• A framework for analysing blockchain technology adoption: Integrating institutional, market and technical factors

      Janssen, M.; Weerakkody, Vishanth J.P.; Ismagilova, Elvira; Sivarajah, Uthayasankar; Irani, Zahir (2020-02)
      The adoption of blockchain technologies require the consideration of a broad range of factors, over and above the predominantly technology focus of most current work. Whilst scholarly literature on blockchain technology is only beginning to emerge, majority are focused on the technicalities of the technology and tend to ignore the organizational complexities of adopting the technology. Drawing from a focused review of literature, this paper proposed a conceptual framework for adoption of blockchain technology capturing the complex relationships between institutional, market and technical factors. The framework highlights that varying outcomes are possible, and the change process is focal as this shapes the form blockchain applications take. Factors presented in the framework (institutional, market and technical) interact and mutually influence each other. The proposed framework can be used by organisations as a reference point for adopting blockchain applications and by scholars to expand, refine and evaluate research into blockchain technology.
    • Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy

      Dwivedi, Y.K.; Hughes, L.; Ismagilova, Elvira; Aarts, G.; Coombs, C.; Crick, T.; Duan, Y.; Dwivedi, R.; Edwards, J.; Eirug, A.; et al. (Elsevier, 2021-04)
      As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.
    • Blockchain for next generation services in banking and finance: cost, benefit, risk and opportunity analysis

      Osmani, M.; El-Haddadeh, R.; Hindi, N.; Janssen, M.; Weerakkody, Vishanth J.P. (2021-04)
      Purpose – The purpose of this paper is to help in providing a better understanding of the application of blockchain technology in the context of the banking and finance sectors. The aim is to outline blockchain’s benefits, opportunities, costs, risks as well as challenges of the technology in the context of banking and finance services Design/methodology/approach – Careful examination of the extant literature, including utilising relevant academic-based research databases has been carried out. It covered reviewing various research contributions published in peer-reviewed journals, academic reports, as well as technical reports to help in identifying related benefits, opportunities, costs, and risks. Findings – The findings reveal that there are limited contributions in utilising blockchain in the banking and finance sectors when compared with other sectors. As such, the study highlighted the relevant perspective of benefits, opportunities, costs, and risks within such sectors. Practical implications – This study helps in offering a focal point to banking and financial sector managers and decision-makers for realising the benefits of blockchain technology as well as developing strategies and programmes to overcome the identified challenges. Originality/value – This study highlights the need for a holistic understanding of the various aspects of cost, benefits, risk and opportunities to create blockchain applications that work for banking and finance sectors
    • Challenges for adopting and implementing IoT in smart cities: An integrated MICMAC-ISM approach

      Janssen, M.; Luthra, S.; Mangla, S.; Rana, Nripendra P.; Dwivedi, Y.K. (2019-12)
      The wider use of Internet of Things (IoT) makes it possible to create smart cities. The purpose of this paper is to identify key IoT challenges and understand the relationship between these challenges to support the development of smart cities. Design/methodology/approach: Challenges were identified using literature review, and prioritised and elaborated by experts. The contextual interactions between the identified challenges and their importance were determined using Interpretive Structural Modelling (ISM). To interrelate the identified challenges and promote IoT in the context of smart cities, the dynamics of interactions of these challenges were analysed using an integrated Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC)-ISM approach. MICMAC is a structured approach to categorise variables according to their driving power and dependence. Findings: Security and privacy, business models, data quality, scalability, complexity and governance were found to have strong driving power and so are key challenges to be addressed in sustainable cities projects. The main driving challenges are complexity and lack of IoT governance. IoT adoption and implementation should therefore focus on breaking down complexity in manageable parts, supported by a governance structure. Practical implications: This research can help smart city developers in addressing challenges in a phase-wise approach by first ensuring solid foundations and thereafter developing other aspects. Originality/value: A contribution originates from the integrated MICMAC-ISM approach. ISM is a technique used to identify contextual relationships among definite elements, whereas MICMAC facilitates the classification of challenges based on their driving and dependence power. The other contribution originates from creating an overview of challenges and theorising the contextual relationships and dependencies among the challenges.
    • Driving Innovation through Big Open Linked Data (BOLD): Exploring Antecedents using Interpretive Structural Modelling

      Dwivedi, Y.K.; Janssen, M.; Slade, E.L.; Rana, Nripendra P.; Weerakkody, Vishanth J.P.; Millard, J.; Hidders, J.; Snijders, D. (2016)
      Innovation is vital to find new solutions to problems, increase quality, and improve profitability. Big open linked data (BOLD) is a fledgling and rapidly evolving field that creates new opportunities for innovation. However, none of the existing literature has yet considered the interrelationships between antecedents of innovation through BOLD. This research contributes to knowledge building through utilising interpretive structural modelling to organise nineteen factors linked to innovation using BOLD identified by experts in the field. The findings show that almost all the variables fall within the linkage cluster, thus having high driving and dependence powers, demonstrating the volatility of the process. It was also found that technical infrastructure, data quality, and external pressure form the fundamental foundations for innovation through BOLD. Deriving a framework to encourage and manage innovation through BOLD offers important theoretical and practical contributions.
    • An Empirical Validation of a Unified Model of Electronic Government Adoption (UMEGA)

      Dwivedi, Y.K.; Rana, Nripendra P.; Janssen, M.; Lal, B.; Williams, M.D.; Clement, M. (2017-04)
      In electronic government (hereafter e-government), a large variety of technology adoption models are employed, which make researchers and policymakers puzzled about which one to use. In this research, nine well-known theoretical models of information technology adoption are evaluated and 29 different constructs are identified. A unified model of e-government adoption (UMEGA) is developed and validated using data gathered from 377 respondents from seven selected cities in India. The results indicate that the proposed unified model outperforms all other theoretical models, explaining the highest variance on behavioral intention, acceptable levels of fit indices, and significant relationships for each of the seven hypotheses. The UMEGA is a parsimonious model based on the e-government-specific context, whereas the constructs from the original technology adoption models were found to be inappropriate for the e-government context. By using the UMEGA, relevant e-government constructs were included. For further research, we recommend the development of e-government-specific scales.E-
    • Social Media: The Good, the Bad, and the Ugly

      Dwivedi, Y.K.; Kelly, G.; Janssen, M.; Rana, Nripendra P.; Slade, E.L.; Clement, M. (2018-06)
    • Trustworthiness of digital government services: deriving a comprehensive theory through interpretive structural modelling

      Janssen, M.; Rana, Nripendra P.; Slade, E.L.; Dwivedi, Y.K. (2018-05)
      Having its origin in public administration, trustworthiness is a significant concept in digital government research, influencing the relationships between citizens and governments. However, the interrelationships between the facets of trustworthiness are given inadequate attention. Therefore, the aim of this research was to develop a theory detailing the factors affecting citizens’ perceptions of e-government trustworthiness. A comprehensive review of public administration and information systems literature highlighted 20 pertinent variables. The interrelationships of these variables were identified and categorized according to their driving and dependence power by employing interpretive structural modelling. The proposed model was then drawn based on the level partitioning of variables and interrelationships of the variables determined using the final reachability matrix. The findings reveal that current conceptualizations of digital government trustworthiness take a too narrow view. The findings can help government policy makers with understanding the interrelated factors associated with trustworthiness in the context of digital government services and implement them in effective strategic planning.