Journal of Occupational

Nowadays, in analyzing the causes of accidents by passing through the technical, human-technical error, and social stages, most organizations emphasize organizational factors as effective causes of industrial accidents [1]. According to some research, many work-related accidents are rooted in organizational factors [2]. According to the latest official statistics published by the Ministry of Cooperatives, Labor, and Social Welfare (MCLSW) regarding work-related accidents between 2017 and 2019, 10,697 such accidents and 843 deaths have been recorded in 2017 alone. Also, the statistics provided by MCLSW show that in Kerman, as a leading province in the mining industry, the indicators of accidents at work in the industry and mining sector in 2019 have increased compared to the previous year [3]. Also, the rate of occupational injuries leading to death in the mining sector increased by eight percent in 2019 compared to the previous year [4].

By reviewing the results of safety audits in many industrial and mining companies, it is found that the implementation of safety, health, and environmental policies, as well as compliance with some requirements of the standard of occupational safety and health management, are not considered. The management needs to organize and prioritize operational plans required to prevent accidents and reduce deviations from safety and health policies. This is not possible unless there is a preliminary estimate of the current safety situation. In general, occupational safety in organizations is a vital issue that affects the personal, professional, and social life of individuals, as well as the economy of countries; thus, it is necessary to pay attention to improving the performance of organizations in the field of safety and prevent work-related accidents and diseases. Hence, occupational measures should be taken [5]. In order to take measures to control accidents and their injuries effectively, it is necessary to identify and study the factors affecting safety performance [6]. Therefore, identification of human and technical factors (direct or indirect) affecting safety seems necessary. Indeed, if safety performance improvement is considered, occupational accident statistics will be decreased. In this research, the question is which model is suitable to improve the safety performance of employees in industrial and mining plants in Shahr-e-Babak city?

Safety performance is generally repetitive and non-innovative behavior [7]. In other words, it is part of safety activities that describe the behavioral aspects of staffs safety [8], affecting directly or indirectly safety; thus, safety performance refers to the set of actions and behaviors of employees to maintain and improve safety and health level of themselves and their colleagues [9]. Indeed, a comprehensive performance of a safety management system is the same as safety performance [6]. Measuring employee safety performance is also a basis for assessing workplace safety [9]. Further, identifying the current issues of the organizations and strengthening the effective factors can lead to improving their safety performance in the future. On the one hand, safety performance has different organizational dimensions [10], i.e., the characteristics within the organization and its general characteristics affected by various factors. Organizational factors affecting safety performance include individual, teamwork, safety management, and organizational levels [7]. Safety performance evaluation is a complex issue. This complexity is, on the one hand, due to the number of variables involved in the subject and, on the other hand, due to the existence of linguistic words adding ambiguous components to the decision [10]. Therefore, recognizing organizational factors affecting safety performance based on the results of various researches is necessary.

Safety performance has a relatively strong relationship with safety motivation and knowledge. Also, the safety and psychological climate of the group have a vital effect on safety performance [11]. Safety climate is, indeed, the attitude of employees towards workplace safety, and its recognition and measurement are essential in assessing safety performance. The main reason for measuring safety climate is creating opportunities to improve the safety performance of organizations [12]. In other words, safety climate is the common understanding that employees have about their work environmant [13]. Research shows that, in addition to the safety climate, other factors such as knowledge and motivation also affect safety performance [12]. The importance of safety knowledge is that the person knows how to follow safety rules [14]. Safety knowledge has a positive relationship with safety performance, thus improving it since employees with safety knowledge about work do things more safely [11]. In fact, this knowledge is a part of personal characteristics that affect a person's safety performance, depending on the individual's understanding of safety risks, as well as ways to deal with and avoid them [8]. Safety knowledge is passed on to employees through safety training. This training is, indeed, information and knowledge given to a person to identify job risks, know how to control them, how to act in an emergency, what personal safety equipment to use for safe work, and how to prevent danger [15]. Therefore, safety training can also be an effective factor in safety performance in the organization.

Safety motivation is another factor affecting the improvement of safety performance. It is the motivation of employees to perform job duties in a safe manner [16]. In other words, safety motivation is the factor that causes a person to participate in safety activities effectively [17]; it is vital that employees have the necessary motivation to comply with safety [14].

Individual factors, physical, mental, or psychological, are among those affecting safety performance. Some of these factors typically are related to a person's personality that is unchangeable; however, some others are related to skills, attitudes, risk perception, and motivation [18]. Postlethwaitea et al. (2009) and Clark et al. (2005), in their studies, showed the effect safety performance of personality traits. According to the results of some research, the conscience has a direct effect on safety performance [19, 20].

Other factors effective in improving safety performance include safety observance, attitude, and participation. Observance of safety are activities performed to maintain the workplace, consisting of the safety procedures and guidelines, safety equipment, and compliance activities with the safety standards [8]. According to job performance theories, participation in safety can be introduced as one of the dimensions of safety behavior [21]. It refers to behaviors that support organizational goals in this field, such as participation in voluntary safety activities or attending safety committee meetings [22]. According to some research, attitudes of staff and supervisors to safety and its performance have a significant relationship [18]. The attitude refers to the inner desire of individuals to evaluate people, objects, and situations, and their interpretation is both desirable and undesirable; also, safety motivation is defined as an individual's desire to show safe behaviors and the valued behaviors related.

Safety management and compliance with the requirements of health, safety, and environment (HSE) management system, human, safety acceptance (behaviors focused on accepting minimum safety standards in the workplace), job satisfaction, and safety leadership are other factors related to safety performance [21].

Materials and Methods

The present research was applied in terms of objectives and descriptive in terms of data collection. Data were collected through the review of previous studies, and interpretive structural modeling was used for the development of the model and identification of the relationship between variables. The sources were reviewed until theoretical saturation to ensure all components were extracted. This study aimed to find factors that improve the safety performance of employees in industrial and mining companies. The relationships between criteria and their type are determined through structural-interpretive modeling, which makes it possible to structure a set of different and related factors in a comprehensive and organized model, use some basic concepts of graph theory, and describe the complex pattern of conceptual relationships between variables. In this modeling method, based on the judgment of groups (experts), it is decided how variables are related to each other, thus being considered an interpretation.

This method extracts a general structure from a complex set of variables based on their relationships; hence, it is structural. Particularly, it shows the specific relationships of the variables and the overall structure in a graphical model. Therefore, the present study was performed using the interpretive-structural modeling approach. A pairwise comparison questionnaire was used to prioritize the factors. Furthermore, human resource and safety managers of industrial and mining companies in Shahr-e-Babak city were selected as research experts. They all had the theoretical knowledge, practical experience, intention, and ability to participate in the research. Therefore, 25 experts in safety management were selected based on purposive sampling with respect to the research approach. They were selected from Shahr-e-Babak city, one of the mining and industrial cities of the country, with high-risk jobs.

The research process consists of three phases:

1. Criteria identification stage: in this stage, the criteria were collected by studying the research literature to improve safety performance. For this purpose, to prepare a list of criteria, non-repetitive ones were first collected. Then, among the criteria repeated in the researches with the same meaning, one case was mentioned in the list.

2. Criteria screening stage: in this stage, first, the effective criteria in the organization were identified through interviews with chiefs, and then, the fuzzy screening technique was used to determine the most important criteria.

3. The stage of determining the relationship between variables and their type (modeling): in this stage, the questionnaire for determining the relationship in the interpretive-structural modeling method was completed by the organization experts. Then, by converting the relationship matrix to interpretive-structural modeling and creating consistency in the relationship matrix, the corresponding graph was drawn, and the type of variables was determined using the Mick-Mac analysis. In this analysis, research variables are divided into four categories (autonomous, dependent, connected, independent variables) according to conductivity (number of elements of the achievement set) and dependence power (number of elements of the prerequisite set).

Results

In this study, first, based on the theoretical foundation of research, repetitive and non-repetitive factors affecting safety performance improvement were reviewed, and then with the help of experts (specialists) and fuzzy screening, 9 were identified ( C1:safety climate, C2:Safety motivation, C3:Safety knowledge, C4:Safety attitude, C5:Conscientiousness, C6:Safety training, C7:Safety Management, C8:Observe safety, C9:Safety partnership). The fuzzy AHP was used to prioritize the identified indices. Thus, 17 indices were acknowledged and classified into 9 main criteria (Table 1).

Table 1. Initial access matrix

A structural self-interaction matrix (SSIM) was formed, according to Warfield's (1974) instructions [23]. Experts' opinions were used to determine the type of relationship between variables. The experts' opinions were extracted from the questionnaires based on the majority vote rule, and then the relationship symbols of this matrix were converted to 0,1 and placed in the initial access matrix. The matrix obtained in this step shows how variables interact.

Next, with the compatibility of the initial access matrix, the final access matrix was ​​formed. To match the matrix, mathematical rules were used to achieve the final access matrix; thus, the achievement matrix reached the power of K + 1 (K≥1). The matrix empowerment operation was performed based on the Boolean rule; according to this rule, 1+0=1and 0+1=1, 1+1=1 and 0+0=0. To determine the level and priority of variables, the set of achievements and prerequisites for each variable were determined. As presented in Table 2, by adding the numbers on each row, the conductivity power is determined, and by adding the numbers to each column, the degree of dependence is determined. The conductivity power of each variable is the final number of the variables (including itself) that can play a role in creating them, and the degree of dependence is the number of variables that affect the relevant variable and lead to its achievement.

Table 2. Formation of the final access matrix

In the next step, the final access matrix was ​​divided into several levels. This division helps clarify the role of each of the components and their two-way interaction, as well as facilitating the process of their analysis. Therefore, after determining the set of achievements and prerequisites for each variable, common elements in the sets for each variable were identified. Later, the level of variables was determined. In the first table, the variable with exactly the same set of achievements and their common elements was considered to have the highest level. After determining this variable or variables, they were removed from the table, and with the other remaining variables in the table, the second levels were identified; this continued until the level of all variables was determined (Table 3).

Table 3. Determining the levels of factors affecting the improvement of workers' safety performance

Finally, after determining the relationships and level of variables, an interpretive-structural model was drawn. For this purpose, first, the variables were arranged in order from top to bottom in terms of surface, and the relationships between them were drawn based on the initial achievement matrix. The direction of the arrows was determined from the final matrix (Fig 1).

Fig. 1. ISM graph to improve workers' safety performance

Level one is the most influential level, and the last level is the most effective one, which acts as the foundation stone of the model. As shown in Fig. 1, the final model obtained in this study consists of four levels. In the ISM, the relationships and interrelationships between criteria, as well as their effectiveness at different levels, are well-demonstrated, leading to a better understanding of the decision-making by experts. The fourth level criteria of the lowest part of the graph have the most relevance and impact on the system by changing which the system changes. Criteria at higher levels are less effective and more influenced by other criteria. Thus, criteria 6, 8, and 9, known as the first level criteria, are placed in the model's first level. Therefore, they are more influenced by lower-level criteria. Similarly, other criteria are specified at other levels of the model.

Finally, structural analysis was performed using the Mik-Mak method. Factors with high penetrating power are called main factors. These factors fall into one of two groups of connected and independent criteria (Table 4).

Table 4. Degree of conductivity and dependence of safety performance improvement factors

As observed, all factors, except for 9 in the second (dependent) group, are in the first (autonomous) group. These factors have poor conductivity and dependence (Fig. 2).

Fig. 2. Power_dependence chart (MIC-MAC chart)