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.

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.


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.

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.


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