IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11578-d660435.html
   My bibliography  Save this article

How Is the Sustainable Consumption Intention Model in Food Industry under Preference Uncertainties? The Consumer Willingness to Pay on Recycled Packaging Material

Author

Listed:
  • Chih-Cheng Chen

    (Department of Business Administration, Mingdao University, Pitou Township 523, Taiwan)

  • Raditia Yudistira Sujanto

    (Department of Business Administration, Asia University, Taichung City 413, Taiwan
    Department of Communication, Universitas Aisyiyah Yogyakarta, Yogyakarta 55592, Indonesia)

  • Ming-Lang Tseng

    (Institute of Innovation and Circular Economy, Asia University, Taichung City 413, Taiwan
    Department of Medical Research, China Medical University Hospital, China Medical University, Taichung City 413, Taiwan)

  • Anthony S. F. Chiu

    (Department of Industrial Engineering, De La Salle University, Manila 1004, Philippines)

  • Ming K. Lim

    (College of Mechanical Engineering, Chongqing University, Chongqing 400044, China
    Faculty Research Centre for Business in Society, Coventry University, Coventry CV1 5FB, UK)

Abstract

Food packaging is costly to consumers and generates a huge volume of packaging waste, especially in Indonesia. Prior studies have neglected to construct a causal sustainable consumption intention model in food industry and link to the consumer willingness to pay under preference uncertainties. To address the gaps, this study explores consumer attributes to build a causal sustainable consumption intention model and takes the model to address the consumer willingness to pay under preference uncertainties. This study proposes a causal model that integrates five aspects of sustainable consumption intention model: (1) sustainable consumption knowledge, attitudes, and behaviors; (2) government policy and regulation on sustainable consumption; (3) recycled packaging eco-labeling certification; (4) supply chain innovation and infrastructure; and (5) sustainable product purchasing features. This study uses the fuzzy Delphi method to confirm the reliability and validate the criteria and applies cause and effect model to address the causal model. In addition, this study collects 428 valid responses to address the willingness to pay for causal sustainable consumption intention model and a cognitive best-worst choice experiment to confirm the model in the food industry. The result reveals that recycled packaging eco-labeling certification is the major aspect for enhancing the model, followed by government policy and regulation and supply chain innovation and infrastructure. In practice, consumers incur inconvenience in purchasing sustainable food products but prefer recycled packaging material at a standardized price.

Suggested Citation

  • Chih-Cheng Chen & Raditia Yudistira Sujanto & Ming-Lang Tseng & Anthony S. F. Chiu & Ming K. Lim, 2021. "How Is the Sustainable Consumption Intention Model in Food Industry under Preference Uncertainties? The Consumer Willingness to Pay on Recycled Packaging Material," Sustainability, MDPI, vol. 13(21), pages 1-22, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11578-:d:660435
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11578/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/21/11578/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chiou‐Fong Wei & Chang‐Tang Chiang & Tun‐Chih Kou & Bruce C Y Lee, 2017. "Toward Sustainable Livelihoods: Investigating the Drivers of Purchase Behavior for Green Products," Business Strategy and the Environment, Wiley Blackwell, vol. 26(5), pages 626-639, July.
    2. Yang, Yang & Hobbs, Jill E. & Natcher, David C., 2020. "Assessing consumer willingness to pay for Arctic food products," Food Policy, Elsevier, vol. 92(C).
    3. Davis-Sramek, Beth & Robinson, Jessica L. & Darby, Jessica L. & Thomas, Rodney W., 2020. "Exploring the differential roles of environmental and social sustainability in carrier selection decisions," International Journal of Production Economics, Elsevier, vol. 227(C).
    4. Aysun Kahraman & İpek Kazançoğlu, 2019. "Understanding consumers' purchase intentions toward natural‐claimed products: A qualitative research in personal care products," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 1218-1233, September.
    5. Silvia Coderoni & Maria Angela Perito, 2020. "Sustainable consumption in the circular economy. An analysis of consumers’ purchase intentions for waste-to-value food," Post-Print hal-03385002, HAL.
    6. Reynolds, Christian & Goucher, Liam & Quested, Tom & Bromley, Sarah & Gillick, Sam & Wells, Victoria K. & Evans, David & Koh, Lenny & Carlsson Kanyama, Annika & Katzeff, Cecilia & Svenfelt, Åsa & Jack, 2019. "Review: Consumption-stage food waste reduction interventions – What works and how to design better interventions," Food Policy, Elsevier, vol. 83(C), pages 7-27.
    7. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    8. Juutinen, Artti & Mitani, Yohei & Mäntymaa, Erkki & Shoji, Yasushi & Siikamäki, Pirkko & Svento, Rauli, 2011. "Combining ecological and recreational aspects in national park management: A choice experiment application," Ecological Economics, Elsevier, vol. 70(6), pages 1231-1239, April.
    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. Mostaghel, Rana & Chirumalla, Koteshwar, 2021. "Role of customers in circular business models," Journal of Business Research, Elsevier, vol. 127(C), pages 35-44.
    2. Han-Shen Chen, 2020. "The Construction and Validation of a Sustainable Tourism Development Evaluation Model," IJERPH, MDPI, vol. 17(19), pages 1-20, October.
    3. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    4. Junnan Wu & Xin Liu & Dianqi Pan & Yichen Zhang & Jiquan Zhang & Kai Ke, 2023. "Research on Safety Evaluation of Municipal Sewage Treatment Plant Based on Improved Best-Worst Method and Fuzzy Comprehensive Method," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    5. Rambabu Lavuri & Abhinav Jindal & Umair Akram & Bhukya Koteswara Rao Naik & Alrence Santiago Halibas, 2023. "Exploring the antecedents of sustainable consumers' purchase intentions: Evidence from emerging countries," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(1), pages 280-291, February.
    6. Han-Shen Chen & Chu-Wei Chen, 2019. "Economic Valuation of Green Island, Taiwan: A Choice Experiment Method," Sustainability, MDPI, vol. 11(2), pages 1-17, January.
    7. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    8. Qi, Danyi & Li, Ran & Penn, Jerrod & Houghtaling, Bailey & Prinyawiwatkul, Witoon & Roe, Brian E., 2021. "Does Nudging More Vegetable Consumption Result in More Waste? Evidence from a Randomized Dining Experiment," 2021 Annual Meeting, August 1-3, Austin, Texas 313980, Agricultural and Applied Economics Association.
    9. Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1778-1798, October.
    10. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    11. Yuanxin Liu & FengYun Li & Yi Wang & Xinhua Yu & Jiahai Yuan & Yuwei Wang, 2018. "Assessing the Environmental Impact Caused by Power Grid Projects in High Altitude Areas Based on BWM and Vague Sets Techniques," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    12. Ximing Chen & Jie Shang & Muhammad Zada & Shagufta Zada & Xueqiang Ji & Heesup Han & Antonio Ariza-Montes & Jesús Ramírez-Sobrino, 2021. "Health Is Wealth: Study on Consumer Preferences and the Willingness to Pay for Ecological Agricultural Product Traceability Technology: Evidence from Jiangxi Province China," IJERPH, MDPI, vol. 18(22), pages 1-13, November.
    13. Chen Liu & Trung Thang Nguyen, 2020. "Evaluation of Household Food Waste Generation in Hanoi and Policy Implications towards SDGs Target 12.3," Sustainability, MDPI, vol. 12(16), pages 1-20, August.
    14. Ravindra Singh Saluja & Varinder Singh, 2023. "Attribute-based characterization, coding, and selection of joining processes using a novel MADM approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 616-655, June.
    15. Jaiswal, Deepak & Kant, Rishi, 2018. "Green purchasing behaviour: A conceptual framework and empirical investigation of Indian consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 60-69.
    16. Yu Hao & Yingting Wang & Qiuwei Wu & Shiwei Sun & Weilu Wang & Menglin Cui, 2020. "What affects residents' participation in the circular economy for sustainable development? Evidence from China," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(5), pages 1251-1268, September.
    17. Ghadimi, Pezhman & Donnelly, Oisin & Sar, Kubra & Wang, Chao & Azadnia, Amir Hossein, 2022. "The successful implementation of industry 4.0 in manufacturing: An analysis and prioritization of risks in Irish industry," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    18. Guo, Mengzhuo & Zhang, Qingpeng & Liao, Xiuwu & Chen, Frank Youhua & Zeng, Daniel Dajun, 2021. "A hybrid machine learning framework for analyzing human decision-making through learning preferences," Omega, Elsevier, vol. 101(C).
    19. Lingfei Wang & Yuqin Yang & Guoyan Wang, 2022. "The Clean Your Plate Campaign: Resisting Table Food Waste in an Unstable World," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    20. Junli Zhang & Guoteng Wang & Zheng Xu & Zheren Zhang, 2022. "A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids," Energies, MDPI, vol. 15(12), pages 1-20, June.

    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:13:y:2021:i:21:p:11578-:d:660435. 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.