Dynamic Innovation Information System (DIIS) for a New Management Age

Abstract

Innovations are essential for global development and market dynamics. Innovation management is central to organizations for gaining adaptability and dynamic capabilities to ensure their sustainability over time. Right decisions are essential for the implementation of innovations. However, on many occasions, especially in the product development process, decisions are taken based on static analysis, qualitative criteria, questionnaires, and/or quantitative evaluations that are outdated. Moreover, many innovation developments do not consider the existing databases in their information systems of similar innovation projects, especially in the early phases of new innovations when evaluations are mainly driven by area, group, or person. Furthermore, inventions are introduced in different regions, plants, and socio-economic situations, providing different results. In this context, considering that innovations shape our current and future world, including all products and services, as well as how humans, organizations, and machines interact, the significance of the paper is clear. Therefore, it is necessary to develop an innovation management model based on the Viable System Model to cope with any potential future environment based on internal organizational capabilities. For this purpose, the paper designs a Digital Ecosystem for the Fourth Industrial Revolution (DE4.0) based on the Plan-Do-Check-Act methodology applicable to any information system consisting of a digital twin, a simulation model, databases from existing information systems, and quality management techniques. This DE4.0 provides a huge advantage for the applicability and scalability of innovations as it allows one to plan, monitor, assess, and improve. Moreover, based on the conceptual model, a generic project evaluation scheme is developed, providing a platform for innovation project management and control during the whole innovation life cycle. As a result, the research provides a scientific and practical contribution for an integrated management of innovations based on the best information and set of techniques available. Based on this framework, a supply-chain case study is developed. The results show how, depending on the intended goals, the past experiences, the evolution of the innovation, and the innovation scope, indicators can be influenced towards reaching the initial goals and reducing the innovation risks. Finally, a discussion about the potential use and role of the DE4.0 for innovation projects and the related learning process is performed.

Understanding drivers of innovation in information technology companies using a grounded theory approach

“…This study focuses on organizational innovation; as a result, it demonstrates minimal adoption of themes studied at the individual level in the literature, such as Information systems that include blockchain, simulation software for innovation decision-making and Enterprise Resource Planning, due to their limited department-specific usage in IT firms to enhance individual innovation capacity (Saldanha et al , 2020; Moussa and El Arbi, 2020; Kassen, 2022). The extant literature discusses commercial best practices for software processes, process improvement models and Information systems for organizational innovativeness (Szopinski, 2020; Gallego-García, 2022). However, this study explains the factors that influence how the operational process is established and evolves in IT companies and describes how employees peruse these processes as best practices for process improvisation and innovation development.…”

A Maintenance-Based Project Management Approach towards Organizational Sustainability Goals

“…To sum up, it is observed how maintenance and quality have been traditionally considered after the product or/and service design, i.e., when they were already in operation, however a great gap existed on their application since the beginning in the design process. This gap is pursued to be addressed with this paper and complement with digitalization ecosystems for its support [24] to reduce the organizational risks such as the investments in new assets.…”

“…Nowadays, the PMBOK has ten main areas of knowledge [23] and although quality is one of them, there is a gap towards different industrial sectors and supply chains [23]. In this sense and based on the previously defined quality toolkit, it could provide the means for this purpose, while working for its introduction in industry 4.0 environments thanks to the Digital Ecosystems of Industry 4.0 [24].…”

Scientific Approaches and Key Aspects of the Model of Implementation of Innovative Technologies in the Production Management System of Industrial Enterprises

“…У роботі [3] автори підкреслюють важливість управління інноваціями в організаціях. Також наголошується на необхідності створення Цифрової Екосистеми для Четвертої Промислової Революції (DE4.0), що включає цифрові двійники, імітаційне моделювання систем, методи управління якістю для ефективного управління інноваціями.…”