The Role of Multilateral Coordination in Transport Policy: The Case of the Maghreb Countries

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper aims at describing how multilateral cooperation policies are influencing national transport policies in developing countries. It considers the evolution of national transport policies and institutional frameworks in Algeria, Morocco and Tunisia in the last 10 years, and analyses the influence that EU cooperation programmes (particularly those within the Euromed programme initiative) and international coordination activities have played in the evolution towards efficient, sustainable transport systems in those countries. Notwithstanding the significant socioeconomic, political and institutional differences among the three countries, three major traits are common to the transport policy framework in all cases: a focus on megaprojects; substitution of traditional ministerial services by ad hoc public agencies to develop those megaprojects, and progressive involvement of international private players for the operation (and eventually the design and construction) of new projects, focusing on know-how transfer rather than investment needs. The hypotheses is that these similarities are largely due to the influence of the international cooperation promoted by the European Union since the mid- 1990s. The new decision making situation is characterized by the involvement of two new relevant stakeholders, the EU and a limited number of global transport operators. The hierarchical governance model evolves towards more complex structures, which explain the three common traits mentioned above. International coordination has been crucial for developing national transport visions, which are coherent with a regional, transnational system.

Everything in di Dark Muss Come to Light: A Postcolonial Investigation of the Practice of Extra Lessons at the Secondary Level in Jamaica's Education System

Despite the vast research examining the evolution of Caribbean education systems, little is chronologically tied to the postcolonial theoretical perspectives of specific island-state systems, such as the Jamaican education system and its relationship with the underground shadow education system. This dissertation study sought to address the gaps in the literature by critically positioning postcolonial theories in education to examine the macro- and micro-level impacts of extra lessons on secondary education in Jamaica. The following postcolonial theoretical (PCT) tenets in education were contextualized from a review of the literature: (a) PCT in education uses colonial discourse analysis to critically deconstruct and decolonize imperialistic and colonial representations of knowledge throughout history; (b) PCT in education uses an anti-colonial discursive framework to re-position indigenous knowledge in schools, colleges, and universities to challenge hegemonic knowledge; (c) PCT in education involves the "unlearning" of dominant, normative ideologies, the use of self-reflexivity, and deconstruction; and (d) PCT in education calls for critical pedagogical approaches that reject the banking concept of education and introduces inclusive pedagogy to facilitate "the passage from naïve to critical transitivity" (Freire, 1973, p. 32). Specifically, using a transformative mixed-methods design, grounded and informed by a postcolonial theoretical lens, I quantitatively uncovered and then qualitatively highlighted how if at all extra lessons can improve educational outcomes for students at the secondary level in Jamaica. Accordingly, the quantitative data was used to test the hypotheses that the practice of extra lessons in schools is related to student academic achievement and the practice of critical-inclusive pedagogy in extra lessons is related to academic achievement. The two-level hierarchical linear model analysis revealed that hours spent in extra lessons, average household monthly income, and critical-inclusive pedagogical tents were the best predictors for academic achievement. Alternatively, the holistic multi-case study explored how extra-lessons produces increased academic achievement. The data revealed new ways of knowledge construction and critical pedagogical approaches to galvanize systemic change in secondary education. Furthermore, the data showed that extra lessons can improve educational outcomes for students at the secondary level if the conditions for learning are met. This study sets the stage for new forms of knowledge construction and implications for policy change.

Growing global brands in foreign markets: A brand equity perspective. Impact of national culture on trademark registrations in emerging economy: Evidence from Russia. ACES Working Papers, August 2010

In this study we explore how firms deploy intellectual property assets (trademarks) in international context and the impact of cultural characteristics on such activities. Trademarks capture important elements of firm's brand-building efforts. Using growth model, a special case of hierarchical linear model, we demonstrate that that stock of trademarks in foreign market increase future trademark activity. Also, we explore the moderating roles of two cultural dimensions, individualism and masculinity, on such relationships. The findings indicated that firms from countries closer to host market (Russia) on individualism dimension tend to register more trademarks in host market. The opposite result is observed for masculinity dimension.

Goal orientation, ability and task performance: A moderated analysis

Achievement goal orientation represents an individual's general approach to an achievement situation, and has important implications for how individuals react to novel, challenging tasks. However, theorists such as Yeo and Neal (2004) have suggested that the effects of goal orientation may emerge over time. Bell and Kozlowski (2002) have further argued that these effects may be moderated by individual ability. The current study tested the dynamic effects of a new 2x2 model of goal orientation (mastery/performance x approach/avoidance) on performance on a simulated air traffic control (ATC) task, as moderated by dynamic spatial ability. One hundred and one first-year participants completed a self-report goal orientation measure and computerbased dynamic spatial ability test and performed 30 trials of an ATC task. Hypotheses were tested using a two-level hierarchical linear model. Mastery-approach orientation was positively related to task performance, although no interaction with ability was observed. Performance-avoidance orientation was negatively related to task performance; this association was weaker at high levels of ability. Theoretical and practical implications will be discussed.

Measuring the operational performance of intensive care units using the analytic hierarchy process approach

Purpose - The purpose of this study is to develop a performance measurement model for service operations using the analytic hierarchy process approach. Design/methodology/approach - The study reviews current relevant literature on performance measurement and develops a model for performance measurement. The model is then applied to the intensive care units (ICUs) of three different hospitals in developing nations. Six focus group discussions were undertaken, involving experts from the specific area under investigation, in order to develop an understandable performance measurement model that was both quantitative and hierarchical. Findings - A combination of outcome, structure and process-based factors were used as a foundation for the model. The analyses of the links between them were used to reveal the relative importance of each and their associated sub factors. It was considered to be an effective quantitative tool by the stakeholders. Research limitations/implications - This research only applies the model to ICUs in healthcare services. Practical implications - Performance measurement is an important area within the operations management field. Although numerous models are routinely being deployed both in practice and research, there is always room for improvement. The present study proposes a hierarchical quantitative approach, which considers both subjective and objective performance criteria. Originality/value - This paper develops a hierarchical quantitative model for service performance measurement. It considers success factors with respect to outcomes, structure and processes with the involvement of the concerned stakeholders based upon the analytic hierarchy process approach. The unique model is applied to the ICUs of hospitals in order to demonstrate its effectiveness. The unique application provides a comparative international study of service performance measurement in ICUs of hospitals in three different countries. © Emerald Group Publishing Limited.

Probabilistic methods for drug discovery

This thesis introduces a flexible visual data exploration framework which combines advanced projection algorithms from the machine learning domain with visual representation techniques developed in the information visualisation domain to help a user to explore and understand effectively large multi-dimensional datasets. The advantage of such a framework to other techniques currently available to the domain experts is that the user is directly involved in the data mining process and advanced machine learning algorithms are employed for better projection. A hierarchical visualisation model guided by a domain expert allows them to obtain an informed segmentation of the input space. Two other components of this thesis exploit properties of these principled probabilistic projection algorithms to develop a guided mixture of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the chemical space. Probabilistic hierarchical visualisation techniques provide an effective soft segmentation of an input space by a visualisation hierarchy whose leaf nodes represent different regions of the input space. We use this soft segmentation to develop a guided mixture of local experts (GME) algorithm which is appropriate for the heterogeneous datasets found in chemoinformatics problems. Moreover, in this approach the domain experts are more involved in the model development process which is suitable for an intuition and domain knowledge driven task such as drug discovery. We also derive a generative topographic mapping (GTM) based data visualisation approach which estimates feature saliency simultaneously with the training of a visualisation model.

Determinants of sponsorship fit:a multilevel analysis

Sponsorship fit is frequently mentioned and empirically examined as a success factor of sponsorship. While sponsorship fit has been considered as a determinant of sponsorship success, little knowledge exists about the antecedents of sponsorship fit. In the present paper, individual and firm-level antecedents of sponsorship fit are examined in a single hierarchical linear model. Results show that sponsorship fit is influenced by the perception of benefits, the firm’s regional identification, sincerity, relatedness to the sponsored activity, and its dominance. On a partnership level, results show that contract length contributes to sponsorship fit while contract value is found to be unrelated.

Petroleum pipeline construction planning:a conceptual framework

A cross-country pipeline construction project is exposed to an uncertain environment due to its enormous size (physical, manpower requirement and financial value), complexity in design technology and involvement of external factors. These uncertainties can lead to several changes in project scope during the process of project execution. Unless the changes are properly controlled, the time, cost and quality goals of the project may never be achieved. A methodology is proposed for project control through risk analysis, contingency allocation and hierarchical planning models. Risk analysis is carried out through the analytic hierarchy process (AHP) due to the subjective nature of risks in construction projects. The results of risk analysis are used to determine the logical contingency for project control with the application of probability theory. Ultimate project control is carried out by hierarchical planning model which enables decision makers to take vital decisions during the changing environment of the construction period. Goal programming (GP), a multiple criteria decision-making technique, is proposed for model formulation because of its flexibility and priority-base structure. The project is planned hierarchically in three levels—project, work package and activity. GP is applied separately at each level. Decision variables of each model are different planning parameters of the project. In this study, models are formulated from the owner's perspective and its effectiveness in project control is demonstrated.

The impact of service characteristics on the switching costs-customer loyalty link

This research investigates the interrelationship between service characteristics and switching costs and makes two contributions to the service retailing literature: (1) As a means of better understanding the effectiveness of switching costs, the study suggests a two-dimensional typology of switching costs, including internal and external switching costs and (2) it reveals that the effect of these switching costs on customer loyalty is contingent upon four service characteristics (the IHIP characteristics of service). We carried out a meta-analytic review of the literature on the switching costs-customer loyalty link and created a hierarchical linear model using a sample of 1,694 customers from 51 service industries. Results reveal that external switching costs have a stronger average effect on customer loyalty than do internal switching costs. Moreover, we find that IHIP characteristics moderate the links between switching costs and customer loyalty. Thus, the link between external switching costs and customer loyalty is weaker in industries higher in the four service characteristics (as compared to industries lower in these characteristics), while the opposite moderating effect of service characteristics for the internal switching costs-loyalty link is noted. © 2014 New York University.

DIMUSE: An integrated framework for distributed multimedia system with database management and security support

With the recent explosion in the complexity and amount of digital multimedia data, there has been a huge impact on the operations of various organizations in distinct areas, such as government services, education, medical care, business, entertainment, etc. To satisfy the growing demand of multimedia data management systems, an integrated framework called DIMUSE is proposed and deployed for distributed multimedia applications to offer a full scope of multimedia related tools and provide appealing experiences for the users. This research mainly focuses on video database modeling and retrieval by addressing a set of core challenges. First, a comprehensive multimedia database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) is proposed to model high dimensional media data including video objects, low-level visual/audio features, as well as historical access patterns and frequencies. The associated retrieval and ranking algorithms are designed to support not only the general queries, but also the complicated temporal event pattern queries. Second, system training and learning methodologies are incorporated such that user interests are mined efficiently to improve the retrieval performance. Third, video clustering techniques are proposed to continuously increase the searching speed and accuracy by architecting a more efficient multimedia database structure. A distributed video management and retrieval system is designed and implemented to demonstrate the overall performance. The proposed approach is further customized for a mobile-based video retrieval system to solve the perception subjectivity issue by considering individual user's profile. Moreover, to deal with security and privacy issues and concerns in distributed multimedia applications, DIMUSE also incorporates a practical framework called SMARXO, which supports multilevel multimedia security control. SMARXO efficiently combines role-based access control (RBAC), XML and object-relational database management system (ORDBMS) to achieve the target of proficient security control. A distributed multimedia management system named DMMManager (Distributed MultiMedia Manager) is developed with the proposed framework DEMUR; to support multimedia capturing, analysis, retrieval, authoring and presentation in one single framework.

Essays on corporate reputation: Antecedents and consequences

This dissertation studied the determinants and consequences of corporate reputation. It explored how firm-, industry-, and country-level factors influence the general public’s assessment of a firm’s reputation and how this reputation assessment impacted the firm’s strategic actions and organizational outcomes. The three empirical essays are grounded on separate theoretical paradigms in strategy, organizational theory, and corporate governance. The first essay used signaling theory to investigate firm-, industry-, and country-level determinants of individual-level corporate reputation assessments. Using a hierarchical linear model, it tested the theory based on individual evaluations of the largest companies across countries. Results indicated that variables at multiple analysis levels simultaneously impact individual level reputation assessments. Interactions were also found between industry- and country-level factors. Results confirmed the multi-level nature of signaling influences on reputation assessments. Building on a stakeholder-power approach to corporate governance, the second essay studied how differences in the power and preferences of three stakeholder groups—shareholders, creditors, and workers—across countries influence the general public’s reputation assessments of corporations. Examining the largest companies across countries, the study found that while the influence of stock market return is stronger in societies where shareholders have more power, social performance has a more significant role in shaping reputation evaluations in societies with stronger labor rights. Unexpectedly, when creditors have greater power, the influence of financial stability on reputation assessment becomes weaker. Exploring the consequences of reputation, the third essay investigated the specific effects of intangible assets on strategic actions and organizational outcomes. Particularly, it individually studied the impacts of acquirer acquisition experience, corporate reputation, and approach toward social responsibilities as well as their combined effect on market reactions to acquisition announcements. Using an event study of acquisition announcements, it confirmed the significant impacts of both action-specific (acquisition experience) and general (reputation and social performance) intangible assets on market expectations of acquisition outcomes. Moreover, the analysis demonstrated that reputation magnifies the impact of acquisition experience on market response to acquisition announcements. In conclusion, this dissertation tried to advance and extend the application of management and organizational theories by explaining the mechanisms underlying antecedents and consequences of corporate reputation.

A generic method of engagement to elicit regional coastal management options

Stakeholder engagement is important for successful management of natural resources, both to make effective decisions and to obtain support. However, in the context of coastal management, questions remain unanswered on how to effectively link decisions made at the catchment level with objectives for marine biodiversity and fisheries productivity. Moreover, there is much uncertainty on how to best elicit community input in a rigorous manner that supports management decisions. A decision support process is described that uses the adaptive management loop as its basis to elicit management objectives, priorities and management options using two case studies in the Great Barrier Reef, Australia. The approach described is then generalised for international interest. A hierarchical engagement model of local stakeholders, regional and senior managers is used. The result is a semi-quantitative generic elicitation framework that ultimately provides a prioritised list of management options in the context of clearly articulated management objectives that has widespread application for coastal communities worldwide. The case studies show that demand for local input and regional management is high, but local influences affect the relative success of both engagement processes and uptake by managers. Differences between case study outcomes highlight the importance of discussing objectives prior to suggesting management actions, and avoiding or minimising conflicts at the early stages of the process. Strong contributors to success are a) the provision of local information to the community group, and b) the early inclusion of senior managers and influencers in the group to ensure the intellectual and time investment is not compromised at the final stages of the process. The project has uncovered a conundrum in the significant gap between the way managers perceive their management actions and outcomes, and community's perception of the effectiveness (and wisdom) of these same management actions.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Clustering of variables with a three-way approach for health sciences

© 2014 Cises This work is distributed with License Creative Commons Attribution-Non commercial-No derivatives 4.0 International (CC BY-BC-ND 4.0)