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Although general courses related to humanities, social sciences, education and pure sciences are popularly taught through distance mode, through the institutions involved in teaching distance mode techniques for some time, more practical application courses such as engineering technology and applied sciences are less popular as distance mode teaching till recent. The current technical advancement is making it possible for more practical application courses to be offered through distance education techniques. The Faculty of Engineering Technology of the Open University of Sri Lanka is one of the few faculties involved in teaching of engineering technology through distance mode in the region. Faculty offers courses leading to diploma in technology, bachelor in engineering technology, postgraduate diplomas and postgraduate degrees in engineering through distance mode. The diplomats and graduates passing out from the faculty have to compete with the diplomats and graduates passing out from the conventional universities in the common job markets. Hence to maintain a high quality of the diploma/degree is important. Attempt is made to develop a quality assurance system that will help to maintain a high standard of the faculty diploma/graduate output. This study investigates the strengths, and in particular the weaknesses of quality assessment practices used in conducting subject reviews in Sri Lankan universities, especially when it comes to subject reviews in relation to more practical application courses such as engineering technology and applied sciences. This paper describes the aspects that were looked into: adopted current practices & the weaknesses, areas identified to check on quality maintenance, and measures to be taken to improve in developing a quality assurance mechanism based on the Faculty of Engineering Technology at Open University of Sri Lanka.

The aim of the study reported in this article was to establish whether the quality of clothes of a given brand is perceived and assessed by consumers at the same level. An additional purpose was to identify the features that characterize the quality of popular, among Polish young female consumers, clothing brands and to classify them according to their quality level (perceived and assessed).

The article presents two approaches to consumer assessment of the quality of clothes: the survey method, in which the product quality was determined by 320 Polish female young respondents (19–25) based on their own previous experiences and impressions related to a particular clothing brand, and a direct assessment of shirts of selected brands using a sensory quality assessment method, a five-point hedonic scale with the verbal anchor (115 evaluators).

The research has revealed a significant difference between the perception of selected quality features of brands and the consumer assessment of the products. The perception maps developed based on the PROFIT analysis (PROperty FITting) as well as on cluster analysis provided interesting information about the situation of selected brands and their features in comparison with others and allowed to identify strong and weak features characterizing a given category.

This study has several limitations. First and foremost, the research results cannot be generalized to all consumers because they encompass the results from one national context and one population of respondents (young females). It should also be noted that the conducted research comprises only the most popular clothing brands available on the Polish market, in particular, the fast fashion segment brands. Furthermore, it would be advisable to carry out a sensory assessment of the quality of other clothing items offered under the brand names investigated.

This research could be a valuable source of information for clothing company managers, thanks to which they could better manage their brand and its position on the market. When undertaking marketing activities consisting of building positive perceptions about the product, it is important to make sure that the product offers an attractive sensory experience. When real quality deviates from consumer perceptions about the quality, managers should take corrective actions to restore and even improve the brand image in the eyes of the consumer, as well as to ensure the brand and the products offered under it a stable position on the market.

By comparing two approaches to consumer quality assessment, discrepancies between declared and real (sensory) quality of clothes have been identified and the distinctive features that differentiate selected brands regarding their quality level have been indicated.

This paper aimed to assess the service quality of the main seaports in Oman, which were Sohar, Ad Duqm and Salalah. The aim was to come up with ways to enhance the port service quality (PSQ) in Oman so that it could align with the Sultanate of Oman Logistics Strategy (SOLS) 2040 goals and achieve excellent and efficient operations.

To evaluate the service quality level of the port operators, this paper used a descriptive research design with Resources, Outcome, Process, Management, Image/reputation and Social (ROPMIS) modelling.

The findings indicated that the overall PSQ rating was currently between “satisfactory” and “very satisfactory” levels. However, the study also found that by empowering resources, outcomes, processes, management, image and social responsibility aspects, the port operators could provide a “high” quality of service, making their seaport operations more effective and efficient.

The study offers recommendations for improving port services in Oman, including investment in modern seaports, upgrading infrastructure and facilities, ensuring safety and efficiency of cargo operations, meeting and exceeding customer expectations, adopting new technology and automation, hiring policies that attract diverse talents, implementing environmentally friendly practices and improving governance. Overall, this study contributes to the literature and managerial practices in PSQ aspects and its contribution to the SOLS 2040 in Oman.

The originality and novelty of this study lie in its comprehensive assessment of the service quality of Oman's ports and the identification of areas for improvement to achieve outstanding service levels.

Several healthcare quality assessment tools measure the processes and outcomes of the care system. The actual physical infrastructure (buildings and organizational) aspects are, however, rarely considered. The purpose of this paper is to describe the process of validation and weighting of an evidence-informed framework for the quality assessment of hospital facilities from social, environmental and organizational perspectives to complement other assessments.

Sustainable High-quality Healthcare version 2 (SustHealth v2) is the updated version of an existing framework composed of three domains (social, environmental and organizational quality). To validate and establish a relevant weighting, interviews were conducted with 15 professionals within the field of healthcare planning, design, research and management. The study has been conducted through semi-structured interviews and the application of the Simon Roy Figueras (SRF) procedure for the elicitation of weights criteria. The data collected have been processed through the DecSpace web platform.

Among the three domains, the organizational qualities appear to be the most important (W = 49%), followed by the environmental (W = 29%) and social aspects (W = 22%). Relevant indicators such as future-proofing, wayfinding and users’ space control emerged as the most important within each macro-area. Those results are confirmed by the outcome of the interviews that highlight user/patient-centeredness, wayfinding strategies and space functionality as the most important concepts to foster in existing healthcare facilities improvement.

The study highlights important structural and organizational aspects that hospital managers and planners can consider when dealing with healthcare facilities’ quality improvement.

The use of the SRF multicriteria method is novel in this context when used to weight an assessment tool with a focus on hospital built environment.

Ensuring quality is one of the most significant challenges in microtask crowdsourcing tasks. Aggregation of the collected data from the crowd is one of the important steps to infer the correct answer, but the existing study seems to be limited to the single-step task. This study aims to look at multiple-step classification tasks and understand aggregation in such cases; hence, it is useful for assessing the classification quality.

The authors present a model to capture the information of the workflow, questions and answers for both single- and multiple-question classification tasks. They propose an adapted approach on top of the classic approach so that the model can handle tasks with several multiple-choice questions in general instead of a specific domain or any specific hierarchical classifications. They evaluate their approach with three representative tasks from existing citizen science projects in which they have the gold standard created by experts.

The results show that the approach can provide significant improvements to the overall classification accuracy. The authors’ analysis also demonstrates that all algorithms can achieve higher accuracy for the volunteer- versus paid-generated data sets for the same task. Furthermore, the authors observed interesting patterns in the relationship between the performance of different algorithms and workflow-specific factors including the number of steps and the number of available options in each step.

Due to the nature of crowdsourcing, aggregating the collected data is an important process to understand the quality of crowdsourcing results. Different inference algorithms have been studied for simple microtasks consisting of single questions with two or more answers. However, as classification tasks typically contain many questions, the proposed method can be applied to a wide range of tasks including both single- and multiple-question classification tasks.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.

Quality assurance (QA) in open and distance learning (ODL) has always become universal concerns of stakeholders. The quality of ODL has been confronted with challenges in terms of the diversity of inputs, processes, the complex supply chain management of ODL and recent paradigm shift into online learning. Assuring the quality of ODL are daunting tasks at individual, institution and system levels. Completed before the beginning of the COVID-19 outbreak, this study aims to better understand the implementation of QA system in three Asian open universities (OUs), namely University of the Philippines Open University (UPOU), Universitas Terbuka (UT), Indonesia and Allama Iqbal Open University (AIOU), Pakistan.

A qualitative method was employed involving analysis of documents of the three Asian OUs and focus group discussions and interviews with management and staff. Data collected were then analyzed to draw conclusions and possible recommendations.

Findings of this study presented good practices, challenges and rooms for improvement of the QA system in the three Asian OUs. Focusing on students and stakeholders in their QA effort, this study has revealed that quality begins with inner self and is multidimensional. QA is principally viewed as continuous improvement, as mechanism and assessment and as effort at exceeding expectations of students and stakeholders. The recent challenge for QA is to embrace a delicate process of ODL transformation into online digital system. The recent COVID-19 outbreak has further implications and challenged QA implementation in ODL in higher education into the next level of complexity.

This study revealed the diversities in how OUs met the societal needs of their respective stakeholders and addressed the challenges ahead for QA in ODL.

These findings were expected to enhance the understanding of the theory and practice of QA in ODL and to contribute to quality improvement of ODL programs.

The purpose of this study is to empirically develop and validate a practical, consistent and specific scale to assess perceived service quality at the service encounter at quick-service restaurants (QSRs).

Development and validation of the scale involved a five-stage process. Data were collected from 430 customers of a QSR belonging to an international brand located in Barcelona. Surveys were applied immediately after the service encounter, using the face-to-face method. The scale development procedure involved exploratory and confirmatory factor analyses.

The results suggest a specific and parsimonious measurement scale, whose structure comprises 14 items in four dimensions. In contrast to previous studies, this study identified the appropriateness of splitting the interaction quality dimension into two single dimensions, one focusing on the interaction time and other on staff–customer interaction. Furthermore, these indicate that a speedy service, pleasant treatment and food quality are the most valued attributes in QSR.

This scale is a useful instrument to administer and assure service quality standards within QSR management systems. Its practical approach and short survey length ease data collection, considering that customers spend short amounts of time in this type of restaurant. Furthermore, it could also be used by franchisors and restaurant operators as a tool to monitor continuing compliance with service quality standards.

The resulting scale introduces a novel four-factor structure with high goodness of fit to effectively measure customers' perceived service quality in QSRs, where the ease of use and speed of gathering client responses are a key factor for successful implementation.