Enhancing the employability of fashion students through the use of 3D CAD

The textile and apparel industry has one of the longest and most intricate supply chains within manufacturing. Advancement in technology has facilitated its globalisation, enabling companies to span geographical borders. This has led to new methods of communication using electronic data formats. Throughout the latter part of the 20th Century, 2D CAD technology established itself as an invaluable tool within design and product development. More recently 3D virtual simulation software has made small but significant steps within this market. The technological revolution has opened significant opportunities for those forward thinking companies that are beginning to utilise 3D software. This advanced technology requires designers with unique skill sets. This paper investigates the skills required by fashion graduates from an industry perspective. To reflect current industrial working practices, it is essential for educational establishments to incorporate technologies that will enhance the employability of graduates. This study developed an adapted action research model based on the work of Kurt Lewin, which reviewed the learning and teaching of 3D CAD within higher education. It encompassed the selection of 3D CAD software development, analysis of industry requirements, and the implementation of 3D CAD into the learning and teaching of a selection of fashion students over a three year period. Six interviews were undertaken with industrial design and product development specialists to determine: current working practices, opinions of virtual 3D software and graduate skill requirements. It was found that the companies had similar working practices independent of the software utilised within their product development process. The companies which employed 3D CAD software considered further developments were required before the technology could be fully integrated. Further to this it was concluded that it was beneficial for graduates to be furnished with knowledge of emerging technologies which reflect industry and enhance their employability skills

Consumer attitudes and preference exploration towards fresh-cut salads using best–worst scaling and latent class analysis

This research explored the preferences and buying habits of a sample of 620 consumers of fresh-cut, ready-to-eat salads. A best–worst scaling approach was used to measure the level of preference stated by individuals regarding 12 attributes for quality (intrinsic, extrinsic and credence) of fresh-cut salads. The experiment was carried out through direct interviews at several large-scale retail outlets in the Turin metropolitan area (north-west of Italy). Out of the total number of questioned consumers, 35% said they did not consume fresh-cut salads. On the contrary, the rest of the involved sample expressed the highest degree of preference towards the freshness/appearance attribute, followed by the expiration date and the brand. On the contrary, attributes such as price, organic certification and food safety did not emerge as discriminating factors in consumer choices. Additionally, five clusters of consumers were identified, whose preferences are related both to purchasing styles and socio-demographic variables. In conclusion, this research has highlighted the positive attitude of consumers towards quality products backed by a brand, providing ideas for companies to improve within this sector and implement strategies to answer the needs of a new segment of consumers, by determining market opportunities that aim to strengthen local brands

Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

[EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations

The Role of Management Practices in Closing the Productivity Gap

There is no doubt that management practices are linked to the productivity and performance of a company. However, research findings are mixed. This paper provides a multi-disciplinary review of the current evidence of such a relationship and offers suggestions for further exploration. We provide an extensive review of the literature in terms of research findings from studies that have been trying to measure and understand the impact that individual management practices and clusters of management practices have on productivity at different levels of analysis. We focus our review on Operations Management (om) and Human Resource Management (hrm) practices as well as joint applications of these practices. In conclusion, we can say that taken as a whole, the research findings are equivocal. Some studies have found a positive relationship between the adoption of management practices and productivity, some negative and some no association whatsoever. We believe that the lack of universal consensus on the effect of the adoption of complementary management practices might be driven either by measurement issues or by the level of analysis. Consequently, there is a need for further research. In particular, for a multi-level approach from the lowest possible level of aggregation up to the firm-level of analysis in order to assess the impact of management practices upon the productivity of firms

Leachate treatment by conventional coagulation, electrocoagulation and two-stage coagulation (conventional coagulation and electrocoagulation)

Leachate is widely explored and investigated due to highly polluted and difficult to treat. Leachate treatment commonly involves advanced, complicated and high cost activities. Conventional coagulation is widely used in the treatment of wastewater but the sludge production becomes the biggest constraint in this treatment. Electrocoagulation is an alternative to conventional method because it has the same application but produce less sludge and requires simple equipment. Thus, combination of conventional coagulation and electrocoagulation can improve the efficiency of coagulation process in leachate treatment. This article is focusing on the efficiency of single and combined treatment as well as the improvement made by combined treatment. Based on review, the percentage reduction of current density and dose of coagulant was perceptible. As much 50% reduction of current density, duration of treatment, and dose of coagulant able to be obtained by using combined treatment. This combined treatment is able to reduce the cost and at the same time reduce the duration of treatment. Hence, the combined treatment offers an alternative technique for landfill leachate treatment on the removal of pollutants

CSR marketing outcomes and branch managers' perceptions of CSR

Purpose The purpose of this paper is to analyze the role of bank branch managers’ perceptions of corporate social responsibility (CSR) in CSR marketing outcomes. Design/methodology/approach The paper proposes a causal model establishing that managers’ perceptions of CSR influence the perception of CSR held by the branch’s customers, which in turn directly affects customer satisfaction, customer trust, customer engagement and customer loyalty. The unit of analysis in this quantitative study is the bank branch. Two questionnaires were administered: one to branch managers and another to five customers in each branch. Findings Branch managers’ perceptions of CSR have a marked influence on customers’ perceptions of CSR, which again have a notable impact on the relationship variables studied: customer satisfaction, customer trust, customer engagement and customer loyalty. Research limitations/implications The sample was taken from two banks in the same country (Spain) and only five customers were interviewed in each branch. The type of customers analyzed should be taken into account since a growing number of customers now carry out all of their banking online and are less likely to visit their branch. Practical implications The results highlight the importance of adopting socially responsible actions not only in the bank as a whole, but also in individual branches. It would, therefore, seem crucial for high level bank executives not only to involve branch managers in the bank’s CSR strategy, but also to empower them to undertake CSR actions that involve the customers and local community with which they interact. Originality/value First, the paper reveals the differences within the same organization in the way its CSR strategy is implemented. Second, intermediary figures or supervisors are shown to have a key role in ensuring the organization’s CSR strategy is effective. Third, the study emphasizes the importance of customers’ perception of CSR in achieving the main outcomes of relationship marketing (satisfaction, trust, engagement and loyalty). Fourth, the methodology applied in the study is innovative in its construction of dyads in which the branch is the unit of analysis, enabling a comparison between the manager’s perceptions of CSR with that of five customers from the same branch. Fifth, the findings add to the knowledge of a particularly relevant sector in the recent economic crisis, namely, the retail banking industry

Development and evaluation of Formula Editor (a tool-based approach to enhance reusability in software product line model checking) on SAFER case study

Although model checking is extensively used for verification of single software systems, currently there is insufficient support for model checking in product lines. The presence of commonalities within the different products in the product line requires that the properties and the corresponding specifications for these properties be verified for every product in the product line. Specification and management of properties for every product in a product line can incur high overhead and make the task of model checking very difficult. It is hence essential to exploit the presence of commonalities to our advantage by providing reusability in model checking of product lines. Since different products in the product line need to be checked for same or similar properties, reuse of properties specified for one product for other products within a product line will significantly reduce the overall property specification and verification time. FormulaEditor is a property specification and management tool for enhancing the reusability of model checking of software product lines. The core of the technique is a product line-oriented user interface to guide users in generating, selecting, managing, and reusing useful product line properties, and patterns of properties for model checking. The previous version of the FormulaEditor tool supports Cadence SMV models, but not the typical CMU-SMV models. This work extends the FormulaEditor tool to allow verification of models written in CMU-SMV. The advantage of providing support to another model checker is twofold: first, it enhances the tool\u27s capability to check design specifications written in different models; and second, it allows users to specify the same design in different modeling languages to detect problems