Quantum computing is considered a potentially paradigm-shifting technology with significant long-term economic and societal potential. Despite its still limited technological maturity and numerous unresolved technical challenges, the field is already attracting substantial private and public investment. This development follows the typical pattern of the GARTNER HYPE CYCLE, in which a phase of inflated expectations is often followed by disillusionment once short-term application successes fail to materialize. Consequently, quantum computing faces the risk that current investment and innovation dynamics may decline if realistic and economically relevant application perspectives are not identified. It becomes apparent that such perspectives cannot be unlocked solely through conventional, company-specific applications, but require an expansion of the search space. In particular, new problem areas must be considered in which not only economic but also broader socio-economic value contributions can be generated. Against this background, the dissertation aims to develop a methodology for identifying socio-economic application cases for paradigm-shifting technologies using quantum computing as an example. The methodology is intended to enable potential users to identify problem areas at early stages of technological development in which the use of quantum computing could generate significant long-term socio-economic value. As a result, a methodology was developed that follows the TRIZ-principle of first abstracting specific technological problems and then systematically transferring them to potential application fields through generic problem and solution patterns. In this way, a structured link between technological characteristics and potential application contexts is established. The methodology consists of five interconnected sub-models: problem-related indicators for identifying quantum relevant problem structures, generic application types as abstract solution classes, an application matrix for systematically linking these elements, a socio-economically grounded search space based on selected UN Sustainable Development Goals, and a procedural model for the practical application of the methodology.
Quantum computing is considered a potentially paradigm-shifting technology with significant long-term economic and societal potential. Despite its still limited technological maturity and numerous unresolved technical challenges, the field is already attracting substantial private and public investment. This development follows the typical pattern of the GARTNER HYPE CYCLE, in which a phase of inflated expectations is often followed by disillusionment once short-term application successes fail to materialize. Consequently, quantum computing faces the risk that current investment and innovation dynamics may decline if realistic and economically relevant application perspectives are not identified. It becomes apparent that such perspectives cannot be unlocked solely through conventional, company-specific applications, but require an expansion of the search space. In particular, new problem areas must be considered in which not only economic but also broader socio-economic value contributions can be generated. Against this background, the dissertation aims to develop a methodology for identifying socio-economic application cases for paradigm-shifting technologies using quantum computing as an example. The methodology is intended to enable potential users to identify problem areas at early stages of technological development in which the use of quantum computing could generate significant long-term socio-economic value. As a result, a methodology was developed that follows the TRIZ-principle of first abstracting specific technological problems and then systematically transferring them to potential application fields through generic problem and solution patterns. In this way, a structured link between technological characteristics and potential application contexts is established. The methodology consists of five interconnected sub-models: problem-related indicators for identifying quantum relevant problem structures, generic application types as abstract solution classes, an application matrix for systematically linking these elements, a socio-economically grounded search space based on selected UN Sustainable Development Goals, and a procedural model for the practical application of the methodology.
In the medium- and long-term future, quantum technologies will become a megatrend shaping global industrial value creation. Quantum technologies will open novel pathways for manufacturing systems innovations, while also providing new opportunities for Sustainable Development. Manufacturing companies must already strive for a better understanding of quantum technologies and their potential applications if they are to maintain and improve their competitive advantage in the future. An overview of the theoretical background and state-of-the-art for quantum technologies and manufacturing systems is presented. Fields of application for quantum technologies are explored in the context of relevant manufacturing systems domains. Potential applications are proposed based on an analysis and synthesis of relevant literature, industrial case studies, as well as the authors’ ideations. A case is laid out for how quantum technologies can potentially facilitate industrial symbiosis within limited global ecological boundaries. In other words, the case study describes how Sustainable Development can be potentially facilitated using quantum computing and quantum AI.
Quantum computing environments are composed of heterogeneous layers spanning hardware, software development kits, and applications. Practitioners curating these environments face a fragmented and rapidly evolving landscape with few principled guides for navigation. This paper presents a framework for evaluating quantum computing environment choices through a socio-technical lens, developed using Design Science Research methodology. Drawing on the quantum software engineering literature as well as organizational and socio-technical research, the framework introduces three analytical constructs: gravity wells and their properties, which characterize how certain technologies and structural conditions exert increasing pull on surrounding environment choices, and socio-technical desiderata, which articulate the normative goals against which those pulls can be evaluated. The framework supports practitioners in making deliberate, context-aware environment choices that preserve architectural flexibility and support the evolutionary development of the field. Demonstration and evaluation of the framework is conducted through exemplary cases. The contribution advances both the theory of quantum ecosystems and the practical guidance available to organizations and practitioners navigating the current, evolving field of quantum computing.
The rapid advancements in quantum computing hold transformative potential for addressing critical global challenges and achieving sustainable development. This paper presents a conceptual framework that aligns quantum computing innovations with the United Nations Sustainable Development Goals (SDGs). It explores key areas such as renewable energy optimization, smart city infrastructure, and climate change mitigation. The study also emphasizes sustainability challenges, including environmental impacts, ethical concerns, and socio-economic considerations like workforce transitions and digital equity. A novel Carbon-aware Quantum Computing model is introduced to minimize the environmental footprint of quantum systems. Finally, the paper proposes a roadmap for ethical and scalable adoption of quantum technologies, ensuring inclusive and resilient societal growth.
Quantum computing has been rapidly evolving as a field, with innovations driven by industry, academia, and government institutions. The technology has the potential to accelerate computation for solving complex problems across multiple industrial sectors. Finance and economics, with many problems exhibiting computationally heavy requirements, comprise a high-profile sector where quantum computing could have a significant impact. Therefore, it is important to identify and understand to what extent the technology could find utility in the sector. This technical review is written for quantum applications researchers, quantitative analysts in finance and economics, and researchers in related mathematical sciences. It is divided into two parts: (i) a survey of quantum algorithms pertinent to problems in finance and economics, and (ii) mapping of several use cases in the sector to the potential quantum algorithms presented in part (i). We discuss some challenges on the pathway to achieving quantum advantage. Ultimately, this review aims to be a catalyst for interdisciplinary research that will accelerate the advent of the practical advantages of quantum technologies to solve complex problems in this sector.
Quantum computing has evolved from a largely theoretical discipline into a field of growing interest for commercial and industrial applications. Recent advances in quantum hardware, algorithms, and cloud-based access have enabled early experimentation outside academic environments, raising questions about its potential impact on real-world decision-making and operational problems. This paper provides an overview of the current state of quantum computing with a focus on its emerging relevance in commercial contexts. It examines the categories of problems that have attracted attention from industry, particularly those involving high combinatorial complexity such as optimization, scheduling, logistics, and resource allocation. The analysis also reviews the global landscape of companies and initiatives engaged in quantum computing, highlighting different technological approaches, maturity levels, and regional characteristics. In parallel, the paper discusses the principal challenges and limitations that constrain widespread adoption, including hardware immaturity, algorithmic readiness, cost factors, and organizational requirements. By considering both opportunities and risks, this study aims to present a balanced and realistic perspective on the role quantum computing may play in business environments. The objective is to clarify the current position of quantum computing within the broader technological landscape and to support informed interpretation of its potential, limitations, and future trajectory in commercial applications.
Quantum technologies (QTs) hold the promise to transform a wide range of industries, such as computing, communications, finance, healthcare, defense, space, and beyond. Of the various QTs, the most relevant is presently quantum computing (QC), of significant projected market potential, with some estimates forecasting it to reach many billion dollars over the next few years. There are, however, risks to factor, as highlighted in this perspective, the most relevant technical, economic, and societal risks. Those financial and societal are projected to become increasingly relevant phased with the progressing solution of the technical issues. The synergy with artificial intelligence comes with further opportunities as development can be faster and more effective, but also increases risks. AI presents numerous opportunities, but it also comes with several risks and challenges. Some of the major risks associated with AI include bias and fairness, transparency and explainability, job displacement, security concerns, ethical concerns, privacy issues, lack of regulation and standards, and exponential growth and unintended consequences. Balancing the advantages of AI-driven quantum technologies with associated risks presents a significant challenge. It necessitates careful consideration of ethical, economic, and technical aspects to ensure that these technologies are developed and deployed in a manner that is beneficial and equitable for everyone. Graphical Abstract