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Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran

Environmental Sciences Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran
Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran 1983969411, Iran
Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, 500123 Brasov, Romania
Australian Centre for Culture, Environment, Society and Space, School of Geography and Sustainable Communities, University of Wollongong, Wollongong, NSW 2522, Australia
Centre for Ecosystem Science, University of New South Wales, Sydney, NSW 2052, Australia
Author to whom correspondence should be addressed.
Sustainability 2022, 14(9), 5508;
Received: 27 March 2022 / Revised: 21 April 2022 / Accepted: 26 April 2022 / Published: 4 May 2022
(This article belongs to the Special Issue Sustainable Tourism and Tourist Satisfaction)


The COVID-19 epidemic has caused unprecedented impacts on the travel and tourism industry. The current study traced the impacts of COVID-19 on tourism in Iran using an “Impact Pathway (IP)” approach to identify impacts and possible mitigation strategies. The results illustrate two main impact pathways: negative impacts along the economic-institutional and socio-cultural dimensions, and positive impacts along the physical-environmental dimension. Using SWOT (strengths, weaknesses, opportunities, and threats) and ANP (analytic network process) models, we identified defensive and review strategies as optimal for increasing resilience against the impacts of COVID-19. These strategies control the threats and weaknesses of negative impacts and enhance the opportunities and strengths emerging from the COVID-19 pandemic for tourism. We use this information to identify optimal strategies for dealing with the impacts of this crisis on tourism. Most prominently among them is the development of an integrated management system that improves the coordination of the response of local government to crisis and that better orchestrates the combined efforts and integration of non-governmental organizations.

1. Introduction

Tourism plays an essential role in the economic, social, and cultural development of many countries. Globally, tourism numbers reached 1.5 billion, generating approximately $1.5 trillion in spending [1]. The main positive effects of tourism include economic benefits such as tax revenues, job creation, or diversification of local economies [2,3,4]. However, the tourism industry is also vulnerable to ‘shock’ like a pandemic or a natural disaster. Tourism is among the most affected sectors by the COVID-19 pandemic, for instance, that has caused a global collapse in tourism demand due to severe disruptions in travel and mobility [5,6,7,8]. Due to air travel suspensions, lockdowns and social distancing protocols implemented worldwide, the tourism sector has been particularly impacted [9]. Current estimates indicate that 75 million jobs in various tourism sectors around the world are in crisis, and the industry has lost more than $2.1 trillion in turnover [10]. According to the latest reports from the World Trade Organization and the World Travel Council, revenue from the industrial tourism section has dropped by a third to $450 billion due to the outbreak of COVID-19. The World Bank report on the economic impacts of the pandemic shows a drastic reduction in personal income, the growth of trade and the GDP of many countries. In addition, literature has emerged that examines the economic and social impacts of COVID-19 on tourism, as well as employee uncertainty and business innovation, and how tourism might look in the future [11,12,13,14]. It should be noted that the COVID-19 has affected each country differently, and the degree of recovery or containment varies as well [15]. In this research, we investigate the impacts of COVID-19 along environmental, social, and economic dimensions using Iran as a case study.
Iran offers unique natural features and attractions that position it as a prime nature-based tourism destination in the world [16]. During the COVID-19 pandemic, all tourism sectors in Iran were affected, just as they were in other developed or developing countries. In Iran, the disruption of domestic and international travel due to COVID-19 and related unemployment have led to a crisis in the tourism industry [17]. According to the Chamber of Commerce, Industries, Mines, and Agriculture of Iran [18], travel decreased by 54% in 2020 compared to the same period in 2019. The employment status of more than 80,000 tourism industry employees has been severely threatened. Accommodation, hospitality offers, air, rail and road transport, cultural, artistic and recreational industries, educational services, and food production have all been directly affected. The National Cultural Heritage, Tourism, and Handicrafts Administration stated that the spread of COVID-19 not only caused the bankruptcy of many tourism agencies, hotels, and restaurants, but it has also imposed expenses of more than $121 million on the tourism sector and resulted in the death of more than 1000 employers. As a result, travel offices, tourism services and facilities, guides, and educational institutions have suffered major economic losses [18]. COVID-19 has also impacted on the social and psychological dimensions of Iran. Issues arising from the pandemic include increasing levels of anxiety among tourists and tourism communities, escalating health problems, increasing levels of social tension, the inability of the government to effectively control the spread of the disease due to the lack of coordination among local government organizations, and an overall decrease in social resilience. However, the spread of COVID-19 has also had noticeable positive impacts on the environment, including a decrease in pollution, waste, the consumption of materials and energy and the deterioration of ecosystems [19,20,21] used for nature-based tourism activities as reported elsewhere [22,23,24].
Impacts and possible mitigation strategies against COVID-19 need to be identified for national strategy development to make countries more resilient to such a crisis in the future, even if each country faces challenges from the pandemic that are unique [25]. In this research, we draw from a tourism expert panel’s expertise to assess the Impact- Pathway (IP) of COVID-19 on the various tourism sectors in Iran. We use this information to identify optimal strategies for dealing with the impacts of this crisis on tourism. Thus, the main questions addressed by this research are: (a) What are the main impacts of COVID-19 on different dimensions of tourism? and (b) What are the optimal strategies for controlling the negative impacts and strengthening the positive ones?

2. Theoretical Background

Tourism as a human-based industry is highly vulnerable to the complex influences of a pandemic [3,4,26,27]. To reveal vulnerabilities, a considerable body of literature has studied the impacts of other pandemics and found pathways of influence on the tourism industry such as by SARS [28], avian influenza [29], Ebola [7,30], and influenza [31].
For instance, Sönmez et al. [32] investigated the effects of COVID-19 on the health and safety of immigrant hospitality workers in the United States. Their results revealed that restrictions and lockdowns have devastated tourism-dependent destinations and displaced millions of vulnerable workers, causing them to lose their livelihoods. Beck & Hensher [33] explained the impact of COVID-19 on travel and home activities in Australia during the bans, such as the reduction in social transitions, increasing virtual and online education, the launch of travel bans and closures of air agencies, closures of cinemas, leisure, and sports centers, and consequently unemployment and economic losses. Sharma et al. [34] studied the revival of the tourism industry in the post COVID-19 era showing that tourism and economic growth depend on various factors, in particular the role of local communities in tourism. Qiu et al. [35] studied the social costs of tourism during the COVID-19 pandemic. They explored residents’ perceptions of the dangers of tourism activities and the sequential social costs and public health risks. Yang et al. [36] stated that welfare policies in response to COVID-19 should be revised to provide financial support in all aspects, including tourism, health, and other affected areas. Their results revealed that hotel, airline, shipping, and rental car sectors had experienced a significant economic loss during the COVID-19 pandemic. Sharma & Nicolau [37] traced the impacts of COVID-19 on travel, tourism, and trade. These studies have identified various impacts of COVID-19 on the tourism industry such unemployment, bankruptcy of businesses, growth of economic pressure on tourism destinations and similar as collated in Table 1 [35,37,38].
In spite of this growing body of literature, research is lacking on practical mitigation strategies to deal with COVID-19 impacts on tourism and related businesses. To address this gap and to present appropriate strategies to control negative impacts of COVID-19 we used an Impact Pathway (IP) approach. This approach is commonly adopted to assess the type and extent of impacts on projects and events such as agricultural [48] aquatic [49]. IP analysis provides a comprehensive evaluation of change processes (from inputs to impacts; Figure 1) influencing projects and events and allows to evaluate analyses (i.e., a process of converting input to impact) and decision-making processes over time. In addition, it accommodates the viewpoints of different stakeholders and incorporates information from a variety of sources. This approach is structural in that it collects and classifies the knowledge available among a group of experts who are sufficiently familiar with the field in question [48]. As shown in Table 1, a list of impacts of COVID-19 on tourism was provided through the examination of previous studies. We have classified this information along 3 dimensions (physical-environmental, socio-cultural, and economic-institutional), 22 variables/fields of impact and 44 indicators (Table 1). As shown in Table 1, COVID-19 can affect multiple tourism variables, including security, employment and income, education, institutions, prices, pollutions, and ecosystems. The present study examined the positive and negative aspects of these variables.

3. Research Methods

3.1. Research Framework

First, the Impact Pathway (IP) was explored to identify and categorize the main impacts of COVID-19 on tourism using an expert panel. Then, the IP approach was employed to develop optimum strategies for managing and mitigating the negative effects and strengthening the positive ones using SWOT (strengths, weaknesses, opportunities, and threats) and ANP (analytic network process) models. The internal (strengths and weaknesses) and external factors (opportunities and threats) were also identified using the viewpoints of experts. The goal was to identify the SWOT factors and integrate quantitative principles for strategic planning. This hybrid model has been applied widely in various study contexts [50,51,52,53] to determine optimal strategies. More details on the study methodology are depicted in Figure 2.

3.2. Research Procedure

The IP approach was used as a tool for logic-based evaluation, which can help prevent some of the shortcomings of other current impact assessment methods. The logical framework of the research shows four links in a simple “impact chain” (Figure 1). The chain concept was used to formulate research strategies and to capture the structure of the impact. A logical sequence of four main stages in the impact chain (input, outputs, outcomes, and impacts) was explored, including several indicators. This process deals with how COVID-19 affects the tourism industry in the stage, which in each stage states what impact the defined indicators have on the environmental-physical, demographic-social and economic-institutional dimensions, and finally these impacts in two directions (i.e., positive and negative) are checked. In the next step, the impacts of COVID-19 on tourism were considered along the physical-environmental, socio-cultural, and economic-institutional dimensions and in conjunction with the different variables and indicators. The IP captures the process that runs from inputs to outputs, and to outcomes and impacts to clarify the causal mechanisms without temporality (i.e., the continuity of the impact, without being temporary or over a short period).
As can be seen in Figure 3, the IP approach is conducted in five steps: determination of the case study; discussion with the actors; construction of the IP narrative and determination of internal and external factors and subfactors; identification and assessment of impact responses and prioritization of indicators using the ANP model; and finally, the validation of the results. Accordingly, the IP was used in five phases as follows:
Iran was identified as the case study because of its abundance of tourist attractions and the growing demand of tourists for natural, historical-archeological, cultural, and religious sites as well as its artificial attractions.
A group of 35 experts in tourism who are familiar with different tourism industry sectors in Iran was selected.
To construct the IP narrative of the COVID-19 impacts on tourism, the strengths, weaknesses, opportunities, and threats were formulated using the SWOT model, and appropriate solutions for dealing with the impacts of COVID-19 were presented. Figure 4 depicts the steps in the development of the SWOT matrix.
The impacts and indicators were identified and assessed with the participation of the expert panel. At this stage, the experts described the kind of change that they perceived as resulting from a specified situation. Then, for each indicator, the experts assessed negative and positive impacts and determined a value from 1 to 5 for each impact (very low, low, moderate, high, and very high). Using the ANP model, the strategies were then prioritized, and the optimal strategy was selected. The ANP model, one of the multi-criteria decision analysis (MCDA) methods, has various advantages, including measuring different criteria based on their relationships, the complexity of other issues, and achieving better results [54]. The ANP procedure is realized through four steps [55,56]: (I) Modeling and converting a problem into a network structure: When the problem is converted into a network structure, the nodes are presented as clusters. The elements within a cluster may be related to one or all other cluster elements. Elements within a cluster may also interact with each other. (II) Establishment of a matrix of pairwise comparisons and determination of priority vectors: At this stage, the decision elements in each cluster are compared based on how important they are for the two-to-two control dimensions. A special vector can represent the impact of each element on other elements. The vector of internal significance indicates the relative importance of elements or clusters. The interdependence between the cluster criteria is also compared and examined according to Table 2. (III) Creation of a supermatrix and conversion into a limited supermatrix: To achieve general priorities into a system with reciprocal impacts, internal priority vectors are entered in the appropriate matrix columns. The result is presented in a supermatrix; each section demonstrates the relationship between the two clusters in a system. The hierarchical analysis process becomes a networking process if the dimensions have reciprocal impacts. The interactions among the dimensions are possible. (IV) Selection of the best alternative: If the supermatrix created in the third step considers the whole network and the options are also included in the supermatrix, the overall priority of the options from the column of options in the supermatrix of the normalized limit will be available. Suppose the supermatrix includes only a portion of the interconnected network, and the options are not considered in the supermatrix. In that case, further calculations are needed to represent the overall priority of the options. The option that has the highest overall priority is ultimately selected as the best option for the subject.
To validate the results, the expert panel met in three rounds. In the first round, indicators extracted from theoretical literature were presented to the experts, and they were asked to express their viewpoints about them. In the second round, experts were prompted to suggest additional indicators, and internal and external factors for the SWOT analysis. In the third round, the total selection of indicators and factors obtained from the panel meetings were presented to the experts. They were asked to express their final viewpoints to reach a consensus. The process concluded with a validation stage to ensure the accuracy of the views where the experts reviewed the final list of impact indicators and factors.
Figure 4. Main steps of the SWOT model.
Figure 4. Main steps of the SWOT model.
Sustainability 14 05508 g004
Table 2. Relative preference values for pairwise comparisons [55].
Table 2. Relative preference values for pairwise comparisons [55].
Intensity of ImportanceDefinition
1Equal importance
3Moderate importance
5Strong importance
7Very strong importance
9Absolute importance
2, 4, 6, 8Intermediate values

4. Results

4.1. Respondent Characteristics

As shown in Table 3, about 62% of the respondents were male and 38% female. Most of the respondents were between 30 and 40 years old (42.9%). In terms of education most of the experts had a M.Sc. degree in tourism-related fields. Overall, 54.3% of the respondents were employed in different tourism sectors. Furthermore, most of the respondents stated that they had 6–10 years of experience in the tourism industry.

4.2. Construction of the Narrative of the IP and Assessment of COVID-19 Impacts

The list of impact indicators was generated using a mixed methodology consisting of a review of theoretical and empirical literature and sourcing expert viewpoints. The panel of experts added 15 indicators to the list of indicators in Table 1, which were categorized into different dimensions and variables. In the physical-environmental dimension, the four indicators of customers in shopping malls and stores, level of theater and cinema usage, level of religious and cultural place usage, and level of local arts and crafts sales in tourism destinations were added to the previous list. Three indicators were added to the socio-cultural dimension, comprising the volume of tourism festivals, level of social resilience, and tourism advertising. Eight indicators were added to the economic-institutional dimension: volume of work of non-government organizations, number of non-government organizations, revenues of non-government organizations, level of employees’ income, level of residents’ welfare in tourism destinations, agro-tourism, nature-based and ecotourism, and urban and rural tourism. Table 4 presents the list of indicators related to different sectors of tourism that have been affected by COVID-19.
Of the 60 indicators 25 indicators captured positive impacts while 35 indicators captured negative impacts. Of these, 17 indicators were rated in the two highest of five classes and evidencing their perception as causing high to very high impacts.
The highest negative impacts of COVID-19 on tourism were perceived along the economic-institutional dimension (coefficient of 4.35), followed by the socio-cultural dimension with a coefficient of 3.43, and the physical-environmental dimension with a coefficient of 2.87. The highest scores of 4.88 were achieved by the following two indicators: “income of employees in different sectors of tourism” and “closure/bankruptcy of tourism businesses”. Conversely, the lowest score of 1.97 was reached by the “average prices of estate and commodities”. According to the results, the highest negative impacts of COVID-19 on tourism dimensions were, respectively, economic-institutional with a coefficient of 4.35, socio-cultural with a coefficient of 3.43, and physical-environmental with a coefficient of 2.87.
A diagram of the IP involved in the relationship between COVID-19 and tourism is presented in Figure 5. This diagram depicts the steps from inputs to outputs to outcomes and finally to direct (impacts 1) and indirect (impacts 2) impacts. COVID-19 is presented as the input that yields 10 outputs, 12 outcomes, 22 direct impacts, and 16 indirect impacts. This reflects the inclusion of only the most important impacts in accordance with expert opinion. We refer to output indicators as those directly influenced by COVID-19 which include: recession in the tourism industry, decrease in travel motivation among tourists, decrease in congestion level of roads and touristic places, and decrease in the number of trips. Indicators affected by outputs were categorized as outcomes which include: low use of tourism infrastructures, such as accommodation, restaurants, shopping malls, etc. Finally, indicators that were the results of outcomes were considered either direct (impacts 1) or indirect (impacts 2) impacts. The most important direct impacts include: a decrease in pollution, decrease in resource consumption, reduction of organizations’ revenues and volume of work, decrease in different types of tourism, and improvement in statuses of ecosystems, society, quality of attractions, and tourists’ behaviors.

4.3. Developing a Response Pathway (RP) Approach to Manage COVID-19 Impacts on Tourism

At this stage of the RP approach, a matrix of internal and external factors and subfactors of the impacts of COVID-19 on tourism was created using the SWOT model with the four components of strengths, weaknesses, opportunities, and threats. First, four components (i.e., strengths, weaknesses, opportunities, and threat) were determined; then, a pairwise comparison of factors and subfactors was performed using the ANP model with the help of the experts (Table 5). The highest score was given to weaknesses, and the lowest score was given to opportunities. Weaknesses reached a score of 0.388 compared to strengths that reached a score of 0.321; and threats with a score of 0.157 compared to opportunities with a score of 0.132.

4.4. Optimal Strategies to Mitigate the Impacts of COVID-19

As shown in Table 6, experts found the SO strategy (Aggressive Strategy), developed by combining strengths and opportunities, sufficiently aggressive; in particular, concentrating on institutional capacity-building and the development of local NGOs in public education on crisis management. These measures can improve both the environmental situation and protect tourist attractions. Moreover, information and communication networks can provide an opportunity to harness the learnings of countries that implement progressive and innovative measures to deal with COVID-19 in tourism destinations. The second strategy is the ST strategy developed by combining strengths and threats. According to ST (Diverse Strategy), it is necessary to use the capacity of local NGOs for public education and support to increase social resilience, further, to reduce economic and financial pressure and bankruptcies, and to develop cooperation among local governments and NGOs in decreasing pollution levels and conserving tourism attractions.
Another solution presented adopts the WO strategy (Review Strategy), which emphasizes revising some rules and regulations to develop institutional cooperation in crisis management and institutional capacity-building to develop education and public awareness in controlling the negative impacts of the COVID-19 crisis. This strategy was created considering weaknesses and opportunities. Other solutions in this regard target decreased pollution levels by controlling travel to tourism destinations, and also harness the learnings of progressive countries and their management of COVID-19. Undoubtedly, one major problem of tourism destinations is the low capacity for adaptation during COVID-19 which renders the development of adaptive management measures as necessary. Finally, the defensive WT strategy considers weaknesses and threats. This strategy attempts to develop institutional cooperation to prevent bankruptcies in businesses and economic pressure on households during the COVID-19 crisis. It also emphasizes the development of an adaptive management system in tourism destinations to decrease the anxiety experienced by government, tourists, and local communities. Indeed, the spread of COVID-19 has created a sense of apprehension among people, and local governments in Iran have not yet controlled this problem. To increase the level of social resilience, increased financial support of households may be necessary and measures that increase employment and income levels of households during this crisis. Further measures that complement this strategy include developing the necessary infrastructure to increase the level of social resilience, and education and public awareness campaigns to deal with COVID-19 impacts on tourism-related occupations and the lives of local households (i.e., controlling the sudden crisis of COVID-19 outbreaks and reducing their effects on public life).
Afterwards, pairwise comparisons were conducted to select the best strategy based on the strengths, weaknesses, opportunities, and threat factors (Table 7).
Building the ANP model helped reveal that the most important strategy for controlling the impacts of COVID-19 on tourism is the WT strategy, with a score of 0.378 (Table 6). The WO strategy is ranked second with a score of 0.321. The ST strategy with a score of 0.265 and the SO strategy with a score of 0.178 are ranked third and fourth, respectively (Figure 6).

4.5. Positive and Negative Impacts of COVID-19 on Tourism

The current study explored the impacts of COVID-19 on tourism along the physical-environmental, socio-cultural, and economic-institutional dimensions using the IP approach. The results highlighted two main impact pathways of COVID-19 in the tourism sector of Iran (Figures S1 and S2). The first pathway addresses the negative impacts of COVID-19, which are frequently manifested in the socio-cultural and economic-institutional dimensions in various forms, such as the recession of many tourism businesses, increased economic and financial pressures on tourism communities, and decreased travel motivation among tourists (Figure S1). The second pathway is the positive impacts of COVID-19, which have occurred mainly in the physical-environmental dimension (Figure S2). In this field, positive impacts include a reduction in different pollutions, improvement of ecosystems and vegetation conditions, and decrease of energy and water consumption.

5. Discussion

Kasare [57] stated that the tourism industry in Asia had suffered enormously from the COVID-19 pandemic, and the pandemic has caused unemployment, bankruptcy, revenue losses, and budget deficits in tourism. The form and nature of tourism offered will likely change post-COVID-19 [58]; hence it is essential to discuss tourism changes post-COVID-19. For this matter, the diverse reasons for the devastating impacts of COVID-19 on the Iranian tourism industry need to be understood. One major reason constitutes the lack of coordination among relevant organizations along with the inferior orchestration of a mitigation response. Relatedly, during the 2003 crisis in Southeast Asia caused by the SARS-CV virus, McKercher and Chon [59] warned how the lack of coordination and the incorrect decisions of those responsible for tourism had a significant impact on tourism flows. One of the lessons learned from that experience is the need for a strong collaboration and coordination at the national and international levels and across all departments involved in the tourism industry [60,61]. The lack of cooperation and institutional weakness has also been investigated by Nicola et al. [6], who substantiated numerous economic and social damages caused by COVID-19 for local communities in their research because of that, including unemployed workforces across all economic sectors and a decrease in the availability of different jobs.
Also, in Iran, local governments failed to implement the necessary safety and health measures for tourists by developing effective health protocols. Robina-Ramírez et al. [60] highlighted that the development of safety protocols plays a key role among tourism authorities and communities to facilitate the recovery process of a tourism destination. Moreover, tourism needs health measures to protect tourists and to create perceptions of safety which contribute to a satisfying visitor experience [62]. Destination and tourism service providers need to be selected carefully for their commitment to be compliant and trained in the implementation of protocols [63].
Furthermore, the low social resilience and adaptation capacity of tourists and local communities in the Iranian workforce have intensified the severity of the crisis. It has previously been shown that policymakers are crucial to achieving disaster resilience in the tourism industry, and effective collaboration among stakeholders is essential for the sustainability and enhancement of resilience [64,65]. Policies need to be implemented to establish workplace safety protocols, which could include providing masks, social distancing, physical workspace modifications, and screening and tracing protocols [66]. Finally, inadequate education, poor infrastructure development, and financial problems have further exacerbated the situation. These are however more complex societal and urban management planning issues that are beyond the discussion of this paper.
Villages and small towns where tourism is a main source of income faced a particular challenging situation without receiving government support. Certainly, the negative impacts of COVID-19 have not been limited to small settlements; many large cities, tourism businesses (such as travel agencies, hotel companies, etc.) have gone bankrupt, and as a result, the number of unemployed community members has increased. In this crisis business owners have faced severe financial problems to the point of no recovery. This problem is not limited to Iran, of course, and has occurred in most countries worldwide as confirmed by other studies [6,67,68,69,70,71]. The social and economic effects of COVID-19 in Iran are mainly negative and in some cases irreparable, which is also consistent with findings elsewhere [36,72,73,74,75].
According to our results, the COVID-19 pandemic had dramatic adverse effects on many tourism businesses in Iran, and similar results were obtained in other countries [70,76,77]. The tourism industry is one of the world’s largest employers and is highly sensitive to the COVID-19 pandemic [78], and due to COVID-19, employment in this sector is decreasing [79]. The tourism and travel industries have and continue to be greatly affected by COVID-19, especially airlines and the retail segments, with very substantial reductions in income and liquidity [37]. Also, our findings showed that one of the most negative impacts of COVID-19 was the decrease in employees’ income across different tourism sectors. COVID-19 impact studies suggest that the loss of income, unemployment, and growing COVID-19 health concerns negatively impact tourism employees’ experience of well-being [80,81,82], and their consumption sentiment and habits [83]. The bankruptcy of tourism businesses is noticeable across all regions of the world [84], similar to our results. For example, Nguyen [85] claimed that large hospitality enterprises are likely to be more resilient to the effects of the pandemic, and small businesses are at a greater risk of closing down and bankruptcy. Also, it has been documented that large airlines worldwide are facing bankruptcy due to the COVID-19 pandemic [86]. Recovery was most easily achieved where financial assistance was provided.
However, some positive impacts of COVID-19 were also noted along the physical-environmental dimension. These include reduced pollution, waste, consumption and deterioration of ecosystem and vegetation conditions due to lower visitation numbers, and consistent with findings elsewhere [5,6,35,70,87,88,89,90]. For example, due to decreased visitor arrivals, lockdowns, curfews, and social distancing, visitation to beaches and other natural spaces around the globe have decreased. Consequently, waste in these places [91], and other environmental issues were reduced [92]. Also, there has been a reduction in noise levels in tourism attractions due to a decrease in transportation use [91]. Moreover, many countries have experienced a reduction in NO2 [93,94,95,96] CO and PM2.5 [94], and better Air Quality Index [97] levels after the lockdown. We showed that tourist behavior was changing due to COVID-19, which is in line with previous findings [98,99,100,101,102]. For example, Kim et al. [101] showed that COVID-19 positively influences biosecurity travel behavior. Also, Parady et al. [103] found that Japanese people adopted self-protective behaviors, such as reducing their ‘eating out’ frequency, travel frequency, and leisure activity participation. Moreover, the lockdown rules have allowed wildlife to freely move in areas once frequented by humans [5] and disturbance of wildlife in national parks was reduced [104]. In line with our findings, LeTourneux et al. [105] found reduced wildlife hunting during the COVID-19 pandemic. At the same time, multiple authors have found that park visitation increased during the pandemic such as Geng et al. [100], which confirms a change in tourist behaviours and the need for more parks and outdoor green areas to equip for future crisis.
In spite of these examples for positive impacts, such changes are likely temporary: as the pandemic ends and industrial and economic activities are being resumed, environmental impacts will follow. Monitoring programs by government and education programs to raise public awareness of tourism impacts are urgently needed in Iran and put in action prior to the resumption of the usual tourism activity to preserve the natural and other heritage of the country that attracts visitors [106]. At least some efforts were made to seize the opportunity of the past year to repair some of the damaged attractions and to develop better services to attract tourists in the future.

6. Conclusions

To develop strategies, the SWOT model was developed to discuss measures to manage the impacts of COVID-19. The results revealed that the WT and WO strategies highlight the need for better institutional cooperation to control the negative impacts of COVID-19 and to strengthen the positive ones. Revising some rules and regulations to develop an integrated management system and to increase institutional cooperation is critical and would enhance a coordinated response of institutions in the face of a crisis. Secondly, adaptive management measures need to be implemented to decrease the anxiety experienced among stakeholders (local governments, tourists, and tourism communities) and to enhance adaptive capabilities. The experience of recent months has revealed that alongside economic damages, public anxiety increased exponentially during the spread of COVID-19, and this issue has affected all aspects of social life. Therefore, the development of an adaptive management program that emphasizes resilience over complexities and uncertainties can mitigate the severity of the negative impacts of the COVID-19 crisis. Local governments must increase their investment in developing such programs, and public education to deliver them, to enhance social resilience and the sense of security felt by tourists and communities. Offering NGOs more opportunities to support the otherwise highly centralized government system of community support in Iran is an important avenue to explore as the pandemic continues. Fostering institutional capacity-building and creating a cooperation platform between government and non-government stakeholders would help with the delivery of education to tourists and local communities and increase their participation in overcoming the crisis. Our research has revealed multi-faceted and insightful findings around the issues we examine. Our attention has been primarily focused on two issues: first, a conceptual one, which is linked to identifying several reasonable and measurable factors associated with identifying impacts and possible mitigation strategies of COVID-19 on tourism; second, proposing a strategy for resilience and adaptation in Iran. While the strategy is specific to Iran, it can also be seen to provide a template against which to plan for the recovery of tourism in other countries. One of the future lines of research will be to analyze the result of our strategies for tourists, the perception of Iran as a tourist destination amongst Middle-East countries, and the recovery of the tourist industry sectors.
Because of the high degree of uncertainty in tourism, our limited understanding of the consequences of actions, and the possibility of a new pandemic, challenges and fears will always exist. Research indicates that the challenges of the pandemic require similar measures to tackling sustainability challenges by fostering resilience, adaptivity, flexibility, collaboration, and co-creation. Despite some limitations, our findings provide a good starting point for further research at a national level. In a few years, it will be possible to reconsider our methodology applied in this article using other indicators and evaluating the COVID-19 impacts on various tourism sectors. It is also suggested to use the same indicators but other MCDA methodologies (e.g., TOPSIS, fuzzy-TOPSIS, fuzzy-AHP, and fuzzy-ANP) to compare the results or develop a ranking system for different countries. Also, our study surveyed national experts that entail potential bias, assuming that participants might be influenced by social desirability. Therefore, future studies could consider sourcing opinions from international focus groups to explore additional avenues of analysis.

Supplementary Materials

The following supporting information can be downloaded at:, Figure S1: Negative impacts of COVID-19 on tourism in Iran; Figure S2: Positive impacts of COVID-19 on tourism in Iran.

Author Contributions

Conceptualization, P.S., H.V. and H.E.; methodology, P.S., H.V., H.E. and S.M.M.S.; software, P.S.; validation, P.S. and H.E.; formal analysis, P.S., H.E. and S.M.M.S.; investigation, P.S. and H.E.; data curation, P.S. and H.E.; visualization, S.M.M.S.; writing—original draft preparation, P.S. and H.V.; writing—review and editing, S.M.M.S., M.V.M. and I.D.W.; supervision, H.E., S.M.M.S. and M.V.M.; funding acquistion, S.M.M.S. and M.V.M. All authors have read and agreed to the published version of the manuscript.


The APC was funded by the Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author (H.E.), upon reasonable request.


Seyed Mohammad Moein Sadeghi’s research at the Transilvania University of Brasov, Romania, has been supported by the program entitled “Transilvania Fellowship for Postdoctoral Research/Young Researchers. The authors would like to thank the three anonymous reviewers.

Conflicts of Interest

The authors declare no conflict of interest.


  1. UNWTO. World Tourism Barometer; UNWTO: Madrid, Spain, 2016. [Google Scholar]
  2. Sobhani, P.; Esmaeilzadeh, H.; Sadeghi, S.M.M.; Marcu, M.V. Estimation of Ecotourism Carrying Capacity for Sustainable Development of Protected Areas in Iran. Int. J. Environ. Res. Public Health 2022, 19, 1059. [Google Scholar] [CrossRef] [PubMed]
  3. Jordan, E.J.; Spencer, D.M.; Prayag, G. Tourism Impacts, Emotions and Stress. Ann. Tour. Res. 2019, 75, 213–226. [Google Scholar] [CrossRef]
  4. Nunkoo, R.; Ramkissoon, H. Small Island Urban Tourism: A Residents’ Perspective. Curr. Issues Tour. 2010, 13, 37–60. [Google Scholar] [CrossRef]
  5. Lokhandwala, S.; Gautam, P. Indirect Impact of COVID-19 on Environment: A Brief Study in Indian Context. Environ. Res. 2020, 188, 109807. [Google Scholar] [CrossRef]
  6. Naramski, M.; Szromek, A.R.; Herman, K.; Polok, G. Assessment of the Activities of European Cultural Heritage Tourism Sites during the COVID-19 Pandemic. J. Open Innov. Technol. Mark. Complex. 2022, 8, 55. [Google Scholar] [CrossRef]
  7. Novelli, M.; Burgess, L.G.; Jones, A.; Ritchie, B.W. ‘No Ebola … Still Doomed’—The Ebola-Induced Tourism Crisis. Ann. Tour. Res. 2018, 70, 76–87. [Google Scholar] [CrossRef]
  8. Higgins-Desbiolles, F.; Bigby, B.C.; Doering, A. Socialising Tourism After COVID-19: Reclaiming Tourism as a Social Force? J. Tour. Futures 2021, 1–12. [Google Scholar] [CrossRef]
  9. Rogerson, C.M.; Baum, T. COVID-19 and African Tourism Research Agendas. Develop. S. Afr. 2020, 37, 727–741. [Google Scholar] [CrossRef]
  10. Candia, S.; Pirlone, F. Tourism Environmental Impacts Assessment to Guide Public Authorities towards Sustainable Choices for the Post-COVID Era. Sustainability 2022, 14, 18. [Google Scholar] [CrossRef]
  11. Carr, A. COVID-19, Indigenous Peoples and Tourism: A View from New Zealand. Tour. Geogr. 2020, 22, 491–502. [Google Scholar] [CrossRef]
  12. Dube, K.; Nhamo, G.; Chikodzi, D. COVID-19 pandemic and prospects for recovery of the global aviation industry. J. Air Transp. Manag. 2021, 92, 102022. [Google Scholar] [CrossRef]
  13. Foo, L.-P.; Chin, M.-Y.; Tan, K.-L.; Phuah, K.-T. The Impact of COVID-19 on Tourism Industry in Malaysia. Curr. Issues Tour. 2021, 24, 2735–2739. [Google Scholar] [CrossRef]
  14. Aronica, M.; Pizzuto, P.; Sciortino, C. COVID-19 and Tourism: What Can We Learn from the Past? World Econ. 2022, 45, 430–444. [Google Scholar] [CrossRef]
  15. Li, Z.; Zhang, X.; Yang, K.; Singer, R.; Cui, R. Urban and Rural Tourism Under COVID-19 in China: Research on the Recovery Measures and Tourism Development. Tour. Rev. 2021, 76, 718–736. [Google Scholar] [CrossRef]
  16. Komasi, H.; Hashemkhani Zolfani, S.; Cavallaro, F. The COVID-19 Pandemic and Nature-Based Tourism, Scenario Planning Approach (Case Study of Nature-Based Tourism in Iran). Sustainability 2022, 14, 3954. [Google Scholar] [CrossRef]
  17. Masaeli, A.; Rezaei, N.; Derafshi, K.; Basakha, M. Effects of Corona Epidemic on Labor Employment in Iran’s Tourism-Related Industries. Tour. Manag. Stud. 2022, 16, 279–308. [Google Scholar]
  18. Anonymous. Economic Effects of Coronavirus on Tourism Industry of Iran. Tehran; Research Center of Iran Chamber of Commerce, Industries, Mines and Agriculture: Tehran, Iran, 2021; Available online: (accessed on 25 December 2021).
  19. Babbitt, C.W.; Babbitt, G.A.; Oehman, J.M. Behavioral Impacts on Residential Food Provisioning, Use, and Waste During the COVID-19 Pandemic. Sustain. Prod. Consump. 2021, 28, 315–325. [Google Scholar] [CrossRef]
  20. Berman, J.D.; Ebisu, K. Changes in US Air Pollution During the COVID-19 Pandemic. Sci. Total Environ. 2020, 739, 139864. [Google Scholar] [CrossRef]
  21. Kang, H.; An, J.; Kim, H.; Ji, C.; Hong, T.; Lee, S. Changes in Energy Consumption According to Building Use Type Under COVID-19 Pandemic in South Korea. Renew. Sustain. Energy Rev. 2021, 148, 111294. [Google Scholar] [CrossRef]
  22. Corlett, R.T.; Primack, R.B.; Devictor, V.; Maas, B.; Goswami, V.R.; Bates, A.E.; Koh, L.P.; Regan, T.J.; Loyola, R.; Pakeman, R.J. Impacts of the Coronavirus Pandemic on Biodiversity Conservation. Biol. Conserv. 2020, 246, 108571. [Google Scholar] [CrossRef]
  23. Smith, M.K.S.; Smit, I.P.; Swemmer, L.K.; Mokhatla, M.M.; Freitag, S.; Roux, D.J.; Dziba, L. Sustainability of Protected Areas: Vulnerabilities and Opportunities as Revealed by COVID-19 in a National Park Management Agency. Biol. Conserv. 2021, 255, 108985. [Google Scholar] [CrossRef]
  24. Orden-Mejía, M.; Carvache-Franco, M.; Huertas, A.; Carvache-Franco, W.; Landeta-Bejarano, N.; Carvache-Franco, O. Post-COVID-19 Tourists’ Preferences, Attitudes and Travel Expectations: A Study in Guayaquil, Ecuador. Int. J. Environ. Res. Public Health 2022, 19, 4822. [Google Scholar] [CrossRef] [PubMed]
  25. Jones, P. A Review of the UK’s Tourism Recovery Plans Post COVID-19. Athens J. Tour. 2022, 9, 9–18. [Google Scholar] [CrossRef]
  26. Martínez-Garcia, E.; Raya, J.M.; Majó, J. Differences in Residents’ Attitudes Towards Tourism Among Mass Tourism Destinations. Int. J. Tour. Res. 2017, 19, 535–545. [Google Scholar] [CrossRef][Green Version]
  27. Milman, A.; Pizam, A. Social Impacts of Tourism on Central Florida. Ann. Tour. Res. 1988, 15, 191–204. [Google Scholar] [CrossRef]
  28. Dombey, O. The Effects of SARS on the Chinese Tourism Industry. J. Vacat. Mark. 2004, 10, 4–10. [Google Scholar] [CrossRef]
  29. Rittichainuwat, B.N.; Chakraborty, G. Perceived Travel Risks Regarding Terrorism and Disease: The Case of Thailand. Tour. Manag. 2009, 30, 410–418. [Google Scholar] [CrossRef]
  30. Cahyanto, I.; Wiblishauser, M.; Pennington-Gray, L.; Schroeder, A. The Dynamics of Travel Avoidance: The Case of Ebola in the US. Tour. Manag. Perspect. 2016, 20, 195–203. [Google Scholar] [CrossRef]
  31. Page, S.; Yeoman, I.; Munro, C.; Connell, J.; Walker, L. A Case Study of Best Practice—Visit Scotland’s Prepared Response to An Influenza Pandemic. Tour. Manag. 2006, 27, 361–393. [Google Scholar] [CrossRef]
  32. Sönmez, S.; Apostolopoulos, Y.; Lemke, M.K.; Hsieh, Y.-C.J. Understanding the Effects of COVID-19 on the Health and Safety of Immigrant Hospitality Workers in the United States. Tour. Manag. Perspect. 2020, 35, 100717. [Google Scholar] [CrossRef]
  33. Beck, M.J.; Hensher, D.A. Insights into the Impact of COVID-19 on Household Travel and Activities in Australia–The Early Days Under Restrictions. Transp. Policy 2020, 96, 76–93. [Google Scholar] [CrossRef] [PubMed]
  34. Sharma, G.D.; Thomas, A.; Paul, J. Reviving Tourism Industry Post-COVID-19: A Resilience-Based Framework. Tour. Manag. Perspect. 2021, 37, 100786. [Google Scholar] [CrossRef] [PubMed]
  35. Qiu, R.T.; Park, J.; Li, S.; Song, H. Social Costs of Tourism During the COVID-19 Pandemic. Ann. Tour. Res. 2020, 84, 102994. [Google Scholar] [CrossRef] [PubMed]
  36. Yang, Y.; Zhang, H.; Chen, X. Coronavirus Pandemic and Tourism: Dynamic Stochastic General Equilibrium Modeling of Infectious Disease Outbreak. Ann. Tour. Res. 2020, 83, 102913. [Google Scholar] [CrossRef] [PubMed]
  37. Sharma, A.; Nicolau, J.L. An Open Market Valuation of the Effects of COVID-19 on the Travel and Tourism Industry. Ann. Tour. Res. 2020, 83, 102990. [Google Scholar] [CrossRef]
  38. Sigala, M. Social Media and Crisis Management in Tourism: Applications and Implications for Research. Inf. Technol. Tour. 2011, 13, 269–283. [Google Scholar] [CrossRef]
  39. Lin, J.C.; Lin, H.H.; Lu, S.Y.; Chien, J.H.; Shen, C.C. Research on the Current Situation of Rural Tourism in Southern Fujian in China After the COVID-19 Epidemic. Open Geosci. 2022, 14, 24–43. [Google Scholar] [CrossRef]
  40. Hall, C.M. Tourism Planning; Policies, Processes and Relationships; Person Education Limited: Edinburg Gate, UK, 2000. [Google Scholar]
  41. Shokouei, H.; Movahed, A. Understanding the Pattern of Tourist Space in Isfahan Using GIS System. Space Plan. 2002, 6, 95–114. [Google Scholar]
  42. Lee, C.-C.; Chang, C.-P. Tourism Development and Economic Growth: A Closer Look at Panels. Tour. Manag. 2008, 29, 180–192. [Google Scholar] [CrossRef]
  43. Inskeep, E. Tourism Planning: An Integrated and Sustainable Development Approach; John Wiley & Sons: Hoboken, NJ, USA, 1991. [Google Scholar]
  44. Taghvayi, M.; Akbari, M. An Introduction to Urban Tourism Planning and Management; Payam Alavi: Isfahan, Iran, 2008. [Google Scholar]
  45. Shamaei, A.; Musivand, A.J. Leveling of Isfahan Cities in Terms of Tourism Infrastructure Using TOPSIS and AHP Models. J. Urban Stud. Res. 2009, 3, 37–58. [Google Scholar]
  46. Zheng, Y.; Goh, E.; Wen, J. The Effects of Misleading Media Reports About COVID-19 on Chinese Tourists’ Mental Health: A Perspective Article. Anatolia 2020, 31, 337–340. [Google Scholar] [CrossRef][Green Version]
  47. Tucker, H. Coronavirus Bankruptcy Tracker: These Major Companies are Failing Amid the Shutdown. Forbes. 2020. Available online: (accessed on 17 December 2021).
  48. Springer-Heinze, A.; Hartwich, F.; Henderson, J.S.; Horton, D.; Minde, I. Impact Pathway Analysis: An Approach to Strengthening the Impact Orientation of Agricultural Research. Agric. Syst. 2003, 78, 267–285. [Google Scholar] [CrossRef]
  49. Briones, M.; Dey, M.; Ahmed, M.; Stobutzki, I.; Prein, M.; Acosta, B. Impact Pathway Analysis for Research Planning: The Case of Aquatic Resources Research in the WorldFish Center. NAGA WorldFish Cent. Quart 2004, 27, 51–55. [Google Scholar]
  50. Kurttila, M.; Pesonen, M.; Kangas, J.; Kajanus, M. Utilizing the analytic hierarchy process (AHP) in SWOT analysis—A hybrid method and Its Application to a Forest-Certification Case. For. Policy Econ. 2000, 1, 41–52. [Google Scholar] [CrossRef]
  51. Kajanus, M.; Kangas, J.; Kurttila, M. The Use of Value Focused Thinking and the A’WOT Hybrid Method in Tourism Management. Tour. Manag. 2004, 25, 499–506. [Google Scholar] [CrossRef]
  52. Kangas, J.J.; Kajanus, M.; Leskinen, P.; Kurttila, M. Incorporating MCDS and Voting Into SWOT–Basic Idea and Experiences. Serbian J. Manag. 2016, 11, 1–13. [Google Scholar] [CrossRef][Green Version]
  53. Arsić, S.; Nikolić, D.; Živković, Ž. Hybrid SWOT-ANP-FANP Model for Prioritization Strategies of Sustainable Development of Ecotourism in National Park Djerdap, Serbia. For. Policy Econ. 2017, 80, 11–26. [Google Scholar] [CrossRef]
  54. Hadiwijaya, N.A.; Hamdani, H.; Syafrianto, A.; Tanjung, Z. The decision model for selection of tourism site using analytic network process method. Int. J. Intell. Syst. Appl. 2018, 9, 23–31. [Google Scholar] [CrossRef]
  55. Saaty, T.L. Decision Making with Dependence and Feedback: The Analytic Network Process; RWS Publications: Pittsburgh, PA, USA, 1996; p. 370. [Google Scholar]
  56. Zhang, J.; Zhang, Y. Assessing the Low-Carbon Tourism in the Tourism-Based Urban Destinations. J. Clean. Prod. 2020, 276, 124303. [Google Scholar] [CrossRef]
  57. Kasare, K.S. Effects of coronavirus disease (COVID-19) on Tourism Industry of India. Stud. Indian Place Names 2020, 40, 362–365. [Google Scholar]
  58. Zhu, H.; Deng, F. How to Influence Rural Tourism Intention by Risk Knowledge During COVID-19 Containment in China: Mediating Role of Risk Perception and Attitude. Int. J. Environ. Res. Public Health 2020, 17, 3514. [Google Scholar] [CrossRef] [PubMed]
  59. McKercher, B.; Chon, K. The Over-Reaction to SARS and the Collapse of Asian Tourism. Ann. Tour. Res. 2004, 31, 716. [Google Scholar] [CrossRef] [PubMed]
  60. Robina-Ramírez, R.; Sánchez, M.S.-O.; Jiménez-Naranjo, H.V.; Castro-Serrano, J. Tourism Governance During the COVID-19 Pandemic Crisis: A Proposal for A Sustainable Model to Restore the Tourism Industry. Environ. Dev. Sustain. 2021, 24, 1–22. [Google Scholar] [CrossRef] [PubMed]
  61. Toubes, D.R.; Araújo Vila, N.; Fraiz Brea, J.A. Changes in Consumption Patterns and Tourist Promotion After the COVID-19 Pandemic. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 1332–1352. [Google Scholar] [CrossRef]
  62. Rahman, M.K.; Gazi, M.A.I.; Bhuiyan, M.A.; Rahaman, M.A. Effect of COVID-19 Pandemic on Tourist Travel Risk and Management Perceptions. PLoS ONE 2021, 16, e0256486. [Google Scholar] [CrossRef]
  63. Mirzaei, R.; Sadin, M.; Pedram, M. Tourism and COVID-19: Changes in Travel Patterns and Tourists’ Behavior in Iran. J. Tour. Futures 2021, in press. [Google Scholar] [CrossRef]
  64. Filimonau, V.; De Coteau, D. Tourism Resilience in the Context of Integrated Destination and Disaster Management (DM2). Int. J. Tour. Res. 2020, 22, 202–222. [Google Scholar] [CrossRef][Green Version]
  65. Altshuler, A.; Schmidt, J. Does and How Resilience Matter? Global Implications for the Tourism Industry in the Context of COVID-19. Worldw. Hosp. Tour. Themes 2021, 13, 431–436. [Google Scholar]
  66. Shivakoti, A. Impact of COVID-19 on Tourism in Nepal. Gaze J. Tour. Hospital 2021, 12, 1–22. [Google Scholar] [CrossRef]
  67. Sigala, M.; Dolnicar, S. Chapter 7 Entrepreneurship Opportunities; Dolnicar, S., Ed.; Goodfellow Publishers: Oxford, UK, 2017. [Google Scholar] [CrossRef]
  68. Higgins-Desbiolles, F. Socialising Tourism for Social and Ecological Justice After COVID-19. Tour. Geogr. 2020, 22, 610–623. [Google Scholar] [CrossRef][Green Version]
  69. Norouzi, N.; de Rubens, G.Z.; Choupanpiesheh, S.; Enevoldsen, P. When Pandemics Impact Economies and Climate Change: Exploring the Impacts of COVID-19 on Oil and Electricity Demand in China. Energy Res. Soc. Sci. 2020, 68, 101654. [Google Scholar] [CrossRef] [PubMed]
  70. Sigala, M. Tourism and COVID-19: Impacts and Implications for Advancing and Resetting Industry and Research. J. Bus. Res. 2020, 117, 312–321. [Google Scholar] [CrossRef] [PubMed]
  71. Zenker, S.; Kock, F. The Coronavirus Pandemic–A Critical Discussion of a Tourism Research Agenda. Tour. Manag. 2020, 81, 104164. [Google Scholar] [CrossRef] [PubMed]
  72. Catterberg, G.; Moreno, A. The Individual Bases of Political Trust: Trends in New and Established Democracies. Int. J. Public Opin. Res. 2006, 18, 31–48. [Google Scholar] [CrossRef][Green Version]
  73. Fong, L.H.N.; Law, R.; Ye, B.H. Outlook of Tourism Recovery Amid an Epidemic: Importance of Outbreak Control by the Government. Ann. Tour. Res. 2020, 86, 102951. [Google Scholar] [CrossRef]
  74. Uğur, N.G.; Akbıyık, A. Impacts of COVID-19 on Global Tourism Industry: A Cross-Regional Comparison. Tour. Manag. Perspec. 2020, 36, 100744. [Google Scholar] [CrossRef]
  75. Uslaner, E.M. Trust and the Economic Crisis of 2008. Corp. Reput. Rev. 2010, 13, 110–123. [Google Scholar] [CrossRef]
  76. OECD. Mitigating the Impact of COVID-19 on Tourism and Supporting Recovery. OECD Tourism Papers N° 2020/03; OECD Publishing: Paris, France, 2020. [Google Scholar]
  77. Arbulú, I.; Razumova, M.; Rey-Maquieira, J.; Sastre, F. Can Domestic Tourism Relieve the COVID-19 Tourist Industry Crisis? The Case of Spain. J. Destin. Mark. Manag. 2021, 20, 100568. [Google Scholar] [CrossRef]
  78. Chang, C.L.; McAleer, M.; Ramos, V. A Charter for Sustainable Tourism After COVID-19. Sustainability 2020, 12, 3671. [Google Scholar] [CrossRef]
  79. Pham, T.D.; Dwyer, L.; Su, J.-J.; Ngo, T. COVID-19 Impacts of Inbound Tourism on Australian Economy. Ann. Tour. Res. 2021, 88, 103179. [Google Scholar] [CrossRef]
  80. Carnevale, J.B.; Hatak, I. Employee Adjustment and Well-Being in the Era of COVID-19: Implications for Human Resource Management. J. Bus. Res. 2020, 116, 183–187. [Google Scholar] [CrossRef] [PubMed]
  81. McGuire, D.; Germain, M.-L.; Reynolds, K. Reshaping HRD in Light of the COVID-19 Pandemic: An Ethics of Care Approach. Adv. Dev. Hum. Resour. 2021, 23, 26–40. [Google Scholar] [CrossRef]
  82. Peterson, R.R.; DiPietro, R.B. Exploring the Impact of the COVID-19 Pandemic on the Perceptions and Sentiments of Tourism Employees: Evidence from a Small Island Tourism Economy in the Caribbean. Int. Hospital Rev. 2021, 35, 156–170. [Google Scholar] [CrossRef]
  83. Martins, A.; Riordan, T.; Dolnicar, S. A Post-COVID-19 Model of Tourism and Hospitality Workforce Resilience. socarXiv 2020. Available online: (accessed on 17 December 2021).
  84. Huynh, D.V.; Truong, T.T.K.; Duong, L.H.; Nguyen, N.T.; Dao, G.V.H.; Dao, C.N. The COVID-19 Pandemic and Its Impacts on Tourism Business in a Developing City: Insight from Vietnam. Economies 2021, 9, 172. [Google Scholar] [CrossRef]
  85. Nguyen, K.T.T. Safety Plan During COVID-19 Pandemic in Restaurant Industry: Case Study: KOKORO Sushi; Laurea University: Vantaa, Finland, 2020. [Google Scholar]
  86. Dube, K.; Nhamo, G.; Chikodzi, D. COVID-19 Cripples Global Restaurant and Hospitality Industry. Curr. Issues Tour. 2021, 24, 1487–1490. [Google Scholar] [CrossRef]
  87. Hall, C.M. Publish and Perish? Bibliometric Analysis, Journal Ranking and the Assessment of Research Quality in Tourism. Tour. Manag. 2011, 32, 16–27. [Google Scholar] [CrossRef]
  88. Imani Jajarmi, H. Social Consequences of Coronavirus Outbreak in Iranian Society. Sci. Quart. Soc. Imp. Assess. 2020, 2, 5553859. [Google Scholar]
  89. Nicola, M.; Alsafi, Z.; Sohrabi, C.; Kerwan, A.; Al-Jabir, A.; Iosifidis, C.; Agha, M.; Agha, R. The Socio-Economic Implications of the Coronavirus Pandemic (COVID-19): A Review. Int. J. Surg. 2020, 78, 185–193. [Google Scholar] [CrossRef]
  90. Lenart-Boroń, A.M.; Boroń, P.M.; Prajsnar, J.A.; Guzik, M.W.; Żelazny, M.S.; Pufelska, M.D.; Chmiel, M.J. COVID-19 Lockdown Shows How Much Natural Mountain Regions Are Affected by Heavy Tourism. Sci. Total Environ. 2022, 806, 151355. [Google Scholar] [CrossRef]
  91. Zambrano-Monserrate, M.A.; Ruano, M.A.; Sanchez-Alcalde, L. Indirect Effects of COVID-19 on the Environment. Sci. Total Environ. 2020, 728, 138813. [Google Scholar] [CrossRef] [PubMed]
  92. Bhuiyan, M.A.H.; Hassan, S.; Darda, M.A.; Habib, M.W. Aspects of Sustainable Tourism Development and COVID-19 Pandemic. Preprints 2020, 2020080418. [Google Scholar]
  93. Gautam, S. COVID-19: Air Pollution Remains Low as People Stay at Home. Air Qual. Atmos. Health 2020, 13, 853–857. [Google Scholar] [CrossRef] [PubMed]
  94. Sharma, S.; Zhang, M.; Gao, J.; Zhang, H.; Kota, S.H. Effect of Restricted Emissions During COVID-19 on Air Quality in India. Sci. Total Environ. 2020, 728, 138878. [Google Scholar] [CrossRef] [PubMed]
  95. Tobías, A.; Carnerero, C.; Reche, C.; Massagué, J.; Via, M.; Minguillón, M.C.; Alastuey, A.; Querol, X. Changes in Air Quality During the Lockdown in Barcelona (Spain) One Month Into the SARS-CoV-2 Epidemic. Sci. Total Environ. 2020, 726, 138540. [Google Scholar] [CrossRef]
  96. Wang, Q.; Su, M. A Preliminary Assessment of the Impact of COVID-19 on Environment—A Case Study of China. Sci Total Environ. 2020, 728, 138915. [Google Scholar] [CrossRef]
  97. He, G.; Pan, Y.; Tanaka, T. The Short-Term Impacts of COVID-19 Lockdown on Urban Air Pollution in China. Nat. Sustain. 2020, 3, 1005–1011. [Google Scholar] [CrossRef]
  98. de Bruin, W.B.; Bennett, D. Relationships Between Initial COVID-19 Risk Perceptions and Protective Health Behaviors: A National Survey. Am. J. Prev. Med. 2020, 59, 157–167. [Google Scholar] [CrossRef]
  99. Wen, J.; Kozak, M.; Yang, S.; Liu, F. COVID-19: Potential Effects on Chinese Citizens’ Lifestyle and Travel. Tour. Rev. 2020, 76, 74–87. [Google Scholar] [CrossRef]
  100. Geng, D.C.; Innes, J.; Wu, W.; Wang, G. Impacts of COVID-19 Pandemic on Urban Park Visitation: A Global Analysis. J. For. Res. 2021, 32, 553–567. [Google Scholar] [CrossRef]
  101. Kim, M.J.; Bonn, M.; Hall, C.M. Traveler Biosecurity Behavior During the COVID-19 Pandemic: Effects of Intervention, Resilience, and Sustainable Development Goals. J. Travel Res. 2021. [Google Scholar] [CrossRef]
  102. El-Said, O.; Aziz, H. Virtual Tours a Means to An End: An Analysis of Virtual Tours’ Role in Tourism Recovery Post COVID-19. J. Travel Res. 2022, 61, 528–548. [Google Scholar] [CrossRef]
  103. Parady, G.; Taniguchi, A.; Takami, K. Analyzing Risk Perception and Social Influence Effects on Self-Restriction Behavior in Response to the COVID-19 Pandemic in Japan: First Results. Transp. Res. Interdiscip. Perspect. 2020, 7, 100181. [Google Scholar] [CrossRef]
  104. Sumanapala, D.; Wolf, I.D. The Changing Face of Wildlife Tourism During the COVID-19 Pandemic: An Opportunity to Strive Towards Sustainability? Curr. Issues Tour. 2022, 25, 357–362. [Google Scholar] [CrossRef]
  105. LeTourneux, F.; Grandmont, T.; Dulude-de Broin, F.; Martin, M.-C.; Lefebvre, J.; Kato, A.; Bêty, J.; Gauthier, G.; Legagneux, P. COVID19-Induced Reduction in Human Disturbance Enhances Fattening of an Overabundant Goose Species. Biol. Conserv. 2021, 255, 108968. [Google Scholar] [CrossRef] [PubMed]
  106. Heydari Chianeh, R.; Nasrollahzadeh, Z.; Abdollahi, M. An Evaluation of Tourism Higher Education in Iran Based on SWOT Model. J. Tour. Plan. Dev. 2012, 1, 129–152. [Google Scholar]
Figure 1. The logical framework of the research.
Figure 1. The logical framework of the research.
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Figure 2. The process of research.
Figure 2. The process of research.
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Figure 3. Main steps of the impact pathway (IP) approach.
Figure 3. Main steps of the impact pathway (IP) approach.
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Figure 5. Impact Pathways (IPs) involved in the relationship between COVID-19 and tourism.
Figure 5. Impact Pathways (IPs) involved in the relationship between COVID-19 and tourism.
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Figure 6. Selection of the best strategy.
Figure 6. Selection of the best strategy.
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Table 1. List of dimensions, variables (fields of impact), and indicators of COVID-19 impacts on tourism and sources of published literature.
Table 1. List of dimensions, variables (fields of impact), and indicators of COVID-19 impacts on tourism and sources of published literature.
Physical-environmentalEnvironmental pollutionsLevel of water resource pollution[39,40,41,42]
Level of soil pollution and erosion
Level of air pollution
Level of noise pollution and noise intensity in tourist destinations
Level of visual pollution
EcosystemsCondition of mountains, forests, and deserts
Animals’ habitatsLevel of wildlife hunting
Level of habitat destruction
VegetationQuantitative and qualitative
status of vegetation
Resources consumptionLevel of energy consumption and types of fuels
Level of water resource consumption
Waste and sewage productionAmount of waste produced in tourist destinations
Quality of environmental resources and climateQuality of water, soil and air resources
SafetyNumber of accidents
Accommodation and food servicesUsage level of accommodations outside of nature (hotels, inns, and guesthouses)
Usage level of accommodations inside of nature (forest residences)
Number of restaurant customers
Infrastructure and tourism facilitiesLevel of highway cost and toll services
Level of information and communication networks (internet, social networks, telephone, newspapers, etc.)
Level of parking lot usage
Socio-culturalTourism attractions and activitiesLevel of protection for natural attractions[36,38,39,40,41,42,43,44,45,46]
Level of protection for cultural and religious attractions
Level of protection for historical and ancient attractions
Level of protection for man-made attractions
TransportationNumber of air trips
Number of vehicle trips
Number of rail trips (train and metro)
Number of sea voyages
Number of freight and transit trips
PsychicTravel motivation among tourists
Level of economic pressure among households
SecurityLevel of social security against crime and conflict
BehaviorLevel of change in tourists’ behavior
TrafficLevel of congestion in roads and public places
Education and informationLevel of services and educational programs
Level of information about tourism activities of different sites
Economic—institutionalInstitutional elementsThe volume of government agencies working in tourism[35,39,41,44,45,47]
Revenues of government institutions
Employment and incomeClosure/bankruptcy of tourism businesses
Number of employers in different sectors of tourism
Plans and projectsThe volume of tourism plans and projects
Economic diversityVolume of activities about tourism industries
Volume of activities about tourism-related services
Local pricesAverage price of estate and commodities
Table 3. Descriptive profile of the respondents.
Table 3. Descriptive profile of the respondents.
CharacteristicsFrequency (n) (Total n = 35)Percentage
AgeLess than 30514.28
30–40 1542.85
40–50 822.57
EducationBachelor’s degree1234.29
M.Sc. degree1542.86
Ph.D. degree822.85
EmploymentEmployed in different sectors of tourism1954.28
Employed in non-tourism sectors1028.57
Experience in tourism6–10 years2160.00
10–20 years925.72
More than 20 years514.28
Table 4. The values and means of indicators of impacts.
Table 4. The values and means of indicators of impacts.
DimensionsVariablesIndicators of ImpactsIndicators ValueImpact TypeImpact Range
Physical-environmental (average impacts of dimensions = 2.87)Environmental pollutionsLevel of water resource pollution2.94PM
Level of soil pollution and erosion2.91PM
Level of air pollution2.97PM
Level of noise pollution and noise intensity in tourist destinations2.77PM
Level of visual pollution2.74PM
EcosystemsCondition of mountains, forests, and deserts2.88PM
Animals’ habitatsLevel of wildlife hunting3.42PH
Level of habitat destruction3.17PH
VegetationQuantitative and qualitative status of vegetation2.97PM
Resource consumptionLevel of energy consumption and types of fuels2.91PM
Level of water resources consumption3.11PH
Waste and sewage productionAmount of wastes for tourist destinations2.42PM
Amount of effluents and sewages for tourist destinations2.40PM
Quality of environmental resources and climateQuality of water, soil, and air resources3.20PH
SafetyLevel of accidents2.42PM
Accommodation and food servicesLevel of accommodation usage (hotels, inns, and guesthouses)3.34NH
Usage level of villas and forest residences3.51NH
Number of restaurant customers3.40NH
Level of shopping malls and stores customers3.68NH
Infrastructure and tourism facilitiesLevel of highways’ cost and toll services2.45PM
Level of information and communication networks (internet, social networks, telephone, newspapers, etc.)2.62PM
Level of theaters and cinemas usage2.42NM
Level of religious and cultural places usage2.57NM
Level of parking lot usage2.14NM
Level of local arts and crafts sales in tourism destinations2.62NM
Socio-cultural (average impacts of dimensions = 3.43)Tourist attractions and activitiesLevel of natural attractions’ protection3.22PH
Level of cultural and religious attractions’ protection2.88PM
Level of historical and ancient attractions’ protection2.88PM
Level of man-made attractions’ protection2.77PM
The volume of tourism festivals2.65NM
TransportationNumber of air trips3.48NH
Number of road cars trips3.28NH
Number of rail trips (train and metro)3.34NH
Number of sea voyages3.37NH
Number of freight and transit trips3.20NH
PsychicTravel motivation among tourists3.22NH
Level of economic pressure among households4.22NVH
SecurityLevel of social security against crime and conflict3.88PH
BehaviorLevel of change in tourists behavior3.94PH
Level of social resilience4.20NVH
TrafficLevel of congestion in roads and public places4.02PVH
Education and informationLevel of services and educational programs3.77NH
Level of information about tourism activities of different sites3.25NH
Tourism advertising3.65NH
Economic-institutional (average impacts of dimensions = 4.35)Institutional elementsThe volume of governmental agencies’ work in relation to tourism4.34NVH
Revenues of governmental institutions4.28NVH
The volume of non-governmental organizations’ work (tourism agencies, NGOs, local associations and councils, etc.)4.57NVH
Number of non-governmental organizations4.22NVH
Level of non-governmental organizations revenues4.54NVH
Employment and incomeClosure/bankruptcy of tourism businesses4.88NVH
Number of employers in different sectors of tourism4.74NVH
Level of employees’ income in different sectors of tourism4.88NVH
Level of the residents’ welfare of tourist destinations4.22NVH
Plans and projectsThe volume of tourism plans and projects4.45NVH
Economic diversityVolume of activities about tourism industries4.68NVH
Volume of activities about tourism-related services4.54NVH
Level of agro-tourism development4.34NVH
Level of nature-based and ecotourism development4.77NVH
Level of urban and rural tourism development4.22NVH
Local pricesAverage prices of estate and commodities1.97PL
Type of impact: P = Positive, N = Negative; Range of impact: VL (Very low) = range of values from 0–1; L (Low) = range of values from 1–2; M (Moderate) = range of values from 2–3; H (High) = range of values from 3–4; VH (Very high) = range of values from 4–5.
Table 5. Weighting of factors and sub factors of the SWOT matrix.
Table 5. Weighting of factors and sub factors of the SWOT matrix.
Internal FactorsFactors WeightSWOT SubfactorsSubfactor WeightFinal Weight
Strengths0.321S1: Existence of local NGOs in public education and crisis management0.1980.063
S2: Low level of environmental pollution0.1920.061
S3: Low level of traffic and population density in tourism destinations0.1750.056
S4: Improvements the protection of tourism attractions (natural, cultural and religious, historical, and man-made)0.1560.050
Weaknesses0.388W1: Low level of organizational cooperation in crisis management0.2380.092
W2: Weaknesses in some of the rules and regulations0.2220.086
W3: Low level of adaptive ability among tourists and local communities in crisis situations0.218
W4: Low level of education and public awareness0.1850.084
W5: Low level of health infrastructure and facilities in controlling negative impacts of COVID-19 in tourism destinations0.1780.071
W6: Low volume of trips and flights to tourism destinations0.1640.063
Opportunities0.132O1: Possibility of improvements in the environment and wildlife in tourism destinations0.2110.027
O2: Possibility of decreasing the amount of waste and sewage in tourism destinations0.1820.024
O3: Possibility of decreasing the consumption of water, energy and types of fuels in tourism destinations0.1770.023
O4: Learning opportunities provided by advanced countries in controlling COVID-19 in tourism destinations0.1660.021
O5: Possibility of institutional capacity-building in ecotourism destinations0.1540.020
O6: Using the capacity of informational networks to raise public awareness0.1480.019
O7: Possibility of forming new ideas and innovations about tourism development under COVID-190.1280.016
Threats0.157T1: Bankruptcy of tourism businesses0.2140.034
T2: High economic pressure among households in tourism destinations0.1940.030
T3: Decrease of income and employment levels in tourism destinations0.1740.027
T4: Lack of financial support from tourism communities during spread of COVID-190.1630.025
T5: Increase of anxiety levels among government, tourists and local communities0.1580.024
T6: Probability of forming public demonstrations due to decrease of social resilience levels0.1460.022
Table 6. Matrix of strategies to mitigate the impacts of COVID-19 in Iran.
Table 6. Matrix of strategies to mitigate the impacts of COVID-19 in Iran.
SWOT MatrixStrengths (S)Weaknesses (W)
Opportunities (O)Aggressive strategy (SO)Review strategy (WO)
Institutional capacity-building and development of local NGOs in public education and crisis management
Improvement of environmental conditions and protection of tourism attractions via control of population density, decrease of pollution, waste, and water and energy consumption
Harnessing knowledge and communication networks from the experience of countries adopting progressive measures for controlling negative impacts of COVID-19
Revising rules and regulations to develop institutional cooperation in crisis management to control negative impacts of COVID-19
Institutional capacity-building to develop education and raise public awareness of controlling negative impacts of COVID-19
Improvement of environmental conditions and decrease in pollution levels via controlling the spread of COVID-19 to tourism destinations
Using successful experiences of advanced countries and new ideas in increasing adaption level in local communities during the crises
Threats (T)Diverse strategy (ST)Defensive strategy (WT)
Using the capacity of local NGOs in public education and financial support to increase social resilience and to decrease economic pressure and businesses’ bankruptcy
Financial support by government for households
Controlling population density in tourism spaces to prevent the spread of COVID-19
Developing cooperation among local governments and NGOs in decreasing pollution levels and conserving tourism attractions
Development of institutional cooperation to prevent business bankruptcies and economic pressure to households
Increasing adaptive response in tourism destinations to decrease anxiety levels among government, tourists and local communities
Increase of financial support for households via developing necessary infrastructure and services
Increase levels of social resilience and prevent public uproar
Development of education and public awareness campaigns to increase employment and income levels of households
Table 7. Matrix of weighted strategies using the ANP model.
Table 7. Matrix of weighted strategies using the ANP model.
Internal FactorsFactors WeightSWOT SubfactorsSubfactors
Weaknesses (W)0.388W10.1280.1840.1450.1840.114
Strengths (S)0.321S10.1980.1250.1310.1470.125
External FactorsFactors WeightSWOT SubfactorsSubfactors
Threats (T)0.157T10.1980.1240.1360.1740.126
Opportunities (O)0.132O10.2080.1140.1230.1270.145
Strategies Final Weight 0.1780.2650.3210.378
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Sobhani, P.; Veisi, H.; Esmaeilzadeh, H.; Sadeghi, S.M.M.; Marcu, M.V.; Wolf, I.D. Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran. Sustainability 2022, 14, 5508.

AMA Style

Sobhani P, Veisi H, Esmaeilzadeh H, Sadeghi SMM, Marcu MV, Wolf ID. Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran. Sustainability. 2022; 14(9):5508.

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Sobhani, Parvaneh, Hadi Veisi, Hassan Esmaeilzadeh, Seyed Mohammad Moein Sadeghi, Marina Viorela Marcu, and Isabelle D. Wolf. 2022. "Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran" Sustainability 14, no. 9: 5508.

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