Assessing the resilience of rural tourism in Indonesia during and after the Covid-19 pandemic using the multimoora method

Ariyani, Nafiah; Fauzi, Akhmad Article Assessing the resilience of rural tourism in Indonesia during and after the Covid-19 pandemic using the multimoora method Amfiteatru Economic Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Ariyani, Nafiah; Fauzi, Akhmad (2024) : Assessing the resilience of rural tourism in Indonesia during and after the Covid-19 pandemic using the multimoora method, Amfiteatru Economic, ISSN 2247-9104, The Bucharest University of Economic Studies, Bucharest, Vol. 26, Iss. Special Issue No. 18, pp. 1329-1347, https://doi.org/10.24818/EA/2024/S18/1329 This Version is available at: https://hdl.handle.net/10419/319807 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1329 ASSESSING THE RESILIENCE OF RURAL TOURISM IN INDONESIA DURING AND AFTER THE COVID-19 PANDEMIC USING THE MULTIMOORA METHOD Nafiah Ariyani1 and Akhmad Fauzi2 * 1) Sahid University of Economics and Business Faculty, Jakarta, Indonesia 2) Bogor Agricultural University of Economics and Management Faculty, Bogor, Indonesia Please cite this article as: Nafiah, A. and Akhmad, F. 2024. Assessing the Resilience of Rural Tourism in Indonesia During and After the Covid-19 Pandemic Using the Multimoora Method. Amfiteatru Economic, 26(Special Issue No. 18), pp. 1329-1347. DOI: https://doi.org/10.24818/EA/2024/S18/1329 Article History Received: 16 August 2024 Revised: 21 September 2024 Accepted: 6 October 2024 Abstract Tourism villages play a vital role in developing rural areas in Indonesia. However, they are vulnerable to external shocks, including economic fluctuations and recent public health events like the COVID-19 pandemic. This study analyses the resilience of 24 tourism village destinations in Indonesia from 2019 to 2022. The MULTIMOORA method (multi-objective optimisation by ratio analysis plus the full multiplicative form) was employed to assess resilience. The findings indicate that most tourism villages in Indonesia experienced significant impacts during the initial year of the pandemic. However, they demonstrated the ability to recover, as evidenced by changes in their rankings before and after the pandemic. This result suggests that tourism villages in Indonesia show strong capacity and performance to rebound from pandemic-related shocks. The novelty of this research lies in its ability to provide a comprehensive and timely assessment of the resilience of tourism villages in Indonesia during the COVID-19 pandemic, utilising a robust methodological approach and offering valuable insights into their capacity to recover from external shocks. The research significantly contributes to the broader literature on tourism village resilience. It provides empirical evidence, methodological innovation, and valuable insights into the economic resilience of the sector in the face of external shocks. The findings have implications for policymakers, researchers, and practitioners working in tourism development. * Corresponding author, Akhmad Fauzi – e-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2024 The Author(s). AE Assessing the Resilience of Rural Tourism in Indonesia During and After the Covid-19 Pandemic Using the Multimoora Method 1330 Amfiteatru Economic Keywords: rural tourism resilience; pandemic shock; Multimoora; rural development JEL Classification: R580, Z320, Z380 Introduction Rural tourism has become a global trend due to its perceived benefits in economic, social, and environmental aspects. As stated by Shin et al. (2017), Jamini and Dehghani (2022), and Stepanova et al. (2023), rural tourism has gained momentum and become a new kinetic energy in revitalising rural development, stimulating economic growth, and providing various direct benefits to its residents. Rodrigues et al. (2021) argue that rural tourism is a sustainable development strategy capable of creating jobs, generating income, combating rural depopulation, fostering socio-economic networks, preserving cultural and natural heritage, and improving the quality of life for rural populations. What exactly is rural tourism? The concept of rural tourism remains challenging to define precisely. This is related to the lack of consensus on what constitutes rural areas (Bosworth and Turner, 2018). According to OECD (1994), the definition of rural depends on the specific analytical goals or policy issues. Consequently, It is challenging to create a universally applicable definition of rural tourism across all regions and countries (Ayazlar and Ayazlar, 2015). Bernard Lane was the first to define rural tourism, namely tourism that occurs in rural areas (Lane, 1994). However, this simple definition is inadequate for various purposes (Bran et al., 2010). Rosalina et al. (2021) state that the universal definition of rural tourism lacks consensus, and a precise definition is still difficult to grasp because rural tourism is complex, encompassing multifaceted activities that vary across regions and countries. Instead, researchers have developed their definitions based on their unique experiences and contexts in each country (Nair et al., 2015). The UNWTO defines rural tourism as “a type of tourism activity in which the visitor’s experience is related to a wide range of products generally related to nature-based activities, agriculture, rural lifestyle/culture, angling and sightseeing (Peira et al., 2021). To address the lack of a definition for rural tourism, Bernard Lane proposed that rural tourism should encompass several key characteristics: (1) it must be located in rural areas, (2) it must reflect the distinctive features of rural tourism, (3) it involves small-scale buildings and settlements, (4) it connects with local communities and their families, (5) it centres around villages and small towns, and (6) it includes complex economic, environmental, and historical patterns (Lane, 2009; Lane and Kastenholz, 2015). Adding to the conception of rural tourism, the World Tourism Organization (WTO) defines rural tourism as a type of tourism that offers visitors personal interactions, experiences with the physical environment and rural life, and participation in local activities, traditions, and lifestyles (Aref and Gill, 2015). Despite its recognised role in various countries, the COVID-19 pandemic, with its unprecedented impacts, has raised significant concerns about the sustainability of rural tourism. The tourism sector, including rural tourism, was one of the first severely affected by the COVID-19 pandemic (Harchandani and Shome, 2021). According to (Gössling et al., 2020), the COVID-19 pandemic has posed a significant threat to global tourism. The sector has been forced to face various risk situations and push to develop strategies to quickly adapt New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1331 to various economic, political, or social disruptions it has caused (Lamhour et al., 2023). This situation underscores the importance of resilience strategies in this sector (Kürüm Varolgüneş et al., 2022). Hu et al. (2021) indicate that given the impact of the COVID-19 outbreak, special attention is needed to enhance the resilience of rural tourism systems. Yu et al. (2023) emphasise that resilience is a crucial variable in helping rural tourism recover from the pandemic's impacts. Resilience essentially involves developing creative ways to plan, prepare and adapt to risks (Basurto-Cedeño and Pennington-Gray, 2018). As a developing country, rural tourism plays a crucial role in Indonesia. It is set as direction for developing tourism in rural areas, which is expected to enhance economic growth and the welfare of rural communities while preserving nature and the environment and promoting the development and preservation of rural culture (Ariyani et al., 2022). In Indonesia, rural tourism is defined as tourism that presents rural activities and local wisdom as attractions (Wirdayanti et al., 2021). Rural tourism in Indonesia is institutionalised as tourist villages (Ariyani and Fauzi, 2024). Nuryanti (1993) defines a tourist village as a combination of accommodation, attractions, and supporting facilities with traditional village life. Over time, the number of tourist villages in Indonesia has continued to increase. In 2019, before the COVID-19 pandemic, the number of tourist villages reached 1,831 (Ariyani and Fauzi, 2023). These villages are categorised into four groups based on their development: pilot, developing, advanced, and independent villages. Following the implementation of Large-Scale Social Restrictions (PSBB) in response to the widespread COVID-19 pandemic, many tourist villages in Indonesia ceased operations (Damanik et al., 2022). PSBB significantly reduced mobility in workplaces, recreational areas, and transit zones. The decrease in visitor numbers led to the collapse of many tourist villages, resulting in workers losing their income and livelihoods (Pramana et al., 2022). The impact of COVID-19 on tourist villages in Indonesia varies. Some villages that performed well before the pandemic were severely affected, with many even closing operations. Meanwhile, other villages survived. This fact is due to the varying levels of resilience among tourist villages. Resilience in tourist villages is also highly dynamic, a village may have good resilience in one year but experience a sharp decline the following year, while other villages may improve. This phenomenon is intriguing as it can help researchers and practitioners in tourism development identify factors determining the resilience of tourist villages, including policymakers in developing policies to strengthen the resilience of tourist villages. This study aims to (1) analyse the resilience of tourist villages in Indonesia during and after the COVID-19 pandemic, (2) determine the ranking of tourist village resilience, and (3) trace changes in the ranking of tourist village resilience during this period. This task is particularly challenging due to tourism systems' complex and dynamic nature, involving many interrelated and nonlinear variables and activities (Baggio, 2020). The results of this study will provide breakthroughs in explaining how the performance of tourist villages in Indonesia before and after the COVID-19 pandemic and identifying which villages are the most resilient and the variables determining this. This study uses the MULTIMOORA method (Multi-Objective Optimization by Ratio Analysis plus Full Multiplication Form) to address these issues. The output of the MULTIMOORA method is a ranking derived from combining the results of three ternary ranking techniques: the Ratio System, Benchmark Approach, and Full Multiplication Form. AE Assessing the Resilience of Rural Tourism in Indonesia During and After the Covid-19 Pandemic Using the Multimoora Method 1332 Amfiteatru Economic This study provides two significant theoretical contributions to the field of rural tourism. First, it enhances our understanding of resilience in the context of tourism and rural development. This paper also offers an in-depth analysis of the challenges faced by rural tourist villages in Indonesia, including infrastructure deficiencies, limited accessibility, and environmental issues, thus adding valuable insights to the existing literature on rural development and tourism. Additionally, this study introduces the MULTIMOORA method as a new analytical framework for assessing and ranking the resilience of rural tourist villages, thereby enriching the methodological tools available for tourism research. The findings of this research will be valuable for policymakers in enhancing the resilience of rural tourism based on appropriate parameters in strengthening resilience. The paper is structured into five sections. After the introduction, section two provides a literature review. The third section outlines the location and the method used for the study. Section four presents the findings and discussion, and section five concludes with the key conclusions drawn from the research. Literature review Since the 21st century, resilience has increasingly been accepted as a framework for understanding global systems. The concept of resilience was first introduced by Holling (1973) to model fluctuations in ecological systems due to human-environment interactions. So far, academics and other stakeholders have not reached a consensus on a definition that can generally explain resilience. Resilience is defined in various ways by different experts, depending on their specific field of study. However, resilience fundamentally represents a dynamic measure of a system's ability to adapt and recover from challenges that threaten its future function and development (Folke et al., 2010; Southwick et al., 2014; Hosseini et al., 2016; Heslinga et al., 2020). Proag (2014) states that resilience has two primary forms: (1) hard resilience, which describes the direct strength of a system or institutional structure under pressure, and (2) soft resilience, which indicates the system's ability to absorb and recover from disruptions without fundamental changes to its functions or structure. Wibowo and Hariadi (2024) suggest that resilience represents a process or outcome in specific phenomena influenced by many factors. Fiksel (2003) argues that the resilience of a system depends on at least three factors: (1) absorptive capacity, which is the ability to absorb disruptive events; (2) adaptive capacity, which is the ability to adjust to these events; and (3) restorative capacity, which is the ability to recover. Lew et al. (2016) assert that resilience can be an alternative indicator of integrated sustainable development. In the tourism sector, resilience typically refers to how tourism destinations respond to disruptive natural disasters that affect the area and its surroundings, limiting their capacity to host tourists (Filimonau and De Coteau, 2020). Sharma et al. (2021) describe tourism resilience as the ability of a destination and its management to adapt to various risks during natural disasters or emergencies. (Dewi, 2020) expands on this definition, viewing tourism resilience as the capacity to handle natural disasters, social conflicts, policy changes, climate change, and impacts on surrounding ecosystems. Kaushal and Srivastava (2021) and Buultjens et al. (2017) emphasise that tourism resilience encompasses the industry's ability to endure both self-induced and external crises threatening stability and sustainable development. Additionally, resilience in tourism considers the effects of socio-economic New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1333 shocks, community resilience, and the overall impact of the tourism industry on regional resilience (Ibanescu et al., 2020). The concept of resilience in tourism extends beyond just socio-economic shocks (McCartney et al., 2021). It encompasses the environmental and ecological sustainability of both formal and informal tourism enterprises (Biggs et al., 2012), the vulnerability of tourism businesses and organisations (Annarelli and Nonino, 2016), and the role of community involvement in enhancing destination resilience (Kwok et al., 2016). Additionally, it addresses disruptions to hotel operations (Brown et al., 2018), risk analysis and management, disaster resilience and sustainability (Basurto-Cedeño and PenningtonGray, 2018), as well as climate change resilience (Dogru et al., 2019), recovery from the impacts of COVID-19 (McCartney et al., 2021), and the well-being of households dependent on tourism (Munanura et al., 2021). Furthermore, research on resilience in tourism also applies to rural areas, highlighting community resilience in rural tourism (Lew et al., 2016), tourism initiatives aimed at enhancing rural land resilience (Shi et al., 2022), the dynamics of rural tourism in Japan during the new normal (Ohe, 2022), and the vulnerability and adaptive capacity of rural tourism systems in response to COVID-19 (Yu et al., 2023). The COVID-19 pandemic has underscored the critical relationship between tourism and resilience (Ibanescu et al., 2022). While the pandemic's long-term effects on regional growth are still being debated, tourism-dependent areas have faced significant challenges, especially during the initial outbreak (Hidalgo et al., 2022). Sharma et al. (2021) emphasise the need for tourism destinations to demonstrate resilience in order to survive, adapt, and thrive in the post-pandemic era. To evaluate the resilience of a tourism area, a suitable measurement tool is essential. Sharma et al. (2021) propose a framework that assesses resilience through four key dimensions: government response, technological innovation, local community engagement, and trust in consumer and tourism management. By measuring tourism destination resilience, stakeholders can gain valuable insights to strengthen resilience and develop effective recovery strategies (Ibanescu et al., 2022). The concept of resilience has fundamentally shifted our understanding of decision-making in the face of unexpected events and tourism development. Scholars and policymakers increasingly advocate for a resilience-based approach to tourism, especially in marginalised or underserved regions (Cellini and Cuccia, 2015; Hall et al., 2020; Ritchie and Jiang, 2019). Resilience offers a holistic framework encompassing emergency preparedness, contingency planning, competitiveness, and sustainable development. As such, it has become a central focus in many policy strategies designed to mitigate disaster risks and enhance financial stability (Béné et al., 2014). Liu-Lastres et al. (2020) highlight the vital role of resilience in the tourism sector in recovering destinations in Aceh, Indonesia. Wibowo and Hariadi (2024) argue that Indonesian tourism lacked the necessary resilience to navigate the economic instability and evolving trends during and after the COVID-19 pandemic. Similarly, research in Papua, Indonesia by Dewi (2020) revealed that the pandemic adversely affected the economic, social, and cultural dimensions, ultimately impacting the resilience of ecotourism destinations. Conversely, Ariyani et al. (2023) found that tourist villages in Indonesia demonstrated a strong capacity to recover from the shocks of the pandemic, particularly in areas with a high Development Village Index and a stable visitor count, thanks to the enforcement of strict health protocols and the introduction of innovative tourism offerings. AE Assessing the Resilience of Rural Tourism in Indonesia During and After the Covid-19 Pandemic Using the Multimoora Method 1334 Amfiteatru Economic Methodology This research was conducted in four provinces: Central Java, East Java, West Java, and West Nusa Tenggara. The number of villages studied was 24. The criteria used to select the villages were as follows: the village represents a favourite tourist spot in the region, data is available, the village has economic and social implications for the rural economy in the area, and the COVID-19 pandemic has impacted the village. Detailed data of the 24 villages and their attractions are presented in Table 1. Table no.1. Profile of research object tourism villages No Tourist Village Regency Province Main Tourist Attraction 1 Pentingsari Sleman Special Region of Yogyakarta Watch welcoming dance, traditional dance learning, traditional music learning 2 Karangrejo Magelang Central Java Mountain panorama tour 3 Wanurejo Magelang Central Java Traditional farming tour, village visit, practice making Javanese sugar 4 Bleberan Gunung Kidul Special Region of Yogyakarta Horse-drawn carriage tour, Javanese fashion show, Javanese music ensemble learning 5 Tinalah Kulon Progo Special Region of Yogyakarta Cave tour, cultural tour 6 Gunung Gajah Pemalang Central Java Exploring nature, river tubing, camping 7 Pulau Cemara Brebes Central Java Mountain panorama tour 8 Mandiraja Pemalang Central Java Beach panorama tour 9 Wana Wisata Boyolali Central Java Waterfall panorama tour 10 Tlogoweru Demak Central Java Reservoir panorama tour, floating stalls 11 Wonosari Grobogan Central Java Owl breeding, fishing 12 Tlogowero Temanggung Central Java Rever panorama tour, culinary delights 13 Bilebante Central Lombok West Nusa Tenggara Camping ground, swimming pool, fishing market, bicycle path 14 Tambaksari Pasuruan East Java Countryside panorama tour, camping ground 15 Pampang Gunung Kidul Special Region of Yogyakarta Nature and culture tour 16 Bendolawang Malang East Java Nature and river tubing tour 17 Malangjiwan Klaten East Java Agrotourism, nature panorama tour 18 Beji Gunung Kidul Special Region of Yogyakarta Traditional natural baths tour 19 Tetebatu East Lombok West Nusa Tenggara Natural panorama and customary forest tour 20 Sade Central Lombok West Nusa Tenggara Rural natural panorama tour, cycling tour, camping ground 21 Bonjeruk Central Lombok West Nusa Tenggara Traditional tribe tour 22 Hanjeli Sukabumi West Java Waterfalls panorama tour, traditional culinary 23 Tepus Gunung Kidul Special Region of Yogyakarta Harvesting and pounding Hanjeli (coix lachrymal-jobi l) 24 Cibuntu Kuningan West Java Traditional dances, village tour, and beach panorama tour Source: Ministry of Tourism and Creative Economy Republic of Indonesia (2022) New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1335 This research uses secondary data in the form of notes from tourist village managers relevant to the indicators of the research variables. Considering the absence of a single definition of rural tourism or a uniform theoretical framework and measures, the research introduces a measure of rural tourism resilience in Indonesia, structured on two dimensions: capacity and performance. The capacity relates to the resources that are part of the rural tourism system, and the performance refers to the work results of the tourism village during and after a shock occurs. Indicators of the capacity and resilience performance of tourist villages in Indonesia are presented in Table 2. Table no. 2. Resilience indicators of rural tourism Capacity Dimension Performance Dimension Capacity Building (X1): number of trainings conducted in a year Tourist (X4): number of tourists during the year Employee (X2): number of employees in a year Income (X5): total income for a year Village Development Index (X3): a composite index that measures village development in Indonesia from various aspects: social, economic, environmental, accessibility, village Governance, and basic services. Cost (X6): total cost for a year The data collection process used document observation. To ensure the validity of the data, the researcher cross-checked the head of the tourist village manager via telephone. Data collection was carried out between March and September 2023. The analysis covers the period from 2019, when the pandemic began in Indonesia, to 2022 when it had significantly subsided. Data analysis The resilience of rural tourism was analysed using the multi-objective optimisation by ratio analysis and full multiplicative form method (MULTIMOORA) developed by Brauers and Ginevičiu (2010). The MULTIMOORA method is a multi-criteria decision analysis (MCDA) method. The method considers various factors, such as the economic impact of the pandemic, the social impact of the pandemic, the environmental impact of the pandemic, and the ability of rural tourism destinations to adapt to change. The MULTIMOORA method was used to identify the most resilient rural tourism destinations during and after the pandemic. Table no. 3. Performance of MOORA relative to other MCDA methods MCDM Method Computational Time Simplicity Mathematical Calculation Stability Information Type MOORA Very less Very simple Minimum Good Quantitative AHP Very less Very critical Maximum Poor Mixed TOPSIS Moderate Moderately critical Moderate Medium Quantitative PROMETHEE High Moderately critical Moderate Medium Mixed Source: Brauers and Zavadskas (2012) Table 3 compares the MOORA method (part of MULTIMOORA) and other MCDM methods regarding computational time, simplicity, calculation, stability, and information type. Hafezalkotob et al. (2019) highlighted the advantages of using MULTIMOORA, including its simple mathematics, low computational time, ease of use for decision-makers, AE Assessing the Resilience of Rural Tourism in Indonesia During and After the Covid-19 Pandemic Using the Multimoora Method 1336 Amfiteatru Economic utilisation of three different methods for subordinate rankings, and integration of rankings through aggregation tools. Unlike many MCDA methods that rely on a single utility method for ranking selection, the MULTIMOORA method combines rankings from three subordinate ranking methods to produce an integrated ranking. Given the criticality of ranking stability in assessing resilience, the choice of MULTIMOORA for this study is deemed appropriate. While MULTIMOORA offers several advantages, it also presents certain challenges, as highlighted by Hafezalkotob et al. (2019). One of the challenges lies in determining the relative importance of criteria through a weighting method. The subjective and objective approaches to assigning weights may yield different results compared to the conventional MULTIMOORA method, which does not involve weighting. Additionally, various methods are available for aggregating rankings, ranging from the straightforward rank position method to the more complex dominance theory method, particularly when dealing with multiple criteria and units of analysis. Similarly, using MULTIMOORA in situations involving target-based criteria like the Sustainable Development Goals (SDGs) for tourism development can pose challenges. The MULTIMOORA consists of three calculation methods, i.e., the ratio system, the reference point, and the multiplicative form. The final of these three systems results in a MULTIMOORA ranking, as seen in Figure 1. Figure no. 1. Diagram of MULTIMOORA Source: Brauers and Zavadskas (2012) The ratio system of MOORA is calculated as follows: Given the decision matrix , also known as a matrix of the response of alternative j on objective i, i=1,2…n as the objectives, and j=1,2,…m as alternatives, the normalised of this decision matrix is given as the following : (eq 1) The ratio system of MOORA is calculated according to the following formula (eq 2) where and are the number of criteria to be maximised and minimised, respectively. New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1343 References Altuntas, S., Dereli, T. and Yilmaz, M. K., 2015. Evaluation of excavator technologies: Application of data fusion based multimoora methods. Journal of Civil Engineering and Management, 21(8), pp. 977-997. https://doi.org/10.3846/13923730.2015. 1064468. Annarelli, A. and Nonino, F., 2016. 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