Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management

Risk Evaluation and Attack Detection in Heterogeneous IoMT Devices Using Hybrid Fuzzy Logic Analytical Approach

The rapidly expanding Internet of Medical Things (IoMT) landscape fosters enormous opportunities for personalized healthcare, yet it also exposes patients and healthcare systems to diverse security threats. Heterogeneous IoMT devices present challenges that need comprehensive risk assessment due to their varying functionality, protocols, and vulnerabilities. Hence, to achieve the goal of having risk-free IoMT devices, the authors used a hybrid approach using fuzzy logic and the Fuzzy Analytical Hierarchy Process (FAHP) to evaluate risks, providing effective and useful results for developers and researchers. The presented approach specifies qualitative descriptors such as the frequency of occurrence, consequence severity, weight factor, and risk level. A case study with risk events in three different IoMT devices was carried out to illustrate the proposed method. We performed a Bluetooth Low Energy (BLE) attack on an oximeter, smartwatch, and smart peak flow meter to discover their vulnerabilities. Using the FAHP method, we calculated fuzzy weights and risk levels, which helped us to prioritize criteria and alternatives in decision-making. Smartwatches were found to have a risk level of 8.57 for injection attacks, which is of extreme importance and needs immediate attention. Conversely, jamming attacks registered the lowest risk level of 1, with 9 being the maximum risk level and 1 the minimum. Based on this risk assessment, appropriate security measures can be implemented to address the severity of potential threats. The findings will assist healthcare industry decision-makers in evaluating the relative importance of risk factors, aiding informed decisions through weight comparison.

Evaluating modern intrusion detection methods in the face of Gen V multi-vector attacks with fuzzy AHP-TOPSIS

The persistent evolution of cyber threats has given rise to Gen V Multi-Vector Attacks, complex and sophisticated strategies that challenge traditional security measures. This research provides a complete investigation of recent intrusion detection systems designed to mitigate the consequences of Gen V Multi-Vector Attacks. Using the Fuzzy Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), we evaluate the efficacy of several different intrusion detection techniques in adjusting to the dynamic nature of sophisticated cyber threats. The study offers an integrated analysis, taking into account criteria such as detection accuracy, adaptability, scalability, resource effect, response time, and automation. Fuzzy AHP is employed to establish priority weights for each factor, reflecting the nuanced nature of security assessments. Subsequently, TOPSIS is employed to rank the intrusion detection methods based on their overall performance. Our findings highlight the importance of behavioral analysis, threat intelligence integration, and dynamic threat modeling in enhancing detection accuracy and adaptability. Furthermore, considerations of resource impact, scalability, and efficient response mechanisms are crucial for sustaining effective defense against Gen V Multi-Vector Attacks. The integrated approach of Fuzzy AHP and TOPSIS presents a strong and adaptable strategy for decision-makers to manage the difficulties of evaluating intrusion detection techniques. This study adds to the ongoing discussion about cybersecurity by providing insights on the positive and negative aspects of existing intrusion detection systems in the context of developing cyber threats. The findings help organizations choose and execute intrusion detection technologies that are not only effective against existing attacks, but also adaptive to future concerns provided by Gen V Multi-Vector Attacks.

Interpretation of the coupling mechanism of ecological security and urbanization based on a Computation-Verification-Coupling framework: Quantitative analysis of sustainable development

In recent decades, China's rapid urbanization has produced numerous economic benefits while simultaneously creating substantial risks to ecological security. China's 14th Five-Year Plan and the United Nations Sustainable Development Goals (SDGs) have recently explicitly called for the coordinated development of ecological security and urbanization. Given this context, it is important to explore the mechanism by which ecological security and urbanization are coupled and coordinated to promote sustainable development. In this study, an index of the relationship between ecological security and urbanization was established via high-resolution data, and a "Computation-Verification-Coupling" (CVC) framework was constructed. The accuracy of the ecological security index was verified using a linear regression model, and the coordination level between ecological security and urbanization was analyzed via a coupled coordination model (CCM). The results revealed a steady increase in the ecological security index from 2010 to 2020; the proportion of the area above the medium level increased from 63.1 % to 74.1 %. The urbanization index in core counties exhibited rapid growth, with level V urbanized areas expanding from 5.5 % to 9.9 %. The ecological security verification model produced a coefficient of determination (R²) of 0.75685, indicating a satisfactory degree of predictive capability. From 2010-2020, the coupled coordination improved, with the high coordination area accounting for 48.8 % and the extreme discoordination area decreasing from 1.8 % to 1.0 %. Coordinated development exhibited a stable progression, characterized by a cyclical evolution from initial coupling to antagonistic coupling and finally to coordinated development. This framework can be used not only to investigate the relationship between ecological security and urbanization but also to provide a quantifiable measure of progress toward achieving the SDGs.

The development of national waqf index in Indonesia: A fuzzy AHP approach

As one of the alternative forms of Islamic Social Finance, Waqf could be potentially developed to achieve the Sustainable Development Goals in Indonesia, particularly providing a major solution for socio-economic problems, such as poverty, improving education quality, and giving a lifelong learning opportunity, unemployment, and many more. But, unfortunately, due to the absence of a universal standard of Waqf evaluation, the implementation of Waqf in Indonesia has not been optimal. Therefore, this study proposes the National Waqf Index (Indeks Wakaf Nasional or IWN) for improving the governance system and measuring waqf performance at national and regional levels. Through literature review and focus group discussion (FGD), this study develops six factors, namely regulatory (with three sub-factors), institution (with two sub-factors), process (with four sub-factors), system (with three sub-factors), outcome (with two sub-factors), and impact (with four sub-factors). Using the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) involving experts from government, academic, and industry, this study finds that the priority of IWN is a regulatory factor (0.282) followed by institution factor (0.251), process factor (0.190), system factor (0.156), outcome factor (0.069), and impact factor (0.050). The findings from this study will strengthen the existing literature in Waqf and be used to develop the governance system to improve performance.

Modeling the effect of emergency response on domino effects in the coal gasification process by fuzzy hierarchical analysis and Bayesian network

Emergency response has an important impact on the mitigation of the domino effects. However, consequence analysis of the domino effect often ignores emergency response due to its complexity and uncertainty. In this paper, Fuzzy Analytic Hierarchy Process (FAHP) is adopted to evaluate the reliability of emergency response process. On this basis, using Bayesian Network (BN) model, the domino effect under the influence of emergency response is modeled. Based on the total duration of the above-mentioned emergency response process to determine the consequences of domino effect under the action of safety barriers. The application of the approach has been demonstrated by an illustrative case study. The results show that the probability of domino effect is reduced by an order of magnitude when active barriers, passive barriers and emergency response are considered together. This work can provide relevant basis for formulating safety protection measures in chemical process industry.

Identifying Key Factors for Burnout Among Orthopedic Surgeons Using the Analytic Hierarchy Process Method

Objectives: To develop an evaluation model for, and identify key factors contributing to, burnout in orthopedic surgeons, providing a reference for the management of burnout among orthopedic surgeons in hospitals. Methods: We developed an analytic hierarchy process (AHP) model with 3 dimensions and 10 sub-criteria based on an extensive literature review and expert assessment. We used expert and purposive sampling and 17 orthopedic surgeons were selected as research subjects. The AHP process was then used to obtain the weights and to prioritize the dimensions and criteria for burnout in orthopedic surgeons. Results: The dimension of C ₁ (personal/family) was the key factor affecting burnout in orthopedic surgeons, and in the sub-criteria, the top four sub-criteria were C ₁₁ (little time for family), C ₃₁ (anxiety about clinical competence), C ₁₂ (work-family conflict), and C ₂₂ (heavy work load). Conclusion: This model was effective in analyzing the key factors contributing to job burnout risk, and the results can inform improved management of the levels of burnout affecting orthopedic surgeons in hospitals.

Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India

Objectives. Hospitals provide direct and indirect employment benefits to medical professionals. Accidents in hospitals often lead to disastrous consequences such as fatalities, property damage and economic losses. It is, therefore, imperative to have an occupational health and safety (OHS) policy that aims to reduce work-related accidents to acceptable levels. This study aims to investigate health risks to staff from various hazards and suggest control measures to prevent recurrence of accidents. Methods. A two-stage fuzzy multi-criteria decision-making (MCDM) approach incorporating the fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order preference for similarity to ideal solution (TOPSIS) was applied to assess the hazards in a leading multi-speciality hospital in Chennai. Results. The top three hazards identified in the workplace were electrical hazards, faulty medical equipment, and ventilation and air conditioning hazards. Subsequently, control measures were suggested to reduce the recurrence of hazards. Finally, a survey of hospital accidents occurring in India between 2010 and 2020 was conducted and compared with the results of this study. Conclusions. The survey findings show similarity to the hazard rankings obtained in this work, thus validating the methodology used for the assessment of hazards in hospitals. Electrical hazards and faulty medical equipment should be monitored.

Assessing the sustainable safety practices based on human behavior factors: an application to Chinese petrochemical industry

Sustainable and safe development is a key issue in petrochemical industry. However, many catastrophic accidents and irreversible environmental pollution have occurred in the petrochemical industry, most of which are caused by human behavior factor. The purpose of this paper is to evaluate and improve the sustainable safety performance of a petrochemical plant from the perspective of human behavior factors. Therefore, this study proposes an extended behavior-based safety (BBS) approach that combines the application of fuzzy analytic hierarchy process (FAHP) and fuzzy comprehensive evaluation (FCE) to assess sustainable safety performance of a petrochemical plant. The results show the importance of human behavior factors, and we should pay attention to the practical application of petrochemical industry. Finally, BBS management can reduce occupational injuries and accidents, which will enhance the sustainable safety development of the petrochemical industry.

Systematic Literature Review on Indicators Use in Safety Management Practices among Utility Industries

Background: Workers in utility industries are exposed to occupational accidents due to inadequate safety management systems. Accordingly, it is necessary to characterize and compare the available literature on indicators used in safety management practices in the utility industries. Methods: The systematic literature review was based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis statement. This study considered 25 related studies from Web of Science and Scopus databases. Results: Further review of these articles resulted in three mains performance indicators; namely, driven leading indicators, observant leading indicators, and lagging indicators consisting of 15 sub-indicators. Conclusions: Future studies should consider researching a more comprehensive range of utility industries, measuring subjective and objective indicators, integrating risk management into safety management practices, and validating the influence of leading indicators on safety outcomes. Further, researchers recommend including accidents, fatalities, lost time injuries, and near misses in safety outcomes.

Fuzzy AHP-Based Design Performance Index for Evaluation of Ferries

Within waterborne public transportation (WPT), one often observes a mismatch between the operational requirements and ferry characteristics. A method to holistically evaluate ferries with respect to local requirements could lead to tailored procurement and targeted refurbishment of existing fleet. In this study, we develop a structure for operational requirements and use it as a basis for a ferry evaluation methodology. The requirements’ structure follows a three-level hierarchy starting from broad vessel design to mandatory requirements to performance requirements. The performance requirements are based on the three pillars of sustainability, aided by commuter surveys carried out in Stockholm ferries, interviews with public transport providers (PTP) and previous literature. The evaluation of the ferry is performed using analytic hierarchic process (AHP) to convert the PTP’s subjective preferences and ferry performance into a single dimensionless index. Rules for quantification of performance metrics including social performance are proposed. The uncertainties associated with AHP are addressed by employing fuzzy AHP based on extent analysis and fuzzy AHP in combination with particle swarm optimization. Two applications including performance assessment of existing ferries and assembly of a modular ferry are discussed. The method can lead to objective decision making in ferry evaluation, potentially leading to a more efficient WPT.

Selection of suitable distance education platforms based on human–computer interaction criteria under fuzzy environment

The rapid spread of the COVID-19 pandemic has affected not only the health industry but also the education sector. E-learning systems have recently become a compulsory part of all education institutions, including schools, colleges, and universities worldwide because of the COVID-19 pandemic crisis. The objectives of the current study were twofold: (1) to conduct an analytical approach for ranking of distance education platforms based on human–computer interaction criteria and (2) to identify the most appropriate distance learning platform for teaching and learning activities by using multi-criteria decision-making approaches. Selection criteria were grouped into human–computer interaction-related criteria, such as ease of use, possibility of causing mental workload, user-friendly interface design, presentation method, and interactivity. In the selection procedure, a spherical fuzzy extension of Analytical Hierarchy Process was utilized to identify the weights of selection criteria and to rank distance education platforms. The results revealed that the most important criterion was the possibility of causing mental workload while the most preferable e-learning system was identified as “A3”.

Reducing Waste in Healthcare through Occupational Safety and Health Measures: A Study of Manufacturing Industries in Taiwan

Occupational accidents and diseases cause the loss of valuable workers and lead to high healthcare expenses. Because occupational accidents and diseases are ascribed to inadequate working conditions and work environments, they can be prevented through a well-established occupational safety and health management system, which can ensure workers' health and reduce the expense of healthcare. The study investigated the shortage of work-related occupational safety and health (OSH) measures in medium-sized manufacturing industries. This study mainly focused on qualitative interviews with 15 labor inspectors and 25 business executives from OSH participating to investigate the problems of occupational safety and health in the manufacturing industries in Taiwan. The results of a qualitative study show that the most important problems with OSH management are employers' negligence and workers' insufficient knowledge about OSH management. The research results revealed the following eighteen significant shortcomings of OSH management: employers care mostly about production profit and do not care much for OSH; OSH data collection and OSH planning are not suitable for the workplace; many managers of OSH affairs are not qualified, in terms of their professional or academic backgrounds; and the repair of workplaces' roofs often results in falling accidents, especially before or after a typhoon, because of workers' failure to use safety belts and/or to follow OSH guidelines. In order to address the shortcomings and bottlenecks, the study also presented recommendations for how to implement and revise the OSH Act and how to research and enhance OSH management. The results of this study will not only supply the Ministry of Labor (Taiwan) with data to plan the strategy of OSH management but also will allow employers and workers to improve OSH management in the workplace in order to prevent the occurrence of occupational accidents.

Evaluation of Ergonomics-Related Disorders in Online Education Using Fuzzy AHP

The aim of the presented work is to analyze the ergonomics-related disorders in online education using the fuzzy AHP approach. A group dialogue with online education academicians, online education students, biotechnologists, and sedentary computer users has been performed to spot ergonomics-related disorders in online education. Totally eight ergonomics-related disorders in online education have been identified, and the weight of each disorder has been computed with triangle-shaped fuzzy numbers in pairwise comparison. Furthermore, the ergonomics-related disorders in online education are kept in four major categories such as afflictive disorders, specific disorders, psychosocial disorders, and chronic disorders. These four categories of ergonomics-related disorders in online education are evaluated and compared using fuzzy analytical hierarchical process methodology to get ranked in terms of priorities. The results may be instrumental for taking appropriate corrective actions to prevent ergonomics-related disorders.

Modeling of occupational safety and health factors in production organizations and the formation of measuring scales of occupational safety climate

This article explores the impact of the main occupational safety and health (OSH) factors in the overall OSH climate of production organizations in the territory of the Republic of Serbia, South Serbia, as an important segment of their strategic development. The article aims to validate and test the proposed conceptual model of OSH. Hence, the SmartPLS methodology was applied. Statistical analysis was performed using SPSS version 21.0. The hypothesized model was developed and tested on a sample of 871 participants employed in production companies. The results indicate that the development of an OSH climate in production organizations primarily depends on the commitment of the management to the OSH system. The results obtained indicate that the methods used in this research can be successfully used in order to identify the OSH factors in the work process, and thus to manage the quality of the work environment.

Study of roof water inrush forecasting based on EM-FAHP two-factor model

To solve the problem of predicting and evaluating coal mine roof water inrush accidents, based on the background of Hongliu coal mine, the relevant weight values of the main control factors of water inrush were determined based on the water-richness index method, combined with the entropy method and FAHP two-factor method. The grid processing function of GIS and the kriging interpolation method are used to draw thematic maps of the main controlling factors, and the weight values of the water permeability indicators are coupled into the GIS. The FLAC^3D numerical simulation software is used to analyze the water-conducting fracture zone after the mining of the Hongliu Coal Seam numerical simulation of development and water pressure distribution changes. The results show that the permeability hazard zoning map obtained by the EM-FAHP two-factor model is in line with the results of the damage height and the increased water pressure zone obtained by the numerical simulation.

A novel machine learning application: Water quality resilience prediction Model

Resilience-informed water quality management embraces the growing environmental challenges and provides greater accuracy by unpacking the systems' characteristics in response to failure conditions in order to identify more effective opportunities for intervention. Assessing the resilience of water quality requires complex analysis of influential parameters which can be challenging, time consuming and costly to compute. It may also require building detailed conceptual and/or physically process-based models that are difficult to build, calibrate and validate. This study utilises Artificial Neural Network (ANN) to develop a novel application to predict water quality resilience to simplify resilience evaluation. The Fuzzy Analytic Hierarchy Process method is used to rank water basins based on their level of resilience and to identify the ones that demand prompt restoration strategies. The commonly used 'magnitude * duration of being in failure state' quantification method has been used to formulate and evaluate resilience. A 17-years long water quality dataset from the 22 water basins in the State of São Paulo, Brazil, was used to train and test the ANN model. The overall agreement between the measured and simulated WQI resilience values is satisfactory and hence, can be used by planners and decision makers for improved water management. Moreover, comparative analyses show similarities and differences between the 'level of criticalities' reported in each zone by Environment Agency of the state of São Paulo (CETESB) and by the resilience model in this study.

Analytic Hierarchy Process-Based Airport Ground Handling Equipment Purchase Decision Model

The Airport ground handling services (AGHS) equipment supplier provider selection requires a safety guarantee in terms of the daily operations AGHS provider. AGHS providers seek to avoid aircraft damage and airline delays and ensure the provision of reliable and high-quality services. The primary objective of this paper was to develop purchasing decision model of the analytic hierarchy process (AHP), AHP-fuzzy linear programming (FLP), and AHP-Taguchi loss function (TLF) multi-choice goal programming (MCGP) purchase decision models to help the AGHS purchasing managers in selecting the best AGHS equipment supplier provider. The constructed models were assessed, and results obtained for the AHP-FLP and AHP-TLF-MCGP models were compared. We conducted a real-world example of supplier selection by an AGHS company by using the proposed models. The proposed model provides useful information and has practical value for AGHS providers.

Supplier evaluation with order allocation in mega-projects

Purpose

The purpose of this study is to provide a model for evaluating, prioritizing and allocating orders to suppliers in the supply chain for mega-projects.

Design/methodology/approach

By using an integrated model (based on fuzzy analytic network process), suppliers are selected and the appropriate amounts are allocated to them in mega-projects. Initially, a hierarchical model of the research method was introduced. Then, the results on reliability and validity analysis of research measurement tools were presented. Finally, prioritization and allocation of orders to suppliers, with a case study of Iran Mall project, was carried out using Decision Making Trial and Evaluation Laboratory (DEMATEL) and analytic network process (ANP). T-test was used to evaluate the research hypotheses.

Findings

The findings were examined against conventional numerical analysis techniques. Finally, implication and recommendations for future work were presented.

Originality/value

The originality of this work is about using multi-criteria decision-making techniques for evaluating suppliers in mega-projects.

Comparison of Fuzzy AHP and AHP in Multicriteria Inventory Classification While Planning Green Infrastructure for Resilient Stream Ecosystems

As climate change-induced weather variability increases, various green infrastructure plans, such as stream ecosystems, have been studied to overcome ecological and environmental problems arising from extreme weather events; however, our understanding of them and their resilience to extreme weather events is considerably limited. This study proposes a multicriteria inventory classification while planning green infrastructure for resilient stream ecosystems under extreme weather events. Literature reviews, expert surveys, and reliability/validity analyses were used to enlist indicators for this classification. The analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (fuzzy AHP) were used to compute the weights and ranks of indicators for identifying critical indices while planning green infrastructure. The AHP and fuzzy AHP analysis suggested that meteorological phenomena and disasters, hydraulic characteristic of streams, land use/geographic characteristics, and experience/damage restoration were important factors. High weights were attributed to aquatic ecology, potentially vulnerable areas, population, topography, and heat waves. The weights and ranks attributed by AHP and fuzzy AHP varied slightly, but the indicator groups with high and low weights were the same; hence, primary indicators to be considered while planning green infrastructure for resilient stream ecosystems could be suggested. These results could be used as a preliminary analysis in establishing countermeasures against climate change or in distributing budgets for green infrastructure plans.

Flight safety assessment based on an integrated human reliability quantification approach

Human error is an important risk factor for flight safety. Although the human error assessment and reduction technique (HEART) is an available tool for human reliability derivation, it has not been applied in flight safety assessment. The traditional HEART suffers from imprecise calculation of the assessed proportion of affect (APOA) because it heavily depends on a single expert’s judgment. It also fails to provide remedial measures for flight safety problems. To overcome these defects of the HEART, this study proposes an integrated human error quantification approach that uses the improved analytic hierarchy process method to determine the APOA values. Then, these values are fused to the HEART method to derive the human error probability. A certain flight task is completed to assess human reliability. The results demonstrate that the proposed method is a reasonable and feasible tool for quantifying human error probability and assessing flight safety in the aircraft manipulation process. In addition, the critical error-producing conditions influencing flight safety are identified, and improvement measures for high-error-rate operations are provided. The proposed method is useful for reducing the possibility of human error and enhancing flight safety levels in aircraft operation processes.

Analyzing the Importance of Driver Behavior Criteria Related to Road Safety for Different Driving Cultures

Driver behavior has been considered as the most critical and uncertain criteria in the study of traffic safety issues. Driver behavior identification and categorization by using the Fuzzy Analytic Hierarchy Process (FAHP) can overcome the uncertainty of driver behavior by capturing the ambiguity of driver thinking style. The main goal of this paper is to examine the significant driver behavior criteria that influence traffic safety for different traffic cultures such as Hungary, Turkey, Pakistan and China. The study utilized the FAHP framework to compare and quantify the driver behavior criteria designed on a three-level hierarchical structure. The FAHP procedure computed the weight factors and ranked the significant driver behavior criteria based on pairwise comparisons (PCs) of driver's responses on the Driver Behavior Questionnaire (DBQ). The study results observed "violations" as the most significant driver behavior criteria for level 1 by all nominated regions except Hungary. While for level 2, "aggressive violations" is observed as the most significant driver behavior criteria by all regions except Turkey. Moreover, for level 3, Hungary and Turkey drivers evaluated the "drive with alcohol use" as the most significant driver behavior criteria. While Pakistan and China drivers evaluated the "fail to yield pedestrian" as the most significant driver behavior criteria. Finally, Kendall's agreement test was performed to measure the agreement degree between observed groups for each level in a hierarchical structure. The methodology applied can be easily transferable to other study areas and our results in this study can be helpful for the drivers of each region to focus on highlighted significant driver behavior criteria to reduce fatal and seriously injured traffic accidents.

Exploring the Role of Advertising Types on Improving the Water Consumption Behavior: An Application of Integrated Fuzzy AHP and Fuzzy VIKOR Method

In recent years, many cities have suffered from a shortage of drinking water, mainly due to population growth. Hence, the desire to curb undue water consumption through the identification of the main factors affecting consumer behavior has become very important in managing drinking water supplies. Modifying the consumption pattern means institutionalizing of a sustainable culture in water consumption among consumers and the identification of the main criteria affecting their behavior. In 2018, a survey was applied to examine the role of mass media advertising in modifying the water consumption pattern in Iran. An integration of fuzzy AHP and fuzzy VIKOR was proposed based on group decision making, and fuzzy trapezoidal sets used to model linguistic variables and to deal with uncertainty in opinions. We devised and conducted a questionnaire with 24 main criteria and 8 sub-criteria to measure the impact of advertising on water consumption. The case study population in this study included all urban households over 15 cities of Iran. A total of 5630 questionnaires were distributed among the various populations with cluster method. Then, by analyzing the results, advertisements using animation had the highest impact on consumer behavior, among the available alternatives, and could play a significant role in modifying the water consumption pattern. Additionally, a fuzzy evaluation technique is performed to validate the result of the applied method. Subsequently, a sensitivity analysis was conducted to validate the stability of the final ranking. Finally, the prioritization results of the types of advertising by the proposed method were compared with the results of the fuzzy AHP method.

Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept

In this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the computational strength of the Fuzzy Weighted Average (FWA) based on left and right scores in order to obtain aggregates for the design alternatives considering the relative importance of the design criteria as needed in the optimal design. The model was applied to evaluate four design concepts of a RAF with six design features having numerous sub-features. Results obtained from the evaluation process shows that there are differences in final values of the design alternatives. However, a close variation exists between these values. These differences can be accrued to the interrelationships between the design features and sub-features obtained from the Fuzzy Synthetic Extent (FSE) of the FAHP and an unambiguity judgment of the FWA when aggregating availability of the design features and sub-features in the design alternatives.

Comparing the alternatives for the most favourable personal protective equipment

Evaluation of personal protective equipment is a very demanding task in designing an effective workplace safety programme. There is variable equipment to prevent job accidents, to protect workers' health and safety and to minimize the damage of any possible accident. Comparing the alternatives for the most favourable equipment, e.g. possible high noise levels, is one of the most difficult issues to deal with. In this study, the analytic hierarchy process method allows selection of personal protective equipment analytically, which is used to decide on efficient personal protection equipment when choosing protective shoes, helmets, earmuffs and dust masks.

Factors that Sustain Health and Safety Management Practices in the Food Industry

Due to the significant change in business organizations, scholarly interest has diverted from studying the determinants of financial performance to understanding the environmental activities, sustainability practices, and health and safety management practices. Despite the extensive literature, it is yet to understand either internal or external factors that improve health and safety management practices in SMEs. This research examines the influence of the internal factors—intellectual capital, information technology capabilities (ITC), and entrepreneurial orientation, and the external capabilities—government financial support, institutional pressure, and managerial networking on six health and safety management practices: management commitment, staff training, worker involvement, safety communication and feedback, safety rules and procedures, and safety promotion policies. We researched 410 Pakistani SMEs from the food business industry. The results indicate that intellectual capital significantly improves management commitment, safety communication and feedback, and safety rules and produces; ITC significantly improves management commitment and safety communication and feedback; and entrepreneurial orientation significantly facilitates safety training and worker involvement only. In the external capabilities, government financial support has a significant influence on management commitment, worker involvement, safety rules and policies, and safety promotion policies. Institutional pressure has a significant influence on management commitment, safety training, safety communication, and feedback and safety promotion policies. Managerial networking significantly influences safety training, worker involvement, safety rules and procedures, and safety promotion policies of SMEs. Focusing only on the food industry is the major limitation of this research, this study recommends SMEs to give sufficient attention to their internal and external factors to enhance health and safety management practices. Further implications are discussed.

Quantitative assessment of enterprise environmental risk mitigation in the context of Na-tech disasters

As an important causative factor of environmental accidents, natural disasters have recently received much attention for environmental risk assessment. Typhoons are one of the most frequent natural disasters in the northern Pacific Ocean and South China Sea and cause enormous damage to agriculture, daily livelihood, and industry. In this study, an environmental risk assessment for industrial enterprises is conducted when considering typhoon disasters. First, a Na-tech (natural hazard triggering technological disasters) environmental risk assessment index system with the aid of an analytic hierarchy process and fuzzy evaluation model (ERA-FAM) is developed to explore the major determinants related to risk level. The impact of typhoon disasters on environmental risk from chemical enterprises is discussed using a comparative analysis of risk levels with and without typhoon disaster scenarios. A chemical plant located in Zhejiang, China, is selected as a case study using this methodology. Three hypothetical scenarios are assumed, based on actual situations, to explore the impact of various factors on environmental risk. The results demonstrate that production factors and surrounding environmental conditions are the most sensitive factors for typhoon disasters, while emergency preparation is most important for reducing environmental risk. The influence of typhoons on environmental risk values is much higher for enterprises with imperfect management and vulnerable water risk receptors. Incorporating disaster management into environmental risk management will aid in developing strategies and policies for environmental risk mitigation and risk reduction practices.

Evaluating Safety Systems for Machine Tools with Computer Numerical Control using Analytic Hierarchy Process

Computer numerical control (CNC) machine tools are complex production systems with fully automatic machine parts. Nowadays, high feed rates and machining speeds are used during the machining process. Human operators are still needed to set-up the machine, load/unload workpieces and parts, load the machining code, and supervise the machining process. The operators work in an environment where automated high-speed motions occur, and consequently, CNC machine tools have to be equipped with safety systems. The approach presented in this paper was to evaluate the main safety systems of CNC machine tools based upon the analytic hierarchy process (AHP). The analyzed systems were divided into six main categories and compared pairwise using five criteria proposed by the authors. The approach and the obtained results significantly relied upon the situation found at the industrial company used as a benchmark for the research. The analysis reveals that, among considered safety devices, manually operated controls are the most efficient ones. Finally, a sensitivity analysis was conducted to test the stability of the AHP solution.

Predicting changing pattern: building model for consumer decision making in digital market

Purpose

Consumers have the multiple options to choose their products and services, which have a significant impact on the pattern of consumer decision making in digital market and further increases the challenges for the service providers to predict their buying pattern. In this sense, the purpose of this paper is to propose a structural hierarchy model for analyzing the changing pattern of consumer decision making in digital market by taking an Indian context.

Design/methodology/approach

To accomplish the objectives, the research is conducted in two phases. An extensive literature review is performed in the first phase to list the factors related to the changing pattern of consumer decision making in digital market and then fuzzy Delphi method is applied to finalize the factors. In the second phase, fuzzy analytic hierarchy process (AHP) is employed to find the priority weights of finalized factors. The fuzzy set theory allows capturing the vagueness in the data.

Findings

The findings obtained in this study shows that consumers are much conscious about innovative and trendy products as well as brand and quality; therefore, the service providers must think about these two most important factors so that they can able to retain their consumer in their online portal.

Practical implications

The analysis shows that “innovative and trendy” is the first priority factor for the consumers followed by “brand and quality” and “fulfilment and time energy.” The proposed model can help the marketers and service providers in predicting customers’ preferences and their changing pattern efficiently under vague surroundings. The outcomes of this research work not only help the service provider to update their products and services according to consumers’ needs but can also help them to increase profit and minimize their risk.

Originality/value

This work contributes to consumer research literature focusing on problem evaluation in the context of changing pattern of consumer decision making in digital era.

An analysis of the factors affecting the adoption of cloud consumer relationship management in the machinery industry in Taiwan

In recent years, cloud computing services have developed rapidly and are being widely used, but most applications focus on consumers. However, a few successful cases of enterprise application systems have been constructed and adopted by companies. To understand the factors that affect the adoption by a company of cloud Customer Relationship Management (CRM), which is an enterprise application system, this study used a Technology Organization Environment Framework (TOE) as a theoretical framework, reviewed related literature on the relevant factors affecting the adoption of a cloud service, and then constructed a three-level hierarchical table of the factors. A pairwise comparison questionnaire was then designed and issued to top managers of firms in the machinery industry in Taiwan that have adopted cloud CRM. A fuzzy analytical hierarchy process (FAHP) was then used to calculate the weights of the factors, based on the returned questionnaires. The results show that enterprises in the machinery industry gave priority to the factor, ‘support of senior managers’, followed by the factors ‘organizational policies’ and ‘system information security’. Some implications of the findings are discussed, which can serve as a guide for the successful adoption of cloud CRM in machinery industry if firms allocate their resources appropriately to these important factors. These results can also be used by the service providers of cloud CRM to devise effective marketing strategies.

The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process

Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timely manner. Delayed diagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For this reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there have been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent diagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and anthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA severity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized weight vector. The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime symptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%, and 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA group. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also recommended (sensitivity = 87.12% and specificity = 72.22%).

Safety management practices in small and medium enterprises in India

Background

Small and medium enterprises (SMEs) are often the main pillar of an economy. Minor accidents, ergonomics problems, old and outdated machinery, and lack of awareness have created a need for implementation of safety practices in SMEs. Implementation of healthy working conditions creates positive impacts on economic and social development.

Methods

In this study, a questionnaire was developed and administered to 30 randomly chosen SMEs in and around Mumbai, Maharashtra, and other states in India to evaluate safety practices implemented in their facilities. The study also looked into the barriers and drivers for technology innovation and suggestions were also received from the respondent SMEs for best practices on safety issues.

Results

In some SMEs, risks associated with safety issues were increased whereas risks were decreased in others. Safety management practices are inadequate in most SMEs. Market competitiveness, better efficiency, less risk, and stringent laws were found to be most significant drivers; and financial constraints, lack of awareness, resistance to change, and lack of training for employees were found to be main barriers.

Conclusion

Competition between SMEs was found to be major reason for implementation of safety practices in the SMEs. The major contribution of the study has been awareness building on safety issues in the SMEs that participated in the project.