<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AJIBM</journal-id><journal-title-group><journal-title>American Journal of Industrial and Business Management</journal-title></journal-title-group><issn pub-type="epub">2164-5167</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ajibm.2016.612105</article-id><article-id pub-id-type="publisher-id">AJIBM-72953</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Business&amp;Economics</subject></subj-group></article-categories><title-group><article-title>
 
 
  A Study of Tourist Loyalty Driving Factors from Employee Satisfaction Perspective
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ronglin</surname><given-names>Xu</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jianqiong</surname><given-names>Wang</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Jiuzhaigou Administration Bureau, Jiuzhaigou County, China</addr-line></aff><aff id="aff1"><addr-line>School of Economics and Management, Southwest Jiaotong University, Chengdu, China</addr-line></aff><pub-date pub-type="epub"><day>20</day><month>12</month><year>2016</year></pub-date><volume>06</volume><issue>12</issue><fpage>1122</fpage><lpage>1132</lpage><history><date date-type="received"><day>November</day>	<month>17,</month>	<year>2016</year></date><date date-type="rev-recd"><day>Accepted:</day>	<month>December</month>	<year>20,</year>	</date><date date-type="accepted"><day>December</day>	<month>23,</month>	<year>2016</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  With the continuous development of tourism, the driving mechanism of tourist loyalty has become one of the hot topics in the tourist behavior study. Existing researches often explore this question with little focus on the interaction of tourist and employees. This paper, however, proposes a conceptual model of tourist loyalty from employee satisfaction perspective. Our hypothesis is that service quality and tourist loyalty could directly be affected by employee satisfaction and indirectly be affected by employee emotion. To test this, we take Jiuzhaigou and Huanglong scenic spots as examples in the empirical study. The research results reveal that among the three latent variables of employee satisfaction, working environment and living conditions affect service quality of employee positively, meanwhile, working environment, living conditions and working rewards indirectly affect service quality through employee emotion. Service quality affects the tourist loyalty significantly. To cultivate tourist loyalty and achieve sustainable tourism development, scenic spots should take more measures to enhance their employee satisfaction and tourism service quality.
 
</p></abstract><kwd-group><kwd>Tourist Loyalty</kwd><kwd> Employee Satisfaction</kwd><kwd> Service Quality</kwd><kwd> Employee Emotion</kwd><kwd> Scenic Spot</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Customer loyalty directly affects the efficiency of enterprises. In the service industry, an enterprise can increase its profits by 25% to 85% if its customer defection rate is reduced by 5% [<xref ref-type="bibr" rid="scirp.72953-ref1">1</xref>] . Under such increasingly competitive circumstance, tourist loyalty is regarded as an important means to maintain the tourist destination preference [<xref ref-type="bibr" rid="scirp.72953-ref2">2</xref>] . Loyal tourists will not only bring the loyalty of the destination that they have visited, but also will bring the tourist loyalty to the whole area [<xref ref-type="bibr" rid="scirp.72953-ref3">3</xref>] . Since the late 1990s, tourist loyalty has gradually become a new hot spot in the study of tourist destination behavior<sup> </sup> [<xref ref-type="bibr" rid="scirp.72953-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref4">4</xref>] . The key to cultivate tourist loyalty is to identify the factors which influence it.</p><p>Existing researches often explore the impact of the various elements of the destination on the tourist loyalty from the perspective of tourists’ perception, but they seldom consider the factors such as employee satisfaction and service quality. For example, Wang and Mei (2006) constructed the tourism destination satisfaction model and discussed the influence of the tourist satisfaction on the tourist loyalty from the perspective of tourist satisfaction [<xref ref-type="bibr" rid="scirp.72953-ref5">5</xref>] ; Li (2011) constructed the ancient village tourist loyalty model from the perspective of tourists perceived value [<xref ref-type="bibr" rid="scirp.72953-ref2">2</xref>] ; Wu et al. (2011) studied the influence factors of Xi’an tourist loyalty from the perspectives of tourism destination image, satisfaction and loyalty and other tourist perception indexes [<xref ref-type="bibr" rid="scirp.72953-ref6">6</xref>] ; Tian et al., (2015) established the integration model of tourist satisfaction and loyalty, which is based on the dual perspective of cognition and emotion [<xref ref-type="bibr" rid="scirp.72953-ref7">7</xref>] ; Qi (2015) and Zhang et al. (2016) studied the relationship between tourism destination image and tourist loyalty [<xref ref-type="bibr" rid="scirp.72953-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref9">9</xref>] .</p><p>Improving employee satisfaction is the main way to enhance enterprise management and service quality. In the modern tourism enterprises, employee satisfaction directly affects the relationship between enterprises and customers, and at the same time affects the future development of tourism enterprises [<xref ref-type="bibr" rid="scirp.72953-ref10">10</xref>] . Employees of scenic spots are the main body of tourism services. Tourists feel satisfied or unsatisfied with the tourism services provided by the employees. Previous researches show that the service quality of scenic spot has remarkable influence on the tourist loyalty [<xref ref-type="bibr" rid="scirp.72953-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref13">13</xref>] .</p><p>In this paper, two questionnaires are used―employee self-assessment questionnaire of service quality and the tourist questionnaire. The survey results are matched by using a sample pairing method from the perspective of employee satisfaction. On this basis, the paper uses structural equation model to explore the influence pathways and to what extent the employee satisfaction and service quality impact on tourist loyalty, and provides new ideas to improve the tourist loyalty.</p></sec><sec id="s2"><title>2. Conceptual Model Design</title><p>In the process of tourism services, scenic spot employees meet tourists directly, and provide tourists with their services. Previous research shows that employee satisfaction affects the quality of their services [<xref ref-type="bibr" rid="scirp.72953-ref14">14</xref>] and affects tourist loyalty through their services<sup> </sup> [<xref ref-type="bibr" rid="scirp.72953-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref13">13</xref>] .</p><p>Parasuraman et al. (1985) constructed a service quality margin model and pointed out that service delivery not only has significant impact on customers’ perception of service quality, but also measure most of the five dimensions of service quality. Employee is the main body of the service delivery, so employee satisfaction level would directly affect the customer perception of service quality [<xref ref-type="bibr" rid="scirp.72953-ref15">15</xref>] . The “service-profit chain” is the most typical and widely adopted model for studying employee satisfaction and service quality. Heskett et al. (1994) thinks employees who are satisfied would enhance their service quality by improving work and productivity continuously [<xref ref-type="bibr" rid="scirp.72953-ref16">16</xref>] . Based on 206 high-level service companies including hotel industry studying results, Yee (2008) found out that employee satisfaction has a significant correlation with service quality [<xref ref-type="bibr" rid="scirp.72953-ref17">17</xref>] .</p><p>Abraham (1998) puts forward that there is significant correlation between employee disorder emotion state and service quality [<xref ref-type="bibr" rid="scirp.72953-ref18">18</xref>] . Through the longitudinal study, Stephane &amp; Morgan (2002) found that unhappy mood would bring down the job satisfaction, which consequently bring down the service quality [<xref ref-type="bibr" rid="scirp.72953-ref19">19</xref>] . Thus we can assume that employee emotion have positive significant influence on service quality.</p><p>Tourism service quality affects tourist loyalty [<xref ref-type="bibr" rid="scirp.72953-ref20">20</xref>] . When tourists experience high- level service, their willingness to rebuy and recommend would be much more remarkable [<xref ref-type="bibr" rid="scirp.72953-ref21">21</xref>] . Satisfaction is widely considered as one of the main variables which directly affect tourist loyalty in the field of consumer behavior and marketing [<xref ref-type="bibr" rid="scirp.72953-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref23">23</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref24">24</xref>] . The consumers who are satisfied with the products or service quality would be more likely to rebuy and recommend orally, while the latter two behaviors are the core elements of tourist loyalty.</p><p>Based on the above documents and logical argumentation, a conceptual model is proposed as shown in <xref ref-type="fig" rid="fig1">Figure 1</xref> and the following assumptions in the light of the American customer satisfaction index (Customer Satisfaction Index American) [<xref ref-type="bibr" rid="scirp.72953-ref25">25</xref>] , the conceptual model of tourist satisfaction degree in tourist destination [<xref ref-type="bibr" rid="scirp.72953-ref5">5</xref>] , the concept model of tourist satisfaction [<xref ref-type="bibr" rid="scirp.72953-ref26">26</xref>] . Within this model, employee satisfaction consists of three dimensions, which includes employee’s working environment, living conditions and working rewards. Tourist loyalty consists of attitude loyalty and behavior loyalty. Both employee emotion and service quality contain only one dimension.</p></sec><sec id="s3"><title>3. Research Method</title><sec id="s3_1"><title>3.1. Questionnaire Design</title><p>In this paper, two questionnaires were designed for scenic spot employees and tourist respectively. Referring to the satisfaction measurement scale [<xref ref-type="bibr" rid="scirp.72953-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref28">28</xref>] and considering the actual situation of Jiuzhaigou and Huanglong scenic spots, we constructed the indicators of employee satisfaction and employee emotion for the employee questionnaire. Indicators of employee service quality was designed by referring to the service</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Conceptual model (Hypothesis 1: Employee satisfaction has a significant positive impact on service quality; Hypothesis 2: Employee satisfaction has a significant positive impact on employee emotion; Hypothesis 3: Employee emotion has a significant positive impact on the service quality; Hypothesis 4: Service quality has a positive impact on tourist loyalty)</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/2-2120874x2.png"/></fig><p>quality measurement scale raised by Wen (2006) [<xref ref-type="bibr" rid="scirp.72953-ref29">29</xref>] and the United States SERVQUAL scale [<xref ref-type="bibr" rid="scirp.72953-ref21">21</xref>] . In brief, the employee questionnaire consists of 4 sections: social and demographic characteristics of the employee (4 questions), employee satisfaction (11 questions), employee emotion (5 questions) and employee service quality (6 questions). In the tourist questionnaire, indicators of service quality were constructed in the same way with the employee questionnaire, and indicators of tourist loyalty were designed by referring to other related literatures [<xref ref-type="bibr" rid="scirp.72953-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref31">31</xref>] . The tourist questionnaire consists of 3 sections: social and demographic characteristics of the tourist (7 questions), employee service quality (6 questions) and tourist loyalty (9 questions).</p><p>A five score Likert Scale was employed to measure the index of the questionnaires. The higher the score is, the higher the tourist evaluation value would be. This paper designed 2 reverse questions in the questionnaires, and the related scores were counted in reverse during the statistical analysis of data. The reliability of each questionnaire was tested by SPSS17.0 software. Except the Cronbach α coefficient of the working environment is 0.73, those of the other dimensions are all greater than 0.8. These results indicate the questionnaires are reliable.</p></sec><sec id="s3_2"><title>3.2. Data Collection</title><p>The research data of this paper were collected in Huanglong and Jiuzhaigou, the two famous scenic spots in Sichuan Province southwest China. Surveys were conducted on June 21<sup>st</sup>, 2013-August 19<sup>th</sup>. 1200 questionnaires were issued in total, and after screening, the actual effective questionnaires were 916 copies. Among them, the numbers of effective questionnaires of employees and tourist were 459 and 457 respectively. The effective recovery rate of the questionnaires was 76.33%.</p></sec></sec><sec id="s4"><title>4. Results</title><sec id="s4_1"><title>4.1. Sample Pairing</title><p>In the survey questionnaires, there were 6 pairs of identical measurement items according to the service quality of employee self-rating and tourist rating (<xref ref-type="table" rid="table1">Table 1</xref>). In this paper, these characteristic variables were used as the co-variant of propensity score model, and samples were paired with propensity score matching method.</p><p>The following Logit regression model was established according to the matching items:</p><disp-formula id="scirp.72953-formula34"><graphic  xlink:href="http://html.scirp.org/file/2-2120874x3.png"  xlink:type="simple"/></disp-formula><p>y stands for employee and visitor variables. When the service quality is evaluated by tourist and scenic employees, y values 1 and 0 respectively; p is propensity score and ε is residual term. The following formula can be obtained after Logit regression:</p><disp-formula id="scirp.72953-formula35"><graphic  xlink:href="http://html.scirp.org/file/2-2120874x4.png"  xlink:type="simple"/></disp-formula><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Service behavior variables used in the employee and tourist questionnaire respectively</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Code</th><th align="center" valign="middle" >The service quality measurement of tourist rating</th><th align="center" valign="middle" >Code</th><th align="center" valign="middle" >The service quality measurement of employee self-rating</th></tr></thead><tr><td align="center" valign="middle" >A1</td><td align="center" valign="middle" >The service skill of the employees of this scenic spot is professionally.</td><td align="center" valign="middle" >E1</td><td align="center" valign="middle" >I can provide professional and fast service.</td></tr><tr><td align="center" valign="middle" >A2</td><td align="center" valign="middle" >The employees of this scenic spot possess essential emergency handling ability.</td><td align="center" valign="middle" >E2</td><td align="center" valign="middle" >I have a certain ability to deal with emergency.</td></tr><tr><td align="center" valign="middle" >A3</td><td align="center" valign="middle" >The employees know this scenic spot well and can answer tourist questions such as where the drinks are sold.</td><td align="center" valign="middle" >E3</td><td align="center" valign="middle" >I know this scenic spot well and can answer tourist questions such as where the nearest washroom is, etc.</td></tr><tr><td align="center" valign="middle" >A4</td><td align="center" valign="middle" >The employees would take the initiative to greet visitors, for example, “hello”, and “welcome”.</td><td align="center" valign="middle" >E4</td><td align="center" valign="middle" >I would take the initiative to greet visitors, for example, “hello”, and “welcome”.</td></tr><tr><td align="center" valign="middle" >A5</td><td align="center" valign="middle" >The employees can use courtesies at work and serve with smile.</td><td align="center" valign="middle" >E5</td><td align="center" valign="middle" >I can use courtesies at work and service with smile.</td></tr><tr><td align="center" valign="middle" >A6</td><td align="center" valign="middle" >The scenic spot has complete and first-rate guide team.</td><td align="center" valign="middle" >E6</td><td align="center" valign="middle" >Guides of this scenic spot can offer clearly and detailed interpretation.</td></tr></tbody></table></table-wrap><p>In this formula, p is propensity score, while X is characteristic variable which includes service technology, emergency capability, and the knowledge of the scenic spot, the active greeting, courtesies and the tour guide team. The research steps are as followed: calculating the propensity score of each sample with this formula; running the Logit model [<xref ref-type="bibr" rid="scirp.72953-ref32">32</xref>] by using Stata statistical software and matching the samples under the principle of the nearest distance matching. Finally, a total of 350 samples were obtained. Among them, both the sample numbers of employee and tourist were 175. Then paired samples T test was carried out by using the characteristic variables of the two matched groups of samples. The results showed that the mean difference between the service quality self-evaluated by employees and the service quality evaluated by tourist was not significant (P &gt; 0.05), which indicated that the paired questionnaires were consistent. Thus the sample capacity was 175 after merging two databases.</p></sec><sec id="s4_2"><title>4.2. Validity and Reliability Analysis</title><p>In this paper, 4 dimensions (employee satisfaction, employee emotion, service quality and tourist loyalty) were carried through the exploratory factor analysis by using statistical software SPSS. After the samples were tested by KMO and Bartlett, the principal component analysis was adopted to maximize the variance of orthogonal rotation, and the factors whose characteristic value was greater than 1 were extracted. Screening the observed variables must follow two principles: a question cannot be automatically generated into a factor and the factor loading items must be greater than 0.5. Therefore, 7 latent variables that included working environment, living conditions, working rewards, service quality, employee emotions, behavior loyalty and attitude loyalty and 26 specific measurement items were formed (<xref ref-type="table" rid="table2">Table 2</xref>). In light of using AMOS software to calculate the standardized path coefficient and testing the convergent validity of scale with Average Variance Extracted, the computational formula is<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/2-2120874x5.png" xlink:type="simple"/></inline-formula>. In this formula, λ is the standardized path coefficients of each path during the process of factor analysis, while n represents the number of paths. Analysis results show that the AVE</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Variables used in the tourist loyalty model</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"   rowspan="2"  >Dimension</th><th align="center" valign="middle"  rowspan="2"  >Measurement description</th><th align="center" valign="middle"  colspan="3"  >Rotation factor load matrix</th></tr></thead><tr><td align="center" valign="middle" >Factor 1</td><td align="center" valign="middle" >Factor 2</td><td align="center" valign="middle" >Factor 3</td></tr><tr><td align="center" valign="middle"  colspan="2"   rowspan="6"  >Service quality</td><td align="center" valign="middle" >Service technology</td><td align="center" valign="middle" >0.894</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Emergency handling ability</td><td align="center" valign="middle" >0.879</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Degree of cognition about the scenic spot</td><td align="center" valign="middle" >0.856</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Active greeting</td><td align="center" valign="middle" >0.830</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Use courtesies and serve with smile</td><td align="center" valign="middle" >0.795</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Tour guide team</td><td align="center" valign="middle" >0.712</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Total explained variance</td><td align="center" valign="middle"  colspan="2"  >63.51%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  rowspan="7"  >Tourist loyalty</td><td align="center" valign="middle"  rowspan="4"  >Attitude loyalty</td><td align="center" valign="middle" >Hope to visit the scenic spot again</td><td align="center" valign="middle" >0.843</td><td align="center" valign="middle" >0.245</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Be considerate of the defects in the facilities and services of the scenic spot</td><td align="center" valign="middle" >0.826</td><td align="center" valign="middle" >0.326</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >In similar scenic spots, I would like to spend more money in this one</td><td align="center" valign="middle" >0.817</td><td align="center" valign="middle" >0.330</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Would like to strongly recommend this scenic spot to others</td><td align="center" valign="middle" >0.807</td><td align="center" valign="middle" >0.293</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Behavior loyalty</td><td align="center" valign="middle" >Prepare to visit the scenic spot again within the next three years</td><td align="center" valign="middle" >0.219</td><td align="center" valign="middle" >0.837</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Compared to other similar spots, I would firstly visit this one next time</td><td align="center" valign="middle" >0.334</td><td align="center" valign="middle" >0.836</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Have purchased other related services of this scenic spot</td><td align="center" valign="middle" >0.310</td><td align="center" valign="middle" >0.767</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Explanatory variance</td><td align="center" valign="middle" >40.754%</td><td align="center" valign="middle" >33.727%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >Total explained variance</td><td align="center" valign="middle"  colspan="2"  >74.481%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  rowspan="9"  >Employee satisfaction</td><td align="center" valign="middle"  rowspan="2"  >Working environment</td><td align="center" valign="middle" >Location of the scenic spot</td><td align="center" valign="middle" >0.050</td><td align="center" valign="middle" >0.817</td><td align="center" valign="middle" >0.061</td></tr><tr><td align="center" valign="middle" >tidiness and aesthetic degree of the working environment of scenic spot</td><td align="center" valign="middle" >0.300</td><td align="center" valign="middle" >0.826</td><td align="center" valign="middle" >0.131</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Living conditions</td><td align="center" valign="middle" >The general conditions and service quality of staff canteen</td><td align="center" valign="middle" >0.376</td><td align="center" valign="middle" >0.391</td><td align="center" valign="middle" >0.611</td></tr><tr><td align="center" valign="middle" >Living environment and conditions of employee dormitory.</td><td align="center" valign="middle" >0.168</td><td align="center" valign="middle" >−0.046</td><td align="center" valign="middle" >0.837</td></tr><tr><td align="center" valign="middle" >Traffic conditions (can easily commute between the company and the residence)</td><td align="center" valign="middle" >0.132</td><td align="center" valign="middle" >0.467</td><td align="center" valign="middle" >0.612</td></tr><tr><td align="center" valign="middle"  rowspan="4"  >Working rewards</td><td align="center" valign="middle" >Salary</td><td align="center" valign="middle" >0.799</td><td align="center" valign="middle" >0.164</td><td align="center" valign="middle" >0.278</td></tr><tr><td align="center" valign="middle" >Fringe benefits</td><td align="center" valign="middle" >0.797</td><td align="center" valign="middle" >0.228</td><td align="center" valign="middle" >0.282</td></tr><tr><td align="center" valign="middle" >Holiday time</td><td align="center" valign="middle" >0.783</td><td align="center" valign="middle" >0.132</td><td align="center" valign="middle" >0.381</td></tr><tr><td align="center" valign="middle" >Reward and punishment system</td><td align="center" valign="middle" >0.768</td><td align="center" valign="middle" >0.141</td><td align="center" valign="middle" >0.279</td></tr><tr><td align="center" valign="middle"  colspan="2"  ></td><td align="center" valign="middle" >Explanatory variance</td><td align="center" valign="middle" >31.130%</td><td align="center" valign="middle" >18.183%</td><td align="center" valign="middle" >15.129%</td></tr><tr><td align="center" valign="middle"  colspan="2"  ></td><td align="center" valign="middle" >Total explained variance</td><td align="center" valign="middle"  colspan="3"  >64.442%</td></tr><tr><td align="center" valign="middle"  colspan="2"   rowspan="4"  >Employee emotion</td><td align="center" valign="middle" >I work with high enthusiasm.</td><td align="center" valign="middle" >0.861</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >I like the present job very much.</td><td align="center" valign="middle" >0.821</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >I'm tired of my job. (−)</td><td align="center" valign="middle" >0.804</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >I have a strong dissatisfaction with the present work. (−)</td><td align="center" valign="middle" >0.780</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  colspan="2"  ></td><td align="center" valign="middle" >Total explained variance</td><td align="center" valign="middle" >65.514%</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>Note: “−” means negative questions.</p><p>values of all latent variables are more than 0.5, which means that they have a good explanatory validity.</p><p>In this paper, the SPSS software is used to analyze the reliability of each latent variable. The results show that the questionnaire reliability is good because the Cronbach coefficient of working environment and employee living conditions exceed the minimum standard 0.5, and the Cronbach α coefficient of the rest of the latent variables are all greater than 0.8 (<xref ref-type="table" rid="table3">Table 3</xref>).</p></sec><sec id="s4_3"><title>4.3 Model Construction and Hypothesis Testing</title><p>The model regards working environment, employee living conditions and working rewards as exogenous variables, while it regards employee emotion, service quality, attitude loyalty and behavior of tourist loyalty as endogenous variables. The testing relies on the use of AMOS17.0 analysis software to fit and analyze the data. The result indicates that the ratio of χ<sup>2</sup> and df is 735.572/284 = 2.590 &lt; 3, which achieves acceptable standards; other indexes（NFI, CFI, IFI, TLI）were all above 0.8, basically met the basic requirements (<xref ref-type="table" rid="table4">Table 4</xref>).</p><p>Path coefficient analysis results show that the impact of the relationship among the rest of the variables have been confirmed, except that the working rewards have no direct significant impact on the service quality (<xref ref-type="fig" rid="fig2">Figure 2</xref>).</p></sec></sec><sec id="s5"><title>5. Discussion and Conclusion</title><p>This paper conducts a questionnaire survey on the employees of Jiuzaigou and Huanglong scenic spots and the tourist. Samples are paired with propensity score matching method. On the basis of better validity test and reliability analysis, the structural equation model of tourist loyalty is built with 26 specific measurement indexes and 7</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Cronbach α values of the variables</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >Cronbach α</th></tr></thead><tr><td align="center" valign="middle" >Service quality</td><td align="center" valign="middle" >0.906</td></tr><tr><td align="center" valign="middle" >Attitude loyalty</td><td align="center" valign="middle" >0.905</td></tr><tr><td align="center" valign="middle" >Behavior loyalty</td><td align="center" valign="middle" >0.852</td></tr><tr><td align="center" valign="middle" >Working environment</td><td align="center" valign="middle" >0.791</td></tr><tr><td align="center" valign="middle" >Living conditions</td><td align="center" valign="middle" >0.695</td></tr><tr><td align="center" valign="middle" >Working rewards</td><td align="center" valign="middle" >0.856</td></tr><tr><td align="center" valign="middle" >Employee emotion</td><td align="center" valign="middle" >0.870</td></tr></tbody></table></table-wrap><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Goodness of fit test results</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >χ<sup>2</sup></th><th align="center" valign="middle" >df</th><th align="center" valign="middle" >NFI</th><th align="center" valign="middle" >CFI</th><th align="center" valign="middle" >IFI</th><th align="center" valign="middle" >TLI</th><th align="center" valign="middle" >RMSEA</th></tr></thead><tr><td align="center" valign="middle" >735.572</td><td align="center" valign="middle" >284</td><td align="center" valign="middle" >0.879</td><td align="center" valign="middle" >0.848</td><td align="center" valign="middle" >0.851</td><td align="center" valign="middle" >0.812</td><td align="center" valign="middle" >0.096</td></tr></tbody></table></table-wrap><p>Note: NFI means Normed Fit Index, CFI means Comparative Fit Index, IFI means Incremental Fit Index, TLI means Tucker-Lewis Index, RMSEA means Root-Mean-Square-Error-of-Approximation.</p><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> Testified path relationship graph (Note: * means P &lt; 0.05, ** means P &lt; 0.01.)</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/2-2120874x6.png"/></fig><p>potential variables which include working environment, employee living conditions, working rewards, employee emotion, service quality, attitude loyalty and behavior loyalty. The path analysis is carried out by using AMOS software. In 3 latent variables (working environment, employee living conditions, and working rewards) that constituted employee satisfaction, only the effect of working rewards on service quality is not significant, the rest of the variables are positively affecting the service quality. It is consistent with the research conclusions of Douglas in 1992 that “with high employee satisfaction, employees would be more prone to service-oriented behavior, thus providing high quality service in the process of service delivery” [<xref ref-type="bibr" rid="scirp.72953-ref33">33</xref>] . And at the same time, high employee satisfaction also positively affects the service quality through employee emotion. Lee explored the relations between service quality and destination loyalty by studying the loyalty of forest tourist [<xref ref-type="bibr" rid="scirp.72953-ref34">34</xref>] . The result showed that the forest tourist who had high perception of service quality tended to have higher satisfaction and participation, which could bring higher destination loyalty finally. It is consistent with the study result of this paper that “service quality affects tourist loyalty positively and significantly”.</p><p>Under such increasingly competitive circumstance, more and more tourism enterprises adopt the strategy of customer orientation and require service personnel to provide quality services to customers. Existing researches indicate that the factors like employee service quality, service standardization and not high enough standardization have affected the quality of tourism service in Jiuzhaigou scenic spot [<xref ref-type="bibr" rid="scirp.72953-ref35">35</xref>] . This paper reveals the intrinsic link of employee satisfaction, service quality and tourist loyalty. The more advantageous working conditions always cultivate the employees with higher satisfaction. They not only have higher loyalty for the service industry, but would also offer better service to the customers; therefore, the customers would highly appraise the service quality that they received [<xref ref-type="bibr" rid="scirp.72953-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref36">36</xref>] [<xref ref-type="bibr" rid="scirp.72953-ref37">37</xref>] . Enhancing the staff working environment and living conditions, improving reasonable working rewards and strengthening the management of employee emotion are the important cutting-points of upgrading Jiuzhaigou and Huanglong scenic spots’ service quality and tourist loyalty. As to all the items of the survey in this paper, 73.1% of employees are opposed to the statement that they have plenty of holiday time (choosing “somewhat disagree” and “strongly disagree”). Managers should ease the negative emotions of employees by specifically adopting some measures such as staggering holidays. Performance evaluation of employees is one of the most important human resource management measures in enterprise management. The key to enhance service quality and tourist loyalty is the scientific formulation of employee service quality standards and effective supervision.</p><p>Compared with previous studies, this paper explores the influence pathways and to what extent the employee satisfaction and service quality impact on tourist loyalty, and provides a new perspective for the study of tourist destination loyalty. But we only choose two geographically adjacent national level scenic spots with similar resource characteristics and development level in the empirical study of this paper. Meanwhile, its small sample size may have a certain impact on the conclusions of this study.</p></sec><sec id="s6"><title>Acknowledgements</title><p>The paper was supported by Sichuan International Cooperation Program (2016HH0080).</p></sec><sec id="s7"><title>Cite this paper</title><p>Xu, R.L. and Wang, J.Q. (2016) A Study of Tourist Loyalty Driving Factors from Employee Satisfaction Perspective. American Journal of Industrial and Business Management, 6, 1122-1132. http://dx.doi.org/10.4236/ajibm.2016.612105</p></sec></body><back><ref-list><title>References</title><ref id="scirp.72953-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Reichheld, F.F. and Sasser, E. (1990) Zero Defections: Quality Comes to Services. 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