Ethical Considerations and Possible Research Questions for the CEOs and Employees

Section 1: Ethical Considerations

Ethical considerations shall be important during investigating problems inherent in nurturing a data-driven culture in organizations because the research shall target Chief Executive Officers (CEOs), and employees of different organizations. The ethics section of the dissertation discusses the ethical principles specific to the study in the light of observing the simple rules of research practice as enshrined in honesty, openness, and respect. Consequently, ethical issues particular to the research problem include obtaining informed consent from the participants, maintaining the researchers' independence and addressing arising conflicts of interests associated to the research, conserving the anonymity and confidentiality of both participants and/or data collection and presentation issues, and conserving integrity during results analysis and presentation, throughout the research process (Walliman, 2017).

Obtaining Informed Consent from the C.E.Os and Employees

The CEOs and respective employees of the target organizations shall be entitled to a succinct explanation of the purpose of the research, and that their participation would add knowledge to understanding the problems encountered in cultivating data-driven organizations. Furthermore, informed consent would entail information of the participants' necessity to take part in the research process by volunteering, and that their withdrawal from the research shall be acceptable at any time without giving reasons for their actions. Therefore, participants would sign a consent form to indicate their understanding and agreement of the research purpose as a participation condition (Grady, 2015).

Conservation of Integrity during Analysis and Presentation of Data

Data analysis and presentation would be critical to the justification of cultivating a data-driven culture in organizations vis-a-vis Big Data (BD) and Artificial Intelligence (AI). The research would lead to the collection of potentially complex data from both primary and secondary sources, implying that subsequent analysis and presentation would be strenuous. For instance, large volumes of data concerning the integration of AI and BD would require in-depth analysis and presentation (Wessels, Visagie & Van Heerdem, 2015). Therefore, there shall be no manipulation of results, however insignificant, during analysis and presentation.

Anonymity and Confidentiality

Anonymity and confidentiality of participants, data, and results dissemination would be critical to the success of the research. The research would involve potential access to sensitive BD and AI strategic information through interviews and questionnaires. Some organizations and participants may treat such information with confidentiality, rendering it unstable and inaccessible to industrial competitors (Magnani et al., 2018). Therefore, no personal information or sensitive organizational secrets would be publicized or stored, and that the researcher shall maintain data anonymity and confidentiality in the research process and dissertation.

Addressing Arising Conflicts of Interests and Researchers' Independence

Conflicts of interests and independence of researchers cover issues related to resources or support advanced to the researcher, perceptions of other researchers and the media about the entire research process, and the commercial interests of the researcher and others. First, being open and explicit in the dissertation about the support and resources received for the research would address the potential conflicts of interests' ethical part of the research. Second, as organizations hunger for more information about the power of BD and AI, research information should be succinct in the light of researcher's independence. The media and other researchers could discredit the results if they have reason to doubt the central researcher's results (Harris & Atkinson, 2015). Possibly, bias in the research process would likely be the focus of the media and the research fraternity, leading to the invalidity of the research process. In light of this, the researchers would exercise independence, regardless of any stakeholders' ill interests for all stages of the research, from literature review to the final discussion of the analyzed results.

Possible Sources of Harm

Any stakeholder is susceptible to a research process having risks, especially where scientific experiments involve humans. Additionally, harm in research is not only physical but also mental or emotional. Investigating the problems of adapting data-driven cultures by organizations has no direct physical risks, but both emotional, psychological, and financial risks are possible to occur. Firstly, unethically sharing organizational data related to usage of Big Data and AI from one organization could potentially cause economic harm should the information fall into the competitor's hands (Harris & Atkinson, 2015). Additionally, participants might be subjected to both emotional and mental damage should they feel exposed in by the research process. Resolutely, the research process would preserve both the confidentiality and anonymity of the CEOs and employees and data from organizations.

Section 2: Possible Research Questions

Interview Questions for CEOs

For questions 1 to 5, choose No or Yes.

1. Do you understand the meaning of the term "Data-driven" culture? {Yes} {No}

2. If the answer to question 1 above is "Yes," do you know the features of an effective data-driven culture and how to enhance one in your organization? {Yes} {No}

3. If your answer to question 1 is "No," do you agree that you lack abilities to apply a data-driven culture in your organization? {Yes} {No}

4. Are you familiar with the definition of Big Data and Artificial Intelligence? {Yes} {No}

5. As a CEO of your organization, are your informed decisions guided by the use of Big Data and Artificial Intelligence concepts? {Yes} {No}

For questions 6 to 10, choose the appropriate expression

6. Do you agree that CEOs require the ability to apply self-reflection mechanisms to cultivate a data-driven culture?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

7. Real-time application of data-driven cultural concepts is necessary for effective organizational performance.

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

8. Is motivation important for adapting a data-driven culture in an organization?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

9. Does belief impact ayour leadership capability to adapt a data-driven organizational culture?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

10. How often do you attribute your organizational performance to the application of real-time Big Data and Artificial intelligence concepts?

• Very often
• Often
• Less often
• Never

11. Do you believe a data-driven organizational culture affects industrial leadership? {Yes} {No}

12. Is motivation necessary for cultivating a data-driven organizational culture? {Yes} {No}

13. Do you agree that high-performing industrial leaders use Big Data and Artificial Intelligence? {Yes} {No}

14. How does motivation affect your leadership ability to embrace a data-driven cultural revolution?

• Strongly
• Weakly
• Am not sure

15. Do you motivationally orient organizational goals through the use of Big Data and Artificial intelligence? {Yes} {No}

16. Is industrial leadership competitively dependent on your motivational levels? {Yes} {No}

17. Do you believe self-efficacy and CEO leadership depends on the success of incorporating Big Data and Artificial Intelligence in organizational culture?

• Strongly believe
• Believe
• Disbelief
• Strongly disbelief

18. Do CEOs need to see the value of a data-driven cultural revolution to embrace performance outcomes? {Yes} {No}

19. Overall organizational synergies have their roots to improved goal orientation and motivational performance, do you agree? {Yes} {No}

20. Adaptive data-driven cultural revolutions strategically position organizations industrially, do you agree? {Yes} {No}

Interview Questions for Employees

1. Do you understand the meaning of data-driven organizational culture? {Yes} {No}

2. Can you differentiate between Big Data and Artificial Intelligence? {Yes} {No}

3. How would you rate the importance of Big Data and Artificial Intelligence to organizational performance?

• Very important
• Important
• Less important
• Am not sure

4. Do you agree that leadership style affects the use of Big Data and Artificial Intelligence in your organization? [Yes] [No]

5. Is a long-term commitment to a data-driven culture dependent on the top management? [Yes] [No]

6. Are resource constraints responsible for lack data-driven decision-making process in the organization [Yes] [No]

7. Is the transformation to a data-driven cultural organization dependent on accountability in the overall organization structure? [Yes] [No]

8. Is your organization's vision integrated with Big Data and Artificial Intelligence concepts? [Yes] [No]

9. Does the performance of your organization reflect a data-driven revolution [Yes] [No]

10. Do you agree that your organization's top leadership fully embraces a data-driven culture?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

11. Do you need the training to embrace a data-driven culture in your organizations? [Yes] [No]

12. Do you know of any rival organizations which have adapted Big Data and Artificial Intelligence? [Yes] [No]

13. Do you agree that your organization is accountable to a data-driven cultural transformation?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

14. How often do you train for data-data driven transformational needs?

• Very often
• Often
• Less often
• Never

15. Are you motivated by your top management to embrace Big Data and Artificial intelligence in decision-making? [Yes] [No]

16. Does your organization orient long-term goals to Big Data and Artificial Intelligence? [Yes] [No]

17. Do you agree that your organization prioritizes training for transformation to the data-driven organizational culture?

• Strongly disagree
• Disagree
• Agree
• Strongly disagree

18. Are your current skills necessary for the data-driven cultural transformation? [Yes] [No]

19. Would consider your organization to be an industrial leader because of its data-driven organizational culture? [Yes] [No]

20. How would you rate your organization concerning Big Data and Artificial Intelligence usage?

• Very highly
• Highly
• Lowly
• Very lowly

References

Grady, C. (2015). Enduring and emerging challenges of informed consent. New England Journal of Medicine, 372(9), 855-862.

Harriss, D. J., & Atkinson, G. (2015). Ethical standards in sport and exercise science research: 2016 update. Int J Sports Med, 36(14), 1121-1124.

Magnani, A., D'Angelo, G., Ferretti, S., & Marzolla, M. (2018). Anonymity and Confidentiality in Secure Distributed Simulation. arXiv preprint arXiv:1808.02231.

Walliman, N. (2017). Research methods: The basics. Routledge.

Wessels, J. S., Visagie, R. G., & Van Heerden, M. (2015). Fostering Research Integrity through Institutional Policies: The Case of a Selected Institution of Higher Education.