Using the howey test as an identifier of innovative activity

Abstract

The article explores the applicability of the Howey test as an identifier of innovative activity in the field of digital intellectual property assets. The purpose of the study is to substantiate the classification of copyright-based digital intellectual assets as objects of innovative activity through a comprehensive analysis of compliance with all four conditions of the Howey test, taking into account the specifics of the digital economy and network-based market structures. It is established that investment in digital intellectual assets involves the allocation of financial and intangible resources to the creation, structuring, legal formalization and commercialization of digital media files, which, through the incorporation of ownership attributes and metadata, are transformed into full-fledged assets with measurable economic value. The study demonstrates that the common enterprise within this innovation process is represented by specialized network intermediaries whose portfolios are formed as an aggregation of individual authors’ and investors’ portfolios and function as a collective form of intellectual capital. The existence of profit expectation is justified by the mechanism of repeated licensing of digital assets, while the dependence of income on the activity of a promoter is confirmed by the intermediary’s role in market exposure, pricing, promotion, transaction processing and copyright protection. It is shown that the uniqueness of digital intellectual assets, the non-standardized nature of demand and the high level of uncertainty significantly increase investment risk, which is a defining characteristic of innovative activity. The paper proposes an interpretation of the formation and continuous updating of internal, external and administrative metadata as a process of information quality enhancement that reduces uncertainty and increases the innovative attractiveness and revenue potential of digital intellectual assets. The obtained results contribute to the development of theoretical approaches to innovation studies in the digital economy and may be applied in designing models for evaluating and managing portfolios of digital intellectual assets.