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Relative performance evaluation (RPE) is a widely practiced employee appraisal process in the services industry. In a global delivery model, teams are spread across different geographical locations. The team members work on various tasks under the guidance of different managers and at times under more than one manager for performing the same task. Such complexities make RPE of the team members quite challenging. The paper proposes a methodical step-by-step approach to simplify the evaluation process without compromising on the rigour.

RPE has followed three different approaches. First is the traditional way, wherein evaluators had a common meeting to discuss and arrive at relative evaluation and ranking of members of the peer group employees. In the second, the number of evaluators and employees in a peer group were split in to 2 subgroups. The evaluators provided independent ratings and rankings. Simple mathematical tool then derived the combined ranking. In the third approach, each evaluator evaluated each employee in the peer group and provided the relative ranking for each employee. Again, mathematical tools provided the final ranking considering inputs from all evaluators. All the three evaluation approaches were analysed through an inter-rater agreement method.

All the three approaches for evaluation provided similar results giving confidence that less time-consuming methods could be adopted by evaluators without compromising on the rigour of the evaluation. The outcome of the exercise proved effective as the complaints reaching the ombudsmen reduced as compared to the earlier years. Considerable evaluation time was also saved. The study described in this paper is carried out in a non-unionized, Indian private sector services firm. Its effectiveness in other set ups is yet to be tested.

The research is carried out in the Indian Engineering services firm operating in the Knowledge based sector. Though study results are encouraging, the adaptability of methodology across different sectors and geographies is yet to be tested. More broad based studies are needed to evaluate suitability across firms and regions.

Relative evaluation exercise is challenging for evaluators. Although openness in evaluation is desired, it also makes evaluators uncomfortable in appearing to be taking sides or being opposing a candidate's ranking. The proposed approach brings in anonymity to each evaluator without scarifying individual evaluation.

The proposed methodology can be deployed across different services industries as the proposed methodology is business domain agnostic. It can be easily ported and tailored to align with an individual organization's evaluation philosophy. The suitability and effectiveness of the method can be studied under various types of firms like manufacturing, private, public, NGO, labour oriented, etc. As the proposed method reduces efforts, the stake holders can focus on understanding the relation between employee performance measurement, employee engagement, and long-term outcomes related to employee performance evaluation.

The proposed employee evaluation method leverages inter-rater reliability and agreement tool as a consensus approach to the relative performance ranking exercise. Such an approach to relative performance ranking is original as no prior studies with such an approach are found in the existing Literature.

Although educators would likely agree that values and ethics are important in all disciplines, they have particular importance for practice-oriented fields. These applied professionals need to solve complex social problems that require the application of ethical standards and value perspectives. While the importance of value-engaged practice is known to the applied field, there is little research and conversation about how values can be integrated into teaching. This chapter synthesizes values-education approaches in various practice-based disciplines such as public administration (PA), program evaluation, social work, and public health. This chapter draws from empirical and theoretical works as well as the authors' experiences developing, participating in, and conducting values-based research on professionals and professional education.

The purpose of this paper is to define the evaluation criteria for Chinese female lower body shapes and simplify the evaluation process of shapewear, including girdles, shaping pants, etc.

The study utilized a machine learning algorithm based on support vector regression and optimized by a genetic algorithm to construct an evaluation model for the contour beauty of Chinese female lower body shapes. A total of 64 virtual 3D models of women were measured. These models were rated by 42 raters using the Likert 9 psychological scale and data was obtained from 310 female samples.

Eight factors were selected and used to create a regression prediction model. The model achieved an accuracy of 84.7% for the training samples and 86.6% for the test samples.

The model can be utilized to assess the aesthetic appeal of the female lower body and to evaluate the shaping impact of shapewear. The research and evaluation of shapewear for the female lower body are of great significance, particularly in enhancing production efficiency.

The purpose of this research is to address the need for a robust system to accurately determine a cutoff score by using the Angoff method and leveraging the Rasch infit and outfit statistics of item response theory by detecting and removing misfitting items in a test.

Researchers in educational evaluation support the use of grades as a complete measure to evaluate students’ overall academic performance. In higher education, determining cutoff scores is crucial for assessing academic progress and achievement. Higher education institutions worldwide set predefined minimal standards of success, sometimes referred to as cutoff thresholds. These thresholds serve as benchmarks for assessing performance quality and determining eligibility for academic credit or advancement.

The proposed approach combines the Angoff method with Rasch item fit statistics to precisely determine the cutoff score by excluding items that do not fit well (misfitting items) in a test. This methodology holds the potential to enhance the fairness and accuracy of grading practices, ensuring that assessments align with educational objectives and provide meaningful feedback to students.

The value of this research extends to various fields where cutoff scores are used for decision-making purposes. By using Rasch item fit statistics and the Angoff method, practitioners and researchers can enhance the quality and validity of their assessments.

Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

This paper aims to generate knowledge about relevant evaluation topics that align with and represent the unique character of the midwifery programme for students living in the rural and remote areas of Scotland.

The first two central concepts of Practical Participatory Evaluation (P-PE) framed the research design: the data production process and (2) the knowledge co-construction process. The data were collected using a semi-structured approach via online discussions, dialogues and email-based consultation among programme stakeholders. A structural analysis was performed: the units of meaning (what was said) were extracted, listed and quantified in units of significance (what the texts were talking about), from which the key topics for evaluation emerged.

A community of 36 stakeholdersengaged in the discussions, dialogues and consultations. The stakeholders identified 58 units of significance. Fifteen subthemes were constructed in five main themes: student profile, student well-being, E-pedagogy, student journey/transition from being a nurse to becoming a midwife and learning in (an online) geographically remote and isolated area. The themes, or topics of evaluation, are dynamic functions and underlying mechanisms of the commonly used evaluation measures student progress and student evaluation.

This P-PE is a single-site study, focusing on a unique programme consisting of a specific group of students living and studying a specific geographic area, affecting the transferability of the findings.

In collaboration with stakeholders, parameters to evaluate the uniqueness of the programme in addition to higher education institution routinely collected data on student progress and satisfaction were systematically identified. The themes highlight that if student progress and satisfaction were the only evaluation parameters, knowledge and understanding of the contributing factors to (un)successfulness of this unique online midwifery programme could be missed.

The primary objective of this research paper was to examine the objectivity of the preselected items evaluation (PIE) method, a prevalent translation scoring method deployed by international institutions such as UAntwerpen, UGent and the University of Granada.

This research critically analyzed the scientific and theoretical bottlenecks associated with the PIE method, specifically focusing on its parameters, namely the p-value and d-index, in adherence to established statistical protocols. Proposed remedies to mitigate the identified bottlenecks and augment the efficacy of the method were grounded in practicality.

The paper provided an extensive overview of the PIE method, which served as the foundation for the subsequent analysis and discussions. This research presented potential avenues for refinement and contributed to the current debate on objective translation assessment by addressing the theoretical and practical challenges associated with the PIE method.

Translation researchers, practitioners and international institutions seeking to enhance the accuracy and reliability of translation evaluation should consider the implications of this research’s findings.

Although several publications focused on the role of the PIE method in translation evaluation, no study(ies) is available to critically analyze the scientific and theoretical bottlenecks of this translation evaluation method.

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.

This study aims to investigate the stakeholders’ (employers and students) involvement in economics and management programs quality assurance in Italian universities from the external audit perspective.

The research tests if employers are positively associated with the coherence between program objectives and job prospects, and if student involvement is positively associated with student orientation, tutorship and flexibility for specific types of students (differently abled students and working students). Based on data from the Italian Agency for Quality Assurance (ANVUR) in Italian universities, this study selects a sample of 44 bachelor and master university programs.

When a program coordinator assures coherence between competencies included in the study plan and job prospect, the employers’ involvement in the plan and management of the program increases and becomes more effective. High-quality services regarding student orientation, tutorship and flexibility for specific types of students increase the students’ involvement in university governance.

Findings contribute to literature extending the stakeholder theory in universities, better specifying how employers and students may play a key role in improving the quality assurance of teaching activities.

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.