 2019).

Regardless of reports, the government has made tremendous progress in the last ten years, particularly in the infrastructure sector: highway, main roads, airports and seaports have been built to connect Indonesia’s main cities. Moreover, policies in tourism sector have been upgraded to accommodate and attract more foreign tourists to visit Indonesia. In fact, the government has designated 10 new priority destinations also known as the ʻ10 new Balis’ (Kementerian Pariwisata, 2019).

For centuries, Indonesia has been a famed “spice” destination for European travellers in search of “spices – gold of the era”. Indonesia is an amazing collection of people, places, sights, sounds and natural wonders in the world (Oey, 1990). Consisting of more than 17, 000 islands, Indonesia is the world’s largest archipelago with its 5, 000 km long, located around the Equator between Asia and the Australian continent, and between the Pacific and Indian oceans. The diversity of flora, fauna and their ecosystems, as well as its culture, are potential attractions for tourism industry (Anak Agung Gde Raka Dalem, 2002).

In 2019, 16.1 million foreign tourists visited Indonesia spending 18.4 billion USD in foreign exchange. Indonesia was awarded the fourth most popular destinations according to Trip Advisor Traveller’s Choice 2020, ninth according to Agoda Top 10 City Destination 2019. In addition, the government has set its priority to develop essential infrastructure in accordance to accessibility, attraction and amenity; in fact, they have designated five out of ten priority destinations – Danau Toba, Borobudur, Lombok-Mandalika, Labuan Bajo-Komodo and Manado-Likupang-Bitung (Bank Indonesia, 2020) – as super-priority. With 6.2 million tourists in 2019, Bali is still the most famous Indonesia’s tourism destination, while other destinations are left behind. It is necessary for the country to develop other potential destinations based on scientific approach of its destination competitiveness to give travellers more choices to visit.

The purpose and the novelty of this study are to develop and formulate a tourism destination competitive advantage model for Indonesia, which currently does not exist. The model will be based on the perception analysis of competitiveness indicators from Bali and five designated super-priority destinations in Indonesia from supply side, both public and private sectors. It is important for Indonesia to have a model that represents its competitive advantage in tourism and the results of this study will serve as a guideline for Indonesia to continue maintaining the existing superior indicators while enhancing indicators that have low performance levels, but are nevertheless important in the tourists’ eyes. This model is expected to be a useful reference for the development of Indonesia’s tourism industry.

2. Literature Review

Aside from the tourism destination competitiveness model developed by TTCI, there are pretty available models developed by scholars. For instance, Crouch and Ritchie’s (1999, 2003) conceptual model is composed of five dimension with 36 variables; Crouch (2011) tested the model in England with 83 respondents. Dwyer and Kim (2003a, 2003b) refined Crouch and Ritchie’s, (1999, 2003) model by making it more practical to measure the destination competitiveness. This made a significant contribution to the development of the TDC framework (Azzopardi & Nash, 2017).

Gooroochurn and Sugiyarto (2005) proposed a tourism competitiveness model with eight main indicators. Heath (2003) came up with a strategic planning framework that has five dimensions with 26 components in South Africa. Cucculelli and Goffi (2016) proposed an extension of Crouch and Ritchie’s, (1999, 2003) model by introducing a set of sustainability indicators and testing their role in explaining the competitiveness of a tourism destination in Italy and Brazil three years later (Goffi et al., 2019). It is clear that tourism has become a key driver for socio-economic progress and one of the major players in international commerce (UNWTO, 2020), unfortunately, none of the models to date have been proven to be satisfactory (Dwyer & Kim, 2003a).

2.1. Destination Competitiveness

Competitiveness appears to be a simple concept (Crouch & Ritchie, 1999, 2003), however, the literature revealed a diversity of perspectives in defining, understanding, and measuring competitiveness (Dwyer & Kim, 2003a), and its measure will vary depending on the choice of base year and/ or the base country (Gooroochurn & Sugiyarto, 2005).

In the context of tourism, competitiveness refers to the ability of a destination to compete effectively and profitably in order to deliver goods and services that perform better than other destinations, providing a memorable tourism experience (Dwyer & Kim, 2003a), having said this, members of the tourism industry need to understand how to measure and achieve competition thus improving their competitive edge (Hong, 2008).

Research on how competitiveness indicator is measured through many methods had been done by many scholars, (Kozak & Rimmington, 1999; Lemy et al., 2020; Long, 2020; Mazanec et al., 2007; Mendola & Volo, 2017; Salinas Fernández et al., 2020; Wei Lee Chin & Hampton, 2017).

Hassan (2000); Lee and Syah; (2018); Nguyen et al. (2020); Than et al. (2020) investigated the environmental impact and sustainability, while Alberti and Giusti (2012); Dugulan et al. (2010); Salazar (2007) discussed cultural heritage in tourism. Studies about price competitiveness were done by Dwyer, Forsyth, and Rao (2000); Natalia et al. (2019) proposed a methodological measurement for tourism accessibility; Santos et al. (2014) studied destinations’ life cycle stage.

2.2. Destination Competitive Advantages

According to Porter (1990), competitive advantage is created and maintained through a highly localized process where differences in national values, culture, economic structure, institutions and history all contribute to successful competitiveness. In the context of the tourism industry, any destination need to ensure that it has ‘appeal’ and offer travellers a superior experience compare to its competitors (Dwyer & Kim, 2003a).

Many works had described competitive advantage in tourism, such as: competitive advantage through authenticity of Scotland (King, 2007); cultural tourism (Chang & Liu, 2009); residential tourism (Ribes et al., 2011); competitive advantage of the Turkish tourism industry (Özer et al., 2012); on rural tourism (Chin et al., 2017); determinants of competitive advantages for the EU-28 countries (Algieri et al. 2018); from business perspective (Michael et al., 2019); and wine tourism (Frost et al., 2020).

In this study, Indonesia’s competitive advantage is determined based on destination attributes/indicators that have a high level of importance, and high and low performance based on the perception of supply side using IPA and CFA.

2.3. Importance-Performance Analysis (IPA)

Importance-performance analysis has been used as a method in tourism destination research. IPA provides a direct and straightforward Interpretation. The four quadrants are based on a measurement combination of level of importance and performance (Martilla & James, 1977). Indicators on Quadrant B are highly important and performing excellently or “keep up the good work” quadrant. Quadrant A, “concentrate here”, reveals the indicators are highly important; however, they lack in performance and require improvement. Quadrant B and A are important since they reveal a potential competitive advantage in the attributes. On the other hand, quadrant C, “low priority”, reflects the indicators that both less important and low performing, while quadrant D, “possible overskill”, has low importance, but good performance. Quadrant C and D will most likely be ignored as they serve the least priority for resource allocation (Oh, 2001; Sugiarto, 2017).

Several scholars use IPA to analyze the competitiveness of destinations (Chu & Choi, 2000; Dwyer et al., 2016; Enright & Newton, 2004; Dwyer, Dragicevic, Armenski, & Mihalic, 2014; Dwyer, Knezevic Cvelbar, & Edwards, 2012).

2.4. Confirmatory Factor Analysis (CFA)

The main objective of using a confirmatory factor analysis (CFA) is to measure a predefined model fits with an observed set of data, a maximum likelihood estimation (DeCoster, 1998; Sugiarto, 2017). Confirmatory factor analysis is carried out using LISREL 10.2 to all indicators that have passed the validity and reliability test.

Some tourism researchers who use CFA are Asmelash and Kumar (2019), Gooroochurn and Sugiyarto (2005), López-Gamero et al. (2009), Lo, Songan, Ramayah, and Yeo (2013), Mazanec et al. (2007), Pesamaa and Hair (2008), Ribes et al. (2011), Vorhies and Morgan (2005), Wang and Hsu (2010).

In this study, the factor reduction resulted from IPA analysis will then be confirmed using CFA to develop a good fit criteria model as required. This model eventually will be the final model of the competitive advantage of Indonesia’s tourism destination.

3. Research Methodology

This study uses a mix of qualitative and quantitative methods divided into four stages. The first stage is to develop a model of competitiveness indicator from the literatures; this is called an “early model”. The second stage involves testing the early model to industry players from both the public and private sectors in Bali through in-depth interviews and filling in the questionnaire; the results are used to develop an “advanced model’. In the third stage, the questionnaires for the advanced model are distributed to industry players of five super-priority destinations in Indonesia: Danau (Lake) Toba Geopark, Borobudur & Prambanan Temples, Lombok-Mandalika, Labuan Bajo-Komodo and Manado-Likupang-Bitung. Data obtained from Bali and other five destinations will be analyzed at the final stage using importance-performance analysis and confirmatory factor analysis.

3.1. Research Stage 1

Crouch and Ritchie (1999, 2003) published a conceptual ‘Calgary” model, then Dwyer and Kim (2003a, 2003b) successfully refined its theoretical concept into a practical one that could be operationally measured. The models developed by Crouch and Ritchie (1999, 2003) and Dwyer and Kim (2003a, 2003b) are widely adapted by other scholars. Crouch and Ritchie’s (1999, 2003) model had been tested for its applicability in the South Bana district by Andrades and Dimanche (2017) and Drakulić Kovačević et al. (2018) who combined Crouch and Ritchie (1999, 2003) and TTCI’s model to measure destination competitiveness in Russia. As for Dwyer and Kim’s (2003a, 2003b) “Integrated” model, it has been tested by (Tanja, Vladimir, & Nemanja, 2015; Gomezelj & Mihalič, 2008; Dwyer, Knezevic Cvelbar, & Edwards, 2012) and some other countries.

Even though TTCI is the most used, it is not perfect as stated by Pulido-Fernández and Rodríguez-Díaz (2016) who criticized the comprehensiveness of the model created by TTCI, hence, Indonesia should not benchmark its competitiveness solely based on the TTCI model and needs to develop its own model that represents its characteristic.

Ninety-three selected indicators in 18 dimensions of the “early model” were built and mainly adapted from Crouch and Ritchie (1999, 2003), Dwyer and Kim (2003a, 2003b) models with additional consideration from Goffi et al. (2019) who studied in a developing country; TTCI (WEF, 2019) that became reference for Indonesia in measuring competitiveness position; Getz (2008) on special events; Fitch Solutions (2019) that raised some issues in Indonesian Tourism Report Q4–2019; Lubis et al. (2009) who examined competitiveness factors originating from nature and socio- culture in Danau Sentarum, Indonesia; and Ministry of Tourism and Creative Economy programs on tourism.

3.2. Research Stage 2

Quantitative research through questionnaire and qualitative research through in-depth interviews were carried out for active players in Bali. Bali is a world-class tourism destination with more than 100 years of experience where both industry players and the community have solid industry competencies.

The questionnaire (18 dimensions with 93 indicators) was distributed to all 10 respondents two weeks before in-depth interviews were conducted. They were asked to fill in the questionnaire of the “early model” and assessed each indicator based on the level of importance and its performance following the IPA technique. A five point Likert scale is used to rate 1 as “very un-important” to 5 “very important” for the level of importance and a five-point Likert scale also to rate 1 as “very bad” to 5 as “very good” for performance measurement.

On the day of the interviews, the questionnaires were collected and participants were then asked their opinions based on the questionnaire, for instance, regarding the natural dimension, the question was: how important are the natural indicators in attracting tourists to Bali and what is the performance in attracting tourist? From the angle of government tourism support, the questions were: what is your opinion regarding infrastructure, policy, government support? Do you think that the government has been doing a great job supporting tourism? Similar questions continue for other dimensions. By doing this, the researchers do not only have the quantitative data, but also have strong reasons for why they rate the indicators with certain values.

In-depth interviews were conducted with ten VVIP stakeholders such as the Chairman of Bali Tourism Board, Secretary of Government Tourism Office, Chairman of Hotel and Restaurant Association (PHRI), Chairman of Travel Agency Association (ASITA), Secretary General of Tour Leader Association (HPI), Vice Chairman of PCO Association (SIPCO), Managing Director of Indonesia Tourism Development Corporation (ITDC), Head of Village Tourism Association, Chairman of Indonesia Hotel General Manager Association, and Expert staff of Regional Tourism Promotion Agency.

The second stage of the research will enrich the “early model” and enable the researcher to develop the “advanced model”.

3.3. Research Stage 3

The “advanced model” is tested in five designated super-priority destinations: Lake Toba Geopark, Borobudur & Prambanan Temples, Lombok-Mandalika, Labuan Bajo- Komodo and Manado-Likupang-Bitung. Similar to Bali, the respondents were asked to assess each indicator based on its importance and performance following IPA technique.

In order to ensure that the questionnaire gets to the right respondents, the selection of respondents was carried out using the “snowball effect”. As a result, that the respondents are naturally selected and fit with the criteria of qualified expertise, experience and competency in tourism industry, such as director of BPODT (Lake Toba Authority Governing Body), governor assistant for tourism, head of tourism office, chairmen of ASITA, hotel & restaurant owners/general managers, chairman/secretary of tour leader association, travel director, travel agency and others.

Below is the distribution of respondents based on destination; apart from the 10 respondents from Bali, the study succeeded in gathering another 52 qualified respondents from five designated super-priority destinations. The mean sample industry experience is 19.8 years, as Table 1.

Table 1: Frequency of Respondents Based on Industry Category

3.4. Research Stage 4

A data-driven approach is used to build the relationship of competitiveness indicator and competitive advantages, thereby leveraging these advantages enable to generate a strategic model to compete in the international tourism industry. From 64 questionnaires distributed to Bali and five super-priority destinations, the study managed to collect 62 filled-in questionnaires; two of the respondents did not fill in appropriately so their questionnaires were not included in the data analysis. Amongst the 62 questionnaires, there were six respondents who did not fill in completely (one to four of 102 indicators, and only one missed 14 indicators). When they were asked back why they did not fill in the questions, they said that they just could not rate it. Given this situation, data cleansing is carried out for missing indicators by providing the mean value of its indicator and do not significantly affect original mean value of the indicators.

The obtained data were analyzed using importance- performance grid to find which indicators sat in quadrant B “keep up the good work” and quadrant A “concentrate here”. Indicators in quadrants C and D will not be analyzed further since those indicators are less important. The indicators from quadrant B and A will be processed further to develop competitive advantage model using confirmatory factor analysis (CFA) with LISREL 10.2 software.

4. Results and Discussions

4.1. Result from Qualitative Research

The exploration of competitiveness indicators from eight competitiveness indicator models mainly from Crouch and Ritchie (1999, 2003), Dwyer and Kim (2003b, 2003a) are representative of the characteristics of Indonesia as a developing country. The model consists of 93 indicators with 18 dimensions.

Results from in-depth interviews in Bali provide a very deep insight regarding the importance of culture in tourism. All respondents concluded that culture plays major role in Bali tourism industry, while natural beauty is a bonus. Bali’s main attraction for foreign tourists is the incorporation of indigenous cultures and traditions in their everyday lives. The role of culture was further strengthened when in-depth interviews were conducted in Lake Toba Geopark revealed even that Lake Toba has a world-class natural beauty with its unique geological history and is one of UNESCO’s Global Geoparks. However, most tourists only spend one or two nights in the destination. They admitted that arts and cultural performances have not been capitalized to encourage longer stay. Indeed, every district in Lake Toba has its own unique culture and traditions.

Given these findings, there is need to add indicators related to indigenous culture and traditions to the “early model”. Thus, the researcher revisited cultural activities from literatures; adding six more indicators related to culture to the model and spread into three dimensions: four in Cultural Heritage, one in Range of Activities and one in Entertainment and Special Events, as shown in Table 2.

Table 2: Additional Indicators from Bali’s Interview

Another strength of Bali in attracting tourists is the friendliness of the people towards tourists, it is one of the factors of Bali tourism development (Suradnya, 2005) and this is supported by Goffi et al. (2019), which includes the friendliness of local residents as one of indicators in his research. Friendliness toward residents/hospitality of residents is then added to the dimension of Quality of Services, as Table 2 reveals.

In-depth interviews also found that there must be a separation of indicators between the role of public and private sectors in Human Resource Development and Environmental Management because each sector has a different role. Bali, with its “Tri Hita Kirana” concept, has long history of maintain harmonious relationships relationship, not only with nature, but also horizontal (human) and vertical (God) relationships. This concept has established Bali as a great example of sustainable tourism in Indonesia, which is economically viable, but does not destroy the natural environment (Swarbrooke, 1999). As enforced by Crouch and Ritchie (1999, 2003), it is only a matter of time before the destination’s natural capital will be depleted.

Considering the result from the qualitative research above, there were nine additional indicators to the early model from 93 to 102 indicators.

4.2. Results from Quantitative Research

Results from IPA demonstrated that the mean performance of indicators is 3.68 and the mean level of importance is 4.60. Out of 102 indicators, the total 61 indicators fall into quadrants B and A. 29 indicators, which have a high level of importance and high performance were sat into quadrant B “keep up the good work”; 32 indicators were in quadrant A “concentrate here”, which means those indicators have high a level of importance, but low performance, see Figure 1.

Figure 1: Importance-Performance Grid with Indicator Ratings for Indonesia’s Tourism Destinations

These 61 good indicators are mapped to various overarching dimensions. The remaining 61 bad indicators that fell into quadrant C and D will not be analyzed further as they do not reflect the competitiveness indicator of the model.

With regards to dimension, there are four dimensions, which left only one indicator since other indicators in the same dimension are neither sat in quadrant C or D, they are:

– Range of Activities, which leaves a nature-based activity.

– Shopping, which leaves a quality/variety of local handicrafts.

– Entertainment, which leaves a culinary.

– Location, which leaves a perception of “exoticness” of tourist location.

Since nature-based activity indicator have close relation to Natural Dimension, it is incorporated into the Natural Dimension; quality/variety of local handicrafts and culinary are incorporated into the Cultural/Heritage dimension and perceived ‘exoticness’ of location is incorporated into Demand Factor dimension. Thus, the 18 dimensions of the early model now have been reduced into 14 dimensions with 61 good indicators.

The results show that seven dimensions – Natural, Cultural/Heritage, Tourism Infrastructure, Accessibility, Quality of Services, Price Competitiveness, Safety and Security as well as Demand Factor – are potential competitive advantages for Indonesia’s tourism destinations that need to be confirmed by confirmatory factor analysis later on. These findings are in line with the work of Crouch (2011) that physiography and climate, cultural and history, safety and security, cost/value, accessibility, awareness/image are amongst the top ten most important elements of destination competitiveness.

In term of Price Competitiveness, it is in line with Gooroochurn and Sugiyarto (2005) where Indonesia is one of the top five countries on this indicator. The level of tourist safety, standards of land, and sea and air transport including the mitigation of natural disasters also have good performance; this is in contrast with the report from Fitch that addressed this issues and TTCI report. What needs to be improved in this dimension is the reliability of police services and the mitigation of terrorist attacks; these two factors appear to be closely related. As for the Quality of Services, respondents perceived that tourist oriented service behaviors are already in place, though the level of professional skill and the over-tourism management have to admit that this needs to be improved. From the Demand Factors, respondents considered that all components perform well, however these need to be confirmed from the real perception from tourists later on.

There are six important dimensions that have low performance: General Infrastructure, Destination Management Organization (DMO), Human Resources Development, Environmental Management, Business Environment and Government Support for Tourism. To some extent, this is in line with the TTCI report where infrastructure and enabling environment needs to be improved. It is understandable as the development of general infrastructures and tourism infrastructure started less than 10 years and it is progressing. Nevertheless, accommodation quality/variety and airport efficiency/quality, telecommunication system for tourist, and socio cultural environment are in good standing.

The low performance of DMO could be explained by Indonesia’s many tourism offices such as tourism boards, tourism management agencies, regional tourism promotion offices and the like; it seems that the role and functions of each of these organizations must be clarified again and streamlined, with collaboration from the government, so that the main objectives of developing the tourism industry can be achieved effectively. This will greatly benefit other dimensions such as government support for tourism and human resources. Brent Ritchie and Crouch, (2010) revealed that DMO is a determining factor for the competitiveness and success of a sustainable tourism destination.

Concerning Environmental Management, respondents admit that there is still a lack of recognition on the importance of sustainable tourism development from both the private and public sectors. Law enforcement as well as the monitoring on this area need to be improved. Goffi et al. (2019) in his study of Brazil, asserts that sustainability influences tourism destination competitiveness in emerging economy; it is not only essential for preserving the ecosystem, but also for improving the competitiveness of sociocultural attractions.

Surprisingly, with regards to the Range of Activities dimension (water-based, adventure-based, recreational facilities) and the Entertainment dimension (nightlife, amusement, carnival, concert, festival, other special events) are not considered important according to respondents.

4.3. Validity Test Results (Pearson’s Correlation)

Validity test is carried out using SPSS version 26 for all 14 dimensions and 61 indicators using Pearson’s correlation. It demonstrates that all indicators measured were valid. Whereas 41 indicators have Pearson’s correlation values above 0.8, 18 indicators are in the 0.5–0.8 range, and only two indicators are below 0.5, with values of 0.495 and 0.402. The results of the significance test stated that all indicators are significant at a level of 0.05.

4.4. Reliability Test Results (Cronbach’s Alpha)

The reliability test is carried out using SPSS version 26 for all 14 dimensions and 61 indicators. The Cronbach’s alpha value of 13 tested dimensions is above 0.7, only one dimension (Natural) has a Cronbach’s alpha value of 0.567. Even though, it is reasonable to keep this Natural dimension and follow the CFA measurement model as if one of those four indicators in the Natural dimension is eliminated, it will result in a smaller Cronbach’s alpha value. There is a stronger reason to keep the Natural dimension in; it is still considered an important aspect of destination competitiveness; with a Cronbach’s alpha value above 0.55, it is decided that the Natural dimension is quite reliable.

4.5. Confirmatory Factor Analysis (CFA)

The CFA measurement model is carried out using LISREL version 10.2 on each of the 14 dimensions. This constructs a competitive model that fits the criteria where the loading factors are above 0.5. Price Competitiveness and Business Environment have two indicators that are closely related, thus the two dimensions are finally combined into one new dimension, Price Competitiveness & Business Environment. Testing the CFA path diagram also demonstrates that Accessibility of Destination needs to be combined with Tourism Infrastructure in order to have a good fit criteria model; the new dimension has eight indicators after it is merged. After the merge, the final number of dimensions has been reduced to 12.

Seven indicators do not fit into the model: one indicator out of five – friendliness of residents toward tourists/hospitality of residents – was removed from Quality of Services because it is similar to another indicator (tourist oriented service) in the same dimension; one indicator out of four – entrepreneurial quality of local tourism stakeholders – was removed from Business Environment; three indicators out of nine – investment environment for tourism development, support for IT infrastructure for tourism and access to venture capital – were removed from Government Support;. two indicators out of seven – perceived “exoticness” of location and tourist “respect” for local tradition – were also removed from Demand Factors. The removal of these seven indicators brings the total number to 54 indicators. Results from the CFA measurement model of 12 dimensions with its 54 indicators are shown in Table 3.

Table 3: Result of Goodness of Fit Criteria of 12 Dimensions

** : Good fit.

* : Close fit.

5. Conclusion

The tourism industry in Indonesia is considerably young and less mature. Even though Indonesia has so many exotic and untapped destinations across the country, such as Komodo Island, Lake Toba, Raja Ampat and so many others, the most well-known tourist destinations are Bali and Borobudur. Findings show that there are seven dimensions of competitive advantage that are ready to be leveraged to attract more world travellers. The seven dimensions are a part of the top ten most important destination competitiveness according to Crouch (2011), and are also, to some extent, consistent with Goffi et al. (2019) on his study in another developing country, Brazil.

On top of that, there are five other important dimensions that need to be improved immediately in order to support those seven dimensions: General Infrastructure, DMO, Human Resources Development, Environmental Management, and Government Support for Tourism, where the government must play a critical role in terms of advancing infrastructure, tourism and environmental policy as well as training and providing certification for industry players.

Indonesia has the capacity to welcome much more tourists to visit and enjoy its natural beauty and cultural diversity, especially if it is supported by good infrastructure.

Provided that tourism contributes as the second largest foreign exchange to the Indonesia GDP, it is clear that the respondents are highly appreciative of the government’s tremendous efforts. Despite the progress made, future efforts can only be achieved if the government creates policies that will strengthen the tourism industry. For the past few years, the tourism strategy was carried out through accessibilities, attraction, amenities, promotion and industry players (Bank Indonesia, 2020). Hopefully, with the formulation of a competitive advantage model consisting of 12 dimensions and 54 indicators, this will become a guideline for policymakers to design an effective and focused strategy.

The competitive advantage model could potentially contribute to making tourism the largest foreign exchange contributor for the country, as Table 4.

Table 4: The Main Dimension and Indicators of Indonesia’s Tourism Destination Competitive Advantage Model

6. Contribution

This would be the first study to use a combination of IPA and CFA in defining the competitive advantage of a destination, which contributes to the body of knowledge of destination competitiveness. The findings of this study give valuable practical implications as they provide a deeper understanding of destination competitiveness in developing countries, where natural and cultural resources are abundant. Unfortunately, supporting factors such as infrastructure and tourism policy are still in the development phase. Finally, the study has an important managerial implication for all stakeholders to actively participate in sustainable tourism.

7. Limitations and Further Research

The research was done during the COVID-19 pandemic, hence the number of people willing to respond to the questionnaire and be interviewed was limited. This research could be furthered with more adequate number of respondents with the remaining five new Balis so as the competitive advantage model will have a more subtle framework. Moreover, the research is only conducted from the supply side, leaving the author curious as to whether or not the resulting competitive advantage matches the demand side. Therefore, a similar study from the demand side needs to be investigated in the future.