Uncovering the Intellectual Core of the Information Systems Discipline

By Anna Sidorova, Nicholas E. Evangelopoulos, J. Valacich, Thiagarajan Ramakrishnan. MIS Q., 2008

626 citations recorded by the source corpus.

Subfields: Communication, Management Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/b2bf68dfca66a058268c64c629d02f86c7ca2d6d

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Citations in the corpus

Exploring determinants of voting for the "helpfulness" of online user reviews: A text mining approach (2011, methodology): “part of reviews on the product as shown in “cons” part [26].”
Research Commentary - Digital Infrastructures: The Missing IS Research Agenda (2010, background): “Digital Infrastructure: The Orphan of the IS Field Traditionally, the IS field has focused on IT governance and system development in well-bounded organizational contexts, along with studying IT's effects on individuals, groups, organizations, and markets (Sidorova et al. 2008).”
Strategizing information systems-enabled organizational transformation: A transdisciplinary review and new directions (2012, background): “Nevertheless, in future research, due to the importance of governing agency in understanding OT (Schwarz and Hirschheim, 2003) its coding should be developed to open up the black box.”
Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry (2016, methodology): “For the frequency analysis [18], the following procedure in Fig.”
Voice of airline passenger: A text mining approach to understand customer satisfaction (2019, methodology): “Source: Generated based on previous LSA applications (Sidorova et al., 2008; Yalcinkaya & Singh, 2015; Kulkarni et al., 2014; Xu and Li, 2016; Ahmad and Laroche, 2017).”
Bridging the Qualitative-Quantitative Divide: Guidelines for Conducting Mixed Methods Research in Information Systems (2013, background): “Diversity in research methods is considered a major strength of information systems (IS) research (Lee 1999; Robey 1996; Sidorova et al. 2008).”
Family Firm Heterogeneity: A Definition, Common Themes, Scholarly Progress, and Directions Forward (2021, background): “Using a factor-analytic approach, rotations of the semantic space reveal factors that represent underlying themes (Sidorova et al., 2008).”
Big Data and supply chain management: a review and bibliometric analysis (2016, background): “Such a discussion assists in revealing the intellectual core and identity construction of the discipline by looking into keywords used by research papers (and top-cited authors) and their aggregation (Scott and Lane 2000; Sidorova et al. 2008).”
Standing on the Shoulders of Giants: Challenges and Recommendations of Literature Search in Information Systems Research (2015, background): “For example, Wareham et al. (2005) set the starting date of their meta-analysis of ecommerce research to 1997 because they wanted to have a representative sample of literature from the years before and after the dot.”
It is not for fun: An examination of social network site usage (2012, background): “…of Chao Wen 2012 It is not for fun: An examination of social network site usage Chenyan Xu, University of North Texas Sherry Ryan, University of North Texas Victor Prybutok, University of North Texas Chao Wen, Eastern Illinois University Available at: https://works.bepress.com/chao_wen/5/”
Computing in Everyday Life: A Call for Research on Experiential Computing (2010, background): “A quick review of four recent studies (Banker and Kauffman 2004; Orlikowski and Iacono 2001; Orlikowski and Scott 2008; Sidorova et al. 2008) shows that in the majority of past IS studies, computing was conceptualized as a discrete symbolic representations of something in the real world—…”
A scientometric analysis of knowledge management and intellectual capital academic literature (1994-2008) (2010, background): “Based on organizational identity literature, there are several arguments that need to be considered (Sidorova et al., 2008).”
Explaining Data-Driven Document Classifications (2014, methodology): “A follow-up analysis is presented in Appendix A based on a suite of text classification problems (the 20 Newsgroups) widely used in the research literature.”