| Since the1980s, highway in our country is playing a more and more important role for its rapid development. At the same time, with economic development and ideological changes, people’s sense of service is getting stronger. The requirement of the quality of services received in the process of traffic on highway is becoming higher. So the improvement of highway service quality becomes an issue that need to be solved.Combined with the SERVQUAL model and structural equation model, this paper studied on highway service quality evaluation system and factors of zone of tolerance, and then constructed game models between service related parties (highway operators, customers and service contractors), which is to provide reference for highway service quality improvement.Firstly, considering the particularity in highway service, this paper proposed evaluation index system of highway service quality based on SERVQUAL and summary analysis of previous studies, which include5first index signs on the basis of five dimensions of service quality, as well as27second index signs based on the practical problems in the area of highway service. These indicators integrated the particularity in highway service into service quality evaluation scale and made a detailed description of service quality in specific areas.Secondly, in order to ensure the scientificity and rationality, an empirical analysis was made on the highway perceived service quality and customer satisfaction survey. And then the theoretical model was further tested and corrected by survey data, which confirmed the highway service quality theoretical model and revealed the intrinsic relationship between perceived service quality and the five dimensions, that is to say, responsiveness, assurance, empathy, reliability and tangibility do have a significant effect on perceived service quality. Among them, responsiveness is most concerned by customers.Thirdly, in order to realize the zone of tolerance in highway service quality, this paper made in-depth exploration of the width and influence factors of zone of tolerance through questionnaires and statistics by AMOS17.0and SPSS17.0, which verified the rationality of the hypothesis, namely, past experience, environmental factors and customer attitude significantly affect adequate expectation. Past experience, environmental factors and customer attitude significantly affect desired expectation. In addition, there is a negative correlation between the width of zone of tolerance in highway service quality and the importance of service. Finally, from the perspectives of highway operator and customer, highway operators and highway operator and service contractor, this paper constructed game models to analyze their actions respectively. Game analysis between highway operator and customer shows that there exists nash equilibrium (no pay, no improvement) without consideration of customer flowing, and when considering customers flowing and the sum of the profits from customer flowing for highway operator improve and don’t improve highway service quality is greater than the total cost they are possible to pay, there exists nash equilibrium (no pay, improvement). Game analysis between highway operators shows that there exists nash equilibrium (improvement, improvement) under two circumstances, the first one is when short-term profits after improving highway service quality are lower than previous and the profits from customer flowing is greater than cost, and the second one is when short-term profits after improving highway service quality are higher than previous. At these times, highway operator tends to choose to improve service quality. Game analysis between highway operator and service contractor shows that the probability of the highway operator to regulate is related to the cost service contractor need to pay when improving the quality of service, the punishment cost, the profits service contractor get after improving service quality and cooperation benefits. The probability of service contractor improving service quality is related to the punishment cost and the regulatory cost. |