Strategic management in the Telecom industry to create competitive advantage

O presente trabalho teve por objetivos a identificação de uma estratégia e o desenvolvimento de um modelo que permita às operadoras de telecomunicações a sua sustentabilidade, bem como a identificação de caminhos para a adaptação a uma realidade sempre em mudança como é a da indústria das telecomunicações. Numa primeira parte do trabalho elaborou-se uma revisão de literatura do atual estado da arte das principais estratégias relevantes e com aplicação à indústria de telecomunicações. A pesquisa realizada investigou a estrutura atual da indústria de telecomunicações e o estado da competitividade das operadoras de telecomunicações. Dos resultados desta foi possível constatar uma evolução constante da tecnologia e dos modelos de negócio neste ecossistema, assim como a presença de uma pressão concorrencial significativa exercida sobre as operadoras, quer por parte das empresas já existentes no mercado quer por parte das emergentes. As operadoras têm de transformar o seu modelo de rede e de negócios para se adaptarem às mudanças e às tendências da indústria e do mercado. Com base na revisão de literatura, elegeu-se a metodologia baseada num inquérito de pesquisa empírica para aferir o estado da indústria e derivar as estratégias possíveis. Este inquérito foi efetuado a especialistas da área de telecomunicações de diferentes subsectores e países para abordar todos os elementos estratégicos do modelo de negócio futuro. Os resultados da pesquisa revelaram que as empresas que operam no mercado da Internet (Over The Top - OTT) representam a maior ameaça sobre o futuro dos operadores de telecomunicações. Os operadores só vão conseguir responder através da modernização de sua rede, melhorando a qualidade, reduzindo o custo global, e investindo em produtos inovadores e diferenciados e em serviços. Os resultados do inquérito revelam-se de acordo com os pressupostos da Blue Ocean Strategy. A aplicabilidade da Blue Ocean Strategy foi aprofundada permitindo concluir que o valor inovador obtido simultaneamente através da redução de custos e da diferenciação permitem aumentar as vantagens dos operadores existentes em termos das infra-estruturas físicas detidas e das relações estabelecidas com os clientes. O caso particular da fibra óptica até casa (FTTH) foi considerado como aplicação da Blue Ocean Strategy a uma nova tecnologia que as operadoras podem implementar para criar novas soluções e abrir segmentos de mercado inexplorados. Os resultados do inquérito e da investigação realizada à aplicação da Blue Ocean Strategy foram combinados para propor um novo modelo de negócio para as operadoras de telecomunicações que lhes permite, não só responder aos desafios existentes, mas, também, ter uma melhor posição competitiva no futuro. Foi, ainda, realizado um estudo de caso que destacou como a Verizon Communications foi capaz de transformar a sua rede e o modelo de negócio em resposta ao aumento da pressão competitiva. Através do valor da inovação transferida aos seus clientes, a Verizon foi capaz de aumentar significativamente as suas receitas e satisfação do cliente.

Competitive destination analysis in Southern European countries

Purpose – The purpose of this paper is to analyse the competitiveness of the European Union Member States of Southern Europe (France, Greece, Italy, Portugal and Spain) as tourist destinations for European Union Member States of Central and Northern Europe (Austria, Belgium, Denmark, Finland, Germany, The Netherlands, Ireland, Sweden and the UK). Design/methodology/approach – Application of the market share analysis tool, initially developed by Faulkner, using secondary data from Eurostat – statistical office of the European communities. Findings – The results obtained show that France, Greece, Italy, Portugal and Spain present distinct levels of competitiveness for the various generating countries, with changes having occurred in the period between 1999 and 2007. Originality/value – The paper offers refreshment of Faulkner's tool and an insight into tourist flows in Europe as a tool for tourism and hospitality managers.

Competitive Intelligence : Aufbau einer Informationsbasis und Entscheidungssystematik zur Definition strategischer Zielmärkte

Im Rahmen der Globalisierung und des daraus resultierenden Wettbewerbs ist es für ein Unternehmen von zentraler Bedeutung, Wissen über die Wettbewerbssituation zu erhalten. Nicht nur zur Erschließung neuer Märkte, sondern auch zur Sicherung der Unternehmensexistenz ist eine Wettbewerbsanalyse unabdingbar. Konkurrenz- bzw. Wettbewerbsforschung wird überwiegend als „Competitive Intelligence“ bezeichnet. In diesem Sinne beschäftigt sich die vorliegende Bachelorarbeit mit einem Bereich von Competitive Intelligence. Nach der theoretischen Einführung in das Thema werden die Ergebnisse von neun Experteninterviews sowie einer schriftlichen Expertenbefragung innerhalb des Unternehmens erläutert. Die Experteninterviews und -befragungen zum Thema Competitive Intelligence dienten zur Entwicklung eines neuen Wettbewerbsanalysekonzeptes. Die Experteninterviews zeigten, dass in dem Unternehmen kein einheitliches Wettbewerbsanalysesystem existiert und Analysen lediglich ab hoc getätigt werden. Zusätzlich wird ein Länderranking vorgestellt, das zur Analyse europäischer Länder für das Unternehmen entwickelt wurde. Die Ergebnisse zeigten, dass Dänemark und Italien für eine Ausweitung der Exportgeschäfte bedeutend sind. Der neu entwickelte Mitbewerberbewertungsbogen wurde auf Grundlage dieser Ergebnisse für Dänemark und Italien getestet.

Entscheidungshilfe bei Internationalisierungsstrategien in der Nutzfahrzeugindustrie durch Competitive Intelligence - am Anwendungsbeispiel Afrika

Die nachhaltige Verschiebung der Wachstumsmärkte in Richtung Emerging Markets (und hier insbesondere in die BRIC-Staaten) infolge der Wirtschaftskrise 2008/2009 hat die bereits weit reichend konsolidierte Nutzfahrzeugindustrie der Triadenmärkte in Nordamerika, Europa und Japan vor eine Vielzahl von Herausforderungen gestellt. Strategische Ziele wie die Festigung und Steigerung von Absatzvolumina sowie eine bessere Ausbalancierung von zyklischen Marktentwicklungen, die die Ertragssicherung und eine weitestgehend kontinuierliche Auslastung existenter Kapazitäten sicherstellen soll, sind in Zukunft ohne eine Marktbearbeitung in den ex-Triade Wachstumsmärkten kaum noch erreichbar. Dies verlangt eine Auseinandersetzung der betroffenen Unternehmen mit dem veränderten unternehmerischen Umfeld. Es gilt neue, bisher größtenteils unbekannte Märkte zu erobern und sich dabei neuen – teilweise ebenfalls wenig bekannten - Wettbewerbern und deren teilweise durchaus unkonventionellen Strategien zu stellen. Die Triade-Unternehmen sehen sich dabei Informationsdefiziten und einer zunehmenden Gesamtkomplexität ausgesetzt, die zu für sie zu nachteiligen und ungünstigen nformationsasymmetrien führen können. Die Auswirkungen, dieser Situation unangepasst gegenüberzutreten wären deutlich unsicherheits- und risikobehaftetere Marktbearbeitungsstrategien bzw. im Extremfall die Absenz von Internationalisierungsaktivitäten in den betroffenen Unternehmen. Die Competitive Intelligence als Instrument zur unternehmerischen Umfeldanalyse kann unterstützen diese negativen Informationsasymmetrien zu beseitigen aber auch für das Unternehmen günstige Informationsasymmetrien in Form von Informationsvorsprüngen generieren, aus denen sich Wettbewerbsvorteile ableiten lassen. Dieser Kontext Competitive Intelligence zur Beseitigung von Informationsdefiziten bzw. Schaffung von bewussten, opportunistischen Informationsasymmetrien zur erfolgreichen Expansion durch Internationalisierungsstrategien in den Emerging Markets wird im Rahmen dieses Arbeitspapieres durch die Verbindung von wissenschaftstheoretischen und praktischen Implikationen näher beleuchtet. Die sich aus dem beschriebenen praktischen Anwendungsbeispiel Competitive intelligence für afrikanische Marktbearbeitung ergebenden Erkenntnisse der erfolgreichen Anwendung von Competitive Intelligence als Entscheidungshilfe für Internationalisierungsstrategien sind wie folgt angelegt: - Erweiterung der Status-quo, häufig Stammmarkt-zentristisch angelegten Betrachtungsweisen von Märkten und Wettbewerbern in Hinblick auf das reale Marktgeschehen oder Potentialmärkte - bias-freie Clusterung von Märkten bzw. Wettbewerbern, oder Verzicht auf den Versuch der Simplifizierung durch Clusterbildung - differenzierte Datenerhebungsverfahren wie lokale vs. zentrale / primäre vs. sekundäre Datenerhebung für inhomogene, unterentwickelte oder sich entwickelnde Märkte - Identifizierung und Hinzuziehung von Experten mit dem entscheidenden Wissensvorsprung für den zu bearbeitenden Informationsbedarf - Überprüfung der Informationen durch Datentriangulation

Application of Decision-Making Theory to the Regulation of Muscular Work Rate During Self-Paced Competitive Endurance Activity.

Successful participation in competitive endurance activities requires continual regulation of muscular work rate in order to maximise physiological performance capacities, meaning that individuals must make numerous decisions with regards to the muscular work rate selected at any point in time. Decisions relating to the setting of appropriate goals and the overall strategic approach to be utilised are made prior to the commencement of an event, whereas tactical decisions are made during the event itself. This review examines current theories of decision-making in an attempt to explain the manner in which regulation of muscular work is achieved during athletic activity. We describe rational and heuristic theories, and relate these to current models of regulatory processes during self-paced exercise in an attempt to explain observations made in both laboratory and competitive environments. Additionally, we use rational and heuristic theories in an attempt to explain the influence of the presence of direct competitors on the quality of the decisions made during these activities. We hypothesise that although both rational and heuristic models can plausibly explain many observed behaviours in competitive endurance activities, the complexity of the environment in which such activities occur would imply that effective rational decision-making is unlikely. However, at present, many proposed models of the regulatory process share similarities with rational models. We suggest enhanced understanding of the decision-making process during self-paced activities is crucial in order to improve the ability to understand regulation of performance and performance outcomes during athletic activity.

The significance of Marx's value for strategy theory: competitive advantage and the issue of tautology within the resource-based view of the firm

Marxian thinking following the TSSI (Temporal Single System Interpretation) of Marx is applied to refute the allegation of a tautology in the resource-based view of the firm--paired with providing an explanation of how and why resources create value--, where resources are synonymous with Marx's categories of constant and variable capital. Refuting the allegation naturally leads to the holy grail of resource-based thinking, i.e. the question of what, conceptually, constitutes a firm's competitive advantage within the industry context. The article achieves its objectives by tying the resource-based view into Marx's theory value.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.

VPP´s multi-level negotiation in smart grids and competitive electricity markets

The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs’ management. The proposed methodology is implemented and tested in MASCEM – a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.

Virtual power producers simulation - negotiating renewable distributed generation in competitive electricity markets

Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Competitive analysis of partitioned scheduling on uniform multiprocessors

Consider the problem of scheduling a set of sporadically arriving tasks on a uniform multiprocessor with the goal of meeting deadlines. A processor p has the speed Sp. Tasks can be preempted but they cannot migrate between processors. We propose an algorithm which can schedule all task sets that any other possible algorithm can schedule assuming that our algorithm is given processors that are three times faster.

Competitive analysis of static-priority partitioned scheduling on uniform multiprocessors

Consider the problem of scheduling a set of sporadically arriving tasks on a uniform multiprocessor with the goal of meeting deadlines. A processor p has the speed Sp. Tasks can be preempted but they cannot migrate between processors. On each processor, tasks are scheduled according to rate-monotonic. We propose an algorithm that can schedule all task sets that any other possible algorithm can schedule assuming that our algorithm is given processors that are √2 / √2−1 ≈ 3.41 times faster. No such guarantees are previously known for partitioned static-priority scheduling on uniform multiprocessors.

A two-competitive approximate schedulability analysis of CAN

Consider the problem of deciding whether a set of n sporadic message streams meet deadlines on a Controller Area Network (CAN) bus for a specified priority assignment. It is assumed that message streams have implicit deadlines and no release jitter. An algorithm to solve this problem is well known but unfortunately it time complexity is non-polynomial. We present an algorithm with polynomial time-complexity for computing an upper bound on the response times. Clearly, if the upper bound on the response time does not exceed the deadline then all deadlines are met. The pessimism of our approach is proven: if the upper bound of the response time exceeds the deadline then the response time exceeds the deadline as well for a CAN network with half the speed.