考虑游客拥挤感知的旅游线路优化设计
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摘要
为提升游客的旅游体验和景区的服务水平,探讨景点拥挤状态下游客的拥挤感知及其调适行为,分析游客拥挤-调适行为对游线设计的影响及其机理.引入热门链路概念,依据热门链路的热度、位置排序分析旅游线路的多样性.以景点满意度最大、景点间走行时间最短、景点拥挤度最低为优化目标,考虑游客参观景点个数、游览时间等约束条件,建立多目标景区线路优化模型,并利用粒子群算法进行线路优度评价.最后,分析景点拥挤度权重系数对线路优化的影响,以颐和园景区为例,开展拥挤景区内游客游线及其行为调查与分析,进行游线优化.结果显示:游客感知拥挤时,为提高旅游体验会采取认知调适、行为调适和不再调适等调适策略;颐和园浅度游和深度游链路式优化游线中可分别包含1～2和2～3个热门链路.深度游优化游线(No. 75)的优度值为57. 39,高于颐和园推荐游线,表明优化模型精度较高.线路中包含的热门链路数量、热度、位置排序和拥挤值影响游线优度值,随着拥挤度权重系数的提高,部分游线的优度值增加,可改变游线的推荐排序.
Tourists' crowding perception and adjustment behavior under crowded condition were explored and the influence mechanism of tourists' crowding-adjustment behavior on tour routes design was analyzed to enhance the tourists' experience and service level of scenic site. "Hot link "was defined and the diversity of tour routes was analyzed according to the popularity and sorting location of "Hot link". Tour routes multi-objective optimization functions were prompted for the tour route design regarding the maximum satisfaction and the minimum walking time between scenic spots and the minimum crowding degree as the optimal objectives. Considering the number of visiting scenic spots,visiting time and other constraint conditions,the goodness value of the tour route was calculated based on the particle swarm optimization model. The impacts of weighed coefficient of crowding degree of scenic spots on tour routes optimization were discussed. A questionnaire of tourists' tour route and behavior information was carried out in the Summer Palace and the optimal tour routes were listed and categorized. Results show that adjustment behaviors such as cognitive adjustment, behavior adjustment and cease adjustment are adaptive to improving tour experience when tourist perceive crowded. The "Hot link"number of quick tour and depth tour is 1-2 and 2-3 respectively. The goodness value of depth tour route( No. 75) is57. 39 and is bigger than official recommended tour route,which indicates the optimization model has a higher accuracy. The number,popularity,sorting location and crowding degree value of "Hot link "affect tour routes' goodness value. With the increase of weighed coefficient of crowding degree of scenic spots,some tour routes' goodness value increases,and the recommended sorting changes.
Tourists' crowding perception and adjustment behavior under crowded condition were explored and the influence mechanism of tourists' crowding-adjustment behavior on tour routes design was analyzed to enhance the tourists' experience and service level of scenic site. "Hot link "was defined and the diversity of tour routes was analyzed according to the popularity and sorting location of "Hot link". Tour routes multi-objective optimization functions were prompted for the tour route design regarding the maximum satisfaction and the minimum walking time between scenic spots and the minimum crowding degree as the optimal objectives. Considering the number of visiting scenic spots,visiting time and other constraint conditions,the goodness value of the tour route was calculated based on the particle swarm optimization model. The impacts of weighed coefficient of crowding degree of scenic spots on tour routes optimization were discussed. A questionnaire of tourists' tour route and behavior information was carried out in the Summer Palace and the optimal tour routes were listed and categorized. Results show that adjustment behaviors such as cognitive adjustment, behavior adjustment and cease adjustment are adaptive to improving tour experience when tourist perceive crowded. The "Hot link"number of quick tour and depth tour is 1-2 and 2-3 respectively. The goodness value of depth tour route( No. 75) is57. 39 and is bigger than official recommended tour route,which indicates the optimization model has a higher accuracy. The number,popularity,sorting location and crowding degree value of "Hot link "affect tour routes' goodness value. With the increase of weighed coefficient of crowding degree of scenic spots,some tour routes' goodness value increases,and the recommended sorting changes.
引文
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[9] HUANG H C. The application of ant colony optimization algorithm in tour route planning[J]. Journal of Theoretical and Applied Information Technology,2013,52(3):343-347.
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[12]马晓龙.基于游客行为的旅游线路组织研[J].地理与地理信息科学,2005,21(2):98-101.MA X L. A study on organization of tour routes based on tourists behaviors[J]. Geography and Geo-Information Science,2005,21(2):98-101.(in Chinese)
[13] TSAI C Y, CHUNG S H. A personalized route recommendation service for theme parks using RFID information and tourist behavior[J]. Decision Support Systems,2012,52(2):514-527.
[14] SHOVAL N,ISAACSON M. Sequence alignment as a method for human activity analysis in space and time[J]. Annals of Association of American Geographers,2007,97(2):282-297.
[15] ASAKURA Y,IRYO T. Analysis of tourist behavior based on the tracking data collected using a mobile communication instrument[J]. Transportation Research Part A:Policy and Practice,2007,41(7):684-690.
[16] HE Z Q,WU Z,ZHOU B C,et al. Tourist routes recommendation based on latent dirichlet allocation model[C]∥Proceedings of 2015 12th Web Information System and Application Conference. Washington,DC:IEEE Computer Society,2015:201-206.
[17] SHELBY B, VASKE J J, HEBERLEIN T A.Comparative analysis of crowding in multiple locations:results from fifteen years of research[J]. Leisure Sciences,1989,11:269-291.
[18]武鑫森.景区主客观拥挤感知研究[D].北京:北京工业大学,2017:42-52.WU X S. Research on subjective and objective crowding perception in scenic spots[D]. Beijing:Beijing University of Technology,2017:42-52.(in Chinese)
[19] HAMMITT W E,PATTERSON M E. Coping behavior to avoid visitor encounters:its relationship to wildland privacy[J]. Journal of Leisure Research,1991,23(3):225-237.
[20]张丛文.拥挤情境下游客调适行为研究——以西溪国家湿地公园为例[D].杭州:浙江工商大学,2012:23-26.ZHANG C W. Tourist coping behavior in crowding environment:a case study on the Xixi National Wetland Park in Hangzhou[D]. Hangzhou:Zhejiang Gongshang University,2012:23-26.(in Chinese)
[21]汪宇明.核心边缘理论在区域旅游规划中的应用[J].经济地理,2002,22(3):372-375.WANG Y M. Core-periphery geographical theory in regional tourism planning[J]. Economic Geography,2002,22(3):372-375.(in Chinese)
[22]黄潇婷.旅游者时空行为研究[M].北京:中国旅游出版社,2011:141-142.HUANG X T. Tourists spatial-temporal behavior study[M]. Beijing:China Travel&Tourism Press,2011:141-142.(in Chinese)
[23] LEWIS H F,SEXTON T R. On the tour partitioning heuristic for the unit demand capacitated vehicle routing problem[J]. Operations Research Letters,2007,35(3):374-378.
[24]李宁.粒子群优化算法的理论分析与应用研究[D].武汉:华中科技大学,2006:109-115.LI N. Analysis and application of particle swarm optimization[D]. Wuhan:Huazhong University of Science and Technology,2006:109-115.(in Chinese)
[25] MASLOW A H. A theory of human motivation[J].Psychological Review,1943,50(4):30-37.
[2]李渊,丁燕杰,王德.旅游者时间约束和空间行为特征的景区旅游线路设计方法研究[J].旅游学刊,2016,31(9):50-60.LI Y,DING Y J,WANG D. A new approach for designing tourist routes by considering travel time constraints and spatial behavior characteristics of tourists[J]. Tourism Tribune,2016,31(9):50-60.(in Chinese)
[3] UYSAL M. Satisfaction components in outdoor recreation and tourism settings[J]. E-review of Tourism Research,2003,1(3):35-38.
[4]曹旭.旅游线路优化设计研究[D].兰州:西北民族大学,2010:22-31.CAO X. The research of tourist route on optimization design[D]. Lanzhou:Northwest University for Nationalities,2010:22-31.(in Chinese)
[5]谢深洪.岳麓山风景名胜区旅游线路设计研究[D].长沙:湖南师范大学,2013:35-58.XIE S H. Tourist route design research on Yuelu Mountain scenic area[D]. Changsha:Hunan Normal University,2013:35-58.(in Chinese)
[6]饶亚玲.基于客流疏导的景区游览线路优化研究[D].泉州:华侨大学,2015:46-60.RAO Y L. A research on scenic tour route optimization based on passenger flow counseling[D]. Quanzhou:Huaqiao University,2015:46-60.(in Chinese)
[7]唐耀平,余宏,王文木,等.基于多目标的TSP模型在永州市旅游线路设计中的应用[J].中南林业科技大学学报,2011,31(10):154-157.TANG Y P,YU H,WANG W M,et al. Application of TSP model based multi-objective in Yongzhou city’s tourist routes[J]. Journal of Central South University of Forestry&Technology,2011,31(10):154-157.(in Chinese)
[8] HAN Y, GUAN H Z, GUAN J Y. Tour route multiobjective optimization design based on the tourist satisfaction[J]. Discrete Dynamics in Nature and Society,2014,2014(1):1-8.
[9] HUANG H C. The application of ant colony optimization algorithm in tour route planning[J]. Journal of Theoretical and Applied Information Technology,2013,52(3):343-347.
[10] ZHENG W M,LIAO Z X,QIN J. Using a four-step heuristic algorithm to design personalized day tourroute within a tourist attraction[J]. Tourism Management,2017,62:335-349.
[11]周尚意,李淑方,张江雪.行为地理与城市旅游线路设计——以苏州一日游线路设计为例[J].旅游学刊,2002,17(5):66-70.ZHOU S Y,LI S F,ZHANG J X. Behavioral geography and city tour route design—a case study of“one-day tour in Suzhou”[J]. Tourism Tribune,2002,17(5):66-70.(in Chinese)
[12]马晓龙.基于游客行为的旅游线路组织研[J].地理与地理信息科学,2005,21(2):98-101.MA X L. A study on organization of tour routes based on tourists behaviors[J]. Geography and Geo-Information Science,2005,21(2):98-101.(in Chinese)
[13] TSAI C Y, CHUNG S H. A personalized route recommendation service for theme parks using RFID information and tourist behavior[J]. Decision Support Systems,2012,52(2):514-527.
[14] SHOVAL N,ISAACSON M. Sequence alignment as a method for human activity analysis in space and time[J]. Annals of Association of American Geographers,2007,97(2):282-297.
[15] ASAKURA Y,IRYO T. Analysis of tourist behavior based on the tracking data collected using a mobile communication instrument[J]. Transportation Research Part A:Policy and Practice,2007,41(7):684-690.
[16] HE Z Q,WU Z,ZHOU B C,et al. Tourist routes recommendation based on latent dirichlet allocation model[C]∥Proceedings of 2015 12th Web Information System and Application Conference. Washington,DC:IEEE Computer Society,2015:201-206.
[17] SHELBY B, VASKE J J, HEBERLEIN T A.Comparative analysis of crowding in multiple locations:results from fifteen years of research[J]. Leisure Sciences,1989,11:269-291.
[18]武鑫森.景区主客观拥挤感知研究[D].北京:北京工业大学,2017:42-52.WU X S. Research on subjective and objective crowding perception in scenic spots[D]. Beijing:Beijing University of Technology,2017:42-52.(in Chinese)
[19] HAMMITT W E,PATTERSON M E. Coping behavior to avoid visitor encounters:its relationship to wildland privacy[J]. Journal of Leisure Research,1991,23(3):225-237.
[20]张丛文.拥挤情境下游客调适行为研究——以西溪国家湿地公园为例[D].杭州:浙江工商大学,2012:23-26.ZHANG C W. Tourist coping behavior in crowding environment:a case study on the Xixi National Wetland Park in Hangzhou[D]. Hangzhou:Zhejiang Gongshang University,2012:23-26.(in Chinese)
[21]汪宇明.核心边缘理论在区域旅游规划中的应用[J].经济地理,2002,22(3):372-375.WANG Y M. Core-periphery geographical theory in regional tourism planning[J]. Economic Geography,2002,22(3):372-375.(in Chinese)
[22]黄潇婷.旅游者时空行为研究[M].北京:中国旅游出版社,2011:141-142.HUANG X T. Tourists spatial-temporal behavior study[M]. Beijing:China Travel&Tourism Press,2011:141-142.(in Chinese)
[23] LEWIS H F,SEXTON T R. On the tour partitioning heuristic for the unit demand capacitated vehicle routing problem[J]. Operations Research Letters,2007,35(3):374-378.
[24]李宁.粒子群优化算法的理论分析与应用研究[D].武汉:华中科技大学,2006:109-115.LI N. Analysis and application of particle swarm optimization[D]. Wuhan:Huazhong University of Science and Technology,2006:109-115.(in Chinese)
[25] MASLOW A H. A theory of human motivation[J].Psychological Review,1943,50(4):30-37.