基于TPB和TAM整合扩展模型的景区预约行为意向研究

doi:10.12054/lydk.bisu.249

摘要/Abstract

摘要：

本研究以4处上海市4A级景区为案例地，整合计划行为理论、技术接受模型，围绕构念“担忧”构建游客景区预约行为意向整合扩展模型，使用偏最小二乘法结构方程模型（PLS-SEM）进行模型检验。研究发现：主观规范、景区预约态度和知觉行为控制对景区预约行为意向有显著直接影响；感知易用性相较于感知有用性对知觉行为控制的影响更为显著；因疫情产生的担忧情绪通过主观规范和知觉行为控制间接影响景区预约行为意向。研究在理论上对传统模型进行整合拓展，从技术和管理角度为优化景区预约方式提供理论依据与实践建议。

关键词: 景区预约; 计划行为理论; 技术接受模型; 担忧; 偏最小二乘法结构方程模型

Abstract:

Based on the theory of planned behavior “TPB” and TAM, this study introduces the construct of “worry” to integrate this theoretical model and then proposes some relevant hypotheses. The results of using PLS-SEM to test the data reveal that subjective norms, reservation attitude, and perceived behavioral control have a direct significant impact on the behavior intention of attractions reservation. Compared with perceived ease of use, perceived usefulness has a greater influence on perceived behavior control. The “worry” caused by the epidemic exhibits a direct influence on subjective norms and perceived behavioral control. The model exhibits good explanatory and predictive power. This study also provides a theoretical basis and practical suggestions for tourist attraction reservation from the perspective of technology and management.

Keywords: tourist attraction reservation; theory of planned behavior; technology acceptance model; worry; PLS-SEM

中图分类号:

苏悦, 张宏梅. 基于TPB和TAM整合扩展模型的景区预约行为意向研究[J]. 旅游导刊, 2024, 8(2): 70-90.

SU Yue, ZHANG Hongmei. Reservation Intention of Tourist Attraction Based on TPB and TAM Integrated Expansion Model[J]. Tourism and Hospitality Prospects, 2024, 8(2): 70-90.

图/表 7

参考文献 55

[1]	Ajzen I. Perceived behavioral control,self-efficacy,locus of control,and the theory of planned behavior[J]. Journal of Applied Social Psychology, 2002, 32(4):665-683.
[2]	Armitage C J, Conner M T. Efficacy of the theory of planned behaviour:A meta-analytic review[J]. British Journal of Social Psychology, 2001, 40(4):471-499.
[3]	Bae S Y, Chang P J. The effect of coronavirus disease-19 (COVID-19)risk perception on behavioural intention towards “untact” tourism in South Korea during the first wave of the pandemic (March 2020)[J]. Current Issues in Tourism, 2021, 24(7):1017-1035.
[4]	Bagozzi R P, Yi Y. Assessing method variance in multitrait-multimethod matrices:The case of self-reported affect and perceptions at work[J]. Journal of Applied Psychology, 1990, 75(5):547-560.
[5]	Bentler P M, Bonett D G. Significance tests and goodness of fit in the analysis of covariance structures[J]. Psychological Bulletin, 1980, 88(3):588-606.
[6]	Borkovec T D, Ray W J, Stober J. Worry:A cognitive phenomenon intimately linked to affective,physiological,and interpersonal behavioral processes[J]. Cognitive Therapy and Research, 1998, 22(6):561-576.
[7]	Butler G, Mathews A. Anticipatory anxiety and risk perception[J]. Cognitive Therapy and Research, 1987, 11(5):551-565.
[8]	Chen H L, Huang X, Li Z Y. A content analysis of Chinese news coverage on COVID-19 and tourism[J]. Current Issues in Tourism, 2022, 25(2):198-205.
[9]	Chin W, Cheah J H, Liu Y D, et al. Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research[J]. Industrial Management & Data Systems, 2020, 120(12):2161-2209.
[10]	Chin W W, Marcolin B L, Newsted P R. A partial least squares latent variable modeling approach for measuring interaction effects:Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study[J]. Information Systems Research, 2003, 14(2):189-217.
[11]	Choi Y K, Totten J W. Self-construal’s role in mobile TV acceptance:Extension of TAM across cultures[J]. Journal of Business Research, 2012, 65(11):1525-1533.
[12]	Cohen J. Statistical Power Analysis for the Behavioral Sciences[M]. New York: Academic press, 2013.
[13]	Davis F D. A Technology Acceptance Model for Empirically Testing New End-user Information Systems:Theory and Results[D]. Cambridge: Massachusetts Institute of Technology, 1986.
[14]	Davis F D. Perceived usefulness,perceived ease of use,and user acceptance of information technology[J]. MIS Quarterly, 1989, 13(3):319-340.
[15]	Davis F D, Bagozzi R P, Warshaw P R. User acceptance of computer technology:A comparison of two theoretical models[J]. Management Science, 1989, 35(8):982-1003.
[16]	Dugas M J, Gagnon F, Ladouceur R, et al. Generalized anxiety disorder:A preliminary test of a conceptual model[J]. Behaviour Research and Therapy, 1998, 36(2):215-226.
[17]	Elci A, Abubakar A M, Ilkan M, et al. The impact of travel 2.0 on travelers booking and reservation behaviors[J]. Business Perspectives and Research, 2017, 5(2):124-136.
[18]	Elliott M A, Armitage C J, Baughan C J. Drivers’ compliance with speed limits:An application of the theory of planned behavior[J]. Journal of Applied Psychology, 2003, 88(5):964-972.
[19]	Fishbein M A, Ajzen I. Belief,attitude,intention,and behavior:An introduction to theory and research[J]. Contemporary Sociology, 1977, 6(2):244-245.
[20]	Fischhoff B, De Bruin W B, Perrin W, et al. Travel risks in a time of terror:Judgments and choices[J]. Risk Analysis, 2004, 24(5):1301-1309.
[21]	Fornell C, Larcker D F. Evaluating structural equation models with unobservable variables and measurement error[J]. Journal of Marketing Research, 1981, 18(1):39-50.
[22]	Freimuth V S, Hovick S R. Cognitive and emotional health risk perceptions among people living in poverty[J]. Journal of Health Communication, 2012, 17(3):303-318.
[23]	Hair J F, Hult G T M, Ringle C M, et al. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)[M]. 3^rd ed. Thousand Oaks: Sage Publications, 2022.
[24]	Hair J F, Risher J J, Sarstedt M, et al. When to use and how to report the results of PLS-SEM[J]. European Business Review, 2019, 31(1):2-24.
[25]	Han J H, Kwon H J, Kim D. A study on factors influencing Chinese tourists’ intention to use online travel reservation services[J]. The Journal of Society for e-Business Studies, 2013, 18(4):257-272.
[26]	Henseler J. On the convergence of the partial least squares path modeling algorithm[J]. Computational Statistics, 2010, 25(1):107-120.
[27]	Henseler J, Ringle C M, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling[J]. Journal of the Academy of Marketing Science, 2015, 43(1):115-135.
[28]	Hock M, Ringle C M. Local strategic networks in the software industry:An empirical analysis of the value continuum[J]. International Journal of Knowledge Management Studies, 2010, 4(2):132-151.
[29]	Jahari S A, Yang I C M, French J A, et al. COVID-19 and Beyond:Understanding travel risk perception as a process[J]. Tourism Recreation Research, 2023, 48(3):449-464.
[30]	Kiatkawsin K, Bui N A, Hrankai R, et al. The moderating roles of sensation seeking and worry among nature-based adventure tourists[J]. International Journal of Environmental Research and Public Health, 2021, 18(4):2021.
[31]	Lee J H, Lee S H, Sim K W. A study on the impact of visitor satisfaction of Nogodan area at the Jirisan National Park on behavioral intentions:Focus on appropriateness of national park reservation system as a moderating variable[J]. The Journal of Korean Institute of Forest Recreation, 2015, 19(1):85-91.
[32]	Li T T, Zhu Z X. A meta-analysis of online travel booking services adoption:The moderating effects of national or regional economic development level and culture differences[J]. Aslib Journal of Information Management, 2023, 75(6):1209-1234.
[33]	Mursityo Y T. Analysis of Brawijaya University academic information systems acceptance on the user characteristic,system quality,support of top management and information technology,perceived usefulness,and perceived ease of use[J]. Journal of Information Technology and Computer Science, 2018, 3(2):202-213.
[34]	Podsakoff P M, Organ D W. Self-reports in organizational research:Problems and prospects[J]. Journal of Management, 1986, 12(4):531-544.
[35]	Schmiege S J, Bryan A, Klein W M P. Distinctions between worry and perceived risk in the context of the theory of planned behavior[J]. Journal of Applied Social Psychology, 2009, 39(1):95-119.
[36]	Sim K W, Choe Y, Jang J, et al. A study on the differences in the cognition of the visitor-reservation system:Focused on Uiryeong-gil area in Bukhansan National Park[J]. Journal of Forest and Environmental Science, 2021, 37(1):69-78.
[37]	Tenenhaus M, Vinzi V E, Chatelin Y M, et al. PLS path modeling[J]. Computational Statistics & Data Analysis, 2005, 48(1):159-205.
[38]	Vasey M W, Borkovec T D. A catastrophizing assessment of worrisome thoughts[J]. Cognitive Therapy and Research, 1992, 16(5):505-520.
[39]	Vishwakarma P, Mukherjee S, Datta B. Antecedents of adoption of virtual reality in experiencing destination:A study on the Indian consumers[J]. Tourism Recreation Research, 2020, 45(1):42-56.
[40]	Wang T, Watanabe T. Introducing management actions to unmanaged campsites in Daisetsuzan National Park,Japan:A discussion based on a reservation system in Taiwan’s national parks[J]. Land, 2022, 11(3):337.
[41]	Wetzels M, Odekerken-Schröder G, Van Oppen C. Using PLS path modeling for assessing hierarchical construct models:Guidelines and empirical illustration[J]. MIS Quarterly, 2009, 33(1):177-195.
[42]	Wolff K, Larsen S,. Tourist worries, here and now vs. there and then:The effect of item wording in the Tourist Worry Scale[J]. Tourism Management, 2013(35):284-287.
[43]	Zhao Y Z, Wang H, Guo Z, et al. Online reservation intention of tourist attractions in the COVID-19 context:An extended technology acceptance model[J]. Sustainability, 2022, 14(16):10395.
[44]	李东和, 张鹭旭. 基于TAM的旅游App下载使用行为影响因素研究[J]. 旅游学刊, 2015, 30(8):26-34.
	[ LI Donghe, ZHANG Luxu. Model of influential factors for downloading and using tourism apps based on a technology acceptance model[J]. Tourism Tribune, 2015, 30(8):26-34.]
[45]	李卓. 当八成5A级旅游景区开始预约后,我们该怎么看待预约旅游?[N]. 经济日报, 2020-05-15.
	[ LI Zhuo. When 80% of the 5A-level tourist attractions begin to make reservations,what should we think of booking tours?[N]. Economic Daily, 2020-05-15.]
[46]	邱宏亮. 基于TPB拓展模型的出境游客文明旅游行为意向影响机制研究[J]. 旅游学刊, 2017, 32(6):75-85.
	[ QIU Hongliang. Developing an extended theory of planned behavior model to predict outbound tourists’ civilization tourism behavioral intention[J]. Tourism Tribune, 2017, 32(6):75-85.]
[47]	汤丹丹, 温忠麟. 共同方法偏差检验:问题与建议[J]. 心理科学, 2020, 43(1):215-223.
	[ TANG Dandan, WEN Zhonglin. Statistical approaches for testing common method bias:Problems and suggestions[J]. Journal of Psychological Science, 2020, 43(1):215-223.]
[48]	王子梦, 万红莲, 石雯洁, 等. 基于女性视角的低碳旅游综合评价研究——以陕西省宝鸡市为例[J]. 地域研究与开发, 2022, 41(1):110-115.
	[ WANG Zimeng, WAN Honglian, SHI Wenjie, et al. Comprehensive evaluation research on low-carbon tourism from the female perspective:A case study of Baoji city in Shaanxi province[J]. Areal Research and Development, 2022, 41(1):110-115.]
[49]	闫岩. 计划行为理论的产生、发展和评述[J]. 国际新闻界, 2014, 36(7):113-129.
	[ YAN Yan. A review on the origins and development of the theory of planned behavior[J]. Journal of International & Communication, 2014, 36(7):113-129.]
[50]	杨翾, 彭迪云, 谢菲. 基于TAM/TPB的感知风险认知对用户信任及其行为的影响研究——以支付增值产品余额宝为例[J]. 管理评论, 2016, 28(6):229-240.
	[ YANG Xuan, PENG Diyun, XIE Fei. A study on the effects of TAM/TPB-based perceived risk cognition on user’s trust and behavior taking Yu’ebao,a value-added payment product,as an example[J]. Management Review, 2016, 28(6):229-240.]
[51]	岳鸿飞, 刘佳昊. 我国预约旅游的发展特征和发展对策[J]. 发展研究, 2021(2):73-79.
	[ YUE Hongfei, LIU Jiahao. The development characteristics and countermeasures of China’s reservation travel[J]. Development Research, 2021(2):73-79.]
[52]	张圆刚, 余向洋, 程静静, 等. 基于TPB和TSR模型构建的乡村旅游者行为意向研究[J]. 地理研究, 2017, 36(9):1725-1741.
	[ ZHANG Yuangang, YU Xiangyang, CHENG Jingjing, et al. Recreational behavior and intention of tourists to rural scenic spots based on TPB and TSR Models[J]. Geographical Research, 2017, 36(9):1725-1741.]
[53]	周浩, 龙立荣. 共同方法偏差的统计检验与控制方法[J]. 心理科学进展, 2004, 12(6):942-950.
	[ ZHOU Hao, LONG Lirong. Statistical remedies for common method biases[J]. Advances in Psychological Science, 2004, 12(6):942-950.]
[54]	朱长宁, 鲁庆尧, 王树进. 基于拓展计划行为理论的休闲农业旅游行为意向研究[J]. 西北农林科技大学学报(社会科学版), 2016, 16(5):143-149.
	[ ZHU Changning, LU Qingyao, WANG Shujin. Research on leisure agricultural tourism behavioral intention based on expanded theory of planned behavior[J]. Journal of Northwest A&F University (Social Science Edition), 2016, 16(5):143-149.]
[55]	朱东国, 刘婷. 基于网络文本内容分析的红色旅游经典景区预约平台建设[J]. 长沙大学学报, 2022, 36(1):65-72.
	[ ZHU Dongguo, LIU Ting. Construction of reservation platform for classic red tourism scenic spots based on content analysis of network text[J]. Journal of Changsha University, 2022, 36(1):65-72.]

变量 Variable	类别 Category	数量（份） Quantity	占比（%） Percentage
性别 Gender	男	163	49
性别 Gender	女	172	51
年龄 Age	18岁及其以下	6	2
	18~30岁	231	69
	30~40岁	76	23
	40~50岁	16	5
	50~60岁	3	1
	60岁及以上	3	1
婚姻状况 Marriage Status	未婚	234	70
婚姻状况 Marriage Status	已婚	101	30
职业 Occupation	企/事业单位/国家机关/党群组织单位负责人	63	19
	农/林/牧/渔/水利业生产/运输操作人员	8	2
	专业技术人员	94	28
	商业/服务业人员	42	13
	退休人员	3	1
	待业/下岗	7	2
	办事人员	7	2
	个体户/自由职业者	13	4
	学生	45	13
	其他	53	16
受教育程度 Educational attainment	高中及以下	16	5
	专科	23	7
	本科	170	51
	研究生及以上	126	38

变量 Variable	类别 Category	数量（份） Quantity	占比（%） Percentage
性别 Gender	男	163	49
性别 Gender	女	172	51
年龄 Age	18岁及其以下	6	2
	18~30岁	231	69
	30~40岁	76	23
	40~50岁	16	5
	50~60岁	3	1
	60岁及以上	3	1
婚姻状况 Marriage Status	未婚	234	70
婚姻状况 Marriage Status	已婚	101	30
职业 Occupation	企/事业单位/国家机关/党群组织单位负责人	63	19
	农/林/牧/渔/水利业生产/运输操作人员	8	2
	专业技术人员	94	28
	商业/服务业人员	42	13
	退休人员	3	1
	待业/下岗	7	2
	办事人员	7	2
	个体户/自由职业者	13	4
	学生	45	13
	其他	53	16
受教育程度 Educational attainment	高中及以下	16	5
	专科	23	7
	本科	170	51
	研究生及以上	126	38

变量 Variable	题项 Item	标准化因子负荷量 Standardized load	克隆巴赫系数 Cronbach’s α	组合信度 CR	平均方差抽取量 AVE
景区预约态度 ATT	总的来说，我喜欢使用景区预约	0.850	0.916	0.941	0.799
	总的来说，我是赞成使用景区预约的	0.927
	总的来说，我对使用景区预约持积极态度	0.901
	总的来说，景区预约参观是很有吸引力的	0.895
景区预约行为意向 BI	我愿意增加景区预约的使用频率	0.888	0.891	0.925	0.754
	相比于现场购买景区门票，线上预约永远是我的首选	0.862
	我愿意推荐别人使用景区预约功能	0.901
	我愿意了解和使用景区预约平台开发出的更多功能	0.821
担忧 Worry	出游的时候，我经常担心出游计划受到新冠疫情政策变动的影响而随时中断	0.870	0.868	0.919	0.792
	出游时，我担心景区可能会受疫情影响而关闭	0.925
	当我在游玩时，我担心出游目的地变成中高风险区	0.874
知觉行为控制 PBC	我相信在以后的出游中，我有能力完成线上预约	0.867	8.824	0.895	0.739
	采用哪一个景区预约渠道是完全由我自己来决定的	0.853
	我有足够的时间来预约景区	0.859
感知易用性 PEU	对我来说，熟练使用景区预约系统是很容易的	0.884	0.892	0.933	0.822
	对我来说，寻找景区预约平台很容易	0.917
	总的来说，利用景区预约操作很方便	0.918
感知有用性 PU	在旅行中使用景区预约系统可以帮助我有效地规划行程	0.883	0.932	0.951	0.830
	使用景区预约有助于提高我的旅行体验质量	0.920
	使用景区预约系统可以使我的旅行游览更加便利	0.933
	我发现景区预约对我的旅行安排很有用	0.909
主观规范 SN	那些对我重要的人对我使用景区预约的行为表示支持	0.958	0.959	0.974	0.925
	那些对我重要的人对我使用景区预约的行为表示理解	0.967
	那些对我重要的人对我使用景区预约的行为表示赞同	0.959

变量 Variable	题项 Item	标准化因子负荷量 Standardized load	克隆巴赫系数 Cronbach’s α	组合信度 CR	平均方差抽取量 AVE
景区预约态度 ATT	总的来说，我喜欢使用景区预约	0.850	0.916	0.941	0.799
	总的来说，我是赞成使用景区预约的	0.927
	总的来说，我对使用景区预约持积极态度	0.901
	总的来说，景区预约参观是很有吸引力的	0.895
景区预约行为意向 BI	我愿意增加景区预约的使用频率	0.888	0.891	0.925	0.754
	相比于现场购买景区门票，线上预约永远是我的首选	0.862
	我愿意推荐别人使用景区预约功能	0.901
	我愿意了解和使用景区预约平台开发出的更多功能	0.821
担忧 Worry	出游的时候，我经常担心出游计划受到新冠疫情政策变动的影响而随时中断	0.870	0.868	0.919	0.792
	出游时，我担心景区可能会受疫情影响而关闭	0.925
	当我在游玩时，我担心出游目的地变成中高风险区	0.874
知觉行为控制 PBC	我相信在以后的出游中，我有能力完成线上预约	0.867	8.824	0.895	0.739
	采用哪一个景区预约渠道是完全由我自己来决定的	0.853
	我有足够的时间来预约景区	0.859
感知易用性 PEU	对我来说，熟练使用景区预约系统是很容易的	0.884	0.892	0.933	0.822
	对我来说，寻找景区预约平台很容易	0.917
	总的来说，利用景区预约操作很方便	0.918
感知有用性 PU	在旅行中使用景区预约系统可以帮助我有效地规划行程	0.883	0.932	0.951	0.830
	使用景区预约有助于提高我的旅行体验质量	0.920
	使用景区预约系统可以使我的旅行游览更加便利	0.933
	我发现景区预约对我的旅行安排很有用	0.909
主观规范 SN	那些对我重要的人对我使用景区预约的行为表示支持	0.958	0.959	0.974	0.925
	那些对我重要的人对我使用景区预约的行为表示理解	0.967
	那些对我重要的人对我使用景区预约的行为表示赞同	0.959

变量 Variable	主观规范 SN	景区预约态度 ATT	感知易用性 PEU	感知有用性 PU	担忧 Worry	知觉行为控制 PBC	景区预约行为意向 BI
主观规范 SN	0.962
景区预约态度 ATT	0.637	0.894
感知易用性 PEU	0.634	0.563	0.907
感知有用性 PU	0.671	0.663	0.557	0.911
担忧 Worry	0.160	0.175	0.177	0.180	0.890
知觉行为控制 PBC	0.680	0.621	0.700	0.555	0.225	0.860
景区预约行为意向 BI	0.617	0.762	0.560	0.583	0.227	0.631	0.868