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1
Trachenko, M. B., and O. D. Gaisha. "Evaluation of the Effectiveness of Financing Industrial Clusters." Russian Economic Journal, no. 5 (November 2019): 36–47. http://dx.doi.org/10.33983/0130-9757-2019-5-36-47.
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The article is solving an actual problem — development of a system of indicators to evaluate the effectiveness of financing industrial clusters in Russia. The article analyzes the cluster models of Russian and foreign authors, identifies their strengths and weaknesses. A universal information model of the cluster was developed, reflecting the interaction of the participants among themselves and with external stakeholders of the cluster development. The developed model has three control loops: internal cluster stakeholders, cluster, cluster's region. Each has the specificity of the movement of inventory and cash flows, information interaction in the implementation of cluster policy, and reflects the interests of various stakeholders of industrial clusters. The model lays the groundwork to justify a three-tier system of indicators to evaluate the effectiveness of financing industrial clusters. The subsystems of the indicators of the impact of the industrial cluster on the regional economy, of the indicators of the industrial cluster development and the subsystem of the indicators of the financial condition of enterprises participating in the industrial cluster are highlighted in the proposed system. The study used the methods of bibliographic and logical analysis, synthesis and systems approach, mathematical methods of statistical data processing. The developed system of indicators for assessing the effectiveness of financing industrial clusters can be used to conduct current and subsequent monitoring of financing the implementation of cluster programs, to prepare decisions on the allocation of budgetary funds by state and municipal authorities, and to potential investors to determine the most promising investment instruments.
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ABLYAMITOVA, A. L. "OPPORTUNITIES FOR THE FORMATION OF INTEGRATION SYSTEMS IN THE AGRO-INDUSTRIAL COMPLEX." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 2, no. 5 (2021): 47–54. http://dx.doi.org/10.36871/ek.up.p.r.2021.05.02.009.
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The paper substantiates the theoretical foundations of the formation of agricultural territorial-industrial cluster associations, the mechanism of their effective functioning and ensuring the competitiveness of integrated business entities. The structural model of the regional association of agro-industrial clusters and cooperatives is justified. The proposed model of regional cluster integration includes industry-specific product clusters. It is proposed to create an agricultural service cooperative at the village level, and a multifunctional service cooperative at the district level.
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Li, Rongsheng, and Nasruddin Hassan. "Information retrieval algorithm of industrial cluster based on vector space." Open Physics 17, no. 1 (March 28, 2019): 60–68. http://dx.doi.org/10.1515/phys-2019-0007.
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AbstractThe current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption. Thus, in this paper, a information retrieval algorithm based on vector space for industrial clusters is proposed. By optimizing the unlawful labels in the database network, dividing the web pages of the industrial cluster information database and calculating the keyword scores of the relevant information of the industrial cluster corresponding to a web page, a set of well-divided database pages is obtained, and the purification of the industrial cluster information database is realized. According to the purification of industrial cluster information database, RFD algorithm is used to extract the page data features of purified industrial cluster information database. The extracted results are substituted into the information retrieval, and the vectors composed of retrieval units are used to describe the information of various types of industrial clusters and each retrieval. The matching results of information retrieval are obtained by calculating the correlation between the information of industrial clusters and the query, and the information retrieval of industrial clusters is completed. Experimental results show that the algorithm has high precision and recall ratio, short retrieval time and low energy consumption.
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TYUKAVKIN, N. M. "MODELING OF INNOVATIVE ACTIVITY IN THE REGIONAL INDUSTRIAL COMPLEX." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 6 (2020): 111–18. http://dx.doi.org/10.36871/ek.up.p.r.2020.06.01.016.
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The article discusses the economic and managerial issues of modeling domestic innovation in industry. The linear and nonlinear modeling of innovation is disclosed. The stages of the innovation life cycle are investigated, the structure of innovative projects is considered, the procedure for selecting innovative projects is proposed, the selection scheme is presented, which is the basis for modeling technical complexes and technological activities for various purposes. The theoretical aspects of modeling, the practice of organizing modeling on the example of the Samara region are considered. To solve the problems of developing the economy of the Samara region, a comprehensive transition to the path of innovative development and the creation of a knowledge-based economy is necessary. The model of innovative development of the industrial complex of the region proposed by the author integrates the efforts of state authorities and industrial business in the formation and development of high-tech clusters. It follows that the priority task in this area is the creation of a new regional innovation system. The most significant result of the work is the proposal to organize a cluster model of innovative activity in the region, to create a cluster innovation infrastructure. It is noted that the innovative model for the development of industry in the region must be built using the innovative potential of industrial clusters, as well as on the basis of clusters to form the innovative infrastructure of the region. Clusters, having a significant innovative potential in their structure, diffuse innovations into other economic systems of the region. For this purpose, the author proposes to create an innovation development center in the cluster in order to coordinate innovative activity of both enterprises resident in the cluster and other industrial structures of the region. A mechanism is proposed for implementing the model of innovative development of the region, in which system benchmarks are set by the levels of resource, industrial, investment and innovative potentials of the region. Based on a comprehensive analysis of the region’s potential and “growth poles” for the development of innovative activity, the parameters of innovative development are compared with the criteria base.
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Liu, Xiao Tie. "On Industrial Cluster Development of Industrial Parks: A Case Study of Jiangxi Province in China." Applied Mechanics and Materials 55-57 (May 2011): 2003–8. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.2003.
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This paper analyzes the current development of industry clusters of the industrial parks in Jiangxi. It is found that most of the industrial parks are in the stage of agglomeration, others are in the transitional phase from agglomeration to cluster and the remaining, namely about the one-third industrial parks, are still in the concentrated phase. There is a large gap between the development of the industrial parks in Jiangxi and the requirements of industry clusters, which is embodied in the fact that the industrial structures converge, the growth of industrial chain is incomplete and the supporting system of production is imperfect. Finally, the countermeasures are proposed from the perspective of the government to promote the development of industry clusters of the industrial parks in Jiangxi. These countermeasures mainly are to make the industrial orientation clear, to plan a good industrial layout, to develop the industrial parks based on the mechanism of industriy clusters, to actively explore appropriate development models, to strengthen the construction of industrial supporting system and to create an innovation environment for industry clusters in the industrial parks.
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Yu, Haiying, Minghui Jiang, and Chengzhang Li. "Chaos theory perspective for industry clusters development." Modern Physics Letters B 30, no. 08 (March 30, 2016): 1650112. http://dx.doi.org/10.1142/s0217984916501128.
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Industry clusters have outperformed in economic development in most developing countries. The contributions of industrial clusters have been recognized as promotion of regional business and the alleviation of economic and social costs. It is no doubt globalization is rendering clusters in accelerating the competitiveness of economic activities. In accordance, many ideas and concepts involve in illustrating evolution tendency, stimulating the clusters development, meanwhile, avoiding industrial clusters recession. The term chaos theory is introduced to explain inherent relationship of features within industry clusters. A preferred life cycle approach is proposed for industrial cluster recessive theory analysis. Lyapunov exponents and Wolf model are presented for chaotic identification and examination. A case study of Tianjin, China has verified the model effectiveness. The investigations indicate that the approaches outperform in explaining chaos properties in industrial clusters, which demonstrates industrial clusters evolution, solves empirical issues and generates corresponding strategies.
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Tavares, Maryana Scoralick De Almeida, Cláudia Fabiana Gohr, Sandra Morioka, and Thereza Rakel da Cunha. "Systematic literature review on innovation capabilities in clusters." Innovation & Management Review 18, no. 2 (March 22, 2021): 192–220. http://dx.doi.org/10.1108/inmr-12-2019-0153.
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Purpose This paper aims to map literature about innovation capabilities (IC) taking into consideration industrial clusters to propose a conceptual framework that synthetizes the main factors and subfactors responsible for ICs; in addition, the paper also proposes a research agenda. Design/methodology/approach A systematic literature review (SLR) was performed; academic papers were analyzed qualitatively and quantitatively. Findings The authors provide a descriptive analysis followed by a thematic synthesis, in which we present 05 enablers and 20 critical factors (CF) of IC in clusters. The proposed framework emphasizes what needs to be done or improved to increase IC in cluster-based companies. Based on this systematic review and the framework proposed, the authors identified opportunities for future research. Research limitations/implications The enablers and CF identified through SLR were not validated empirically. Therefore, future studies on the current topic are required to validate the framework by investigating which factors are more relevant to cluster-based companies that intend to improve their innovative performance. Practical implications The present findings have important implications for the identification of the factors and subfactors that may contribute to the development of IC, which may help managers and decision-makers in recognizing which factors are the most responsible for business innovation. Originality/value The paper identifies enablers related to the development of IC in industrial cluster and presents a research agenda. The framework represents a guideline for companies to achieve better innovation performance.
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Khutieva, Elena, Alexander Maizel, and Marina Vlasova. "Industrial clusters in St. Petersburg as a basis for development of Arctic territories." MATEC Web of Conferences 170 (2018): 02006. http://dx.doi.org/10.1051/matecconf/201817002006.
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The exploitation of Arctic resources is becoming now one of the most important directions of Russia’s strategic development. The coordination center for this project is St. Petersburg. The article assesses the potential of this region which forms an essential prerequisite for the effective implementation of the given work from the standpoint of the state and prospects of industrial clusters formed in its territory. The subjects of the cluster environment of St. Petersburg relevant programs of state support are divided into three categories: 2 innovative territorial clusters, 3 territorial clusters, 9 territorial clusters administered by the Center for cluster development. Specific recommendations for them are proposed on the basis of analysis of their strengths and weaknesses, as well as assessment of opportunities and threats to their development.
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Dürrenmatt, David J., and Willi Gujer. "Identification of industrial wastewater by clustering wastewater treatment plant influent ultraviolet visible spectra." Water Science and Technology 63, no. 6 (March 1, 2011): 1153–59. http://dx.doi.org/10.2166/wst.2011.354.
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A procedure is proposed which allows the detection of industrial discharge events at the inlet of a wastewater treatment plant without the need for measurements performed at the industry, for special equipment and for exact knowledge of the industrial sewage. By performing UV/Vis measurements at the inlet of a plant and analyzing them with a two-staged clustering method consisting of the self-organizing map algorithm and the Ward clustering method, typical sewage clusters can be found. In an experiment performed at a mid-sized Swiss plant, one cluster of a cluster model with five clusters could be attributed to an industrial laundry. Out of 95 laundry discharging events measured in a validation period, 93 were correctly detected by the proposed algorithm, two were false positives and five were false negatives.
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Kornus, Anatolii, Serhii Siutkin, and Olesia Kornus. "CLUSTER APPROACH IN THE SYSTEM OF INDUSTRIAL TOURISM." GEOGRAPHY AND TOURISM, no. 53 (2019): 9–15. http://dx.doi.org/10.17721/2308-135x.2019.53.9-15.
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The aim. The study is based on the need for a more thorough systematization and justification of the cluster approach to the development of the tourism industry in Ukraine, as well as the study of regional features of the clustering process of industrial tourism market. Methodology. The methodological base of the study is the theory of economic clusters, as well as individual elements of the concepts of territorial production complexes and regional intersectoral complexes that were developed before it. The study used various theoretical methods and techniques of scientific geographical research, in particular analysis, synthesis, systematization and others. Results. The essence of the cluster approach and the features of tourism clusters in the context of industrial tourism are briefly described. The analysis of world experience in improving the competitiveness of regions through the implementation of cluster policies and the targeted creation of territorial tourism clusters is carried out. The structure of production-tourist clusters, the features of establishing their boundaries are shown. We believe that the modern concept of production-tourism clusters, as sets of technologically connected and geographically concentrated enterprises, is quite capable of combining and absorbing the existing socio-geographical categories such as “territorial-recreational complexes” and “recreational-tourist complexes”. In our opinion, the formation of several industrial-tourist clusters in each of the regions of Ukraine looks justified in the current socio-economic conditions. Scientific novelty. Based on the existing approaches to the definition of tourist clusters, the concept of a production-tourism cluster is formulated. By the latter, we understand the territorial enterprises combination of industry, agriculture, transport, services, or any other segment of the economy that have tourist attractiveness and conduct excursions to their facilities. In addition, the necessary elements of tourism infrastructure (transport, hotel and restaurant services, etc.) should be presented as part of such a cluster. A scheme for the gradual development of regional production-tourism clusters is proposed. Practical significance. The results of the study can be used in the formation of regional strategies for socio-economic development, as well tourism development programs in the regions of Ukraine. The formation of production-tourism clusters will strengthen the promotion of domestic tourism. Host production tourism may well become a kind of platform for local development, and successful promotion of the region will positively affect its economy. Clustering can be a powerful tool to increase the level of tourism activities. The cluster approach will provide greater combination and interpenetration of various types of recreational and tourist activities. This will make recreational activities more effective, as more recreational needs will be met per unit of time.
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Scheel, Carlos. "Knowledge clusters of technological innovation systems." Journal of Knowledge Management 6, no. 4 (October 1, 2002): 356–67. http://dx.doi.org/10.1108/13673270210440866.
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One of the main producers of wealth and prosperity of industrialized countries is the existence of sustainable systems, capable of converting technological innovation assets into substantial levels of industrial productivity, wealth and global competitiveness. However, very little has been capitalized from these cases for less developed regions. A framework is proposed (5Ls model), capable of empowering firms from industrial sectors of developing countries to: reach competitive Leverages; to Link and aLign these industrial clusters to their empowerment external drivers (academia, banking, complementary industries and government); to benchmark the cluster performance, against the best practices and Learn from the gaps; and, finally, to Lead and integrate the well performing clusters into world class value systems. To achieve these performances, a knowledge system architecture is proposed, which includes the 5Ls model supported by an effective structure of technological innovation systems (TIS), designed to administrate the collaboration network of diverse organizations, aligned to a common goal: the economic, social, political and cultural development of developing regions.
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YASHIN, Sergei N., Egor V. KOSHELEV, and Dmitrii A. SUKHANOV. "Articulating the development strategy for the innovation and industrial cluster by the compound option method." Finance and Credit 27, no. 7 (July 29, 2021): 1647–71. http://dx.doi.org/10.24891/fc.27.7.1647.
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Subject. The article focuses on the development strategy for the innovation and industrial cluster by the compound option method. Objectives. We articulate the development strategy for the innovation and industrial cluster by the compound option method, which would allow for flexible administrative decisions on the cluster evolution. Methods. The proposed method is based on the use of the compound option method, which includes constituents as follows: 1) the option for the reduction in the cluster strategy and withdrawal from it; 2) the option for the development and dissemination of experience across the cluster; 3) the option for the rearrangement and temporary suspension of the cluster strategy. Results. To illustrate the proposed method, we formulated the development strategy for the pilot innovation and industrial cluster of power engineering in the Nizhny Novgorod Oblast, which is represented with the backbone company PAO TNS Energo NN. The real option method helped increase the value of the cluster’s strategy. Combining the compound real option just as we suggest, it will be possible to avoid unreasonable administrative decisions on the withdrawal from the current strategy, which would provide for multiple, already existing tactical opportunities for the cluster’s development. The value of the current strategy, first of all, absorbs a put option. This is an option to reduce the cluster’s strategy or withdraw from it. Afterwards if the current strategy is continued, three call options are added to it. Conclusions and Relevance. The findings can be useful for governmental authorities in planning the development of innovation and industrial clusters and the harmonious advancement of the country.
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Wang, Hong Fei. "Research on a Model of Order Allocation for Virtual Enterprises." Advanced Materials Research 215 (March 2011): 282–85. http://dx.doi.org/10.4028/www.scientific.net/amr.215.282.
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Industrial clusters can be found very often in the world, particularly in many developing countries. To build virtual enterprise based on an industrial cluster is one of the most important ways to improve the agility and competitiveness of manufacturing enterprises in the cluster. One of the key factors towards the success of virtual enterprises is the correct selection of cooperative partners in the virtual enterprise. An approach of order allocation and partner selection in the environment of industrial clusters is proposed. This approach is composed of two stages: task-resource matching and quantitative evaluation. In the first stage the potential candidates are identified and in the second stage evolutionary programming is applied to deal with partner selection and order allocation problem. The target function, in which the load rate of candidate enterprise is taken as the main variable, is developed, and a simplified example is used to verify the feasibility of the proposed approach. The result suggests that the proposed model and the algorithm obtain satisfactory solutions.
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MAKSIMOVA, N. A. "DEVELOPMENT OF AN INDUSTRIAL CLUSTER WITHIN THE FRAMEWORK OF ENSURING THE ECONOMIC SECURITY OF THE ENTERPRISE." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 8 (2021): 43–50. http://dx.doi.org/10.36871/ek.up.p.r.2021.08.01.005.
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The article analyzes the classifications of clusters in the conditions of digitalization of various industries, the development of an industrial cluster and cluster analysis based on the "nearest neighbor" principle. Management solutions are proposed that contribute to ensuring the economic security of the enterprise.
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Glukhov, V. V., A. V. Babkin, and N. S. Alekseeva. "Stages and Algorithm for Assessing the Intellectual Capital of an Innovative Industrial Cluster." Economics and Management 26, no. 11 (January 16, 2021): 1217–26. http://dx.doi.org/10.35854/1998-1627-2020-11-1217-1226.
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Aim. The presented study aims to identify stages and propose an algorithm for assessing the intellectual capital of an innovative industrial cluster.Tasks. The authors classify the types of intellectual capital of an innovative industrial cluster; propose the structure of the intellectual capital of an innovative industrial cluster; develop the stages for assessing the intellectual capital of an innovative industrial cluster and an algorithm for assessing the intellectual capital of an innovative industrial cluster.Methods. This study uses a combination of general scientific and natural scientific methods of cognition: observation, generalization, abstraction, and the graphical approach. These methods are used to consistently solve the tasks of the study.Results. During the analysis of the types of intellectual capital of innovative industrial clusters, the authors classify them according to three criteria: carrier, involvement in the processes of the innovative industrial cluster, and the type of existence. The proposed classification allows the authors to develop the structure of intellectual capital of an innovative industrial cluster, which is presented in the form of four levels characterized by compressibility. The authors develop and describe the stages of assessing the intellectual capital of an innovative industrial cluster and propose an algorithm for its assessment consisting of three stages: preparatory, main, and final.Conclusions. The study describes stages and an algorithm for assessing the intellectual capital of an innovative industrial cluster, which can be used to manage intellectual capital in order to increase its value and develop an innovative industrial cluster.
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Wang, Tao, Yon Gan Zhang, and Wei Jiang. "Implications from Swarm Simulation on Industrial Clusters’ Evolution." Advanced Materials Research 403-408 (November 2011): 5308–12. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.5308.
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This paper argues that the phenomenon of industrial clusters is a kind of complex and dynamic process. With the heterogeneity of firms involved in clusters and their open connections with external environment being reasonably justified, the paper thinks that the evolution of industrial clusters should be observed and studied by the approach of computer simulation. Some factors from inside or outside, local or global, work together to drive the growth and decline of industrial clusters. Some implications are drawn through the analysis of the results by simulations designed on java-swarm platform. Suggestions are proposed accordingly.
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Bezerra, Maria Clara da Cunha, Cláudia Fabiana Gohr, and Sandra Naomi Morioka. "Linking Cluster Characteristics and Organizational Capabilities for Sustainability—Framework Development and Application." Sustainability 13, no. 3 (January 21, 2021): 1068. http://dx.doi.org/10.3390/su13031068.
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Despite previous research in the literature indicating the relationship between corporate sustainability, organizational capabilities and industrial clusters, this interconnection has not yet been satisfactorily explored and requires further investigation. Therefore, this paper proposes a theoretical framework that relates five cluster characteristics (CC) in developing seven Organizational Capabilities for Sustainability (OCS), which are identified in the literature review. To refine the theoretical framework, seven companies were inserted in a Brazilian footwear cluster. Out of the 29 proposed relationships in the theoretical framework, 16 were evidenced and they generated our research propositions. This study primarily expands the literature by providing theoretical and empirical evidence for the role that clusters can have in enabling companies to develop OCS and in turn improve their corporate sustainability.
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AGGARWAL, ARADHNA. "PROMOTING AGGLOMERATION ECONOMIES AND INDUSTRIAL CLUSTERING THROUGH SEZs: EVIDENCE FROM INDIA." Journal of International Commerce, Economics and Policy 02, no. 02 (December 2011): 201–27. http://dx.doi.org/10.1142/s1793993311000282.
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This paper argues that traditional theoretical approaches to SEZs are unable to adequately explain the rationale and economic contribution of SEZs in India and proposes an alternative approach based on the economics of agglomeration, in general, and industrial clustering, in particular. It argues that although SEZs are not treated as clusters in the SEZ literature, they share characteristics with the latter. It uses the proposed approach to evaluate the role of SEZs in promoting cluster-based industrialisation and entrepreneurship in the country. The analysis presented in the paper is based on observations during field visits to selected operational SEZs across nine states and in-depth interviews with bureaucrats, developers, entrepreneurs and employees.
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GLOTKO, Andrey, Irina SYCHEVA, Alexander DUNETS, Andrey POLTARYKHIN, Pavel ZHURAVLEV, and Anna TUBALETS. "Integration Processes in the Agro-Industrial Complex of the Regions: Development and Environmental Problems." Journal of Environmental Management and Tourism 10, no. 3 (July 22, 2019): 613. http://dx.doi.org/10.14505//jemt.10.3(35).15.
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This paper is devoted to the methodology for assessing the development of extra- and intra-integration structures. This methodology consists of three levels of economic assessment of the agro-industrial sector: the regional level, the economic sector level, and the enterprise level. The agro-industrial complex of the Altai Republic has positive business dynamics due to the development of the livestock industry. Through assessing the business outlook for agro-industrial integration using the three levels, it has been determined that the livestock industry has the greatest potential for creating large integrated structures in the Altai Republic.
The study justifies the need for creating an internal cluster (intra-cluster) in the maral deer breeding sphere of the Altai Republic, and an external cluster (extra-cluster) in the sphere of meat-and-dairy cattle breeding in the Altai Republic and the Altai Territory. The authors propose a ‘business-as-usual’ and a target scenario for the development of the agro-industrial complex of the Altai Republic until 2025.
The target scenario reflects the effectiveness of the proposed measures for the development of the agro-industrial complex of the Altai Republic. According to this scenario, the formation of intra-clusters and extra-clusters in 2025 will lead to an increase in total profits of the livestock industry enterprises under analysis by 451 million rubles and of budget allocations by 194.3 million rubles. The goal of this study is to develop theoretical and methodological guidelines for shaping and developing integrated structures in the agro-industrial complex.
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Li, Wei, Dean Kong, Qiang Xu, Xiaoyu Wang, Xiang Zhao, Yongji Li, Hongzhi Han, Wei Wang, and Zhenyu Chen. "A Wind Farm Active Power Dispatch Strategy Considering the Wind Turbine Power-Tracking Characteristic via Model Predictive Control." Processes 7, no. 8 (August 12, 2019): 530. http://dx.doi.org/10.3390/pr7080530.
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In this paper, an industrial application-oriented wind farm automatic generation control strategy is proposed to stabilize the wind farm power output under power limitation conditions. A wind farm with 20 units that are connected beneath four transmission lines is the selected control object. First, the power-tracking dynamic characteristic of wind turbines is modeled as a first-order inertial model. Based on the wind farm topology, the wind turbines are grouped into four clusters to fully use the clusters’ smoothing effect. A method for frequency-domain aggregation and approximation is used to obtain the clusters’ power-tracking equivalent model. From the reported analysis, a model predictive control strategy is proposed in this paper to optimize the rapidity and stability of the power-tracking performance. In this method, the power set-point for the wind farm is dispatched to the clusters. Then, the active power control is distributed from the cluster to the wind turbines using the conventional proportional distribution strategy. Ultra-short-term wind speed prediction is also included in this paper to assess the real-time performance. The proposed strategy was tested using a simulated wind farm based on an industrial wind farm. Good power-tracking performance was achieved in several scenarios, and the results demonstrate that the performance markedly improved using the proposed strategy compared with the conventional strategy.
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Laiko, Oleksandr, Sergey Kovalenko, and Oleksandr Bilousov. "PROSPECTS FOR THE DEVELOPMENT OF CLUSTER FORMS OF ENTREPRENEURSHIP IN EUROREGIONS." Baltic Journal of Economic Studies 6, no. 5 (December 2, 2020): 118–28. http://dx.doi.org/10.30525/2256-0742/2020-6-5-118-128.
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The aim of the proposed research consists in outlining prospects of cluster mechanism application and verification of the cluster strategy in view of innovative development of cross-border regions against the background on strengthening integration processes. The work is dedicated to research of theoretical, methodical and applicable basis of strategic management of development of international integration associations as network-like structures of intra-branch and inter-branch cooperation on their mesolevel. The research method is based on mesoeconomic synthesis of development concepts in industrial and innovative clusters and international integration associations. To the authors’ opinion, it enables to work out both mechanism and scientific understanding of development trends in modern integration systems. The scientific hypothesis of the proposed work suggests that the cluster approach is the most efficient mechanism of development of international economic cooperation under modern conditions and, finally, is a mesolevel of competitive international integration systems and necessary pre-condition of qualitative progress of integration of Ukraine into the EU. The authors propose to develop integration processes of mesolevel within the framework of unified economic space basing upon clustering. Concept, structure and life cycle of net forms of self-organization of a cross-border economic space in conditions of developing a postmodern economy are considered. Conclusion is drawn to state that the cross-border clusters concept construes an approach adequate to modern challenges to stimulate economic development of peripheral regions with inherent features and advantages taking into account comprehensive dynamic competition and coordination of problems of meso– and macrolevels with conditions accompanying operation and activity of particular business entities. Under such circumstances, cluster policy consists in creating conditions for formation and development of cross-border clusters, but, under no circumstances, in artificial generation of such clusters. Theoretical positions and methodological approaches to the formation of industrial clusters within European regions are systematized. The essence of cross-border and internal relationships of the cluster as a factor in increasing competitiveness in the increasingly Euroregion integration processes and the need to enhance the role of peripheral regions within the framework of crossborder cooperation. The strategic priorities for spatial development of new forms of cross-border cooperation in the context of regional policy of the EU are outlined.
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Berestetska, O. M. "Stimulation of Innovative Development of Textile Industry of the Western Region of Ukraine." Podilian Bulletin: Agriculture, Engineering, Economics, no. 29 (November 30, 2018): 129–34. http://dx.doi.org/10.37406/2706-9052-2018-2-16.
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The article deals with the problems of innovative development of the textile industry enterprises of the western region of Ukraine. The experience of functioning of industrial parks in foreign countries is investigated, features of organization, problems and prospects of development of industrial parks in the western region of Ukraine are highlighted. Understanding the competitive advantages of new production systems and the active formation of regional innovation clusters opens new prospects for dynamic economic development to the regions. Studies of foreign experience, problems and perspectives on the formation of a developed innovation infrastructure of the textile industry have been carried out in the context of research: the creation of technological parks, industrial parks and clusters in Ukraine. It is proposed to study the experience of the advanced countries in the organization of the textile cluster, which can positively affect the country's competitiveness
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Hamdan, Basma, Hamdi Bashir, and Ali Cheaitou. "A novel clustering method for breaking down the symmetric multiple traveling salesman problem." Journal of Industrial Engineering and Management 14, no. 2 (February 10, 2021): 199. http://dx.doi.org/10.3926/jiem.3287.
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Purpose: This study proposes a new two-stage clustering method to break down the symmetric multiple traveling salesman problem (mTSP) into several single standard traveling salesman problems, each of which can then be solved separately using a heuristic optimization algorithm.Design/methodology/approach: In the initial stage, a modified form of factor analysis is used to identify clusters of cities. In the second stage, the cities are allocated to the identified clusters using an integer-programming model. A comparison with the k-means++ clustering algorithm, one of the most popular clustering algorithms, was made to evaluate the performance of the proposed method in terms of four objective criteria.Findings: Computational results and comparison on 63 problems revealed that the proposed method is promising for producing quality clusters and thus for enhancing the performance of heuristic optimization algorithms in solving the mTSP.Originality/value: Unlike previous studies, this study tackles the issue of improving the performance of clustering-based optimization approaches in solving the mTSP by proposing a new clustering method that produces better cluster solutions rather than by proposing a new or improved version of a heuristic optimization algorithm for finding optimal routes.
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Kayvanfar, Vahid, S. M. Moattar Husseini, Zhang NengSheng, Behrooz Karimi, and Mohsen S. Sajadieh. "A practical supply-demand hub in industrial clusters: a new perspective." Management Research Review 42, no. 1 (January 21, 2019): 68–101. http://dx.doi.org/10.1108/mrr-03-2017-0094.
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PurposeThis paper aims to optimize the interactions of businesses located within industrial clusters (ICs) by using a supply-demand hub in ICs (SDHIC) as a conjoint provider of logistics and depository facilities for small- and medium-sized enterprises (SMEs) as producers, where all of these interactions are under supervision of a third-party logistics provider (3PL).Design/methodology/approachTo evaluate the values of SDHIC, three mathematical models are proposed, optimally solved via GAMS and then compared. Also, a “linear relaxation-based heuristic” procedure is proposed to yield a feasible initial solution within a significant shorter computational time. To illustrate the values of SDHIC, comprehensive calculations over a case study and generated sets of instances are conducted, including several sensitivity analysis.FindingsThe experimental results demonstrate the efficiency of SDHIC for SMEs via combining batches and integrating the holding space of inventories, while the outcomes of the case study are aligned with those obtained from random sample examples, which confirms the trueness of used parameters and reveals the applicability of using SDHIC in real world. Finally, several interesting managerial implications for practitioners are extracted and presented.Practical implicationsSome of the managerial and practical implications are optimizing interactions of businesses involved in a supply chain of an IC containing some customers, suppliers and manufacturers and rectifying the present noteworthy gaps pertaining to the previously published research via using real assumptions and merging upstream and downstream of the supply chain through centralizing on storage of raw materials (supply echelon) and finished products (demand echelon) at the same place simultaneously to challenge a classic concept in which supply and demand echelons were being separately planned regarding their inventory management and logistics activities and showing the positive consequences of such challenge, showing the performance improvement of the proposed model compared to the classic model, by increasing the storing cost of raw materials and finished products, considering some disadvantages of using SDHIC and showing the usefulness of SDHIC in total, presenting some applied findings according to the obtained results of sensitivity analysis.Originality/valueThe key contributions of this paper to the literature are suggesting a new applied mathematical methodology to the supply chain (SC) of ICs by means of a conjoint provider of warehousing activities called SDHIC, comparing the new proposed model with the two classic ones and showing the proposed model’s dominancy, showing the helpful outcomes of collaborating 3PL with the SMEs in a cluster, proposing a “linear relaxation-based heuristic” procedure to yield a feasible initial solution within a significant shorter computational time and minimizing total supply chain costs of such IC by optimum application of facilities, lands and labor.
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Zhuang, Yi Jie, Min Wang, and Xiao Chong Pan. "Research on Cloud Computing Industrial Cluster Innovation Evaluation Model." Advanced Materials Research 711 (June 2013): 647–51. http://dx.doi.org/10.4028/www.scientific.net/amr.711.647.
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In this paper, a Bayesian network-based assessment model used for evaluating the innovation of cloud computing industry is presented. Firstly, the innovation measurement model of cloud computing industrial clusters is designed. Then Bayesian network assessment and the self-learning method to the model are proposed. Finally, accompanying with empirical data, the most likely innovation status value of cloud computing industrial clusters and key variables influencing the innovation status value can be predicted. This model can provide the theory basis for researching the innovative development of cloud computing industries.
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Kharlamov, A. V., and A. E. Sibgatullin. "Formation and Development of Innovation Clusters as a Prerequisite for the Transition Towards Intensive Economic Growth." Economics and Management 26, no. 9 (November 25, 2020): 1005–12. http://dx.doi.org/10.35854/1998-1627-2020-9-1005-1012.
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The presented study examines innovative economic growth and its stimulating processes based on the development of innovative clusters. This involves determining the regulatory role of the government and choosing a regulatory model that would reflect the specific features of the examined country’s economic system. Aim. The study aims to consider foreign and Russian experience to formulate proposals for improving the conceptual mechanism that would ensure Russia’s transition towards predominantly intensive economic growth using the opportunities provided by innovative clusters. Tasks. The authors analyze the strategic direction of development of the global and national economies; determine the potential of clusters and cluster development as a tool that facilitates and guides economic growth; identify problem areas in the cluster development of the Russian economy and substantiate a set of measures aimed at eliminating them; determine the methods of government involvement in facilitating cluster development and substantiate the choice of the most appropriate method for a particular national economy; consider the foreign experience of transforming industrial clusters into innovative clusters and adapt it to the Russian economy. Methods. This study critically analyzes different scientific approaches to determining the essence of a cluster and the nature of its impact on the development of economic entities and the national economy as a whole. It also uses analytical tools to propose an adjustment of existing approaches to cluster regulation in Russia and to facilitate the creation of innovative clusters. Results. The role of innovation clusters in Russia and globally is determined in the context of the transition to predominantly intensive economic growth. The major problems that make it impossible to receive maximum benefits from clustering are highlighted. The relationship between innovation and cluster development is determined with allowance for the competitiveness index. The changes necessary for ensuring high-quality economic growth and improving the efficiency of clusters, particularly innovative clusters, are proposed. Factors that ensure successful innovative development in accordance with the main directions of cluster policy are identified. Conclusions. Examination of the role of clusters in the formation of predominantly intensive economic growth, the current state of the Russian economy, and existing cluster policy models makes it possible to evaluate the prospects for the development of the Russian economy using the potential of innovative clusters.
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Asadi, Roya, Sameem Abdul Kareem, Shokoofeh Asadi, and Mitra Asadi. "A dynamic semisupervised feedforward neural network clustering." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 31, no. 1 (May 3, 2016): 30–54. http://dx.doi.org/10.1017/s0890060416000160.
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AbstractAn efficient single-layer dynamic semisupervised feedforward neural network clustering method with one epoch training, data dimensionality reduction, and controlling noise data abilities is discussed to overcome the problems of high training time, low accuracy, and high memory complexity of clustering. Dynamically after the entrance of each new online input datum, the code book of nonrandom weights and other important information about online data as essentially important information are updated and stored in the memory. Consequently, the exclusive threshold of the data is calculated based on the essentially important information, and the data is clustered. Then, the network of clusters is updated. After learning, the model assigns a class label to the unlabeled data by considering a linear activation function and the exclusive threshold. Finally, the number of clusters and density of each cluster are updated. The accuracy of the proposed model is measured through the number of clusters, the quantity of correctly classified nodes, and F-measure. Briefly, in order to predict the survival time, the F-measure is 100% of the Iris, Musk2, Arcene, and Yeast data sets and 99.96% of the Spambase data set from the University of California at Irvine Machine Learning Repository; and the superior F-measure results in between 98.14% and 100% accuracies for the breast cancer data set from the University of Malaya Medical Center. We show that the proposed method is applicable in different areas, such as the prediction of the hydrate formation temperature with high accuracy.
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Wahdan, Hayam G., Hisham M. Abdelslam, and Sally S. Kassem. "An Efficient Optimization Algorithm for Modular Product Design." Journal Européen des Systèmes Automatisés 54, no. 2 (April 27, 2021): 195–207. http://dx.doi.org/10.18280/jesa.540201.
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Modularity concepts play an important role in the process of developing new complex products. Modularization involves dividing a product into a set of modules - each of which consisting of a set of components - that are interdependent in the same cluster and independent between clusters. During this process, a product can be represented using a Design Structure Matrix (DSM). A DSM acts as a tool for system analysis to provide clear visualization of product elements. In addition, DSM, shows the interactions between these product elements. This paper aims to propose an efficient optimization algorithm that dynamically divides a DSM into an optimal number and size of clusters in a way that minimizes total coordination cost; the interactions inside clusters (modules) and interactions between clusters. Given problem complexity, five metaheuristic optimization algorithms are proposed and tested to solve it; these algorithms are used to determine: (1) the optimal clusters’ number within a DSM, and (2) the optimal components assignment clusters to minimize the total coordination cost. The five used metaheuristics are: Cuckoo Search, Modified Cuckoo Search, Particle Swarm Optimization, Simulated Annealing, and Gravitational Search Algorithm. Eighty problems with different properties are generated and used to examine the proposed algorithms for effectiveness and efficiency. Extensive comparisons are conducted and analyzed. Cuckoo Search is outperforming the other four algorithms.
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Vorobev, Aleksandr. "Cluster Information Disclosure in Strategic Planning of Region’s Economy." Vestnik Volgogradskogo gosudarstvennogo universiteta. Ekonomika, no. 4 (February 2020): 118–25. http://dx.doi.org/10.15688/ek.jvolsu.2019.4.12.
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The article represents the results of the analysis of existing approaches to describing economic clusters. These approaches use self-dependent characteristics that complicate evaluating and comparing clusters. Consequently, the author offers the concept of information disclosure of a cluster and its overall indicator. This indicator enables to evaluate clusters, to define a stage of their functioning and to compare results of their activity with other clusters. The existing Russian methods of describing clusters form the basis for this article. These methods are proposed by the Cluster observatory of Higher School of Economics and the Geographic information system “Industrial Parks, Science and Technology Parks and Clusters” of the Russian Federation. The author singles out three aspects of characteristics: attributive, quantitative, qualitative. The characteristics used for calculating the overall indicator of disclosure are quantitative and qualitative. They are generalized and unified using indicators of the project of the Ministry of Economic Development of the Russian Federation “Development of the Innovation Clusters – Leaders of World-Class Investment Attractiveness”. The author offers two approaches to using the information disclosure indicator: dynamic and reference. The dynamic approach enables to define a stage of cluster development using the relation of the current condition to the previous one. The reference approach defines cluster development in relation to a standard that describes its global competitiveness. Both offered approaches can be used by regional and federal government bodies as well as cluster management for taking strategic decisions on the region development.
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Lytvynenko, Nataliia, Maryna Khmara, Nataliia Rylach, Olga Spektor, and Serhii Orekhov. "Methods of calculating the efficiency of clusters and possible modalities for their development." Revista de la Universidad del Zulia 11, no. 31 (October 1, 2020): 97–118. http://dx.doi.org/10.46925//rdluz.31.08.
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The objective of the article is to analyze the method of calculating the efficiency of high-tech clusters and alternative models of their development. Method. The methodological basis of the study is a series of general and specific cognition methods. In the research process, the following were used: the formal-logical method, the system and the structural, comparative-legal, logical-legal and other scientific research methods. Results of the investigation. Four groups of efficiency indicators of the organizational and economic regulation mechanism of the administrative activity of a business cluster are defined. The difference between traditional industrial clusters and innovation clusters is considered. Examples of successful cluster operation in some countries around the world are studied. Practical meaning. It is emphasized that the efficiency of the cluster, and therefore its development, is significantly influenced by the availability of scientific potential and activity of research institutes, as well as access to non-reimbursable funds (institutions, agencies) and the operation of technology parks. Value / originality. It is observed that due to globalization, the role of clusters in competition is increasingly important. In this context, the forms of cluster development in Ukraine were proposed, as well as examples of successful clusters in Ukraine were considered.
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Knudsen, Brage Rugstad, Hanne Kauko, and Trond Andresen. "An Optimal-Control Scheme for Coordinated Surplus-Heat Exchange in Industry Clusters." Energies 12, no. 10 (May 16, 2019): 1877. http://dx.doi.org/10.3390/en12101877.
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Industrial plants organized in clusters may improve their economics and energy efficiency by exchanging and utilizing surplus heat. However, integrating inherently dynamic processes and highly time-varying surplus-heat supplies and demands is challenging. To this end, a structured optimization and control framework may significantly improve inter-plant surplus-heat valorization. We present a Modelica-based systems model and optimal-control scheme for surplus-heat exchange in industrial clusters. An industry-cluster operator is assumed to coordinate and control the surplus-heat exchange infrastructure and responsible for handling the surplus heat and satisfy the sink plants’ heat demands. As a case study, we use an industry cluster consisting of two plants with surplus heat available and two plants with heat demand. The total surplus heat and heat demand are equal, but the availability and demand are highly asynchronous. By optimally utilizing demand predictions and a thermal energy storage (TES) unit, the operator is able to supply more than 98% of the deficit heat as surplus heat from the plants in the industry cluster, while only 77% in a corresponding case without TES. We argue that the proposed framework and case study illustrates a direction for increasing inter-plant surplus-heat utilization in industry clusters with reduced use of peak heating, often associated with high costs or emissions.
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Pang, Liyuan, Yangmin Zhou, and Yingjing Chu. "Research on Integrated Learning of Industrial Clusters in Self-Created Districts." Wireless Communications and Mobile Computing 2021 (September 14, 2021): 1–8. http://dx.doi.org/10.1155/2021/8925688.
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Under the premise of coordinated procurement bilateral and multi-issue negotiation, adaptive negotiation strategy has become an essential factor for multiagent conflict resolution. This paper studies an adaptive negotiation strategy based on selective integrated learning, which effectively improves negotiation. First, take the suppliers and purchasing companies in the cluster supply chain as the research objects and analyze the characteristics of multilateral negotiation of collaborative procurement. Secondly, the support vector machine algorithm performs adaptive learning for each evaluation data set to estimate the concession range. On this basis, remove the few submodels that perform poorly, recombine the calculation weights, and establish a multiagent clustered supply collaborative procurement negotiation model. The simulation experiment proves the feasibility of the adaptive negotiation strategy and the effectiveness of the adaptive coordination strategy based on selective ensemble learning proposed in this paper from the aspects of concession range prediction error rate, prediction accuracy rate, and negotiation utility.
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Bevilacqua, Carmelina, Ilaria Giada Anversa, Gianmarco Cantafio, and Pasquale Pizzimenti. "Local Clusters as “Building Blocks” for Smart Specialization Strategies: A Dynamic SWOT Analysis Application in the Case of San Diego (US)." Sustainability 11, no. 19 (October 8, 2019): 5541. http://dx.doi.org/10.3390/su11195541.
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The paper aimed at exploring the role of local industrial clusters as a part of an important evidence-based pathway for operationalizing smart specialization policy. Hitherto, the scientific debate has been largely focused on the relationship of clusters with the local business environment to boost competitiveness and has mostly searched for the operationalization of smart specialization policy in economically successful regions. However, the understanding of the role of local clusters (LCs), in terms of cluster industries that serve local businesses and residents, as potential “building-blocks” of Smart Specialization Strategies (S3) still lacks interpretive studies. We proposed a conceptual framework to unveil those factors of LCs that may be enhanced in the S3 policy design, around the concepts of adaptiveness and responsiveness to structural and influencing features of a local economic system. The distinction between Local and Traded clusters, applied in the US context, allows the identification of Local Cluster performance because of the availability of a robust data set. Accordingly, a tool is proposed to investigate those factors that are likely empowering smart specialization strategies: The dynamic SWOT analysis on the case of San Diego provides interesting insights toward building this conceptual framework. The findings may help explain how to relate LCs with smart specialization as building-blocks, based on potential risks and opportunities associated with the local economic system.
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Puppim de Oliveira, Jose A., and Charbel Jose Chiappetta Jabbour. "Environmental Management, Climate Change, CSR, and Governance in Clusters of Small Firms in Developing Countries." Business & Society 56, no. 1 (July 27, 2016): 130–51. http://dx.doi.org/10.1177/0007650315575470.
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One of the key debates in the literature on small and medium enterprises (SMEs) and corporate social responsibility (CSR) in developing countries has to do with the role that local industrial districts, or so-called industrial clusters, play in the promotion of CSR in those countries. While there is now an embryonic literature on this subject, we lack systematic, integrated analytical frameworks that can improve our understanding of the role that governance of clusters play in addressing CSR concerns in SMEs in developing countries. This article develops such a conceptual framework drawing on the literatures on cluster governance, CSR, SMEs, and environmental management (EM) as they relate to the developing countries. The authors argue that environmental improvements in SME clusters can be achieved through three basic types of cluster governance: legal enforcement, supply chain pressure, and voluntary engagement in CSR. The proposed framework is an attempt to show how each type of cluster governance is likely to induce different responses in cluster-based SMEs. These responses are related to stages of CSR in which SMEs engage, the barriers to EM they face, the types of EM practices they use, the climate change strategy types they use, and the kinds of benefits that accrue to SMEs from engagement in CSR. The authors put foward a framework that can be useful for both academics and practitioners as they seek to reflect on the interconnectedness of these themes from a research, policy, and practice perspective.
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Mercado-Caruso, Nohora, Marival Segarra-Oña, David Ovallos-Gazabon, and Angel Peiró-Signes. "Identifying Endogenous and Exogenous Indicators to Measure Eco-Innovation within Clusters." Sustainability 12, no. 15 (July 29, 2020): 6088. http://dx.doi.org/10.3390/su12156088.
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Scientific and business environment literature shows that green, sustainable innovation or eco-innovation has proven to be a source of competitive advantage today. The industrial clusters, their dynamism, and the synergies created within them attract a lot of attention from the scientific community. However, to date, the joint study of these two concepts and, more specifically, the factors that drive eco-innovation specifically in a cluster, have not been studied in depth. This article models eco-innovation in industrial clusters, thus addressing this gap and proposing a model based on information gathered from the literature and a detailed analysis of behavior in relation to eco-innovation in different sectors. Results suggest that including eco-innovation variables and measures may have positive implications such as improvements at the strategic level and the reduction of costs and use of resources. An eco-innovation model for clusters is proposed. It considers eight key factors that seek to raise its competitive level by promoting eco-innovation within clusters. The model includes five internal factors that analyze business capabilities and three external factors that study the effect of launching eco-innovative activities. This model could help the companies’ managers and those responsible for clusters in creating more successful strategies to increase competitiveness by enhancing eco-innovation. It could also serve as a guide for government entities in the performance of eco-innovative activities in economic sectors.
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Koshelev, Egor, and Sergei Yashin. "Using a Compound Real Option to Develop an Innovation Strategy for an Industrial Cluster." SHS Web of Conferences 110 (2021): 04007. http://dx.doi.org/10.1051/shsconf/202111004007.
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The purpose of this paper is to apply such a technology to develop an innovation strategy for the pilot clusters defined by the state, which would allow to make flexible management decisions. The proposed method for this involves the use of a compound real option, which includes the following components to be applied in the following order: 1) an option to reduce and exit the cluster strategy, 2) an option to develop and replicate the experience in the cluster, 3) an option to change over and temporarily stop the cluster strategy, and 4) an option to delay the start of the new cluster strategy. Combining a compound real option exactly as presented avoids unreasonable managerial decisions to withdraw from the current cluster strategy, which would include multiple tactical cluster development opportunities that have already been implemented. In other words, a put option is first added to the evaluation of the current strategy. This is an option to reduce and exit the cluster strategy. And then if the current strategy continues, the next three call options are added to it.
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KUDRYAVTSEVA, Tatiana, and Eunice Omolola OLANIYI. "Identification and Analysis of the Cluster Structure of a Territory and its Impact on Regional Development: An example of Russia." Journal of Advanced Research in Law and Economics 10, no. 4 (June 30, 2019): 1322. http://dx.doi.org/10.14505//jarle.v10.4(42).33.
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Identification, development, and management of the cluster structure of territories is an important factor of economic growth. The purpose of this study is to determine the cluster structure of Russian regions and assess the impact of these cluster specialization on the size of gross regional product (GRP). For this purpose, the methodology of the European Cluster Observatory was used and the following indicators were calculated: ‘Location quotient’, ‘Cluster size’, and ‘Cluster focus’ for 37 clusters in 83 regions of the Russian Federation within the period from 2009 to 2018. The calculation was performed using the developed automated database ‘Clusters of Russian regions’.
Based on the results obtained, the cluster specialization was determined and hypotheses were tested on the presence of positive externalities, i.e. on the existence of a positive correlation between the cluster specialization of regions and the size of their GRP from 2011 to 2015. Thus, the authors conclude that the increased specialization of Russian regions lled to positive agglomeration effects - externalities. The proposed toolkit can serve as a reference for the development and justification of the state industrial cluster policy.
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Lei, Qi, and Tong Li. "Identification approach for bottleneck clusters in a job shop based on theory of constraints and sensitivity analysis." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 6 (May 1, 2015): 1091–101. http://dx.doi.org/10.1177/0954405415583884.
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Manufacturing systems are constrained by one or more bottlenecks. Reducing bottlenecks improves the entire system. Finding bottlenecks, however, is a difficult task. In this study, a new bottleneck detection method based on theory of constrains and sensitivity analysis is presented to overcome the disadvantages of existing bottleneck identification methods for a job shop. First, a bottleneck index matrix is obtained by examining the sensitivity of system production performance to the capacity of each machine. Technique for order preference by similarity to ideal solution is then employed to calculate the comprehensive bottleneck index of each machine. Based on the calculation result, bottleneck machine clusters under different hierarchies are obtained through hierarchical cluster analysis. The designed identification approach, as a prior-to-run method, can identify bottleneck machine clusters under different hierarchies before the overall system circulation, thereby providing good guidance for subsequent production optimization. Finally, a set of job-shop scheduling problem benchmarks with different scales is selected for comparison between the proposed approach and existing approaches, such as, the shifting bottleneck detection method, the bottleneck detection method based on orthogonal experiment, and the bottleneck cluster identification method. By comparison, the proposed approach is proven to be credible and superior.
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Anshari, Muhammad, Mohammad Nabil Almunawar, and Abdur Razzaq. "Developing Talents vis-à-vis Fourth Industrial Revolution." International Journal of Asian Business and Information Management 12, no. 4 (October 2021): 20–32. http://dx.doi.org/10.4018/ijabim.20211001.oa2.
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The growing numbers of unemployment raises concerns around the world. With the arrival of the Fourth Industrial Revolution (4IR) many believed that 4IR might increase the unemployment rate by replacing the current jobs with automated machines such as robots whereas some argued that 4IR might reduce the unemployment rate by creating millions of new jobs. The paper aims to share the scenario of Industry 4.0 processes that affect future talent management, in determining which jobs will be severely affected, and that will be less affected. The talent mapping is a conceptual framework of job landscapes and the following four clusters examine job characteristics: machine-centric to human-centric, routine to complex, and optimization to identity. A qualitative method was deployed to extracts primary data from educators' perspectives in developing talents required for 4IR through Education 4.0. The adoption of Education 4.0 will be advantageous for developing talent in keeping up with the progressive and demanding talents in 4IR. The proposed model defined that clusters of machine-centric are jobs performed routinely on an application basis and usually structured and do not require any compassion or emotions. While developing talents for clusters in human-centric jobs, it may be difficult to replace humans due to complexities in the decision-making process and required compassion for task completion.
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Athoillah, Ibid, and Firda Pratiwi. "Development of an Asset Management System Integrated with GIS and K-Means Algorithm for Large Industrial Area." International Journal of Engineering & Technology 7, no. 4.1 (September 12, 2018): 113. http://dx.doi.org/10.14419/ijet.v7i4.1.28237.
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The large industrial area has more than a thousand assets that make asset management activities to become more challenging. However, the current asset management in several industrial companies still records the asset information in paper-based documents. Therefore, the technical problems found in current practices in the field are the difficulties in determining the actual position of assets and which group of asset belongs accurately. To overcome those problems and to improve the asset management activities, an asset management system using GIS (Geographic Information System) and K-Means Algorithm is proposed. GIS to visualize the asset coordinate and condition on a geographical map, manage and store the assets detail information and K-Means Clustering Algorithm to cluster the assets based on their coordinate and simplifies the scattered asset. The system is developed using the Waterfall model. The system is native applications built using electron framework and can be accessed within industrial area network only, to keep the user convenience and security of asset data. The Leaflet used as interactive map software frameworks to visualize the industrial map, manage the geospatial data and mapped the industrial asset, including machinery, equipment, land, and building. For the initial operation, the system contains more than 700 assets data with 6 categories and 4 clusters. This system improves the assets accuracy, reduces the time of asset management practices, and the asset clusters can be used as decision support for industrial asset management activities.
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Markov, Leonid S., Vladislav B. Kurmashev, and Aleksey Yu Nizkovskiy. "Russian Cluster Policy in the Context of Cooperation." World of Economics and Management 19, no. 4 (2019): 38–51. http://dx.doi.org/10.25205/2542-0429-2019-19-4-38-51.
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The paper studies a profound change in the Russian cluster policy at the federal level based on the analysis of regulatory framework. The work demonstrates virtual abandoning of cluster policies in all areas, i.e. winding-up direct support for industrial cluster projects and failure to start funding complex investment projects for the development of innovative territorial clusters which has even lost their normative basis for financing as well as to backup regional cluster development centers. The main reason for such a reverse is the lack of cooperation among the domestic clusters. At the same time, the main aim of the government efforts in the field of cluster formation and other related processes – stimulation of cooperation projects – has remained unchanged. In order to avoid setbacks in other initiatives for development of such cooperation, it seems advisable to introduce an extended classification of joint cluster projects, which in many ways determines the specifics of partnership relations. The proposed classification is based on the type of connectivity among the participants, the symmetry of the alliances and the organizational form of project implementation. It is shown that the domestic cluster policy deals with the most challenging type of cooperative projects.
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Kochetova, Zh Yu, O. V. Bazarsky, T. A. Kuchmenko, and N. V. Maslova. "Ecological Problems of the Aviation-Missile Cluster and Optimization of Geomonitoring Using a Piezo Sensor." Ecology and Industry of Russia 22, no. 8 (August 1, 2018): 32–38. http://dx.doi.org/10.18412/1816-0395-2018-8-32-38.
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The data of eleven-year monitoring of soil and subsoil contamination by kerosene, heavy metals, formaldehyde and nitrates on the territory of the aviation-missile cluster are presented. The adjusted index of total contamination with priority contaminants of soils and subsoil of various functional zones of the cluster (aviation-missile, industrial, residential-transport, recreational) have been calculated. Using the rank correlation coefficient of Spearman, a relationship was established between the content of priority contaminants in soil and subsoil. On the basis of the correlation analysis, the choice of kerosene as a marker compound for soil and subsoil contamination of air-missile clusters is justified. A piezo sensor was developed for the rapid analysis of kerosene in soil and subsoils in "on-site" mode without sampling and sample preparation. Optimization of ecological monitoring of soils and subsoil with the application of a test method for determining kerosene in the territories of aviation-missile clusters is proposed.
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Смирнов, Evgeny Smirnov, Юсим, Vyacheslav Yusim, Блинкова, and D. Blinkova. "The Impact of Public Policy on Industrial Clustering Economic Security." Economics 4, no. 6 (December 9, 2016): 43–50. http://dx.doi.org/10.12737/21400.
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The article analyzes the influence on the state economic security policies implemented by the clustering of industry. In this work it was evaluated the efficiency of clusters. The evaluation was conducted in terms of economic, social and technological efficiency. Proposed and evaluated the effectiveness of development of subjects of the Russian Federation from positions of the theory of economic-technological systems. The proposed criterion allows to link the technological capacity of territories with the level of gross regional product and economic security of the region and ensures the consistent development of longand short-term period of the state, business structures and people. The use of this criterion will allow us to move to a managed economy
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Song, Xinwei, Yulan Gao, Dongmei Shen, and Rusheng Jia. "Study on the Pollution Control of Down Washing Wastewater in West Anhui, China." E3S Web of Conferences 165 (2020): 02035. http://dx.doi.org/10.1051/e3sconf/202016502035.
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The down industry is one of the special agricultural industrial clusters in West Anhui province, China. There are large drainage and large pollution load in the washing down industry. By analysing the characteristics of wastewater from down washing industry, it is proposed that the enterprises of down industry should separate heavily polluted wastewater from slightly polluted and reuse the wastewater directly or after regeneration treatment. According to the gathering situation of down feather industrial enterprises in West Anhui province, it is proposed to build down feather industrial park and down specialized sewage treatment plant in the industrial gathering area, so as to solve the pollution problem of enterprises through centralized treatment and make industry bigger and stronger.
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Kukharchyk, A. G. "MULTIMODAL CLUSTER CREATION." Economic innovations 19, no. 1(63) (April 24, 2017): 132–38. http://dx.doi.org/10.31520/ei.2017.19.1(63).132-138.
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The prospects of the transport development and production associations in the sea-economic system complex of Ukraine are considered in the paper. The definition of a cluster is given, its types are analyzed. It is proposed to create a multimodal cluster in the Odessa region. Maritime trade ports become centers for the intensification of transport and freight flows. The development of interaction forms comes from the simplest port and industrial zones through their association in port-industrial units based on the general infrastructure, the creation of port-industrial complexes and the formation of transport and industrial complexes, representing an informal association of transport and industrial enterprises. As well as related organizations located in a certain territory and operating on the principles of commonality of interests. A higher level of interaction between enterprises, organizations and institutions in the system of a sea-economy complex should be the creation of multimodal clusters in the marine regions of the country, involving the involvement of educational institutions, research institutes, banks, insurance companies and other companies in the sphere of interaction, which will create an atmosphere of trust between power and business, improve the competitive environment, provide productivity growth both to industrial enterprises and to port activity and related activities.
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Laveyne, Joannes, Jens Baetens, Greet Van Eetvelde, and Lieven Vandevelde. "Addressing the Challenges of a Nuclear Phase-Out with Energy Synergies on Business Parks." Proceedings 58, no. 1 (September 12, 2020): 22. http://dx.doi.org/10.3390/wef-06928.
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Similar to many other Western countries, Belgium has committed to internationally set climate goals, such as the reduction in primary energy consumption and the increase in the share of renewable energy production in the total energy mix. Additionally, Belgium has decided to phase out its nuclear energy production, the nation’s largest source of low carbon electricity. In this paper, the role of Belgian business parks and industrial clusters in contributing to the climate goals is investigated, based on the experiences of the authors on several business parks and industrial clusters. The concepts of cogeneration, advanced thermal grids, and local energy communities are discussed and applied on pilot clusters. Their effectiveness towards achieving the climate goals is evaluated, and finally, some policy recommendations are proposed. The results are based on the Belgian situation but are valid for other countries facing similar challenges.
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Hubbe, Martin A. "When defects dominate: Rheology of nanofibrillated cellulose suspensions." BioResources 16, no. 1 (November 1, 2020): 16–18. http://dx.doi.org/10.15376/biores.16.1.16-18.
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Conventional rheological tests can be difficult to carry out in the case of suspensions of nanofibrillated cellulose (NFC). Such suspensions tend to migrate away from the walls of a rheometer device, leaving a low-viscosity layer. The very high aspect ratio of typical nanofibrillated cellulose particles favors formation of tangled clusters. But application of hydrodynamic shear can cause fragmentation of those clusters. It is proposed in this essay that some focus be placed on the fragments of entangled clusters of NFC and interactions between them at their fractured surfaces. The condition of near-uniform, defect-free structures of nanocellulose spanning the volume within a sheared suspension might be regarded as an unlikely circumstance. Isaac Newton started with a very simple equation to start to understand rheology. It is proposed that a similarly bold and simplified approach may be needed to account for the effects of broken entangled clusters of NFC on flow phenomena, their assessment, and their consequences related to industrial processes.
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Yan, Bo, Cong-Yan Cai, and Ping Shi. "Multi-level two-way cross-chain inventory coordination model that combines the same level with different levels in multi-supply chains." SIMULATION 93, no. 11 (May 2, 2017): 973–83. http://dx.doi.org/10.1177/0037549717706169.
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A cross-chain inventory emergency replenishment model that comprises the enterprises of manufacturers, wholesalers, and retailers at the same level and at different levels based on a co-opetition relationship in cluster supply chains is constructed in this work. The model is built by studying two three-level supply chains that each comprises manufacturers, wholesalers, and retailers using the system dynamics method. Subsequently, the proposed cross-chain inventory collaboration model is compared with currently available models and then simulated using the system dynamics simulation software Vensim. Simulation results show that the proposed model further improves existing theoretical research achievements in the field both locally and abroad, thereby advancing theoretical research on cross-chain inventory collaboration. This study also provides decision-making references for the practice of inventory collaboration among enterprises in industrial clusters.
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Czyżewska, Dorota. "Empirical Evidence and Frst Assessment of the Competitiveness Clusters Policy in France." International Journal of Management and Economics 39, no. 1 (October 17, 2014): 18–27. http://dx.doi.org/10.2478/ijme-2014-0019.
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Abstract The paper is an attempt to show the competitiveness clusters policy as a key element of the new French industrial policy using recent evaluation results of this policy. The aim of the paper is threefold. Firstly, objectives of the competitiveness clusters policy as well as their characteristics, spatial distribution across the country, selected statistical data concerning their functioning are overviewed. Secondly, evaluation results of the French competitiveness clusters policy and a comparison of this instrument to similar ones existing in leading EU countries are provided. Thirdly, some crucial challenges resulting from the evaluation and policy orientations are proposed in order to increase the effectiveness of the competitiveness clusters policy in France. The descriptive analysis has been used in the paper as research method. The competitiveness clusters policy was launched in 2005 to raise the international profile of French technology clusters and promote growth and job-creation in high value-added industries, anchoring these industries in a regional context. Apart from selected positive effects of the competitiveness clusters policy, some not very promising conclusions concerning this policy can therefore be drawn in terms of the number of innovation or patent applications. In order to improve the effectiveness of this industrial policy measure, some structural changes presented in the paper need to be implemented in this field.
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Popelo, О., M. Butko, A. Revko, O. Garafonova, and О. Rasskazov. "STRATEGY OF THE FORMATION AND DEVELOPMENT OF AN INNOVATIVE AGROINDUSTRIAL CLUSTER OF THE REGION IN A CONTEXT OF DECENTRALIZATION OF THE AUTHORITATIVE POWERS." Financial and credit activity: problems of theory and practice 2, no. 37 (April 30, 2021): 219–30. http://dx.doi.org/10.18371/fcaptp.v2i37.230180.
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Abstract. A research method of determining the clustering potential of the industrial complex of the region is proposed within the article. The main objective of the research is the development of a strategy of the formation and development of an innovative agroindustrial cluster of the region in the setting of decentralization of authoritative powers. In modern economic conditions, the search and application of new, adequate approaches to innovative development of agroindustrial enterprises is reasonably required. It is proved that the most significant form of the implementation of the agroindustrial enterprise potential is innovative clusters, which should be considered as economic subjects concentrated and technologically related on the geographical grounds and technologically new ones, which form territorial production complexes on a specific territory. It is substantiated that the policy of decentralization of authoritative powers is a significant catalyst for the cluster development, especially the agroindustrial production and economic recovery of many rural areas. This article studies the objective of intensification of the formation processed of innovative agroindustrial clusters in the regions of Ukraine. The block diagram showing the result estimation of clustering development of innovative agroindustrial enterprises of the region is proposed. A conceptual model of formation and development of innovative agroindustrial cluster of the region, which is based on structural modernization of economic space, solution of economic, social and ecological problems due to effective use of available areal resources, is developed. Keywords: cluster, innovation, agroindustrial enterprises, agroindustrial cluster of agroindustrial complex, decentralization, production core, innovative core. JEL Classification R00, R11 Formulas: 7; fig.: 2; tabl.: 1; bibl.: 12.