Zhongjie Wang

Bio: Zhongjie Wang is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Service (business) & Service system. The author has an hindex of 15, co-authored 143 publications receiving 806 citations.

A Survey of Business Component Identification Methods and Related Techniques

Abstract: With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem. Keywords—Business component, component granularity, component identification, reuse performance.

Model-based approaches for interoperability of next generation enterprise information systems: state of the art and future challenges

Abstract: Enterprise businesses are more than ever challenged by competitors that frequently refine and tailor their offers to clients. In this context, enterprise information systems (EIS) are especially important because: (1) they remain one of the last levers to increase the performance and competitiveness of the enterprise, (2) we operate in a business world where the product itself has reached a limit of performance and quality due to uniform capacity of industrial tools in a globalized economy and (3) the EIS can increase the product value thanks to additional digital services (built on data associated to the product) in order to meet and fit better client's needs. However, the use of EISs reaches a limit in collaborative environments because enterprises management methods diverge and EISs are mainly inflexible resource packages that are not built with an interoperability objective. Consequently, we need to make EISs interoperable in order to achieve the needed gains competitiveness and performance. This paper contribution can be summarized as follows: (1) it relates existing work and it examines barriers that, at the moment, are preventing further improvements due to current methodological and technological limits, and (2) it proposes a conceptual framework and five challenges that model based approaches must overcome to achieve interoperability between EIS in the near and long term.

Novel Artificial Bee Colony Algorithms for QoS-Aware Service Selection

Abstract: Service selection is crucial to service composition in determining the composite Quality of Service (QoS). The proliferation of composable services on the Internet and the practical need for timely delivering optimized composite solutions motivate the adoption of population-based algorithms for QoS-aware service selection. However, existing population-based algorithms are generally complicated to use, and often used as a general approach to solving different optimization problems. We propose to develop specialized algorithms for QoS-aware service selection, based on the artificial bee colony algorithm (ABC). ABC is a new and simpler implementation of swarm intelligence, which has proven to be successful in solving many real-world problems, especially the numerical optimization problems. We develop an approximate approach for the neighborhood search of ABC, which enables effective local search in the discrete space of service selection in a way that is analogical to the search in a continuous space. We present three algorithms based on the approach. All the three algorithms are designed to improve the performance and meanwhile preserve the simplicity of ABC. Each algorithm applies a different technique to leverage the unique characteristics of the service selection problem. Experimental results show higher accuracy and convergence speed of the proposed algorithms over the state of the art algorithms.

Genetic algorithm for collaboration cost optimization-oriented partner selection in virtual enterprises

Abstract: Partner selection is a key step to organize a well-designed virtual enterprise in which collaboration cost between partners is considered to be one of the most important performance indicators that influence the run-time efficiency of virtual enterprise However, in current solutions there is usually a lack of precise and comprehensive considerations on the collaborations, which makes the selection results not optimal enough The paper elaborately analyses various collaboration patterns between distributed partners with the corresponding evaluation metrics for collaboration time and cost A genetic algorithm solution for collaboration cost optimization-oriented partner selection is then developed The performance of this algorithm is demonstrated by a case, and the results of this trial demonstrate the real life capability of the algorithm

The Oxford Handbook of Innovation

Abstract: This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective

Abstract: The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the processand supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-PhysicalSystems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decisionmakers to assess their need for transformation towards Industry 4.0 practices. Keywords—Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain. Malte Brettel, chairholder, is with the Aachen University (RWTH), Kackertstraße 7, 52072 Aachen (e-mail: brettel@win.rwth-aachen.de). Niklas Friederichsen is with the Aachen University (RWTH), Kackertstraße 7, 52072 Aachen, (corresponding author; phone: +49/(0)241 80 99397; e-mail: friederichsen@win.rwth-aachen.de). Michael Keller and Marius Rosenberg are with the Aachen University (RWTH), Kackertstraße 7, 52072 Aachen (e-mail: keller@win.rwthaachen.de, rosenberg@win.rwth-aachen.de).

Enterprise Systems: State-of-the-Art and Future Trends

Abstract: Rapid advances in industrial information integration methods have spurred tremendous growth in the use of enterprise systems. Consequently, a variety of techniques have been used for probing enterprise systems. These techniques include business process management, workflow management, Enterprise Application Integration (EAI), Service-Oriented Architecture (SOA), grid computing, and others. Many applications require a combination of these techniques, which is giving rise to the emergence of enterprise systems. Development of the techniques has originated from different disciplines and has the potential to significantly improve the performance of enterprise systems. However, the lack of powerful tools still poses a major hindrance to exploiting the full potential of enterprise systems. In particular, formal methods and systems methods are crucial for modeling complex enterprise systems, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of enterprise systems as they relate to industrial informatics.