42 resultados para Definition in terminology


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This paper addresses the topic of knowledge management in multinational companies (MNCs). Its purpose is to examine the role of expatriates in knowledge acquisition and transfer within MNCs. Specifically it focuses on knowledge acquisition and transfer from one MNC head office located in Germany to two Portuguese subsidiaries as a basis for competitive advantage in their Portuguese subsidiaries. A qualitative research methodology is used, specifically through an exploratory case study approach, which examines how international assignments are important for the role of expatriates In knowledge acquisition and transfer between foreign head offices and their Portuguese subsidiaries. The data were collected through semi structured interviews to 10 Portuguese repatriates from two Portuguese subsidiaries of one foreign MNC. The findings suggest that the reasons that lead to expatriating employees from Portuguese subsidiaries to foreign head offices are connected to (1) knowledge management strategies to development the subsidiary’s performance; (2) new skills and knowledge acquisition by future team leaders and business/product managers in Portuguese subsidiaries; (3) procuring knowledge, from agents in head office, to be disseminated amongst co-workers in Portuguese subsidiaries; (4) acquiring global management skills, impossible to acquire locally and; (5) developing global projects within MNC. Also our results show that knowledge acquisition and transfer from foreign head office, through subsidiaries’ expatriates, contributes directly to the Portuguese subsidiaries’ innovation, improved performance, competitive advantage and growth in the economic sectors in which they operate. Moreover, evidence reveals that expatriation is seen as a strategy to fulfil some of the main organisational objectives through their expatriates (e.g., create new products and business markets, develop and incorporate new organisational techniques and processes, integrate global teams within multinational corporation with a responsibility on the definition of global objectives). The results obtained suggest that expatriates have a central role in acquiring and transferring strategic knowledge from MNC head office to their subsidiaries located in Portugal. Based on the findings, the paper discusses in detail the main theoretical and managerial implications. Suggestions for further research are also presented. The study’s main limitation is the small size of the sample, but its findings and methodology are quite original and significant.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

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The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.

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The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

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The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.

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The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

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Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

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The use of appropriate acceptance criteria in the risk assessment process for occupational accidents is an important issue but often overlooked in the literature, particularly when new risk assessment methods are proposed and discussed. In most cases, there is no information on how or by whom they were defined, or even how companies can adapt them to their own circumstances. Bearing this in mind, this study analysed the problem of the definition of risk acceptance criteria for occupational settings, defining the quantitative acceptance criteria for the specific case study of the Portuguese furniture industrial sector. The key steps to be considered in formulating acceptance criteria were analysed in the literature review. By applying the identified steps, the acceptance criteria for the furniture industrial sector were then defined. The Cumulative Distribution Function (CDF) for the injury statistics of the industrial sector was identified as the maximum tolerable risk level. The acceptable threshold was defined by adjusting the CDF to the Occupational, Safety & Health (OSH) practitioners’ risk acceptance judgement. Adjustments of acceptance criteria to the companies’ safety cultures were exemplified by adjusting the Burr distribution parameters. An example of a risk matrix was also used to demonstrate the integration of the defined acceptance criteria into a risk metric. This work has provided substantial contributions to the issue of acceptance criteria for occupational accidents, which may be useful in overcoming the practical difficulties faced by authorities, companies and experts.

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Since the middle of the first decade of this century, several authors have announced the dawn of a new Age, following the Information/ Knowledge Age (1970-2005?). We are certainly living in a Shift Age (Houle, 2007), but no standard designation has been broadly adopted so far, and others, such as Conceptual Age (Pink, 2005) or Social Age (Azua, 2009), are only some of the proposals to name current times. Due to the amount of information available nowadays, meaning making and understanding seem to be common features of this new age of change; change related to (i) how individuals and organizations engage with each other, to (ii) the way we deal with technology, to (iii) how we engage and communicate within communities to create meaning, i.e., also social networking-driven changes. The Web 2.0 and the social networks have strongly altered the way we learn, live, work and, of course, communicate. Within all the possible dimensions we could address this change, we chose to focus on language – a taken-for-granted communication tool, used, translated and recreated in personal and geographical variants, by the many users and authors of the social networks and other online communities and platforms. In this paper, we discuss how the Web 2.0, and specifically social networks, have contributed to changes in the communication process and, in bi- or multilingual environments, to the evolution and freeware use of the so called “international language”: English. Next, we discuss some of the impacts and challenges of this language diversity in international communication in the shift age of understanding and social networking, focusing on specialized networks. Then we point out some skills and strategies to avoid babelization and to build meaningful and effective content in mono or multilingual networks, through the use of common and shared concepts and designations in social network environments. For this purpose, we propose a social and collaborative approach to terminology management, as a shared, strategic and sense making tool for specialized communication in Web 2.0 environments.

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Aim of the paper: The purpose of this paper is to examine human resources management practices (HRM practices) in small firms and to improve the understanding of the relationship between this kind of practices and business growth. This exploratory study is based on the resource-based view of the firm and empirical work carried out in two small firms by relating HRM practices with the firms’ results. Contribution to the literature: This is an in-depth study of HRM practices and its impact on performance growth in micro firms, isolating and controlling for most of the contextual and internal variables considered in the literature that relate HRM to growth. Firm growth analysis was broadened by the use of several dependent variables: employment growth and operational and financial performance growth. Some hypotheses for further research in identifying HRM practices in small business and its relation with firm growth are suggested. Methodology: Case study methodology was used to study two firms. The techniques used to collect data were semi-structured interviews to the owner and all the employees, unstructured observation at the firms’ facilities (during two days), entrepreneur profile definition (survey answer) and document data collection (on demographic characterization and performance results). Data was analyzed through content analysis methodology, and categories derived from the interviews’ protocols and literature. Results and implications: Results revealed that despite the firms’ organizational characteristics similarities, they differ significantly in owners’ motivation to grow, HRM practices and organizational performance and growth. Future studies should pay special attention to owner willingness to grow, to firms’ years of experience in business, to staff’s years of experience in their field of work and turnover. HRM practices in micro/small firms should be better defined and characterized. The external image of management posture relating to longitudinal financial results and growth should also be explored.

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Scientific literature has strengthened the perpetuation of inequality factors in the labour market based on gender, despite the on-going endeavour of various political bodies and legal norms against the vertical and horizontal segregation of women. National and European statistical data shows the relevance and timeless features of theories of market segmentation associated with the labour market dating back to the 70’s of the 20th century. Hence, the European Community considers as a priority in the Europe 2020 strategy, the definition of “policies to promote gender equality […] to increase labour force participation thus adding to growth and social cohesion”. If we consider that on the one hand, social economy is fairly recognised to be equated with market actors and the State for its economic and social role in tackling the current crisis, and on the other hand, that the ideals of the sector, systematised in the “Framework Law of Social Economy” (Law no. 30/2013 8th of May), particularly in article 5 proposing “the respect for the values […] of equality and non-discrimination […], justice and equity […]”, we aim to reflect on indicators that uncover a vertical and horizontal segregation in the labour market. Departing from a mixed methodological approach (extensive and intensive), subject to the topic of "Social Entrepreneurship in Portugal" in social economy organisations, we detect very high rates of employment feminisation, with a ratio of 1 man (23%) for every 3 women (77%). Women are mainly earmarked for technical and operational activities, arising from the privileged intervention areas, namely education, training, health, elderly, families, poverty, ultimately being underrepresented in statutory boards and, as such, far removed from deliberations and strategic resolutions. This is particularly visible in the existing hierarchy of functions and management practices of the responsibility of male members. Thus, it seems easily verified that the sector is travelling away from the ideals of justice and social equity, which can crystallise the "non-place" of women in the definition of a strategic direction of social economy and in the most invisible/private “place” of the organisational setting.