Techno-economic evaluation of 3G and beyond mobile business alternatives

Three business case scenarios in the context of emerging mobile access network technologies and business players have been studied and the economical results are presented. The aim is to cover some of the most interesting business alternatives in providing the new 3G and beyond services including cases where the operator may have an existing second-generation cellular network or not, and a license for the 3G UMTS network or not. The scenarios have been analyzed in different Western European country groups that are not exactly representative of any defined country, but rather share typical demographic characteristics. Investments and operational expenditures are identified and the results show how diverse business models and technologies lead to different revenue, cost, and profitability profiles. The business case scenarios include incumbent’s 3G evolution with UMTS compared to an alternative 3G technology deployment with mobile WiMAX, new entrant’s UMTS deployment business case, and a greenfield CDMA450 deployment business case.     

The option to expand to a next generation access network infrastructure and the role of regulation in a discrete time setting: A real options approach

Serious concerns have been raised, especially across Europe, about the role of regulation in network infrastructure investments. More specifically, the installation of optical fiber closer to customer premises, the so-called next generation access networks, requires massive investments in the face of demand and regulatory uncertainty. The purpose of this paper is to assess whether specific regulatory scenarios (permanent regulation, regulatory forbearance, regulatory holidays and sunset clauses) alter the timing of the investment decision of an incumbent to expand to a new network infrastructure exploiting the binomial lattice approach from real options analysis.     

Corporate Social Responsibility and Employee Outcomes: Interrelations of External and Internal Orientations with Job Satisfaction and Organizational Commitment

Journal of Business Ethics - We bring together social identity and social exchange perspectives to develop and test a moderated mediation model that sheds light on employees’ perceptions...     

REVISITING THE REAL WAGES–UNEMPLOYMENT RELATIONSHIP. NEW RESULTS FROM NON-LINEAR MODELS

We examine the long-run real wages–unemployment relationship for five OECD countries over the period 1960:1–2001:4. Given the theoretical possibility of non-linear equilibrium due to downward real wage rigidity we employ econometric tests that allow for the presence of non-linearities in the long-run equilibrium. We adopt the notion of 'hidden co-integration' suggested by Granger and Yoon . This methodology has several advantages with respect to other non-linear models. We find statistical evidence that, in general, there is a long-run positive relation between real wages and unemployment only when both are affected by positive shocks. We also find a negative relationship between unemployment and productivity. The empirical analysis is complemented with the estimation of error correction models for all countries.     

FORECASTING INFLATION USING DYNAMIC MODEL AVERAGING*

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods that incorporate dynamic model averaging. These methods not only allow for coefficients to change over time, but also allow for the entire forecasting model to change over time. We find that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.     

ON THE SOURCES OF UNCERTAINTY IN EXCHANGE RATE PREDICTABILITY

In a unified framework, we examine four sources of uncertainty in exchange rate forecasting models: (i) random variations in the data, (ii) estimation uncertainty, (iii) uncertainty about the degree of time variation in coefficients, and (iv) uncertainty regarding the choice of the predictor. We find that models that embed a high degree of coefficient variability yield forecast improvements at horizons beyond one month. At the one‐month horizon, and apart from the standard variance implied by unpredictable fluctuations in the data, the second and third sources of uncertainty listed above are key obstructions to predictive ability. The uncertainty regarding the choice of the predictors is negligible.     

The role of productive efficiency on entry and post‐entry performance under different strategic orientation: the case of the Greek plastics and rubber industry

The present study formulates and empirically tests the hypothesis that the post‐entry performance and growth of new firms is affected by the way in which crucial resources are combined during the decision‐making process to enter the industry or not. Further, the study empirically tests the hypothesis that multifaceted productive efficiency influences both the entry decision and the entrants' post‐entry performance. The proposed analytical framework allows for testing these hypotheses under different strategic orientations assumed to be followed by entrants. Results of the estimated partial observability model provide support to these hypotheses in almost all of the examined cases. Copyright © 2008 John Wiley & Sons, Ltd.     

Cointegration modeling of interrelated factor demands: With an application to labor–import substitution in the European Union

In this paper we present techniques for cointegration modeling of interrelated factor demands. These techniques respect the non-stationary character of the price and quantity data, and permit specification of general, dynamic factor demand models based on error correction forms derived from cointegration. Therefore, we do not have to assume ad hoc dynamic forms. Moreover, we ensure that estimated relations are structural, and not spurious. Cointegrating vectors are estimated subject to all standard economic theory restrictions by using a procedure, which we call dynamic SUR. We show how consistent error correction models can be specified and estimated. In addition, we test the neoclassical restrictions both in the short- and the long run. The new methods are used to shed light on the major problem of the European Union (unemployment) and its relationship with imports. The empirical analysis is conducted for five countries of the European Union with an emphasis to the south: The UK, France, Greece, Italy, and Spain.     

Integrating machine learning and workflow management to support acquisition and adaptation of workflow models

Current workflow management systems (WFMS) offer little aid for the acquisition of workflow models and their adaptation to changing requirements. To support these activities we propose to apply techniques from machine learning, which enable an inductive approach to workflow acquisition and adaptation. We present a machine learning component that combines two different machine learning algorithms: the first induces the structure of sequential workflows and the second is responsible for the induction of transition conditions. The second task can be solved by applying standard decision rule induction algorithms. In this contribution we focus mainly on the algorithms for the first task. For this purpose we describe two algorithms based on the induction of hidden Markov models. The first algorithm is a bottom‐up, specific‐to‐general algorithm and the other applies a top‐down, general‐to‐specific strategy. Both algorithms have been implemented in a research prototype. In six scenarios we evaluate and compare the two algorithms experimentally. The induced workflow models can be imported by the business process management system ADONIS. Copyright © 2000 John Wiley & Sons, Ltd.     

Economies of scale,cost minimization and productivity in telecom markets under economic crisis: evidence from Greece

Telecommunications has entered a new age of development with advanced technology and increased competition with established players. The main focus of telecom operators is to maintain and increase their market shares by creating a loyal customer base and technology advancements. However, it remains difficult for telecom operators to evaluate their performance and competence within a fast-changing environment, especially since the telecom business is complex and involves unknown trade-offs. The current study proposes a series of methods in order to evaluate the performance of telecommunication companies, using as a case study the Hellenic Telecommunications Organization (OTE). OTE’s importance lies on its role as one of the leading companies in Greece affecting the economy. On the methodological side, this paper applies the linear regression analysis to measure and evaluate the performance of OTE. The results show that during the period 2005-2015 there are events which affect the operation of OTE and create conditions for cost optimization which are of great importance and they determine the future evolution of the organization. The results of this study are expected to be utilized as guidelines for the telecom operators as well as for regulators and decision makers in general.