Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value
Abstract
:1. Introduction
2. Theoretical Framework and Research Hypotheses
2.1. Perceived Value
2.2. Perceived Benefit
2.3. Perceived Risk
2.4. Environmental Concern
2.5. Social Trust
3. Research Method
3.1. Measurement Development
3.2. Data Collection
4. Data Analysis and Results
4.1. Measurement Model
4.2. Structural Model
4.3. Effect Analysis
5. Discussion and Implications
5.1. Discussion
5.2. Implications
5.2.1. Theoretical Implications
5.2.2. Practical Implications
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Geng, Y.; Ji, W.; Wang, Z.; Lin, B.; Zhu, Y. A review of operating performance in green buildings: Energy use, indoor environmental quality and occupant satisfaction. Energy Build. 2019, 183, 500–514. [Google Scholar] [CrossRef]
- Zuo, J.; Zhao, Z. Green building research–current status and future agenda: A review. Renew. Sustain. Energy Rev. 2014, 30, 271–281. [Google Scholar] [CrossRef]
- Li, Y.; Yang, L.; He, B.; Zhao, D. Green building in China: Needs great promotion. Sustain. Cities Soc. 2014, 11, 1–6. [Google Scholar] [CrossRef]
- Li, Q.; Long, R.; Chen, H. Differences and influencing factors for Chinese urban resident willingness to pay for green housings: Evidence from five first-tier cities in China. Appl. Energy 2018, 229, 299–313. [Google Scholar] [CrossRef]
- Hoffman, A.J.; Henn, R. Overcoming the social and psychological barriers to green building. Organ. Environ. 2008, 21, 390–419. [Google Scholar] [CrossRef] [Green Version]
- Darko, A.; Zhang, C.; Chan, A.P.C. Drivers for green building: A review of empirical studies. Habitat Int. 2017, 60, 34–49. [Google Scholar] [CrossRef]
- Olubunmi, O.A.; Xia, P.B.; Skitmore, M. Green building incentives: A review. Renew. Sustain. Energy Rev. 2016, 59, 1611–1621. [Google Scholar] [CrossRef] [Green Version]
- He, C.; Yu, S.; Han, Q.; de Vries, B. How to attract customers to buy green housing? Their heterogeneous willingness to pay for different attributes. J. Clean. Prod. 2019, 230, 709–719. [Google Scholar] [CrossRef]
- Zhang, L.; Wu, J.; Liu, H. Policies to enhance the drivers of green housing development in China. Energy Policy 2018, 121, 225–235. [Google Scholar] [CrossRef]
- Shi, Q.; Lai, X.; Xie, X.; Zuo, J. Assessment of green building policies–A fuzzy impact matrix approach. Renew. Sustain. Energy Rev. 2014, 36, 203–211. [Google Scholar] [CrossRef]
- Sang, P.; Yao, H.; Zhang, L.; Wang, S.; Wang, Y.; Liu, J. Influencing factors of consumers’ willingness to purchase green housing: A survey from Shandong Province, China. Environ. Dev. Sustain. 2020, 22, 4267–4287. [Google Scholar] [CrossRef]
- Martek, I.; Hosseini, M.R.; Shrestha, A.; Edwards, D.J.; Seaton, S.; Costin, G. End-user engagement: The missing link of sustainability transition for Australian residential buildings. J. Clean. Prod. 2019, 224, 697–708. [Google Scholar] [CrossRef]
- Chan, A.P.C.; Darko, A.; Olanipekun, A.O.; Ameyaw, E.E. Critical barriers to green building technologies adoption in developing countries: The case of Ghana. J. Clean. Prod. 2018, 172, 1067–1079. [Google Scholar] [CrossRef]
- Huang, N.; Bai, L.; Wang, H.; Du, Q.; Shao, L.; Li, J. Social network analysis of factors influencing green building development in China. Int. J. Environ. Res. Public Health 2018, 15, 2684. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, X.; Hu, W. Attention and sentiment of Chinese public toward green buildings based on Sina Weibo. Sustain. Cities Soc. 2018, 44, 550–558. [Google Scholar] [CrossRef]
- Liu, Y.; Hong, Z.; Zhu, J.; Yan, J.; Qi, J.; Liu, P. Promoting green residential buildings: Residents’ environmental attitude, subjective knowledge, and social trust matter. Energy Policy 2018, 112, 152–161. [Google Scholar] [CrossRef]
- Hu, H.; Geertman, S.; Hooimeijer, P. The willingness to pay for green apartments: The case of Nanjing, China. Urban Stud. 2014, 51, 3459–3478. [Google Scholar] [CrossRef]
- Chau, C.K.; Tse, M.S.; Chung, K.Y. A choice experiment to estimate the effect of green experience on preferences and willingness-to-pay for green building attributes. Build. Environ. 2010, 45, 2553–2561. [Google Scholar] [CrossRef]
- Golbazi, M.; Danaf, A.E.; Aktas, C.B. Willingness to pay for green buildings: A survey on students’ perception in higher education. Energy Build. 2020, 216, 109956. [Google Scholar] [CrossRef]
- Heinzle, S.L.; Boey Ying Yip, A.; Low Yu Xing, M. The influence of green building certification schemes on real estate investor behaviour: Evidence from Singapore. Urban Stud. 2012, 50, 1970–1987. [Google Scholar] [CrossRef]
- Khan, R.A.J.; Thaheem, M.J.; Ali, T.H. Are Pakistani homebuyers ready to adopt sustainable housing? An insight into their willingness to pay. Energy Policy 2020, 143, 111598. [Google Scholar] [CrossRef]
- Luo, W.; Kanzaki, M.; Matsushita, K. Promoting green buildings: Do Chinese consumers care about green building enhancements. Int. J. Consum. Stud. 2017, 41, 545–557. [Google Scholar] [CrossRef]
- Zhao, D.; He, B.; Johnson, C.; Mou, B. Social problems of green buildings: From the humanistic needs to social acceptance. Renew. Sustain. Energy Rev. 2015, 51, 1594–1609. [Google Scholar] [CrossRef]
- Martek, I.; Hosseini, M.R.; Shrestha, A.; Edwards, D.J.; Serdar, D. Barriers inhibiting the transition to sustainability within the Australian construction industry: An investigation of technical and social interactions. J. Clean. Prod. 2019, 211, 281–292. [Google Scholar] [CrossRef]
- He, Q.; Zhao, H.; Shen, L.; Dong, L.; Cheng, Y.; Xu, K. Factors Influencing residents’ intention toward green retrofitting of existing residential buildings. Sustainability 2019, 11, 4246. [Google Scholar] [CrossRef] [Green Version]
- Jia, J.J.; Wu, H.; Nie, H.; Fan, Y. Modeling the willingness to pay for energy efficient residence in urban residential sector in China. Energy Policy 2019, 135, 111003. [Google Scholar] [CrossRef]
- Judge, M.; Warren-Myers, G.; Paladino, A. Using the theory of planned behaviour to predict intentions to purchase sustainable housing. J. Clean. Prod. 2019, 215, 259–267. [Google Scholar] [CrossRef]
- Rajaie, M.; Hosseini, S.M.; Malekmohammadi, I. Proposing a socio-psychological model for adopting green building technologies: A case study from Iran. Sustain. Cities Soc. 2018, 45, 657–668. [Google Scholar] [CrossRef]
- Zahan, I.; Chuanmin, S.; Fayyaz, M.; Hafeez, M. Green purchase behavior towards green housing: An investigation of Bangladeshi consumers. Environ. Sci. Pollut. Res. 2020, 27, 38745–38757. [Google Scholar] [CrossRef] [PubMed]
- Zhang, L.; Chen, L.; Wu, Z.; Zhang, S.; Song, H. Investigating young consumers’ purchasing intention of green housing in China. Sustainability 2018, 10, 1044. [Google Scholar] [CrossRef] [Green Version]
- Woodruff, R.B. Customer value: The next source for competitive advantage. J. Acad. Mark. Sci. 1997, 25, 139–153. [Google Scholar] [CrossRef]
- Zeithaml, V.A. Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. J. Mark. 1988, 52, 2–22. [Google Scholar] [CrossRef]
- Kim, H.; Chan, H.C.; Gupta, S. Value-based adoption of mobile internet: An empirical investigation. Decis. Support Syst. 2007, 43, 111–126. [Google Scholar] [CrossRef]
- Liu, Y.; Sun, X.; Sun, T.; Shi, X.R.; Liu, J. Promoting green residential buildings by increasing homebuyers’ willingness to pay: Evidence from Sino-Singapore Tianjin Eco-city in China. J. Clean. Prod. 2019, 238, 117884. [Google Scholar] [CrossRef]
- Li, Q.; Long, R.; Chen, H.; Chen, F.; Cheng, X. Chinese urban resident willingness to pay for green housing based on double-entry mental accounting theory. Nat. Hazards 2019, 95, 129–153. [Google Scholar] [CrossRef]
- Zhang, Y.; Yuan, J.; Li, L.; Cheng, H. Proposing a value field model for predicting homebuyers’ purchasing behavior of green residential buildings: A case study in China. Sustainability 2019, 11, 6877. [Google Scholar] [CrossRef] [Green Version]
- Ofek, S.; Portnov, B.A. Differential effect of knowledge on stakeholders’ willingness to pay green building price premium: Implications for cleaner production. J. Clean. Prod. 2020, 251, 119575. [Google Scholar] [CrossRef]
- Tan, W.; Goh, Y. The role of psychological factors in influencing consumer purchase intention towards green residential building. Int. J. Hous. Mark. Anal. 2018, 11, 788–807. [Google Scholar] [CrossRef]
- Zhang, L.; Sun, C.; Liu, H.; Zheng, S. The role of public information in increasing homebuyers’ willingness-to-pay for green housing: Evidence from Beijing. Ecol. Econ. 2016, 129, 40–49. [Google Scholar] [CrossRef]
- Jiang, Y.; Kim, Y. Developing multi-dimensional green value: Extending social exchange theory to explore customers’ purchase intention in green hotels–evidence from Korea. Int. J. Contemp. Hosp. Manag. 2015, 27, 308–334. [Google Scholar] [CrossRef]
- He, X.; Zhan, W.; Hu, Y. Consumer purchase intention of electric vehicles in China: The roles of perception and personality. J. Clean. Prod. 2018, 204, 1060–1069. [Google Scholar] [CrossRef]
- Park, E.; Kwon, S.J. What motivations drive sustainable energy-saving behavior? An examination in South Korea. Renew. Sustain. Energy Rev. 2017, 79, 494–502. [Google Scholar] [CrossRef]
- Kim, M.; Jeesun, O.; Park, J.; Joo, C. Perceived value and adoption intention for electric vehicles in Korea: Moderating effects of environmental traits and government supports. Energy 2018, 159, 799–809. [Google Scholar] [CrossRef]
- Wang, Y.; Gu, J.; Wang, S.; Wang, J. Understanding consumers’ willingness to use ride-sharing services: The roles of perceived value and perceived risk. Transp. Res. Part C Emerg. Technol. 2019, 105, 504–519. [Google Scholar] [CrossRef]
- Babin, B.J.; Darden, W.R.; Griffin, M. Work and/or Fun: Measuring hedonic and utilitarian shopping value. J. Consum. Res. 1994, 20, 644–656. [Google Scholar] [CrossRef]
- Kim, J.T.; Todorovic, M.S. Towards sustainability index for healthy buildings-via intrinsic thermodynamics, green accounting and harmony. Energy Build. 2013, 62, 627–637. [Google Scholar] [CrossRef]
- Darko, A.; Chan, A.P.C.; Gyamfi, S.; Olanipekun, A.O.; He, B.; Yu, Y. Driving forces for green building technologies adoption in the construction industry: Ghanaian perspective. Build. Environ. 2017, 125, 206–215. [Google Scholar] [CrossRef]
- Liu, K.S.; Liao, Y.T.; Hsueh, S.L. Implementing smart green building architecture to residential project based on Kaohsiung, Taiwan. Appl. Ecol. Envrion. Res. 2017, 15, 159–171. [Google Scholar] [CrossRef]
- Sweeney, J.C.; Soutar, G.N. Consumer perceived value: The development of a multiple item scale. J. Retail. 2001, 77, 203–220. [Google Scholar] [CrossRef]
- Barbopoulos, I.; Johansson, L. The consumer motivation scale: Development of a multi-dimensional and context-sensitive measure of consumption goals. J. Bus. Res. 2017, 76, 118–126. [Google Scholar] [CrossRef] [Green Version]
- Hartmann, P.; Apaolaza-Ibáñez, V. Consumer attitude and purchase intention toward green energy brands: The roles of psychological benefits and environmental concern. J. Bus. Res. 2012, 65, 1254–1263. [Google Scholar] [CrossRef]
- Yue, T.; Liu, J.; Long, R.; Chen, H.; Li, Q.; Liu, H.; Gu, Y. Effects of perceived value on green consumption intention based on double-entry mental accounting: Taking energy-efficient appliance purchase as an example. Environ. Sci. Pollut. Res. 2021, 28, 7236–7248. [Google Scholar] [CrossRef]
- Song, X.; Lu, Y.; Shen, L.; Shi, X. Will China’s building sector participate in emission trading system? Insights from modelling an owner’s optimal carbon reduction strategies. Energy Policy 2018, 118, 232–244. [Google Scholar] [CrossRef]
- Zhang, Y.; Xiao, C.; Zhou, G. Willingness to pay a price premium for energy-saving appliances: Role of perceived value and energy efficiency labeling. J. Clean. Prod. 2020, 242, 118555. [Google Scholar] [CrossRef]
- Noppers, E.H.; Keizer, K.; Bolderdijk, J.W.; Steg, L. The adoption of sustainable innovations: Driven by symbolic and environmental motives. Glob. Environ. Chang. 2014, 25, 52–62. [Google Scholar] [CrossRef]
- Portnov, B.A.; Trop, T. Factors affecting homebuyers’ willingness to pay green building price premium: Evidence from a nationwide survey in Israel. Build. Environ. 2018, 137, 280–291. [Google Scholar] [CrossRef]
- Darko, A.; Chan, A.P.C.; Ameyaw, E.E.; He, B.; Olanipekun, A.O. Examining issues influencing green building technologies adoption: The United States green building experts’ perspectives. Energy Build. 2017, 144, 320–332. [Google Scholar] [CrossRef] [Green Version]
- Bamberg, S. How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. J. Environ. Psychol. 2003, 23, 21–32. [Google Scholar] [CrossRef]
- Newton, J.D.; Tsarenko, Y.; Ferraro, C.; Sands, S. Environmental concern and environmental purchase intentions: The mediating role of learning strategy. J. Bus. Res. 2015, 68, 1974–1981. [Google Scholar] [CrossRef]
- Fujii, S. Environmental concern, attitude toward frugality, and ease of behavior as determinants of pro-environmental behavior intentions. J. Environ. Psychol. 2006, 26, 262–268. [Google Scholar] [CrossRef]
- Untaru, E.; Ispas, A.; Candrea, A.N.; Luca, M.; Epuran, G. Predictors of individuals’ intention to conserve water in a lodging context: The application of an extended theory of reasoned action. Int. J. Hosp. Manag. 2016, 59, 50–59. [Google Scholar] [CrossRef]
- Goh, S.K.; Balaji, M.S. Linking green skepticism to green purchase behavior. J. Clean. Prod. 2016, 131, 629–638. [Google Scholar] [CrossRef]
- Xie, X.; Lu, Y.; Gou, Z. Green building pro-environment behaviors: Are green users also green buyers? Sustainability 2017, 9, 1703. [Google Scholar] [CrossRef] [Green Version]
- Policarpo, M.C.; Aguiar, E.C. How self-expressive benefits relate to buying a hybrid car as a green product. J. Clean. Prod. 2020, 252, 119859. [Google Scholar] [CrossRef]
- Rousseau, D.M.; Sitkin, S.B..; Burt, R.S.; Camerer, C. Not so different after all: A crossdiscipline view of trust. Acad. Manag. Rev. 1998, 23, 393–404. [Google Scholar] [CrossRef] [Green Version]
- Siegrist, M. The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk Anal. 2000, 20, 195–204. [Google Scholar] [CrossRef]
- Stern, P.C. What psychology knows about energy conservation. Am. Psychol. 1992, 47, 1224–1232. [Google Scholar] [CrossRef]
- Siegrist, M.; Cvetkovich, G. Perception of hazards: The role of social trust and knowledge. Risk Anal. 2002, 20, 713–720. [Google Scholar] [CrossRef] [PubMed]
- Park, E.; Ohm, J.Y. Factors influencing the public intention to use renewable energy technologies in South Korea: Effects of the Fukushima nuclear accident. Energy Policy 2014, 65, 198–211. [Google Scholar] [CrossRef]
- Van Dongen, D.; Claassen, L.; Smid, T.; Timmermans, D. People’s responses to risks of electromagnetic fields and trust in government policy: The role of perceived risk, benefits and control. J. Risk Res. 2014, 16, 945–957. [Google Scholar] [CrossRef]
- Yang, C.; Tu, J.; Jiang, Q. The influential factors of consumers’ sustainable consumption: A case on electric vehicles in China. Sustainability 2020, 12, 3496. [Google Scholar] [CrossRef] [Green Version]
- Chen, K.; Ren, C.; Gu, R.; Zhang, P. Exploring purchase intentions of new energy vehicles: From the perspective of frugality and the concept of “mianzi”. J. Clean. Prod. 2019, 230, 700–708. [Google Scholar] [CrossRef]
- Grewal, D.; Gotlieb, J.; Marmorstein, H. The moderating effects of message framing and source credibility on the price-perceived risk relationship. J. Consum. Res. 1994, 21, 145–153. [Google Scholar] [CrossRef]
- Featherman, M.S.; Pavlou, P.A. Predicting e-services adoption: A perceived risk facets perspective. Int. J. Hum. Comput. Stud. 2003, 59, 451–474. [Google Scholar] [CrossRef] [Green Version]
- Gao, Y.; Yang, G.; Xie, Q. Spatial-temporal evolution and driving factors of green building development in China. Sustainability 2020, 12, 2773. [Google Scholar] [CrossRef] [Green Version]
- Hair, J.F.; Sarstedt, M.; Pieper, T.M.; Ringle, C.M. The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Plan. 2012, 45, 320–340. [Google Scholar] [CrossRef]
- Hair, J.F.; Hair, J.F.; Sarstedt, M.; Sarstedt, M.; Ringle, C.M.; Ringle, C.M.; Mena, J.A.; Mena, J.A. An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Market. Sci. 2012, 40, 414–433. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
- Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis, 6th ed.; Pearson Prentice Hall: Upper Saddle River, NJ, USA, 2006. [Google Scholar]
- Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef]
- Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 1988. [Google Scholar]
- Dodds, W.; Monroe, K.; Grewal, D. Effects of price, brand, and store information on buyers’ product evaluations. J. Mark. Res. 1991, 28, 307–319. [Google Scholar]
- Wang, Y.; Li, Y.; Zhang, J.; Su, X. How impacting factors affect Chinese green purchasing behavior based on Fuzzy Cognitive Maps. J. Clean. Prod. 2019, 240, 118199. [Google Scholar] [CrossRef]
- Noppers, E.H.; Keizer, K.; Milovanovic, M.; Steg, L. The importance of instrumental, symbolic, and environmental attributes for the adoption of smart energy systems. Energy Policy 2016, 98, 12–18. [Google Scholar] [CrossRef] [Green Version]
- Xu, X.; Hua, Y.; Wang, S.; Xu, G. Determinants of consumer’s intention to purchase authentic green furniture. Resour. Conserv. Recycl. 2020, 156, 104721. [Google Scholar] [CrossRef]
- Borin, N.; Cerf, D.C.; Krishnan, R. Consumer effects of environmental impact in product labeling. J. Consum. Res. 2011, 28, 76–86. [Google Scholar] [CrossRef]
- Wang, S.; Wang, J.; Wang, Y.; Yan, J.; Li, J. Environmental knowledge and consumers’ intentions to visit green hotels: The mediating role of consumption values. J. Travel Tour. Mark. 2018, 35, 1261–1271. [Google Scholar] [CrossRef]
Construct | Item | Measurement |
---|---|---|
Purchase intention (PI) | PI1 | Compared with the traditional housings, I would prefer to GHs. |
PI2 | The next time I purchase a house, I would give priority to GHs. | |
PI3 | I would like to recommend friends to purchase GHs. | |
Perceived value (PV) | PV1 | Compared to the sacrifice that I need to make, GHs are worthwhile. |
PV2 | GHs are considered to be a good buy. | |
PV3 | Overall, GHs deliver me good value. | |
Perceived functional benefit (PFB) | PFB1 | GHs are conducive to improve the residents’ living comfort at home. |
PFB2 | GHs are beneficial to improve the residents’ health conditions. | |
PFB3 | GHs are useful to reduce household expenditures, such as water and electricity charges. | |
PFB4 | GHs are favorable to improve the residents’ quality of living. | |
Perceived emotional benefit (PEB) | PEB1 | Living in GHs would be enjoyable. |
PEB2 | Living in GHs would give me pleasure. | |
PEB3 | Living in GHs would make me feel relaxed. | |
PEB4 | Living in GHs would bring me a sense of harmony with nature. | |
Perceived green benefit (PGB) | PGB1 | GHs contribute to the prevention of climate warming. |
PGB2 | GHs contribute to the reduction in the carbon footprint. | |
PGB3 | GHs contribute to environmental protection. | |
PGB4 | GHs contribute to the reduction in environmental pollution. | |
PGB5 | GHs contribute to the reduction in consumption of natural resource. | |
Perceived social benefit (PSB) | PSB1 | Living in GHs would improve the way I am perceived. |
PSB2 | Living in GHs would gain me social approval. | |
PSB3 | Living in GHs would make a good impression on others. | |
PSB4 | Living in GHs would help me to feel acceptable to others. | |
Perceived performance risk (PPR) | PPR1 | GHs may fall short of the level of benefits I expect. |
PPR2 | GHs may not work satisfactorily due to a low level of operation and management. | |
PPR3 | GHs may not perform the functions that were described by the developer. | |
PPR4 | GHs may not perform well and cause problems in my life. | |
Perceived financial risk (PFR) | PFR1 | I am concerned that GHs are too expensive to purchase. |
PFR2 | I am concerned that GHs may have higher maintenance costs than traditional housing. | |
PFR3 | I am concerned that GHs may have higher repair costs than traditional housing. | |
PFR4 | I am concerned about suffering financial losses when purchasing and living in GHs. | |
Environmental concern (EC) | EC1 | I am concerned about the environment. |
EC2 | I am willing to make sacrifices to protect the environment. | |
EC3 | I am emotionally involved in environmental protection issues. | |
Social trust (ST) | ST1 | I trust the quality of assessment standards for GHs developed by the official authorities. |
ST2 | I trust the experts’ evaluation in the GHs assessment process. | |
ST3 | I trust the authenticity of application documents provided by the developers/investors/consultants. |
Category | Number | Percentage (%) | |
---|---|---|---|
Gender | Female | 361 | 49.6 |
Male | 367 | 50.4 | |
Age | 18–29 | 241 | 33.1 |
30–39 | 309 | 42.5 | |
40–49 | 131 | 18.0 | |
50–59 | 33 | 4.5 | |
60 and above | 14 | 1.9 | |
Education level | High school and below | 56 | 7.7 |
Junior college | 118 | 16.2 | |
Bachelor | 418 | 57.4 | |
Master’s degree or above | 136 | 18.7 | |
Household income per year (CNY 10,000) | Less than 10 | 135 | 18.6 |
10–15 | 156 | 21.4 | |
15–25 | 193 | 26.5 | |
25–50 | 180 | 24.7 | |
More than 50 | 64 | 8.8 |
Construct | Items | Standard Loadings | Cronbach’s α | CR | AVE |
---|---|---|---|---|---|
Purchase intention (PI) | PI1 | 0.933 | 0.911 | 0.944 | 0.850 |
PI2 | 0.923 | ||||
PI3 | 0.909 | ||||
Perceived value (PV) | PV1 | 0.892 | 0.884 | 0.928 | 0.811 |
PV2 | 0.904 | ||||
PV3 | 0.906 | ||||
Perceived functional benefit (PFB) | PFB1 | 0.885 | 0.867 | 0.909 | 0.715 |
PFB2 | 0.867 | ||||
PFB3 | 0.819 | ||||
PFB4 | 0.809 | ||||
Perceived emotional benefit (PEB) | PEB1 | 0.896 | 0.909 | 0.936 | 0.786 |
PEB2 | 0.887 | ||||
PEB3 | 0.891 | ||||
PEB4 | 0.872 | ||||
Perceived green benefit (PGB) | PGB1 | 0.860 | 0.917 | 0.938 | 0.751 |
PGB2 | 0.858 | ||||
PGB3 | 0.880 | ||||
PGB4 | 0.904 | ||||
PGB5 | 0.829 | ||||
Perceived social benefit (PSB) | PSB1 | 0.886 | 0.927 | 0.948 | 0.821 |
PSB2 | 0.920 | ||||
PSB3 | 0.923 | ||||
PSB4 | 0.892 | ||||
Perceived performance risk (PPR) | PPR1 | 0.882 | 0.927 | 0.947 | 0.818 |
PPR2 | 0.923 | ||||
PPR3 | 0.916 | ||||
PPR4 | 0.897 | ||||
Perceived financial risk (PFR) | PFR1 | 0.890 | 0.925 | 0.946 | 0.815 |
PFR2 | 0.919 | ||||
PFR3 | 0.919 | ||||
PFR4 | 0.882 | ||||
Environmental concern (EC) | EC1 | 0.867 | 0.847 | 0.907 | 0.765 |
EC2 | 0.884 | ||||
EC3 | 0.873 | ||||
Social trust (ST) | ST1 | 0.893 | 0.882 | 0.927 | 0.809 |
ST2 | 0.927 | ||||
ST3 | 0.878 |
PI | PV | PFB | PEB | PGB | PSB | PPR | PFR | EC | ST | |
---|---|---|---|---|---|---|---|---|---|---|
PI | 0.922 | |||||||||
PV | 0.663 | 0.901 | ||||||||
PFB | 0.471 | 0.493 | 0.846 | |||||||
PEB | 0.536 | 0.546 | 0.481 | 0.887 | ||||||
PGB | 0.437 | 0.475 | 0.473 | 0.543 | 0.867 | |||||
PSB | 0.502 | 0.554 | 0.371 | 0.625 | 0.461 | 0.906 | ||||
PRR | −0.217 | −0.251 | 0.006 | −0.057 | −0.061 | −0.175 | 0.905 | |||
PFR | −0.164 | −0.144 | 0.101 | 0.079 | 0.037 | −0.053 | 0.667 | 0.903 | ||
EC | 0.396 | 0.372 | 0.507 | 0.296 | 0.384 | 0.298 | −0.065 | 0.041 | 0.875 | |
ST | 0.519 | 0.565 | 0.512 | 0.508 | 0.461 | 0.480 | −0.225 | −0.120 | 0.311 | 0.899 |
Hypotheses | Path | Path Coefficient | t-Value | p-Value | Hypothesis Supported |
---|---|---|---|---|---|
H1 | PV→PI | 0.664 | 18.530 | 0.000 | Yes |
H2a | PFB→PV | 0.256 | 5.014 | 0.000 | Yes |
H2b | PEB→PV | 0.198 | 3.603 | 0.000 | Yes |
H2c | PGB→PV | 0.127 | 2.583 | 0.010 | Yes |
H2d | PSB→PV | 0.249 | 5.460 | 0.000 | Yes |
H3a | PPR→PV | −0.130 | 2.641 | 0.008 | Yes |
H3b | PFR→PV | −0.090 | 1.572 | 0.116 | No |
H4a | EC→PEB | 0.153 | 4.069 | 0.000 | Yes |
H4b | EC→PGB | 0.266 | 5.658 | 0.000 | Yes |
H4c | EC→PSB | 0.165 | 4.584 | 0.000 | Yes |
H4d | EC→PFR | 0.087 | 1.917 | 0.055 | No |
H5a | ST→PFB | 0.512 | 15.290 | 0.000 | Yes |
H5b | ST→PEB | 0.460 | 11.904 | 0.000 | Yes |
H5c | ST→PGB | 0.379 | 9.712 | 0.000 | Yes |
H5d | ST→PSB | 0.429 | 11.340 | 0.000 | Yes |
H5e | ST→PPR | −0.225 | 5.793 | 0.000 | Yes |
H5f | ST→PFR | −0.147 | 3.945 | 0.000 | Yes |
Construct | Total Standardized Effects on GH Purchase Intention |
---|---|
PV | 0.664 |
PFB | 0.170 |
PEB | 0.131 |
PGB | 0.084 |
PSB | 0.165 |
PPR | −0.086 |
PFR | −0.060 |
EC | 0.064 |
ST | 0.278 |
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Zhao, S.; Chen, L. Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value. Int. J. Environ. Res. Public Health 2021, 18, 4074. https://doi.org/10.3390/ijerph18084074
Zhao S, Chen L. Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value. International Journal of Environmental Research and Public Health. 2021; 18(8):4074. https://doi.org/10.3390/ijerph18084074
Chicago/Turabian StyleZhao, Shiwen, and Liwen Chen. 2021. "Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value" International Journal of Environmental Research and Public Health 18, no. 8: 4074. https://doi.org/10.3390/ijerph18084074
APA StyleZhao, S., & Chen, L. (2021). Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value. International Journal of Environmental Research and Public Health, 18(8), 4074. https://doi.org/10.3390/ijerph18084074