Littérature scientifique sur le sujet « SECS-P/13 SCIENZE MERCEOLOGICHE »

2015 - 2016
The theme of competences is characterized by the complex nature, as the possible definitions can be traced back to various fields that belong to the psychology, the world of work and the quality of the reference society. The concept of competence, depending on the perspective of analysis, has assumed different meanings over time, pointing to conceptual uncertainties that inevitably reflect on the procedures to define its measurability and transferability. The polysemy of the term competence is probably not due to terminological fragility but is due to a not yet completely consolidated concept. Thus, this ambiguity is perceptible both in the theoretical matrices but more so in its modes of use so it seems interesting to note that competence assumes value and centrality precisely in function of the vision of the reality that it generates. Although the concept of competence derives from uncertain perimeters, it represents a significant "attraction" as: in knowledge economy, competence is a source of added value and competitive advantage in the light of the dynamic needs of the customer and the uncertainties of the market. whose development of employee skills is an important component of personal development and individual self-management. To simplify the discourse on skills, a multidimensional lens can be useful, capable of highlighting the different approaches to the theme and illustrating the backgrounds to which they refer. Therefore, in this paper some of the most important contributions and models that have fueled the debate on skills have been analyzed. The purpose is not to propose a systematic literature review, but to present the main points of view of the scholars of the industry and some of the different meanings that this notion can assume. These are the theoretical basics from which to start with the theme of recognition, validation and certification of skills that have been debated over many years and in the main segments of labortraining policies. Such attention is probably due to the "unifying function" of skills certification in the labor market, as a process capable of ensuring fluidity and support for the employment transitions of individuals. In fact, aspects such as mobility, interdisciplinarity and the internationalization of workers increasingly require the construction of training and professional paths rich in diverse experiences and competences, able to adapt to changing demands and conditions, but also recognizable by the organizations and professional communities. Expanding the needs of skills and training opportunities corresponds to the extension of what is defined as the learning environment through the rediscovery of non-formal and informal learning. Therefore, the identification, validation and certification of competences can be considered as fundamental processes for the purpose of enhancing human capital as, in the transition from the training chain to the employment market, allow a rethinking of learning outcomes, more recognizable and informative. In transitions in the labor market, these processes embody impetus on worker mobility by favoring reintegration through the emergence of tacit skills and those accrued in nonformal and informal areas, considered subsidiary and functional to access to job opportunities. Therefore, skills are considered the "common metric", the "interoperable" language that allows different systems (school, training, universities, businesses, public institutions) to refer to the same "competence standards". For these reasons, for decades, these issues have played an important role in the labor, education and training policies of the European Union and Italy. In this regard, a further aim of the dissertation work was to analyze the theoretical framework of validation and competence certification processes as well as the relevance of the concept of lifelong learning, which is also a shared reference framework for the concrete exercise of rights of European citizens to recognize their training pathways and experiences of life and work throughout the community. The examination of the "certification" pathway continued with the analysis of the main approaches, policies and tools adopted by the European Union and Italy for its implementation. Finally, the results of a preliminary investigation into the usefulness of the Europass Portfolio and the Diploma Supplement, presented by the graduates of the University of Salerno, were presented. These premises are fundamental to better understand the context of the proposed approach in this dissertation, which aims to achieve cross-competence certification. The context developed refers to Corporate Social Responsibility and Competence Model. The progressive and rapid evolution of the concept of Corporate Social Responsibility (CSR) over the last few years has prompted a rethink of the same goals that companies are called upon to pursue, alongside the traditional production function, which constitutes the constituent element of their being and work, the principles of sustainability, in a way that is capable of enhancing not only economic capital, but also natural and human capital. This represents the response of organizations to continual changes in the outside world, so better services or goods not only affect the corporate image but also in terms of energy saving orientation, reduced distribution costs, environment and greater protection of workers. Therefore, there is a need to go beyond the generic concept of Corporate Social Responsibility, taking into account rather the concept of corporate sustainability, whereby the satisfaction of the needs and expectations of the parties involved must be supported by means of 'triple bottom line approach. In the light of this, human capital formation exerts a significant impetus on the economic and social growth path of a community, as defined by economist Gary S. Becker in 1964, according to which human capital represents the whole of the productive capacity that an individual acquires through the accumulation of general or specific knowledge, of savoir-faire. It is an intangible resource that, like any other capital, has the capacity to reproduce, throughout the life of the individual, through different types of learning: formal, non-formal and informal. In particular, modern technologies, greater market demands and the search for a combination of efficiency and quality assurance, which have led to the emergence of new forms of production organization, will also have considerable repercussions on the level of qualifications and skills required to workers. In addition to a greater need for more declarative and procedural specific knowledge, key qualifications, system understanding and professional skills are also important. Therefore, job-based learning becomes more and more important to qualify workers inside and to benefit from new organizational forms. Learning potential involves the possibility that learning processes take place in a particular workplace. This is the result of the interaction between the characteristics of workers (qualifications already possessed, learning abilities and willingness to learn) and learning opportunities offered by the job. While the other model considered as the context of the proposed approach in this study is the model based on the ontologies proposed by Miranda et al. (2017) that enables you to represent your skills through the Semantic Web's own languages and tools. This model represents the tool that, within CSR, and thus the enhancement of human capital, enables you to organize, represent and "standardize" skills in order to govern the various factors that affect the CSR Management path. In addition, it is based on the idea that it is possible to implement an approach that identifies, evaluates and certifies skills in organizations by exploiting ontologies or through the ability to describe knowledge within a specific domain, while also enabling the automatic processing by the computers of the knowledge thus represented. Therefore, in the light of this theoretical framework and theoretical context, the main aim of this paper lies in the possibility of implementing a model based on competence-oriented ontologies in CSR organizations, in order to increase the competitive advantage precisely through the management of human resources, or through the management of their intangible skills. The experimentation of this implementation took place at the company Sada Spa. [edited by author]
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Today cruise tourism represents an important share of tourism market. During 2018 this sector has handled 28.5 millions of passengers at the global level, whit an increasing higher than 600% from 1990 to today. At the same time, cruise sector is responsible of a large amount of impacts for the local communities, host territories, atmosphere and waterways. This sector is a touristic product multi-destination by sea because includes a large number of intermediate ports, selected for touristic attractions in order to satisfying a more detailed demand (e.g. by a medium level target of consumer-users with a fair awareness of environmental implications). This thesis, as a part of for the scientific disciplinary sector SECS-P/13 (Commodities Sciences), offers an opportunity to analyze the relationship between the growth of the cruise market and the management of environmental sustainability. We have tried to understand how sustainability approach it is implemented, both on the product supply’s side (cruise companies) and consumer's product side (cruise passengers). Then, this analysis allowed us to know weaknesses and strengths of this tourism sector. This thesis consists of three parts: a part is a review thesis (First Part - Review), a part is a descriptive and comparative research thesis (First Part - Regulations, Second Part - Impacts and Sustainability Report) and the last part is an experimental thesis (Third part - Applications). With the thesis "Environmental sustainability in cruise tourism. Some applications" we have offered some points of analysis for scientific research, in particular in the field of environmental impacts.

The environment, understood as the biophysical support to human society and economic systems, is a relevant variable to firm management. The way the environment is managed can affect not only firm competitiveness but also firm environmental performance both in the short and long-term. The environment generates the inputs (in terms of stocks of natural capital and flows of ecosystem services) supporting human economy and receives back outputs and by-products (waste and emissions) generated by human activities. Therefore the environment does a constant work providing inputs and receiving outputs throughout each function and businesses phase of firms, playing a key role for their development and sustainability. This thesis examines the following two main issues: 1) how to apply environmental management theory in the context of tourism industry, and 2) how to assess the environmental performance and sustainability of Small and Medium-sized Hotel Enterprises (SMHEs) by using a multicriteria assessment framework. Both a specific economic sector and different type of firms are investigated: the tourism industry and selected SMHEs in the Province of Trento. The environmental management theory, through an online survey of SMHEs in the Province of Trento, explores the implementation of environmental practices, the characteristics of enterprises as environmental determinants and the motivations and perceptions to environmental commitment. Environmental accounting is instead employed to assess environmental costs and impacts associated to selected hotels in the Province of Trento.

Background: Ethiopia is a country with 9 ethnically-based administrative regions and 2 city administrations, often cited, among other things, with high fertility rates and rapid population growth rate. Despite the country’s effort in their reduction, they still remain high, especially at regional-level. To this end, the study of fertility in Ethiopia, particularly on its regions, where fertility variation and its repercussion are at boiling point, is paramount important. An easy way of finding different characteristics of a fertility distribution is to build a suitable model of fertility pattern through different mathematical curves. ASFR is worthwhile in this regard. In general, the age-specific fertility pattern is said to have a typical shape common to all human populations through years though many countries some from Africa has already started showing a deviation from this classical bell shaped curve. Some of existing models are therefore inadequate to describe patterns of many of the African countries including Ethiopia. In order to describe this shape (ASF curve), a number of parametric and non-parametric functions have been exploited in the developed world though fitting these models to curves of Africa in general and that of Ethiopian in particular data has not been undertaken yet. To accurately model fertility patterns in Ethiopia, a new mathematical model that is both easily used, and provides good fit for the data is required. Objective: The principal goals of this thesis are therefore fourfold: (1). to examine the pattern of ASFRs at country and regional level,in Ethiopia; (2). to propose a model that best captures various shapes of ASFRs at both country and regional level, and then compare the performance of the model with some existing ones; (3). to fit the proposed model using Hierarchical Bayesian techniques and show that this method is flexible enough for local estimates vis-´a-vis traditional formula, where the estimates might be very imprecise, due to low sample size; and (4). to compare the resulting estimates obtained with the non-hierarchical procedures, such as Bayesian and Maximum likelihood counterparts. Methodology: In this study, we proposed a four parametric parametric model, Skew Normal model, to fit the fertility schedules, and showed that it is flexible enough in capturing fertility patterns shown at country level and most regions of Ethiopia. In order to determine the performance of this proposed model, we conducted a preliminary analysis along with ten other commonly used parametric and non-parametric models in demographic literature, namely: Quadratic Spline function, Cubic Splines, Coale-Trussell function, Beta, Gamma, Hadwiger distribution, Polynomial models, the Adjusted Error Model, Gompertz curve, Skew Normal, and Peristera & Kostaki Model. The criterion followed in fitting these models was Nonlinear Regression with nonlinear least squares (nls) estimation. We used Akaike Information Criterion (AIC) as model selecction criterion. For many demographers, however, estimating regional-specific ASFR model and the associated uncertainty introduced due those factors can be difficult, especially in a situation where we have extremely varying sample size among different regions. Recently, it has been proposed that Hierarchical procedures might provide more reliable parameter estimates than Non-Hierarchical procedures, such as complete pooling and independence to make local/regional-level analyses. In this study, a Hierarchical Bayesian procedure was, therefore, formulated to explore the posterior distribution of model parameters (for generation of region-specific ASFR point estimates and uncertainty bound). Besides, other non-hierarchical approaches, namely Bayesian and the maximum likelihood methods, were also instrumented to estimate parameters and compare the result obtained using these approaches with Hierarchical Bayesian counterparts. Gibbs sampling along with MetropolisHastings argorithm in R (Development Core Team, 2005) was applied to draw the posterior samples for each parameter. Data augmentation method was also implemented to ease the sampling process. Sensitivity analysis, convergence diagnosis and model checking were also thoroughly conducted to ensure how robust our results are. In all cases, non-informative prior distributions for all regional vectors (parameters) were used in order to real the lack of knowledge about these random variables. Result: The results obtained from this preliminary analysis testified that the values of the Akaike Information criterion(AIC) for the proposed model, Skew Normal (SN), is lowest: in the capital, Addis Ababa, Dire Dawa, Harari, Affar, Gambela, Benshangul-Gumuz, and country level data as well. On the contrary, its value was also higher some of the models and lower the rest on the remain regions, namely: Tigray, Oromiya, Amhara, Somali and SNNP. This tells us that the proposed model was able to capturing the pattern of fertility at the empirical fertility data of Ethiopia and its regions better than the other existing models considered in 6 of the 11 regions. The result from the HBA indicates that most of the posterior means were much closer to the true fixed fertility values. They were also more precise and have lower uncertainty with narrower credible interval vis-´a-vis the other approaches, ML and Bayesian estimate analogues. Conclusion: From the preliminary analysis, it can be concluded that the proposed model was better to capture ASFR pattern at national level and its regions than the other existing common models considered. Following this result, we conducted inference and prediction on the model parameters using these three approaches: HBA, BA and ML methods. The overall result suggested several points. One such is that HBA was the best approach to implement for such a data as it gave more consistent, precise (the low uncertainty) than the other approaches. Generally, both ML method and Bayesian method can be used to analyze our model, but they can be applicable to different conditions. ML method can be applied when precise values of model parameters have been known, large sample size can be obtained in the test; and similarly, Bayesian method can be applied when uncertainties on the model parameters exist, prior knowledge on the model parameters are available, and few data is available in the study.
Background: L’Etiopia è una nazione divisa in 9 regioni amministrative (definite su base etnica) e due città. Si tratta di una nazione citata spesso come esempio di alta fecondità e rapida crescita demografica. Nonostante gli sforzi del governo, fecondità e cresita della popolazione rimangono elevati, specialmente a livello regionale. Pertanto, lo studio della fecondità in Etiopia e nelle sue regioni – caraterizzate da un’alta variabilità – è di vitale importanza. Un modo semplice di rilevare le diverse caratteristiche della distribuzione della feconditàè quello di costruire in modello adatto, specificando diverse funzioni matematiche. In questo senso, vale la pena concentrarsi sui tassi specifici di fecondità, i quali mostrano una precisa forma comune a tutte le popolazioni. Tuttavia, molti paesi mostrano una “simmetrizzazione” che molti modelli non riescono a cogliere adeguatamente. Pertanto, per cogliere questa la forma dei tassi specifici, sono stati utilizzati alcuni modelli parametrici ma l’uso di tali modelliè ancora molto limitato in Africa ed in Etiopia in particolare. Obiettivo: In questo lavoro si utilizza un nuovo modello per modellare la fecondità in Etiopia con quattro obiettivi specifici: (1). esaminare la forma dei tassi specifici per età dell’Etiopia a livello nazionale e regionale; (2). proporre un modello che colga al meglio le varie forme dei tassi specifici sia a livello nazionale che regionale. La performance del modello proposto verrà confrontata con quella di altri modelli esistenti; (3). adattare la funzione di fecondità proposta attraverso un modello gerarchico Bayesiano e mostrare che tale modelloè sufficientemente flessibile per stimare la fecondità delle singole regioni – dove le stime possono essere imprecise a causa di una bassa numerosità campionaria; (4). confrontare le stime ottenute con quelle fornite da metodi non gerarchici (massima verosimiglianza o Bayesiana semplice) Metodologia: In questo studio, proponiamo un modello a 4 parametri, la Normale Asimmetrica, per modellare i tassi specifici di fecondità. Si mostra che questo modello è sufficientemente flessibile per cogliere adeguatamente le forme dei tassi specifici a livello sia nazionale che regionale. Per valutare la performance del modello, si è condotta un’analisi preliminare confrontandolo con altri dieci modelli parametrici e non parametrici usati nella letteratura demografica: la funzione splie quadratica, la Cubic-Spline, i modelli di Coale e Trussel, Beta, Gamma, Hadwiger, polinomiale, Gompertz, Peristera-Kostaki e l’Adjustment Error Model. I modelli sono stati stimati usando i minimi quadrati non lineari (nls) e il Criterio d’Informazione di Akaike viene usato per determinarne la performance. Tuttavia, la stima per le singole regioni pu‘o risultare difficile in situazioni dove abbiamo un’alta variabilità della numerosità campionaria. Si propone, quindi di usare procedure gerarchiche che permettono di ottenere stime più affidabili rispetto ai modelli non gerarchici (“pooling” completo o “unpooling”) per l’analisi a livello regionale. In questo studia si formula un modello Bayesiano gerarchico ottenendo la distribuzione a posteriori dei parametri per i tassi di fecnodità specifici a livello regionale e relativa stima dell’incertezza. Altri metodi non gerarchici (Bayesiano semplice e massima verosimiglianza) vengono anch’essi usati per confronto. Gli algoritmi Gibbs Sampling e Metropolis-Hastings vengono usati per campionare dalla distribuzione a posteriori di ogni parametro. Anche il metodo del “Data Augmentation” viene utilizzato per ottenere le stime. La robustezza dei risultati viene controllata attraverso un’analisi di sensibilità e l’opportuna diagnostica della convergenza degli algoritmi viene riportata nel testo. In tutti i casi, si sono usate distribuzioni a priori non-informative. Risultati: I risutlati ottenuti dall’analisi preliminare mostrano che il modello Skew Normal ha il pi`u basso AIC nelle regioni Addis Ababa, Dire Dawa, Harari, Affar, Gambela, Benshangul-Gumuz e anche per le stime nazionali. Nelle altre regioni (Tigray, Oromiya, Amhara, Somali e SNNP) il modello Skew Normal non risulta il milgiore, ma comunque mostra un buon adattamento ai dati. Dunque, il modello Skew Normal risulta il migliore in 6 regioni su 11 e sui tassi specifici di tutto il paese. Conclusioni: Dunque, il modello Skew Normal risulta globalmente il migliore. Da questo risultato iniziale, siè partiti per costruire i modelli Gerachico Bayesiano, Bayesiano semplice e di massima verosimiglianza. Il risultato del confronto tra questi tre approcci è che il modello gerarchico fornisce stime più preciso rispetto agli altri.

Companies are more and more interested in the sustainability character of products, services and processes and, for this reason, appropriate and suitable assessment tools supporting the transition to a green economy are highly necessary. Currently, there are a number of methods and approaches for assessing products’ economic, environmental and social impact and for improving their sustainability performances; among these, the Life Cycle Thinking (LCT) approach emerged as the most useful and effective to reach sustainability goals. Indeed, LCT aims to reduce a product’s resource use and emissions to the environment as well as to improve its socio-economic performance through its whole life cycle. LCT is made operational through Life Cycle Management (LCM) that is a management approach that puts the tools and methods of the LCT basket into practice. Many different tools are basic elements of LCM, but Life Cycle Assessment (LCA), Life Cycle Costing (LCC) and Social Life Cycle Assessment (S-LCA) are undoubtedly the most appreciated to assist product-related decision-making activities, from the extraction and processing of raw materials, manufacturing, distribution, use, reuse, maintenance, recycling and final disposal. LCA is already an internationally standardized tool (ISO 14040:2006 and ISO 14044:2006), on the contrary LCC and S-LCA still lack of international standardization (even if guidelines and general frameworks are available) and, especially S-LCA is still in the experimental stages for many aspects of its methodological structure. Considering that the S-LCA is still in its infancy, an analysis of this assessment tool is a useful starting point for a detailed description of the current situation and of the degree of advancement of the general theory on the subject and, in particular, on the various approaches and tools applied. Indeed, in recent years several different methods towards S-LCA have been developed. In this thesis a literature overview of S-LCA is presented. The overview has been carried out using two level of analysis: a bibliometric analysis in order to highlight the role and impact of S-LCA studies within the scholarly communities and, a critical analysis in order to show methodological differences and needs for future development of S-LCA. Finally, the findings of the literature review will be the key elements from which starting an applicative analysis. In particular, considering that S-LCA makes use of generic and site-specific quantitative, semi-quantitative and qualitative data, and that it complements the environmental LCA and LCC, the S-LCA method (extended with LCA analysis) will be applied to selected a product of a textile factory, “San Lorenzo Group”, located in San Marco D’Alunzio (Messina), in order to point verify its applicability and the potentiality to integrate its results into the company decision-making process.

According to the UN report 2014, more and more people are migrating from rural area to urban area which is expected to increase with the passage of time. But this unmanageable expansion causes negative environmental, economic and social impactsoncities which arethe biggest challenge to sustainability. There are different aspects that influence city metabolism and its sustainability like infrastructures, transportation, aging of building, energy consumption, etc. Employing effective management of urban infrastructure is one of the main ways to ensure sustainability and provide good living condition to the citizens. The central goal of this thesis is to propose a life cycle thinking based sustainability assessment framework for the evaluation of urban infrastructures which will guide the policy and decision makers in their decisions for the evaluation of sustainable development through a set of sustainability criteria and indicators. In order to identify the main requirements of the proposed sustainability assessment framework for urban infrastructure, first, a qualitative literature review of current sustainability approaches developed or applied in the built infrastructure context has been carried out. Then the main findings of the literature review have been used as inputs to design the proposed integrated framework. The framework is composed of three sections: (i) project structuring (ii) project analysis (iii) resolution/implementation. Finally, the most critical part of the proposed framework (Identification of key criteria and indicators) has been implemented in the context of Middle East countries, specifically UAE and Saudi Arabia, infrastructure projects, in order to test the applicability of the proposed sustainability assessment framework.

This thesis investigates company-level assessment of circular economy (CE) and sustainability, addressing three key research gaps: (1) the lack of consensus on the methodological approach to CE assessment, (2) unclarity on how companies are currently assessing their CE strategies, and (3) the lack of considering company needs in designing assessment approaches. The paper-based thesis used a mix of qualitative and quantitative methods to establish answers to these questions; methods include a systematic literature review, a comparative analysis, a survey approach, interviews, and the design and validation of a CE assessment framework called SCEIA. Key conclusions are that CE assessment is a dynamic process; that Life Cycle Assessment (LCA) can be considered a valuable method for assessing the environmental impacts of CE strategies; and that companies currently make use most often of (1) tailormade assessment approaches and (2) LCA.