investigating the factors affecting the investment decision in residential development
TRANSCRIPT
INVESTIGATING THE FACTORS AFFECTING THE
INVESTMENT DECISION IN RESIDENTIAL DEVELOPMENT
By
NARANG SOMIL
2007
An Individual Management report presented in part consideration for the degree of
MBA (Finance)
Factors affecting investment decision in residential development 2007
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Acknowledgements
I would like to extend my sincere gratitude to the project supervisor Bob Berry for his
guidance, valuable comments and support throughout this project.
I would also like to thank Andrea Richardson for giving me the company project through
where I got the motivation to do research on this topic. I appreciate all the help extended
by her.
Finally I would like to thank all the survey respondents for expressing their opinions on
the management service and affordable housing obligations which helped me in coming
up with good findings. We hope the conclusions drawn in this report will assist Southreef
Properties Ltd in future or any developer and would be of help to understand the factors
affecting the purchase decision in a Residential Development.
I would like to dedicate this project to my sweet younger brother, who motivated me
throughout the project. I would also like to dedicate this project to my family and Maa.
Finally I would like to take this opportunity to thank my MBA course members, lecturers
and other staff for making this year a truly memorable experience.
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Abstract
The purpose of this project is to provide a rare insight into the motivation behind
residential property investors when looking to purchase an apartment. The factors driving
demand preferences for housing are constantly changing, difficult to measure, and often
deemed to be a complex bundle of attributes. The project attempts to answer the
following questions:
What are the factors affecting the investment decision in a Residential Development? To
identify the significance and weight of such factors in the decision making process.
To what extent the rise in interest rates affect the customer’s decision of different income
profiles in purchasing a residential apartment?
The project is organized as follows. It starts with a brief outline of previous studies and
literature on rational decision making and bounded rationality framework in the
investment decision making. The literature review is followed by the primary data
collection through two questionnaires to examine the significant factors affecting the
investment decision making. The study uses factor analyses to understand the cluster of
factors affecting the investment decision of people of different income profiles and
regression analysis to identify the effect of rise in interest rates on people of different
income groups. The study involves two hypotheses, first relates to the importance of On-
site management and second relates to the effect of interest rates on the investment
decision.
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CONTENTS
Chapter 1: Introduction…………………………………..……..9
1.1 Overview of UK housing system……………….10 Chapter 2: Literature Review……………………………..……13 2.1 Introduction………………………………..…...14 2.2 Bounded Rationality……………………………14 2.3 Behavioral Decision Making……………..……16 2.4 Macro factors…………………………………..18 2.4.1 Growth rate in GDP……….…………..….21 2.4.2 Inflation…………………….…………..…21 2.4.3 Interest rates……………………………...22 2.4.4 Growth in money supply……………….…22 2.4.5 Household spending………………………22 2.5 Micro factors……………………………..…....24 2.5.1 Renting Vs Buying ………..………27 2.6 Conclusions…………………………………….29 Chapter 3: Research Methodology …….………………………...30 3.1 Questionnaire…………………………………...31 3.2 Management Service Questionnaire……………32 3.3 Purchasing Behavior questionnaire…………….33
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3.4 Pilot survey………………………………………….34 Chapter 4: Findings and Discussion………………………………….35 4.1 Introduction…………………………………………..36 4.2 Results of the survey……………………………..….36 4.3 Income group classification……………………….…38 4.4 Factor Analysis……………………………………...38 4.5 Results from Factor analysis………………………..40 4.6 Low Income group………………………………….41 4.7 Middle Income group……………………………….42 4.8 Higher Income group……………………………….44 4.9 On-site and Offsite management……………………45 4.10 Likelihood of purchase with rise in Interest rates…...51 4.11 Regression Analysis…………………………………54 4.12 Assumptions…………………………………………55 4.13 Results of Regression analysis………………………57 Chapter 5: Limitations………………………………………………....58 5.1 Limitations of Postal survey………………………….59 5.2 Limitations of Online survey…………………………59
5.3 Assumptions…………….……………………….……60
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Chapter 6: Conclusion………………………………………………….62 6.1 Further Research……………………………….………63 Chapter 7: References………………………………..…………………65 Chapter 8: Appendix……………………………………………………71
Appendix 1: Management service questionnaire…………....72
Appendix 2: Purchasing Behavior questionnaire……………77
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List of Tables and Figures
Figure 1: Change in Real House prices in UK…………………………12
Figure 2: Macro factors………………………………………………...20
Figure 3: Factors influencing purchase decision……………………….37
Figure 4: Income bracket of the respondents…………………………..38
Figure 5: Graphical Representation of the model……………………...40
Figure 6: Factor analysis for low income group………………………..41
Figure 7: Paired sample t test for factors for low income group…….....42
Figure 8: Factor analysis for Middle income group…………....………43
Figure 9: Paired sample T test for factors for middle income group…..44
Figure 10: Factor analysis for High income group…………………….45
Figure 11: Paired sample t test for factors for High income group……45
Figure 12: Location of management company………………………...46
Figure 13: Breakdown of Factors for On-site management……….......48
Figure 14: Scores given for onsite and offsite management…………..49
Figure 15: Satisfaction levels for Onsite and Offsite management……49
Figure 16: Paired sample t test for Onsite and Offsite management…..50
Figure 17: Number of respondents and average score by respondents..52
Figure 18: Rating given by respondents of different income profiles...52
Figure 19: Likelihood of purchase in case of rise in Interest rates……53
Figure 20: Graphical Representation of the regression model………..56
Figure 21: Results of Regression analysis…………………………….57
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Chapter 1: Introduction
“The key to growth is the introduction of higher dimensions of
consciousness into our awareness”
Lao Tzu
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Introduction:
The foundation of this Individual management project is based on my knowledge
acquired through my group internship project at Southreef Properties Ltd. The objective
of the group project was to understand respondent’s perception about the management
service of current city centre developments and mixed tenure developments and its
impact on the buying behaviour of people. While understanding the customer purchasing
behaviour, I got encouraged to do in-depth research on the weight of various micro and
macro factors influencing the customer’s decision to invest in a Residential Development.
The study aims to look at various micro factors that affect the purchase decision. The
researcher tries to analyse this by conducting factor analyses and paired sample t test on
the compressed factors.
Through this study we also aim to test the following hypotheses:
H0.1: There is no difference between the satisfaction levels of onsite and offsite
management and hence no effect on the purchase decision.
H1.1: The satisfaction levels of onsite and offsite management differ
significantly, hence have a significant effect on the purchase decision.
H0.2: Rise in interest rates does not affect different income groups differently.
H1.2: Rise in interest rates will affect different income groups differently.
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1.1 Overview of UK housing market:
Introduction:
This section aims to provide an insight into UK housing market and makes the reader
aware of the current scenario of the market. Real estate is the world’s biggest business,
accounting for 15% of global gross domestic product (GDP) with assets of US$50 trillion
compared with US$30 trillion in equities (Bloomberg, 2004). More than 50% of the
world’s total assets are invested in direct real estate and securitized real estate investment
vehicles such as real estate investment trusts (REITs) or real estate stocks (Brown and
Matysiak, 2000). Real estate is an integral part of the economy and its returns are linked
to the macro economy and business conditions (Liu and Mei, 1992). There are a large
number of studies done to understand the risk-return performance and pricing of real
estate in the macroeconomic context. However, there is little literature on understanding
the factors affecting or drivers behind the real estate investment decision.
Housing market is an important sector in the UK economy, with a large share of
household wealth and debt held in and against nation’s home in form of investments and
mortgages or loans respectively. In the last decade average overall house prices have
increased by 180% and since 1996 national house prices have risen by 150% after
accounting for general inflation (Paul Samter, 2007). Housing demand continues to grow
faster than supply and with a strong economy prices look set to continue to increase.
Cyclical Trends in Housing Market:
UK has experienced four house price cycles since 1970. The first cycle was caused by the
Barber boom in the early 1970’s. The second cycle, at the end of the 1970’s, was caused
by general inflation which followed the 1979 oil shock. After this period till early 1990s
the economy was dogged by high inflation, high unemployment and volatile growth.
High inflation made housing an attractive investment but with house building being very
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low resulted in house price inflation. The government responded to inflationary
environment by rising interest rates and allowing sterling to appreciate against the US
dollar which caused slump in house prices (See figure 1).
The increase in the volume of credit, deregulation of the financial market and the
growing economy contributed to the late 1980’s boom in house prices. In the late 1980s
there was an inflationary boom in UK in which period house prices peak at over 30% and
general inflation went over 10%. Financial deregulation made mortgage rates more
dependent on interest rates and the reliance on variable rate mortgages made the housing
market very sensitive to macroeconomic variable via fluctuations in debt and
consumption. The volume and share of mortgage debt in GDP reached 53% in 1990
(Wilcox, 1999). But later continuous increase in housing and mortgage cost made
housing less affordable again and caused the slump in early 1990’s. The policy action
taken to reduce inflation led to a recession which intertwined with falling house prices
and the result was that many people lost their homes or faced negative equity resulting in
such circumstances that in some cases outstanding debt on the mortgage exceeded the
resale value of their home (See figure 1).
Late 1990’s witnessed the period of fourth cycle in house prices which was a result of
growing economy, low unemployment and low mortgage rates. House prices increased
by around 13% between 1990 and 1993 and then stabilised at the end of 1995.
Figure 1: Change in Real house prices in UK over the period 1970-1998.
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Source: Council of Mortgage lenders.
Current Housing Market:
Later in the early-mid 1990s, mortgage market experienced a lot of changes and this
resulted into a competitive lending environment. This transformation of mortgage market
with development and increased sophistication of credit risk management tools helped
lenders to identify, position themselves and target the previously underserved parts of the
market. Lenders then started making use of new techniques such as accounting for
individual borrower circumstances in affordability models in determining the amount to
be lent to an individual.
The cost of servicing debt has decreased dramatically since the early 1990s as interest
rates have fallen and competitive pressures have squeezed lenders’ margins. Lenders are
competing more strongly to attract existing mortgage holders and it has become much
easier for customers to switch between lenders to get lower interest rates. Remortgaging
activity accounted for approximately 37% in 2006 in comparison to less than 20% ten
years ago (David Miles, 2004). Fixed rate mortgages have become more popular and
accounted for over 60% of loans extended in 2006 (Miles, 2004).
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.
Chapter 2: Literature Review
“The difficulty of literature is not to write, but to write what you
mean; not to affect your reader, but to affect him precisely as you
wish”
Louis Stevenson
Why Serviced Apartments?
Literature Review
Bounded Rationality
Behavioural Decision making
Macro economic factors affecting the decision
to invest
Micro factors affecting the decision to invest
Conclusions
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2.1 Introduction:
The previous section dealt with the purpose of the study, laying down testable hypothesis
and overview of UK housing market. This chapter attempts to have a closer look at the
written literature. The study first looks at understanding the concept of bounded
rationality and behavioural decision making process. Later it looks at various macro and
micro factors that underpin the decision making process, which affect the decision to
invest in a residential property.
2.2 Bounded Rationality:
Rationality is the core behavioural assumption in the orthodox neoclassical economics.
Principles of maximisation, self-interest and consistent choice commonly underpin this
view of the rational economic factor. The proponents of the theory of rational investor
assume that an individual makes decision on the basis of these principles. It also assumes
that an investor has perfect information of his surroundings and he makes the decisions
with the sole objective of profit maximisation. This theory has been opposed by
neoclassical economic theory which proposes that every investor or every person has
limited access to the information and an individual is bounded by external constraints and
one’s own behaviour. It assumes that not all information is freely available and there are
time and cost constraints on the availability of the information.
Bounded rationality is distinguished from rationality as “the perfect human rationality
that is assumed in classical and neoclassical economic theory and the reality of human
behaviour as it is observed in economic life” (Simon,1992, p.3). Ratcliffe(1972)
understood that the essence of property is human behaviour and the premise that property
discipline is an applied science was argued strongly by Grasskaamp (1991). It has been
argued that bounded rationality perspective could be a useful supplement to the work that
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considers the role of heuristics in affecting real estate decision making in the valuation
profession (Diaz, 1990ab, 1999).
Heuristics in essence, is a cognitive data reduction process. “A heuristic is a cognitive
short-cut that allows for a reduction in the amount of information processed (Harding,
1999, p 350).Cognitive process simplification can be based on data, as well as declarative
and procedural knowledge” (Harding, 1999, p 350).
The behavioural assumption of bounded rationality embodies rejection of perfect
knowledge and optimisation on the part of economic actors, which characterises the
treatment of rationality in the neoclassical economics orthodoxy and instead involves an
element of being limited or bounded (Bruin and Hartle, 2003). The neoclassical condition
of “perfect human rationality” locates constraints in external environment, while Simon’s
concept of bounded rationality views constraints arising from the cognitive limitations of
individuals themselves (Brun and Dupuis,2000). In particular, individuals lack the
capacity to “take account of all the available information, compile exhaustive list of
alternative courses of action, and ascertain the value and probability of each of possible
outcomes” (Hindess,1998, p.69). The bounded rationality perspective shifts the emphasis
from neoclassical “Homo economics” which demonstrates characteristics of optimisation
and consistency based on perfect knowledge, to acknowledge imperfect knowledge and
satisficing behaviour (Susan Flint-Hartle, 2003). It can be seen that in real life individual
investors have limited information and imperfect knowledge while making residential
real estate decisions. These reasons affect their investment decisions and that is why
individuals are not always able to achieve optimality within the context of a dynamic and
complex property investment market. Investors tend to invest in tried investment products
and have preference for products with which they are comfortable. Investors are mindful
of past performance and they try to relate the current circumstances to past and then make
their investment decision.
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2.3 Behavioral Decision making:
As mentioned above, that the behaviour of an individual plays an important part in the
decision making process. Following section discusses that an investor decision making
behaviour does not follow a set of rules but it is subject to decision environment and
individual differences between decision takers.
The literature on investor decision making behaviour focuses on rational, normative
models that treat investor behaviour as highly structured and formalized. It is dominated
by rationalist perspectives and focused on examination of sets of rules that people should
follow, rather than studying that how decisions are actually made (Gallimore, Hansz and
Gray,2000). The limited amount of investigation of property decision making (e.q
Anderson and Settle, 1996; Farragher and Kleinman, 1996; Miles et al., 1989) has been
concerned primarily with the rules and techniques that people adopt with known
normative models of the decision process (Phyrr, 1989; Hartigay and Yu, 1993).
The behavioral decision theory has challenged rationalist approaches and looks more
closely at the decision environment and individual differences between decision takers
(Tversky and Kahneman,1974). Barkham(1996) argues that the property sector is the
most organizationally diverse in the UK economy. Much behavioral research that applies
to property, focuses on the way the individuals act as solitary actors or groups. Corporate
decision making also involves heuristics and biases similar to those displayed by
individuals because of behavioral momentum, fear of regret and an aversion to realizing
sunk costs.
Property decision making is a theory of analysis that attempts to provide a framework in
which investors can make decisions to maximize their wealth. These decisions are
generally characterized as multi-level procedures. Phyrr, 1989 has proposed a ten-step
model involving the generation of alternative ways to fulfill the initial strategy, three
stages of detailed financial feasibility research, closing with management and disposal
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issues. The literature on decision making suggests certain key behaviors exhibited by
investors at environmental, strategic and tactical levels such as the definition of goals and
objectives and a comprehensive search for alternative projects that meet the initial
criteria, formulation of a fully-defined strategy and criteria for selection and assessment
of property generated from environmental information sources. Research has shown that
the availability of information can affect the decision-making processes of investors.
Adair, 1994 found that investment most often occurs when the information is readily
available to the investor about his preferred sector. This would imply that market
imperfections, such as the heterogeneous pattern of market information, cause investors
to move away from normative models of investment behavior.
The factor that affects the property investment behavior is that not all investment is
unintentional. Investors make investment decisions with an intention to hold the property
for either long term or short term. According to study done by Judith Yates, 1996 in
Australia, a significant proportion of individual investors have shown a long term
commitment to investment in illiquid residential property yielding variable short-term but
steady long-term returns. These individual investors have been less responsive to profit
maximizing criteria and have shown a long term commitment while institutional
investors differed from them and were unwilling to invest in illiquid residential property
and preferred profit maximization over long term investment. This is partly the result of
taxation system that favored small scale investors over large-scale investors. The
potential benefits from economies of scale and risk pooling were perceived to be
insufficient to offset the effects of cumulative land taxes which reduced the returns on
residential rental property and this influenced the large-scale investors to have a short-
term objective (Yates, 1996, pp 47-48).
Behavior decision making represents what actually happens when investors make
decisions. It has been shown that investors often fail to consider long-term investment
prospects in term of short-term forecasts. They avoid booking a financial loss when the
investment in showing loss but valuation at the year end make them involve in
investment behavior as if they were investing for only one year (Thaler,1997). Investment
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decision makers have been found to overreact to current information and display
excessive optimism. They treat information received through personal contacts more
important than general market information. Investors tend to relate past incidents or
memories to present in forming their decisions. Even economic forecasters exhibits over-
reaction in responding to recent information by making large forecast changes (Ehrbeck
and Waldmann,1996). Forecasters exhibit wishful thinking when forecasting economic
events as opposed by normative investment model (Olsen, 1997). These factors interact
to reduce an investor’s adherence to a strictly normative investment model and suggest
the importance of behavioral investment model.
2.4 Macro economic factors:
Introduction:
The last section discussed about the bounded rationality framework, importance of
decision environment and differences between individual behaviour in decision making
process. The following section discuses various macro factors that underpin these
behavioural decision making process. On the basis of these factors different individuals
make their investment decisions. An individual perceive these factors differently and then
form one’s decision to invest in a residential property.
There are a lot of demand and supply factors that drive real housing prices. Factors that
influence the demand for housing over longer horizons include growth in household
disposable income, gradual shifts in demographics (such as the relative size of older and
younger generations), permanent features of the tax system that might encourage home
ownership as oppose to other forms of wealth accumulation, and the average level of
interest rates. The availability and cost of land, the cost of construction and investments
in the improvement of the quality of the existing housing stock are longer-term
determinants of housing supply (Tsatsaronis and Zhu, 2004).
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Housing markets also depend on a number of factors that include the length of planning
and construction phases and the inertia of existing land planning schemes. Other factors
affecting the liquidity of housing markets are the transaction costs which include VAT,
stamp and registration duties and inheritance taxes and finally the uncertainty about
future prospects that follows periods of heightened volatility.
Housing investment decisions depend critically on the availability, cost and flexibility of
debt financing. A declining interest rate environment, which keeps servicing costs of
mortgages within the household budget limits imposed by current income, typically
boosts the demand for residential real estate. The residential real estate market has
benefited from the increased reliance on market-based channels of financing. The spread
of credit scoring methods and standardised mortgage contracts, coupled with a growing
appetite for tradable instruments among portfolio institutional investor, has led to the
growing securitization of mortgage assets. Credit institutions that used to hold a large
volume of mortgages on their balance sheets now have the option to sell any unwanted
exposure in the secondary market (Tsatsaronis and Zhu, 2004). Some of the benefits due
to these reduced costs and the improved liquidity of mortgage assets have been passed on
to households in the form of lower transaction fees and more flexible mortgage contract
terms. These flexible mortgage contract terms are in turn driving the demand for
residential housing.
Mortgage accounting practices can influence the creditor’s appetite for exposure to the
market and in turn feedback from house prices influences the availability of finance. The
level of ceilings on the loan-to-value (LTV) ratios and valuation methods of property
determine the ability of banks to lend against the real estate collateral. Methods that base
lending decisions on the current market values tend to increase the sensitivity of credit
availability to market conditions and helps to create a positive momentum in market
demand, valuations that are based on historical levels of prices would tend to lag current
market trends exerting a countercyclical influence on credit availability. The feedback
from property prices to credit growth is strong where there is greater prevalence of
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variable rate mortgages and more market-based property valuation practices for loan
accounting are used.
The earlier part of the section discussed the effect of macro factors on the demand and
supply in housing market. The following section describes the role and effects of macro
factors on the investment behaviour and demand for residential property.
Figure 2: Macro factors
Macro factors
Growth rate in
Money supply
InflationGDP growth
rate
Household
spending
Interest rates
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2.4.1 Growth rate in GDP:
GDP is a measure of all currently produced goods and services valued at market prices
and is thus an aggregated value of all the industries in an economy (Liow, Ibrahim and
Huang, 2005). During periods of high economic growth, there is confidence within the
economy and the individual investors and this stimulates the demand for the commercial
and residential property. Firms seeking expansion would then require more commercial
space and with the confidence in the economy individual investors might invest in
residential property with a view to make profit in future. On the contrary, in periods of
economic downturn investor’s confidence may be dampened resulting into less
investment into residential property which in turn brings down the price of the property.
2.4.2 Inflation:
Inflation rate plays a significant role in real estate investment decision. Inflation is
generally measured by changes in Consumer Price Index (CPI) which measures the retail
prices of a fixed “market basket” of several thousand goods and services purchased by
households (Liow, Ibrahim and Huang, 2005). There are two kinds of inflation, expected
and unexpected inflation rate. Unexpected inflation rate is defined as difference between
actual and the expected rate. Ferson and Harvey (1991) argue that unexpected inflation
could be a source of economic risk and a risk premium would be added for such an
investment which has exposure to unexpected inflation.
A low level of inflation helps decrease speculation in housing markets and reduces house
price volatility. The reason for this is that capital gains under the low inflation may be
lower than user costs of capital, especially if low inflation is sustained by high interest
rates.
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2.4.3 Interest Rates:
Interest rates have effects on both the future cash flow of firms and individuals and
discount rates. Interest rates are considered in calculating the discount rate or cost of
capital to appraise the investment decision. Discount rate is calculated by adding the risk
free rate and the inflation rate. This discount rate is used for property investment
appraisal decisions. Higher interest rate will increase the debt service or mortgage cost
and will affect the investment in the residential property while lower interest rate will
reduce the cost and thus will drive the investments in residential property.
2.4.4 Growth in Money Supply:
Money supply is represented by M2 and is a broad measure of money in an economy.
Increases in money supply will give rise to greater inflation uncertainty and will have an
adverse impact on real estate markets. The excessive growth in money supply may lead
to an inflationary environment and might affect the investments because of higher
discount rates (Liow, Ibrahim and Huang, 2005).
2.4.5 Household spending:
House prices influence household spending in various ways. An increase in house prices
increases wealth and consumers spend more with increase in house prices. Another effect
of increase in house prices is that it raises the collateral available to certain households
and reduces credit constraints placed upon them, allowing them to buy more. Most
importantly, prices and consumption are influenced by common factors and these factors
can change income expectations which might drive an increase or decrease in both house
prices and consumer spending simultaneously rather than one leading the other
(Attansio, Blow, Hamilton and Leicester; Diana Kasparova and Michael White, 2001).
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Previous studies:
According to study done by Anne de Bruin and Susan Flint- Hartle, 2003 in New Zeland,
there are various reasons motivating the property investment decision. Economic reasons
motivating the property investment decision which were highlighted in the study were
return on investment, wealth accumulation through long-term capital gain/growth and
attitude to risk. The availability of cheap mortgages was proposed as another important
factor which increases the chances of long term capital appreciation. According to the
concept “real wealth increase” highlighted in the study by Dupuis(1992) , the smaller the
outlay of the investor’s own equity in the property, the size of the deposit, the greater is
the wealth increase. Hence, “it is even possible to make real wealth gains from nothing
but capacity to pay a mortgage, to the extent that if all of the purchase price of a house
can be borrowed and upon resale of that house all the relative increase goes to the owner”
(Dupuis, 1992). With financial institutions increasingly willing to lend on smaller sized
deposits, the scope for real wealth gain does however increase. Intense competition
among financial institution for share of residential mortgage market ensures ample
availability of funds at competitive interest rates. Exemption of capital gains tax on
housing is another motivating factor influencing property investment decisions.
A study was also done by Anne de Bruin and Susan Flint-Hartle, 2003 in New Zeland, to
understand the implications of low inflation on property investment decisions. In this
questions were asked by way of postal survey and interviews to assess the implications of
low inflation on the decision to invest in a property. The bounded rationality concept sees
constraints arising from the cognitive limitations of individuals themselves, particularly
their lack of ability to embrace all available information. The results suggested that some
lacked the specific knowledge about the impact of low inflation while some had the
knowledge that low inflation erodes the potential for capital gain but this did not alter
their belief that the decision to invest in a property was a sound one. People were rather
more comfortable with the investment which leads to interpret this as satisficing
behaviour. The study also focused on that how portfolio diversification and attitude to
risk influences the decision to invest. A diversified portfolio to spread the risk is a
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standard rule of investment. Respondents were asked to rank their investment categories
in order of importance to them. Investment in property was highlighted as the most
important investment by majority of respondents. There were various motives which
guided the investment in property such as some perceived property to be a safe
investment, some made losses in share market so they started to invest in property and
some acted purely on advice of a financial planner. Therefore these investors may said to
be rational, albeit “boundedly rational”. Low risk and good investment returns were other
reasons for investing in residential property. Finally, optimisation is not the primary
decision making criteria but there are other social and contextual factors in operation
guiding the investment decision. The bounded rationality framework permits recognition
of composite constraints as an integral part of the decision-making environment.
2.5 Micro factors:
The investment decision of an investor is affected by Macro and Micro factors, the above
section dealt with analysing the effect of macro factors, the following section discuses
about the effect of micro factors.
The factors driving demand preferences for housing are constantly changing, difficult to
measure and often deemed to be a complex bundle of attributes (Richard & Reed, 2007).
The benefits of housing ownership can be said as twofold, first to provide shelter for the
entire household, second, as an investment for the owner occupier (Hutchison, 1994).
Other than providing shelter, housing also provides a long-term investment and security
of tenure.
Zangerle (1927) and Henderson (1931) had done pioneering studies on real estate
appraisal and had paid attention to the effects of environmental and building factors such
as landscape views, vegetation, noise, air pollution and building patterns on property
values. The study by Boris A. Portnov, Yakov Odish and Larissa Fleishman, 2003
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proposes that Environmental amenities in a residential neighbourhood (proximity to open
areas, attractive views, etc) encourage homeowners to invest more in the physical
expansion and maintenance of their properties- in building additions, modifications,
renovations, gardening etc. With the passage of time, these investments improve
neighbourhood appearance and as a result the property prices increases. However, if the
environmental conditions are not appealing, the local homeowners see little value in
investing in the maintenance of their properties, assuming that such investment is
unlikely to pay off in the future. Consequently the physical conditions of individual
properties in the neighbourhood deteriorate leading to low housing prices.
There are various factors affecting the property investment decisions. Investors generally
consider a large number of factors before forming their property investment decisions:
• Building characteristics such as number of floors, number of apartments per floor,
overall physical condition of the building and relative condition of the building
relative to the adjacent properties.
• Apartment characteristics such as balcony, parking, storage shed and private
garden.
• Location characteristics such as elevation of the building above the sea level,
landscape views, proximity to open areas, commercial areas and other location
specific amenities and disamenities.
Tom Kauko, 2003 has identified location as a composite effect of a set of locational
attributes in property value formation and property investment behaviour. He identifies
that the negative locational externalities such as social, physical or visual ones and the
positive locational externalities such as services, greenry, status and taxes influence the
investment behaviour and property value formation. Locational externalities such as
proximity to public transport, proximity to city, shops, parks, schools and major roads
gives rise to demand which in turn have a positive effect on property values. Various
studies in past have emphasized the importance of positive externalities of parks, water
parks, greenbelts, access to recreational facilities on the property values and the demand
Factors affecting investment decision in residential development 2007
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for the property. Public services and all the benefits provided helps in improving the
image of the place and hence positive effect on value whereas the higher taxes imposed
have a negative effect on value (Miller, 1982). Kauko,2003 gave the concept of
capitalization theory, which suggests that an environmental improvement or a public
good provided by local government leads to higher house prices in the vicinity, unless
the good causes significant negative externalities and becomes bad.
The study done by Richard Reed and Mills, 2007 came up with an interesting factor that
influences the decision to buy a residential property. Reed’s study highlighted the
importance of Lifecycle factors such as the family formation, marriage or the size of
existing house in the decision to buy a new house. The study also concluded that other
than financial factors, Lifestyle and Socio-economic factors play an important role and
are some of the central drivers behind the decision of first time owner’s purchase.
There are various studies done to investigate the effects of housing rehabilitation
programs on property values (Ding et al., 2000; Simons et al., 1998) which indicate that
residential investment in a new construction and rehabilitation has positive effect on
property values, specifically in low-income neighbourhoods. Sungur and Cgdas (2003)
list such elements as housing system, greenry, cleanliness, quality of construction,
landscape view, location and low traffic level as the components of environmental quality
that influence the user’s satisfaction. For instance, the proximity to arterial roads and
other sources of noise and air pollution may lower the apartments’s price, while beautiful
scenery and the high socio-economic status of the neighbourhood may raise apartment
price (Massey,1985;Yizhak,2003). Recent studies confirm that specific local
externalities, such as proximity to industry and refineries affect property values
negatively (Lentz and Wang, 1998). The neighbourhood environment both social and
physical factors affects the demand for the apartment and its price. Unfavourable
environmental conditions in a neighbourhood may lead to a higher turnover of its housing
stock, and to a gradual drop in the socio-economic status of its residents. Favourable
environmental conditions are likely to lead to a lower turnover and to gradual
Factors affecting investment decision in residential development 2007
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strengthening of the neighbourhood’s population (Boris A. Portnov, Yakov Odish and
Larissa Fleishman, 2003).
In most empirical studies, the Hedonic Price Modeling (HPM) is used to identify and
measure the effect of environmental valuables and building characteristics on property
values. This modeling approach assumes that the monetary value of a dwelling unit or a
residential property depends on the attributes a particular house or apartment may
possess. The attributes are namely physical size the dwelling and environmental
characteristics such as the number of rooms, age, location etc (Becker and Lavee, 1999
and Rosiers, 2002).
2.5.1 Renting Vs Buying:
Investment in housing is a considerable source of wealth for many individuals (Hilland &
Detersen, 1994; Reed, 2001). The actual level of such investment is reflected by both the
price initially paid for the property, and investment in post-occupancy changes and
modifications, such as additional rooms, shaded patios and balconies etc (Etzion,
2001).Making the incorrect housing decision can have an adverse effect on the long-term
wealth of the household and many first-time buyers are fully aware of the inflationary
characteristics associated with the property (Hennessey, 2003).
The decision to purchase a house is no longer an automatic and progressive step in a
household’s lifecycle – house purchasers are now faced with an increasingly complex
“rent Vs buy” decision. Benefits of housing ownership can again be summarized as two
fold, first being to provide shelter for the entire household and second as an investment
for the owner occupier (Hutchinson, 1994). Both buying and renting a house provides
shelter. Investment in house can provide different returns in different regions while in
case of renting a house, the funds saved can be redirected to other investment vehicles.
Both renting and buying have their own pros and cons.
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Interest in private rental market has been revived, this renewed interest can be seen from
a number of perspectives. A decrease in the level of support extended by government for
social rented housing and limiting it to lower-income groups people and reduced demand
for owner occupation has reinforced interest in private rental sector (Boelhower and van
der Heijden, 1994). Increased emphasis on labour flexibility has affected the variability
of incomes. The need for mobility has reduced the demand for home ownership and high
interest rates have restrained access to home ownership (Doling, 1988; Haurin and Gill,
1987). All these factors partly contribute to rise in the rental market.
The demand for rental housing also arose from difficulties and uncertainties of low and
variable wages and from the inability of households to access owner occupation.
Investment in rental housing provides investment opportunities for investors (Hamnett &
Randolph, 1988 p.47). The changing economic and social climate contributes to demand
for rental housing such as people unwilling to take on responsibilities for home
ownership because of long term commitments or because of affordability problems and
people wishing to leave existing households for better employment opportunities. All
these factors contribute to increased demand for rental housing.
There are various factors and advantages associated with homeownership and renting
which influence the purchasing or renting decision. All these factors must be accounted
for to estimate the demand for purchasing or renting. The benefits associated with home
ownership are:
• Eventual debt-free ownership after all mortgages have been paid.
• Ability to alter residence in any manner at the discretion of home owner for home
improvement.
• Intangible sense of pride in home ownership (Heikkila, 2000).
• Hedge against inflation with gradual but overall increase in overall value of the
property (Waxman, 2000).
• Capital appreciation.
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The benefits associated with renting are:
• Minimum capital outlay either weekly or monthly or in whatever agreed form.
• Fixed rent for an agreed period which is not subject to fluctuations in interest
rates.
• No Entry/ Exit fees such as stamp duty, solicitor’s fees, loan application and
processing fees, building inspection fees associated with home ownership.
• Higher level of mobility.
• No Capital maintenance cost.
• No possible negative equity with downturn in housing market.
All the above mentioned factors need to be considered for depending on the need and
desirability of the individual. If one needs the sense of pride of home ownership or capital
appreciation, then one would prefer purchasing the property. If one wants higher level of
mobility and cannot pay huge monetary sum or wants to pay only minimum agreed
amount per month, then one would prefer renting a property.
Conclusions of Literature Review:
It can be inferred from this section that an individual makes decisions which are bounded
by limited access to the information and behavioral differences. The literature discussed
about various macro and micro factors that underpin the behavioral decision making
process and affect the decision to invest in a residential property. The importance of
locational characteristics, building characteristics and social and physical environment
were also discussed. We understood that factors driving demand preferences for housing
are constantly changing and are a complex bundle of attributes.
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Chapter 3: Research Methodology
“Ask a question and you’re a fool for three minutes; do not ask a
question and you’re a fool for the rest of your life”
Chinese Proverb
Methodology
Qualitative
ResearchQuantitative
Research
“Management service
questionnaire”
“Purchasing
Behavior
questionnaire”
Factor Analyses
Paired sample t test
Linear Regression
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3. Research Methodology:
The research in this project is based on Qualitative and Quantitative research. Qualitative
research is done by administering two questionnaires and Quantitative research is done
by conducting factor analyses and Paired Sample t test on the extracted factors. Two
questionnaires were prepared for the group research; few questions were specifically
included in the questionnaires to identify the factors affecting the investment decision in
a residential property
3.1 Questionnaire:
Survey research has become a staple for policy analysts over past several decades and has
always served as a critical data source in the study of issues of interest to sociologists,
demographers, and political scientists (Jagannathan, 2001).
The group prepared two questionnaires to understand the customer perception about the
management service of current developments and mixed tenure developments. We also
looked at the impact of management service on the buying behaviour of people. One
questionnaire focusing on the management service (Appendix1) and the other focusing
on the mixed tenure developments (Appendix2). The group did postal survey for the
management service questionnaire and online survey for the mixed tenure developments
questionnaire.
While designing questionnaires, some questions were specifically designed focusing on
the individual project. These questions were then included in the questionnaires for group
project. The first question was “What are the important matters when considering your
next move or purchase” (Question 8 of Management Service questionnaire and question 5
of purchasing behaviour questionnaire), this question was asked after question 7 “Please
rate the probability of you purchasing a city centre apartment as your next move” which
set the tone for question 8. Question8 was asked to determine the weight of various micro
Factors affecting investment decision in residential development 2007
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and macro factors influencing customer’s decision to purchase a residential apartment.
Question 3 & 4 of “Management service questionnaire” (Appendix1) were asked to
determine the importance of On-site management in a development and its influence on
the purchaser’s decision to invest in a residential property.
Another question “Please rate the probability of you purchasing a city centre apartment as
your next move if interest rates move up by 0.5% to 6.25% from the current rate”
(Question 18 of Management Service questionnaire) was asked to determine the effect of
rise in interest rates on respondents decision to purchase a residential apartment
(Appendix1). Yet another question was asked to determine annual household income of
the respondents (Question 19 of Management service questionnaire and Question 12 of
purchasing behaviour questionnaire). Both these questions were then analysed to research
the effect of rise in interest rates have on the customer’s decision of different income
profiles in purchasing a residential apartment. The researcher combined the data from
both the questionnaires for question on factors affecting the purchase decision. Data was
collected for the factors affecting the purchase of a property from both the questionnaires
Question 8 of Management service questionnaire (Appendix 1) and Question 5 of
Purchasing Behaviour questionnaire (Appendix 2).
3.2 Management service Questionnaire:
A postal survey of residents who live in apartments within the NG1 postcode was
conducted (Appendix 1). Questionnaires were sent to about 800 city centre residents by
the way of post with an enclosed pre-paid envelope addressed to the University. A
covering letter was posted along with survey questionnaire requesting the respondents to
submit the questionnaire no later than 12 noon on Friday, 31 August 2007. To encourage
the respondents to submit the questionnaire on time Southreef Properties announced a
draw in which respondents will have the opportunity to win £250. It was mentioned that
the draw will take place on 10th of September.
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We got 58 responses for this questionnaire a response rate of 8.5%. Targeting city centre
residents was essential to understand as these are the people who are currently staying in
apartments in the city centre developments .These people are of same profile and have
similar characteristics to the target market of Southreef Properties Ltd. These are the
people who might be considering purchasing or renting another apartment so it was
essential to know their view on the management service and what are the factors that
influence their decision in purchasing an apartment in any development.
3.3 Purchasing Behaviour questionnaire:
An online survey was done to understand how mixed tenure residential developments are
perceived and what influences customers decision to purchase or rent. Online survey was
conducted to understand the effects of affordable housing on the development. Question
5 of this questionnaire focused on identifying the factors affecting the decision to invest
in a residential property (Appendix 2).
Online survey was conducted by posting the questionnaire on the web server and an e-
mail was sent out to all the professors and faculties of University of Nottingham
requesting them to fill it. This could be a good sample as these people have similar
profile and characteristics of the target market. The questionnaire was sent to about
approximately 600 staff members from different departments of University of
Nottingham. Online survey was also done by sending the questionnaires to the MBA
cohort as these could be people who might be living in an apartment and would consider
in future to buy or rent an apartment in a mixed use or mixed tenure development.
We got in total 66 responses to this questionnaire, a response rate of 11%. Here in this
questionnaire, we could not include the question that “Please rate the probability of you
buying or renting an apartment if the interest rates increase by 0.5% from the current
rates” because this would have effect on the focus of the questionnaire. So to not to affect
the quality of the questionnaire, this question was not included.
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3.4 Pilot Survey:
A pilot survey of the ‘Management service questionnaire’ was conducted within the
MBA cohort at The University of Nottingham. The purpose of the survey was to identify
any difficulties in understanding the questions posed in the questionnaire. The pilot
survey was done by e-mailing the questionnaire to the MBA cohort and asking for their
comments on the interpretation of the questions. Emphasis was given on the feedback
given by the MBA cohort coming from varied experience and backgrounds. The
questionnaire was also shown to Bob Berry, my supervisor, for his comments on the
questionnaire. His comments on the questionnaire were very helpful in designing the
questions for my individual project. The ‘Management service questionnaire’ was
amended quiet a number of times which improved the quality of the questionnaire.
.
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Chapter 4: Findings and Discussion
“The person who sends out positive thoughts activates the
world around him positively and draws back to himself
positive results”
Norman Vincent Peale
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4. Findings and Discussion:
4.1 Introduction:
The questionnaire aimed to investigate the factors affecting the purchase or investment
decision in a Residential Development. It also focused on identifying the rise of interest
rates on the purchase decision. The researcher used factor analysis to compress the
factors affecting the purchase decision and has related it to different income group
respondents. The researcher has conducted regression analysis to find the effect of rise in
interest rates on the purchase decision and also conducted T test the importance of On-
site management.
4.2 Results of the survey:
Question 8 of Management Service questionnaire and question 5 of Purchasing behaviour
questionnaire was asked to determine that what are the significant factors influencing the
purchasing or renting decision of customers in general. Scores were given to each factor
from 5 to 1 depending on the importance of the factor to the customer in making their
purchase decision. About 129 respondents rated these factors on a scale of 1 to 5. Then
these total scores were divided by the number of respondents to report average scores for
each factor. Here the maximum score and minimum score for any factor is 5 and 1
respectively. The findings suggest that Location (4.60) was cited as the most influential
factor, followed by value for money (4.38), Size of Living Accommodation (4.22).
Access to car parking (4.13) and Number of bedrooms (4.04) were other important
influencing factors. On-site management was rated with the score of 3.95 implying that it
was an important factor but only after the primary factors such as location and value for
money. So it can be inferred that On-site management is important but only after basic
criteria of the location and size of the dwelling are fulfilled. (See figure 3).
Factors affecting investment decision in residential development 2007
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Access to public transport (3.53) and On-site security (3.64) were other important factors.
Developers should consider all these factors into account to improve the perception and
services offered in their development to distuinguish themselves from other
developments.
Figure 3: Factors influencing purchase decision
Important factors influencing purchase decission
3.323.53
4.60
3.30
4.044.22
3.95
3.29
4.38
3.64
4.13
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Developers reputation
Access to public
Location
Close to recreation
Number of bed
Size of living
On-site manage
Sense of com
Value for
On-site security
Access to car
Criterion
Avera
ge s
core
out of 5
Question 19 of Management Service questionnaire and question 13 of Purchasing
behaviour questionnaire was asked to determine the annual household income of the
respondents to relate that what factors affect the people of different income groups.
Findings suggest that majority of respondents (35%) were from higher income group.
(See figure 4).
Factors affecting investment decision in residential development 2007
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Figure 4: Income bracket of the respondents.
4.3 Income group classification:
The researcher looked at the Annual Survey of Hours and Earnings to determine the
average UK salary and for the purpose of classifying respondents in different income
groups. According to ASHE 2006 survey results, the median weekly pay for full time
employees in UK grew by 3.7% in April 2006 to reach 447 pounds. So we could classify
low income group in £0-£20,000, middle income group within £20,000-£40,000 and
£40,000 and over within higher income group (Source: Annual Survey of Hours and
Earnings, 2006).
4.4 Factor analysis:
Once we collected responses from Question 8 (Factors) &19 (Household Income) of
Management service questionnaire (Appendix 1) and Question 5 (Factors) & 12
(Household Income) of Purchasing Behaviour questionnaire (Appendix 2). We used
factor analysis to compress the data and entangle the complex linear relationships
What is the income bracket of repondent
10.34%
17.24%
18.97%10.34%
8.62%
34.48%
10,000-19,000
20,000-29,999
30,000-39,999
40,000-49,999
50,000-59,999
60,000+
Factors affecting investment decision in residential development 2007
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between the data, since the questionnaire had 11 criterions that could affect the purchase
decision of respondents therefore in order to facilitate the analysis of data, the study uses
factor analysis to classify data based on Co- variance and Correlation. This approach
would facilitate prospective developers to better understand the relationships between set
of variables and develop applicable strategies to fulfill the needs of the purchasers. The
researcher understands that different income group people have different needs therefore
the study uses factor analysis for three income groups:
• Low income group (£0 - £20,000)
• Middle income group (£20,000 - £40,000)
• High income group (£40,000 and above)
The researcher used factor analysis because of following:
• Parsimony or Data Reduction: Factor analysis is used to reduce mass data into
condensed and more comprehendible formant.
• Structure in data: Factor analysis is used to uncover the basic structure in data
analysis. It condenses complex data into more comprehensible factors on the basis
on underlying structure of data.
• Hypothesis testing: Factor analysis helps test hypothesis as it classifies clusters of
data under one factor it becomes easier for the researcher to identify factors that
are more important than others.
• Data Transformation: Factor analysis is used to transform data especially in case
of financial research, as a lot of information is highly co related which gives rise
to the problems of multicolinearity in Data. Factor analysis technique eradicates
this problem and transforms data without loosing relevant information.
Besides this factor analysis is also used for mapping i.e. systematic attempt to chart major
empirical concepts, sources of variation. The researcher used factor analysis to help the
developer target and position the project rightly, as mentioned that earlier different
income groups have different needs. This would help developers to identify the target
Factors affecting investment decision in residential development 2007
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segment and for the success of such project the developer would need to concentrate on
the factors that have a highest score when compared to other factors.
Figure 5: Graphical Representation of the model
Graphical representation of the model
Divide the respondents
based on 3 income
groups: Low income,
Middle income and
high income group.
Conduct individual t
tests to evaluate the
importance of the
factors indivisually
Conduct factor
analysis based on the
responses given by
each income group
Conduct paired
sample t test to
ensure that the
important factors are
statistically different
from others
4.5 Results from factor analysis:
The study conducts factor analysis based on income groups; we would first look at the
results of low-income group that consists of respondents in the income bracket of £0-
20,000. The Kaiser-Meyer-Olkin (KMO) measure of sample adequacy is 0.23, and any
value between 0.3-0.7 says that the sample is adequate to run a factor analysis. The
Bartlett’s test of Sphericity, that measures for the adequacy of sample and looks at the
correlation among the components to analyze if the data set needs factor analysis. The
Bartlett’s test of Sphericity is measured in terms of Chi-square, in our case the Chi-square
statistics is 84.178 at 55 degrees of freedom this says that there was significant co relation
Factors affecting investment decision in residential development 2007
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in the data and the data warrants factor analysis. The determinant for the co variance
matrix is .0065 that is higher than the significant value of 0.0001. In case of lower
income groups factor analysis compressed the components into 3 factors:
Figure 6: Factor analysis for low income group
4.6 Low Income group:
Once factor analysis compressed the data into 3 factors we ran t tests (the scores of which
are reported in the diagram above) to determine which of these factor proves to be the
most significant factor (See Figure 6). The researcher reckons that factor 1 that has a t
score of 30.63 is the most important factor for this income group. For lower income
group Access to public transport, Number of bedrooms, Location and Value for Money
cluster are the important factors. In order to find the importance of the factor in relation
with the other factors the researcher also conducted a paired sample t test for factor 1 and
Factors affecting investment decision in residential development 2007
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factor 3 in this case, as both these factors are relatively important factors. The results of
the paired sample t tests are listed below:
Figure 7: Paired sample t test for factors for low income group
Name Factor 1 Factor 3
Mean 4.15 3.38
Standard deviation 0.97 1.12
Paired sample score 2.56 2.56
T score 30.63 21.08
We observe here that the paired sample t score when comparing factor 1 and factor 3 is
2.56 which is higher than the cut off level of +/-1.96 this means that factor 1 is
statistically more significant than factor 3 and can act as a Unique selling proposition if a
developer wants to target low income groups.
4.7 Middle-income group:
The middle-income group in our sample consists of respondents that have income
between £20,000-40,000. The Kaiser-Meyer-Olkin (KMO) measure of sample adequacy
is .575 that is much higher than what the study has in lower income group but still above
the level of 0.50 and says that the sample is adequate to conduct a factor analysis. The
Bartlett’s test of Sphericity that measures for the adequacy of sample and looks at the
correlation among the components to see the need for factor analysis. As said earlier this
test is measured in terms of Chi-square in this case Chi-square is 72.08 at 55 degrees of
freedom. This says that our test is significant at .05 level of significance, the determinants
for Co-variance is 0.080 that is higher than the .0001 cut off level. The compressed
factors and its components are presented below:
Factors affecting investment decision in residential development 2007
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Figure 8: Factor analysis for Middle income group.
The test compressed the data into 4 factors (which are listed above with their respective t
scores) it is evident from above chart that factor 1 i.e. Location, Number of beds, Size of
living and Value for money are the factors that are most important to middle income
group people (See figure 8). In order to make sure that factor 1 can act as a differentiating
factor if one wants to target the middle income group the study conducts paired sample t
test (between factor 1 and factor 2 the next strongest factor in terms of t scores). The
statistics for the paired sample t test are reported below:
Figure 9: Paired sample T test for factors for middle income group.
Factors affecting investment decision in residential development 2007
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Name Factor 1 Factor 2
Mean 4.39 3.58
Standard deviation .88 1.26
Paired sample score 6.36 6.36
T score 57.71 32.92
The results of the paired sample t tests suggest that factor 1 is statistically more
significant than factor 2 as the t score is 6.36, that is above the critical t level of +/-1.96.
The researcher feels that factor 1 can act, as a unique selling proposition if one wants to
target the middle income group, laying emphasis on the services that fall under factor 1
can help a developer better position their houses/apartments in the market.
4.8 Higher income group:
The higher income group in our sample consists of respondents that have income of
£40,000 and over. The Kaiser-Meyer-Olkin (KMO) measure of sample adequacy is .569
that says that the sample size is adequate to conduct a factor analysis. The Bartlett’s test
of Sphericity is 150.96 at 55 degrees of freedom that says that the test is statistically
significant at 0.05 level of significance. The covariance matrix determinant is .060, which
is higher than the critical level of .0001. This means that the sample size is adequate and
the sample warrants a factor analysis. The compressed factors and its components are
represented below in figure 10.
Figure 10: Factor analysis for Higher income group
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The test compressed the components into 4 factors that are listed above with their
respective t scores. We find that factor 1 that comprises of Sense of community, location,
Number of bedrooms and value for money is relatively more important than the other 3
factors. In order to see that factor 1 can act as a differentiating factor the researcher also
looks at paired sample t test for factor 1 and factor 3 to ensure that factor 1 is statistically
more significant than factor 3. The results of the paired sample t test are given in figure
11 below:
Figure 11: Paired sample t test for factors for High income group.
Name Factor 1 Factor 3
Mean 4.10 3.54
Standard deviation .99 1.13
Paired sample score 5.39 5.39
T score 63.70 47.86
Factors affecting investment decision in residential development 2007
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We can see that factor 1 is statistically more significant than factor 3 with a t score of
5.39 that is higher than +/-1.96. The researcher feels that factor 1 can act, as a unique
selling proportion in terms of satisfaction level if one wants to target the higher income
group.
4.9 Onsite and off site management as an influencing factor in
purchase decision:
The study also looks at the comparison between onsite and offsite management as an
influencing factor in purchase decision (Question 3&4 of Management service
questionnaire). The questionnaires asked the respondents to rate their apartment
management based on 4 criterions depending on how satisfied or dissatisfied they were
with those aspects of their management. The respondents were also asked to state
whether their apartment management was onsite or offsite (Question 2 of Questionnaire
1).The figure 12 below shows the responses as rated by the respondents.
Figure 12: Location of management company.
Where is your Management Company located
19%
14%
7%
21%
34%
5%
On-site
Nottingham
Outskirts
East Midlands
IN UK
Don’t know
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As one can see from the above graph that 19% of the respondents reported that they have
on site management in their apartments, the rest of the respondents had offsite
management of which 14% reported that their management company was located in UK,
7% said that their management company was located in the outskirts of the city, 5%
reported that they had no information on where there management company was located
while 21% said that their management company was located in east-midlands.
The researcher feels that the respondents would rate on site management higher than off
site management on all the 4 criterions. The study aims to test the following hypothesis
about onsite and off site management:
H0: There is no difference between the satisfaction levels of onsite and offsite
management and hence no effect on the purchase decision.
H1: The satisfaction levels of onsite and offsite management differ
significantly, hence have a significant effect on the purchase decision.
Figure 13: Breakdown of Factors for On-site management.
The respondents were asked to rate their satisfaction level on the following criterion:
Factors affecting investment decision in residential development 2007
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Management
company
Satisfaction
Cleanliness
General
maintenance
Handling of
request and
complains
Value for
money
The respondents were asked to rate their satisfaction on the following scale:
• Satisfied
• Neither satisfied nor dissatisfied
• Dissatisfied
In order to quantify these responses we use the following scale:
Satisfied Neither satisfied nor Dissatisfied Dissatisfied
10 5 2
Factors affecting investment decision in residential development 2007
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Figure 14: Scores given for onsite and offsite management.
The matrix below shows the average scores given by onsite and off site management:
According to our sample study, the respondents rated On-site management higher on
almost all the 4 criterions especially on Handling of request and complaints and Value for
money (See figure 14 and 15). The study now aims to explore that are these differences
statistically different the researcher therefore conducts paired sample t tests between all
the 4 criterions of onsite and off site management. The graph below depicts the
satisfaction levels of onsite and offsite management.
Figure 15: Satisfaction levels for Onsite and Offsite management.
Satisfaction levels in case of Onsite and off site
management
6.93
5.866.21 6.29
4.774.30
3.553.02
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Cleanliness Genral
maintenance
Handling of
request and
compains
Value for
money
Criterions
Average satifaction score out of
10
Onsite
management
Offsite
management
Cleanliness Genral maintenance Handling of request and compainsValue for money
Onsite management 6.93 5.86 6.21 6.29
Offsite management 4.77 4.30 3.55 3.02
Factors affecting investment decision in residential development 2007
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The study now aims to explore that are these differences statistically different. The
researcher therefore conducts paired sample t tests between all the 4 criterions of onsite
and off site management. The results of the paired sample t tests are presented in the table
below: (See figure16).
Figure 16: Paired sample t test for Onsite and Offsite management.
Cleanliness General
Maintenance
Handling of
requests and
complains
Value for
Money
Onsite Management 9.04 8.02 10.82 6.64
Off site
Management
6.48 5.99 8.41 4.90
Paired (onsite and
offsite
Management)
1.69 2.11 4.06 3.44
The t values for all the criterions in case of onsite management are higher than those of
off site management. In order to see that the satisfaction level in case of onsite
management is higher than off site management the researcher conducts paired sample t
tests, the results of which are also attached in the above table (See figure16). We can
observe although the satisfaction levels in cleanliness for onsite management are higher
than those for off site management, the difference however is not statistically significant
as the t values are lower than the 1.96 cut off level. The satisfaction levels in case of
General maintenance, Handling of requests and complains and value for money are
higher than those of offsite management and the difference is statistically significant with
t statistics of 2.11, 4.06 and 3.44 respectively and all of these are higher than the critical t
value of 1.96. Therefore we reject the null hypothesis at 0.5 level of significance (See
figure 16).
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The researcher feels that On-site management can act as a significant differentiating
factor and given enough awareness can also affect the purchase decision of people
looking for apartments.
4.10 Likelihood of purchase in case of rise in interest rates:
One of the questionnaires aimed to gather opinion of people about the affect of purchase
decision if there were a rise in interest rates (Question 18 & 19 of Management service
questionnaire, Appendix1). This was to know that to what effect the rise of interest rates
have on their purchase decision. The researcher has divided the respondents into 3
categories based on annual income:
• Low income group (£0-20,000)
• Middle income group (£20,000-£40,000)
• High income group (£40,000 and above)
The researcher feels that respondents in the high-income group would be willing to
purchase a property despite rise in interest rates. Looking at the current scenario and the
effortless increase in the real estate market the high-income group respondents would still
be willing to purchase properties.
The response to this question was consistent with the hypothesis laid above. The
respondents were asked to rate their willingness to purchase on a scale of 1-5 where:
• 1= Highly Unlikely
• 2= Unlikely
• 3= Neither likely not unlikely
• 4= Likely
• 5= Highly likely
The average ratings of the respondents are presented in the figure 17 below:
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Figure 17: Number of respondents and average score given by respondents.
Low Income Middle Income High Income
Number of
respondents
6 21 30
Average score given
by Respondents
2.17 2.29 2.97
The average scores given by respondents in the Low-income group is 2.17 which is
skewed towards unlikely, even the middle income groups decision seems to be affected
by the rising interest rates. However as predicted the higher income groups willingness to
purchase seems to be unaffected by rising interest rates and the score of 2.97 is skewed
towards 3 which, this says that their decision will be unaffected by the rising interest
rates.
The matrix below shows the responses given by each of the group:
Figure 18: Rating given by respondents of different income profiles.
Highly likelyLikely Neither likely nor unlikelyUnlikely Highly unlikely
Low income 0 0 3 1 2
Middle income 0 2 8 5 6
High income 7 6 2 9 6
There were 7 respondents in case of high-income group who expressed their willingness
to purchase as highly likely despite of rising interest rates and 6 of the respondents said
that they would be likely to purchase despite the rising interest rates. In case of lower
income group 3 of the 6 respondents were undecided on their purchase decision if the
interest rates rose. Due to these 3 respondents the average score of low-income group
rose significantly, if we exclude these 3 cases the average score of low-income group as
rated by respondents would fall to 1.33 that says that they would be unlikely to purchase
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in case of rising interest rates. Similarly in case of middle income group 8 respondents
are undecided about their purchase decision if we remove these respondents the average
score of middle income group respondents would fall to as low as 1.84 in case of high
income group intensity of the affect on score is less and the score would be reduced
marginally to 2.96.
The figure 19 below shows a graphical representation of the number of respondents and
their willingness:
Figure 19: Likelihood of purchase in case of rise in Interest rates.
Income wise likelihood of purchase
0 0
50
17
33
0
10
38
24
29
2320
7
30
20
0
10
20
30
40
50
60
Highly
likely
Likely Neither
likely nor
Unlikely Highly
unlikely
Likelihood of purchase
Percentage of respondents
Low income
Middle income
High income
One can observe that high-income group respondents have expressed their willingness to
purchase despite the rising interest rates. The researcher also wanted to conduct a t test to
find the significance of responses but due to the inadequacy in sample size such a test
could not be conducted. However the study infers from the graphs and analysis above
that purchase decisions of high-income group are less likely to be affected by rising
Factors affecting investment decision in residential development 2007
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interest rates. In order to identify the effect of interest rates the researcher conducted
regression analysis.
4.11 Regression analysis
In order to test the hypothesis of impact of rise in interest rates on different income
groups we conduct a linear regression analysis. The idea here is that if rise in interest
rates have a differential impact on different income groups the intercept (alpha) of the
regression will be higher for high income group than middle income group. The study
uses linear regression for the following reasons:
• To establish a relationship between dependent variable (likelihood of purchase)
and independent variable (dummy variable).
• The dependent variable is random in nature hence the regression would aim to
establish a relation between income group and the likelihood (willingness to
purchase and income groups).
• The study uses the following regression equation to predict the dependent
variable:
Yi = α+ β (D) +i
Where:
Yi= Dependent variable
α = Intercept
β= Beta
D= Dummy variable
i= Error term.
• The dummy variable is set to 0 if the income group in question is a low income
group and it is set to 1 if the income group is middle or high income group.
• Dummy variables are useful as they enable us to use a single regression equation
for multiple groups.
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• In order to make the result of regression comparable the researcher conducts two
such regressions based on middle income and high income group. The study then
compares the intercepts of both the regressions.
4.12 Assumptions:
The study makes following assumptions about the data in order to conduct linear
regression:
• The study assumes a linear relation between the dependent and the independent
variables.
• The independent variable is categorical or quantifiable in nature.
• There is no perfect co linearity between predictor variables.
• The residual terms are uncorrelated that is they are independent terms and has no
auto correlation.
• The residuals in the model are random and normally distributed with a mean of
zero (that is they are random).
The figure 20 below shows graphical representation of the model:
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Figure 20: Graphical Representation of the model
Income group classification:
Based on the questionnaires the researcher has classified the income groups into 3
categories:
1. Low income group
2. Middle income group
3. High income group
The Low income group comprises of respondents in income group of 0-£20,000. The
middle income group comprises of respondents in the income group of £20,000-£40,000
Graphical representation of model
Distribute income
groups as high
income, middle
income and low
income
Conduct regression
1 for middle and low
income group and
set the dummy 1 for
middle income
Conduct regression
2 for low income and
high income group
set dummy 1 for high
income
Compare the
intercepts of both
regressions
If intercept of high
income group is
higher than middle
income group then
alter. Is true
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this group inculcated the average UK salary that is £ 25,000. The high income group
consists of respondents in the income bracket of £40,000 and above.
4.13 Results of Regression analyses:
The study looks at testing the following hypothesis:
H0 = Rise in interest rates do not affect different income groups differently
H1 = Rise in interest rates will affect different income groups differently.
The results of regression show that there is a deferential impact of interest rates on
different income groups. The following table depicts the results of regression analysis:
Figure 21: Results of Linear Regression:
Type R2 Alpha (α) T values
Middle income group .026 2.0 4.44
High income group .088 2.167 3.90
The table(See figure 21) above summarises the statistics of regressions carried out in
order to test the hypothesis. It is evident from the table that high income group
respondents are less likely to change their purchase decision in case of rising interest
rates. The intercept in case of high income group is 2.167 and in case of middle income
group is 2.00 the t value for intercept of middle income group is higher that the t vale for
high income group however both the values are statistically significant and above the cut
off level of 1.96. The table also shows that R2 in both the cases is low, but this doesn’t
affect the result of the studies as the method deployed in this case is more concerned with
looking at the values of α more than any thing else.
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Chapter 5: Limitations
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5. Limitations:
The research in this project specifically aimed at the city centre residents of Nottingham
for Management Service questionnaire and staff of University of Nottingham for the
Purchasing Behavior questionnaire. The research aimed at identifying the factors
affecting the purchase decisions and the effect of rise in interest rates on such decisions.
5.1 Limitations of the Postal survey:
In this research there were certain limitations which could have affected the outcome of
certain results. The group did postal survey of city centre apartment residents living in
Nottingham. The survey didn’t include people living elsewhere in Nottingham and people
living in houses, who might also be considering purchasing an apartment in future. The
postal survey was conducted during summers, when most of the people were on vacations
which could have affected the response rate.
5.2 Limitations of Online Survey:
The limitation of this questionnaire was that it focused more on the effects of affordable
housing on the development. The group received 66 responses for this questionnaire, a
response rate of 11% for about 600 respondents. To not to affect the focus of the
questionnaire the question on interest rate wasn’t included in this questionnaire. So the
data and responses from this questionnaire could not be used to analyze the effect of rise
in interest rates on purchase decision of people of different income profiles. The
questionnaire was complex and lengthy which may have altered the customers’ responses
by finding them difficult if not impossible to understand. The online survey was
conducted during summers, when most of the people are on vacations and this might
have affected the response rate. Another limitation was that we had a moderate response
rate and subsequently a small data set for our analysis due to the fact that mixed income
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housing is a sensitive matter and not many people would like to express their comments
on such a sensitive issue.
5.3 Assumptions:
The researcher has combined responses of both the questionnaires for the study to have a
large data set in order to produce better results. Data was collected for the factors
affecting the purchase of a property from both the questionnaires Question 8&19 of
Management service questionnaire (Appendix 1) and Question 5&12 of Purchasing
Behaviour questionnaire (Appendix 2). This was done to understand the factors that are
more important to people of Low, Middle and Higher Income group.
Another assumption is that purchasing behaviour of people in Nottingham is akin to the
purchasing behaviour of people all over UK. Factors affecting the decision to invest for
people in Nottingham are assumed to be similar to factors affecting the decision of people
all over UK.
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Chapter 6: Conclusions
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6. Conclusion:
This research identified, prioritized and categorized factors affecting the decision to
invest in a residential property of different income groups. To facilitate the analysis of
data, the study uses factor analysis to classify data based on Co- variance and Correlation
and compressed the number of factors into clusters. These clusters of factors were then
related to various income groups, as different income group people have different needs.
It can be inferred from the study that factors such as Access to public transport, Number
of bedrooms, Location and Value for Money were highly rated by lower income group
people. Location, Number of bedrooms, Size of living accommodation and Value for
money were the factors that were highly valued by middle income group people. Higher
income group people rated number of bedrooms, sense of community, location and value
for money as the most important factors. So for a developer like Southreef properties,
which is targeting at the higher end of the market should consider all the factors which
were rated highly by middle income and higher income group people. A developer should
keep in mind all these factors i.e. large number of bedrooms, location, value for money,
Size of living accommodation, Sense of community and Value for money and try to cater
these services better in order to target and position its development successfully.
The research also focused on to determine the satisfaction levels of On-site and Off-site
management with respect to services such as General maintenance, Handling of requests,
complaints and value for money. After conducting quantitative analyses this study
accepts the alternative hypotheses and concludes that satisfaction level in case of On-site
management are statistically higher than those of Offsite management. The researcher
feels that including On-site management with high levels of service commitments would
act as a differentiating factor and contribute to the future valued of the development. So a
developer, like Southreef Properties should include On-site management in their
development.
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The researcher also conducted a study to determine the extent of effect of 0.5% rise in
interest rates on the purchase decision of various income groups. According to the
research, Low-income group and middle income group people seem to be affected by the
rise in interest rates. The research confirmed with the help of regression analyses that
respondents in the high-income group would be generally be willing to purchase a
property despite a rise in interest rates. So the study accepts the alternative hypotheses,
that high income group people are less likely to be affected by 0.5% rise in interest rates
in their purchase decision.
The conclusions drawn from the study should be helpful to Southreef Properties Ltd or
for any other development. These factors should be considered by the developer for the
success of the development.
6.1 Further Research:
The researcher has implemented basic statistical tools and questionnaires to analyze the
important factors affecting the purchase decision. But there are avenues open for further
research in terms of using focused questionnaires for the primary research on
investigating the micro factors affecting the investment decision of the respondents.
There is scope for a focused study with a larger sample and more advanced techniques
could be used to produce better results.
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Chapter 7: References
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Chapter 8: Appendix
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Appendix1:
Management Service Questionnaire
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MANAGEMENT SERVICE 1. Is there a service charge for the upkeep of communal parts of the property? Yes No 2. Is your management company located …? On-site In the Nottingham City Centre In Nottingham, but outside the City Centre In the East Midlands Elsewhere in the UK Don’t know ANSWER THIS QUESTION IF YOU HAVE AN ON-SITE MANAGEMENT/CONCIERGE
SERVICE. 3. Thinking about the communal areas of your property, how satisfied are you with the
management in respect of: Very Fairly Not There are no Satisfied satisfied satisfied communal
areas Cleanliness General maintenance Handling of requests/complaints Value for money ANSWER THIS QUESTION IF YOU DO NOT HAVE AN ON-SITE MANAGEMENT/CONCIERGE
SERVICE. 4. Thinking about the communal areas of your property, how satisfied are you with the
management in respect of: Very Fairly Not There are
no Satisfied satisfied satisfied communal
areas Cleanliness General maintenance Handling of requests/complaints Value for money 5. How would you rate the importance of a management service within apartment blocks? High Importance Medium Importance Low Importance 6. Which area of the management service would you most like to see improved? Please tick one only
Cleanliness General maintenance Handling of requests complaints Value for money Other (please state) ___________________________________________________________
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YOUR FUTURE PLANS 7. Please rate the probability of you purchasing a city centre apartment as your next move? Please tick one only Highly likely Likely Neither likely Unlikely Highly Unlikely Nor unlikely 8. What are the important matters when considering your next move or purchase?
Please tick the appropriate box, where 1 = not at all important and 5 = extremely important. 1 2 3 4 5 Developer’s reputation Good access to public transport Location
Close to recreation and leisure facilities Number of bedrooms Size of living accommodation On-site-management facilities Strong sense of community among neighbours Value for money Good on-site security Access to car parking Other (Please state) _______________________________________________________
9. Which other services are you likely to use in an apartment complex, if made available at a reasonable charge?
Highly Likely Neither likely Unlikely Highly Likely or Unlikely Unlikely Apartment cleaning Car valeting Laundry Ironing Key holding** Personal Shopping Gym Contract parking Storage facilities Car Hire Other (please state) _______________________________________________________ **Taking delivery of groceries, watering plants whilst on holiday, etc. 10. Are you considering moving or buying another property within the next 2 years? Yes No Don’t know If your answer is yes go to question No 11. 11. If purchasing an apartment, will you purchase the property …? As an individual As an investor As a shared owner with a partner
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As a shared owner with friend(s) As a shared owner with a housing association or similar association
PERSONAL PROFILE 12. Please tick your relevant age band? 18 – 24 25 – 34 35 – 53 35 – 45 45 – 55 55 plus 13. Are you currently working either full-time or part-time? (This includes any part-time working by students and those on training courses.) No Yes 14. Which of the following best describes the type of work you have in your main job? Please tick one only Senior management or professional Intermediate management, administrative or professional Supervisor, clerical, junior management, administrative or professional Manual worker (with industry qualifications) Manual worker (without industry qualifications) Self-employed 15. How long have you lived at your current address?
a) Less than a year b) Between 1 and 2 years c) Between 2 and 5 years d) 5 years plus
16. How many people live in your household? Number of adults Number of children 17. How many bedrooms do you have? 1 2 3 Other please state _______ 18. Please rate the probability of you purchasing a city centre apartment as your next move if interest rates move up to 6% from the current rate? Please tick one only
Highly Likely Neither likely Unlikely Highly Likely or Unlikely Unlikely 19. What is your household annual income (before tax deductions)? £10,000 - £19,999 £40,000 - £49,999 £20,000 - £29,999 £50,000 - £59,999 £30,000 - £39,999 £60,000 or over
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THE UNIVERSITY OF NOTTINGHAM WILL DETACH THIS PART OF THE FORM WHEN RECEIVED IN ORDER THAT THE QUESTIONNAIRES REMAIN ANONYMOUS. FULLY COMPLETED QUESTIONNAIRES WILL BE PLACED IN THE DRAW AND THE WINNER TO RECEIVE £250 CASH. NAME : ADDRESS : TELEPHONE NO. : E-MAIL :
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Appendix 2:
A sample response to:
“Purchasing Behaviour
Questionnaire”
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We are working with the Nottingham University Business School on a research project to understand how
mixed tenure residential developments are perceived and what influences your decision to purchase or rent.
Mixed tenure developments include residences that are available to purchase outright, with a mortgage or on a shared ownership basis and may also include residences available to rent privately or on an affordable basis (i.e. through a Housing Association or Local Council). We would ask that you complete the questionnaire and return it to us as soon as possible. We can assure you that all information received will be treated as strictly confidential. THANK YOU FOR TAKING THE TIME TO COMPLETE THIS SURVEY. Section A – Purchasing and Renting Profile & Preferences 1. Please rate the probability of you purchasing a property in the next 2 years. Please tick one only
Highly
Likely Likely
Neither unlikely
nor likely Unlikely
Highly
Unlikely
Go to question 3. 2. Please rate the probability of you renting a property in the next 2 years. Please tick one only
Highly
Likely Likely
Neither unlikely
nor likely Unlikely
Highly
Unlikely
Go to question 3 and then to question 5. 3. What type of property will you consider purchasing/renting? House Apartment Other ____________________ (please state) 4. Will you be purchasing as: An owner-occupier An investor Through the New Homebuy Scheme (i.e. shared ownership) 5. What are the important matters when considering your next property to rent or purchase?
Please tick the appropriate box, where 1 = not at all important and 5 = extremely important. 1 2 3 4 5 Developer’s reputation Good access to public transport Location
Close to recreation and leisure facilities Number of bedrooms Size of living accommodation On-site management services Development tenure, i.e. private or mixed Sense of community among neighbours Value for money On-site security Access to car parking
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Other (Please state) _______________________________________________________
5. Please rate the probability of you purchasing or renting a property within a development
that includes the following tenures … Please tick the most appropriate box for each statement
Ω See definitions below Highly
Likely Likely
Neither unlikely
nor likely Unlikely
Highly
Unlikely
Private purchase only
Private purchase & private rent
Private purchase & shared ownership
Private purchase & affordable rent
Private purchase, shared ownership &
private rent
Private purchase, shared ownership,
private rent & affordable rent
Shared ownership & private rent
Shared ownership & affordable rent
Private rent & affordable rent
Ω Private purchase – purchase all of the property with or without a mortgage Shared ownership – purchase a share of the property with the assistance from a Housing
Association or similar body Private rent – Renting directly from a private landlord Affordable rent – Renting from a Housing Association or Local Council 6. Would you consider a development that included properties for affordable rent if …
(Please tick the most appropriate box for each statement)
Highly
Likely Likely
Neither unlikely
nor likely Unlikely
Highly
Unlikely
All affordable tenants are employed
All affordable tenants are key workers**
There is a mix of affordable tenants, i.e.
employed and unemployed
All affordable tenants are subject to
rigorous vetting procedures prior to
allocation
24 hour CCTV & security is present
On-site management suite & concierge
service is present
An access control system is present
The development is designed to keep the
separate tenures in separate blocks.
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**A key worker is someone who works in a key public service, such as teachers, fire fighters, police officers, clinical NHS staff (excluding doctors and dentists) etc.
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7. Please tick the statement that you feel most relevant to each statement: Please tick one box for each statement
Strongly
Agree Agree
Neither Agree Nor
Disagree Disagree
Strongly
Disagree
Mixed tenure should be introduced into
residential apartment developments.
Mixed tenure is more suited in housing
developments rather than apartment
developments.
The inclusion of affordable tenants within
an apartment development will negatively
affect the future value of all the
apartments within that development.
The inclusion of affordable tenants within
an apartment development will positively
affect the future value of all the
apartments within that development.
I would be willing to rent in a mixed tenure
apartment development.
I would be willing to purchase in a mixed
tenure apartment development.
Mixed tenure apartment developments are
desirable and sustainable.
Section B: Personal Profile 8. Please tick your relevant age band? Please tick one 18 – 24 35 – 44 55 plus 25 – 34 45 – 54 9. Are you …? Male Female 10. Are you currently working? (This includes any part-time working by students and those on training courses.) No Yes Other ____________________
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11. Which of the following best describes the type of work you have in your main job? Please tick one Senior management or professional Intermediate management, administrative or professional Supervisor, clerical, junior management, administrative or professional Manual worker (with industry qualifications) Manual worker (without industry qualifications) Self-employed 12. What is your household annual income (before tax deductions)? Please tick one £10,000 - £19,999 £40,000 - £49,999 £20,000 - £29,999 £50,000 - £59,999 £30,000 - £39,999 £60,000 or over
PLEASE USE THE SPACE BELOW TO PROVIDE ANY OTHER COMMENTS: