• Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

      Dwivedi, Yogesh K.; Hughesa, Laurie; Ismagilova, Elvira; Aarts, Gert; Coombs, Crispin; Crick, Tom; Duan, Yanqing; Dwivedi, Rohita; Edwards, John; Eirug, Aled; et al. (Elsevier, 2019-08-27)
      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.
    • Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda

      Duan, Yanqing; Edwards, John S.; Dwivedi, Yogesh Kumar; University of Bedfordshire; Aston University; Swansea University (Elsevier, 2019-02-07)
      Artificial intelligence (AI) has been in existence for over six decades and has experienced AI winters and springs. The rise of super computing power and Big Data technologies appear to have empowered AI in recent years. The new generation of AI is rapidly expanding and has again become an attractive topic for research. This paper aims to identify the challenges associated with the use and impact of revitalised AI based systems for decision making and offer a set of research propositions for information systems (IS) researchers. The paper first provides a view of the history of AI through the relevant papers published in the International Journal of Information Management (IJIM). It then discusses AI for decision making in general and the specific issues regarding the interaction and integration of AI to support or replace human decision makers in particular. To advance research on the use of AI for decision making in the era of Big Data, the paper offers twelve research propositions for IS researchers in terms of conceptual and theoretical development, AI technology-human interaction, and AI implementation.
    • Citizens’ adoption of an electronic government system: towards a unified view

      Rana, Nripendra P.; Dwivedi, Yogesh Kumar; Lal, Banita; Williams, Michael D.; Clement, Marc; Swansea University; Nottingham Trent University (Springer, 2015-11-24)
      Sluggish adoption of emerging electronic government (eGov) applications continues to be a problem across developed and developing countries. This research tested the nine alternative theoretical models of technology adoption in the context of an eGov system using data collected from citizens of four selected districts in the state of Bihar in India. Analysis of the models indicates that their performance is not up to the expected level in terms of path coefficients, variance in behavioural intention, or the fit indices of the models. In response to the underperformance of the alternative theoretical models to explain the adoption of an eGov system, this research develops a unified model of electronic government adoption and tests it using the same data. The results indicate that the proposed research model outperforms all alternative models of technology adoption by explaining 77 % of variance in behavioural intention, with acceptable values of fit indices and significant relationships between each pair of hypothesised factors.
    • Editorial: How to develop a quality research article and avoid a journal desk rejection

      Dwivedi, Yogesh Kumar; Hughes, Laurie; Cheung, Christy M.K.; Conboy, Kieran; Duan, Yanqing; Dubey, Rameshwar; Janssen, Marijn; Jones, Paul; Sigala, Marianna; Viglia, Giampaolo; et al. (Elsevier, 2021-09-21)
      The desk rejection of submitted articles can be a hugely frustrating and demotivating process from the perspective of the researcher, but equally, a time-consuming and vital step in the process for the Editor, tasked with selecting appropriate articles that meet the required criteria for further review and scrutiny. The feedback from journal Editors within this editorial, highlights the significant gaps in understanding from many academics of the journal assessment process and acceptance criteria for progression to the review stage. This editorial offers a valuable “lived-in” perspective on the desk rejection process through the lens of the Editor, via the differing views of nine leading journal Editors. Each Editor articulates their own perspectives on the many reasons for desk rejection, offering key insight to researchers on how to align their submissions to the specific journal requirements and required quality criteria, whilst demonstrating relevance and contribution to theory and practice. This editorial develops a succinct summary of the key findings from the differing Editor perspectives, offering a timely contribution of significant value and benefit to academics and industry researchers alike.
    • An empirical validation of a unified model of electronic government adoption (UMEGA)

      Dwivedi, Yogesh Kumar; Rana, Nripendra P.; Janssen, Marijn; Lal, Banita; Williams, Michael D.; Clement, Marc; Swansea University; Delft University of Technology; Nottingham Trent University (Elsevier, 2017-03-31)
      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.
    • A generalised adoption model for services: a cross-country comparison of mobile health (m-health)

      Dwivedi, Yogesh Kumar; Shareef, Mahmud Akhter; Simintiras, Antonis C.; Lal, Banita; Weerakkody, Vishanth; Swansea University; North South University, Dhaka; McMaster University; Nottingham Trent University; Brunel University (Elsevier, 2015-07-17)
      Which antecedents affect the adoption by users is still often a puzzle for policy-makers. Antecedents examined in this research include technological artefacts from the Unified Theory of Acceptance and Use of Technology (UTAUT), consumer context from UTAUT2 and psychological behaviour concepts such as citizens' channel preference and product selection criteria. This research also investigated cultural domination on citizens' behavioural perception. The data for this study was collected among citizens from three countries: USA, Canada, and Bangladesh. The findings suggest that the UTAUT model could partially shape technology artefact behaviour and the extended UTAUT must consider specific determinants relevant to cognitive, affective, and conative or behavioural aspects of citizens. The model helps policy-makers to develop mobile healthcare service system that will be better accepted. The finding also suggests that this mobile service system should reflect a country's cultural traits. These findings basically extend the theoretical concept of UTAUT model to articulate adoption behaviour of any complex and sensitive ICT related issues like mobile healthcare system.
    • Impact of COVID-19 pandemic on information management research and practice: transforming education, work and life

      Dwivedi, Yogesh Kumar; Hughes, D. Laurie; Coombs, Crispin; Constantiou, Ioanna; Duan, Yanqing; Edwards, John S.; Gupta, Babita; Lal, Banita; Misra, Santosh; Prashant, Prakhar; et al. (Elsevier Ltd, 2020-07-31)
      The COVID-19 pandemic has forced many organisations to undergo significant transformation, rethinking key elements of their business processes and use of technology to maintain operations whilst adhering to a changing landscape of guidelines and new procedures. This study offers a collective insight to many of the key issues and underlying complexities affecting organisations and society from COVID-19, through an information systems and technological perspective. The views of 12 invited subject experts are collated and analysed where each articulate their individual perspectives relating to: online learning, digital strategy, artificial intelligence, information management, social interaction, cyber security, big data, blockchain, privacy, mobile technology and strategy through the lens of the current crisis and impact on these specific areas. The expert perspectives offer timely insight to the range of topics, identifying key issues and recommendations for theory and practice.
    • Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making

      Cao, Guangming; Duan, Yanqing; Edwards, John S.; Dwivedi, Yogesh Kumar; Ajman University; University of Bedfordshire; Aston University; Swansea University (Elsevier, 2021-06-08)
      While using artificial intelligence (AI) could improve organizational decision-making, it also creates challenges associated with the “dark side” of AI. However, there is a lack of research on managers’ attitudes and intentions to use AI for decision making. To address this gap, we develop an integrated AI acceptance-avoidance model (IAAAM) to consider both the positive and negative factors that collectively influence managers’ attitudes and behavioral intentions towards using AI. The research model is tested through a large-scale questionnaire survey of 269 UK business managers. Our findings suggest that IAAAM provides a more comprehensive model for explaining and predicting managers’ attitudes and behavioral intentions towards using AI. Our research contributes conceptually and empirically to the emerging literature on using AI for organizational decision-making. Further, regarding the practical implications of using AI for organizational decision-making, we highlight the importance of developing favorable facilitating conditions, having an effective mechanism to alleviate managers’ personal concerns, and having a balanced consideration of both the benefits and the dark side associated with using AI.
    • Working from home during Covid-19: doing and managing technology-enabled social interaction with colleagues at a distance

      Lal, Banita; Dwivedi, Yogesh Kumar; Haag, Markus; ; University of Bradford; Swansea University; University of Bedfordshire (Springer, 2021-08-27)
      With the overnight growth in Working from Home (WFH) owing to the pandemic, organisations and their employees have had to adapt work-related processes and practices quickly with a huge reliance upon technology. Everyday activities such as social interactions with colleagues must therefore be reconsidered. Existing literature emphasises that social interactions, typically conducted in the traditional workplace, are a fundamental feature of social life and shape employees' experience of work. This experience is completely removed for many employees due to the pandemic and, presently, there is a lack of knowledge on how individuals maintain social interactions with colleagues via technology when working from home. Given that a lack of social interaction can lead to social isolation and other negative repercussions, this study aims to contribute to the existing body of literature on remote working by highlighting employees' experiences and practices around social interaction with colleagues. This study takes an interpretivist and qualitative approach utilising the diary-keeping technique to collect data from twenty-nine individuals who had started to work from home on a full-time basis as a result of the pandemic. The study explores how participants conduct social interactions using different technology platforms and how such interactions are embedded in their working lives. The findings highlight the difficulty in maintaining social interactions via technology such as the absence of cues and emotional intelligence, as well as highlighting numerous other factors such as job uncertainty, increased workloads and heavy usage of technology that affect their work lives. The study also highlights that despite the negative experiences relating to working from home, some participants are apprehensive about returning to work in the traditional office place where social interactions may actually be perceived as a distraction. The main contribution of our study is to highlight that a variety of perceptions and feelings of how work has changed via an increased use of digital media while working from home exists and that organisations need to be aware of these differences so that they can be managed in a contextualised manner, thus increasing both the efficiency and effectiveness of working from home.