Index

Abstract

The present research paper aims to identify the level of creative leadership among university leaders in Riyadh, Saudi Arabia and its relationship to their thinking styles. It also reveals the differences between the level of creative leadership and thinking styles according to university type (public or private) and gender. Moreover, it adopted the analytical descriptive method. The sample comprised (60) university leaders. The field data was collected using the creative leadership scale and thinking styles scale. The results indicated a high level of creative leadership among educational university leaders in Riyadh. In terms of the thinking styles, the realist, pragmatist, idealistic, analyst, and synthesis were ranked first, second, third, fourth, and fifth, respectively. Moreover, there were statistically significant differences between the mean ranks of the participants on the flexibility domain according to university type (public or private) favoring educational leaders in public universities. There were no statistically significant differences among the other domains and total score of the creative leadership scale, as well as among the total score and domains of thinking styles scale according to university type (public or private) and gender.

Keywords: Analyst thinking style, Creative leadership, Idealistic thinking style, Pragmatist thinking style, Realist thinking style, Synthesis thinking style, University leaderships.

Received: 27 October 2020 / Revised: 25 February 2021 / Accepted: 29 March 2021/ Published: 16 April 2021

Contribution/ Originality

Creative leadership is the basis of creativity. No creative environment can be found under a leadership that does not believe in development. Moreover, thinking styles build personality and develop confronting life situations. Therefore, the present study can promote higher education institutions as creative leadership among university leaders enhances thinking styles.


1. INTRODUCTION

The success of a leader lies in thinking styles and applied practices. Creative leadership is always changing to continue in dynamic environments and to demonstrate the ability to compete and excel (Imran, 2014). According to Qaraeen (2000) having ambitious, creative, and effective leaders is important to improve education in universities. Authors have various opinions concerning the characteristics of creative leadership. For example, Al-Serafy (2003) reported that a creative leader should demonstrate

It is a common belief that leadership may meet challenges, problems, or circumstances. However, the leader's good management and commitment help overcome these obstacles. When creativity becomes a new factor, institutions will change their organizational structure (Eid, 2015). Several studies have examined creative leadership, such as Al-salami (2012) that identified the relationship between creative leadership and organizational climate in public intermediate schools in Jeddah from the perspective of principals and teachers. The results indicated that the characteristics of creative leadership are moderately practiced. Al-Ghamdi (2012) examined the degrees of practice and training needs of creative leadership from the perspective of academic leaders at Albaha University. The results illustrated the low degree of practicing creative leadership’s domains. The highest practicing domains were fluency, flexibility, originality, and problem sensitivity. There were statistically significant differences between the mean responses of the participants in the degree of the practice of creative leadership favoring heads of departments. However, there were no statistically significant differences according to gender and college type.

Eid (2015) reported a high level of challenges that prevent achieving creative leadership in Saudi universities, the very high degree of the characteristics of the appropriate work environment for creative leadership, and the high need for creative leadership skills. The study demonstrated statistically significant differences in the mean scores of the participants according to gender, favoring men. Moreover, women needed higher creative leadership skills. Yossef and Rakha (2017) identified the level of personal and administrative skills among university leaders at Najran University. The results highlighted a high level of interpersonal and administrative skills and a moderate level of leadership creativity among university leaders. Moreover, they revealed a positive correlation between the personal and administrative variables and the level of leadership creativity.

Al Hussein (2018) identified the degree of practicing creative leadership in four domains (i.e., originality, flexibility, problem sensitivity, and fluency) among the principals of primary schools and the obstacles that prevent practicing creative leadership from the teachers' point of view in Hawtat Bani Tamim, Saudi Arabia. The findings reported a high practice of creative leadership concerning originality, flexibility, and fluency and a moderate degree of sensitivity to problems, as well as personal and administrative obstacles. Al-Owain (2019) examined the reality of practicing creative leadership among leaders of the general administration of education in Qassim from the perspective of educational supervisors in the (problems, thinking, and decision) domains. All domains were moderate.

Thinking styles have received the attention of psychologists and authors to study and develop theories, and prepare appropriate measures (Al-Shammari, 2010). Sternberg (2002) assumed the relationship between thinking styles and leadership behavior, indicating that understanding leaders’ thinking styles contributes to understanding their administrative style and thus are developed the theory of thinking styles. Several perceptions and theories have tried to understand the preferred thinking styles, such as the theory of mental self-government (Sternberg, 1988) that was later known as thinking styles and the theory of Harrison and Bramson (1982) indicating five styles of thinking (Epstein, Pacini, Denes-Raj, & Heier, 1996). Harrison and Bramson (2002) categorized the styles of thinking as synthesist, idealistic, pragmatist, analyst, and realist. Each person has a certain degree of these styles of thinking (Jones, 2006). Sternberg (2002) argues that several factors affect the favorite thinking styles, such as heredity, social gains, feedback, training, parental treatment styles, age, and educational environment. An important variable in the development of thinking styles is gender. When we raise children, we prepare them socially based on our perception of masculinity and femininity, not reality (Altaeb, 2006).

Creative leadership requires intellectual skills demonstrated by the leader's ability to think logically, judge things properly, predict, and make the right decisions (AlSalem & Saleh, 2000). Borlandoe (2005) indicated that there are various preferences of thinking styles according to senior positions, heads of department, and administrative staff. The idealistic and realist thinking styles were ranked the highest. Sofo (2005) aimed to identify the preferred thinking styles among contemporary Chinese leaders and compared the thinking styles of educational and non-educational leaders. The findings showed the strong preferences of Chinese leaders for executive (realist) thinking styles, independent thinking style, and the style of exploration and analysis. Al-Atoum (2007) examined the prevailing thinking styles among school principals in Irbid, Jordan using the modified Sternberg and Wagner thinking styles scale for the Jordanian environment. The results indicated that the most common thinking styles were the executive, the liberal, and the hierarchically ranked ones respectively. No gender-based differences were found.

Subuh (2015) identified thinking styles and their relationship to decision-making among primary school teachers using the modified scale of thinking styles (Harrison & Bramson, 1982) for the Egyptian environment and the decision-making scale. The results indicated a statistically significant positive correlation between the scores of the participants on the scales of thinking styles and decision-making. There was a statistically significant impact of the pragmatist, analyst, and idealistic thinking styles on decision-making among teachers. Azeez (2015) highlighted that the preferable thinking styles among secondary school counselors are the synthesist, idealistic, pragmatist, analyst, and realist, respectively. There were no statistically significant differences according to gender. Moreover, Margret and Lavanya (2017) examined the relationship between hemispheric dominance, thinking style preferences, and emotional intelligence among college students using three scales: the alert scale of cognitive style (Crane, 1989) the thinking styles scale (Harrison & Bramson, 1977) and the emotional intelligence scale (Schutte et al., 1998). The results indicated a significant positive relationship between hemispheric dominance and emotional intelligence, as well as emotional intelligence preferences and the (synthesist, idealistic, and analyst) thinking styles.

Chen (2018) identified the relationship between thinking styles and academic achievement based on the internet. The findings indicated that thinking styles showed remarkably positive effects on learning acquisition on academic achievement. Paik, Lee, and Pak (2019) examined the relationship between moral philosophy, thinking style, and administrative ethical decision-making. The results revealed that Korean managers become more dependent on utilitarianism in making ethical decisions. Al-Shammari (2010) examined the relationship between thinking styles and leadership skills among high and moderate secondary school achievers in Kuwait using the Sternberg model of thinking styles (Sternberg, 2002). The results indicated that there were statistically significant differences in the correlation coefficient between thinking styles and leadership skills, favoring high achievers. Although several studies tackled thinking styles, few of them addressed leadership (Minbashian, Birney, & Bowman, 2019).

2. STATEMENT OF THE PROBLEM

Providing ambitious, effective, and creative leaders who are able to use appropriate thinking styles is important for improving education (Twiqat, 2007).Leadership is thus important for universities as it leads managers and members of the educational system to enhance creativity with excellence (Makahleh, 2014). The influence of scientific and technological development on contemporary management thinking allows management thinking to identify new creative trends and developments (Abdul-Maksoud, 2006). Moreover, creative leadership directs the enormous and various energies of university management towards excellence, creativity, quality, and the global competition because creative administration, thinking level, and advanced planning are the basis for excellence (Khairallah, 2009). Donald (2000) found that higher education departments need creative administration. Feither (2002) suggests that universities to set priorities and should innovate and keep pace with developments and changes.

2.1. Objectives

The present research paper aims to identify the relationship between the level of creative leadership and the prevailing thinking styles among educational leaders. Hence, it sets forth following objectives:

2.2. Questions

2.3. Significance

2.3.1. Theoretical Significance

2.4. Practical Significance

2.5. Definition of Terms

Creative Leadership: Al-Fayoumi (2007) defines creative leadership as the potential of uncovering new facts or laws and producing a huge number of ideas. The authors define university educational leadership as "the leadership style that is possessed by educational leaders e.g., deans, vice-deans, heads of departments, and their deputies and who are characterized by problem sensitivity, fluency, originality, and flexibility. Thinking Styles: Sternberg (2002) indicates that it is the preferred individual style in handling situations. The authors adopted the concept of Harrison and Bramson (1982) as "the preferred individual style in processing information while solving problems".

3. LIMITATIONS

3.1. Subject Limitations

Spatial limitations: The study was applicable only in public and private universities in Riyadh.
Temporal limitations: Data collection tools were applied only at the end of the first semester of 2019-2020.

4. METHODOLOGY AND PROCEDURES

4.1. Method

The research paper utilized the analytical descriptive approach that focused on a phenomenon to diagnose, reveal its aspects, and identify the relationship between its elements (Al-Azzawi, 2008).

4.2. Population and Sampling

The population consisted of all the educational leaders at the public and private universities in Riyadh. A pilot study was carried on (35) leaders outside the main sample from Saudi universities to calculate the psychometric characteristics of the scales and verify their applicability. The sample was randomly selected based on a link created for this study and circulated to various Saudi universities including King Saud University, Imam Muhammad Ibn Saud Islamic University, Princess Nourah bint Abdulrahman University, Dar Al Uloom University, Arab East University, and Prince Sultan University. The link was repeatedly circulated via social media. After (75) days, the responses were limited, and hence the sample size comprised (60) leaders (Table 1). It is worth mentioning that one of the difficulties encountered by the authors was the low response of the population to the scales probably because of their busy schedule.  

Table-1. The distribution of the sample according to gender.

Gender
No.
Percentage
Male
20
33.3%
Female
40
67.7%
Total
60
100%

Table 1 shows that two-thirds of the sample (67.7%) represent females, whereas one-third (33.3%) represent the males.

Table-2. The distribution of the sample according to university type (public-private).

University type
No.
Percentage
Public
49
81.7 %
Private
11
18.3%
Total
60
100 %

Table 2 indicates that (49) participants (81.7%) work at public universities, whereas (11) participants (18.3%) belong to private universities.

4.3. Tools

4.3.1.  First: The creative leadership scale

The authors developed the creative leadership scale that comprised (51) items distributed to four main domains: Problem sensitivity (11 items), fluency (9 items), originality (16 items), and flexibility (15 items).

The scale was presented to (7) faculty members who approved most of the items. The items they did not approve were modified in accordance with their comments.

The authors estimated the validity of the scale after applying it to 35 educational leaders in Riyadh universities from the pilot sample by calculating the Pearson correlation coefficient between the score of each item and the total score of the domain, as presented in Table 3.

Table-3. The correlation coefficient between the score of each item and the total score of the domain of the creative leadership scale (N = 35).

Problem sensitivity
Fluency
Originality
Flexibility
No. of items
Correlation coefficient
No. of items
Correlation coefficient
No. of items
Correlation coefficient
No. of items
Correlation coefficient
1
0.705**
1
0.371*
1
0.709**
1
0.652**
2
0.595**
2
0.780**
2
0.738**
2
0.758**
3
0.573**
3
0.817**
3
0.740**
3
0.514**
4
0.741**
4
0.600**
4
0.553**
4
0.726**
5
0.728**
5
0.667**
5
0.778**
5
0.748**
6
0.617**
6
0.425*
6
0.708**
6
0.823**
7
0.650**
7
0.533**
7
0.711**
7
0.720**
8
0.682**
8
0.336*
8
0.801**
8
0.711**
9
0.657**
9
0.770**
9
0.861**
9
0.781**
10
0.648**
10
0.594**
10
0.713**
10
0.797**
11
0.694**
11
0.659**
11
0.701**
12
0.545**
12
0.567**
13
0.670**
13
0.787**
14
0.584**
14
0.798**
15
0.390*
16
0.778**

Note: *Significant at the level of (0.05)    **Significant at the level of (0.01).

Table 3 illustrates that the correlation coefficient is statistically significant at the level of (0.05). The authors calculated the correlation coefficient between the score of each domain and the total score of the scale, as shown in Table 4.

Table-4. The correlation coefficient between the score of each domain and the total score of the scale (N= 35).

Domain
Total
Problem sensitivity
0.883**
Fluency
0.703**
Originality
0.929**
Flexibility
0.864**

Table 4 indicates that the correlation coefficient is statistically significant at the level of (0.01). Thus, the scale has a high degree of validity.

The reliability was estimated by calculating Cronbach's alpha for each domain of the scale and the split-half methods (Spearman-Brown and Guttman), as shown in Table 5.

Table-5. The reliability of the creative leadership scale (N=35).

Domain
No. of items
Reliability
Cronbach’s Alpha
Split-half
Spearman-Brown
Guttman
Problem sensitivity
11
0.866
0.789
0.782
Fluency
10
0.796
0.705
0.693
Originality
16
0.920
0.871
0.869
Flexibility
14
0.925
0.876
0.876
Total
51
0.957
0.903
0.902

Table 5 shows that the values of the reliability coefficient using Cronbach’s alpha ranged from (0.796) to (0.957), whereas the split-half methods (Spearman-Brown and Guttman) ranged from (0.693) to (0.903), indicating the high degree of reliability of the scale.

4.3.2  Second: The thinking styles scale (Harrison & Bramson, 1982)

The thinking styles scale was developed by Harrison and Bramson (1982) including the (synthesist, idealistic, pragmatist, analyst, and realist) thinking styles. It comprised (90) items distributed to (18) daily situations with five possible responses for each situation. Thus, (5) represents the most applicable behavior, and (1) is the least applicable.

The validity was estimated by calculating the correlation coefficient between the scores on each of the five thinking styles. The results concluded a negative correlation between the synthesist style and both the idealistic and pragmatist styles (Habib, 1995). Moreover, a low correlation was found between thinking styles limited to (0.04-0.45). Elsayed (2003) had concluded a relative independence between these five styles. The correlation coefficient is significant at the level of (0.001) (ElSokkary & Elhageen, 2006). Habib (1995) found that the reliability coefficient for synthesist thinking, idealistic thinking, pragmatist thinking, analyst thinking, and realist thinking is 0.83, 0.78, 0.81, 0.86, 0.80, respectively. Elsayed (2003) utilized Cronbach’s alpha to calculate the reliability that scored 0.79 for synthesist thinking, 0.77 for idealistic thinking, 0.76 for pragmatist thinking, 0.74 for analyst thinking, and 0.65 for realist thinking. ElSokkary and Elhageen (2006) found the reliability score 0.81 for synthesist thinking, 0.83 for idealistic thinking, 0.80 for pragmatist thinking, 0.78 for analyst thinking, and 0.84 for realist thinking.

The validity was estimated after applying it to 35 educational university leaders in Riyadh using internal consistency, by calculating the Pearson correlation coefficient between the score of each item and the total score of the domain.

Table-6. The correlation coefficient between the score of each item and the total score of the domain (N = 35).

Synthesist thinking style
Idealistic thinking style
Pragmatist thinking style
Analyst thinking style
Realist thinking style
No. of items
Correlation coefficient
No. of items
Correlation coefficient
No. of items
Correlation coefficient
No.  of items
Correlation coefficient
No. of items
Correlation coefficient
1A
0.512**
2A
0.399*
3A
0.339*
4A
0.440**
5A
0.500**
2B
0.486**
1B
0.444**
4B
0.451**
3B
0.502**
5B
0.389*
5C
0.454**
4C
0.457**
1C
0.462**
3C
0.464**
2C
0.494**
4D
0.395*
3D
0.387*
5D
0.483**
1D
0.391*
2D
0.395*
3E
0.476**
1E
0.391*
2E
0.499**
5E
0.399*
4E
0.382*
2F
0.487**
3F
0.484**
4F
0.372*
5F
0.461**
1F
0.455**
1G
0.462**
2G
0.492**
3G
0.389*
4G
0.375*
5G
0.460**
2H
0.404*
1H
0.490**
4H
0.524**
3H
0.364*
5H
0.449**
5I
0.388*
4I
0.372*
1I
0.455**
3I
0.449**
2I
0.493**
4J
0.538**
3J
0.446**
5J
0.398*
1J
0.385*
2J
0.366*
3K
0.345*
1K
0.471**
2K
0.376*
5K
0.454**
4K
0.487**
2L
0.467**
3L
0.462**
4L
0.489**
5L
0.467**
1L
0.488**
1M
0.402*
2M
0.398*
3M
0.495**
4M
0.356*
5M
0.364*
2N
0.607**
1N
0.385*
4N
0.369*
3N
0.441**
5N
0.471**
5O
0.531**
4O
0.449**
1O
0.356*
3O
0.360*
2O
0.492**
4P
0.479**
3P
0.489**
5P
0.467**
1P
0.489**
2P
0.495**
3Q
0.486**
1Q
0.468**
2Q
0.382*
5Q
0.395*
4Q
0.512**
2R
0.395*
3R
0.385*
4R
0.361*
5R
0.442**
1R
0.517**

Note: *Significant at the level of (0.05)      **Significant at the level of (0.01).

Table 6 indicates that the correlation coefficient between the score of each item and the total score of the domain is statistically significant at the level of (0.05).

The reliability was estimated by calculating the reliability coefficient of Cronbach's alpha for each domain of the scale and split-half methods (Spearman-Brown and Guttman), as shown in Table 7.

Table-7. The reliability of the thinking styles scale (N = 35).

Domain
No.  of items
Reliability
Cronbach’s Alpha
Split-half
Spearman-Brown
Guttman
Synthesist thinking style
18
0.617
0.628
0.625
Idealistic thinking style
18
0.625
0.648
0.647
Pragmatist thinking style
18
0.572
0.584
0.582
Analyst thinking style
18
0.615
0.621
0.620
Realist thinking style
18
0.612
0.625
0.622

Table 7 shows that the values of the reliability coefficient using Cronbach’s alpha ranged from (0.572) to (0.625), whereas the reliability values using split-half methods (Spearman-Brown and Guttman) ranged from (0.582) to (0.648). These values are accepted, suggesting the scale's reliability.

5. RESULTS

5.1. Results of the First Question

To answer this question, the authors calculated the differences in the mean scores of the participants on the creative leadership scale and the hypothetical means of the domains and the total score using One sample t-test, as shown in Table 8.

Table-8. The differences in the mean scores of the participants.

Domains
No.
Hypothetical means
Mean
Standard deviation
“T” value
Significance
Problem sensitivity
60
33
45.80
4.82
20.564
0.000
Fluency
60
30
40.67
4.67
17.702
0.000
Originality
60
48
65.55
8.27
16.447
0.000
Flexibility
60
42
59.88
7.24
19.122
0.000
Total
60
153
211.90
22.15
20.597
0.000

Table 8 shows statistically significant differences at the level of (0.01) in the mean scores of the participants on the creative leadership scale and the hypothetical means of the domains and the total score favoring the participants, suggesting the high level of creative leadership among educational university leaders in Riyadh. This result is consistent with Al Hussein (2018).  In contrast, it differs from Al-Ghamdi (2012); Al-Owain (2019) and Yossef and Rakha (2017). 

5.2. Results of the Second Question

To answer this question, the authors calculated the mean scores of the participants on each of the five styles measured by the scale and the standard deviation and then arranged them according to the higher mean and if the means are equal, then according to the standard deviation. Table 9 shows the results.

Table-9. Means and standard deviations of thinking styles.

Thinking style
No.
Mean
Standard deviation
Rank
Synthesist
60
50.97
11.56
5
Idealistic
60
53.75
10.36
3
Pragmatist
60
56.17
13.18
2
Analyst
60
52.78
12.70
4
Realist
60
56.33
13.33
1

Table 9 shows that the realist thinking style was ranked first, the pragmatist thinking style ranked second, the idealistic thinking style ranked third, the analyst thinking style ranked fourth, and the synthesist thinking style ranked fifth. This result indicates that the educational university leaders in Riyadh use all five thinking styles with close arithmetic means. While this result agreed with Sofo (2005) it differed from Borlandoe (2005).

5.3. Results of the Third Question

To answer this question, the authors calculated the Pearson correlation coefficient between the domains, the total score of the creative leadership scale, and the five thinking styles, as shown inTable 10.

Table-10. The Pearson correlation coefficient between the domains, the total score of the creative leadership scale, and the five thinking styles.

Creative leadership
                          Thinking style
Problem sensitivity
Fluency
Originality
Flexibility
Total
Synthesist
0.460**
0.385**
0.539**
0.415**
0.518**
Idealistic
-0.073-
-0.061-
0.083
0.196
0.066
Pragmatist
-0.401-**
-0.322-*
-0.557-**
-0.477-**
-0.519-**
Analyst
0.506**
0.431**
0.634**
0.560**
0.621**
Realist
-0.428-**
-0.378-**
-0.585-**
-0.574-**
-0.579-**

Table 10 illustrates a statistically significant positive relationship at the level of (0.01) or less between the domains of the creative leadership scale, its total score, and the (synthesist-analyst) thinking styles. Moreover, a statistically significant negative relationship at the level of (0.05) or less was found between the domains of the creative leadership scale, its total score, and the (pragmatist-realist) thinking styles. No statistically significant relationship was found between the domains of the creative leadership scale, its total score, and the idealistic thinking style. After reviewing the literature, no study linked creative leadership and thinking styles except for Al-Shammari (2010).

5.4. Results of the Fourth Question

To answer this question, the authors revealed the moderation of the subgroup’s distribution. The results of the Smirnov-Kolmogorov Test and the Shapiro-Wilk Test showed non-moderation in the distribution. Accordingly, the authors utilize the Mann-Whitney Test that gave the results shown in Table 11.

5.5. University Type

Table-11. The results of the Mann-Whitney Test for differences in the level of creative leadership.

Creative leadership
University type
No.
Means of ranks
Sum of ranks
“Z” value
Significance
Problem sensitivity
Public
49
32.14
1575.00
-1.544-
0.123
Private
11
23.18
255.00
Total
60
Fluency
Public
49
30.98
1518.00
-0.451-
0.652
Private
11
28.36
312.00
Total
60
Originality
Public
49
31.38
1537.50
-0.823-
0.411
Private
11
26.59
292.50
Total
60
Flexibility
Public
49
32.59
1597.00
-1.968-
0.049
Private
11
21.18
233.00
Total
60
Total
Public
49
31.99
1567.50
-1.395-
0.163
Private
11
23.86
262.50
Total
60

Table-12. The results of the Mann-Whitney Test for differences in the level of thinking styles.

Thinking style
University type
No.
Means of ranks
Sum of ranks
“Z” value
Significance
Synthesist
Public
49
30.87
1512.50
-0.360-
0.719
Private
11
28.86
317.50
Total
60
Idealistic
Public
49
30.65
1502.00
-0.152-
0.879
Private
11
29.82
328.00
Total
60
Pragmatist
Public
49
29.70
1455.50
-0.760-
0.447
Private
11
34.05
374.50
Total
60
Analyst
Public
49
31.57
1547.00
-1.031-
0.302
Private
11
25.73
283.00
Total
60
Realist
Public
49
29.64
1452.50
-0.818-
0.413
Private
11
34.32
377.50
Total
60

Table 11 indicates statistically significant differences at the level of (0.05) in the means of ranks of participants’ scores on the flexibility domain according to university type (public-private), favoring educational leaders at public universities. There were no statistically significant differences between the means of ranks of participants’ scores in the remaining domains of the creative leadership scale and its total score according to university type (public-private).

Table 12 indicates no statistically significant differences between the means of ranks of participants’ scores in all domains of the thinking styles scale according to university type (public-private).

5.6. Gender

Table-13. The results of the Mann-Whitney Test in creative leadership according to gender.

Creative leadership
Gender
No.
Means of ranks
Sum of ranks
“Z” value
Significance
Problem sensitivity
Male
20
29.78
595.50
-0.228-
0.819
Female
40
30.86
1234.50
Total
60
Fluency
Male
20
31.33
626.50
-0.260-
0.795
Female
40
30.09
1203.50
Total
60
Originality
Male
20
30.13
602.50
-0.118-
0.906
Female
40
30.69
1227.50
Total
60
Flexibility
Male
20
28.78
575.50
-0.544-
0.587
Female
40
31.36
1254.50
Total
60
Total
Male
20
28.98
579.50
-0.478-
0.632
Female
40
31.26
1250.50
Total
60

Table 13 illustrates no statistically significant differences between the means of ranks of the participants’ scores in all domains and the total score of the creative leadership scale according to gender. This finding agrees with the results of Al-Ghamdi (2012) and differs from the results of Eid (2015).

Table-14. The results of the Mann-Whitney test in thinking styles according to gender.

Thinking style
Gender
No.
Means of ranks
Sum of ranks
“Z” value
Significance
Synthesist
Male
20
27.13
542.50
-1.107-
0.268
Female
40
32.19
1287.50
Total
60
Idealistic
Male
20
24.78
495.50
-1.905-
0.057
Female
40
33.36
1334.50
Total
60
Pragmatist
Male
20
34.88
697.50
-1.400-
0.162
Female
40
28.31
1132.50
Total
60
Analyst
Male
20
27.10
542.00
-1.096-
0.273
Female
40
32.20
1288.00
Total
60
Realist
Male
20
35.15
703.00
-1.488-
0.137
Female
40
28.18
1127.00
Total
60

Table 14 indicates no statistically significant differences between the means of ranks of participant’s scores in the domains of the thinking styles scale according to gender. The differences in the idealistic thinking style almost reached the level of significance (0.05), favoring females.

This result is consistent with Al-Atoum (2007) that revealed no statistically significant differences in thinking styles according to gender and Borlandoe (2005) that showed that the idealistic thinking style is the most preferred among female leaders.

6. LIMITATIONS

The study suffers some difficulties, such as the weak response of the participants to the scales, making it difficult to generalize the results because of the relatively small sample size.

The study did not cover some variables that may affect in one way or another creative leadership and thinking styles, such as experience, personality, and institutional needs.

7. RECOMMENDATIONS

It is important to include creativity features for the criteria of screening and nominating educational leaders and to develop creative leadership and its characteristics in the preparation and qualification programs for educational leaders.

Further studies should include some variables that may affect creative leadership and thinking styles, such as experience, personality, and institutional needs. Moreover, leaders should be selected based on their thinking styles. Private universities should empower their leaders to practice flexibility to achieve creative leadership.

Funding: This research paper was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University, through the Research Funding Program (Grant No#RFP-1440-1).

Competing Interests: The authors declare that they have no competing interests.

Acknowledgement: Both authors contributed equally to the conception and design of the study.

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