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As tower cranes are highly dangerous, the problem of insufficient investment in tower safety needs to be solved urgently, and this study aims to solve the problem of insufficient investment in safety caused by the imbalance of interests of tower safety-related subjects and to propose targeted solutions.

Tower crane rental enterprises, contractors and government departments are selected to construct the game model, calculate the equilibrium point and stability and determine the optimal stabilization strategy. Finally, MATLAB software is used to model and simulate the impact of parameter changes on each party’s choice of strategies.

(1) The optimal combination of strategies is safety input by tower companies, leasing of qualified towers by contractors and providing non-financial incentives by the government. (2) The degree of synergistic coefficient γ, the level of government penalty coefficient α and the increase in accident probability p positively affect the adoption of proactive safety measures by tower crane leasing enterprises and contractors. (3) Excessive differences in safety costs may lead firms to adopt hostile safety measures.

This paper creatively uses safety input and tower crane leasing enterprises as the perspective and object of research on tower security. The research results are of great significance in guiding the government to formulate regulatory and incentive policies and in promoting enterprises to implement safety input to ensure construction safety collaboratively. It also provides new research cases for promoting the entire special equipment industry to realize adequate and effective safety input.

The purposes of this study were (1) to explore empirical challenges in dimensioning safety buffers and their implications and (2) to organise those challenges into a framework.

In a multiple-case study following an exploratory, qualitative and empirical approach, 20 semi-structured interviews were conducted in six cases. Representatives of all cases subsequently participated in an interactive workshop, after which a questionnaire was used to assess the impact and presence of each challenge. A cross-case analysis was performed to situate empirical findings within the literature.

Ten challenges were identified in four areas of dimensioning safety buffers: decision management, responsibilities, methods for dimensioning safety buffers and input data. All challenges had both direct and indirect negative implications for dimensioning safety buffers and were synthesised into a framework.

This study complements the literature on dimensioning safety buffers with qualitative insights into challenges in dimensioning safety buffers and implications in practice.

Practitioners can use the framework to understand and overcome challenges in dimensioning safety buffers and their negative implications.

This study responds to the scarcity of qualitative and empirical studies on dimensioning safety buffers and the absence of any overview of the challenges therein.

There are rising issues with the delivery performance of Malaysian low-cost housing (LCH) because the occupants are inclined to perceive safety hazards. Among the safety issues raised during the occupancy period in LCH are structural instability and falling building fragments. Without defining the occupants’ requirements in the early housing development, it is hard to determine the prevailing safety factors. Hence, this paper emphasises the application of post occupancy evaluation (POE) that incorporates participation from the occupants as a tool to assess the safety performance of Malaysian LCH. The purpose of this study is to develop a framework of POE integrated with safety elements for Malaysian LCH.

This research was carried out with a quantitative method using questionnaires as the survey instrument involving safety inspection survey and satisfaction surveys. The inspection survey and Occupants’ Satisfaction Survey were carried out based on 24 LCH projects located in the federal territory of Kuala Lumpur, Malaysia. In total, 380 samples were used for both surveys. Statistical correlation was used to affirm the incorporation of occupants’ participation towards safety performance in the POE approach. The Spearman’s rho (r) correlation was used in the analysis for variables in both surveys which consisted of an ordinal scale.

The correlation result revealed that there was a significant relationship among all safety attributes between safety performance and occupants’ satisfaction. Therefore, a framework consisting of POE and safety elements has been proposed based on the significance of both variables. The development process of the framework used the vital phases of POE and inputs of safety elements which consisted of three main stages: planning phase as safety input, conducting phase as safety process and applying phase as safety output.

The surveys were limited to the rented People’s Housing Programme located in Kuala Lumpur and not extensively to all LCH programmes in Malaysia. The surveys were also not carried out to other LCH programmes such as the Hardcore Poor Housing Programmes and the low- to medium-cost housing because of the limitations of time and resources.

This research has introduced a new dimension for safety performance assessment in LCH using the POE as the safety performance tool. By allowing the participation of occupants for safety assessment, this study stresses the fundamental concept of POE by highlighting the importance of obtaining feedback from the building occupants.

As a proactive measure, the proposed framework was introduced as an improved procedure to inspect safety performance in LCH during occupancy, in lieu of the current assessment process. Receiving complaints from the occupants after the occurrence of incidents is demarcated as a reactive approach, whereas the current inspection survey does not incorporate the occupants’ participation. Feedback from occupants is not a routine of building assessment during occupancy; hence, using POE is generally a new dimension of safety performance in Malaysian LCH.

To improve unsafe workplace of Chinese SMEs, this paper aims to use the multi-agent simulation experiment to reveal the relationship between employees’ safety voice and safety level of enterprises.

Through simulation of employees’ safety voice activities, enterprises’ production activities, enterprises’ safety activities, an experiment platform is built. The experiment introduces external variable of labor resource and sets four experimental situations considering whether labor resource is sufficient and whether employees’ value is significant.

The result shows that not all the employees’ safety voice can change small- and medium-sized enterprises’ safety level. When there is sufficient labor supply, employee safety voice cannot improve the safety level of enterprises; when there is short of labor and employee safety voice is strong, safety level can be effectively improved. When employees have the strikingly different value variance, safety voice of common employees cannot improve safety level of enterprises, but employee safety voice with high value can improve safety level.

This fully provides that under the circumstances of disappearing demographic dividend in China, improving employees’ safety awareness and reasonably using their safety voice can boost SMEs to enhance safety level.

Workers' unsafe behavior is the main cause of construction safety accidents, thereby highlighting the critical importance of behavior-based management. To compensate for the limitations of computer vision in tackling knowledge-intensive issues, semantic-based methods have gained increasing attention in the field of construction safety management. Knowledge graph provides an efficient and visualized method for the identification of various unsafe behaviors.

This study proposes an unsafe behavior identification framework by integrating computer vision and knowledge graph–based reasoning. An enhanced ontology model anchors our framework, with image features from YOLOv5, COCO Panoptic Segmentation and DeepSORT integrated into the graph database, culminating in a structured knowledge graph. An inference module is also developed, enabling automated the extraction of unsafe behavior knowledge through rule-based reasoning.

A case application is implemented to demonstrate the feasibility and effectiveness of the proposed method. Results show that the method can identify various unsafe behaviors from images of construction sites and provide mitigation recommendations for safety managers by automated reasoning, thus supporting on-site safety management and safety education.

Existing studies focus on spatial relationships, often neglecting the diversified spatiotemporal information in images. Besides, previous research in construction safety only partially automated knowledge graph construction and reasoning processes. In contrast, this study constructs an enhanced knowledge graph integrating static and dynamic data, coupled with an inference module for fully automated knowledge-based unsafe behavior identification. It can help managers grasp the workers’ behavior dynamics and timely implement measures to correct violations.

At present, the statistics of human error events in domestic civil aviation are limited, and the analysis indicators are difficult to quantify. The purpose of this study is to reduce the incidence of human error events and improve the safety of civil aviation.

In this paper, a safety prevention evaluation method combining analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) is proposed. The risk factors of civil aviation safety are identified through questionnaire survey and calculated by MATLAB software.

The results of the study are as follows: a safety risk evaluation index system including 4 first-level indicators and 16 second-level indicators is constructed; the AHP is used to calculate the weight of the influencing factors of human error and sort them; and the FCE method is used to quantitatively evaluate the safety prevention of civil aviation human error and put forward the countermeasures.

This study also has some limitations. While it provides an overall quantitative identification of civil aviation safety risk factors, the research methods chosen, such as the questionnaire survey method and the AHP, involve individual subjectivity. Consequently, the research results may have errors. In the preliminary preparation of the follow-up study, we should analyze a large number of civil aviation accident investigation reports, more accurately clarify the human error factors and completely adopt the quantitative analysis method in the research method.

This study identifies the risk factors of civil aviation safety and conducts a reasonable analysis of human error factors. In the daily training of civil aviation, the training can be focused on previous man-made accidents; in view of the “important” influencing factors, the aviation management system is formulated to effectively improve the reliability of aviation staff; according to the evaluation criteria of human error in civil aviation, measures to prevent and control accidents can be better formulated.

In view of these four kinds of influencing factors, the corresponding countermeasures and preventive measures are taken according to the discussion, so as to provide the basis for the prevention of aviation human error analysis, management and decision-making, prevent the risk from brewing into safety accidents and improve the safety of aviation management.

Based on the questionnaire survey, this study creatively applies the safety prevention evaluation method combining AHP and FCE to the study of civil aviation human error, integrates the advantages of qualitative and quantitative methods, flexibly designs qualitative problems, objectively quantifies research results and reduces subjective variables. Then, by discussing civil aviation safety management measures to avoid risk factors, reduce the incidence of human error events and improve the safety of civil aviation.

For strategic and competitive insights, the purpose of this paper is to measure and benchmark the comparative operating efficiencies of Association of Southeast Asian Nations’ (ASEAN) major airlines and present a new interpretation along with managerial implications.

This research statistically tests returns to scale and the equality of mean efficiencies for 15 ASEAN airlines covering the period 2010-2014. The disaggregate input efficiency of ASEAN airlines is computed by comparing the target and actual inputs.

The disaggregate input efficiency of ASEAN airlines shows that aircraft efficiency is the lowest, operating cost efficiency is better, and available seat efficiency is the best.

This paper applies data envelopment analysis models, disaggregated input efficiency measures, and bootstrapping approaches to compute the operational efficiency of ASEAN airlines. Strategic suggestions are made to improve the operational efficiency of ASEAN airlines.

ARCIS is an information system holding titles, researchers' names and institutes, administrative codes, free keywords and costs for about 4,500 research projects sponsored by the Agricultural Research Council (ARC), the Ministry of Agriculture, Fisheries and Food (MAFF), the Department of Agriculture and Fisheries for Scotland (DAFS) and the Department of Agriculture, Northern Ireland (DANI).

The main purpose of the present study is to develop appropriate construct to benchmark occupational health and safety performance in industrial setting so that deficiencies can be highlighted and possible strategies can be evolved to improve the performance.

Data envelopment analysis (DEA), being a robust mathematical tool, has been employed to evaluate the safety performance of industries. DEA, basically, takes into account the input and output components of a decision‐making unit (DMU) to calculate technical efficiency (TE). TE is treated as an indicator for safety performance of DMUs and comparison has been made among them.

A total of 30 Indian organizations under three industrial categories such as construction, refractory and steel are chosen for comparison purpose. It has been observed that safety performance of construction industries is consistently low as compared to other categories of industries. TE has been calculated using two types of models of DEA such as constant return to scale (CRS) and variable return to scale (VRS). A paired two‐sample t‐test indicates that TEs obtained using two models are significantly different. Mean efficiency of 30 samples is found as 0.898 using CRS model whereas same is calculated as 0.942 using VRS.

The limitations may be number of input and output components considered for each DMU. If different set of inputs and outputs may be considered, the results may be different. Another limitation may be the number of industrial sectors considered in the study.

The method, being a generic one, can be adopted by the managers to assess present safety performance and find a suitable peer to which, it should follow to improve own TE followed by in what respect it has to improve. Industrial safety and occupational health concerns in industries is not only important from government regulation point of view but also essential for enhancing productivity and profitability to become competitive in the marketplace. The practical limitation may be collection data quantitatively from various DMUs because many a time the DMUs are unwilling to share data.

This work proposes use of simple mathematical tool like DEA for benchmarking based on safety performance in Indian industries. In Indian context, safety performance of industrial settings has hardly been assessed. The study provides a simple but comprehensive methodology for improving safety performance. The study also outlines comparative evaluation of safety practices in different industries.

The quantitative understanding of the safe input management practices of vegetable producers is essential for both food safety and environmental protection. The purpose of this study is to investigate the current status of safe production in vegetable enterprises and examine the key risk factors affecting the safe production of vegetables from the perspective of agricultural inputs.

Based on the theory of risk analysis, a framework of safe vegetable production risk analysis is constructed from the perspective of production input behaviour. Based on 202 valid questionnaires in Beijing, China, this paper identifies direct risks in input management through statistical descriptive analysis; determines weights through an expert elicitation process and calculates weighted safety values accordingly; and finally uses a categorical regression model to explore the indirect risks affecting corporate safety production.

The results show that direct risk factors include seed treatment risk, pesticide and fertilizer use criteria risk, pesticide and fertilizer operation risk, and pesticide application object risk. The production safety value of Beijing's enterprises is found to be high in the north and south regions, and low in the central region. Finally, some indirect risk factors, namely the cognition of agricultural product safety laws, the cognition of pesticide safety intervals, the cognition of prohibited pesticides and the possession of brands, are found to have positive and significant impacts on the safe production behaviour of enterprises.

These findings provide entry points for interventions aimed at reducing dependence on pesticides and fertilizers and promoting input management for safe vegetable production in enterprises, thus avoiding vegetable safety incidents due to improper practices in the production chain.

Partnerships have the potential to create significant benefits for all participants provided that there is a mutual understanding of and respect for the inputs required and the outputs sought from the arrangements by each party. The aim of this study was to explore the inputs required and the outputs achieved by partners as a function of the level of involvement required within the partnership arrangement. The study has investigated the extent to which the input criteria defined by the DTI and the output criteria defined by Kanter, within three health and safety initiatives involving homeworker‐employer, employee‐employer, and contractor‐employer partnerships varied, as a function of the level of partnership defined by Thompson and Sanders. The examination of the partnership arrangements within the three case studies demonstrated that the inputs were very similar whether the arrangements were classified as co‐operation, collaboration or coalescence, although the extent of the output criteria was greatest in the case of the coalescence partnership. The results illustrated the level of inputs required within a range of partnership arrangements in the context of health and safety management and the range of outputs that might be anticipated.

This paper aims at developing a methodology capable of controlling accidents and failures in oil and gas production activities.

Fuzzy analysis that is based on fuzzy linguistics, rule matrix, rule structures, and system operating rules is utilised. Fuzzy methodology is applied to develop a safety control model for the prevention of accidents and failures in oil and gas production activity offshore platforms.

The model is demonstrated with a case study, thereby suggesting the feasibility of the applied approach in practical cases.

Primarily, the study aims to guarantee safety. Also uncertainties and imprecision that commonly characterize safety measurement systems are tracked. The time‐consuming activity in measurement and the requirement of lots of specific information about the process is avoided.

The results from the study provide valuable baseline information for future research investigating how safety of oil platforms is affected by some factors.

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.

A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.

First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.

Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.

The purpose of this paper is to assess the perceptions of safety officers on Occupational Health and Safety (OHS) norms extended to the workforce in Indian industries, understand implementation levels and find out deficiencies existing therein.

In this study, the authors utilized factor analysis to develop an instrument specifically responsible for assessing OHS norms in three major industrial sectors through a broad‐based questionnaire survey. The pattern of influence of input parameters on outputs such as injury level and material damage is difficult to establish, possibly due to existence of some nonlinear relationship among them. Therefore, a neural network approach is adopted to carry out sensitivity analysis and identify important deficient items.

Exploratory factor analysis has been carried out on the responses to the designed questionnaire. In total, nine factors with 23 items have been extracted and interpreted. As neural networks are capable of mimicking human cognitive process, the perceptions mechanism of safety officers can be easily modeled via neural networks. Sector‐wise deficient items have been identified and strategies for their improvement have been proposed.

The major limitation may be the number of industrial sectors considered in the study. Although the proposed model is quite generic, its performance needs to be tested with other categories of industries.

Although perceptions of safety officers on their immediate work environment help to formulate constructive safety policy and procedures, involvement of a few representatives from the workforce during the implementation level may assist to substantially reduce injury level and material damage, since the workers are more conversant with work practices, are exposed to risk environments and can sustain injuries if accidents occur.

The paper uses advanced statistical and intelligent techniques for assessment of OHS practices. A comparative evaluation of present practices among three major types of Indian industry has been made. Further, the paper proposes an OHS instrument for Indian industry. The paper offers new directions for researchers to devise a comprehensive methodology that aims at reducing occupational health risks.

Following a brief review of the current status of offshore safety regulations in the UK, several issues pertaining to the problems encountered in applying the existing reliability and safety analysis methods in quantitative safety appraisal studies, especially in the early concept design stage of maritime engineering products, are discussed. Presents three novel risk assessment and decision support frameworks. These include a design trade‐off approach using Taguchi method, a safety based decision support system based on artificial neural network techniques, and a fuzzy‐logic‐based synthesis incorporating the Dempster‐Shafer approach for making multiple attribute decision. Three illustrative examples are used to demonstrate the novel tools, together with the discussion on the conditions under which each approach may be applied effectively. Finally, recommendations on further development in safety modelling, decision‐making techniques and their integration into safety management systems, are suggested.

Safety research has focused on drivers, pedestrians and vehicles, with scarce attention given to highway traffic officers (HTOs). This paper develops a robust prediction model which enables highway safety authorities to predict exclusive incidents occurring on the highway such as incursions and environmental hazards, respond effectively to diverse safety risk incident scenarios and aid in timely safety precautions to minimise HTO incidents.

Using data from a highway incident database, a supervised machine learning method that employs three algorithms [namely Support Vector Machine (SVM), Random Forests (RF) and Naïve Bayes (NB)] was applied, and their performances were comparatively analysed. Three data balancing algorithms were also applied to handle the class imbalance challenge. A five-phase sequential method, which includes (1) data collection, (2) data pre-processing, (3) model selection, (4) data balancing and (5) model evaluation, was implemented.

The findings indicate that SVM with a polynomial kernel combined with the Synthetic Minority Over-sampling Technique (SMOTE) algorithm is the best model to predict the various incidents, and the Random Under-sampling (RU) algorithm was the most inefficient in improving model accuracy. Weather/visibility, age range and location were the most significant factors in predicting highway incidents.

This is the first study to develop a prediction model for HTOs and utilise an incident database solely dedicated to HTOs to forecast various incident outcomes in highway operations. The prediction model will provide evidence-based information to safety officers to train HTOs on impending risks predicted by the model thereby equipping workers with resilient shocks such as awareness, anticipation and flexibility.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

It is a well-accepted note that to enhance safety performance in a project by preventing hazards, recognizing the safety leading indicators is of paramount importance.

In this research, the relationship between safety leading indicators is determined, and their impacts on the project are assessed and visualized throughout the time of the project in a proactive manner. Construction and safety experts are first interviewed to determine the most important safety leading indicators of the construction industry, and then the relationships that may exist between them are identified. Furthermore, a system dynamics model is generated using the interviews and integrated with an add-on developed on the building information modeling (BIM) platform. Finally, the impacts of the safety leading indicators on the project are calculated based on their time of occurrence, impact time and effective radius.

The add-on generates a heat-map that visualizes the impacts of the safety leading indicators on the project through time. Moreover, to assess the effectiveness of the developed tool, a case study is conducted on a station located on a water transfer line. In order to validate the results of the tool, a survey is also conducted from the project's staff and experts in the field. Previous studies have so far focused on active safety leading indicators that may result in a particular hazard, and the importance of the effects that safety leading indicators have on another is not considered. This study considers their effects on each other in a real-time manner.

Using this tool project's stakeholders and staff can identify the hazards proactively; hence, they can make the required decisions in advance to reduce the impact of associated events. Moreover, two other potentially contributions of the presented work can be enumerated as: firstly, the findings provide a knowledge framework of active safety leading indicators and their interactions for construction safety researchers who can go on to further study safety management. Secondly, the proposed framework contributes to encouragement of time-based location-based preventive strategies on construction sites.

In China, external supervision on construction safety mainly comes from the government and supervision engineers (SEs). However, the construction safety supervisory mechanism (CSSM) contains some dilemmas affecting the improvement of safety performance, such as the declining impact of SEs, the increasing rent-seeking behaviors of contractor and excessive government interference. This study aims to depict and analyze the CSSM in China from an evolutionary game view. The objectives are to understand the supervision strategy and evolutionary behaviors of different stakeholders, propose suggestions for improving safety performance and help the key safety supervision stakeholders, especially the government, formulate a suitable safety supervision strategy.

This research uses tripartite dynamic evolutionary game theory to study the CSSM in China and solve the stable equilibrium solution using system dynamics.

This study has revealed the game relationship of construction safety supervision mechanisms in China and solved the stable equilibrium solution. The results prove that a supervision engineer (SE) plays a crucial role in the CSSM, and “supervision engineer useless” is an unreasonable assertion. For government supervision agency (GSA), excessive inspection and free-market regulation are neither wise strategies. GSA can reduce the inspection frequency when general contractors (GCs) input high safety investments and SEs implement responsible supervision. But keeping proper government supervision to avoid GC's unlawful behaviors and SE's rent-seeking is indispensable. In addition, excessive governmental supervision will weaken SE's role, so the government should transfer some supervision powers to SE.

This study focuses on the dynamic evolution process between GSA, GC and SE. This method is different from most research that neglected the dynamic characteristic of system and game solution stability. The research methods not only contribute to construction safety supervision policy-making in China but also help to improve supervision efficiency in other countries and other fields.

Concern for health, safety and environment (HSE) is increasing in many developing countries, especially in energy industries. Improving power plants efficiencies in terms of HSE issues requires considering these issues in performance assessment of power generation units. This study aims to discuss the use of data envelopment analysis methodology for the performance assessment of electrical power plants in Iran by considering HSE and conventional indicators.

Installed capacity, fuel consumption, labor cost, internal power, forced outage hours, operating hours and total power generation along with HSE indices are taken into consideration for determining the efficiency of 20 electric power plants or decision-making units (DMUs). Moreover, DMUs are ranked based on their relative efficiency scores.

Results show that HSE factors are significant in performance assessment of the power plants studied in this research, and among HSE factors, health has the most powerful impact on the efficiency of the power plants.

The approach of this study could be used for continuous improvement of combined HSE and conventional factors. It would also help managers to have better comprehension of key shaping factors in terms of HSE.

Despite the increasing prominence of employee voice in organizational innovation and productivity, employees continue to struggle to influence matters that affect them at work. The purpose of this paper is to model work group context and manager behavior as the predictors of employee upward voice. Further, a mediating role of employee psychological safety is examined in this link.

With data from 575 employees representing various technology firms in India, the authors test the hypothesized relationships using covariance-based structural equation modeling.

Results indicate coworkers upward voice and manager pro-voice behavior to significantly impact employee upward voice with a mediating impact of psychological safety. This implies that perceived psychological safety plays a significant role in explaining the impact, coworkers and manager behavior would have on regulating employee upward voice.

This study contributes to the employee voice literature from an Indian context, where upward communication is culturally discouraged.

The purpose of this paper is to propose a practical framework to measure the safety performance of workers in the Indian construction industry. The key safety performance indicators are identified and ordered on the premise that the higher order assignment of an indicator implies a strong indication of an effective safety performance.

Various indicators of safety performance in the construction industry were identified from extant literature review combined with author's personal viewpoint. The identified variables were inquired for appropriateness for the Indian construction scenario by consultation with experts. Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) technique was considered for the ranking of the indicators from most to least important.

The most important highlight of the study was the importance of the role of management by participating in informing workers about the safety rules and compliance toward safety measures. Proper and timely safety training to the workers and equipping them with sophisticated safety equipment for daily activities is perceived to be highly important in ensuring a safe and healthy workplace environment. Controlling the absenteeism rate reduces the burden of extra work on the employees, thereby, encouraging safe work-related behavior.

Senior management should make safety induction programs compulsory at the time of joining of the employees. The guidelines for safety practices, rules and information about the safety equipment should be properly documented and arranged in safety manuals. Periodical drills involving visual demonstration of the safety practices should be followed to ensure safety at workplace.

The purpose of this paper is to introduce an innovative data envelopment analysis (DEA) model entitled “Non‐binary Arithmetic Operator Dual‐role” (NAOD) under free disposability assumption for selecting the refrigerated containers in cold chain management (CCM).

In classical DEA models, it is assumed that all of input and output variables play a certain role. However, in some cases, some variables play both input and output roles, simultaneously. These variables in DEA are called “dual‐role” factors. This study introduces a new approach to deal with these factors in the process of evaluating a set of homogeneous refrigerated containers, which is based on Free Disposal Hull (FDH) (one of the DEA models). However, in previous dual‐role models, this variable is considered as a binary variable. In this paper, a partial role for dual‐role factors is considered.

The main findings of this paper are: for the first time, the NAOD model is developed for the container selection problem in the context of CCM and the dual‐role factors are considered for the container selection problem. The NAOD model determines partial role of dual‐role factors and can consider multiple dual‐role factors. For the first time, the container selection problem is solved by an FDH model. The result of NAOD model is validated by genetic algorithm.

The paper makes a sufficient contribution to the practice of operations research. It is the first study which applies advanced DEA models for selecting the containers in the context of the CCM. To the best of the authors' knowledge, there is no other reference that deals with container selection in the context of CCM in the presence of dual‐role factors.

This study is a systematic literature review of the application of artificial intelligence (AI) in safety-critical systems. The authors aim to present the current application status according to different AI techniques and propose some research directions and insights to promote its wider application.

A total of 92 articles were selected for this review through a systematic literature review along with a thematic analysis.

The literature is divided into three themes: interpretable method, explain model behavior and reinforcement of safe learning. Among AI techniques, the most widely used are Bayesian networks (BNs) and deep neural networks. In addition, given the huge potential in this field, four future research directions were also proposed.

This study is of vital interest to industry practitioners and regulators in safety-critical domain, as it provided a clear picture of the current status and pointed out that some AI techniques have great application potential. For those that are inherently appropriate for use in safety-critical systems, regulators can conduct in-depth studies to validate and encourage their use in the industry.

This is the first review of the application of AI in safety-critical systems in the literature. It marks the first step toward advancing AI in safety-critical domain. The paper has potential values to promote the use of the term “safety-critical” and to improve the phenomenon of literature fragmentation.

UK oil and gas producers through unilateral action and consensus have been ultimately responsible for many key safety improvements in global helicopter services. With production assets no longer concentrated in the hands of a few major operators, the question is whether this leadership role can be assured in the future. This paper aims to summarise doctoral research that examined the economics of safety in the offshore helicopter industry.

The offshore helicopter industry has particular characteristics, including: greater levels of safety training and choice is severely limited. A carefully structured questionnaire was presented to a sample of offshore helicopter passengers, and the responses analysed in depth.

Shifts in perceptions of safety risk are predictable, and potentially measurable, and translate into demands for action based on a mechanism of individual choice. It is then the cumulative effects of any shift in individual choices that determine the scale and scope of organisational response required by the employer and/or its agents.

This research data is only sufficient to predict the manner in which perceptions of safety impact on the sustainability of offshore helicopter travel.

The fundamental characteristics and dynamics of offshore helicopter travel still have the potential to result in some significant instability amongst the offshore workforce, and within the industry. There is strong evidence that oil and gas producers need to be prepared to take a leadership role. As the demands for consensus increase, this research can be developed into a useful analysis and safety management aid.

Nowadays, maintenance companies form networks, where multiple organizations and actors can deliver value to the customers. Current literature does not take into account how the value created by the entire network can be measured. The purpose of this paper is to address this research gap by identifying how the value created by the maintenance network as well as the participating individual organization can be measured simultaneously.

The research has been carried out using the qualitative research approach. The findings of the study are based on literature search as well as research processes carried out in two maintenance service networks.

The study presents a framework and propositions on how to measure network value in maintenance services. According to the results, the network value can be measured from the following five perspectives: financial capital, i.e., savings or growth; end customer capital such as the end customer satisfaction and recommending customers; network capital, i.e., know-how development and learning; sustainable capital such as business continuity and environmental safety; and relationship capital, such as reputation and new contacts.

Despite the increasing amount of literature on performance measurement in networks, theory is still lacking that reflects the complexity and dynamism when value is delivered to customers through maintenance networks. Significant novelty of the research is based on combining network, service, and value perspectives in performance measurement.

This study aimed to develop and validate a health education booklet (Be SAFE booklet) as a guide to improving knowledge, attitude, and practice toward drowning prevention and water safety among parents of primary school children in a local community in Selangor.

This methodological study was conducted in two phases: the development of the content, and validation of the educational material. Booklet development involved content survey and design development. These steps consisted of a content analysis method, information from current literature, document analysis from the stakeholder, and input from parents or guardians and children. The validation by nine panel experts and 15 parents/guardians involved both review, content validity, and face validity.

The booklet was developed by emphasizing on four main aspects related to drowning prevention and water safety; namely, supervision, alertness, first aid, and education. The assessment rated by the content validity index (CVI), resulted in an I-CVI ranging from 0.78 to 1 and S-CVI of 0.94; the face validity achieved a level of agreement with an average of 94 percent. The results indicated that the Be SAFE booklet was validated and could be considered useful in helping to promote drowning prevention and water safety among primary school pupils' parents.

This article contributed ideas for the concept and aspect of health messages to be incorporated into health education materials for drowning prevention and water safety.

The purpose of this paper is to examine employees’ safety behaviours (ESBs) within the beverage manufacturing industry. It also assessed employees’ perception of their own safety behaviours. It further investigated the impact of organisational culture (OC) on ESBs. Finally, the study identified the likely determinants of ESBs.

A survey methodology was employed as an appropriate approach. In total, 197 valid questionnaires were retrieved from employees working in the beverage manufacturing industry. The questionnaires were processed for quantitative analyses to test the hypotheses. A simple regression analysis was carried out to assess employees’ perception of their own safety behaviours and to investigate the impact of OC on ESBs. Descriptive frequencies and percentages were used to identify the determinants of ESBs.

The results suggest that employees’ perception of their own safety behaviour was positive. OC was reported to have a strong positive impact on ESBs. Safe working conditions, job satisfaction and organisational leadership were identified as the key organisational determinants of safety behaviours among the employees.

Interpreting these findings must be done with caution as the sample size was relatively small and solely obtained from four beverage manufacturing firms. Generalising the findings from this study must also be carefully done as the study is industry-specific and country-specific.

Besides the loss of talents through unsafe behaviours, accidents can hurt work performance, productivity and profitability of an organisation. Industry organisations and their managers can therefore implement perceptual, organisational and cultural interventions that reinforce appropriate safety behaviours among employees at the workplace.

Understanding these cultural, perceptual and organisational perspectives on ESBs is not only a significant input for safety behavioural analysis and interventions but can also reduce the socioeconomic cost of unsafe and risk behaviours among employees at the firm, industry, national and global levels.

The empirical tests of employees’ perception of their own safety behaviours are heavily biased towards data originating from the developed country industry settings which suggest that the dynamics of ESBs in the less developed economies are likely to be unknown. This study is first to examine ESBs in a developing country beverage manufacturing industry setting.

This purpose of this study is to outline an inclusive development strategy for crime prevention interventions. Crime prevention interventions are delivered to the target audience to convey an evidence-based message to dissuade would-be offenders from carrying out crimes. However, rarely is the target audience involved when designing crime prevention interventions.

Using the Delphi method, this paper documents the design of an intervention aimed at improving young drivers’ compliance with road rules, incorporating feedback from both a panel of experts and the target audience of the intervention. While expert feedback guided the content and the context of the intervention, the feedback from the target audience was critical in ensuring that effective delivery and messaging of the crafted intervention would occur.

By drawing on expert and experiential insights, this exploratory method of intervention design provided a simple and effective way of ensuring the effective delivery of a crime prevention message.

Although this study focussed on a road safety intervention, the crime prevention applications of this method are broad.

This paper outlines a collaborative methodology that utilises expert and experiential knowledge towards the design and development of a crime prevention intervention, in this case, targeted at young drivers.

The purpose of this paper is to survey Swedish healthcare leaders' patient safety awareness, the priority they give to safety issues and their views on suitable safety management strategies.

A total 623 leaders of a sample of 1,129 responded to a mail questionnaire (55 percent response rate). Descriptive statistics of the responses are presented as frequency distributions across respondent subgroups. Means were tested for similarity by a repetitive one‐way ANOVA procedure. Homogeneous response groups were sought by hierarchical cluster analysis.

Swedish healthcare leaders show relatively high safety awareness and how their organizations prioritize safety management. There is a marked polarization between leaders; half feel that the system works reasonably well, and that adequate funds are available to improve or maintain services. The other half thinks the system needs major change and calls for additional funding. A majority sees system errors as the main cause for adverse events; a substantial minority find human errors to be more important. Two‐thirds were willing to make safety performance information on organizations and specialties public, one third was restrictive.

Survey instruments used to explore leaders' patient safety views have not yet been rigorously tested against psychometric criteria. One hospital type was slightly over‐represented and three regions somewhat under‐represented in the respondent groups.

This is the first systematic attempt to explore the views of Swedish healthcare leaders on patient safety. It provides input to a national strategy to improve patient safety.

Standards have restricted the use of networks and programmable electronics in safety‐related applications. New standards have released technology to enable improvements in safety and ensure developments take place within an overall safety framework. Best practice in the additional protocol enhancements required is discussed. The installation of a safety‐related fieldbus, replacing conventional hardwiring in a machine safety system is used to illustrate the potential of the technology. The use of fieldbus in safety‐related applications is shown to reduce complexity and enhance functionality, whilst enabling significantly reduced ownership cost.

The construction industry is considered one of the most dangerous industries especially in developing countries such as Egypt. Although safety in Egypt is regulated by mainly four pivotal legislations, namely, Law No. 12 (2003) and Ministerial Decrees No. 211, 126 and 134, construction accident records in Egypt are high. Accordingly, this paper aims to develop a framework to activate the health and safety regulations in the Egyptian construction industry.

To achieve this aim, a research methodology consisting of a literature review and a survey questionnaire was developed to accomplish three objectives. First, a literature review was used to identify the causes of site accidents and strategies adopted in different countries to improve and enforce safety, safety roles of stakeholders. Second, a survey questionnaire was conducted with a representative sample of large- and medium-sized construction firms in Egypt to examine their perception of the causes of site accidents. Finally, a framework was developed to activate the health and safety regulations in the Egyptian construction industry.

The research identified 16 causes of construction site accidents. These causes were classified into three categories based on the party responsible for the occurrence of site accidents, namely, workers, organization management and government. Results of data analysis showed that “lack of housekeeping” and “lack of governmental inspection for safety” were ranked the highest causes of site accidents in the Egyptian construction industry, whereas “inefficiency of old safety equipment or no safety equipment at all” and “reluctance to input resources for safety” were ranked the least causes.

This research provides valuable information about the nature of the construction industry with a particular focus on site accidents, causes and impacts of construction site accidents. The study highlighted the safety roles of the Egyptian Governmental bodies in Egypt to improve and enforce safety. The research tackled a topic that received scant attention in construction literature especially in the Egypt context. The framework presented in this paper represents a synthesis that is important and adds value to the knowledge in a manner that has not previously occurred in the Egyptian construction industry.

This study aims to reduce the construction safety accidents of prefabricated building (PB) projects, improve the efficiency and effectiveness of safety supervision by government departments, and provide theoretical reference for improving the safety supervision system of PB construction.

Considering the information asymmetry between government supervision departments and construction contractors and the interactive relationship between the two parties under bounded rationality, we propose an evolutionary game model for the construction safety dynamic supervision of PBs and analyze the evolutionary strategy of the game. The system dynamics (SD) method is used to simulate and analyze the evolutionary game process under a dynamic supervision strategy and the adjustment of external variables.

The cost difference between the government's strong and weak supervision, the construction contractor's additional expenditure for strengthening safety management, and other factors affect system stability. The government can dynamically adjust the penalties based on the construction contractor's subjective willingness to ignore safety management and further adjust their rate of change based on the completion of the supervision goals to improve the efficiency and effectiveness of construction safety supervision.

This study makes contributions in two areas. Through a combination of SD and an evolutionary game, it provides new insights into the strategic choice of the main body related to PB construction safety. Additionally, considering the nonlinear characteristics of construction safety supervision, it provides useful universal suggestions for PB construction safety.

This paper aims to investigate governance in service triads, specifically studying significant steering and connecting coordination failures, to reveal typically hidden characteristics and consequences.

This study focuses on coordination functions and activities between a buyer (a government department), a customer (a military service) and two service providers. Rich data on these normally confidential service ties are drawn from an official report into the causes of a fatal accident involving a UK reconnaissance aircraft and specifically from the evidence presented regarding the earlier development of its complex safety case. The authors also analysed a range of additional secondary data sources.

The authors examine the sources, drivers and manifestation of coordination failures. The authors uncover a series of coordination failures driven from the bridge position, revealing that while bounded rationality and opportunism influenced steering coordination failures, connecting coordination failures were associated with knowledge asymmetry, dyadic inertia and unethical practices.

Organisations and governments delivering complex projects and knowledge-intensive professional services should guard against outsourcing the “coordination” activity to a third party, thereby relinquishing the bridge position. Handing over the bridge position to an integrator would leave the client vulnerable to coordination dysfunctions such as bounded rationality, opportunism, knowledge asymmetry, dyadic inertia and unethical practices.

The study links the previously separate research streams of service triads and inter-organizational coordination. While extant research pays attention to mainly positive control functions, this study focuses on all three actors in two (failed) service triads – and highlights the impact of coordination activities and failures.

Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study.

First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment.

The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments.

This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

Safety is arguably the most important “quality” attribute of commercial aviation, yet it rarely figures into overt interfirm rivalry. Usually, airlines do not even allude to their safety record vis-à-vis rivals in their advertising and press statements. Moreover, statistical analysis by independent parties usually indicates that peer airlines within the same geographic region and segment of the industry have indistinguishable safety records (Barnett, 2010).

The purpose of this paper is to employ a system dynamics approach to develop a mathematical model for managing magnitude and risk factors of injuries in a manufacturing industry. This is to provide the decision makers with a systemic‐strategy to capture the transition of industries, especially manufacturing, into world‐class safe workplaces.

An accident investigation register was administered to capture needed data to estimate the model parameters and identify risk factors of injuries. The principle of system dynamics (SD) was employed to identify the relevant safety‐related components and their interrelationships. Applying the concept of causality analysis, causal loop and SD flow diagrams indicating how prevention activities may eliminate hazardous conditions were delineated and a mathematical model to predict the main variables involved in manufacturing safety programme was formulated.

The validity of the model was demonstrated using the observed data from accident investigation and register review; and a satisfactory agreement was found between the observed data and the model predictions.

The proposed model's attribute of predicting the probability of injuries or preventions is remarkable and thus, useful for managing sustainable safety control programmes.

This paper presents a manufacturing safety programme using equation‐oriented technique to predict the main variables required for managing magnitude and risk factors of injuries in a manufacturing plant.

This study aimed to identify driving factors of safety attitudinal ambivalence (AA) and explore their influence. Construction workers' intention to act safely can be instable under conflicting information from safety management, co-workers and habitual unsafe behaviour. Existing research explained the mechanism of unsafe behaviours as individual decisions but failed to include AA, as the co-existence of both positive and negative attitude.

This study applied system dynamics to explore factors of construction workers' AA and simulate the process of mitigating the ambivalence for less safety behaviour. Specifically, the group model building approach with eight experts was used to map the causal loop diagram and field questionnaire of 209 construction workers were used to collect empirical data for initiating parameters.

The group model building identified five direct factors of AA, namely the organisational safety support, important others' safety attitude, emotional arousal, safety production experience and work pressure, with seven feedback paths. The questionnaire survey obtained the initial values of the factors in the SD model, with the average ambivalence at 0.389. The ambivalence between cognitive and affective safety attitude was the highest. Model simulation results indicated that safety experience and work pressure had the most significant effects, and safety experience and positive attitude of co-workers could compensate the pressure from tight schedule and budget.

This study provided a new perspective of the dynamic safety attitude under the co-existence of positive and negative attitude, identified its driving factors and their influencing paths. The group model building approach and field questionnaire surveys were used to provide convincible suggestions for empirical safety management with least and most effective approaches and possible interventions to prevent unsafe behaviour with tight schedule and budget.

To collate data on internal temperatures of domestic refrigerators in New Zealand.

A survey of 127 domestic refrigerators in urban and rural locations in New Zealand was carried out during 2004‐2005. Data loggers were used to record internal temperatures every ten minutes over a 72‐hour period. A short questionnaire was also administered to participants.

The overall mean temperature was 5.2 °C (standard deviation 2.5 °C). A significant proportion (34 per cent) had a mean temperature >6 °C, while 55 per cent had a mean temperature of >5 °C. There were no statistically significant differences between mean temperatures in refrigerators in rural and urban (two cities) locations. Most consumers were aware of ideal refrigeration temperatures, but lacked the means (thermometers) to check actual operating temperatures.

The temperature data collected by this survey will be useful for modelling domestic refrigerator storage as a component of food safety quantitative risk models. These data can indicate the amount of time that refrigerators have an internal temperature above a minimum bacterial growth temperature, although the behaviour of bacteria under such fluctuating conditions is not well understood.

These data can assist with food safety promotion and act as an input into food safety risk assessments.

Claims there is growing application of continuous improvement strategies across a wide range of operational activities. This paper reports on a case study, set in the UK research division of a multinational chemical company, in which the six key principles of continuous improvement have been applied to health and safety management. The case study builds on the benefits of a proactive team‐based approach and addresses workforce behaviours and practices. The study emphasises, in particular, the importance of the integration of the process into the existing health and safety management system in order to address the long‐term maintenance issues. In order to achieve this, communication of strategic targets, milestones, progress and the involvement of all employees in the continuous improvement process have been identified as of paramount importance.

The purpose of this paper is to develop a novel network and dynamic data envelopment analysis (DEA) model for evaluating sustainability of supply chains. In the proposed model, all links can be considered in calculation of efficiency score.

A dynamic DEA model to evaluate sustainable supply chains in which networks have series structure is proposed. Nature of free links is defined and subsequently applied in calculating relative efficiency of supply chains. An additive network DEA model is developed to evaluate sustainability of supply chains in several periods. A case study demonstrates applicability of proposed approach.

This paper assists managers to identify inefficient supply chains and take proper remedial actions for performance optimization. Besides, overall efficiency scores of supply chains have less fluctuation. By utilizing the proposed model and determining dual-role factors, managers can plan their supply chains properly and more accurately.

In real world, managers face with big data. Therefore, we need to develop an approach to deal with big data.

The proposed model offers useful managerial implications along with means for managers to monitor and measure efficiency of their production processes. The proposed model can be applied in real world problems in which decision makers are faced with multi-stage processes such as supply chains, production systems, etc.

For the first time, the authors present additive model of network-dynamic DEA. For the first time, the authors outline the links in a way that carry-overs of networks are connected in different periods and not in different stages.

Describes the use of safety attitudes as the basis for an intervention to improve safety performance in a power generation company. Following an initial survey using the safety attitude questionnaire developed by the SRU, a set of initiatives was developed. The initiatives included setting up safety teams, the introduction of written action plans, the provision of workforce safety budgets and an enhanced profile for management action. The initiatives were implemented by the SRU over a period of one year. Following the intervention there were improvements in safety attitude, lost time accident rates, self‐reported accident rates and absenteeism levels.

Describes the objectives of the Schools Involvement Programme of the Metropolitan Police Service and the range of services offered by schools involvement officers. Summarizes a variety of activities and topics for both younger and older pupils on the theme of personal safety. Provides a detailed account of tips for older pupils on staying safe in various situations, such as while on the street, travelling on public transport, earning money or out with a girlfriend or boyfriend.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

Safety management is a key point and poses a challenge in joint testing. To detect and address potential accidents' hidden dangers early, this paper conducts research on the safety control technology for high-speed railway joint tests by incorporating the concept of hazardous events.

Aiming at ensuring the safety of high-speed railway combined inspections and trials, this paper starts from the dual prevention mechanism. It introduces the concept of threatening events, defines them and analyzes the differences between threatening events and railway accidents. The paper also proposes a cause model for threatening events in high-speed railway combined inspections and trials, based on three types of hazard sources. Furthermore, it conducts research on the control strategies for these threatening events.

The research on safety control technology for high-speed railway combined operation and testing, based on the analysis of threatened events, offers a new perspective for safety management in these operations. It also provides theoretical and practical support for the transition from passive prevention to active risk pre-control, which holds significant theoretical and practical value.

The innovation mainly includes the following three aspects: (1) Building on the traditional dual prevention mechanism, which includes risk hierarchical management and control as well as hidden danger investigation and management, a triple prevention mechanism is proposed. This new mechanism adds the management of threatening events as the third line of defense. The aim is to more comprehensively identify and address potential security risks, thereby enhancing the efficiency and effectiveness of security management. (2) In this paper, the definition of a railway threatening event is clarified, and the causative model of a high-speed railway threatening event based on three kinds of danger sources is proposed. (3) This paper puts forward the control strategy of the high-speed railway combined operation and trial, which includes five key links: identification, reporting, analysis, rectification and feedback, which provides a new perspective for the safety management of the high-speed railway combined operation and trial and has important theoretical and application value.

In comparison to other industries, the construction industry is one of the most dangerous industries. Behavior-based safety (BBS) is a common and useful technique for risk indicator processing. Almost all studies are based on the BBS checklist, but very few of them focus on the increasing dangers faced by construction workers and the important factors that lead to accidents. This research represents a risk spatiotemporal analysis and visual tracking approach based on BBS and Building Information Modeling (BIM).

After the literature review, a BBS checklist was developed. Then a survey was conducted based on the BBS checklist and the temporal evolution of risks has been completed. After that, managing the risk with the automatic rule checking (ARC) system using BIM was conducted simultaneously to develop a framework by conducting a case study.

Based on the grey clustering analysis, this work provides a temporal evolution analysis approach for dynamic analyzing BBS risk. According to the grey relational analysis (GRA) data, the main key factor of risk was the missing guardrail/handrail system. After that, a case study was performed and the system automatically warn in the preconstruction phase that the barrier is missing as the system benefits.

A systematic framework has been provided for risk analysis through which high health and safety performance outcomes can be achieved on construction projects. This study will assist design engineers in addressing the potential danger to employees during the preconstruction stage and monitoring dynamic changes in risk on any construction site.

Examining emotional solidarity that drives tourists’ nostalgia has received significant attention, offering valuable insights that can aid in the selection of a travel destination. However, tourists’ nostalgia, along with its antecedents—perceived safety risk and emotional solidarity, has gained less attention within the setting of Pakistan. Therefore, this research has been carried out and validated a research framework using the stimulus-organism-response model to investigate the links between perceived safety risk, emotional solidarity—welcoming nature, emotional closeness, sympathetic understanding, perceived nostalgia, and destination advocacy intentions. In addition, this model employed destination attachment—place identity and place dependence—as a boundary condition on the relationships between emotional solidarity and advocacy intentions.

This study collected 545 responses through two methods: offline distribution of print copies of the questionnaire and online surveys from domestic tourists who visited scenic destinations last year. Structural equation modeling (SEM) was performed using AMOS 26, and the PROCESS macro was conducted using IBM SPSS 28.

The findings highlighted that perceived safety risk negatively influences emotional solidarity—welcoming nature, emotional closeness, sympathetic understanding—, resulting in a positive effect on perceived nostalgia. Furthermore, tourists’ perceived nostalgia positively triggers advocacy intentions. The findings also confirmed the boundary conditions of destination attachment—place identity and place dependence—on the association between emotional solidarity and perceived nostalgia.

Three major practical implications of these findings: First, ensuring visitor safety with smart security measures, digital tools for quick response, and local community involvement. Second, highlighting local markets, art, and architecture to enrich cultural experiences and promote accessibility and diversity. Finally, using marketing to generate nostalgic experiences through local collaborations, professional storytelling, and engaging social media content to build emotional ties and curiosity.

In terms of originality, this is pioneering research intended at developing and validating the model in the context of Pakistani destinations. Furthermore, this marks the initial step in examining the proposed relationships between perceived safety risk and emotional solidarity in fostering tourists' perceived nostalgia, ultimately leading to a strong desire to advocate for the destination.