Dr Alex Zarifis

Universities, like many other organizations, are going through a disruptive digital transformation. The alure of AI and automation, allowing smarter, more responsive and scalable universities is clear. What is less clear is what a university will look like five years into this process. We identified four business models that can give leaders a destination for the digital transformation journey (Zarifis and Efthymiou 2022):

(1) This first education business models that is optimized for AI is to focus and disaggregate: In addition to the classroom the successful delivery of education requires a supply chain. With the changes in this supply chain caused by AI an educator can chose to focus on one part of this supply chain. They can focus on the part of the supply chain where their skills are best suited and build an ecosystem for the rest.

Figure 1. Four education business models that are optimised for AI (adapted from (Zarifis, Holland, and Milne 2019))

(2) The second model that is optimized for AI is to keep the existing education model and add AI: Despite the transformational nature of AI, some universities use AI to make the existing model more effective without changing it fundamentally. This may involve more back-office AI applications and less student facing applications.

(3) The third education model that is optimized for AI is an educator expanding beyond the current model: In this model the educator takes advantage of new opportunities emerging from AI and digital transformation. The educator keeps their existing part of the education supply chain, but they also add new processes that take advantage of AI to reach more students and more data.

(4) The fourth model that is optimized for AI is the model of a disruptor entering education: As technology plays a more decisive role in many areas, including education, tech savvy companies can use their advanced systems and existing user base and add other new services. Education can be added as a new feature to a platform in a similar way that banking and insurance services have been added.

The four models presented give a strategic direction and make it easier for the leader of the digital transformation to communicate it. The leader of digital transformation will have to make many choices along this journey, so it is important that all the decisions are compatible with the chosen education business model.

References

Zarifis A. & Efthymiou L. (2022) ‘The four business models for AI adoption in education: Giving leaders a destination for the digital transformation journey’, IEEE Global Engineering Education Conference (EDUCON), pp.1866-1870. Available from: https://doi.org/10.1109/EDUCON52537.2022.9766687

Zarifis A., Holland C.P. & Milne A. (2019) ‘Evaluating the impact of AI on insurance: The four emerging AI and data driven business models’, Emerald Open Research, pp.1-17. Available from (open access): https://emeraldopenresearch.com/articles/1-15/

Dr Alex Zarifis

Ransomware attacks are not a new phenomenon, but their effectiveness has increased causing far reaching consequences that are not fully understood. The ability to disrupt core services, the global reach, extended duration, and the repetition of these attacks has increased their ability to harm an organization.

One aspect that needs to be understood better is the effect on the consumer. The consumer in the current environment, is exposed to new technologies that they are considering to adopt, but they also have strong habits of using existing systems. Their habits have developed over time, with their trust increasing in the organization in contact directly, and the institutions supporting it. The consumer now shares a significant amount of personal information with the systems they have a habit of using. These repeated positive experiences create an inertia that is hard for the consumer to move out of. This research explores whether the global, extended, and repeated ransomware attacks reduce the trust and inertia sufficiently to change long held habits in using information systems. The model developed captures the cumulative effect of this form of attack and evaluates if it is sufficiently harmful to overcome the e-loyalty and inertia built over time.

Figure 1. The steps of a typical ransomware attack

This research combines studies on inertia and resistance to switching systems with a more comprehensive set of variables that cover the current e-commerce status quo. Personal information disclosure is included along with inertia and trust as it is now integral to e-commerce functioning effectively.

As you can see in the figure the model covers the 7 factors that influence the consumer’s decision to stop using an organization’s system because of a ransomware attack. The factors are in two groups. The first group is the ransomware attack that includes the (1) ransomware attack effect, (2) duration and (3) repetition. The second group is the E-commerce environment status quo which includes (4) inertia, (5) institutional trust, (6) organizational trust and (7) information privacy.

Figure 2.  Research model: The impact of ransomware attacks on the consumer’s intentions

The implications of this research are both theoretic and practical. The theoretic contribution is highlighting the importance of this issue to Information Systems and business theory. This is not just a computer science and cybersecurity issue. We also linked the ransomware literature to user inertia in the model.

There are three practical implications: Firstly, by understanding the impact on the consumer better we can develop a better strategy to reduce the effectiveness of ransomware attacks. Secondly, processes can be created to manage such disasters as they are happening and maintain a positive relationship with the consumer. Lastly, the organizations can develop a buffer of goodwill and e-loyalty that would absorb the negative impact on the consumer from an attack and stop them reaching the point where they decide to switch system.

Dr Alex Zarifis presenting research on ransomware

References

Zarifis A., Cheng X., Jayawickrama U. & Corsi S. (2022) ‘Can Global, Extended and Repeated Ransomware Attacks Overcome the User’s Status Quo Bias and Cause a Switch of System?’, International Journal of Information Systems in the Service Sector (IJISSS), vol.14, iss.1, pp.1-16. Available from (open access): https://doi.org/10.4018/IJISSS.289219

Zarifis A. & Cheng X. (2018) ‘The Impact of Extended Global Ransomware Attacks on Trust: How the Attacker’s Competence and Institutional Trust Influence the Decision to Pay’, Proceedings of the Americas Conference on Information Systems (AMCIS), pp.2-11. Available from: https://aisel.aisnet.org/amcis2018/Security/Presentations/31/