Download Ethical investment: How do moral considerations influence

Ethical investment: How do moral considerations
influence investment behaviour?
Eva Hofmann*, Erik Hoelzl & Erich Kirchler
University of Vienna, Austria
Abstract: In recent years, a change in shareholders’ demand can be noted: more and more
investors ask for ethical investment opportunties. Investors are not only influenced by
financial benefits but also by moral considerations. For example, shares of companies
involved in the tobacco, alcohol or gambling industry are considered ‘sin stocks’ by some
investors and therefore are not traded. Rational decision theorists argue that moral
considerations would introduce inefficiency by reducing the number of investment options
and therefore only financial considerations should govern investment decisions. However, the
increasing demand for ethical investment indicates that investment decisions are influenced
by additional factors, for example attitudes and moral values. The discrepancy between
rational decision theory and actual shareholders’ demand opens a wide field of research for
economic psychology. Several economic and psychological models can be applied to explain
ethical behaviour. In the present study, we test suitability of: (a) multiple attribute utility
theory, (b) theory of planned behaviour, and (c) issue-contingent model of ethical decision
making in organisations. In an experimental setting, 141 participants traded company shares
on a computer simulated asset market. Over 12 periods, companies varied in ethicalness (i.e.,
how the company treats their employees) and in profitability (i.e., whether the expected
dividend for a share was low, medium or high). Participants’ bids and asks for shares were
recorded. Results indicate that moral considerations influence investment decisions.
Differences between the three models and implications for the understanding of ethical
investment behaviour are discussed.
Keywords: Behavioural finance, ethical decision making, ethical investment
Acknowledgement: The authors would like to thank Nicole Fabbro and Silvia Hansbauer for
helping with data collection and the ‘Verein zur Foerderung der Wirtschaftspsychologie’ for
financial support.
*
Corresponding Author:
Eva Hofmann,
Department of Economic Psychology, Educational Psychology and Evaluation,
Faculty of Psychology,
University of Vienna,
Universitaetsstrasse 7
1010 Vienna
Austria
T: +43 1 4277 47882
F: +43 1 4277 47889
[email protected]
Introduction
Ethical investment is a relatively new catch phrase in the European world of finance.
Sometimes also called sustainable investment or socially responsible investment, this kind of
investment subsumes on the one hand the funding of companies and investing in funds that
guarantee compliance to certain positive ethical criteria. On the other hand it represents the
disregard of companies according to certain negative ethical criteria (Hofmann, Penz &
Kirchler, under review; Lewis, Webley, Winnett & Mackenzie, 1998). Positive ethical criteria
involve e.g., environmental protection and fair trade with the Third World, negative ethical
criteria include e.g., the utilisation of nuclear power, the disdain of human rights, and so
called ‘sin stocks’, i.e., shares of companies involved in the tobacco, alcohol or gambling
industry (Anand & Cowton, 1993). Thus, since the 1980s, when the first ethical investment
fund was launched by the life insurance company Friends Provident in the UK, more and
more investors in Europe have been considering not only their financial benefits but also
ethical issues when deciding on investments.
In the view of rational decision theorists, the average human being – the rational homo
economicus – is motivated exclusively by financial benefits; ethical thoughts are not relevant
for behaviour. They argue that moral considerations would introduce inefficiency by reducing
the number of investment options (Lewis, 2001; Cullis, Lewis & Winnett, 1992).
Incorporating exclusively ethical investments in a portfolio and for this reason diminishing
the portfolio, increases either the risk or reduces the profit of this portfolio and therefore
makes it less efficient than conventional portfolios. Thus, only financial considerations should
govern investment decisions. However, the increasing demand for ethical investment
indicates that investment decisions are influenced not only by financial benefits but also by
additional factors, such as attitudes and moral values. This discrepancy between rational
decision theory and actual shareholders’ demand opens a wide field of research for economic
psychology to discover those factors.
Several theoretical models can be applied to explain ethical behaviour in general. In the
current paper the suitability for investment behaviour of some of these models is tested. In
particular, three approaches are compared: (a) multiple attribute utility theory, (b) theory of
planned behaviour (Ajzen, 1985), and (c) issue-contingent model of ethical decision making
in organisations (Jones, 1991).
The multiple attribute utility theory (MAUT) is based on assumptions of a rational decision
maker. It is presumed that when assessing different alternatives, homo economicus values the
alternative with the highest utility most. In multiple attribute utility theory, utility is separated
into attributes. For each alternative the utility (MAU) is determined by the sum over the utility
of each attribute (ui) multiplied by the weight of importance of the attributes (wi) (Formula 1).
Because of the separation of attributes, the multiple attribute utility theory represents a
theoretical background for a practical method to measure utility (Baron, 2000).
MAU = ∑ wi ui
(1)
i
The multiple attribute utility theory was already applied to study several decision problems
concerning ethical issues. Studies investigated the evaluation of issues such as environmental
planning (Kwak, Yoo & Kim, 2001; Kwak, Yoo & Kim, 1998) or health related matters
(Chapman, Elstein, Kuzel, Nadler, Sharifi & Bennett, 1999; Kasubek & Aschenbrenner,
1978). These studies corroborate that the multiple attribute utility theory is a practical
approach to simplify decision making by the evaluation of different alternatives.
The theory of planned behaviour (Ajzen, 1985, 1991) is a social psychological concept for
predicting human behaviour. It is based on the theory of reasoned action (Fishbein & Ajzen,
1975) which was extended by a factor. The theory of planned behaviour postulates that a
person’s intention to perform a behaviour is the immediate determinant of that behaviour.
Intention, in turn, is a function of three factors: Attitude toward the behaviour, subjective
1
norm and perceived behavioural control (Figure 1). The attitude toward the behaviour
represents a personal factor which comprises the positive and negative evaluation of
performing the behaviour. The factor subjective norm relates to social pressure to perform the
behaviour. The perceived behavioural control covers the subjective controllability to perform
the behaviour and depends on earlier experiences and expected obstructions. It represents the
factor by which the theory of reasoned action was extended. Thus, the attitude toward the
behaviour, the subjective norm and the perceived behavioural control influence, via the
intention, behaviour.
The relation between the factors of the theory of planned behaviour (Ajzen, 1985, 1991) was
often supported and was also used to explain ethical behaviour. The theory was applied to
such behaviours as environmental friendliness (e.g., Bamberg, Rolle & Weber, 2003;
Montalvo-Corral, 2002), health promotion (e.g., Schifter & Ajzen, 1985) or money
management (e.g., Bobek & Hatfield, 2003; East, 1993), once directly to ethical investment
behaviour (Borrello, Morricone, Pedon & Benevene, 2004).
Figure 1: The theory of planned behaviour (Ajzen, 1985, 1991; p.181)
Attitude
toward the
behaviour
Subjective
norm
Intention
Behaviour
Perceived
behavioural
control
The issue-contingent model of ethical decision making in organisations (Jones, 1991) is a
model that predicts ethical behaviour. Based on Rest’s model (1986) the issue-contingent
model describes the decision process: Decision makers (1) recognise the moral issue, then (2)
make a moral judgement and (3) establish a moral intent and finally, (4) engage in moral
behaviour. These four components are influenced by two other factors: Moral intensity and
organisational factors. Moral intensity represents the strength with which the moral issue
influences the decision process and therefore determines all four decision components. It is
composed of six subordinate factors: Magnitude of consequences, social consensus,
probability of effect, temporary immediacy, proximity and concentration of effect.
Organisational factors influence the decision process solely in the last two components,
establishing moral intent and engaging in moral behaviour. Organisational factors are
comprised by the subordinate factors group dynamics, authority factors and socialisation
process (Figure 2). These manifold factors in the model generate complex interdependencies.
Parts of the issue-contingent model of ethical decision making in organisations (Jones, 1991)
were supported and explained ethical behaviour. The issue-contingent model was applied to
ethical business decisions such as environmental pollution (Flannery & May, 2000; May &
Pauli, 2002), product safety (May & Pauli, 2002; Weber, 1996) and fraud (Carlson, Kacmar
& Wadsworth, 2002; Weber, 1996). According to these studies, moral intensity determines
the factors “recognise moral issue” and “make a moral judgment”; it is weakly supported that
it also influences the factor “establish moral intent”. To our knowledge, the model as a whole
has never been tested.
2
Figure 2: The issue-contingent model of ethical decision making in organisations (Jones,
1991; p.379)
Moral intensity
Magnitude of consequences
Social consensus
Probability of effect
Temporal immediacy
Proximity
Concentration of effect
Recognise
moral issue
Make moral
judgement
Establish
moral intent
Engage in
moral
behaviour
Organisational factors
Group dynamics
Authority factors
Socialisation process
It is the aim of the current study to answer three research questions: (1) Does ethicalness have
an influence in investment decisions? If ethicalness influences investment decisions, (2) can
this influence be explained by decision models? (3) Which model can explain the influence of
ethicalness in investment behaviour best? Subsequently these questions will be answered by
means of a questionnaire and a computer simulated asset market.
Method
Overall, 141 persons, 86 females and 55 males, took part in the study. Participants were
mainly students of the University of Vienna and of the Vienna University of Economics and
Business Administration. Therefore, participants were on average of 25 years (M=24.74,
SD=4.12). Twenty-seven participants invested in shares, whereas 13 of them invested in
ethical shares. Forty-five participants were members or donators of at least one charity.
All participants were recruited either personally or via e-mail at the universities in June 2004.
They were informed that they would take part in an experiment on investment behaviour
lasting two hours for which they would receive 5 Euro as a compensation for their time. In
addition they would have the chance, according to their performance in the experiment, to win
a book voucher worth 50 Euro. When they agreed to take part in the experiment, they were
given a questionnaire, which they had to complete and return before the computer simulated
asset market.
The questionnaire consisted of total 86 items and took 20 minutes to complete. First, the
participants read a description of companies and for each company successively completed 19
items. They had to imagine that they had inherited a certain amount of money and shares of
the company and were asked, whether they would like to add more shares of the companies to
their portfolio. The descriptions were four fictitious scenarios describing company A as a
personnel promoting company, which enhances projects for older employees, presenting
company B also as a personnel promoting company, which enhances equal promotion
prospects for all employees. Company C was described as a personnel neglecting company
with the regular business practice is to release older employees at the age of 45 if legally
possible, and company D was also presented as a personnel neglecting company, which
refuses any promotion prospects for its employees. One quarter of the participants received a
questionnaire in which they got information about company A first and then about company
C, B and D, the others found a sequence of companies C-A-D-B, B-D-A-C or D-B-C-A. After
each company description 19 questions had to be answered on a seven-point-scale. These
3
items measured the perceived ethicalness of the companies (1 item; utility), the factor
intention (1 item; establishing moral intent), a semantic differential for an attitude scale (4
items; attitude toward the behaviour), a subjective norm scale (2 items), a control scale (2
items; perceived behavioural control), a moral intensity scale (6 items), a moral judgement
scale (2 items; making a moral judgement) and the factor moral issue (1 item; recognising the
moral issue)1. Following all four company descriptions and the respective questions,
participants filled in a single item concerning personal importance of ethicalness of
investments (weight of importance), which was worded generally and did not correspond to
one of the four companies specifically. The final part of the questionnaire included nine items
asking for socio-demographic data, such as gender, age and possession of conventional and
ethical shares.
The computer simulation was conducted with participants in groups of 14 persons in the
computer laboratory of the Faculty of Psychology at the University of Vienna. Each group
received an intensive training to learn the market mechanisms on the simulated asset market.
In a continuous double auction (Smith, 1994), they were allowed to make bids and asks2 for
company shares, and to accept existing bids and asks of other participants. As soon as all
participants understood the mechanisms and were able to employ them, the simulation was
started. Over 12 periods participants successively traded shares of the companies A, B, C and
D which were described exactly as in the questionnaire. During one period only shares of one
company were traded. Over the periods each company paid either low, medium or high
dividends. Every period the participants were informed which share was going to be traded
and which dividend was to be expected in the forthcoming period. On the information screen
the participants were presented 5 different possible dividends which occurred with a 20%
probability each.3 Again, the sequence of the companies in the computer simulation was
balanced; the order of the companies were A-C-B-D, C-A-D-B, B-D-A-C or D-B-C-A. The
sequences of the amount of expected values of dividends stayed the same for all companies.
In the first period, when shares of a certain company were traded, a medium dividend had to
be expected, in the second period a high dividend was anticipated and in the third a low
dividend. After each period participants were informed about their earnings of the previous
period and then received information concerning the following period. After the 12th period
the profit earned over the entire computer simulation, was displayed and the lottery to gain the
book voucher took place. The higher a participant’s profit compared to the other 13
participants was, the higher was the chance to win the book voucher. All participants were
paid 5 Euro.
Results
For the statistical analysis, data from the questionnaire were matched with the bids and asks
from the computer simulation via a personalised code. Although 12 sessions with 14
participants each were conducted, for two reasons the data of 27 participants could not be
included in the analysis. First, some personalised codes on the questionnaire did not comply
with the ones from the computer simulation, so that the data could not be matched; second,
some participants did not fill in all items of the questionnaire, which was needed to undertake
1
The influence of organisational factors in the issue-contingent model of ethical decision making in
organisations is not included, because investment behaviour in the experiment bases solely on individual
decisions, which are not affected by organisational regulations.
2
A bid is a participant’s offer to buy a certain share at a pronounced price. An ask is a participant’s offer to sell a
certain share at a pronounced price.
3
When a low profit had to be expected the screen displayed possible dividends of 0, 1, 3, 5 and 6 experimental
currency units (expected value=3); at a medium expected profit it displayed 0, 39, 41, 53 and 67 experimental
currency units (expected value=40); and at a high expected profit it displayed 0, 74, 82, 118 and 126 (expected
value=80). The exact amount of the distributed dividend for each period was randomised depending on possible
dividends and probability.
4
the analysis of the models, and are excluded for that reason. Thus, data from 141 participants
remain for analysis.
Table 1: Descriptives for model components (questionnaire data, n=141)
attribute utility (multiple attribute utility)
intention (establish moral intent)
attitude (attitude towards the behaviour)
subjective norm
control (perceived behavioural control)
moral intensity
social consensus
moral judgement (make moral judgement)
moral issue (recognise moral issue)
Personnel promoting
companies
Company A
Company B
M
SD
M
SD
16.45 9.22 15.11 9.25
4.92
1.91
5.11
1.87
5.82
1.00
5.71
1.10
4.68
1.63
4.72
1.60
6.31
1.04
6.32
0.97
3.64
1.19
3.55
1.23
6.08
1.45
5.86
1.39
3.84
1.98
3.73
1.87
5.06
2.18
4.92
2.12
Personnel neglecting
companies
Company C
Company D
M
SD
M
SD
-7.16 6.39 -4.29 8.12
2.94
1.91
2.92
1.69
3.16
1.47
3.34
1.36
2.55
1.27
2.87
1.41
5.67
1.45
5.76
1.28
3.49
1.21
3.39
1.14
3.90
1.99
4.03
1.89
2.05
1.36
2.14
1.35
5.27
2.06
5.20
2.04
The scales from the questionnaire (Table1) were tested for their reliability. Whereas the scales
attitude, subjective norm and moral judgement hold very good Cronbach-α (minimal α=.74,
maximal α=.90), the scales control (minimal α=.29, maximal α=.40) and moral intensity
(minimal α=.61, maximal α=.73) maintain less satisfying reliability. It is assumed that the
disappointing reliability of the scale control emerges from ceiling effects which are due to the
experimental approach of the study.4 The scale moral intensity is reduced by the item for
social consensus, which measured moral intensity depending on how moral the companies are
perceived while the other five items of the scale are independent of moral perception.5
According to the theoretical background the scale attribute utility is generated by a
multiplication of the items utility and weight of importance for each company.
Table 2: Descriptives for investment behaviour (asset market data)
low profit
bids
asks
medium profit
bids
asks
high profit
bids
asks
Personnel promoting companies
Company A
Company B
M
SD
M
SD
23.42
15.87
23.94
16.30
n=79
n=87
40.61
19.81
35.68
30.68
n=72
n=72
43.90
19.73
41.07
14.89
n=92
n=85
60.86
37.23
57.21
15.70
n=94
n=84
59.08
18.83
55.08
21.04
n=97
n=79
77.95
27.95
77.71
33.41
n=93
n=84
Personnel neglecting companies
Company C
Company D
M
SD
M
SD
20.63
13.91
19.03
15.22
n=82
n=75
34.37
23.04
29.21
21.12
n=78
n=68
38.06
19.22
36.19
17.96
n=95
n=80
52.10
20.56
55.79
30.82
n=88
n=94
51.16
20.83
50.48
23.75
n=85
n=88
76.32
39.68
68.46
20.30
n=78
n=85
Participants’ investment behaviour (Table 2) was recorded in the computer simulation. Bids
and asks of participants were collected in all periods. Overall 5337 bids were recorded. From
these bids, 3593 were accepted by other participants and led to a trade. Additionally, 4590
asks were recorded. From these asks, 3090 were accepted by other participants and led to a
trade. Because it is to be assumed that participants tend to bargain while selling and buying
shares in the computer simulation, their bids and asks do not exactly represent their evaluation
of the shares. Lower bids and higher asks are made, while the exact evaluation is in between
their range. Therefore, for the subsequent analysis the highest bid and the lowest ask per
4
In the experiment participants should have felt objectively as well as subjectively to be in charge of the
investment decision.
5
The exclusion of social consensus increases the reliability of moral intensity, especially for the personnel
neglecting companies (minimal α=.74, maximal α=.77).
5
period of each participant are used. Interval regression (Stewart, 1993) is used for the
statistical analysis. It allows the dependent variable to exist of intervals as well as lower and
upper bounds, when participants gave solely bids or solely asks and also allows to account for
repeated measures.
The first research question (1), whether ethicalness has an influence in investment decisions,
is tested with an interval regression using behaviour as dependent variable and ethicalness6
and low and high profit7 as predictors. The statistical test reveals that ethicalness as well as
profit have significant influence (Chi2(5)=178.41, p<.001; Table 3). According to the
coefficients, ethical behaviour of companies compared to non ethical behaviour increases bids
and asks by 5.58 experimental currency units. Low expected profits compared to medium
profits decrease bids and asks by 18.61 experimental currency units; high expected profits
compared to medium expected profits increase them by 17.16 experimental currency units.
Interactions between ethicalness and profits do not have significant influence on behaviour.
Therefore they are not taken into account in subsequent analyses. Ethicalness has an influence
in investment decisions in the experiment.
Table 3: Interval regression results for investment behaviour on profit and ethicalness
b
SE
p
2
dependent variable: behaviour
ethicalness
low profit
high profit
constant
Wald Chi (5)=178.41, p<.001, n=1362
5.58
1.77
.002
-18.61
1.74
<.001
17.16
2.05
<.001
44.20
1.58
<.001
The second research question (2), whether the influence of ethicalness can be explained by
decision models, is again tested with interval regressions. Although the dependent variable is
once more behaviour, besides low and high profit the predictors vary according to the tested
model. (a) According to the multiple attribute utility theory the predictor attribute utility is
introduced to the interval regression. Statistics show that the multiple attribute utility theory
significantly can explain the influence of ethicalness (Chi2(3)=166.34, p<.001; Table 4). Each
single unit of attribute utility increases the bids and asks by 0.23 experimental currency units.
(b) Whether the theory of planned behaviour can explain the influence of ethicalness in
investment behaviour, is tested in two stages with interval regression and linear regression.
First, in the interval regression the dependent variable is again behaviour with intention as
predictor. Statistics reveal that the theory of planned behaviour can explain the influence of
ethicalness (Chi2(3)=166.23, p<.001; Table 4). Each single unit of intention increases the bids
and asks by 0.94 experimental currency units. Second, intention is the dependent variable, and
the predictors to form intention are attitude, subjective norm and control. Results illustrate
that the overall model is significant (R2=.523, p<.001; Table 4). Attitude (b=0.51, p<.001) as
well as subjective norm (b=0.45, p<.001) significantly influence intention, only control does
not show any significant effects. According to the statistical analysis the theory of planned
behaviour can make clear the influence of ethicalness in investment behaviour, but intention
is solely determined by attitude and subjective norm.
6
The variable ethicalness is dichotomous and features 1 for company A and B, which were perceived as
behaving ethically, and 0 for company C and D, which were perceived as not behaving ethically. Companies A
and B, and C and D were pooled into ethicalness, because earlier regression analyses revealed that their
influences on behaviour do not differ between company A and B, and C and D.
7
The variables low and high profit are dichotomous. The variable low profit features 1 for periods in which the
expected dividend was low, and 0 in all other periods. The variable high profit features 1 for periods in which the
expected dividend was high, and 0 in all other periods.
6
Table 4: Interval/OLS regression results by theoretical model
b
SE
p
Multiple attribute utility theory
dependent variable: behaviour
Wald Chi2(3)=166.34, p<.001, n=1362
attribute utility
0.23
0.06
<.001
low profit
-18.33
1.79
<.001
high profit
15.69
1.70
<.001
constant
46.95
1.26
<.001
Theory of planned behaviour
dependent variable: behaviour
Wald Chi2(3)=166.23, p<.001, n=1362
intention
0.94
0.37
.010
low profit
-18.32
1.80
<.001
high profit
15.65
1.70
<.001
constant
47.01
1.27
<.001
dependent variable: intention
R2=.523, F(3, 141)=221.83, p<.001, n=564
attitude
0.51
0.07
<.001
subjective norm
0.45
0.07
<.001
control
-0.001
0.07
.993
constant
0.04
0.39
.927
Issue-contingent model of ethical decision making in organisations
dependent variable: behaviour
Wald Chi2(5)=175.30, p<.001, n=1362
intention
0.72
0.45
.108
moral intensity
-1.37
0.66
.039
social consensus
0.68
0.47
.143
low profit
-18.28
1.80
<.001
high profit
15.41
1.69
<.001
constant
45.41
3.01
<.001
dependent variable: intention
R2=.411, F(3, 141)=152.93, p<.001, n=564
moral intensity
-0.13
0.08
.103
social consensus
0.37
0.05
<.001
moral judgement
0.52
0.05
<.001
constant
1.07
0.31
.001
2
dependent variable: moral judgement
R =.266, F(5, 141)=49.91, p<.001, n=564
moral intensity
0.42
0.08
<.001
social consensus
0.31
0.04
<.001
moral issue
0.17
0.04
<.001
constant
-0.93
0.31
.003
dependent variable: moral issue
R2=.140, F(2, 141)=17.51, p<.001, n=564
moral intensity
0.66
0.11
<.001
social consensus
-0.04
0.05
.397
constant
3.01
0.50
<.001
(c) Whether the issue-contingent model of ethical decision making in organisations can clarify
the influence of ethicalness in investment behaviour, is tested with a four step regression
analysis. First, an interval regression is applied to investigate the influence of intention, moral
intensity and social consensus on bids and asks. Again, statistics show that the issuecontingent model of ethical decision making in organisations fits to clarify the influence of
ethicalness (Chi2(5)=175.30, p<.001; Table 4). Nevertheless, solely the influence of moral
intensity (b=-1.37, p=.039) is significant, intention and social consensus do not have
significant influence. Second, a linear regression explains how intention, now dependent
variable, is generated by the predictors moral intensity, social consensus and moral
judgement. This regression (R2=.411, p<.001; Table 4) shows that social consensus (b=0.37,
p<.001) and moral judgement (b=0.52, p<.001) increase intention, but that moral intensity
does not have a significant influence. Third, a linear regression is applied to clarify the
influence of moral intensity, social consensus and moral issue on moral judgement. Results
(R2=.266, p<.001; Table 4) reveal that moral intensity (b=0.42, p<.001), social consensus
(b=0.31, p<.001) and moral issue (b=0.17, p<.001) significantly influence moral judgement.
Fourth, the last linear regression tests the influence of moral intensity and social consensus on
7
moral issue. Statistics (R2=.140, p<.001; Table 4) show an influence of moral intensity
(b=0.66, p<.001) but not of social consensus. Overall, the issue-contingent model of ethical
decision making in organisations can only be supported with reservations. Although all four
regression analyses are significant and therefore statistics validate that the issue-contingent
model of ethical decision making in organisations can clarify the influence of ethicalness in
investment behaviour, not all theoretically assumed predictors are of influence.
The third research question (3) concerned the comparison between models. For the test
whether the multiple attribute utility theory explains the influence of ethicalness better than
the theory of planned behaviour, the Bayesian information criterions (BIC'; Raftery, 1996) are
estimated. The difference between the Bayesian information criterions of the theory of
planned behaviour (BIC1'=-314.24) and of the multiple attribute utility theory (BIC2'=-317.46)
provides positive support for the multiple attribute utility theory (BIC'1- BIC'2=3.22). Again,
the Bayesian information criterions are generated for the test of, whether the theory of
planned behaviour explains the influence of ethicalness better that the issue-contingent model
of ethical decision making in organisations. The difference between the Bayesian information
criterions of the issue-contingent model of ethical decision making in organisations (BIC1'=309.39) and of the theory of planned behaviour (BIC2'=-314.24) provides positive support for
the theory of planned behaviour (BIC'1- BIC'2=4.85). The difference between the Bayesian
information criterion of the issue-contingent model of ethical decision making in
organisations (BIC1'=-309.39) and of the multiple attribute utility theory (BIC2'=-317.46)
provides very strong support for the multiple attribute utility theory (BIC'1- BIC'2=8.07).Thus,
these results show that multiple attribute utility theory explains the influence of ethicalness in
investment behaviour better than the theory of planned behaviour and than the issuecontingent model of ethical decision making in organisations.
Discussion
The results of the present study show that ethicalness of companies has an effect on
investment behaviour. Based on these results theoretical models are applied to explain how
ethicalness is constituted. The analysis using three theoretical models, multiple attribute
utility theory, theory of planned behaviour (Ajzen, 1985, 1991) and issue-contingent model of
ethical decision making in organisations (Jones, 1991), reveals that investment behaviour is
mainly influenced by expected profits but also by participants’ utility of ethicalness, by
intention to invest and by moral intensity of the investment. According to the model
comparison multiple attribute utility theory fits best to describe investment behaviour.
Although multiple attribute utility theory describes investment behaviour best, and although it
is economical with few variables, this model misses a certain feature. It cannot explain how
the factor ethicalness is constituted and does not provide insight into the decision process. On
the contrary, the theory of planned behaviour pictures this decision process, where the factors
attitude, subjective norm and control determine intention which affects behaviour. Current
results show that attitude and subjective norm predict intention. The issue-contingent model
of ethical decision making in organisations also describes the decision process, but it is very
complex and contains five different factors, which interrelate with each other. These
interrelations make it more difficult to test the model. The factors influence each others
directly as well as via third factors. Although all three models have their limitations, the
theory of planned behaviour seems to be most appropriate to clarify the influence of
ethicalness in investment behaviour, because the regression statistics are significant and it
additionally can describe the decision process leading to investment behaviour.
The present paper offers several starting points for future research. An interesting field study
could investigate the effect of perceived behavioural control on investment behaviour and
confirm the assumption that the missing impact in the current study would show up in a field
study where objective and subjective control are not given. A larger study could again test the
8
Issue-Contingent Model of Ethical Decision Making in Organisations using small single
experiments to avoid too many interrelations between the factors.
The findings of the present paper can practically be applied in marketing for ethical funds and
shares. Although there are some studies (Gallup, 1997, 2002; Hofmann et al., under review)
investigating in which attributes of ethical investment investors are interested and what
ethicalness of investments is composed of, the present experimental approach records actual
behaviour and does not rely on self reports. According to the findings marketing strategies for
ethical funds and shares should take into account the profit investors can realise. Although
some investors might consider ethical investment a kind of donation (Hofmann et al., under
review), the majority is very much interested in financial returns. The theoretical explanation
of ethicalness facilitates to identify the target group for ethical funds and shares. As the utility
of ethicalness and attitudes towards the investment behaviour are important, it can be assumed
that a certain philanthropic and environmentally friendly lifestyle features investors’ interests
in ethical investment (see also Lewis et al., 1998). Finally, opinion leaders could attract
investors, because the strong influence of subjective norm shows that social agreement, which
would be communicated by opinion leaders, plays a role in investment decision making.
The current study presents how moral considerations influence investment behaviour and
gives practical suggestions for marketing strategies, but its main contribution is the disclosure
of the discrepancy between rationality and ethicalness. Regarding ethical investment
behaviour, not only rationality but also ethicalness influence behaviour. Thus, “… the heart
…” [might] “… have reasons that reason cannot know.” (Lopes, 1994, p. 220).
References
Ajzen, I. (1985). From intentions to actions: A theory of planned behaviour. In J. Kuhl & J.
Beckmann (eds.), Action-Control: From Cognition to Behaviour (pp.11-39). Heidelberg:
Springer.
Ajzen, I. (1991). The theory of planned behaviour. Organisational Behaviour and Human
Decision Processes, 50, 179-211.
Anand, P. & Cowton, C.J. (1993). The ethical investor: Exploring dimensions of investment
behaviour. Journal of Economic Psychology, 14, 377-385.
Bamberg, S., Rolle, D. & Weber, C. (2003). Does habitual car use not lead to more resistance
to change of travel mode? Transportation, 30, 97-108.
Baron, J. (2000). Thinking and Deciding (3rd ed.). Cambridge: Cambridge University Press.
Bobek, D. & Hatfield, R. (2003). An investigation of the theory of planned behaviour and the
role of moral obligation in tax compliance. Behavioural Research in Accounting, 15, 13-38.
Borrello, M.G., Morricone, M., Pedon, A. & Benevene, P. (2004). Ethical finance between
saving and investment. Paper presented at the 29th Annual Colloquium of the International
Association for Economic Psychology/ SABE-IAREP Conference, Philadelphia, USA.
Carlson, D.S., Kacmar, K.M. & Wadsworth, L.L. (2002). The impact of moral intensity
dimensions on ethical decision making: Assessing the relevance of orientation. Journal of
Managerial Issues, 14, 15-30.
Chapman, G.B., Elstein, A.S., Kuzel, T.M., Nadler, R.B., Sharifi, R. & Bennett, C.L. (1999).
A multi-attribute model of prostate cancer patients’ preferences for health states. Quality of
Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and
Rehabilitation, 8, 171-180.
Cooper, C. & Schlegelmilch, B. (1993). Key issues in ethical investment. Business Ethics: An
European Review, 2, 213-227.
Cullis, J.G., Lewis, A. & Winnett, A. (1993). Paying to be good? U.K. ethical investments.
Kyklos, 45, 3-24.
East, R. (1993). Investment decisions and the theory of planned behaviour. Journal of
Economic Psychology, 14, 337-375.
9
Flannery, B.L. & May, D.R. (2000). Environmental ethical decision making in the U.S. metalfinishing industry. Academy of Management Journal, 43, 642-662.
Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour. Reading: Addison
Wesley.
Gallup (1997). Repräsentative Umfrage. Ökologische und soziale Geldanlage. Vienna.
[Representative survey. Ecological and social investment]
Gallup (2002). Repräsentative Umfrage. Ökologische und soziale Geldanlage. Vienna.
[Representative survey. Ecological and social investment]
Hofmann, E., Penz, E. & Kirchler, E. (under review). The ‘whys’ and ‘hows’ of ethical
investment. An explorative approach to capture theoretically an early-stage market. Journal
of Business Ethics.
Jones, T.M. (1991). Ethical decision making by individuals in organizations: An issuecontingent model. Academy of Management Review, 16, 366-395.
Kasubek, W. & Aschenbrenner, K.M. (1978). Optimierung subjektiver Urteile. Anwendung
der multiattributen Nutzentheorie bei medizinischen Therapieentscheidungen. Zeitschrift für
Experimentelle und Angewandte Psychologie, 25, 594-616. [Optimisation of subjective
judgements. Application of the Multiple Attribute Utility Theory for decisions of medical therapy.]
Kwak, S.-J., Yoo, S.H. & Kim,T-Y. (2001). A constructive approach to air-quality valuation
in Korea. Ecological Economics, 38, 327-244.
Kwak, S.-J., Yoo, S.H. & Kim,T-Y. (1998). Applying multi-attribute utility theory to decision
making in environmental planning: A case study of the electric utility in Korea. Journal of
Environmental Planning an Management, 41, 597-609.
Lewis, A. (2001). Good money, bad money: The case of socially responsible investment in
UK. World Futures, 56, 399-408.
Lewis, A., Webley, P., Winnett, A. & Mackenzie, C. (1998). Morals and markets: Some
theoretical and policy implications of ethical investing, in P. Taylor-Goodby (ed.), Choice
and Public Policy: The Limits of Welfare Markets (pp. 164-182). Basingstoke: Macmillan.
Lopes, L.L. (1994). Psychology and economics: Perspectives on risk, cooperation, and the
marketplace. Annual Review of Psychology, 45, 197-227.
May, D.R. & Pauli, K.P. (2002). The role of moral intensity in ethical decision making.
Business and Society, 41, 84-117.
Montalvo-Corral, C. (2002). Environmental Policy and Technological Innovation: Why Do
Firms Adopt or Reject New Technologies?. Cheltenham: Elgar.
Raftery, A.E. (1996). Bayesian model selection in social research. In P.V. Marsden (ed.),
Sociological Methodology (Vol. 25, pp.111-163). Oxford: Basil Blackwell.
Schifter, D.B. & Ajzen, I. (1985). Intention, perceived control and weight loss: An application
of the theory of planned behaviour. Journal of Personality and Social Psychology, 49, 843851.
Schlegelmilch, B. (1997). The relative importance of ethical and environmental screening:
Implications for the marketing of ethical investment funds. International Journal of Bank
Marketing, 15, 48-53.
Smith, V.L. (1994). Economics in the laboratory. Journal of Economic Perspectives, 8, 113131.
Sparkes, R. (2001). Ethical investment: Whose ethics, which investment?. Business Ethics: A
European Review, 10, 194-205.
Stewart, M. (1983). On least squares estimation when the dependent variable is grouped.
Review of Economic Studies, 50, 737-753.
Taylor, R. (2000). How new is socially responsible investment?. Business Ethics: A European
Review, 9, 174-179.
Weber, J. (1996). Influences upon managerial moral decision making: nature of the harm and
magnitude of consequences. Human Relations, 49, 1-22.
10