Mapping the intellectual structure of the coronavirus field (2000-2020): a co-word analysis

Over the two last decades, coronaviruses have affected human life in different ways, especially in terms of health and economy. Due to the profound effects of novel coronaviruses, growing tides of research are emerging in various research fields. This paper employs a co-word analysis approach to map the intellectual structure of the coronavirus literature for a better understanding of how coronavirus research and the disease itself have developed during the target timeframe. A strategic diagram has been drawn to depict the coronavirus domain’s structure and development. A detailed picture of coronavirus literature has been extracted from a huge number of papers to provide a quick overview of the coronavirus literature. The main themes of past coronavirus-related publications are (a) “Antibody- Virus Interactions,” (b) “Emerging Infectious Diseases,” (c) “Protein Structure-based Drug Design and Antiviral Drug Discovery,” (d) “Coronavirus Detection Methods,” (e) “Viral Pathogenesis and Immunity,” and (f) “Animal Coronaviruses.” The emerging infectious diseases are mostly related to fatal diseases (such as Middle East respiratory syndrome, severe acute respiratory syndrome, and COVID-19) and animal coronaviruses (including porcine, turkey, feline, canine, equine, and bovine coronaviruses and infectious bronchitis virus), which are capable of placing animal-dependent industries such as the swine and poultry industries under strong economic pressure. Although considerable research into coronavirus has been done, this unique field has not yet matured sufficiently. Therefore, “Antibody-virus Interactions,” “Emerging Infectious Diseases,” and “Coronavirus Detection Methods” hold interesting, promising research gaps to be both explored and filled in the future

Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Digital transformation (DT) is prevalent in businesses today. However, current studies to guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly what DT is and the capabilities needed to enable it successfully. With the aim of filling the gaps, this paper presents a novel bibliometric framework that unearths clues from scientific articles and patents. The framework incorporates the scientific evolutionary pathways and hierarchical topic tree to quantitatively identify the DT research topics’ evolutionary patterns and hierarchies at play in DT research. Our results include a comprehensive definition of DT from the perspective of bibliometrics and a systematic categorization of the capabilities required to enable DT, distilled from over 10,179 academic papers on DT. To further yield practical insights on technological capabilities, the paper also includes a case study of 9,454 patents focusing on one of the emerging technologies - artificial intelligence (AI). We summarized the outcomes with a four-level AI capabilities model. The paper ends with a discussion on its contributions: presenting a quantitative account of the DT research, introducing a process based understanding of DT, offering a list of major capabilities enabling DT, and drawing the attention of managers to be aware of capabilities needed when undertaking their DT journey

Value Co-Creation Propositions: A Self-Determination Theory of Customer Acceptance, Trust and Wellbeing

With the emergence of shared business models, hospitality and tourism consumers are faced with the decision to accept value propositions from various service providers, including traditional, collaborative and shared. Grounded in service-dominant logic, theory of acceptance, theory of value, self-determination theory and generational theory, this dissertation examines why consumers accept value propositions from service providers and what drives customers to collaborate with front-line employees. The research uses three studies that utilized a destination resort context with a mixed factorial equal cells experimental design. Study 1 utilized a 3 (generations) x 3 (business models) x 4 (value propositions) factorial between-within subjects design. Study 2 manipulated independent self-determination factors and used 3 (generations) x 2 (customers vs. employees) x 2 (strong or weak SDT factor) x 4 (value propositions). Study 3 extended study 2 by examining the additive effects of self-determination factors. The new conceptual framework of propositions-acceptance-collaboration was tested. This study is the first to simultaneously examine different value proposition results in three different business models and explore the differences between customers and employees in perceptions of collaboration. Mediation effects of co-created value and levels of acceptances on personal, organizational and collaborative results were tested and established. Strong self-determination factors positively influenced co-created value appraisal and outcomes of collaboration. Additive self-determination factors had a positive impact on outcomes when compared with independent factors