literature review - E-commerce industry - efficient supply chain management

Research Article

An exploratory study of investment behaviour of investors

Mark KY Mak1 and WH Ip2

Abstract The financial industry plays a significant role in Mainland Chinese and Hong Kong economies and has aroused increasing managerial and academic interests in recent decades. Individual investors are becoming more cautious towards financial investment which makes it difficult for financial service providers to formulate marketing strategies after experiencing several financial crises. Prior research has suggested that financial investment behaviour would be affected by various factors, including the demographic characteristics of individuals; however, they seldom study the differences in financial investment behaviour between Mainland Chinese and Hong Kong investors or provide an easy-to-use approach for practical usage. This exploratory study aims at filling the identified research gap by proposing linear regression models of the financial investment behaviour of Mainland Chinese and Hong Kong investors. Based on the results of regression analyses, (i) there exist significant differences in financial investment behaviour between Mainland Chinese and Hong Kong investors, and (ii) investors’ psychological, sociological and demographic factors are significant predictors of their investment behaviour/preferences. Thus, financial service providers are able to predict the investment behaviour/pre- ference of its customers and formulate marketing and strategic decisions, such as customizing the financial investment portfolio of customers on the basis of regression models built.

Keywords Regression, exploratory study, investor behaviour, statistical analysis, financial industry

Date received: 24 January 2017; accepted: 12 April 2017

Introduction

As an international financial centre, Hong Kong offers a

variety of financial products, such as mutual funds, stocks

and bonds, for individual investors to invest. Due to the

close proximity, low tax rate, similarities of language and

culture and global access, Hong Kong remains the top off-

shore investment destination for Mainland Chinese inves-

tors. 1

These facts encourage the financial industry in Hong

Kong to review marketing strategies for targeting this fast-

growing market segment, that is, Mainland Chinese inves-

tors investing in the offshore Hong Kong market.

At the same time, individual investors are becoming

more cautious towards financial investment and make it

difficult for financial service providers to formulate mar-

keting strategies after experiencing several financial

crises. 2

Indeed, financial service providers face the chal-

lenge of understanding the investment behaviour and

preferences of their customers for long-term benefits. 2

In

order to have better market analysis and customer relation-

ship management, various finance theories have been pro-

posed by researchers.

Traditional finance theories assume that investment

behaviour is rational. 3

However, well-known events such

as the financial tsunami between 2007 and 2008, displaying

apparently irrational behaviour, have caused a rethink in

1 Lerado Financial Group Company Limited, Hong Kong Island, Hong

Kong 2 Department of Industrial and Systems Engineering, The Hong Kong

Polytechnic University, Hung Hom, Kowloon, Hong Kong

Corresponding Author:

Mark KY Mak, Lerado Financial Group Company Limited, Hong Kong

Island, Hong Kong.

Email: [email protected]

International Journal of Engineering Business Management

Volume 9: 1–12 ª The Author(s) 2017

DOI: 10.1177/1847979017711520 journals.sagepub.com/home/enb

Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License

(http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without

further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/

open-access-at-sage).

the domain, and the emerging field of behavioural finance

has become a popular field of study in an attempt to explain

this irrational behaviour. Under the theory of behavioural

finance, researchers suggest that the investment behaviour

of individual investors in real life is influenced by a com-

bination of specific psychological factors, such as overcon-

fidence, 4,5

representativeness 4

and herding behaviour. 6

The research focusing on psychological investment

behaviour, however, steers away from sociological factors

and personality traits. It seems investment behaviour is a

complicated domain that combines both rational and emo-

tional elements rather than just one. Furthermore, beha-

vioural finance is not purely based on psychological

factors but also sociological factors in the study of invest-

ment behaviour. 7

Moreover, demographic factors such as

age and gender are also important in explaining investor

behaviour. 8

Behavioural finance seems to explain reality

and to provide a better framework in the way the investors

behave. It is crucial to take psychological, sociological and

demographic factors into account to explore the major attri-

butes of how investors behave. 7,9

A review of the existing literature demonstrated that

researchers focus mainly on identifying factors influencing

investor behaviour and/or examining their impact on

investment decisions. 10–12

Studies seldom investigated

how to predict investors’ preference based on the factors

influencing their behaviour. This gap is probably due to

researchers lacking access to the huge volumes of strictly

confidential financial transaction data required to draw

such conclusions from studying real behaviour.

In order to gain a deep understanding of investment beha-

viour of individual investors in Hong Kong and Mainland

China, statistical analyses are applied in this study, aimed at

identifying the differences in investment behaviour/prefer-

ence between Mainland Chinese investors and Hong Kong

investors and explaining investment behaviour determined

by rational, emotional as well as demographic factors. Over-

all, several research questions are identified, including

� What are the factors in the difference of the beha- viour identified in the previous literature?

� What are the major attributes to explain investment behaviour?

� How do the major attributes identified predict inves- tors’ behaviour/preferences in Hong Kong and

Mainland China?

Literature review and hypotheses development

Importance of understanding consumer behaviour in financial market

In today’s increasingly competitive business environment,

a clear understanding of sophisticated consumer behaviour

is a key element for ensuring success. There are many

scholars who have examined the definition of consumer

behaviour. In general, consumer behaviour is the study of

customers and the processes they use to choose, consume

and dispose of products and services that satisfy their needs

and influence their experience. 13

Understanding the underlying mechanisms that to lead

to these customers’ responses, therefore, helps business

organizations make better managerial decisions, regarding

providing the right product or service to their customers. 14

An in-depth understanding of consumer behaviour further

helps business organizations to plan for the future buying

behaviour patterns of customers and formulate the appro-

priate marketing strategies in order to build long-term cus-

tomer relationships.

In financial markets, investors are the customers or con-

sumers. Exploring the behaviour of investors is therefore

important for financial institutions to devise appropriate

strategies and to market appropriate financial products or

offer new financial products to investors in order to better

satisfy their needs. To study investor behaviour, research-

ers have largely adopted the concept of behavioural finance

during the last decade. 3

Overview of behavioural finance

Behavioural finance refers to the application of psychology

to finance. 15

Behavioural finance offers an alternative tool

to study investor behaviour and the causes of market

anomalies. Scholars have applied behavioural finance to

explain financial market anomalies such as stock market

bubbles, overreaction and underreaction to new informa-

tion 16,17

that do not conform the traditional finance theory.

For example, Shefrin and Statman 18

found that excessive

optimism creates speculative bubbles in financial markets.

Researchers also widely applied behavioural finance to

explain emotional investor behaviour in recent years.

Frankfurter and McGoun 19

also indicated that psychology

and sociology is the essence of behavioural finance. How-

ever, according to the available literature described above,

researchers have emphasized the importance of psycholo-

gical factors and overlooked other factors in the concept of

behavioural finance.

Other researchers support the view that sociological and

demographic factors are also important to explain investor

behaviour. 7,8

Though some researchers have studied the

impacts of other factors such as gender or age on invest-

ment behaviour, these studies only explored the influences

with regard to investor behaviour but did not discuss any

findings about the financial decision-making process of

investors or predict their preference on financial products.

For example, Yang 20

investigated, through case studies, the

influence of both gender and age differences towards finan-

cial investment behaviour in terms of overconfidence,

account-open time and trade frequency. These studies

within the field of behavioural finance provide evidence

2 International Journal of Engineering Business Management

that demographic factors such as age and gender should be

considered when studying investor behaviour.

Overall, in order to make the research closer to reality

and to better comprehend the way the investors behave, this

study took psychological, sociological and demographic

factors into account to explore how and why investors

behave differently. Identifying the major attributes to

explain investment behaviour by leveraging psychological,

sociological and demographic factors is thus essential for

this study in order to address the gap in knowledge.

Key attributes influencing financial investment behaviour

In general, research in behavioural finance provides evi-

dence that investors’ decisions are affected by behavioural

factors. 21

Researchers found that investors do not behave in

a merely rational manner across financial markets and there

are a variety of factors influencing their decision-making in

investment; among those factors, psychological factors,

sociological factors and demographic factors are the major

elements. 22–24

To study behaviour under more realistic

conditions and to better categorize the way investors

behave, this study identifies and evaluates the major attri-

butes in the literature explaining investment behaviour

under three constructs, namely, the psychological factor,

sociological factor and demographic factor, and how these

attributes impact on the investors’ decision-making.

Key psychological attribute. Regarding the psychological fac- tor, individual investors are driven by experience or

through an investment appraisal process to make invest-

ment decisions. 25–27

Past experience, as a consequence,

affects investors’ risk perception in terms of attitude to risk

and risk tolerance. 28

This is also supported by Byrne, 29

indicating the positive correlation between investment

experience and risk. Researchers further pointed out that

accumulated investment experience significantly affects

investment decisions of individual investors in terms of

anchoring bias and overconfidence. 30

These indicate that

the investment experience of individual investors forms a

strong basis for investment decisions and is therefore

included in this study by considering it as an important

psychological attribute that influences financial investment

behaviour.

Key demographic attributes. According to Maditinos et al.31

and Sadi et al., 32

the demographic factor is one of the

behavioural factors that plays a significant role in deter-

mining the behaviour and decisions of investors. For

example, demographic factors influence one’s choice of

investment products. 33–35

Kabra et al. 36

found that the

main factors affecting investment behaviour and inves-

tors’ decisions are age and gender. According to Huber-

man and Jiang, 37

age and the amount of funds held tend to

indicate a negative correlation. Age is always an essential

factor and has a significant relationship with investment

behaviour according to the literature and thus is included

in this study.

Gender is another crucial demographic attribute that

affects the investment decision-making process and

investor behaviour. 38

Many researchers suggested that

there are gender differences in risk attitude and thus in

the choices of financial investment products. 34,39

Many

existing studies supported that female investors are more

conservative than male investors when investing and

tend to show greater risk aversion than male inves-

tors. 39,40

For financial service providers to offer finan-

cial products which are best suited for investors of

different genders, understanding the gender difference

in the investment behaviour of individuals is crucial and

thus is taken into account in this study.

Key sociological attributes. According to the extant literature, education level,

41,42 income level

3,42 and marital sta-

tus 9,42

are found to be significant sociological attributes

determining investors’ behaviour and influencing their

investment decision. Al-Ajmi 41

conducted an exploratory

study and concluded that income level and education level

are positively correlated with risk tolerance. Shaikh and

Kalkundrikar 42

conducted an exploratory study and con-

firmed that income level, education level and marital sta-

tus are factors affecting investors’ behaviour and

decision-making. Fares and Khami 43

identified that the

education level of investors is statistically significant to

investment decision. Rizvi and Fatima 3

also found a sig-

nificant positive correlation between income and invest-

ment frequency. More studies revealing the significant

relevance of these sociological factors, including educa-

tion level, income level and marital status, in investment

decisions and investor behaviour can be found in the lit-

erature. 43,44

With the support of the literature review,

these three attributes, income level, education level and

marital status, are considered in this study.

Table 1 summarizes all the psychological, sociological

and demographic factors and attributes of behavioural

finance considered in this study.

The literature discussion above highlighted that finan-

cial investment behaviour is commonly influenced by

demographic, psychological and sociological factors, and

Table 1. Factors and key attributes considered.

Factor Key attribute(s) Review reference

sources

Psychological Investment experience 25–30

Demographic Age 36,37,44

Gender 34,36,38–40,44

Sociological Education level 41–44

Income level 3,41,42,44

Marital status 9,42

Mak and Ip 3

the major attributes that explain investment behaviour are

age, income level, educational level, gender, investment

experience and marital status. However, little research

has been devoted to the behaviour of individual inves-

tors. 45,46

Furthermore, Hong Kong is the top offshore

investment destination for the Mainland Chinese investors.

Investors in Hong Kong are mainly mixed, with Mainland

Chinese investors and local investors having different char-

acteristics. In order to answer the third research question

identified in Introduction, the following hypotheses are

proposed:

H1: The investment behaviour/preference of the Main-

land Chinese and Hong Kong investors, when consid-

ered together, can be predicted by the six attributes –

age, income level, educational level, gender, investment

experience and marital status.

H2: The fund share amount held by the Mainland Chi-

nese and Hong Kong investors, when considered sepa-

rately, can be predicted by the six attributes.

H3: The choice of country-specific financial investment

options selected by the Mainland Chinese and Hong

Kong investors, when considered separately, can be pre-

dicted by the six attributes.

Regression models and data

Regression models

To explore the problems in understanding financial

investment behaviour as well as to study the effects of

the six variables, as identified from literature review, on

investment behaviour of the Mainland Chinese and

Hong Kong investors, a quantitative interpretation of the

literature review was conducted for subsequent explora-

tory study. Based on the hypothesis, a table of variables

is created (Table 2) and three regression models are

constructed.

Model 1a

fundholdT ¼aþb1 ageT þ b2 incomelevelT þb3 educationlevelT þ b4 genderT þb5 investmentexperienceT þb6 maritalstatusT

where the variable of the fund share amount held

( fundholdT ) is a function of age ( ageT ), income level

( incomelevelT ), gender ( genderT ), educational level

( educationallevel T ), investment experience (invertment-

experience T ) and marital status ( maritalstatusT ). a represents the regression constant. bj ðj ¼ 1; 2 . . . ; 6Þ denotes the regression coefficients for each independent

variable.

Model 1b

fundcurrencyT ¼aþb1 ageT þb2 incomelevelT þb3 educationlevelT þ b4 genderT þb5 investmentexperienceT þb6 maritalstatusT

where the variable of the choice of country-specific finan-

cial investment options selected ( fundcurrencyT ) is a func-

tion of age ( ageT ), income level ( incomelevelT ), gender

( genderT ), educational level ( educationallevel T ), invest-

ment experience ( investmentexperienceT ) and marital sta-

tus ( maritalstatusT ). a represents the regression constant. bj ðj ¼ 1; 2 . . . ; 6Þ denotes the regression coefficients for each independent variable.

The first regression model helps give a general picture

for understanding whether and how the six key attributes

identified affect and predict the investment behaviour of

both the Mainland Chinese and Hong Kong investors. In

order to have an in-depth examination on the differences in

investment behaviour between Mainland Chinese and

Hong Kong investors, the second and third models are

constructed to analyse how the six attributes identified

affect investors specifically in Mainland China and Hong

Kong in terms of the fund share amount held and choice of

country-specific financial investment option selected,

respectively.

Model 2a

fundholdCN ¼aþb1 ageCN þ b2 incomelevelCN þb3 educationlevelCN þ b4 genderCN þb5 investmentexperienceCN þb6 maritalstatusCN

Model 2b

fundholdHK ¼aþ b1 ageHK þ b2 incomelevelHK þ b3 educationlevelHK þ b4 genderHK þ b5 investmentexperienceHK þ b6 maritalstatusHK

Model 3a

fundcurrencyCN ¼aþb1 ageCN þb2 incomelevelCN þb3 educationlevelCN þ b4 genderCN þb5 investmentexperienceCN þb6 maritalstatusCN

Model 3b

fundcurrencyHK ¼aþ b1 ageHK þ b2 incomelevelHK þ b3 educationlevelHK þ b4 genderHK þ b5 investmentexperienceHK þ b6 maritalstatusHK

4 International Journal of Engineering Business Management

Data

To analyse how the major attributes identified under demo-

graphic, psychological and sociological constructs affect

investors in both Hong Kong and Mainland China, finan-

cial transaction data and investors’ characteristics are col-

lected and analysed to support this research. The data of

customers from 2012 to 2014 were collected from a finan-

cial services provider listed in the Hong Kong Stock

Exchange. In recent years, the number of its customers

from Mainland China has been considerably increasing,

and thus the institution desires to learn about the investment

behaviour of mainlanders and understand the differences in

investment preference between mainland Chinese and

Hong Kong investors. This is the reason why the institution

supports this research by providing the confidential data

about its customers and makes this research possible by

overcoming the obstacle – failing to access to the huge

volume of financial transaction data that is confidential.

As the research aims to explore the individual investor

behaviour, a relative large sample size is recommended in

this kind of exploratory research for generating valid

results. As mentioned by Saunders et al., 47

a larger sample

size can help produce more reliable results as the samples

can be more representative. In this research, 142,496 sam-

ples were collected from a financial services provider listed

in the Hong Kong Stock Exchange, of which 87,057 sam-

ples were from Mainland Chinese investors and 55,439

were from Hong Kong investors.

Table 3 provides descriptive statistics for investors’

characteristics.

Table 2. Notation of variables.

Notation Representation Notation Representation Notation Representation

fundholdT The fund share amount held by investors

fundholdCN The fund share amount held by Mainland Chinese investors

fundholdHK The fund share amount held by Hong Kong investors

fundcurrencyT The choice of country- specific financial investment options selected by investors

fundcurrencyCN The choice of country-specific financial investment options selected by Mainland Chinese investors

fundcurrencyHK The choice of country- specific financial investment options selected by Hong Kong investors

ageT Age of investors

ageCN Age of Mainland Chinese investors

ageHK Age of Hong Kong investors

incomelevelT Income level of investors

incomelevelCN Income level of Mainland Chinese investors

incomelevelHK Income level of Hong Kong investors

educationlevelT Education level of investors

educationlevelCN Education level of Mainland Chinese investors

educationlevelHK Education level of Hong Kong investors

genderT Gender of investors

genderCN Gender of Mainland Chinese investors

genderHK Gender of Hong Kong investors

investmentexperienceT Investment experience of investors

investmentexperienceCN Investment experience of Mainland Chinese investors

investmentexperienceHK Investment experience of Hong Kong investors

maritalstatusT Marital status of investors

maritalstatusCN Marital status of Mainland Chinese investors

maritalstatusHK Marital status of Hong Kong investors

a Regression constant

bj ðj ¼ 1; 2 . . . ; 6Þ Regression coefficient

Mak and Ip 5

Assumption analysis

To ensure the validity of the regression models, several

requirements in applying multiple regression models,

including linearity, multivariate normality, homogeneity

of variance and multicollinearity, are tested. As men-

tioned by Poole and O’Farrell 48

and Antonakis and

Dietz, 49

the models are only valid when these require-

ments are tested and satisfied. Before conducting the

actual regression analyses, preliminary analyses are con-

ducted to ensure the requirements for the regression

models are fulfilled.

Linearity test. Figure 1 shows the significance of the linear relationship for model 1a. From Figure 1, the p value for all

variables are <0.0001, indicating that significant linear

relationships between all independent variables and depen-

dent variable exist. Thus, the assumption of linearity for

regression is fulfilled.

Multivariate normality test. Figure 2 shows the histogram of the standardized residuals for model 1a. According to Ste-

vens, 50

if residuals fit a normal curve, multivariate normal-

ity is not a problem. The histogram of the residuals of

model 1a shows a symmetrical bell-shape and fairly normal

distribution. Thus, the assumption of multivariate normal-

ity is fulfilled.

Homogeneity of variance. Figure 3 shows the scatter plot of the residuals for model 1a. According to Osborne and

Waters, 51

if residuals scatter randomly and close to the zero

axis, homogeneity of variance is not a problem. Homoge-

neity of variance is not a problem for model 1a in our study

as an almost horizontal band of points is scattered around

and close to the zero axis, as shown in Figure 3. Thus, the

assumption of homogeneity of variance is fulfilled.

Multicollinearity. Figure 4 shows the values of the coeffi- cients of determination (R

2 ) and variance inflation factors

Table 3. Descriptive statistics.

Mainland Chinese Hong Kong

Frequency Percentage

Amount of fund share held

Frequency Percentage

Amount of fund share held

Mean Variance Mean Variance

Marital status Divorced 1736 2.0 320.20 536,282.26 1156 2.1 15.82 311.31 Married 48,423 55.6 121.76 2,213,504.50 14,703 26.5 51.09 156,248.17 Single 36,898 42.4 29.81 12,524.81 39,580 71.4 29.08 13,370.21 Total 87,057 100.0 86.74 1,250,327.26 55,439 100.0 34.64 51,089.72

Gender Female 57,294 65.8 90.61 1,843,410.28 24,337 43.9 27.71 3330.20 Male 29,763 34.2 79.29 108,577.21 31,102 56.1 40.07 88,395.31 Total 87,057 100.0 86.74 1,250,327.26 55,439 100.0 34.64 51,089.72

Age 0–24 3991 4.6 20.96 3214.61 4564 8.2 16.74 767.42 25–29 24,607 28.3 31.96 18,667.56 19,558 35.3 23.04 1942.98 30–34 20,773 23.9 47.04 18,838.95 14,085 25.4 31.00 4086.63 35–39 15,977 18.4 73.83 51,271.84 8144 14.7 38.87 16,685.62 40–44 10,148 11.7 126.30 117,385.82 4340 7.8 55.78 94,869.81 45–49 6420 7.4 220.76 261,766.61 1886 3.4 158.18 1,133,002.77 50–54 3651 4.2 460.34 28,281,137.04 2467 4.4 30.64 3402.27 55 and over 1490 1.7 97.32 202,074.94 395 0.7 61.51 15,648.61 Total 87,057 100.0 86.74 1,250,327.26 55,439 100.0 34.64 51,089.72

Educational level Elementary 191 0.2 657.67 1,895,934.40 442 0.8 40.64 6357.03 Junior 9763 11.2 144.14 10,512,259.97 25,639 46.2 27.36 17,769.82 Senior and above 77,103 88.6 78.06 74,801.48 29,358 53.0 40.91 80,777.85 Total 87,057 100.0 86.74 1,250,327.26 55,439 100.0 34.64 51,089.72

Household’s net worth

Below HKD100,000

25,091 28.8 27.31 19,121.63 37,751 68.1 24.11 1857.15

HKD100,000– 300,000

33,214 38.2 35.57 6033.15 12,508 22.6 41.66 38,737.45

HKD300,000– 500,000

8019 9.2 58.43 18,073.38 4150 7.5 38.00 4321.43

HKD500,000– 1M

5813 6.7 110.23 73,910.99 491 0.9 66.01 13,164.51

HKD1M and above

14,920 17.1 86.74 1,250,327.26 539 1.0 555.36 3,906,787.08

Total 87,057 100.0 306.67 7,151,080.17 55,439 100.0 34.64 51,089.72

6 International Journal of Engineering Business Management

(VIF) calculated for model 1a. According to Hart and

Sailor, 52

if tolerance (T), which is defined as T ¼ 1 � R

2 , is below 0.20, the multicollinearity problem is a

severe problem. Furthermore, the attributes are moder-

ately correlated if the value of VIF is between 1 and 5. 53

In our study, correlations are at acceptable levels as the

T values for the six key attributes are over 0.20 and the

VIF values are between 1 and 5. These indicate low

multicollinearity and thus the assumption of multicolli-

nearity is fulfilled.

Having fulfilled all the requirements, the multiple

regression model 1a is confirmed to be valid and actual

regression analysis is then conducted. Similar assump-

tion analyses as discussed for model 1a are also con-

ducted for models 1b, 2a, 2b, 3a and 3b, and all the

requirements are fulfilled. In the next section, the results

are reported.

Results and analysis

With the help of the 142,496 observation samples, regres-

sion analyses are conducted in this section to assess the

relationships between the key attributes identified and the

investment behaviour/preferences between Mainland Chi-

nese and Hong Kong investors.

Tables 4 and 5 show the results for the standardized

coefficients and adjusted R 2 .

Effects of key attributes on investment behaviour/preference

From the regression results of model 1a (Table 4), all

the six key attributes identified have a significant (at

0.01 level) effect on the fund share amount held when

Mainland Chinese and Hong Kong investors are consid-

ered together. Thus, age, income level, education level,

gender, investment experience and marital status are

Figure 2. SPSS output for histogram of residuals.

Figure 3. SPSS output for analysis of residuals.

Figure 1. IBM SPSS Statistics (SPSS) output for multiple correlation coefficient.

Mak and Ip 7

statistically significant predictors of the fund share

amount held by Mainland Chinese and Hong Kong

investors.

From the regression results of model 1b (Table 4), five

out of the six key attributes, excluding gender (p value ¼ 0.223 > 0.1), identified have a significant (at 0.01 level)

effect on the choice of the country-specific financial invest-

ment option selected when Mainland Chinese and Hong

Kong investors are considered together. Thus, only age,

income level, education level, investment experience and

marital status are statistically significant predictors of the

choice of the country-specific financial investment option

selected by Mainland Chinese and Hong Kong investors.

By leveraging the results shown in Table 4, it is con-

cluded that the financial investment behaviour/preference

of Mainland Chinese and Hong Kong investors, when con-

sidered together, are inseparable with regard to their demo-

graphic factor (i.e. age), psychological factor (i.e.

investment experience) and sociological factor (i.e. income

level, education level and marital status).

Effects of key attributes on the fund share amount held

From the regression results of model 2a (Table 4), all the

six key attributes identified have a significant (at 0.01

level) effect on the fund share amount held by Mainland

Chinese investors. Thus, it is confirmed that age, income

level, education level, gender, investment experience and

marital status are statically significant predictors of the

fund share amount held by Mainland Chinese investors.

From the regression results of model 2b (Table 4), five

out of the six key attributes, excluding education level (p

value ¼ 0.107 > 0.1), identified have a significant (at 0.01 level) effect on the fund share amount held by Hong Kong

investors. Thus, only age, income level, gender, investment

experience and marital status are statistically significant

predictors of the fund share amount held by Hong Kong

investors.

By leveraging the results shown in Table 4, it is con-

cluded that the fund share amount held by Mainland Chi-

nese and Hong Kong investors, when considered together,

are inseparable with their demographic factor (i.e. age and

gender), psychological factor (i.e. investment experience)

and sociological factor (i.e. income level and marital sta-

tus). The top three most significant attributes are age,

income level and investment experience. The standardized

coefficient of age is �0.030 for Mainland Chinese inves- tors and 0.024 for Hong Kong investors. The standardized

coefficient of income level is 0.277 for Mainland Chinese

Table 4. Results of regression analyses for models 1 and 2.

Model 1a Model 1b Model 2a Model 2b

age �0.022*** 0.025*** �0.030*** 0.024*** incomelevel 0.273*** 0.030*** 0.277*** 0.241*** educationlevel 0.013*** 0.014*** 0.016*** �0.007 gender �0.012*** 0.004 �0.011*** 0.021*** investment

experience �0.014*** 0.119*** �0.023*** �0.035***

maritalstatus �0.013*** �0.020*** �0.021*** 0.015*** R2 0.074 0.018 0.075 0.060

*Statistical significance at the 0.1 level. **Statistical significance at the 0.05 level. ***Statistical significance at the 0.01 level.

Table 5. Results of regression analyses for model 3.

Model 3a Model 3b

age 0.015*** �0.027*** incomelevel �0.020*** 0.032*** educationlevel 0.006 0.015*** gender 0.003 0.011*** investmentexperience 0.140*** 0.121*** maritalstatus 0.014*** 0.005 R2 0.021 0.006

*Statistical significance at the 0.1 level. **Statistical significance at the 0.05 level. ***Statistical significance at the 0.01 level.

Figure 4. SPSS output for the measure of tolerance.

8 International Journal of Engineering Business Management

investors and 0.241 for Hong Kong investors. The standar-

dized coefficient of investment experience is �0.023 for Mainland Chinese investors and �0.035 for Hong Kong investors. In spite of the differences in the magnitude of

the three most significant attributes, the directions of the

relationship are similar, except for age. For example,

income level has a positive effect on the fund share amount

held by Mainland Chinese and Hong Kong investors. How-

ever, age has a negative effect on the fund share amount

held by Mainland Chinese investors but a positive effect on

Hong Kong investors. In other words, younger Mainland

Chinese and older Hong Kong investors tend to hold a

higher fund share.

Effects of key attributes on the choice of the country- specific financial investment option selected

From the regression results of model 3a (Table 5), four out

of six key attributes, excluding education level (p value ¼ 0.141 > 0.1) and gender (p value ¼ 0.325 > 0.1), identified have a significant (at 0.01 level) effect on the choice of the

country-specific financial investment option selected by

Mainland Chinese investors. Thus, it is confirmed that age,

income level, investment experience and marital status are

statically significant predictors of the choice of the country-

specific financial investment option selected by Mainland

Chinese investors.

From the regression results of model 3b (Table 5), five

out of the six key attributes, excluding marital status (p

value ¼ 0.127 > 0.1), identified have a significant (at 0.01 level) effect on the choice of the country-specific

financial investment option selected by Hong Kong inves-

tors. Thus, only age, income level, education level, gender

and investment experience are statistically significant pre-

dictors of the choice of the country-specific financial

investment option selected by Hong Kong investors.

By leveraging the results shown in Table 5, it is con-

cluded that the choice of the country-specific financial

investment options selected by Mainland Chinese and

Hong Kong investors, when considered together, are

closely correlated with the demographic factor (i.e. age),

psychological factor (i.e. investment experience) and

sociological factor (i.e. income level and marital status).

The three most significant attributes are the age, income

level and investment experience. The standardized coeffi-

cient of age is 0.015 for Mainland Chinese investors and

�0.027 for Hong Kong investors. The standardized coeffi- cient of income level is �0.020 for Mainland Chinese investors and 0.032 for Hong Kong investors. The standar-

dized coefficient of investment experience is 0.140 for

Mainland Chinese investors and 0.121 for Hong Kong

investors.

Investment experience has a positive effect on the

choice of country-specific financial investment options

selected by both Mainland Chinese and Hong Kong inves-

tors. On the contrary, age and income level have different

effects on the choice of the country-specific financial

investment options selected by Mainland Chinese and

Hong Kong investors. For example, younger Mainland Chi-

nese investors and older Hong Kong investors tend to have

the same choice of the country-specific financial invest-

ment option.

Table 6 summarizes the impacts of key factors and attri-

butes on the investment behaviour of Mainland Chinese

and Hong Kong investors. The table summarizes the rela-

tionship (direction and magnitude) between the key attri-

butes, the fund share amount held and the choice of the

country-specific financial investment options selected by

investors.

Discussion

Practical and strategic importance of this research

With reference to the results of regression models 1 (Table

4), 2 (Table 4) and 3 (Table 5), there exist significant dif-

ferences in the financial investment behaviour/preference,

in terms of the fund share amount held and the choice of the

country-specific financial investment option selected,

between Mainland Chinese and Hong Kong investors. For

example, the impact of age on the fund share amount held

Table 6. Impacts of key attributes.

Factor Attribute

Fund share amount held Choice of the country-specific

financial investment option selected

Mainland Chinese investors

Hong Kong investors

Mainland Chinese investors

Hong Kong investors

Psychological Investment experience �0.023 �0.035 þ0.140 þ0.121 Demographic Age �0.030 þ0.024 þ0.015 �0.027

Gender �0.011 þ0.021 N/A þ0.011 Sociological Education level þ0.016 N/A N/A þ0.015

Income level þ0.277 þ0.241 �0.020 þ0.032 Marital status �0.021 þ0.015 þ0.014 N/A

þ: relationship in the positive direction; �: relationship in the negative direction; N/A: absence of a significant relationship.

Mak and Ip 9

by and choice of the country-specific financial investment

option selected by Mainland Chinese and Hong Kong

investors is opposite. Similarities between the investment

behaviour of Mainland Chinese and Hong Kong investors

are also found. Particularly, the three most significant attri-

butes, age, income level and investment experience, influ-

encing investment behaviour for both Mainland Chinese

and Hong Kong investors are the same, though the influ-

ence may in the opposite directions. Also, income level has

a positive effect, while investment experience has a nega-

tive effect on the fund share amount held by investors.

In view of the similarities in investment behaviour for

both Mainland Chinese and Hong Kong investors, financial

service providers can utilize the findings to design and

promote different financial investment products based on

the demographic, psychological and sociological attributes,

particularly income level and investment experience, of

individual investors from Mainland Chinese and Hong

Kong. The following targeted marketing strategy can be

formulated:

Target group 1: High-income investors

From the regression results of models 2a and 2b (Table

4), income level has a significant (at 0.01 level) and posi-

tive effect (0.277, 0.241) on the fund share amount held by

both Mainland Chinese and Hong Kong investors. Finan-

cial service providers should therefore invest more money

in advertising and strengthening their products, as well as

designing a wider range of financial investment portfolios

so as to attract these high-income investors to invest.

Target group 2: Less experienced investors

From the regression results of models 2a and 2b

(Table 4), investment experience has a significant (at

0.01 level) and negative effect (�0.023, �0.035) on the fund share amount held by both Mainland Chinese and

Hong Kong investors. The possible reasons are listed

below. As individual investors become more experi-

enced, they become more conservative and show less

enthusiasm in fund investment. Therefore, high-risk

funds with a potential of offering higher returns are only

attractive to less experienced investors. Financial service

providers should then design higher yield funds and

allocation funds so as to raise the investment interests

of investors with less investment experience for the

highest profits.

Furthermore, in view of the differences in investment

behaviour between Mainland Chinese and Hong Kong

investors, financial service providers can utilize the find-

ings to design and promote different financial investment

products based on the demographic attribute of age. The

following strategy can be formulated for financial service

providers to better tackle Mainland Chinese and Hong

Kong investors:

Target group 3: Hong Kong investors aged 45–49

The results of regression analyses of models 2a and 2b

(Table 4) indicate that age is a statistically significant pre-

dictor for the fund share amount held by both Mainland

China and Hong Kong investors. However, the results indi-

cate that younger investors from Mainland China and older

investors from Hong Kong hold a higher fund share. The

results of descriptive analysis (Table 3) further identified

that Hong Kong investors aged between 45 and 49 show

great enthusiasm for investment and hold the highest fund

share on average (i.e. 158.18 unit). Thus, Hong Kong inves-

tors aged between 45 and 49 should be the key age group

for development and they are investors of great potential.

Financial service providers should then invest more money

in advertising and strengthen their products, as well as

designing higher yield funds so as to attract these enthusi-

astic and high purchasing power Hong Kong investors aged

between 45 and 49 to invest more in terms of frequency and

money. In the following subsection, limitations of this

research are discussed.

Limitations

In this research, financial transaction data and investors’

characteristics are collected from a single case company.

Despite the fact that 142,496 samples were collected and

used in the regression analyses, the empirical results may

not represent fully the financial investment behaviour or

investment preferences of all Mainland Chinese and Hong

Kong investors, given the limited number of case compa-

nies. In the future, more financial transaction data and

investors’ characteristics should be collected from other

Hong Kong-based financial service providers to make the

results more generalized and convincing.

Conclusions

The financial industry plays a significant role in the Main-

land China and Hong Kong economies and has aroused

increasing managerial and academic interest in recent

decades. Unfortunately, after the financial crisis of 2008

and the global crisis of 2009, investors are becoming more

cautious towards investments, especially in high-risk finan-

cial products. Furthermore, Hong Kong is the top offshore

investment destination for the Mainland Chinese investors.

Investors in Hong Kong are mainly mixed, with Mainland

Chinese investors and local investors having different char-

acteristics. These make it more difficult for financial ser-

vice providers to understand customers’ financial

investment behaviour and investment preferences.

Attempting to address the real-world challenges and

research gap, this study has (i) empirically identified that

demographic, psychological and sociological factors cause

different investment behaviour and (ii) identified that the

major attributes that explain and predict investment

10 International Journal of Engineering Business Management

behaviour/preferences of Mainland Chinese and Hong

Kong investors are age, income level, educational level,

gender, investment experience and marital status. Regres-

sion analyses and data provided by one of the Asia’s lead-

ing financial service providers were used to help the

financial industry formulate strategic and marketing

strategies.

This exploratory study helps to fill the identified

research gap and enable financial service providers to bet-

ter understand their customers’ financial investment beha-

viour and investment preferences from the perspective of

investors’ characteristics. With the huge volumes of confi-

dential transaction data and investors’ characteristics avail-

able, the research results are believed to be able to reflect

the real behaviour of individual investors from Mainland

China and Hong Kong and can offer financial service pro-

viders a foundation for sustainable strategies formulation.

In future research, it is suggested to extend the regression

results to build a data mining model to market the most

appropriate products to individual investors from Mainland

Chinese and Hong Kong and to gain a better understanding

of their financial investment behaviour in an effective and

efficient manner.

Acknowledgements

The authors thank the editors and reviewers for their valuable

comments and suggestions that have improved the quality of the

article. The authors would like to thank the Department of Indus-

trial and Systems Engineering, The Hong Kong Polytechnic Uni-

versity for their support in this work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with

respect to the research, authorship, and/or publication of this

article.

Funding

The author(s) received no financial support for the research,

authorship, and/or publication of this article.

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