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    Outpacing the Competition: A Design Principle Framework for Comparative Digital Maturity Models
    (SCITEPRESS - Science and Technology Publications, 2025)
    Digital maturity models (DMMs) already have a long history of providing organizations with structured approaches for assessing and guiding their digital transformation initiatives. While descriptive and prescriptive DMMs have seen extensive development, comparatively few models focus on benchmarking digital maturity internally as well as externally across multiple organizations. Moreover, existing literature frequently highlights persistent shortcomings, including limited theoretical grounding, methodological inconsistencies, and inadequate empirical validation. This study addresses these gaps by synthesizing insights from a systematic literature review of 58 publications into a cohesive set of design principles for comparative DMMs. We differentiate between “usage design principles,” which adapt established descriptive and prescriptive DMM components to comparative contexts, and newly formulated principles developed specifically to accommodate implicit data sources and support ongoi ng benchmarking. The resulting framework provides researchers and practitioners with a foundation for designing, evaluating, and selecting comparative DMMs that are more conceptually robust, methodologically sound, and empirically viable. Ultimately, this work aims to enhance the overall maturity and applicability of comparative DMMs in advancing organizational digital transformation.
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    Why Digital Maturity Models Fail: An Exploratory Interview Study Within the Digital Transformation Steering Process
    (SCITEPRESS - Science and Technology Publications, 2025)
    Digital Maturity Models (DMMs) are widely used tools to assess and guide organizational digital transformation (DT). However, their practical contribution to the transformation process often fails due to insufficient stakeholder involvement, inadequate adaptability, or unsuitable assessment tools. This study explores these shortcomings through a socio-technical lens, analyzing why DMMs fail to deliver value in transformation processes. Drawing on an exploratory interview study with experts from the industry, eight key dimensions of failure, such e.g. as misalignment with organizational strategies, cultural resistance, and inadequate iterative usage practices, were identified. These initial results reveal that beyond the design of DMMs, systemic organizational and procedural barriers significantly hinder DMM utility. Building on that, ultimately, a comprehensive framework of utility barriers and derived requirements for building and integrating DMMs should be developed.
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    Scopus© Citations 1
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    Towards Assessing Digital Maturity: Utilizing Real-Time Public Data for Organizational Benchmarking
    This paper details the creation of a novel Comparative Digital Maturity Model (CDMM), enabling organizations to dynamically benchmark their digital maturity against peers by utilizing real-time, publicly available news data sources. Traditional Digital Transformation (DT) models typically rely on static data such as annual reports, interviews, and questionnaires. Ad-dressing this gap, our model adopts a Practice-Based View (PBV) within a Design Science Research (DSR) methodology, ensuring a robust, iterative development process through focus group discussions and expert inter-views in collaboration with industry stakeholders. The results demonstrate that the CDMM effectively captures the evolving nature of DT across sec-tors, providing continuous, up-to-date assessments that overcome the limi-tations of static evaluations.
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    Are Digital Transformation Investments Paying Off? Evidence from the Consumer Staples Industry
    (2025) ;
    Gnos, Basil
    This paper investigates the financial outcomes of digital transformation (DT) investments, distinguishing between short-term market reactions and medium-term effects on valuation and capital costs. Using an event study and panel data analyses in the European consumer goods industry, the re-search shows that single DT announcements do not yield significant ab-normal returns, while sustained digital maturity correlates with higher mar-ket-to-book ratios and lower capital costs. These findings offer potential strategic insights into prioritizing DT investments for competitive ad-vantage.
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    Towards a CNN-Based Method for Improving Long-Term Storability of Apples: A Socio-Technical Approach to Pre-Warehouse Fault Detection
    (2024) ;
    Pfeifer, Magdalena
    Efficient post-harvest management of apple supply chains is critical to min-imize waste and preserve fruit quality, particularly in the storage phase. This study addresses the inefficiency and inaccuracy of defect and disease assessment in Controlled Atmosphere (CA) storage intake, where rapid and reliable evaluation of large quantities is imperative. Existing literature fo-cuses on machine learning applications in pre-harvest crop monitoring, but practical, post-harvest solutions remain underexplored. We propose the de-velopment of a Convolutional Neural Network (CNN) for detecting apple defects that seamlessly integrates into existing CA storage warehousing op-erations. Employing Action Design Research, this interdisciplinary study collaborates with a medium-sized fruit storage enterprise in Styria, Austria, iteratively refining a CNN model through an Action Design Research (ADR) team. This research not only aims to fill the gap between academic methodologies and practical application but also seeks to enhance opera-tional efficiency, demonstrating the real-world utility of advanced machine learning in agriculture.
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    Assessing supply chain resilience using the ISM approach
    This paper aims to increase understanding and simplify the applicability of the concept of supply chain resilience by identifying the variables involved and their interrelationships using the Interpretive Structural Modeling (ISM) approach. A multiple case study approach is used to explore the theoretical foundation and practical application of resilience strategies in seven individual cases. The research provides an overview of companies' resilience practices and formulates hypotheses regarding influencing relationships within these strategies. The results offer insight into the application of the concept of supply chain resilience, providing practitioners with a clearer understanding of the factors involved and their composition.
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