The combined model: proposition of a unified framework integrating innovation diffusion and hype dynamics for innovation readiness assessment

Abstract This paper aims to add a new approach to the task of evaluating the stage of innovation diffusion. Innovation diffusion and maturity are described through a range of frameworks that highlight various aspects of innovation. Keeping in mind that innovation diffusion is indeed a complex phenomenon that probably cannot be fully understood through just one lens, we have decided to choose a combination of frameworks. This choice was guided by the central objective of this paper: to explicitly clarify the market dynamics of innovation diffusion for the practical application of futures studies in business strategy. Thus this article introduces the Combined Model—a conceptual integration aligning population adoption stages with market expectation stages on a unified temporal axis. The model offers a diagnostic framework of four Opportunity Gates (Vision, Validation, New Normal, and Exit), enabling practitioners to evaluate when to experiment, when to validate, when to scale, and when to assess whether an innovation is becoming a new market normal, remaining niche, or exiting the market. A real business case illustrates the explanatory and diagnostic capacity of the model: Alfa Activity (2013). The article contributes to innovation theory by suggesting a framework that joins behavioural and perceptual models of innovation diffusion and helps to cross-validate them against each other, and to foresight practice by introducing a readiness-based diagnostic approach. Limitations are acknowledged, including the need for quantitative formalisation and deeper empirical validation. This article aims to suggest a new framework and exemplify it with a real market case in retrospect; moreover, the suggested approach does not aim to be predictive, it is designed as descriptive and interpretative, helping gain more insight in the unraveling innovation dynamics, from first signals of possible future to them becoming the new normal. Future research directions include integration with weak-signal frameworks, dynamic modelling, and narrative analysis.