Minggu, 07 Juni 2015
Senin, 30 Maret 2015
Nama : Virgiawan Rahman
NPM :
27211300
Kelas :
4 EB 17
Matakuliah : Akuntansi Internasional
The Role of Individual Variables,
Organizational Variables and Moral Intensity Dimensions in Libyan Management
Accountants’ Ethical Decision Making
Ahmed Musbah •
Christopher J. Cowton • David Tyfa
Received: 21
April 2014/Accepted: 7 October 2014 The
Author(s) 2014. This article is published with open access at Springerlink.com
Abstract This
study investigates the association of a broad set of variables with the ethical
decision making of management accountants in Libya. Adopting a cross-sec-
tional methodology, a questionnaire including four differ- ent ethical
scenarios was used to gather data from 229 participants. For each scenario,
ethical decision making was examined in terms of the recognition, judgment and
intention stages of Rest’s model. A significant relationship was found between
ethical recognition and ethical judg- ment and also between ethical judgment
and ethical intention, but ethical recognition did not significantly pre- dict
ethical intention—thus providing support for Rest’s model. Organizational
variables, age and educational level yielded few significant results. The lack
of significance for codes of ethics might reflect their relative lack of devel-
opment in Libya, in which case Libyan companies should pay attention to their
content and how they are supported, especially in the light of the
under-development of the accounting profession in Libya. Few significant results
were also found for gender, but where they were found, males showed more
ethical characteristics than females. This unusual result reinforces the
dangers of gender ste- reotyping in business. Personal moral philosophy and
moral intensity
dimensions were generally found to be significant predictors of the three stages
of ethical decision making studied. One implication of this is to give more
attention to ethics in accounting education, making the connections between
accounting practice and (in Libya) Islam. Overall, this study not only adds to
the available empirical evidence on factors affecting ethical decision making, notably
examining three stages of Rest’s model, but also offers rare insights into the
ethical views of practising management accountants and provides a benchmark for
future studies of ethical decision making in Muslim majority countries and
other parts of the devel- oping world.
Keywords Ethical
decision making Management
accountants Rest’s model Libya
Introduction
Much research
has been conducted on ethical issues, moral development and ethical decisions
within the general area of business. Some of that research has examined the
ethical reasoning, moral development and ethical decision-making processes of
accounting students and, to some extent, practising accountants, investigating
the variables that might influence their decisions (e.g. Buchan 2005; Ethe-
rington and Schulting 1995; Johl et al. 2012; Marques and Azevedo-Pereira 2009;
O’Leary and Stewart 2007; Svan- berg 2011). However, management accounting is
under-represented in research on accounting ethics in general (Bampton and
Cowton 2013) and in research into ethical decision making in particular. Yet
management accounting is one of the major subject areas in accounting and has
an important role to play in ensuring organizational effectiveness, being
‘concerned with the provision of information to individuals within the
organization to help them make better decisions and improve the efficiency and
effectiveness of existing operations’ (Drury 2004,p.4).Managementaccountants
have several important responsibilities within their orga- nizations, including
budgeting, forecasting, planning, con- trolling operations, safeguarding
assets, managing financial resources and providing information for management
control in general (Woelfel 1986). The aim of this study is to investigate the
association of individual variables, organizational variables and moral
intensity dimensions variables with the ethical decision making of management
accountants. It thus adds to the very limited research on the ethics of
practising manage- ment accountants. Moreover, it is unique in focusing on
Libyan management accountants and, as such, it provides a basis for further
research into ethical decision making in other developing countries, particularly
Muslim majority ones. A further notable feature of the study is that it
examines three stages of Rest’s decision-making model— which is used to frame
the research—whereas most of the many previous studies in business ethics focus
on only one or two stages. The paper is structured as follows. First,
literature regarding the ethical decision-making process is reviewed,
identifying significant related variables and presenting hypotheses. The
research method used is then described, followed by presentation and discussion
of results. Finally, the conclusions, limitations and suggestions for future
research are given.
Literature
Review
Ethical Decision
Making Background
Ethical decision
making is defined as ‘‘a process by which individuals use their moral base to
determine whether a certain issue is right or wrong’’ (Carlson et al.
2002,p.16). Rest’s (1979, 1986)theoreticalframeworkisprobablythe most
influential in terms of research on the ethical deci- sion-making process within
organizations. Rest proposed a four-stage ethical decision-making sequence to
describe individuals’ cognitive stages when facing an ethical dilemma: (1)
ethical recognition—being able to interpret the situation as being ethical or
unethical; (2) ethical judgment—deciding which course of action is ethically
right; (3) ethical intention—prioritizing ethical alterna- tives; and (4)
ethical behaviour—engaging in ethically driven behaviour. Rest argues that all
four stages are conceptually different and that success in one stage does not
mean success in other stages. Wotruba (1990) states that these stages generally
occur in the sequence implied, although they can affect each other. Since the
early 1980s, most ethical decision-making studies and models within the
business area have been heavily based upon Rest’s framework. Business
researchers from different countries in areas such as marketing, accounting and
management have adopted this framework. However, most individual studies have
focused on only one or two stages of Rest’s framework (e.g. Sweeney and
Costello 2009;Weeksetal. 1999;YetmarandEastman
2000).AccordingtothecomprehensivereviewsofO’Fal- lon and Butterfield (2005) and
Craft (2013), taken together, only 18 of more than 250 studies (7 %) have
investigated the three stages of ethical decision making focused upon in this
study (e.g. Bass et al. 1999;NguyenandBiderman 2008). Rest’s basic model has
been developed by various authors. For example, Trevin
˜o(1986)offeredaninterac- tionist ethical decision model, influenced by
Kohlberg’s (1969)theory,andincludesthreepartsofRest’smodelof the ethical
decision-making process. Trevin ˜o’s model describes the ethical
decision-making process in three stages from recognizing the ethical issue,
through to cog- nitive processing, and then finally engaging in real action.
Both individual and organizational variables are incorpo- rated within this
process. Trevin ˜o proposes that ethical decision making is the outcome of an
interaction between individual and organizational variables regarding the individual’s
thinking about ethical dilemmas. Including these variables in an ethical
decision making framework is an important development, since it adds an
explanatory element to Rest’s framework. Hunt and Vitell (1986) developed a
positive theory of marketing ethics by including moral philosophy. Both
deontological and teleological evaluations are used in ethical judgments,
followed by intentions to act and finally ethically driven behaviour. Hunt and
Vitell (1986) argue that ethical judgment does not always agree with the
intention of action, and also ethical behaviour is not always consistent with
the ethical intention. Although Hunt and Vitell add a stage of teleological
evaluation, in which the consequences of the decision are evaluated, they do
not suggest a systematic association between possible conse- quences and
subsequent intentions and behaviour (Jones 1991). Based on Rest’s (1986) model,
Jones (1991) proposed an issue-contingent model of ethical decision making.
Jones argues that, although most models of ethical decision making in business
ethics research were developed on Rest’s (1986) sequential, four component
model, none of these models incorporated the characteristics of the moral issue
itself as either an independent variable or a moder- ating variable (Jones
1991).Jonesclaimsthat characteristics of the ethical issue itself are crucial
deter- minants of the decision-making process, and therefore should be included
in the model of ethical decision making. Thus, business ethics decision-making
research has been built using theoretical models derived from Rest’s (1986)
model of ethical decision making (Groves et al. 2008). Traditionally, one or
more stages (recognition, judgment, intention and behaviour) have been treated
as the outcome variables, while researchers have investigated individual and
organizational variables and moral intensity charac-teristics as predictor
variables (Loe et al. 2000;O’Fallon and Butterfield 2005).Asmentionedearlier,mostprior
research has focused on only one or two stages of ethical decision
making(O’Fallon and Butterfield 2005),whereas this study looks at three out of
the four stages (ethical recognition, ethical judgment and ethical intention).
Only the final stage, ethical behaviour, is omitted, because of its sensitivity
and the related difficulties in measuring it (i.e. observing subjects engaged in
ethical/unethical behaviour). This study examines five individual variables
(age, gender, work experience, educational level and personal moral philosophy),
four organizational variables (type of industry, organizational size, code of
ethics and ethical climate) and three dimensions of moral intensity (magni-
tude of consequences, social consensus and temporal immediacy). The theoretical
framework is shown in Fig. 1. There were several reasons for selecting the
particular variables shown in Fig. 1 from the range of variables covered in the
literature. Firstly, some of these variables— for example age, gender, code of
ethics, ethical climate, magnitude of consequences and social consensus—have
been studied more than other variables in business ethics research (O’Fallon
and Butterfield 2005).Thiswouldbe sufficient reason for including them in the
study, but little research has investigated these variables within developing
countries (Al-Khatib et al. 1995;Shafer 2008)suchas Libya. Secondly, some
variables—such as type of industry, level of education and some dimensions of
moral intensity (e.g. temporal immediacy)—have been paid insufficient attention
by business ethics researchers across countries (e.g. Craft 2013).Thepreviousliteraturerelatingtothe
included variables is reviewed below.
Individual
Variables
A number of
individual variables including demographic characteristics, traits of
personality and beliefs have been proposed to have a significant relationship
with ethical decision-making stages (e.g. Haines and Leonard 2007; Marta et al.
2008;Shafer 2008;VitellandPatwardhan
2008).Forsomeofthevariables,theempiricalresultslook mixed, but on closer
examination it is found that any significant results are all, or mostly, in a
particular direc- tion. One of the possible reasons for other studies finding no
significant relationship is limited sample size, but this cannot be determined
conclusively in the case of any par- ticular study.
Gender
The possible
influence of gender on ethical decision mak- ing has been studied more than any
other variable in business ethics research (O’Fallon and Butterfield 2005).
Differences associated with gender have been theoretically explained in various
ways. Socialization theory (Gilligan 1982) hypothesizes that men and women
bring different sets of values to the workplace because of early sociali-
zation. Women, accordingly, tend to evaluate ethical issues in terms of their
caring view of others, understanding relationships and responsibility to the
entire community; whereas men tend to recognize ethical issues from a per-
spective of rules, fairness, rights and justice. In their meta- analysis,
Jaffee and Hyde (2000) find support for this theory. On the other hand,
structural theory suggests that the occupational environment and the rewards
and costs structure within the workplace will overcome the impact of gender
differences caused by early socialization (Betz et al. 1989). Thus, women and
men will respond equally to ethical issues in the workplace (Reidenbach et al.
1991). In their reviews, Ford and Richardson (1994), Loe et al. (2000),
O’Fallon and Butterfield (2005) and Craft (2013)1 report more than one hundred
results and conclude that gender often tends to produce no significant results,
but when differences are found, women are more sensitive to ethical issues than
men (e.g. Fang and Foucart 2013; Fer- rell and Skinner 1988; Fleischman and
Valentine 2003; Galbraith and Stephenson 1993; Oumlil and Balloun 2009). More
recent research (e.g. Kuntz et al. 2013; Walker et al. 2012) has shown similar
varied results. Given that the results tend to show either no difference or
that females are more ethical than males, this study hypothesizes: Kohlberg’s
theory of moral development suggests a posi- tive impact of age on moral
development as individuals generally move from lower to higher stages of moral
rea-
soning as they
grow older (Borkowski and Ugras 1998). However, research shows inconsistent and
mixed results (Craft 2013; O’Fallon and Butterfield 2005). Some studies (e.g.
Bateman and Valentine 2010; Brady and Wheeler 1996; McMahon and Harvey 2007;
Walker et al. 2012) indicate that age is positively and significantly correlated
with ethical decision making, while others find no signifi- cant relationship
(e.g. Kuntz et al. 2013; Marta et al. 2004; Pierce and Sweeney 2010). However,
it is not generally suggested that ethical decision making is negatively cor-
related with age. Thus, this study hypothesizes:
Educational
Level
Based on the
argument that the length of formal education is an important influence on an
individual’s moral devel- opment (Kohlberg 1981), many researchers suggest that
educational level has a positive impact on the ethical decision-making process
(e.g. Browning and Zabriskie 1983; Kracher et al. 2002; Pierce and Sweeney
2010). However, some researchers (e.g. Dubinsky and Ingram 1984; Marques and Azevedo-Pereira
2009) have not found a significant relationship between the two. Again, though,
it is not generally suggested that increased educational level is negatively
associated with ethical decision making. Thus, this study hypothesizes:
Work Experience
When considering
the effect of work experience on the ethical decision-making process,
Kohlberg’s (1969) theory provides a framework which could suggest a relationship
between work experience and moral development (Trevin ˜o 1986). Glover et al.
(2002) argue that greater experience may be associated with greater awareness
of what is ethi- cally acceptable. Dawson (1997) also proposes that ethical
standards change with years of experience. Ford and Richardson (1994) and Loe
et al. (2000) conclude that empirical research continues to present mixed
results. Nevertheless, recent studies (e.g. Fang and Foucart 2013; O’Leary and
Stewart 2007; Pierce and Sweeney 2010; Valentine and Bateman 2011) generally
indicate a positive relationship between work experience and ethical decision
making, consistent with Kohlberg’s (1969) theory and Trevin ˜o’s (1986)
argument. Thus, this study hypothesizes:
Moral Philosophy
Personal moral
philosophy is another individual variable that has been extensively studied.
Business ethics researchers agree that individuals within organizations will
respond based on their own moral philosophies when encountering situations
having an ethical content (Shultz and Brender-Ilan 2004; Singhapakdi et al.
2000). For example, Hunt and Vitell (1986) stress the importance of moral
philosophies—deontology and teleology—in their model of ethical decision
making. The most common model of personal moral philosophy that has been
examined in the business ethics literature (e.g. Marta et al. 2008) is
Schlenker and Forsyth’s (1977) two-dimensional model consisting of idealism and
rela- tivism. Forsyth (1980, p. 175) posits that these dimensions are distinct;
while moral idealism refers to ‘‘the degree to which an individual focuses upon
the inherent rightness or wrongness of actions regardless of the results of
those actions’’, moral relativism refers to ‘‘the extent to which individuals
reject universal moral rules or standards’’. In making ethical decisions, moral
idealists use idealistic rather than practical criteria; those who have high
ideal- ism believe that desirable results can be attained, and harming others
is universally and always bad and should be avoided (Swaidan et al. 2004).
Relativists, on the other hand, assume that moral rules are relative to the
society and culture in which they occur (Schlenker and Forsyth 1977). Thus,
moral relativists do not accept universal moral rules and codes in making
ethical decisions. Forsyth (1980, 1992 developed an instrument, the Ethics
Position Questionnaire (EPQ), to measure these two dimensions of personal moral
philosophy. Using the EPQ, empirical research, in general, has produced
consistent results suggesting that moral idealism has a significant positive
relationship with ethical decision making, and moral relativism has a
significant negative relationship with ethical decision making (Craft 2013;
O’Fallon and Butterfield 2005). Based on the above, this study hypothesizes:
H1e Idealism is
positively related to ethical recognition, judgment and intention.
H1f Relativism
is negatively related to ethical recogni- tion, judgment and intention.
Organizational
Variables
Organizational
variables are defined as ‘‘characteristics of the decision setting (versus characteristics
of the decision maker or the decision) that should influence the decision-
making process and outcomes’’ (Ross and Robertson 2003, p. 214). These
variables include, for example, codes of
ethics, ethical
climate, organizational size, top manage- ment, organizational structure and
organization culture. Trevin ˜o’s (1986) model proposes that organizational
vari- ables often influence an individual’s ethical decisions.
Code of Ethics
Codes of ethics
have been widely researched in the business ethics literature because of their
potentially significant relationship with ethical decisions (Loe et al. 2000;
O’Fallon and Butterfield 2005). Stevens (1994, p. 64) defines codes of ethics as
‘‘written documents through which corporations hope to shape employee behaviour
and produce change by making explicit statements as to desired behaviour’’.
Thus, a code of ethics in an organization can provide important guidance for
the behaviour of employees (Pater & Anita, 2003; Schwartz, 2002). It is
argued that a code of ethics might not be sufficient by itself to ensure that
the individuals within organizations make ethical decisions (Webley and Werner
2008). For example, successfully communicating a code of ethics to all members
and enforcing it could also be necessary for a code of ethics to work (Chia-Mei
and Chin-Yuan 2006; Cleek and Leonard 1998). Nevertheless, research has
generally suggested that the presence of a code of ethics is positively related
to ethical decision making (Loe et al. 2000; O’Fallon and Butterfield 2005; e.g.
Kaptein 2011; McKinney et al. 2010; Pflugrath et al. 2007). Thus, the following
hypothesis is formulated:
H2a The presence
of a code of ethics is positively related to ethical recognition, judgment and
intention.
Ethical Climate
Ethical climate
is another important organizational variable that has been found to have some
significant influence on employees’ ethical decisions (Ortas et al. 2013). Victor
and Cullen (1988, p. 101) define it as ‘‘the prevailing
Table 1
Theoretical dimensions of ethical climate
Locus of
analysis
Individual Local
Cosmopolitan
Ethical
criterion
Egoism
Self-interest Company interest Efficiency
Benevolence
Friendship Team interest Social responsibility
Principle
Personal morality
Company rules
and procedures
Laws and professional
codes
Source Victor
and Cullen (1988)
Role of
Individual Variables, Organizational Variables and Moral Intensity Dimensions perceptions
of typical organizational practices and proce- dures that have ethical
content’’. They argue that the ethical climate at the workplace will be a
crucial source for employees’ information relating to the ‘‘right’’ or ethical
behaviours within organizations. Based on theories from moral philosophy (e.g.
Williams 1985) and moral psy- chology (Kohlberg 1981), Victor and Cullen (1988)
theo- rize that ethical climate within organizations differs along the three
categories of ethical theory (egoism, benevolence and principle) and the three
loci of analysis (individual, local and cosmopolitan). Nine types of ethical
climate result (see Table 1). It is by far the most completely developed
framework and has been used by several researchers (Miao-Ling 2006). Victor and
Cullen (1987, 1988) suggest that climates characterized by self-interest
(egoistic/individual) and firm interest (egoistic/local) are more likely to be
corre- lated with questionable or unethical behaviour. In con- trast, climates
that emphasize following law and professional codes (principle/cosmopolitan)
and social responsibility or serving the public interest (benevolent/
cosmopolitan) should be associated with more ethical decisions. In their
surveys, Loe et al. (2000) and O’Fallon and Butterfield (2005) review
thirty-four studies and conclude that there is increasing evidence that ethical
climates’ dimensions have a significant relationship with individuals’
decisions. More recently, some studies (Beeri et al. 2013; Elango et al. 2010;
Lu and Lin 2013) indicate a significant impact of ethical climate on ethical
decision stages, while some others (e.g. Buchan 2005; Shafer 2008) provide no
significant results. Thus, this study hypothesizes:
H2b Ethical
climate types are significantly related to ethical recognition, judgment and
intention.
Trevin ˜o et al.
(1998) argue that a reduced number of ethical climate dimensions could be used
to describe the principal characteristics of an organization’s ethical con-
text. In the present study, four out of the nine types of ethical climate are
investigated (organization interest, social responsibility, personal morality,
and law and pro- fessional code). These types have been the most investi- gated
in previous studies. Social responsibility and personal morality may be found
within countries, like Libya, where religion and cultural dimensions are
expected to play a significant role in individuals’ ethical decisions (e.g.
Singhapakdi et al. 2001). Law and professional code and organization interest
have been investigated in several studies, especially in developed countries
(e.g. DeConinck 2004; Parboteeah and Kapp 2008; Wimbush et al. 1997), but only
a few studies have investigated these types of ethical climate in developing
countries (Shafer 2008, 2009).
Organizational
Size
Organizational
size is another characteristic that can have an impact on employees’ ethical
decision making and is also a typical control variable in organizational
research. Differences in work environment between large and small organizations
exist (Appelbaum et al. 2005). It is argued that large organizations might have
business advantages that small organizations might not; therefore, small orga-
nizations might be under pressure to make an unethical decision to compete with
larger organizations (Clarke et al. 1996; Vitell and Festervand 1987). In
contrast, Ford and Richardson (1994) conclude that there is a significant
negative relationship between organizational size and individuals’ ethical
decision making such that, when the size of an organization increases,
individuals’ ethical behaviour decreases. However, more recent research has
revealed a positive significant relationship between orga- nizational size and
ethical decisions or no significant relationship (Doyle et al. 2014; Marta et
al. 2008; Pierce and Sweeney 2010; Sweeney et al. 2010). Given the thrust of
the more recent empirical research, this study hypothesizes:
Industry Type
Industry type
has sometimes been found to have an impact on individual ethical decisions
(e.g. Ergeneli and Arıkan 2002; Forte2004; Roozen et al. 2001; e.g. Shafer et
al. 2001) and, again, is a typical control variable in organizational research.
For example, individuals who work at a place where potentially dangerous
products are produced may be more sensitive to recognizing ethical issues than
individuals who work for companies pro- ducing relatively safe products. Thus,
this study hypothesizes:
Moral Intensity
Jones (1991)
noted that various ethical decision-making models (e.g. Ferrell and Gresham
1985; Rest 1986; Trevin ˜o 1986) included several individual and organizational
vari- ables, but none incorporated the characteristics of ethical issue itself.
However, for example, the issue of misusing equipment in an organization is not
as severe as releasing a dangerous product into the market (McMahon and Harvey
2007). Jones used Rest’s (1986) ethical decision-making model to build his new
construct, which he labelled ‘moral intensity’. According to Jones (1991, p.
372), moral intensity is ‘‘a construct that captures the extent of issue-
related moral imperative in a situation’’. It consists of six components: the
magnitude of consequences of an uneth- ical act (the sum of the harm or benefit
to victims or beneficiaries in a moral act), social consensus (the degree of
social acceptance that a given act is good or evil), probability of effect (the
probability that a given act might actually take place and the probability of
its potential for harm or good), temporal immediacy (the length of time between
the present and the onset of consequences of the moral act in question),
proximity (feeling of nearness that the moral agent has for victims) and
concentration of effect (an inverse function of the number of people affected
by an act of given magnitude). Since the late 1990s, moral intensity has been
given more attention by researchers. Loe et al. (2000), O’Fallon and Butterfield
(2005) and Craft (2013) report fifty-six studies related to the impact of moral
intensity dimen- sions on ethical decision making. Most of these studies (e.g.
Karacaer et al. 2009; May and Pauli 2002; McMa- hon and Harvey 2007;
Singhapakdi et al. 1996; Sweeney and Costello 2009) reveal a positive
significant relation- ship with the ethical decision-making process. These
results are supported by recent research (e.g. Valentine and Bateman 2011;
Valentine and Hollingworth 2012). Although some studies (e.g. Barnett and
Valentine 2004; Davis et al. 1998; May and Pauli 2002; Svanberg 2011) show no
significant relationship, research in general shows a significant and positive
relationship between moral intensity dimensions and ethical decision-making
stages. In practice, researchers have examined a limited range of moral
intensity dimensions (Craft 2013). The role of magnitude of consequences and
social consensus in ethical decisions has been investigated in different areas
such as marketing, management and accounting, revealing more consistent results
than the other moral intensity dimensions (O’Fallon and Butterfield 2005).
Furthermore, there has been limited research concerning the relationship
between temporal immediacy and ethi- cal decision making (O’Fallon and
Butterfield 2005), where temporal immediacy is positively related to moral
intensity. Based on the above, this study hypothesizes:
H3a Magnitude of
consequences is positively related to ethical recognition, judgment and
intention.
H3b Social
consensus is positively related to ethical recognition, judgment and intention.
H3c Temporal
immediacy is positively related to ethical recognition, judgment and intention.
Method
A
cross-sectional research design was employed to collect data from Libyan
management accountants. Participants were assured that their participation
would be voluntary and all responses kept confidential. Since all participants
were Arabic native speakers, the questionnaire was trans- lated into Arabic by
one of the researchers, who is an Arabic native speaker, and checked by three
Arabic aca- demics with more than 20 years of work experience in teaching
English language courses. Arabic questionnaires were piloted to fifteen Libyan
PhD students studying at four British universities. The questionnaire included
four pre-tested scenarios. The four scenarios were originally developed and
produced in a videotape by the Institute of Management Accountants (IMA) in the
USA and adapted by Flory et al. (1992). They have been used in accounting
studies (e.g. Leitsch 2004, 2006; Sweeney and Costello 2009; Yang and Wu 2009)
to examine ethical decision-making stages and moral inten- sity dimensions.
They were considered to illustrate prac- tical accounting issues familiar to
Libyan management accountants—a key feature of scenarios (Randall and Gibson
1990; Weber 1992)—but were adjusted to render them more natural for the Libyan
context. For example, Arabic names were used, and the circumstances of the
decision maker in scenario 4 (college fees) were replaced with different, but
structurally similar, circumstances (hospital fees). The four scenarios
included approving a questionable expense report (scenario 1), manipulating
company books (scenario 2), by-passing company policy (scenario 3) and
extending questionable credit (scenario 4). They are reproduced in the Appendix.
The ethical viola- tions presented in scenarios 2 and 3 were considered more
severe (Flory et al. 1992). Because of the shortcomings of the postal service
and the limited penetration of the internet in Libya, 71 Libyan manufacturing
companies were visited to distribute the questionnaires. Based on a list
provided by the financial/ management accounting manager in each company, the
questionnaire was administered to 392 Libyan management accountants working
within Libyan companies. A total of 229 (58.40 %) completed questionnaires were
collected from the companies. In their review, Randall and Gibson (1990) found
that response rates ranged commonly from 21 to 50 % in business ethics
literature. Bampton and Cowton (2013) found similar results in accounting ethics
research. Thus, the response rate of this study was felt to be more than
satisfactory. The issue of non-response bias was considered; using an
independent samples t test each time, the mean scores of the three dependent
variables (ethical recognition, judgment and intention) of late and early
respondents were compared. No significant differences between the two groups
were found (p\0.05). The pos- sibility of social desirability response bias was
addressed by asking for the questionnaire to be returned in a sealed envelope
and using scenarios rather than asking about the respondent’s own experience
and behaviour. From Table 2,itcanbeseenthatnearlyhalfofthe respondents (45 %)
are more than 40 years old and 75 % are male. Just over a third of the
participants (37 %) have work experience between 5 and 15 years and 58 % have a
Bachelor’s degree. Almost two-thirds of the participants (65 %) work in
companies that are owned by the state. Further, large numbers of participants
(28 and 31 %) work for Food companies and Oil, Gas and Chemicals compa- nies,
respectively, while a minority of participants (4 %) work for Textiles and
Furniture companies. Finally, more than 62 % of the participants reported that
their companies have no code of ethics.
Measures
With regard to
ethical decision-making stages and moral intensity dimensions, participants
were asked to indicate their agreement on a 5-point rating scale (from (1) ‘strongly
disagree’ to (5) ‘strongly agree’). As in the case of much previous research
(Leitsch 2006;Mayand Pauli 2002;McMahonandHarvey 2006;O’Learyand Stewart
2007;SweeneyandCostello 2009;Valentine and Hollingworth 2012;Valentineetal.
2013;Yangand Wu 2009),single-itemscaleswereusedtomeasurethe three stages of
ethical decision making and the moral intensity dimensions. Ethical recognition
was measured by asking participants whether the situation in each scenario
included an ethical issue, ‘‘the situation above involves an ethical problem’’
(Singhapakdi et al. 1996). Ethical judgment was measured by asking participants
whether they agreed with the decision maker’s decision in each scenario, ‘‘[The
decision maker] should not do the proposed action’’ (May and Pauli
2002).Ethical intention was measured by asking participants whether they agreed
or not with the action the decision maker made, ‘‘If I were [the decision
maker], I would make the same decision’’ (reverse-coded) (Singhapakdi et al.
1996). Regarding moral intensity dimensions, magnitude of consequences was
assessed by ‘‘The overall harm (if any) as a result of the action would be very
small’’ (reverse- coded). Social consensus was measured by ‘‘Most people would
agree that the action is wrong’’. Temporal
Table 2
Demographic characteristics of participants
a Formal
industry classification in Libya according to central industrial information and
documentation
Age and gender
\30 years 30–\35 years 35–40 years [40 years Total
Females (%) 8 6
7 4 25 Males (%) 9 11 14 41 75 % 17 17 21 45 100
Work experience
and gender \5 years 5–\15 years 15–25 years [25 years Total
Females (%) 7 12
5 1 25 Males (%) 11 25 25 14 75 % 18 37 30 15 100
Educational
level High school or equivalent Higher Department Bachelor’s Master’s or higher
% 16 21 58 5
Ownership
State-owned company
Joint venture
(State and private)
Private company
Joint venture
(State and foreign)
Joint venture
(Private and foreign)
% 65 12 12 6 5
Industry typea
Food Textiles,
furniture
Engineering,
metal and electric
Oil, gas and
chemicals
Cement and
building materials
% 28 4 18 31 19
Organizational
size 50–499 employees 500–999 employees [999 employees
% 42 22 36
Codes of ethics
Participants who said yes Participants who said no
% 38 62
immediacy was
measured by ‘‘the decision maker’s action will not cause any harm in the
immediate future’’ (reverse- coded). Personal moral philosophy was measured by
adopting the well-established Ethics Position Questionnaire (EPQ) constructed
by Forsyth (1980). It has been successfully used and validated by several
ethics studies (e.g. Chan and Leung 2006;Dubinskyetal. 2004;MarquesandAzevedo-
Pereira 2009;Shafer 2008;SinghapakdiandVitell 1993). The EPQ consists of two
scales, each containing 10 items provided with a scale of agreement based on a
5-point rating (from (1) ‘strongly disagree’ to (5) ‘strongly agree’) to
measure personal moral philosophy (idealism and rela- tivism). The internal
reliability result for this instrument (idealism a = 0.74 and relativism a =
0.79) showed an acceptable level of Cronbach’s alpha for each dimension
(Nunnally 1978). The Ethical Climate Questionnaire (ECQ) developed by Victor
and Cullen (1987, 1988)wasadoptedtomeasurethe ethical climate in Libyan
companies. It has been used and validated in a number of prior studies (e.g.
Cullen and Victor 1993;DeConinckandLewis 1997;Fritzsche 2000; Lu and Lin
2013;MalloyandAgarwal 2001;Shafer 2008). The scale of agreement is based on a
6-point rating (from (5) ‘completely true’ to (0) ‘completely false’). Four of
the nine ethical climate types were examined in this study: organization
interest, social responsibility, personal morality and law and professional
code. In their meta- analysis, Martin and Cullen (2006) concluded that in most
organizations studied, not all distinct climate types existed. Trevin ˜o et al.
(1998) argue that evidence shows that a reduced number of the dimensions of
ethical climate could be used to explain some characteristics of the moral
situ- ation within organizations. These types have been most investigated in
previous studies, and therefore are expected to be found within Libyan
companies. For example, social responsibility and personal morality may be
found within countries where religion and cultural dimensions (power distance,
uncertainty avoidance, and collectivism) play a significant role in individuals’
ethical decisions. The internal reliability result of this instrument showed an
acceptable level of Cronbach’s alpha for each climate type: organization interest
a = 0.72, social responsibility a = 0.74, personal morality a = 0.65 and law
and pro- fessional code a = 0.79 (Nunnally 1978).Severalbusiness ethics studies
obtained similar levels of reliability for the four types of ethical climate
investigated (e.g. Agarwal and Malloy 1999;Shafer 2008, 2009;Upchurch 1998;Van-
Sandt et al. 2006;Vardi 2001;VeneziaandCallano 2008). For measuring categorical
variables, participants were asked to provide information about their gender,
age, years of experience, educational level, type of industry, their
company’s size
and whether their companies have a code of ethics or any kind of ethical
guidelines.
Data Analysis
Data were
entered into SPSS (version 20). Categorical variables of gender, age,
educational level, work experi- ence, organizational size, type of industry and
code of ethics were analysed using independent samples t tests and one-way
independent samples ANOVA tests. Continuous variables of personal moral
philosophy, ethical climate types, moral intensity dimensions and ethical
recognition and judgment were analysed using hierarchical multiple regression.
The sequence of variable entry into the regression hierarchy reflected the
theoretical model—both the stages of Rest’s model and the logic of the various
factors (e.g. individual factors are essentially ‘‘prior’’ to the others). When
ethical recognition was the criterion variable, the order of predictor variable
entry into the regression was individual variables followed by organizational
variables and then moral intensity dimensions in the final model. When ethical
judgment was the criterion, ethical recogni- tion was entered first, followed by
the above order for other variables. Similarly, ethical recognition and ethical
judg- ment were entered first when ethical intention was the criterion. Several
previous studies (e.g. Bateman et al. 2013;MarquesandAzevedo-Pereira
2009;Sweeneyetal. 2010;SweeneyandCostello 2009;ValentineandBateman
2011;YangandWu 2009)havealsochosenthisorderof variable entry. The data were
checked for outlying and influential values but no responses needed removing.
Scatterplots of standardized predicted values versus standardized residuals
were used to assess assumptions of normality, linearity and homoscedasticity
(Tabachnick and Fidell 2007).Only 13 % of the scatterplots showed assumption
violations, and regression is reasonably robust to minor violations (Howell
2006).Thevarianceinflationfactorshowednomulticol- linearity, and the
Durbin-Watson test showed that errors were independent. The sample size was
adequate with at least 15 cases per predictor (Field 2009;VitellandPat- wardhan
2008).
Results
Analysis of
Categorical Variables
Means, standard
deviations and results for one-way inde- pendent groups ANOVA and t tests are
shown in Tables 3 and 4.Meansindicatethat,onaverage,Libyan management
accountants recognized the ethical issue pre- sented in each scenario, judged
it as unethical and had limited intention to behave unethically across
individual variables, organizational variables and moral intensity dimensions
(mean scores were 3 or above). With respect to gender, only two significant
results were found in relation to the ethical recognition stage. Moreover, the
results were in the opposite direction to that predicted; males displayed
significantly higher ethical recognition. Thus, H1a was rejected. Also, there
were only two significant differences in ethical recognition based on age and
one for work experience and two significant differences in ethical intention
based on education level. Thus, H1b, H1c and H1d were rejected. With regard to
categorical organizational variables, similar results were found: two
significant differences for organizational size (one in ethical judgment and one
in ethical intention) and no significant differences based on code of ethics and
type of industry. Accordingly, H2a, H2b and H2c were rejected.2
Multiple
Regression Analysis of Continuous Variables
Ethical
Recognition
Model 1, as shown
in Table 5,indicatesthatpersonal moral philosophy (idealism and relativism)
accounts for 7 to 9 % of the variation in ethical recognition of manage- ment
accountants in the first three scenarios (p\0.001). When the types of ethical
climate were added (model 2), these proportions increased, ranging from 10 to
12 %, also in the first three scenarios (p\0.001). However, these increases
(DR2) were only significant in scenario three (p\0.05). Finally, by adding moral
intensity dimensions to the model (model 3), the proportions again were
improved; they explained 14–32 % of the variation in ethical recognition of
management accountants. The model was now significant for all scenarios
(p\0.001). With the exception of scenario 1, all increases (DR2) were statisti-
cally significant (p\0.001). The b-values depicted in Table 5 (model 3) indicate
that moral idealism had a positive significant relationship with ethical
recognition in scenarios 1, 2 and 3. Moral relativism showed a negative
significant relationship with ethical recognition in scenario 1 and 3. Thus,
hypotheses H1e and
H1f were
supported with respect to the ethical recognition stage. There were only a few
significant results related to ethical climate types; law and professional codes
had only one positive significant relationship in scenario 3 and the same for
social responsibility in scenario 1. Finally, there was a significant negative
relationship between personal morality and ethical recognition in scenario 1.
Therefore, there was limited support for H2b with respect to the eth- ical
recognition stage. Regarding moral intensity dimensions, a significant positive
relationship was found between magnitude of consequences and ethical
recognition in scenarios 2 and 3, and similarly for social consensus in
scenarios 3 and 4. Temporal immediacy was positively and significantly related
to ethical recognition in the four scenarios. Thus, hypotheses H3a, H3b and H3c
were supported with respect to the ethical recognition stage.
Ethical Judgment
Table 6
indicates that ethical recognition explained 11–33 % of the variation in
ethical judgment, and the model was significant in the four scenarios (p\0.001).
By adding personal moral philosophy components (model 2) and ethical climate
types (model 3), these proportions were enhanced ranging from 17 to 36 %, and
the models were again significant. Including moral intensity dimensions (model
4) led to a statistically significant improvement in all scenarios (p\0.001),
accounting for 20 to 51 % of the variation in ethical judgment. The b-values in
Table 6 (model 4) indicate that moral idealism had a positive significant
relationship with ethical judgment in scenarios 1 and 2. In contrast, moral
relativism was not significantly related to ethical judgment in any scenario,
and hence there was limited support for H1e and H1f with regard to ethical
judgment. With respect to ethical climate types, b-values showed very limited
significant relationships. Thus, H2b was rejected with respect to ethical
judgment. For moral intensity dimensions, the b-values of magnitude of
consequences showed a positive significant relationship in scenario 4 and
similarly for temporal imme- diacy in scenario 1. Social consensus had a
positive signifi- cant relationship with ethical judgment in scenarios 3 and 4.
Thus, thesefindings provide some statistical support for H3b and limited support
for H3a and H3c with regard to ethical judgment. Finally, ethical recognition
was a positive sig- nificant predictor of ethical judgment in all four
scenarios.
Ethical
Intention
Table 7 shows
that ethical recognition and ethical judg- ment (model 2) explained 10 to 33 %
of the variation in
2 It was decided
not to report the following regressions with dummy- coded categorical variables
included, given their lack of relationship with the ethical decision making
stages. If one does include them, then their minimal influence is confirmed (only
5 % of the additional results generated from the categorical predictors were
significant in the final regression models, while 93 % of the significant continuous
predictors were still significant).
Table3CategoricalindividualvariablesandEDMstages:Mean(S.D.)andinferentialresults
VariablesandScenariosEthicalrecognitionEthicaljudgmentEthicalintention
123412341234
Age
\30years4.0(1.2)3.9(1.1)3.5(1.1)3.0(1.2)4.3(1.0)4.2(0.9)3.6(1.0)3.5(1.1)4.1(1.0)3.8(1.0)3.5(1.1)3.3(1.2)
30–\35years4.2(1.0)4.1(1.0)3.6(1.2)3.3(1.2)4.3(1.0)4.0(1.1)3.8(1.0)3.6(1.1)4.0(1.0)3.7(1.3)3.5(1.3)3.4(1.2)
35–40years4.3(0.9)4.2(.09)3.7(1.1)3.5(1.9)4.5(0.7)4.0(1.2)3.4(1.1)3.6(1.0)3.9(1.2)3.6(1.3)3.3(1.2)3.5(1.2)
[40years4.2(1.0)4.4(0.8)3.5(1.1)3.6(1.1)4.3(0.9)4.3(0.8)3.8(1.0)3.7(1.0)4.1(1.0)3.7(1.4)3.4(1.1)3.3(1.2)
F0.562.67*0.393.50*0.731.652.230.480.650.130.310.34 Gender
Females4.0(1.1)4.0(1.1)3.6(1.1)3.1(1.3)4.4(0.8)4.1(0.9)3.6(1.1)3.5(1.1)4.0(0.9)3.8(1.0)3.5(1.1)3.3(1.1)
Males4.2(1.0)4.3(0.8)3.6(1.1)3.5(1.1)4.3(0.9)4.2(1.0)3.7(1.0)3.7(1.0)4.1(1.1)3.7(1.4)3.4(1.2)3.4(1.2)
t-1.40-2.23*0.23-2.24*0.39-0.79-0.80-0.660.59-0.88-0.880.65 Educationallevel
HighSchoolandID3.8(1.1)4.1(1.0)3.2(1.0)3.4(1.0)4.5(0.6)4.3(0.8)3.9(1.0)3.7(1.0)3.9(1.0)3.2(1.4)3.5(1.5)2.9(1.1)
HigherDiploma4.2(1.0)4.3(0.8)3.5(1.2)3.2(1.4)4.3(0.9)4.2(1.0)3.5(1.1)3.4(1.1)4.1(1.2)3.6(1.3)3.3(1.2)3.2(1.2)
Bachelor’s4.2(0.9)4.2(0.9)3.7(1.1)3.5(1.1)4.3(0.9)4.1(1.0)3.6(1.0)3.7(1.0)4.0(1.1)3.9(1.2)3.4(1.1)3.5(1.1)
Master’sormore4.5(0.7)4.2(0.9)3.8(1.1)3.9(0.7)4.4(0.8)4.0(1.2)4.3(0.7)3.7(1.1)4.3(0.8)3.5(1.4)3.9(1.0)3.3(1.3)
F2.060.231.201.300.320.242.380.870.443.23*0.943.20* Workexperience
\5years4.1(1.0)4.0(1.2)3.6(1.1)2.7(1.2)4.3(0.9)4.1(0.9)3.6(1.0)3.5(1.1)4.2(0.9)3.9(1.0)3.5(1.1)3.3(1.1)
5–\15years4.3(0.9)4.2(0.9)3.8(1.1)3.5(1.1)4.4(0.9)4.1(1.1)3.6(1.1)3.5(1.1)4.0(1.1)3.7(1.3)3.4(1.2)3.5(1.2)
15–25years4.0(1.1)4.4(0.7)3.5(1.2)3.6(1.1)4.4(0.9)4.3(0.9)3.6(1.1)3.7(1.0)3.9(1.1)3.9(1.2)3.5(1.2)3.3(1.2)
[25years4.3(0.9)4.3(1.0)3.5(1.0)3.7(1.0)4.3(0.8)4.3(0.7)4.0(0.9)3.9(0.9)4.3(0.9)3.4(1.6)3.4(1.2)3.1(1.2)
F1.091.701.037.80**0.100.661.491.181.631.450.371.39
1scenario1;2scenario2;3scenario3;4scenario4
*p\0.05 **p\0.001
Table4CategoricalorganizationalvariablesandEDMstages:Mean(S.D.)andinferentialresults
VariablesandScenariosEthicalrecognitionEthicaljudgmentEthicalintention
123412341234
Codeofethics
Hascodeofethics4.2(1.0)4.3(0.8)3.7(1.1)3.6(1.1)4.2(0.8)4.1(1.0)3.7(1.0)3.5(1.0)3.9(1.1)3.6(1.3)3.4(1.2)3.1(1.2)
Hasnocodeofethics4.2(1.0)4.2(1.0)3.5(1.2)3.3(1.2)4.4(1.0)4.2(0.9)3.7(1.0)3.7(1.1)4.1(1.0)3.8(1.2)3.4(1.1)3.5(1.1)
t-0.340.591.401.47-1.35-0.990.01-1.35-1.41-1.29-0.49-1.97 Organizationalsize
50–499employees4.2(1.0)4.3(0.9)3.5(1.2)3.5(1.2)4.4(0.9)4.1(1.0)3.5(1.1)3.8(0.9)4.0(1.1)3.4(1.4)3.3(1.2)3.3(1.2)
500–999employees4.2(1.1)4.0(1.0)3.6(1.2)3.2(1.3)4.1(1.0)4.2(0.9)3.7(1.0)3.3(1.2)3.9(1.0)3.6(1.3)3.3(1.2)3.2(1.2)
[999employees4.2(0.9)4.3(0.9)3.7(1.1)3.5(1.1)4.5(0.7)4.3(0.9)3.8(1.0)3.6(1.0)4.2(1.0)4.1(1.0)3.6(1.1)3.4(1.1)
F0.121.900.831.564.70*0.651.302.901.816.58*1.000.72 Industrytype
Food4.1(1.2)4.3(0.9)3.6(1.2)3.4(1.3)4.3(0.9)4.2(0.8)3.8(0.9)3.6(1.1)4.1(1.0)3.7(1.3)3.5(1.2)3.2(1.2)
Textiles,paperandfurniture4.5(0.7)4.1(1.1)4.2(1.0)3.7(1.3)4.3(1.3)3.9(1.3)3.6(1.2)3.9(1.0)4.1(1.3)3.2(1.3)3.6(1.3)3.4(1.0)
Metal,electricandengineering4.2(0.7)4.1(0.9)3.5(1.0)3.5(1.1)4.3(0.9)4.0(1.1)3.6(1.0)3.6(1.0)3.9(1.0)3.6(1.3)3.3(1.3)3.2(1.2)
Oil,gasandchemicals4.2(1.0)4.3(0.9)3.6(1.1)3.4(1.1)4.5(0.7)4.3(0.9)3.7(1.0)3.7(1.1)4.2(1.0)4.0(1.1)3.5(1.0)3.5(1.0)
Cementandbuilding4.1(1.0)4.1(1.0)3.6(1.1)3.4(1.1)4.2(0.9)4.3(1.0)3.4(1.1)3.6(1.0)4.0(1.1)3.6(1.3)3.1(1.1)3.4(1.2)
F0.580.610.830.251.401.031.390.290.371.261.520.63
*p\0.05
**p\0.001 1scenario1;2scenario2;3scenario3;4scenario4
ethical
intention in all scenarios (p\0.001). When adding personal moral philosophy
(model 3), the proportions were improved and explained 14–37 % of the variation
in ethical intention in the four scenarios (p\0.001). Including eth- ical
climate types showed no significant improvement in the model. Finally, adding
the dimensions of moral inten- sity enhanced the model (model 5), accounting
for 31–48 % of the variation in ethical intention. These increases (DR2) were
statistically significant in all scenarios. The b-values shown in Table 7 (model
5) indicate that moral idealism had a positive significant relationship with
ethical intention but only for scenario 1. However, more significant and
negative relationships were found regarding the impact of moral relativism on
ethical intention. Thus, H1e and H1f were supported with respect to the ethical
intention stage. No significant result was found related to the relationship
between ethical climate types and ethical
intention. Thus,
H2b was rejected with regard to the ethical intention stage. The b-values of
moral intensity dimensions indicate that magnitude of consequences is
positively and significantly related to ethical intention in the four sce-
narios. However, b-values of social consensus and tem- poral immediacy revealed
limited significant results related to ethical intention. Hence, these results
provide a full support for H3a and limited support for H3b and H3c with regard
to ethical intention. Finally, while ethical recogni- tion was not a significant
predictor of ethical intention, ethical judgment had a positive significant
relationship with ethical intention in three of the four scenarios.
Discussion
In this section,
the results of this study in terms of the associations between individual
variables, organizational
Table 5
Hierarchical regression results for ethical recognition (continuous variables)
Variables and
scenarios Scenario 1 Scenario 2 Scenario 3 Scenario 4
B St. E b B St.
E b B St. E b B St. E b
Model 1 Constant
2.46 0.58 2.85 0.54 2.59 0.67 3.73 0.71 Idealism 0.54 0.13 0.27** 0.49 0.12
0.27** 0.46 0.15 0.21* 0.02 0.16 0.01 Relativism -0.20 0.09 -0.15* -0.24 0.08
-0.19* -0.32 0.10 -0.21* -0.13 0.11 -0.09 R2 (F) 0.08 (9.34**) 0.09 (10.29**)
0.07 (7.91**) 0.01 (0.82) Model 2 Constant 2.67 0.61 2.69 0.57 2.24 0.70 3.59
0.75 Idealism 0.55 0.13 0.28** 0.48 0.13 0.26** 0.42 0.15 0.19* 0.01 0.17 0.01
Relativism -0.18 0.10 -0.13 -0.26 0.09 -0.21* -0.35 0.10 -0.29* -0.14 0.11
-0.09 LC -0.11 0.10 -0.10 0.05 0.09 0.05 0.31 0.11 0.23* 0.16 0.12 0.11 CI
-0.04 0.10 -0.03 0.10 0.09 0.10 0.08 0.11 0.07 -0.02 0.12 -0.01 SR 0.23 0.11
0.20* 0.01 0.10 0.01 -0.13 0.12 -0.10 -0.02 0.14 -0.01 PM -0.19 0.08 -0.18*
-0.08 0.07 -0.08 -0.12 0.09 -0.10 -0.08 0.10 -0.06 R2 (F) 0.12 (4.73**) 0.10
(4.03*) 0.12 (4.69**) 0.02 (0.65) DR2 (FD) 0.04 (2.31) 0.02 (0.91) 0.05 (2.94*)
0.01 (0.58) Model 3 Constant 2.62 0.64 1.34 0.58 0.20 0.67 2.43 0.72 Idealism
0.55 0.13 0.28** 0.38 0.12 0.21* 0.33 0.14 0.15* -0.10 0.15 -0.04 Relativism
-0.20 0.10 -0.15* -0.16 0.08 -0.12 -0.26 0.09 -0.17* -0.19 0.10 -0.12 LC -0.13
0.10 -0.10 -0.03 0.09 -0.01 0.30 0.10 0.21* 0.10 0.11 0.07 CI -0.04 0.10 -0.03
0.05 0.09 0.05 0.07 0.10 0.06 0.01 0.11 0.01 SR 0.21 0.11 0.18 0.04 0.10 0.04
-0.19 0.11 -0.15 -0.05 0.12 -0.03 PM -0.20 0.08 -0.18* -0.05 0.07 -0.05 -0.01
0.08 -0.01 -0.08 0.09 -0.06 MC -0.04 0.07 -0.05 0.24 0.06 0.27** 0.19 0.08
0.17* -0.06 0.09 -0.05 SC -0.03 0.05 -0.04 0.05 0.05 0.06 0.20 0.07 0.19* 0.39
0.07 0.36** TI 0.14 0.06 0.16* 0.14 0.06 0.16* 0.26 0.08 0.25* 0.28 0.09 0.24*
R2 (F) 0.14 (3.77**) 0.25 (7.77**) 0.32 (11.14**) 0.24 (7.29**) DR2 (FD) 0.02
(1.77) 0.15 (13.79**) 0.21 (21.36**) 0.22 (20.26**)
LC law and
codes; CI company interest; SR social responsibility; PM personal morality; MC
magnitude of consequences; SC social consensus; TI temporal immediacy * p\0.05
** p\0.001
Role of
Individual Variables, Organizational Variables and Moral Intensity Dimensions
123
variables and
moral intensity and the three stages of ethical decision making are discussed.
Individual
Variables
In terms of
personal moral philosophy, the results indicate that moral idealism was the
individual variable that was generally the strongest predictor of the three
stages of ethical decision making for management accountants. Moral relativism
was sometimes found to be negatively
related (but
generally less strongly than moral idealism) to the decision. These results are
consistent with previous research (e.g. Dubinsky et al. 2004;SparksandHunt
1998; Yetmar and Eastman 2000).Intheirreviewoftheethical decision-making
literature, O’Fallon and Butterfield (2005) come to the conclusion that idealism
and relativism revealed fairly consistent results over the last few decades of
ethical research. They conclude that idealism is posi- tively related to
ethical decision making, while relativism is negatively associated with ethical
decision making.
Table 6
Hierarchical regression results for ethical judgment (continuous variables)
Variables and
scenarios Scenario 1 Scenario 2 Scenario 3 Scenario 4
B St.E b B St.E
b B St.E b B St.E b
Model 1 Constant
3.15 .24 2.27 0.27 2.13 .20 1.86 0.18 ER 0.29 0.06 0.33** 0.45 0.06 0.44** 0.43
0.05 0.47** 0.52 0.05 0.58** R2 (F) 0.11 (26.55**) 0.19 (51.42**) 0.22
(61.74**) 0.33 (110.02**) Model 2 Constant 2.10 0.52 1.07 0.54 1.38 0.57 0.82
0.55 ER 0.26 0.06 0.29** 0.39 0.06 0.37** 0.42 0.06 0.46** 0.52 0.05 0.58**
Idealism 0.27 0.12 0.16* 0.43 0.12 0.22** 0.17 0.13 0.08 0.21 0.12 0.10
Relativism 0.01 0.08 0.01 -0.12 0.08 -0.09 0.01 0.09 0.01 0.05 0.08 0.03 R2 (F)
0.13 (10.93**) 0.24 (22.38**) 0.23 (21.27**) 0.35 (38.36**) DR2 (FD) 0.02
(2.89) 0.05 (6.56*) 0.01 (1.03) 0.01 (2.02) Model 3 Constant 2.21 0.54 1.11
0.57 1.21 0.60 0.61 0.58 ER 0.24 0.06 0.27** 0.38 0.07 0.37** 0.41 0.06 0.45**
0.51 0.05 0.57** Idealism 0.28 0.12 0.16* 0.43 0.12 0.23* 0.14 0.13 0.07 0.17
0.12 0.08 Relativism 0.00 0.08 0.00 -0.12 0.08 -0.09 0.01 0.09 0.01 0.05 0.08
0.03 LC 0.12 0.09 0.11 0.06 0.09 0.05 0.02 0.10 0.02 0.17 0.09 0.13 CI 0.05
0.09 0.05 0.01 0.09 0.01 -0.03 0.10 -0.03 -0.11 0.09 -0.09 SR -0.03 0.09 -0.03
-0.03 0.10 -0.03 0.16 0.11 0.13 0.04 0.10 0.04 PM -0.19 0.07 -0.20* -0.05 0.07
-0.04 -0.06 0.08 -0.05 -0.02 0.07 -0.01 R2 (F) 0.17 (6.32**) 0.24 (9.59**) 0.24
(9.61**) 0.36 (17.13**) DR2 (FD) 0.04 (2.61*) 0.00 (0.24) 0.01 (.89) 0.01
(1.13) Model 4 Constant 1.92 0.56 0.49 0.59 0.42 0.61 -0.49 0.54 ER 0.22 0.06
0.25** 0.29 0.07 0.28** 0.28 0.06 0.31** 0.38 0.05 0.42** Idealism 0.28 0.12
0.16* 0.42 0.12 0.22* 0.15 0.12 0.07 0.08 0.11 0.04 Relativism -0.01 0.08 -0.01
-0.08 0.08 -0.06 0.02 0.08 0.02 0.10 0.07 0.07 LC 0.11 0.09 0.10 0.02 0.09 0.01
0.03 0.09 0.02 0.16 0.08 0.12 CI 0.02 0.09 0.02 -0.02 0.09 -0.02 -0.03 0.09
-0.03 -0.11 0.08 -0.10 SR -0.03 0.09 -0.03 -0.01 0.10 -0.00 0.08 0.10 0.06 0.07
0.09 0.06 PM -0.18 0.07 -0.19* -0.03 0.07 -0.03 -0.01 0.07 -0.01 -0.02 0.06
-0.02 MC 0.00 0.06 0.00 0.08 0.07 0.09 0.03 0.07 0.03 0.28 0.06 0.28** SC 0.04
0.04 0.06 0.09 0.05 0.11 0.27 0.06 0.27** 0.13 0.06 0.13* TI 0.13 0.05 0.17*
0.11 0.07 0.12 0.10 0.07 0.11 0.12 0.07 0.11 R2 (F) 0.20 (5.37**) 0.28 (8.20**)
0.32 (10.02**) 0.51 (22.07**) DR2 (FD) 0.03 (2.79*) 0.04 (3.99*) 0.08 (8.59**)
0.15 (21.86**)
LC law and
codes; CI company interest; SR social responsibility; PM personal morality; MC
magnitude of consequences; SC social consensus; TI temporal immediacy; ER
ethical recognition * p\0.05 ** p\0.001
A. Musbah et al.
123
Table 7
Hierarchical Regression Results for Ethical Intention (Continuous Variables)
Variables and
scenarios Scenario 1 Scenario 2 Scenario 3 Scenario 4
B St.E b B St.E
b B St.E b B St.E b
Model 1 Constant
3.10 0.30 2.01 0.38 1.90 0.24 1.97 0.22 ER 0.23 0.07 0.22* 0.40 0.09 0.29**
0.42 0.06 0.41** 0.40 0.06 0.40** R2 (F) 0.05 (10.58*) 0.09 (20.71**) 0.17
(45.09**) 0.16 (41.97**) Model 2 Constant 1.35 0.35 1.56 0.43 0.95 0.27 0.93
0.25 ER 0.06 0.07 0.06 0.31 0.10 0.23* 0.23 0.07 0.23* 0.11 0.07 0.11 EJ 0.56
0.08 0.47** 0.20 0.09 0.15* 0.45 0.07 0.40** 0.56 0.08 0.50** R2 (F)0.24 (34.46**)
0.10 (12.69**) 0.29 (45.47**) 0.33 (52.52**) DR2 (FD) 0.20 (55.68**) 0.02
(4.35*) 0.12 (38.19**) 0.17 (53.10**) Model 3 Constant 0.53 0.58 2.92 0.77 0.62
0.62 2.63 0.61 ER 0.01 0.07 0.01 0.29 0.10 0.21* 0.22 0.07 0.21* 0.08 0.07 0.08
EJ 0.52 0.07 0.44** 0.19 0.10 0.15* 0.44 0.07 0.39** 0.59 0.08 0.52** Idealism
0.43 0.13 0.21* -0.05 0.17 -0.02 0.14 0.14 0.06 -0.21 0.13 -0.09 Relativism
-0.21 0.09 -0.15* -0.32 0.11 -0.19* -0.07 0.09 -0.04 -0.26 0.09 -0.16* R2 (F)
0.29 (21.80**) 0.14 (8.89**) 0.30 (22.97**) 0.37 (31.04**) DR2 (FD) 0.05
(7.17*) 0.04 (4.67*) 0.00 (0.62) 0.04 (6.77*) Model 4 Constant 0.52 0.62 2.67
0.81 0.41 0.65 2.75 0.64 ER -0.01 0.07 -0.01 0.27 0.10 0.20* 0.20 0.07 0.20*
0.08 0.07 0.08 EJ 0.51 0.08 0.43** 0.19 0.10 0.14 0.43 0.07 0.38** 0.60 0.08
0.54** Idealism 0.43 0.13 0.21* -0.08 0.18 -0.03 0.12 0.14 0.05 -0.19 0.13
-0.08 Relativism -0.22 0.09 -0.15* -0.35 0.12 -0.21* -0.09 0.10 -0.06 -0.27
0.09 -0.17* LC 0.07 0.10 -0.06 0.14 0.13 0.09 0.06 0.11 0.04 -0.16 -0.11 0.11
CI 0.08 0.11 0.07 0.08 0.13 0.06 0.08 0.10 0.06 0.15 0.10 0.12 SR 0.12 0.11
0.10 -0.02 0.14 -0.02 0.05 0.11 0.04 0.06 0.11 0.04 PM -0.09 0.08 -0.08 -0.05
0.10 -0.04 -0.06 0.08 -0.05 -0.10 0.08 -0.08 R2 (F) 0.30 (11.38**) 0.15
(4.80**) 0.31 (11.90**) 0.38 (16.31**) DR2 (FD) 0.01 (0.97) 0.01 (0.75) 0.01
(0.88) 0.02 (1.37) Model 5 Constant 0.10 0.63 1.17 0.77 -0.80 0.62 1.77 0.62 ER
-0.02 0.07 -0.02 0.12 0.10 0.09 0.04 0.07 0.04 0.05 0.06 0.05 EJ 0.48 0.08
0.40** 0.05 0.16 0.04 0.32 0.07 0.28** 0.37 0.08 0.33** Idealism 0.41 0.13
0.20* -0.07 0.11 -0.03 0.13 0.13 0.06 -0.24 0.12 -0.11* Relativism -0.21 0.09
-0.14* -0.25 0.12 -0.15* -0.08 0.09 -0.05 -0.22 0.09 -0.14* LC -0.10 0.10 -0.07
0.02 0.12 0.02 0.11 0.10 0.08 -0.17 0.09 -0.08 CI 0.07 0.11 0.06 0.01 0.09 0.01
0.07 0.09 0.06 0.12 0.09 0.09 SR 0.10 0.11 0.08 0.05 0.13 0.04 0.00 0.10 -0.00
0.09 0.10 0.06 PM -0.07 0.08 -0.06 -0.01 0.09 -0.01 0.02 0.07 0.02 -0.10 0.07
-0.08 MC 0.13 0.06 0.14* 0.25 0.09 0.21* 0.30 0.08 0.28** 0.18 0.08 0.16* SC
0.01 0.05 0.01 0.34 0.07 0.32** 0.12 0.06 0.11 0.11 0.06 0.10 TI 0.08 0.06 0.09
0.13 0.09 0.11 0.15 0.08 0.14 0.26 0.08 0.23* R2 (F) 0.34 (9.66**) 0.31
(8.44**) 0.44 (14.66**) 0.48 (17.68**) DR2 (FD) 0.04 (3.84*) 0.16 (15.50**)
0.13 (15.50**) 0.10 (13.59**)
LC law and
codes; CI company interest; SR social responsibility; PM personal morality; MC
magnitude of consequences; SC social consensus; TI temporal immediacy; ER
ethical recognition; EJ ethical judgment * p\0.05 ** p\0.001
Role of
Individual Variables, Organizational Variables and Moral Intensity Dimensions
123
Sparks and Hunt
(1998, p. 105) suggest two factors to explain the negative relationship between
moral relativism and the ethical decision-making stages, ethical recognition in
particular: ‘‘First, the disbelief in moral absolutes might reduce the
likelihood of ethical violations standing out among other issues. In a world
where all issues are rela- tivistic shades of grey, ethical issues might blend
in with everything else. Second, relativists might consider ethical issues in general
to be less important than nonrelativists’’. These findings suggest that Libyan
management accountants tend to be idealistic rather than relativistic when
making ethical decisions. This indicates that their actions may be influenced
more by universal moral rules, which produce positive consequences for all
those involved (i.e. absolutists) (Forsyth 1992).Severalstudiesconducted in
Muslim countries including Egypt (Attia et al. 1999; Marta et al.
2003),JordanandSaudiArabia(Martaetal. 2004),UAE(Al-Khatibetal.
2005),Morocco(Oumliland Balloun 2009)andIndonesia(LuandLu 2010)haveshown
similar results, i.e. that Muslims are more idealistic and less relativistic.
The Islamic tradition places ethical/social activity ahead of individual profit
maximization (Beekun et al. 2008;Rice 1999),andIslamurgesstrictadherenceto the
ethical injunctions of the Quran. In Libya, Islam is the major source of the
written laws and most of the legal environment surrounding business
transactions (Kilani 1988).Therefore,strictadherencetothetraditionofIsla- mic
faith in Libya would strengthen deontological norms and moral rules in
individuals’ ethical systems. The influ- ence of Islam could be one possible
explanation for the finding that idealism had a positive relationship with ethi-
cal decision making. When this finding is compared with similar results from
non-Muslim countries (Al-Khatib et al. 1997;VanKenhoveetal.
2001),thisexplanationmightbe questioned, but the present results imply that one
approach to enhancing the ethical decision-making process within the Libyan
business environment would be to encourage idealistic philosophy and, during
the education process for accountants, to help make them aware of the
connections between accounting practice and Islam. In relation to demographic variables,
there were few significant differences in the ethical recognition, judgment and
intention of management accountants based on their age, gender and level of
education. Several researchers investigating the relationship between age and
ethical decision-making stages have reported similar results (e.g. Barnett and
Valentine 2004;Callan 1992;Martaetal. 2004;McMahonandHarvey
2007).Thelackofsignificant findings for educational level also does not conflict
with several studies (e.g. Chan and Leung 2006;Sparksand Hunt
1998).Limitedmoraldevelopmentonceinwork might be one reason for the lack of
difference based on age and education level. Moral development literature
indicates
that without
intervention or an appropriate environment, the majority of adult people will
never exceed the con- ventional level suggested by Kohlberg’s model (Steven et
al. 2006).Also,pastresearchhasdemonstratedthat accountants tend to be at Stage
4 of moral development or lower (Green and Weber 1997).Anotherreasonmightbe
that Libyan accounting education failed to prepare Libyan accountants to deal
with such issues. Although researchers have repeatedly reported that moral
development is asso- ciated with level of education (Armstrong et al. 2003;
Steven et al. 2006),thispresumablydependsonthenature of the education. If there
are ethical failures in accounting practice, it is probable that at least some
of the blame can be placed on the education system (Gray et al. 1994). The
present results may suggest that integrating courses of ethics, perhaps with an
Islamic emphasis, in accounting education and paying more attention to ethical
training of management accountants could enhance the process of ethical
decision making of Libyan accountants. However, this issue may not have been
considered yet by the Libyan higher education sector. For example, the Centre
for Quality Assurance and Accreditation for Higher Education Institutions in
Libya did not include any type of ethical material in its suggested curricula
for Libyan universities (Centre for Quality Assurance and Accreditation for
Higher Education Institutions 2008).Moreover,thelimitedpro- fessional
organization of accountants within Libyan com- panies means that the training
would have to be arranged by the companies themselves rather than being part of
continuing professional development instituted by a pro- fessional association
(cf. Cowton 2009). Regarding the differences in ethical decision making based
on gender, female management accountants were significantly less sensitive than
their male counterparts in recognizing the ethical issues in two of the four
scenar- ios—though no significant differences were found in ethi- cal judgment
and ethical intention based on gender. These limited significant results,
especially for ethical recogni- tion, are only consistent with the study of
Marques and Azevedo-Pereira (2009), who found that male chartered accountants
were significantly more ethical than female chartered accountants in two out of
five scenarios. It is possible that ethical gender differences here may be
attributed to other reasons such as age or years of experi- ence (Dawson
1997).Thefemaleaccountantswhopartic- ipated in this study are generally younger
than their male counterparts (56 % of females, but only 27 % of males, had ages
less than 35 years) and generally have less work experience (76 % of females
but only 48 % of males have less than 15 years’ work experience). The younger
and less-experienced females may be less sensitive to ethical issues. However,
given the paucity of significant differ- ences in gender, age and work
experience in general, this
suggestion
should be treated cautiously. Future research is needed to see whether any
gender differences are based on these variables. With respect to work
experience itself, there was only one significant result. Previous studies have
reported similar findings (e.g. Nill and Schibrowsky 2005; Roozen et al.
2001).O’LearyandStewart(2007)found little evidence of the possible impact of
work experience but argued that the direction of the relationship is still
ambiguous. In their review, O’Fallon and Butterfield
(2005)concludethattherelationshipbetweenworkexpe- rience and ethical decision
making was inconsistent.
Organizational
Variables
There were no
significant differences in ethical decision making based on code of ethics and
industry type and only two significant differences for organizational size.
Knowl- edge of the existence of a code is a necessary prerequisite for its
effectiveness, but the results here suggest that those management accountants
who perceive that their company has a code are not significantly different from
those who do not (whether the company has a code or not). This might be a
particular concern in Libya and other developing countries that have not yet made
much progress in developing an accounting profession with a strong code of
ethics. Several researchers (Cooper and Frank 1997;Laczniak and Inderrieden
1987;Verschoor 2002)havearguedthata corporate code of ethics by itself may not
be sufficient to significantly influence the ethical decision-making process.
There are many possible reasons for this result. One is that the content of the
code is limited or, in this case, is not particularly relevant to the work of
the management accountants. Laczniak and Inderrieden (1987) claim that a code
of ethics may be associated with the process of ethical decision making only
when combined with sanctions. Rottig and Heischmidt (2007) suggest that a code
of ethics should be systematically and empirically examined in conjunction with
additional determinants of ethical deci- sion making such as ethical training.
The results of this study suggest that managers of Libyan companies should
check that the content of their code of ethics is up to date and relevant,
communicated to staff and supported appro- priately. Future research within a
Libyan context could focus exclusively on codes of ethics, and hence
investigate more fully their content and organizational factors such as
rewards, sanctions, communication and training to see if these things influence
the relationship between having a code of ethics and making ethical decisions.
An alternative explanation for this result may be related to other factors such
as ownership and type of market (planned market such as in Libya). Agarwal and
Malloy (1999)reportthat,instate-ownedorganizations,organi- zational variables
are not a significant determinant of
ethical
decisions. They propose that the organization might not have sufficient impact
on its members. As noted in Table 2,themajorityofmanagementaccountants(65%)
work within companies that are owned by the state and 18 % are joint venture
between the state and other parties. This could be a possible reason for the
lack of significant findings. Traditionally, different organizations in the
public sector may be quite similar in terms of their culture regardless of
their types (banks, manufacturers, non-profit organizations, etc.). This may be
because they are resour- ced by similar state means. If these companies were to
operate in a free market where their features are different from those that
operate in a non-free market, then code of ethics, size and type of industry
might have an influence on the ethical decision-making process. Most past
research has shown that these variables have a significant positive relationship
with ethical decision-making stages within organizations that operate in a free
market (e.g. Barnett et al. 1993;Pflugrathetal. 2007;WeeksandNantel 1992). With
regard to the nine ethical climate types suggested by Victor and Cullen (1987,
1988),pastresearchhasfound a significant relationship with the ethical
decision-making process. However, some have argued that these types do not
always exist within organizations (Martin and Cullen
2006).Inthepresentstudy,fourtypesofethicalclimate were examined, and limited
significant results were found. Only personal morality was found to have a
significant relationship with the ethical decision-making stages in only one
scenario and law and professional codes only had one significant relationship
with ethical recognition and one with ethical judgment, each in a different
scenario. Empirical research has shown similar results, with ethical climate
having limited or no significant relationship with ethical decision-making
stages (e.g. Buchan 2005;De- Coninck and Lewis 1997;Shafer
2008).Briefly,theenvi- ronment surrounding Libyan companies (i.e. public sector)
or the other types of ethical climate may be better pre- dictors of ethical
decision-making scores.
Moral Intensity
Dimensions
All the issues
included in the given scenarios were clear and represent unethical actions, of
varying degrees, which could be commonly found in the work setting (Leitsch
2006;SweeneyandCostello 2009).Jones(1991)claims that clear differences of
ethical intensity between scenarios are essential in ascertaining moral
intensity’s influence. In general, at least some moral intensity dimensions
signifi- cantly predicted the ethical decision making of Libyan management
accountants in this study. This result supports Jones’ (1991) issue-contingent
model of ethical decision making and is consistent with several empirical
studies (Barnett 2001;Floryetal. 1992;Leitsch 2004, 2006; Sweeney and Costello
2009;ValentineandHollingworth 2012). Magnitude of consequences and social
consensus sig- nificantly predicted management accountants’ ethical
decision-making stages in many presented scenarios. This may be because the
issues displayed in the scenarios had a clear unethical content. An ethical
issue with a high level of moral salience will produce a high level of moral
intensity (Jones 1991).Barnett(2001)arguesthatolder individuals perceive the
magnitude of consequences as the most important dimension because of their
higher level of moral reasoning; 66 % of the participants in this study were
aged 35 years or more, with 45 % aged more than 40 years old. The prevalence of
social consensus as a significant predictor suggests that management accoun-
tants’ views of society’s attitudes to issues may impact their ethical decision
making (Rest 1986).Kohlberg’s (1969)theoryofmoraldevelopmentpositsthatatcon-
ventional levels of ethical reasoning, individuals are impacted by rules set by
society, which reflect the con- sensus of the community on the ethical
characteristics of specific actions. Further, Jones (1991) argues that indi-
viduals consider societal standards to decrease uncertainty when faced with
ethical issues. Therefore, individuals will be more likely to make an ethical
decision which is con- sistent with societal standards. Previous empirical
research on temporal immediacy has been limited and yielded mixed results, with
some studies finding that it has little or no association with the ethical
decision-making process (Barnett 2001;BarnettandVal- entine
2004)andothersthatitisassociatedsignificantly with ethical decision-making
stages (Singhapakdi 1999; Singhapakdi et al. 1996;VitellandPatwardhan 2008;Yang
and Wu 2009).Theresulthereisconsistentwiththe findings of Leitsch (2006) and
Yang and Wu (2009) who used similar scenarios. Similar to magnitude of conse-
quences and social consensus, temporal immediacy was also sometimes a
significant predictor of the three stages of management accountants’ ethical
decision making and justified its inclusion in the study. However, most past
research (see for example the review of O’Fallon and Butterfield
2005)revealsthatmagnitudeofconsequences and social consensus are generally more
significantly related than temporal immediacy. This result could be attributed
to the adequate information provided in each scenario regarding the onset of
consequences. It might also reflect a different conception of time in Libyan
culture; this is an issue for further investigation.
Relationship
between Stages
According to
Rest (1986), ethical decision-making stages generally occur in a sequential
manner and can affect each
other (Wotruba
1990).Ethicalrecognitionandethical judgment were added to the regression model
to examine the relationships between stages within the Libyan context.
Researchers have tested ethical decision-making stages as independent variables
to each other and found significant statistical relationships between them
(Bateman et al. 2013; Leitsch 2006;SweeneyandCostello 2009;Yangetal.
2006).Thiswouldbeexpected,giventhelogicalstructure of Rest’s model, though the
less than perfect correlation justifies looking at three rather than just one or
two stages—which previous research has tended to do. The results of this study
also show a significant relationship between ethical recognition and ethical
judgment and also between ethical judgment and ethical intention, but ethical
recognition did not significantly predict ethical intention in the final
regression model. This is consistent with his model of moral intensity
dimensions, in which Jones (1991)proposesthatethicalrecognitionimpactsethical
intention only through ethical judgment. This confirms Rest’s model of ethical
decision making that there is no direct association between ethical recognition
and ethical intention.
Conclusion
Research into
the ethics of management accounting and management accountants is
under-represented in the jour- nal literature (Bampton and Cowton
2013).Furthermore, most of the significant body of research into ethical deci-
sion making, building on Rest’s model, has been conducted in developed western
countries, often using only one or two stages of the model. This study
investigated the role of several variables in the ethical decision making of
man- agement accountants in an emerging country, namely Libya. Unlike most
previous research, it examined three of the four stages of ethical decision
making (Rest 1986).The empirical relationships between the three stages
provided support for the use of Rest’s model. The results revealed that moral
intensity dimensions and personal moral phi- losophy explained a significant
proportion of the variance in management accountants’ ethical recognition,
judgment and intention (while ethical recognition predicted ethical judgment
which in turn predicted ethical intention). Com- paratively few significant
results were found in relation to the organizational variables, age, gender and
educational level and the three ethical decision-making stages. How- ever,
where gender revealed a significant relationship with ethical decision making,
it was males who tended to be more ethical, which is an unusual result.
Moreover, tem- poral immediacy was more prominent than in previous studies. The
apparent lack of impact of company codes of ethics suggests that companies
should pay more attention
to their content
and to how they are supported, especially— in the case of management
accountants—while the accounting profession in Libya remains under-developed.
Limitations and
Future Research
As is the case
with all research in business ethics and other areas, the study is subject to
some limitations. Although the study sample should be representative of the
intended tar- get population and the results of the survey can be gen- eralized,
the sample was limited to management accountants who work for manufacturing
companies. The results may not be uncritically generalized to management
accountants who work for other organizations such as banks or governmental
organizations. However, given that management accountants, in general, have
similar tasks regardless of the organizations they work for, this limita- tion
may not be a big concern. In order to produce a questionnaire of reasonable
length, and following the practice of most previous researchers, single item
measures for each stage of the ethical decision- making process and each
dimension of moral intensity were adopted here. One item might not be sufficient
to measure each stage of the ethical decision-making process in a fully reliable
way, and thus the results should be interpreted with caution. Although all the
measures used in the present study have been validated in previous research,
future studies that have a narrower research agenda—and hence do not have the
same pressure on the length of the research instrument—could perhaps use
multiple item measures and so also provide useful evidence on the shortcomings,
if any, of single item measures. In addition to guiding further research on
ethical decision making, the present study also suggests that a more intensive
study of corporate codes of ethics in Libya would be useful. The challenge of
measuring ethical recognition in this study should be acknowledged, given that
when respondents are asked about ethical issues, their sensitivity is
heightened. However, this issue is common to the large body of previous
research on which the present study builds. Moreover, it
shouldalsobenotedthatthefocusisnotontheabsolutelevel of ethical recognition as
such but on the association of cer- tain independent variables with variations
in ethical recog- nition (and judgment and intention).
Giventhedearthofmanagementaccountingethicsresearch across countries, and the
important role that management accountantsplay, especiallywithin
manufacturingcompanies, more research is needed regarding the area of
management accounting ethics in general and organizational factors affecting
management accountants’ ethical decision-making process in particular. It would
also be useful to compare management accountants working in different sectors,
such as
manufacturing,
banks and public services. If, as it is thought might be the case in Libya,
management accountants in developing, formerly planned economies show great
similar- ities because of their common background, it would be inter- esting to
undertake longitudinal research to track any industry effects thatmight
developover time. It would also be useful to conduct a study across several
different Muslim majority countries and to look at other sorts of developing
countries.
Open Access This
article is distributed under the terms of the Creative Commons Attribution
License which permits any use, dis- tribution, and reproduction in any medium,
provided the original author(s) and the source are credited. Appendix
Scenario C1
Muftah Salem is
a young management accountant at a large, public company. After some experience
in accounting at headquarters, he has beentransferred to one ofthe company’s
recently acquired divisions, run by its previous president, Abdalganee Ahmed.
Abdalganee has been retained as vice president of this new division, and Muftah
is his accountant. With a marketing background and a practice of calling his
ownshots,Abdalganeeseemstoplaybyadifferentsetofrules than those to which Muftah
is accustomed. So far it is work- ing, as earnings are up and sales projections
are high. The main area of concern to Muftah is Abdalganee’s expense reports.
Abdalganee’s boss, the division president, approves the expense reports without
review, and expects Muftah to check the details and work out any discrepancies
with Ab- dalganee. After a series of large and questionable expense
reports,MuftahchallengesAbdalganeedirectlyaboutcharges to the company for
delivering some personal furniture to Abdalganee’shome.Althoughcompanypolicyprohibitssuch
charges, Abdalganee’s boss again signed off on the expense. Muftah feels
uncomfortable with this and tells Abdalganee
thatheisconsideringtakingthemattertotheauditdepartment at the headquarters for
review. Abdalganee reacts sharply, reminding Muftah that ‘‘the department will
back me any- way’’ and that Muftah’s position in the company would be in
jeopardy. Action Muftah decides not to report the expense charge to the
department of auditing of public companies.
Scenario C2
Suaad Mabrok, a
company controller, is told by the chief financial officer that in an executive
committee meeting the chief executive officer (CEO) told them that the company
‘‘has to meet its earnings forecast, is in need of working capital, and that’s
final.’’ Unfortunately, Suaad does not see how additional working capital can be
raised, even through increased borrowing, since income is well below the
forecast sent to the bank. Kaled suggests that Suaad review bad debt expense
for possible reduction and holding sales open longer at the end of the month.
He also brushes off the management letter request from the outside auditors to
write down the spare parts inventory to reflect its ‘‘true value.’’ At home at
the weekend, Suaad discusses the sit- uation with her husband, Nasser, a senior
manager of another company in town. ‘‘They’re asking me to manip- ulate the
books,’’ she says. ‘‘On the one hand,’’ she com- plains, ‘‘I am supposed to be
the conscience of the company and on the other, I’m supposed to be absolutely
loyal.’’ Nasser tells her that companies do this all the time, and when
business picks up again she’ll be covered. He reminds her how important her
salary is to help maintain their comfortable lifestyle, and that she should not
do anything drastic that might cause her to lose her job. Action Suaad decides
to go along with the suggestions proposed by her boss.
Scenario C3
Osama Zahed, the
plant’s chief accountant, is having a friendly conversation with Fasal Jamal,
operations manager and old college buddy, and Hassan Haron, the sales man-
ager. Fasal tells Osama that the plant needs a new computer system to increase
operating efficiency. Hassan adds that with the increased efficiency and decreased
late deliveries their plant will be the top plant next year. However, Fasal
wants to bypass the company policy which requires that items greater than five
thousand Dinars receive prior Board approval and be capitalized. Fasal would
prefer to generate purchase orders for each component part of the system, each
being under the five thousand Dinars limit, and thereby avoid the approval
‘‘hassle.’’ Osama knows that this is clearly wrong from a company and an
accounting standpoint, and he says so. Nevertheless, he eventually says that he
will go along. Six months later, the new computer system has not lived up to
expectations. Osama indicates to Hassan that he is really worried about the
problems with the computer, and the auditors will disclose how the purchase was
handled in the upcoming visit. Hassan acknowledges the situation by saying that
production and sales are down, and his sales representatives are also upset.
Fasal wants to correct the problems by upgrading the system (and increasing the
expenses), and urges Osama to ‘‘hang in there.’’ Acton: feeling certain that
the system will fail without the upgrade, Osama agrees to approve the
additional expense.
Scenario C4
Yusuf Ali is the
assistant controller at Bader Electronics, a medium-sized manufacturer of
electrical equipment. Yusuf is in his late fifties and plans to retire soon. His
daughter has a very rare kind of illness which needs lots of money to help her
get an operation abroad. Therefore, financial concerns are weighing heavily on
his mind. Yusuf’s boss is out of the office recuperating from health problems,
and in his absence Yusuf is making all decisions for the depart- ment. Yusuf
receives a phone call from an old friend requesting a sizable amount of
equipment on credit for his new business. Yusuf is sympathetic but cognizant of
the risk of extending credit to a new company, especially under Manam’s strict
credit policy for such transactions. When Yusuf mentions this conversation to
Fayez, the general manager, he is immediately interested. Fayez notes that the
company needs an additional 250,000 Dinar in sales to meet the quarterly budget
and, thus, ensure bonuses for management, including Yusuf. Action Yusuf decides
to make the sale to his friend’s new business.
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