Business models in servitization

This chapter sheds light on the different business models of manufacturing companies that have servitized their business operations. This chapter presents four distinctive yet simultaneously pursued business models for servitized manufacturers: (1) the product business model, (2) the service-agreement business model (3) the process-oriented business model, and (4) the performance-oriented business model. Depending on the direction taken, dedicated customer needs targeted, value propositions adopted, and services and solutions provided, a servitized manufacturer should decide which business model(s) the firm will adopt with different customers.fi=vertaisarvioitu|en=peerReviewed

Blockchain and Organizational Characteristics : Towards Business Model Innovation

Blockchain seems to challenge the current business models by providing opportunities for new value creation. However, several research gaps remain in literature in evaluating how firms can leverage new approaches to innovation management and opportunities created by blockchain. Supporting organizational characteristics affecting digital innovation management process also need attention in order to challenge the traditional theories while developing unique fundamental assumptions between innovation processes and outcomes. Thus, blockchain and organizational characteristics need to be understood as an encompassing, overarching and interrelated ecosystem in digital innovation management. Grounding on digitalization and innovation management, this research conceptualizes how blockchain technology and supporting organizational characteristics (i.e., R&D investment, strategic alignment, cultural support, top management knowledge and involvement, insights from customers and end-users) can be integrated for business model innovation. This research develops a conceptual framework involving multi-disciplinary collaborative actions that strengthen and empower business model innovation.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Creativity, Innovation, Entrepreneurship and Communication of Design: Proceedings of the AHFE 2020 Virtual Conferences on Creativity, Innovation and Entrepreneurship, and Human Factors in Communication of Design, July 16-20, 2020, USA. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-51626-0_9.fi=vertaisarvioitu|en=peerReviewed

Extensive Copy-Number Variation of Young Genes across Stickleback Populations

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Key Factors on Utilizing the Production System Design Phase for Increasing Operational Performance

Production system lifecycle includes phases ranging from concept pre-study to ramp-up and operations. Manufacturing companies often face challenges to reach operational performance targets during ramp-up time and operation phase. The design phase is considered crucial as major decisions related to the future production system are taken during this phase. There is an opportunity to utilize the production system design phase to improve the operational performance during both the ramp-up and operation phase. This research aims to identify the critical factors of the design process that affect the performance in the ramp-up and operational phase. A case study was conducted in a pharmaceutical company where a completed project of launching a new production line for a new product was followed in retrospect. Data were collected by conducting interviews with different members involved in the project and the production team on the shop floor. By qualitative data analysis, critical factors affecting the project´s operational performance were identified; such as level of internal technical competency; involvement level of future line manager, operator and project sponsor within the project team; project team´s competency; pre-study of the business case; time pressure to complete the project; expertise of product and process; organization’s continuous improvement culture; and relationship with the supplier. © 2020, IFIP International Federation for Information Processing.QC 20200930</p

MES Implementation: Critical Success Factors and Organizational Readiness Model

Part 10: ICT for Collaborative ManufacturingInternational audienceManufacturing Execution Systems (MES) have evolved to alleviate the drawbacks of Enterprise Resource Planning (ERP) systems by providing real-time information exploitation from the shop floor. In parallel with the increasing number of companies adopting MES, MES vendors have exponentially increased over the past two decades. While companies tend to focus merely on the technological aspects of the MES implementation, the adoption of MES implies an organizational transformation process that needs to be properly addressed by companies for implementation success. This is important because the new functions, services, and operability offered by the MES needs to be aligned with existing business processes and practices. Considering the human, technological, and organizational aspects holistically, this paper outlines critical success criteria and proposes an organizational readiness model for MES implementation

A case study of user adherence and software project performance barriers from a sociotechnical viewpoint

A marine propeller company and a technical university collaborated to optimize the company’s existing propeller design software. This paper reviews the project based on a sociotechnical perspective to organizational change on (a) how the university-company project and user involvement were organized, and (b) what the main management barriers were and why they may have occurred. Fieldwork included interviews and observations with university and company stakeholders over thirteen months. The data was analyzed and sorted into themes describing the barriers, such as lack of a planned strategy for deliverables or resource use in the project; the users exhibited low adherence towards the optimized software, as well as there was limited time and training allocated for them to test it. Lessons learned suggest clarifying stakeholder roles and contributions, and engaging the users earlier and beyond testing the software for malfunctions to enhance knowledge mobilization, involve them in the change and increase acceptance