Tugas

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.

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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**)

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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