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In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

The purpose of this study is to examine the impact of educational service quality (ESQ) on student academic performance via the mediating role of student satisfaction.

To serve the study’s purpose, the study adopted a quantitative research approach. Three public universities representing 30% of the ten public universities located in the Southern part of Ethiopia participated in the study. Questionnaires were the main tools for gathering data. The adapted questionnaire, consisting of 116 items was administered to 400 randomly selected regular undergraduate graduating class students. The quantitative data collected via questionnaire were analyzed using descriptive and advanced inferential statistics.

The quantitative findings revealed that there is a statistically positive association between overall education service quality and students’ satisfaction (r = 0.712). The findings proved that the facets of education service quality accounted for 71.2% of the variations in students’ satisfaction in the universities. The quantitative findings further showed that the education service quality has a statistically indirect effect on students’ academic performance via the mediating role of students’ satisfaction (test statistic = 31.5311573, std. error = 0.00122536 and p-value = 0). The findings further confirmed that the overall education service quality accounted for 12.7% of the variations in students’ academic performance via student satisfaction in the universities.

The present study was conducted in public universities located in the Southern part of Ethiopia. The findings and conclusions of the study may not be generalizable to all Ethiopian public universities. Future researchers and scholars should conduct their study in all Ethiopian public universities by taking a representative sample from the Ethiopian public universities.

The present finding suggests that an improvement in ESQ leads to students’ satisfaction and that could contribute to boosting their academic performance. The findings of the present may help the practitioners who measure higher education service quality by providing how the provision of ESQ indirectly influences the student’s academic performance in the universities.

The findings of this study confirmed that the facets of ESQ are associated with students’ satisfaction and this, in turn, indirectly influences their academic performance. Student academic performance is one of the key indicators of quality education, and it has its influences on the social, political and economic development of a country. The findings of the present research provide valuable insights to higher education management bodies, higher quality assurance agencies and the Federal Ministry of Education to learn the indirect effect of ESQ on students’ academic performance and take necessary measures to improve the Ethiopian higher education quality.

The contributions of ESQ in the higher education sector are enormous. However, the existing service quality literature in higher education mainly focuses on the interrelation among service quality, student satisfaction, loyalty and behavioral intentions. Little is known about the indirect influence of ESQ on student academic performance (one of the key indicators of quality education), principally in Ethiopian higher education, the place of current research. The present study showed the indirect impact of ESQ on student academic performance in Ethiopian public universities. The study, therefore, suggests that university management bodies should actively monitor the quality of their services and commit themselves to boosting students’ learning outcomes.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

The purpose of this study was to fill the gap in understanding the impact of Drug Recognition Expert (DRE) evidence and testimony in driving under the influence (DUI) trials. This was accomplished by documenting and analyzing the perceptions of DREs and the DRE program across different stakeholders to understand how and when this type of evidence is used in DUI trials.

The methodology is a qualitative case study of the DRE program in one police agency in Washington. Data were collected using semi-structured interviews with criminal justice actors and state-level experts on their perceptions of the DRE program for the agency. Themes were developed from these interviews to analyze their perceptions of the efficacy and utility of DREs in trials.

While the courts in Washington accept DRE evidence in criminal trials, DRE evidence is largely absent in the adjudication process. Participants noted multiple reasons for this, including the lack of trials, the primacy of blood evidence and the expansion of the Advanced Roadside Impaired Driving Enforcement (ARIDE) program.

Although the DRE program has been around for decades, there is a lack of peer-reviewed studies regarding DRE evidence, and no studies regarding how court actors perceive and use DRE evidence. Understanding when and how DRE evidence is utilized in DUI trials can increase its value and utility by prosecutors and the national DRE program.

Quality assessment of textile products is of prime concern to intimately meet consumer demands. The dilemma faced by textile producers is to figure out the stability among quality criteria and efficiently deal with target specifications. Hence, the basic devotion is to attain the optimum value product which entirely satisfies the views and perceptions of consumers. Selection of best fabric among several alternatives in the presence of contradictory measures is a disputing problem in multicriteria decision-making.

In the current study, the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) are proficiently used to solve the problem in selection of branded woven shawls. AHP method verifies comparative weights of the criteria selection, while the ranking of fabric alternatives grounded on specific net-outranking flows is executed through PROMETHEE II method.

The collective AHP and PROMETHEE approaches are applied for the useful accomplishment of grading of branded shawls based on multicriteria weights, used for effective selection of fabric materials in the textile market.

In the apparel industry, fabric and garment manufacturers often rely on hit-and-trial methods, leading to significant wastage of valuable resources and time, in achieving the desirable fabric qualities. The implementation of the findings can assist apparel manufacturers in streamlining their fabric selection processes based on multiple criteria. By adopting this method, industry players can make informed decisions, ensuring a balance between quality standards and consumer expectations, thereby enhancing both product value and market competitiveness.

The methods of Visual PROMETHEE and AHP are assimilated to offer a complete method for the selection and grading of fabrics with reference to multiple selection criteria.

This paper aims to investigate why followers have low perceptions of leader openness and thus feel reluctant to communicate novel ideas by examining leader–follower relationship conflict (i.e. interpersonal incompatibility) and a follower’s power distance orientation (i.e. an acceptance of uneven power distribution in organizations) as antecedents.

The research administrators conducted a three-wave work behavior survey in Study 1, a laboratory experiment in Study 2, and an online experiment in Study 3.

The results demonstrated that leader–follower relationship conflict reduced followers’ perceptions of leader openness. However, the negative impact of relationship conflict became non-significant when followers have high power distance orientations (i.e. an acceptance of uneven power distribution in organizations). The findings also showed an indirect interaction effect of leader–follower relationship conflict and followers’ power distance orientation on the followers’ communication of novel ideas through the followers’ perceptions of leader openness.

The research suggests that followers with higher power distance orientations are more likely to communicate novel ideas consistently because their relationship conflicts with their leaders do not negatively influence their perceptions of leader openness. Although researchers traditionally view cultures with a high level of power distance value as an obstacle to employee creativity, the present study reveals the benefits of an individual-level power distance orientation.

Positive psychology helps us understand the knowledge required to contribute to adolescents' societal development and adjustability. Adolescence is the crucial stage to work on for a balanced personality. The present study concerned adolescents' self-strength, happiness, and help-seeking behaviour. The authors aimed to explore the relationship between adolescents' self-strength and happiness and investigate the mediational effect of adolescents' help-seeking behaviour on their self-strength and happiness.

The research design of the current quantitative study was correlational, and 809 adolescents from China and Pakistan participated in the present study. Data were personally collected from participants through self-developed scales.

We deployed Pearson correlation and simple mediation using SPSS software and found a linear, positive, strong (r = 0.654, n = 809, p = 0.000 < 0.01) and statistically significant correlation between adolescents' self-strength and happiness. The authors also found a significant indirect effect of help-seeking on adolescents' self-strength and happiness at (β = 0.373, t(907) = 7.01).

Using self-reported scales to gather information was one of the study's limitations. Adolescents may have misunderstood the notion or construct narrated in words or responded biasedly despite the bilingual scales.

This study offers social and practical implications for educators, parents, and school administrators to address the development of adolescents' personalities using a positive psychology lens.

The findings are of significant importance for teachers working in the elementary schools. They may work on adolescents' self-strength, happiness, and help-seeking to develop balanced personalities.

Security assurance evaluation (SAE) is a well-established approach for assessing the effectiveness of security measures in systems. However, one aspect that is often overlooked in these evaluations is the assurance context in which they are conducted. This paper aims to explore the role of assurance context in system SAEs and proposes a conceptual model to integrate the assurance context into the evaluation process.

The conceptual model highlights the interrelationships between the various elements of the assurance context, including system boundaries, stakeholders, security concerns, regulatory compliance and assurance assumptions and regulatory compliance.

By introducing the proposed conceptual model, this research provides a framework for incorporating the assurance context into SAEs and offers insights into how it can influence the evaluation outcomes.

By delving into the concept of assurance context, this research seeks to shed light on how it influences the scope, methodologies and outcomes of assurance evaluations, ultimately enabling organizations to strengthen their system security postures and mitigate risks effectively.