IDEAS home Printed from https://ideas.repec.org/a/eee/forpol/v174y2025ics1389934125000759.html

How demand-side incentive policies drive the diffusion of forest wellness tourism products: An agent-based modeling analysis

Author

Listed:
  • Li, Ying
  • Liu, Yuxin
  • Wang, Wenlong

Abstract

The market share of forest wellness tourism is relatively low, and there is an urgent need to formulate effective promotion strategies. However, there is a lack of research on the effectiveness of diffusion incentive policies tailored to the characteristics of forest wellness tourism products. Moreover, the interdependent decision-making process among consumers adds complexity to policy evaluation. To this end, the study develops a micro-level diffusion model for forest wellness tourism products based on the infectious disease model. Using agent-based modeling (ABM), it simulates the diffusion processes of different tiers of forest wellness tourism products under various demand-side incentive policies and examines the relative effectiveness of different policy measures and their combinations. The simulation results show that: ① When the subsidy intensity exceeds 0.5, the diminishing effect on the promotion of the diffusion of comfort-oriented forest wellness tourism products becomes more apparent. ② Implementing wellness base certification policies in comfort-oriented forest wellness tourism products has a stronger effect on the final diffusion outcome. ③ Relying solely on information promotion policies to diffuse comfort-oriented forest wellness tourism products is a long-term process. ④ The priority of policy implementation varies depending on the different levels of products. ⑤ To enhance cost-effectiveness and sustainability, economic and non-economic incentive policies should be combined to promote forest wellness tourism products. The research results provide a scientific basis for relevant government departments to deeply understand the micro-logic of changes in the forest wellness tourism market and optimize relevant incentive policies.

Suggested Citation

  • Li, Ying & Liu, Yuxin & Wang, Wenlong, 2025. "How demand-side incentive policies drive the diffusion of forest wellness tourism products: An agent-based modeling analysis," Forest Policy and Economics, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:forpol:v:174:y:2025:i:c:s1389934125000759
    DOI: 10.1016/j.forpol.2025.103496
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1389934125000759
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.forpol.2025.103496?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhu, Ronghui & Ma, Tieju, 2025. "Policy mixes to promote the diffusion of battery electric vehicles with an agent-based model and experiments using the case of China," Energy Economics, Elsevier, vol. 142(C).
    2. Ganglmair-Wooliscroft, Alexandra & Wooliscroft, Ben, 2016. "Diffusion of innovation: The case of ethical tourism behavior," Journal of Business Research, Elsevier, vol. 69(8), pages 2711-2720.
    3. Tan-Soo, Jie-Sheng & Li, Jun & Qin, Ping, 2023. "Individuals' and households' climate adaptation and mitigation behaviors: A systematic review," China Economic Review, Elsevier, vol. 77(C).
    4. Zhongjun Tang & Huike Zhu, 2020. "Nonlinear Dynamic Analysis of New Product Diffusion considering Consumer Heterogeneity," Complexity, Hindawi, vol. 2020, pages 1-20, September.
    5. Zhang, Tong & Burke, Paul J. & Wang, Qi, 2024. "Effectiveness of electric vehicle subsidies in China: A three-dimensional panel study," Resource and Energy Economics, Elsevier, vol. 76(C).
    6. Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
    7. Martin Rixen & Jürgen Weigand, 2013. "Agent-Based Simulation Of Consumer Demand For Smart Metering Tariffs," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 10(05), pages 1-26.
    8. Aral, Sinan & Muchnik, Lev & Sundararajan, Arun, 2013. "Engineering social contagions: Optimal network seeding in the presence of homophily," Network Science, Cambridge University Press, vol. 1(2), pages 125-153, August.
    9. Li, Ying & Wen, Ting, 2024. "Psychological mechanism of forest-based wellness tourism decision-making during the prevention and control of COVID-19," Forest Policy and Economics, Elsevier, vol. 160(C).
    10. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    11. Fan, Ruguo & Bao, Xuguang & Du, Kang & Wang, Yuanyuan & Wang, Yitong, 2022. "The effect of government policies and consumer green preferences on the R&D diffusion of new energy vehicles: A perspective of complex network games," Energy, Elsevier, vol. 254(PA).
    12. Julia Wenger & Georg Jäger & Annukka Näyhä & Simon Plakolb & Paul Erich Krassnitzer & Tobias Stern, 2024. "Exploring potential diffusion pathways of biorefinery innovations—An agent‐based simulation approach for facilitating shared value creation," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4652-4693, July.
    13. Zhang, Tianyu & Dong, Peiwu & Zeng, Yongchao & Ju, Yanbing, 2022. "Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model," Journal of Business Research, Elsevier, vol. 139(C), pages 90-105.
    14. Hu, Xianfeng & Wang, Shanyong & Zhou, Rongting & Gao, Lan & Zhu, Zujun, 2023. "Policy driven or consumer trait driven? Unpacking the EVs purchase intention of consumers from the policy and consumer trait perspective," Energy Policy, Elsevier, vol. 177(C).
    15. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    16. Qiao Liu & Qiaowei Shen & Zhenghua Li & Shu Chen, 2021. "Stimulating Consumption at Low Budget: Evidence from a Large-Scale Policy Experiment Amid the COVID-19 Pandemic," Management Science, INFORMS, vol. 67(12), pages 7291-7307, December.
    17. García-Maroto, I. & García-Maraver, A. & Muñoz-Leiva, F. & Zamorano, M., 2015. "Consumer knowledge, information sources used and predisposition towards the adoption of wood pellets in domestic heating systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 207-215.
    18. Li Wang & Myagmarsuren Damdinsuren & Yuanhao Qin & Ganzorig Gonchigsumlaa & Yadmaa Zandan & Zilin Zhang, 2024. "Forest Wellness Tourism Development Strategies Using SWOT, QSPM, and AHP: A Case Study of Chongqing Tea Mountain and Bamboo Forest in China," Sustainability, MDPI, vol. 16(9), pages 1-25, April.
    19. Diaz-Rainey, Ivan & Ashton, John K., 2015. "Investment inefficiency and the adoption of eco-innovations: The case of household energy efficiency technologies," Energy Policy, Elsevier, vol. 82(C), pages 105-117.
    20. Nejad, Mohammad G. & Amini, Mehdi, 2024. "Designing profitable seeding Programs: The effects of social network properties and consumer homophily," Journal of Business Research, Elsevier, vol. 173(C).
    21. Ayako Ebata & Mauricio Espinoza & Giel Ton, 2025. "Food safety certification in urban food markets: the willingness to pay for safer meat in Peru," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 17(2), pages 461-476, April.
    22. Silvia, Chris & Krause, Rachel M., 2016. "Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: An agent-based model," Energy Policy, Elsevier, vol. 96(C), pages 105-118.
    23. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mousavi, Ebrahim & Zare, Hassan & Moula, Ahmad, 2025. "A Novel Hybrid Lexicon and Economic Optimized kNN Framework for Sentiment Analysis in Tourism Platforms," MPRA Paper 127063, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    2. Jie Gu & Yunjie Xu, 2022. "Battle of positioning: exploring the role of bridges in competitive diffusion," Journal of Computational Social Science, Springer, vol. 5(1), pages 319-350, May.
    3. Xiao, Yu & Liu, Liangliang, 2024. "How does information competition affect new product diffusion? Insights from computational experiments," Journal of Business Research, Elsevier, vol. 183(C).
    4. Ganglmair-Wooliscroft, Alexandra & Wooliscroft, Ben, 2022. "An investigation of sustainable consumption behavior systems – Exploring personal and socio-structural characteristics in different national contexts," Journal of Business Research, Elsevier, vol. 148(C), pages 161-173.
    5. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    6. Wang, Zhuowei & Yu, Jiangbo (Gabe) & Chen, Anthony & Fu, Xiaowen, 2024. "Subsidy policies towards zero-emission bus fleets: A systematic technical-economic analysis," Transport Policy, Elsevier, vol. 150(C), pages 1-13.
    7. Bernd Frick & Franziska Prockl, 2018. "Information Precision In Online Communities: Player Valuations On Www.Transfermarkt.De," Working Papers Dissertations 37, Paderborn University, Faculty of Business Administration and Economics.
    8. Najmeh Madadi & Azanizawati Ma’aram & Kuan Yew Wong, 2017. "A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1300992-130, January.
    9. Mike W. Peng, 2019. "Global competition and diffusion of the “A” list," Frontiers of Business Research in China, Springer, vol. 13(1), pages 1-23, December.
    10. Lefeng, Shi & Shengnan, Lv & Chunxiu, Liu & Yue, Zhou & Cipcigan, Liana & Acker, Thomas L., 2020. "A framework for electric vehicle power supply chain development," Utilities Policy, Elsevier, vol. 64(C).
    11. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    12. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    13. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    14. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    15. Yogesh V. Joshi & David J. Reibstein & Z. John Zhang, 2009. "Optimal Entry Timing in Markets with Social Influence," Management Science, INFORMS, vol. 55(6), pages 926-939, June.
    16. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    17. Rodrigues, João L. & Bolognesi, Hugo M. & Melo, Joel D. & Heymann, Fabian & Soares, F.J., 2019. "Spatiotemporal model for estimating electric vehicles adopters," Energy, Elsevier, vol. 183(C), pages 788-802.
    18. Guo, Xuezhen, 2014. "A novel Bass-type model for product life cycle quantification using aggregate market data," International Journal of Production Economics, Elsevier, vol. 158(C), pages 208-216.
    19. Rachel Lacroix & Anna Timonina-Farkas & Ralf W. Seifert, 2023. "Utilizing additive manufacturing and mass customization under capacity constraints," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 281-301, January.
    20. Zhongya Han & Dongyuan Zhao & Fengxia Sun & Huike Zhu, 2025. "A study on the diffusion model of new energy passenger vehicles with consideration of product value," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-25, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:forpol:v:174:y:2025:i:c:s1389934125000759. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/forpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.