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Residents’ Green Purchasing Intentions in a Developing-Country Context: Integrating PLS-SEM and MGA Methods

Author

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  • Bin Wang

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Jionghua Li

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Ao Sun

    (School of Geographical Science, Qinghai Normal University, Xining 810008, China)

  • Yongming Wang

    (College of Tourism, Hunan Normal University, Changsha 410081, China)

  • Dianting Wu

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

This paper aims to examine the determinants of green purchasing intentions among different resident groups in a developing-country context. We first expand the theory of planned behaviour (TPB) and build a theoretical model based on green purchasing intention, including attitude, perceived behavioural control, subjective norms, environmental concern, habit, and socio-demographic characteristics (i.e., age, gender, residential area, and educational level). Following this, we collect 552 questionnaires from residents in Tianjin Municipality, China. We use partial least squares structural equation modelling (PLS-SEM) to analyse the green purchasing intention of the population sample and then employ a multi-group analysis (MGA) to explore the group differences in residents’ green purchasing intention. The results show that green purchasing intention is significantly and positively influenced by attitude, perceived behavioural control, subjective norms, and environmental concern but not by habit. The relationship chain of environmental concern→subjective norms→purchasing intention is the strongest. The results of the MGA show that for residential-area groups, the relationships between attitudes, perceived behavioural control, and habits and purchasing intention differ significantly between the downtown group and the outside-the-city group. For the educational-level groups, the relationship between environmental concern and subjective norms differs significantly between the high-education group and the low-education group. Finally, these findings contribute to the literature on the TPB model on green purchasing intention and provide some suggestions for the local government and green marketers.

Suggested Citation

  • Bin Wang & Jionghua Li & Ao Sun & Yongming Wang & Dianting Wu, 2019. "Residents’ Green Purchasing Intentions in a Developing-Country Context: Integrating PLS-SEM and MGA Methods," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
  • Handle: RePEc:gam:jsusta:v:12:y:2019:i:1:p:30-:d:299477
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    2. Andreea Barbu & Ștefan-Alexandru Catană & Dana Corina Deselnicu & Lucian-Ionel Cioca & Alexandra Ioanid, 2022. "Factors Influencing Consumer Behavior toward Green Products: A Systematic Literature Review," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    3. Bin Wang & Qiuxia Zheng & Ao Sun & Jie Bao & Dianting Wu, 2021. "Spatio-Temporal Patterns of CO 2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM," Mathematics, MDPI, vol. 9(21), pages 1-24, October.
    4. Long Chen & Chenglu Yang & Peng Jing & Qifen Zha & Xingyue Wang & Weichao Wang, 2023. "Are they willing to switch from non-driving to driving? An exploratory study among Chinese older people," Transportation, Springer, vol. 50(4), pages 1125-1163, August.
    5. Yaprak Kurtsal & Davide Viaggi, 2020. "Exploring Collaboration and Consumer Behavior in Food Community Networks and Constraints Preventing Active Participation: The Case of Turkey," Sustainability, MDPI, vol. 12(8), pages 1-24, April.
    6. Shehawy, Yasser Moustafa, 2023. "In green consumption, why consumers do not walk their talk: A cross cultural examination from Saudi Arabia and UK," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    7. Zhiqin Zou & Arash Farnoosh & Tom Mcnamara, 2021. "Risk analysis in the management of a green supply chain," Post-Print hal-03181313, HAL.

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