Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran
Abstract
:1. Introduction
2. Theoretical Background
3. Research Methods
3.1. Research Framework
3.2. Research Procedure
- (1)
- 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.
- (2)
- A group of 35 experts in tourism who are familiar with different tourism industry sectors in Iran was selected.
- (3)
- 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.
- (4)
- 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.
- (5)
- 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.
Intensity of Importance | Definition |
---|---|
1 | Equal importance |
3 | Moderate importance |
5 | Strong importance |
7 | Very strong importance |
9 | Absolute importance |
2, 4, 6, 8 | Intermediate values |
4. Results
4.1. Respondent Characteristics
4.2. Construction of the Narrative of the IP and Assessment of COVID-19 Impacts
4.3. Developing a Response Pathway (RP) Approach to Manage COVID-19 Impacts on Tourism
4.4. Optimal Strategies to Mitigate the Impacts of COVID-19
4.5. Positive and Negative Impacts of COVID-19 on Tourism
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Dimensions | Variables | Indicators | References |
---|---|---|---|
Physical-environmental | Environmental pollutions | Level 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 | |||
Ecosystems | Condition of mountains, forests, and deserts | ||
Animals’ habitats | Level of wildlife hunting | ||
Level of habitat destruction | |||
Vegetation | Quantitative and qualitative status of vegetation | ||
Resources consumption | Level of energy consumption and types of fuels | ||
Level of water resource consumption | |||
Waste and sewage production | Amount of waste produced in tourist destinations | ||
Quality of environmental resources and climate | Quality of water, soil and air resources | ||
Safety | Number of accidents | ||
Accommodation and food services | Usage 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 facilities | Level of highway cost and toll services | ||
Level of information and communication networks (internet, social networks, telephone, newspapers, etc.) | |||
Level of parking lot usage | |||
Socio-cultural | Tourism attractions and activities | Level 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 | |||
Transportation | Number of air trips | ||
Number of vehicle trips | |||
Number of rail trips (train and metro) | |||
Number of sea voyages | |||
Number of freight and transit trips | |||
Psychic | Travel motivation among tourists | ||
Level of economic pressure among households | |||
Security | Level of social security against crime and conflict | ||
Behavior | Level of change in tourists’ behavior | ||
Traffic | Level of congestion in roads and public places | ||
Education and information | Level of services and educational programs | ||
Level of information about tourism activities of different sites | |||
Economic—institutional | Institutional elements | The volume of government agencies working in tourism | [35,39,41,44,45,47] |
Revenues of government institutions | |||
Employment and income | Closure/bankruptcy of tourism businesses | ||
Number of employers in different sectors of tourism | |||
Plans and projects | The volume of tourism plans and projects | ||
Economic diversity | Volume of activities about tourism industries | ||
Volume of activities about tourism-related services | |||
Local prices | Average price of estate and commodities |
Characteristics | Frequency (n) (Total n = 35) | Percentage | |
---|---|---|---|
Gender | Male | 22 | 62.00 |
Female | 13 | 38.00 | |
Age | Less than 30 | 5 | 14.28 |
30–40 | 15 | 42.85 | |
40–50 | 8 | 22.57 | |
50+ | 7 | 20.00 | |
Education | Bachelor’s degree | 12 | 34.29 |
M.Sc. degree | 15 | 42.86 | |
Ph.D. degree | 8 | 22.85 | |
Employment | Employed in different sectors of tourism | 19 | 54.28 |
Employed in non-tourism sectors | 10 | 28.57 | |
Unemployed | 6 | 17.15 | |
Experience in tourism | 6–10 years | 21 | 60.00 |
10–20 years | 9 | 25.72 | |
More than 20 years | 5 | 14.28 |
Dimensions | Variables | Indicators of Impacts | Indicators Value | Impact Type | Impact Range |
---|---|---|---|---|---|
Physical-environmental (average impacts of dimensions = 2.87) | Environmental pollutions | Level of water resource pollution | 2.94 | P | M |
Level of soil pollution and erosion | 2.91 | P | M | ||
Level of air pollution | 2.97 | P | M | ||
Level of noise pollution and noise intensity in tourist destinations | 2.77 | P | M | ||
Level of visual pollution | 2.74 | P | M | ||
Ecosystems | Condition of mountains, forests, and deserts | 2.88 | P | M | |
Animals’ habitats | Level of wildlife hunting | 3.42 | P | H | |
Level of habitat destruction | 3.17 | P | H | ||
Vegetation | Quantitative and qualitative status of vegetation | 2.97 | P | M | |
Resource consumption | Level of energy consumption and types of fuels | 2.91 | P | M | |
Level of water resources consumption | 3.11 | P | H | ||
Waste and sewage production | Amount of wastes for tourist destinations | 2.42 | P | M | |
Amount of effluents and sewages for tourist destinations | 2.40 | P | M | ||
Quality of environmental resources and climate | Quality of water, soil, and air resources | 3.20 | P | H | |
Safety | Level of accidents | 2.42 | P | M | |
Accommodation and food services | Level of accommodation usage (hotels, inns, and guesthouses) | 3.34 | N | H | |
Usage level of villas and forest residences | 3.51 | N | H | ||
Number of restaurant customers | 3.40 | N | H | ||
Level of shopping malls and stores customers | 3.68 | N | H | ||
Infrastructure and tourism facilities | Level of highways’ cost and toll services | 2.45 | P | M | |
Level of information and communication networks (internet, social networks, telephone, newspapers, etc.) | 2.62 | P | M | ||
Level of theaters and cinemas usage | 2.42 | N | M | ||
Level of religious and cultural places usage | 2.57 | N | M | ||
Level of parking lot usage | 2.14 | N | M | ||
Level of local arts and crafts sales in tourism destinations | 2.62 | N | M | ||
Socio-cultural (average impacts of dimensions = 3.43) | Tourist attractions and activities | Level of natural attractions’ protection | 3.22 | P | H |
Level of cultural and religious attractions’ protection | 2.88 | P | M | ||
Level of historical and ancient attractions’ protection | 2.88 | P | M | ||
Level of man-made attractions’ protection | 2.77 | P | M | ||
The volume of tourism festivals | 2.65 | N | M | ||
Transportation | Number of air trips | 3.48 | N | H | |
Number of road cars trips | 3.28 | N | H | ||
Number of rail trips (train and metro) | 3.34 | N | H | ||
Number of sea voyages | 3.37 | N | H | ||
Number of freight and transit trips | 3.20 | N | H | ||
Psychic | Travel motivation among tourists | 3.22 | N | H | |
Level of economic pressure among households | 4.22 | N | VH | ||
Security | Level of social security against crime and conflict | 3.88 | P | H | |
Behavior | Level of change in tourists behavior | 3.94 | P | H | |
Level of social resilience | 4.20 | N | VH | ||
Traffic | Level of congestion in roads and public places | 4.02 | P | VH | |
Education and information | Level of services and educational programs | 3.77 | N | H | |
Level of information about tourism activities of different sites | 3.25 | N | H | ||
Tourism advertising | 3.65 | N | H | ||
Economic-institutional (average impacts of dimensions = 4.35) | Institutional elements | The volume of governmental agencies’ work in relation to tourism | 4.34 | N | VH |
Revenues of governmental institutions | 4.28 | N | VH | ||
The volume of non-governmental organizations’ work (tourism agencies, NGOs, local associations and councils, etc.) | 4.57 | N | VH | ||
Number of non-governmental organizations | 4.22 | N | VH | ||
Level of non-governmental organizations revenues | 4.54 | N | VH | ||
Employment and income | Closure/bankruptcy of tourism businesses | 4.88 | N | VH | |
Number of employers in different sectors of tourism | 4.74 | N | VH | ||
Level of employees’ income in different sectors of tourism | 4.88 | N | VH | ||
Level of the residents’ welfare of tourist destinations | 4.22 | N | VH | ||
Plans and projects | The volume of tourism plans and projects | 4.45 | N | VH | |
Economic diversity | Volume of activities about tourism industries | 4.68 | N | VH | |
Volume of activities about tourism-related services | 4.54 | N | VH | ||
Level of agro-tourism development | 4.34 | N | VH | ||
Level of nature-based and ecotourism development | 4.77 | N | VH | ||
Level of urban and rural tourism development | 4.22 | N | VH | ||
Local prices | Average prices of estate and commodities | 1.97 | P | L |
Internal Factors | Factors Weight | SWOT Subfactors | Subfactor Weight | Final Weight |
---|---|---|---|---|
Strengths | 0.321 | S1: Existence of local NGOs in public education and crisis management | 0.198 | 0.063 |
S2: Low level of environmental pollution | 0.192 | 0.061 | ||
S3: Low level of traffic and population density in tourism destinations | 0.175 | 0.056 | ||
S4: Improvements the protection of tourism attractions (natural, cultural and religious, historical, and man-made) | 0.156 | 0.050 | ||
Weaknesses | 0.388 | W1: Low level of organizational cooperation in crisis management | 0.238 | 0.092 |
W2: Weaknesses in some of the rules and regulations | 0.222 | 0.086 | ||
W3: Low level of adaptive ability among tourists and local communities in crisis situations | 0.218 | |||
W4: Low level of education and public awareness | 0.185 | 0.084 | ||
W5: Low level of health infrastructure and facilities in controlling negative impacts of COVID-19 in tourism destinations | 0.178 | 0.071 | ||
W6: Low volume of trips and flights to tourism destinations | 0.164 | 0.063 | ||
Opportunities | 0.132 | O1: Possibility of improvements in the environment and wildlife in tourism destinations | 0.211 | 0.027 |
O2: Possibility of decreasing the amount of waste and sewage in tourism destinations | 0.182 | 0.024 | ||
O3: Possibility of decreasing the consumption of water, energy and types of fuels in tourism destinations | 0.177 | 0.023 | ||
O4: Learning opportunities provided by advanced countries in controlling COVID-19 in tourism destinations | 0.166 | 0.021 | ||
O5: Possibility of institutional capacity-building in ecotourism destinations | 0.154 | 0.020 | ||
O6: Using the capacity of informational networks to raise public awareness | 0.148 | 0.019 | ||
O7: Possibility of forming new ideas and innovations about tourism development under COVID-19 | 0.128 | 0.016 | ||
Threats | 0.157 | T1: Bankruptcy of tourism businesses | 0.214 | 0.034 |
T2: High economic pressure among households in tourism destinations | 0.194 | 0.030 | ||
T3: Decrease of income and employment levels in tourism destinations | 0.174 | 0.027 | ||
T4: Lack of financial support from tourism communities during spread of COVID-19 | 0.163 | 0.025 | ||
T5: Increase of anxiety levels among government, tourists and local communities | 0.158 | 0.024 | ||
T6: Probability of forming public demonstrations due to decrease of social resilience levels | 0.146 | 0.022 |
SWOT Matrix | Strengths (S) | Weaknesses (W) |
---|---|---|
Opportunities (O) | Aggressive strategy (SO) | Review strategy (WO) |
|
| |
Threats (T) | Diverse strategy (ST) | Defensive strategy (WT) |
|
|
Internal Factors | Factors Weight | SWOT Subfactors | Subfactors Weight | Strategies | |||
---|---|---|---|---|---|---|---|
SO | ST | WO | WT | ||||
Weaknesses (W) | 0.388 | W1 | 0.128 | 0.184 | 0.145 | 0.184 | 0.114 |
W2 | 0.143 | 0.165 | 0.132 | 0.162 | 0.141 | ||
W3 | 0.167 | 0.142 | 0.149 | 0.147 | 0.126 | ||
W4 | 0.202 | 0.124 | 0.154 | 0.184 | 0.139 | ||
W5 | 0.173 | 0.178 | 0.136 | 0.119 | 0.146 | ||
W6 | 0.148 | 0.168 | 0.125 | 0.147 | 0.136 | ||
Strengths (S) | 0.321 | S1 | 0.198 | 0.125 | 0.131 | 0.147 | 0.125 |
S2 | 0.156 | 0.137 | 0.147 | 0.127 | 0.133 | ||
S3 | 0.192 | 0.114 | 0.124 | 0.114 | 0.154 | ||
S4 | 0.175 | 0.138 | 0.172 | 0.138 | 0.178 | ||
External Factors | Factors Weight | SWOT Subfactors | Subfactors Weight | Strategies | |||
SO | ST | WO | WT | ||||
Threats (T) | 0.157 | T1 | 0.198 | 0.124 | 0.136 | 0.174 | 0.126 |
T2 | 0.203 | 0.138 | 0.152 | 0.163 | 0.136 | ||
T3 | 0.225 | 0.115 | 0.127 | 0.187 | 0.162 | ||
T4 | 0.215 | 0.132 | 0.116 | 0.119 | 0.147 | ||
T5 | 0.162 | 0.187 | 0.171 | 0.126 | 0.131 | ||
T6 | 0.117 | 0.130 | 0.125 | 0.176 | 0.165 | ||
Opportunities (O) | 0.132 | O1 | 0.208 | 0.114 | 0.123 | 0.127 | 0.145 |
O2 | 0.198 | 0.138 | 0.145 | 0.135 | 0.138 | ||
O3 | 0.238 | 0.184 | 0.174 | 0.141 | 0.178 | ||
O4 | 0.185 | 0.165 | 0.126 | 0.169 | 0.115 | ||
O5 | 0.172 | 0.148 | 0.113 | 0.128 | 0.164 | ||
O6 | 0.205 | 0.136 | 0.122 | 0.143 | 0.175 | ||
O7 | 0.168 | 0.188 | 0.210 | 0.162 | 0.128 | ||
Strategies Final Weight | 0.178 | 0.265 | 0.321 | 0.378 |
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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. https://doi.org/10.3390/su14095508
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. https://doi.org/10.3390/su14095508
Chicago/Turabian StyleSobhani, 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. https://doi.org/10.3390/su14095508