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Volume 37, Issue 2 (2022)
GeoRes 2022, 37(2): 171-188 |
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Received: 2021/08/24 | Accepted: 2022/01/3 | Published: 2022/04/8
Received: 2021/08/24 | Accepted: 2022/01/3 | Published: 2022/04/8
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Porkhosravani M, Shahzeidi S, Azizi Zarandi A. Evaluation of Tourism Development by Systems Dynamics Model (Case Study: Shahdad City in the Northeast of Kerman). GeoRes 2022; 37 (2) :171-188
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1- Department of Geography and Urban Planning, Literature and Humanities, Shahid Bahonar University of Kerman, Kerman, Iran
2- Department of Geography and urban planning, Literature and Humanities, University of Guilan, Rasht, Iran
2- Department of Geography and urban planning, Literature and Humanities, University of Guilan, Rasht, Iran
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Introduction
Today, tourism and the tourism economy are increasingly becoming one of the main pillars of the global commercial economy, and development planners and policymakers also regard the tourism industry as a fundamental pillar of sustainable development. In this regard, through sound planning and the identification of tourism advantages and limitations, it is possible to contribute to national development and the diversification of the national economy [Rokanuddin Eftekhari & Mahdavi, 2006]. This issue constitutes a complex and dynamic process encompassing economic, political, cultural, and environmental dimensions, which is influenced by the diverse and often conflicting interests and values of various groups and stakeholders and continues its dynamism according to different social and economic needs and the spatial capacities of each region [Negi, 2003]. Tourism can be described as the sum of phenomena and relationships arising from interactions among tourists, governments, host communities, universities, and non-governmental organizations in the processes of attraction, transportation, accommodation, and regulation of tourists and other visitors [Weaver & Oppermann, 2000], and it can become a driving force for sustainable development [World Tourism Organization, 2013].
Adopting a systems perspective on tourism policies allows for the examination of the various dimensions influencing this field. This approach not only contributes to a better understanding of this complex system, but also helps identify the root causes of problems in this sector and prevents superficial interventions that focus on addressing consequences rather than underlying causes [Kumar, 2012]. At present, tourism is one of the most dynamic economic activities, playing a significant role in development and generating numerous social, economic, environmental, and cultural benefits [Ebrahimzadeh et al., 2014]. In recent decades, government policies have emphasized tourism development as a means of combating unemployment and generating income; beyond the debates arising from increasing specialization and a production-oriented view of tourism, these policies also highlight the importance of flexibility in tourism development [Jansen & Lievois, 2003]. Consequently, tourism holds a special position in the development of geographical regions. When the dimensions and contexts related to tourism are properly identified, more effective scientific and practical steps toward regional development can undoubtedly be taken. This situation becomes more evident when a region possesses diverse and unique tourism potentials and, at the same time, tourism development can contribute to alleviating regional deprivation [Papoli Yazdi & Saghaei, 2006].
Given the multiplicity of sectors influencing the tourism industry, the application of a system dynamics approach plays an important role in evaluating tourism development in different regions. System dynamics was first introduced in the late 1950s by Jay Forrester at the Massachusetts Institute of Technology (MIT) as a method for modeling and simulating dynamic industrial systems. The foundation of system dynamics (SD) theory is that system behavior is determined by system structure, meaning that situations can be analyzed from an objective external perspective. Accordingly, real-world dynamic processes can be simulated using mathematical models. The problem-solving stages in the system dynamics approach include problem identification and definition, construction of a conceptual model (causal loop diagram), development of a mathematical model (stock–flow diagram), model simulation and validation, and the definition and analysis of different scenarios [Hosseinzadeh & Molavi, 2019].
In recent decades, researchers have conducted various studies using system dynamics models. Among these, Georgantzas [2003] have examined the quantity and value of hotels in Cyprus within the context of tourism system dynamics and explaines how Cyprus’s future strategy (2010) would affect tourist arrivals. Accordingly, the value chain of Cypriot hotels and tourists was examined, and several strategic scenarios were calculated using a system dynamics simulation model to explore what might occur in Cyprus’s tourism sector over the next 40 years. The scenario analysis showed that the sensitivity of the hotel value chain in Cyprus is related to parameters such as tourism policy, tourism growth, tourism seasonality, and other factors.
Jiang et al. [2010] have investigated investment in transportation infrastructure and the development of cultural heritage tourism in the historic villages of Xidi and Hongcun in southern China using a system dynamics model. The results showed that the effects of short- and long-term investments in transportation infrastructure on tourism development can be effectively predicted by this model. To achieve maximum tourism revenue, both villages can adopt an aggressive strategy involving continuous investment in transportation infrastructure and the utilization of existing land resources. Based on this approach, simulation-derived scenarios presented several development strategies and forecasts for the two villages over a 20-year period.
Mai and Kambiz [2011] examine tourism development using a participatory systems approach in the Cat Ba region of Vietnam. This study demonstrates that different stakeholders have different perceptions of the system and pursue different managerial objectives, and that these divergent expectations lead to unforeseen conflicts among stakeholders, which can negatively affect tourism development. Within this participatory approach, a comprehensive understanding of the interconnections and relationships among system components is essential for sustainable tourism development. Accordingly, the model was proposed as a framework for decision-making and capacity building by public and private stakeholders responsible for developing, managing, and conserving the system.
Kumar [2012] also investigates regional infrastructure planning and management for tourism development in the state of Orissa, India. This study employes a system dynamics approach and considered three key infrastructures including roads, railways, and accommodation facilities and demonstrates that the model can serve as an appropriate and reliable tool for forecasting, policymaking, and decision-making in planning and management, thereby providing a more favorable outlook for tourism development. The author emphasizes that these structures and the integration of their impacts exert significant effects on the tourism system.
Asasuppakit and Thiengburanathum [2014] evaluate sustainable urban infrastructure in Chiang Mai and its impacts on tourism. The aim of this study is to develop an urban infrastructure assessment model using a system dynamics approach as a key decision-support system, focusing on the city’s transportation carrying capacity. The development of causal loop diagrams and a city framework model as a case study demonstrated the analysis of the impacts of urban infrastructure on tourism.
Mai and Smith [2018] have conducted another study on scenario-based planning for tourism development using system dynamics modeling on Cat Ba Island, Vietnam. The results indicate that the current trajectory of tourism development on Cat Ba Island is unsustainable, and that growth constraints may be reached by 2022 due to water shortages, pollution, and overcrowding. Over time, this tourism destination exceeds its growth limits, increasing the risk of carrying capacity erosion through resource depletion and environmental degradation.
Sedarati et al. [2019] have examined the application of system dynamics in tourism planning and development. Following a systematic literature review, 27 articles are selected and analyzed, revealing that the system dynamics method is highly suitable for addressing numerous problems and offers considerable potential for providing tourism decision-makers and supervisors with strategic and operational policy development tools across different levels of analysis.
Wang et al. [2020] have evaluated tourism carrying capacity and its impacts on urban tourism economic growth in China, defining carrying capacity as a destination’s ability to absorb tourists. In this macro-level system dynamics model, three subsystems and 47 parameters are considered. Nine urban tourism destinations in China are selected as study cases. The results indicate that, in order to promote sustainable tourism development, management should focus on environmental policies and tourist management.
Pizzitutti et al. [2017] conduct a study on scenario planning for tourism management using system dynamics modeling and developed dynamic models for electricity, goods, land, and accommodation infrastructure over medium- and long-term horizons. Fu et al. [2011] examine the sustainability of the tourism industry in China and used a dynamic systems model as a tool to analyze government policies for sustainable tourism development. This model includes four fundamental components: tourists, tourism facilities, environmental impacts, and government revenue.
Ran [2012] have sought to improve understanding of the values of different tourism stakeholders and their impacts on tourism development by proposing a system-based model for the Gucheng area of Lijiang City, China. Through modeling, simulation, and testing, various factors influencing tourism development, such as marketing, tourism service capacity, economic growth, and natural resources are identified. The model was then tested, and different policies for sustainable tourism development were proposed and evaluated, along with their positive and negative impacts.
Jakulin [2017] examines systems approaches to tourism and, accordingly, map the elements of the tourism industry. Using the iceberg metaphor, the study presents a clear depiction of the tourism industry and ultimately identified the systems approach as one of the most appropriate and practical approaches for addressing complex issues such as tourism. In Iran, the application of this method in tourism studies is limited, and only a small number of studies have addressed systems approaches to tourism, including [Samadi et al., 2012; Zare Mehrjerdi et al., 2014; Mohammadi et al., 2017; Moghimi & Mohaghar, 2018; Hosseinzadeh & Molavi Arabshahi, 2018; Dabbagh & Khatami, 2020].
Considering the importance of the issue and the diversity of natural, historical, archaeological, and ecotourism attractions in the Shahdad region located in the western Lut Desert, this city was selected as the case study. The region is recognized as one of Iran’s major tourism hubs and is experiencing rapid tourism development. Accordingly, this study seeks to evaluate and analyze tourism development in this region using a system dynamics approach.
Methodology
This study was applied in nature and adopted a descriptive–analytical approach. A system dynamics methodology was employed in this research. This approach was introduced in the early 1960s by Jay Forrester at the Massachusetts Institute of Technology (MIT). System dynamics was an approach for modeling and simulating complex physical and socio-economic systems, through which policies for managing and transforming such systems can be formulated [Samadi et al., 2012]. This method integrates behavioral and social sciences with detailed planning and accounting techniques and requires the design and construction of innovative models involving a large number of interacting parameters. System dynamics was particularly applicable in situations involving complex and critical decision-making processes, where an integrated insight into fundamental problems is required, problems that may influence outcomes over years or even decades. This approach assists policymakers and decision-makers in evaluating the advantages and disadvantages of existing or potential policy options.
System dynamics has strong capacity for strategic, macro-, micro-, and cross-sectoral planning, and its application leads to the design of effective organizations and policies. In contexts characterized by high diversity among components and parameters, it enabled the explanation, prediction, and monitoring of structures and behaviors. In such cases, conventional econometric and planning methods were often ineffective, as they were unable to incorporate all model parameters within a comprehensive system or accurately predict potential future events. Therefore, in the present study, a system dynamics model was used to achieve a better understanding of the relationships among parameters [Sterman, 2010].
System dynamics is a hybrid methodology comprising both quantitative and qualitative components. In the quantitative phase, in addition to reviewing library and documentary sources, previous studies in this field and in-depth interviews with experts were used to identify the parameters involved in the model, the main factors influencing tourism, and the relationships among them. In the qualitative phase, the primary parameters were first identified, after which the influence of each parameter on others, independently of additional parameters, was examined. Furthermore, a questionnaire was distributed among experts to determine certain initial values. After developing the causal logic of the model, its conceptual structure was reviewed and validated by specialists in the field.
In the quantitative phase, initial data were collected from the Kerman Provincial Organization of Cultural Heritage, Handicrafts, and Tourism, as well as from subject-matter experts. These data were used to calculate the initial values of state parameters in the model, as well as constants and exogenous parameters, which were expressed in percentage terms. Model development, simulation, and validation were carried out using Vensim software (version 9.2.2). Given the broad applicability of system dynamics modeling to various issues, Sterman proposed five stages for implementing this method. Accordingly, the problem-solving process using a system dynamics approach includes: (1) problem identification and definition (establishing a clear problem framework); (2) development of a conceptual model; (3) construction of a mathematical model; (4) model simulation and validation; and (5) definition and analysis of alternative scenarios [Hosseinzadeh & Molavi, 2019].
Location of the Study Area
Shahdad city is located in the western part of the Lut Plain, in the northeastern region of Kerman Province, and historically served as the center of the ancient Aratta region. To the southwest, it borders the mountainous and cold regions of Sirch, with elevations exceeding 4,000 meters, while to the northeast it connects to desert areas. To the east, it lies approximately 30 kilometers from the Lut Plain and overlooks a region known as Takab, which constitutes the core area of Shahdad. The average annual precipitation in the region is less than 30 millimeters [Ramesht & Shahzeidi, 2008]. The plain in which Shahdad is situated is formed at the confluence of three rivers: Kharashkan, Shahdad, and Jaftan. The Shahdad River flows through a tectonic valley and is a perennial river that supplies water to the region. The Shahdad Kaluts are located approximately 43 kilometers from the city, with an average length of 145 kilometers and an average width of 80 kilometers, and are commonly referred to as the legendary Lut Desert [Ghazanfarpour et al., 2020].
Model Development and Flow Structure
System dynamics is a method for studying and managing complex systems characterized by feedback processes. Due to interactions among different components of a system, understanding system behavior requires a systemic perspective. Such understanding can only be achieved through comprehensive examination of all components and the relationships among them within a unified system. Models are simplified representations of reality, and the primary objective of system dynamics modeling is to gain insight into system relationships in order to examine potential policies for system improvement.
In system dynamics, various tools are employed to represent system structure and enhance understanding. One of the most important aspects of this approach is identifying key subsystems and their interactions within the overall system. In this study, an effort was first made to identify the main subsystems of the Shahdad tourism system and present them in an integrated conceptual framework [Asadi, 2015]. This framework formed the basis for understanding the interactions and feedback mechanisms governing tourism development in the study area.
To develop the subsystem structure and overall model logic, relevant literature on dynamic modeling, particularly in tourism studies was thoroughly reviewed. Indicators and parameters were identified based on previous research, including tourism income, tourist population, tourist inflow and outflow, attraction diversity, time-related factors, tourist satisfaction, tourism carrying capacity, environmental pollution, and local residents’ willingness to support tourism development [Samadi et al., 2012; Lajevardi et al., 2019; Asadi, 2015; Hosseinzadeh & Molavi, 2018; Nasim Sobhan et al., 2015; Dabbagh & Khatami, 2020]. The structure of the model was then developed in accordance with the principles of system dynamics modeling [Sterman, 2000].
The proposed model structure was reviewed by experts in dynamic modeling from the University of Tehran and Shahid Bahonar University of Kerman. In addition, interviews were conducted with university faculty members and officials from the Kerman Provincial Organization of Cultural Heritage and Tourism to incorporate both academic and practical insights. The quantitative relationships among parameters were adopted from established studies [Hosseinzadeh & Molavi, 2018; Nasim Sobhan et al., 2015] and validated by domain experts. After integrating the model components, simulations and validation procedures were carried out, and the results, including sensitivity analyses, were reviewed by experts. Based on their feedback, the necessary modifications were applied, and the final results were updated accordingly.
Findings
The parameters used in the Shahdad tourism system include different types of state, flow, and auxiliary parameters, each defined with specific measurement units appropriate to the tourism system. The initial values of key state parameters, such as tourism attractions, local residents’ willingness to support tourism, and constant parameters of the model, were obtained from the Kerman Provincial Organization of Cultural Heritage, Handicrafts, and Tourism, as well as through interviews with domain experts. The values of these parameters were considered to vary within a range of 0 to 100 percent.
It should be noted that the primary application of the system dynamics approach lies in situations where the behavior of a phenomenon emerges from natural dynamics and the interactions among endogenous system parameters. In this study, it was assumed that the system follows its general and natural development trajectory; therefore, the system dynamics approach was considered appropriate for analyzing the tourism system. Throughout the research process, an important assumption was maintained: the values of system parameters are largely determined through their interactions with one another. After collecting the required data, comprising statistical information provided by experts and the provincial cultural heritage and tourism organization, the relationships among different system components were established through numerical functions, and the overall behavior of the model was examined. Once the model was executed without errors and the functional relationships were correctly specified, the software confirmed the dimensional consistency of the model. Given that the simulation results were consistent with real-world conditions, the model was subsequently used to simulate future periods.
Following model execution and simulation of the factors influencing tourism development in Shahdad, the behavior of key parameters, model validation outcomes, and sensitivity of model parameters were analyzed. Based on these results, different development scenarios were examined.
The simulation results indicate that, during the initial phase of the simulation period, population growth does not increase as expected; in other words, the willingness of local residents to remain in or engage with the region declines when no additional budget is allocated for tourism development or when issues such as inadequate infrastructure, lack of security, and similar constraints persist. Under such conditions, a reduction in population is accompanied by a relative decrease in environmental pollution compared to previous periods. However, if policymakers and authorities devote greater attention to the region, population levels and local residents’ willingness are expected to increase over subsequent periods, eventually leading to population growth. This increase reflects a higher demand for expanded capacities within the region. In turn, increased tourism capacity contributes to higher tourism revenues and ultimately enhances tourist satisfaction. If the tourism industry continues to operate under these improved conditions, an increase in both domestic and international tourists can be expected in the coming years. The main negative consequence of this trend is a potential rise in environmental pollution over time.
Model validation and testing were conducted throughout the modeling process. These procedures involved examining the structural consistency of the model, including the coherence and compatibility of its various components, to determine whether the developed model was appropriate for achieving the intended objectives. One of the key tests applied in this study was the extreme conditions test, which evaluates whether the system exhibits expected behavior under extreme assumptions and whether the model structure responds appropriately.
For example, if the number of tourists and tourism revenues increase substantially, a corresponding and amplified increase in environmental pollution is expected. Model simulations confirmed that multiplying the tourist population and tourism revenue leads to a significant rise in environmental pollution levels, demonstrating that the model behaves logically under extreme conditions.
Sensitivity analysis focused on examining changes in model outputs resulting from variations in assumptions related to constant parameters. The results show that altering the tourism development budget, or more specifically, development expenditures across different sectors, leads to significant changes in the behavior of the average tourist population parameter. This indicates that the number of tourists is highly sensitive to tourism development costs.
Due to the interactions among different components of the system, the effects of selected factors on other parameters were further examined through the development of multiple scenarios.
In the first scenario, while holding all other factors constant, including initial indicator values and the availability of additional budget, the effect of tourism capacity on tourism revenue was analyzed. The results demonstrate that as a destination’s tourism capacity increases and its overall tourism position improves, both tourist arrivals and tourism revenues rise accordingly.
In the second scenario, it was assumed that no additional budget is allocated to tourism development in Shahdad. Under this condition, a reduction in the diversity of tourism attractions occurs, particularly due to limited exploration and restoration of historical and archaeological sites. Consequently, tourism attractiveness declines, followed by a decrease in local residents’ willingness to support tourism.
In the third scenario, the injection of additional funds into the tourism development system was considered. The results show that the availability of supplementary budgets leads to increased diversity of tourism attractions, preventing a decline in tourism attractiveness and supporting sustained tourism development.
In the fourth scenario, the implementation of specific tourism policies, such as the development of appropriate infrastructure, diversification of tourism attractions, and improvement of related services, results in increased local residents’ willingness and a rising trend in tourist arrivals compared to previous years.
In the fifth scenario, an increase in local residents’ willingness and international tourist arrivals leads to a corresponding rise in tourism revenues. As a consequence of this growth, environmental pollution levels also exhibit an upward trend relative to previous periods.
Discussion
Over the past half-century, the growth and development of tourism have played a significant role in economic and social activities [Sharpley, 2009] and have continued to expand. Even in periods of slower growth, tourism demonstrates a clear long-term upward trend. Some scholars consider tourism to be a panacea for regional development challenges; however, such a perspective is not entirely realistic, as the benefits of tourism may be accompanied by substantial negative impacts. An examination of the positive and negative effects of tourism indicates that decisions regarding tourism development must be made with great care. Social problems, insufficient investment, geographical constraints, and infrastructural issues, such as security, marketing, and promotion are among the factors that hinder the development of the tourism industry in a region. In addition, the lack of essential social infrastructure, including hotels, tourism facilities, cultural heritage sites, and similar amenities, represents one of the current social bottlenecks, the improvement of which requires systematic planning [Eslami Dolabi & Sheikhi, 2011].
In this study, the city of Shahdad can be considered both an example and a model of tourism development within the country. Shahdad is one of Iran’s important tourist destinations, and despite the significant growth in tourism demand in recent years, effective utilization of its tourism capacity and the realization of its positive outcomes have been limited. This situation is mainly due to several shortcomings, including inadequate promotion of natural attractions, weak infrastructure, insufficient welfare services, and poor accommodation facilities. Consequently, long-term planning is essential for sustainable tourism development in the region [Manafian & Daneshvar, 2014]. Undoubtedly, Shahdad attracts a large number of tourists throughout the year, and the influx of visitors beyond the region’s actual carrying capacity leads to various environmental, economic, and social consequences for local residents. In other words, the primary issue in recent years has not been a lack of tourism demand, but rather the absence of sufficient capacity and infrastructure to properly manage tourists in the region. This deficiency may even result in the degradation of tourism attractions and, in the long run, a decline in tourism demand [Rezaei et al., 2015].
In the present research, the tourism system of Shahdad was simulated using a system dynamics modeling approach. Given that tourism is closely associated with human systems, in which emotions and feelings play a crucial role in tourists’ decision-making processes, tourism development constitutes a complex, dynamic, and unstructured problem. Moreover, tourism development organizations do not have sufficient budgets to simultaneously address all relevant issues in the short term; therefore, prioritization is necessary. The sensitivity analysis conducted in this study revealed that the model is highly sensitive to the budget and expenditures allocated to tourism development in Shahdad. Accordingly, considering the limited tourism development budget of the Kerman Provincial Tourism Organization, various scenarios and policy options for budget allocation were designed. These included allocating a greater share of the budget to infrastructure, particularly entry and exit infrastructure allocating more funds to services with an emphasis on recreational facilities, and allocating increased resources to accommodation and welfare infrastructure, among other sectoral priorities.
Conclusion
If efforts are made to increase tourism demand without providing the necessary infrastructure to accommodate incoming tourists, the adopted development process is likely to fail. Therefore, achieving sustainable tourism objectives requires comprehensive training of all personnel employed in the tourism sector, along with concrete measures aimed at improving conditions and establishing the required infrastructure. Such actions contribute to balancing the tourism system and ultimately enable it to pursue its intended goals effectively.
The findings of this study assist policymakers by allowing them to test various tourism development policies within the proposed model and select the most appropriate strategy. Based on the simulation results, it is evident that tourism is a highly sensitive industry. In other words, both short-term and long-term planning, combined with strategic approaches, can provide the necessary foundation for the development and expansion of this sector. Furthermore, private-sector participation, through the establishment of tourism centers and offices in Shahdad and other regions, alignment with global tourism knowledge, and the provision of accurate information to tourists, can contribute significantly to the dynamism and sustainability of tourism development in the country.
Acknowledgments: The authors would like to express their sincere appreciation to the Kerman Provincial Organization of Cultural Heritage and Tourism for providing the required data for this research promptly and free of charge.
Ethical Permission: No ethical issues were reported by the authors.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Porkhosravani M (First Author), Statistical Analysis (34%); Shahzeidi SS (Second Author), Principal Researcher (33%); Azizi Zarandi A (Third Author), Introduction Writer/Discussion Writer (33%)
Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors
Today, tourism and the tourism economy are increasingly becoming one of the main pillars of the global commercial economy, and development planners and policymakers also regard the tourism industry as a fundamental pillar of sustainable development. In this regard, through sound planning and the identification of tourism advantages and limitations, it is possible to contribute to national development and the diversification of the national economy [Rokanuddin Eftekhari & Mahdavi, 2006]. This issue constitutes a complex and dynamic process encompassing economic, political, cultural, and environmental dimensions, which is influenced by the diverse and often conflicting interests and values of various groups and stakeholders and continues its dynamism according to different social and economic needs and the spatial capacities of each region [Negi, 2003]. Tourism can be described as the sum of phenomena and relationships arising from interactions among tourists, governments, host communities, universities, and non-governmental organizations in the processes of attraction, transportation, accommodation, and regulation of tourists and other visitors [Weaver & Oppermann, 2000], and it can become a driving force for sustainable development [World Tourism Organization, 2013].
Adopting a systems perspective on tourism policies allows for the examination of the various dimensions influencing this field. This approach not only contributes to a better understanding of this complex system, but also helps identify the root causes of problems in this sector and prevents superficial interventions that focus on addressing consequences rather than underlying causes [Kumar, 2012]. At present, tourism is one of the most dynamic economic activities, playing a significant role in development and generating numerous social, economic, environmental, and cultural benefits [Ebrahimzadeh et al., 2014]. In recent decades, government policies have emphasized tourism development as a means of combating unemployment and generating income; beyond the debates arising from increasing specialization and a production-oriented view of tourism, these policies also highlight the importance of flexibility in tourism development [Jansen & Lievois, 2003]. Consequently, tourism holds a special position in the development of geographical regions. When the dimensions and contexts related to tourism are properly identified, more effective scientific and practical steps toward regional development can undoubtedly be taken. This situation becomes more evident when a region possesses diverse and unique tourism potentials and, at the same time, tourism development can contribute to alleviating regional deprivation [Papoli Yazdi & Saghaei, 2006].
Given the multiplicity of sectors influencing the tourism industry, the application of a system dynamics approach plays an important role in evaluating tourism development in different regions. System dynamics was first introduced in the late 1950s by Jay Forrester at the Massachusetts Institute of Technology (MIT) as a method for modeling and simulating dynamic industrial systems. The foundation of system dynamics (SD) theory is that system behavior is determined by system structure, meaning that situations can be analyzed from an objective external perspective. Accordingly, real-world dynamic processes can be simulated using mathematical models. The problem-solving stages in the system dynamics approach include problem identification and definition, construction of a conceptual model (causal loop diagram), development of a mathematical model (stock–flow diagram), model simulation and validation, and the definition and analysis of different scenarios [Hosseinzadeh & Molavi, 2019].
In recent decades, researchers have conducted various studies using system dynamics models. Among these, Georgantzas [2003] have examined the quantity and value of hotels in Cyprus within the context of tourism system dynamics and explaines how Cyprus’s future strategy (2010) would affect tourist arrivals. Accordingly, the value chain of Cypriot hotels and tourists was examined, and several strategic scenarios were calculated using a system dynamics simulation model to explore what might occur in Cyprus’s tourism sector over the next 40 years. The scenario analysis showed that the sensitivity of the hotel value chain in Cyprus is related to parameters such as tourism policy, tourism growth, tourism seasonality, and other factors.
Jiang et al. [2010] have investigated investment in transportation infrastructure and the development of cultural heritage tourism in the historic villages of Xidi and Hongcun in southern China using a system dynamics model. The results showed that the effects of short- and long-term investments in transportation infrastructure on tourism development can be effectively predicted by this model. To achieve maximum tourism revenue, both villages can adopt an aggressive strategy involving continuous investment in transportation infrastructure and the utilization of existing land resources. Based on this approach, simulation-derived scenarios presented several development strategies and forecasts for the two villages over a 20-year period.
Mai and Kambiz [2011] examine tourism development using a participatory systems approach in the Cat Ba region of Vietnam. This study demonstrates that different stakeholders have different perceptions of the system and pursue different managerial objectives, and that these divergent expectations lead to unforeseen conflicts among stakeholders, which can negatively affect tourism development. Within this participatory approach, a comprehensive understanding of the interconnections and relationships among system components is essential for sustainable tourism development. Accordingly, the model was proposed as a framework for decision-making and capacity building by public and private stakeholders responsible for developing, managing, and conserving the system.
Kumar [2012] also investigates regional infrastructure planning and management for tourism development in the state of Orissa, India. This study employes a system dynamics approach and considered three key infrastructures including roads, railways, and accommodation facilities and demonstrates that the model can serve as an appropriate and reliable tool for forecasting, policymaking, and decision-making in planning and management, thereby providing a more favorable outlook for tourism development. The author emphasizes that these structures and the integration of their impacts exert significant effects on the tourism system.
Asasuppakit and Thiengburanathum [2014] evaluate sustainable urban infrastructure in Chiang Mai and its impacts on tourism. The aim of this study is to develop an urban infrastructure assessment model using a system dynamics approach as a key decision-support system, focusing on the city’s transportation carrying capacity. The development of causal loop diagrams and a city framework model as a case study demonstrated the analysis of the impacts of urban infrastructure on tourism.
Mai and Smith [2018] have conducted another study on scenario-based planning for tourism development using system dynamics modeling on Cat Ba Island, Vietnam. The results indicate that the current trajectory of tourism development on Cat Ba Island is unsustainable, and that growth constraints may be reached by 2022 due to water shortages, pollution, and overcrowding. Over time, this tourism destination exceeds its growth limits, increasing the risk of carrying capacity erosion through resource depletion and environmental degradation.
Sedarati et al. [2019] have examined the application of system dynamics in tourism planning and development. Following a systematic literature review, 27 articles are selected and analyzed, revealing that the system dynamics method is highly suitable for addressing numerous problems and offers considerable potential for providing tourism decision-makers and supervisors with strategic and operational policy development tools across different levels of analysis.
Wang et al. [2020] have evaluated tourism carrying capacity and its impacts on urban tourism economic growth in China, defining carrying capacity as a destination’s ability to absorb tourists. In this macro-level system dynamics model, three subsystems and 47 parameters are considered. Nine urban tourism destinations in China are selected as study cases. The results indicate that, in order to promote sustainable tourism development, management should focus on environmental policies and tourist management.
Pizzitutti et al. [2017] conduct a study on scenario planning for tourism management using system dynamics modeling and developed dynamic models for electricity, goods, land, and accommodation infrastructure over medium- and long-term horizons. Fu et al. [2011] examine the sustainability of the tourism industry in China and used a dynamic systems model as a tool to analyze government policies for sustainable tourism development. This model includes four fundamental components: tourists, tourism facilities, environmental impacts, and government revenue.
Ran [2012] have sought to improve understanding of the values of different tourism stakeholders and their impacts on tourism development by proposing a system-based model for the Gucheng area of Lijiang City, China. Through modeling, simulation, and testing, various factors influencing tourism development, such as marketing, tourism service capacity, economic growth, and natural resources are identified. The model was then tested, and different policies for sustainable tourism development were proposed and evaluated, along with their positive and negative impacts.
Jakulin [2017] examines systems approaches to tourism and, accordingly, map the elements of the tourism industry. Using the iceberg metaphor, the study presents a clear depiction of the tourism industry and ultimately identified the systems approach as one of the most appropriate and practical approaches for addressing complex issues such as tourism. In Iran, the application of this method in tourism studies is limited, and only a small number of studies have addressed systems approaches to tourism, including [Samadi et al., 2012; Zare Mehrjerdi et al., 2014; Mohammadi et al., 2017; Moghimi & Mohaghar, 2018; Hosseinzadeh & Molavi Arabshahi, 2018; Dabbagh & Khatami, 2020].
Considering the importance of the issue and the diversity of natural, historical, archaeological, and ecotourism attractions in the Shahdad region located in the western Lut Desert, this city was selected as the case study. The region is recognized as one of Iran’s major tourism hubs and is experiencing rapid tourism development. Accordingly, this study seeks to evaluate and analyze tourism development in this region using a system dynamics approach.
Methodology
This study was applied in nature and adopted a descriptive–analytical approach. A system dynamics methodology was employed in this research. This approach was introduced in the early 1960s by Jay Forrester at the Massachusetts Institute of Technology (MIT). System dynamics was an approach for modeling and simulating complex physical and socio-economic systems, through which policies for managing and transforming such systems can be formulated [Samadi et al., 2012]. This method integrates behavioral and social sciences with detailed planning and accounting techniques and requires the design and construction of innovative models involving a large number of interacting parameters. System dynamics was particularly applicable in situations involving complex and critical decision-making processes, where an integrated insight into fundamental problems is required, problems that may influence outcomes over years or even decades. This approach assists policymakers and decision-makers in evaluating the advantages and disadvantages of existing or potential policy options.
System dynamics has strong capacity for strategic, macro-, micro-, and cross-sectoral planning, and its application leads to the design of effective organizations and policies. In contexts characterized by high diversity among components and parameters, it enabled the explanation, prediction, and monitoring of structures and behaviors. In such cases, conventional econometric and planning methods were often ineffective, as they were unable to incorporate all model parameters within a comprehensive system or accurately predict potential future events. Therefore, in the present study, a system dynamics model was used to achieve a better understanding of the relationships among parameters [Sterman, 2010].
System dynamics is a hybrid methodology comprising both quantitative and qualitative components. In the quantitative phase, in addition to reviewing library and documentary sources, previous studies in this field and in-depth interviews with experts were used to identify the parameters involved in the model, the main factors influencing tourism, and the relationships among them. In the qualitative phase, the primary parameters were first identified, after which the influence of each parameter on others, independently of additional parameters, was examined. Furthermore, a questionnaire was distributed among experts to determine certain initial values. After developing the causal logic of the model, its conceptual structure was reviewed and validated by specialists in the field.
In the quantitative phase, initial data were collected from the Kerman Provincial Organization of Cultural Heritage, Handicrafts, and Tourism, as well as from subject-matter experts. These data were used to calculate the initial values of state parameters in the model, as well as constants and exogenous parameters, which were expressed in percentage terms. Model development, simulation, and validation were carried out using Vensim software (version 9.2.2). Given the broad applicability of system dynamics modeling to various issues, Sterman proposed five stages for implementing this method. Accordingly, the problem-solving process using a system dynamics approach includes: (1) problem identification and definition (establishing a clear problem framework); (2) development of a conceptual model; (3) construction of a mathematical model; (4) model simulation and validation; and (5) definition and analysis of alternative scenarios [Hosseinzadeh & Molavi, 2019].
Location of the Study Area
Shahdad city is located in the western part of the Lut Plain, in the northeastern region of Kerman Province, and historically served as the center of the ancient Aratta region. To the southwest, it borders the mountainous and cold regions of Sirch, with elevations exceeding 4,000 meters, while to the northeast it connects to desert areas. To the east, it lies approximately 30 kilometers from the Lut Plain and overlooks a region known as Takab, which constitutes the core area of Shahdad. The average annual precipitation in the region is less than 30 millimeters [Ramesht & Shahzeidi, 2008]. The plain in which Shahdad is situated is formed at the confluence of three rivers: Kharashkan, Shahdad, and Jaftan. The Shahdad River flows through a tectonic valley and is a perennial river that supplies water to the region. The Shahdad Kaluts are located approximately 43 kilometers from the city, with an average length of 145 kilometers and an average width of 80 kilometers, and are commonly referred to as the legendary Lut Desert [Ghazanfarpour et al., 2020].
Model Development and Flow Structure
System dynamics is a method for studying and managing complex systems characterized by feedback processes. Due to interactions among different components of a system, understanding system behavior requires a systemic perspective. Such understanding can only be achieved through comprehensive examination of all components and the relationships among them within a unified system. Models are simplified representations of reality, and the primary objective of system dynamics modeling is to gain insight into system relationships in order to examine potential policies for system improvement.
In system dynamics, various tools are employed to represent system structure and enhance understanding. One of the most important aspects of this approach is identifying key subsystems and their interactions within the overall system. In this study, an effort was first made to identify the main subsystems of the Shahdad tourism system and present them in an integrated conceptual framework [Asadi, 2015]. This framework formed the basis for understanding the interactions and feedback mechanisms governing tourism development in the study area.
To develop the subsystem structure and overall model logic, relevant literature on dynamic modeling, particularly in tourism studies was thoroughly reviewed. Indicators and parameters were identified based on previous research, including tourism income, tourist population, tourist inflow and outflow, attraction diversity, time-related factors, tourist satisfaction, tourism carrying capacity, environmental pollution, and local residents’ willingness to support tourism development [Samadi et al., 2012; Lajevardi et al., 2019; Asadi, 2015; Hosseinzadeh & Molavi, 2018; Nasim Sobhan et al., 2015; Dabbagh & Khatami, 2020]. The structure of the model was then developed in accordance with the principles of system dynamics modeling [Sterman, 2000].
The proposed model structure was reviewed by experts in dynamic modeling from the University of Tehran and Shahid Bahonar University of Kerman. In addition, interviews were conducted with university faculty members and officials from the Kerman Provincial Organization of Cultural Heritage and Tourism to incorporate both academic and practical insights. The quantitative relationships among parameters were adopted from established studies [Hosseinzadeh & Molavi, 2018; Nasim Sobhan et al., 2015] and validated by domain experts. After integrating the model components, simulations and validation procedures were carried out, and the results, including sensitivity analyses, were reviewed by experts. Based on their feedback, the necessary modifications were applied, and the final results were updated accordingly.
Findings
The parameters used in the Shahdad tourism system include different types of state, flow, and auxiliary parameters, each defined with specific measurement units appropriate to the tourism system. The initial values of key state parameters, such as tourism attractions, local residents’ willingness to support tourism, and constant parameters of the model, were obtained from the Kerman Provincial Organization of Cultural Heritage, Handicrafts, and Tourism, as well as through interviews with domain experts. The values of these parameters were considered to vary within a range of 0 to 100 percent.
It should be noted that the primary application of the system dynamics approach lies in situations where the behavior of a phenomenon emerges from natural dynamics and the interactions among endogenous system parameters. In this study, it was assumed that the system follows its general and natural development trajectory; therefore, the system dynamics approach was considered appropriate for analyzing the tourism system. Throughout the research process, an important assumption was maintained: the values of system parameters are largely determined through their interactions with one another. After collecting the required data, comprising statistical information provided by experts and the provincial cultural heritage and tourism organization, the relationships among different system components were established through numerical functions, and the overall behavior of the model was examined. Once the model was executed without errors and the functional relationships were correctly specified, the software confirmed the dimensional consistency of the model. Given that the simulation results were consistent with real-world conditions, the model was subsequently used to simulate future periods.
Following model execution and simulation of the factors influencing tourism development in Shahdad, the behavior of key parameters, model validation outcomes, and sensitivity of model parameters were analyzed. Based on these results, different development scenarios were examined.
The simulation results indicate that, during the initial phase of the simulation period, population growth does not increase as expected; in other words, the willingness of local residents to remain in or engage with the region declines when no additional budget is allocated for tourism development or when issues such as inadequate infrastructure, lack of security, and similar constraints persist. Under such conditions, a reduction in population is accompanied by a relative decrease in environmental pollution compared to previous periods. However, if policymakers and authorities devote greater attention to the region, population levels and local residents’ willingness are expected to increase over subsequent periods, eventually leading to population growth. This increase reflects a higher demand for expanded capacities within the region. In turn, increased tourism capacity contributes to higher tourism revenues and ultimately enhances tourist satisfaction. If the tourism industry continues to operate under these improved conditions, an increase in both domestic and international tourists can be expected in the coming years. The main negative consequence of this trend is a potential rise in environmental pollution over time.
Model validation and testing were conducted throughout the modeling process. These procedures involved examining the structural consistency of the model, including the coherence and compatibility of its various components, to determine whether the developed model was appropriate for achieving the intended objectives. One of the key tests applied in this study was the extreme conditions test, which evaluates whether the system exhibits expected behavior under extreme assumptions and whether the model structure responds appropriately.
For example, if the number of tourists and tourism revenues increase substantially, a corresponding and amplified increase in environmental pollution is expected. Model simulations confirmed that multiplying the tourist population and tourism revenue leads to a significant rise in environmental pollution levels, demonstrating that the model behaves logically under extreme conditions.
Sensitivity analysis focused on examining changes in model outputs resulting from variations in assumptions related to constant parameters. The results show that altering the tourism development budget, or more specifically, development expenditures across different sectors, leads to significant changes in the behavior of the average tourist population parameter. This indicates that the number of tourists is highly sensitive to tourism development costs.
Due to the interactions among different components of the system, the effects of selected factors on other parameters were further examined through the development of multiple scenarios.
In the first scenario, while holding all other factors constant, including initial indicator values and the availability of additional budget, the effect of tourism capacity on tourism revenue was analyzed. The results demonstrate that as a destination’s tourism capacity increases and its overall tourism position improves, both tourist arrivals and tourism revenues rise accordingly.
In the second scenario, it was assumed that no additional budget is allocated to tourism development in Shahdad. Under this condition, a reduction in the diversity of tourism attractions occurs, particularly due to limited exploration and restoration of historical and archaeological sites. Consequently, tourism attractiveness declines, followed by a decrease in local residents’ willingness to support tourism.
In the third scenario, the injection of additional funds into the tourism development system was considered. The results show that the availability of supplementary budgets leads to increased diversity of tourism attractions, preventing a decline in tourism attractiveness and supporting sustained tourism development.
In the fourth scenario, the implementation of specific tourism policies, such as the development of appropriate infrastructure, diversification of tourism attractions, and improvement of related services, results in increased local residents’ willingness and a rising trend in tourist arrivals compared to previous years.
In the fifth scenario, an increase in local residents’ willingness and international tourist arrivals leads to a corresponding rise in tourism revenues. As a consequence of this growth, environmental pollution levels also exhibit an upward trend relative to previous periods.
Discussion
Over the past half-century, the growth and development of tourism have played a significant role in economic and social activities [Sharpley, 2009] and have continued to expand. Even in periods of slower growth, tourism demonstrates a clear long-term upward trend. Some scholars consider tourism to be a panacea for regional development challenges; however, such a perspective is not entirely realistic, as the benefits of tourism may be accompanied by substantial negative impacts. An examination of the positive and negative effects of tourism indicates that decisions regarding tourism development must be made with great care. Social problems, insufficient investment, geographical constraints, and infrastructural issues, such as security, marketing, and promotion are among the factors that hinder the development of the tourism industry in a region. In addition, the lack of essential social infrastructure, including hotels, tourism facilities, cultural heritage sites, and similar amenities, represents one of the current social bottlenecks, the improvement of which requires systematic planning [Eslami Dolabi & Sheikhi, 2011].
In this study, the city of Shahdad can be considered both an example and a model of tourism development within the country. Shahdad is one of Iran’s important tourist destinations, and despite the significant growth in tourism demand in recent years, effective utilization of its tourism capacity and the realization of its positive outcomes have been limited. This situation is mainly due to several shortcomings, including inadequate promotion of natural attractions, weak infrastructure, insufficient welfare services, and poor accommodation facilities. Consequently, long-term planning is essential for sustainable tourism development in the region [Manafian & Daneshvar, 2014]. Undoubtedly, Shahdad attracts a large number of tourists throughout the year, and the influx of visitors beyond the region’s actual carrying capacity leads to various environmental, economic, and social consequences for local residents. In other words, the primary issue in recent years has not been a lack of tourism demand, but rather the absence of sufficient capacity and infrastructure to properly manage tourists in the region. This deficiency may even result in the degradation of tourism attractions and, in the long run, a decline in tourism demand [Rezaei et al., 2015].
In the present research, the tourism system of Shahdad was simulated using a system dynamics modeling approach. Given that tourism is closely associated with human systems, in which emotions and feelings play a crucial role in tourists’ decision-making processes, tourism development constitutes a complex, dynamic, and unstructured problem. Moreover, tourism development organizations do not have sufficient budgets to simultaneously address all relevant issues in the short term; therefore, prioritization is necessary. The sensitivity analysis conducted in this study revealed that the model is highly sensitive to the budget and expenditures allocated to tourism development in Shahdad. Accordingly, considering the limited tourism development budget of the Kerman Provincial Tourism Organization, various scenarios and policy options for budget allocation were designed. These included allocating a greater share of the budget to infrastructure, particularly entry and exit infrastructure allocating more funds to services with an emphasis on recreational facilities, and allocating increased resources to accommodation and welfare infrastructure, among other sectoral priorities.
Conclusion
If efforts are made to increase tourism demand without providing the necessary infrastructure to accommodate incoming tourists, the adopted development process is likely to fail. Therefore, achieving sustainable tourism objectives requires comprehensive training of all personnel employed in the tourism sector, along with concrete measures aimed at improving conditions and establishing the required infrastructure. Such actions contribute to balancing the tourism system and ultimately enable it to pursue its intended goals effectively.
The findings of this study assist policymakers by allowing them to test various tourism development policies within the proposed model and select the most appropriate strategy. Based on the simulation results, it is evident that tourism is a highly sensitive industry. In other words, both short-term and long-term planning, combined with strategic approaches, can provide the necessary foundation for the development and expansion of this sector. Furthermore, private-sector participation, through the establishment of tourism centers and offices in Shahdad and other regions, alignment with global tourism knowledge, and the provision of accurate information to tourists, can contribute significantly to the dynamism and sustainability of tourism development in the country.
Acknowledgments: The authors would like to express their sincere appreciation to the Kerman Provincial Organization of Cultural Heritage and Tourism for providing the required data for this research promptly and free of charge.
Ethical Permission: No ethical issues were reported by the authors.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Porkhosravani M (First Author), Statistical Analysis (34%); Shahzeidi SS (Second Author), Principal Researcher (33%); Azizi Zarandi A (Third Author), Introduction Writer/Discussion Writer (33%)
Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors
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