1 Middle East Technical University, Ankara, Turkey
2 South African College of Applied Psychology, Johannesburg, South Africa
Each individual has unique personality traits which affect decision-making process. Those traits are defined as cautiousness, openness to experience, decision difficulty, agency, emotion neutrality, goal orientation, intuitive awareness, plan orientation, pro-activity, and rationality.
The study aimed to show how established personality traits as dimensions of decision-making can be used to classify four distinct decision-making styles. The personality styles are defined as avoidant, designer, flexible, and auditor styles.
A global survey was conducted to gather information on individual decision-making styles. Quantitative methods, such as tabular analysis, mean score equivalency test, correlation analysis, discriminant analysis and chi-square test for association have been used.
We found that there are significant gender differences in personality styles. This is partially due to the differences in emotion-neutrality scores among men and women. Female respondents are more emotional, a finding that is common in educational workers.
The results reinforce that gender differences in emotions exist. For a socially interactive occupation such as education, being emotional might lead to better communication.
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* Address correspondence to this author at the Middle East Technical University, Ankara, Turkey; E-mail: email@example.com
Understanding decision-making styles aims to help researchers and managers understand the phenomenon of why individuals participate in activities that may result in high-risk and possibly damaging outcomes [1Scott SG, Bruce RA. Decision-making style. The development and assessment of a new measure Educ Psychol Meas 1995; 55(5): 818-31. 7]. One may only look as far as the decisions made by professionals in the financial sectors are concerned that resulted in the 2008 global financial crisis, or the British exit from the European Union and seemingly self-destructive decision that leaders make in relation to climate change, to understand why understanding decision-making styles has become a significant aspect of leadership. Within professional sectors, including the education sector, making decisions that will have a significant impact on the lives of people is so commonplace that Lunenburg [2Lunenburg FC. National Policy/Standards.The Wiley Handbook of Educational Supervision 2018; 379-405. Internet [http://dx.doi.org/10.1002/9781119128304.ch16] ] suggests that it is “a way of life”, that saturates all levels of organisation (from leadership, management, administrators to the grassroots level). Even though research indicates that there is a correlation between the democratisation of decision-making autonomy and positive relationships within the organisation [3Cranston NC. Collaborative decision-making and school-based management: Challenges, rhetoric and reality. J Educ Enq 2001.], there remains a lack of understanding how decision-making styles influence the dimensions of decision-making and how this has an impact on the development of policy and practices, especially in professions where a sense of purpose and emotion plays a significant role, such as the education sector.
1.1. Personality Traits that Contribute to Possible Decision-making Styles
According to Barry and Steward [4Barry B, Stewart GL. Composition, process, and performance in self-managed groups: the role of personality. J Appl Psychol 1997; 82(1): 62-78. [http://dx.doi.org/10.1037/0021-9010.82.1.62] [PMID: 9119798] ], the role of personality is an important factor in self-managed groups. Decision-making, as a phenomenon in the realm of psychology, has received ample attention [5Kahneman D, Tversky A. Choices, Values and Frames 2000.]. Existing research prefers to place emphasis on the neurological aspects of decision-making or chooses to explore the linear processes of decision-making, rather than a phenomenological approach in which the different decision-making styles are aligned with styles of decision-making. Neuro-biological enquiry places an emphasis on specific areas of the brain and the direct link between decision-making and neurological processes. Conversely, a sequential or linear understanding of decision-making processes elucidates how alternative strategies and how each of these strategies determine the conceivable outcomes per strategy and lean towards comparative estimations that may lead to the desired outcomes based on the consequences of each [6Simon HA. Administrative Behavior: A Study of Decision-making Processes in Administrative Organization 1997.].
Scott and Bruce [1Scott SG, Bruce RA. Decision-making style. The development and assessment of a new measure Educ Psychol Meas 1995; 55(5): 818-31. 7] describe the decision-making as a process of “learned habitual response patterns exhibited by an individual when confronted with a decision situation”. Delineation is drawn between five discrete styles: rational, intuitive, reliant, avoidant and spontaneous. Despite such demarcation, a deeper appreciation of the phenomenon of decision-making processes or style of individuals or groups remains to be explored by either the neuro-biological, sequential or linear or decision-making style approaches. In this article, we propose 10 dimensions of decision-making. These dimensions are connected and derived from the phenotypic personality traits [7Goldberg LR. The structure of phenotypic personality traits. Am Psychol 1993; 48(1): 26-34. [http://dx.doi.org/10.1037/0003-066X.48.1.26] [PMID: 8427480] ] the existence of human agency [8Bandura A. Human agency in social cognitive theory. Am Psychol 1989; 44(9): 1175-84. [http://dx.doi.org/10.1037/0003-066X.44.9.1175] [PMID: 2782727] ] and self-determination theory [9Gagné M, Deci EL. Self-determination theory and work motivation. J Organ Behav 2005. [http://dx.doi.org/10.1002/job.322] ] that may expound the decision-making process: cautiousness, openness to experience [10Connelly BS, Ones DS, Chernyshenko OS. Introducing the Special Section on Openness to Experience. Review of openness taxonomies, measurement, and nomological net J Pers Assess 2014; 96(1): 1-16.], agency [11Spicer DP, Sadler-Smith E. An examination of the general decision making style questionnaire in two UK samples. J Manag Psychol 2005; 20(2): 137-49. [http://dx.doi.org/10.1108/02683940510579777] ], decision difficulty, emotion neutrality [12Lerner JS, Li Y, Valdesolo P, Kassam KS. Emotion and decision making. Annu Rev Psychol 2015; 66(1): 799-823. [http://dx.doi.org/10.1146/annurev-psych-010213-115043] [PMID: 2 5251484] ], goal orientation [8Bandura A. Human agency in social cognitive theory. Am Psychol 1989; 44(9): 1175-84. [http://dx.doi.org/10.1037/0003-066X.44.9.1175] [PMID: 2782727] ], intuitive awareness [13Malewska K. The profile of an intuitive decision maker and the use of intuition in decision-making practice. Management 2017; 22(1): 31-44. [http://dx.doi.org/10.2478/manment-2018-0003] ], plan orientation [8Bandura A. Human agency in social cognitive theory. Am Psychol 1989; 44(9): 1175-84. [http://dx.doi.org/10.1037/0003-066X.44.9.1175] [PMID: 2782727] ], pro-activity [14Petri HL, Govern JM. Motivation: Theory, Research, and Application Wadsworth, Cengage Learning; 2013.] and rationality [6Simon HA. Administrative Behavior: A Study of Decision-making Processes in Administrative Organization 1997.]. In our investigation, we measured the aforementioned dimensions from data collected via an online survey of 356 respondents. The results confirm that each dimension is uniquely correlated with the decision-making processes. Significant gender and employment sector differences are clear in regard to emotion-neutrality in decision-making.
1.2. Role of Emotions and Gender on Decision-making
Emotions reflect a combination of conscious and unconscious processes, linked to behaviours that include the decision-making process. Many studies investigated the role of emotional intelligence in life [15Salovey P, Grewal D. The science of emotional intelligence. Curr Dir Psychol Sci 2005; 14: 281-5. [http://dx.doi.org/10.1111/j.0963-7214.2005.00381.x] -17Zammuner VL. Men’s and women’s lay theories of emotion.Gender and emotion 2000; 48-70. [http://dx.doi.org/10.1017/CBO9780511628191.004] ]. Emotional intelligence is a significant predictor of depressive symptoms [18Gomez-Baya D, Mendoza R, Paino S, de Matos MG. Perceived emotional intelligence as a predictor of depressive symptoms during mid-adolescence: A two-year longitudinal study on gender differences. Pers Individ Dif 2017; 104: 303-12. [http://dx.doi.org/10.1016/j.paid.2016.08.022] ]. Emotional training is an integral part of education [19McConnell MM, Eva KW. The role of emotion in the learning and transfer of clinical skills and knowledge. Acad Med 2012; 87(10): 1316-22. [http://dx.doi.org/10.1097/ACM.0b013e3182675af2] [PMID: 2291 4515] ]. Negative emotions tend to reduce the effectiveness of the education process [20Sutter-Brandenberger CC, Hagenauer G, Hascher T. Students’ self-determined motivation and negative emotions in mathematics in lower secondary education- Investigating Reciprocal Relations Contemp Educ Psychol 2018; 55: 166-75.]. Emotion is the inner sense that generates feelings, and moods that emanate as a result of an experienced stimulus. Humans experience emotions in terms of an evaluative judgment of ‘liking’ or ‘disliking’ a person, situation or an object [21Tripathi MN. Dissecting affect : An attempt to understand its influence on consumer decision making. XIMB J Manag 2015; 2(1): 98-114.]. Emotions cannot be dissociated from routine situations, including that of the decision-making process. The human experience of emotions may inhibit the efficacy of the individual or group’s decision-making process.
The role of gender in an emotional setting is of great interest. Research suggests that there are existing gender differences that affect the emotional decision-making process [22Carli LL, Loeber CC, Lafleur SJ. Nonverbal behavior, gender, and influence. J Pers Soc Psychol 1995; 68(6): 1030-41. [http://dx.doi.org/10.1037/0022-35184.108.40.2060] -26Volden C, Wiseman AE, Wittmer DE. When are women more effective lawmakers than men? Am J Pol Sci 2013; 57(2): 326-41. [http://dx.doi.org/10.1111/ajps.12010] ]. However, this is still a controversial subject due to the discrimination faced by female decision-makers. Some studies suggest that the role of female politicians is an integral part of the democratic decision-making process [27Niederle M, Vesterlund L. Gender differences in competition. Negotiation J 2008; 24(4): 447-63. [http://dx.doi.org/10.1111/j.1571-9979.2008.00197.x] -29Bauer G, Burnet JE. Gender quotas, democracy, and women’s representation in Africa: Some insights from democratic Botswana and autocratic Rwanda. Womens Stud Int Forum 2013; 41: 103-12. [http://dx.doi.org/10.1016/j.wsif.2013.05.012] ] and manly emotions are beneficial for men [30Hess U, David S, Hareli S. Emotional restraint is good for men only: The influence of emotional restraint on perceptions of competence. Emotion 2016; 16(2):208–13 Available from: http://doi.apa.org/getdoi.cfm?doi=10.1037/emo0000125, 31Robertson J, Lin C-W, Woodford J, Danos K, Hurst M. The (Un)emotional male: Physiological, verbal, and written correlates of expressiveness. J Men’s Stud 2001; 9(3): 393-412. [Internet]. [http://dx.doi.org/10.3149/jms.0903.393] ]. Some research suggests that age can also be a moderating factor in closing the gender gap in leadership [32Chaturvedi S, Zyphur MJ, Arvey RD, Avolio BJ, Larsson G. The heritability of emergent leadership: Age and gender as moderating factors. Leadersh Q 2012; 23(2): 219-32. [http://dx.doi.org/10.1016/j.leaqua.2011.08.004] , 33Fabes RA, Martin CL. Gender and age stereotypes of emotionality. Pers Soc Psychol Bull 1991; 17(5): 532-40. [http://dx.doi.org/10.1177/0146167291175008] ]. Nevertheless, being a professional woman comes with additional challenges [34Kalysh K, Kulik CT, Perera S. Help or hindrance? Work–life practices and women in management. Leadersh Q 27(3): 504-18. [http://dx.doi.org/10.1016/j.leaqua.2015.12.009] -37Sojo VE, Wood RE, Wood SA, Wheeler MA. Reporting requirements, targets, and quotas for women in leadership. Leadersh Q 27(3): 519-36. [http://dx.doi.org/10.1016/j.leaqua.2015.12.003] ]. Stereotyping is the common hurdle faced by female professionals [38Levy SR, Stroessner SJ, Dweck CS. Stereotype formation and endorsement: The role of implicit theories. J Pers Soc Psychol 1998; 74(6): 1421-36. [http://dx.doi.org/10.1037/0022-35220.127.116.111] -40Ritter BA, Yoder JD. Gender differences in leader emergence persist even for dominant wo men: An updated confirmation of role congruity theory. Psychol Women Q 2004; 28: 187-93. [http://dx.doi.org/10.1111/j.1471-6402.2004.00135.x] ]. Gender-based occupational factors lead to sustained gender disparities in a professional business and even in education [41Gaucher D, Friesen J, Kay AC. Evidence that gendered wording in job advertisements exists and sustains gender inequality. J Pers Soc Psychol 2011; 101(1): 109-28. [http://dx.doi.org/10.1037/a0022530] [PMID: 21381851] -46Hoyt CL, Murphy SE. Managing to clear the air: Stereotype threat, Women, And leadership. Leadersh Q 2016; 27(3): 387-99. [http://dx.doi.org/10.1016/j.leaqua.2015.11.002] ]. There is also a common belief that stereotyping also exists in emotional settings [47Plant EA, Hyde JS, Keltner D, Devine PG. The gender stereotyping of emotions. Psychol Women Q 2000; 24(1): 81-92. [http://dx.doi.org/10.1111/j.1471-6402.2000.tb01024.x] -50Boven LV, Robinson MD. Boys don’t cry: Cognitive load and priming increase stereotypic sex differences in emotion memory. J Exp Soc Psychol 2012; 48(1): 303-9. [http://dx.doi.org/10.1016/j.jesp.2011.09.005] ]. That is why measuring emotions has become a science itself.
Among psychologists and philosophers, there is a shared impasse on how to demarcate and measure emotions [51Scherer KR. What are emotions? and how can they be measured. Social Science Information 2005; 44: 695-729.]. Measuring emotions, using physical tools, is a substantial struggle for researchers [52Duffy MC, Lajoie SP, Pekrun R, Lachapelle K. Emotions in medical education: Examining the validity of the Medical Emotion Scale (MES) across authentic medical learning environments. Learn Instr 2018. [http://dx.doi.org/10.1016/j.learninstruc.2018.07.001] ] resulting in reliance on self-reporting measures of emotions [53Pekrun R, Bühner M. Self-Report measures of academic emotions. In: Patricia A, Alexander , Pekrun R, Linnenbrink-Garcia L, Eds. International Handbook of Emotions in Education Routledge; 2014.]. According to Ekman and Cordaro [54Ekman P, Cordaro D. What is meant by calling emotions basic Emot Rev [Internet] 2011 Oct 20 [cited 2018 Oct 8]; 3(4): 364-70.Available from: http://journals.sagepub.com/doi/10.1177/1754073911410740 [http://dx.doi.org/10.1177/1754073911410740] ] “[e]motions are discrete, automatic responses to universally shared, culture-specific and individual-specific events”. Self-reporting, in a twist of irony, is based on incidental mood and is difficult to establish reliability in a test, re-test scenario. Individuals that self-report as emption-reliant are often affected by strong emotional states that either activate or deactivate behaviours, concomitantly impacting how they react to situations where they are required to make decisions. If an individual or a group perceives that preferential outcomes are likely, this triggers emotions resulting in an ‘ amplification that may reflect on our affective responses to positive and negative outcomes’ [55Tversky A, Fox CR. Weighing Risk and Uncertainty.Choices, Values, and Frames 2000; 93-117.]. Consequently, individuals that self-report as emotion-reliant may look for a solution that feels right, rather than one that is congruent to specific guidelines or desired outcomes. Decisions that feel uncomfortable, yet are more likely to yield the desired outcomes are left by the wayside.
2. MATERIALS AND METHODS
We assumed that there are 10 dimensions of the decision-making process. These dimensions can be listed as cautiousness, openness to experience, decision difficulty, agency, emotion neutrality, goal orientation, intuitive awareness, plan orientation, pro-activity, and rationality. We conducted an online survey designed by Google forms. The survey was posted to online forums. As the survey was conducted online, there was no pressure or motivation to state biased answers. The only motivation for the survey respondents was to help this academic research by their contribution. The survey was completely anonymous with no personal identification possibility. We collected information on the participants' age group, educational attainment, gender, current location, and current occupation. In order to measure the decision-making attributes, we followed a quantitative approach. Specifically, we asked survey participants to rank how they make decisions for each dimension. The answer scale was from 1 (not like me) to 10 (very much like me). Here is how each dimension is measured:
Cautiousness: I am very cautious when it comes to new experiences.
Openness to Experience: I feel comfortable following my intuitions when I'm making decisions.
Agency: I prefer to have complete freedom over making my own decisions.
Decision Difficulty: Making decisions is difficult for me, I prefer to follow somebody else’s advice.
Emotion Neutrality: My emotions are neutral and objective when I make a decision.
Goal Orientation: I am goal orientated and I’m willing to change the plan to achieve the goal.
Intuitive Awareness: I depend on my intuitive awareness to make decisions.
Plan Orientation: I am a logical and plan-orientated decision-maker and I don’t like changing the plan.
Pro-Activity: I prefer being pro-active when making decisions.
Rationality: I prefer to think about a decision I have to make in a rational way.
Google survey analytics was not enough to perform detailed statistical reporting on the data. Therefore, we used different data analysis and visualization tools to explain our data. Initial data organization was performed with Excel 2016. Minitab software is used to create relevant statistical tables. Finally, Tableau 2018.3 is utilized to create cross tabulation tables and visual analytics.
In terms of demographic information, the age distribution shows normal behaviour. Out of 356 respondents, 103 of them stated that they are around 36-45 years old. Next comes 46-55 interval, followed with 26-35 interval each of which has 86 and 79 respondents, respectively. In terms of gender, our data is similar to that of Karwowski [56Karwowski M. Did curiosity kill the cat? relationship between trait curiosity, creative self-efficacy and creative personal identity. Eur J Psychol 2012; 8(4): 547-58. [http://dx.doi.org/10.5964/ejop.v8i4.513] ]. 204 of all responses were of females; of which 89 were of those working in an education sector. 152 of all responses were of males, of which, 50 were of those working in an education sector. 134 responses were from Africa, followed by Europe (97), America (39), Middle-East [49Timmers M, Fischer A, Manstead A. Ability versus vulnerability: Beliefs about men’s and women’s emotional behaviour. Cogn Emotion 2003; 17(1): 41-63. [http://dx.doi.org/10.1080/02699930302277] [PMID: 29715738] ] and Australasia [37Sojo VE, Wood RE, Wood SA, Wheeler MA. Reporting requirements, targets, and quotas for women in leadership. Leadersh Q 27(3): 519-36. [http://dx.doi.org/10.1016/j.leaqua.2015.12.003] ]. Table 1 below shows cross-tabulation of respondents based on different demographic factors (Table 1).
It is worth noting about (Table 1) that while we have data on individual occupations, the sectoral data was highly diversified including administrative positions, agriculture, business and financial operations, computer design, education and training, engineering, entertainment, fashion, government, healthcare, hospitality, legal professions, marketing, media, military, retired, service, student, and even unemployed. However, the number of educational sector workers constitutes almost 40% of the data. Therefore, we decided to combine all other occupational sectors into the “Others” category. That also helped us to test if educational sector workers are more likely to have different personality categories. Similarly, in the original data, the educational attainment had categories such as doctorate degree, post-graduate degree, university degree, secondary school, and technical degrees. In order to see if having a university degree makes a difference, educational attainment has also been categorized. Those with a doctorate degree, post-graduate degree, or at least a university degree have been categorized as University+ whereas those with a secondary school or technical degrees categorized as others.
Table 1 Cross-tabulation based on Gender/Education vs age, geography, and occupation.
Table 2 Statistical Analysis of decision-making dimensions.
Table 3 Correlation between decision-making dimensions.
In the model, we assumed 10 dimensions in the decision-making process. Based on these dimensional measurements, the individuals can be categorized into 4 styles of decision-making. These decision-making styles are avoidant, designer/auditor, flexible, and fluent. A quick statistical analysis of the decision-making dimensions is shown in Table 2.
It is of interest to see whether each dimension is a unique one or redundant. Thus, if some measurements are highly correlated with each other, then these measurements would be redundant. Table 3 shows us the correlation between measured dimensions.
The correlation matrix in Table 3 suggests that each dimension is a unique one. There is almost no correlation between dimensions. The only correlation that is higher than 0.5 is the correlation between the openness (Q8) and Intuitive Awareness (Q2) which is equal to 0.52. However, these dimensions are obviously complementary with each other and can be used to classify the decision-making styles without redundancy. The decision-making dimensions are used to categorize each respondent into a specific personality type. As most answers were clustered at values above the arithmetic means, we first transformed the variables by normalization. The normalized values work as follows:
Here each Zi value refers to the normalized score of decision-making dimension. Xi is the original score (from 1 to 10), mean (X) is the arithmetic mean, and Std. Dev. (X) is the standard deviation. This transformation enables us to see where each decision-maker stands according to other survey respondents.
Using 10 dimensions of decision-making, each individual is classified into a specific personality type. The decision-making styles are avoidant, designer/auditor, flexible, and fluent decision-making styles. We tested the decision-making classifications using both linear and quadratic discriminant analysis. According to the linear analysis, out of 356 respondents, the model estimated 303 of them correctly. The quadratic discriminant analysis performed much better. The quadratic model estimated 333 classifications correctly. This translates into a success rate of 93.5%. A summary of classification results is shown in Table 4.
According to the model, 150 of the respondents had fluid type of character, 146 had flexible type character, 31 could be called avoidant, and 29 could be called as designer/auditor style.
The quadratic classification method has correctly identified both avoidant and design/auditor decision-making styles correctly (100% success rate). Out of 146 flexible decision-making styles, 132 were classified correctly; 7 were misclassified as fluid, 6 were misclassified as avoidant, 1 was misclassified as designer/auditor type (90.4% success rate). Out of 150 fluid decision-making styles, 141 were classified correctly; 3 were misclassified as avoidant, 3 were misclassified as design/auditor, and 3 were misclassified as flexible type (94% success rate). These results suggest that personality classification based on decision-making dimensions was very well according to quadratic discrimination analysis.
Based on the above decision-making styles, it is also of interest to see whether associated individual characteristics such as age, educational attainment, gender, geographical location, and occupational sector affect the decision-making styles. Therefore, we tested each of these factors using Chi-square tests for association. For duality purposes, anyone below 35 is classified as a young professional, whereas above 35 is another category. Educational attainment measures whether the individual has a university degree or not. Gender is simply classified as male or female. Geographic location measures whether the individual is located in the western world or not. Occupational sector measures whether the individual is working in an educational institution or in another sector.
The default (null) hypothesis for the effect of each individual characteristic is as follows:
H0: The decision-making style is independent of individual characteristic.
The alternative hypothesis is defined as follows:
Ha: The decision-making style is affected from individual characteristics.
These tests are conducted using Minitab analysis for an association. The computer output also included details on the true and expected number of respondents under each category. However, in Table 5, we report only the simplified results based on analysis:
As can be seen in Table 5, the chi-square tests for association do not suggest any significant relation between decision-making styles and personal socio-demographic characteristics. These findings imply that factors such as age, educational attainment, gender, geography, and occupation do not affect decision-making styles. However, if we consider the significance value of 90% instead of 95%, then gender can be considered as an effective factor in personality. Therefore, it is worth investigating the effect of gender on personality type. Table 6 shows the results for detailed chi-square test for association between gender and personality styles.
Table 4 Summary of Classifications.
Table 5 Chi-square Test Results.
Table 6 Detailed Chi-square Test for Association between Gender and Style.
Table 7 Gender Difference on Decision-Making Dimensions.
The fractional numbers in Table 6 correspond to the expected number of respondents based on probability distribution whereas the integers correspond to the actual number of respondents. For independence, the actual numbers should be as close as possible to the expected numbers. For Designer/Auditor and Fluid decision-making styles, these numbers are very close. However, 24 females and 7 males are classified as avoidant type whereas these numbers are expected to be 17.76 and 13.24, respectively. Thus, female respondents are more likely to have avoidant personality compared to their male counterparts. Similarly, 76 females and 70 males are classified as flexible type, whereas these numbers are expected to be 83.66 and 62.34, respectively. Thus, male respondents are more likely to have flexible personality compared to their female counterparts. These results suggested that gender might be a significant factor in personality classification. Therefore, we decided to test each individual decision-making factor to see if gender differences are significant. The individual test results for each dimension of decision-making are shown in Table 7.
Based on Table 7, one can conclude that there are minor gender differences in decision making process. Female decision makers are slightly more cautious, pro-active, rational, intuitively aware, slightly less comfortable, goal oriented, and plan oriented compared to male decision makers. They also experience higher decision difficulty accompanied with more decision freedom when compared with male counterparts. However, none of these factors are statistically significant. The only significant divergent factor is emotion neutrality. Female decision-makers are less emotion neutral than male decision-makers. Our results in Fig. (1) suggest that this finding is amplified for educational sector workers (teachers, university lecturers, lab instructors, teaching assistants).
The visual in Fig. (1) shows the confidence interval for the mean values. Females are less emotion-neutral compared to male decision-makers. While this factor is insignificant for those who work in other sectors, the gender difference is magnified within the education and training sector. The average emotion-neutrality score for females working in the education sector is 5.2, whereas males have an average emotion-neutrality score of 6. This implies a significant difference of 0.8 points between male and female workers in the education sector. Thus, females working in the education sector are more likely to make emotional decisions.
This result also partially explains the association between gender and decision-making style. As females are more likely to make emotional decisions, they are also more likely to be considered as avoidant, and less likely to be considered as fluent decision-making style. Similarly, the avoidant behaviour is less observed in male decision-makers and they are more likely to fall into fluent decision-making style.
Mean Emotion-Neutrality Scores by Gender and Occupation.
The results suggest that female participants have a significantly stronger leaning towards making emotion-dependent decisions; a finding that is specifically strong in the education sector. Hutson-Comeaux and Kelly [57Hutson-Comeaux SL, Kelly JR. Gender stereotypes of emotional reactions: How we judge an emotion as valid. Sex Roles 2002; 47(1–2): 1-10. [http://dx.doi.org/10.1023/A:1020657301981] ] assert that women show more emotional expression, which supports these findings. However, there is no indication in the data that the prevalence of emotion should be mistaken as an antithesis of rationality, which is supported by the findings of Gaudine and Thorne [58Gaudine A, Thorne L. Emotion and ethical decision-making in organizations. J Bus Ethics 2001; 31(2): 175-87. [http://dx.doi.org/10.1023/A:1010711413444] ] as well as Pulsford, [59Pulsford M. Constructing men who teach: Research into care and gender as productive of the male primary teacher. Gend Educ 2014; 26(3): 215-31. [http://dx.doi.org/10.1080/09540253.2014.901719] ]. A stronger emotion-dependent approach to making decisions does not lead to irrationality, conversely, it should rather be considered as an inimitable characteristic of the decision-making process.
It is important to reiterate that emotions are an innate part of the decision-making process [60Yik M, Russell JA, Steiger JHA. A 12-Point circumplex structure of core affect. Emotion 2011; 11(4): 705-31. [http://dx.doi.org/10.1037/a0023980] [PMID: 21707162] ]. Research suggests that emotional behaviour may as a matter fact contribute to less deleterious decision-making [61Seo MG, Barrett LF. Being emotional during decision making good or bad? An empirical investigation. Acad Manage J 2007; 50(4): 923-40. [http://dx.doi.org/10.5465/amj.2007.26279217] [PMID: 18449361] ]. As the inclusion of emotional intelligence training has become a primary aspect of the corporate ethos [62George JM. Emotions and leadership: The role of emotional intelligence. Hum Relat 2000; 53(8): 1027-55. [http://dx.doi.org/10.1177/0018726700538001] ], the acceptance of emotion as a dimension of decision-making has grown. Specifically, in the educational sector, school leaders who show emotion-neutral decision-making may face opposition from millennial parents who are more versed in the importance of a better student-teacher relationship. This assertion may be of significance when one considers that female teachers are more likely to encourage innovative educational ideas in comparison to their male counterparts. Emotion and gender is another important, if not controversial field of inquiry [63Arreman IE, Weiner G. Gender, research and change in teacher education: A Swedish dimension. Gend Educ 2007; 19(3): 317-37. [http://dx.doi.org/10.1080/09540250701295478] ].
Research on the stereotyping of women in the workplace confirms that there remain stereotypical claims that women are more emotional than their male counterparts [64Barrett LF, Bliss-Moreau E. She’s emotional. He’s having a bad day: Attributional explanations for emotion stereotypes. Emotion 2009; 9(5): 649-58. [http://dx.doi.org/10.1037/a0016821] [PMID: 19803587] ]. Negative stereotyping is a contributing factor to why female workers remain under-represented in management, politics and senior leadership [65Bergeron DM, Block CJ, Echtenkamp BA. Disabling the able: Stereotype threat and women’s work performance. Hum Perform 2006; 19(2): 133-58. [http://dx.doi.org/10.1207/s15327043hup1902_3] -67Fischbach A, Lichtenthaler PW, Horstmann N. Leadership and gender stereotyping of emotions: Think manager - Think male? J Pers Psychol 2015; 14(3): 153-62. [http://dx.doi.org/10.1027/1866-5888/a000136] ]. Colloquially known as the glass ceiling, this stereotyping may impede the career progression of female workers [68Cross C, Linehan M. Barriers to advancing female careers in the high-tech sector: Empirical evidence from Ireland. Burke RJ, editor Women Manag Rev 2006; 2006; 21(1): 28-39.-71Heilman ME. Gender stereotypes and workplace bias. Res Organ Behav 2012; 32: 113-35. [http://dx.doi.org/10.1016/j.riob.2012.11.003] ]. In addition, research indicates that scientific fields such as in medical science, being a female doctor can affect a patient’s perceived performance by the medical practitioner [72Roter DL, Hall JA. Women doctors don’t get the credit they deserve. J Gen Intern Med 2015; 30(3): 273-4. [http://dx.doi.org/10.1007/s11606-014-3081-9] [PMID: 25361687] , 73Roter DL, Hall JA, Aoki Y. Physician gender effects in medical communication: A meta-analytic review. JAMA 2002; 288(6): 756-64. [http://dx.doi.org/10.1001/jama.288.6.756] [PMID: 12169083] ]. However, there is also research that suggests that where gender diversity of company boards is present, such diversity is not indicative of superior financial performance in these companies [74Carter DA, D’Souza F, Simkins BJ, Simpson WG. The gender and ethnic diversity of US boards and board committees and firm financial performance. Corp Gov An Int Rev 2010; 18(5): 396-414. [http://dx.doi.org/10.1111/j.1467-8683.2010.00809.x] ]. The relationship between gender and race is also of interest [75Martin CL, Parker S. Folk theories about sex and race differences. Pers Soc Psychol Bull 1995; 21(1): 45-57. [http://dx.doi.org/10.1177/0146167295211006] ]. In some studies, the term ‘race’ is replaced by ethnicity [76Reid PT, Comas-Diaz L. Gender and ethnicity: Perspectives on dual status. Sex Roles 1990; 22(7–8): 397-408. [http://dx.doi.org/10.1007/BF00288160] ].
The role of gender differences in emotion dependence may also be accredited to the parochial cultures or even to the ethnicity of the participants in gender-based research [77Brody LR. The socialization of gender differences in emotional expression: Display rules, infant termperament, and differentiation.Gender and emotion: Social psychological perspectives 2000; 24-47. [http://dx.doi.org/10.1017/CBO9780511628191.003] -79Fischer AH, Rodriguez Mosquera PM, van Vianen AEM, Manstead ASR. Gender and culture differences in emotion. Emotion 2004; 4(1): 87-94. [http://dx.doi.org/10.1037/1528-3518.104.22.168] [PMID: 15053728] ]. Some studies claim that the prejudice against women is prevalent when decision-making takes place in mixed gender groups [80Cottrell CA, Neuberg SL. Different emotional reactions to different groups: A sociofunctional threat-based approach to “prejudice”. J Pers Soc Psychol 2005; 88(5): 770-89. [http://dx.doi.org/10.1037/0022-3522.214.171.1240] [PMID: 15898874] ]. The relationship between the gender-role composition of the group and explicit gender role division in group-based decision-making has a significant impact on how emotional dependence in women is perceived [81Johnson RA, Schulman GI. Gender-role composition and role entrapment in decision-making groups. Gend Soc 1989; 3(3): 355-72. [http://dx.doi.org/10.1177/089124389003003005] ]. The prevalence of male bias in such research findings is concerning and leads one to question the validity of equal representation in the participant samples of such research.
However, as cracks in the glass ceiling begin to appear, typecasts perceptions of women in the workplace are changing and the gender-gap is shrinking as more women find their way into private and public sector leadership positions as well as taking precedence as active contributors in the economy [82Duehr EE, Bono JE. Men, women, and managers: Are stereotypes finally changing? Person Psychol 2006; 59(4): 815-46. [http://dx.doi.org/10.1111/j.1744-6570.2006.00055.x] , 83Eagly AH, Diekman AB, Johannesen-Schmidt MC, Koenig AM. Gender gaps in sociopolitical attitudes: A social psychological analysis. J Pers Soc Psychol 2004; 87(6): 796-816. [http://dx.doi.org/10.1037/0022-35126.96.36.1996] [PMID: 15598107] ]. Active participation of women workers in the labour market might lead to an organic reduction in gender-differentiated roles within the economy [84Charles M. A world of difference: International trends in women’s economic status 2011; Vol. 37]. As an example, entrepreneurs are more likely to encourage family-oriented company policies [85Adkins CL, Samaras SA, Gilfillan SW, Mcwee WE. The relationship between owner characteristics, company size, and the work-family culture and policies of women-owned businesses. J Small Bus Manag 2013; 51(2): 196-214. [http://dx.doi.org/10.1111/jsbm.12014] ]. Similarly, businesses that encourage women in leadership positions have an increased likelihood to nurture female-friendly policies [86Tate G, Yang L. Female leadership and gender equity: Evidence from plant closure. J Financ Econ 2015; 117(1): 77-97. [http://dx.doi.org/10.1016/j.jfineco.2014.01.004] ].
4.1. Decision-making in the Education Sector
A significant finding is that emotion-dependence in decision-making in the education sector is more prominent than in the business sector. It is noteworthy to explore the controversy of emotions as a point of contention in the education sector. According to the theory of self-determination, motivation is a phenotypical dimension of success in education [87Deci EL, Ryan RM, Vallerand RJ, Pelletier LG. Motivation and education: The self-determination perspective. Educ Psychol 1991; 26(3–4): 325-46. [http://dx.doi.org/10.1080/00461520.1991.9653137] ]. Establishing a professional-emotional student-teacher relationship is an important positive motivational force in the school setting, especially in elementary [88Hargreaves A. Mixed emotions: Teachers’ perceptions of their interactions with students. Teach Teach Educ 2000; 16(8): 811-26. [http://dx.doi.org/10.1016/S0742-051X(00)00028-7] ] and fully inclusive schools where special education needs and poverty in the school community are prevalent.
If the findings show that female teachers are more likely to be emotion-dependent in their decision-making style, we must consider how this finding influences the outcomes of female students. Women teachers play a crucial role as role-models in traversing traditional (and perceived) gender boundaries in education [89Liu HY, Li YL. Crossing the gender boundaries: The gender experiences of male nursing students in initial nursing clinical practice in Taiwan. Nurse Educ Today 2017; 58: 72-7. [http://dx.doi.org/10.1016/j.nedt.2017.08.006] [PMID: 28917155] ]. For example, the performances of girls in mathematics courses are not dissimilar than their male counterparts [90Frenzel AC, Pekrun R, Goetz T. Girls and mathematics - A “hopeless” issue? A control-value approach to gender differences in emotions towards mathematics. Eur J Psychol Educ 2007; 22(4): 497-514. [http://dx.doi.org/10.1007/BF03173468] ]. Thus, the question then remains why there are still a disproportionate number of girls excelling in mathematics and science. We know that gender does not have an influence on the self-efficacy of students at secondary school [91Salavera C, Usán P, Jarie L. Emotional intelligence and social skills on self-efficacy in Secondary Education students. Are there gender differences? J Adolesc 2017; 60(60): 39-46. [http://dx.doi.org/10.1016/j.adolescence.2017.07.009] [PMID: 287 50267] ], that said, empirical research by Halberstadt et al. [92Halberstadt AG, Castro VL, Chu Q, Lozada FT, Sims CM. Preservice teachers’ racialized emotion recognition, anger bias, and hostility attributions. Contemp Educ Psychol 2018; 54: 125-38. [http://dx.doi.org/10.1016/j.cedpsych.2018.06.004] ] indicates that the acknowledgement of emotions is often subject to the racial and gender bias of teachers. Communication is an essential component of the relationship [93Karnieli-Miller O, Michael K, Eidelman S, Meitar D. What you “see” is how you communicate: Medical students’ meaning making of a patient’s vignette. Patient Educ Couns 2018; 101(9): 1645-53. [http://dx.doi.org/10.1016/j.pec.2018.04.004] [PMID: 29691110] ]. Socially facilitative behaviour is more likely to be shown by feminine personalities [94Eagly AH, Karau SJ. Gender and the Emergence of Leaders: A Meta-Analysis. J Pers Soc Psychol 1991; 60(5): 685-710. [http://dx.doi.org/10.1037/0022-35188.8.131.525] ]. However, there might be gender differences in perceived communication [95Mast MS, Kadji KK. How female and male physicians’ communication is perceived differently. Patient Educ Couns 2018; 101(9): 1697-701. [http://dx.doi.org/10.1016/j.pec.2018.06.003] [PMID: 29903628] ]. Emotional intelligence does have an impact on the successful outcomes of all students insofar as students with higher emotional intelligence show higher performance in assessments [96Chew BH, Zain AM, Hassan F. Emotional intelligence and academic performance in first and final year medical students: A cross-sectional study. BMC Med Educ 2013; 13(1): 44. [http://dx.doi.org/10.1186/1472-6920-13-44] [PMID: 23537129] ].
4.2. Role of Mood Disorders on Emotions
The significance of emotions as a unique human phenomenon and as a dimension of decision-making is a unique contribution to either conscious or unconscious state of mind [97Winkielman P, Berridge K, Sher S. Emotion, Consciousness, and Social Behavior The Oxford Handbook of Social Neuroscience 2011; 195-211.]. Consequently, the role emotions play, as a dimension of decision-making as well as the importance of incidental emotions, the presence of mood disorders and other mental health difficulties merit further investigation.
Incidental emotions tie macro-level phenomena, such as “ambient weather, sport outcomes…[or] the state of the nation” as well as the behaviour of individuals together [12Lerner JS, Li Y, Valdesolo P, Kassam KS. Emotion and decision making. Annu Rev Psychol 2015; 66(1): 799-823. [http://dx.doi.org/10.1146/annurev-psych-010213-115043] [PMID: 2 5251484] ]. To what degree incidental emotions contribute to the efficiency of the decision-making process must yet be explored. In the same way, the pervasiveness on mood disorders and the impact of mood disorders as an impediment to effective decision-making need further clarification. As an example, the use of antidepressants within the education profession has seen significant amplification and an estimated 10% of teachers depend on mood enhancers to cope with workload pressures. In addition, six out of 10 teachers suggest that teaching has a deleterious effect on their mental health [98Pells R. One in ten teachers taking antidepressants to cope with work stresses 2017.]. Despite this, Destoop, et al. [99Destoop M, Schrijvers D, De Grave C, Sabbe B, De Bruijn ERA. Better to give than to take? Interactive social decision-making in severe major depressive disorder. J Affect Disord 2012; 137(1-3): 98-105. [http://dx.doi.org/10.1016/j.jad.2011.12.010] [PMID: 22240086] ] claim that there is no suggestion regarding the role major depressive disorder plays in the way teachers make decisions concerning fairness and neutrality in the decision-making process. Concurringly, individuals with bipolar disorder are inclined to have low decision consistency and have a propensity towards erratic choices [100Yechiam E, Hayden EP, Bodkins M, O’Donnell BF, Hetrick WP. Decision making in bipolar disorder: A cognitive modeling approach. Psychiatry Res 2008; 161(2): 142-52. [http://dx.doi.org/10.1016/j.psychres.2007.07.001] [PMID: 18848361] ]. Such contradiction in decision-making could have a damaging effect on the procedural, administrative and psycho-educational decisions that all pervade the decision-making of teachers on a daily basis. Therefore, we suggest that the impact of mood disorders on the decision-making style of individuals needs further investigation.
In this article, we revealed results of an international survey conducted on a global scale. The survey asked respondents to quantify how they make daily decisions. We specifically gathered information on their levels of cautiousness, openness to experience, decision difficulty, agency, emotion neutrality, goal orientation, intuitive awareness, plan orientation, pro-activity, and rationality when making decisions. Despite the survey was conducted anonymously, we gathered socio-demographic information such as age group, educational attainment, gender, current location, and current occupation that provided a deeper understanding of the phenomenon of decision-making. The participants were categorized into four different decision-making styles, based on how they responded to the decision-making dimension questions. These decision-making styles have been listed as avoidant, designer/auditor, flexible, and fluid decision-makers. Of the total participants, 150 were classified as fluid, 146 were classified as flexible, 31 were found to be avoidant, and 29 had a designer/auditor decision-making style. We tested whether personal socio-demographic characteristics such as age, educational attainment, gender, geography, and occupational sector are effective in the construction of decision-making styles. We found that except the gender dimension, these factors are not positively correlated with any decision-making style. Females showed a greater propensity towards having an avoidant decision-making style and less likely to be considered as having a fluent decision-making style. This phenomenon warranted further investigation and we also tested whether there are also substantial differences in decision-making dimensions for women in relation to men. We found that, in terms of emotion neutrality dimension, significant differences exist between female and male respondents; a fact more visible in the education sector.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
HUMAN AND ANIMAL RIGHTS
No animals/humans were used for studies that are basis of this research.
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or otherwise.
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