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.

Real option analysis offers interesting insights on the value of assets and on the profitability of investments, which has made real options a growing field of academic research and practical application. Real option valuation is, however, often found to be difficult to understand and to implement due to the quite complex mathematics involved. Recent advances in modeling and analysis methods have made real option valuation easier to understand and to implement. This paper presents a new method (fuzzy pay-off method) for real option valuation using fuzzy numbers that is based on findings from earlier real option valuation methods and from fuzzy real option valuation. The method is intuitive to understand and far less complicated than any previous real option valuation model to date. The paper also presents the use of number of different types of fuzzy numbers with the method and an application of the new method in an industry setting.

No abstract

No abstract