O31 - Innovation and Invention: Processes and IncentivesReturn

The research presented aims to close a gap in the measurement of digital maturity for the domain of service which was identified through a systematic literature review. The study provides a holistic Digital Service Transformation Maturity Self-Assessment Model for service provider companies in a B2B-context based on analysis of different digital maturity models and by means of a qualitative approach through expert feedback in a Delphi-process and additional complementary literature review to define maturity assessment items. The presented Digital Service Transformation Maturity Model comprises 8 factors, 27 subfactors and 403 related specific assessment items describing digital maturity from a holistic point of view. The model has been further converted into a simple and practical tool to self-assess and visualize current state of digital maturity. The assessment model finally was pilot tested and the outcomes are also outlined in this article. The designed model provides practical implications for the ease of evaluating and improving digital maturity levels in every aspect of its factors and contributes to the successful management of digital transformation in service provider organizations by offering effective guidance how to move to the desired future maturity level based on a solid understanding of current digital maturity accomplishments.

This study explores how supply chain management (SCM) information system (IS) capabilities can lead to superior business performance, and what are the detailed capabilities and methods to master volatility and uncertainties in business environments. Key concepts in SC modelling have been identified for decreasing SC complexity and increasing SC agility and key methods for supply network planning and synchronisation for optimising business performance and objectives that are often contradicting at the same time. The study developed a best practice recommendation for profit-optimised SCM for companies with capital intensive and capacity constrained resources such as in the steel companies and others of the industry, and for managing their integration between SC domains and between technological and organisations' needs simultaneously. Finally, the study shows how Industry 4.0 innovations such as Smart Services and blockchain technology can provide new value potentials such as cross-organisational network effects and increased autonomy in SC ecosystems, and concludes with suggestions for further research in needed rules and semantics for SC ecosystem collaboration.

Scarcity, or limited resources, is the fundamental economic problem the humanity faces continuously. Without it, economics would be meaningless. Science-fiction literature depicts societies where abundance is becoming persistent feature. Humans no longer participate in the production process itself, machines become sentient thanks to artificial intelligence and everyone has access to all goods and services desired. Scarcity as a multiple-born phenomenon, namely originating with labour and land, has been eradicated. Everyone is fully satisfied, exchange is non-existing, the medium of exchange - money - is no longer required. This paper compares some of the most representative economic thoughts in science - fiction genre since 1910s. Main purpose is to identify whether the societies have really achieved post-scarcity or they are only transitional theories, suffocating from still-present scarcity. Results of the paper suggest that even though the societies look like and are presented as they achieved post-scarcity, they are still experiencing scarcity in certain forms and use a medium of exchange to redistribute resources. This implies that these theories rather depict a socialistic utopia than a fully emerged post-scarcity society, even in the most progressive novels scarcity still occurs. Only the Culture series indicate signs of fully developed post-scarcity era.

A model for managing strategic alignment and dynamic capabilities (DC) of Supply Chain Management (SCM) information systems (IS) has been developed and applied to a traditional German steel company and a highly innovative Austrian steel company. Different concepts of leading researchers have been combined to get a holistic and detailed view of IS capabilities' impact on strategic fit. The model enables companies to identify ideal levels to strategic fit needed from SC integration and its antecedents for predefining architectural artefacts as sources for dynamic capabilities. The study contributes to new insights into the IT productivity paradox, where possibilities from IS investments remain unused. Essential concepts for optimising SC performance by reducing SC complexity and increasing SC agility have been identified and integrated. The study highlights value enabler and Artificial Intelligence (AI) methods of digital SC models and how the model's ontology can be used to increase alignment autonomy. Finally, the approach supports organisational learning and development of cognitive profiles through collective assimilation and sensemaking effects.

This exploratory study addresses the need to identify specific and holistic upfront expectations into industrial value engineering projects for best tailored preparation of an efficient project execution. The analysis includes a total base population of 90 projects, which were conducted between 2010 and 2018 in 16 different industries. Out of those, 63 projects had a narrower value engineering context and have been analyzed with the support of a CAQDAS tool (Computer Assisted Qualitative Data Analysis Software). Analytical results show that participants' expectations in value engineering projects vary depending on their industrial environments, but cope with existing studies on critical success factors for project management. Based on the findings the author recommends further research on fast project execution, closing the gap between trainingand project content as well as emphasizing the necessity of rigor with regards to the utilization and application of terminology, which includes sharpening the correct interpretation of value engineering, its tools and contents.