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Publications and highlights

Within the IRC, we have multiple academics and research partners that publish pioneering work in a variety of areas.

Publications are split into subject areas:

Digital Health

Digital Health is the use of digital technology to improve healthcare quality and efficiency within both the public and private sector with external and internal systems.

Weizi Li, Kecheng Liu, Hongqiao Yang and Changrui Yu’s ‘Integrated clinical pathway management for medical quality improvement-based on a semiotically inspired systems architecture’ expertly addresses the hospital challenge of ‘information silos’ among systems, which lead to a lack of knowledge sharing and information accuracy, medical errors, inefficient treatment processes and poor healthcare service quality. This data integration platform was developed as part of clinical pathway processes and co-designed with hospital end users (information department and clinicians). The design includes platform architecture with existing systems, pathway and operational knowledge base and inference engine, system module and multi-agent systems interaction mechanisms design. This research has been implemented in hospitals and proven valuable.

Digital Transformation and Society

Digital Transformation and Society looks that the methods and data used to see the human impact on Digital and Digital's impact on people, how they interlink and how they change and evolve over time.

ETSP (Euclidian Travelling Salesman Problem) Heuristics

The Travelling Salesperson Problem (TSP) describes a situation where an imaginary individual wishes to visit multiple cities once before returning to his/her own city. This type of problem is known as a nondeterministic polynomial (NP) hard problem, since the factorial number of solutions results in it being impractical to solve using exhaustive processing. Interestingly, when presented as a Euclidean graph (i.e. ETSP), humans identify near optimal solutions almost effortlessly, despite billions of possible tours. In this research, we consider human processing of the ETSP, and try to model human problem solving and/or develop simple heuristics that can provide low cost near optimal solutions. Stephen Gulliver and others have delved heavily into this area.

Publications on this subject:

  • Kyritsis, M., Gulliver, S., Feredoes, E., Ud Din S. (Submitted) Human Behaviour in the Euclidean Travelling Salesperson Problem: Computational Modelling of Heuristics and Figural Effects, Cognitive Systems Research.
  • Kyritsis, M., Blathras, G., Gulliver, S. and Vasiliki-Alexia, V. (2017) Sense of direction and conscientiousness as predictors of performance in the Euclidean travelling salesman problem. Heliyon, 3 (11). e00461. ISSN 2405-8440 doi: https://doi.org/10.1016/j.heli...
  • Kyritsis, M., Gulliver, S. and Feredoes, E. (2017) Acknowledging crossing-avoidance heuristic violations when solving the Euclidean travelling salesperson problem. Psychological Research. ISSN 1430-2772 doi: https://doi.org/10.1007/s00426...

Consumer behaviour and personalised recommendation within e-commerce systems

Understanding online consumer behaviour and improving the quality of online services became the focal point for both academia and industry to fully exploit the value of e-commerce websites. In particular, we explore questions such as to what extent a consumer’s online friends influence his/her decision, and how can we make good recommendations for consumers?

By analysing large scale review data from consumers, we found that 75% of consumer decisions based on whether or not to comment/consume a product are influenced by his/her online friends. A network-based model is therefore developed describing this behaviour. In addition, we explore theoretical methods to describe the similarity between different products/services, based on the collective behaviour of the consumers. These developed measures are applied to make accurate, diverse and stable recommendations for consumers which predict their potential interests.

Publications on this subject:

  • Pan, X., Hou, L., Liu, K., & Niu, H. (2018). Do reviews from friends and the crowd affect online consumer posting behaviour differently? Electronic Commerce Research and Applications, 29, 102-112.
  • Hou, L., Pan, X., & Liu, K. (2018). Balancing the popularity bias of object similarities for personalised recommendation. The European Physical Journal B, 91(3), 47.
  • Hou, L., Liu, K. (2017) Common neighbour structure and similarity intensity in complex networks. Physics Letters A 381, 3377–3383.
  • Pan, X., Hou, L., & Liu, K. (2017). Social influence on selection behaviour: Distinguishing local-and global-driven preferential attachment. PloS one, 12(4), e0175761.
  • Hou, L., Liu, K., Liu, J., & Zhang, R. (2017). Solving the stability–accuracy–diversity dilemma of recommender systems. Physica A: Statistical Mechanics and its Applications, 468, 415-424.

Understanding E-learning implementation

E-learning has gained much focus from educators and researchers, yet implementation of e-learning systems often fails. The purpose of Stephen Gulliver's research is to understand implementation preferences and barriers. This research initially undertook an in-depth review of literature concerning e-learning implementation barriers. A total of 259 papers were identified, published between 1990 and 2016. Hermeneutics and data-driven qualitative content analysis was used to define 68 unique barriers, which was thematically grouped into four conceptual categories, i.e. Technology (T), Individual (I), Pedagogy (P), and Enabling Conditions (EC) - which led to the conceptualization of “TIPEC” framework*. Subsequent research, including two BISA PhD projects, have looked at aspects of E-learning implementation, to understand how we can best use technology and/or pedological delivery of information.

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Publications on this subject:

  • Ali, S., Gulliver, S., and Uppal, M. A. (Submitted) Role of Individual Culture on Students’ E-learning Device Preference: Analysis of Higher Education Service Quality Indicators
  • *Uppal, M. A., Ali, S. and Gulliver, S. (2018) Factors determining e-learning service quality. British Journal of Educational Technology, 49 (3). pp. 412-426. ISSN 1467-8535 doi: https://doi.org/10.1111/bjet.1...
  • Ali, S., Uppal, M. A. and Gulliver, S. (2018) A conceptual framework highlighting e-learning implementation barriers. Information Technology & People, 31 (1). pp. 156-180. ISSN 0959-3845 doi: https://doi.org/10.1108/ITP-10...

E-Leadership through strategic alignment: an empirical study of small- and medium-sized enterprises in the digital age

Weizi Li, Kecheng Liu, Maksim Belitski, Abby Ghobadian & Nicholas O'Regan’s paper helped develop an empirically derived e-leadership model. Initially we developed a theoretical model of e-leadership drawing on strategic alignment theory. This provides a theoretical foundation on how SMEs can harness digital technology in support of their business strategy enabling sustainable growth. The resulting diagnostic model enables SME decision makers to exercise effective e-leadership by creating productive alignment between business strategy and digital technology improving longevity and growth prospects.

Digital Environment

This sections explores the framework and surroundings of the Digital environment, studies focus on information found within everyday life so they can be put onto digital platforms to maximise productivity within that physical space. This theme is usually focused on the set-up of digital platforms and services within companies and the most efficient ways in starting these large scale projects and decisions. The Digital Environment covers cloud storage internet of things and many more.

Sharm Manwani and Oliver Bossert's "The challenges and responses for enterprise architects in the digital age. Journal of Enterprise Architecture" pulls from the collaboration between McKinsey and Henley Business School Enterprise Architecture (EA) Survey to assess the outcomes and capabilities of EA to look at the challenges brought about by the digital age.