Network behaviour for tourism business resilience

Abstract

This study applies a relationship perspective to study tourism crisis management and resilience. Despite the growing academic interest in crisis management, few studies have examined how tourism businesses utilise their networks as a crisis management strategy. This research uses a multi-case study design and longitudinal data collection to study the effects of a natural disaster on tourism businesses in Lombok, Indonesia. Results indicate that the characteristics and capabilities of individual tourism business actors and their networking behaviour affected the speed of their recovery. Networks can be used as a strategic tool and business recovery is improved by strengthening network resilience.

Keywords

Crisis disaster resilience relationship marketing network behaviour

Introduction

Tourism is open sector, susceptible to disasters, either natural or man-made, particularly if these creates severe loss of life and long-term damage to the destination (Faulkner, 2001; Hall, 2010). The susceptibility of the tourism industry to disasters requires tourism stakeholders to exhibit resilience in the recovery period (Prayag, 2018). Recovery from a disaster is dependent on the scale of the event, and its character, as well as the destination stakeholder’s resilience. Previous studies have highlighted the importance of crisis management strategies at a destination level for recovery and resilience of a destination (Biran et al., 2014). These studies place the control of recovery at a destination level and often treat resilience as similar to that of an ecosystem (Becken, 2013) where there is a ‘natural’ and general response with a characteristic time frame. In this study however, destination recovery is considered to depend on the ability of individual businesses to deal with a crisis and it is these companies that are the source of its resilience (Williams & Vorley, 2014). This suggests that to gain a deeper understanding of destination resilience, it is important to study individual tourism businesses recovery after a crisis. Their strategies and mechanisms in dealing with a crisis shape their resilience and that of their destination.

There is no universal guide for how to deal with a crisis or disaster, and tourism businesses must adapt to each situation (Campiranon and Scott, 2014). A tourism destination consists of businesses in the hotel, restaurant, tour operator and transportation sectors that together produce a visitor experience. Crisis recovery for a tourist destination is influenced by the abililty of individual operators to deal with business uncertainty after natural disasters such as an earthquake or tsunami (Becken and Khazai, 2017). The interdependence among organisations and how they interact after a natural disaster affects their recovery (Fontanari and Ewald, 2018). Business interaction is also shaped by the abililties of individual operators (Saufi et al., 2018). In responding to a disaster, a tourism business manager may need to change their pattern of interactions. This will dynamically reshape the destination network which may lead to favourable or unfavourable business outcomes for other businesses.

A business can enhance its performance through establishing, maintaining, or breaking relationships with other business firms (Aarstad et al., 2015). In the context of the tourism industry, however, few researchers have studied behavioural issues in business relationship development (Rahimi et al., 2017; Saufi et al., 2018), particularly in dealing with disaster and crisis (Campiranon and Scott, 2014). As a result, there is little understanding of how stakeholders utilise their business relationships and networks as a crisis management strategy (Granville et al., 2016; Jiang and Ritchie, 2017). The current study is aimed at analysing how tourism organisations develop their resilience by establishing business networks as a part of their strategy in response to disaster and crisis (Choi and Cai, 2017; Jiang and Ritchie, 2017).

This analysis of business network behaviour leads to three main questions: First, how do businesses in the tourism industry utilise their business relationships/network in a disaster? Second, how does a tourism businesses’ network behaviour affect their resilience? Third, how does the behaviour of tourism businesses vary during a disaster? This study explores how tourism businesses utilise their business relationships in the response and recovery phases of a disaster (Becken et al., 2014; Prayag, 2018; Paraskevas and Quek, 2019). These questions are addressed through a case study of resilience in the context of earthquake disasters in Lombok, Indonesia.

Literature review

Disaster, crisis, and resilience

In response to the various definitions of the terms, crisis and disaster, Faulkner (2001) synthesised the characteristics of a disaster or crisis and found five essential constituents as follows:

A triggering event, which is so significant that it challenges the existing structure, routine operations or survival of the organisation; high threat, short decision time and an element of surprise and urgency; a perception of an inability to cope among those directly affected; a turning point, when decisive change, which may have both positive and negative connotations, is imminent (p. 138).

The unpredictable arrival of a disaster results in businesses having little ability to evacuate during the event (Faulkner, 2001), and only to respond to it (Prideaux et al., 2003). A disaster is an external event over which a business has no control, while a crisis emerges due to some internal business failure to act (Carlsen and Liburd, 2008; Prideaux et al., 2003). The term “crisis” then emphasises human decisions (individual, organisation and society) as a cause (Scott and Laws, 2005). Therefore, a disaster can lead to a crisis for a business if it fails in its strategy development and implementation (Kim and Marcouiller, 2015).

In the tourism context, a disaster is a catastrophic or shock event, which has negative consequences for a tourism system (Scott and Laws, 2005). A crisis is caused by endogenous or exogenous factors that have major impacts on the sector, and which tourism businesses are unable to control (Pforr and Hosie, 2008). The effects of a crisis can be reduced or ameliorated by sound management that includes prevention/identification, planning, response, recovery and learning from the event (Pforr and Hosie, 2008; Prayag, 2018). Such a crisis management approach can be proactive or reactive. Proactive crisis management aims at developing the capacity of businesses to cope with adversity and disruption with limited consequences in any situation (Paraskevas and Quek, 2019). Therefore, the term crisis concerns how tourism businesses respond to disasters by developing and reshaping strategies, tactics and approaches to minimise negative business consequences.

The term resilience is one of the attributes of a social-ecological system together with adaptability and transformability (Walker et al., 2004). Resilience is defined as the ability of a system to strive to maintain its structure, function, identity, and outcomes when dealing with external impacts. Adaptability is the ability of actors, in a system, to manage their resilience, while transformability is the ability to create an essential a new system when the existing system of ecological, economic or social structure cannot be maintained (Walker et al., 2004)

In tourism, the term resilience refers to the ability of tourism actors to manage the effects of a crisis. Prayag (2018) argues that resilience can relate to changes which can be sudden and extraordinary (i.e., a crisis), or incremental or cumulative. Resilience also focuses on the ability of a business to adapt, respond and evolve in a crisis situation. Therefore, resilience refers to a business owner’s awareness of the overall situation (crisis or normal situation), vulnerabilities and adaptive capacity in a complex, dynamic and interconnected environment (Paraskevas and Quek, 2019). A resilience perspective is complementary to that of crisis management. The two concepts are intertwined, with organisation resilience depending on effective crisis management (Tasic et al., 2019).

There is a limited literature discussing resilience in a disaster (Becken and Khazai, 2017), or resilience and crisis management (Dahles and Susilowati, 2015; Kim and Marcouiller, 2015; Paraskevas and Quek, 2019). Kim and Marcouiller (2015) were the first to use resilience in the context of disasters and crisis. They define the term resilience as the capacity of people, organisations, systems or tourism destinations to develop adaptive responses to the negative effects of disasters and avoid potential loss or return to the state prior to the disaster. This definition suggests that one can assert resilience at different levels, i.e., individual, business and destination. Destination resilience is the ability to return to feelings of safety and normality, clearance and repair of physical infrastructure and recovery in term of visitor expenditure. Physical and business recovery at a destination reflects the resilience of the destination (Khazai et al., 2018). Disaster resilience refers to the capacity of people or businesses at a destination to develop adaptive responses to minimise business risks and loss (Kim and Marcouiller, 2015). Destination resilience is determined by the resilience of the businesses in the destination.

Business resilience leads to survival, adaptation and innovation in the recovery phase (Dahles and Susilowati, 2015). The organisations’ adaptability and innovative capability can ensure business continuity and maintaining marketing performance through a crisis recovery period. An organisation’s flexibility and creativity in responding to the crisis are paramount in determining their resilience (Williams & Vorley, 2014). Put simply, in event of a crisis, a business’s resilience reflects their ability to manage a crisis.

Tourism networks

A destination can be viewed as a tourism system and composed of a network of interdependent organisations, which collectively co-produce/co-create various tourism products/services (Saufi et al., 2018; Scott and Laws, 2005; Scott et al., 2008), and implement joint marketing activities. A destination is a co-producing network (Aarstad et al., 2015). In this view, a tourism destination is a collective business organisation embedded in a network for co-creation and marketing of tourism products/services. An important implication of this network view is that it focuses attention on the interactions and relationships between one organisation and another, and between the organisations and their customers. This system perspective suggests that a crisis or disaster that creates a sudden change in one part of this network may be subsequently transferred to other parts of the system (Scott et al., 2008).

A crisis can lead a tourism destination stakeholder network to being reconfigured into a more efficient structure and may lead to stronger/closer relationships between businesses. A network with strong relationships can achieve a better recovery than businesses acting alone. This is particularly true when the businesses in the network face a common problem, i.e., recovery of business after a disaster. Indeed Granville et al. (2016) argues that collaboration among stakeholders is vital in every stage of crisis management. The relationship marketing literature views a destination as a co-producing system where interactions between tourism industry players dynamically guide the evolution of the network. That network can develop and change overtime due to changes in its environment. A disaster therefore generates negative effects on a tourism network which need to be managed by that network (Scott and Laws, 2005).

Thus, a destination is a group of tourism business in a co-producing and marketing network that needs to work as partners to recover after a disaster. The loyalty, co-operation, commitment and mutual reinforcement of a network of businesses supports (or constitutes) the resilience of a destination. Destination resilience is built based on network cohesion and cooperation. Nonetheless, how tourism businesses utilise this network as a crisis management strategy has received little attention. Collaboration and networking among tourism business organisations is a crucial theme in investigating resilience and crisis management after disasters such as the COVID-19 (Prayag, 2020).

Several authors (Bhaskara and Filimonau, 2021; Ho et al., 2022; Kuščer et al., 2022; Ntounis et al., 2021; Park et al., 2022; Pocinho et al., 2022) argue that the COVID-19 pandemic differs from other crises due to its magnitude and effects (Aldao et al., 2021). The negative impacts of COVID-19 on tourism include travel restrictions, social distancing and stay-at-home orders, radically shifting patterns of leisure consumption and social life, and having severe consequences (Kuščer et al., 2022). Nevertheless, Prayag (2020) argues that the pandemic does not fundamentally change the way resilience is understood or researched in tourism studies. Certainly, an in-depth understanding of how tourism organisations develop resilience is still lacking (Ho et al., 2022). Prayag (2020) points out that interrelationships between resilience at the organisational and individual levels (human capital) and collaboration between business organisations requires attention. Our knowledge about what forms the resilience of tourism practitioners and business organisations is limited (Adams et al., 2021; Bhaskara and Filimonau, 2021; Wided, 2022).

The resilience of tourism businesses and individual actors after a natural disaster is an understudied topic in the crisis management literature. Similarly, collaboration and networking behaviour is important in developing a crisis management strategy. The Lombok earthquakes are an opportunity to investigate these topics. Therefore, this study examines the relationship between tourist organisation resilience, human capital and networking behaviour after a crisis.

Methods

Earthquake in Lombok: The context of the study

The Indonesian tourism industry has been impacted by several natural and man-made disasters, which have had devastating effects on tourist visits to the country (Saufi et al., 2018). These disasters include terrorist attacks in Bali in 2002 and 2005, a tsunami in Aceh in 2004, an earthquake in Yogjakarta in 2006, and more recently, a sequence of earthquakes in Lombok in 2018–2019 on which this paper focuses.

The context of a qualitative investigation is critical because of the myriad of unique interactions that can occur in different situations. It is therefore important to provide detail about a case so that a reader can understand its findings and how they may apply to their own situation (Kelly, 2016). The context of this study is in Lombok after it was affected by a sequence of earthquakes. A magnitude 6.4 earthquake hit Lombok on 29 July 2018, and was followed by several other seismic events, ending in September 2018. The strongest earthquake (magnitude 7.0) struck in August. This quake created the most damage leaving 436 people dead and 783 people severely injured. Tens of thousands of houses and public buildings were damaged and 353,000 people had to shelter in tents for months (BBC Indonesia, 2018). The earthquake created more than US$ 350 million in damages to houses, public buildings, and roads (BBC Indonesia, 2018). These losses included damage to a number of hotels and restaurants particularly in Northern Lombok, the Gili Islands and at the foot of Mount Rinjani (Poltekpar Lombok, 2018). Around 26% of star-rated hotel rooms were damaged and unable to be occupied. For hotels in the Gili Islands and around Mount Rinjani, the room occupancy plummeted from an average of 80% before the earthquake to essentially zero occupancy during the earthquake period in July, August and September. Another earthquake occurred again in March 2019 and two travellers from Malaysia died. This disaster resulted in a business crisis and created challenges for the resilience of tourism businesses in Lombok. This study examines how tourism businesses developed business relationships to deal with the difficulties of the crisis.

Research paradigm and data collection

The study follows naturalistic traditions and explores a real world setting to generate thick and rich understandings of how tourism businesses utilise their relationships for management of a crisis. As one of the research members is a tourism practitioner, the adoption of qualitative approach allows his experience and values to infuse the process of this study. Qualitative approach is useful in identifying answers to ‘how’ and ‘why’ questions about a complex event (Kelly, 2016). This exploratory study seeks to explain ‘how’ and ‘why’ tourism practitioner utilize their business networks in the context of Lombok Island. Qualitative researchers investigate the complex interrelationships among many variables and must not exclude key variables or mis-define the relationship between variables (Mahoney, 2007). Reduction or simplification may lead loss in understanding of complexity of the phenomena (Gummesson, 2006). A qualitative approach is useful to provide a holistic understanding of phenomena. In this case the researchers used qualitative methods to understand the complexity of interrelation among various companies and their network behaviour (Table 1).

Table 1.

The companies selected in the study.

Companies	Informant	Market segment targeted	Company’s experience at the destination
B Tours	Director	Chinese and European visitors	More than 40 years
Family owned, old, big company and located in the city	Director	Chinese and European visitors	More than 40 years
I-A Tours	Manager/owner	Foreign and domestic	More than 30 years
Family owned, old, big company and located in the city	Manager/owner	Foreign and domestic	More than 30 years
L-R hotel	General manager	Government and (mainly) domestic visitors	More than 30 years
Family owned, old, big company and located in the city	General manager	Government and (mainly) domestic visitors	More than 30 years
A-T Tours	Manager/owner	Foreign and domestic visitors	More than 30 years
Family owned, old, big company and located in the city	Manager/owner	Foreign and domestic visitors	More than 30 years
R-T Tours	Manager/owner	Far east visitors	5 years
Family owned, new, located in the city	Manager/owner	Far east visitors	5 years
S-K Villas	Local manager	Australian and European visitors	3 years
Foreign owner/small, located in Kuta beach Mandalika Lombok	Local manager	Australian and European visitors	3 years
S-M Hotel	Local manager	Indonesian corporates and government	10 years
Nasional chain hotel, located in the city	Local manager	Indonesian corporates and government	10 years
Y-O Tour	Manager/owner	Malaysian, Indian and Australian visitors	15 years
Family owned, medium size, located in the city	Manager/owner	Malaysian, Indian and Australian visitors	15 years
B-R Tour	Manager/owner	Corporate and individuals’ domestic visitors	5 years
Family owned, small	Manager/owner	Corporate and individuals’ domestic visitors	5 years

Purposive and snowball sampling were adopted where the tourism organisations (companies) were selected through identifying an initial business and then asking for referrals to others. As dictated by the research objective, this qualitative approach does not rely on statistical generalisation, but instead on obtaining a deeper understanding of the phenomenon (how the tourism organisations utilise their relationships after disaster hit Lombok). Maximum variation was sought among the companies interviewed to enhance the theoretical generalizability of the findings (Curtis et al., 2000).

The authors approached and explained the purpose of the study to the informants, then interviewed them between October 2018 and March 2019 with follow-up in-depth interviews during June to September 2019. This allowed the authors to gather information regarding the companies’ business during low and peak seasons after the disaster. Informants were also re-interviewed via Whats-App messenger between those periods. This allowed the researchers to establish confirmability of the data. A total of nine informants were interviewed face to face two to three times, with each interview lasting from 45 to 90 min. The informants were aged between 24 and 80 years and varied in term of business experiences from moderate to extensive. Pseudonyms are used to protect the informant’s privacy. In this study, the informants are seen as the actors who perform and control activities and resource for the network (Aarstad et al., 2015).

To enhance trustworthiness of the study, the authors used iterative triangulation between the literature review, data, and the authors’ subjective intuition (Lewis, 1998). The data gathering process was begun after the first earthquake struck the island in the peak season of 2018. This earthquake stranded several foreign hikers on Mount Rinjani. Two informants took part in the evacuation of these tourists, working closely with other tourism businessmen and local government employees. The data gathering process continued over a period of 14 months to track and understand each company’s behaviour and strategy. At the beginning of the study, the authors observed how local tourism business actors communicated and coordinated when responding to the first earthquake on 29 July 2018. They communicated using the WhatsApp group of the Mataram Chapter of the Indonesian Marketing Association (IMA) of which the authors were members. This Whats-App group enabled the authors to make initial contact with the respondents. The authors also read and analysed local newspapers (Suara NTB and Lombok Post) during data collection, to learn about the ongoing situation after the initial disaster. This information was used by the authors to prepare a semi-structured interview protocol prior to the face-to-face interviews.All interviews were recorded, and all transcripts were read repeatedly, carefully checking for missed important passages or incorrect coding, and as interpretation developed, passages were recoded with multiple codes. This enabled reflection and a deeper understanding of the data. The authors interpreted the informants’ interpretation of their own experience, actions and views. The informants and the authors’ subjectivity were critical in the process of theory generation.

The authors recorded all interviews and revisited/re-contacted the informants concerning these interviews to assure confirmability of the study. The authors used triangulation of sources of evidence by combining data collection methods such as archives (documentation of local newspapers) and in-depth interviews. The authors relied on the general inductive approach developed by Thomas (2006) as the strategy for data analysis. This approach provides a systematic set of procedures for analysing qualitative data that can produce reliable and valid findings by identifying themes that are most relevant to the research objectives. This approach fits with the inductive tradition in which the authors did not adopt previous theory or a body of literature. The literature, however, was used to establish a critical understanding that stimulated the move to the next phase of the research process, particularly the data analysis. Therefore, to facilitate the interpretation of the data, a further examination of the literature was required. This is part of a hermeneutic process for the conscious search for meaning and understanding as the analysis moves from pre-understandings to understandings on a higher level (Gummesson, 2005) in which the extant literature facilitates progress. During the research process, data were interpreted and reinterpreted as a continuous process of establishing pre-understanding and obtaining a deeper understanding.

Findings

The findings were displayed according to two phases after the initial earthquake. The response phase took place between the first earthquake (29 July 2018) and October 2018, around a month after the last shock. The recovery phase took place between one and 3 months after the disaster ended.

The response phase

During the response phase in the aftermath of the earthquakes, informants stated that they focused on altruistic and humanitarian issues. They relied on their business contacts to help the affected people as strong co-operation already existed among this network. Their business relationships were utilised for humanitarian purposes and these business owners worked together in providing aid for the earthquake victims. The aid included providing free food, shelter, accommodation, transportation, and medical treatment. In the response phase, the actors transformed their business network into a social network as their activities and goals were shifted from profit to giving humanitarian aid. In other words, the networks became mechanisms to facilitate social activities, and not business interactions. At this stage, there was no clear pattern and variation in the companies’ network behaviour as the companies under study had similar ways in responding to the disasters.

Several respondents discussed why they undertook an altruistic approach. They provided two main reasons. The first was to help people but the second was related to a concern with Lombok’s destination image. These two reasons formed a common bond between the informants, as observed below:

There are two things that encouraged us to do it, first, humanitarian reasons. Secondly, actually if we manage disasters well, it can be a way to build our good image. (AW/A-T Tours).

We acted without command we moved in the same direction, namely tourists. We all realise that they are our life. Even then, we are also aware that this is not the only time we have experienced a disaster, the wars in the 1980s, SARS, boom Bali I and II, we naturally learn from experiences. We have been formed and we also must not forget how we struggled until our tourism advanced. That’s what we try to protect (TH/I-A Tours).

The tourism business actors saw parallels between the current earthquake in Lombok and the effect of various natural and man-made disasters that had hit other destinations in Indonesia, such as terrorist attact in Bali in 2002 and 2005. They had learnt from previous crises that they had to work closely to minimise negative impact of the disaster on the destination. When they faced this common problem, the actors participated spontaneously and actively in various ways, and communication and coordination among them became increasingly intense. The informants considered that this led to the development of a more solid social network among the destination’s businesses. Two of key informants acted as initiators, executors and fund raisers for disaster relief, while their partners give financial and non-financial support such food, shelter, transportation and coffins. The actors had different roles but a mutual goal, i.e., providing humanitarian aid. The network facilitated and united their efforts. Indeed, the network became bigger as they worked with their competitors from Bali.

The recovery phase (1–3 months after the disaster ends)

Unlike the response phase, the business suggested variation in term of how they utilised their business network. Therefore, the businesses that had similarities were grouped together. The identification of the groups or category was initially based on the speed of their business recovery. Within the first 3 months after the disasters, the first category of companies showed no sign of recovery, the second group had slow recovery and the third category had a quick recovery of their business profitability. These categories were labelled as low, moderate and strong resilience.

Three companies (CB Tours, I-A Tours and L-R Hotel) in the low resilient category were passive and they did not exchange information or cooperate with their partners. For the first 3 months after the disaster ended, they were silent and had very few customers (less than 10% of normal). The respondents admitted that they failed to work with partners to provide an attractive offering, i.e., recovery rate was in inadequate time. Their partners (hotels) offered a low rate only for 1 month, which was too short for these companies to develop, design and promote innovative tour packages. These companies also did not try and expand to new markets or initiate new business relationships. These businesses were larger in size, with more experience in the destination than companies in other categories. Their strategy was to survive by waiting for a return to a normal situation without any change in their network, hence their behaviour is labelled as passive.

…this condition is really bad. Number of guests drastically reduced in August and September. I could say the hotel guests were zero, I could say that. Our income declined, the hotel was damaged, and we have to fix it, we have to invest again, we have to spent more, so much cost (LN/L-R Hotels)

Three companies (A-T Tours, R-T Tours and S-K Villas) in the moderate resilience category tried to change their business by adopting or increasing the use of digital marketing. They began planning to develop more attractive offers by collaborating with partners. They began to look for new potential market segments by looking for new business partners, but this was done rather slowly, first 3 months after the disaster and due to a drastic decline in their sales. This is seen in the case of R-T Tours who only began to try and market in Australia 7 months after the disaster. Therefore, this behaviour was labelled as slow-reactive.

Moreover, three companies (S-M Hotel, Y-O Tours and B-R Tours) in the strong resilience category had already adopted digital marketing and used various e-commerce channels to market their services. They maintained their business performance by identifying and establishing new business relationships. At the same time, they also maintained and enhanced their existing business relationships by active communication with their business partners and using word of mouth from tourists. This indicates proactive alignment of their business relationships/network. One company described their proactive behaviour:

we just had to be more vigorous to convince the market. Within the first month, my team has been to Jakarta for a sales mission or promotion. In September, October and November we kept moving, we visited Jakarta every month. We also visited several industrial centres in January, we went to Gresik and Surabaya, we looked for new customers in the industrial centres continuously. This week my team is in Jakarta, my team has twice visited Jakarta this month. We aggressively maintain or meet our customers (S-M Hotel).

As the quote above shows, S-M Hotel had a strong focus on recovery and increased their efforts to strengthen existing business relationships and to try to find new customers. They proactively looked for potential customers in the industrial centres of Java. The hotel manager searched for opportunities to provide volunteers with accommodation, as the manager realised that large companies from Java would send volunteers to take part in humanitarian activities. These volunteers would need accommodation. The same approach was used by the other two companies (B-R Tours and Travel and Y-O Tour and Travel).

Further, the actors in the strong resilience category put business relationship development as the highest priority. This can be observed below:

We seek new customers and maintain relationships with existing ones. We already have a plan, and it still must go on. We don't want to be affected by this disaster. If someone asks me why I went to Gersik, I said first, there were many big and well-known companies there. I went there to maintain contact with companies like petrochemicals, they stay with us here (S-M Hotel).

“We have many partners throughout Malaysia. First, I made sure that they happy with us, they will bring us tourists then I asked them to provide a review. I interact directly with tourists and ask them to provide a review on my fan page” (B-R Tours)

These findings indicate that during the response phase, the tourism business actors utilised their network in similar ways due to their common objectives. However, the findings suggest variations in recovery phase. The companies varied in term of their business recovery speed, network behaviour and network resilience.

Discussion

In order to answer the first and the second questions, the discussion below analyses how the companies utilised their business relationships in the response and recovery phases of a disaster. During the response phase, the tourism business actors realised that the future of their business depended on how they responded and helped tourists during disasters. The destination faced acquiring a negative post disaster image due to the earthquake. The businesses recognised that they faced a long and hard process, but that a new and better image was essential for the destination and their businesses (Miller et al., 2017). As a result, the tourism business actors worked closely together because they had the same objectives i.e., provision of humanitarian aid and minimalising the negative effects of the disaster on the destination’s image. These common concerns bonded them together. Figure 1 below illustrates how they worked together forming a cohesive social network (Scott et al., 2008).

Figure 1.

A cohesive social network.

Nonetheless, in the recovery phase the companies under study varied in term of their behaviour in utilising business relationships. Constant comparison among the companies/cases allowed identification of unique topics/themes based on which categories were established. This constant comparison also facilitated the identification of shared features and patterns across the businesses understudy. As suggested by the findings, three categories of companies were identified according to their business recovery speed which is taken as an indication of the strength of their resilience (Paraskevas and Quek, 2019). The characteristics of business in each category varied in terms of their network behaviour and resilience, as illustrated in Table 2 below:

Table 2.

Business characteristics of resilience categories.

Category (company)	Case features
Low resilience: (B. Tours; I-A Tours and L-R Hotel)	Business recovery	Network resilience: Weak and inactive/unprofitable business relationships
	No sign of recovery, No/very low reservation (less than 10%) within the first 3 months of the disasters. This situation did not improve until 1 year after the disaster.
	Relational/network behaviour: Passive
	Limited communication and cooperation with partners, no innovation in their offerings and no market and business relationship expansion.
Moderate resilience: (A-T Tours; R-T Tours and S-K Villas)	Business recovery:	Network resilience: Weak/unexpanded
	Slow recovery: Within the first 3 months gained a small number of reservation but able to obtain higher number of reservations for the next 6 months.
	Relational/network behaviour: Slow-reactive
	Communication and cooperation maintained but rather slow and reactive, tried to identify new business partners; market/business expansion was considered, but no new business relationship established/no market expansion within the first year.
Strong resilience (S-M Hotel, Y-O Tour and B-R Tour)	Business recovery:	Network resilience: Strong and expanded
	Quick recovery, business was active within the first 3 months and gained many reservations for the next 6 months.
	Relational/network behaviour: Proactive
	Proactive in strengthening business relationships by visiting and convincing partners. Aggressive and flexible search for new markets, and building/establishing new business relationships as well as developing creative offerings based on market analysis.

The results suggest that business in the three categories differed in term of recovery speed and their network resilience. All companies faced the same conditions and showed similar behaviour in the response phase but experienced different business recovery speeds. Companies that demonstrated strong resilience used a proactive network behaviour during their recovery. The proactive companies initiated or strengthened business relationships during the recovery period, while passive companies made limited efforts and invested few resources in their business relationships (Choi and Cai, 2017). The later companies decreased their commitment and did not use business network for quick recovery. They could not maintain business interactions and cooperation with their partners to create a more attractive offering during the recovery phase.

All the companies in the strong resilience category showed proactive behaviour in strengthening and building business relationships. This helped to convince their customers/partners that Lombok was safe, which is important for business recovery (Campiranon and Scott, 2014). They were flexible in providing attractive offers and were widely used for volunteer accommodation. B-R Tours and Travel strengthened their business relationships with hotels on Lombok with the aim of being able to provide attractive “recovery rates”. B-R Tours and Travel kept their commitment in the Malaysian market because of the high interest of travellers and volunteers from that country. When another earthquake occurred again in March 2019, the manager of B-R Tours and Travel used Labuan Bajo as an alternative to Lombok. This effort was successful because of the long-standing relationships with local representatives. The same approachwas used by Y- O tours and Travel.

The companies in the third (strong resilience) category were able to provide services to volunteers in the aftermath of the disaster because they had strong relationships with government and non-government institutions before the disaster. They were able to maintain these relationships in the recovery phase. The companies in the third category relied on their business relationships, cooperating and creating more attractive offerings, discounting to volunteers but also launching efforts to gain normal revenue customers as well as searching for new-prospective markets and partners. The companies in this category paid attention to maintaining and strengthening their relationships while developing new business relationships and expanding to new markets/destinations.

Such strong business relationships facilitate co-production of more attractive offerings, resulting in better business recovery and resilience. Relationships are regarded as one of main key success factors in recovery phase of crisis management (Campiranon and Scott, 2014). Developing strong business relationships is an important strategy for strengthening business resilience and allowing a business to cope with adversity after a disaster (Prayag, 2018). Cooperation with others to maintain their economic exchanges in difficult situations can facilitate a business’s recovery (Sulhaini and Sulaimiah, 2017). Thus, these findings indicate that business resilience is underpinned by network behaviour and thus by network resilience

In response to Question 3, through constant comparison among the cases and categories, it seems that the network behaviour is shaped by the character and capabilities of the leaders/decision makers (referred to as the actors in the study). This can be observed in the table below.

Table 3 shows that business resilience is related to business relationships/network resilience which in turn is shaped by the relational behaviour of the actors/leaders in which their character and capabilities play fundamental roles. The business actors in the strong resilience category displayed a strong spirit, optimistic/positive thinking and exhibited high creativity/innovativeness, flexibility, and analytical ability in their strategic moves during recovery phase. Furthermore, the “strong resilience” actors share similarities in terms of characteristics, as depicted in Table 4.

Table 3.

Case features regarding network behaviour, resilience, capabilities, and characteristics.

Category	Case features
Category	Network behaviour & resilience	Capabilities and characteristics of the actors/leaders
Less resilience	Network behaviour: Passive	Operational rigidity, tend to be pessimistic, lack of creativity and innovativeness
No sign of recovery (B. Tours; I-A Tours and L-R Hotel)	Network resilience: Weak and inactive/unprofitable
Moderate resilience	Network behaviour: Slow	Analytical, operational inflexibility, slow respond, tend to be pessimistic.
Slow recovery (A-T Tours; R-T Tours and S-K Villas)	Network resilience: Weak and unexpanded
Strong resilience	Network behaviour: Proactive	Creative/innovative, analytical, operational flexibility, high rapidity, positive thinking/optimism, high spirit
Quick recovery (S-M Hotel, Y-O Tour and Travel and B-R Tour and Travel)	Network resilience: Strong and expanded

Table 4.

Similarities in the characteristics of strong resilient tourism actors.

The characteristics of strong resilient actors	Details
Creative and innovative	Capability of the actors in creating new service through co-creation in the network, i.e., new services/tour packages, new service rate or new destinations.
Analytical	This relates to the actors’ cognitive capability to analyse and comprehend the market situation so that they can predict the likelihood consequences on their business and take appropriate actions. This capability enables the actors to be operationally flexibility and innovative
High rapidity	Capability of the actors to rapidly adapt and establish priorities after the disasters by visiting and intensive communication to the partner to convince them that they are not heavily affected by the disasters and still safe. Also, they establish business relationships with new partners for new product/service offering soon after the disaster
Flexibility	Capability to adapt positively in response to the difficult situation by staying flexible in marketing the services, finding/tapping opportunities in different/new market segment (i.e., volunteer tourism) or new destinations and thus initiate and develop new business relationships while maintaining business relationships in their traditional market. This capability enables the actors to expand the business networks and ensuring the generation of revenue during crisis
Optimism/positive thinking	How actors view the impact of disasters on the current and future state of their business. They believe that there are still opportunities even in a difficult situation. An actor with positive thinking will have a great focus on identifying opportunities in new market segment/destination rather than thinking too much on the natural disasters. On the contrary, a pessimistic actor will tend to wait and see as they view the crisis as the result of multi-causes situation. They believe that it is too hard to recover the business due to the occurrence of the natural disasters, the increasing price of domestic airline ticket, strong competition with e-commerce and global market situations
Spirit	Actors’ belief in their own ability and spirit to improvise in stressful business and market situations. These two main characteristics energise the actor’s capabilities above.

Network behaviour has been conceptualised on an organisational level involving actors’ activities in developing their direct and indirect business relationships (Thornton et al., 2015) which can be assumed to affect business performance and thus recovery and resilience. This definition stresses the role of actors and their behavioural tendency to utilise and influence their business relationships in recovery phase. After natural disasters, an unexpected/negative business environment is to be expected, thus, the business actor’s resilience becomes critical. Hence, resilience is related to how business actors deal with their business environment to keep their tourism business running (Saufi et al., 2018). An individual actor’s resilience is affected by their accumulation of abilities and characteristics that enable them to adjust to or transform the difficult situations they experience into one of evolution and progress (Tabassum et al., 2019). This study identifies several characteristics that explain variations among the three categories. Favourable capabilities and characteristics of individual actors will result in more proactive/aggressive behaviour in developing business relationships/networks, which ultimately lead to positive impacts on their business. In other words, favourable capabilities and characteristics of actors underlies profitable business relationships and network resilience from which business can attain strong resilience.

The findings of the current study support and extend the findings of other studies on resilience. Engeset (2020) found that hotel resilience during a crisis depends on the entrepreneurial skills and capacity for hard work of the actors. Similarly, Ho et al. (2022) argue that the unique nature of the coproduction and cocreation services in the hospitality and tourism industries require highly flexible and responsive leaders especially during the pandemic COVID-19. The pandemic created environmental uncertainties that require the leader of hotel and travel companies to take strategic actions promptly. This current study identifies other characteristics and capabilities of actors (see Table 4) that determine their resilience. The study also expands the understanding that individual resilience determines resilience on different levels i.e. business organisations, network and thus inter-organisation.

Resilience begins at the individual level, then the organisational level and then the inter-organisational level (Yao and Fabbe-Costes, 2018). Since a tourist destination seen as a coproducing system, an actor should not act alone but rely heavily on his networks to recovery the business and the destination (Luthe and Wyess, 2014; Orchiston, 2013). This study further explains that individual resilience depends on their characteristics and capabilities in managing all activities to employ business relationships by means to enhance their organisation’s resilience. This also means the business relationships/networks stay active, productive, and profitable for the organisations. High resilience individuals will respond effectively aligning the networks through which resilience of the network and the organisations can be assumed. This suggests that high resilience actors will view their business relationships/network as strategic tools to guarantee their business resilience, and they will show a positive behaviour and develop mechanisms for their networks to gain guests in a crisis. The figure below illustrates the findings.

Figure 2 illustrates that business resilience depends on individual actors’ resilience, in which their characteristics and capabilities play fundamental roles in their network behaviour. Resilience actors engender their business resilience by utilising relationship marketing strategy. Furthermore, their behaviour reflects their passive or proactive ways in initiating, establishing and developing numerous business relationships to strengthen their business resilience. Favourable characteristics and capabilities energise a more proactive relational behaviour. They strategically align the relationships/network for recovery purpose and, thus, it can be said that the network is a strategic tool to strengthen organisational resilience. The more favourable characteristics and capabilities of the actors, the more resilience of the actors in dealing with the crisis. This leads to more resilience networks and business. Therefore, the business actors are the true sources of their network and organisation resilience.

Figure 2.

Interactions between levels of resilience.

Conclusion, implication and future research directions

Conclusion

Some authors (Granville et al., 2016; Jiang and Ritchie, 2017) have pointed out that collaboration is essential in tourism crisis management. This study has used a relationship marketing perspective to explore how tourism businesses resilience in a destination is affected by sequential earthquakes. The study differs from previous studies in two ways. First, this study analyses resilience at three different levels, i.e., individual actors, business networks and the business. Second, the study collected longitudinal data, starting from when the disaster occurred up to 14 months after the disaster. This enabled the authors to observe consistency of the tourism business actors’behaviour and strategy in dealing with the crisis. The study indicates that in the response phase in Lombok, companies responded in similar ways and turned the business networks into social networks. The networks are activated to deliver humanitarian aids and to reduce negative impacts on the destination image. In the recovery phase, however, the business network behaviours varied, leading to differences in business and network resilience. More proactive network behaviour led to resilience of the business and the network. The characteristics and capabilities of the company’s leader/manager make these differences. Their characteristic and capabilities specify their individual, network and organisation resilience. Natural disasters seem to be a natural selection process for leaders and only those who have favourable capabilities and characters can success. They are able to develop and align effective strategies, tactics and approaches to recover quickly through their business networks. Therefore, it can be concluded that the recovery phase of crisis management is a proactive phase for individual and business resilience. This is a critical phase for business continuity after a disaster. Individuals who are not proactive in using their network will jeopardize the sustainability of their business. Resilience individuals proactively direct and steer their business and networks for crisis management after disasters.

Resilience of tourism business depends very much on resilience of individual entrepreneurs/managers and how they oriented on internal relationships with staff (Prayag et al., 2020). This study however found that tourism business resilience depends on how individual business actors oriented toward external relationships/business networks. This study provides further explanations that the leader/manager is the main actor in business relationship development, and their capabilities and characteristics underline their capability to adapt and stay innovative in difficult situations. They can mitigate the negative effects of a disaster by proactively deploying and expanding their business network to acquire new customers and modify their offerings.

Managerial implications

As the study suggests, a business network is supported by actors with the capabilities and characteristics to rejuvenate business performance in a difficult market situation. Also, organisational resilience depends on the resilience of these decision makers/leaders who navigate a crisis by strengthening business network allowing co-creation of new services. The crisis forces the actors to employ their network for their organisation’s recovery and to maintain their revenue during the crisis. Therefore, as the true source of network and organisational resilience, the actors need to develop their characters and capabilities, which enable them to develop a more proactive network behaviour. Their optimism, sprit, creativity, flexibility and analytical ability stimulate their business to find new ways to survive and adaptive to new business reality. In a destination that is prone to disaster and crisis, having favourable characters and capabilities to respond and adapt quickly and effectively through business networks is becoming a prerequisite in today’s successful business actors. Also, the actors can collaborate to build a social network in the destination where their business reside, which aims for volunteering during and after the disaster events.

Furthermore, a destination is a coproducing system where actors work together in cohesive business networks, the resilience of a destination depends on their network resilience. Network resilience is based on actors’ resilience in coping with negative effects of a disaster on their organisation and the image of the destination. Their resilience capability is seen in their network behaviour and how they prioritise, commit, and utilise their network for recovery of the business organisation and the destination. It is imperative for actors to build their relational capabilities to minimise the negative effects on the business and the destination, particularly in a destination that susceptible to natural disasters.

Resilience at the inter-organisational level depends on how actors utilise their networks proactively and strategically for recovery. Actors with certain characteristics and capabilities have stronger network resilience. Developing those characteristics and capabilities are essential for an actors’ crisis preparedness. These characteristics and capabilities need to be developed long before a disaster occurs. This is especially true for actors in destinations that are prone to disasters. Before a disaster and crisis happens, tourism industry actors should nurture their capabilities to respond, anticipate, react and adapt before, during and after a crisis to ensure a quick recovery. Actors should prepare by developing strategies including proactively utilising business network for recovery purposes.

Footnotes

Acknowledgements

We have been fortunate, as a number of people helped us for this publication. We thank our informants who provided their precious time and useful information. Also, we have been supported by our colleagues at the Department of Management, University of Mataram, Lombok Indonesia.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Sulhaini

Author Biographies

Sulhaini is a Professor at Management Department, University of Mataram. Her research interests are international marketing, relationship marketing, tourism marketing and consumer culture. She received her BA in Management from the University of Mataram, M.Sc in International Marketing and Management from Copenhagen Business School – Denmark; and Ph.D in International Marketing from Sheffield Hallam University, England – UK. Her studies are published in various journals, among others: J. Global Business Advancement (2016), Journal of Relationship Marketing (2017 and 2020), Int. J. Applied Management (2019), Management and Marketing: Challenge for the Knowledge Society (2019), Asia Pacific Management Review.

Akhmad Saufi holds a PhD in international Tourism and Hospitality Management from Griffith University. He is a Senior Lecturer of Tourism Management in the Department of Management at the Faculty of Economic and Business University of Mataram, Indonesia. He is currently managing the Monitoring Center of Sustainable Tourism Observatory of University of Mataram. He has published a number of papers in some preferred journals, including Journal of Sustainable Tourism (2014), and International Journal of Culture, Tourism and Hospitality Research (2021). His current research interests are in the areas of host community participation, sustainable practices in tourist destination and tourism entrepreneurship.

Lalu Edy Herman is a Lecturer and Researcher at Management Department University of Mataram, West Nusa Tenggara, Indonesia. His research is mainly about Marketing especially in Relationship Marketing and entrepreneurship and small business development with a focus on the community sustainability aspects. His studies are published in several jounals, among others: Ijaber (2015), Quality - Access to Success Journal (2018), Journal of Relationship Marketing (2018), Int. J. Services, Economics and Management (2018), Business: Theory and Practice (2020), Journal of Xi'an Shiyou University (2021), and Journal of Southwest Jiaotong University (2021)

Noel Scott is Adjunct Professor of Tourism Management at the University of the Sunshine Coast, Australia. Noel has worked as a tourism researcher for 26 years and has led research and consulting projects in sustainable tourism training, tourism branding, destination management, tourism experience design and China tourism. His recent focus is on use of cognitive psychology theory and psychophysiological methods to understand tourist experiences. He has over 300 academic articles published including 16 books. He is a Fellow of the Council of Australian University Tourism and Hospitality Educators, and a member of the International Association of China Tourism Scholars. Email nscott1@usc.edu.au.

References

Aarstad

Ness

Haugland

(2015) Destination evolution and network dynamics: new research agendas. In: Chambers

Rakic

(eds) Tourism Research Frontiers: Beyond the Boundaries of Knowledge. Bingley, UK: Emerald Group Publishing Limited, 141–164.

Adams

Choe

Mostafanezhad

, et al. (2021) (Post-) pandemic tourism resiliency: Southeast Asian lives and livelihoods in limbo. Tourism Geographies 23(4): 915–936.

Aldao

Blasco

Espallargas

, et al. (2021) Modelling the crisis management and impacts of 21st century disruptive events in tourism: the case of the COVID-19 pandemic. Tourism Review 76(4): 929–941. DOI: 10.1108/TR-07-2020-0297.

BBC Indonesia (2018) Gempa Lombok: Korban meninggal dunia mencapai 436 orang, kerugian tembus Rp 5 triliun. Available at: https://www.bbc.com/indonesia/indonesia-45165817 (accessed 12 January 2020).

Becken

(2013) Developing a framework for assessing resilience of tourism sub-systems to climatic factors. Annals of Tourism Research 43: 506–528. DOI: 10.1016/j.annals.2013.06.002.

Becken

Khazai

(2017) Resilience, tourism and disasters. In: Butler

(ed) Tourism and Resilience. Oxfordshire, UK: CABI, 96–104.

Becken

Mahon

Rennie

, et al. (2014) The tourism disaster vulnerability framework: an application to tourism in small island destinations. Natural Hazards 71(471): 955–972.

Bhaskara

Filimonau

(2021) The COVID-19 pandemic and organisational learning for disaster planning and management: A perspective of tourism businesses from a destination prone to consecutive disasters. Journal of Hospitality and Tourism Management 46: 364–375.

Biran

Liu

, et al. (2014) Consuming post-disaster destinations: the case of Sichuan, China. Annals of Tourism Research 47: 1–17.

10.

Campiranon

Scott

(2014) Critical success factors for crisis recovery management: a case study of Phuket hotels. Journal of Travel & Tourism Marketing 31(3): 313–326.

11.

Carlsen

Liburd

(2008) Developing a research agenda for tourism crisis management, market recovery and communications. Journal of Travel & Tourism Marketing 23(2–4): 265–276.

12.

Choi

Cai

(2017) The role of relationship quality in integrated destination marketing. Journal of Travel & Tourism Marketing 35(5): 541–552.

13.

Curtis

Gesler

Smith

, et al. (2000) Approaches to sampling and case selection in qualitative research: examples in the geography of health. Social Science and Medicine 50: 1001–1014.

14.

Dahles

Susilowati

(2015) Business resilience in times of growth and crisis. Annals of Tourism Research 5: 34–50.

15.

Engeset

(2020) “For better or for worse” – the role of family ownership in the resilience of rural hospitality firms. Scandinavian Journal of Hospitality and Tourism 20(1): 68–84.

16.

Faulkner

(2001) Towards a framework for tourism disaster management. Tourism Management 22: 135–147.

17.

Fontanari

Ewald

(2018) The market of the tour operators in Germany within a disruptive environment. In: Innerhofer

Fontanari

Pechlaner

(eds) Destination Resilience. New York, NY: Routledge, 184–201.

18.

Granville

Mehta

Pike

(2016) Destinations, disasters and public relations: stakeholder engagement in multi-phase disaster management. Journal of Hospitality and Tourism Management 28: 73–79.

19.

Gummesson

(2005) Qualitative research in marketing, roadmap for a wilderness of complexity and unpredictability. European Journal of Marketing 39(3/4): 309–327.

20.

Gummesson

(2006) Qualitative research in management: addressing complexity, context and persona. Management Decision 44(2): 167–179.

21.

Hall

(2010) Crisis events in tourism: subjects of crisis in tourism. Current Issues in Tourism 13: 401e417.

22.

GKS

Lam

Law

(2022) Conceptual framework of strategic leadership and organizational resilience for the hospitality and tourism industry for coping with environmental uncertainty. Journal of Hospitality and Tourism Insights. Epub ahead of print. DOI: 10.1108/JHTI-09-2021-0242.

23.

Jiang

Ritchie

(2017) Disaster collaboration in tourism: motives, impediments and success factors. Journal of Hospitality and Tourism Management 31: 70–82.

24.

Kelly

(2016) A different type of lighting research – A qualitative methodology. Lighting Research & Technology 49: 933–942.

25.

Khazai

Mahdavian

Platt

(2018) Tourism Recovery Scorecard (TOURS) – Benchmarking and monitoring progress on disaster recovery in tourism destinations. International Journal of Disaster Risk Reduction 27: 75–84.

26.

Kim

Marcouiller

(2015) Considering disaster vulnerability and resiliency: the case of hurricane effects on tourism-based economies. The Annals of Regional Science 54: 945–971.

27.

Kuščer

Eichelberger

Peters

(2022) Tourism organizations’ responses to the COVID-19 pandemic: an investigation of the lockdown period. Current Issues in Tourism 25(2): 247–260. DOI: 10.1080/13683500.2021.1928010.

28.

Lewis

(1998) Iterative triangulation: a theory development process using existing case studies. Journal of Operation Management 16: 455–469.

29.

Luthe

Wyess

(2014) Assessing and planning resilience in tourism. Tourism Management 44: 161–163.

30.

Mahoney

(2007) Qualitative methodology and comparative politics. Comparative Political Studies 40(2): 122–144. DOI: 10.1177/0010414006296345.

31.

Miller

Gonzalez

Hutter

(2017) Phoenix tourism within dark tourism: rebirth, rebuilding and rebranding of tourist destinations following disasters. Worldwide Hospitality and Tourism Themes 9(2): 196–215.

32.

Ntounis

Parker

Skinner

, et al. (2021) Tourism and hospitality industry resilience during the COVID-19 pandemic: evidence from England. Current Issues in Tourism 25: 1–14. DOI: 10.1080/13683500.2021.1883556.

33.

Orchiston

(2013) Tourism business preparedness, resilience and disaster planning in a region of high seismic risk: the case of the Southern Alps, New Zealand. Current Issues in Tourism 16(5): 477–494. DOI: 10.1080/13683500.2012.741115.

34.

Paraskevas

Quek

(2019) When Castro seized the Hilton: risk and crisis management lessons from the past. Tourism Management 70: 419–429.

35.

Park

Kim

(2022) How does COVID-19 differ from previous crises? A comparative study of health-related crisis research in the tourism and hospitality context. International Journal of Hospitality Management 103: 103199. DOI: 10.1016/j.ijhm.2022.103199.

36.

Pforr

Hosie

(2008) Crisis management in tourism. Journal of Travel & Tourism Marketing 23(2–4): 249–264.

37.

Pocinho

Garcês

de Jesus

(2022) Wellbeing and resilience in tourism: a systematic literature review during COVID-19. Frontiers in Psychology 12: 748947. DOI: 10.3389/fpsyg.2021.748947.

38.

Poltekpar Lombok (2018) Kajian dampak ekonomi pariwisata pasca gempa di Lombok dan Sumbawa. Indonesia: Tourism Ministry. Tourism Polytechnic Lombok.

39.

Prayag

(2018) Symbiotic relationship or not? Understanding resilience and crisis management in tourism. Tourism Management Perspectives 25: 133–135.

40.

Prayag

Spector

Orchiston

, et al. (2020) Psychological resilience, organizational resilience and life satisfaction in tourism firms: insights from the Canterbury earthquakes. Current Issues in Tourism 23(10): 1216–1233. DOI: 10.1080/13683500.2019.1607832.

41.

Prayag

(2020) Time for reset? COVID-19 and tourism resilience. Tourism Review International 24: 179–184. DOI: 10.3727/154427220X15926147793595.

42.

Prideaux

Laws

Faulkner

(2003) Events in Indonesia: exploring the limits to formal tourism trends forecasting methods in complex crisis situations. Tourism Management 24: 475–487.

43.

Rahimi

Köseoglu

Ersoy

, et al. (2017) Customer relationship management research in tourism and hospitality: a state-of-the-art. Tourism Review 72(2): 209–220.

44.

Saufi

Reid

Patiar

(2018) Understanding the host community's experiences of creating small autochthonous tourism enterprises in Lombok, Indonesia. In: Lima

King

(eds) Tourism and Ethnodevelopment Inclusion, Empowerment and Self-determination. Abingdon, Oxon: Routledge, 170–187.

45.

Scott

Laws

(2005) Tourism crises and disasters: enhancing understanding of system effects. Journal of Travel & Tourism Marketing 19(2–3): 149–158.

46.

Scott

Laws

Prideaux

(2008) Tourism crisis and marketing recovery strategies. Journal of Travel & Tourism Marketing 23(2–4): 1–13.

47.

Sulhaini Sulaimiah (2017) Assessing value co-creation and new product success from cultural orientations and relationship marketing perspectives. Journal of Relationship Marketing 16(1): 21–39.

48.

Tasic

Amir

Tan

, et al. (2019) A multilevel framework to enhance organizational resilience. Journal of Risk Research 23: 2–27.

49.

Tabassum

Shafique

Konstantopoulou

, et al. (2019) Antecedents of women managers’ resilience: a conceptual discussion and implications for HRM. International Journal of Organisational Analysis 27(2): 241–268.

50.

Thomas

(2006) A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation 27: 237–246.

51.

Thornton

Hennerberg

Naudé

(2015) An empirical investigation of network-oriented behaviors in business-to-business markets. Industrial Marketing Management 49: 167–180.

52.

Walker

Holling

Carpenter

, et al. (2004) Resilience, adaptability and transformability in social-ecological systems. Ecology and Society 9(2): 5.

53.

Wided

(2022) Achieving sustainable tourism with dynamic capabilities and resilience factors: a post disaster perspective case of the tourism industry in Saudi Arabia. Cogent Social Sciences 8: 2060539. DOI: 10.1080/23311886.2022.2060539.

54.

Williams

Vorley

(2014) Economic resilience and entrepreneurship: lessons from theSheffield City Region. Entrepreneurship and Regional Development 26: 257–281. DOI: 10.1080/08985626.2014.894129.

55.

Yao

Fabbe-Costes

(2018) Can your measure resilience if you are unable to define it? The analysis of supply network resilience. Supply Chain Forum: An International Journal 19(4): 255–265.