Power and Distribution Network Structure in the People's Republic of China - The Case of an Inland City in Transition

The aim of the current study is to examine the influence of the channel external environment on power, and the effect of power on the distribution network structure within the People’s Republic of China. Throughout the study a dual research process was applied. The theory was constructed by elaborating the main theoretical premises of the study, the channel power theories, the political economy framework and the distribution network structure, but these marketing channel concepts were expanded with other perspectives from other disciplines. The main method applied was a survey conducted among 164 Chinese retailers, complemented by interviews, photographs, observations and census data from the field. This multi-method approach enabled not only to validate and triangulate the quantitative results, but to uncover serendipitous findings as well. The theoretical contribution of the current study to the theory of marketing channels power is the different view it takes on power. First, earlier power studies have taken the producer perspective, whereas the current study also includes a distributor perspective to the discussion. Second, many power studies have dealt with strongly dependent relationships, whereas the current study examines loosely dependent relationships. Power is dependent on unequal distribution of resources rather than based on high dependency. The benefit of this view is in realising that power resources and power strategies are separate concepts. The empirical material of the current study confirmed that at least some resources were significantly related to power strategies. The study showed that the dimension resources composed of technology, know-how and knowledge, managerial freedom and reputation was significantly related to non-coercive power. Third, the notion of different outcomes of power is a contribution of this study to the channels power theory even though not confirmed by the empirical results. Fourth, it was proposed that channel external environment other than the resources would also contribute to the channel power. These propositions were partially supported thus providing only partial contribution to the channel power theory. Finally, power was equally distributed among the different types of actors. The findings from the qualitative data suggest that different types of retailers can be classified according to the meaning the actors put into their business. Some are more business oriented, for others retailing is the only way to earn a living. The findings also suggest that in some actors both retailing and wholesaling functions emerge, and this has implications for the marketing channels structure.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

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Knowledge-sharing in a teamwork The study examines the link between knowledge-sharing that takes place in a team and the dimensions and objectives of the team s activities. The question the study poses is: How does knowledge-sharing in a team relate to the team s activities? The exchange of knowledge is examined using knowledge-sharing networks and the conversion model, which describes the process of knowledge formation. The answer to the question is sought through four empirical articles describing the activities of a team from the viewpoint of quality, fairness, power related to knowledge management, and performance. One of the articles used in the study describes the role of networks in work life more generally. It attempts to shed light on the manner in which team-related networks operate as part of a more extensive structure of organizational networks. Finland is one of the most eager users of teamwork, if numbers are used as a yardstick. About half of all Finnish wage earners worked in teams in 2009, and comparisons show that the use of teams in Finland is above the EU average. This study focuses on so-called semi-autonomous teams, which carry out permanent work tasks. In such teams, tasks are interdependent, and teams are jointly responsible for ensuring that the work is done. Team members may also, at least to some extent, agree between themselves on how the tasks are carried out and are able to take part in the decision-making process. Such teamwork makes knowledge-sharing an important element for the team s activities. Knowledge and knowledge-sharing have become a major resource, allowing organizations to operate and even compete in today s increasingly competitive markets. A single team or a single organization cannot, however, possess all the knowledge required for carrying out the tasks assigned to it. Although it is difficult to copy the knowledge generated in an organization, it is important to share the knowledge within and between organizations. External links supply teams and organizations with important knowledge that allows them to keep their operations up-to-date and their structures well-functioning. In fact, knowledge provides teams and organizations with an intangible resource that improves their capacity to interact with their environment and to adjust to it. For this reason, it is important to examine both the internal and external knowledge-sharing taking place in a team. The findings of the study show that in terms of quality, fairness, performance and the knowledge management issues concerning a team, its social network structure is both internally and externally connected with its activities. A team structure that is internally coherent and at the same time open to external contacts, is, with certain restrictions, connected with the quality, fairness, and performance of the team. The restrictions concern differences between procedural and interactional justice, public and private sectors, and the team leaders and ordinary team members. The role of the team leader is closely connected with the management of networks that are considered valuable. The results of the study indicate that teamwork is supervisor-dominated. Thus, teamwork does not substantially strengthen the influence of individual employees as players in knowledge-transfer networks. However, ordinary team members possess important peer contacts inside the organization. Teamwork clearly allows employees to interact in a democratic manner, and here the transfer of tacit knowledge plays an important role. Keywords: teamwork, knowledge-sharing, social networks, organization

Governance theory as a framework for empirical research : a case study on local environmental policy-making in Helsinki, Finland

Governance has been one of the most popular buzzwords in recent political science. As with any term shared by numerous fields of research, as well as everyday language, governance is encumbered by a jungle of definitions and applications. This work elaborates on the concept of network governance. Network governance refers to complex policy-making situations, where a variety of public and private actors collaborate in order to produce and define policy. Governance is processes of autonomous, self-organizing networks of organizations exchanging information and deliberating. Network governance is a theoretical concept that corresponds to an empirical phenomenon. Often, this phenomenon is used to descirbe a historical development: governance is often used to describe changes in political processes of Western societies since the 1980s. In this work, empirical governance networks are used as an organizing framework, and the concepts of autonomy, self-organization and network structure are developed as tools for empirical analysis of any complex decision-making process. This work develops this framework and explores the governance networks in the case of environmental policy-making in the City of Helsinki, Finland. The crafting of a local ecological sustainability programme required support and knowledge from all sectors of administration, a number of entrepreneurs and companies and the inhabitants of Helsinki. The policy process relied explicitly on networking, with public and private actors collaborating to design policy instruments. Communication between individual organizations led to the development of network structures and patterns. This research analyses these patterns and their effects on policy choice, by applying the methods of social network analysis. A variety of social network analysis methods are used to uncover different features of the networked process. Links between individual network positions, network subgroup structures and macro-level network patterns are compared to the types of organizations involved and final policy instruments chosen. By using governance concepts to depict a policy process, the work aims to assess whether they contribute to models of policy-making. The conclusion is that the governance literature sheds light on events that would otherwise go unnoticed, or whose conceptualization would remain atheoretical. The framework of network governance should be in the toolkit of the policy analyst.

Multiple Perspectives on Networks: Conceptual Development, Application and Integration in an Entrepreneurial Context

Multiple Perspectives on Networks: Conceptual Development, Application and Integration in an Entrepreneurial Context. The purpose of this thesis is to enhance cross-fertilization between three different approaches to network research. The business network approach may contribute in terms of how relationships are created, developed and how tie content changes within ties, not only between them. The social network approach adds to the discussion by offering concepts of structural change on a network level. The network approach in entrepreneurship contributes by emphasizing network content, governance and structure as a way of understanding and capturing networks. This is discussed in the conceptual articles, Articles 2 and 3. The ultimate purpose of this thesis is to develop a theoretical and empirical understanding of network development processes. This is fulfilled by presenting a theoretical framework, which offers multiple views on process as a developmental outcome. The framework implies that change ought to be captured both within and among relationships over time in the firm as well as in the network. Consequently, changes in structure and interaction taking place simultaneously need to be included when doing research on network development. The connection between micro and macro levels is also stressed. Therefore, the entrepreneur or firm level needs to be implemented together with the network level. The surrounding environment impacts firm and network development and vice versa and hence needs to be integrated. Further, it is necessary to view network development not only as a way forward but to include both progression and regression as inevitable parts of the process. Finally, both stability and change should be taken into account as part of network development. Empirical results in Article 1 show support for a positive impact of networks on SME internationalization. Article 4 compares networks of novice, serial and portfolio entrepreneurs but the empirical results show little support for differences in the networks by type of entrepreneur. The results demonstrate that network interaction and structure is not directly impacted by type of entrepreneur involved. It indicates instead that network structure and interaction is more impacted by the development phase of the firm. This in turn is in line with the theoretical implications, stating that the development of the network and the firm impacts each other, as they co-evolve.

Discriminative learning of Bayesian networks via factorized conditional log-likelihood

We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.

Structure, function and intracellular dynamics of alphavirus replication complexes

Intracellular membrane alterations are hallmarks of positive-sense RNA (+RNA) virus replication. Strong evidence indicates that within these exotic compartments, viral replicase proteins engage in RNA genome replication and transcription. To date, fundamental questions such as the origin of altered membranes, mechanisms of membrane deformation and topological distribution and function of viral components, are still waiting for comprehensive answers. This study addressed some of the above mentioned questions for the membrane alterations induced during Semliki Forest virus (SFV) infection of mammalian cells. With the aid of electron and fluorescence microscopy coupled with radioactive labelling and immuno-cytochemistry techniques, our group and others showed that few hours after infection the four non structural proteins (nsP1-4) and newly synthesized RNAs of SFV colocalized in close proximity of small membrane invaginations, designated as spherules . These 50-70 nm structures were mainly detected in the perinuclear area, at the limiting membrane of modified endosomes and lysosomes, named CPV-I (cytopathic vacuoles type I). More rarely, spherules were also found at the plasma membrane (PM). In the first part of this study I present the first three-dimensional reconstruction of the CPV-I and the spherules, obtained by electron tomography after chemical or cryo-fixation. Different approaches for imaging these macromolecular assemblies to obtain better structure preservation and higher resolution are presented as unpublished data. This study provides insights into spherule organization and distribution of viral components. The results of this and other experiments presented in this thesis will challenge currently accepted models for virus replication complex formation and function. In a revisitation of our previous models, the second part of this work provides the first complete description of the biogenesis of the CPV-I. The results demonstrate that these virus-induced vacuoles, where hundreds of spherules accumulate at late stages during infection, represent the final phase of a journey initiated at the PM, which apparently serves as a platform for spherule formation. From the PM spherules were internalized by an endocytic event that required the activity of the class I PI3K, caveolin-1, cellular cholesterol and functional actin-myosin network. The resulting neutral endocytic carrier vesicle delivered the spherules to the membrane of pre-existing acidic endosomes via multiple fusion events. Microtubule based transport supported the vectorial transfer of these intermediates to the pericentriolar area where further fusions generated the CPV-I. A signal for spherule internalization was identified in one of the replicase proteins, nsP3. Infections of cells with viruses harbouring a deletion in a highly phosphorylated region of nsP3 did not result in the formation of CPV-Is. Instead, thousands of spherules remained at the PM throughout the infection cycle. Finally, the role of the replicase protein nsP2 during viral RNA replication and transcription was investigated. Three enzymatic activities, protease, NTPase and RNA-triphosphatase were studied with the aid of temperature sensitive mutants in vitro and, when possible, in vivo. The results highlighted the interplay of the different nsP2 functions during different steps of RNA replication and sub-genomic promoter regulation, and suggest that the protein could have different activities when participating in the replication complex or as a free enzyme.