Evolutionary game analysis of land income distribution in tourism development

Abstract

Social stability is the key to the sustainable development of tourism destinations. And reasonable distribution of land revenue during tourism development can effectively avoid social conflicts at these destinations. This study explores the dynamic nature and stabilization of land revenue distribution for tourism development. It does so by developing an evolutionary game model. In this model, the main stakeholders include the government, developers and local communities, and analysis of the model indicates that the process of distributing land revenue is profoundly influenced by land transfer methods. Specifically, a developer chooses land transfer methods by weighing the land cost (consisting of land prices and taxes) or the benefit under non-cooperation with different land transfer methods. Meanwhile, the local community chooses whether to cooperate by considering the land income (consisting of land prices) or non-cooperative benefits. With different game sequences, the stakeholders will consider different conditions. Moreover, government taxation and subsidization policies are found to have little influence on the land transfer market in the long run. Instead, to avoid potential conflicts and social instability, the government should provide a good political environment for community participation. This study offers important implications for policymaking involving land income distribution for tourism destinations.

Keywords

community participation evolutionary game analysis land transfer revenue distribution tourism development

Introduction

Sustainable development of tourism destinations is an important topic that underpins contemporary approaches to tourism destination planning and management (Andrades and Dimanche, 2017; Ruhanen, 2012). Destination planning and management require considerations from different perspectives, such as economics, ecology, society and culture. The development of tourism may lead to spatial conflicts (Aswani et al., 2015), which are often costly and time-consuming and may cause social instability in tourism destinations (Williams et al., 1998). Meanwhile, social stability is also of utmost importance to the sustainability of destinations, without which it will have repercussions for the tourism development, such as the dwindling tourists, and, therefore, should be carefully maintained.

Many current conflicts in tourism destinations are caused by problems related to land use and community benefits (Adeyinka-Ojo et al., 2014). In many destinations, especially those in developing countries, the distribution of economic benefits – particularly land revenue distribution – is a major cause of conflicts (Bao and Sun, 2006). Land resources are non-renewable, and, in general, land use conflicts are prevalent in developing countries. Moreover, in contrast to government entities and developers, local communities scarcely benefit from land transfers, owing either to the communities’ lack of negotiating power or the absence of public consultation procedures in these countries (Higgins-Desbiolles, 2018).

Landowners could be individuals (e.g. Western countries) or communities (e.g. China). Except for a few countries where the transaction of landownership is forbidden, private interests can buy or lease private land from its owners to improve the economic efficiency of land use (Holden and Otsuka, 2014; Kytzia et al., 2011). The distribution of land revenue in tourism development largely depends on land transfer methods. However, in most countries, the transaction of private land is still under the control of the government by registration. Therefore, in the game of land revenue distribution, three types of players have consistently been involved – namely, the government, the developer and the local community.

Evolutionary game theory is a classical paradigm adopted extensively to study the interaction among agents and provide a framework for the analysis of stakeholders with bounded rationality (Roca et al., 2009; Wallace and Young, 2015). The latter is of considerable value to investigate issues related to fairness and efficiency. On the basis of the evolutionary game analysis, this research analyses the game of land income distribution in tourism development among government, developers and local communities, which will contribute to the understanding of the interaction between three key stakeholders in decision-making process and the influence of different land transfer methods on land income distribution in tourism development. By identifying the evolutionary stable strategies (ESS) of the three players, this study offers other policy insights from the perspective of community participation to help reduce conflicts and promote sustainable development of tourism destinations.

Literature review

Tourism destination development and land transfer

Rational development of tourism based on scientific evidence can help expedite the process of urbanization and promote the economic development of urban and rural areas (Xi et al., 2013; Zamfir and Corbos, 2015). However, a few tourism destinations are facing the problem of approaching their growth limit (Kytzia et al., 2011; Perles-Ribes et al., 2017). In this case, political environment is the key to the sustainable development of tourism (Absalyamov et al., 2019: 389–395; Scheyvens, 2018). A good tourism policy can help the destination achieve rapid tourism growth, whereas political instability can lead to a significant tourism recession (Andrades and Dimanche, 2017; Henderson, 2006, 2015). Besides, the negotiating power of stakeholders is unequal in the game of tourism development where the policymakers are in a dominant position in the most circumstances (Andergassen et al., 2017; Andrew et al., 2017). However, few tourism policymakers would prioritize the environmental benefits over the economic output when it comes to land use-related issues (Nesheim et al., 2014).

Many problems in the development of rural tourism result from unfair revenue distribution (Zhou and Huang, 2004). Land transfer methods, consisting of either land sales or leases, play a major role in community participation in tourism development land revenue distribution. In the land sales market, the redistribution of private land seems administrative (Teklu and Lemi, 2015). In most countries, sales of private land require government permission, as the government has a priority right to purchase the land. However, it easily leads to bribery and corruption (Koroso et al., 2013) as well as a negative attitude among landowners, resulting from unreasonable land compensation and resettlement (Liang and Zhu, 2015). Moreover, local communities resist land sales because of past bad experiences, such as enforced and environmentally unfriendly projects. Such resistance is also caused by the land attachment of landowners (Lisec et al., 2014). By contrast, the land rental market is spontaneously formed in the private sector, owing to a shortage of land resources. To a certain extent, the rental market is more vital for land access by the poor (Jin and Deininger, 2010). However, redistributing the land to more productive managers can help increase the economic efficiency of land use (Chamberlin and Ricker-Gilbert, 2016; Teklu and Lemi, 2015; Vranken and Swinnen, 2006).

The effectiveness of land transfer is subject to policies of land price and land transfer methods (Forbord et al., 2014; Renard, 2000: 159–190). The government typically participates in the land transfer market through land registration and taxation, which has even become a primary income source for some local governments (Takeuchi, 2013). In the short term, adjustment in tax policy can change the timing and revenue of a land transfer transaction. However, in the long run, tax policies have no impact on the land market (Nirmal, 2017: 89–103), and market forces likely outweigh the government’s power in the land transfer (Borras, 2005).

Community participation

Along with the government and the developer, the local community is a key pillar in the sustainable development of tourism (Higgins-Desbiolles, 2018). Given the situation that different stakeholders often have different attitudes towards tourism development, reaching an agreement among them is difficult. The key to solve such conflicts is to have a thoroughly consideration of different perspectives from stakeholders in tourism planning and development (Ruhanen, 2012; Simpson, 2001). In particular, the community should be encouraged to participate in the process of land use and tourism planning (Fallon and Kriwoken, 2003; Williams et al., 1998). By enhancing the negotiating power of the community in the distribution of tourism development revenue, community participation provides a possible approach to solving conflicts and promotes a rational distribution of tourism revenue. However, a conservative political environment may prevent local communities from participating in tourism development, especially in developing countries (Mihalič et al., 2016; Tosun, 2000). In addition, the direct intervention of government tends to weaken the discourse power of local communities in decision-making (Taylor, 2007).

Community participation is a double-edged sword for tourism development. On the one hand, with a better understanding of tourism destinations, the local community can help promote the success of a tourism project. If the community is in agreement on tourism development, then community representatives can be elected to participate in the process and increase decision-making efficiency (Irvin and Stansbury, 2004). However, the contribution of local communities can be wasted because public consultation is often ignored by other powerful stakeholders such as developers and even the government (Davidson et al., 2007). On the other hand, community participation may decrease the efficiency of decision-making and increase the costs of tourism development if the members hold different opinions (Hardy and Pearson, 2017; Rasoolimanesh et al., 2017; Tosun, 2006). It is much more common in the real world that heterogeneity exists in local communities due to residents having different income levels, various family backgrounds and especially different involvement in tourism (Alesina and La-Ferrara, 2000). Even if most of the residents support the tourism project, some of them are probably still uncooperative and aggressive, and may have conflicts with the developer. However, these potential risks should not be taken as an excuse for governments and developers to neglect public consultation. In existing cases, communities’ opinions have become the key to the success of tourism projects because community members have a better understanding of the local area (Higgins-Desbiolles, 2018).

Evolutionary game theory

Traditional game theory takes the Nash equilibrium as its core foundation. Each economic agent is assumed to pursue maximum profits and can analyse all the information without any limitation (Fatima et al., 2005). Apart from the hypothesis of perfect rationality, the game structure and environment are also assumed to be determined before the game occurs (Wang et al., 2011). Thus, traditional game analysis is based on a static viewpoint, which scarcely explains why players keep adjusting their behaviour to maximize their payoff (Hofbauer and Sigmund, 2003). In the real world, economic agents are not constantly rational or foresighted, and they commonly discover the best strategy through trial-and-error, whereby the game could reach a stable point in the long term (Newton, 2018). Therefore, the idea of robust equilibrium is introduced from biological evolutionary theory into evolutionary game theory, forming the concept of the evolutionary stable strategies (ESS) (Roca et al., 2009).

In evolutionary game theory, although game players have bounded rationality, they can still learn via genetic algorithm learning. Social rather than individual learning – generally through imitation, communication and experimentation (Fatima et al., 2005; Reichmann, 1999) – can be employed to promote the sustainable development of tourism destinations (Fuchs et al., 2014; Schianetz et al., 2007). For economic agents, the best strategy for players may not be the one with maximum individual profits but the one with the best response to the potential strategies of opponents with bounded rationality (Ellingsen, 1997; Fatima et al., 2005; Rees et al., 2009; Wallace and Young, 2015). In addition, the evolution of players’ behaviour affects the rules and environment of the game as well as the players’ reputation and commitment (Frechette et al., 2015; Newton, 2018).

In existing tourism sociology research, game theory is often utilized to investigate issues such as low-carbon tourism, sustainable tourism, tourism corporate social responsibility and cooperation and competition in regional tourism that involves the government, the developer and the tourist (He et al., 2018; Theodoulidis et al., 2017; Weng and Li, 2017). While the local communities in tourism destinations are also the key pillar in tourism development, in practice their importance is often overlooked by other powerful stakeholders. In the recent literature, only the game model proposed by Yang et al. (2015) considered communities together with the government and developers. However, Yang et al. (2015) primarily focused on the payoff of tourism development, such as tax, land price and employment, and did not address the influence of land transfer methods on community participation in tourism revenue distribution. The latter will be the focus as follows.

Model

Research variables

In this article, a model is set to simulate conditions in tourism development land revenue distribution and to seek a solution when there is a disagreement among the three stakeholders (government, developer and the local community). Since conflict in tourism development is usually caused by land revenue distribution, if the developer has no intention to begin a transaction, obviously no conflict exists. Developers tend to initiate a transaction with the local community if they find a prime location for a tourism project. This implies that the developer intends to use the land for a tourism project but has not decided how to obtain land use rights. Therefore, in this model, the developer’s choice is which land transfer method to use instead of whether to use the land or not.

Developing a new tourism project typically requires a large amount of land, and the developer may choose to purchase or rent private land. The project development typically involves a game among the government, the developer and the local community. First, the government has two choices: (1) to subsidize the land transfer for tourism development (in spite of taxation, subsidies are provided to financially support the developer and the local community) and (2) not to subsidize the land transfer for tourism development and levy land transfer taxes. Subsequently, the developer has two options as well: (1) to buy private land from the community under government permission, with a lump sum of land cost (including land price and land transfer tax), and (2) to rent the land from the local community with an annuity. Lastly, the local community has two choices: (1) to cooperate with the other stakeholders when all the residents reach an agreement, promote the development of the tourism project and obtain land income (a lump sum or an annuity), and (2) not to cooperate or even block the tourism project when there is disagreement within the community. In this way, the local community cannot obtain new land revenue and may have to pay a high price of legal costs, fines or penalties for taking inappropriate actions to clash with the developer.

This evolutionary game model of government, developer and local community aims to analyze the land income distribution in tourism development. To simplify the model, the following assumptions were taken: first, the three players are specific economic agents. The government comprises the policymaker of tourism destination development, the developer comprises the project investor and the local community comprises the landowner. All the players are assumed to pursue maximum economic benefits. Secondly, the three players have bounded rationality, but they can obtain information and gain experience by individual and social learning. Therefore, the government and developer can make decisions based on their own multiple experiences as well as the experiences of others. In terms of the local community, however, there are two situations. One is that the local community can also learn by both methods in the land rental market. The other is that they can learn from other communities by social learning, even when each community can only participate in the land sales market once the transaction is completed.

On the basis of different strategies, the three players will have different costs and benefits (see Table 1 for all the variables). Three points require clarification in advance: first, only when the local community chooses to cooperate and the land transfer transaction is completed will the government subsidies, land transfer tax and land cost/benefit materialize. Secondly, except for the decision probabilities of each stakeholder (x, y and z) range from 0 to 1, all the variables are set to range in $[0, + \infty)$ . Last but not least, to compare a lump sum with an annuity in the same model, the present value interest factor of annuity (PVIFA) is introduced into this model. The abbreviation of PVIFA's formula is $(P / A, i, n)$ , containing the average interest rate during the operating period (represented as $i$ ) and the operating period (represented as $n$ ). All the variables regarding annuity are defined as the present value of the annuity in this model. For instance, the developer’s benefit from the tourism project refers to the present value of the project income that the developers obtain annually during the operating period. That is, the total developer’s revenue of the tourism project is equal to the average annual project revenues × $(P / A, i, n)$ , which is similar as the benefits/costs of land rental tax and the land rental – the total land rental tax/land rental is equal to the annual land rental tax/land rental × $(P / A, i, n)$ .

(1) Cost–benefit analysis of the government

Table 1.

Variables of the research.

Government	Developer	Local community
α: The cost of subsidizing the developer	$R$ : The present value of project annual revenue	β: The government’s subsidies
β: The cost of subsidizing the local community	α: The government’s subsidies	$l_{1}$ : The present value of land rental revenue
β: The cost of subsidizing the local community	$l_{1}$ : The present value of land rental cost	$l_{2}$ : The revenue from land sales
$t_{1}$ : The present value of land rental tax	$l_{2}$ : The price cost of purchasing the land	φ: The cost of community participation
$t_{2}$ : The tax from land sales	$t_{1}$ : The present value of tax cost of land lease	$r_{1}$ : The benefit of community participation
θ: The cost of coordinating the project	$t_{2}$ : The tax cost of land purchase	ε: The cost of resisting
θ: The cost of coordinating the project	$i_{1}$ : The benefit of negotiation	ε: The cost of resisting
$g$ : The cost of handling the resistance	μ: The cost of negotiation	$r_{2}$ : The benefit of resisting
$g$ : The cost of handling the resistance	$i_{2}$ : The benefit from protest	$r_{2}$ : The benefit of resisting
σ: Rent-seeking revenue	γ: The cost from protest
σ: Rent-seeking revenue	σ: The cost of rent-seeking

Note: All the above variables are set to range in $[0, + \infty)$ .

When the government chooses to subsidize the transfer of land for tourism development, it will provide subsidies to the developer and the local community. The government cost of supporting the developer is set as α, and that of subsidizing the local community is set as β. If the land is transferred, then the government will receive a certain amount of tax. The present value of the annual tax revenue is set as $t_{1}$ when the land is rented, and the tax revenue as $t_{2}$ when the land is sold. Normally, the government does not enter the land rental market directly. However, when the government subsidizes land transfer for tourism development, and when the community also has a non-cooperative attitude to prevent the project from being implemented, the government will help coordinate the project, and the coordination cost of the government is set as θ. If the government does not subsidize the land transfer, then it will not intervene. In the land sales market, when the government does not subsidize the land transfer, the developer may seek rental from the government to obtain permission for tourism development land use. The government’s rent-seeking income is set as σ. In this case, however, if the community has a non-cooperative attitude, conflicts will likely break out, where the government must pay a certain amount of governance costs, set as g.

(2) Cost–benefit analysis of the developer

In a given tourism destination, all else being equal, the revenue of a specific tourism project is relatively fixed regardless of land transfer method. The present value of annual project income for the developer is set as $R$ . If the government subsidizes land transfer for tourism development, then the developer can also receive government subsidies (α). If the government does not subsidize the land transfer of tourism development, then the developer will seek rental from the government to gain permission to use the land in the tourism project. The developer’s rent-seeking cost is set as σ.

When the developer chooses to lease, the present value of the land lease price is set as $l_{1}$ , and the present value of the land lease tax is set as $t_{1}$ . If the community chooses not to cooperate, then the developer will negotiate with the community and set the developer’s negotiation cost to μ. However, the negotiation may also bring benefits to the developer, set as $i_{1}$ ; when the developer chooses to purchase, the purchase cost of land price is $l_{2}$ , and the tax cost of land purchase is $t_{2}$ . If the community chooses not to cooperate, given that the redistribution of land resources is generally dominated by the government, then the community may take actions to enhance its bargaining power. The developer’s loss caused by community protests is set as γ. In certain cases, the protests may also bring benefits to the developer (e.g. a good image of actively dealing with conflicts is widely reported by the media), which is set as $i_{2}$ .

(3) Cost–benefit analysis of the community

If the local community chooses to cooperate, then it can obtain land rental annually. The present value of the annual rental is set as $l_{1}$ and the land sales income as $l_{2}$ . At this time, if the government chooses to subsidize the land transfer for tourism development, then the local community can obtain government subsidies (β). However, if the community chooses a non-cooperative attitude when the land is leased, the developer will negotiate with the community for land revenue distribution. The community’s cost to participate in the negotiation is $φ$ , but it may also bring certain benefits, set as $r_{1}$ . Similarly, when the land is sold, the local community may take actions to resist, which may bring benefits ( $r_{2}$ ) to the community as well as costs (ε).

Research model and propositions

In the game of land income distribution in tourism development, each player has two different strategies: (1) the government has the probability of $x$ to subsidize the land transfer of tourism projects as well as the probability of $1 - x$ to choose not to subsidize; (2) the developer has the probability of $y$ to rent the land, and the probability of $1 - y$ to purchase the land; and (3) the local community has the probability of $z$ to choose cooperation, and the probability of $1 - z$ to have a non-cooperative attitude.

On the basis of the evolutionary game matrix of land income distribution (see Table 2), the expected benefits from each strategy of the government and the averaged benefit of the government’s strategies can be computed. The expected benefit of the strategy to subsidize is

Table 2.

Evolutionary game matrix.

G	D	LC	G	D	LC
$S (x)$	$R (y)$	$C (z)$	$t_{1} - α - β$	$R + α - l_{1} - t_{1}$	$β + l_{1}$
	$R (y)$	$NC (1 - z)$	$- θ$	$i_{1} - μ$	$r_{1} - φ$
	$P (1 - y)$	$C (z)$	$t_{2} - α - β$	$R + α - l_{2} - t_{2}$	$β + l_{2}$
	$P (1 - y)$	$NC (1 - z)$	$- g$	$i_{2} - γ$	$r_{2} - ε$
$NS (1 - x)$	$R (y)$	$C (z)$	$t_{1}$	$R - l_{1} - t_{1}$	$l_{1}$
	$R (y)$	$NC (1 - z)$	0	$i_{1} - μ$	$r_{1} - φ$
	$P (1 - y)$	$C (z)$	$t_{2} + σ$	$R - l_{2} - t_{2} - σ$	$l_{2}$
	$P (1 - y)$	$NC (1 - z)$	$σ - g$	$i_{2} - γ - σ$	$r_{2} - ε$

Note: G: government; D: developer; LC: local community; S: subsidization; NS: non-subsidization; R: rent; P: purchase; C: cooperation; NC: non-cooperation. The variables of x, y and z range from 0 to 1.

E {(G)}^{x} = y z (t_{1} - α - β) - y (1 - z) θ + (1 - y) z (t_{2} - α - β) - (1 - y) (1 - z) g

The expected benefit of the strategy not to subsidize is

E {(G)}^{1 - x} = y z t_{1} + (1 - y) z (t_{2} + σ) + (1 - y) (1 - z) (σ - g)

Then the averaged benefit of both government’s strategies is

E (G) = x E {(G)}^{x} + (1 - x) E {(G)}^{1 - x} = y z t_{1} + (1 - y) z t_{2} + (1 - x) (1 - y) σ - x y (1 - z) θ - x z (α + β) - (1 - y) (1 - z) g

Thereafter, the replicator dynamic equation of the government’s strategy $F (G)$ can be computed, which is

F (x) = x [E {(G)}^{x} - E (G)] = x (x - 1) \{y [(1 - z) θ - σ] + z (α + β) + σ\}

Similarly, the replicator dynamic equation of developers and local communities can be calculated separately (see Online Appendix I and II for the details). The results are shown below

F (y) = y (y - 1) \{z [l_{1} + t_{1} + i_{1} - μ - (l_{2} + t_{2} + i_{2} - γ)] + (i_{2} - γ - i_{1} + μ) - (1 - x) σ\}

and

F (z) = z (z - 1) [y (r_{1} - l_{1} - φ) + (1 - y) (r_{2} - l_{2} - ε) - x β]

According to the replicator dynamic equations of the government (formula (4)), in the long-term game of land revenue distribution in tourism projects, the present value of the land lease tax ( $t_{1}$ ) and the cost to handle the resistance (g) will not affect the government’s decision-making. Similarly, according to the replicator dynamic equations of the developer (formula (5)), in the long-term game of land revenue distribution in tourism projects, the revenue of tourism projects ( $R$ ) and government subsidies (α) has no impact on the developer’s choice of land transfer methods.

Model analysis

Stability analysis of individual strategies

The stability analysis principle of the individual strategy is consistent. That is, (1) when the value of replicator dynamic equation is constantly 0, which means that the replicator dynamic equation is stable, then the individual strategy is in a stable state; and (2) when the value of replicator dynamic equation is uncertain, according to the stability theorem for differential equations, if the value of a differential equation is less than 0, then its original equation is stable – that is, the individual strategy of the game is in a stable state. Therefore, individual strategy stability analysis follows a few general steps: (i) calculate the value of the independent variable that can make the value of replicator dynamic equations (formulas (4) to (6)) constant to 0, which implies that $F = 0$ is consistently true; (ii) when the value of the replicator dynamic equation is uncertain, find the values of the independent variable that makes $F = 0$ , which could be the stable points; (iii) compute the differential equation of the replicator dynamic equation $F^{'}$ ; and (iv) find the value or conditions when $F^{'} < 0$ , where the original equation is stable – that is, the stability of the individual strategy is achieved. The stability analysis of the government’s strategy is shown in the following example:

To facilitate analysis, let $y_{0} = \frac{z (α + β) + σ}{σ - (1 - z) θ}$ or $z_{0} = \frac{σ + y (θ - σ)}{y θ - (α + β)}$ represent the roots of $F (x) = 0$ , except $x_{1} = 0$ and $x_{2} = 1$ . Apparently, they are symmetric; thus, $y_{0} = \frac{z (α + β) + σ}{σ - (1 - z) θ}$ is taken as an example to analyse the individual strategy stability of the government. From the replicator dynamic equation for the government (see formula (4)), obviously $F (x) = 0$ for any $x$ when $y = y_{0}$ . When $y \neq y_{0}$ , two possible stable points can be obtained with $F (x) = 0$ (i.e. $x_{1} = 0$ and $x_{2} = 1$ ). According to the stability theorem for differential equations, $x^{'}$ is the evolutionary stable strategy if $F^{'} (x) < 0$ when $x = x^{'}$ , and the differential equation of formula (4) is shown below

F^{'} (x) = (2 x - 1) \{y [(1 - z) θ - σ] + z (α + β) + σ\}

Proposition 1: When $(1 - z) θ > σ$ , owing to $θ > 0$ and $0 < z < \frac{θ - σ}{θ}$ (which is because all the variables are set above 0), the following can be derived: $θ > σ$ , $y_{0} < 0 < y$ and $y [(1 - z) θ - σ] + z (α + β) + σ > 0$ , which implies that if $x_{1} = 0$ , then $F^{'} (x) < 0$ for any $y$ .

Proposition 2: When $(1 - z) θ < σ$ , then $y_{0} > 0$ , two possible situations exist: (i) when $0 < y_{0} < y$ , $y [(1 - z) θ - σ] + z (α + β) + σ < 0$ , which implies that if $x_{2} = 1$ , $F^{'} (x) < 0$ for any $y$ ; and (ii) when $0 < y < y_{0}$ , $y [(1 - z) θ - σ] + z (α + β) + σ > 0$ , which implies that if $x_{1} = 0$ , then $F^{'} (x) < 0$ for any $y$ .

As a result, when the probability of the developer and the local community’s decision-making is certain (the probability of the developer choosing to lease is $y_{0}$ and choosing to purchase is $1 - y_{0}$ , whereas $y_{0}$ depends on the probability of the local community’s decision ( $z$ )), regardless of the choice the government makes, the game of land income distribution for the tourism project remains stable. This means that the ESS of the government is the current strategy. On the contrary, when the probability of the developer and the local community’s decision-making is uncertain, the government will consistently choose not to subsidize when $x_{1} = 0$ or choose to subsidize when $x_{2} = 1$ . As proposition 1 indicates, when the coordination cost of the government is greater than the potential rent-seeking income, the government will not subsidize the land transfer of the tourism development. Proposition 2 indicates that the greater the probability that the developer chooses to lease (i.e. $max (0, y_{0}) < y < 1$ ), the more likely it is that the government will choose not to subsidize.

Through the stability analysis of the developer’s strategy (see Online Appendix III), a few findings can be obtained: (1) when the probability of the government and the local community’s decision-making is certain, regardless of the choice the developer makes, the game remains stable, which means that the ESS of the developer is the current strategy, but when the probability of the government and the local community’s decision-making is uncertain, the developer will consistently choose to lease or buy the land; and (2) when the negotiated net benefit of the developer is less than that of the protest, there is a greater probability that the local community will cooperate, and the developer is more likely to lease. However, when the total cost of land lease is greater than the total cost of land purchase (without considering the rent-seeking cost), the developer will consistently choose to purchase. Otherwise, the developer will choose to rent the land instead.

Through the stability analysis of the local community’s strategy (see Online Appendix IV), here are a few findings: (1) when the probability of the government and developer’s decision-making is certain, regardless of choice the local community makes, the game remains stable, which means that the ESS of the local community is the current strategy, whereas when the probability of the government and the developer’s decision-making is uncertain, the local community may consistently choose to cooperate or not; and, (2) regardless of land transfer method, when the land revenue of the local community is greater than the non-cooperative benefits, the local community will choose to cooperate; otherwise, it will remain non-cooperative.

In sum, when the probability of all the players is determined, all the stakeholders will stabilize the current strategies. By contrast, when the probability is uncertain, each player will have its own conditions to consider; eventually, the evolutionary game will conditionally remain stable. However, the interaction between the players and the specific evolutionary stable strategies still requires further analysis.

ESS analysis among three stakeholders

The stability of the evolutionary game among three or more players can be analysed using the Jacobian matrix. The replicator dynamic equations of the government, the developer and the local community can form a dynamic system. According to evolutionary game theory, the ESS is a strict Nash equilibrium, which must be a pure strategy (Yu, 2007: 216–230; Zhan and Zou, 2014). From the analysis of individual strategies, eight possible evolutionary stability strategies exist, corresponding to eight possible stable points in the dynamic system – that is, $A (0, 0, 0)$ , $B (1, 0, 0)$ , $C (0, 1, 0)$ , $D (0, 0, 1)$ , $E (1, 1, 0)$ , $F (0, 1, 1)$ , $G (1, 0, 1)$ and $H (1, 1, 1)$ . The Jacobian matrix of this dynamic system is shown below

[\begin{matrix} F^{'} (x) & x (x - 1) [(1 - z) θ - σ] & x (x - 1) (α + β) \\ y (y - 1) σ & F^{'} (y) & y (y - 1) [l_{1} + t_{1} + i_{1} - μ - (l_{2} + t_{2} + i_{2} - γ)] \\ - z (z - 1) β & z (z - 1) [r_{1} - l_{1} - φ - (r_{2} - l_{2} - ε)] & F^{'} (z) \end{matrix}]

According to Lyapunov’s direct method (Yan et al., 2010), in the third-order Jacobian matrix, if the matrix eigenvalues are all negative, the critical point of the dynamic system is stable, hence the ESS. If the matrix eigenvalues appear partially positive, the critical point of the dynamic system is a saddle point. If the matrix eigenvalues are all positive, the critical point of the dynamic system is unstable. Table 3 exhibits the results of ESS analysis.

Table 3.

Results of ESS analysis.

Critical point	Eigenvalues			States	Conditions
$A (0, 0, 0)$	−	+/−	+/−	Saddle/stable	$i_{1} - μ < i_{2} - γ - σ; r_{2} - ε > l_{2}$
$B (1, 0, 0)$	+	+/−	+/−	Unstable/saddle	–
$C (0, 1, 0)$	−	+/−	+/−	Saddle/stable	$i_{1} - μ > i_{2} - γ - σ; r_{1} - φ > l_{1}$
$D (0, 0, 1)$	−	+/−	+/−	Saddle/stable	$l_{2} + t_{2} + σ < l_{1} + t_{1}; r_{2} - ε < l_{2}$
$E (1, 1, 0)$	+	+/−	+/−	Unstable/saddle	–
$F (0, 1, 1)$	−	+/−	+/−	Saddle/stable	$l_{1} + t_{1} < l_{2} + t_{2} + σ; r_{1} - φ < l_{1}$
$G (1, 0, 1)$	+	+/−	+/−	Unstable/saddle	–
$H (1, 1, 1)$	+	+/−	+/−	Unstable/saddle	–

From the results above, $A (0, 0, 0)$ , $C (0, 1, 0)$ , $D (0, 0, 1)$ and $F (0, 1, 1)$ are the stable points in this dynamic system. Therefore, four possible evolutionary stable strategies exist in the game of land revenue distribution in tourism development. However, regardless of the case, the government will not subsidize the land transfer of tourism projects in the long term, as shown below.

$A (0, 0, 0)$ represents the ESS (do not subsidize, purchase, do not cooperate) of the government, the developer and the local community, respectively. If the developer’s net benefit of negotiation is less than that of protest (deducting the cost of rent-seeking) and the local community’s net benefit of resistance is greater than the income from land sale, then the developer will choose to buy the land and the local community will choose not to cooperate.

$C (0, 1, 0)$ represents the ESS (do not subsidize, lease, do not cooperate) of the government, the developer and the local community, respectively. If the developer’s net benefit of negotiation is greater than the difference between the net benefit of protest and the rent-seeking cost, and the local community’s net benefit of participation is greater than the land lease income, then the developer will choose to rent the land and the local community will choose not to cooperate.

$D (0, 0, 1)$ represents the ESS (do not subsidize, purchase, cooperate) of the government, the developer and the local community, respectively. If the developer’s total costs of land purchase (including the rent-seeking cost) are less than the total costs of land rental, and the local community’s net benefit of resistance is greater than the income of land sales, then the developer will choose to buy the land and the local community will choose to cooperate.

$F (0, 1, 1)$ represents the ESS (do not subsidize, lease, cooperate) of the government, the developer and the local community, respectively. If the developer’s total costs of land purchase (including the rent-seeking cost) are greater than the total costs of land rental, and the local community’s net benefit of participation is less than the income of land leases, then the developer will choose to rent the land and the local community will choose to cooperate.

Discussion and conclusions

Discussions of results

This study explores land income distribution in tourism projects by building an evolutionary game model with the main stakeholders including the public agent (the government), the private sector (the developer) and residents (the local community). The novelty of this research is multifold. First, in the practice of tourism development, under the intervention of the government, the developer and the local community typically face conflicts over issues of land use and income distribution. The three stakeholders achieve their ESS by learning from each other and adjusting their decision-making behaviour. Based on the assumption of bounded rationality, this research adopts the evolutionary game analysis method with the model considering the three key stakeholders simultaneously. In this way, the analytical findings may be closer to reality than previous studies. Secondly, this study conducts individual stability analysis as well as multiplayer evolutionary game analysis on the decision-making behaviour of the government, the developer and the local community. By further comparing the two results, we can see how the decision-making behaviour of a particular player is shown to be influenced by the other stakeholders. Last but not least, the model takes into consideration how land transfer methods (by purchase or lease) influence land income distribution (with a lump sum or an annuity). To compare a lump sum with an annuity in the same model, the PVIFA from accounting research was introduced into the analysis. Our model shows that the developer can pay the land income to the local community in a lump sum by land purchase or let the local community obtain the land revenues of tourism development annually through land lease, which is consistent with practical experience.

The results of the individual strategy stability analysis of the government, developer and local community can be interpreted as follows:

When the decision-making probability of the government, the developer and the local community is certain, the game of land income distribution in tourism development will be stable in the current strategies, which are supposed as the ESS. The result shows that, in the long run, experienced players can fully collect information from other players through social learning (Fatima et al., 2005), adapt to each other’s decision-making behaviour, and stabilize in the best response strategy (Rees et al., 2009; Wallace and Young, 2015).

When the decision-making probability of each play cannot be determined, the three players have their own conditions to consider in making their decisions. The government pays attention to the coordination cost of subsidization and cares about the rent-seeking income if there are no subsidies. The developer focuses on the total land cost under different land transfer methods without considering the rent-seeking cost, as well as its benefits if the local community does not cooperate. By contrast, the local community will compare the difference between the cooperative and non-cooperative benefits under different land transfer methods. In the case of non-cooperation, the community will also consider land income as opportunity cost.

The results from the ESS analysis can be interpreted as follows:

In the long run, regardless of the strategies the developer and local community adopt, the government will not subsidize land transfer for tourism development projects. As ESS is a stable strategy determined by long-term evolution, this finding shows that, apart from tax policy, the government’s subsidy policy will not affect the land transfer market in the long run, which complements previous research results (Nirmal, 2017). That may be because in the long term, the incentive effect of government subsidies will decrease as other costs increase, such as the increasing labour costs or the potential cost of changes in interest rates. Moreover, it is indicated that, the administrative power will eventually surrender to market power in the private land transfer market, which is also consistent with previous research results (Borras, 2005).

The conditions for the developer to purchase are as follows: (i) the total cost of purchasing land (including the rent-seeking cost) is less than the total cost of land lease, and (ii) the net benefit of negotiation is less than that of protest (deducting rent-seeking costs). Either of these two conditions would suffice for the developer to purchase land; otherwise, the developer would choose to lease. Depending on the decision sequence, the developer will make decisions by considering different conditions. When the developer makes the first move, the developer will compare the total land cost of different transfer methods. Specifically, in the land sales market, the developer will take the rent-seeking cost into consideration, which largely depends on governmental agents. When the community tends to choose not to cooperate, the developer will compare the net benefit of non-cooperation in different situations. Therefore, it makes sense that, in existing cases, the community usually strives to gain the initiative through non-cooperation in the land revenue distribution of tourism projects.

The conditions for the local community to choose cooperation are as follows: (i) the land sales income is greater than the net benefit of resistance, and (ii) the land rental income is greater than the net benefit of community participation. It seems that the communities are more likely to stay in a passive position in the land revenue distribution of tourism development. Instead of comparing the land income under land sales and land leases, both conditions depend on the choice of the developer. If not in the above two cases, the local community will choose not to cooperate when conflicts easily break out. The community’s cost of resistance is generally not related to the land transfer methods but is related to the way the community resists. If the community chooses to protect its rights by law, the cost may be small. Otherwise, if the community combats the tourism project by inappropriate behaviour or even violence, legal costs, fines and punishment could be great.

Conclusions

Based on the results of evolutionary game analysis, land income distribution in tourism development can be considered a game between the developer and the local community. Directly intervening in the land transfer market is not a long-term solution for the government because it is difficult to sustain in the long run, owing to great financial pressure. However, a government can indirectly influence the land transfer market by creating a positive and equal policy to promote the development of community participation. The direct intervention of the government often weakens the negotiating power of the community (Taylor, 2007). In the current land sales market, the developer tends to be in a favourable position through rent-seeking, ignoring public consultation procedures and community appeals. Without a good political environment to support community participation, community residents will take certain actions to achieve community participation. These may include asking for assistance via social media, petitioning public agents and even taking to the streets to protest against the tourism project, which could escalate to political incidents. Conflicts over land use and revenue distribution have caused social instability in tourist destinations, undermining their sustainable development. Therefore, in the long run, to reduce these conflicts, the most effective strategy for the government is not to directly intervene in the land transfer market but provide a good political environment for community participation.

According to the results, the game sequence will influence each stakeholder to consider different decision-making conditions. The results show that the developer probably makes the first move, which is consistent with actual situations. For example, when a developer selects a region as the best location for a new tourism project, the developer must make an offer to the local community. In this case, the developer will only compare the total cost of land lease with the one of land purchase. The data can be obtained or estimated through market conditions or relevant policies. The local community can only choose whether to accept the offer or not. On the basis of the developer’s decision, the local community will compare the cooperative and non-cooperative benefits under the corresponding land transfer methods. Although the community may stay passive in the land revenue distribution, the local community can also gain the initiative through non-cooperation. For instance, the local community may strongly refuse to transfer the land if the developer has a negative reputation in previous projects. Therefore, the developer will weigh the benefit against the costs under different land transfer methods, in the context of the community not cooperating to propose a better land transfer and income distribution plan.

In addition, heterogeneities are common among stakeholders, such as the level of participation in tourism or other differences (e.g. in income levels and family backgrounds) (Alesina and La-Ferrara, 2000). This leads to the display of different attitudes towards land transfer and tourism development among the internal members of the community. This phenomenon is also reflected in the evolutionary game model, where each player holds a certain probability for each strategy. The latter can be understood as the percentage of the people who choose the current strategy within the group. However, in the long run, when relevant conditions are met, the probability will evolve into a certain value (0 or 1), which indicates that, under a long-term evolution, consensus will be formed within the community. Therefore, managers and organizers cannot use the inconsistency of opinions within the community as an excuse to ignore the public consultation process.

A few limitations exist in the current research that should be addressed in future research. First of all, previous studies have affirmed that some public agents would weigh the quality of natural environments over the economic benefits when it comes to land transfer and utilization (Nesheim et al., 2014). Moreover, local communities have emotional connections with the land as well (Lisec et al., 2014). However, this model is constructed on the basis of cost–benefit analysis, considering economic and social costs and benefits without taking into consideration other aspects such as ecology, culture and psychology. The latter also influences the decision-making behaviour of the stakeholders. Secondly, the model explores the impact of the game environment on the behaviour of the players, but the evolution of the player’s behaviour itself also affects the game structure, rules and environment (Frechette et al., 2015; Newton, 2018). Based on the model’s current assumptions, analysing and discussing such issues is difficult. Future research should examine and address these issues.

Lastly, the current model takes into consideration the costs and benefits of the public sector, the private developer and the local community, which results in practical difficulties obtaining real data to test the model. For instance, accessing the data of certain variables is unlikely in this model, such as the rent-seeking cost of a developer or the rent-seeking benefit of the government. On the other hand, data acquisition of certain variables in the model requires professional knowledge on asset evaluation and the estimation of opportunity cost, such as the benefits and costs of developers negotiating with the local community as well as the community’s benefits and costs of participation, which are also beyond the scope of the current research.

Supplemental material

Supplemental Material, Appendix - Evolutionary game analysis of land income distribution in tourism development

Supplemental Material, Appendix for Evolutionary game analysis of land income distribution in tourism development by Pang Qingyun and Zhang Mu in Tourism Economics

Footnotes

Acknowledgements

The authors sincerely thank Professor Rob Law and Dr Xiang Zheng for their help in checking the grammar and words, and Dr Wang Jiajie for his guidance on the research methods.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study is supported by the Guangdong Provincial Science and Technology Plan Project (grant no. 2018A070712022).

ORCID iD

Pang Qingyun

Supplemental material

Supplemental material for this article is available online

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