Related papers: The trickle down from environmental innovation to …
Research in Data Envelopment Analysis has created rankings of the ecological efficiency of countries' economies. At the same time, research in economic complexity has provided new methods to depict productive structures and has analyzed how…
The concept of traceability between artifacts is considered an enabler for software project success. This concept has received plenty of attention from the research community and is by many perceived to always be available in an industrial…
Despite our familiarity with specific technologies, the origin of new technologies remains mysterious. Are new technologies made from scratch, or are they built up recursively from new combinations of existing technologies? To answer this,…
A fundamental question in the conjunction of information theory, biophysics, bioinformatics and thermodynamics relates to the principles and processes that guide the development of natural intelligence in natural environments where…
This paper studies the macroeconomic effects of news about future technological advancements in the green sector. Utilizing the economic value of green patents granted to publicly listed companies in the U.S., we identify green technology…
Artificial Intelligence is increasingly pervasive across domains, with ever more complex models delivering impressive predictive performance. This fast technological advancement however comes at a concerning environmental cost, with…
Targeting sustainability in our industrial society requires integrating specific criteria in the design process of products and processes. A paradigm shift is necessary in the economical, social and political systems to ensure the natural…
As sustainability takes center stage across businesses, green and energy-efficient choices are more crucial than ever. While it is becoming increasingly evident that software and the software industry are substantial and rapidly evolving…
The environmental sustainability of Information Technology (IT) has emerged as a critical concern, driven by the need to reduce both energy consumption and greenhouse gas (GHG) emissions. In the context of cloud-native applications deployed…
We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition…
Models on innovation, for the most part, do not include a comprehensive and end-to-end view. Most innovation policy attention seems to be focused on the capacity to innovate and on input factors such as R&D investment, scientific…
How does technological interdependence affect innovation? We address this question by examining the influence of neighbors' innovativeness and the structure of the innovators' network on a sector's capacity to develop new technologies. We…
This study shows evidence for collaborative knowledge creation among individual researchers through direct exchanges of their mutual differentiated knowledge. Using patent application data from Japan, the collaborative output is evaluated…
The sustainability impacts of ICT systems are difficult to assess and govern due to structural complexity, fragmented measurement practices, and unclear responsibilities across system layers. We argue that these challenges cannot be…
The immense technological progress in artificial intelligence research and applications is increasingly drawing attention to the environmental sustainability of such systems, a field that has been termed Green AI. With this contribution we…
Technological knowledge evolves not only through the generation of new ideas, but also through the reinterpretation of existing ones. Reinterpretations lead to changes in the classification of knowledge, that is, reclassification. This…
We analyze the curriculum of the early common-years of engineering in our institute using tools of statistical physics of complex networks. Naturally, a course programme is structured in a networked form (temporal dependency and…
This study investigates entropy's potential for analyzing scientific research patterns across disciplines. Originating from thermodynamics, entropy now measures uncertainty and diversity in information systems. We examine Shannon Entropy,…
Process mining is a research area focusing on the design of algorithms that can automatically provide insights into business processes. Among the most popular algorithms are those for automated process discovery, which have the ultimate…
The growing adoption of Industrial Internet of Things (IIoT) technologies enables automated, real-time collection of manufacturing process data, unlocking new opportunities for data-driven product development. Current data-driven methods…