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Applying configurational analysis to IS behavioural research: a methodological alternative for modelling combinatorial complexities
Author(s) -
Liu Yong,
Mezei József,
Kostakos Vassilis,
Li Hongxiu
Publication year - 2017
Publication title -
information systems journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.635
H-Index - 89
eISSN - 1365-2575
pISSN - 1350-1917
DOI - 10.1111/isj.12094
Subject(s) - qualitative comparative analysis , set (abstract data type) , management science , computer science , fuzzy set , interpretation (philosophy) , regression analysis , government (linguistics) , econometrics , outcome (game theory) , data science , operations research , fuzzy logic , mathematics , engineering , mathematical economics , artificial intelligence , machine learning , linguistics , philosophy , programming language
An important limitation of regression‐based analysis stems from the assumption of symmetric relationships between variables, which is often violated. To overcome this limitation within IS research, we propose the use of the fuzzy‐set qualitative comparative analysis (FsQCA) method. The paper elaborates on the rationale for applying this approach to IS behavioural research and how to tailor FsQCA for this purpose. A systematic interpretation of the technique covering its mathematical properties and advanced features is provided. Drawing from an illustrative study of mobile government services adoption by residents of rural areas, the paper demonstrates FsQCA's potential to supplement regression‐based IS behavioural research, by (i) examining asymmetric relationships between a set of antecedents and the IS phenomenon of interest, (ii) providing nuanced coverage of necessary and sufficient conditions for emergence of an IS behavioural outcome, and (iii) identifying various configurations of conditions in association with users' demographic characteristics. © 2015 Blackwell Publishing Ltd