Submitted:
29 August 2024
Posted:
30 August 2024
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Abstract
Keywords:
1. Introduction
1.1. Literature Review
2. Materials and Methods
2.1. Study Area
2.2. Methodology

3. Results
3.1. Identification of Key Drivers Influencing Food Tourism in Rural Areas of Iran
3.1.1. Evaluation of the Impact and Influence of Factors Affecting the Development of Food Tourism in Rural Areas of Iran
3.1.2. Factors Determining or Influencing the Development of Food Tourism in Rural Areas of Iran

3.1.3. Dual-Purpose Factors (Risk Factors and Target Variables) of Food Tourism Development in Rural Areas of Iran
3.1.4. Influential Factors on Food Tourism Development in Rural Areas of Iran

3.1.5. Independent or Exceptional Factors in Food Tourism Development in Rural Areas of Iran

3.1.6. Regulatory Factors in Food Tourism Development in Rural Areas of Iran
3.2. Scenario development for food tourism in rural areas of Iran
Scenario Analysis for Food Tourism Development in Rural Areas of Iran
| Group | Scenario number | Consistency value | Icons. Descript. | Total impact score | Characteristics |
| 3 |
Scenario No. 9 | -1 | 1 | 15 | In this group, Scenario 9 and Scenario 10 are positioned in a state of complete crisis, as illustrated in Figure 5-5. These scenarios depict a full-scale crisis where there is no evidence of efforts to improve or even maintain the current situation, except for Government support and assistance, which continues along its current trajectory. The critical features of these scenarios, detailed in Table 10, encompass a severe reduction or deterioration in all key factors: a decrease in the number of festivals, an increase in prices, a decline in food quality, a degradation of infrastructure quality, reduced government support for food tourism, and diminished investments in the development of food tourism . |
| Scenario No. 10 | 0 | 0 | 20 |


4. Discussion
5. Conclusions
- Conduct studies on the impact of food tourism development on other tourism sectors.
- Identify the competitiveness capacities of food tourism among the provinces of Iran.
- Assess the position of Iranian provinces in terms of food tourism development capacities using MCDM techniques.
- Investigate the obstacles and constraints of food tourism development in rural areas of Iran.
- Identify strategies to attract private and public sector participation in investments for food tourism development.
Appendix A




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| Researcher / Researchers | Year | Title | Method | Results |
| [78] | 2007 | Maslow’s hierarchy and food tourism in Finland: five cases |
multiple-case design and Descriptive research The empirical data has been collected from literature, studies, websites, and conducting an interview. For data analysis, analytic generalization has been utilized. |
Understanding the needs and motivations of tourists, reducing taxation, selling products and goods at lower prices, income, harmonizing regulations, increasing competition among companies involved in food production, holding meetings, conferences, and trade shows, and cohesive marketing efforts can be effective in the development of food tourism in Finland |
| [79] | 2008 | The determinants of gastronomic tourists’ satisfaction: a second-order factor analysis | Descriptive research The data has been collected through a survey using 377 questionnaires. For data analysis, the AMOS software (structural equation modeling) has been utilized. |
The three main factors affecting the satisfaction of food tourists in Portugal are: Food-related factors (local dishes, presentation of food, authenticity, and uniqueness). Price and quality of food (beverage prices, course prices, food quality, and staff service). Atmosphere and environment (ethnic decor, decoration, modern music, lighting, and entertainment). |
| [22] | 2011 | Local Food Tourism Networks and Word of Mouth | The descriptive-analytical method has been employed for this study. Data has been gathered through postal surveys (475 questionnaires) and interviews. | In Wisconsin, oral advertising plays a pivotal role in forming and maintaining local food tourism networks by connecting farmers and restaurateurs. Additionally, word-of-mouth advertising primarily informs tourists about tourism opportunities in the region. |
| [75] | 2011 | An examination of food tourist’s behaviour: Using the modified theory of reasoned action |
The descriptive-analytical method was employed, and data was collected from 305 questionnaires among tourists participating in the food festival. The collected data was analyzed using SPSS 17.0 and AMOS 4.0 software. | In the southwestern United States, perceived value, contentment, and satisfaction for intention to return are important behavioural determinants for food tourism. |
| [80] | 2015 | Influence of Festival Attribute Qualities on Slow Food Tourists’ Experience, Satisfaction Level and Revisit Intention: The Case of the Mold Food and Drink Festival |
quantitative research Data was collected through 209 questionnaires completed among participants in the food festival. The data was analyzed using SPSS and AMOS software. |
Programs, food quality, and other recreational and welfare facilities at the festival can effectively develop food tourism in Wales by increasing visitor satisfaction and encouraging repeat visits. |
| [81] |
2019 |
Insight from insiders: A phenomenological study for exploring food tourism policy in Ireland 2009-2019 | Phenomenological hermeneutics (a qualitative method for examining the lived experience of stakeholders related to food tourism) Data were collected through conducting 10 semi-structured, in-depth interviews. The data were analyzed using thematic analysis method. |
Key policymakers, networking and clustering, social entrepreneurs, government support, creation of regional tourism brands, linking food with cultural initiatives, and marketing strategies have played a pivotal role in developing food tourism in Ireland. |
| [39] | 2020 | Food tourism value: Investigating the factors that influence tourists to revisit |
multivariate analysis method Multivariate analysis method 891 questionnaires were used to collect the data. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for data analysis. |
aste/quality value, health value, price, emotional value, and credibility are among the factors that have a positive impact on the attitude of food tourists in the city of Shiraz, Iran. |
| [42] | 2021 | Investigating Determinants of Street Food Attributes and Tourist Satisfaction: An Empirical study of Food Tourism Perspective | positivist research approach Positivist research approach Data were collected through questionnaire completion among 331 tourists. Smart PLS 3.0 was used for data evaluation. |
Quality of services, marketing techniques, diversification and coordination of tourism products, improvement of agricultural techniques, enhancement of destination reputation, and improvement of place branding are among the most important factors and strategies for food tourism growth in Kuala Lumpur, Malaysia. |
| [49] | 2022 | Mapping Research on Food Tourism: A Review Study |
descriptive and bibliometric analysis Descriptive and bibliographic analysis The data was collected from published articles (in the most reputable journals, with the participation of top authors, and from leading countries that have researched food tourism) from 2006 to 2021. Statistical tools such as modularity class and PageRank have been used for data analysis. |
Studies in the field of food tourism have mainly been conducted in Britain and Canada. During this period, the main focus of studies in food tourism has been increasing tourist satisfaction and loyalty. Additionally, the results have shown that experience, local, preservation, development, motivation, market, culture, cuisine, model, behaviour, image, perception, intention, loyalty, value, attitude, active, technology, content, use, and review are the key keywords in studies in the field of food tourism. |
| [26] | 2023 | Determining food tourism consumption of wild mushrooms in Yunnan Provence, China: A projection-pursuit approach |
quantitative methods The data was obtained through the completion of 500 questionnaires. The projection pursuit model (PPM) and structural equation modeling (SEM) were used for data analysis. |
The quality and quantity of food resources, attention to tourists’ needs, and tourists’ perceptions are the most important factors influencing the development of wild mushroom-related food tourism in Yunnan Province, China. |
| Encoding | Factors | Reference | Encoding | Factors | Reference |
|---|---|---|---|---|---|
| A1 | Understanding the motivations and needs of tourists | [78] | A27 | Coordination of laws and policies | [19,72,80] |
| A2 | Reduction in tax rates | [78] | A28 | Attention to tourists’ food interests. | [89] |
| A3 | The decoration of food, its colour, and presentation | [72,79] | A29 | Satisfaction and contentment for repeat visit intention | [75] |
| A4 | Increasing competition among companies involved in food production | [78] | A30 | The internet and web (Information and Communication Technology) in the tourism sector |
[90] |
| A5 | Creating campaigns and organizing festivals, events, meetings, conferences, and trade shows. |
[78,79,80], [91,92] | A31 | Advertising, especially word-of-mouth and social media advertising | [20,22,41] |
| A6 | The authenticity of food | [40,79] | A32 | The quality, shape, and colour of food containers | [93] |
| A7 | Prices (for food, drinks, courses, etc.) | [39,78,79] | A33 | Personnel (attire and interaction manner, ensuring safety by them) | [20,79,89] |
| A8 | The quality of food | [79,89] | A34 | Marketing |
[41,42,48], [57,78] |
| A9 | Designing the ambient decoration of the destination (considering ethnicities, furniture, artworks, environmental embellishments, lighting quality, entertainment such as music, shows, etc.) | [79,89] | A35 | Accurate capacity assessment of assets | [94] |
| A10 | Industrial reconstruction | [95] | A36 | Continuous and comprehensive evaluation of food tourism destinations | [94] |
| A11 | Proximity/accessibility to accommodation | [95] | A37 | Investment. | [96] |
| A12 | The quality of infrastructure |
[57,95] | A38 | Collaboration and stakeholder participation | [19,74,92], [94] |
| A13 | Local lifestyle | [95] | A39 | Enhancing more interaction between tourists and local communities. | [19] |
| A14 | National food holidays calendar | [96] | A40 | Adding a dreamy aspect to festivals | [92] |
| A15 | High capacity in agriculture and animal husbandry | [26,96] | A41 | Elevating the level of motivation for well-being and exclusivity in the local community | [92] |
| A16 | Formation of tourism companies | [96] | A42 | The fluid identity of the festival and its food. | [92] |
| A17 | Government support and assistance | [57] | A43 | Travel information provision | [20] |
| A18 | Diversity of food | [40] | A44 | Development and promotion of street food | [76] |
| A19 | Respect for tourists’ dietary regime laws in tourist destinations | [82] | A45 | Food safety | [76] |
| A20 | Traditional restaurants | [96] | A46 | Attention to the authenticity of the tourism destination. | [56] |
| A21 | The perceived quality by tourists | [26] | A47 | Establishment of food museums |
[96] |
| A22 | Improving communication between tourists and the host community | [96] | A48 | Providing quantitative and qualitative information about food |
[20] |
| A23 | Awareness (local and general) of tourists’ preferences and food tourism | [57] | A49 | Food tourism managers | [20] |
| A24 | Values (health value, emotional value, experience and consumption value of local food, perceived value for repeat visit intention, valuing local people) | [39,41,75] | A50 | Innovation and creativity in food and destination | [20,58,79], [95] |
| A25 | Cooking motivation | [40] | A51 | Observance of health protocols | [20] |
| A26 | Adaptation and coordination of tourism products | [42] | A52 | Human risks such as the COVID-19 pandemic and... | [20] |
| MDI characteristics | |
|---|---|
| Matrix size | 52 |
| Number of iterations | 2 |
| Number of zeros | 359 |
| Number of ones | 896 |
| Number of twos | 874 |
| Number of threes | 575 |
| Number of P | 0 |
| Total | 2345 |
| Fillrat | 86.72 |
| Iteration | Influence | Dependence |
|---|---|---|
| 1 | 99% | 96% |
| 2 | 100% | 100% |
| Rank | Label | Direct influence | Label | Direct dependence | Label | Indirect influence | Label | Indirect dependence |
|---|---|---|---|---|---|---|---|---|
| 1 | A5 | 279 | A15 | 251 | A5 | 271 | A15 | 248 |
| 2 | A10 | 270 | A3 | 231 | A15 | 267 | A9 | 234 |
| 3 | A15 | 270 | A9 | 231 | A37 | 267 | A3 | 233 |
| 4 | A37 | 270 | A6 | 228 | A10 | 266 | A6 | 228 |
| 5 | A7 | 265 | A10 | 224 | A7 | 264 | A20 | 224 |
| 6 | A12 | 260 | A13 | 224 | A12 | 258 | A10 | 224 |
| 7 | A17 | 249 | A20 | 224 | A17 | 252 | A13 | 223 |
| 8 | A8 | 247 | A4 | 222 | A8 | 237 | A40 | 223 |
| 9 | A3 | 231 | A40 | 222 | A3 | 227 | A4 | 222 |
| 10 | A50 | 231 | A14 | 215 | A50 | 226 | A35 | 213 |
| 11 | A35 | 226 | A35 | 215 | A35 | 223 | A44 | 213 |
| 12 | A40 | 224 | A44 | 215 | A20 | 223 | A14 | 212 |
| 13 | A44 | 222 | A48 | 212 | A40 | 220 | A23 | 211 |
| 14 | A1 | 219 | A23 | 210 | A18 | 220 | A48 | 211 |
| 15 | A18 | 219 | A11 | 208 | A1 | 218 | A18 | 210 |
| 16 | A20 | 219 | A18 | 208 | A44 | 217 | A25 | 210 |
| 17 | A45 | 203 | A25 | 208 | A4 | 201 | A11 | 205 |
| 18 | A4 | 201 | A24 | 205 | A45 | 200 | A30 | 204 |
| 19 | A49 | 199 | A28 | 203 | A49 | 200 | A45 | 203 |
| 20 | A25 | 194 | A30 | 203 | A25 | 193 | A1 | 202 |
| 21 | A48 | 194 | A45 | 203 | A48 | 193 | A24 | 202 |
| 22 | A52 | 189 | A31 | 201 | A30 | 192 | A28 | 201 |
| 23 | A27 | 187 | A1 | 199 | A27 | 191 | A31 | 199 |
| 24 | A30 | 187 | A50 | 199 | A52 | 191 | A2 | 197 |
| 25 | A23 | 185 | A2 | 196 | A23 | 189 | A50 | 197 |
| 26 | A19 | 183 | A29 | 194 | A19 | 182 | A29 | 194 |
| 27 | A38 | 180 | A43 | 194 | A38 | 181 | A49 | 193 |
| 28 | A39 | 180 | A49 | 194 | A36 | 180 | A43 | 193 |
| 29 | A36 | 178 | A16 | 189 | A39 | 179 | A32 | 189 |
| 30 | A21 | 173 | A19 | 189 | A21 | 175 | A19 | 188 |
| 31 | A2 | 171 | A32 | 187 | A47 | 175 | A22 | 188 |
| 32 | A26 | 171 | A22 | 185 | A28 | 172 | A16 | 187 |
| 33 | A47 | 171 | A34 | 185 | A2 | 171 | A34 | 180 |
| 34 | A13 | 169 | A36 | 180 | A33 | 170 | A51 | 180 |
| 35 | A28 | 169 | A42 | 178 | A13 | 170 | A39 | 178 |
| 36 | A33 | 169 | A51 | 178 | A26 | 169 | A36 | 177 |
| 37 | A51 | 167 | A12 | 176 | A34 | 168 | A42 | 177 |
| 38 | A22 | 162 | A39 | 176 | A51 | 167 | A12 | 176 |
| 39 | A34 | 162 | A38 | 171 | A32 | 163 | A38 | 171 |
| 40 | A24 | 160 | A46 | 169 | A14 | 162 | A46 | 170 |
| 41 | A29 | 160 | A26 | 167 | A22 | 161 | A27 | 168 |
| 42 | A32 | 160 | A41 | 167 | A29 | 161 | A41 | 168 |
| 43 | A14 | 157 | A27 | 164 | A24 | 159 | A26 | 165 |
| 44 | A41 | 155 | A8 | 160 | A31 | 154 | A17 | 162 |
| 45 | A42 | 153 | A33 | 160 | A42 | 153 | A33 | 159 |
| 46 | A31 | 151 | A17 | 157 | A41 | 152 | A37 | 159 |
| 47 | A6 | 144 | A37 | 157 | A9 | 145 | A8 | 157 |
| 48 | A16 | 144 | A7 | 155 | A16 | 145 | A7 | 154 |
| 49 | A9 | 141 | A47 | 151 | A6 | 143 | A21 | 151 |
| 50 | A43 | 137 | A5 | 148 | A46 | 138 | A47 | 150 |
| 51 | A46 | 137 | A21 | 148 | A43 | 136 | A5 | 146 |
| 52 | A11 | 132 | A52 | 139 | A11 | 135 | A52 | 145 |
| Abbreviation mark | Key factors of food tourism development |
Possible scenarios for each factor |
Subcategories of each factor |
Degree of desirability | Status |
| A | Creating campaigns and organizing festivals, events, meetings, conferences, and trade shows |
A1 | The expansion of the number of festivals | Desirable | Green |
| A2 | Continuation of the current trend | Average | Yellow | ||
| A3 | Reduction in the number of festivals | Undesirable | Red | ||
| B | Prices (for food, drinks, courses, etc.) |
B1 | Reduction in prices | Desirable | Green |
| B2 | Continuation of the current trend | Average | Yellow | ||
| B3 | Increase in prices | Undesirable | Red | ||
| C | The quality of food |
C1 | Improvement in the quality of food | Desirable | Green |
| C2 | Continuation of the current trend | Average | Yellow | ||
| C3 | Reduction in the quality of food | Undesirable | Red | ||
| D | The quality of infrastructure |
D1 | Improvement in the quality of infrastructure | Desirable | Green |
| D2 | Continuation of the current trend | Average | Yellow | ||
| D3 | Reduction in the quality of infrastructure | Undesirable | Red | ||
| E | Government support and assistance |
E1 | Increase in government support for food tourism | Desirable | Green |
| E2 | Continuation of the current trend | Average | Yellow | ||
| E3 | Reduction in government support for food tourism | Undesirable | Red | ||
| F | Investment |
F1 | Increase in investments for the development of food tourism | Desirable | Green |
| F2 | Continuation of the current trend | Average | Yellow | ||
| F3 | Reduction in investments for the development of food tourism | Undesirable | Red | ||
| Total | 18 | ---- | ---- |
| Scenario Status | The number of scenarios |
| Weak (possible) scenarios | 196 |
| Scenarios with maximum incompatibility: 1 (Compatibility 1) | 10 |
| Strong or probable scenarios | 4 |
| Group | Scenario number | Consistency value | Icons. Descriptor. | Total impact score | Characteristics |
| 1 | Scenario No. 1 | 0 | 0 | 55 | All factors except one in this group will be in their most desirable state. These factors include creating campaigns and organizing festivals, events, meetings, conferences, and trade shows with an expanded number of festivals; improvement in the quality of food and infrastructure; increased government support for food tourism; and higher investments for its development. The only exception is the pricing factor, which continues its current trend in Scenario 2, reflecting ongoing conditions. |
| Scenario No. 2 | 0 | 0 | 49 |
| Group | Scenario number | Consistency value | Icons. Descript. | Total impact score | Characteristics |
| 2 |
Scenario No. 3 | -1 | 3 | 4 | In this group, two factors, Creating campaigns and organizing festivals, events, meetings, conferences and trade shows, and The quality of infrastructure, are collectively in critical conditions across all six scenarios. Scenario three involves a Reduction in prices for the Prices (for food drinks courses etc.) factor, while scenarios five and six for the Government support and assistance factor are favorable. Other factors remain in either current state continuation or critical conditions across all scenarios. |
| Scenario No. 4 | -1 | 3 | 2 | ||
| Scenario No. 5 | -1 | 2 | 10 | ||
| Scenario No. 6 | -1 | 2 | 14 | ||
| Scenario No. 7 | -1 | 1 | 9 | ||
| Scenario No. 8 | 0 | 0 | 15 |
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