O33 - Technological Change: Choices and Consequences; Diffusion ProcessesReturn

Global mergers and faster business cycles create weakly harmonized supply chain (SC) systems. Industry 4.0’s smart digitalization opportunities significantly alter business model innovation rates. Consequently, the complexity of aligning value exploration and exploitation has increased, often missing the needed integration level. A holistic systems engineering (SE)-driven methodology for innovation, transformation, and optimizing smart SC systems is not available so far. Case studies at SAP SE's development organization for Industry 4.0 SCM solutions and three automotive companies explored objectives, obstacles, and methods for digital transformation. The results were synthesized into a holistic SC business model transformation and optimization methodology. Complementary to traditional SCM, the study proposes SE-driven meta-modelling to improve the performance, resilience, and synchronization of end-to-end supply chains. Moreover, holistic simulations and evaluation methods for the ambidexterity of SC business models have been developed, enhancing the effectiveness of value exploration and exploitation, and innovation productivity by holistically viewing emergence and convergence throughout SC capabilities' life cycles. Ambidexterity management and dynamic capabilities are addressed by SE methods like capability engineering and complex dynamic systems theory, integrated into a concise SE model.

This study aims to prove the factors that affect learning outcomes achievement of management accounting courses. The sample is accounting students at four major universities in East Java, Indonesia. The questionnaire was filled out using a Google form, and the number of samples was 417 respondents. Hypothesis testing using partial least squares. Nine hypotheses were tested with gender as a moderating variable. Performance expectations and effort affect student intensity and subsequently affect active participation. Changes in facilitation conditions and the level of participation affect the achievement of learning outcomes. Different from prediction, gender was not shown to be a moderating variable.

The use of digital technologies for state-relevant institutions, government organisations and administrations has grown steadily in recent decades. Therefore, the question arises whether the mastery of these technologies has an influence on a state’s ability to act and whether state sovereignty is affected. In the European Union, the concept of digital sovereignty of states is being intensively discussed. However, it is unclear what exactly is meant by the term digital sovereignty and how it can be defined. The research gap is the lack of a clear qualitative and quantitative definition of that term, so that the goal of the article is to provide an overview of a qualitative definition. That is the basis for a quantiative model. To achive that goal a hierarchical component model is developed for concretisation. Furthermore, the components are decomposed into sub-components, each of which is then quantified by suitable metric parameters, which are populated from secondary data sources for states and subjected to selected quantitative analyses. To verify and validate whether the component model and the parameters are suitable and robust for measuring digital sovereignty, a comparative index is formed and compared with existing indices.

Technostress as an academic domain has evolved significantly since year 1984. Based on the systematic literature review (SLR), eight determinants of technostress were identified which were classified into individual and organizational categories. Individual determinants were further divided into demographic, psychographic and cognitive categories. Outcome of the SLR was the development of a comprehensive framework of technostress. This study can facilitate the top management and the HR managers of organizations to adopt appropriate change management interventions while implementing and augmenting new technologies.