IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3121-d1372580.html
   My bibliography  Save this article

Abolishing Single-Use Plastic Water Bottles in Dubai Hotels as a Voluntary Act—Scenarios and Environmental Impacts

Author

Listed:
  • Sameh Al-Shihabi

    (Industrial Engineering and Engineering Management Department, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Ridvan Aydin

    (Industrial Engineering and Engineering Management Department, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Zehra Canan Araci

    (Industrial Engineering and Engineering Management Department, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Fikri Dweiri

    (Industrial Engineering and Engineering Management Department, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Mohammed Obeidat

    (Department of Industrial Engineering, Faculty of Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan)

  • Mohammad Fayez Al Bataineh

    (Electrical and Communication Engineering Department, College of Engineering, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
    Telecommunications Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan)

Abstract

Dubai, a popular vacation spot, has launched an initiative to reduce reliance on single-use plastic water bottles. Tourists in Dubai widely utilize PET (Polyethylene Terephthalate) water bottles, and significant quantities of greenhouse gases (GHG) are released during the production and disposal of PET bottles. In response to Dubai’s initiative, some hotels eliminated PET bottles and substituted them with environmentally favorable alternatives. These hotels are considered adopters of the initiative, while other hotels that might follow are imitators. Thus, innovation diffusion theory (IDT) is used in this work to forecast the transition of hotels to non-PET bottles. The diffusion of this new behavior is simulated using a system dynamic (SD) model, where factors pushing imitators to abolish PET bottles are found using the Delphi method and hotel surveying. Moreover, the importance of each identified factor is found using an analytical hierarchical process (AHP). Since hotels are divided into several categories based on their service quality, the analysis shows that hotels are affected by other hotels in their category or better categories. Using this conceptual understanding, Bass and generalized Bass modeling are used in the SD model to study how imitating hotels will follow the adopters. Best-, average-, and worst-case scenarios are studied to help decision-makers understand what to expect in the future. For the best- and average-case scenarios, the SD simulation shows that all hotels will potentially have abolished PET bottles in 25 years. However, only 16% of hotels will have cancelled PET bottles in 25 years if the worst-case scenario occurs; thus, decision-makers need to intervene to expedite the process.

Suggested Citation

  • Sameh Al-Shihabi & Ridvan Aydin & Zehra Canan Araci & Fikri Dweiri & Mohammed Obeidat & Mohammad Fayez Al Bataineh, 2024. "Abolishing Single-Use Plastic Water Bottles in Dubai Hotels as a Voluntary Act—Scenarios and Environmental Impacts," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3121-:d:1372580
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3121/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/8/3121/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arun Vishwanath, 2005. "Impact of personality on technology adoption: An empirical model," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(8), pages 803-811, June.
    2. Saimin Huang & Hongchang Wang & Waqas Ahmad & Ayaz Ahmad & Nikolai Ivanovich Vatin & Abdeliazim Mustafa Mohamed & Ahmed Farouk Deifalla & Imran Mehmood, 2022. "Plastic Waste Management Strategies and Their Environmental Aspects: A Scientometric Analysis and Comprehensive Review," IJERPH, MDPI, vol. 19(8), pages 1-31, April.
    3. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    4. Roehrich, Gilles, 2004. "Consumer innovativeness: Concepts and measurements," Journal of Business Research, Elsevier, vol. 57(6), pages 671-677, June.
    5. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    6. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    7. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    8. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    9. John Yeung & Albert Chan & Daniel Chan & Leong Kwan Li, 2007. "Development of a partnering performance index (PPI) for construction projects in Hong Kong: a Delphi study," Construction Management and Economics, Taylor & Francis Journals, vol. 25(12), pages 1219-1237.
    10. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
    11. Kang, DongHo & Auras, Rafael & Singh, Jay, 2017. "Life cycle assessment of non-alcoholic single-serve polyethylene terephthalate beverage bottles in the state of California," Resources, Conservation & Recycling, Elsevier, vol. 116(C), pages 45-52.
    12. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    13. Sameh Al-Shihabi & Mahmoud Barghash, 2023. "A System Dynamic Model for Polyethylene Terephthalate Supply Chain in the United Arab Emirates—Status, Projections, and Environmental Impacts," Sustainability, MDPI, vol. 15(17), pages 1-14, August.
    14. Dhirasasna, NiNa & Sahin, Oz, 2021. "A system dynamics model for renewable energy technology adoption of the hotel sector," Renewable Energy, Elsevier, vol. 163(C), pages 1994-2007.
    Full references (including those not matched with items on IDEAS)

    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. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    3. Claudia Furlan & Cinzia Mortarino & Mohammad Salim Zahangir, 2021. "Interaction among three substitute products: an extended innovation diffusion model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 269-293, March.
    4. 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.
    5. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    6. Kaldasch, Joachim, 2011. "Evolutionary model of an anonymous consumer durable market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(14), pages 2692-2715.
    7. Park, Sang Yong & Kim, Jong Wook & Lee, Duk Hee, 2011. "Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects," Energy Policy, Elsevier, vol. 39(6), pages 3307-3315, June.
    8. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    9. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    10. Guseo, Renato & Guidolin, Mariangela, 2015. "Heterogeneity in diffusion of innovations modelling: A few fundamental types," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 514-524.
    11. Dhirasasna, NiNa & Sahin, Oz, 2021. "A system dynamics model for renewable energy technology adoption of the hotel sector," Renewable Energy, Elsevier, vol. 163(C), pages 1994-2007.
    12. Karakaya, Emrah, 2016. "Finite Element Method for forecasting the diffusion of photovoltaic systems: Why and how?," Applied Energy, Elsevier, vol. 163(C), pages 464-475.
    13. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    14. Shi, Xiaohui & Li, Feng & Bigdeli, Ali Ziaee, 2016. "An examination of NPD models in the context of business models," Journal of Business Research, Elsevier, vol. 69(7), pages 2541-2550.
    15. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
    16. Chien, Chen-Fu & Chen, Yun-Ju & Peng, Jin-Tang, 2010. "Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle," International Journal of Production Economics, Elsevier, vol. 128(2), pages 496-509, December.
    17. Renato Guseo & Mariangela Guidolin, 2008. "Cellular automata and Riccati equation models for diffusion of innovations," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 291-308, July.
    18. Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
    19. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    20. Fernández-Durán, J.J., 2014. "Modeling seasonal effects in the Bass Forecasting Diffusion Model," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 251-264.

    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:gam:jsusta:v:16:y:2024:i:8:p:3121-:d:1372580. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.