A Non-Fungible Token, usually referred to by its acronym NFT, uses technology that involves data on a blockchain that cannot be changed after they have been added. Therefore, while they share similar blockchain technology with cryptocurrencies, the functionality is different.
NFT’s functionality enables them to be used to prove ownership of an intangible-digital, or tangible-physical, asset, and the associated rights the owner has.
The most popular practical application of NFTs for digital assets is proving ownership of digital art, virtual items in computer games, and music.
The unique features of NFTs are becoming increasingly appealing as we spend more of our time online. Despite this increased popularity there is a lack of clarity over the final form this digital asset will take. The purchasing process in particular needs to be clarified.
This research developed a model of the purchasing process of NFTs and the role of trust in this process. The model identified that the purchasing process of NFTs has four stages and each stage requires trust.
You see here in the figure, the four stages in the purchasing process on the left, and the trust required in each of these stages along the center. Finally, on the right you see that trust in all four stages leads to trust in an NFT purchase.

Figure 1. Model of consumer trust at each stage of the NFT purchasing process

The four stages of the purchase are: First, set up a cryptocurrency wallet to pay for the NFT, and to be able to receive it. Second purchase cryptocurrency with the cryptocurrency wallet, third use the cryptocurrency wallet to pay for an NFT on an NFT marketplace and finally, there is the fourth, after sales service that may involve returns, or some other form of support.
The model that is supported by our analysis identified four stages to trust: First trust in the cryptocurrency wallet, second trust in the cryptocurrency purchase, third trust in the NFT marketplace, and fourth trust in after-sales services and resolving disputes.

Reference:
Zarifis, A. & Castro, L.A. (2022) ‘The NFT purchasing process and the challenges to trust at each stage’, Sustainability, vol.14, no.24:16482, pp.1-13. Available from (open access): https://doi.org/10.3390/su142416482

Dr Alex Zarifis

This research explores the beliefs of a consumer from outside China, that is buying Chinese products. The findings highlight the importance of the cues of the country-of-origin, on foreign consumers’ intention to purchase Chinese products. The results also enhance our understanding of consumers’ beliefs on purchasing foreign products in general (Bao et al., 2022).

There are three practical implications:

Firstly, this study highlights several significant factors that may enable e-commerce managers, to strengthen consumers’ intention to purchase Chinese products. Cross-border e-commerce platforms should improve product quality, brand image, control cost and follow international business norms, as these act as a guarantee for foreign consumers.

Figure 1. Impacts of country-of-origin image on product evaluation and purchase intention

Secondly, cross-border e-commerce platforms should provide different advertising or marketing strategies for products with different levels of involvement. For example, for low-involvement products, managers should put more advertising effort into the product itself, and emphasize the quality of the product, and the high speed of delivery. For high-involvement products, marketing should emphasize the image of the product’s country of origin.

Thirdly, consumers’ nowadays may perceive more external-product cues, instead of the product itself. Cross-border e-commerce platform managers should be aware that the image of the product’s country of origin, heavily influences the consumers’ perceived product value. Nevertheless, they should also pay attention to the cross-border e-commerce company’s social norms, and develop effective policies to maintain consumers’ interests and rights.

Reference

Bao Y., Cheng X. & Zarifis A. (2022) ‘Exploring the impact of country-of-origin image and purchase intention in cross-border e-commerce’, Journal of Global Information Management, vol.30, iss.2, pp.1-20. Available from (open access): https://doi.org/10.4018/JGIM.20220301.oa7

Dr Alex Zarifis
There has been rapid development in Cross-Border E-Commerce (CBEC) in recent years, and it is strengthening the global economy. However, compared to other trade mechanisms, the mechanism of CBEC is more complex. It appears that staff with special talents are needed to start a business trading across borders. Research has presented some solutions for the challenges of cross-border e-commerce from the perspective of the enterprise. However, not enough is known about the cross-border e-commerce talents requirements, and how to train people to develop them.

Requirements of CBEC talents
We found four core the requirements of Cross-Border E-Commerce talents (Cheng et al., 2019): (1) Firstly, having business and marketing knowledge is critical to Cross-Border E-Commerce talents. Both theoretical and practical knowledge are important components in business and marketing knowledge. (2) Secondly, technical skills for trading online is necessary. For example, dealing with all the problems in the process of online trading is important. (3) Thirdly, it’s common to handle difficult situations when business across borders, hence analytical ability is needed for them to solve these problems. (4) Last but not least, all these skills we mentioned are not independent of having practical ability in business, which is the core the requirement.
In summary, business and marketing knowledge, technical skills, analytical ability and practical ability in business were found to be the four core requirements of CBEC talents.

Figure 1. Training model for people working in cross-border e-commerce

Training model for CBEC talents
After finding the four core requirements, we analyzed several teaching methods. We then chose Problem-Based Learning (PBL), which typically involves learning based on solving real problems. We applied WeChat in the training model, so the real work environment is replicated more closely. Writing a business plan was also applied in the training model as the way of practicing practical skills. The problem oriented training model encourages discussions and learning new knowledge. By successfully applying the model in teaching, this research provides a new direction to cultivate the CBEC talents.

Reference
Cheng X., Su L. & Zarifis A. (2019) ‘Designing a talents training model for cross-border e-commerce: A mixed approach of problem-based learning with social media’, Electronic Commerce Research, vol.19, iss.4, pp.801-822. Available from: https://doi.org/10.1007/s10660-019-09341-y

Dr Alex Zarifis

Online learning is an extremely important part of education. By learning from the experience of COVID-19, we can have engaging and rewarding online learning, and avoid being disrupted by new natural disasters.

An individual’s ability to use their working memory to process information, and make decisions, is affected by the cognitive load they perceive. Cognitive load refers to the total amount of mental effort being used in the working memory.

Adopting the Cognitive Load Theory, this study mainly focuses on the antecedents of cognitive load generated by external factors. It explores the internal influence mechanism of cognitive load on user satisfaction, combined with the theory of expectation confirmation. At the same time, we also explore whether the level of cognitive ability will affect user satisfaction. Based on this research background, this study explores three research questions (Zuo et al. 2021).

(1) The first question explored is: In the context of a pandemic, what are the factors that affect cognitive load? We found that the influencing factors of cognitive load are very strongly related to the satisfaction with the platform. They can be divided firstly into typical factors that are important when using technology, and secondly specific factors that are caused by a pandemic. The typical factors that are important when using technology include social factors, perceived autonomy, content quality, and self-efficacy.

Figure 1. Online learner satisfaction model

(2) The second question explored is: How does cognitive load affect the satisfaction of online learning users, and what is its internal influence mechanism? We found that the antecedents of satisfaction which are emphasised by most of the learners interviewed, can be summed up in two constructs: One of the two is expectation confirmation which has more to do with the information system, and the other is perceived usefulness that is more related with what is being learned.

(3) The third and final question explored is: Will an individual with a different cognitive ability, perceive different levels of cognitive load, for the same online learning task? It appears that this is the case, but the cognitive load perceived by people with different educational levels may be a research gap that needs to be explored further.

The model of online learner satisfaction put forward here, can help optimize satisfaction, and help us be prepared to overcome challenges like pandemics.

Reference

Zuo Y., Cheng X., Bao Y. & Zarifis A. (2021) ‘Investigating user satisfaction of university online learning courses during the COVID-19 epidemic period’, Proceedings of the 54th Hawaii International Conference on System Sciences, pp.1139–1148. Available from: https://doi.org/10.24251/HICSS.2021.139

New research!

Central Bank Digital Currencies (CBDC) are digital money issued, and backed, by a central bank. Consumer trust can encourage or discourage the adoption of this currency, which is also a payment system and a technology. CBDCs are an important part of the new Fintech solutions disrupting finance, but also more generally society. This research attempts to understand consumer trust in CBDCs so that the development and adoption stages are more effective, and satisfying, for all the stakeholders. This research verified the importance of trust in CBDC adoption, and developed a model of how trust in a CBDC is built (Zarifis & Cheng 2023).

Figure 1. Model of how trust in a Central Bank Digital Currencies (CBDC) is built in six ways

There are six ways to build trust in CBDCs. These are: (1) Trust in government and central bank issuing the CBDC, (2) expressed guarantees for the user, (3) the positive reputation of existing CBDCs active elsewhere, (4) the automation and reduced human involvement achieved by a CBDC technology, (5) the trust building functionality of a CBDC wallet app, and (6) privacy features of the CBDC wallet app and back-end processes such as anonymity. The first three trust building methods relate to trust in the institutions involved, while the final three relate to trust in the technology used. Trust in the technology is like the walls of a new building and institutional trust is like the buttresses that support it.

This research has practical implications for the various stakeholders involved in implementing and operating a CBDC but also the stakeholders in the ecosystem using CBDCs. The stakeholders involved in delivering and operating CBDCs such as governments, central banks, regulators, retail banks and technology providers can apply the six trust building approaches so that the consumer trusts a CBDC and adopts it.

Dr Alex Zarifis

Reference

Zarifis A. & Cheng X. (2023) ‘The six ways to build trust and reduce privacy concern in a Central Bank Digital Currency (CBDC)’. In Zarifis A., Ktoridou D., Efthymiou L. & Cheng X. (ed.) Business digital transformation: Selected cases from industry leaders, London: Palgrave Macmillan, pp.115-138. https://doi.org/10.1007/978-3-031-33665-2_6

New research!

Fintech is changing the services to consumers, and their relationship with the organizations that offer them. This change is neither top-down nor bottom-up, but is being driven by many different stakeholders in many different parts of the world, making it hard to predict its final form. This research identifies five business models of Fintech that are ideal for AI adoption, growth and building trust (Zarifis & Cheng, 2023).

The five models of Fintech are (a) an existing financial organization disaggregating and focusing on one part of the supply chain, (b) an existing financial organization utilizing AI in the current processes without changing the business model, (c) an existing financial organization, an incumbent, extending their model to utilize AI and access new customers and data, (d) a startup finance disruptor only getting involved in finance, and finally (e) a tech company disruptor adding finance to their portfolio of services.

Figure 1. The five Fintech business models that are optimised for AI

The five Fintech business models give an organization five proven routes to AI adoption and growth. Trust is not always built at the same point in the value chain, or by the same type of organization. The trust building should usually happen where the customers are attracted and on-boarded. This means that while a traditional financial organization must build trust in their financial services, a tech focused organization builds trust when the customers are attracted to other services.

This research also finds support that for all Fintech models the way trust is built, should be part of the business model. Trust is often not covered at the level of the business model and left to operation managers to handle, but for the complex ad-hoc relationships in Fintech ecosystems this should be resolved before Fintech companies start trying to interlink their processes.

Alex Zarifis

Reference

Zarifis A. & Cheng X. (2023) ‘The five emerging business models of Fintech for AI adoption, growth and building trust’. In Zarifis A., Ktoridou D., Efthymiou L. & Cheng X. (ed.) Business digital transformation: Selected cases from industry leaders, London: Palgrave Macmillan, pp.73-97. https://doi.org/10.1007/978-3-031-33665-2_4

New research!

Digital transformation is being driven by AI that is acting as a catalyst for business advancement. We looked at eight cases of digital transformation and found nine key themes. We looked at cases of digital transformation in finance, tourism, transport, entertainment and social innovation (Zarifis et al. 2023).

Figure 1. The tightly coiled ‘spring’ of digital transformation leader’s innovation, and the followers

The first of the nine main themes identified here is: (1) Digital transformation leaders will constantly innovate, while digital transformation laggards will have a stop-start approach. Digital transformation leaders will rapidly innovate going through regular iterative evolutions of their technologies, moving through repeated cycles of agile developments metaphorically forming a ‘spring’. New innovations and in-house skills are built up in this process of constant innovation. Continuing with the metaphor this tightly coiled ‘spring’ will store ‘energy’ propelling the organization forward. Digital transformation laggards will have a stop-start approach copying certain solutions of the leaders but not keeping up. Metaphorically a far less tightly coiled ‘spring’.

The other eight themes identified are: (2) There are no simple answers, or a single way to go forward, with digital transformation. (3) Each sector of the economy has its own opportunities, challenges and must find its own path forward. (4) Changes in one sector of the economy, such as the financial sector, will send a ripple of change across other sectors of the economy. (5) Change needs a shared vision, and digital transformation needs leaders to create the shared vision. (6) Digital transformation needs trust and cooperation on every level: Teams, organizations, governments and super-organizations like the EU. (7) People will still have a role: Staff, customers and other stakeholders are still important. (8) There is a dark side of digital transformation that may have not been fully revealed to us yet. (9) Digital transformation should happen hand in hand with sustainability and resilience.

Those are the nine main themes of digital transformation identified based on the cases we looked at. A leader of digital transformation must disassemble the technology, processes, business models and strategies, involved and then put together their own collage of what they want to achieve, and their own montage of the journey there.

Dr Alex Zarifis

Reference

Zarifis A., Efthymiou L. & Cheng X. (2023) ‘Sustainable digital transformation in finance, tourism, transport, entertainment and social innovation’. In Zarifis A., Ktoridou D., Efthymiou L. & Cheng X. (ed.) Business digital transformation: Selected cases from industry leaders, London: Palgrave Macmillan, pp.1-16. https://doi.org/10.1007/978-3-031-33665-2_1

Mobile apps utilize the features of a mobile device to offer an ever-growing range of functionalities. These apps access our personal data, utilizing both the sensors on the device, and big data from several sources. Nowadays, Artificial Intelligence (AI) is enhancing the ability to utilize more data, and gain deeper insight. This increase in access and utilization of personal information offers benefits, but also challenges to trust. The reason we are re-evaluating trust in this scenario, is because we need to re-calibrate for the increasing role of AI.

This research explores the role of trust, from the consumer’s perspective, when purchasing mobile apps with enhanced AI. Models of trust from e-commerce are adapted to this specific context. The model developed was tested, and the results support it.

Figure 1. Consumer trust and privacy concerns in mobile apps with enhanced AI

The intention to use the mobile app is impacted by (1) propensity to trust, (2) institution-based trust, (3) trust in the mobile app, and (4) the perceived sensitivity of personal information, are found to impact

The first three of those four, are broken down further into their constituent parts. (1) Propensity to trust is based on a person’s (1a) trusting stance in general, and (1b) their general faith in technology. (2) Institution-based trust is strengthened firstly by (2a) structural assurance and (2b) situational normality. Structural assurance of the internet includes guarantees, regulation, promises and related laws. The users evaluation of situational normality can be formed by app reviews. Out of the whole model the institution based factors are the weakest.

Trust in the mobile app (3) is more complex, it is based on five variables. These are (3a) trust in vendor, (3b) trust in app functionality, (3c) trust in genuineness of app, (3d) how human the technology appears to be, and (3e) trust in personal data use.

Those are the main findings of this research. The model is helpful because it can guide the stakeholders involved in mobile apps in how to build trust. By using the model they can identify what they need to communicate better, and what they need to change in the apps, or somewhere else in the ecosystem.

Reference

Zarifis A. & Fu S. (2023) ‘Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence’, Digital, vol.3, no.4, pp.286-299. Available from (open access): https://doi.org/10.3390/digital3040018

#trust #information privacy #artificial intelligence #mobile commerce #mobile apps #big data

Dr Alex Zarifis

This report offers a balanced analysis of the opportunities, and challenges, caused by the many moving parts of the cryptoasset ecosystem in Latin America and the Caribbean. I am happy to have contributed to this as one of the co-authors. I found it particularly interesting how some countries want to lead in the adoption of cryptoassets while others want to be more cautious. The countries that lead believe in their ability to regulate cryptoassets and manage any risks that emerge. They want to have first mover advantage. Other countries do not believe being an early, enthusiastic, adopter is worth the risks, and prefer to wait until the industry and the regulation mature. Both approaches are valid, but in both strategies it is important to follow developments closely. This is where this report can be helpful in gaining insights into this sector’s development, market trends, challenges and opportunities, as well as regulatory and policy issues.

The cryptoasset sector has grown across Latin America and the Caribbean in recent years and this expansion has led to increased employment opportunities. Many cryptoasset firms are now full-service fintech providers. The regulatory views on digital assets have shifted, with around a third of public sector respondents being more positive towards cryptoassets. The private sector participants are also more positive now, and they collaborate more with regulators through innovation hubs and sandboxes. The private sector respondents also see growth opportunities in DeFi services and onboarding corporate clients.

However, there are also challenges to address with the most important one being the lack of regulatory clarity. Public sector respondents believe they need more expertise in cryptoassets.

Reference

Proskalovich R., Jack C., Zarifis A., Serralde D.M., Vershinina P., Naidoo S., Njoki D., Pernice I., Herrera D. & Sarmiento J. (2023) ‘Cryptoasset ecosystem in Latin America and the Caribbean’, University of Cambridge – Cambridge Center for Alternative Finance (CCAF). Available from: https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/crypotasset-ecosystem-in-latin-america-and-the-caribbean/

Dr Alex Zarifis

My new research developed a model of trust in making payments with the Ethereum (Zarifis, 2023). I published the first peer reviewed research on trust in payments with Bitcoin in 2014 (Zarifis et al. 2014), and I wanted to apply my experience from that to understanding the consumer’s perspective to making Ethereum payments.

Ethereum is being utilised in various ways, including smart contracts and payments. Despite some similarities with Bitcoin, Ethereum is a different technology, with different governance and support.

Ethereum payments require digital wallets and the process is different to paying in traditional fiat currencies like the Euro. When a person wants to take an action without controlling all the parameters, and some risk is unavoidable, trust is necessary.

Figure 1. Model of trust in making Ethereum payments, TRUSTEP

The model demystifies how trust is built in consumer payments with Ethereum. The model starts with the individual’s predisposition and then covers the factors from the specific context of Ethereum payments. From the person’s individual characteristics, their willingness to innovate in finance and technology have a role. There are then five variables from the contexts: Adoption and reputation, stable value and low transaction fees, effective regulation, payment intermediaries and trust in the seller. The personal and contextual factors together influence trust in the Ethereum payment process and making a payment with Ether.

While the model has similarities to previous models of trust, such as the role of each individual’s psychological predisposition and the role of reputation, the role of institutions such as regulators and the importance of trust in the retailer, the distinct characteristics of Ethereum also play a role. In fact, the factors related to the distinct characteristics of Ethereum have the strongest support based on the average of the responses. This research can be added to a growing body of research in trust that illustrates how users’ beliefs in each cryptocurrency need to be explored separately.

Furthermore, the role of the organizations involved in the payment process are shown. While trust in the retailer is usually a factor in retail payments, the regulators and payment intermediaries are not always a significant factor, so it is a useful contribution to show that this is the case here.

That is what I want to share with you here. If you have experiences related to what I am talking about, please let me know, I would love to hear from you.

Reference

Zarifis A. (2023) ‘A Model of Trust in Ethereum Token ‘Ether’ Payments, TRUSTEP’, Businesses, vol.3, no. 4: pp.534-547. Available from (open access): https://doi.org/10.3390/businesses3040033

Zarifis A., Efthymiou L., Cheng X. & Demetriou S. (2014) ‘Consumer trust in digital currency enabled transactions’, Lecture Notes in Business Information Processing-Springer, vol.183, pp.241-254. Available from: http://link.springer.com/chapter/10.1007/978-3-319-11460-6_21#

Please sign this petition for the editor to credit me for my work, by replying to this post or sending me a private message. This is a short overview of what happened to the best of my understanding:

I was given the task by a lecturer of UCLAN I had worked with in the past (I hired her for her first academic job) to turn a good student dissertation into a research paper. I am often given the task of turning research into a paper because my first language is English and I have a decent record at getting papers published.

It took many hours to turn it into a paper, I identified the most valuable parts and wrote several sections of the final paper. For example I strengthened the link to trust which is my specialist subject. The paper was published in a journal in 2018. The first author credited on the paper is the student, then the two supervisors from UCLAN and lastly me. I have an email from one of the co-authors from UCLAN expressing her gratitude for the publication and stating that based on the work I did, my name should not have been last on the list but further up.

In 2020 I came across the same paper published in a different journal, without my name as co-author. I contacted the editor and told him the paper is already published and not retracted when it was published a second time. Based on the ethics guidelines of the journal there were two options available to the editor as I understand it:

a) Based on the ethics guidelines of the journal, credit the author that was left out as he has the best evidence imaginable that he is a co-author, and the corresponding author belatedly acknowledged he should be credited. (I also have several emails, drafts etc. as evidence)

b) Based on the ethics guidelines of the journal, retract the paper the editor published in his journal because it was published before and not retracted.

He did not act on the evidence that the paper is already published, waited for the corresponding author to retract the original paper and then said he could not take into account the original version, despite it being published at the time it was published again, and only retracted when the co-author left out, used it as evidence. (the original paper has already been cited several times and is still widely available)

I contacted the corresponding author from UCLAN and he said in writing (I have the email) that he would ask the editor to add me and if the editor did not agree he would add me as co-author on another paper to make up for the mistake. Neither happened.

I have several emails, drafts and a published paper, that was not retracted when it was published a second time, that has been cited several times, proving irrefutably I am a co-author of that paper.

Neither the editor, the publisher or the co-authors have taken action to correct this. The action that has been taken so far is for some people to contact my work to try to make my life harder.

Please sign this petition for the editor to credit me for my work. You can sign the petition by replying to this article or sending me a private message with your name and if you want your affiliation.

Evidence

I provide here a small subset of the evidence, the papers that cite the original publication with me as co-author. If anyone wants to see the emails that prove everything I have said, I can show them.

Here is the citation of the original paper:

Michael P., Dimitriou S., Glyptis L. & Zarifis A. (2018) ‘e-Government implementation challenges in developing countries: The project manager’s perspective’, International Journal of Public Administration and Management Research (IJPAMR), vol.4, no.3, pp.1-17. Available from: http://www.rcmss.com/index.php/ijpamr

The original publication was published and not retracted for over two years before this:

‘Glyptis L., Christofi M., Vrontis D., Del Giudice M., Dimitriou S, Michael P. (2020) ‘E-Government implementation challenges in small countries: The project manager’s perspective’, Technological Forecasting and Social Change’

Here are some people that cited the original paper with me as a co-author:

An e-government implementation framework: A developing country case study A Apleni, H Smuts – Responsible Design, Implementation and Use of …, 2020 – Springer The implementation of Information and Communication Technology (ICT) is seen globally as a means to efficient and effective delivery of business and organisational mandates …

The role of political will in enhancing e-government: An empirical case in Indonesia SY Defitri – Probl. Perspect. Manag, 2022 – businessperspectives.org E-government is an issue that is widely discussed by several studies because it has an impact on improving government performance. Weak political will of the heads of state and …

Quality Evaluation of E-Government Services–The Case of Albania R Keco, I Tomorri, K Tomorri – Transylvanian Review of Administrative …, 2023 – rtsa.ro QUALITY EVALUATION OF E-GOVERNMENT SERVICES – THE CASE OF ALBANIA Remzi KECO Ilir TOMORRI Kejsi TOMORRI Page 1 20 Abstract Albania has passed a period of three …

Analysis of Information System Audit Using Control Objectives for Information and Related Technology 5 Framework on Permata Hebat Application MS Muryantoro, DA Efrilianda – Journal of Advances in …, 2023 – journal.unnes.ac.id Permata Hebat application is an application created as a service to develop micro businesses among housewifes in Semarang City. However, to fulfill this expectation, of …

Challenges in E-governments: A case study-based on Iraq NA Jasim, EM Hameed, SA Jasim – IOP Conference Series …, 2021 – iopscience.iop.org An effective and competent way to deliver business and organizational mandates is via deploying Information and Communication Technology (ICT). Parts of a government’s job is …

Dr Alex Zarifis

Collaborative Consumption (CC) and the sharing economy, where consumers do not purchase a product or service, but share it, is growing in popularity. This is due to a trend away from ownership towards experiencing. The first two areas of the economy that this business model disrupted were fare sharing and renting rooms for short periods. Other areas are also influenced but it is unclear which sectors of the economy will be disrupted next. Smaller niches of the economy, or areas where more public-sector involvement is necessary, such as the elderly and the disabled may not be at the forefront and may be the laggards losing out on possible benefits for years.

This research evaluates the current CC business models and identifies 13 ways they add value from the consumer’s perspective. This research further explores whether CC business models fall into two categories in terms of what the consumer values. In the first category, they require a low level of trust while in the second category a higher level of trust is necessary. Our survey evaluates whether there was a difference between CC business models that require a low level of trust such as a taxi service and those that required a high level of trust such as supporting the elderly and disabled.

Figure 1. Comparative spider diagram of value added by collaborative consumption business models for low and high required trust

The analysis verified that the consumer requires 13 types of value added from the business model which can be separated into three categories which are personal interest, communal interest and trust building. It is important for organizations to acknowledge how they relate to these dimensions.

It was found that CC business models can be separated into those that require a relatively low level of trust such as fare sharing and those that require a high level of trust such as supporting the elderly and disabled, as we can see in the figure here. For the business models that only require low trust, the consumer considered the personal interest value added more important, while in the those requiring more trust the consumer rated the value added of trust building higher.

The findings suggest that changing CC business model from one that requires low trust to one that requires higher trust necessitates a significant improvement in how the organisation builds trust. This can be considered a ‘step’ change in trust-building which would have to be a consideration at business model level. Iterative improvements at operational level may not increase trust sufficiently.

Reference

Zarifis A., Cheng X. & Kroenung J. (2019). Collaborative consumption for low and high trust requiring business models: From fare sharing to supporting the elderly and disabled, International Journal of Electronic Business, vol.15, no.1, pp.1-20. Available from (open access): https://www.inderscienceonline.com/doi/abs/10.1504/IJEB.2019.099059

Dr Alex Zarifis


Have you made a purchase from a three dimensional Virtual World (VW)? Probably not, only a small minority have. When VWs first became popular fifteen years ago, people jumped to the conclusion that they were the future, the new platform to socialise online. Their adoption however did not end up being exponential. So why do the experts often think VWs, with their additional functionality are the future, but that future has not come yet? We decided to ask the consumer.
There is a degree of understanding on what each channel can offer but the relative advantage of each channel in relation to the others is less understood. By relative advantage we mean something the one channel, for example three dimensional VWs, have an advantage over two dimensional, traditional, websites. This research, evaluates the relative advantage between the channels of three-dimensional VWs, two-dimensional websites, and offline retail shops. The consumer’s preferences across the three channels, were distinguished across six relative advantages.

Figure 1 The three channels and six relative advantages in multichannel retail
In the figure, you can see at the top the six different relative advantages, and beneath them, how the three different channels perform, in relation to these relative advantages. Participants, showed a preference for offline and 2D websites, in most situations apart from enjoyment, entertainment, sociable shopping, the ability to reinvent yourself, convenience and institutional trust where the VWs were preferred.
We can look in more detail at the fifth relative advantage, that VWs have higher institutional trust compared to 2D websites. Consumers value the role of the VW as an institution in relation to trust. One feature that is appreciated is that the buyer does not receive your banking details. Some participants value the role of the VWs administration in identifying and warning about specific threats.
The findings illustrated in the figure, show that the consumer’s preference varies across the three channels, and six RAs. An organization pursuing a multichannel strategy, can adapt their offerings in each channel to fully utilize these different preferences.
While on most issues VWs are the least appealing from the three channels, framing the comparison with the six relative advantages shows how they have a useful and complementary role to play in multichannel retail. For example, customer support can be done in VWs. An organization, can use these findings to shape their business model and strategy.

Reference
Zarifis A. (2019) ‘The six relative advantages in multichannel retail for three-dimensional Virtual Worlds and two-dimensional websites’, Proceedings of the 10th ACM Conference on Web Science, June 19–21, Boston, USA, pp.363-372. Available from: https://dl.acm.org/doi/pdf/10.1145/3292522.3326038

Dr Alex Zarifis

Several countries’ economies have been disrupted by the sharing economy. However, each country and its consumers have different characteristics including the language used. When the language is different does it change the interaction? If we have a discussion in English and a similar discussion in German will it have the same meaning exactly, or does language lead us dawn a different path? Is language a tool or a companion holding our hand on our journey?

This research compares the text in the profile of those offering their properties in England in English, and in Germany in German, to explore if trust is built, and privacy concerns are reduced, in the same way.

Figure 1. How landlords build trust in the sharing economy

The landlords make an effort to build trust in themselves, and the accuracy of the description they provide. The landlords build trust with six methods: (1) The first is the level of formality in the description. More formality conveys a level of professionalism. (2) The second is distance and proximity. Some landlords want to keep a distance so it is clear that this is a formal relationship, while others try to be more friendly and approachable. (3) The third is ‘emotiveness’ and humour, that can create a sense of shared values. (4) The fourth method of building trust is being assertive and passive aggressive, that sends a message that the rules given in the description are expected to be followed. (5) The fifth method is conformity to the platform language style and terminology that suggests that the platform rules will be followed. (6) Lastly, the sixth method to build trust is setting boundaries that offer clarity and transparency.

Privacy concerns are not usually reduced directly by the landlord as this is left to the platform. The findings indicate that language has a limited influence and the platform norms and habits have the largest influence. We can say that the platform has choreographed this dance sufficiently between the participants so that different languages have a limited influence on the outcome.

Reference

Zarifis A., Ingham R. & Kroenung, J. (2019) ‘Exploring the language of the sharing economy: Building trust and reducing privacy concern on Airbnb in German and English’, Cogent Business & Management, vol.6, iss.1, pp.1-15. Available from (open access): https://doi.org/10.1080/23311975.2019.1666641

Short videos are very popular but if they take up a-lot of people’s time, they gradually change people’s living habits. Therefore it is useful to understand the negative implications of short videos. The results show that users’ viewing many short videos can have negative emotions, and these negative emotions can affect users’ intention to continue to use short video platforms. The model developed in this research shows that there are three negative emotions caused by six factors. Two of these three negative emotions then influence the intention to continue using short videos.

Fig 1. Model of users’ negative emotions and continuous usage intention in short video platforms

From the six factors that cause negative emotions, the five are related to flow theory. Flow theory is relevant here because watching short videos is a flow experience. Flow theory is a state where someone is fully immersed in an activity, they are enjoying it and other things do not seem to matter as much.

The first of the five factors related to flow theory is the low efficiency the user has in their work and other tasks, due to watching short videos. The second is time distortion, meaning that the users perception of time is not as accurate during this activity. What might feel like a short amount of time can be much longer. The third is the harm to their health. Both mental and physical health can be harmed by spending a long time watching short videos. The fourth is the online addiction they experience, making them want to keep watching the short videos. The fifth is online procrastination, making the user watch more short videos to delay working and making decisions related to their work.

The sixth factor that can cause negative emotions is illusion of control. The theory of illusion of control suggests that in some situations a person can be overconfident about their control of a situation. A person can have a level of optimism that they will get the outcome they want, that is unrealistic. The negative emotions include anxiety, sadness and remorse. The research found strong support that sadness and remorse influence the users intention to continue using the short videos.

Reference:
Cheng X., Su X., Yang B., Zarifis A. & Mou J. (2023) ‘Understanding users’ negative emotions and continuous usage intention in short video platforms’, Electronic Commerce Research and Applications, vol.58, 101244, pp.1-15. https://doi.org/10.1016/j.elerap.2023.101244

Artificial intelligence (AI) and related technologies are creating new opportunities and challenges for organizations across the insurance value chain. Incumbents are adopting AI-driven automation at different speeds, and new entrants are attempting to use AI to gain an advantage over the incumbents. This research explored four case studies of insurers’ digital transformation. The findings suggest that a technology focused perspective on insurance business models is necessary and that the transformation is at a stage where we can identify the prevailing approaches. The findings identify the prevailing five insurance business models that utilize AI for growth: (1) focus on a smaller part of the value chain and disaggregate, (2) absorb AI into the existing model without changing it, (3) incumbent expanding beyond existing model, (4) dedicated insurance disruptor, and (5) tech company disruptor adding insurance services to their existing portfolio of services (Zarifis & Cheng 2022).

Figure 1. Updated model of five business models in insurance with disruptors split into two types

In addition to the five business models illustrated in Figure 1, this research identified two useful avenues for further exploration: Firstly, many insurers combined the two first business models. For some products, often the simpler ones, such as car insurance, they focused and disaggregated. For other parts of their organization, they did not change their model, but they absorbed AI into their existing model. Secondly, new entrants can be separated into two distinct subgroups: (4) disruptor focused on insurance and (5) disruptor focused on tech but adding insurance.

Reference

Zarifis A., & Cheng X. (2022). AI Is Transforming Insurance With Five Emerging Business Models. In Encyclopedia of Data Science and Machine Learning (pp. 2086–2100). IGI Global. Available from (open access): https://www.igi-global.com/chapter/ai-is-transforming-insurance-with-five-emerging-business-models/317609

New Fintech and Insurtech services are popular with consumers as they offer convenience, new capabilities and in some cases lower prices. Consumers like these technologies but do they trust them? The role of consumer trust in the adoption of these new technologies is not entirely understood. From the consumer’s perspective, there are some concerns due to the lack of transparency these technologies can have. It is unclear if these systems powered by artificial intelligence (AI) are trusted, and how many interactions with consumers they can replace. There have been several adverts recently that emphasize that their company will not force you to communicate with AI and will provide a real person to communicate with are evidence of some push-back by consumers. Even pioneers of AI like Google are offering more opportunities to talk to a real person an indirect acknowledgment that some people do not trust the technology. Therefore, this research attempts to shed light on the role of trust in Fintech and Insurtech, especially if trust in AI in general and trust in the specific institution play a role (Zarifis & Cheng, 2022).

Figure 1. A model of trust in Fintech/Insurtech

This research validates a model, illustrated in figure 1, that identifies the four factors that influence trust in Fintech and Insurtech. As with many other models of human behavior, the starting point is the individual’s psychology and the sociology of their environment. Then, the model separates trust in a specific organization and trust in a specific technology like AI. This is an important distinction: Consumers have beliefs about the organization they bring with them and other pre-existing beliefs on AI. Their beliefs on AI might have been shaped by experiences with other organizations.

Therefore, the validated model shows that trust in Fintech or Insurtech is formed by the (1) individual’s psychological disposition to trust, (2) sociological factors influencing trust, (3) trust in either the financial organization or the insurer and (4) trust in AI and related technologies.

This model was initially tested separately for Fintech and Insurtech. In addition to validating a model for trust in Fintech and Insurtech separately, the two models were compared to see if they are equally valid or different. For example, if one variable is more influential in one of the two models, this would suggest that the model of trust in one of them is not the same as in the other. The results of the multigroup analysis show that the model is indeed equally valid for Fintech and Insurtech. Having a model of trust that is suitable for both Fintech and Insurtech is particularly useful as these services are often offered by the same organization, or even the same mobile application side by side.

Reference

Zarifis A. & Cheng X. (2022) ‘A model of trust in Fintech and trust in Insurtech: How Artificial Intelligence and the context influence it’, Journal of Behavioral and Experimental Finance, vol. 36, pp. 1-20. Available from (open access): https://doi.org/10.1016/j.jbef.2022.100739

This research was featured by Duke University:

Zarifis A. (2022) ‘Trust in Fintech and trust in Insurtech are influenced by Artificial Intelligence’, Duke University (Global Financial Economics Center). Available from: https://sites.duke.edu/thefinregblog/2022/11/11/trust-in-fintech-and-trust-in-insurtech-are-influenced-by-artificial-intelligence/

The interest in Non-fungible Tokens (NFTs) has ‘exploded’ recently, but it is not clear what final form they will take. This innovation will have difficulties reaching a wider audience until more clarity is achieved on two main issues: What exactly are the NFT business models, and how do they build trust. The findings of recent research (Zarifis and Cheng, 2022), illustrated in figure 1, show that there are four NFT business models:

(1) The first business model is an NFT creator: They can create digital art that is then minted as an NFT, and sold on an NFT platform. The NFT competitive advantages include having proof of irrefutable ownership, and the ability to sell a piece of art that is unique or limited to a low number. The reliability and transparency of the NFT, build trust with the consumer.

Figure 1: The four NFT business models

(2) The second business model is an NFT marketplace, selling creators’ NFTs: The competitive advantage of NFTs as part of this business model is once again the irrefutable ownership, and that it gives consumers digital art they can own. The purchase history of the consumers is transparent, so this gives insights into their interests. As with the previous business model, a community and trust are built between the collectors.

(3) The third business model is a Company offering their own NFT, typically a fan token: This business model has several NFT processes. These are to sell NFTs for profit, to give NFTs as rewards, make payment with fan tokens, give an NFT so that the person receiving it has certain utilities and rights, such as voting rights. The competitive advantages of NFTs, within this business model, are that they allow fans to feel closer to their team and builds a community and trust between the fans.

(4) The fourth business model is a Computer game with NFT sales: There can be in-game purchases of NFT minted virtual items, limited or unique in game purchases and players can be rewarded for playing, know as ‘play to earn’. This offers incentives to game developers to continue producing rare items, provides an ongoing revenue stream for existing games, and builds a community and trust between the players.

This research was the basis of Dr Alex Zarifis keynote speech in front of around 300 people at the 2022 JEBDE’s 2nd Academic Conference on Electronic Business & Digital Economics on the 28/09/22.

Reference

Zarifis A. & Cheng X. (2022) ‘The business models of NFTs and Fan Tokens and how they build trust’, Journal of Electronic Business & Digital Economics, vol.1, pp.1-14. Available from: https://doi.org/10.1108/JEBDE-07-2022-0021

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/