Realizing desired effects from digitized product affordances: A case study of key inhibiting factors

Despite the potential of IoT-enriched digitized products, firms struggle to generate desired impact. We investigate the alignment of actualized digitized product potentials (i.e., affordances) with organizational goals, examining how the emergence of critical inhibiting factors affect the generation of desired effects. We conduct an embedded single case study of four actualized digitized product potentials within a professional equipment manufacturer and explore how the emergence of inhibiting factors prevents the generation of desired effects. Using Necessary Condition Analysis (NCA), six key inhibiting factors are identified. Our findings contribute to affordance theory and digital innovation research in three ways: a) we provide an extended affordance-actualization model that theorizes the process by which emerging key inhibiting factors are addressed via the implementation of (re-)actions to generate desired effects that are aligned with the organizational goals of actualized digitized product potentials, (b) we identify six key inhibiting factors that affect the generation of desired effects and that re-examine the role of data with respect to the “technology” element in affordance theory, and (c) we apply NCA to affordance theory for the first time and show how it can contribute to identifying critical factors during the realization of technology potentials. • Literature review: We have added more detail in appendix A about how we conducted our systematic literature review. • Formulation of propositions in Table 1 : To avoid redundancy in the formulation of the propositions, we have rewritten the propositions in the table creating three high-level propositions for each category and relating them to the investigated subfactors. • Contribution to digital innovation management: We have rewritten parts of the contribution to clarify how our findings add to the body of literature.

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Publication Details

Journal
Decision Support Systems
Published
2024-11-04
DOI
https://doi.org/10.1016/j.dss.2024.114365
Citations
5
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.64
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article

Realizing desired effects from digitized product affordances: A case study of key inhibiting factors

Martin Mocker, Jan Dul, Eric van Heck, Ainara Novales
5 citations
Decision Support Systems
Big Data and Business Intelligence
2.64
article

Realizing desired effects from digitized product affordances: A case study of key inhibiting factors

Martin Mocker, Jan Dul, Eric van Heck, Ainara Novales
article en
5 citations

Abstract

Despite the potential of IoT-enriched digitized products, firms struggle to generate desired impact. We investigate the alignment of actualized digitized product potentials (i.e., affordances) with organizational goals, examining how the emergence of critical inhibiting factors affect the generation of desired effects. We conduct an embedded single case study of four actualized digitized product potentials within a professional equipment manufacturer and explore how the emergence of inhibiting factors prevents the generation of desired effects. Using Necessary Condition Analysis (NCA), six key inhibiting factors are identified. Our findings contribute to affordance theory and digital innovation research in three ways: a) we provide an extended affordance-actualization model that theorizes the process by which emerging key inhibiting factors are addressed via the implementation of (re-)actions to generate desired effects that are aligned with the organizational goals of actualized digitized product potentials, (b) we identify six key inhibiting factors that affect the generation of desired effects and that re-examine the role of data with respect to the “technology” element in affordance theory, and (c) we apply NCA to affordance theory for the first time and show how it can contribute to identifying critical factors during the realization of technology potentials. • Literature review: We have added more detail in appendix A about how we conducted our systematic literature review. • Formulation of propositions in Table 1 : To avoid redundancy in the formulation of the propositions, we have rewritten the propositions in the table creating three high-level propositions for each category and relating them to the investigated subfactors. • Contribution to digital innovation management: We have rewritten parts of the contribution to clarify how our findings add to the body of literature.

Decision Support SystemsVol. 189
IIT@MIT (US), Reutlingen University (DE), Erasmus University Rotterdam (NL)
Openalex Percentile: Top 8%
Big Data and Business Intelligence
2.64
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