APPENDIX EHow to Link Digital Transformation and Value with the Residual Income Valuation Model

The main philosophy behind all conducted financial analysis was to apply a balanced mix of scientific rigor and practitioner‐minded pragmatism for operationalization. This implied no distractions by specialized valuation research models and helped to keep track of accessible digital transformation data, instead of dwelling into theoretical peculiarities of detailed model parametrization. Financial valuation methods have been grouped in many different ways, depending on their objective and approach (Falkum 2011; Vartanian 2003). As indicated earlier, direct and foundational digital transformation, technology/IT/IS, innovation, and corporate finance‐value research over time have applied a seemingly “infinite” variation of customized approaches out of this basket of potential valuation analysis.

From a practitioner perspective, further reviewing this substantial breadth of models was of no further interest for this research, as it has already been extensively analyzed in corresponding meta‐studies, for example, for IT‐payoff (Kohli and Devaraj 2003; Sabherwal and Jeyaraj 2015) or for innovation‐payoff (Vartanian 2003) and, after careful consideration, added no further relevant insights. Instead, the much more promising angle was the subset of approaches, which found theoretically sound ways to integrate nonaccounting “other information” into models otherwise fully based on publicly ...

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