Accounting professionals work in a stressful environment where their social life might have effect on work performance and unethical behavior. For this study, a survey is conducted for members of Istanbul Chamber of Certified Accountants, Turkey. The number of respondents is 491. The methodology used in the research is a multiple regression. The research questions are whether there is an effect of work-life balance on ethical behavior at work and if the work life balance and accounting ethics differentiate based on demographic factors for the respondents. The main objectives of the research are to test the relationship, and analyze four different independent variables of work life balance to find out whether they contribute to accounting ethics. Other objectives of the research are testing the differentiation of work life balance and accounting ethics based on gender, age, education and marital status. The main hypothesis is that there is a relationship between accounting ethics and work life balance. Based on the results, the main hypothesis is statistically accepted.
Keywords:Accounting, ethics, Accounting, profession, Occupationa, ethics, Personal, life, Demographic, factors, Work-life, balance.
Received: 1 May 2018 / Revised: 24 May 2018 / Accepted: 28 May 2018 / Published: 31 May 2018
There are many studies that explain ethical behavior but this study is unique to combine work-life balance and accounting ethics by a survey applied to Istanbul Chamber of Certified Accountants. This creates many practical opportunities to rethink the way accountants are employed. The availability of differentiation analysis also helps to focus some potentially problematic cases and take proactive decisions.
Work life balance is the individual’s fulfillment of all of the responsibilities at work with minimum conflicts between roles, and creating a balance between works, family and personal life.
The birth of the concept of work life balance is interesting. As Korkmaz and Erdogan (2014) point out the start of the work life balance concept dates back to 1930s as a result of improvements in the industry, increase in global competition, and change in the structure of workforce. Before World War II, a company named W.K. Kellog changed the three eight hour shifts to four six hour shifts. This increased the free time for workers which resulted in an increase in motivation and efficiency.
It is logical to think that there will be a positive correlation between work life balance and motivation at work. According to Aydemir and Dinc (2015) the motivations of the employees are higher when they have less conflicts between work and personal life. When they have more work life balance, the employees can fulfill their responsibilities in both work and family.
The changes in the work environments have been studied since the last quarter of the 20th century. These changes have effects on employer, employee, business and society. Many people have to work to live. This creates work-life conflicts in the new world order which are tried to be balanced by different applications in different environments, and in different countries.
As other employees, accountants also face these challenges. The decision making of the accountants however may be affected from external factors. These decisions are important for many stakeholders of the company. Moreover, the decisions may be triggered by some unethical factors. The goal of this paper is to investigate the relationship between the effect of work life balance and accounting ethics.
The paper is organized as follows. In chapter 2 some of the recent works in the literature are discussed. The research methodology is described in Chapter 3. In Chapter 4, the main results of the research are given. In chapter 5 the results of the paper are discussed in detail. Finally chapter 6 summarizes the conclusions of the study and proposals for accounting ethics.
One interesting discussion is whether ethical behavior can be developed by education. There are works in the literature which argue that accounting ethics classes would increase ethical behavior at work.
Huss and Patterson (1993) discussed the outcomes of accounting ethics lectures. According to authors, ethics can nowadays be seen as an important part of accounting education. Therefore one might accept that including lectures on accounting ethics during the undergraduate education of accounting increase the moral values of accounting students. The task is to determine which values to teach and how to teach them. As the acceptance of these values take time, students should be involved in accounting ethics seminars even when they become professionals. The classes may involve case studies related to accounting ethics along with theories.
The legislation in accounting ethics is not an easy task because it is neither practical nor possible to discuss every possible scenario that accountants might face during their careers. Therefore people who develop code of ethics in this field should face this problem.
Usurelu et al. (2010) studied creative accounting with a special focus on national code of ethics in Romania. A good ethical background is necessary for accounting professionals not only for compliance with specific rules and laws but also for interpreting the underlying motives and theories. This requires development of values and virtues with which one can make decisions on several ethical situations faced during his/her career. The financial statements include information on any relevant issues that influence ethical behavior. Therefore regulatory system should be developed based on these principles.
Similar concerns are faced by other researchers in literature. The well-known principle-rule based dilemma in accounting profession also exists for the accounting ethics. Most researchers think that standards in this particular field should be principal based.
Spalding and Oddo (2011) studied the ethical standard of American Institute of Certified Public Accountants. In their view, the rules should establish minimum behavioral requirements. The standard should do more than removal of the falsification of accounting data. It should establish minimum ethical standards which should be principal based rather than rule based.
There are many who argue that accountants’ unethical behavior might lead to loss of funds by the public investors and even claim this leads to systematic deterioration of the system. Therefore a common understanding of accounting ethics is at least as important as a good auditing infrastructure.
Bengu et al. (2014) researched the relationship between accounting and financial crisis. According to them several relationships are deviations from the basic concepts of accounting such as social responsibility, overuse of fair value accounting, creative accounting, preparation of wrong financial reports, misleading auditing reports, and off-balance sheet applications.
Accountants have better positions in firms nowadays than before. Even managers without financial background try to learn more about accounting and finance. It is therefore interesting to analyze whether accounting employees with different leadership roles view the organization differently.
Bobek et al. (2015) made a survey to understand perceptions of accounting professionals. The respondents are 139 accounting professionals who either have a leader or non-leader role. The results show that accounting professionals with a leader role perceive the environment of the institution significantly stronger. They found no geographical difference. However in local firms ethical perception of the institution can be weaker.
Most people share the idea that it is important to develop values of accounting ethics during education not to have more problems during the professional career. This can be taught in undergraduate level or even in earlier years of education.
Cameron and O’Leary (2015) studied ethical characteristics of undergraduate students during their final semester. The results show that following ethical training, their behaviors in legal and moral scenarios improve. However their behaviors in moral only scenarios remain unchanged. To avoid this lack of awareness, accounting ethics should be inserted throughout the entire curriculum as well as a separate course.
There are more studies in the literature which try to find out a better way for teaching accounting ethics. It is easy to give students hours of theories on ethics. However it might not be effective when compared with case based classes should be questioned.
Gong (2017) reviewed the book Ethics in Accounting: A decision making approach in a journal paper. Gong argues that the book makes it easy for students with no background in accounting ethics to understand the topics by using simple human intuitions and recent case studies. The idea of the book is to focus on decision making rather than theories. However the class topics may include more comprehensive cases such as financial instruments, leases and revenue. Also related topics such as information asymmetry, corporate governance and agency problems can be discussed.
In times of high financial volatility the risk of manipulation is higher. As Erdogdu (2017) points out especially in the last decade, owing to economic instabilities and fragility in global economies, properties markets have showed high volatility.
Finally despite best efforts, there will always be unethical accountants who try to breach the system as in other professions. There are attempts in the literature which try to give early warning signal that a case of accounting manipulation might exist.
Vladu et al. (2017) used financial ratios to study accounting manipulation. They used companies that used earnings manipulation and other ethical companies for the period 2005-2012. By using statistical techniques they prove that financial ratios can be used for detecting manipulation. The possibility increases when there is an unusual increase in receivables, increasing leverage and decrease in sales.
The methodology in this paper is a survey. The goal of this survey is to measure the relationship between the work-life balance and accounting ethics. The people who were surveyed are members of Istanbul Chamber of Certified Accountants (ICCA), Turkey. The number of members for the ICCA by the time of the research is 38.976. The sample required for this research is computed as 380.
For this purpose 1.000 surveys are distributed from which 491 responded.
The methodology in analyzing the survey results is regression. The results are given using 5 % level of significance. The software used for this research is SPSS 23.00.
The main hypothesis tested in this research is that there is a relationship between work-life balance and behaving against accounting ethics.
For a deeper analysis, differentiation is also tested for work-life balance and accounting ethics. Work life balance is tested to see if there is a statistically significant differentiation in independent variables based on gender, age, education and marital status. The independent variables used in the research are the effect of personal life to work, the effect of work to personal life, work-life growth, and the effect of working with husband/wife or other relative.
Accounting ethics is also tested to see whether there is a statistically significant differentiation in personal characteristics of the respondents based on gender, age, education and marital status. The personal characteristics used in this research are ethical behavior, honesty, reliability, and objectivity, and responsibility.
4.1. Testing the Main Hypothesis
A multiple regression to represent the effect of work life balance on ethical behavior is given in Table 1. According to the regression results, work-life balance explains 10,3% of the variance of ethical behavior. The contribution of work-life balance to variance is significant.
Therefore the main hypothesis that there is a relationship between accounting ethics and work-life balance is accepted. (p=0,000; F=14,183). In other words, ethical behavior can be explained by work life balance.
The independent variables can then be analyzed separately. Results have shown that the effect of personal life to work has no impact on ethical behavior at work. (p=0,576>0,05) The effect of work to personal life (p=0<0,05), work-life growth (p=0<0,05) and the effect of working with husband/wife or other relative (p=0,019<0,05) does influence ethical behavior. With these results, the main hypothesis that there is a relationship between work-life balance and accounting ethics is accepted. This is because three independent variables used in explaining work life balance(the effect of work to personal life, work life growth, and the effect of working with husband/wife or other relative) are statistically significant. This leads the model to be statistically reliable. (Model p=0<0,05)
Table-1. The Effect of Work-Life Balance on Ethical Behavior
Independent Variable |
β |
t |
p |
F |
Model(p) |
R2 |
Constant |
3,531 |
19,530 |
,000 |
14,183 |
,000 |
,103 |
The effe |
,020 |
,55 |
,576 |
|||
t of personal life to work |
||||||
The effect of work to personal life |
-,157 |
-4,339 |
,000 |
|||
Work-life Growth |
,175 |
4,970 |
,000 |
|||
The effect of working with husband/wife or other relative |
-,068 |
-2,344 |
,019 |
Table-2. The Differentiation of Work-life balance based on Gender
N |
Mean |
Std. Deviation |
F |
p |
|
The effect of personal life to work |
1,498 |
,222 |
|||
Female |
219 |
35,973 |
,93524 |
||
Male |
279 |
35,140 |
,99570 |
||
The effect of work to personal life |
,422 |
,516 |
|||
Female |
219 |
30,651 |
,95755 |
||
Male |
279 |
27,930 |
,97700 |
||
Work-life Growth |
,219 |
,640 |
|||
Female |
219 |
30,582 |
,92325 |
||
Male |
279 |
31,640 |
,94533 |
||
The effect of working with husband/wife or other relative |
10,068 |
,002 |
|||
Female |
219 |
30,342 |
106,980 |
||
Male |
279 |
27,581 |
121,504 |
4.2. Differentiation Analysis of Work-Life Balance
The differentiation analysis of work life balance based on gender is given in Table 2. According to the results, only differentiation can be seen in variable the effect of working with husband/wife or other relative. The mean for female gender is statistically higher in the effect of working with husband/wife or other relative. Two other variables don’t differentiate based on gender; The effect of personal life to work, and effect of work to personal life and work life growth.
The Differentiation of Work-life balance based on Age is analyzed in Table 3. According to results all of the independent variables show differentiation based on age. The means are different when affecting work-life balance in different age categories.
Table-3. The Differentiation of Work-life balance based on Age
N |
Mean |
Std. Deviation |
F |
P |
Difference |
|
The effect of personal life to work |
4,143 |
,003 |
||||
29 or less |
24 |
33,250 |
102,119 |
3>2 |
||
30-35 |
192 |
34,188 |
,98409 |
5>1 |
||
36-45 |
192 |
36,500 |
,99000 |
5>2 |
||
46-55 |
66 |
35,091 |
,71052 |
5>3 |
||
56 or more |
24 |
41,500 |
,99957 |
5>4 |
||
Total |
498 |
35,506 |
,96950 |
|||
The effect of work to personal life |
4,271 |
,002 |
||||
29 or less |
24 |
25,313 |
,86071 |
3>1 |
||
30-35 |
192 |
27,969 |
,95536 |
4>1 |
||
36-45 |
192 |
29,570 |
103,115 |
5>1 |
||
46-55 |
66 |
30,455 |
,91977 |
5>2 |
||
56 or more |
24 |
35,000 |
,62554 |
5>3 |
||
Total |
498 |
29,127 |
,97692 |
5>4 |
||
Work-life Growth |
6,207 |
,000 |
||||
29 or less |
24 |
32,813 |
,92464 |
3>2 |
||
30-35 |
192 |
30,000 |
,97280 |
3>4 |
||
36-45 |
192 |
32,031 |
,88937 |
5>1 |
||
46-55 |
66 |
28,864 |
,94175 |
5>2 |
||
56 or more |
24 |
38,438 |
,49350 |
5>3 |
||
Total |
498 |
31,175 |
,93622 |
5>4 |
||
The effect of working with husband/wife or other relative |
4,460 |
,002 |
||||
29 or less |
24 |
23,125 |
105,101 |
2>1 |
||
30-35 |
192 |
29,766 |
114,326 |
2>5 |
||
36-45 |
192 |
28,750 |
113,142 |
3>1 |
||
46-55 |
66 |
30,682 |
121,809 |
3>5 |
||
56 or more |
24 |
21,875 |
114,029 |
4>1 |
||
Total |
498 |
28,795 |
116,044 |
4>5 |
||
The differentiation of work-life balance based on education is given in Table 4. According to the results, there is a statistically significant differentiation based on education. The means are different for certain education categories in all of the independent variables. All of the independent variables which are the effect of personal life to work, the effect of work to personal life, work life growth and the effect of working with husband/wife or other relative differentiate based on education.
The differentiation of work-life balance based on marital status is given in Table 5. According to the results, the effect of work to personal life and work life growth differentiate based on marital status. For both of the variables, married marital status has higher mean. However the independent variables the effect of personal life to work and the effect of working with husband/wife or other relative doesn’t differentiate based on marital status.
Table-4. The Differentiation of Work-life balance based on Education
N |
Mean |
Std. Deviation |
F |
P |
Difference |
|
The effect of personal life to work |
5,161 |
,000 |
||||
High School |
57 |
34,526 |
,81199 |
2>4 |
||
Vocational |
30 |
36,200 |
,62665 |
3>4 |
||
University |
312 |
36,654 |
,94346 |
|||
Master’s or higher |
99 |
32,242 |
113,687 |
|||
Total |
498 |
35,056 |
,96950 |
|||
The effect of work to personal life |
3,764 |
,005 |
||||
High School |
102 |
31,974 |
,91336 |
1>2 |
||
Vocational |
66 |
27,000 |
,96356 |
1>3 |
||
University |
189 |
28,678 |
102,007 |
|||
Master’s or higher |
80 |
29,545 |
,84694 |
|||
Total |
477 |
29,127 |
,97692 |
|||
Work-life Growth |
2,563 |
,038 |
||||
High School |
102 |
28,816 |
,82390 |
4>1 |
||
Vocational |
66 |
32,500 |
,87346 |
|||
University |
189 |
31,178 |
,95031 |
|||
Master’s or higher |
80 |
32,121 |
,95856 |
|||
Total |
477 |
31,175 |
,93622 |
|||
The effect of working with husband/wife or other relative |
3,015 |
,018 |
||||
High School |
102 |
27,632 |
,97333 |
3>4 |
||
Vocational |
66 |
30,000 |
,99134 |
|||
University |
189 |
29,712 |
119,449 |
|||
Master’s or higher |
80 |
26,212 |
116,735 |
|||
Total |
477 |
28,795 |
116,044 |
|||
Table-5. The Differentiation of Work-life balance based on Marital Status
N |
Mean |
Std. Deviation |
F |
p |
|
The effect of personal life to work |
,265 |
,607 |
|||
Married |
303 |
35,307 |
,97550 |
||
Single |
195 |
35,815 |
,96178 |
||
The effect of work to personal life |
7,535 |
,011 |
|||
Married |
303 |
30,050 |
,91414 |
||
Single |
195 |
27,692 |
105,363 |
||
Work-life Growth |
4,428 |
,009 |
|||
Married |
303 |
32,079 |
,88872 |
||
Single |
195 |
29,769 |
,99164 |
||
The effect of working with husband/wife or other relative |
36,187 |
,145 |
|||
Married |
303 |
28,218 |
125,990 |
||
Single |
195 |
29,692 |
,98262 |
||
4.3. Differentiation Analysis of Accounting Ethics
The differentiation of accounting ethics is also analyzed for the same factors. These factors are gender, age, education and marital status. However in this analysis, the differentiation is investigated in three different personal characteristics rather than the independent variables previously analyzed in the differentiation analysis of work-life balance. These groups of personal characteristics are ethical behavior, honesty, reliability and objectivity, and responsibility.
As in the analysis for work-life balance, the first factor to be analyzed for accounting ethics is gender. The results of this analysis is given in Table 6. The only differentiation based on gender is ethical behavior. According to the results female gender has a higher mean. The groups of personal characteristics; honesty, reliability and objectivity and responsibility don’t differentiate based on gender.
Table-6. The Differentiation of Accounting Ethics based on Gender
N |
Mean |
Std. Dev. |
F |
p |
|
Ethical Behavior |
9,866 |
,002 |
|||
Female |
219 |
35,656 |
,66758 |
||
Male |
279 |
34,363 |
,81239 |
||
Honesty, reliability, and objectivity |
,678 |
,411 |
|||
Female |
219 |
35,228 |
,74774 |
||
Male |
279 |
33,262 |
,79526 |
||
Responsibility |
3,588 |
,059 |
|||
Female |
219 |
38,995 |
,89115 |
||
Male |
279 |
36,559 |
,91149 |
The second analysis for the differentiation of accounting ethics is age. In Table 7, the differentiation of accounting ethics in personal characteristics of the respondents based on age is given. According to the results, all personal characteristics differentiate based on age. All of the groups of personal characteristics which are shown to be statistically significant in this analysis are ethical behavior, honesty, reliability and objectivity, and responsibility. As seen in the table, some age groups have significantly higher mean than others.
Table-7. The Differentiation of Accounting Ethics based on Age
N |
Mean |
Std. Deviation |
F |
P |
Difference |
|
Ethical Behavior |
7,435 |
,000 |
||||
29 or less |
24 |
31,694 |
,30029 |
2>4 |
||
30-35 |
192 |
34,621 |
,82736 |
3>1 |
||
36-45 |
192 |
36,875 |
,65337 |
3>2 |
||
46-55 |
66 |
32,208 |
,83795 |
3>4 |
||
56 or more |
24 |
32,321 |
,53587 |
3>5 |
||
Total |
498 |
34,931 |
,75417 |
|||
Honesty, reliability, and objectivity |
4,299 |
,002 |
||||
29 or less |
24 |
34,167 |
,54507 |
2>4 |
||
30-35 |
192 |
33,854 |
,86470 |
3>4 |
||
36-45 |
192 |
35,339 |
,68973 |
5>4 |
||
46-55 |
66 |
30,909 |
,82077 |
|||
56 or more |
24 |
35,417 |
,58823 |
|||
Total |
498 |
34,127 |
,78010 |
|||
Responsibility |
7,990 |
,000 |
||||
29 or less |
24 |
35,417 |
,81539 |
2>4 |
||
30-35 |
192 |
37,188 |
,90994 |
3>1 |
||
36-45 |
192 |
39,844 |
,88507 |
3>2 |
||
46-55 |
66 |
33,030 |
,91095 |
3>4 |
||
56 or more |
24 |
38,333 |
,63702 |
5>4 |
||
Total |
498 |
37,631 |
,90979 |
|||
In Table 8, the differentiation of accounting ethics based on education is given. According to the results, only ethical behavior and responsibility differentiate based on education. As seen in the table, some education levels have significantly higher mean than others. In the analysis, the group of personal characteristics honesty, reliability and objectivity don’t differentiate based on education.
The differentiation of accounting ethics based on marital status is presented in Table 9. According to the analysis only ethical behavior differentiates based on marital status. The results reveal that married marital status has a higher mean. The groups of personal characteristics that are not significant are honesty, reliability and objectivity and responsibility. Therefore these characteristics don’t differentiate based on marital status.
Table-8. The Differentiation of Accounting Ethics based on Education
N |
Mean |
Std. Deviation |
F |
P |
Difference |
|
Ethical Behavior |
7,790 |
,000 |
||||
High School |
57 |
31,805 |
,79058 |
2>1 |
||
Vocational |
30 |
39,714 |
,64915 |
2>3 |
||
University |
312 |
34,863 |
,78435 |
2>4 |
||
Master’s or higher |
99 |
35,498 |
,56570 |
3>1 |
||
Total |
498 |
34,931 |
,75417 |
4>1 |
||
Honesty, reliability, and objectivity |
1,308 |
,271 |
||||
High School |
102 |
32,719 |
104,684 |
|||
Vocational |
66 |
32,500 |
,94762 |
|||
University |
189 |
34,375 |
,77411 |
|||
Master’s or higher |
80 |
34,646 |
,51797 |
|||
Total |
477 |
34,127 |
,78010 |
|||
Responsibility |
4,939 |
,002 |
||||
High School |
102 |
34,912 |
,95971 |
3>1 |
||
Vocational |
66 |
37,667 |
,99481 |
3>4 |
||
University |
189 |
38,750 |
,93656 |
|||
Master’s or higher |
80 |
35,657 |
,68752 |
|||
Total |
477 |
37,631 |
,90979 |
|||
Table-9. The Differentiation of Accounting Ethics based on Marital Status
N |
Mean |
Std. Dev. |
F |
p |
|
Ethical Behavior |
6,965 |
,002 |
|||
Married |
303 |
35,813 |
,69470 |
||
Single |
195 |
33,560 |
,82147 |
||
Honesty, reliability, and objectivity |
13,478 |
,474 |
|||
Married |
303 |
34,340 |
,68695 |
||
Single |
195 |
33,795 |
,90697 |
||
Responsibility |
1,419 |
,234 |
|||
Married |
303 |
38,119 |
,87195 |
||
Single |
195 |
36,872 |
,93602 |
||
The relationship between accounting ethics and work-life balance is analyzed with the help of a survey in this research. This survey is conducted specifically for this paper in the Istanbul Chamber of Certified Accountants. The number of respondents is 491.
The main hypothesis of the research is that there is a relationship between work life balance and ethical behavior. Work life balance is explained in four different independent variables; the effect of personal life to work, the effect of work to personal life, work life growth, and the effect of working with husband/wife or other relative.
A multiple regression is required to test the main hypothesis. The result is that there is a statistically significant relationship between work-life balance and ethical behavior. Model p is acceptable under 5% level of significance. A more comprehensive analysis can be made directly with this regression. This is the analysis of independent variables that explain work-life balance used in the regression of ethical behavior. The effect of personal life to work doesn’t affect ethical behavior. This result indicates that the situations arise in personal life do not influence ethical behavior at work. The effect of work to personal life decreases ethical behavior. Work-life growth increases ethical behavior. The effect of working with husband/wife or other relative leads to unethical behavior.
Differentiation analysis is made to analyze the relationship between socio demographic characteristics of respondents and work-life balance. These socio demographic characteristics are gender, age, education and marital status. This hypothesis is tested with a multiple regression.
Women traditionally take more responsibility at home even if they are working. According to Fidan (2005) although women which are working take less time for housework than women which are not working, there is a considerable time difference when compared to men. This causes to take less time for themselves and reduces their energy at work, increases stress, and therefore reduces competition opportunity with men at work.
However according to the differentiation analysis of work life balance based on gender, only one of the four pre-mentioned independent variables which is the effect of working with husband/wife or other relative is differentiating based on gender. Female gender has a higher mean, which means women may have a work-life balance problem when working with husband or other relative. The independent variables the effect of personal life to work, the effect of work to personal life, and work life balance are not differentiating based on gender according to this analysis.
According to Kagnicioglu (2013) in addition to the description of proper work in today’s World, one should consider to take the time for himself/herself and his/her family, and to increase the quality of life by the opportunities created by technology and organization especially for the Generation Y. Proper work is defined by ILO and used in their researches. The conditions that create proper work include the availability to work flexibly, child and elderly care services, and parental leave. As it could be understood from their discussion age is a factor in the necessities of work life balance.
There is also a differentiation detected for age. According to the differentiation analysis of work life balance based on age, the age group 56 and more experiences the effect of personal life to work, the effect of work to personal life, and work life growth more. However the same age group experiences working with husband/wife or other relative statistically less than the others. In this analysis all of the independent variables of work life balance which are the effect of personal life to work, the effect of work to personal life, work life growth and working with husband/wife or other relative differentiate based on age.
The differentiation also exists based on education. The differentiation of work life balance based on education analysis reveals that master’s or more education has less influence of the effect of personal life to work than vocational and university groups. High school group has more effect of work to personal life than vocational and university. Master’s or higher education group has a significantly higher work-life growth than high school. Finally university education group are more influenced by working with husband/wife or other relative than master’s or higher group. Also in this analysis, all of the independent variables of work life balance; the effect of personal life to work, the effect of work to personal life, work life growth and working with husband/wife or other relative are statistically significant.
Another differentiation studied is marital status. According to the differentiation of analysis of work life balance based on marital status, married people have more effect of work to personal life and work-life growth. The independent variables the effect of personal life to work and working with husband/wife or other relative are not statistically significant in explaining the differentiation of work life balance based on marital status.
The other major group of differentiation analysis is accounting ethics. It is also analyzed to see if there is a differentiation based on same socio demographic characteristics which are gender, age, education and marital status. But this time they are tested in personal characteristics of the respondents which are ethical behavior, honesty, reliability and objectivity and responsibility.
The only statistically significant personal characteristic in explaining the differentiation of accounting ethics based on gender is ethical behavior. Accordingly women behave more ethically than men and this difference is statistically significant according to this survey’s results. The variables that explain accounting ethics by groups of personal characteristics (honesty, reliability and objectivity and responsibility) are not statistically significant.
All personal characteristics are statistically differentiating based on age in explaining accounting ethics. The groups of personal characteristics that explain accounting ethics and differentiate based on age are ethical behavior, honesty reliability and objectivity and responsibility. According to the differentiation analysis of accounting ethics based on age, age group 36-45 behaves most ethically. For the characteristic honesty, reliability and objectivity age group 46-55 has less mean than age groups 30-35, 36-45 and 56 and more. The age group 36-45 is also superior in responsibility than 29 or less, 30-35 and 46-55.
Only ethical behavior and responsibility are statically significant in explaining the differentiation of accounting ethics based on education. Honesty, reliability and objectivity is not statistically significant. In the differentiation analysis of accounting ethics based on education, vocational education group is the most ethical according to the survey. University education group is more responsible than high school and master’s or higher.
Finally based on marital status only ethical behavior is statistically significant in explaining accounting ethics. Honesty, reliability and objectivity and responsibility are not statistically significant. According to the differentiation analysis of accounting ethics based on marital status, statistically married marital status is more ethical than single.
Based on the research, it is clear that an emphasis should be given to accounting ethics which is statistically affected by work-life balance. The results also indicate that the effect of work to personal life decreases ethical behavior. Therefore it is suggested that accounting firms should reconsider their job descriptions, responsibilities, working hours, and number of employees in order to make sure that the effect of work to personal life doesn’t influence ethical behavior.
Another issue that firms might useful from the findings of the survey is that the effect of working with husband/wife or other relative decreases ethical behavior. To avoid this risk the firms might develop policies to employ these people at separate locations, making them responsible from different duties.
It’s also seen from the research those who can balance work and life have a tendency to work more ethically. The occupational institutions and the government should give an emphasis to working conditions of the accountants.
Ethical rules about the accounting occupation in Turkey are in the forms of law and legislations. This brings a problem of referring to multiple sources about when applying rules. To avoid this, the principles and rules on accounting ethics can be evaluated as a whole. Occupational institutions should be responsible in accepting and applying these.
Based on research results, accountants have different tendencies of ethical behavior and responsibility based on education. The vocational education group is the most ethical according to the results. Therefore accounting ethics should be taught as in the vocational education by accounting cases. This could increase the ethical behavior and responsibility of accountants when they work professionally.
Occupational ethics can be improved with education as in developed countries. Because of this occupational rules should be prepared in written by a single institution. Occupational ethics can be taught as a class in higher education and in universities. These classes are proposed not only for accounting department but for all departments.
Another interesting result of the survey is that the age group 36-45 behaves more ethically and responsibly than other age groups. It’s also seen that age group 46-55 have the least honesty, reliability and objectivity characteristic. The results show that accountants tend to take more risks or forget about accounting ethics during a certain period of their career. It’s therefore important to be reminded of accounting ethics throughout the career emphasizing possible consequences. As a focus, age group 46-55 or that years of experience in the profession can be targeted to be included in accounting ethics seminars by occupational institutions.
Finally, it is suggested that accountants should be taught ethics during accounting education. In addition, seminars and conferences on occupational ethics can often be organized for accountants during their careers. In addition in-service education can often be made by the occupational institution to develop a common understanding of occupational ethics.
For further research, the other effects of work life balance to work can be studied in accounting profession. Also the research itself can be analyzed based on different demographic factors. It would be also interesting to do the research in different countries to analyze cultural effects.
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
Contributors/Acknowledgement: Both authors contributed equally to the conception and design of the study. |
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