Analytic Hierarchy Process Analysis Research Articles

Charting the future of green HRM practices: insights from theories, context, characteristics and methodologies (TCCM) framework and analytical hierarchy process (AHP) analysis

PurposeThe term “green human resource management” (Green HRM) is becoming more prevalent in both academics and business. This study’s main objective is to locate current understanding and trends in Green HRM literature by examining the available Green HRM literature. And prioritize the Green HRM practices in higher education institutions (HEIs). The study also identifies prevailing theories, context, characteristics and methodologies as current research interests to identify potential future research areas in Green HRM.Design/methodology/approachThe study opted for a multi-method approach, combining theories, context, characteristics and methodologies (TCCM) for literature review and the analytical hierarchy process (AHP) for methodological analysis. The article selection process is illustrated via a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart. The study examines Green HRM literature using the TCCM framework as it aids in identifying commonly used theories, constructs and methods, suggesting future research directions (FRDs). After identifying core Green HRM practices, the study prioritizes them for the HEIs using the AHP.FindingsThe comprehensive analysis of the literature is provided by the TCCM framework, which identifies the most influential theories, contexts, characteristics and methodologies used in Green HRM literature. The most used theory was found to be the ability-motivation-opportunity (AMO) theory, followed by social identity theory. In context, the hospitality industry was the dominating sector/industry of the domain. Under the characteristics, various variables in Green HRM literature were identified and classified as antecedents, mediators, moderators and outcomes. The most used research method was quantitative, and the most opted research design was empirical. FRDs are also suggested analyzing the current trends of the Green HRM field. The finding of AHP indicates that green recruitment and selection holds the highest level of importance among Green HRM in HEIs.Research limitations/implicationsThis study is vital for past-future orientation, in which the past is explored in order to build new routes of Green HRM research. It used research publications from the Scopus database, and future studies may use other databases to improve understanding of Green HRM research.Practical implicationsAHP weights and ranks aid decision-makers in assessing Green HRM practice importance, facilitating pairwise comparisons before implementation in the HEIs and other service industries. It guides managers on allocating appropriate importance to each practice for informed decision-making.Social implicationsThis study enriches Green HRM literature using the TCCM framework, categorizing literature into four key areas and offering valuable FRDs for future researchers. Its comprehensive review provides crucial insights into the research landscape of Green HRM, aiding in understanding theories, variables, relevant sectors and methodologies. The study offers comprehensive theoretical implications in the realm of Green HRM.Originality/valueExisting research indicates that no study has employed a multi-method approach combining the TCCM framework and AHP in Green HRM research. The initial TCCM phase conducts a thorough analysis, examining theories, contexts, characteristics and methodology, a unique methodology. It connects TCCM findings to FRDs. In the subsequent phase, AHP prioritizes Green HRM practices for the HEIs based on identified research gaps from TCCM. This innovative fusion of TCCM and AHP, resulting in FRDs and implications, represents the novelty of this paper.

Personal data strategies in digital advertising: Can first-party data outshine third-party data?

As Google explores new personal data strategies, it aims to strike a balance between enhancing privacy and maintaining personalization, ensuring that consumers' data is handled responsibly while still delivering relevant and personalized advertising. This study, based on the privacy calculus framework, employs a mixed-methods approach to address two key objectives: 1) understanding how different levels of personalization impact advertising performance based on the type of data utilized, and 2) exploring the underlying mechanism of consumer reactions to personalized advertising using different types of personal data. To achieve the first research goal, Study 1 integrates Analytic Hierarchy Process (AHP) analysis of survey data from 25 advertisers with econometric analysis of advertising data from a European beauty company. To achieve the second research objective, Study 2 explores consumer perceptions through in-depth interviews and an online survey. The key findings of this study are as follows. The AHP analysis revealed that advertisers prioritize first-party data, especially purchase history, for enhancing personalized targeting. The econometric analysis suggested that while third-party data is currently most effective for enhancing advertising performance, first-party data emerges as a promising alternative in light of evolving advertising policies. Qualitative and quantitative analyses revealed complex interactions between personalization levels, data types, and consumer responses, highlighting the tension between personalization benefit and risk. These insights provide valuable guidance for advertisers, platforms, and policymakers in navigating the changing landscape of digital advertising and personal data privacy.

Three-Dimensional Printed Auxetic Insole Orthotics for Flat Foot Patients with Quality Function Development/Theory of Inventive Problem Solving/Analytical Hierarchy Process Methods

Foot disorders affect approximately 10% of adults, with plantar heel pain significantly impacting foot-related quality of life and altering walking patterns. Flat feet, characterized by a lack of longitudinal arches, can lead to fatigue during walking. This study aims to develop 3D-printed shoe insoles tailored to the needs of patients. The design process incorporates Quality Function Deployment (QFD), Theory of Inventive Problem Solving (TRIZ), and Analytic Hierarchy Process (AHP) methods to create insoles that alleviate concentrated loads while meeting patient requirements. The AHP analysis indicated that patients prioritize insoles that effectively manage pressure distribution to achieve optimal functionality. QFD and TRIZ facilitated the identification of four product alternatives and production specifications. The analysis indicated that 3D-printed insoles made from TPU filament with 20% auxetic infill best align with patient preferences. This auxetic TPU option emerged as the top choice, achieving a priority value of 0.2506 due to its superior functionality and comfort. Load distribution measurements confirmed that TPU with auxetic infill resulted in the lowest load distribution, with a standard deviation of 0.1434 and a 25.4% reduction in maximum load compared to conditions without the insole.

Business Model Adaptation For Foreign Company To Navigate Local Content Requirements In Indonesia’s Upstream Oil and Gas Industry In 2034 Using Inductive Scenario Planning Approach (Case Study Tas)

Complying with local content regulations in the upstream oil and gas industry presents a significant challenge. These regulations aim to enhance local capability, and the industry's yearly transaction value greatly impacts the local industry, necessitating the use of local products. However, despite requiring high technology, this industry mostly relies on imported products. To address this challenge, our research employs a systematic approach that combines scenario planning with Analytic Hierarchy Process (AHP) analysis. Our primary goal is to develop a comprehensive framework that empowers organizations to optimize their business strategies within the context of localization projects. By integrating scenario planning, which allows for the exploration of diverse future scenarios, with AHP analysis, which offers a structured analytical foundation for evaluating and selecting strategies, our research equips decision-makers with a powerful toolset. Through extensive case studies and meticulous analysis, our research sheds light on the nuanced decision-making processes and strategic adaptations that can be achieved through the synergy of scenario planning and AHP analysis in the domain of localization projects. Our findings and insights provide practical guidance to decision-makers grappling with the complexities of local content compliance and the long-term sustainability of business strategies.

Mentoring strategy to improve the effectiveness of succession planning in PT Multimas Nabati Asahan - Serang

This study focuses on analyzing the influence of mentoring conducted by PT Multimas Nabati Asahan Serang on the effectiveness of succession planning, analyzing mentoring that has a dominant influence on succession effectiveness planning, and developing mentoring strategies to increase the effectiveness. The study involved a total of 22 departments within the organization and will span three months, from September 2024 to November 2024. The results of the Analytical Hierarchy Process (AHP) analysis showed that the employee competency factor is the most influential factor in succession planning. The data from the assessment of the weight and priority of alternative elements of strategies to the objectives showed the highest influence was collaborative learning with a weight value of 0.281 and then the second to fifth were alternative strategies for enrichment and expansion of work, project assignment, work rotation, and formal training.

The application of the SPOC teaching model in college elective basketball courses: integrating biomechanical principles for enhanced performance

The SPOC (Small Private Online Course) model is a new teaching model derived from Massive Open Online Courses (MOOC) and is an important direction for the reform and innovation of future higher education. In the practical application of SPOC teaching, subjectivity issues may arise, namely the influence of individual opinions and judgment criteria. The evaluation may focus on certain aspects and neglect others, resulting in incomplete overall assessment results. This paper applies the SPOC teaching model in three time periods: before class, during class, and after class, with a focus on integrating biomechanical principles into the evaluation of student performance in basketball. The study employs various research methods such as literature review, Analytic Hierarchy Process (AHP) analysis, and fuzzy comprehensive evaluation to construct a comprehensive evaluation index system for student ability improvement in SPOC teaching in higher education. This system incorporates biomechanical factors such as movement efficiency, force production, and body mechanics, which are essential for enhancing basketball skills. Based on this, an evaluation method for student ability improvement in college SPOC elective basketball courses is proposed using the AHP-fuzzy evaluation model. This model not only assesses traditional skill metrics but also integrates biomechanical assessments, such as shooting mechanics, dribbling efficiency, and defensive posture. The application of the AHP-fuzzy evaluation model, enhanced with biomechanical insights, demonstrates that his method can effectively improve students basketball abilities. The incorporation of biomechanical principles allows for a more holistic evaluation of student performance, emphasizing the importance of physical mechanics in skill development. The integration of the SPOC teaching model with biomechanical principles in elective basketball courses provides a comprehensive framework for evaluating and improving student performance. By focusing on both skill acquisition and biomechanical efficiency, this approach not only enhances basketball abilities but also fosters a deeper understanding of the physical demands of the sport.

Presentation and analysis of the Geotechnical Coastal Vulnerability Index and validation of its application to coastal erosion problems

This study aims to construct a coastal vulnerability assessment conceptual framework to improve the outcomes of Coastal Vulnerability Index (CVI) for local scale areas. Consequently, a new CVI was created adapted to the specific conditions of the area using seven variables. The new index was named Geotechnical Coastal Vulnerability Index (GCVI) due to the incorporation of two new geotechnical variables: (1) Coastal geotechnical properties and (2) Median grain size distribution. Furthermore, Fuzzy Analytic Hierarchy Process (FAHP) and Principal Component Analysis (PCA) were applied in the methodology to assign weight factors to each variable. For the verification of the GCVI predictions, a validation approach is applied using two different variables (rate of Historical shoreline movement and rate of Bed level change). GCVI results for both FAHP and PCA indicates that the greatest part of the study’s area shoreline is under the regime of high and very high vulnerability. Comparison between the GCVIFAHP and GCVIPCA results indicates higher rates in the high and very high vulnerability classes for the GCVIFAHP, while the GCVIPCA shows lower rates in the same classes. Both analytical methods were used for the validation of the GCVI results and the comparison between them showed that the PCA was more efficient than the FAHP since it was coincided better with the rates of historical shoreline movement and bed level change.

지역 기반 사회적기업 성과지표 표준화에 관한 연구: IPOO 모델을 활용한 지표개발 및 가중치 도출

This study proposes and validates a new performance evaluation framework for social enterprises based on the IPOO (Input-Process-Output-Outcome) model. Existing Social Value Index (SVI) indicators focus primarily on short-term outcomes, failing to adequately reflect the long-term sustainability and public value of social enterprises. To address these limitations, this study designed a systematic evaluation model encompassing inputs, processes, outputs, and outcomes, and validated its reliability through expert opinions and Analytic Hierarchy Process (AHP) analysis. The research was conducted in two phases. First, a comparative evaluation between the existing SVI and the IPOO-based indicators demonstrated the superiority of the new framework in integrating social value, supporting decision-making, and simplifying the evaluation process. Second, the weights of the four key dimensions—Input, Process, Output, and Outcome—along with their sub-components, were derived. The results revealed that the Outcome dimension, which reflects long-term social change, was the most significant. The Output dimension focused on short-term achievements, while the Process and Input dimensions played essential roles in assessing operational efficiency and resource utilization. This study offers a multidimensional framework for evaluating the performance of social enterprises, overcoming the limitations of existing methods. It contributes both academically and practically by providing a reliable tool that captures the diverse objectives of social enterprises. Future research should focus on clarifying the distinctions between Output and Outcome indicators and refining the evaluation procedures.

수도권 내 400m 트랙 스케이트장 건립의 적지 분석: 지리 정보 시스템 기반의 다기준 의사결정

The Korea National Training Center International Rink (Taereung International Skating Rink), the only 400m (full-length) track speed skating rink in South Korea, is under threat by demolition. In response, this study explores optimal locations for constructing a new 400m track speed skating rink using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). The AHP analysis identified accessibility, particularly proximity to subway stations and arterial roads, as the most critical factors in site selection. Using the weights derived from the AHP, site suitability analysis pinpointed optimal locations within the Seoul Metropolitan Area, particularly in parts of Incheon and Gyeonggi Province bordering Seoul. This study is significant as it establishes a GIS-based multi-criteria decision-making framework for selecting suitable sites for a 400m track speed skating rink and demonstrates its practical application. The findings underscore the importance of accessibility in site selection and offer a practical tool for planning future sports facilities.

Strategy for Enhancing the Performance of Marine and Fisheries Resources Surveillance (Case Study at the Marine and Fisheries Resources Surveillance Base in Tual)

This study aims to formulate strategies to enhance the performance of marine and fisheries resource surveillance at the Marine and Fisheries Resources Surveillance Base (PSDKP) in Tual. The effectiveness of surveillance is a key factor in preserving resources and preventing illegal activities that harm the state. This research employs two main analytical approaches, the Analytic Hierarchy Process (AHP) and SWOT analysis, to identify and prioritize the most relevant strategies. The AHP results indicate that human resources (HR) have the highest weight (0.657), followed by infrastructure and surveillance systems (0.259), and policy (0.084). Based on the SWOT analysis, the prioritized strategies include enhancing HR capacity with a weight of 0.571, developing surveillance systems with a weight of 0.191, strengthening cooperation with a weight of 0.123, and advocating for policy and lobbying with a weight of 0.114. The implementation of these strategies is expected to improve surveillance effectiveness, reduce violations, and support the sustainability of marine and fisheries resources in the PSDKP Tual area.

Methodological approaches in prioritizing municipal projects: A case study of the municipality of the holy capital (Makkah)

This study aims to develop a robust prioritization model for municipal projects in the Holy Metropolitan Municipality (Makkah) to address the challenges of aligning short-term and long-term objectives. The research explores How multi-criteria decision-making (MCDM) techniques can prioritize municipal projects effectively while ensuring alignment with strategic goals and local needs. The methodology employs the analytic hierarchy process (AHP) and exploratory factor analysis (EFA) to ensure methodological rigor and data adequacy. Data were collected from key stakeholders, including municipal planners and community representatives, to enhance transparency and reliability. The model’s validity was assessed through latent factor analysis, confirming the relevance of identified criteria and factors. Results indicate that flood prevention projects are the highest priority (0.4246), followed by road projects (0.3532), park construction (0.1026), utility projects (0.0776), and digital transformation (0.0416). The study highlights that certain factors are critical for evaluating and prioritizing municipal projects. “Capacity and Demand” emerged as the most influential factor (0.5643), followed by “Strategic Alignment” (0.2013), “Project Interdependence” (0.1088), “Increasing Investment” (0.0950), and “Risk” (0.0306). These findings are significant as they offer a structured, data-driven approach to decision-making aligned with Saudi Vision 2030. The proposed model optimizes resource allocation and project selection, representing a pioneering effort to develop the first prioritization framework specifically tailored to Makkah’s unique municipal needs. Notably, this is the first study to establish a prioritization method specifically for Makkah’s municipal projects, providing valuable contributions to the field.

국내 고등학교 미술 수업 흥미 증진의 결정요인 분석: AHP 분석을 중심으로

Objectives In current high school education, art is often perceived as a peripheral subject, leading to the loss of its importance and legitimacy. However, art education can significantly alleviate severe academic stress and enhance empathy and creativity among students, particularly in an increasingly individualistic society. This study aimed to identify the key factors that contribute to increasing high school students' interest in art education. Methods To achieve this research objective, a survey was conducted with 50 high school students in their second year or above, from schools located in Seoul, to perform an Analytical Hierarchy Process (AHP) analysis. The collected data were analyzed using an AHP analysis program developed in Excel, allowing for the assessment of the importance and prioritization of various factors. Results The analysis results revealed the following: First, the priority order among the main categories was identified as follows: art class environment factors, student factors, the personal characteristics of the instructor, and teaching methods and class management. Second, within the category of teaching methods and class management, the priorities were as follows: provision of art-related information, differentiated instruction, supplementary guidance, class structure, class diversity, and interaction. Third, regarding the personal characteristics of the instructor, the priorities were humor, the instructor’s capability, the instructor’s knowledge, the instructor’s qualities, and the instructor’s attitude. Fourth, the student factors in art classes were prioritized as future career plans, experience and ability related to art, learning motivation, art-related performance, achievement motivation, and self-efficacy in art. Lastly, the factors related to the art class environment were identified in the following order of priority: support for related facilities, the physical environment of the classroom, safety and hygiene, and accessibility to materials and tools. Conclusions Thus, this study highlights the importance of establishing systems and environments for art education that foster creative activities and psychological stability for high school students. To achieve this, it is essential to establish a clear direction for art education, recognizing its value, significance, and positive effects. The proposed strategy involves gradually building an art education system by first enhancing students' interest and engagement in art classes through the provision of professional knowledge based on humor and wit, as well as fostering a high standard of instructor qualities and attitudes, and identifying and nurturing students' artistic talents and potential. By doing so, it becomes more feasible to secure the necessary systems and physical facilities for art education.

Industrial Engineering and Management Applications: Evaluation of Data Integration Tools for Smart Manufacturing

This study comprehensively evaluates leading data integration tools for smart manufacturing environments using a hybrid Analytic Hierarchy Process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology. As Industry 4.0 drives increased automation and data exchange in manufacturing processes, selecting appropriate data integration tools has become critical yet complex. We assessed seven prominent data integration tools across 24 criteria grouped into six main categories: functionality, vendor-related factors, user experience, cost, reliability, and flexibility. Our data collection was informed by expert interviews, vendor documentation analysis, user reviews, and benchmark testing. The AHP analysis revealed functionality and data integration features as the most crucial criteria (weight: 0.2493), followed by user-related factors (0.1814). The VIKOR method then ranked the tools, with Oracle Data Integrator emerging as the top performer (Q=0.0000), followed by Informatica PowerCenter (Q=0.22391). Our findings highlight the importance of cloud-native solutions and user experience in industrial data integration. This research contributes a robust framework for evaluating data integration tools in imaginative manufacturing contexts and offers insights to guide decision-making in Industry 4.0 initiatives.

Development of Delay and Disruption Cause Monitoring Framework for Megaprojects: A Claim Management Approach from the Contractor’s Perspective to Enhance Sustainability in the Built Environment

Delays and disruptions (D&D) are considered chronic peculiarities of the construction phase of the built environment, especially in megaprojects. Systematic monitoring of claimable D&D causes becomes crucial for the contractors to compensate for their losses caused by delays and disruptions, enabling sustainable use of resources. Thus, this study proposed a delay and disruption (D&D) cause monitoring framework that enables contractors to timely and accurately detect claimable delays and disruption causes/events in megaprojects. At the outset, a systematic literature review was conducted to design an initial version of the framework and extract claimable D&D. Then, focus group discussion (FGD) sessions were conducted to revise and refine the initial version of the framework and a list of claimable D&D causes. Next, a fuzzy Analytical Hierarchy Process (AHP) analysis was conducted to determine the relative importance of each claimable D&D cause in terms of its impact on the megaprojects. Finally, a consistency analysis was conducted to demonstrate the reliability of the dataset. Findings revealed that claimable D&D causes are indispensable parts of the claim management process. In this manner, the proposed framework recommends monitoring the claimable D&D causes regularly during the whole construction phase of the megaprojects. The fuzzy AHP analysis also revealed that causes such as “Suspension of project activities by the owner”, “Errors and clashes in the design”, “Shortage of construction materials in the market”, “Discovery of fossils and historical artifacts”, “Unavailability of the commissioning team on the due date”, and “Late delivery of testing materials and utilities by the owner” were particularly rated as highly critical causes, needing urgent and sophisticated monitoring plan for timely detection and data collection. By introducing a proactive approach to avoid lengthy and costly dispute resolution processes, this study enables decision-makers to enhance sustainability in the built environment.

Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic

Natural images captured in hazy, sandy or low-light conditions degrade significantly and are termed weak image signals (WIS) in this paper. Evaluating their restoration using multiple single-factor indices is challenging due to potential mutual exclusivity, hindering a holistic understanding. A novel no-reference image quality evaluation approach has been devised specifically to assess the visibility enhancement of restored WIS images. This approach constructs a comprehensive index, based on fuzzy theory, to holistically evaluate the restoration effect of WIS. The index is derived from five carefully selected single-factor indices: new visible edge, visible edge gradient, contrast gain, colour naturalness and colour richness. These indices capture improvements in contrast and colour post-restoration. Fuzzy logic is employed to meticulously analyze the contribution of each factor to the overall image performance. The weights assigned to each individual evaluation index are determined through a rigorous analytic hierarchy process (AHP) analysis, utilizing a judgment matrix. The comprehensive evaluation index, denoted as CNC, surpasses the limitations of single-factor indices by capturing even the subtlest changes across all factors, offering a more comprehensive and nuanced assessment. Experimental validation confirms its alignment with subjective evaluations, confirming its effectiveness in comprehensively evaluating the restoring effect of WIS images.

Design of Oral English Teaching Quality Evaluation System Based on AHP-Fuzzy Algorithm

In the evolving landscape of English oral language instruction, the integration of online and offline (blended) teaching methodologies has emerged as a significant approach to enhance learning outcomes. This study addresses the need for a robust and nuanced evaluation framework capable of assessing the quality of blended English oral language teaching. Motivated by the limitations of traditional evaluation methods in capturing the complexities and subjective nuances of blended teaching environments, we propose a novel evaluation model that leverages the Analytic Hierarchy Process (AHP) and Fuzzy Association Analysis. This paper outlines a systematic approach to construct a comprehensive evaluation indicator system tailored to the specific demands of English oral language teaching. Utilizing AHP, we determine the relative weights of various evaluation indicators, laying a solid foundation for a structured assessment framework. Subsequently, Fuzzy Association Analysis is employed to handle the inherent uncertainties and subjectivities associated with teaching quality assessment, thereby facilitating a more accurate and holistic evaluation. An empirical case study is presented to demonstrate the practical application of our proposed AHP-Fuzzy model in evaluating the quality of a specific blended English oral language teaching program. The results underscore the model’s effectiveness in providing a detailed and nuanced assessment of teaching quality, highlighting its superiority over traditional evaluation methods in addressing the complexities of blended teaching environments.

AHP-Driven Strategic Decision Framework for Selecting Optimal Radiopharmaceutical Facility Locations

Given the increasingly important role of radiopharmaceutical products in medical diagnosis and treatment, choosing a strategic location for a new radiopharmaceutical facility is an important decision for pharmaceutical companies. This research develops a multi-criteria decision-making framework for selecting optimal radiopharmaceutical facility locations. The framework begins by generating alternative locations and criteria by using a PESTEL analysis to assess the external environment. Five key criteria were then identified for evaluation: customer proximity, transportation accessibility, operational support, public acceptance, and legal acceptance, with each criterion further broken down into specific sub-criteria. The Analytical Hierarchy Process (AHP) method was used to weigh these criteria and sub-criteria based on expert and stakeholder input, and to evaluate the alternative locations. Results of the AHP analysis showed that proximity to customers and accessibility to transportation were the most important criteria, leading to the selection of Cikarang as the optimal location due to its proximity to hospitals, convenient transportation access, and compliance with regulations and permits. Sensitivity analysis confirmed the robustness of this choice against variations in criteria weights. This framework provides a structured approach for pharmaceutical companies in strategic decision-making regarding the siting of radiopharmaceutical facilities.

Analysis of risk factors faced by Chinese international students based on fuzzy comprehensive evaluation model

IntroductionChina has contributed the most international students to the global higher-education sector for over a decade. Existing research has indicated various risk factors faced by international students. However, few studies have examined the risks experienced by Chinese international students. Two research questions were investigated in this study: (1) Which risk factor has the greatest impact on Chinese international students when studying abroad? and (2) Which risk factor is most frequently experienced by Chinese international students when studying abroad?MethodTo address these questions, this study proposes a fuzzy comprehensive evaluation model for evaluating the risk factors faced by Chinese international students. The model comprises six second-level factors and 22 third-level indicators, which was empirically examined by data collected through 556 questionnaires. The analytical hierarchy process and factor analysis were employed to calculate the index weight of second-level factors and third-level indicators.ResultsThe results reveal that the risk factor, psychological discrepancy, has the greatest impact and is most likely to be experienced by Chinese international students. The paper provides an integrated research perspective to study the risk of international students.DiscussionThe paper discussed the factors that impact the risk faced by Chinese international students. The risk faced by Chinese international students was found to be high. Psychological discrepancy, academic choice, and cross-cultural adaptation were the three risk factors that were most likely to be experienced by Chinese international students. Psychological discrepancy, barriers to study, and unforeseen incidents had the highest impact on total risk. Therefore, attention should be paid to these risk factors to avoid the occurrence of risk and its negative impacts.

Development and validation of an unsafe behavior checklist for workers.

The purpose of this study is to develop and validate a simple unsafe behavior checklist to assess the extent of unsafe behavior among workers in an industrial setting. The checklist was developed using Focus Group Interview (FGI) and Analytical Hierarchy Process (AHP) analysis methodology. Preliminary testing was conducted with an unspecified sample and the correlation between unsafe behavior and accident experience was validated. The analyzed and compared the correlation between the type of unsafe behavior and accident experience and demonstrated the suitability of the unsafe behavior checklist. A risk sensitivity and risk-taking checklist was employed to identify five types of unsafe behavior. This study concludes that the unsafe behavior checklist can be used to predict accident concerns among workers with high types of dangerous behavior. This can help improve unsafe behavior and reduce the frequency of incidents. Therefore, the "Unsafe behavior Checklist" developed in this study can be used as an early indicator of the extent to which workers are aware of dangers in industrial workplaces in order to prevent accidents.

Quality Evaluation of Effective Abrasive Grains Micro-Edge Honing Based on Trapezoidal Fuzzy Analytic Hierarchy Process and Set Pair Analysis

Studying the factors affecting machining accuracy, surface quality, and machining efficiency in the powerful honing machining process system, analyzing the basic law between various errors and machining quality, exploring the method of evaluating the quality of honing, and improving the machining quality and transmission performance of hardened gears has important engineering application value. Firstly, this paper establishes an effective abrasive grains micro-edge honing quality evaluation model, proposes a method based on the Trapezoidal Fuzzy Analytic Hierarchy Process (Tra-FAHP) and Set Pair Analysis (SPA) to comprehensively evaluate the quality of the honing process, and obtains the influence weights of each factor on the quality of honing. Secondly, the paper analyzes the influence rules of three types of abrasive grain sizes on helix error, tooth pitch error, tooth profile error, surface roughness, and honing efficiency. Finally, the correctness of the established comprehensive evaluation model of honing quality was verified with the threshold method and weights. The research results show that the model can correctly evaluate the quality of hardened gear honing and can be applied to studying the influence of abrasive grain micro-edge honing on machining characteristics.