Abstract
A framework is established for evaluating the adaptability of rural households to tourism disturbance in the suburbs of a metropolis, based on the theory of the social-ecological system with tourism as the system disturbance. Two traditional villages in Beijing suburbs are selected as study cases and compared in terms of the development stage of tourism and the phases and approaches of adaption by rural households to tourism disturbance. Stepwise regression and grey relational analysis are applied to investigate the factors influencing the functionality and stability of the rural social-ecological system. Keywords: rural tourism; livelihood diversity; adaptation; social-ecological system; system functionality and stability 1. Introduction households and the dynamic changes of their activities. Rural tourism in China emerged since the mid-1980s We here define rural households as aboriginal residents (Cai, 2002) and has gradually become a major type of in rural areas, who were formerly engaged in farming. tourism. In Beijing, for example, there were 17,000 First, an on-site survey is conducted to compare host families and 69,000 employees in rural tourism by different phases of adaption and identify approaches the end of 2014; they received 38.3 million tourists and of adaption by rural households. Next, qualitative and made a revenue of 3.6 billion RMB. Rural tourism has quantitative analyses are performed to identify the key become the most important approach for the farmers factors influencing the adaptability of rural households to get out of poverty and has been implemented and to select an appropriate set of indicators of throughout the country. adaptability and functionality. Furthermore, rigorous The booming of rural tourism plays a positive role statistical methods are used to calculate the impact of in promoting economic development in rural areas and various factors and evaluate the adaptation level and increasing the employment and income of farmers. adaptation potential of rural households in the rural Meanwhile, it has a positive effect on improving the SES. agricultural added value and enriching the lives of rural residents (Hall et al., 2003; Jiang et al., 2008). 2. Theoretical Background However, the rapid development of rural tourism has The theory of SES is one of the frontiers of research strongly disturbed the rural social-ecological system in tourism geography for its integrated and dynamic (SES) and increased the eco-environmental load, perspective linking both social and ecological elements. leading to a significant impact on the work and lives of The SES, which regards tourism as a disturbance, rural households. is a special platform that examines the human-land Studies on rural tourism have assessed the economic, relationship from the perspective of tourism (Folke social, cultural and ecological impacts of tourism et al., 2002). The theory of SES concerns the impact on rural areas (Liu, 2000). However, few research of tourists' activities on the entire SES, including the has been conducted from the perspective of rural impact of living (mainly human-beings) and non- living entities in the system. According to this theory, various factors and activities in the system have a non- linear impact (Strickland-Munro & Allison, 2010). In *Contact Author: Linlin Dai, Associate Professor, terms of system theory, although conventional linear College of Urban and Environmental Sciences, approaches may provide effective information in Peking University, Room 3245, Building Yifu 2, the short term, it still needs to be improved (Farrell Peking University, 100871, China & Twining-Ward, 2004). There is a need to reflect Tel: +86-13691577440 Fax: +86-1062757815 E-mail: linlindai@pku.edu.cn the concerns regarding a non-linear, integrated ( Received April 5, 2017 ; accepted July 23, 2018 ) environmental matrix, in addition to the energy flow, DOI http://doi.org/10.3130/jaabe.17.417 material flow, and information flow. Therefore, in Journal of Asian Architecture and Building Engineering/September 2018/424 417 addition to the conventional linear research approach, farming, which is approximately one-tenth of the total it is necessary to establish a model with closely linked area of the village. Moreover, other problems such as economic, social, and environmental phenomena and on-street parking and catering constantly emerge. network structures. The SES is closely associated with the theory of adaptability, resilience and vulnerability (Walker & Salt, 2012), which are the key words to describe how the system is responsive to disturbance (Wang et al., 2010; Holling, 1973). The theory of adaptability emphasizes the responsive subjects in the system (Nelson et al., 2007). It considers that the behavioral subjects in the system have massive self- organizing behaviors that, to a certain degree, ensure the homeostasis of the system by adapting to its spontaneous change or external disturbance (Wang et al., 2010). The theory of adaptability has a clear view on the subjects, which considers the features of the adaptive subjects and the dynamics and scope of their adaptation (Niehof, 2004). With regard to adaptability, both theories identify the same elements, i.e., the features, processes, and results of adaptation (Engle, Fig.1. Location of Cuandixia and Huanglingxi 2010; Smit & Wandel, 2006). Based on the theory of adaptability, the theory of resilience not only takes 3.2 Data Collection and Methods into consideration the capacity of the system to cope Background data were obtained from the official with disturbance but also gives consideration to the tourism website and the local tourism management difference between incremental regulation and mode departments' website. Primary data were collected conversion (Below et al., 2012). through questionnaire surveys and recorded interviews Here, adaptability refers to that, to adapt to the through an on-site investigation during the May Day impact brought by tourism development, rural Holiday in 2015. households adjust the use of land, labor and other According to the development level of tourism resources to maintain the current or achieve better reception and the population levels of the two villages, living conditions. The core issue is to adjust and use we first surveyed the host families in Cuandixia and resources and their inherent capability to adapt to the assigned equal numbers of host and non-host families environment. in Huanglingxi. Each household was counted as one valid sample. Forty-seven valid samples were obtained 3. Methodology and Data from Cuandixia, all of which were households 3.1 The Cases involved in tourism; forty-eight valid samples were Cuandixia and Huanglingxi are two adjacent villages obtained from Huanglingxi, including eighteen located in the western suburbs of Beijing. Both of households involved in tourism and thirty non-involved them were formed in the Ming Dynasty, and they are households. The contents of the survey mainly typical representatives of settlements in the northern included demographic information, social capital, mountainous areas of China. These two traditional agricultural production, tourism business-running, the villages belong to the Cuanbai Scenic Area. opinion towards tourism development, and cognition Cuandixia has a population of 98. Tourism started in of policies etc. In-depth interviews were conducted the early 1990s, and nearly all of the current villagers with village cadres to understand the tolerance and are engaged in tourism. Huanglingxi has a population adaptability of households to rural tourism. The time of 180. Tourism development started in 2010, and one- span of the interview and survey for each person was third of current villagers are occupied in tourism. The 30 minutes at minimum. preservation of the overall architectural style is slightly The survey results were analyzed to identify the better, while tourism is relatively less developed in phase characteristics and typical approaches of Huanglingxi compared to Cuandixia. adaption of rural households in the two villages at As a rural tourism destination in Beijing, Cuandixia different stages of tourism development. Next, an has received numerous tourists. The volume of tourists influencing factor and indicator system of functionality brings intense disturbance, for example, parking was established by referring to the existing research problems. The village has widened the main street (Below et al., 2012). We then use grey relational and built two large parking lots at the foot of the analysis to indicate the influencing factors of system mountain. The car park on the south side of the main stability. street occupies the space that was originally used for 418 JAABE vol.17 no.3 September 2018 Linlin Dai Eighteen influencing factors from seven categories We compare the samples from the two villages in were considered, all of which meet the first three terms of mean household income, living conditions, Gauss-Markov assumptions. Stepwise regression was the population engaged in tourism and the types of applied to further select the variables, using the last tourism services (Fig.2.). The results show that in two Gauss-Markov assumptions as criteria. In brief, terms of tourism services, 33.3% of the host families in the dependent variables were regressed against each Huanglingxi only provide accommodations, whereas explanatory variable; then, the explanatory variable the remaining households have only one more service, with the greatest contribution was chosen, and the which is catering; in Cuandixia, all host families other explanatory variables were gradually introduced. offer accommodations and catering, whereas 17% Through stepwise regression, only the important of them also provide transport services, souvenirs, explanatory variables that had no significant multi- exhibition visiting guide, and agricultural products, collinearity were retained in the model. among various other services. The income of rural All data were normalized before regression. households is remarkably different between the two Therefore, the constant was excluded from the villages. Households in Cuandixia earn a substantially estimates, and the regression coefficient of each factor higher income. Meanwhile, family size is larger in could be regarded as the level of impact. Given that Cuandixia since more villagers are migrant workers in five Gauss-Markov assumptions were taken into Huanglingxi. Moreover, the villagers of Huanglingxi consideration for the model estimation, the estimation are less satisfied with the quality of life, the living ability of the model was not affected by data environment, and tourism-related income. Nonetheless, normalization. they are more satisfied with the neighborhood. 4. Level and Process of Adaptation of Rural Households to Tourism Disturbance 4.1 Comparison of the States Before and After Adapting to Tourism Disturbance The original work of villagers in Cuandixia was farming, and it was mainly conducted in terraced fields and farmland near the village. Now it has transformed into the solicitation of customers on the main street, in addition to the preparation of meals, the reception of tourists, and the sale of agricultural products grown in their own courtyard. There exists intense competition between the villagers. Meanwhile, their activities are mostly limited to the main street and the courtyards, thereby reducing the likelihood of conversation at the edge of a field in the past. Huanglingxi was previously one of the major coal- Fig.2. Normalized Indicators of Adaptation Characteristics of producing villages, thus coal mining used to be the Rural Households in Cuandixia and West Huangling leading industry. In addition to developing ecological agriculture and tourism, the village continues to C o m b i n e d wi t h t h e a c t u a l l e v e l o f t o u r i sm integrate the primary and tertiary industries now. development in the two villages revealed by the on-site However, the on-site investigation reveals that a large investigation, we conclude that tourism development population of villagers in Huanglingxi do not work in has entered the phase of relative steady in Cuandixia the village but are migrant workers in nearby cities. whereas it is still at an early stage in Huanglingxi. The remaining adults cannot leave the village due to 4.3 Typical Adaptive Patterns to Tourism Disturbance the need to care for children or elder people. Therefore, The choice of adaption approaches is influenced these villagers "have to stay here" for tourism or other by the individuals, the community system, available work. resources, socio-cultural background within the village, 4.2 Comparison of Different Phases of Adaption to and the neighborhood. Tourism Disturbance The basic choice that rural households need to make In Cuandixia, 92.7% of rural households are is the main source of income, which includes tourism currently engaged in tourism. In Huanglingxi, the services, wages, and the government subsidies. Four current structure of livelihood is more balanced, with types of adaption by rural households are summarized 38.4% of rural households engaged in tourism, 24.9% by combining the above choices. The four types are: being migrant workers, and 34.8% engaged in sheep (1) exclusive tourism – rural households have been raising, beekeeping and business; the remainders live exclusively engaged in tourism for years; (2) primarily from rental income. tourism – rural households are also engaged in other work in addition to tourism, the income from tourism JAABE vol.17 no.3 September 2018 Linlin Dai 419 accounts for 60% of total household income or more; were closed, a large number of villagers lost their (3) partly tourism – the income from tourism accounts livelihood and thus migrated to work in urban areas. for 30-60% of the total household income; and (4) The remaining residents are unwilling but have to stay primarily other work – rural households rely on other to take care of family members or for other reasons. sources of income, either without involvement in These villagers have no option but to operate tourism. tourism operation or the income from tourism accounts for 30% or less of the total family income. The types 5. Influencing Factors of Adaptability of adaptation are compared in the two villages. The 5.1 Influencing Factors of System Functionality outcomes of the four types are illustrated in Fig.3. (1) Annual Family Income as the Proxy Variable of Points in the upper right-hand corner indicate the System Functionality optimal choice that maximizes both annual family Stepwise regression is performed using a 95% income and the diversity of livelihood simultaneously. confidence interval (the same applies below), and the The 'primary tourism' type is close to the optimal results are as follows. Four variables are introduced: situation, while for the 'partly tourism' type, it is M1, indicating the amount of family asset, G2, difficult to achieve the optimal level. indicating village factor, L1, indicating the total labor (family members working in tourism and employees), and L5, indicating the number of employees. The equation is expressed as Y1 = 0.399M1 + 0.283G2 + 0.262L1 + 0.209L5 All of the significance values are smaller than 0.03, indicating that the validity of the equation is good and up to 97%. The regression equation has R = 0.791 and adjusted R² = 0.601, indicating that it can explain 60.1% of the system functionality. The result falls within an acceptable range. The collinearity diagnosis shows that the four variables have low linearity, with the eigenvalues being approximately 1. The maximum condition index value is 1.978, which is much smaller than 10, suggesting that the equation has no significant multicollinearity. In summary, the model is acceptable, Fig.3. Outcomes of the Four Types of Adaption and all four factors introduced have a positive impact. 4.4 Process of Adaption to Tourism Disturbance L1 and L5 are both labor factors. The sum of their The environmental homeostasis and the impacts is greater than that of the material resources development of rural households have changed after factor represented by M1. The relationship between tourism development. The initial imbalance is mainly the impact of various factors is labor factor > material manifested by the occupation of ecological resources resources > geographic location, which is explained by tourism and the vanishing of traditional agricultural below. lifestyle. In various respects, the life satisfaction of Labor factor: The number of labors shows a highly rural households has declined. The basic needs of positive correlation with the family income. The family rural households remain unmet, prompting them to size has a slightly stronger impact than the number of change and adapt. Moreover, different rural households employees. are subject to various driving factors of adaptability, Material resources: Compared to other material resulting in the differentiation of adaptability. This resources, the operating area is retained in the model result, in turn, affects the SES to varying degrees. and obtains an impact of 0.399. Thus, this factor is an For instance, all of the households in Cuandixia important material resource of rural households, since are exclusively engaged in agritainment, leading to it represents the scale of operation and the maximum traffic congestion and challenged by limited land and number of tourists that can be accommodated. water resources. Available natural resources for rural Village factor: The village is an important indicator households are reduced, and various crops are no of geographical location. Different villages may have longer planted. Approximately fifty households have remarkably different resources and conditions, in added floors or renovated and covered the courtyard addition to different phases and patterns of tourism for more reception capacity. The newly added parts of development. In the proposed model, the village factor houses take different architectural styles and materials is set as Cuandixia = 1 and Huanglingxi = 0. The compared to the original buildings, thereby destroying regression coefficient is positive, indicating that the the landscape and the identity of the village. rural households of Cuandixia have better adaptability Prior to tourism development, most villagers in to tourism and stronger system functionality. Huanglingxi worked nearby in coal mining, which Drivers of adaptability that are not retained include: guaranteed their income. When the coal mines economic resources (E), natural capital (N), social 420 JAABE vol.17 no.3 September 2018 Linlin Dai capital (S), and cognition factor (R). As stated below, stability by livelihood types but also to measure the these factors are more relevant to the tourism operating income fluctuation of rural households over a relatively income of rural households. long period of time (one year). (2) Tourism Income as the Proxy Variable of System Livelihood diversity is measured as the number Functionality of types of livelihood activities undertaken by each The following variables are introduced: M1 – family. The time engaged in a livelihood activity the amount of family asset, G2 – village factor, E1 should be no less than thirty hours per month and – the number of available acquainted lenders, L5 – no less than two months per year (Du et al., 2012). number of employees, R1 – the evaluation of tourism Therefore, we assign value 1 to households engaged in development opportunities, and L6 – training or not. one livelihood activity value 2 to households engaged The equation is expressed as in two livelihood activities, and so on. Y2 = 0.498M1 + 0.304G2 – 0.246E1 + 0.212L5 + The income volatility of rural households is 0.239R1 + 0.176L6 measured as follows: the monthly income of each All of the significance values are smaller than household is calculated for 12 months a year to 0.024, suggesting that the validity of the equation obtain the level of income fluctuation. The results are is good and up to 97.6%. The regression equation processed by grey relational degree before being used h a s R = 0.892 a n d a d j u s t e d R ² = 0.775. T h u s , as the indicator to measure income volatility. the equation can explain 77.5% of the system The relational degrees of various factors with functionality and has good explanatory power. The livelihood diversity and income volatility have a equation has very slight and negligible collinearity. correlation coefficient of 0.815. This result indicates Therefore, the model is acceptable. that these two factors have a strong correlation with The relationship between the impact of various each other and that the indicator of income volatility factors is material resources > labor factor > geographic can be used as a reference. The relational degrees of location > economic resources > cognition factor, which various factors are shown in Table 1. The relational is explained below. coefficients are all above 0.54, and the maximum value Labor, material resources and geographic location is 0.89. are the three most important factors that determine the According to existing research, we treat the factors family income and the tourism income. With respect with a relational degree greater than 0.75 as key to tourism income, the impact of labor is reduced, variables. The impact of various variables is then whereas material resources surpass the labor factor and analyzed. become the most significant influencing factor. (1) Labor Capital availability is chosen as the proxy variable Among the six factors, four relevant variables are of economic resources. The regression result shows selected: L1, L3, L4, and L6, which indicates that that this factor has a negative impact, which can be the quantity, structure, and quality of labor have a related to the system error of statistical analysis. The great impact on system stability. In terms of relational reason is, in the on-site investigation, many households degree, L4 ranks 1st and 9th and L3 ranks 2nd and responded to the question based on an impression. 5th in livelihood diversity and income volatility, 29.2% of households stated that "I have no need to respectively; L1 ranks 7th and 8th; and L6 ranks 11th borrow money from acquaintances" or "I have no and 7th. idea how many acquaintances I have that will loan me The survey shows that villagers concurrently money". We consider the households that have no need engaged in tourism and migrant work and those relying to borrow as that they use their own capital to raise the on wages and government subsidies are mostly from funds for tourism operation and business expansion. Huanglingxi. There are mainly two kinds of situations. Regarding the cognition factor, the evaluation of For middle-aged couples, men are mostly concurrently tourism development opportunities is chosen as a proxy engaged in tourism and migrant work, while the variable. The implication is that rural households, spouse assists with tourism operation and child care. as the subjects of activities with subjective initiative In a few cases, the man is only engaged in tourism in and rational behavior, can effectively recognize the the busy season and engaged in migrant work or relies opportunities and risks of tourism development. on the government subsidies in the off season. For old Among the labor drivers, the newly added proxy couples, they mostly cooperate in operating tourism variable is L6 – training or not. This variable indicates and also receives retirement pension or the government that, although the number of labors can greatly affect subsidies, with their children being migrant workers. total family income, the quality of labor can affect the Total labor is a major factor that affects system income from tourism operation to a higher degree. functionality and stability simultaneously. Thus, the 5.2 Influencing Factors of System Stability amount of labor is fundamental for guaranteeing sound We choose livelihood diversity as a proxy variable of system functions, addressing tourism disturbance and system stability and introduce the measure of income maintaining system stability. This factor is also a key volatility. The purpose is not only to indicate system impact factor for the adaptability of rural households. JAABE vol.17 no.3 September 2018 Linlin Dai 421 Table 1. Relational Degree of Various Factors with Livelihood Diversity and Income Volatility Relational degree with Relational degree with Variable Ranking Ranking livelihood diversity income volatility L1 Total labor 0.822779 7 0.871921 8 L2 Number of tourism operations 0.735879 19 0.790019 16 Number of villagers relying on wages and L3 0.879279 2 0.904136 5 government subsidies Number of villagers concurrently engaged in L4 0.885058 1 0.862633 9 tourism and migrant work L5 Number of employees 0.749085 17 0.854723 10 L6 Training or not 0.793378 11 0.894175 7 E1 Number of available acquainted lenders 0.785652 12 0.784610 17 E2 Time of operation 0.571678 23 0.545151 23 N1 Arable land area 0.838297 4 0.899584 6 M1 Amount of family asset 0.824476 6 0.924029 3 M2 House renovation time 0.716756 21 0.729552 20 S1 Number of cadres in the village/town 0.862118 3 0.908939 4 S2 Internet promotions 0.646871 22 0.612663 22 S3 Promotion and utilization of network media 0.764471 15 0.765384 18 R1 Tourism development opportunities 0.747403 18 0.763611 19 R2 Policy usefulness 0.824750 5 0.833058 12 G1 Accessibility 0.720056 20 0.824758 13 G2 Village factor 0.818351 8 0.941193 2 Y1 Annual family income 0.804153 10 0.947666 1 Y2 Annual tourism income 0.750163 16 0.795347 15 Y3 Satisfaction with quality of life 0.769437 13 0.819621 14 Y4 Satisfaction with environment 0.765952 14 0.847297 11 Y5 Satisfaction with income 0.814738 9 0.706962 21 Training or not can also affect system functionality union website (http://www.njllm.com) and have posted and stability simultaneously. The survey reveals that the operating information and real pictures online. trained labor can choose migrant work during the Although the website shows a large page view number, tourism off-season and thus enhance system stability. online registration charges a fee, thus no households (2) Material Resources in Huanglingxi has registered. After some households The relational degrees of M1 rank 6th and 3rd. The registered on a review website (http://www.dianping. larger the family asset is, the more likely the family is com/), turnover suddenly increased. However, the to run tourism exclusively or primarily. majority of rural households in Huanglingxi do not In other words, rural households who have know how to use this network platform. Therefore, large family asset tend not to choose other means we believe that the impact of S3 may have been of livelihood. Moreover, the choice is inevitably underestimated in this investigation. influenced by seasonal fluctuations in the tourism (4) Cognition industry. The relational degrees of R2 rank 5th and 12th. (3) Social Capital However, both of these values are relatively high. The relational degrees of S1 rank 3rd and 4th, This result indicates that rural households that are whereas those of S3 rank 15th and 18th. The optimistic about the prospect of tourism development investigation shows that rural households with a higher and a higher cognition of relevant policies will be more proportion of family members as cadres in the village/ proactive in tourism operation and thereby improve town have a relatively high quality of family culture the livelihood diversity. However, the survey reveals and more advanced operating philosophy. However, a significant polarization in the cognition of national there is only one cadre at the village/town level in each and local policies. Middle-aged couples exclusively of the four households from Cuandixia and in each of engaged in tourism typically do not understand and the three households from Huanglingxi. Owing to the are not optimistic about the policies. Although middle- small sample size, there may be a large error in the aged to old couples do not understand the policies, impact of S1 on system stability. they are highly optimistic and supportive. Many of With regard to the promotion and utilization them stated "thanks to the country" and "thanks to the of network media, many rural households have government". Because many people in middle-aged recognized its importance. In Cuandixia, for example, to old-aged couples have pensions or the government most households have registered on an agritainment subsidies, their income is more stable. 422 JAABE vol.17 no.3 September 2018 Linlin Dai (5) Geographic Location although tourism operation has created a higher level The relational degrees of G2 rank 8th and 2nd, with of income and improved system functionality, its a large gap in between. Despite the higher level of excessive homogenization has also brought greater tourism development in Cuandixia, a higher proportion income volatility and reduced system stability. In of villagers are exclusively engaged in tourism, and the Huanglingxi, the large numbers of villagers dependent operation is strongly homogenized. These phenomena on wages and government subsidies and those lead to greater income volatility and result in lower concurrently engaged in tourism and migrant work system stability in Cuandixia. are advantageous for improving system stability; (6) Economic Resources however, they are disadvantaged for improving system The relational degrees of E1 rank 12th and 17th. functionality. As noted above, many households do not care about Tourism as a disturbance can facilitate the system the number of available acquainted lenders. Thus, the in reaching a new homeostasis that is not necessarily explanatory power of E1 is poor. desirable. Only the collaborative development of (7) Natural Capital various types of operation can promote the healthy Although the relational degrees of N1 rank 4th development of the system. The development of and 6th, the on-site investigation shows that many tourism contributes to the income improvement of households do not value how much land they own. rural households and the occurrence of their adaptive Large areas of land are currently abandoned and behavior. Meanwhile, the situation leads to a gradual unmanaged. Rural households give no consideration to dominance of tourism in the villages, resulting in transferring the contractual operation right of the land. challenges to the limited infrastructure resources The reason is that the water for irrigation is inadequate and seriously homogenized landscape. Moreover, in Beijing. Meanwhile, rural households often choose it increases the mutual competition between rural migrant work or tourism for a higher payment, holding households, which is unfavorable for the long-term that the economic return of planting crops is too small. development of the village. Therefore, the development of various types of operation should be encouraged to 6. Conclusions improve system functionality and stability and which This study discusses the capacity, the approaches could ultimately protect and vitalize the traditional and processes of adaption in the SES with the case villages. of traditional villages' coping with the disturbance of tourism. The following conclusions are drawn. Acknowledgements The village factor has a great impact on the rural This study was funded by the National Natural SES. The government needs to pay close attention Science Foundation of China (No. 51578005) and the to this factor and regulate it properly. Despite the 111 Project (No. B14001). close proximity of Cuandixia and Huanglingxi in the Cuanbai Scenic Area, the two villages are in References 1) Below, T. B., Mutabazi, K. D., Kirschke, D. (2012). 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Journal
Journal of Asian Architecture and Building Engineering
– Taylor & Francis
Published: Sep 1, 2018
Keywords: rural tourism; livelihood diversity; adaptation; social-ecological system; system functionality and stability
