802 research outputs found

    Green Purchase: The influence of Pro-environmental Behavioral intention on Consumer green purchase decision

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    Masteroppgave International Buisness and Marketing - Nord universitet 201

    Emotional Exhaustion, Motivation and Job Outcomes: a Study of Hotel Frontline Employees in Phuket

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    The objectives of this study were 1) to study the relationship of emotional exhaustion, and motivation on frontline employees' job outcomes; 2) to identify the prior motivating factor for work of hotel frontline employee in Phuket. A cross-sectional sample survey was conducted. The target population was all hotel frontline employees in Phuket, Thailand, during the survey period. Data was analyzed using both univariate and multivariate techniques with SPSS and LISREL 8.5. Using LISREL 8.5, the Structural Equation Modeling (SEM) was employed to determine the causal relationship between predictor variable and to test the hypotheses to confirm the casual relationships. Results indicate that job outcomes (job satisfaction, organizational commitment, job performance and turnover intension) of hotel frontline employee have casual relationships with motivation and emotional exhaustion. Both emotional exhaustion and motivation have a significant influence on job satisfaction and organizational commitment. Even though job satisfaction does not always lead to higher employees' perceived job performance, the organizational commitment still favorable affect job performance. For the top five of motivation factors of hotel frontline employees in Phuket, the study found that pay is the most value for hotel frontline employee, next job security, present co-worker, physical working condition and hotel recognition is ranking respectively. This finding suggests that it would be worthwhile for hotel managers to make greater concern in motivation and emotional exhaustion factors, in order to enhance job outcomes of hotel frontline employees. Additionally, the present study suggests that using multiple motivation theories which are better than focusing on one theory because the national culture plays an important role in determining the conditions for motivating people.School of Hotel and Restaurant Administratio

    Teleosemantics and the hard problem of content

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    Hutto and Myin claim that teleosemantics cannot account for mental content. In their view, teleosemantics accounts for a poorer kind of relation between cognitive states and the world but lacks the theoretical tools to account for a richer kind. We show that their objection imposes two criteria on theories of content: a truth-evaluable criterion and an intensionality criterion. For the objection to go through, teleosemantics must be subject to both these criteria and must fail to satisfy them. We argue that teleosemantics meets the truth-evaluable criterion and is not required to meet the intensionality criterion. We conclude that Hutto and Myin’s objection fails

    Two set-theoretic approaches to the semantics of adjective-noun combinations

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    This work addresses the problem of adjective-noun combinations. Conventionally, adjectives belong to a hierarchy. This has the consequence that a uniform treatment of adjectives is unattainable---without resorting to notions such as possible worlds, which are difficult to map into competent computer programs. In this work, we propose two set-theoretic approaches to the semantics of adjective-noun combinations. The first hypothesizes that an adjective-noun compound is a subset of its constituent noun. The second hypothesizes that the adjective-noun combinations can semantically be thought of as a set intersection involving the adjective(s) and the head noun of the compound. This work argues that the class of adjectives known as privative can be accommodated within an existing class in the adjective hierarchy, known as subsective . This step is important for the provision of uniform treatments of adjective-noun combinations. The two approaches make use of types, both for gaining a finer granularity of analysis and for imposing structure on the problem domain. It is shown that the mixture of a typing system with set theory provides promising results that are manifested in the provision of compositional solutions to the adjective-noun combinations. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .A24. Source: Masters Abstracts International, Volume: 43-01, page: 0229. Adviser: Richard Frost. Thesis (M.Sc.)--University of Windsor (Canada), 2004

    Becoming a young farmer in the digital age— An island perspective

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    This study investigates the career construction paths of young farmers and aims to contribute to the literature on the “young farmer problem.” Of particular relevance is this study’s focus on the potential of islands as a new career landscape in the digital age. Young farmers’ subjective experiences toward careers were analyzed based on narrative interviews, quantitative surveys and expert interviews from two EU islands: Crete and the Azores. Firstly, the study provides insights on the behavioral and cognitive dimensions of the career construction model by identifying followed career paths. Secondly, we turn our focus to the role of digital communications in career construction and, thirdly, the study examines the geographical dimension of the model. We find that involvement with farming entails complex career patterns that evolve into passion. Whether their involvement follows planned or unplanned paths, protean career attitudes, desire to experiment, and a strong sense of career self-concept play significant roles in shaping the career narratives. “Experience” and “management” dimensions of online communication drive the construction of careers as a part of a professional identity mechanism. Our results reveal that the “island effect” (maintaining a part-time farming culture) plays a role in cohesive singular and multiple career self-concepts.info:eu-repo/semantics/publishedVersio

    The Effects of Private Insurance on Measures of Health: Evidence from the Health and Retirement Study

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    In this paper we investigate whether the presence of private insurance leads to improved health status. Using the Health and Retirement study we focus on adults in late middle age who are nearing entry into Medicare. Estimation addresses endogeneity of the insurance participation decision in health outcome regressions. Two models are tested, an instrumental variables models, and a model with endogenous treatment effects due to Heckman (1978). Insurance participation and health behaviors enter with a lag to allow their effects to dissipate over time. Separate regressions were run for groupings of chronic conditions. We find that the overall impact of insurance on health tends to be significantly downwards biased if no adjustment for endogeneity is made. With corrections there is a four-fold increase in the insurance effect; yielding a 7 percent increase in the overall health measure for the uninsured. Results are consistent across IV and treatment effects models, and for all major groupings of medical conditions. Thus, the effect of private insurance on health may be larger than previously estimated. As for policy, expanding coverage to the uninsured should result in substantial health improvement. By conjecture, this is likely to reduce the need for health care when individuals retire and enter Medicare, potentially leading to savings.

    Towards using intelligent techniques to assist software specialists in their tasks

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    L’automatisation et l’intelligence constituent des prĂ©occupations majeures dans le domaine de l’Informatique. Avec l’évolution accrue de l’Intelligence Artificielle, les chercheurs et l’industrie se sont orientĂ©s vers l’utilisation des modĂšles d’apprentissage automatique et d’apprentissage profond pour optimiser les tĂąches, automatiser les pipelines et construire des systĂšmes intelligents. Les grandes capacitĂ©s de l’Intelligence Artificielle ont rendu possible d’imiter et mĂȘme surpasser l’intelligence humaine dans certains cas aussi bien que d’automatiser les tĂąches manuelles tout en augmentant la prĂ©cision, la qualitĂ© et l’efficacitĂ©. En fait, l’accomplissement de tĂąches informatiques nĂ©cessite des connaissances, une expertise et des compĂ©tences bien spĂ©cifiques au domaine. GrĂące aux puissantes capacitĂ©s de l’intelligence artificielle, nous pouvons dĂ©duire ces connaissances en utilisant des techniques d’apprentissage automatique et profond appliquĂ©es Ă  des donnĂ©es historiques reprĂ©sentant des expĂ©riences antĂ©rieures. Ceci permettra, Ă©ventuellement, d’allĂ©ger le fardeau des spĂ©cialistes logiciel et de dĂ©brider toute la puissance de l’intelligence humaine. Par consĂ©quent, libĂ©rer les spĂ©cialistes de la corvĂ©e et des tĂąches ordinaires leurs permettra, certainement, de consacrer plus du temps Ă  des activitĂ©s plus prĂ©cieuses. En particulier, l’IngĂ©nierie dirigĂ©e par les modĂšles est un sous-domaine de l’informatique qui vise Ă  Ă©lever le niveau d’abstraction des langages, d’automatiser la production des applications et de se concentrer davantage sur les spĂ©cificitĂ©s du domaine. Ceci permet de dĂ©placer l’effort mis sur l’implĂ©mentation vers un niveau plus Ă©levĂ© axĂ© sur la conception, la prise de dĂ©cision. Ainsi, ceci permet d’augmenter la qualitĂ©, l’efficacitĂ© et productivitĂ© de la crĂ©ation des applications. La conception des mĂ©tamodĂšles est une tĂąche primordiale dans l’ingĂ©nierie dirigĂ©e par les modĂšles. Par consĂ©quent, il est important de maintenir une bonne qualitĂ© des mĂ©tamodĂšles Ă©tant donnĂ© qu’ils constituent un artĂ©fact primaire et fondamental. Les mauvais choix de conception, ainsi que les changements conceptuels rĂ©pĂ©titifs dus Ă  l’évolution permanente des exigences, pourraient dĂ©grader la qualitĂ© du mĂ©tamodĂšle. En effet, l’accumulation de mauvais choix de conception et la dĂ©gradation de la qualitĂ© pourraient entraĂźner des rĂ©sultats nĂ©gatifs sur le long terme. Ainsi, la restructuration des mĂ©tamodĂšles est une tĂąche importante qui vise Ă  amĂ©liorer et Ă  maintenir une bonne qualitĂ© des mĂ©tamodĂšles en termes de maintenabilitĂ©, rĂ©utilisabilitĂ© et extensibilitĂ©, etc. De plus, la tĂąche de restructuration des mĂ©tamodĂšles est dĂ©licate et compliquĂ©e, notamment, lorsqu’il s’agit de grands modĂšles. De lĂ , automatiser ou encore assister les architectes dans cette tĂąche est trĂšs bĂ©nĂ©fique et avantageux. Par consĂ©quent, les architectes de mĂ©tamodĂšles pourraient se concentrer sur des tĂąches plus prĂ©cieuses qui nĂ©cessitent de la crĂ©ativitĂ©, de l’intuition et de l’intelligence humaine. Dans ce mĂ©moire, nous proposons une cartographie des tĂąches qui pourraient ĂȘtre automatisĂ©es ou bien amĂ©liorĂ©es moyennant des techniques d’intelligence artificielle. Ensuite, nous sĂ©lectionnons la tĂąche de mĂ©tamodĂ©lisation et nous essayons d’automatiser le processus de refactoring des mĂ©tamodĂšles. A cet Ă©gard, nous proposons deux approches diffĂ©rentes: une premiĂšre approche qui consiste Ă  utiliser un algorithme gĂ©nĂ©tique pour optimiser des critĂšres de qualitĂ© et recommander des solutions de refactoring, et une seconde approche qui consiste Ă  dĂ©finir une spĂ©cification d’un mĂ©tamodĂšle en entrĂ©e, encoder les attributs de qualitĂ© et l’absence des design smells comme un ensemble de contraintes et les satisfaire en utilisant Alloy.Automation and intelligence constitute a major preoccupation in the field of software engineering. With the great evolution of Artificial Intelligence, researchers and industry were steered to the use of Machine Learning and Deep Learning models to optimize tasks, automate pipelines, and build intelligent systems. The big capabilities of Artificial Intelligence make it possible to imitate and even outperform human intelligence in some cases as well as to automate manual tasks while rising accuracy, quality, and efficiency. In fact, accomplishing software-related tasks requires specific knowledge and skills. Thanks to the powerful capabilities of Artificial Intelligence, we could infer that expertise from historical experience using machine learning techniques. This would alleviate the burden on software specialists and allow them to focus on valuable tasks. In particular, Model-Driven Engineering is an evolving field that aims to raise the abstraction level of languages and to focus more on domain specificities. This allows shifting the effort put on the implementation and low-level programming to a higher point of view focused on design, architecture, and decision making. Thereby, this will increase the efficiency and productivity of creating applications. For its part, the design of metamodels is a substantial task in Model-Driven Engineering. Accordingly, it is important to maintain a high-level quality of metamodels because they constitute a primary and fundamental artifact. However, the bad design choices as well as the repetitive design modifications, due to the evolution of requirements, could deteriorate the quality of the metamodel. The accumulation of bad design choices and quality degradation could imply negative outcomes in the long term. Thus, refactoring metamodels is a very important task. It aims to improve and maintain good quality characteristics of metamodels such as maintainability, reusability, extendibility, etc. Moreover, the refactoring task of metamodels is complex, especially, when dealing with large designs. Therefore, automating and assisting architects in this task is advantageous since they could focus on more valuable tasks that require human intuition. In this thesis, we propose a cartography of the potential tasks that we could either automate or improve using Artificial Intelligence techniques. Then, we select the metamodeling task and we tackle the problem of metamodel refactoring. We suggest two different approaches: A first approach that consists of using a genetic algorithm to optimize set quality attributes and recommend candidate metamodel refactoring solutions. A second approach based on mathematical logic that consists of defining the specification of an input metamodel, encoding the quality attributes and the absence of smells as a set of constraints and finally satisfying these constraints using Alloy

    Ontology Engineering: a Survey and a Return on Experience

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    Ontology is a new object of IA that recently came to maturity and a powerful conceptual tool of Knowledge Modeling. It provides a coherent base to build on, and a shared reference to align with, in the form of a consensual conceptual vocabulary, on which one can build descriptions and communication acts. This report presents the object that is called "an ontology" and a state of the art of engineering techniques for ontologies. Then it describes a project for which we developed an ontology and used it to improve knowledge management. Finally it describes the design process and discuss the resulting ontology
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