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This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.

Prior research has emphasised the importance of the early phases of construction projects, as well as the difficulties of procuring engineering services – especially due to the uncertainties. Despite that, studies on the public procurement of engineering services are scarce. Although scholars have shown that uncertainty may affect the choice of control modes, the level of uncertainty that characterises services is not addressed by the two task characteristics: knowledge of the transformation process and output measurability. The purpose is to investigate organisational control in public procurement of engineering services.

The existing control model was adjusted in this study by conceptually adding uncertainty as a third aspect to the two task characteristics. A single case study of the Swedish Transport Administration was used. The empirical data, comprising 14 interviews with managers from the client and engineering consulting companies, were analysed using flexible pattern matching and visual mapping approaches and then illustrated using the model.

The public client did not base its choice of control modes on uncertainty, but rather on the other two task characteristics. Consequently, the service providers argued that the chosen control modes reduced their creativity, increased their financial risks and caused unclear responsibilities. This study therefore shows that uncertainty is an important factor to consider in the choice of control modes, both from a theoretical perspective and from the service providers' point of view. The developed model may therefore be useful for researchers as well as practitioners.

This study is the first attempt to add uncertainty as a task characteristic when choosing control modes. The results contribute to the scarce control literature regarding the procurement of engineering services for construction projects and the procurement of other services with high uncertainty.

This study aims to focus on the sustainability of prefabricated medical emergency buildings (PMEBs) renovation after the epidemic, to address the problem that large numbers of PMEBs may be abandoned for losing their original architectural functions. This study develops an evaluation system to identify and measure sustainable factors for PMEBs’ renovation schemes. Qualitative and quantitative analysis of PMEBs’ renovation scheme was conducted based on cloud model evaluation method and selected the renovation scheme in line with sustainable development. The study promotes evaluation methods and decision-making basis for the renovation design of global PMEBs and realizes the use-value of building functions again.

By referring to the existing literature, design standards and expert visiting a set of evaluation index systems which combines the renovation of the PMEBs and the sustainability concept has been established, which calculates the balanced optimal comprehensive weight of each indicator utilizing combination weighting method, and quantifies the qualitative language of different PMEBs’ renovation schemes by experts through characteristics of the cloud model. This paper takes Huoshenshan hospital a representative PMEB during the epidemic period as an example, to verify the feasibility of the cloud model evaluation method.

The research results of this paper are that in the PMEBs’ renovation scheme structural reformative (T11) and corresponding nature with the original building (T13) have the most important influence; the continuity of architectural cultural value (T22) and regional development coherence (T23) are the key factors affecting the social dimension; the profitability of renovated buildings (T34) is the key factor affecting the economic dimension; the environmental impact (T41), resource utilization (T42) and ecological technology (T43) are the key factors in the environmental dimension.

This study contributes to the existing body of knowledge by supplementing a set of scientific evaluation methods to make up for the sustainability measurement of PMEBs’ renovation scheme. The main objective was to make renovated PMEBs meet the needs of urban sustainable development, retain the original cultural value of the buildings, meanwhile enhance their social and economic value and realize the renovation with the least impact on the environment.

User behavior in online information evaluation is the result of a multitude of factors related to social, cultural, personal and psychological issues. The present study aimed to examine the effects of three important psychological variables including personality, self-efficacy and attitude on online information evaluation.

Four validated measures were administrated in person and online among 355 postgraduate students at Shahed University, Tehran, Iran. For testing the possible relationships among the variables, the reliability, normality and Pearson correlation tests were performed by using SPSS 24.0. Moreover, to test the ten hypotheses of the research, the structural equation modeling was considered using AMOS 26.0.

The findings confirmed the first five research hypotheses indicating the direct positive relationships among the four variables except for the impact of self-efficacy on attitude. The mediated effects of the variables were not supported except for the mediating role of attitude in the impact of personality on online evaluation behavior. The variable personality was found to be fundamental among the tested paths because it influenced the information evaluation behavior, both directly and indirectly.

The study showed the impacts of the three variables, which demonstrates that online information evaluation is greatly affected by psychological factors.

This study aims to assess the readiness of both citizens and the government for digital participatory planning (DDP) as a contribution to the undergoing transformative shift toward smart and sustainable cities to address the challenges posed by rapid urbanization. While much attention has been devoted to leveraging technology to mitigate these challenges, there has been a relative lack of emphasis on engaging stakeholders in the planning process in a smart and inclusive manner. DPP stands as a cornerstone for the development of sustainable and smart cities. However, before DPP can be effectively implemented on the ground, it is crucial to assess the city readiness for DPP to ensure its success. This assessment is undertaken as part of Oman's broader initiative to transition into sustainable smart cities in alignment with the goals outlined in Oman Vision 2040.

A generic evaluation framework was identified, validated and customized to the local context by experts using the pile sorting technique based on the social constructivism theory. Then, the revised framework was used to evaluate the readiness of a sample of local citizens and government officials in Oman for the DPP concept.

The inferential statistical analysis revealed that citizens are willing to participate in DPP when trust and transparency with policymakers are enhanced. On the government side, the results showed that there is adequate infrastructure that can enable DPP, and planners have a positive attitude toward DPP provided that trust in citizens' opinions is strengthened. This study concludes with a roadmap for preparation for DPP implementation in smart sustainable cities mandated by Oman Vision 2040. The findings and roadmap can inform policy development, decision-making and urban planning practices toward more inclusive, participatory and technologically enabled urban environments.

The study contributes to the existing body of knowledge by emphasizing the significance of stakeholders' smart involvement in planning processes, social sustainability, evaluating city readiness for DPP and providing practical recommendations for DPP implementation in the context of smart sustainable cities. At a theoretical level, the study contributes a framework for assessing readiness for DPP and emphasizes that mutual trust is not only important for conventional participation practices but it is also essential for smart citizens. This study argues that a building or a city is not sustainable unless it is seen as such by its stakeholders, including the end users. Therefore, effective and smart involvement of the citizens in smart city planning is a precondition for the success of the future cities.

The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.

This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.

The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.

By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.

This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

This paper examines the ways in which Chinese university middle managers evaluate subordinate performance in response to the Chinese Double First-Class University Plan, a national project that ranks the performance of universities. In exploring compromise arrangements, the hybridised valuing activity of middle managers is found to be shaped by emergent and extant macro-foundations.

The qualitative data from 49 semi-structured interviews at five Chinese public universities were conducted. Drawing on macro-foundational studies and the sociology of worth (SW) theory, the analysis helps to identify socially shared patterns of actions and outcomes.

The findings elucidate the interplay between diverse economic, social, political and institutional values and the compromise-making by middle managers. The authors find that contextual factors restrict Chinese academic middle managers' autonomy, preventing workable compromise. Through the selective adoption of international and local management practices, compromise has evolved into a private differential treaty at the operational level.

A nuanced explanation reveals how the macro-foundations of Chinese society influence middle managers who engage with accounting when facilitating compromise. This study helps outsiders better understand the complex convergence and divergence of performance evaluative practices in Chinese universities against the backdrop of global market-based forces and the moral dimensions of organisational life. The findings have wider implications for the Chinese government in navigating institutional steps and developing supportive policies to enable middle managers to advance productive but also sustainable compromise.