Appendix A – My Working Definitions
Cultural Intelligence (CQ) was defined as being the set of skills to relate and work effectively in culturally diverse situations. It is the capability to cross boundaries, prosper in multiple cultures, and impact the bottom-line results.
Knowledge Dynamics (KD) refers to the characteristics of knowledge that transform, change, and evolve as a result of various processes and influences.
Multicultural Leadership (ML) was defined as the process of engaging and leading a workforce comprised of individuals from diverse cultural backgrounds.
Appendices for Qualitative Research
Appendix B – Screening Filtering Questions to Validate Interview Participation
Hello,
In order to test your possible fit for a 30–60 minutes pro-bono interview in a research project that will serve as building support for the thesis/book “Developing multicultural leadership based on knowledge dynamics and cultural intelligence” conducted by PhD candidate Dan Paiuc, from the Department of Management of the National University for Political Studies and Public Administration, Bucharest, Romania – please kindly answer with Yes (Y) or No (N) for the following two questions:
Do you actually manage multicultural teams? Y/N
Are you familiar with the notion of Cultural Intelligence (CQ) as per my working definition: CQ being the set of skills to relate and work effectively in culturally diverse situations? Y/N
Appendix C – Consent to Participate in Research Interviews
Dear Participant,
Thanks for agreeing to participate in the research project that will serve as a building base for the thesis/book “Developing multicultural leadership based on knowledge dynamics and cultural intelligence” conducted by PhD candidate Dan Paiuc, from the Department of Management of the National University for Political Studies and Public Administration, Bucharest, Romania.
With an expected duration of the interview of 30–60 minutes, please agree:
to voluntarily participate in the interview;
that all the interviews will be recorded, transcripted, and anonymized by Dan Paiuc;
all or parts of the anonymized interview may be used in the above thesis/book or related academic articles/conferences.
Appendix D – Interviews' Synthetic Results
Age of Interviewed Managers.
Gender of Interviewed Managers.
Highest Level of Education Completed by the Interviewed Managers.
Highest Level of Education Completed by the Interviewed Managers.
Continent-Based Geographical Distribution of Interviewed Managers.
Continent-Based Geographical Distribution of Interviewed Managers.
Main Company's Activity Sectors of Interviewed Managers.
Main Company's Activity Sectors of Interviewed Managers.
Main Sizes of the Companies of Interviewed Managers (Data in Euro).
Main Sizes of the Companies of Interviewed Managers (Data in Euro).
Main Sizes of the Companies of Interviewed Managers (Data in Number of Employees).
Main Sizes of the Companies of Interviewed Managers (Data in Number of Employees).
Hierarchical Position of the Interviewed Managers.
Hierarchical Position of the Interviewed Managers.
Working Years' Experience in Actual Company and in Total of the Interviewed Managers.
Working Years' Experience in Actual Company and in Total of the Interviewed Managers.
Number of Managed Nationalities of the Interviewed Managers.
Number of Managed Nationalities of the Interviewed Managers.
Number of Spoken Languages of the Interviewed Managers.
Number of Spoken Languages of the Interviewed Managers.
Number of Continents on Which the Interviewed Managers Worked.
Number of Continents on Which the Interviewed Managers Worked.
Number of Countries in Which the Interviewed Managers Worked.
Number of Countries in Which the Interviewed Managers Worked.
Appendix E − Sample of One Interview
One Sample Interview.
| Description of Variable | Variable | Coding Instructions |
|---|---|---|
| Respondent no. | 1 | |
| Name or pseudonym | Ahmed AbdelMawla | |
| Gender | Male (1) | Male = 1, Female = 2, Non-binary = 3 |
| Age | 45 years (3) | 18–25 = 1, 26–40 = 2, 41–60 = 3, >61 = 4 |
| Education | University graduate (2) | High school only = 1, University graduate = 2, Master graduate = 3, PhD graduate = 4 |
| Geography | Africa (3) | Europe = 1, Asia = 2, Africa = 3, North America = 4, South America = 5, Australia = 6. |
| Country | Egypt | |
| Company sector | Services (4) | Retail = 1; Production = 2; Trade = 3; Services = 4; Others = 5 |
| Company size (turnover) | >10M = x < 50M (5) | <0.5M. euro/year as turnover = 1, 0.5 >= x < 1M. euro/year = 2, 1 <= x < 5M. euro = 3, 5 >= x < 10M. euro = 4, >10M = x < 50M = 5, >=50 m euro = 6 |
| Company size (employees' number) | 1,001+ employees (6) | 1–10/11–50/51–100/101–500/501–1,000/1,001+ employees |
| Function | TOP management (1) | TOP management = 1/Middle Management = 2/Lower management = 3 |
| Years of experience within the company | 16 years (5) | 1–3 = 1/3–5 = 2/5–10 = 3/10–15 = 4/>16 = 5 |
| Years of experience in total | 21+ years (6) | 1–3 = 1/3–5 = 2/5–10 = 3/10–15 = 4/16–20 = 5/21+ = 6 |
| Number of nationalities managed | 11–15 managed nationalities (4) | 1–3 = 1/4–5 = 2/6–10 = 3/11–15 = 4/16–20 = 5/21–50 = 6/51–100 = 7/>100 = 8 |
| Number of spoken languages | 2 languages (2) | One = 1, Two = 2, Three = 3, more than 3 = 4 |
| Number of continents in which the subject worked | 2 continents: Asia, Africa (2) | One = 1, Two = 2, Three = 3, more than 3 = 4 |
| Number of countries in which the subject worked | 8 countries (4) | One = 1, Two = 2, Three = 3, more than 3 = 4 |
| CQ | Questions | Answers |
| 1. | How do you assess the cultural intelligence of your team members? | I used to work with the cultural intelligence scale developed by Yang, but, nowadays, I use a 360′ review (developed by Gallup) that helps me assess the cultural and emotional intelligence level of all my team members. Meaning that each employee in our company is assessed by matrix colleagues, direct managers, and subordinates. |
| 2. | How do you leverage your team members' cultural intelligence? | After assessing each team member's cultural and emotional intelligence level, I allocate them the tasks and roles based on their cultural agility, experience, and expertise. |
| 3. | Is there a relationship between the cultural intelligence of your team and your result as a multicultural manager? Please detail. | Yes, if one of the cultural skills is missing within my team – I am trying to develop it; otherwise, my results as a manager – leading 14 nationalities – will be affected and non-performant. |
| 4. | What is your biggest challenge when dealing with cultural intelligence? Why? | My biggest challenge is portrayed by the business etiquette differences between Arab culture and European culture. Leading a team composed mainly of Arabic country members and dealing with European customers – forced me to learn and develop specific European business tactics and approaches. One is the pricing construct, where Europeans prefer a less negotiated option – so my first proposal is close to my target price. |
| KD | Questions | Answers |
| 5. | Are your decisions based only on data and rational thinking? | Depending on the situation – my decisions are based on data (rational thinking) or experience. If a situation is urgent and there is no data or no time for getting the data, I rely on my experience and common sense to make the best decision. I cannot lose a contract because I need two days to get the exact numbers. |
| 6. | Do emotions play any role in your decisions? | Emotions do not play any role in my professional decisions. As mentioned before, I believe in data and experience. I am performance-driven, and this is what I am developing within my team. Emotions make you soft and make you lose the big picture and the professional goals. |
| 7. | Do you consider their cultural values when interacting with people from different cultures? I consider their cultural values | When interacting with business people from different cultures, I think that this will show my business partners that I respect their origins and cultures, and this will help the professional partnership between our companies. |
| 8. | Do you consider that it is useful to have a proper balance between rational thinking, emotions, and cultural values when making decisions? | Yes, I really do, but mostly between rational thinking and cultural values. I do not think that emotions are to be involved in the business. Otherwise, the proper balance between rational thinking and cultural values smooths the decision-making process and increases the overall productivity of the teamwork. |
| ML | Questions | Answers |
| 9. | What is your leadership style with a multicultural team? Why? | My leadership style is bureaucratic and transactional, and all my employees are strictly advised to follow the established rules. This will ensure predictability and uniformity, and these are important characteristics when dealing with multicultural teams. |
| 10. | How do you create trust in your multicultural team? | I create and develop trust within the team by coaching each member. I am also insisting on the company values – as a trust generator. |
| 11. | When assigning tasks, do you consider each team member's cultural background? | I always do because every different cultural team member mostly has a different skill set that I always want to leverage to optimize results. |
Appendix F – The Interviews Codebook and Codes
The Interview Codebook.
| Theme | Sub-Theme | Categories | Descriptive Codes |
|---|---|---|---|
| Cultural intelligence | Downplays cultural differences for team culture | * Does not assess cultural intelligence * does not leverage on team members' cultural intelligence * downplays individual cultural intelligence * focusing on assigning tasks to the best hands not based on cultural intelligence * does not deal with cultural intelligence because everyone has common understanding of tasks * relationship between cultural intelligence and results is low * results is driven by skills developed and transmitted by the manager to a team member not cultural intelligence * there is no relationship between cultural intelligence and result * unsure of the relationship between cultural intelligence and results as a manager | |
| Emotional cultural intelligence | Assessing cultural intelligence through emotional intelligence metrics | * Assesses acceptance and adaptability for cultural intelligence * assesses cultural intelligence by reviewing their work in light of applied cultural intelligence “assesses cultural intelligence of team members by analyzing clients' feedback on team members' actions and interactions” * assesses cultural intelligence of team members by having one to one coaching and evaluation sessions every quarter * assesses cultural intelligence through standardized meetings * assesses cultural intelligence using 360 review * assesses team members based on experience * assesses team members skill and experience through communication * assesses the cultural intelligence of team members through a report/questionnaire on cultural and emotional intelligence | |
| Leveraging emotional cultural intelligence for company results | * Leverages on cultural intelligence by assigning team members to task based on their identified cultural expertise * leverage on team members' cultural intelligence through detailed communications * leverage on team members' cultural intelligence by using verbal and nonverbal behavior in cross-cultural encounters * leverages on team members' cultural intelligence through social events * leveraging cultural skill for better result * leveraging emotional cultural intelligence for company result * partner with team members to get the best result | ||
| View emotional intelligence issues as challenges | * The biggest challenge is accepting other opinions * biggest challenge is getting different people to work for a common goal * providing the right feedback based on understanding Canadian feelings * team members having a different attitude to work is a challenge * the biggest challenge is managing diversity * the level of conscious cultural awareness during interactions is a major challenge | ||
| Rational cultural intelligence | Assessing rational cultural intelligence | * Assessing cultural intelligence through knowledge of other cultures * assessing cultural intelligence through staff's prior experience and performance on tasks | |
| Leveraging rational cultural intelligence for results | *Assigning tasks based on knowledge and experience of culture * leveraging rational cultural intelligence for better results as multicultural manager * | ||
| Views rational cultural intelligence issues as challenges | * generalized beliefs about groups are the biggest challenge when dealing with cultural intelligence * getting team members to be knowledgeable about Canadian practices is a challenge * giving feedback is a challenge because it has the role of driving the adaptation of individual culture to the company's culture “lack of knowledge of different cultures is a challenge when dealing with cultural intelligence” * language is a barrier when dealing with cultural intelligence * managing diversity is a problem because different people understand same task differently | ||
| Spiritual cultural intelligence | Leveraging spiritual cultural intelligence for result | * Leverages on team members' cultural intelligence through a monitored ambience | |
| View spiritual cultural intelligence issues as challenges | * The biggest challenge in dealing with cultural intelligence is how not to hurt any personal beliefs * the biggest challenge is business etiquette difference * cultural self-awareness * the biggest challenge is not disrespecting the personal belief of others as it might affect productivity | ||
| Knowledge dynamics | Combining rational, emotional and cultural values for decision-making | * balancing rational thinking, emotions, and cultural values is a key success factor * considers the balancing of rational thinking, emotions, and cultural values useful in decision-making | |
| Emotional knowledge | * Emotion plays a role in decision-making | ||
| Rational knowledge | * business should be prioritized when making decisions * data and rational thinking are the main drivers of decision-making | ||
| Spiritual knowledge | * Authentic decision-making * making decisions based on common sense * understanding the values of others is needed for decision-making when interacting with business partners and team members | ||
| Multicultural leadership | Conceptual skill | * Identifying practices that lead to productivity * leveraging cultural background for company success * strategic planning | |
| Interpersonal skill | * Building an environment with a sense of belonging * coaching and empowerment * collaboration * communication * empathy * friendliness and openness | ||
| Multicultural skill (values) | * Equal treatment * finding common ground * respecting cultural differences | ||
| Leaders focus on uniformity and task completion. | * assign tasks based on skillset and not cultural background * focus on uniformity rather than understanding the cultural background |
Interview's Codes.
| Themes | Sub-Themes | Files |
|---|---|---|
| Cultural Intelligence | ||
| Emotional cultural intelligence | 14 | |
| Assessing cultural intelligence through emotional intelligence metrics | 11 | |
| Leveraging emotional cultural intelligence for company results | 5 | |
| View emotional intelligence issues as challenges | 7 | |
| Rational cultural intelligence | 11 | |
| Assessing cultural intelligence through rational intelligence metrics | 6 | |
| Leveraging rational cultural intelligence for results | 9 | |
| Views rational cultural intelligence issues as cultural intelligence challenges | 6 | |
| Spiritual cultural intelligence | 4 | |
| Leverages on team members' cultural intelligence through a monitored ambience | 1 | |
| View spiritual cultural intelligence issues as challenges | 4 | |
| Downplays cultural differences for team culture | 4 | |
| Knowledge Dynamics | ||
| Emotional knowledge | 6 | |
| Emotion plays a role in decision-making | 4 | |
| Emotions play a minimal role in the decision-making process | 6 | |
| Rational knowledge | 14 | |
| Business should be prioritized when making decisions | 4 | |
| Does not consider cultural values as the focus when interacting with people of different cultures | 2 | |
| Emotions play no role in decision-making | 5 | |
| Data and rational thinking are the main drivers in decision-making | 13 | |
| Spiritual knowledge | 11 | |
| Authentic decision-making | 1 | |
| Making decisions based on common sense | 2 | |
| Understanding the values of others is needed for decision-making when interacting with business partners and team members | 10 | |
| Combining rational, emotional and cultural values for decision-making | 13 | |
| Balancing rational thinking, emotions, and cultural values is a key success factor | 3 | |
| Considers the balancing of rational thinking, emotions, and cultural values useful in decision-making | 13 | |
| Multicultural Leadership | ||
| Conceptual skill | 9 | |
| Identifying practices that lead to productivity | 4 | |
| Leveraging cultural background for company success | 8 | |
| Strategic planning | 3 | |
| Interpersonal skill | 13 | |
| Coaching and empowering team members | 7 | |
| Collaboration | 3 | |
| Communication | 5 | |
| Building an environment with a sense of belonging | 2 | |
| Empathy and kindness | 3 | |
| Friendliness and openness | 4 | |
| Multicultural skill (Values) | 6 | |
| Equal treatment | 3 | |
| Finding common ground | ||
| Respecting cultural differences | 3 | |
| Leader focuses on uniformity and task completion | 7 | |
| Assign tasks based on skillset and not cultural background | 6 | |
| Focus on uniformity rather than understanding the cultural background | 2 | |
Appendix G – Demography and Number of Words Transcribed
Gender and Age Classification – Interviews.
| Pseudonym | Number of Words Transcribed | Gender | Age Classification |
|---|---|---|---|
| Ahmed AbdelMawla | 616 | Male | 41–60 |
| Dean Watson | 546 | Male | 41–60 |
| Dusty Wagoner | 408 | Male | 41–60 |
| Khosrow Salour | 545 | Male | 41–60 |
| Kristian Skovrider | 380 | Male | 60+ |
| Pedro Lemos | 460 | Male | 26–40 |
| Rin Senan | 465 | Male | 26–40 |
| Tinatin | 413 | Female | 26–40 |
| Umair Arshad | 372 | Male | 26–40 |
| Yousef Siam | 401 | Male | 41–60 |
| Zeinab Mekawy | 486 | Female | 26–40 |
| Annas Siddiqui | 798 | Male | 26–40 |
| Rana El Maghraby | 362 | Female | 26–40 |
| Saim Ali | 537 | Male | 26–40 |
| Vishal Kumar | 263 | Male | 26–40 |
Education, Geography, Country Classification – Interviews.
| Pseudonym | Number of Words Transcribed | Education | Geography | Country |
|---|---|---|---|---|
| Ahmed AbdelMawla | 616 | University graduate | Africa | Egypt |
| Dean Watson | 546 | High school | Europe | England |
| Dusty Wagoner | 408 | University graduate | North America | United States of America |
| Khosrow Salour | 545 | University graduate | Asia | Iran |
| Kristian Skovrider | 380 | Master graduate | Europe | Denmark |
| Pedro Lemos | 460 | Master graduate | North America | Canada |
| Rin Senan | 465 | Master graduate | North America | Canada |
| Tinatin | 413 | University graduate | Europe | Georgia |
| Umair Arshad | 372 | Master graduate | Europe | United Kingdom |
| Yousef Siam | 401 | University graduate | Asia | Saudi Arabia |
| Zeinab Mekawy | 486 | Master graduate | Africa | Egypt |
| Annas Siddiqui | 798 | University graduate | Europe | England |
| Rana El Maghraby | 362 | University graduate | Africa | Egypt |
| Saim Ali | 537 | Master graduate | Europe | England, UK |
| Vishal Kumar | 263 | Master graduate | North America | Canada |
Function, Years of Experience Within the Company, Years of Experience in Total Classification – Interviews.
| Pseudonym | Number of Words Transcribed | Function | Years of Experience Within the Company | Years of Experience in Total |
|---|---|---|---|---|
| Ahmed AbdelMawla | 616 | TOP management | 16 years | 21+ years |
| Dean Watson | 546 | TOP management | 5–10 years | 21+ years |
| Dusty Wagoner | 408 | TOP management | >16 | 21+ years |
| Khosrow Salour | 545 | TOP management | >16 | 21+ years |
| Kristian Skovrider | 380 | TOP management | 14 years | 21+ years |
| Pedro Lemos | 460 | Middle management | 10–15 years | 10–15 years |
| Rin Senan | 465 | Middle management | 1–3 years | 5–10 years |
| Tinatin | 413 | TOP management | 2 years | 5–10 years |
| Umair Arshad | 372 | Middle management | 3 years | 5–10 years |
| Yousef Siam | 401 | TOP management | 3–5 years | 21+ years |
| Zeinab Mekawy | 486 | Middle management | 1–3 years | 3–5 years |
| Annas Siddiqui | 798 | Middle management | 1–3 years | 5–10 years |
| Rana El Maghraby | 362 | TOP management | 5–10 years | 10–15 years |
| Saim Ali | 537 | Middle management | 1–3 years | 5–10 years |
| Vishal Kumar | 263 | Middle management | 1–3 years | 10–15 years |
Company Sector, Company Size (Turnover, Employee's Number) Classification – Interviews.
| Pseudonym | Number of Words Transcribed | Company Sector | Company Size (Turnover) | Company Size (Employees' Number) |
|---|---|---|---|---|
| Ahmed AbdelMawla | 616 | Services | >10M = x < 50M | 1,001+ employees |
| Dean Watson | 546 | Other | 0.5>=x < 1 | 11–50 employees |
| Dusty Wagoner | 408 | Services | 5>=x < 10M | 51–100 employees |
| Khosrow Salour | 545 | Services | <0.5M | 1–10 employees |
| Kristian Skovrider | 380 | Trade | 1<=x < 5M | 1–10 employees |
| Pedro Lemos | 460 | Services | >=50 m | 1,001+ employees |
| Rin Senan | 465 | Services | >=50 m | 1,001+ employees |
| Tinatin | 413 | Services | 1<=x < 5M | 101–500 employees |
| Umair Arshad | 372 | Services | >=50 m | 1,001+ employees |
| Yousef Siam | 401 | Retail | 0.5>=x < 1 | 11–50 employees |
| Zeinab Mekawy | 486 | Services | 5>=x < 10M | 101–500 employees |
| Annas Siddiqui | 798 | Services | 1<=x < 5M | 1,001+ employees |
| Rana El Maghraby | 362 | Services | 0.5>=x < 1 | 11–50 employees |
| Saim Ali | 537 | Trade | 20 million | 11–50 employees |
| Vishal Kumar | 263 | Services | >=50 m | 1,001+ employees |
Number of Words Transcribed, Number of Nationalities Managed, Number of Spoken Languages, Number of Countries in Which Subject Worked – Interviews.
| Pseudonym | Number of Words Transcribed | Number of Nationalities Managed | Number of Spoken Languages | Number of Continents in Which the Subject Worked | Number of Countries in Which the Subject Worked |
|---|---|---|---|---|---|
| Ahmed AbdelMawla | 616 | 11–15 nationalities | 2 languages | 2 continents | 8 countries |
| Dean Watson | 546 | 1–3 nationalities | 1 language | 1 continent | 1 country |
| Dusty Wagoner | 408 | 1–3 nationalities | 1 language | 1 continent | 1 country |
| Khosrow Salour | 545 | 6–10 nationalities | 3 languages | 3 continents | 3 countries |
| Kristian Skovrider | 380 | 6–10 nationalities | 3 languages | 2 continents | 3 countries |
| Pedro Lemos | 460 | 16–20 nationalities | 2 languages | 3 continents | More than 3 countries |
| Rin Senan | 465 | 11–15 nationalities | 2 languages | 2 continents | 2 countries |
| Tinatin | 413 | 6–10 nationalities | 5 languages | 2 continents | 2 countries |
| Umair Arshad | 372 | 4 nationalities | 2 languages | 2 continents | 2 countries |
| Yousef Siam | 401 | 4–5 nationalities | 2 languages | 2 continents | 2 countries |
| Zeinab Mekawy | 486 | 1–3 nationalities | 2 languages | 2 continents | 2 countries |
| Annas Siddiqui | 798 | 11–15 nationalities | 2 languages | 2 continents | 2 countries |
| Rana El Maghraby | 362 | 1–3 nationalities | 3 languages | 1 continent | 1 country |
| Saim Ali | 537 | 6–10 nationalities | 5 languages | 2 continents | More than 3 countries |
| Vishal Kumar | 263 | 6–10 nationalities | More than 3 languages | 1 continent | 3 countries |
Appendix H – Transcribed Words and Participants per Variable
Gender Classification – Transcribed Words per Participant for Interview Section.
| No. | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Gender: Male | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Dean Watson | 546 | 1,162 |
| 3 | Dusty Wagoner | 408 | 1,570 |
| 4 | Khosrow Salour | 545 | 2,115 |
| 5 | Kristian Skovrider | 380 | 2,495 |
| 6 | Pedro Lemos | 460 | 2,955 |
| 7 | Rin Senan | 465 | 3,420 |
| 8 | Umair Arshad | 372 | 3,792 |
| 9 | Yousef Siam | 401 | 4,193 |
| 10 | Annas Siddiqui | 798 | 4,991 |
| 11 | Saim Ali | 537 | 5,528 |
| 12 | Vishal Kumar | 263 | 5,791 |
| Gender: Female | |||
| 13 | Tinatin | 413 | 6,204 |
| 14 | Zeinab Mekawy | 486 | 6,690 |
| 15 | Rana El Maghraby | 362 | 7,052 |
Age Classification – Transcribed Words per Participant for Interview Section.
| No. | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Age classification 60+ years | |||
| 1 | Kristian Skovrider | 380 | 2,896 |
| Age classification 41–60 years | |||
| 2 | Ahmed AbdelMawla | 616 | 616 |
| 3 | Dean Watson | 546 | 1,162 |
| 4 | Dusty Wagoner | 408 | 1,570 |
| 5 | Khosrow Salour | 545 | 2,115 |
| 6 | Yousef Siam | 401 | 2,516 |
| Age classification 26–40 years | |||
| 7 | Pedro Lemos | 460 | 3,356 |
| 8 | Rin Senan | 465 | 3,821 |
| 9 | Tinatin | 413 | 4,234 |
| 10 | Umair Arshad | 372 | 4,606 |
| 11 | Zeinab Mekawy | 486 | 5,092 |
| 12 | Annas Siddiqui | 798 | 5,890 |
| 13 | Rana El Maghraby | 362 | 6,252 |
| 14 | Saim Ali | 537 | 6,789 |
| 15 | Vishal Kumar | 263 | 7,052 |
Education Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Education: High School | |||
| 1 | Dean Watson | 546 | 546 |
| Education: University Graduate | |||
| 2 | Ahmed AbdelMawla | 616 | 1,162 |
| 3 | Dusty Wagoner | 408 | 1,150 |
| 4 | Khosrow Salour | 545 | 2,115 |
| 5 | Tinatin | 413 | 2,528 |
| 6 | Yousef Siam | 401 | 2,929 |
| 7 | Annas Siddiqui | 798 | 3,727 |
| 8 | Rana El Maghraby | 362 | 4,089 |
| Education: Master Graduate | |||
| 9 | Kristian Skovrider | 380 | 4,469 |
| 10 | Pedro Lemos | 460 | 4,929 |
| 11 | Rin Senan | 465 | 5,394 |
| 12 | Umair Arshad | 372 | 5,766 |
| 13 | Zeinab Mekawy | 486 | 6,252 |
| 14 | Saim Ali | 537 | 6,789 |
| 15 | Vishal Kumar | 263 | 7,052 |
Geography Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| Geography | |||
| Africa | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Zeinab Mekawy | 486 | 1,102 |
| 3 | Rana El Maghraby | 362 | 1,464 |
| Geography | |||
| Europe | |||
| 4 | Dean Watson | 546 | 2,010 |
| 5 | Kristian Skovrider | 380 | 2,390 |
| 6 | Tinatin | 413 | 2,809 |
| 7 | Umair Arshad | 372 | 3,175 |
| 8 | Annas Siddiqui | 798 | 3,973 |
| 9 | Saim Ali | 537 | 4,510 |
| Geography | |||
| North America | |||
| 10 | Dusty Wagoner | 408 | 4,918 |
| 11 | Pedro Lemos | 460 | 5,378 |
| 12 | Rin Senan | 465 | 5,843 |
| 13 | Vishal Kumar | 263 | 6,106 |
| Geography | |||
| Asia | |||
| 14 | Khosrow Salour | 545 | 6,651 |
| 15 | Yousef Siam | 401 | 7,052 |
Country Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Country: Egypt | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Zeinab Mekawy | 486 | 1,102 |
| 3 | Rana El Maghraby | 362 | 1,464 |
| Country: England | |||
| 4 | Dean Watson | 546 | 2,010 |
| 5 | Annas Siddiqui | 798 | 2,808 |
| 6 | Umair Arshad | 372 | 3,180 |
| 7 | Saim Ali | 537 | 3,717 |
| Country: Canada | |||
| 8 | Pedro Lemos | 460 | 4,177 |
| 9 | Rin Senan | 465 | 4,642 |
| 10 | Vishal Kumar | 263 | 4,905 |
| Country: Denmark | |||
| 11 | Kristian Skovrider | 380 | 5,283 |
| Country: Saudi Arabia | |||
| 12 | Yousef Siam | 401 | 5,686 |
| Country: Iran | |||
| 13 | Khosrow Salour | 545 | 6,231 |
| Country: Georgia | |||
| 14 | Tinatin | 413 | 6,644 |
| Country: The United States | |||
| 15 | Dusty Wagoner | 408 | 7,052 |
Function Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Function: TOP Management | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Dean Watson | 546 | 1,162 |
| 3 | Dusty Wagoner | 408 | 1,570 |
| 4 | Khosrow Salour | 545 | 2,115 |
| 5 | Kristian Skovrider | 380 | 2,495 |
| 6 | Tinatin | 413 | 2,908 |
| 7 | Yousef Siam | 401 | 3,309 |
| 8 | Rana El Maghraby | 362 | 3,671 |
| Function: Middle Management | |||
| 9 | Pedro Lemos | 460 | 4,131 |
| 10 | Rin Senan | 465 | 4,596 |
| 11 | Umair Arshad | 372 | 4,968 |
| 12 | Zeinab Mekawy | 486 | 5,454 |
| 13 | Saim Ali | 537 | 5,991 |
| 14 | Vishal Kumar | 263 | 6,254 |
| 15 | Annas Siddiqui | 798 | 7,052 |
Years of Experience Within the Company Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| Years of Experince: 1–5 Years | |||
| 1 | Rin Senan | 465 | 465 |
| 2 | Zeinab Mekawy | 486 | 951 |
| 3 | Annas Siddiqui | 798 | 1,749 |
| 4 | Saim Ali | 537 | 2,286 |
| 5 | Vishal Kumar | 263 | 2,549 |
| 6 | Umair Arshad | 372 | 2,921 |
| 7 | Tinatin | 413 | 3,334 |
| 8 | Yousef Siam | 401 | 3,735 |
| Years of Experience: 5–10 Years | |||
| 9 | Dean Watson | 546 | 4,281 |
| 10 | Rana El Maghraby | 362 | 4,643 |
| Years of Experience: 10–15 Years | |||
| 11 | Pedro Lemos | 460 | 5,103 |
| 12 | Kristian Skovrider | 380 | 5,483 |
| Years of Experience: 16+ Years | |||
| 13 | Ahmed AbdelMawla | 616 | 6,099 |
| 14 | Dusty Wagoner | 408 | 6,507 |
| 15 | Khosrow Salour | 545 | 7,052 |
Years of Experience in Total Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| Years of Experience in Total 21+ Years | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Dean Watson | 546 | 1,162 |
| 3 | Dusty Wagoner | 408 | 1,570 |
| 4 | Khosrow Salour | 545 | 2,115 |
| 5 | Kristian Skovrider | 380 | 2,495 |
| 6 | Yousef Siam | 401 | 2,896 |
| Years of Experience 10–15 Years | |||
| 7 | Pedro Lemos | 460 | 3,356 |
| 8 | Rana El Maghraby | 362 | 3,718 |
| 9 | Vishal Kumar | 263 | 3,981 |
| Years of Experience in Total 5–10 Years | |||
| 10 | Rin Senan | 465 | 4,446 |
| 11 | Tinatin | 413 | 4,859 |
| 12 | Umair Arshad | 372 | 5,231 |
| 13 | Annas Siddiqui | 798 | 6,029 |
| 14 | Saim Ali | 537 | 6,566 |
| Years of Experience in Total 3–5 Years | |||
| 15 | Zeinab Mekawy | 486 | 7,052 |
Company Sector Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| Company Sector Services | |||
| 1 | Ahmed Abdel | 616 | 616 |
| 2 | Dusty Wagoner | 408 | 1,024 |
| 3 | Khosrow Salour | 545 | 1,569 |
| 4 | Pedro Lemos | 460 | 2,029 |
| 5 | Rin Senan | 465 | 2,494 |
| 6 | Tinatin | 413 | 2,907 |
| 7 | Umair Arshad | 372 | 3,279 |
| 8 | Zeinab Mekawy | 486 | 3,765 |
| 9 | Annas Siddiqui | 798 | 4,563 |
| 10 | Rana El Maghraby | 362 | 4,925 |
| 11 | Vishal Kumar | 263 | 5,188 |
| Company Trade | |||
| 12 | Kristian Skovrider | 380 | 5,568 |
| 13 | Saim Ali | 537 | 6,105 |
| Company Retail | |||
| 14 | Yousef Siam | 401 | 6,506 |
| Company Other | |||
| 15 | Dean Watson | 546 | 7,052 |
Company Size (Turnover) Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Company Size (Turnover): 0.5M to <1M Euro | |||
| 1 | Khosrow Salour | 545 | 545 |
| 2 | Rana El Maghraby | 362 | 907 |
| 3 | Dean Watson | 546 | 1,453 |
| 4 | Yousef Siam | 401 | 1,854 |
| Company Size (Turnover): 1M to <5M Euro | |||
| 5 | Kristian Skovrider | 380 | 2,234 |
| 6 | Tinatin | 413 | 2,647 |
| 7 | Annas Siddiqui | 798 | 3,445 |
| Company Size (Turnover): 5M to >10M Euro | |||
| 8 | Dusty Wagoner | 408 | 3,853 |
| 9 | Zeinab Mekawy | 486 | 4,339 |
| Company Size (Turnover): 10M to >50M | |||
| 10 | Ahmed Abdel | 616 | 4,955 |
| 11 | Saim Ali | 537 | 5,492 |
| Company Size (Turnover): 50M+ | |||
| 12 | Pedro Lemos | 460 | 5,952 |
| 13 | Rin Senan | 465 | 6,417 |
| 14 | Umair Arshad | 372 | 6,789 |
| 15 | Vishal Kumar | 263 | 7,052 |
Company Size (Employees) Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| Company Size Employee | |||
| 1,001+ Employees | |||
| 1 | Ahmed AbdelMawla | 616 | 616 |
| 2 | Pedro Lemos | 460 | 1,076 |
| 3 | Rin Senan | 465 | 1,541 |
| 4 | Umair Arshad | 372 | 1,913 |
| 5 | Annas Siddiqui | 798 | 2,711 |
| 6 | Vishal Kumar | 263 | 2,974 |
| Company Size | |||
| 101–500 Employees | |||
| 7 | Tinatin | 413 | 3,387 |
| 8 | Zeinab Mkawy | 486 | 3,873 |
| Company Size | |||
| 51–100 | |||
| 9 | Dusty Wagoner | 408 | 4,281 |
| Company Size Employee | |||
| 11–50 Employees | |||
| 10 | Dean Watson | 546 | 4,827 |
| 11 | Yousef Siam | 401 | 5,228 |
| 12 | Rana El Maghraby | 362 | 5,590 |
| 13 | Saim Ali | 537 | 6,127 |
| Company Size | |||
| 1–10 Employees | |||
| 14 | Kristian Skovrider | 380 | 6,507 |
| 14 | Khosrow Salour | 545 | 7,052 |
Number of Nationalities Managed Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Number of Nationalities Managed: 1–3 | |||
| 1 | Dean Watson | 546 | 546 |
| 2 | Dusty Wagoner | 408 | 954 |
| 3 | Zeinab Mekawy | 486 | 1,440 |
| 4 | Rana El Maghraby | 362 | 1,802 |
| Number of Nationalities Managed: 4–5 | |||
| 5 | Umair Arshad | 372 | 2,174 |
| 6 | Yousef Siam | 401 | 2,575 |
| Number of Nationalities Managed: 6–10 | |||
| 7 | Khosrow Salour | 545 | 3,120 |
| 8 | Kristian Skovrider | 380 | 3,500 |
| 9 | Tinatin | 413 | 3,913 |
| 10 | Saim | 537 | 4,450 |
| 11 | Vishal Kumar | 263 | 4,713 |
| Number of Nationalities Managed: 11–15 | |||
| 12 | Ahmed AbdelMawla | 616 | 5,329 |
| 13 | Rin Senan | 465 | 5,794 |
| 14 | Annas Siddiqui | 798 | 6,592 |
| Number of Nationalities Managed: 16–20 | |||
| 15 | Pedro Lemos | 460 | 7,052 |
Number of Languages Spoken Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Number of Languages Spoken: 1 Language | |||
| 1 | Dean Watson | 546 | 546 |
| 2 | Dusty Wagoner | 408 | 954 |
| Number of Languages Spoken: 2 Languages | |||
| 3 | Ahmed AbdelMawla | 616 | 1,570 |
| 4 | Pedro Lemos | 460 | 2,030 |
| 5 | Rin Senan | 465 | 2,495 |
| 6 | Umair Arshad | 372 | 2,867 |
| 7 | Yousef Siam | 401 | 3,268 |
| 8 | Zeinab Mekawy | 486 | 3,754 |
| 9 | Annas Siddiqui | 798 | 4,552 |
| Number of Languages Spoken: 3 Languages | |||
| 10 | Khosrow Salour | 545 | 5,097 |
| 11 | Kristian Skovrider | 380 | 5,477 |
| 12 | Rana El Maghraby | 362 | 5,839 |
| Number of Languages Spoken: More than 3 Languages | |||
| 13 | Vishal Kumar | 263 | 6,102 |
| 14 | Saim Ali | 537 | 6,639 |
| 15 | Tinatin | 413 | 7,052 |
Number of Continents in Which the Subject Worked Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Total | Transcribed Total Words |
|---|---|---|---|
| No of Continents 3 Continents | |||
| 1 | Khosrow Salour | 545 | 545 |
| 2 | Pedro Lemos | 460 | 1,005 |
| No of Continents 2 Continents | |||
| 3 | Ahmed AbdelMawla | 616 | 1,621 |
| 4 | Kristian Skovrider | 380 | 2,001 |
| 5 | Rin Senan | 465 | 2,466 |
| 6 | Tinatin | 413 | 2,879 |
| 7 | Umair Arshad | 372 | 3,251 |
| 8 | Yousef Siam | 401 | 3,652 |
| 9 | Zeinab Mekawy | 486 | 4,138 |
| 10 | Annas Siddiqui | 798 | 4,936 |
| 11 | Saim | 537 | 5,473 |
| No of Continents 1 Continent | |||
| 12 | Dean Watson | 546 | 6,019 |
| 13 | Dusty Wagoner | 408 | 6,429 |
| 14 | Rana El Maghraby | 362 | 6,789 |
| 15 | Vishal Kumar | 263 | 7,052 |
Number of Countries in Which the Subject Worked Classification – Transcribed Words per Participant for Interview Section.
| No | Pseudonym | Transcribed Words | Transcribed Total Words |
|---|---|---|---|
| Number of Countries in Which the Subject Worked: 1 | |||
| 1 | Dean Watson | 546 | 546 |
| 2 | Dusty Wagoner | 408 | 954 |
| 3 | Rana El Maghraby | 362 | 1,316 |
| Number of Countries in Which the Subject Worked: 2 | |||
| 4 | Rin Senan | 465 | 1,781 |
| 5 | Tinatin | 413 | 2,194 |
| 6 | Umair Arshad | 372 | 2,566 |
| 7 | Yousef Siam | 401 | 2,967 |
| 8 | Zeinab Mekawy | 486 | 3,453 |
| 9 | Annas Siddiqui | 798 | 4,251 |
| Number of Countries in Which the Subject Worked: 3 | |||
| 10 | Khosrow Salour | 545 | 4,796 |
| 11 | Kristian Skovrider | 380 | 5,176 |
| 12 | Vishal Kumar | 263 | 5,439 |
| Number of Countries in Which the Subject Worked: More than 3 | |||
| 13 | Ahmed AbdelMawla | 616 | 6,055 |
| 14 | Pedro Lemos | 460 | 6,515 |
| 15 | Saim | 537 | 7,052 |
Appendix I – Total Transcribed Words per Variable
Gender Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | Total Male | Total Female |
|---|---|---|---|
| 15 | 7,052 | 12 | 3 |
Age Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | 26–40 | 41–60 | 60+ |
|---|---|---|---|---|
| 15 | 7,052 | 9 | 5 | 1 |
Education Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | High School | University Graduate | Masters |
|---|---|---|---|---|
| 15 | 7,052 | 1 | 7 | 7 |
Geography Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | Africa | Europe | North America | Asia |
|---|---|---|---|---|---|
| 15 | 7,052 | 3 | 6 | 4 | 2 |
Countries Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | Egypt | England | Canada | Denmark | Saudi Arabia | Iran | Georgia | US |
|---|---|---|---|---|---|---|---|---|---|
| 15 | 7,052 | 3 | 4 | 3 | 1 | 1 | 1 | 1 | 1 |
Company Sector Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | Services | Trade | Other | Retail |
|---|---|---|---|---|---|
| 15 | 7,052 | 11 | 2 | 1 | 1 |
Company size (Turnover) Classification – Total Transcribed Words for Interview Section.
| Total Interviews | Total Words Transcribed | <0.5M.euro/ | 0.5>=x < 1M euro/ | 1<=x < 5M | 5<=x < 10M | 10M = x < 50M | 50M + |
|---|---|---|---|---|---|---|---|
| 15 | 7,052 | 1 | 3 | 3 | 2 | 2 | 4 |
Company Size (Employees) Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | 1,001+ | 11–50 | 51–50 | 1–10 | 101–500 |
|---|---|---|---|---|---|---|
| 15 | 7,052 | 6 | 4 | 1 | 2 | 2 |
Function Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | Top Management | Middle Management |
|---|---|---|---|
| 15 | 7,052 | 8 | 7 |
Years of Experience Within the Company Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | 1–5 | 5–10 | 10–15 | 16+ |
|---|---|---|---|---|---|
| 15 | 7,052 | 8 | 2 | 2 | 3 |
Years of Experience in Total Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | 3–5 | 5–10 | 10–15 | 21+ |
|---|---|---|---|---|---|
| 15 | 7,052 | 1 | 5 | 3 | 6 |
Number of Nationalities Managed Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | 1–3 | 4–5 | 6–10 | 11–15 | 16–20 |
|---|---|---|---|---|---|---|
| 15 | 7,052 | 4 | 2 | 5 | 3 | 1 |
Number of Spoken Languages Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | One | Two | Three | More than 3 |
|---|---|---|---|---|---|
| 15 | 7,052 | 2 | 7 | 3 | 3 |
Number of Continents in Which the Subject Worked Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | One | Two | Three |
|---|---|---|---|---|
| 15 | 7,052 | 4 | 9 | 2 |
Number of Countries in Which Subjects Work Classification – Total Transcribed Words for Interview Section.
| Total Interviewed | Total Words Transcribed | One | Two | Three | More than 3 |
|---|---|---|---|---|---|
| 15 | 7,052 | 3 | 6 | 3 | 3 |
Appendices for Quantitative Research
Appendix J – Introduction Section for Questionnaire
Dear participant,
My name is Dan Paiuc and I am a PhD student at SNSPA Bucharest, Romania. The purpose of my questionnaire is to find out the impact of cultural intelligence and knowledge dynamics on multinational leadership, within organizational context, and I need your co-operation to help me answer this survey questions. I assure you that your responses are just for academic purposes and will be used only for statistical purposes.
It is estimated that this questionnaire will take 10–12 minutes, and I really appreciate your help in fulfilling this research endeavor that will benefit both academic and business-related areas.
Your participation in this survey is completely voluntary and you won't be compensated for it. However, you have the freedom to decline participating in the research or exit the survey at any time without any consequences. It is preferred that you answer all the questions but you are not obligated to. Your survey responses will be stored in a secure electronic format by Google Forms, and any identifying information such as your name, email address, or IP address won't be collected. Hence, your responses will be completely anonymous and in compliance with GDPR policy. It is assured that no one will be able to identify you by your responses, and no one will know if you participated in the study or not. Answering the questionnaire will represent your consent in regards all the above mentions.
Thank you very much for your time, effort, and participation! It is much appreciated.
Appendix K – Descriptive Statistics (Quantitative Research)
Descriptive Statistics for Quantitative Research: Frequencies and Percentages.
| Variables | Group | Category | Frequency | Percentage (%) |
|---|---|---|---|---|
| MCQ1 | 1 | Strongly disagree | 12 | 3.0 |
| 2 | Disagree | 22 | 5.6 | |
| 3 | Somewhat disagree | 36 | 9.1 | |
| 4 | Neutral | 50 | 12.6 | |
| 5 | Somewhat agree | 72 | 18.2 | |
| 6 | Agree | 103 | 26.0 | |
| 7 | Strongly agree | 101 | 25.5 | |
| MCQ2 | 1 | Strongly disagree | 17 | 4.3 |
| 2 | Disagree | 21 | 5.3 | |
| 3 | Somewhat disagree | 24 | 6.1 | |
| 4 | Neutral | 54 | 13.6 | |
| 5 | Somewhat agree | 97 | 24.5 | |
| 6 | Agree | 77 | 19.4 | |
| 7 | Strongly agree | 106 | 26.8 | |
| MCQ3 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 12 | 3.0 | |
| 3 | Somewhat disagree | 36 | 9.1 | |
| 4 | Neutral | 63 | 15.9 | |
| 5 | Somewhat agree | 82 | 20.7 | |
| 6 | Agree | 74 | 18.7 | |
| 7 | Strongly agree | 119 | 30.1 | |
| MCQ4 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 17 | 4.3 | |
| 3 | Somewhat disagree | 36 | 9.1 | |
| 4 | Neutral | 54 | 13.6 | |
| 5 | Somewhat agree | 84 | 21.2 | |
| 6 | Agree | 78 | 19.7 | |
| 7 | Strongly agree | 117 | 29.5 | |
| COCQ1 | 1 | Strongly disagree | 13 | 3.3 |
| 2 | Disagree | 22 | 5.6 | |
| 3 | Somewhat disagree | 38 | 9.6 | |
| 4 | Neutral | 70 | 17.7 | |
| 5 | Somewhat agree | 74 | 18.7 | |
| 6 | Agree | 94 | 23.7 | |
| 7 | Strongly agree | 85 | 21.5 | |
| COCQ2 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 20 | 5.1 | |
| 3 | Somewhat disagree | 42 | 10.6 | |
| 4 | Neutral | 61 | 15.4 | |
| 5 | Somewhat agree | 91 | 23.0 | |
| 6 | Agree | 79 | 19.9 | |
| 7 | Strongly agree | 96 | 24.2 | |
| COCQ3 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 30 | 7.6 | |
| 3 | Somewhat disagree | 42 | 10.6 | |
| 4 | Neutral | 61 | 15.4 | |
| 5 | Somewhat agree | 78 | 19.7 | |
| 6 | Agree | 63 | 15.9 | |
| 7 | Strongly agree | 115 | 29.0 | |
| COCQ4 | 1 | Strongly disagree | 13 | 3.3 |
| 2 | Disagree | 26 | 6.6 | |
| 3 | Somewhat disagree | 32 | 8.1 | |
| 4 | Neutral | 53 | 13.4 | |
| 5 | Somewhat agree | 106 | 26.8 | |
| 6 | Agree | 85 | 21.5 | |
| 7 | Strongly agree | 81 | 20.5 | |
| COCQ5 | 1 | Strongly disagree | 16 | 4.0 |
| 2 | Disagree | 26 | 6.6 | |
| 3 | Somewhat disagree | 25 | 6.3 | |
| 4 | Neutral | 65 | 16.4 | |
| 5 | Somewhat agree | 70 | 17.7 | |
| 6 | Agree | 86 | 21.7 | |
| 7 | Strongly agree | 108 | 27.3 | |
| COCQ6 | 1 | Strongly disagree | 14 | 3.5 |
| 2 | Disagree | 25 | 6.3 | |
| 3 | Somewhat disagree | 46 | 11.6 | |
| 4 | Neutral | 63 | 15.9 | |
| 5 | Somewhat agree | 77 | 19.4 | |
| 6 | Agree | 81 | 20.5 | |
| 7 | Strongly agree | 90 | 22.7 | |
| MOTCQ1 | 1 | Strongly disagree | 0.290 | 0.523 |
| 2 | Disagree | 13 | 3.3 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 36 | 9.1 | |
| 5 | Somewhat agree | 69 | 17.4 | |
| 6 | Agree | 76 | 19.2 | |
| 7 | Strongly agree | 68 | 17.2 | |
| MOTCQ2 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 18 | 4.5 | |
| 3 | Somewhat disagree | 46 | 11.6 | |
| 4 | Neutral | 56 | 14.1 | |
| 5 | Somewhat agree | 61 | 15.4 | |
| 6 | Agree | 82 | 20.7 | |
| 7 | Strongly agree | 123 | 31.1 | |
| MOTCQ3 | 1 | Strongly disagree | 13 | 3.3 |
| 2 | Disagree | 22 | 5.6 | |
| 3 | Somewhat disagree | 33 | 8.3 | |
| 4 | Neutral | 56 | 14.1 | |
| 5 | Somewhat agree | 79 | 19.9 | |
| 6 | Agree | 72 | 18.2 | |
| 7 | Strongly agree | 121 | 30.6 | |
| MOTCQ4 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 18 | 4.5 | |
| 3 | Somewhat disagree | 41 | 10.4 | |
| 4 | Neutral | 60 | 15.2 | |
| 5 | Somewhat agree | 62 | 15.7 | |
| 6 | Agree | 84 | 21.2 | |
| 7 | Strongly agree | 122 | 30.8 | |
| MOTCQ5 | 1 | Strongly disagree | 16 | 4.0 |
| 2 | Disagree | 20 | 5.1 | |
| 3 | Somewhat disagree | 33 | 8.3 | |
| 4 | Neutral | 51 | 12.9 | |
| 5 | Somewhat agree | 78 | 19.7 | |
| 6 | Agree | 83 | 21.0 | |
| 7 | Strongly agree | 115 | 29.0 | |
| BEHCQ1 | 1 | Strongly disagree | 18 | 4.5 |
| 2 | Disagree | 20 | 5.1 | |
| 3 | Somewhat disagree | 36 | 9.1 | |
| 4 | Neutral | 59 | 14.9 | |
| 5 | Somewhat agree | 84 | 21.2 | |
| 6 | Agree | 93 | 23.5 | |
| 7 | Strongly agree | 86 | 21.7 | |
| BEHCQ2 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 21 | 5.3 | |
| 3 | Somewhat disagree | 41 | 10.4 | |
| 4 | Neutral | 57 | 14.4 | |
| 5 | Somewhat agree | 68 | 17.2 | |
| 6 | Agree | 76 | 19.2 | |
| 7 | Strongly agree | 124 | 31.3 | |
| BEHCQ3 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 22 | 5.6 | |
| 3 | Somewhat disagree | 43 | 10.9 | |
| 4 | Neutral | 51 | 12.9 | |
| 5 | Somewhat agree | 80 | 20.2 | |
| 6 | Agree | 70 | 17.7 | |
| 7 | Strongly agree | 121 | 30.6 | |
| BEHCQ4 | 1 | Strongly disagree | 11 | 2.8 |
| 2 | Disagree | 23 | 5.8 | |
| 3 | Somewhat disagree | 38 | 9.6 | |
| 4 | Neutral | 52 | 13.1 | |
| 5 | Somewhat agree | 70 | 17.7 | |
| 6 | Agree | 85 | 21.5 | |
| 7 | Strongly agree | 117 | 29.5 | |
| BEHCQ5 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 19 | 4.8 | |
| 3 | Somewhat disagree | 28 | 7.1 | |
| 4 | Neutral | 48 | 12.1 | |
| 5 | Somewhat agree | 84 | 21.2 | |
| 6 | Agree | 93 | 23.5 | |
| 7 | Strongly agree | 115 | 29.0 | |
| RKD1 | 1 | Strongly disagree | 5 | 1.3 |
| 2 | Disagree | 22 | 5.6 | |
| 3 | Somewhat disagree | 35 | 8.8 | |
| 4 | Neutral | 60 | 15.2 | |
| 5 | Somewhat agree | 93 | 23.5 | |
| 6 | Agree | 103 | 26.0 | |
| 7 | Strongly agree | 78 | 19.7 | |
| RKD2 | 1 | Strongly disagree | 4 | 1.0 |
| 2 | Disagree | 19 | 4.8 | |
| 3 | Somewhat disagree | 24 | 6.1 | |
| 4 | Neutral | 50 | 12.6 | |
| 5 | Somewhat agree | 79 | 19.9 | |
| 6 | Agree | 82 | 20.7 | |
| 7 | Strongly agree | 138 | 34.8 | |
| RKD3 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 17 | 4.3 | |
| 3 | Somewhat disagree | 15 | 3.8 | |
| 4 | Neutral | 67 | 16.9 | |
| 5 | Somewhat agree | 91 | 23.0 | |
| 6 | Agree | 100 | 25.3 | |
| 7 | Strongly agree | 96 | 24.2 | |
| SKD1 | 1 | Strongly disagree | 8 | 2.0 |
| 2 | Disagree | 17 | 4.3 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 78 | 19.7 | |
| 5 | Somewhat agree | 93 | 23.5 | |
| 6 | Agree | 80 | 20.2 | |
| 7 | Strongly agree | 94 | 23.7 | |
| SKD2 | 1 | Strongly disagree | 6 | 1.5 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 48 | 12.1 | |
| 5 | Somewhat agree | 98 | 24.7 | |
| 6 | Agree | 93 | 23.5 | |
| 7 | Strongly agree | 110 | 27.8 | |
| SKD3 | 1 | Strongly disagree | 0.472 | 0.461 |
| 2 | Disagree | 5 | 1.3 | |
| 3 | Somewhat disagree | 10 | 2.5 | |
| 4 | Neutral | 26 | 6.6 | |
| 5 | Somewhat agree | 52 | 13.1 | |
| 6 | Agree | 75 | 18.9 | |
| 7 | Strongly agree | 100 | 25.3 | |
| EKD1 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 9 | 2.3 | |
| 3 | Somewhat disagree | 20 | 5.1 | |
| 4 | Neutral | 39 | 9.8 | |
| 5 | Somewhat agree | 52 | 13.1 | |
| 6 | Agree | 111 | 28.0 | |
| 7 | Strongly agree | 155 | 39.1 | |
| EKD2 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 23 | 5.8 | |
| 3 | Somewhat disagree | 28 | 7.1 | |
| 4 | Neutral | 46 | 11.6 | |
| 5 | Somewhat agree | 83 | 21.0 | |
| 6 | Agree | 83 | 21.0 | |
| 7 | Strongly agree | 124 | 31.3 | |
| EKD3 | 1 | Strongly disagree | 8 | 2.0 |
| 2 | Disagree | 8 | 2.0 | |
| 3 | Somewhat disagree | 38 | 9.6 | |
| 4 | Neutral | 38 | 9.6 | |
| 5 | Somewhat agree | 66 | 16.7 | |
| 6 | Agree | 87 | 22.0 | |
| 7 | Strongly agree | 151 | 38.1 | |
| AS_ML1 | 1 | Strongly disagree | 6 | 1.5 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 54 | 13.6 | |
| 5 | Somewhat agree | 82 | 20.7 | |
| 6 | Agree | 80 | 20.2 | |
| 7 | Strongly agree | 133 | 33.6 | |
| AS_ML2 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 11 | 2.8 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 53 | 13.4 | |
| 5 | Somewhat agree | 83 | 21.0 | |
| 6 | Agree | 83 | 21.0 | |
| 7 | Strongly agree | 131 | 33.1 | |
| AS_ML3 | 1 | Strongly disagree | 11 | 2.8 |
| 2 | Disagree | 8 | 2.0 | |
| 3 | Somewhat disagree | 21 | 5.3 | |
| 4 | Neutral | 47 | 11.9 | |
| 5 | Somewhat agree | 107 | 27.0 | |
| 6 | Agree | 86 | 21.7 | |
| 7 | Strongly agree | 116 | 29.3 | |
| IS_ML1 | 1 | Strongly disagree | 11 | 2.8 |
| 2 | Disagree | 14 | 3.5 | |
| 3 | Somewhat disagree | 32 | 8.1 | |
| 4 | Neutral | 67 | 16.9 | |
| 5 | Somewhat agree | 84 | 21.2 | |
| 6 | Agree | 90 | 22.7 | |
| 7 | Strongly agree | 98 | 24.7 | |
| IS_ML2 | 1 | Strongly disagree | 4 | 1.0 |
| 2 | Disagree | 14 | 3.5 | |
| 3 | Somewhat disagree | 18 | 4.5 | |
| 4 | Neutral | 53 | 13.4 | |
| 5 | Somewhat agree | 78 | 19.7 | |
| 6 | Agree | 85 | 21.5 | |
| 7 | Strongly agree | 144 | 36.4 | |
| IS_ML3 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 8 | 2.0 | |
| 3 | Somewhat disagree | 27 | 6.8 | |
| 4 | Neutral | 52 | 13.1 | |
| 5 | Somewhat agree | 69 | 17.4 | |
| 6 | Agree | 102 | 25.8 | |
| 7 | Strongly agree | 131 | 33.1 | |
| CS_ML1 | 1 | Strongly disagree | 4 | 1.0 |
| 2 | Disagree | 14 | 3.5 | |
| 3 | Somewhat disagree | 20 | 5.1 | |
| 4 | Neutral | 26 | 6.6 | |
| 5 | Somewhat agree | 63 | 15.9 | |
| 6 | Agree | 127 | 32.1 | |
| 7 | Strongly agree | 142 | 35.9 | |
| CS_ML2 | 1 | Strongly disagree | 12 | 3.0 |
| 2 | Disagree | 9 | 2.3 | |
| 3 | Somewhat disagree | 28 | 7.1 | |
| 4 | Neutral | 45 | 11.4 | |
| 5 | Somewhat agree | 85 | 21.5 | |
| 6 | Agree | 95 | 24.0 | |
| 7 | Strongly agree | 122 | 30.8 | |
| CS_ML3 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 33 | 8.3 | |
| 3 | Somewhat disagree | 34 | 8.6 | |
| 4 | Neutral | 50 | 12.6 | |
| 5 | Somewhat agree | 95 | 24.0 | |
| 6 | Agree | 78 | 19.7 | |
| 7 | Strongly agree | 97 | 24.5 | |
| MLS_ML1 | 1 | Strongly disagree | 4 | 1.0 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 46 | 11.6 | |
| 4 | Neutral | 74 | 18.7 | |
| 5 | Somewhat agree | 78 | 19.7 | |
| 6 | Agree | 89 | 22.5 | |
| 7 | Strongly agree | 90 | 22.7 | |
| MLS_ML2 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 10 | 2.5 | |
| 3 | Somewhat disagree | 44 | 11.1 | |
| 4 | Neutral | 53 | 13.4 | |
| 5 | Somewhat agree | 70 | 17.7 | |
| 6 | Agree | 108 | 27.3 | |
| 7 | Strongly agree | 102 | 25.8 | |
| MLS_ML3 | 1 | Strongly disagree | 12 | 3.0 |
| 2 | Disagree | 12 | 3.0 | |
| 3 | Somewhat disagree | 29 | 7.3 | |
| 4 | Neutral | 60 | 15.2 | |
| 5 | Somewhat agree | 93 | 23.5 | |
| 6 | Agree | 91 | 23.0 | |
| 7 | Strongly agree | 99 | 25.0 | |
| ACL_OC1 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 13 | 3.3 | |
| 3 | Somewhat disagree | 41 | 10.4 | |
| 4 | Neutral | 66 | 16.7 | |
| 5 | Somewhat agree | 85 | 21.5 | |
| 6 | Agree | 93 | 23.5 | |
| 7 | Strongly agree | 91 | 23.0 | |
| ACL_OC2 | 1 | Strongly disagree | 5 | 1.3 |
| 2 | Disagree | 17 | 4.3 | |
| 3 | Somewhat disagree | 23 | 5.8 | |
| 4 | Neutral | 46 | 11.6 | |
| 5 | Somewhat agree | 82 | 20.7 | |
| 6 | Agree | 98 | 24.7 | |
| 7 | Strongly agree | 125 | 31.6 | |
| ACL_OC3 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 10 | 2.5 | |
| 3 | Somewhat disagree | 25 | 6.3 | |
| 4 | Neutral | 55 | 13.9 | |
| 5 | Somewhat agree | 97 | 24.5 | |
| 6 | Agree | 77 | 19.4 | |
| 7 | Strongly agree | 125 | 31.6 | |
| CCL_OC1 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 30 | 7.6 | |
| 4 | Neutral | 62 | 15.7 | |
| 5 | Somewhat agree | 99 | 25.0 | |
| 6 | Agree | 96 | 24.2 | |
| 7 | Strongly agree | 85 | 21.5 | |
| CCL_OC2 | 1 | Strongly disagree | 8 | 2.0 |
| 2 | Disagree | 5 | 1.3 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 36 | 9.1 | |
| 5 | Somewhat agree | 77 | 19.4 | |
| 6 | Agree | 104 | 26.3 | |
| 7 | Strongly agree | 140 | 35.4 | |
| CCL_OC3 | 1 | Strongly disagree | 6 | 1.5 |
| 2 | Disagree | 13 | 3.3 | |
| 3 | Somewhat disagree | 23 | 5.8 | |
| 4 | Neutral | 46 | 11.6 | |
| 5 | Somewhat agree | 95 | 24.0 | |
| 6 | Agree | 79 | 19.9 | |
| 7 | Strongly agree | 134 | 33.8 | |
| DEIL_OC1 | 1 | Strongly disagree | 9 | 2.3 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 42 | 10.6 | |
| 4 | Neutral | 65 | 16.4 | |
| 5 | Somewhat agree | 85 | 21.5 | |
| 6 | Agree | 84 | 21.2 | |
| 7 | Strongly agree | 96 | 24.2 | |
| DEIL_OC2 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 10 | 2.5 | |
| 3 | Somewhat disagree | 33 | 8.3 | |
| 4 | Neutral | 68 | 17.2 | |
| 5 | Somewhat agree | 76 | 19.2 | |
| 6 | Agree | 89 | 22.5 | |
| 7 | Strongly agree | 113 | 28.5 | |
| DEIL_OC3 | 1 | Strongly disagree | 6 | 1.5 |
| 2 | Disagree | 9 | 2.3 | |
| 3 | Somewhat disagree | 33 | 8.3 | |
| 4 | Neutral | 53 | 13.4 | |
| 5 | Somewhat agree | 76 | 19.2 | |
| 6 | Agree | 80 | 20.2 | |
| 7 | Strongly agree | 139 | 35.1 | |
| EAIL_OC1 | 1 | Strongly disagree | 5 | 1.3 |
| 2 | Disagree | 10 | 2.5 | |
| 3 | Somewhat disagree | 24 | 6.1 | |
| 4 | Neutral | 51 | 12.9 | |
| 5 | Somewhat agree | 87 | 22.0 | |
| 6 | Agree | 98 | 24.7 | |
| 7 | Strongly agree | 121 | 30.6 | |
| EAIL_OC2 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 34 | 8.6 | |
| 4 | Neutral | 52 | 13.1 | |
| 5 | Somewhat agree | 72 | 18.2 | |
| 6 | Agree | 81 | 20.5 | |
| 7 | Strongly agree | 135 | 34.1 | |
| EAIL_OC3 | 1 | Strongly disagree | 6 | 1.5 |
| 2 | Disagree | 9 | 2.3 | |
| 3 | Somewhat disagree | 30 | 7.6 | |
| 4 | Neutral | 45 | 11.4 | |
| 5 | Somewhat agree | 102 | 25.8 | |
| 6 | Agree | 88 | 22.2 | |
| 7 | Strongly agree | 116 | 29.3 | |
| FTL_OC1 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 12 | 3.0 | |
| 3 | Somewhat disagree | 35 | 8.8 | |
| 4 | Neutral | 58 | 14.6 | |
| 5 | Somewhat agree | 94 | 23.7 | |
| 6 | Agree | 96 | 24.2 | |
| 7 | Strongly agree | 94 | 23.7 | |
| FTL_OC2 | 1 | Strongly disagree | 7 | 1.8 |
| 2 | Disagree | 12 | 3.0 | |
| 3 | Somewhat disagree | 26 | 6.6 | |
| 4 | Neutral | 55 | 13.9 | |
| 5 | Somewhat agree | 68 | 17.2 | |
| 6 | Agree | 90 | 22.7 | |
| 7 | Strongly agree | 138 | 34.8 | |
| FTL_OC3 | 1 | Strongly disagree | 12 | 3.0 |
| 2 | Disagree | 7 | 1.8 | |
| 3 | Somewhat disagree | 30 | 7.6 | |
| 4 | Neutral | 67 | 16.9 | |
| 5 | Somewhat agree | 80 | 20.2 | |
| 6 | Agree | 84 | 21.2 | |
| 7 | Strongly agree | 116 | 29.3 | |
| SL_OC1 | 1 | Strongly disagree | 8 | 2.0 |
| 2 | Disagree | 20 | 5.1 | |
| 3 | Somewhat disagree | 38 | 9.6 | |
| 4 | Neutral | 50 | 12.6 | |
| 5 | Somewhat agree | 105 | 26.5 | |
| 6 | Agree | 101 | 25.5 | |
| 7 | Strongly agree | 74 | 18.7 | |
| SL_OC2 | 1 | Strongly disagree | 10 | 2.5 |
| 2 | Disagree | 15 | 3.8 | |
| 3 | Somewhat disagree | 27 | 6.8 | |
| 4 | Neutral | 55 | 13.9 | |
| 5 | Somewhat agree | 71 | 17.9 | |
| 6 | Agree | 91 | 23.0 | |
| 7 | Strongly agree | 127 | 32.1 | |
| SL_OC3 | 1 | Strongly disagree | 13 | 3.3 |
| 2 | Disagree | 18 | 4.5 | |
| 3 | Somewhat disagree | 29 | 7.3 | |
| 4 | Neutral | 48 | 12.1 | |
| 5 | Somewhat agree | 76 | 19.2 | |
| 6 | Agree | 112 | 28.3 | |
| 7 | Strongly agree | 100 | 25.3 |
Note: MCQ: Metacognitive Cultural Intelligence, COCQ: Cognitive Cultural Intelligence, MOTCQ: Motivational Cultural Intelligence, BEHCQ: Behavioral Cultural Intelligence, RKD: Rational Knowledge Dynamics, SKD: Spiritual Knowledge Dynamics, EKD: Emotional Rational Knowledge Dynamics, AS_ML Administrative Skills, IS_ML: Interpersonal Skills, CS_ML Conceptual Skills, MLS_ML: Multicultural Leadership Skills, ACL_OC: Agility and Change Level, CCL_OC: Community and Connection Level, DIEL_OC: Diversity, Equity, and Inclusion Level, EAIL_OC: Entrepreneurship, Autonomy, and Innovation Level, FTL_OC: Flexibility and Transparency Level, SL_OC: Strength Level of the Company's Culture.
Appendix L – Assessing Normality (Quantitative Research) – Mean Based
Assessing Normality for Quantitative Research – Mean Based.
| Indicators | Minimum | Maximum | Mean | Median | Std. Deviation | Skewness | Kurtosis |
|---|---|---|---|---|---|---|---|
| MCQ1 | 1 | 7 | mai.17 | 6 | 1.653 | −0.764 | −0.285 |
| MCQ2 | 1 | 7 | mai.14 | 5 | 1.672 | −0.787 | −0.079 |
| MCQ3 | 1 | 7 | mai.26 | 5 | 1.591 | −0.670 | −0.276 |
| MCQ4 | 1 | 7 | mai.24 | 5 | 1.618 | −0.707 | −0.290 |
| COCQ1 | 1 | 7 | 5.00 | 5 | 1.640 | −0.592 | −0.448 |
| COCQ2 | 1 | 7 | 05.oct | 5 | 1.575 | −0.534 | −0.511 |
| COCQ3 | 1 | 7 | 05.aug | 5 | 1.693 | −0.488 | −0.800 |
| COCQ4 | 1 | 7 | 5.00 | 5 | 1.616 | −0.669 | −0.244 |
| COCQ5 | 1 | 7 | 05.nov | 5 | 1.719 | −0.721 | −0.363 |
| COCQ6 | 1 | 7 | apr.94 | 5 | 1.695 | −0.515 | −0.642 |
| MOTCQ1 | 1 | 7 | 05.mar | 5 | 1.710 | −0.546 | −0.614 |
| MOTCQ2 | 1 | 7 | mai.22 | 6 | 1.682 | −0.650 | −0.582 |
| MOTCQ3 | 1 | 7 | mai.19 | 5 | 1.696 | −0.702 | −0.392 |
| MOTCQ4 | 1 | 7 | mai.24 | 6 | 1.653 | −0.665 | −0.515 |
| MOTCQ5 | 1 | 7 | mai.18 | 6 | 1.705 | −0.772 | −0.263 |
| BEHCQ1 | 1 | 7 | 05.ian | 5 | 1.675 | −0.690 | −0.293 |
| BEHCQ2 | 1 | 7 | mai.22 | 6 | 1.674 | −0.643 | −0.572 |
| BEHCQ3 | 1 | 7 | mai.18 | 5 | 1.673 | −0.620 | −0.580 |
| BEHCQ4 | 1 | 7 | mai.20 | 6 | 1.687 | −0.703 | −0.461 |
| BEHCQ5 | 1 | 7 | mai.32 | 6 | 1.581 | −0.839 | −0.012 |
| RKD1 | 1 | 7 | 05.nov | 5 | 1.500 | −0.616 | −0.317 |
| RKD2 | 1 | 7 | mai.47 | 6 | 1.532 | −0.835 | −0.102 |
| RKD3 | 1 | 7 | mai.26 | 5 | 1.507 | −0.842 | 0.317 |
| EKD1 | 1 | 7 | mai.69 | 6 | 1.509 | −1.286 | 1.122 |
| EKD2 | 1 | 7 | mai.31 | 6 | 1.630 | −0.817 | −0.164 |
| .EKD3 | 1 | 7 | mai.55 | 6 | 1.559 | −0.964 | 0.120 |
| SKD1 | 1 | 7 | mai.14 | 5 | 1.519 | −0.585 | −0.201 |
| SKD2 | 1 | 7 | mai.36 | 6 | 1.479 | −0.813 | 0.138 |
| SKD3 | 1 | 7 | mai.51 | 6 | 1.454 | −0.875 | 0.159 |
| MLS_ML1 | 1 | 7 | 05.nov | 5 | 1.511 | −0.429 | −0.672 |
| MLS_ML2 | 1 | 7 | mai.27 | 6 | 1.552 | −0.743 | −0.201 |
| MLS_ML3 | 1 | 7 | mai.22 | 5 | 1.546 | −0.777 | 0.110 |
| CS_ML1 | 1 | 7 | mai.72 | 6 | 1.408 | −1.286 | 1.173 |
| CS_ML2 | 1 | 7 | mai.41 | 6 | 1.547 | −0.964 | 0.420 |
| CS_ML3 | 1 | 7 | 05.mai | 5 | 1.663 | −0.605 | −0.536 |
| IS_ML1 | 1 | 7 | mai.17 | 5 | 1.565 | −0.690 | −0.135 |
| IS_ML2 | 1 | 7 | mai.57 | 6 | 1.464 | −0.906 | 0.187 |
| IS_ML3 | 1 | 7 | mai.52 | 6 | 1.478 | −0.933 | 0.293 |
| AS_ML1 | 1 | 7 | mai.43 | 6 | 1.532 | −0.807 | −0.062 |
| AS_ML2 | 1 | 7 | mai.43 | 6 | 1.537 | −0.872 | 0.170 |
| AS_ML3 | 1 | 7 | mai.41 | 6 | 1.479 | −0.945 | 0.674 |
| SL_OC1 | 1 | 7 | 05.aug | 5 | 1.513 | −0.680 | −0.147 |
| SL_OC2 | 1 | 7 | mai.38 | 6 | 1.591 | −0.869 | 0.029 |
| SL_OC3 | 1 | 7 | mai.25 | 6 | 1.608 | −0.898 | 0.094 |
| CCL_OC1 | 1 | 7 | mai.16 | 5 | 1.499 | −0.705 | 0.023 |
| CCL_OC2 | 1 | 7 | mai.63 | 6 | 1.441 | −1.116 | 0.876 |
| CCL_OC3 | 1 | 7 | mai.48 | 6 | 1.487 | −0.874 | 0.220 |
| EAIL_OC1 | 1 | 7 | mai.48 | 6 | 1.429 | −0.853 | 0.242 |
| EAIL_OC2 | 1 | 7 | mai.40 | 6 | 1.586 | −0.785 | −0.237 |
| EAIL_OC3 | 1 | 7 | mai.41 | 6 | 1.446 | −0.800 | 0.178 |
| FTL_OC1 | 1 | 7 | mai.23 | 5 | 1.483 | −0.681 | −0.094 |
| FTL_OC2 | 1 | 7 | mai.49 | 6 | 1.530 | −0.891 | 0.087 |
| FTL_OC3 | 1 | 7 | mai.30 | 6 | 1.554 | −0.766 | 0.049 |
| ACL_OC1 | 1 | 7 | mai.15 | 5 | 1.515 | −0.575 | −0.357 |
| ACL_OC2 | 1 | 7 | mai.47 | 6 | 1.495 | −0.905 | 0.177 |
| ACL_OC3 | 1 | 7 | mai.41 | 6 | 1.481 | −0.784 | 0.125 |
| DEIL_OC1 | 1 | 7 | 05.dec | 5 | 1.571 | −0.571 | −0.405 |
| DEIL_OC2 | 1 | 7 | mai.31 | 6 | 1.513 | −0.669 | −0.230 |
| DEIL_OC3 | 1 | 7 | mai.47 | 6 | 1.517 | −0.794 | −0.125 |
Appendix M – Assessing Normality (Quantitative Research): Kolmogorov-Smirnov and Shapiro-Wilk Test
Assessing Normality for Quantitative Research: Kolmogorov-Smirnov and Shapiro-Wilk Test.
| Kolmogorov-Smirnov | Shapiro-Wilk | |||||
|---|---|---|---|---|---|---|
| Statistic | df | Sig. | Statistic | df | Sig. | |
| MCQ1 | 0.206 | 396 | 0.000 | 0.886 | 396 | 0.000 |
| MCQ2 | 0.173 | 396 | 0.000 | 0.886 | 396 | 0.000 |
| MCQ3 | 0.168 | 396 | 0.000 | 0.889 | 396 | 0.000 |
| MCQ4 | 0.173 | 396 | 0.000 | 0.887 | 396 | 0.000 |
| COCQ1 | 0.181 | 396 | 0.000 | 0.910 | 396 | 0.000 |
| COCQ2 | 0.159 | 396 | 0.000 | 0.910 | 396 | 0.000 |
| COCQ3 | 0.163 | 396 | 0.000 | 0.896 | 396 | 0.000 |
| COCQ4 | 0.187 | 396 | 0.000 | 0.907 | 396 | 0.000 |
| COCQ5 | 0.187 | 396 | 0.000 | 0.886 | 396 | 0.000 |
| COCQ6 | 0.167 | 396 | 0.000 | 0.912 | 396 | 0.000 |
| MOTCQ1 | 0.159 | 396 | 0.000 | 0.900 | 396 | 0.000 |
| MOTCQ2 | 0.197 | 396 | 0.000 | 0.880 | 396 | 0.000 |
| MOTCQ3 | 0.172 | 396 | 0.000 | 0.883 | 396 | 0.000 |
| MOTCQ4 | 0.197 | 396 | 0.000 | 0.881 | 396 | 0.000 |
| MOTCQ5 | 0.184 | 396 | 0.000 | 0.880 | 396 | 0.000 |
| BEHCQ1 | 0.176 | 396 | 0.000 | 0.902 | 396 | 0.000 |
| BEHCQ2 | 0.185 | 396 | 0.000 | 0.882 | 396 | 0.000 |
| BEHCQ3 | 0.169 | 396 | 0.000 | 0.887 | 396 | 0.000 |
| BEHCQ4 | 0.193 | 396 | 0.000 | 0.882 | 396 | 0.000 |
| BEHCQ5 | 0.192 | 396 | 0.000 | 0.878 | 396 | 0.000 |
| RKD1 | 0.181 | 396 | 0.000 | 0.911 | 396 | 0.000 |
| RKD2 | 0.190 | 396 | 0.000 | 0.862 | 396 | 0.000 |
| RKD3 | 0.183 | 396 | 0.000 | 0.889 | 396 | 0.000 |
| EKD1 | 0.252 | 396 | 0.000 | 0.808 | 396 | 0.000 |
| EKD2 | 0.186 | 396 | 0.000 | 0.872 | 396 | 0.000 |
| EKD3 | 0.214 | 396 | 0.000 | 0.840 | 396 | 0.000 |
| SKD1 | 0.154 | 396 | 0.000 | 0.909 | 396 | 0.000 |
| SKD2 | 0.179 | 396 | 0.000 | 0.885 | 396 | 0.000 |
| SKD3 | 0.208 | 396 | 0.000 | 0.868 | 396 | 0.000 |
| MLS_ML1 | 0.175 | 396 | 0.000 | 0.914 | 396 | 0.000 |
| MLS_ML2 | 0.212 | 396 | 0.000 | 0.888 | 396 | 0.000 |
| MLS_ML3 | 0.173 | 396 | 0.000 | 0.895 | 396 | 0.000 |
| CS_ML1 | 0.257 | 396 | 0.000 | 0.815 | 396 | 0.000 |
| CS_ML2 | 0.196 | 396 | 0.000 | 0.865 | 396 | 0.000 |
| CS_ML3 | 0.170 | 396 | 0.000 | 0.900 | 396 | 0.000 |
| IS_ML1 | 0.176 | 396 | 0.000 | 0.901 | 396 | 0.000 |
| IS_ML2 | 0.199 | 396 | 0.000 | 0.855 | 396 | 0.000 |
| IS_ML3 | 0.216 | 396 | 0.000 | 0.861 | 396 | 0.000 |
| AS_ML1 | 0.183 | 396 | 0.000 | 0.871 | 396 | 0.000 |
| AS_ML2 | 0.185 | 396 | 0.000 | 0.868 | 396 | 0.000 |
| AS_ML3 | 0.172 | 396 | 0.000 | 0.872 | 396 | 0.000 |
| SL_OC1 | 0.186 | 396 | 0.000 | 0.909 | 396 | 0.000 |
| SL_OC2 | 0.202 | 396 | 0.000 | 0.868 | 396 | 0.000 |
| SL_OC3 | 0.214 | 396 | 0.000 | 0.877 | 396 | 0.000 |
| CCL_OC1 | 0.170 | 396 | 0.000 | 0.906 | 396 | 0.000 |
| CCL_OC2 | 0.218 | 396 | 0.000 | 0.841 | 396 | 0.000 |
| CCL_OC3 | 0.184 | 396 | 0.000 | 0.866 | 396 | 0.000 |
| EAIL_OC1 | 0.194 | 396 | 0.000 | 0.876 | 396 | 0.000 |
| EAIL_OC2 | 0.193 | 396 | 0.000 | 0.868 | 396 | 0.000 |
| EAIL_OC3 | 0.172 | 396 | 0.000 | 0.883 | 396 | 0.000 |
| FTL_OC1 | 0.177 | 396 | 0.000 | 0.903 | 396 | 0.000 |
| FTL_OC2 | 0.206 | 396 | 0.000 | 0.859 | 396 | 0.000 |
| FTL_OC3 | 0.178 | 396 | 0.000 | 0.884 | 396 | 0.000 |
| ACL_OC1 | 0.177 | 396 | 0.000 | 0.910 | 396 | 0.000 |
| ACL_OC2 | 0.202 | 396 | 0.000 | 0.867 | 396 | 0.000 |
| ACL_OC3 | 0.174 | 396 | 0.000 | 0.879 | 396 | 0.000 |
| DEIL_OC1 | 0.168 | 396 | 0.000 | 0.908 | 396 | 0.000 |
| DEIL_OC2 | 0.186 | 396 | 0.000 | 0.891 | 396 | 0.000 |
| DEIL_OC3 | 0.194 | 396 | 0.000 | 0.866 | 396 | 0.000 |
Appendix N – ANOVA Tests
Descriptives of Age.
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
|---|---|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | 18–25 | 65 | 87.5077 | 31.30950 | 3.88347 | 79.7496 | 95.2658 | 21.00 | 135.00 |
| 26–40 | 136 | 102.9044 | 26.08160 | 2.23648 | 98.4813 | 107.3275 | 22.00 | 140.00 | |
| 41–60 | 160 | 107.2813 | 19.66166 | 1.55439 | 104.2113 | 110.3512 | 27.00 | 136.00 | |
| >61 | 35 | 110.4857 | 22.42553 | 3.79061 | 102.7823 | 118.1892 | 41.00 | 135.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | 18–25 | 65 | 41.8615 | 14.18282 | 1.75916 | 38.3472 | 45.3759 | 9.00 | 62.00 |
| 26–40 | 136 | 48.6324 | 10.49360 | 0.89982 | 46.8528 | 50.4119 | 18.00 | 63.00 | |
| 41–60 | 160 | 50.0250 | 7.69624 | 0.60844 | 48.8233 | 51.2267 | 9.00 | 63.00 | |
| >61 | 35 | 52.4000 | 5.75582 | 0.97291 | 50.4228 | 54.3772 | 35.00 | 63.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | 18–25 | 65 | 55.5385 | 18.92838 | 2.34778 | 50.8482 | 60.2287 | 12.00 | 80.00 |
| 26–40 | 136 | 64.7426 | 12.72501 | 1.09116 | 62.5847 | 66.9006 | 26.00 | 82.00 | |
| 41–60 | 160 | 66.3000 | 9.82027 | 0.77636 | 64.7667 | 67.8333 | 16.00 | 84.00 | |
| >61 | 35 | 69.8286 | 9.49144 | 1.60435 | 66.5681 | 73.0890 | 28.00 | 83.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | 18–25 | 65 | 85.9692 | 28.54874 | 3.54103 | 78.8952 | 93.0433 | 19.00 | 124.00 |
| 26–40 | 136 | 97.7941 | 17.48020 | 1.49891 | 94.8297 | 100.7585 | 51.00 | 126.00 | |
| 41–60 | 160 | 98.2000 | 15.56758 | 1.23073 | 95.7693 | 100.6307 | 18.00 | 125.00 | |
| >61 | 35 | 100.3429 | 11.67436 | 1.97333 | 96.3326 | 104.3531 | 71.00 | 117.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Age Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 20482.453 | 3 | 6827.484 | 11.480 | 0.000 |
| Within groups | 233137.090 | 392 | 594.737 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 3768.579 | 3 | 1256.193 | 12.863 | 0.000 |
| Within groups | 38283.671 | 392 | 97.662 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 6726.078 | 3 | 2242.026 | 13.909 | 0.000 |
| Within groups | 63186.718 | 392 | 161.191 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 8389.068 | 3 | 2796.356 | 8.026 | 0.000 |
| Within groups | 136579.659 | 392 | 348.417 | |||
| Total | 144968.727 | 395 | ||||
Based on the mean values, participants aged between 41 and 60 exhibited higher levels of cultural Intelligence (M = 107.28), while those aged 18–25 demonstrated lower levels of cultural Intelligence (M = 87.507). Furthermore, participants over the age of 61 scored higher in Knowledge Dynamics, Multicultural Leadership, and Organizational Context (M = 52.40, 69.82, and 100.34, respectively) compared to other age groups. A one-way ANOVA indicated a statistically significant difference in all levels of Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context across at least three age groups (F (3, 392) = [11.480, 12.863, 13.909, and 8.026, respectively], p = 0.000).
Descriptives of Education.
| Education Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | High school only | 27 | 88.3333 | 34.50195 | 6.63990 | 74.6848 | 101.9819 | 21.00 | 135.00 |
| University graduate | 164 | 100.6402 | 24.80869 | 1.93723 | 96.8149 | 104.4656 | 32.00 | 134.00 | |
| Master graduate | 157 | 105.6242 | 24.29451 | 1.93891 | 101.7943 | 109.4541 | 22.00 | 140.00 | |
| PhD graduate | 48 | 109.2083 | 20.95279 | 3.02428 | 103.1243 | 115.2924 | 45.00 | 137.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | High school only | 27 | 42.5185 | 14.95216 | 2.87754 | 36.6036 | 48.4334 | 9.00 | 63.00 |
| University graduate | 164 | 47.3110 | 10.73642 | 0.83837 | 45.6555 | 48.9664 | 12.00 | 62.00 | |
| Master graduate | 157 | 49.8917 | 9.00682 | 0.71882 | 48.4718 | 51.3116 | 9.00 | 63.00 | |
| PhD graduate | 48 | 50.6875 | 8.07717 | 1.16584 | 48.3421 | 53.0329 | 19.00 | 62.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | High school only | 27 | 58.0370 | 21.00821 | 4.04303 | 49.7265 | 66.3476 | 12.00 | 81.00 |
| University graduate | 164 | 62.7866 | 13.47197 | 1.05198 | 60.7093 | 64.8639 | 16.00 | 84.00 | |
| Master graduate | 157 | 65.4650 | 11.68087 | 0.93223 | 63.6235 | 67.3064 | 16.00 | 83.00 | |
| PhD graduate | 48 | 69.2708 | 10.03767 | 1.44881 | 66.3562 | 72.1855 | 31.00 | 81.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | High school only | 27 | 85.8148 | 29.54662 | 5.68625 | 74.1266 | 97.5031 | 19.00 | 122.00 |
| University graduate | 164 | 96.3963 | 19.47521 | 1.52076 | 93.3934 | 99.3993 | 26.00 | 125.00 | |
| Master graduate | 157 | 97.5032 | 16.99910 | 1.35668 | 94.8234 | 100.1830 | 18.00 | 126.00 | |
| PhD graduate | 48 | 97.4583 | 16.05040 | 2.31668 | 92.7978 | 102.1189 | 48.00 | 120.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Educational Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 9639.024 | 3 | 3213.008 | 5.162 | 0.002 |
| Within groups | 243980.519 | 392 | 622.399 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 1728.897 | 3 | 576.299 | 5.602 | 0.001 |
| Within groups | 40323.353 | 392 | 102.866 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 2833.766 | 3 | 944.589 | 5.520 | 0.001 |
| Within groups | 67079.030 | 392 | 171.120 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 3260.250 | 3 | 1086.750 | 3.006 | 0.030 |
| Within groups | 141708.477 | 392 | 361.501 | |||
| Total | 144968.727 | 395 | ||||
The table shows descriptive statistics for our four variables across different levels of education. The table provides data on the number of participants, the mean score for each level of education. It can be observed that as the level of education increases, the mean score for all variables also tends to increase.
The significant values in the ANOVA table (i.e., those with a Sig. value less than 0.05) indicate that there are statistically significant differences between the groups for each variable. Specifically, for Cultural Intelligence, there are significant differences between the groups of different education levels (high school only, university graduate, master graduate, and PhD graduate). Similarly, there are significant differences between the education groups for Knowledge Dynamics and Multicultural Leadership.
For Organizational Context, there is a significant difference between the groups, but the significance level is nearer (0.030) than to the typical cut-off of 0.05, indicating a weaker level of significance.
Descriptives of Continent Affiliation.
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
|---|---|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | Africa | 47 | 98.2979 | 29.15246 | 4.25232 | 89.7384 | 106.8574 | 22.00 | 135.00 |
| Asia | 79 | 97.7089 | 30.45221 | 3.42614 | 90.8879 | 104.5298 | 21.00 | 140.00 | |
| Australia | 38 | 109.1579 | 16.37818 | 2.65689 | 103.7745 | 114.5413 | 48.00 | 138.00 | |
| Europe | 130 | 108.8615 | 15.23804 | 1.33646 | 106.2173 | 111.5058 | 37.00 | 135.00 | |
| North America | 73 | 98.9041 | 30.10960 | 3.52406 | 91.8790 | 105.9292 | 27.00 | 136.00 | |
| South America | 29 | 98.4828 | 30.51887 | 5.66721 | 86.8740 | 110.0915 | 24.00 | 135.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | Africa | 47 | 47.6596 | 10.80514 | 1.57609 | 44.4871 | 50.8321 | 21.00 | 63.00 |
| Asia | 79 | 47.1899 | 12.49315 | 1.40559 | 44.3916 | 49.9882 | 9.00 | 63.00 | |
| Australia | 38 | 49.7632 | 9.41946 | 1.52804 | 46.6671 | 52.8593 | 12.00 | 62.00 | |
| Europe | 130 | 50.3231 | 5.56598 | 0.48817 | 49.3572 | 51.2889 | 15.00 | 62.00 | |
| North America | 73 | 46.6712 | 13.01714 | 1.52354 | 43.6341 | 49.7084 | 9.00 | 61.00 | |
| South America | 29 | 47.0690 | 12.05028 | 2.23768 | 42.4853 | 51.6526 | 18.00 | 60.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | Africa | 47 | 63.1489 | 14.51832 | 2.11771 | 58.8862 | 67.4117 | 26.00 | 84.00 |
| Asia | 79 | 62.6709 | 16.43848 | 1.84947 | 58.9889 | 66.3529 | 12.00 | 82.00 | |
| Australia | 38 | 65.9474 | 11.77480 | 1.91012 | 62.0771 | 69.8176 | 16.00 | 80.00 | |
| Europe | 130 | 66.5154 | 7.79707 | 0.68385 | 65.1624 | 67.8684 | 23.00 | 81.00 | |
| North America | 73 | 62.2192 | 15.93062 | 1.86454 | 58.5023 | 65.9361 | 16.00 | 83.00 | |
| South America | 29 | 63.8966 | 15.30720 | 2.84248 | 58.0740 | 69.7191 | 16.00 | 81.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | Africa | 47 | 98.0638 | 17.91575 | 2.61328 | 92.8036 | 103.3241 | 51.00 | 121.00 |
| Asia | 79 | 94.1013 | 23.53045 | 2.64738 | 88.8307 | 99.3718 | 19.00 | 126.00 | |
| Australia | 38 | 93.9474 | 18.23265 | 2.95773 | 87.9544 | 99.9403 | 27.00 | 117.00 | |
| Europe | 130 | 99.7692 | 13.14177 | 1.15261 | 97.4888 | 102.0497 | 32.00 | 125.00 | |
| North America | 73 | 92.7123 | 21.47833 | 2.51385 | 87.7011 | 97.7236 | 18.00 | 125.00 | |
| South America | 29 | 95.2069 | 23.86477 | 4.43158 | 86.1292 | 104.2846 | 26.00 | 122.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Continent Affiliation Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 10961.279 | 5 | 2192.256 | 3.523 | 0.004 |
| Within groups | 242658.264 | 390 | 622.201 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 962.274 | 5 | 192.455 | 1.827 | 0.107 |
| Within groups | 41089.976 | 390 | 105.359 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 1333.848 | 5 | 266.770 | 1.517 | 0.183 |
| Within groups | 68578.947 | 390 | 175.843 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 3276.040 | 5 | 655.208 | 1.803 | 0.111 |
| Within groups | 141692.688 | 390 | 363.315 | |||
| Total | 144968.727 | 395 | ||||
The average scores for Cultural Intelligence vary from 98.30 (Africa) to 109.16 (Australia), and for Knowledge Dynamics, they range from 46.67 (North America) to 50.32 (Europe). The average scores for Multicultural Leadership range from 62.22 (North America) to 66.52 (Europe), and for Organizational Context range from 92.71 (North America) to 99.77 (Europe).
According to the ANOVA table, the differences in mean scores for Cultural Intelligence across the continents are statistically significant (F = 3.523, p = 0.004). However, the mean differences in scores for Knowledge Dynamics, Multicultural Leadership, and Organizational Context are insignificant as the p-value is greater than 0.05.
Descriptives of Company Sector.
| Company Sector Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | Production | 87 | 113.5977 | 17.27914 | 1.85252 | 109.9150 | 117.2804 | 41.00 | 136.00 |
| Retail | 95 | 82.8000 | 29.34338 | 3.01057 | 76.8224 | 88.7776 | 21.00 | 138.00 | |
| Services | 115 | 106.4696 | 21.00013 | 1.95827 | 102.5902 | 110.3489 | 27.00 | 135.00 | |
| Trade | 92 | 107.9348 | 20.86682 | 2.17552 | 103.6134 | 112.2562 | 24.00 | 136.00 | |
| Other | 7 | 113.1429 | 26.58589 | 10.04852 | 88.5550 | 137.7307 | 57.00 | 140.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | Production | 87 | 51.9425 | 6.23448 | 0.66841 | 50.6138 | 53.2713 | 27.00 | 63.00 |
| Retail | 95 | 40.1895 | 13.34748 | 1.36942 | 37.4705 | 42.9085 | 9.00 | 62.00 | |
| Services | 115 | 50.1478 | 7.82623 | 0.72980 | 48.7021 | 51.5936 | 9.00 | 62.00 | |
| Trade | 92 | 51.6522 | 7.62793 | 0.79527 | 50.0725 | 53.2319 | 20.00 | 63.00 | |
| Other | 7 | 45.2857 | 11.52843 | 4.35734 | 34.6237 | 55.9477 | 23.00 | 54.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | Production | 87 | 69.0230 | 9.60859 | 1.03015 | 66.9751 | 71.0709 | 20.00 | 83.00 |
| Retail | 95 | 54.5474 | 16.94344 | 1.73836 | 51.0958 | 57.9989 | 12.00 | 80.00 | |
| Services | 115 | 65.5391 | 11.33717 | 1.05720 | 63.4448 | 67.6334 | 16.00 | 84.00 | |
| Trade | 92 | 68.3261 | 8.57560 | 0.89407 | 66.5501 | 70.1020 | 36.00 | 81.00 | |
| Other | 7 | 65.2857 | 12.85450 | 4.85854 | 53.3973 | 77.1741 | 40.00 | 79.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | Production | 87 | 98.3563 | 17.09343 | 1.83261 | 94.7132 | 101.9994 | 32.00 | 125.00 |
| Retail | 95 | 87.2737 | 24.66647 | 2.53073 | 82.2489 | 92.2985 | 19.00 | 124.00 | |
| Services | 115 | 98.0957 | 17.44514 | 1.62677 | 94.8730 | 101.3183 | 18.00 | 125.00 | |
| Trade | 92 | 100.6957 | 12.97651 | 1.35289 | 98.0083 | 103.3830 | 58.00 | 123.00 | |
| Other | 7 | 102.7143 | 18.65221 | 7.04987 | 85.4639 | 119.9647 | 69.00 | 126.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Company Sector Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 52866.314 | 4 | 13216.579 | 25.741 | 0.000 |
| Within groups | 200753.229 | 391 | 513.435 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 8888.163 | 4 | 2222.041 | 26.198 | 0.000 |
| Within groups | 33164.087 | 391 | 84.819 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 12651.085 | 4 | 3162.771 | 21.596 | 0.000 |
| Within groups | 57261.711 | 391 | 146.449 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 10543.034 | 4 | 2635.759 | 7.667 | 0.000 |
| Within groups | 134425.693 | 391 | 343.800 | |||
| Total | 144968.727 | 395 | ||||
Based on the mean values, participants from the production sector exhibited higher levels of Cultural Intelligence, Knowledge Dynamics, and Multicultural Leadership (M = 113.59, 51.94, and 69.02 accordingly), while the organizational context level was high among those who were from trade sector (M = 100.69) compared to other sectors. A one-way ANOVA indicated a statistically significant difference in all levels of Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context across at least four sectors (F (4, 391) = [25.74, 26.198, 21.596, and 7.667, respectively], p = 0.000).
Descriptives of Company's Size (Company's Yearly Turnover in Millions €).
| Size by Turnover Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | <0.5M. €/year as turnover | 50 | 77.4200 | 32.06695 | 4.53495 | 68.3067 | 86.5333 | 21.00 | 137.00 |
| 0.5>=x < 1M. €/year | 72 | 90.5139 | 29.25796 | 3.44808 | 83.6386 | 97.3892 | 22.00 | 135.00 | |
| 1M. <=x < 5M. €/year | 102 | 108.8431 | 16.60833 | 1.64447 | 105.5810 | 112.1053 | 54.00 | 140.00 | |
| 5M.>=x < 10M. €/year | 107 | 111.0093 | 18.54698 | 1.79300 | 107.4545 | 114.5642 | 37.00 | 136.00 | |
| >10M = x < 50M €/year | 48 | 112.0833 | 13.88989 | 2.00483 | 108.0501 | 116.1165 | 73.00 | 138.00 | |
| >=50M. €/year | 17 | 115.7059 | 22.47989 | 5.45217 | 104.1478 | 127.2640 | 67.00 | 136.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | <0.5M. €/year as turnover | 50 | 40.6200 | 14.16937 | 2.00385 | 36.5931 | 44.6469 | 9.00 | 62.00 |
| 0.5>=x < 1M. €/year | 72 | 42.8611 | 13.55978 | 1.59804 | 39.6747 | 46.0475 | 9.00 | 61.00 | |
| 1M. <=x < 5M. €/year | 102 | 50.8333 | 6.89825 | 0.68303 | 49.4784 | 52.1883 | 20.00 | 62.00 | |
| 5M.>=x < 10M. €/year | 107 | 50.9813 | 7.04029 | 0.68061 | 49.6319 | 52.3307 | 23.00 | 63.00 | |
| >10M = x < 50M €/year | 48 | 52.0833 | 4.59803 | 0.66367 | 50.7482 | 53.4185 | 41.00 | 63.00 | |
| >=50M. €/year | 17 | 53.8824 | 4.94826 | 1.20013 | 51.3382 | 56.4265 | 43.00 | 60.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | <0.5M. €/year as turnover | 50 | 54.5400 | 18.11439 | 2.56176 | 49.3919 | 59.6881 | 12.00 | 80.00 |
| 0.5>=x < 1M. €/year | 72 | 57.2361 | 17.61041 | 2.07541 | 53.0979 | 61.3744 | 16.00 | 82.00 | |
| 1M. <=x < 5M. €/year | 102 | 67.3627 | 8.62392 | 0.85390 | 65.6688 | 69.0566 | 35.00 | 81.00 | |
| 5M.>=x < 10M. €/year | 107 | 67.5888 | 8.85092 | 0.85565 | 65.8924 | 69.2852 | 36.00 | 84.00 | |
| >10M = x < 50M €/year | 48 | 68.8333 | 7.56626 | 1.09209 | 66.6363 | 71.0303 | 46.00 | 83.00 | |
| >=50M. €/year | 17 | 71.2941 | 7.99034 | 1.93794 | 67.1859 | 75.4024 | 50.00 | 82.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | <0.5M. €/year as turnover | 50 | 89.8800 | 25.75524 | 3.64234 | 82.5604 | 97.1996 | 19.00 | 124.00 |
| 0.5>=x < 1M. €/year | 72 | 89.5000 | 25.82771 | 3.04382 | 83.4308 | 95.5692 | 18.00 | 123.00 | |
| 1M. <=x < 5M. €/year | 102 | 101.6176 | 13.28965 | 1.31587 | 99.0073 | 104.2280 | 58.00 | 126.00 | |
| 5M.>=x < 10M. €/year | 107 | 99.0187 | 12.87163 | 1.24435 | 96.5517 | 101.4857 | 54.00 | 118.00 | |
| >10M = x < 50M €/year | 48 | 97.1458 | 15.53718 | 2.24260 | 92.6343 | 101.6574 | 61.00 | 120.00 | |
| >=50M. €/year | 17 | 91.2353 | 23.48278 | 5.69541 | 79.1616 | 103.3090 | 40.00 | 125.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Company's Size (Company's Yearly Turnover in Millions €) Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 60979.700 | 5 | 12195.940 | 24.691 | 0.000 |
| Within groups | 192639.843 | 390 | 493.948 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 7714.298 | 5 | 1542.860 | 17.523 | 0.000 |
| Within groups | 34337.952 | 390 | 88.046 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 12287.708 | 5 | 2457.542 | 16.632 | 0.000 |
| Within groups | 57625.087 | 390 | 147.757 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 9534.358 | 5 | 1906.872 | 5.491 | 0.000 |
| Within groups | 135434.369 | 390 | 347.268 | |||
| Total | 144968.727 | 395 | ||||
The company size is divided into the described six groups, which are based on their annual turnover.
The table provides insights into the relationship between company size and the four variables measured in the study. For instance, in the Cultural Intelligence category, there are 50 companies with a turnover of less than 0.5M. €/year, and the mean turnover for these companies is 77.42M. €/year, with a standard deviation of 32.07M. €/year. Similarly, for the Knowledge Dynamics category, there are 72 companies with a turnover between 0.5M. €/year and 1M. €/year, and the mean turnover for these companies is 42.86M. €/year, with a standard deviation of 13.56M. €/year. The results suggest that there are significant differences between groups for all four factors, as indicated by the low p-values (all <0.05) for the F-tests.
Descriptives of Company's Size (Employees' Number).
| Company's Size (Employees' Number) Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | 1–10 | 53 | 75.5472 | 30.65099 | 4.21024 | 67.0987 | 83.9956 | 21.00 | 137.00 |
| 11–50 | 65 | 90.8308 | 29.50030 | 3.65906 | 83.5210 | 98.1406 | 22.00 | 135.00 | |
| 51–100 | 84 | 107.3810 | 19.04016 | 2.07745 | 103.2490 | 111.5129 | 37.00 | 135.00 | |
| 101–500 | 116 | 112.3448 | 15.99680 | 1.48527 | 109.4028 | 115.2869 | 41.00 | 140.00 | |
| 501–1,000 | 60 | 110.8833 | 15.57169 | 2.01030 | 106.8607 | 114.9059 | 67.00 | 138.00 | |
| 1,000+ employees | 18 | 116.7778 | 20.00163 | 4.71443 | 106.8312 | 126.7244 | 69.00 | 136.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | 1–10 | 53 | 38.7358 | 13.75213 | 1.88900 | 34.9453 | 42.5264 | 9.00 | 62.00 |
| 11–50 | 65 | 44.2923 | 13.72580 | 1.70248 | 40.8912 | 47.6934 | 9.00 | 62.00 | |
| 51–100 | 84 | 49.9881 | 7.77003 | 0.84778 | 48.3019 | 51.6743 | 20.00 | 62.00 | |
| 101–500 | 116 | 51.3879 | 6.52723 | 0.60604 | 50.1875 | 52.5884 | 23.00 | 63.00 | |
| 501–1,000 | 60 | 51.5000 | 4.86600 | 0.62820 | 50.2430 | 52.7570 | 41.00 | 63.00 | |
| 1,000+ employees | 18 | 55.0556 | 3.29835 | 0.77743 | 53.4153 | 56.6958 | 50.00 | 60.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | 1–10 | 53 | 52.8113 | 17.32057 | 2.37916 | 48.0372 | 57.5855 | 12.00 | 80.00 |
| 11–50 | 65 | 58.1692 | 17.65429 | 2.18975 | 53.7947 | 62.5438 | 16.00 | 82.00 | |
| 51–100 | 84 | 66.5476 | 10.37189 | 1.13167 | 64.2968 | 68.7985 | 20.00 | 80.00 | |
| 101–500 | 116 | 67.6207 | 8.42837 | 0.78255 | 66.0706 | 69.1708 | 36.00 | 84.00 | |
| 501–1,000 | 60 | 69.1500 | 6.95707 | 0.89815 | 67.3528 | 70.9472 | 50.00 | 81.00 | |
| 1,000+ employees | 18 | 72.4444 | 6.25180 | 1.47356 | 69.3355 | 75.5534 | 60.00 | 83.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | 1–10 | 53 | 86.5094 | 25.95604 | 3.56534 | 79.3551 | 93.6638 | 19.00 | 124.00 |
| 11–50 | 65 | 92.0615 | 24.61762 | 3.05344 | 85.9616 | 98.1615 | 18.00 | 123.00 | |
| 51–100 | 84 | 99.8452 | 16.41003 | 1.79048 | 96.2840 | 103.4064 | 32.00 | 123.00 | |
| 101–500 | 116 | 101.1121 | 11.48138 | 1.06602 | 99.0005 | 103.2236 | 61.00 | 126.00 | |
| 501–1,000 | 60 | 95.6167 | 15.43064 | 1.99209 | 91.6305 | 99.6028 | 58.00 | 120.00 | |
| 1,000+ employees | 18 | 93.8889 | 23.60182 | 5.56300 | 82.1520 | 105.6258 | 40.00 | 125.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Company's Size (Employees' Number) Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 68443.962 | 5 | 13688.792 | 28.830 | 0.000 |
| Within groups | 185175.581 | 390 | 474.809 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 8668.026 | 5 | 1733.605 | 20.252 | 0.000 |
| Within groups | 33384.224 | 390 | 85.601 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 13747.329 | 5 | 2749.466 | 19.092 | 0.000 |
| Within groups | 56165.466 | 390 | 144.014 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 10121.236 | 5 | 2024.247 | 5.854 | 0.000 |
| Within groups | 134847.491 | 390 | 345.763 | |||
| Total | 144968.727 | 395 | ||||
For Cultural Intelligence, the mean score increases with an increase in the number of employees. The mean score is the lowest for the group with 1–10 employees (75.55) and the highest for the group with over 1,000 employees (116.77). For Knowledge Dynamics, the mean score also increases with an increase in the number of employees. The mean score is the lowest for the group with 1–10 employees (38.74) and the highest for the group with over 1,000 employees (55.06). For Multicultural Leadership, the mean score also increases with an increase in the number of employees. The mean score is the lowest for the group with 1–10 employees (52.81) and the highest for the group with over 1,000 employees (72.44). For Organizational Context, the mean score also increases with an increase in the number of employees. The mean score is the lowest for the group with 1–10 employees (86.51) and the highest for the group with over 1,000 employees (93.89).
Based on the ANOVA table, we can see that all four groups show a significant difference between groups, as indicated by their F-statistics and p-values (all p-values are less than 0.05). This suggests that there are meaningful differences between the groups on the variables being measured. Additionally, the p-values for each group are very low (all less than 0.001), suggesting that the differences between the groups are highly significant.
Descriptives of Function (From a Management Level Point of View).
| Function (From a Management Level Point of View) Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | Lower management | 46 | 103.2609 | 23.65346 | 3.48751 | 96.2367 | 110.2851 | 41.00 | 138.00 |
| Middle management | 145 | 108.4897 | 20.76626 | 1.72454 | 105.0810 | 111.8983 | 32.00 | 137.00 | |
| TOP management | 205 | 98.7024 | 27.84752 | 1.94496 | 94.8676 | 102.5372 | 21.00 | 140.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | Lower management | 46 | 50.3478 | 8.54327 | 1.25964 | 47.8108 | 52.8849 | 26.00 | 63.00 |
| Middle management | 145 | 50.0207 | 8.55819 | 0.71072 | 48.6159 | 51.4255 | 19.00 | 63.00 | |
| TOP management | 205 | 46.8488 | 11.54113 | 0.80607 | 45.2595 | 48.4381 | 9.00 | 63.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | Lower management | 46 | 66.8261 | 12.15512 | 1.79217 | 63.2165 | 70.4357 | 28.00 | 81.00 |
| Middle management | 145 | 66.1241 | 10.60129 | 0.88039 | 64.3840 | 67.8643 | 16.00 | 83.00 | |
| TOP management | 205 | 62.4634 | 14.95303 | 1.04436 | 60.4043 | 64.5225 | 12.00 | 84.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | Lower management | 46 | 92.7609 | 19.83060 | 2.92386 | 86.8719 | 98.6498 | 33.00 | 117.00 |
| Middle management | 145 | 96.9724 | 18.02427 | 1.49683 | 94.0138 | 99.9310 | 26.00 | 123.00 | |
| TOP management | 205 | 96.5073 | 19.78329 | 1.38173 | 93.7830 | 99.2316 | 18.00 | 126.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Function (From a Management Level Point of View) Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 8145.590 | 2 | 4072.795 | 6.520 | 0.002 |
| Within groups | 245473.953 | 393 | 624.616 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 1048.565 | 2 | 524.283 | 5.025 | 0.007 |
| Within groups | 41003.685 | 393 | 104.335 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 1467.446 | 2 | 733.723 | 4.213 | 0.015 |
| Within groups | 68445.350 | 393 | 174.161 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 649.229 | 2 | 324.615 | 0.884 | 0.414 |
| Within groups | 144319.498 | 393 | 367.225 | |||
| Total | 144968.727 | 395 | ||||
For Cultural Intelligence, the mean scores are 103.26 for lower management, 108.49 for middle management, and 98.70 for TOP management. The mean scores are significantly different between groups (p = 0.002). For Knowledge Dynamics, the mean scores are 50.35 for lower management, 50.02 for middle management, and 46.85 for TOP management. The differences between groups are statistically significant (p < 0.05 and = 0.007). For Multicultural Leadership, the mean scores are 66.83 for lower management, 66.12 for middle management, and 62.46 for TOP management. The differences between groups are statistically significant (p < 0.05). For Organizational Context, the mean scores are 92.76 for lower management, 96.97 for middle management, and 96.51 for TOP management. However, the difference between groups is not significant (p > 0.05). Overall, the differences between groups are statistically significant for all dimensions except for Cultural Intelligence. The significance values are very low (p < 0.01), indicating that the differences between the groups are highly significant.
Descriptives of Years of Experience Within the Company.
| Years of Experience within the Company Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | 1–3 | 72 | 92.0694 | 30.44151 | 3.58757 | 84.9160 | 99.2228 | 21.00 | 137.00 |
| 4–5 | 82 | 96.5488 | 29.14296 | 3.21830 | 90.1454 | 102.9522 | 22.00 | 136.00 | |
| 6–10 | 100 | 107.2700 | 23.64931 | 2.36493 | 102.5775 | 111.9625 | 27.00 | 140.00 | |
| 11–15 | 116 | 110.1121 | 15.45078 | 1.43457 | 107.2705 | 112.9537 | 45.00 | 136.00 | |
| 16> | 26 | 102.6538 | 25.69972 | 5.04013 | 92.2735 | 113.0342 | 37.00 | 135.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | 1–3 | 72 | 42.5139 | 13.47611 | 1.58817 | 39.3472 | 45.6806 | 9.00 | 62.00 |
| 4–5 | 82 | 46.7439 | 11.64051 | 1.28548 | 44.1862 | 49.3016 | 21.00 | 62.00 | |
| 6–10 | 100 | 51.1600 | 9.22636 | 0.92264 | 49.3293 | 52.9907 | 9.00 | 63.00 | |
| 11–15 | 116 | 50.5345 | 5.90126 | 0.54792 | 49.4492 | 51.6198 | 19.00 | 61.00 | |
| 16> | 26 | 50.0385 | 8.17548 | 1.60334 | 46.7363 | 53.3406 | 21.00 | 62.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | 1–3 | 72 | 57.4861 | 17.53387 | 2.06639 | 53.3659 | 61.6064 | 12.00 | 80.00 |
| 4–5 | 82 | 62.1707 | 16.24337 | 1.79378 | 58.6017 | 65.7398 | 20.00 | 82.00 | |
| 6–10 | 100 | 66.5300 | 10.37134 | 1.03713 | 64.4721 | 68.5879 | 16.00 | 81.00 | |
| 11–15 | 116 | 67.3707 | 8.27414 | 0.76823 | 65.8490 | 68.8924 | 31.00 | 84.00 | |
| 16> | 26 | 67.7692 | 10.14419 | 1.98944 | 63.6719 | 71.8666 | 34.00 | 79.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | 1–3 | 72 | 89.9167 | 25.59145 | 3.01598 | 83.9030 | 95.9304 | 19.00 | 124.00 |
| 4–5 | 82 | 93.9146 | 21.97653 | 2.42690 | 89.0859 | 98.7434 | 32.00 | 125.00 | |
| 6–10 | 100 | 98.9900 | 17.83453 | 1.78345 | 95.4512 | 102.5288 | 18.00 | 126.00 | |
| 11–15 | 116 | 98.4828 | 12.32141 | 1.14401 | 96.2167 | 100.7488 | 54.00 | 121.00 | |
| 16> | 26 | 100.5385 | 14.50305 | 2.84428 | 94.6806 | 106.3964 | 47.00 | 123.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining the Differences of Years of Experience Within the Company Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 19695.448 | 4 | 4923.862 | 8.230 | 0.000 |
| Within groups | 233924.095 | 391 | 598.271 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 4079.378 | 4 | 1019.845 | 10.501 | 0.000 |
| Within groups | 37972.872 | 391 | 97.117 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 5618.614 | 4 | 1404.653 | 8.542 | 0.000 |
| Within groups | 64294.182 | 391 | 164.435 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 5142.408 | 4 | 1285.602 | 3.595 | 0.007 |
| Within groups | 139826.319 | 391 | 357.612 | |||
| Total | 144968.727 | 395 | ||||
For Cultural Intelligence, the mean score increases with years of experience, from 92.0694 for those with 1–3 years of experience to 102.6538 for those with more than 16 years of experience. The difference between the groups is statistically significant, as evidenced by the 95% confidence intervals for the mean not overlapping. Similarly, for Knowledge Dynamics, the mean score also increases with years of experience, from 42.5139 for those with 1–3 years of experience to 50.0385 for those with more than 16 years of experience. Again, the difference between the groups is statistically significant. For Multicultural Leadership, the mean score also increases with years of experience, from 57.4861 for those with 1–3 years of experience to 67.7692 for those with more than 16 years of experience. Once again, the difference between the groups is statistically significant. For Organizational Context, the mean score also increases with years of experience, from 89.9167 for those with 1–3 years of experience to 100.5385 for those with more than 16 years of experience. The difference between the groups is statistically significant. Overall, the results suggest that as employees gain more years of experience within the company, they tend to score higher on measures of Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
Descriptives of Years of Experience in Total.
| Years of Experience in Total Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | 1–3 | 33 | 89.7879 | 33.46804 | 5.82604 | 77.9206 | 101.6551 | 21.00 | 135.00 |
| 4–5 | 63 | 86.3333 | 28.16942 | 3.54901 | 79.2390 | 93.4277 | 22.00 | 137.00 | |
| 6–10 | 88 | 106.3409 | 21.90622 | 2.33521 | 101.6994 | 110.9824 | 24.00 | 140.00 | |
| 11–15 | 110 | 107.7273 | 20.54840 | 1.95921 | 103.8442 | 111.6104 | 38.00 | 138.00 | |
| 16–20 | 72 | 108.4444 | 21.18655 | 2.49686 | 103.4658 | 113.4230 | 27.00 | 136.00 | |
| 21+ | 30 | 109.9000 | 25.38307 | 4.63429 | 100.4218 | 119.3782 | 37.00 | 135.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | 1–3 | 33 | 42.9091 | 14.57816 | 2.53773 | 37.7399 | 48.0783 | 9.00 | 62.00 |
| 4–5 | 63 | 41.3810 | 12.49829 | 1.57464 | 38.2333 | 44.5286 | 12.00 | 62.00 | |
| 6–10 | 88 | 49.4886 | 9.32059 | 0.99358 | 47.5138 | 51.4635 | 25.00 | 63.00 | |
| 11–15 | 110 | 50.5545 | 7.55965 | 0.72078 | 49.1260 | 51.9831 | 18.00 | 63.00 | |
| 16–20 | 72 | 50.5556 | 8.80283 | 1.03742 | 48.4870 | 52.6241 | 9.00 | 62.00 | |
| 21+ | 30 | 53.1333 | 4.38440 | 0.80048 | 51.4962 | 54.7705 | 46.00 | 63.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | 1–3 | 33 | 57.4545 | 19.92030 | 3.46768 | 50.3911 | 64.5180 | 12.00 | 80.00 |
| 4–5 | 63 | 55.7460 | 16.57531 | 2.08829 | 51.5716 | 59.9205 | 16.00 | 81.00 | |
| 6–10 | 88 | 64.4091 | 12.18878 | 1.29933 | 61.8265 | 66.9916 | 32.00 | 82.00 | |
| 11–15 | 110 | 67.4818 | 8.56998 | 0.81712 | 65.8623 | 69.1013 | 27.00 | 80.00 | |
| 16–20 | 72 | 67.5833 | 11.10989 | 1.30931 | 64.9726 | 70.1940 | 16.00 | 84.00 | |
| 21+ | 30 | 70.0667 | 7.05121 | 1.28737 | 67.4337 | 72.6996 | 57.00 | 81.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | 1–3 | 33 | 86.4545 | 28.44522 | 4.95168 | 76.3683 | 96.5408 | 19.00 | 117.00 |
| 4–5 | 63 | 87.3968 | 24.44978 | 3.08038 | 81.2392 | 93.5544 | 27.00 | 123.00 | |
| 6–10 | 88 | 98.3523 | 17.71423 | 1.88834 | 94.5990 | 102.1056 | 54.00 | 126.00 | |
| 11–15 | 110 | 98.7273 | 13.81855 | 1.31755 | 96.1159 | 101.3386 | 48.00 | 121.00 | |
| 16–20 | 72 | 100.5833 | 15.93804 | 1.87832 | 96.8381 | 104.3286 | 18.00 | 123.00 | |
| 21+ | 30 | 99.8667 | 13.06676 | 2.38565 | 94.9875 | 104.7459 | 61.00 | 117.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Years of Experience in Total Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 30249.959 | 5 | 6049.992 | 10.563 | 0.000 |
| Within groups | 223369.584 | 390 | 572.743 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 5720.260 | 5 | 1144.052 | 12.281 | 0.000 |
| Within groups | 36331.990 | 390 | 93.159 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 9044.574 | 5 | 1808.915 | 11.590 | 0.000 |
| Within groups | 60868.221 | 390 | 156.072 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 10912.602 | 5 | 2182.520 | 6.349 | 0.000 |
| Within groups | 134056.126 | 390 | 343.734 | |||
| Total | 144968.727 | 395 | ||||
For Cultural Intelligence, the mean values increase as the years of experience increase, with the highest mean of 109.9 for those with 21+ years of experience. The lowest mean is for those with 1–3 years of experience, with a mean of 89.8. Similarly, for Knowledge Dynamics, the mean values increase as the years of experience increase, with the highest mean of 53.1 for those with 21+ years of experience. The lowest mean is for those with 1–3 years of experience, with a mean of 42.9. For Multicultural Leadership, the mean values also increase as the years of experience increase, with the highest mean of 67.5 for those with 11–15 years of experience. The lowest mean is for those with 1–3 years of experience, with a mean of 57.5. Finally, for Organizational Context, the mean values increase as the years of experience increase, with the highest mean of 100.6 for those with 16–20 years of experience. The lowest mean is for those with 1–3 years of experience, with a mean of 86.5. Overall, it is clear that the mean values significantly generally increase with more years of experience in all four areas, with some variation between the different categories as p < 0.001.
Descriptives of Number of Managed Nationalities.
| Number of Managed Nationalities Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | 1–3 | 92 | 82.6196 | 30.59298 | 3.18954 | 76.2839 | 88.9552 | 21.00 | 140.00 |
| 4–5 | 72 | 108.3472 | 23.09269 | 2.72150 | 102.9207 | 113.7737 | 45.00 | 137.00 | |
| 6–10 | 54 | 105.0000 | 20.03488 | 2.72640 | 99.5315 | 110.4685 | 24.00 | 135.00 | |
| 11–15 | 66 | 109.7121 | 17.18923 | 2.11585 | 105.4865 | 113.9378 | 41.00 | 134.00 | |
| 16–20 | 35 | 116.2286 | 14.50778 | 2.45226 | 111.2450 | 121.2122 | 60.00 | 135.00 | |
| 21–50 | 45 | 110.2889 | 20.06197 | 2.99066 | 104.2616 | 116.3162 | 32.00 | 138.00 | |
| 51–100 | 24 | 102.1250 | 21.16871 | 4.32104 | 93.1862 | 111.0638 | 37.00 | 126.00 | |
| >100 | 8 | 115.0000 | 16.04458 | 5.67262 | 101.5864 | 128.4136 | 98.00 | 136.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | 1–3 | 92 | 39.4674 | 13.68841 | 1.42712 | 36.6326 | 42.3022 | 9.00 | 62.00 |
| 4–5 | 72 | 51.2639 | 8.93638 | 1.05316 | 49.1639 | 53.3638 | 19.00 | 63.00 | |
| 6–10 | 54 | 51.1296 | 7.19026 | 0.97847 | 49.1671 | 53.0922 | 24.00 | 62.00 | |
| 11–15 | 66 | 50.6818 | 6.12726 | 0.75421 | 49.1755 | 52.1881 | 21.00 | 63.00 | |
| 16–20 | 35 | 51.5143 | 7.08092 | 1.19689 | 49.0819 | 53.9467 | 26.00 | 63.00 | |
| 21–50 | 45 | 51.9333 | 4.42822 | 0.66012 | 50.6030 | 53.2637 | 39.00 | 60.00 | |
| 51–100 | 24 | 50.5833 | 7.37750 | 1.50593 | 47.4681 | 53.6986 | 23.00 | 59.00 | |
| >100 | 8 | 48.8750 | 9.53846 | 3.37235 | 40.9007 | 56.8493 | 27.00 | 56.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | 1–3 | 92 | 54.3261 | 17.35290 | 1.80917 | 50.7324 | 57.9198 | 12.00 | 81.00 |
| 4–5 | 72 | 66.1111 | 13.26072 | 1.56279 | 62.9950 | 69.2272 | 16.00 | 82.00 | |
| 6–10 | 54 | 66.8889 | 9.92741 | 1.35095 | 64.1792 | 69.5986 | 36.00 | 83.00 | |
| 11–15 | 66 | 67.1818 | 8.39580 | 1.03345 | 65.1179 | 69.2458 | 26.00 | 81.00 | |
| 16–20 | 35 | 68.1429 | 8.86879 | 1.49910 | 65.0963 | 71.1894 | 36.00 | 84.00 | |
| 21–50 | 45 | 70.1333 | 7.09225 | 1.05725 | 68.0026 | 72.2641 | 54.00 | 82.00 | |
| 51–100 | 24 | 66.4583 | 8.34568 | 1.70355 | 62.9343 | 69.9824 | 49.00 | 79.00 | |
| >100 | 8 | 65.8750 | 13.37842 | 4.72999 | 54.6904 | 77.0596 | 36.00 | 79.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | 1–3 | 92 | 87.7935 | 25.80763 | 2.69063 | 82.4489 | 93.1381 | 18.00 | 126.00 |
| 4–5 | 72 | 101.4861 | 18.67513 | 2.20088 | 97.0977 | 105.8746 | 26.00 | 123.00 | |
| 6–10 | 54 | 99.8333 | 16.09729 | 2.19056 | 95.4396 | 104.2270 | 40.00 | 125.00 | |
| 11–15 | 66 | 98.2273 | 14.85809 | 1.82890 | 94.5747 | 101.8798 | 48.00 | 123.00 | |
| 16–20 | 35 | 97.8857 | 12.07275 | 2.04067 | 93.7386 | 102.0328 | 63.00 | 117.00 | |
| 21–50 | 45 | 96.9333 | 13.72523 | 2.04604 | 92.8098 | 101.0568 | 66.00 | 125.00 | |
| 51–100 | 24 | 94.6250 | 15.87126 | 3.23971 | 87.9232 | 101.3268 | 58.00 | 117.00 | |
| >100 | 8 | 99.3750 | 19.69726 | 6.96403 | 82.9077 | 115.8423 | 54.00 | 115.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Number of Managed Nationalities Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 53133.968 | 7 | 7590.567 | 14.690 | 0.000 |
| Within groups | 200485.575 | 388 | 516.715 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 9694.700 | 7 | 1384.957 | 16.607 | 0.000 |
| Within groups | 32357.550 | 388 | 83.396 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 12477.996 | 7 | 1782.571 | 12.042 | 0.000 |
| Within groups | 57434.799 | 388 | 148.028 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 9760.731 | 7 | 1,394.390 | 4.001 | 0.000 |
| Within groups | 135207.996 | 388 | 348.474 | |||
| Total | 144968.727 | 395 | ||||
The ranges of managed nationalities are divided into eight categories: 1–3, 4–5, 6–10, 11–15, 16–20, 21–50, 51–100, and greater than 100. The mean values show the central tendency of the data in each group. For example, the mean Cultural Intelligence score for the category of 1–3 managed nationalities is 82.6196, while the mean score for the category of greater than 100 managed nationalities is 115.0000. This indicates that as the number of managed nationalities increases, the mean Cultural Intelligence score also increases. Similarly, the mean Knowledge Dynamics score increases as the number of managed nationalities increases, from 39.4674 for the 1–3 category to 48.8750 for the >100 category. The Multicultural Leadership scores show a steady increase as the number of managed nationalities increases, with the highest mean score of 70.1333 for the 21–50 category. Finally, the Organizational Context scores also increase as the number of managed nationalities increases, with a mean score of 87.7935 for the 1–3 category and a mean score of 111.4828 for the >100 category. In general, the results suggest that there are significant differences between the groups for all four variables (p = 0.000).
Descriptives of Spoken Languages.
| Spoken Languages Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | One | 45 | 76.5556 | 32.24237 | 4.80641 | 66.8689 | 86.2422 | 21.00 | 134.00 |
| Two | 147 | 100.6667 | 25.33754 | 2.08980 | 96.5365 | 104.7968 | 24.00 | 140.00 | |
| Three | 139 | 108.2878 | 19.42815 | 1.64787 | 105.0294 | 111.5461 | 32.00 | 136.00 | |
| More than Three | 65 | 114.1538 | 16.69134 | 2.07031 | 110.0179 | 118.2898 | 54.00 | 138.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | One | 45 | 39.2444 | 14.03106 | 2.09163 | 35.0290 | 43.4598 | 9.00 | 59.00 |
| Two | 147 | 47.5374 | 10.41158 | 0.85873 | 45.8403 | 49.2346 | 18.00 | 63.00 | |
| Three | 139 | 50.2302 | 8.09841 | 0.68690 | 48.8720 | 51.5884 | 12.00 | 62.00 | |
| More than Three | 65 | 52.8769 | 6.68839 | 0.82959 | 51.2196 | 54.5342 | 20.00 | 63.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | One | 45 | 53.9778 | 17.49609 | 2.60816 | 48.7214 | 59.2342 | 12.00 | 81.00 |
| Two | 147 | 62.3537 | 14.27125 | 1.17707 | 60.0274 | 64.6800 | 16.00 | 84.00 | |
| Three | 139 | 66.5540 | 9.97255 | 0.84586 | 64.8814 | 68.2265 | 16.00 | 82.00 | |
| More than Three | 65 | 71.0923 | 7.83367 | 0.97165 | 69.1512 | 73.0334 | 36.00 | 83.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | One | 45 | 86.4000 | 25.66072 | 3.82527 | 78.6907 | 94.1093 | 18.00 | 123.00 |
| Two | 147 | 95.0680 | 20.82532 | 1.71764 | 91.6734 | 98.4627 | 26.00 | 126.00 | |
| Three | 139 | 98.5683 | 15.15000 | 1.28501 | 96.0275 | 101.1092 | 27.00 | 125.00 | |
| More than Three | 65 | 100.7385 | 14.98674 | 1.85888 | 97.0249 | 104.4520 | 54.00 | 121.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Spoken Languages Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 44228.814 | 3 | 14742.938 | 27.600 | 0.000 |
| Within groups | 209390.729 | 392 | 534.160 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 5649.746 | 3 | 1883.249 | 20.280 | 0.000 |
| Within groups | 36402.504 | 392 | 92.864 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 9056.421 | 3 | 3018.807 | 19.445 | 0.000 |
| Within groups | 60856.375 | 392 | 155.246 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 6627.953 | 3 | 2209.318 | 6.260 | 0.000 |
| Within groups | 138340.774 | 392 | 352.910 | |||
| Total | 144968.727 | 395 | ||||
For the construct of Cultural Intelligence, the mean score increases as the number of spoken languages increases. The group that speaks more than three languages has the highest mean score (114.1538), followed by the group that speaks three languages (108.2878), the group that speaks two languages (100.6667), and the group that speaks one language (76.5556). The differences between the means are statistically significant, as the 95% confidence intervals for the means do not overlap and p < 0.001. For the construct of Knowledge Dynamics, the mean score also increases as the number of spoken languages increases. The group that speaks more than three languages has the highest mean score (52.8769), followed by the group that speaks three languages (50.2302), the group that speaks two languages (47.5374), and the group that speaks one language (39.2444). The differences between the means are statistically significant, as p < 0.001. For the construct of Multicultural Leadership, the mean score also increases as the number of spoken languages increases. The group that speaks more than three languages has the highest mean score (71.0923), followed by the group that speaks three languages (66.5540), the group that speaks two languages (62.3537), and the group that speaks one language (53.9778). The differences between the means are statistically significant, as the 95% confidence intervals for the means do not overlap and p < 0.001. Finally, for the construct of Organizational Context, the mean score also increases as the number of spoken languages increases. The group that speaks more than three languages has the highest mean score (100.7385), followed by the group that speaks three languages (98.5683), the group that speaks two languages (95.0680), and the group that speaks one language (86.4000). There is a statistically significant difference (p = 0.000) between the means, as the 95% confidence intervals for the means do not intersect.
Descriptives of Number of Worked Continents.
| Number of Worked Continents Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | One | 166 | 93.6506 | 30.61370 | 2.37608 | 88.9592 | 98.3421 | 21.00 | 140.00 |
| Two | 128 | 108.5234 | 19.20874 | 1.69783 | 105.1637 | 111.8831 | 39.00 | 137.00 | |
| Three | 62 | 107.1452 | 17.13863 | 2.17661 | 102.7928 | 111.4976 | 37.00 | 135.00 | |
| More than Three | 40 | 115.8750 | 14.41720 | 2.27956 | 111.2642 | 120.4858 | 80.00 | 138.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | One | 166 | 45.3976 | 12.44960 | 0.96628 | 43.4897 | 47.3055 | 9.00 | 63.00 |
| Two | 128 | 50.1797 | 9.10432 | 0.80472 | 48.5873 | 51.7721 | 12.00 | 63.00 | |
| Three | 62 | 49.6935 | 6.08570 | 0.77288 | 48.1481 | 51.2390 | 24.00 | 61.00 | |
| More than Three | 40 | 53.3250 | 4.28706 | 0.67784 | 51.9539 | 54.6961 | 46.00 | 61.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | One | 166 | 61.0663 | 15.95947 | 1.23870 | 58.6205 | 63.5120 | 12.00 | 84.00 |
| Two | 128 | 65.7188 | 12.07453 | 1.06725 | 63.6069 | 67.8306 | 16.00 | 83.00 | |
| Three | 62 | 65.4677 | 7.99942 | 1.01593 | 63.4363 | 67.4992 | 36.00 | 79.00 | |
| More than Three | 40 | 71.4750 | 5.83969 | 0.92334 | 69.6074 | 73.3426 | 55.00 | 81.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | One | 166 | 95.5723 | 21.91618 | 1.70103 | 92.2137 | 98.9309 | 18.00 | 126.00 |
| Two | 128 | 96.5391 | 18.99312 | 1.67877 | 93.2171 | 99.8610 | 26.00 | 125.00 | |
| Three | 62 | 97.1613 | 14.07147 | 1.78708 | 93.5878 | 100.7348 | 48.00 | 121.00 | |
| More than Three | 40 | 96.6500 | 14.03211 | 2.21867 | 92.1623 | 101.1377 | 58.00 | 115.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Number of Worked Continents Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 26097.810 | 3 | 8699.270 | 14.988 | 0.000 |
| Within groups | 227521.733 | 392 | 580.413 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 2975.671 | 3 | 991.890 | 9.950 | 0.000 |
| Within groups | 39076.579 | 392 | 99.685 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 4137.239 | 3 | 1379.080 | 8.219 | 0.000 |
| Within groups | 65775.557 | 392 | 167.795 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 144.803 | 3 | 48.268 | 0.131 | 0.942 |
| Within groups | 144823.924 | 392 | 369.449 | |||
| Total | 144968.727 | 395 | ||||
Cultural Intelligence scores generally increase as the number of worked continents increases, with the “More than Three” group having the highest mean score of 115.8750 and the “One” group having the lowest mean score of 93.6506. Similarly, Knowledge Dynamics scores also generally increase as the number of worked continents increases, with the “More than Three” group having the highest mean score of 53.3250 and the “One” group having the lowest mean score of 45.3976.
Meanwhile, Multicultural Leadership scores show a similar trend, with the “More than Three” group having the highest mean score of 71.4750 and the “One” group having the lowest mean score of 61.0663. On the other hand, Organizational Context scores do not show a clear trend based on the number of worked continents. The mean scores for all four groups are relatively close, with the “Three” group having the highest mean score of 97.1613 and the “One” group having the lowest mean score of 95.5723. The significance values provided in the ANOVA table indicate that for Cultural Intelligence, Knowledge Dynamics, and Multicultural Leadership, the significance values are all less than 0.05, which means that there are significant differences between the means of the groups. However, for Organizational Context, the significance value is 0.942, which is greater than 0.05, indicating that there is not enough evidence to suggest that the means of the groups are significantly different.
Descriptives of Number of Worked Countries.
| Number of Worked Countries Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | One | 93 | 81.0430 | 29.98547 | 3.10935 | 74.8676 | 87.2184 | 21.00 | 140.00 |
| Two | 99 | 106.9697 | 19.70106 | 1.98003 | 103.0404 | 110.8990 | 24.00 | 135.00 | |
| Three | 104 | 107.3750 | 20.52571 | 2.01271 | 103.3833 | 111.3667 | 37.00 | 137.00 | |
| More than Three | 100 | 114.2100 | 16.97550 | 1.69755 | 110.8417 | 117.5783 | 61.00 | 138.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | One | 93 | 41.1290 | 12.87923 | 1.33551 | 38.4766 | 43.7815 | 9.00 | 63.00 |
| Two | 99 | 49.2828 | 9.24391 | 0.92905 | 47.4392 | 51.1265 | 19.00 | 63.00 | |
| Three | 104 | 49.7788 | 8.53884 | 0.83730 | 48.1183 | 51.4394 | 12.00 | 63.00 | |
| More than Three | 100 | 52.9200 | 6.09136 | 0.60914 | 51.7113 | 54.1287 | 21.00 | 62.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | One | 93 | 55.9247 | 16.37153 | 1.69765 | 52.5531 | 59.2964 | 12.00 | 81.00 |
| Two | 99 | 64.9394 | 12.08120 | 1.21421 | 62.5298 | 67.3489 | 16.00 | 81.00 | |
| Three | 104 | 65.2212 | 11.84361 | 1.16136 | 62.9179 | 67.5244 | 16.00 | 84.00 | |
| More than Three | 100 | 70.5400 | 7.75694 | 0.77569 | 69.0009 | 72.0791 | 26.00 | 83.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | One | 93 | 89.6989 | 23.12198 | 2.39764 | 84.9370 | 94.4608 | 18.00 | 126.00 |
| Two | 99 | 98.8384 | 18.36407 | 1.84566 | 95.1757 | 102.5010 | 26.00 | 124.00 | |
| Three | 104 | 99.1154 | 17.34533 | 1.70085 | 95.7422 | 102.4886 | 27.00 | 125.00 | |
| More than Three | 100 | 96.7700 | 16.27097 | 1.62710 | 93.5415 | 99.9985 | 48.00 | 121.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Number of Worked Countries Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 60939.841 | 3 | 20313.280 | 41.327 | 0.000 |
| Within groups | 192679.702 | 392 | 491.530 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 7234.444 | 3 | 2411.481 | 27.150 | 0.000 |
| Within groups | 34817.806 | 392 | 88.821 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 10545.933 | 3 | 3515.311 | 23.212 | 0.000 |
| Within groups | 59366.863 | 392 | 151.446 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 5535.418 | 3 | 1845.139 | 5.187 | 0.002 |
| Within groups | 139433.309 | 392 | 355.697 | |||
| Total | 144968.727 | 395 | ||||
The ANOVA results indicate that all four variables have significant differences between the groups. For Cultural Intelligence, the mean difference is highest for those who worked in more than three countries. For Knowledge Dynamics, the mean difference is also highest for those who worked in more than three countries. For Multicultural Leadership, the mean difference is highest for those who worked in more than three countries. For Organizational Context, the mean difference is highest for those who worked in three countries.
Descriptives of Experience in Managing Virtual Teams.
| Experience in Managing Virtual Teams Descriptives | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |||
| Lower Bound | Upper Bound | ||||||||
| Cultural Intelligence | No experience | 51 | 68.7255 | 28.45774 | 3.98488 | 60.7216 | 76.7294 | 21.00 | 131.00 |
| 1–2 years experience | 99 | 99.4141 | 26.73071 | 2.68654 | 94.0828 | 104.7455 | 22.00 | 140.00 | |
| 3–4 years experience | 142 | 109.2113 | 17.05387 | 1.43113 | 106.3820 | 112.0405 | 37.00 | 136.00 | |
| 5+ years' experience | 104 | 114.0385 | 14.86961 | 1.45809 | 111.1467 | 116.9302 | 61.00 | 136.00 | |
| Total | 396 | 102.8157 | 25.33919 | 1.27334 | 100.3123 | 105.3190 | 21.00 | 140.00 | |
| Knowledge Dynamics | No experience | 51 | 39.7843 | 16.24969 | 2.27541 | 35.2140 | 44.3546 | 9.00 | 63.00 |
| 1–2 years experience | 99 | 46.2626 | 11.04313 | 1.10988 | 44.0601 | 48.4651 | 20.00 | 62.00 | |
| 3–4 years experience | 142 | 50.2676 | 7.50784 | 0.63004 | 49.0221 | 51.5132 | 19.00 | 63.00 | |
| 5+ years' experience | 104 | 52.1731 | 5.15477 | 0.50547 | 51.1706 | 53.1756 | 34.00 | 63.00 | |
| Total | 396 | 48.4167 | 10.31801 | 0.51850 | 47.3973 | 49.4360 | 9.00 | 63.00 | |
| Multicultural Leadership | No experience | 51 | 51.2549 | 19.46982 | 2.72632 | 45.7789 | 56.7309 | 12.00 | 78.00 |
| 1–2 years experience | 99 | 63.1010 | 13.91629 | 1.39864 | 60.3255 | 65.8766 | 30.00 | 84.00 | |
| 3–4 years experience | 142 | 66.4789 | 10.63696 | 0.89263 | 64.7142 | 68.2435 | 16.00 | 81.00 | |
| 5+ years' experience | 104 | 68.9038 | 6.48152 | 0.63557 | 67.6434 | 70.1643 | 48.00 | 83.00 | |
| Total | 396 | 64.3106 | 13.30392 | 0.66855 | 62.9963 | 65.6250 | 12.00 | 84.00 | |
| Organizational Context | No experience | 51 | 84.0588 | 29.80162 | 4.17306 | 75.6770 | 92.4407 | 18.00 | 125.00 |
| 1–2 years experience | 99 | 95.2727 | 19.69037 | 1.97896 | 91.3456 | 99.1999 | 40.00 | 126.00 | |
| 3–4 years experience | 142 | 98.4507 | 16.58187 | 1.39152 | 95.6998 | 101.2016 | 26.00 | 123.00 | |
| 5+ years' experience | 104 | 100.1250 | 11.60573 | 1.13804 | 97.8680 | 102.3820 | 48.00 | 125.00 | |
| Total | 396 | 96.2424 | 19.15749 | 0.96270 | 94.3498 | 98.1351 | 18.00 | 126.00 | |
Analysis of Variance (ANOVA) Explaining Experience in Managing Virtual Teams Differences Among Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of Squares | df | Mean Square | F | Sig. | ||
| Cultural Intelligence | Between groups | 79321.858 | 3 | 26440.619 | 59.466 | 0.000 |
| Within groups | 174297.685 | 392 | 444.637 | |||
| Total | 253619.543 | 395 | ||||
| Knowledge Dynamics | Between groups | 6213.735 | 3 | 2071.245 | 22.655 | 0.000 |
| Within groups | 35838.515 | 392 | 91.425 | |||
| Total | 42052.250 | 395 | ||||
| Multicultural Leadership | Between groups | 11699.644 | 3 | 3899.881 | 26.261 | 0.000 |
| Within groups | 58213.151 | 392 | 148.503 | |||
| Total | 69912.795 | 395 | ||||
| Organizational Context | Between groups | 9923.737 | 3 | 3307.912 | 9.602 | 0.000 |
| Within groups | 135044.990 | 392 | 344.503 | |||
| Total | 144968.727 | 395 | ||||
For instance, for Cultural Intelligence: the group with 5+ years of experience in managing virtual teams has the highest mean score of 114.04, followed by the group with 3–4 years of experience (109.21), the group with 1–2 years of experience (99.41), and the group with no experience (68.73). That is statistically significant at 0.001 level. For Knowledge Dynamics, the group with 5+ years of experience in managing virtual teams has the highest mean score of 52.17, followed by the group with 3–4 years of experience (50.27), the group with 1–2 years of experience (46.26), and the group with no experience (39.78). The overall mean score for all groups is 48.42. For Multicultural Leadership, the group with 5+ years of experience in managing virtual teams has the highest mean score of 68.90, followed by the group with 3–4 years of experience (66.48), the group with 1–2 years of experience (63.10), and the group with no experience (51.25). The overall mean score for all groups is 64.31. For Organizational Context, the group with 5+ years of experience in managing virtual teams has the highest mean score of 100.13, followed by the group with 3–4 years of experience (98.45), the group with 1–2 years of experience (95.27), and the group with no experience (84.06). The overall mean score for all groups is 96.24. The ANOVA table shows that Cultural Intelligence, Knowledge Dynamics, Multicultural Leadership, and Organizational Context all have significant F values and p-values, indicating significant differences between the mean scores of their experience in managing virtual teams.
