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The number of candidates applying to public contests (PC) is increasing compared to the number of human resources employees required for selecting them for the Police Force (PF). This work intends to perceive how those public institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process. To achieve this purpose, artificial intelligence (AI) was studied. This paper aims to focus on analysing the AI technologies most used and appropriate to the PF as a complementary recruitment strategy of the National Criminal Investigation police agency of Portugal – Polícia Judiciária.

Using design science research as a methodological approach, the authors suggest a theoretical framework in pair with the segmentation of the candidates and comprehend the most important facts facing public institutions regarding the usage of AI technologies to make decisions about evaluating and selecting candidates. Following the preferred reporting items for systematic reviews and meta-analyses methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how the usage and exploitation of transparent AI positively impact the recruitment process of a public institution, resulting in an analysis of 34 papers between 2017 and 2021.

Results suggest that the conceptual pairing of evaluation and selection problems of candidates who apply to PC with applicable AI technology such as K-means, hierarchical clustering, artificial neural network and convolutional neural network algorithms can support the recruitment process and could help reduce the workload in the entire process while maintaining the standard of responsibility. The combination of AI and human decision-making is a fair, objective and unbiased process emphasising a decision-making process free of nepotism and favouritism when carefully developed. Innovative and modern as a category, group the statements that emphasise the innovative and contemporary nature of the process.

There are two main limitations in this study that should be considered. Firstly, the difficulty regarding the timetable, privacy and legal issues associated with public institutions. Secondly, a small group of experts served as the validation group for the new framework. Individual semi-structured interviews were conducted to alleviate this constraint. They provide additional insights into an interviewee’s opinions and beliefs.

Ensure that the system is fair, transparent and facilitates their application process.

The main contribution is the AI-based theoretical framework, applicable within the analysis of literature papers, focusing on the problem of how the institutions can gain insights about their candidates while profiling them, how to obtain more accurate information from the interview phase and how to reach a more rigorous assessment of their emotional intelligence providing a better alignment of moral values. This work aims to improve the decision-making process of a PF institution recruiter by turning it into a more automated and evidence-based decision when recruiting an adequate candidate for the job vacancy.

Information systems (IS) play an important role in contemporary society, but critical questions remain on their potential use and impact on democracy. This study aims to contribute to the discussion on which technology can be adequate to which major challenge of democratic governance, through the identification and pairing of challenges of democratic governance with specific information technologies with the potential to be used in applications related to this challenge. This perspective can be considered positioned in the confluence between IS, political science and public administration.

Design science research, a research approach in IS, was used. The suggestion of a conceptual framework with pairs of challenges in democratic governance and information technologies was initially developed. In a subsequent phase, this framework was discussed and assessed through interviews with a panel of selected experts in e-government and IS, reaching a revised conceptual framework.

Results suggest that the conceptual pairing of challenges in democratic governance with IS’s solutions such as artificial intelligence, systems integration or blockchain technologies, for instance, if used in a critical, transparent and accountable way, can play a role in capacitating the delivery of better public services and contribute to encouraging citizen trust and political participation. These results may contribute to open a methodological agenda dedicated to the selection of adequate IS resources to address specific challenges of democratic governance, as well as to help in the development of public policies in the area.

Previous studies on digital government offer important insights on the impact of information and communication technologies-enabled public governance tools for government openness, public service efficiency and user-friendliness, and for citizen political participation and societal mobilization. But the literature still lacks a systematic conceptual framework mapping and assessing the role of distinctive IS instruments in democratic challenge-solving and specifying functional relationships between specific technology and democratic outcomes. This paper aims to contribute to filling this analytical gap.

This paper aims to explore explainable artificial intelligence (XAI) in democracy, proposing an applicable framework. With artificial intelligence’s (AI) increasing use in democracies, the demand for transparency and accountability in AI decision-making is recognized. XAI addresses AI “black boxes” by enhancing model transparency.

This study includes a thorough literature review of XAI. The methodology chosen was design science research to enable design theory and problem identification about XAI’s state of the art. Thereby finding and gathering crucial information to build a framework that aims to help solve issues and gaps where XAI can be of major influence in the service of democracy.

This framework has four main steps to be applied in the service of democracy by applying the different possible XAI techniques that may help mitigate existing challenges and risks for the democratic system. The proposed artifact intends to display and include all the necessary steps to select the most suitable XAI technology. Examples were given for every step of the artifact to provide a clear understanding of what was being proposed.

An evaluation of the proposed framework was made through interviews with specialists from different areas related to the topics in the study. The interviews were important for measuring the framework’s validity and originality.

Apart from the challenges related to vehicle technology, the wide-scale deployment of autonomous vehicles (AVs) in cities is linked to unprecedented opportunities and unforeseen impacts. These refer to mobility conditions, infrastructure, land use, wider socio-economic factors, energy use and environmental and climate effects. AVs may affect all these in positive or negative ways, promoting or obstructing the promotion of specific aspects of sustainable urban development. An integrated planning framework is needed to maximise the positive impacts and mitigate the negative ones. The main obstacle in the process of developing such a framework is the absence of empirical data and experience from the implementation of this emerging technology. This chapter outlines the possible impacts of AVs and discusses their uncertainty and trade-offs in relation to sustainable urban development. The categorisation of impacts derives from the priorities of the UN Sustainable Development Goal (SDG) 11: Make cities and human settlements inclusive, safe, resilient, and sustainable. The chapter also highlights the lack of data for the development of an evidence-based planning approach and suggests relevant recommendations to planners. In contrast to the current lack of data, the future abundance of Big Data collected by autonomous road transport systems is discussed in the context of future urban planning purposes. Based on the above, the chapter concludes by stressing the importance of an integrated urban transport planning approach that ensures a positive contribution of AVs to sustainable urban development. Hence, it offers valuable recommendations for policymakers in a range of fields.

Stakeholder satisfaction relates closely to service quality and performance of educational organizations. Often, this relationship is addressed in literature through the lens of excellence models, such as the European Foundation for Quality Management (EFQM) model. Nevertheless, limited studies focus on the effect of the EFQM model enablers on stakeholder satisfaction and hardly any in vocational education. To fill this void, the aim of this paper is to investigate the relationship between EFQM enablers (leadership, human resources, processes) and stakeholder satisfaction under the different perspectives of teachers and students in Greek public vocational education.

To address the research purpose, the authors used the case study methodology. The authors used mixed research methods, the focus group method and survey. Specifically, the focus group method used to distill the EFQM enablers related to the Greek context and to develop a questionnaire administered to teachers and students of a vocational education school. From September 2021 to June 2022, 90 teachers and 216 students participated in the survey.

The partial least squares structural equation modeling (PLS-SEM) method was used for data analysis, indicating that leadership and human resources have a positive and significant relationship with the satisfaction of both students and teachers. However, results did not corroborate the relationship between processes and stakeholder satisfaction either from the student’s or the teacher’s perspective.

This paper fills a gap in existing literature by exploring the impact of EFQM enablers on stakeholder satisfaction in vocational education and training (VET), from the perspectives of both teachers and students. The findings assist VET institutions in prioritizing areas for improvement and help companies to develop strategies that consider key stakeholders' needs.

The purpose of this study is to explore the interplay between electronic service quality, user experience (UX) and overall customer satisfaction. Additionally, it aims to assess the suitability of E-S-QUAL and UX metrics within the cultural context of Greece.

Data were collected from 310 Internet users based on their last online purchase from an e-retail website. To evaluate the conceptual model, the authors used partial least squares structural equation modeling (PLS-SEM).

The findings of this study validate the scales' reliability and validity in the realm of electronic commerce (e-commerce) in Greece. The findings also emphasize the favorable association between e-service quality and UX with overall satisfaction, while indicating that e-service quality plays a partial mediating role in the relationship between UX and customer satisfaction.

The authors' study enhances the existing theory by introducing a new multi-dimensional conceptual framework that illuminates the relative importance of the dimensions within the scales. Additionally, it offers valuable insights into the impacts of e-service quality and UX on overall satisfaction, providing managers and practitioners with a tool to evaluate the quality of their electronic services and make necessary adjustments to meet the needs of their customers.

The purpose of this paper is to investigate perceptions of primary education (PE) teachers with respect to evaluation within the framework of Total Quality Management (TQM) and their readiness to engage in the process of quality improvement. Within this context, a relevant measurement instrument is developed and empirically validated.

The instrument developed herein included 30 items distributed across seven dimensions. It was disseminated among public PE units in Greece, yielding a substantial 2,088 responses. Several tests were performed, including principal component analysis, confirmatory factor analysis and structural equation modelling.

The findings supported the validity and reliability of the instrument, confirming that the proposed measures encapsulate actual dimensions that are most suitable for exploring evaluation perception and readiness in the context of TQM in PE. The study explored several correlations between the validated dimensions and independent variables such as gender, level of education, years of teaching experience and age. These analyses yielded additional valuable insights, enriching the depth of understanding provided by the present research.

The fields of TQM and PE lack empirical evidence. However, this study offers valuable insights into teachers’ perceptions of evaluation and broader quality improvement efforts. This can help school managers, policymakers and practitioners refine their implementation strategies for educational excellence.

To the best of the authors’ knowledge, this study is the first to focus on the examination of evaluation as a key aspect of TQM within the context of PE. Through the development and validation of a real-time measurement instrument, it bridges a significant research gap, providing practitioners and researchers with a vital tool to understand and improve educators’ evaluation perceptions, enabling targeted interventions for enhanced performance.

This research examines the role of a therapist’s attributes, namely, expertise, sociability, likability and mind-set similarity, in building trust, satisfaction and commitment amongst visitors in Indian wellness resorts and hotels.

The text mining approach was adopted to collect a large corpus of 3,94,373 online reviews from TripAdvisor, Google Reviews and hotels.com. Reviews were taken from 1,677 resorts and hotels that deal in spa and wellness care across India. This study uses unsupervised Naïve Bayes classification and n-gram lexical TF-IDF vectorizer method to classify and find the sentiment of the reviews shared by the visitors of the wellness resorts. Additionally, multiple linear regression is performed to understand the impact of the therapist’s identified attributes on the visitor’s relationship quality.

The research found positive sentiment towards the therapist’s likability, and visitors seemed satisfied with the overall wellness service. The sentiment towards trust and commitment is low. The study also found significant links between likability and expertise in building the relationship quality between the therapist and the visitors. The expertise of the therapist enhances visitors’ trust and willingness to return. The therapist’s likability nature helps in increasing visitor satisfaction.

This study helps to understand the service personnel's level of relationship with the customer in hospitality services. Further, the study empirically verifies the important factors that build relationship quality in Indian wellness services.

The present study argues the need for greater clarity in understanding the customer perception of the services provided by wellness therapists in Indian wellness resorts and hotels. The study guides hotel managers to perform training of wellness therapists to improve customer satisfaction. Using the findings of the current study, managers can prioritize therapists’ attributes and realign their core strategies and provide satisfying wellness services to customers.

This study demonstrates the essential qualities a therapist should develop to enhance the relationship with the resort visitors and foster trust, commitment and satisfaction. The study goes a step further by using a vast database of online data for deep insights into the visitor’s view and the use of machine learning for amplifying results.

The purpose of this paper is to investigate consumers’ attitudes and behaviours towards wild and farmed fish, in order to identify possible distinct consumer groups, and to examine potential linkages between characteristics of the consumers’ demographic and socio-economic status and marketing aspects in wild and farmed fish.

Using data from an in-person field survey, a TwoStep cluster analysis was employed in order to detect perceived differences among consumers with different profiles.

The analysis identified two distinct consumer groups differentiated primarily by income: the low-potential aquaculture consumers and the high-potential aquaculture consumers, representing 67 and 33 per cent of the total sample, respectively. The study provides evidence that there is a lesser preference towards farmed fish. Therefore, more efficient marketing strategies are probably needed in order to promote awareness in aquaculture consumption, and potentially contribute in guiltlessness of the whole sector.

There is a lack of detailed empirical research regarding consumer perceptions and particularly potential differentiation for wild and farmed fish. This paper advocates the use of consumer profiles as a basis for the development of consumer-focused strategies in order to improve consumer performance in the sector.