Philosophy and information systems: where are we and where should we go?

A meta-narrative analysis of smart tourism destinations: implications for tourism destination management

“…In conclusion, Gretzel and de Mendonça (2019) emphasize that research on smart tourism destinations calls for more critical perspectives that challenge both public and academic discourses. Therefore, the research field of smart tourism destinations would benefit from paradigms and ideologies being challenged so as to provide greater context to the research (Hassan et al, 2018). Current research achievements would also 'transcend across into constellations of other disciplines' (Hassan et al, 2018, p. 264) due to more pluralistic and cross-border research approaches.…”

Introduction: Why Theory? (Mis)Understanding the Context and Rationale

“…Such a goal limits the IS field to the formalities and restrictions of logico-deductive structures of the natural sciences. As a form of prescriptive theories (Walls et al, 1992;Gregor & Jones, 2007), design theories can draw from multiple sources including those of the arts (Hassan, Mingers, & Stahl, 2018), architecture (Lee, 1991), and humanities. McPhee (1996) describes these two alternative paths of design theory: scientific approach to problem-solving following the natural sciences and the social approach following the human sciences.…”

Data science: developing theoretical contributions in information systems via text analytics

“…Positivist research strives for explanation and prediction, generalizing from sample to population. Interpretivist research seeks contextual interpretation and understanding of a phenomenon [34]. Critical research "focuses on the oppositions, conflicts and contradictions in contemporary society, and seeks to be emancipatory i.e.…”

“…Every paradigm provides a different view on what valid theory is, and what a theory should do. This provides a lot of emphasis on methodological choices rather than on objects of study, at the risk of producing uninteresting and irrelevant knowledge [34]. While we visit methodological issues when reviewing data science contributions in IS, we first review common objectives of data science, which we believe bring it closer to objects of study and relevance.…”