Journal of Marketing Theory and Practice

Technology can deliver a competitive edge for companies (e.g., Grewal et al., 2020; Manis & Madhavaram 2023; Mishra et al., 2022). Many companies have embraced the technology that unlocks the power of big data and analytics. The use of advanced analytics is now pervasive across industries and functional areas. Technology is facilitating cutting-edge, strategic decision-making in healthcare, automotive manufacturing, retail, advertising, construction, government, and more. Regardless of the industry, marketing is undeniably one of the functions experiencing the most significant impact from these technologies.

As the application of tools and techniques has increased, however, so have ethical challenges. It has been suggested that companies who capitalize on advanced analytics will reap significant benefits, but are they putting development speed before ethical consideration? Companies seem caught off guard; focusing on advanced technology to achieve successful results but unprepared to address ethical implications. Ethics is often an afterthought, induced by a lapse in decision-making. In essence, rather than addressing potential issues proactively, companies spend much time in a reactive position resolving concerns. Identifying ethical issues and frameworks to manage ethics is important in addressing potential misconduct.

The current public discussion is fueling companies, customers, and society to acknowledge that there should be a focus on the responsible use of big data and advanced analytics. Nonetheless, developing steps to pursue responsible big data and analytics is proving challenging. Companies are disbanding ethics boards and terminating ethicists due to the inability to come together as a cohesive group (e.g., De Vynck & Oremus 2023). The current conversation around ethical implications appears delayed after years of emphasis on the application and potential benefits. The impact on society is not understood, and there is no regulation to address these issues.

Academic research on ethical implications surrounding big data and analytics has followed a similar pattern. The intersection of big data, analytics, and ethics is fragmented and understudied. While there have been calls to increase research in this area (e.g., Ferrell & Ferrell 2021), there has been research in the area of analytics and more recently advanced analytics. However, many articles are conceptual/theoretical, limited to developing general frameworks of advanced technology in marketing (e.g., Davenport et al., 2020; Huang & Rust 2021), or the successful applications of advanced analytics (e.g., Hermann 2022; Kelly, 2022; Manis & Madhavaram 2023; Rodgers & Nguyen 2022). There have been very few articles on preventing or mitigating unethical outcomes or empirical articles to advance knowledge on processes and directions for successfully managing ethics (e.g., Behera et al., 2022; van Giffen et al., 2022; Hermann 2022; Kelley 2022; Vlačić et al., 2021).

Given the relevance and Gartner’s prediction that “by 2025, 70% of enterprise CMOs will identify accountability for ethical AI in marketing among their top concerns,” it is critical to begin exploring the intersection of big data, analytics, and ethics. Ethics should be woven into the strategic design of the initial adoption of big data and analytics, as well as the continued application. In this time of high-speed development, how do we produce responsible outcomes that weigh the benefits and risks to society?

As you pursue this research topic, here are some research directions to consider:

Embedded in Culture/Governance

• How can companies evaluate compliance with ethical guidelines, and address any potential risks or issues that arise?
• How can companies use audits of data collection, usage, and analytics practices to increase ethical behavior?
• What are the structures in culture/governance to establish ethical conduct?
• What are potential ethical frameworks to manage analytics and AI to protect consumers?

Use/Application in Isolation from other Ethical Decisions

• Explore the ethical challenges associated with targeted marketing campaigns that rely heavily on big data and analytics.
• Investigate consumer attitudes and perceptions regarding the collection and use of personal data in marketing.
• Identify strategies to address privacy issues while leveraging big data and analytics.
• Is task type or application an important consideration when considering ethical regulations?
• How do less regulated versus more regulated industries perform in preventing unethical AI? Are there different processes in place?

Training/Communication

• How can companies provide relevant training on privacy regulations, data handling practices, and bias mitigation techniques?
• How can organizational ethics initiatives be synchronized with technology decisions?

Algorithmic Bias/Mitigation Techniques

• Assess the fairness, transparency, and potential biases that arise from data-driven targeting methods.
• Analyze the potential biases embedded in algorithms used for customer segmentation and decision-making in marketing.
• Explore ways to mitigate bias and promote fairness in data-driven marketing practices.
• What is the role of analysts and developers in incorporating ethics into technology implementation?

Organizational Readiness

• How is big data and artificial intelligence used to determine which products or services to offer in each market?

Corporate/Government/Global Regulations

• How transparent do consumers expect companies to be in their use of big data and analytics?
• What measures or regulations need to be required to prevent data breaches and unauthorized access to personal information?
• What laws and regulations do consumers want in place to protect consumers' rights and privacy in the context of big data and analytics?
• How is data privacy incorporated into all stages of decision-making as it relates to big data, analytics, and AI?

Sales-Related Topics:

• What is the impact of managing sales employees via metrics on well-being?
• When managing customer relationships and their data – is there a tradeoff in human vs. data predictions over time?
• Explore data-driven customer segmenting.
• What is the impact on customer perceptions of the overuse of sales automation tools?
• What is the perception of metrics-driven customer health scoring? Who and how does this impact?
• Explore the use and implications of big data and sales pipeline forecasting.

 

This special issue focuses on advanced analytics (e.g., artificial intelligence) and the ethical implications for companies, customers, and society. Interdisciplinary approaches and submissions from authors representing different disciplines are welcome. Submissions should be original research that has not been published or submitted elsewhere.

 

References

Behera, R. K., Bala, P. K., Rana, N. P., & Kizgin, H. (2022). Cognitive computing based ethical principles for improving organisational reputation: A B2B digital marketing perspective. Journal of Business Research, 141, 685-701.

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.

De Vynck, G. & Oremus, W. (2023). As AI booms, tech firms are laying off their ethicists. The Washington Post. https://www.washingtonpost.com/technology/2023/03/30/tech-companies-cut-ai-ethics/.

Ferrell, O. C., & Ferrell, L. (2021). New directions for marketing ethics and social responsibility research. Journal of Marketing Theory and Practice, 29(1), 13-22.

Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing: A multidisciplinary perspective. Journal of the Academy of Marketing Science, 48, 1-8.

Hermann, E. (2022). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics, 179(1), 43-61.

Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.

Kelley, S. (2022). Employee perceptions of the effective adoption of AI principles. Journal of Business Ethics, 178(4), 871-893.

Manis, K. T., & Madhavaram, S. (2023). AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues. Journal of Business Research, 157, 113485.

Mishra, S., Ewing, M. T., & Cooper, H. B. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 1-22.

Rodgers, W., & Nguyen, T. (2022). Advertising benefits from ethical artificial intelligence algorithmic purchase decision pathways. Journal of Business Ethics, 178(4), 1043-1061.

van Giffen, B., Herhausen, D., & Fahse, T. (2022). Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods. Journal of Business Research, 144, 93-106.

Vlačić, B., Corbo, L., e Silva, S. C., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187-203.

 

This special issue focuses on advanced analytics (e.g., artificial intelligence) and the ethical implications for companies, customers, and society. Interdisciplinary approaches and submissions from authors representing different disciplines are welcome. Submissions should be original research that has not been published or submitted elsewhere. Please select the special issue title Finding the balance between big data, analytics, and ethics when submitting your manuscript.

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