985 resultados para Markets-as-networks


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Effects of localized personal networks on the choice of search methods are studied in this paper using evidence of displaced workers by establishment closure in Thailand Labor Force Survey, 2001. For the blocks/villages level, there is less significant evidence of local interactions between job-seekers and referrals in developing labor markets. The effects of localized personal networks do not play an important role in the probability of unemployed job-seekers seeking assistance from friends and relatives. Convincing evidence from the data supports the proposition that both self-selection of individual background-like professions and access to large markets determine the choice of job search method.

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The financial markets in Turkey provide a laboratory to help resolve these competing views. Islamic law or Sharia contains a number of proscriptions that directly affect financial practices. The payment and receipt of interest is prohibited; so are most kinds of commercial insurance. These interpretations provided the impetus in the Islamic world for the creation of a class of banks that sought to offer Sharia compliant services. The first Islamic Banks in Turkey began operations in the 1980s. Their entry was initially tepid, in no small part because of secularist principles. Islamic financial institutions could not overtly advertise their religious orientation. The country had no “Islamic” banks, only finance houses. They were not Sharia compliant but “interest-free.” Moreover, the government left them in an uncertain regulatory status and subjected them to restrictions on growth. In this environment, the Islamic banks remained a peripheral part of the financial system. With the election of the AKP in 2002, however, the environment for Islamic banks in Turkey changed. Limitations on branch networks and capital raising were lifted. The government removed restrictions on the issuance of Sharia compliant bonds. Officials from the Islamic banks were appointed to the highest levels of government. This Article does several things. First, it examines principles of Islam that affect banking practices, with a particular emphasis on deposit insurance and credit cards. Second, the Article discusses the emergence of secularism in Turkey and the introduction of Islamic banks into the Turkish financial markets. The Article then examine their evolution, with particular emphasis on the changes implemented by the AKP. Finally, the Article examines the impact of these reforms, and what that impact says about Islamic influence in Turkey.

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Multinational companies' (MNCs) corporate social responsibility (CSR) programs frequently comprise a portfolio of disconnected country-level programs or, alternatively, consist of blanket corporate policies that apply in the same way across the geographies where the company operates. Yet, the international nonmarket environment in which CSR programs operate is neither a completely fragmented nor a perfectly homogeneous one. Building on the concept of stakeholder-issue-networks, we develop a model that explicitly takes into consideration the role of geography in the characterization of a firm's nonmarket environment. This allows us to develop a taxonomy of nonmarket environments on the basis of their geographic spread and their degree of cross-border connectedness. We then explore the strategic and organizational implications that different ideal types of (cross-border) nonmarket environments have for the development of international CSR policies.

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Why is Europe lagging on next generation access networks? Fibre-based next generation access (NGA) roll-out across the European Union is one of the goals of the European Commission’s Digital Agenda strategy, however, there remains considerable uncertainty about how the roll-out goal can best be achieved. The underlying differences between the economics of copper-based and new fibre-based broadband infrastructures should lead to a revision of the regulatory framework for telecommunications markets. While the current regulatory measures have been useful in the past decade to sustain competition and facilitate entry into a market with already-existing infrastructures, the need to create new, much faster broadband networks calls for a rethink of the scope and strictness of regulation.

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The paper reports on a study of 28 ethnic Chinese businesses in Brisbane, Adelaide, and Perth, carried out in 2000 and 2001. It focuses on their strategies of vertical, horizontal, and unrelated diversification often combining different activities, products, and markets at the same time. It demonstrates how these practices are socially embedded in their preference for using personal networks. Non-related diversification, in particular, promotes and is facilitated by using weak ties that serve as bridges, leading into new networks (Granovetter, 1973). This can create links to Chinese of different national and dialect origins and to those of other ethnicities. It is suggested that open networks and diversification mutually interact to support each other and may have evolved in tandem from earlier, more closed and niche bound business cultures and practices.

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It is well known that one of the obstacles to effective forecasting of exchange rates is heteroscedasticity (non-stationary conditional variance). The autoregressive conditional heteroscedastic (ARCH) model and its variants have been used to estimate a time dependent variance for many financial time series. However, such models are essentially linear in form and we can ask whether a non-linear model for variance can improve results just as non-linear models (such as neural networks) for the mean have done. In this paper we consider two neural network models for variance estimation. Mixture Density Networks (Bishop 1994, Nix and Weigend 1994) combine a Multi-Layer Perceptron (MLP) and a mixture model to estimate the conditional data density. They are trained using a maximum likelihood approach. However, it is known that maximum likelihood estimates are biased and lead to a systematic under-estimate of variance. More recently, a Bayesian approach to parameter estimation has been developed (Bishop and Qazaz 1996) that shows promise in removing the maximum likelihood bias. However, up to now, this model has not been used for time series prediction. Here we compare these algorithms with two other models to provide benchmark results: a linear model (from the ARIMA family), and a conventional neural network trained with a sum-of-squares error function (which estimates the conditional mean of the time series with a constant variance noise model). This comparison is carried out on daily exchange rate data for five currencies.

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Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency towards specialization has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies to supply niche markets. Thirdly, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than previously was the case. Fourthly, there is a continuous move towards more loosely connected entities that comprise manufacturing networks. More traditional concepts, such as the “keiretsu” and “chaibol” networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these four fundamental challenges to prepare for the industrial networks of 2020 and beyond.

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Previous research suggests that changing consumer and producer knowledge structures play a role in market evolution and that the sociocognitive processes of product markets are revealed in the sensemaking stories of market actors that are rebroadcasted in commercial publications. In this article, the authors lend further support to the story-based nature of market sensemaking and the use of the sociocognitive approach in explaining the evolution of high-technology markets. They examine the content (i.e., subject matter or topic) and volume (i.e., the number) of market stories and the extent to which content and volume of market stories evolve as a technology emerges. Data were obtained from a content analysis of 10,412 article abstracts, published in key trade journals, pertaining to Local Area Network (LAN) technologies and spanning the period 1981 to 2000. Hypotheses concerning the evolving nature (content and volume) of market stories in technology evolution are tested. The analysis identified four categories of market stories - technical, product availability, product adoption, and product discontinuation. The findings show that the emerging technology passes initially through a 'technical-intensive' phase whereby technology related stories dominate, through a 'supply-push' phase, in which stories presenting products embracing the technology tend to exceed technical stories while there is a rise in the number of product adoption reference stories, to a 'product-focus' phase, with stories predominantly focusing on product availability. Overall story volume declines when a technology matures as the need for sensemaking reduces. When stories about product discontinuation surface, these signal the decline of current technology. New technologies that fail to maintain the 'product-focus' stage also reflect limited market acceptance. The article also discusses the theoretical and managerial implications of the study's findings. © 2002 Elsevier Science Inc. All rights reserved.

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Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? First, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example, in assembly operations. Second, the increased tendency towards specialisation has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Third, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than was previously the case. Fourth, there is becoming a continuous move towards more loosely connected entities that comprise manufacturing networks. Finally, in these networks, concepts for supply chain management should address collaboration and information technology that supports decentralised decision-making, in particular to address sustainable and green supply chains. More traditional concepts, such as the keiretsu and chaibol networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these five fundamental challenges to prepare for the industrial networks of 2020 and beyond. © 2010 Springer-Verlag London.

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Academia has followed the interest by companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it seems that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency to specialize forces other parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Thirdly, the capital market for investments in capacity and the trade in manufacturing as a commodity dominates resource allocation to a larger extent. Fourthly, there will be a continuous move toward more loosely connected entities forming manufacturing networks. More traditional concepts, like keiretsu and chaibol networks, do not sufficiently support this transition. Research should address these fundamental challenges to prepare for the industrial networks of 2020 and beyond.

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With the proliferation of Internet, online shopping has become an increasingly essential part of global economy and thus, increasingly important field of research. While the internationalization process of a company has for long been in the focus of academic research, internationalization of e-commerce is a much newer field of study. The earlier empirical research has amply pointed out the difficulties of traditional internationalization models to explain the internationalization process of e-commerce companies. Conversely, business networks have been argued to play a major role in the e-commerce internationalization. The purpose of this study is to study how business networks influence the internationalization process of e-commerce companies. Conducted as a case study, this research studies the internationalization process of two Finnish e-commerce companies, Hong Kong and Hifi Studio, into possibly one of the most booming online markets - Russia. The empirical findings of the study concur with the earlier literature. The observed internationalization process differs from the assumptions of traditional international business models, and business networks are found influential for the process. However, the behavior of the two studied organizations is observed more independent than the network view to internationalization presumes. The trigger to internationalize rises from within the organizations and market potential is the primary explanation for selection of target markets. No network relationships were found to have an effect on foreign market selection, nor selection of mode of operations. This study indicates that exploring foreign markets is actually about investing in specific relationships within a business network, rather than overcoming economic, institutional, and cultural barriers. Companies utilize a wide array of relationships in their internationalization process and may effectively overcome disadvantages of operating in a foreign market by adopting partnerships with correct partners. However, building and maintaining operational business relationships is a demanding process, and organizations should prefer quality over quantity in their partner selection. Moreover, relationships where the focal party possess significant influence and leverage over other actor should be favored. Lastly, relationships need to be continuously evaluated and assessed in comparison with strategic business goals. Ultimately, e-commerce can be considered a new, low-risk, cost-effective, and relationship-oriented internationalization method, suitable especially in volatile market conditions as Russia today. This revolutionary new mode of international business activity calls for more profound focus of business managers and academia alike, as its weight on global trade continues to grow.

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Part 16: Performance Measurement Systems

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Part 5: Service Orientation in Collaborative Networks