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First published online March 23, 2026

How to encourage the public to actively practice green and low-carbon consumption? The interaction between individual psychology and urban situational factors

Abstract

Most studies explaining green and low-carbon consumption behavior mainly focus on a single influence at the individual psychological level, while ignoring the multilevel interaction between macro situational factors and individual factors in nested cities. Therefore, based on large-scale survey data and national statistical data from 35 cities in China, this article integrates individual-level psychological factors with urban-level background factors, employs a multilevel structural equation model (MSEM) to investigate the key influencing factors and mechanisms of individual green and low-carbon consumption behavior. It examines consumption behavior with four different characteristics: green food consumption, green low-carbon travel, green energy consumption, and green living. The results indicate that at the individual level, consumer perceived value and perceived behavioral control actively promote four types of green and low-carbon consumption practices, with conditional value having the most extensive promotion effect. At the urban level, environmental pollution, economic development, and social development can all encourage low-carbon consumption behavior. Moreover, the level of social development positively moderates the relationship between environmental pollution perception and green consumption intention. The level of environmental pollution positively moderates the relationship between environmental attitudes and green low-carbon travel. However, the level of economic development suppresses the promotion effect of environmental pollution perception on environmental attitudes. Therefore, in the formulation of environmental policies, full consideration should be given to the development status of each region. To strengthen regional infrastructure and improve the incentive system for green and low-carbon markets, it is essential to utilize information dissemination channels flexibly.

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Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

1. Vollebregt M, Mugge R, Thuerridl C, et al. Reducing without losing: reduced consumption and its implications for well-being. Sustain Prod Consum 2024; 45: 91–103.
2. Li C, Wang XM, Wang LP. Forecasting carbon emissions peak in Chinese household consumption and selecting low-carbon development strategies: a study based on the extended SPIRPAT model. Environ Prog Sustain Energy 2024a; 44(1): e14537.
3. Guo XG, Wang LF, Guo Y, et al. The impact of sustainable consumption behaviour on natural resource conservation in China: a cross-sectional analysis. Resourc Policy 2024; 89: 104610.
4. Wang LP, Chen LJ, Jin SC, et al. Forecasting the green behaviour level of Chinese enterprises: a conjoined application of the autoregressive integrated moving average (ARIMA) model and multi-scenario simulation. Technol Soc 2025a; 81: 102825.
5. Gazi MAI, Masud AA, Yusof MF, et al. The green mindset: how consumers’ attitudes, intentions, and concerns shape their purchase decisions. Environ Res Commun 2024; 6: 25009.
6. Chwialkowska A, Bhatti WA, Bujac A, et al. An interplay of the consumption values and green behavior in developed markets: a sustainable development viewpoint. Sustain Dev 2024; 32(4): 3771–3785.
7. Wang LP, Chen LJ, Li C. Research on strategies for improving green product consumption sentiment from the perspective of big data. J Retail Consum Serv 2024a; 79: 103802.
8. Menebo MM, Kvale HEH, Bajracharya M, et al. Social exclusion and green consumption: the multi-motive theory approach. Sustain Dev 2023; 31: 3857–3868.
9. Yang MH, Chen H, Long RY, et al. How does government regulation shape residents’ green consumption behavior? A multi-agent simulation considering environmental values and social interaction. J Environ Manag 2023; 331: 117231.
10. Wei HF, Li Z, Chudhery MAZ, et al. How does consumers’ face consciousness influence green self-efficacy and consumption behavior, and how does electronic and social media persuasion moderate these relationships? Comput Human Behav 2024; 153: 108091.
11. Wang LP, Gao PP, Li C. Public response to heterogeneous environmental policies: scenario-based experiments from interest appeal, implementation costs, and commitment mechanism. Energy Sourc B Econ Plann Policy 2024b; 19(1): 2304905.
12. Chen LJ, Zhang JL, You Y. Air pollution, environmental perceptions, and citizen satisfaction: a mediation analysis. Environ Res 2020; 184: 109287.
13. Li C, Wang XM, Wang LP. Interplay of virtual and physical channels in propagating green behavior: a study integrating motivation–opportunity–ability and theory of planned behavior. Environ Dev 2024b; 50: 100997.
14. Golob U, Podnar K, Weder F. Reimagining the sustainable consumer: why social representations of sustainable consumption matter. Bus Ethics Environ Responsibil 2024; 33(4): 847–859.
15. Rozenkowska K. Theory of planned behavior in consumer behavior research: a systematic literature review. Int J Consum Stud 2023; 47: 2670–2700.
16. Wang L, Zhang Q, Wong PPW. Purchase intention for green cars among Chinese millennials: merging the value–attitude–behavior theory and theory of planned behavior. Front Psychol 2022; 13: 786292.
17. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process 1991; 50: 179–211.
18. Shen J, Liang HY, Zafar AU, et al. Influence by osmosis: social media green communities and pro-environmental behavior. Comput Human Behav 2023; 143: 107706.
19. Li C, Wang XM, Wang LP. Examining the crucial societal incentive approaches and their impact mechanisms to enhance the purchase intention of carbon-labeled products: a conjoined application of PLS-SEM and NCA methodologies. Energy Environ 2024c; 37(2): 877–924.
20. Zhang YX, Tao WW. Will energy efficiency affect appliance price? An empirical analysis of refrigerators in China based on hedonic price model. Energy Policy 2020; 147: 11818.
21. Sheth JN, Newman BI, Gross BL. Why we buy what we buy: a theory of consumption values. J Bus Res 1991; 22: 159–170.
22. Song ML, Xie QJ, Wang SH, et al. Could environmental regulation and R&D tax incentives affect green product innovation? J Cleaner Prod 2020; 258: 120849.
23. Rahman I, Nanu L, Sozen E. The adoption of environmental practices in craft breweries: the role of owner-managers’ consumption values, motivation, and perceived business challenges. J Cleaner Prod 2023; 416: 137948.
24. Li C, Wang YL, Wang LP. Guided by the goal of “double carbon”, what is the carbon emission reduction effect of the promotion and application of green technology in China? Environ Res 2024d; 245: 117974.
25. Chwialkowska A. Money and status or clear conscience and clean air: should we vary the marketing interventions depending on tourist's cultural background? J Travel Tourism Market 2021; 38: 75–92.
26. Bennett R, Vijaygopal R. Consumer attitudes towards electric vehicles: effects of product user stereotypes and self-image congruence. Eur J Mark 2018; 52: 499–527.
27. Joshi Y, Uniyal DP, Sangroya D. Investigating consumers’ green purchase intention: examining the role of economic value, emotional value and perceived marketplace influence. J Cleaner Prod 2021; 328: 129638.
28. Garrouch K, Ghali Z. On linking the perceived values of mobile shopping apps, customer well-being, and customer citizenship behavior: moderating role of customer intimacy. J Retail Consum Serv 2023; 74: 103396.
29. Khan SN, Mohsin M. The power of emotional value: exploring the effects of values on green product consumer choice behavior. J Cleaner Prod 2017; 150: 65–74.
30. Ng PML, Cheung CTY, Lit KK, et al. Green consumption and sustainable development: the effects of perceived values and motivation types on green purchase intention. Bus Strategy Environ 2024; 33: 1024–1039.
31. Kashif U, Hong C, Naseem S, et al. Assessment of millennial organic food consumption and moderating role of food neophobia in Pakistan. Curr Psychol 2023; 42: 1504–1515.
32. Garlet TB, de Medeiros JF, Ribeiro JLD, et al. Understanding ethical products: definitions and attributes to consider throughout the product lifecycle. Sustain Prod Consum 2024; 45: 228–243.
33. Jia YJ, Cheng SJ, Shi R. Decision-making behavior of rural residents’ domestic waste classification in northwestern of China: analysis based on environmental responsibility and pollution perception. J Cleaner Prod 2021; 326: 129374.
34. Tan XR, Han LJ, Zhang XY, et al. A review of current air quality indexes and improvements under the multi-contaminant air pollution exposure. J Environ Manag 2021; 279: 111681.
35. Majer JM, Henscher HA, Reuber P, et al. The effects of visual sustainability labels on consumer perception and behavior: a systematic review of the empirical literature. Sustain Prod Consum 2022; 33: 1–14.
36. Wong EYC, Chan FFY, So S. Consumer perceptions on product carbon footprints and carbon labels of beverage merchandise in Hong Kong. J Cleaner Prod 2020; 242: 118404.
37. Grymshi D, Crespo-Cebada E, Elghannam A, et al. Understanding consumer attitudes towards ecolabeled food products: a latent class analysis regarding their purchasing motivations. Agribusiness 2021; 38: 93–107.
38. Li S, Wang JW. Pilot policies for low-carbon cities, low-carbon literacy of residents, and green technology innovation in enterprises. Chin Popul Resour Environ 2023; 33: 93–103. in Chinese.
39. Zhang JF, Qin YC, Zhang LJ, et al. The impact of built environment on residents’ green consumption intention: an empirical study from Zhengzhou. Geograph Res 2021; 40: 2914–2929.
40. Wang LP, Chen LJ, Wang ZJ, et al. Exploring strategies for promoting green technology innovation in enterprises from the perspective of inter-enterprise interaction and enterprise behavioral preferences. Renew Energy 2025b; 250: 123287.
41. Wu H, Xue Y, Hao Y, et al. How does Internet development affect energy-saving and emission reduction? Evidence from China. Energy Econ 2021; 103: 105577.
42. Long RY, Wang JQ, Chen H, et al. Applying multilevel structural equation modeling to energy-saving behavior: the interaction of individual- and city-level factors. Energy Policy 2023; 174: 113423.
43. Qiao S, Yao T, Wang N, et al. “Externally observing” and “internally reflecting”: a study on green consumption intention caused by environmental threats: a dual path model based on moral emotions. Nankai Bus Rev 2024; 27: 137–149. in Chinese.
44. Sun YH, Liu NN, Zhao MZ. Factors and mechanisms affecting green consumption in China: a multilevel analysis. J Cleaner Prod 2019; 209: 481–493.
45. Zhou ZF, Liu JH, Zeng HX, et al. How does soil pollution risk perception affect farmers’ pro-environmental behavior? The role of income level. J Environ Manag 2020; 270: 110806.
46. Tonder EV, Fullerton S, Beer LTD. Cognitive and emotional factors contributing to green customer citizenship behaviours: a moderated mediation model. J Consum Market 2020; 37(6): 639–650.
47. Park HJ, Lin LM. Exploring attitude–behavior gap in sustainable consumption: comparison of recycled and upcycled fashion products. J Bus Res 2020; 117: 623–628.
48. Ru XJ, Wang SY, Yan S. Exploring the effects of normative factors and perceived behavioral control on individual’ s energy-saving intention: an empirical study in eastern China. Resour Conserv Recycl 2018; 134: 91–99.
49. Rausch TM, Kopplin CS. Bridge the gap: consumers’ purchase intention and behavior regarding sustainable clothing. J Cleaner Prod 2021; 278: 123882.
50. Nekmahmud M, Feketefarkas M. Why not green marketing? Determinates of consumers intention to green purchase decision in a new developing nation. Sustainability 2020; 12: 7880.
51. Akhtar R, Sultana S, Masud MM, et al. Consumers’ environmental ethics, willingness, and green consumerism between lower and higher income groups. Resour Conserv Recycl 2021; 168: 105274.
52. Lin HM, Wu JY, Liang JC, et al. A review of using multilevel modeling in e-learning research. Comput Educ 2023; 198: 104762.
53. Preacher KJ, Zhang Z, Zyphur MJ. Multilevel structural equation models for assessing moderation within and across levels of analysis. Psychol Methods 2016; 21: 189–205.
54. Fang J, Wen ZL, Wu Y. Multi-layer regulation effect based on structural equation modeling. Adv Psychol Sci 2018; 26: 781–788.
55. Xing YF, Li MQ, Liao YH. Trust, identity, and public-sphere pro-environmental behavior in China: An extended attitude–behavior–context theory. Front Psychol 2022; 13: 919578.
56. Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci 2015; 43(1): 115–135.
57. Vaithilingam S, Ong CS, Moisescu OI, et al. Robustness checks in PLS-SEM: a review of recent practices and recommendations for future applications in business research. J Bus Res 2024; 173: 114465.
58. Zhang GX, Shen L, Su B. Temperature change and daily urban–rural residential electricity consumption in northwestern China: responsiveness and inequality. Energy Econ 2023; 126: 106973.
59. Ruokamo E, Merilainen T, Karhinen S, et al. The effect of information nudges on energy saving: observations from a randomized field experiment in Finland. Energy Policy 2022; 161: 112731.
60. Saari UA, Damberg S, Froembling L, et al. Sustainable consumption behavior of Europeans: the influence of environmental knowledge and risk perception on environmental concern and behavioral intention. Ecol Econ 2021; 189: 107155.
61. Hair JF, Sarstedt M, Ringle CM. Rethinking some of the rethinking of partial least squares. Eur J Mark 2019; 53: 566–584.
62. Guenther P, Guenther M, Ringle CM, et al. Improving PLS-SEM use for business marketing research. Ind Mark Manag 2023; 111: 127–142.

Biographies

Chuang Li is a professor and doctoral supervisor of the School of Business Administration of Jimei University. He graduated from Shanghai Jiaotong University with a doctor's degree. At present, His research focuses on the resource and environmental management.
Xiaoman Wang, a master of Jimei University. Her area of research is the green and low-carbon consumption focusing on green marketing.
Liping Wang is a professor and doctoral supervisor of the Finance and Economics College of Jimei University. She graduated from Donghua University with a doctor's degree. At present, her research focuses on the green economy and enterprise green management.