Factors That Influence the Decision of Indian Investors to - Copy

International Research Journal of Finance and Economics ISSN 1450-2887 Issue 100 (2012) EuroJournals Publishing, Inc. 2012 http://www.internationalresearchjournaloffinanceandeconomics.com

Factors that Influence the Decision of Indian Investors to Invest in the Real Estate Market

Amarjit S. Gill Corresponding Author, The University of British Columbia (Okanagan Campus)

3333 University Way, Kelowna, BC Canada V1V-1V7 E-mail: [email protected]

Tel: 250-807-8000

Harvinder S. Mand Sikh National College Banga, Sahid Bhagat Singh Nagar

East Punjab, India, Pin Code: 144505 E-mail: [email protected]

Rajen Tibrewala New York Institute of Technology, 1855 Broadway

New York, 10023-7692, USA E-mail: [email protected]

Tel: 212-261-1500

Abstract

This study examines the factors that influence the decision of Indian investors to invest in the real estate market. This paper seeks to extend the findings of Gill et al. (2012). Individuals from India were surveyed to find out their perceptions, feelings, and beliefs on the factors that positively influence their decision to invest in the real estate market. The results show that the investment expertise of investors, the investors motivation from an advisor, the investment propensity of investors, and the age positively influence the decision of Indian investors to invest in the real estate market. The findings also show that the investment behavior and the decision differ based the age of the investors. This study contributes to the literature on the factors that influence the decision of the investors in the real estate market. The study can be useful for the real estate investors and the investment advisors.

Keywords: Investment Expertise, Investment propensity, Motivation from an Advisor, Real Estate Market.

1. Introduction The Indian real estate market plays an important role in the economic development of India.

The Indian financial sector has been experiencing incredible growth during the last decade. According to Asia Pulse (2012), the economic growth rate of India was 8.50% in year 2010-2011. Because of the population and the economic growth, the real estate market is expected to grow at a compounded annual growth rate of 52.5 percent (M2 Presswire, 2012). One of the important factors contributing to the economic growth and the growth in the real estate market is the globalization of

International Research Journal of Finance and Economics - Issue 100 (2012) 113

multinational corporations (Bardhan and Kroll, 2007); that is, multinational corporations are moving into the Indian market, which in turn, increases the demand for the real estate properties in India. Other important factors that are leading to the growth in the Indian real estate market are largely attributed to the wide population base, rising income level, increasing trend of nuclear families, and rapid urbanization. According to several new research reports, the demand for affordable housing is escalating in India. Majority of this demand comes from low-income groups which represents the highest potential target segment for the real-estate developers. Demand from the middle-income group is also accelerating at a considerable pace (M2 Presswire, 2012). Thus, Indian real estate market provides a significant investment opportunity for the investors.

Since the Indian real estate market is an emerging market in a less developed economy, the real estate investors play an important role in the development of the Indian economy (Gill et al., 2012), it is important to understand the factors that have positive influence on the investment decision of Indian investors to invest in the real estate market. Therefore, the resultant thesis is that the investment decision of investors to invest in the real estate market is the function of investment expertise of investors, investors motivation from an advisor, investment propensity of investors, and age; the purpose of this study is to explore these relationships among above variables.

Proxy variables for this study were chosen from previous empirical studies. Five proxy variables (Investment Expertise of Investors, Investors Motivation from an Advisor, Investment Propensity of Investors, Age, and Investment Decision of Investors) were used to conduct this study.

The literature in the behavioral finance usually assumes that the information structure and the characteristics of market participants systematically influence individuals' investment decisions (Al-Tamimi, 2006, p. 225). The theory claims that investors market behavior derives from psychological principles of decision making. The field of the behavioral finance focuses upon the ways investors interpret and act on the information during the process of making investment decisions. In addition, the field of behavioral finance places an emphasis on the investor behavior that at times leads to various market anomalies (Gill and Biger, 2009, p. 136; Gill et al., 2011, p. 329).

This study contributes to the literature on the factors that influence the investment decision of investors in the real estate market. The results of this study can be generalized to the real estate industry.

2. Literature Review Many earlier studies have focused on the investment pattern of institutional investors investment, where as a very few studies have dealt with the investment pattern of individual investors. The field of investment has also become more dynamic than it was a decade ago. Many individuals find investments to be fascinating because they can participate in the decision making process and see the results of their decisions. Not all investments may turn out to be profitable, especially if the investor has not made the correct investment decision. Therefore, investors should realize that investing is not a game but a serious issue that can have a major impact on their future wellbeing (Kabra et al., 2010).

Investment in the real estate market is one of the popular investments because everyone needs a place to live. Factors such as investment expertise of investors, investment motivation from an advisor, and investment propensity of investors influence the investment decision of investors in the real estate market (Gill and Biger, 2008, 2009; Gill et al., 2012).

The investment knowledge of investors is one of the principal risk attributes that impact on their investment propensity. The relative importance of the investors level of the knowledge attribute is a function of idiosyncratic investor and asset characteristics (Gill and Biger, 2008; Gill et al., 2012).

Byrne (2005) describes that improved investment knowledge and experience enable consumers to make better investment decisions. That is, the more accurately investors perceive risk, the better they understand the link between risk and return in the Indian real estate market; and the better the understanding of the link between risk and return , the higher the investment propensity of investors.

114 International Research Journal of Finance and Economics - Issue 100 (2012)

Hamid (1999) indicates that the risk-averse investors continue to be attracted by the relative stability of residential properties and buildings. Investors investment knowledge and experience have both positive and negative impacts on their propensity to invest in the real estate market. That is, if Indian investors perceive higher risk in the Indian real estate market, they are reluctant to invest capital and vice versa (Gill et al., 2012, P. 140).

According to Nagy and Obenberger (1994) the recommendations of family members and friends impact on the investment decisions of investors. ONeal (2004) also suggests that investment advisors play a significant role in investment decisions of investors.

Some empirical studies on the relationship between investment expertise of investors, investors knowledge of neutral information, investor consultation of an advisor, and investment propensity of investors are as follows:

Nagy and Obenberger (1994) collected data through Fortune 500 companies (USA) to examine factors influencing investor behavior. Their findings suggest that the recommendations of brokerage house, individual stock brokers, family members, and coworkers play a role in investment decision.

Al-Tamimi (2006) collected data from United Arab Emirates (UAE) and found that the motivation from an advisor (e.g., family member opinion) and the investors gut feelings on the economy have some positive influence on the behavior of investors.

Gill and Biger (2008) collected data from Canada and found a positive relationship between Canadian investors investment expertise and Canadian investors propensity to invest in the Indian real estate market. The propensity to invest, in turn, positively influences the decision to invest in the real estate market.

Gill and Biger (2009) collected data from Canada and found investors investment expertise and investor consultation of an advisor positively impact on the investment decision of investors.

Kabra et al. (2010) collected data from India and found that investors awareness, benefits provided by investment, and investors age positively impact on the decision of investors.

Gill et al. (2011) collected data from India and found investment expertise of investors, investor consultation of an advisor, and family positively impact on the investment decision of investors.

In summary, literature review indicates that investment expertise of investors, investors knowledge of neutral information, motivation from an advisor, and age influence the decision of the investors to invest.

3. Methods 3.1. Research Design This study will utilize survey research (a non-experimental field study design).

3.2. Measurement All measures pertaining to:

(i) Investment Expertise of Investors and Investment Propensity of Investors were taken from Gill and Biger (2008), and

(ii) Measures pertaining to Investors Motivation from an Advisor and Investment Decision of investors were taken from Gill and Biger (2009). All the scale items were reworded to apply to Indian real estate investors and the reliability of

these re-worded items was re-tested. Respondents were asked to indicate their agreement with each item related to investment expertise of investors, investors motivation from an advisor, investment propensity of investors, and investment decision of investors using a five-point Likert scale ranging from Strongly Disagree to Strongly Agree. Respondents were also asked to indicate their agreement with each item related to investment decision, using a five-point Likert scale ranging from


0%-5% to 76%-100%. Table 4 shows factor analysis and scale items that were used in this study. Table 1 shows the proxy variables and their measurements.

Table 1: Proxy Variables and their Measurements

Dependent Variable Measurement Investment Decision (ID) Measured as the extent to which Indian real estate investors perceive that they allocate

proportion of their total individual portfolio (e.g., personal savings, business, etc.) in the real estate market to i) obtain higher rate of return and ii) diversify risk. Two items were used to measure investment decision of small business owners.

Cronbach alpha: 0.84 Investment expertise of investors (IEOI)

Measured as the extent to which Indian real estate investors are experienced and understand the Indian real estate market risk. Two items were selected to measure the IEOI variable.

Cronbach alpha: 0.85 Investors motivation from an advisor (IMFA)

Measured as the extent to which real estate broker, family members, and friends motivate Indian real estate investors to invest in the real estate market. Three items were used to measure the IMFA variable.

Cronbach alpha: 0.93 Investment propensity of investors (IPOI)

Measured as the extent to which Indian real estate investors are inclined to invest in the Indian real estate market to: i) get rich quickly, ii) diversify risk, and iii) obtain higher rate of return. Three items were used to measure the IPOI variable.

Cronbach alpha: 0.89 Age Age was measured by a single item that asked respondents to indicate their ages. The

average age of Indian real estate investors was calculated (e.g., 31 + 39 / 2 = 35). Categorized alternative responses were: i) 18-30, ii) 31-39, iii) 40-50, iv) 51-59, and v) 60 and over.

3.3. Sampling Frame, Questionnaire Distribution, and Collection The current study consisted of the population of Indian investors. Indian investors living in Punjab (Ludhiana, Malerkotla, Raikot, Banga, Hoshiar Pur, Kaputhala, Phagwara, Jalandhar, and Sahid Bhagat Singh Nagar) area of India were chosen as a sampling frame.

3.4. Sampling Method, Sampling Issues, and Possible Planned Solutions Punjab area (Ludhiana, Malerkotla, Raikot, Banga, Hoshiar Pur, Kaputhala, Phagwara, Jalandhar, and Sahid Bhagat Singh Nagar) of India was chosen as the research site to collect data. The survey did not need to be translated into Punjabi or Hindi for the Indian participants since almost all the investors can read and write English. Researchers were also available for translation. The instruction sheet indicated that participants could contact the researchers by telephone and/or email regarding any questions or concerns they might have about the research.

To avoid sampling bias, data collection team was asked to only choose participants that represent the target population. Non-Indian investors were excluded.

To achieve a convenience sample, an exhaustive list of Indian investors names and telephone numbers were created to distribute surveys and to conduct telephone interviews. Survey questionnaire bundles coupled with an instruction sheet were provided to the surveyors for distribution.

The sample included approximately 800 research participants encompassing Indian investors. A total of 209 surveys were completed over the telephone (approximately 10% of the surveys were completed over the telephone), through personal visits, and received by mail. Two of the surveys were non-usable. The response rate was roughly 26.12%. The remaining cases were assumed to be similar to the selected research participants.


3.5. Issues Related to Confidentiality of the Research Participants All individuals who were approached were ensured that their names will not be disclosed and confidentiality will be strictly maintained. In addition all subjects were requested not to disclose their names on the questionnaire. Since the research was based on the survey questionnaire small business owners were not forced to respond to each specific question.

All subjects were provided with stamped envelopes and confidentiality was ensured. There was no obligation for the subjects to answer our questions over the telephone and in person. Before any telephone interview the person was asked for willingness to participate and of course no one was forced to participate.

Investors Consent Letter specifically indicated that by completing the survey, subjects have consented to participate in the study. Any information that was obtained in connection with this study and that can be identified with subjects will remain confidential and will be disclosed only with subjects permission or as required by law.

4. Analysis, Findings, Discussion, Conclusion, Limitations, and Recommendations for Future Research Table 2 shows descriptive statistics related to this study.

Skewness (all the items): Within the range of -0.591 to -1.121 Cronbach Alpha on the clusters of items (entire sample): IEOI 0.83; IMFA 0.87; IPOI 0.90; and

IDOI 0.93.

Table 2: Investment Expertise of Investors, Investors Motivation from an Advisor, Investment propensity of Investors, and Investment Decision of Investors a

IEOI Strongly Disagree Disagree Uncertain Agree Strongly

Agree Understands the real estate investment risk 1.4% 6.3% 10.1% 56.5% 25.7% Experienced in the Indian real estate investment 1.4% 9.2% 20.8% 51.2% 17.4%

IMFAz Strongly Disagree Disagree Uncertain Agree Strongly

Agree Motivation from real estate broker 1% 9.7% 10.6% 57.5% 21.2% Motivation from family members 1% 7.7% 11.6% 54.6% 25.1% Motivation from friends 1.9% 5.8% 13% 57.5% 21.8%

IPOI Strongly Disagree Disagree Uncertain Agree Strongly

Agree Desire to invest capital to get rich quickly 2.4% 9.2% 12.1% 56% 20.3% Desire to invest capital to diversify risk 3.9% 4.8% 18.8% 50.7% 21.8% Desire to invest capital obtain higher rate of return 3.9% 5.8%` 15.9% 58% 16.4%

IDOI (0%-5%) (6%-25%) (26%-50%) (51%-75%)

(76%-100%)

Proportion of asset allocation to obtain higher rate of return 7.7% 12.1% 31.9% 42.5% 5.8% Proportion of asset allocation to diversify risk 8.7% 11.1% 31.9% 39.6% 8.7%

aN = 207 IEOI = Investment Expertise of Investors IMFA = Investors Motivation from an Advisor IPOI = Investment Propensity of Investors IDOI = Investment Decision of Investors

The principle components analysis (a cluster analysis tool designed to capture the variance in a dataset in terms of principle components) with number of factors set to 4 and a varimax rotation explained 85.29% of the variance in the original scores (see Table 3). As can be seen in Table 4, all the items loaded on the expected factors.


Table 3: Total Variance Explained Rotation Sums of Square Loadings

Component Total Variance Explained

Rotation Sums of Squared Loadings Total % of Variance Cumulative %

1 2.577 25.770 25.770 2 2.173 21.735 47.505 3 1.949 19.486 66.991 4 1.829 18.294 85.286

Extraction Method: Principal Component Analysis

Table 4: Rotated Component Matrix a

Component 1 2 3 4 Investment Expertise of Investors (IEOI) IEOI1) I understand the real estate investment risk in India. 0.237 0.135 0.110 0.894 IEOI2) I have an experience in the Indian real estate investment. 0.188 0.282 0.243 0.819 Investors Motivation from an Advisor (IMFA) IMFA1) My real estate broker motivates me to invest capital in the real estate market.

0.189 0.818 0.299 0.185

IMFA2) My family motivates me to invest capital in the real estate market. 0.399 0.726 0.225 0.248 IMFA3) My friends motivate me to invest capital in the real estate market. 0.499 0.707 0.160 0.196 Investment Propensity of Investors (IPOI) I desire to invest capital in the Indian real estate market to:

IPOI1) Get rich quickly. 0.754 0.327 0.194 0.288 IPOI2) Diversify risk. 0.810 0.268 0.298 0.166 IPOI3) Obtain higher rate of return. 0.810 0.274 0.282 0.206 Investment Decision of Investors (IDOI) What proportion of your total individual portfolio (e.g., personal savings, business, etc.) do you allocate in real estate market to?

IDOI1) Obtain higher rate of return? 0.291 0.240 0.858 0.218 IDOI2) Diversify risk? 0.276 0.258 0.877 0.156

Notes: aExtraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization Rotation converged in 5 iterations

The question subsets were analyzed in order to enable the calculation of the weighted factor scores. In terms of these weighted factor score items: two IEOI, three IMFA, three IPOI, and two IDOI, loaded approximately equally.

Table 5 provides the Pearson correlation for the variables used in the regression model. As shown in Table 5, investment decision of investors (IDOI) is positively correlated with investment expertise of investors (IEOI), investors motivation from an advisor (IMFA), investment propensity of investors (IPOI), and age.

Table 5: Pearson Bivariate Correlation Analysis

IDOI IEOI IMFA IPOI Age IDOI 1 0.475** 0.610** 0.622** 0.302** IEOI 1 0.549** 0.548** 0.143* IMFA 1 0.743** 0.292** IPOI 1 0.239** Age 1

**Correlation is significant at the 0.01 level (2-tailed) *Correlation is significant at the 0.05 level (2-tailed)


4.1. Regression Analysis In this section, we present the empirical findings on the relationships between investment expertise of investors (IEOI), investors motivation from an advisor (IMFA), investment propensity of investors (IPOI), Age, and investment decision of investors (IDOI).

Positive relationships between i) IEOI and IDOI, ii) IMFA and IDOI, iii) IPOI and IDOI, and iv) Age and IDOI were found (see Table 6); that is, investment expertise of investors, investors motivation from an advisor, investment propensity of investors, and age are the predictors of investment decision of investors to invest in the Indian real estate market.

Table 6: Regression Coefficients a, b, c

R2 = 0.463; Adjusted R2 = 0.452; SEE = 0.736; F = 43.55; ANOVAs Test Sig. = 0.000 Regression Equation: IDOI = -0.604 + 0.138 IEOI + 0.251 IMFA + 0.327 IPOI + 0.013 Age

Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity

Statistics VIF B Std. Error Beta Tolerance

(Constant) -0.604 0.269 -2.243 0.026 IEOI 0.138 0.063 0.139 2.175 0.031 0.654 1.529 IMFA 0.251 0.081 0.252 3.112 0.002 0.406 2.462 IPOI 0.327 0.079 0.328 4.126 0.000 0.420 2.383 Age 0.013 0.005 0.130 2.406 0.01 0.913 1.096

a Dependent Variable: IDOI

b Independent Variables: IEOI, IMFA, IPOI, and Age c Linear Regression through the Origin SEE = Standard Error of the Estimate

Note that: A test for multicollinearity was performed. All the variance inflation factor (VIF) coefficients

are less than 3 and tolerance coefficients are greater than 0.40. Age, IEOI, IPOI, and IMFA explain 46.3% of the variance in the degree of IDOI.

4.2. The Differences in Perceived Investment Behavior and Investment Decision Based the Age of

Investors

4.2.1. Multivariate Analysis (i) The exact probability (p) of 0.002 tells that there is a difference between younger investors,

middle age investors, and old age investor on the impact of motivation from an advisor on the investment decision of investors to invest in the real estate market.

(ii) The exact probability (p) of 0.018 tells that there is a difference between younger investors, middle age investors, and old age investor on the impact of investment propensity on the investment decision of investors to invest in the real estate market.

(iii) The exact probability (p) of 0.001 tells that there is a difference between younger investors, middle age investors, and old age investors when they make investment decision to invest in the real estate investors (see Table 7).

Table 7: Multivariate Analysis

Source Dependent Variable Type III Sum

of Squares df Mean Square F Sig.

Corrected Model

IEOI 4.712a 5 0.942 0.941 0.455 IMFA 18.027b 5 3.605 3.855 0.002 IPOI 13.377c 5 2.675 2.792 0.018 IDOI 20.860d 5 4.172 4.576 0.001


Table 7: Multivariate Analysis - continued

Intercept

IEOI 0.079 1 0.079 0.079 0.779 IMFA 0.327 1 0.327 0.349 0.555 IPOI 0.065 1 0.065 0.068 0.794 IDOI 0.712 1 0.712 0.781 0.378

AGE

IEOI 4.712 5 0.942 0.941 0.455 IMFA 18.027 5 3.605 3.855 0.002 IPOI 13.377 5 2.675 2.792 0.018 IDOI 20.860 5 4.172 4.576 0.001

Error

IEOI 201.288 201 1.001 IMFA 187.973 201 0.935 IPOI 192.623 201 0.958 IDOI 183.243 201 0.912

Total

IEOI 206.000 207 IMFA 206.000 207 IPOI 206.000 207 IDOI 204.313 207

Corrected Total

IEOI 206.000 206 IMFA 206.000 206 IPOI 206.000 206 IDOI 204.103 206

Notes: aR2 = 0.023 (Adjusted R2 = -0.001) bR2 = 0.088 (Adjusted R2 = 0.065) cR2 = 0.065 (Adjusted R2 = 0.042) dR2 = 0.102 (Adjusted R2 = 0.080)

4.2.2. Multivariate Regression Analysis (i) Age range (18-35; n = 38): Based on Multiple Regression Analysis, it is concluded that

investment decision of younger investors is a positive function of their i) investment expertise (Beta = 0.274, Sig. = 0.075) and ii) propensity to invest in the real estate market (Beta = 0.391, Sig. = 0.052). In terms of variance explained, IPOI, IEOI, and IMFA explain 44.20% of the variance in investment decision of younger investors.

(ii) Age range (36-55; n = 140): Based on Multiple Regression Analysis, it is concluded that investment decision of middle age investors is a positive function of the motivation from an advisor (Beta = 0.198, Sig. = 0.053) and their propensity to invest in the real estate market (Beta = 0.442, Sig. = 0.000). In terms of variance explained, IPOI, IEOI, and IMFA explain 44.50% of the variance in investment decision of middle age investors.

(iii) Age range (56 and over; n = 29): Based on Multiple Regression Analysis, it is concluded that investment decision of old age investors is a positive function of the motivation from an advisor (Beta = 0.588, Sig. = 0.003). In terms of variance explained, IPOI, IEOI, and IMFA explain 40% of the variance in investment decision of old age investors.

4.2. Discussion This study concentrated on the perceived factors that positively influence the decision of Indian investors to invest in the real estate market. This was done by surveying a sample of real estate investors from Punjab area of India. The findings show that the perceived investment decision of investors is positively associated with investment expertise of investors, investors motivation from an advisor, investment propensity of investors, and age. The findings of this study lend some support to the findings of:

(i) Nagy and Obenberger (1994) who found that the recommendations of brokerage house, individual stock brokers, family members, and coworkers play some role in investment decision.


(ii) Al-Tamimi (2006) who found that motivation from an advisor (e.g., family member opinion) and investors gut feelings on the economy have some positive influence on the behavior of investors. Gill and Biger (2009) who found investors investment expertise and investor consultation of

an advisor positively impact on the investment decision of investors. Kabra et al. (2010) who found that investors awareness, benefits provided by investment, and

investors age positively impact on the decision of investors. Gill et al. (2011) who found that investment expertise of investors, investor consultation of an

advisor, and family positively impact on the investment decision of investors.

Figure 1: Factors Influencing the Real Estate Investment Decision of Investors

Figure 1 shows the factors that influence the real estate investment decision of Indian investors. The overall ranking of the factors that influence the perceived investor behavior to invest in the real estate market is as follows:

(i) IPOI (Beta = 0.328), (ii) IMFA (Beta = 0.252),

(iii) IEOI (Beta = 0.139), and (iv) Age (Beta = 0.130). In conclusion, the investment expertise of investors, the investors motivation from an advisor,

the investment propensity of investors, and the age positively influence the Indian propensity to invest in the real estate market. The findings of this study also show that the investor age improves the investment expertise and the investment propensity of investors (see Table 4).

The findings indicate that the old age investors get motivated more than the middle age investors with the consultation of an advisor. The motivation from an advisor does not impact on the investment behavior and the decision of younger investors. It may be because of the level of education, the generation gap, and the level of financial sources. For example, the younger investors may have lower financial sources than the older investors.

The results show that the older investors do not get motivated by their own expertise and the propensity. Since older investors consult investment advisors, get motivated, and make decisions to invest in the real estate market, investment consultants should be careful to advise older investors to invest in the risky real estate market. The investment advice should be provided based on the risk tolerance of the real estate investors.

4.4. Limitations This study utilized a fixed format, set-questions in the survey , which could have excluded the respondents from providing additional input.

The practical implications of this study are that if Indian investors perceive that:


(i) Their investment expertise is higher, they are more likely to invest in the real estate market.

(ii) Motivation from an advisor is higher, they are more likely to invest in the real estate market.

(iii) Their propensity to invest is higher, they are more likely to invest in the real estate market

4.5. Future Research This study is limited to perceptions and intentions. Because research was done based on the survey questionnaire, respondents did have a chance to add additional information. The future study should consider using other variables such as education, gender, culture, and religion.

References [1] Al-Tamimi, H.A. (2006). Factors influencing individual investor behavior: an empirical study

of UAE financial markets, The Business Review, 5(2), pp. 225-233. [2] Asia Pulse (2012). Indias economic growth to slip to 7% in 2011-12: Senior planner,

Retrieved January 12, 2012 from http://proquest.umi.com/pqdweb?index=2&did=2557268411&SrchMode=1&sid=2&Fmt=3&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1326409260&clientId=29440

[3] Bardhan, A. and C.A. Kroll (2007). Globalization and the real estate industry: Issues, implications, opportunities, pp. 1-36. Retrieved August 5, 2012 from http://web.mit.edu/sis07/www/kroll.pdf

[4] Byrne, K. (2005). How do consumers evaluate risk in financial products?, Journal of Financial Services Marketing, 10(1), pp. 21-37.

[5] Gill, A. and N. Biger (2008). Factors that affect Canadian propensity to direct investment abroad: evidence from the Indian real estate market, The Open Business Journal, 1, pp. 1-9.

[6] Gill, A. and N. Biger (2009). Gender differences and factors that affect stock investment decision of Western Canadian Investors, International Journal of Behavioral Accounting and Finance, 1(2), pp. 135-151.

[7] Gill, A., N. Biger, H. Mand, and S. Gill (2011). Factors that affect mutual fund investment decision of Indian investors, International Journal of Behavioural Accounting and Finance, 2(3/4), pp. 328-345.

[8] Gill, A., S.P. Sharma, H.S. Mand, and N. Mathur (2012). Factors that influence Indian propensity to invest in the real estate market, Journal of Finance and Investment Analysis, 1(2), pp. 137-156.

[9] Kabra, G., P.K. Mishra, and M.K. Dash (2010). Factors influencing investment decision of generations in India: An Econometric Study, Asian journal of Management Research, 2010, pp. 308-326. Retrieved January 1, 2012 from http://www.ipublishing.co.in/ajmrvol1no1/EIJMRS1025.pdf

[10] M2 Presswire (2012). India housing sector to sustain stupendous growth. Retrieved January 2, 2012 from http://proquest.umi.com/pqdweb?index=0&did=2559381671&SrchMode=1&sid=1&Fmt=3&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1326556476&clientId=29440

[11] M2 Presswire (2012). Research and markets: India affordable housing market analysis. Retrieved August 2, 2012 from http://www.researchandmarkets.com/research/q4bml8/india_affordable_h

[12] Nagy, R.A. and R.W. Obenberger (1994). Factors influencing investor behavior, Financial Analysts Journal, 50(40), pp. 63-68.

[13] ONeal, E.S. (2004). Purchase and redemption patterns of US equity mutual funds, Financial Management, 33(1), pp. 63-91.

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