Factors Affecting the Green Housing Purchasing

Factors Affecting Green Housing Purchase
Piyapong Numraktrakul * , Atcharawan Ngarmyarn ** and Supeecha
Panichpathom ***
Real estate industry has played an important part in producing
negative effects on the environment. Many countries have come up
with the idea of green housing which is friendly to the environment.
This study aims to find out factors affecting intention to buy green
housing of the Thai consumers. Online survey has been employed
as data collection method in 2011. The total of 200 samples were
collected from the respondents aged 18 years old and over with at
least bachelor’s degree background. Factor analysis and multiple
regression analysis are used as statistical tools. Six factors have
been hypothesized as independent constructs affecting the intention
to buy green housing positively. Those constructs are – “attitude
toward behavior”, “subjective norm”, “perceived behavioral control”,
“environmentally conscious behavior”, “economic factors” and
“government role”. All hypothesized factors are statistically
significant independent constructs in explaining the intention to buy
green housing. Subjective norm has the greatest influence and the
environmentally conscious behavior has the least effect. The real
estate entrepreneur can apply this finding to stimulate selling of
green housing where the environment contamination can be
reduced, so as the global warming.
Field of research: Real Estate Business
1. Introduction
When talking about green housing, it does not mean a house surrounded by green trees
only, in a wider perspective it includes consumption of energies and other resources
efficiently. The term “green” also implies to eco-friendly, environmentally friendly, and
sustainability (Han and Kim, 2010). Therefore, a green housing is referred to a house that is
built by considering reduction of all contamination to the environment from all factors, such
as location, design, construction, including methods and materials. There must be energy
efficient within the green construction process, for the sake of healthy and happy living of
the occupants. However, it does not only include technical sustainability as mentioned, but
also behavioral sustainability. The later should be part of the occupants who are
environmentally friendly conscious which will result in their living in a sustainable way. The
sustainability behavior is a behavior developed by learning and experiences of people who
have acquired a green housing. If what they really care of is on technical sustainability only,
green housing will not be different from a conventional house (Shiers, 2000; Hostetler and
Noiseux, 2010).
* Piyapong Numraktrakul, graduate student of Master in Real Estate Business, Department of Real Estate
Business, Thammasat Business School, Thammasat University, Thailand. Email: khun.sss@gmail.com
** Atcharawan Ngarmyarn, Ph.D., Department of Real Estate Business, Thammasat Business School,
Thammasat Universtiy, Thailand. Email: a_ngarmyarn@yahoo.com
*** Supeecha Panichpathom, Ph.D., Department of Management Information Systems, Thammasat Business
School, Thammasat Universtiy, Thailand. Email: spanitdmc52@gmail.com
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2. Literature Review
2.1 Theory of Planned Behavior (TPB)
This study employed “Theory of Planned Behavior (TPB)” developed by Ajzen (1991) as a
tool in modeling intention to buy a green housing. TPB, introduced for the first time by Ajzen
(1985), was developed from the theory of reasoned action (TRA) which was accepted as
the first theory that tried to explain and forecast human behavior. Due to weakness of TRA
forecasting ability, Ajzen later developed TPB by adding a variable reflecting a person’s
perceived behavior control and TPB outperformed TRA in predicting and explaining human
behavior. Han and Kim (2010) studied customers’ decision to stay in a green hotel by
adopting TRA and TPB. They found that TPB can predict customers’ behavior on staying in
a green hotel more accurately than TRA. Under TPB, Ajzen (1985) mentioned that
important factors which influenced person’s behavior intention and his/her specific behavior
are attitude towards behavior, subjective norm, and perceived behavior control.
2.1.1 Attitude towards the behavior (ATB)
Attitude towards behavior is the degree of an individual’s favorable or unfavorable on
performing a behavior (Tonglet, Phillips, and Reed, 2004), or an individual’s overall
evaluation of a specific behavior (Han, Hsu and Sheu, 2010). According to Ajzen and
Fishbein (2004), general attitude has lower power than both positive and negative attitude
in predicting a particular behavior. ATB, thus, is self evaluation towards a particular
behavior which will reflect beliefs of a person on the perceived outcomes or benefits that a
person will get from expressing that behavior (Ajzen, 1991; Shim, Eastlick, Lotz and
Warrington, 2001). Many research papers found a positive relationship between attitude
towards behavior and behavior intention, for example, in the field of physical activity
(Jackson, Smith and Conner, 2003; French et al., 2005), internet stock trade (Gopi and
Ramayah, 2007), and online shopping (Shim et al., 2001). Some researchers have studied
factors affecting behavior intention in a household recycling behavior, green hotel
repurchasing, and green product consumption, they found a positive relationship between
an affective attitude towards behavior and behavior intention (Tonglet et al., 2004; Han and
Kim, 2010; Kim and Han, 2010).
2.1.2 Subjective norm (SN)
Subjective norm is awareness of social pressure affecting an individual’s behavior intention.
Such pressure is perceived as important influence to attitude or behavior (Ajzen, 1991;
Tonglet et al., 2004; Han and Kim, 2010; Kim and Han, 2010). Subjective norm is a function
of normative beliefs. It is an individual’s beliefs affected by important others such as family
members who think that an individual should or should not perform a particular behavior
(Rivis and Sheeran, 2003). Moreover, it also plays an important part in determining
environmentally friendly behavior. According to the study by Gupta and Ogden (2009),
even though consumers have positive attitude towards an environmentally friendly or green
consumption, they may not buy a green product. Their study signified to the influence of the
reference groups, or subjective norm on a particular behavior. Han et al. (2010) had studied
the green hotel choice and found that subjective norm had played an important part on an
individual’s decision to stay in a green hotel. The result is consistent with a study done by
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Han and Kim (2010) that subjective norm highly influenced an intention to repeat purchase
of a green hotel positively.
2.1.3 Perceived behavior control (PBC)
According to the study by Ajzen (1991), perception of an ability (how easy or difficult) to
control one’s own behavior plays an important part in predicting behavior intention.
Perceived behavioral control referred to one’s own capability in controlling various factors
affecting actual behavior (Tonglet et al., 2004; Han et al., 2010; Kim and Han, 2010).
Bandura (1991, as cited in Ajzen, 2002) determined self efficacy as one’s own perception of
how successful one could execute his/her behavior according to what he/she had planned
to perform in order to get an expected outcome. Ajzen (2002) separated one’s own ability to
perform a behavior into two which are “perceived behavior control” and “perceived selfefficacy”.
Perceived behavior control is degree of controlling one’s own behavior and
perceived self-efficacy is conviction to one’s own ability to do something. However, these
two are quite similar (Ajzen, 2002, p.668), therefore both are inherited within the perceived
behavioral control construct in this study.
2.2 TPB Model in Green Consumption Context
In order to add some additional constructs to the original TPB model, those constructs must
increase the predictive ability to behavior intention. Additional constructs that are
hypothesized to influence behavior intention according to some researchers are as follows.
2.2.1 Environmentally conscious behavior (ECB)
This construct sometimes called environmentally significant behavior, environmentally
conscious behavior, environmentally friendly behavior, environmentally responsible
behavior, environmentally relevant ecological behavior and simply environmental behavior
(Urban and Zverinova, 2009). Though many researchers have studied about this context,
there is still no agreement on its influence on purchase intention. However, they agree that
consumers are motivated to purchase an environmentally friendly product if they are
convinced on the importance of environmental problems. Finally, such attitude should be
expressed into environmental problem conscious behavior (Thompson, Anderson, Hansen,
and Kahle, 2009; Urban and Zverinova, 2009). This kind of behavior should be deep rooted
in every step of one’s lifestyle (H’Mida, 2009; Kim and Han, 2010). An individual should
perceive an effect of products on an environment and had the purpose to decrease that
effect. Environmentally friendly habit will have a direct effect on purchasing environmentally
friendly products (Kalafatis, East, Pollard and Tsogas, 1999). However, Han et al. (2010)
had studied the effect of environmentally friendly activities on a decision to stay in a green
hotel and found that the level of having the environmentally friendly activities had no
relationship to the decision.
2.2.2 Economic factors (EC)
Economic factors refer to willingness to pay additional money to buy the environmentally
friendly products or agreed on paying higher tax to protect the environment (Paco and
Raposo, 2009). This price premium means amount of money paid additional to the normal
price and is used as an indicator of consumer willingness to pay for a green product
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(Vlosky, Ozanne and Fontenot, 1999). According to the study by D’Souza (2004), though
consumers had been convinced on the importance of the environment, they could still be
sensitive to prices and might not be willing to pay higher for environmentally friendly
products. People who are aware of the importance of environmental problems may not be
willing to pay higher price, and still made purchase decision based on price and quality
rather than environmentally friendly characteristics of products (Gan, Wee, Ozanne and
Kao, 2008). Paco and Raposo (2009) found that economic factors sometimes had higher
influence on decision to purchase environmentally friendly products than negative effect to
the environment.
2.2.3 Government role (GR)
The government role in supporting various activities concerning the environmentally friendly
product consumption has direct effect on consumers’ interest on participating in the
environmental activities. From the study by Haron, Paim and Yahaya (2005, cited in Chen
and Chai, 2010), government played an important part in supporting consumption and
sustainable development in Malaysia by introducing various strategies to create an
awareness on the importance of the environment to the public. There are various ways of
government in getting involved in an environmentally friendly consumption such as rules
and regulations, taxing, interest, subsidies, and research and development (Hudson, 2007).
Chyoung et al.(2006, as cited in Chen and Chai, 2010) found that though an individual is
aware of the environmental importance, he/she still believe that it is the main
responsibilities of the government to take care of the environment. This was consistent to
the study by Raisback and Wardlaw (2008) where an individual who had environmentally
friendly behavior had a high tendency to purchase a green housing if there was a support
from the government.
2.3 Behavior Intention
This construct reflects the motivation to express one’ own behavior which indicate an
individual’s intention, less or more, in revealing such behavior. It is the readiness of an
individual in performing the particular behavior (Ajzen, 1991; Han et al., 2010; Han and Kim,
2010; Kim and Han, 2010). In this study, behavior intention refers to “intention to purchase
green housing (IP)”.
3. Methodology and Model
3.1 Model and Hypotheses
Theory of planned behavior (1985) is selected as an appropriate theory to study behavior of
environmentally friendly product consumption here. However, there might be some other
constructs from the environmental context which also affect intention to purchase a green
housing. In order to predict purchase decision on environmentally friendly product,
especially on green housing, there should be additional constructs which can better explain
the environmentally friendly behavior intention. The proposed model and hypotheses in this
study are shown in figure 1 where all 6 independent constructs are hypothesized to affect
intention to a purchase green housing positively.
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Figure 1. The proposed model and hypotheses. (Additional constructs from the TPB
are in dashed lines.)
Attitude toward
behavior (ATB)
H1(+)
Subjective norm (SN)
H2(+)
Perceived behavioral control
(PBC)
Environmentally conscious
behavior (ECB)
H4(+)
H5(+)
H3(+)
Intention to purchase green
housing (IP)
Economic factor (EF)
H6(+)
Government role (GR)
3.2 Population and Samples
The target customers in this study are people with at least undergraduate education, aged
18 years old and over. The majority of these people are normally in the work force, have
tendency to buy a house at a higher level than those who are younger with less level of
education. The scales used in this study mostly are five-point likert scales ranging from
strongly disagree to strongly agree. With 95 % confidence interval and a unit variance,
allowing about 5% sampling error from the mean which was averaged around 3, the sample
size of 171 [n=(1) 2 (1.96) 2 /(0.15) 2 ] was estimated. However, within this study, the data of
200 samples were collected.
4. Findings
4.1 Exploratory Factor Analysis (EFA)
An exploratory factor analysis (EFA) was performed on 30 original items from the
questionnaire. However, after conducting Cronbach alpha for reliability measures and EFA
to verify convergence within the same trait and divergence between different traits, 6 items
were dropped leaving with 24 items used to investigate the underlying constructs. The KMO
for the EFA is 0.901 confirming a measure of sampling adequacy where the significant
Barlett’s test of sphericity confirms that EFA should be used. There were six factors
extracted according to the hypothesized independent constructs in the proposed model.
The principal axis factoring was performed as extraction method and varimax with Kaiser
normalization was used as rotation method. Factor loadings were shown in Table 1 for
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each independent construct of the hypothesized model with corresponding % variance, %
cumulative variance, and Cronbach alpha.
However, the only one dependent construct of intention to purchase green housing (IP)
measured with 3 items was verified for its reliability and convergence within the same trait.
Cronbach alpha for this reliability measure is .903 and % cumulative variance is 76.7.
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Table 1. Factor loading, % variance, cumulative % variance and Cronbach alpha
Factor
Loading
%
Variance
Cumulative
%Variance
Cronbach
Alpha
1. Economic factors 12.293 12.293 0.893
I am willing to pay more for products with less
contamination to the environment. 0.901
I am willing to pay more for products with
environmental friendly production process. 0.820
I am willing to pay more tax which will be used to
protect the environment. 0.668
I am willing to pay a premium for the green
housing. 0.615
2. Subjective norm 11.063 23.357 0.895
My family thinks that I should buy a green housing. 0.820
My family would want me to buy a green housing 0.778
My family agrees with me to buy the green
housing. 0.630
My family thinks that buying a green housing is a
wise decision. 0.604
3. Government role 10.596 33.952 0.824
I think that the government should help and
support research and development on green
housing. 0.787
I think the government should have financial
incentives on green housing either in the form of
tax reduction or interest subsidizing. 0.709
I think the government should support data on
green housing. 0.701
I think the government should set a law or
regulations on green housing. 0.579
4. Environmentally conscious behavior 9.751 43.703 0.827
I am trying to reduce electricity consumption. 0.908
I am trying to reduce water consumption. 0.884
I am trying to recycle trashes within my household. 0.517
I will always choose to consume products that
contributes the least contaminate to the
environment. 0.399
5. Attitude toward behavior 9.488 53.191 0.808
Buying a green housing is a beneficial decision. 0.771
Buying a green housing is a good idea. 0.681
Buying a green housing is a wise decision. 0.675
Buying a green housing is an admired decision. 0.467
6. Perceived behavioral control 9.182 62.373 0.776
I have enough opportunity (easily access to the
market) in making decision to buy a green housing. 0.717
I have enough time to make a decision to buy a
green housing. 0.672
I have enough money to buy a green housing. 0.564
If I would like to buy a green housing, I have
enough skill and knowledge about the green
housing to make my own decision. 0.554
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4.2 Multiple Regression Analysis
Factor scores of all 6 factors from Table 1, economic factors (EC), subjective norm (SN),
government role (GR), environmentally conscious behavior (ECB), attitude toward behavior
(ATB), and perceived behavioral control (PBC), were used as independent constructs and
factor scores resulted from the 3 items measuring intention to purchase green housing (IP)
was used as a dependent construct in finding a relationship within the hypothesized model
in a subsequent process. The estimated regression equation is as follows.
(7.5) ** (9.0) ** (6.6) ** (2.6) * (5.2) ** (7.6) **
Note: ** The coefficients are statistically significant at p ≤ 0.01.
Where
* The coefficient is statistically significant at p ≤ 0.05.
IP = Intention to purchase green housing
EF = Economic factors
SN = Subjective norm
GR = Government role
ECB = Environmentally conscious behavior
ATB = Attitude toward behavior
PBC = Perceived behavior control
Subjective norm seems to play an important part in predicting purchase intention of green
housing while the environmentally conscious behavior has the least effect. This outcome is
consistent with research result studied by Han et al. (2010) and Han and Kim (2010). The
pressure from family members had higher influence on green housing purchase even more
than an individual’s attitude itself. Though attitude towards buying behavior of an individual
also has positive influence on purchase intension, the coefficient is lower (0.253) than the
family attitude (0.423).
Perceived behavioral control also has positive impact on green housing purchase (0.382)
which is consistent to the study done by Chan and Lau (2002). This factor is the next
important to subjective norm. If an individual recognizes his/her perceived resources and
perceived opportunities there will be higher chance for him/her to reach the buying sources.
Economic factors should be important (0.336) in most house buying. In such case, green
housing should have higher price than a normal house, this finding should not be surprising
since money is still important in making green housing purchase decision (0.320). On the
other hand, support from the government, either in subsidies, tax exempt or available
information certainly support an increase in environmentally friendly product consumption
which is consistent to the study done by Haron et al. (2005, cited in Chen and Chai, 2010).
Moreover, environmentally conscious behavior has positive impact on green housing
purchase (0.116) though not as high as other factors. This finding is more encouraging than
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the work done by Kim and Han (2010) where this kind of behavior did not affect consumers’
intention to stay in a green hotel.
5. Conclusion and Discussion
Real estate industry can cause negative effects on environment from the first step of the
development until the living period of consumers within the household. The daily living of
real estate consumers can cause inefficient consumption of energy, therefore an idea of
green housing where the process of housing development will be environmentally friendly is
in trend in some countries such as U.S. and Australia. In Thailand this concept is not widely
spread because developers are still uncertain about the demand for green housing.
Moreover, a clear picture of this segment is still in doubt, including the consumer
purchasing process and important factors affecting the green housing decision making. So,
this study can help the developers understand more about those factors affecting customer
decision process. Real estate developers can develop strategies based on six independent
constructs to motivate Thai customers to buy more green housing. Since important people
such as family members play an important part in an individual green housing purchase,
then marketers can create good image to motivate all family members to recognize an
importance of living in an environmentally friendly house which consumes energy efficiently
and contaminate an environment the least. It probably leads to lessen the effect from the
global warming too. By providing more information to target customers to have enough skill
and knowledge about green housing, real estate developers can convince consumers that a
purchase decision on green housing is not that difficult. In this study, an environmentally
conscious behavior has the least effect on purchase intention, therefore other factors such
as economic reasons and government motivation should be used to encourage consumers
to purchase a green housing. The developers should keep track on the government support
and rules that help promoting green housing consumption to gain competitive advantage in
real estate industry.
References
Ajzen, I., 1985. From Intentions to Actions: A Theory of planned Behavior. In J. Kuhl & J.
Beckman (Eds.), Action-control: From cognition to behavior. Heidelberg, Germany:
Springer, pp. 11-39.
Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human
Decision Processes, 50, pp. 179-211.
Ajzen, I., 2001. Attitudes. Annual Review of Psychology, 52, pp. 27-58.
Ajzen, I., 2002. Perceived behavioral control, self-efficacy, locus of control, and the theory
of planned behavior. Journal of Applied Social Psychology, 32, pp. 665-683.
Ajzen, I., and Fishbein, M., 2004. The influence of attitudes on behavior. In Handbook of
Attitudes and Attitude Change: Basic Principle. D. Albarracin, B. T. Johnson and M. P.
Zanna (Eds.). Mahwah. NJ: Erlbaum, pp. 173-221.
Chan, R.Y.K. and Lau, L.B.Y., 2002. Explaining Green Purchasing Behavior: A Cross-
Cultural Study on American and Chinese Consumers. Journal of International
Consumer Marketing, 14(2-3), pp. 9-40.
9

Chen, T.B., and Chai, L.T., 2010. Attitude towards the Environment and green Products:
Consumers’ Perspective. Management Science and Engineering, 4 (2), pp. 27-39.
D’Souza, C., 2004. Ecolable programmes: A stakeholder (consumer) perspective.
Corporate Communication. An International Journal, 9(3), 179-188.
French, D.P., Sutton, S., Hennings, S.J., Mitchell, J., Wareham, N.J., Griffin, S., Hardeman,
W., and Kinmonth, A.L., 2005. The Importance of Affective Beliefs and Attitudes in the
Theory of Planned Behavior: Predicting Intention to Increase Physical Activity. Journal
of Applied Social Psychology, 35, pp. 1824–1848.
Gan, C., Wee, H.Y., Ozanne, L., and Kao, T.H., 2008. Consumers’ Purchasing Behavior
towards Green Products in New Zealand. Innovative Marketing, 4(1), pp. 93-102.
Gopi, M., and Ramayah, T., 2007. Applicability of theory of planned behavior in predicting
intention to trade online: Some evidence from a developing country. International
Journal of Emerging Markets, 2 (4), pp. 348 – 360.
Gupta, S., and Ogden, D.T., 2009. To buy or not buy A social dilemma perspective on
green buying. Journal of Consumer Marketing, 26 (6), pp. 376-391.
H’Mida, S., 2009. Factors Contributing in the Formation of Consumers’ Environmental
Consciousness and Shaping green purchasing decisions. IEEE, pp. 957-962.
Han, H., Hsu, L-T., and Sheu C., 2010. Application of the Theory of Planned Behavior to
Green Hotel Choice: Testing the effect of environmental friendly activities. Tourism
Management, 31, pp. 325-334.
Han, H., and Kim, Y., 2010. An investigation of green hotel customer’s decision formation:
Developing an extended model of the theory of planned behavior. International
Journal of Hospitality Management, 29 (4), pp. 659-668.
Hostetler, M. and Noiseux, K., 2010. Are green residential developments attracting
environmentally savvy homeowners Landscape and Urban Planning, 94, pp. 234–
243.
Hudson, P., 2007. Government Intervention In the Energy Efficient Home Marketplace.
School of Public Affairs and Administration Western, Michigan University, Michigan.
Jackson, C., Smith, R.A., and Conner, M., 2003. Applying an extended version of the theory
of planned behaviour to physical activity. Journal of Sports Science, 21, pp. 119-133.
Kalafatis, S.P., East R., Pollard, M., and Tsogas, M. H., 1999. Green marketing and Ajzen's
theory of planned behaviour: a cross-market examination. Journal of Consumer
Marketing, 16 (4/5), pp. 441-460.
Kim, Y., and Han, H., 2010. Intention to pay conventional-hotel prices at a green hotel - a
modification of the theory of planned behavior. Journal of Sustainable Tourism, 18 (8),
pp. 997 – 1014.
10

Paco, A.D., and Raposo, M., 2009. Green segmentation an application to the Potruguese
consumer market. Marketing Intelligence & Planning, 27 (3), pp. 364-379.
Raisbeck, P. and Wardlaw, S., 2009. Considering client-driven sustainability in residential
Housing. International Journal of Housing Markets and Analysis, 2(4), pp. 318-333.
Rivis, A., and Sheeran, P., 2003. Descriptive Norms as an Additional Predictor in the
Theory of Planned Behaviour: A Meta-Analysis. Current Psychology, 33 (3), pp. 218-
233.
Shiers, D. E., 2000. ``Green'' Developments Environmentally Responsible Buildings in the UK
Commercial Property Sector. Property Management, 18 (5), pp. 352-365.
Shim, S., Eastlick, M.A., Lotz, S.L., and Warrington, P., 2001. "An Online Prepurchase
Intention Model: the Role of Intention to Search", Journal of Retailing, 77(10), pp. 397-
416
Thompson, D.W., Anderson, R.C., Hansen, E.N. and Kahle, L.R., 2009. Green
Segmentation and Environmental Certification: Insights from Forest Products.
Business Strategy and the Environment, 19, pp. 319-334.
Tonglet, M, Phillips P.S., and Read, A.D., 2004. Using the Theory of Planned Behaviour to
Investigate the Determinants of Recycling Behaviour: a Case Study from Brixworth.
Resources, Conservation and Recycling, 41 ( 3), pp. 191-214.
Urban, J., and Zverinova, I., 2009. What are the Determinants of Environmentally
Significant Behavior in the Czech Republic: A Secondary Analysis of Two ISSP
Datasets. CUEC WORKING PAPER.
Vlosky, R.P., Ozanne, L.K., and Fontenot, R.J., 1999. A Conceptual Model of US Consumer
Willingness-to-pay for Environmentally Certified Wood Products. Journal of Consumer
Marketing, 16 (2), pp. 122-136.
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