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We analyze economics PhDs’ collaborations in peer-reviewed journals from 1990 to 2014 and investigate such collaborations’ quality in relation to each co-author’s research quality, field and specialization. We find that a greater overlap between co-authors’ previous research fields is significantly related to a greater publication success of co-authors’ joint work and this is robust to alternative specifications. Co-authors that engage in a distant collaboration are significantly more likely to have a large research overlap, but this significance is lost when co-authors’ social networks are accounted for. High quality collaboration is more likely to emerge as a result of an interaction between specialists and generalists with overlapping fields of expertise. Regarding interactions across subfields of economics (interdisciplinarity), it is more likely conducted by co- authors who already have interdisciplinary portfolios, than by co-authors who are specialized or starred in different subfields.
In 2015, the United Nations adopted the Sustainable Development Goals (SDGs), a collection of 17 global objectives to promote economic, social and ecological development in all parts of the world. While the academic discussion on the contribution of companies to the Sustainable Development Goals has recently gained momentum, the role of business-to-business (B2B) partnerships in reaching the SDGs is underexplored, particularly when it comes to North-South relationships. With our research, we aim to fill this gap in the literature by investigating sales partnerships between German manufacturers and their distributors in African markets. Based on a qualitative analysis of 28 interviews with managers of German and African companies, we show that long-term partnerships and job creation, technology transfer, training as well as high standards are significant contributions of companies to achieve the SDGs. While several SDGs such as goals 4,6,13,16 and 17 are addressed by B2B partnership, we also discuss approaches on how the firms’ engagement could be further leveraged and expanded.
This book examines the implementation of the Belt and Road Initiative (BRI) in East Africa. The BRI is considered China's central geopolitical and geo-economic project in the era of President Xi Jinping. Through this work, the author aims to contribute to filling some research gaps, such as the lack of depth in studies of individual BRI projects and the underconsideration of processing narratives in participating countries. The guiding question is the extent to which the BRI is a political or hegemonic project of the CCP-directed state-civil society complex in East Africa. To answer these questions, databases of international organizations and policy documents are analyzed. In addition, the author conducts a qualitative content analysis of newspaper articles from local media houses in the countries of Ethiopia, Kenya, and Tanzania to examine three infrastructure projects. The work illustrates that the BRI contributes to increasing connectivity in East Africa. At the same time, the compression of economic relations and the implementation of infrastructure projects in East Africa lead to numerous consequences and contour a hegemonic project.
The Belt and Road Initiative (BRI) has reinforced China’s business engagement in Sub-Saharan Africa (SSA). While previous international business research focused on the internationalization and investments of Chinese companies, this viewpoint uncovers how both local African and international non-Chinese Small and Medium Sized Enterprises (SMEs) may benefit from and participate in the BRI. A focus is laid on the infrastructure sector accounting for the highest investments since the inception of the BRI in 2013. In a conceptual way, the motives of SMEs to participate in infrastructure project business in the context of the BRI are explored. Investigating the challenges of two large transport infrastructure projects, the business potentials for SMEs become visible. It is argued that SMEs find business potentials particularly as investors, sub-contractors and project management experts in the BRI in Sub-Saharan Africa.
Automatic classification of rotating machinery defects using Machine Learning (ML) algorithms
(2020)
Electric machines and motors have been the subject of enormous development. New concepts in design and control allow expanding their applications in different fields. The vast amount of data have been collected almost in any domain of interest. They can be static; that is to say, they represent real-world processes at a fixed point of time. Vibration analysis and vibration monitoring, including how to detect and monitor anomalies in vibration data are widely used techniques for predictive maintenance in high-speed rotating machines. However, accurately identifying the presence of a bearing fault can be challenging in practice, especially when the failure is still at its incipient stage, and the signal-to-noise ratio of the monitored signal is small. The main objective of this work is to design a system that will analyze the vibration signals of a rotating machine, based on recorded data from sensors, in the time/frequency domain. As a consequence of such substantial interest, there has been a dramatic increase of interest in applying Machine Learning (ML) algorithms to this task. An ML system will be used to classify and detect abnormal behavior and recognize the different levels of machine operation modes. The proposed solution can be deployed as predictive maintenance for Industry 4.0.
Our paper gives first answers on a fundamental question: how can the design of architectures of intelligent digital systems and services be accomplished methodologically? Intelligent systems and services are the goals of many current digitalization efforts today and part of massive digital transformation efforts based on digital technologies. Digital systems and services are the foundation of digital platforms and ecosystems. Digtalization disrupts existing businesses, technologies, and economies and promotes the architecture of open environments. This has a strong impact on new value-added opportunities and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, and social enterprise networks systems are important enablers of digitalization. The current publication presents our research on the architecture of intelligent digital ecosystems and products and services influenced by the service-dominant logic. We present original methodological extensions and a new reference model for digital architectures with an integral service and value perspective to model intelligent systems and services that effectively align digital strategies and architectures with artificial intelligence as main elements to support intelligent digitalization.
Enterprises are currently transforming their strategy, processes, and their information systems to extend their degree of digitalization. The potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems both drives and enables new business designs. Digitalization deeply disrupts existing businesses, technologies and economies and fosters the architecture of digital environments with many rather small and distributed structures. This has a strong impact for new value producing opportunities and architecting digital services and products guiding their design through exploiting a Service-Dominant Logic. The main result of the book chapter extends methods for integral digital strategies with value-oriented models for digital products and services which are defined in the framework of a multi-perspective digital enterprise architecture reference model.
Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This defines the strategical context for composing resilient enterprise architectures for micro-granular digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. Enterprises are presently transforming their strategy and culture together with their processes and information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. In this paper, we are focusing on the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like Internet of Things and Microservices, as part of a new digital enterprise architecture. To integrate micro-granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitalization of services with related products, and their processes.
This chapter presents an introduction to the emerging trends for architecting the digital transformation having a strong focus on digital products, intelligent services, and related systems together with methods, models and architectures. The primary aim of this book is to highlight some of the most recent research results in the field. We are providing a focused set of brief descriptions of the chapters included in the book.