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Journal articles on the topic 'Networks of production'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Sarkhel, Manish, and Nagarajan Krishnamurthy. "Stable Production Networks." International Game Theory Review 22, no. 02 (May 28, 2020): 2040006. http://dx.doi.org/10.1142/s021919892040006x.

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One of the key features which promote growth of industrial clusters is collaboration among firms within such clusters. Collaboration among firms leads to the formation of networks. Stability of these networks is vital to the sustainability of the particular firms. In this paper, we model a supply chain network where a set of downstream firms (players) source inputs from upstream firms (players) who manufacture goods, add value to the products and resell them. The upstream firms produce identical goods and compete on quantities to sell these goods to the downstream firms. The upstream firms procure goods from the downstream firms and sell them. Additionally, upstream firms network among themselves so as to reduce their costs. We model this setting as a two-stage [Formula: see text]-player strategic network formation game. Firms decide their links before competing on quantities in the second stage of the game. Using the defined model, we derive equilibrium quantities and profits as a function of the network structure and number of firms. Following which we analyze the conditions under which different stable network emerge. Our analysis brings forth several interesting insights such as higher connections among downstream players lead to increased profits for upstream manufacturers. From the network stability perspective, we obtain the conditions under which regular, star, etc. network structures are pairwise and bilaterally stable. Furthermore, we also find the conditions under which core–periphery network structures emerge and are stable.

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Sihn, Wilfried, and Peter Kuhlang. "Production networks." CIRP Journal of Manufacturing Science and Technology 4, no. 3 (January 2011): 225. http://dx.doi.org/10.1016/j.cirpj.2011.10.001.

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3

Klein, Oliver, Piotr Pachura, and Christine Tamasy. "GLOBALIZING PRODUCTION NETWORKS." Polish Journal of Management Studies 13, no. 2 (June 2016): 81–89. http://dx.doi.org/10.17512/pjms.2016.13.2.08.

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4

Acemoglu, Daron, and Pablo D. Azar. "Endogenous Production Networks." Econometrica 88, no. 1 (2020): 33–82. http://dx.doi.org/10.3982/ecta15899.

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We develop a tractable model of endogenous production networks. Each one of a number of products can be produced by combining labor and an endogenous subset of the other products as inputs. Different combinations of inputs generate (prespecified) levels of productivity and various distortions may affect costs and prices. We establish the existence and uniqueness of an equilibrium and provide comparative static results on how prices and endogenous technology/input choices (and thus the production network) respond to changes in parameters. These results show that improvements in technology (or reductions in distortions) spread throughout the economy via input–output linkages and reduce all prices, and under reasonable restrictions on the menu of production technologies, also lead to a denser production network. Using a dynamic version of the model, we establish that the endogenous evolution of the production network could be a powerful force towards sustained economic growth. At the root of this result is the fact that the arrival of a few new products expands the set of technological possibilities of all existing industries by a large amount—that is, if there are n products, the arrival of one more new product increases the combinations of inputs that each existing product can use from 2 n−1 to 2 n , thus enabling significantly more pronounced cost reductions from choice of input combinations. These cost reductions then spread to other industries via lower input prices and incentivize them to also adopt additional inputs.

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Wiendahl, H. P., and S. Lutz. "Production in Networks." CIRP Annals 51, no. 2 (2002): 573–86. http://dx.doi.org/10.1016/s0007-8506(07)61701-6.

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6

Zeleny, Milan. "Autopoiesis (self-production) in SME networks." Human Systems Management 20, no. 3 (September 3, 2001): 201–7. http://dx.doi.org/10.3233/hsm-2001-20303.

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Small and medium enterprise networks (SME Networks) are becoming an integral part of the Network Economy. From the ‘industrial districts’ of the Terza Italia to the entrepreneurial clusters of the Silicon Valley, SME's are a significant driving force of economic growth, job creation, disinflation and productivity enhancement in most industrial countries. After decades of research, these local industrial systems are still poorly understood in terms of their sustained processes of innovation, network interaction and competitive adjustments. While there could be some external economies due to agglomeration, division of labor, specialization and lowered transaction costs, differential innovation, interaction and adjustment capabilities are not fully explained by these mechanisms. A theoretical construct of local industrial system is missing. However, no mechanical or graph theory model of network architecture can substitute for what actually makes people in the network interact in order to become technologically innovative and capable of ongoing adjustment to their competitors. Counting the nodes and edges of graphs would be a poor substitute for understanding SME networks as dynamic (‘living’) organic systems they are. In this paper we propose a theoretical construct of network production, renewal and adaptation based on autopoiesis (self-production) of living systems.

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7

Veza, Ivica, and Marko Mladineo. "SUSTAINABILITY THROUGH PRODUCTION NETWORKS." Management and Production Engineering Review 4, no. 4 (December 1, 2013): 76–82. http://dx.doi.org/10.2478/mper-2013-0035.

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Abstract Global economic crisis has brought into question sustainability of many industrial enterprises, especially Large-sized Enterprises (LEs). However, the strength of the European economy are not Large-sized Enterprises, but Small and Medium-sized industrial Enterprises (SMEs). As an alternative to LEs there is networking of SMEs into flexible production networks. Inside production network SMEs can collaborate on new product development forming Virtual Enterprise. SMEs collaborating as one Virtual Enterprise can be seen as a sustainable Large-sized Enterprise. However, to achieve sustainability through production networks, i.e. Virtual Enterprises, it is essential to choose an optimal combination of SMEs in Virtual Enterprise formation process. Since it is a complex task that requires the use of multi-criteria decision-making methods, in this paper PROMETHEE method is used.

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8

Khmara, Marina, Olena Grinenko, Sergii Koroied, Daria Koucherets, and Olekdandr Bukhanevych. "Development of global production networks in a global environment." Problems and Perspectives in Management 15, no. 3 (December 7, 2017): 467–77. http://dx.doi.org/10.21511/ppm.15(3-2).2017.14.

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Production systems in the structure of economic systems occupy the most fundamental place and act as both initial and basic subsystem of any economic development. There is a tendency to change the forms of production and the study of these process systems poses a wider aspect of their dynamics analysis. The article tries to prove both theoretically and practically that global production networks are one of the most important factors in the innovative transformation of countries and regions. It is concluded due to global production networks, being the channel for the transfer of global knowledge and technical know-how to regional structures, regions of the former periphery have quickly become developed, innovative regions with a specialization in the sector of highly qualified services, production of high-tech products, and generation of scientific knowledge. For transnational companies global production networks reduce their costs and financial risks by sharing with other companies, as well as global division of labor, an important part of global production.

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9

Çelik, Şenol. "MODELING AVOCADO PRODUCTION IN MEXICO WITH ARTIFICIAL NEURAL NETWORKS." Engineering and Technology Journal 07, no. 10 (October 31, 2022): 1605–9. http://dx.doi.org/10.47191/etj/v7i10.08.

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An Artificial Neural Network (ANN) model was created in this research to estimate and predict the amount of avocado production in Mexico. In the development of the ANN model, the years that are time variable were used as the input parameter, and the avocado production amount (tons) was used as the output parameter. The research data includes avocado production in Mexico for 1961-2020 period. Mean Squared Error (MSE) and Mean Absolut Error (MAE) statistics were calculated using hyperbolic tangent activation function to determine the appropriate model. ANN model is a network architecture with 12 hidden layers, 12 process elements (12-12-1) and Levenberg-Marquardt back propagation algorithm. The amount of avocado production was estimated between 2021 and 2030 with the ANN. As a result of the prediction, it is expected that the amount of avocado production for the period 2021-2030 will be between 2,410,741-2,502,302 tons.

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10

Friedli, Thomas, Günther Schuh, Gisela Lanza, Dominik Remling, Andreas Gützlaff, and Florian Stamer. "Next Level Production Networks." ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb 114, no. 3 (March 28, 2019): 101–4. http://dx.doi.org/10.3139/104.112057.

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11

Chen, Quanrun, Yuning Gao, Jiansuo Pei, Gaaitzen de Vries, and Fei Wang. "China's domestic production networks." China Economic Review 72 (April 2022): 101767. http://dx.doi.org/10.1016/j.chieco.2022.101767.

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12

Liebau, Heike. "Networks of Knowledge Production." Comparative Studies of South Asia, Africa and the Middle East 40, no. 2 (August 1, 2020): 309–21. http://dx.doi.org/10.1215/1089201x-8524237.

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Abstract This essay explores networks of knowledge exchange and practices of knowledge production between South Asian Muslims and academic circles in Germany between 1915 and 1930. It centers on the brothers Abdul Jabbar Kheiri and Abdul Sattar Kheiri and foregrounds their interaction and encounters with German scholars during the First World War and in Weimar Germany until the brothers' return to India. Taking into consideration the asymmetries at play, the article looks at the motivations for the interest in knowledge exchange on the German and on the Indian sides, which changed in accordance with the different political situations and the positionalities and dependencies of the actors. The knowledge exchange went far beyond the newly emerging discipline of Islamic studies and classical Indology to include disciplines like sociology, economy, philosophy, and art.

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13

Geldermann, J., M. Treitz, and O. Rentz. "Towards sustainable production networks." International Journal of Production Research 45, no. 18-19 (September 15, 2007): 4207–24. http://dx.doi.org/10.1080/00207540701440014.

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14

Bigio, Saki, and Jennifer La’O. "Distortions in Production Networks*." Quarterly Journal of Economics 135, no. 4 (May 18, 2020): 2187–253. http://dx.doi.org/10.1093/qje/qjaa018.

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Abstract How does an economy’s production structure determine its macroeconomic response to sectoral distortions? We study a static, multisector framework in which production is organized in an input-output network and production decisions are distorted. Sectoral distortions manifest at the aggregate level via two channels: total factor productivity (TFP) and the labor wedge. We show that near efficiency, distortions have zero first-order effects on TFP and nonzero first-order effects on the labor wedge, and that a sufficient statistic for the latter are the Domar weights. We thereby provide a Hulten-like theorem for the aggregate effects of sectoral distortions. A quantitative application of the model to the 2008–09 financial crisis suggests that the U.S. input-output structure amplified financial distortions by roughly a factor of two during the crisis.

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15

Carvalho, Vasco M., and Alireza Tahbaz-Salehi. "Production Networks: A Primer." Annual Review of Economics 11, no. 1 (August 2, 2019): 635–63. http://dx.doi.org/10.1146/annurev-economics-080218-030212.

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This article reviews the literature on production networks in macroeconomics. It presents the theoretical foundations for the role of input–output linkages as a shock propagation channel and as a mechanism for transforming microeconomic shocks into macroeconomic fluctuations. The article also provides a brief guide to the growing literature that explores these themes empirically and quantitatively.

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16

Burmeister, Antje, and Kristian Colletis-Wahl. "Proximity in Production Networks." European Urban and Regional Studies 4, no. 3 (July 1997): 231–41. http://dx.doi.org/10.1177/096977649700400303.

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17

Mella, Piero. "The ghost in the production machine: the laws of production networks." Kybernetes 48, no. 6 (June 3, 2019): 1301–29. http://dx.doi.org/10.1108/k-05-2018-0267.

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Purpose Any kind of production flow is obtained not from individual production organizations but from a more or less widespread Production Network of interconnected production modules located in different places and times. All of these modules are, consciously or not, necessarily connected, interacting and cooperating in a coordinated way to combine and arrange, step by step, the factors, materials, components, manpower, machines and equipment to obtain flows of products’ final goods, in particular’ and to sell these where there is a demand for them. The purpose of this paper is to determine, in logical and formal terms, the minimum conditions that bring about the formation of production networks and to discover the laws that explain their dynamics over time. Design/methodology/approach At the global level, the continuous and accelerated economic progress of mankind is witnessed. There is an increase in the quantity and quality of satisfied and yet to be satisfied needs, of attained and yet to be attained aspirations. The increase in productivity and in quality has become unstoppable and appears to guide the other variables in the system. It is natural to ask who produces and governs these phenomena. It does indeed seem there is a Ghost in the “Production” machine whose invisible hand produces growing levels of productivity and quality, increases the quality and quantity of satisfied needs and aspirations and reduces the burden of work, thus producing increasingly higher levels of progress in the entire economic system. This conceptual framework gives a simple answer: there is nothing metaphysical about this evolution towards unstoppable and irreversible progress, and it is produced by the spontaneous genesis and activity of selfish nodes and governed by the rules and laws of the production networks. Findings The author has identified ten “rules of selfish behavior” on the part of the nodes, whose application necessarily and inevitably produces three evolutionary dynamic processes “which refer to the network as an entity” which the author has called the “rules of the production networks” to emphasize their cogency: continual expansion, elasticity-resiliency and continual improvement in performance. The cognitive and creative processes that characterize the nodes do not allow us to predict the actual evolution of production networks; nevertheless, if it is assumed that nodes “consciously or not” follow the 10 “rules of selfish behavior”, then several typical trends, or behavioural schema, can be deduced which the author has called as the “laws of networks”, to highlight their apparent inevitability and cogency. Research limitations/implications More than any other structure, Production Networks display Holland’s features and Arthur’s properties as their modules, viewed as autonomous entities with cognitive functions, represent a collectivity of agents that interact and exchange information with their environment to maintain over time their internal processes through adaptation, self-preservation, evolution and cognition, making individual and collective decisions as part of a network of micro behaviours. Social implications This new conception of production through production networks, which takes into account the “rules” and “laws” regulating their behaviour, also sheds new light on the development of networks and their natural tendency to become globalized. Originality/value Although the concept of a network is becoming more popular in economic and business studies, it is yet to see an interpretation of production as deriving exclusively from the actions of increasingly larger networks. This paper presents an integrated view of production that does not discard the notion that production is carried out by organizations and companies but introduces the broader concept of the integration among organizations, which must be interpreted as nodes of a broader network that produces the flows of all the components needed to obtain the flow of a specific product. This represents an innovative view that will help us in understanding the difficulties policymakers encounter in governing production and controlling the basic variables that characterize it, specifically productivity, quality, quantity, prices and value. This perspective also allows to derive rules and laws for the behaviour of production networks that appear to be cogent and unvarying over time.

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18

Pereira, Adriano, Eugênio De Oliveira Simonetto, Goran Putnik, and Helio Cristiano Gomes Alves de Castro. "How connectivity and search for producers impact production in Industry 4.0 networks." Brazilian Journal of Operations & Production Management 15, no. 4 (November 25, 2018): 528–34. http://dx.doi.org/10.14488/bjopm.2018.v15.n4.a6.

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Technological evolutions lead to changes in production processes; the Fourth Industrial Revolution has been called Industry 4.0, as it integrates Cyber-Physical Systems and the Internet of Things into supply chains. Large complex networks are the core structure of Industry 4.0: any node in a network can demand a task, which can be answered by one node or a set of them, collaboratively, when they are connected. In this paper, the aim is to verify how (i) network's connectivity (average degree) and (ii) the number of levels covered in nodes search impacts the total of production tasks completely performed in the network. To achieve the goal of this paper, two hypotheses were formulated and tested in a computer simulation environment developed based on a modeling and simulation study. Results showed that the higher the network's average degree is (their nodes are more connected), the greater are the number of tasks performed; in addition, generally, the greater are the levels defined in the search for nodes, the more tasks are completely executed. This paper's main limitations are related to the simulation process, which led to a simplification of production process. The results found can be applied in several Industry 4.0 networks, such as additive manufacturing and collaborative networks, and this paper is original due to the use of simulation to test this kind of hypotheses in an Industry 4.0 production network.

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19

Carvalho, Vasco M. "From Micro to Macro via Production Networks." Journal of Economic Perspectives 28, no. 4 (November 1, 2014): 23–48. http://dx.doi.org/10.1257/jep.28.4.23.

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A modern economy is an intricately linked web of specialized production units, each relying on the flow of inputs from their suppliers to produce their own output which, in turn, is routed towards other downstream units. In this essay, I argue that this network perspective on production linkages can offer novel insights on how local shocks occurring along this production network can propagate across the economy and give rise to aggregate fluctuations. First, I discuss how production networks can be mapped to a standard general equilibrium setup. In particular, through a series of stylized examples, I demonstrate how the propagation of sectoral shocks—and hence aggregate volatility— depends on different arrangements of production, that is, on different “shapes” of the underlying production network. Next I explore, from a network perspective, the empirical properties of a large-scale production network as given by detailed US input-output data. Finally I address how theory and data on production networks can be usefully combined to shed light on comovement and aggregate fluctuations.

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Yudachev, S. S., N. A. Gordienko, and F. M. Bosy. "Application of neural networks in industrial production." Glavnyj mekhanik (Chief Mechanic), no. 6 (May 25, 2021): 10–17. http://dx.doi.org/10.33920/pro-2-2106-01.

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The article describes an algorithm for the synthesis of neural networks for controlling the gyrostabilizer. The neural network acts as an observer of the state vector. The role of such an observer is to provide feedback to the gyrostabilizer, which is illustrated in the article. Gyrostabilizer is a gyroscopic device designed to stabilize individual objects or devices, as well as to determine the angular deviations of objects. Gyrostabilizer systems will be more widely used, as they provide an effective means of motion control with a number of significant advantages for various designs. The article deals in detail with the issue of specific stage features of classical algorithms: selecting the network architecture, training the neural network, and verifying the results of feedback control. In recent years, neural networks have become an increasingly powerful tool in scientific computing. The universal approximation theorem states that a neural network can be constructed to approximate any given continuous function with the required accuracy. The back propagation algorithm also allows effectively optimizing the parameters when training a neural network. Due to the use of graphics processors, it is possible to perform efficient calculations for scientific and engineering tasks. The article presents the optimal configuration of the neural network, such as the depth of memory, the number of layers and neurons in these layers, as well as the functions of the activation layer. In addition, it provides data on dynamic systems to improve neural network training. An optimal training scheme is also provided.

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21

Kelly, Philip F. "Production networks, place and development: Thinking through Global Production Networks in Cavite, Philippines." Geoforum 44 (January 2013): 82–92. http://dx.doi.org/10.1016/j.geoforum.2011.10.003.

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22

Arias-Chávez, Dennis, Roger Wilfredo Asencios Espejo, Richard Cervantes Juro, Jessica Camayo Tovar, and José Elias Plasencia Latour. "Scientific Production on Social Networks during the COVID 19 Pandemic." Webology 19, no. 1 (January 20, 2022): 2138–51. http://dx.doi.org/10.14704/web/v19i1/web19144.

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This research seeks to characterize the global scientific production on social networks during the Covid-19 pandemic between the months of January 2020 to September 2021. A bibliometric study was carried out in five databases (Scopus, Web of Science, Google Academic, Microsoft Academic and Crossref). Bibliometric indicators were analyzed in a universe of 7889 articles obtained through Publish or Perish v. 7.19 and the same analytical software of the chosen databases. The results indicate that the article with the most citations is “Students under lockdown: Comparisons of students' social networks and mental health before and during the COVID-19 crisis in Switzerland”. The author with the most scientific production on the subject of social networks is J. Wu. Regarding the journal with the largest number of articles on the subject, IEE Access stands out, a peer-reviewed open access scientific journal published by the Institute of Electrical and Electronic Engineers. While the United States stands as the country with the highest production of articles on social networks. It is concluded that scientific production was mainly directed to the study of the behavior of social networks during the pandemic. This increase generates an attractive phenomenon for researchers, who wish to evaluate and document totally new events for society. Stands as the country with the highest production of articles on social networks. It is concluded that scientific production was mainly directed to the study of the behavior of social networks during the pandemic. This increase generates an attractive phenomenon for researchers, who wish to evaluate and document totally new events for society. Stands as the country with the highest production of articles on social networks. It is concluded that scientific production was mainly directed to the study of the behavior of social networks during the pandemic. This increase generates an attractive phenomenon for researchers, who wish to evaluate and document totally new events for society.

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23

Wilson, John. "Organisational Knowledge Transfer in Modular Production Networks : Experiences from Brazil." International Conference on Business & Technology Transfer 2006.3 (2006): 23–28. http://dx.doi.org/10.1299/jsmeicbtt.2006.3.0_23.

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Multaheb, Samim Ahmad, Bernd Zimmering, and Oliver Niggemann. "Expressing uncertainty in neural networks for production systems." at - Automatisierungstechnik 69, no. 3 (March 1, 2021): 221–30. http://dx.doi.org/10.1515/auto-2020-0122.

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Abstract The application of machine learning, especially of trained neural networks, requires a high level of trust in their results. A key to this trust is the network’s ability to assess the uncertainty of the computed results. This is a prerequisite for the use of such networks in closed-control loops and in automation systems. This paper describes approaches for enabling neural networks to automatically learn the uncertainties of their results.

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25

Werner, Marion. "Review of Global Production Networks." Journal of World-Systems Research 23, no. 2 (August 11, 2017): 765–68. http://dx.doi.org/10.5195/jwsr.2017.745.

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Arellano Caro, Maricela, Claudia Rebolledo, and Zhexiong Tao. "The Integration of Production Networks." Academy of Management Proceedings 2015, no. 1 (January 2015): 17188. http://dx.doi.org/10.5465/ambpp.2015.17188abstract.

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27

Frohm, Erik, and Vanessa Gunnella. "Spillovers in global production networks." Review of International Economics 29, no. 3 (January 19, 2021): 663–80. http://dx.doi.org/10.1111/roie.12526.

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Dörry, Sabine. "Global production networks in finance." Espace géographique 43, no. 3 (2014): 227. http://dx.doi.org/10.3917/eg.433.0227.

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Baqaee, David Rezza. "Cascading Failures in Production Networks." Econometrica 86, no. 5 (2018): 1819–38. http://dx.doi.org/10.3982/ecta15280.

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Popov, Alexander, and Rustem Valiev. "Non-exponential networks in production." MATEC Web of Conferences 224 (2018): 02108. http://dx.doi.org/10.1051/matecconf/201822402108.

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The article describes the characteristics of special types of queuing systems. Special types of queuing systems are listed. The main methods for calculating of non-exponential queuing systems are given.

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Grassi, Basile, and Julien Sauvagnat. "Production networks and economic policy." Oxford Review of Economic Policy 35, no. 4 (2019): 638–77. http://dx.doi.org/10.1093/oxrep/grz021.

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Abstract In this paper, we show how to combine data on input–output tables and recent insights from the theory of production networks in order to inform policy. We first describe the information contained in input–output tables compiled by statistical agencies, and show how to derive relevant statistics of production networks. We then discuss the implications of production networks for policy intervention in a series of domains, such as fiscal policy, industrial policy, or, finance. Finally, we present a quantitative exercise applied to French data in order to illustrate that production networks shape the overall impact of competition policy on the economy.

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32

Morales, Rebecca. "Product Development And Production Networks:." Journal of Industry Studies 1, no. 1 (October 1993): 30–42. http://dx.doi.org/10.1080/13662719300000003.

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Liu, Ernest. "Industrial Policies in Production Networks*." Quarterly Journal of Economics 134, no. 4 (August 14, 2019): 1883–948. http://dx.doi.org/10.1093/qje/qjz024.

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Abstract Many developing economies adopt industrial policies favoring selected sectors. Is there an economic logic to this type of intervention? I analyze industrial policy when economic sectors form a production network via input-output linkages. Market imperfections generate distortionary effects that compound through backward demand linkages, causing upstream sectors to become the sink for imperfections and have the greatest size distortions. My key finding is that the distortion in sectoral size is a sufficient statistic for the social value of promoting that sector; thus, there is an incentive for a well-meaning government to subsidize upstream sectors. Furthermore, sectoral interventions’ aggregate effects can be simply summarized, to first order, by the cross-sector covariance between my sufficient statistic and subsidy spending. My sufficient statistic predicts sectoral policies in South Korea in the 1970s and modern-day China, suggesting that sectoral interventions might have generated positive aggregate effects in these economies.

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Taudes, Alfred, Michael Trcka, and Martin Lukanowicz. "Organizational learning in production networks." Journal of Economic Behavior & Organization 47, no. 2 (February 2002): 141–63. http://dx.doi.org/10.1016/s0167-2681(01)00193-7.

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35

Jansen, S. W. F., Z. Atan, I. J. B. F. Adan, and A. G. de Kok. "Newsvendor equations for production networks." Operations Research Letters 46, no. 6 (November 2018): 599–604. http://dx.doi.org/10.1016/j.orl.2018.10.006.

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36

Ferrarini, Benno, David Hummels, and Clara Lee Yen Yin. "Asia and Global Production Networks." Southeast Asian Economies 34, no. 1 (April 29, 2017): 221–22. http://dx.doi.org/10.1355/ae34-1i.

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Chen, Maggie Xiaoyang. "Interdependence in multinational production networks." Canadian Journal of Economics/Revue canadienne d'économique 44, no. 3 (August 2011): 930–56. http://dx.doi.org/10.1111/j.1540-5982.2011.01661.x.

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38

Gibson, Glenn A., and John Y. Alawneh. "Time-bounds for production networks." International Journal of Production Economics 102, no. 1 (July 2006): 149–66. http://dx.doi.org/10.1016/j.ijpe.2005.02.008.

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Gualdi, Stanislao, and Antoine Mandel. "Endogenous growth in production networks." Journal of Evolutionary Economics 29, no. 1 (January 30, 2018): 91–117. http://dx.doi.org/10.1007/s00191-018-0552-x.

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40

Booth, Alison. "Negotiating diasporic culture: festival collaborations and production networks." International Journal of Event and Festival Management 7, no. 2 (June 6, 2016): 100–116. http://dx.doi.org/10.1108/ijefm-02-2016-0016.

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Purpose Within New Zealand, cultural festivals play a vital role in the local representation of diasporic cultures. By analysing the production design of festivals, in Auckland, New Zealand representing Indian culture between 1995 and 2015, the purpose of this paper is to create a deeper understanding of collaborative networks and power relationships. Using Richard’s pulsar/iterative network theory and Booth’s notion of cultural production networks, a new theoretical model is proposed to visually track the collaborative networks that sustain and bridge cultures, empower communities and fulfil political agendas. Design/methodology/approach This ethnographic research draws upon event management studies, industry practice, ethnomusicology and sociology to take a multi-disciplinary approach to an applied research project. Using Richards’ pulsar and iterative event framework Castells’ network theory, combined with qualitative data, this research considers critical collaborative relationships clusters and how they might impact on the temporal nature of festivals. Findings The 1997 Festival of Asia and the subsequent Lantern Festival in 2000 and Diwali: Festival of Lights in 2002 were pulsar events that played a significant role in collaborative networks that expand across cultures, countries and traditions. The subsequent iterative events have played a vital role in the representation of Asian cultural identity in general and, more specifically, representing of the city’s growing – in both size and cultural diversity – Indian diaspora. Originality/value This research proposes a new conceptual model on festival management and diasporic communities in the Asia-Pacific region. Richards’ and Booth’s conceptual models are used, as a starting point, to offer a new way of considering the importance of looking at collaborative relationships through historical perspectives. The framework explored contributes a new approach to cultural festival network theory and a means to understand the complexity of networks required that engage actors from inside and outside both local and global communities.

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Simonyan, Kristina, and Stefan Fuertinger. "Speech networks at rest and in action: interactions between functional brain networks controlling speech production." Journal of Neurophysiology 113, no. 7 (April 2015): 2967–78. http://dx.doi.org/10.1152/jn.00964.2014.

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Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network.

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Hoyler, Michael, and Allan Watson. "Framing city networks through temporary projects: (Trans)national film production beyond ‘Global Hollywood’." Urban Studies 56, no. 5 (October 3, 2018): 943–59. http://dx.doi.org/10.1177/0042098018790735.

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This article advances research on external urban relations by drawing attention to the role of temporary project-based economic organisation in the formation of inter-firm links between cities. Through a novel empirical examination of (trans)national co-production in the motion picture industry, we reveal how such projects transcend the boundaries of individual production clusters and link urban centres within specific network configurations. Stripping away the ‘top layer’ of Hollywood’s commercially successful feature films, we undertake a social network analysis of film productions in four markets across three continents – China, Germany, France and Brazil – to provide a unique comparative analysis of networked urban geographies. Our findings show that film production networks are grounded in existing structural relations between cities. The spatial forms of these networks range from monocentric in the case of the French film market, to dyadic in the case of China and Brazil, to polycentric in the case of the German film market. Conceptually, we argue that adopting an inter-firm project-based approach can account for the ways in which complex patterns of inter-firm production relations accumulate to form (trans)national city networks. Viewing city networks in this way provides an important alternative perspective to dominant conceptualisations of global urban networks as formed through corporate intra-firm relations.

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Sandkuhl, Kurt, and Alexander Smirnov. "Context-oriented Knowledge Management in Production Networks." Applied Computer Systems 23, no. 2 (December 1, 2018): 81–89. http://dx.doi.org/10.2478/acss-2018-0011.

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Abstract Production networks have been established in many industrial domains with globalized supply structures, sourcing strategies or cooperation environments. Knowledge management in such networks requires a context-oriented approach in order to accommodate for individual and organizational needs when providing relevant knowledge for complex tasks, such as value creation. The focus of this paper is on the procedure by which to determine what actually has to be taken into account as part of the ‘context’ for establishing context-oriented knowledge management, how to capture this context, and how to use it. The variability of organisational and individual tasks both at design time and at runtime is essential for understanding context in production networks. The main contribution of the present study is a context modelling method, including variability identification. The application of this method is demonstrated by using an example of a production network from automotive industries.

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COE, NEIL M., PETER DICKEN, MARTIN HESS, and HENRY WAI-CHEUNG YEUNG. "Making connections: Global Production Networks and World City Networks." Global Networks 10, no. 1 (January 2010): 138–49. http://dx.doi.org/10.1111/j.1471-0374.2010.00278.x.

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Duginets, Ganna. "Global imperatives for development of international production networks: case of Ukraine." Problems and Perspectives in Management 18, no. 1 (February 7, 2020): 57–69. http://dx.doi.org/10.21511/ppm.18(1).2020.06.

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The paper studies the theoretical and methodological principles, regularities, and new trends in the formation of international production networks (IPNs) in the global economic space. It determines the imperatives of their development, substantiating the priority nature of integrating national actors into IPNs. The author applies the methods of fuzzy clustering and classification using the artificial intelligence technologies to data on the dynamics of key economic and technological markers of 35 countries in the 2007–2016 time frame.The work identifies a clustering-like structure in the sample country set; allowing determining patterns in the correlation between a country’s manifested potential for ascending into and within international production networks and certain development and international integration indicators. The sample is thus grouped into six clusters based on the degree of integration into IPNs. Due to the use of classification analysis, the rules for assigning a country to a particular cluster were obtained. According to the results of the study, it was concluded that the main imperative for the development of international production networks is innovative development. The overall concept of localization of Ukrainian enterprises at all stages of value creation within networks was offered.

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Verhaelen, B., F. Mayer, S. Peukert, and G. Lanza. "A comprehensive KPI network for the performance measurement and management in global production networks." Production Engineering 15, no. 5 (March 22, 2021): 635–50. http://dx.doi.org/10.1007/s11740-021-01041-7.

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AbstractThe trend of globalization has led to a structural change in the sales and procurement markets of manufacturing companies in recent decades. In order not to be left behind by this change, companies have internationalized their production structures. Global production networks with diverse supply and service interdependencies are the result. However, the management of global production networks is highly complex. Key performance indicator (KPI) networks already exist at the corporate level and site level to support the management of complex systems. However, such KPI networks are not yet available to support the management of entire production networks. In this article, a KPI network for global production networks is presented, which links the key figures of the site level and the corporate level. By integrating both levels into a comprehensive KPI network, cause and effect relationship between the production-related KPIs and the strategic KPIs of a corporate strategy become transparent. To this end, this KPI network is integrated into a Performance Measurement and Management (PMM) methodology. This methodology consists of three phases: performance planning, performance improvement, and performance review. For testing the practical suitability, the PMM methodology is applied to the production network of an automotive supplier using a simulation model to estimate the effects of proposed improvement actions of the methodology.

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Booth, Alison. "Production Networks: Indian Cultural Production in Aotearoa, New Zealand." European Journal of Tourism Research 12 (March 1, 2016): 207–11. http://dx.doi.org/10.54055/ejtr.v12i.222.

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Alexander, Rachel. "Sustainability in global production networks – Introducing the notion of extended supplier networks." Competition & Change 22, no. 3 (April 3, 2018): 255–73. http://dx.doi.org/10.1177/1024529418768606.

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Research considering globalized production as taking place within global production networks and global value chains has potential to provide insights into the challenges of sustainable production. However, studies employing these approaches to look at manufactured products have often concentrated on connections between lead buyers and upper tier suppliers and given insufficient attention to exploring interactions across all stages of production. In this article, the concept of extended supplier networks is introduced to address this gap by explicitly looking at how all stages of production are connected. The extended supplier network model that is presented provides an analytical framework that enables multiple scales of analysis in the study of sustainability challenges.

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Kim, Hyojoon, Xiaoqi Chen, Jack Brassil, and Jennifer Rexford. "Experience-driven research on programmable networks." ACM SIGCOMM Computer Communication Review 51, no. 1 (January 31, 2021): 10–17. http://dx.doi.org/10.1145/3457175.3457178.

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Many promising networking research ideas in programmable networks never see the light of day. Yet, deploying research prototypes in production networks can help validate research ideas, improve them with faster feedback, uncover new research questions, and also ease the subsequent transition to practice. In this paper, we show how researchers can run and validate their research ideas in their own backyards---on their production campus networks---and we have seen that such a demonstrator can expedite the deployment of a research idea in practice to solve real network operation problems. We present P4Campus , a proof-of-concept that encompasses tools, an infrastructure design, strategies, and best practices---both technical and non-technical---that can help researchers run experiments against their programmable network idea in their own network. We use network tapping devices, packet brokers, and commodity programmable switches to enable running experiments to evaluate research ideas on a production campus network. We present several compelling data-plane applications as use cases that run on our campus and solve production network problems. By sharing our experiences and open-sourcing our P4 apps [28], we hope to encourage similar efforts on other campuses.

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Cooke, Philip. "Global Production Networks and Global Innovation Networks: Stability Versus Growth." European Planning Studies 21, no. 7 (July 2013): 1081–94. http://dx.doi.org/10.1080/09654313.2013.733854.

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