The role of network competence and international business competence in multinational corporations: Subsidiary perspective

On-going process of globalization makes companies all over the world to go beyond the national markets and internationalize. Organizational form of multinational corporation (MNC) has capabilities for establishing the affiliate companies in several countries. Thus, the relocation of resources occurs and particularly, the cross-border transfer of knowledge which possesses the competitive advantage. However, differences in countries` business environments and cultures may constrain this capability. The research aim of this thesis is to investigate the role of subsidiary’s network competence (ability to build and manage the relationships with other local business units) and international business competence in relation to the benefits that MNC receives from a subsidiary. Additionally, subsidiary’s business adaptation, partnerships and knowledge transfer mechanism with parent company and external partners are investigated. This research, conducted in the Finnish-Russian context, consists of theoretical and empirical parts. The qualitative approach in the form of multiple case studies is employed. The empirical data incorporated primary and secondary data in the form of interviews collected in 2013 and 2015 years. Interviews were collected from four Finnish case companies in Saint-Petersburg and Kaluga region and five Russian partner companies. Results are drawn from two cases from Saint-Petersburg. The abductive research approach for the results analysis is adopted. The results indicate that both competencies lead to the subsidiary’s local embeddedness in the form of mutual business activities with local business partners and product adaptation for the local market needs. In addition to the monetary benefits in form of payments or turnover share, local embeddedness brings the knowledge of the local environment which is utilized by an MNC in the long-term planning. Another found tacit benefit is the access to the national market. This is strategically useful benefit not only for parent MNC but also for the subsidiary’s partners, i.e. international suppliers.

Item-level life-cycle model for maintenance network – from cost to additional value

The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

A game-theoretic network formation model

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

ALPS Workshop3 p10 Conscious competence model

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EnvironalPlanning: an analytical network process model for environmentally conscious construction planning

Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.

State-space model identification of a wireless THz network

We model the large scale fading of wireless THz communications links deployed in a metropolitan area taking into account reception through direct line of sight, ground or wall reflection and diffraction. The movement of the receiver in the three dimensions is modelled by an autonomous dynamic linear system in state-space whereas the geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a Wiener model from time-domain measurements of the field intensity.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

A retrospective model of oocyte competence: global mRNA and housekeeping transcripts are not associated with in vitro developmental outcome

Oocyte developmental competence depends on maternal stores that support development throughout a transcriptionally silent period during early embryogenesis. Previous attempts to investigate transcripts associated with oocyte competence have relied on prospective models, which are mostly based on morphological. criteria. Using a retrospective model, we quantitatively compared mRNA among oocytes with different embryo development competence. A cytoplasm biopsy was removed from in vitro matured oocytes to perform comparative analysis of amounts of global polyadenylated (polyA) mRNA and housekeeping gene transcripts. After parthenogenetic activation of biopsied oocytes, presumptive zygotes were cultured individually in vitro and oocytes were classified according to embryo development: (i) blocked before the 8-cell stage; (ii) blocked between the 8-cell and morulae stages; or (iii) developed to the blastocyst stage. Sham-manipulated controls confirmed that biopsies did not alter development outcome. Total polyA mRNA amounts correlate with oocyte diameter but not with the ability to develop to the 8-cell and blastocyst stages. The last was also confirmed by relative quantification of GAPDH, H2A and Hprt1 transcripts. In conclusion, we describe a novel retrospective model to identify putative markers of development competence in single oocytes and demonstrate that global mRNA amounts at the metaphase II stage do not correlate with embryo development in vitro.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

Decision Tree Classification Model In Water Supply Network

With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future.

Estrutura organizacional do tipo network e a satisfação no trabalho

Muitos historiadores afirmam que estamos iniciando uma nova era, a era do conhecimento, da informação, a era digital. Surgem duas grandes armas estratégicas nesse novo ambiente global, para que as empresas sejam competitivas no século vinte e um: a criatividade e a integração. E muitas empresas estão adotando uma nova estrutura organizacional, a estrutura do tipo network, como solução para a gerência da criatividade e da integração. Essa estrutura não se preocupa com novas maneiras de manipular subordinados em vantagem própria. Ao contrário, ela nos desafia a repensar o básico: nossos valores, atitudes e considerações a respeito de liderança, trabalho e tempo. As estruturas hierárquicas convencionais não proporcionam a agilidade de resposta requerida pelo mercado atualmente, devido à burocracia por trás de todas as atividades. As pessoas especializam-se em pequenas atividades, perdendo o sentido do trabalho e a motivação intrínseca. E uma vez que as pessoas são crescentemente reconhecidas como o capital mais importante de qualquer empreendimento, a desmotivação se toma desastrosa para o futuro de qualquer negócio. A reciprocidade empresa-indivíduo é essencial. Esta dissertação pretende analisar o fator humano nos trabalhos realizados dentro da estrutura de network, traçando-se um paralelo entre as propostas dessa estrutura e as necessidades humanas, demonstrando a relação existente entre a estrutura organizacional da criatividade e da integração e a satisfação no trabalho. Iniciamente, apresenta-se uma revisão bibliográfica, sob três diferentes enfoques. Primeiro, explica-se como as transformações mundiais estão afetando a estratégia das empresas. Depois, mostra-se o impacto da estratégia do século vinte e um dentro da organização. Por fim, focaliza-se o lado psicológico do ser humano, suas necessidades, tais quais a autonomia, a competência e o relacionamento interpessoal, os fatores de satisfação intrínsecos e extrínsecos. Assim, pode-se avaliar o impacto de uma nova estrutura organizacional na motivação dos funcionários. A seguir, apresenta-se o projeto de uma pesquisa-piloto dos fatores de satisfação mais relevantes para as pessoas, confirmando-se a importância dos fatores de satisfação intrínsecos. Mostra-se também que os índices de satisfação são diretamente afetados pelo ambiente empresarial onde atuam, de acordo com seu grau de autonomia. Então, são mostradas as conclusões do trabalho e recomendações práticas para mudanças na estrutura organizacional dentro de uma empresa, seus custos e como elas devem ser administradas no longo prazo.

A model of competition and interbank network formation

This work aims to understand the interaction between competition and network formation in the banking market. Combining Matutes and Padilla (1994) and Matutes and Vives (2000), we build a model of imperfect bank competition for deposits in which an interbank relationship network is a key strategic decision: it affects banks’ profit and risk position. The competition level exerts influence in the banking network structure since it affects the network outcomes. As result, we have that different competition levels imply different network topologies. Specifically, greater competition imply denser networks. Finally, when we allow for the possibility of collusion, the denser network can come out in the least competitive environment.