Reducing workplace unsafe behaviour using risk classification, profiling, risk tolerance approach

Abstract

Individuals’ risk tolerance capacity is one of the primary reasons for their unsafe behaviour at the workplace and is commonly identified as an important causal factor for the majority of workplace accidents. Research has exhibited the significance of individuals’ risk tolerance while dealing with risk at workplace. However, limited research is done to explore the influence of various factors on individuals’ risk tolerance. In this paper, questionnaire survey (42 questions based on the 36 factors) data were gathered from 606 miners (various category) belonging from three major coal producing subsidiary of northern India. Based on the responses received on the questionnaire survey, (1) Statistical method is used to identify the critical factors (10 critical factors) among all; (2) risk classification (Personal Protective Equipment, operational and others-3 way) system was introduced based on the nature of risk being taken; and (3) organisational risk profiling was done. The methodology of risk profiling and risk classification introduced in this paper will help the organisation identify the critical groups and the nature of the risks being taken, respectively. Further, by considering the combined effect of all three outcomes, necessary compliances can be carried out like design of training module, framing of safety policies and deployment of suitable manpower.

1. Introduction

Due to inherent risks in the mining industry, workers are exposed to risks relating to health and safety at the workplace. The risks to employees’ safety and health posed by unknown and unforeseen hazards pose challenges to safety professionals and organizations. Despite many measures like a stringent and exhaustive legal framework for evolving mining conditions and methods, the use of sophisticated technology, modern safety monitoring mechanisms, regular trainings to skill the workforce [[1], [2], [3]], the development and usage of customised safety management plans (SMPs) and standard operating procedures (SOPs), etc initiated by researchers, safety professionals, or organizations in order to improve the safety performance of mining industry around the globe, the accident statistics are not at desired levels [4,5]. According to reports, 65% of all occupational injuries and deaths occur in Asia [6]. The Indian mining industry is also no exception to these [7,8] and as an example, according to the DGMS standard note, during the year 2020, there were 39, 25 and 3 fatal accidents involving 42, 33 and 4 fatalities in coal, metal and oil mines, respectively. The numbers of fatal accidents during the year, i.e., 2019, were 53, 40, and 5 for coal, metal, and oil mines, respectively [9].

In general, there are several contributing factors to workplace accidents and are typically categorized into two groups: unsafe conditions and unsafe behaviours [[10], [11], [12], [13]]. An unsafe act is an action or behaviour that departs from accepted safety standards and may harm an individual or group. Researchers have proven that unsafe acts are caused by two factors: (1) internal factors such as risk tolerance, risk perception, and self-efficacy [14,15], and (2) external factors like safety culture, work environment, and conditions [[16], [17], [18], [19], [20], [21]].

Safety professionals consider risk tolerance as an important factor at workplace because employees are frequently confronted with various types of workplace hazards [[22], [23], [24]]. Risk tolerance is at the core of all safety decision making [25]. Safety professionals associated with inherently hazardous industries like mining, aviation, construction, chemicals, nuclear plants, etc. are more concerned with an individual’s risk tolerance level as the consequence of a risky decision may be catastrophic [17,26,27]. Workers with a higher risk tolerance are most likely to expose themselves to hazards, and thereby increasing the likelihood of accidents. Hence, wherever high risk is involved, person with lower risk tolerance is desirable and reducing the degree of risk tolerance of workers would help in improving the safety standards at work.

Risk tolerance is defined as an individual’s capacity or willingness to accept a certain amount of risk to pursue some goal. Also, risk tolerance is a significant component of human behaviour in determining whether an individual takes no risk at all, low risk, moderate risk, or high risk at the workplace. Usually, it is the primary catalyst behind the decision-making activities of individuals while dealing with workplace hazards.

In order to understand the mechanism of risk tolerance while dealing with the risks at the workplace, it is necessary to assess the influence of factors on risk tolerance. Based on the extensive literature review, various researchers concluded that many factors influence an individual’s risk tolerance capacity at the workplace [[28], [29], [30], [31], [32], [33], [34], [35]]. Some factors have a higher influence on an individual’s risk tolerance capacity, whereas others have a moderate, little to no impact, which ultimately influences the decision making of miners while dealing with the hazards at workplace [[36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48]].

Researchers have categorized risk on various parameters like based on the activity, risk rating and nature of hazards [49]. Based on the activity risk are classified as blasting, use of mining operations, exploitation, fortification and amacizar. Similarly, other researchers classified risk as low, medium, high, or extremely high based on the risk rating calculated by the product of consequences, probability, and exposure to the event at the workplace. Authors have also classified risk based on the association with major hazards due to different mining operations like drilling, blasting, transporting, inundation, ventilation, illumination, processing of minerals, fire and coal dust explosion, electrical, and hazards in underground mines like fall of roof, sides, air blast etc [18,[50], [51], [52], [53], [54], [55]]. Risk profiling of any organization is very important activity for identifying the critical groups and treating them and for further suitable deployment of manpower according to risk involved in any activity.

This study aims to evaluate the weightage of each influential factor on risk tolerance and subsequently identify the most significant factor among all using statistical tools. Further, organisational risk profiling and risk classification are done based on the responses received on the specially prepared questionnaire to identify the probable causes and reduce unsafe behaviours or practises at the workplace. For the above-mentioned objectives, a suitable questionnaire was prepared based on the exhaustive list of influential factors obtained from the literature review and previous accident enquiry reports available with DGMS, validated with a base line survey in the mining industry with special reference to the Indian coal industry. After validation, the factors were narrowed down to 36 total factors based on the study area, which were found to be significant based on the responses received from the questionnaire survey. Afterwards, an onsite survey was done with 606 respondents of different categories like non-executive, executive, and supervisory staff, to receive the responses. Based on the received responses, factors were identified, organisational risk profiling and risk classification were done to identify the significant factors, critical groups and nature of risk being taken by these groups respectively. The previous studies conducted were related to or limited to risk perception, and were limited to non-mining fields and were not conducted in Indian conditions. So, the authors have decided to carry out studies on risk tolerance as current studies have shown that risk tolerance substantially influences decision making at the workplace while dealing with risk.

The outcome of the study could be utilised by the organization for deployment of employee according to their risk profiling, the formation of a safety policy considering the focus on critical factors, the design of customised safety training modules for various groups of employees belonging to different levels of risk tolerance, and the selection of employees for rescue training. In addition, the combined consideration of all the three major outcomes of this study will be very helpful tool for improving the safety standards of organisations.

2. Methodology

In this context, initially a comprehensive literature survey, a study of accident enquiry report in safety critical industries with regard to behavioural aspects of individuals at the workplace, and a base line survey in various mines were done. Based on the above study, an exhaustive list of factors was identified and a questionnaire was prepared for the study in order to collect the data set. The selection of mines was based on accessibility, productivity, and the strength of the manpower engaged. An on-site survey was conducted among the identified manpower (all the three classes of miners i.e., executives, supervisory staff, and non-executives were included in the survey) belonging to the selected mines. Data responses received from the onsite survey were analyzed, and subsequently critical factors were identified, organization risk profiling and risk classification was done. Based on the results, recommendation were suggested for the improvement of the safety performance of the organization. The flowchart of the proposed methodology is shown in Fig. 1.

Fig. 1.

Flowchart of the proposed methodology.

2.1. Mine selection and data collection

Total 31 opencast mines from three major coal producing subsidiaries were selected from the northern part of India for data collection, field-based observations, and consultation with mine management and safety professionals. The criteria of subsidiary selection were accessibility (permission and compliance). However, the selection of mines was based upon the annual production (criteria of selection: mines having minimum production of 1000 tons per day) and manpower engaged (criteria of selection: mines having a minimum of 250 skilled and non-skilled workers combined). On the basis of the criteria mentioned and the accessibility issues, the number of mines was narrowed down to the study area. The method of excavation used was a shovel-dumper combination for all the mines from all the subsidiaries. The workers included in the study belong to three categories: executives (which includes associate mine managers, mine managers, general managers, and other higher officials involved in the mining operations directly or indirectly), non-executives (which includes manpower other than executives and supervisory staff such as machine operators, drillers, and helpers, etc.), and supervisory staff (which includes foreman, mining sirdar and overman).

For this study, based on the factors (a total of thirty-six factors) that influence an individual’s risk tolerance with respect to the mining industry, a questionnaire with forty-two (42) close-ended questions was prepared to perform a survey among miners (or respondents) for data collection. The close-ended questions require respondents to answer them based on discrete categories or levels. In general, we divide the questionnaire into three parts. The first part includes four (04) close-ended questions to collect the personal information of respondents, i.e., designation, age, sex and work experience. The second part contains one (01) close-ended question to know the nature of risks miners usually take and one (01) close-ended question to categorize the miners into five classes of risk tolerance.

• 1.Class 1:Very less risk-tolerant
• 2.Class 2:Less risk tolerant
• 3.Class 3:Moderate risk tolerant
• 4.Class 4:High risk tolerant
• 5.Class 5:Very high risk tolerant

Herein, the very less risk-tolerant class represents respondents who take the risk at the workplace very rare, the less risk-tolerant class signifies individuals who take a risk once a year, moderate risk-tolerant class means miners who take risk once a month, high risk-tolerant class denotes respondents who take the risk every other day, and very high risk-tolerant class indicates individuals who take risk daily. The third part includes thirty-six (36) closed-ended questions to capture how much each factor (or feature) influences an individual to take the risk on a Likert scale ranging from one to five, with one meaning minimum influence and five denoting maximum influence.

After completing the standard protocol for consent and the briefing session for the respondent, researchers conducted the questionnaire survey on site, so they could explain the items if respondents had any questions, and a total of 930 questionnaires were sent out to them. They have asked to assess the impact of each influential factors on their risk tolerance capacity and specifically answer the nature of risk they usually take at their workplace based on their experience, along with the frequency of risk taking at their workplace. A total of 324 questionnaires were excluded because of missing values and unprofessional responses. The final sample included 606 valid questionnaires from all three subsidiary A, B and C, yielding a total valid response rate of 65.16%among the 930 forms distributed as shown in Table 1.

Table 1.

Summary of final manpower who completed the questionnaire survey.

Subsidiary	Executive	Non-Executive	Supervisory staff	Total valid response
A	68	65	59	192
B	65	69	72	206
C	62	68	78	208

In Table 2, the demographic profile of the workers is shown, included gender, age, work experience and class. Worker gender distribution showed 98.01% (n = 594) were males, while the remainder were females. The age of workers ranged from 18 to 60. According to the worker experience survey (n = 429), 70.8% had been employed in their current positions for over five years, while 29.2% has been employed for less than five years. The percentage of executive, non -executive and supervisory staff were in the final data set were 32.17%, 33.33%, and 34.5%) respectively.

Table 2.

Demographic characteristics of respondents who completed the survey (N = 606).

Characteristics	Items	Frequency	Percentage %
Gender	Male	594	98.01
	Female	12	1.99
Age	Less than 25 years	67	9.32
	25–35	194	32.11
	35–45	153	31.25
	45–55	140	23.56
	More than 55 years	52	9.11
Work experience	Less than 5 years	69	11.37
	5–10	219	36.15
	10–20	172	28.48
	20–30	107	17.68
	More than 35 years	39	6.32
Designation	Workers	202	33.33
	Supervisory staff	209	34.5
	Executive	195	32.17

2.2. Risk profiling

Risk profiling of any organization gives an idea of distribution of employee based upon the frequency of risk taken by them at workplace while dealing with risk. It helps in identifying the critical groups having high risk tolerant employee. Any organization may use this data for improving the safety standard at workplace by treating them and engaging in safer behavior. It is also important to have a system of periodical risk profiling to have an exact status of individual or organization. The profiling will also be helpful in designing the customized training module for various groups belonging to different risk profile.

In this study, total of 606 miners were categorized based upon the risk profiling. It is found that among all the three subsidiaries, very high risk tolerant employees belong to the subsidiary A and subsidiary C is having maximum number of very low risk tolerant employee as shown in Fig. 2(A-C). Subsidiary A is having highest number of employees falling in the class of high risk tolerant group (21%) whereas subsidiary A is also having maximum employee in the low risk tolerant group. The employee falling under the moderate category was 12%, 19%, 22% for subsidiary A, B and C respectively. From Fig. 2(A-C) it is observed that subsidiary A need immediate attention among all the subsidiaries in order to reduce the risk tolerance level of their employees belonging to critical group for improving the overall safety standard of the subsidiary.

Fig. 2.

Risk profiling of subsidiary A, B and C.

2.3. Risk classification

Researchers have categorized risk on various parameters like based on the activity, risk rating and nature of hazards. In this study, risk classification was based upon the nature of the risk taken by the individual at the workplace related to operational activity, improper use of PPE and other safety equipment, and all others, which includes every other activity not covered in the first two categories.

The operational activity includes drilling, blasting, transporting, failure of dumps, sudden subsidence, processing of minerals, fire and coal dust explosions, electrical, inundation, ventilation, illumination, and hazards in underground mines like falling roofs, sides, air blast, etc. Improper usage of PPE and other safety equipment includes not wearing a helmet and safety shoes, specs, jacket, or gloves due to a number of silly reasons like sweating, irritation, peer pressure, the unavailability of proper sizes, improper training, a lack of safety awareness, etc.

Once the risk profiling was done and the critical groups were identified, the next step was to identify the nature of the risk based on the risk classification system. This will felicitate the organization or mine management to get the complete information about the individual employee and accordingly necessary action could be taken for improving safety.

2.4. Statistical tools for assessment of the effects of input parameters on output

The factors used for the study and preparation of the questionnaire were then evaluated using statistical tools. Statistical methods were employed individually on each factor to check its influence on the output. The Pearson test was carried individually for each subsidiary to identify the critical factors for each subsidiary, and an overall analysis was done to find the factor variation depending upon the responses of the respondents from various subsidiaries. The ranking of the factors was done to find the critical factors among the 36 factors. The pearsons test values have been shown in Table 4. This table has helped to identify the critical 10 factors that can help mine management identify and conduct this survey within the minimum amount of time and resources to attain maximum workplace safety. The identification of the critical factors was done to get the maximum safety with minimum resources and limited time. The list of 10 critical factors for all three subsidiary and cumulative rankings is also done as shown in Table 3.

Table 4.

P-value of the pearsons test.

Factors	P-value	Factors	P-value	Factors	P-value	Factors	P-value	Factors	P-value
F1	3.76E-33	F8	1.25E-21	F15	5.16E-62	F22	3.28E-41	F29	4.69E-40
F2	5.38E-64	F9	4.76E-39	F16	8.83E-40	F23	8.17E-56	F30	1.18E-31
F3	6.99E-55	F10	1.26E-15	F17	7.8E-18	F24	1.89E-37	F31	3.25E-64
F4	5.51E-42	F11	2.01E-31	F18	7.8E-18	F25	1.89E-37	F32	4.65E-26
F5	2.92E-38	F12	5.28E-28	F19	1.23E-20	F26	9.43E-44	F33	3.73E-57
F6	2.79E-36	F13	7.28E-44	F20	3.28E-41	F27	8.61E-50	F34	6.91E-34
F7	1.27E-35	F14	8.63E-41	F21	3.28E-41	F28	4.38E-21	F35	1.16E-13
								F36	3.76E-33

Table 3.

Ranking of critical factors.

RANK	SUBSIDIARY A	SUBSIDIARY B	SUBSIDIARY C	Cumulative Ranking
I.	Socio economic factor	Socio economic factor	Management commitment	Socio economic factor
II.	Outcome of noncompliance	Outcome of noncompliance	Acceptance of wrong practices	Educational background
III.	Decision motivation	Educational background	Familiarity with the task	Outcome of non-compliance
IV.	Overconfidence	Welfare	Educational background	Acceptance of wrong practice
V.	Acceptance of wrong practices	Risk perception	Acceptance of LTA	Management commitment
VI.	Educational background	Decision motivation	Outcome of noncompliance	Familiarity with the task
VII.	Management commitment	Marital status	Socio economic factor	Welfare
VIII.	Marital status	Acceptance of wrong practices	Safety culture	Marital status
IX.	Familiarity with the task	Familiarity with the task	Supervision	Decision motivation
X.	Welfare	Site layout and housekeeping	Welfare	Over confidence

Ethical approval

The only human participation in this study was a questionnaire survey of coal mine workers. While conducting the survey, the purpose of the study was described to the participants, and the questions were oriented basically towards their opinion about the safety culture, practices, etc. There was no question to disclose privacy or any kind of personal matter that is ethical in nature. However, the Doctoral Scrutiny Committee (DSC) of the Institute reviews the process of conducting the study and any results or observations and discusses them before the DSC. The purpose of the survey was explained to the participants, and it was entirely voluntary. Oral informed consent process was followed before commencement of questionnaire survey and all the participants filled out the questionnaire themselves.

3. Results, discussion and conclusion

At any work place, including mining, objective assessment of risk tolerance is very critical to identify group or individuals having high risk tolerance so that their deployment at high risk activities may be avoided and also for identifying suitable methods for behavioral changes of such individuals to improve the safety performance of the organization as a whole. Similarly, organizational risk profiling, risk classification, and identification of significant factors also provides valuable input for improving the safety standard of the organization. With change in region, the risk profile of organization varies as seen in Fig. 2 (A-C). That employees of subsidiary A are more risk tolerant than the other two subsidiaries. Based on the responses received, different observations of the behavioural aspects of all three subsidiary are described later. The non-executives of subsidiary A are also less aware and ignorant of the safety procedure. The executives of subsidiary A were stringent in adhering to safety guidelines. The subsidiary C has more employees belonging to less risk tolerant group as seen in Fig. 2(A-C). The variation in the results may be due to the change in region, which also changes the attitude of society towards safety and working approaches. The workers of subsidiary C were quite aware of safety regulations and SOPs for majority of the operations at the workplace and were also well versed in the usage of all safety equipment and PPE. The supervisors of subsidiary C were ignorant towards the safety guidelines and their proper implementation. The major cause of subsidiary C being less risk tolerant is due to more previous exposure to accidents, which made the workers more aware of the consequences. The average age group of employees was also very less (25–30 years) for subsidiary C in comparison to the other two subsidiaries, which strictly adhered to the safety regulations. The employees of Subsidiary C belong to both region of subsidiary A and B. So, the number of moderates was higher in subsidiary C. The risk classification study was conducted to identify the nature of risk being taken by the critical groups. It was observed that operational related risk was found mostly in subsidiary A. The risk related to PPE was found mostly in Subsidiary C. The subsidiary B employees’ risk was classified under another category. This risk classification and the frequency of repetitions will help the management decide the necessary course of action according to the dire need and formulate proper training programme and a vocational training schedule to uplift the safety standards of the employees in the organization. The workers in each subsidiary have a high risk profile as they are directly exposed to mining operations in the field, and their working hours on the field are longer than those of the other two groups. This may also be due to a lack of education, ignorance, or peer pressure.

The identified critical factors based on the collective data set as shown in Table 4, such as Individual’s risk tolerance is significantly influenced by the Socio-economic condition they belong to and it (F36) may influence individual’s risk tolerance in both ways.

Similarly, Education (F20) helps employee in developing a better understanding of the safety and occupational health requirement at work place which leads to better implementation of safety management system and thereby further enhancing the safety performances of an organization. Therefore, selection of educated persons for the job is essential in safety critical industries in order to improve the safety performance of the organization.

Repetition of particular type of unsafe act (F12) at workplace over a longer period may lead to acceptance of such acts as usual and safe practice in general. Sometime it becomes the most accepted way of performing any job which ultimately increases the level of risk tolerance among employee and so any job performed with such wrong procedures should be immediately stopped.

If the statutory noncompliance (F10) leads to heavy penalty like suspension from job or huge monetary penalty, employee may decide to conduct themselves in a less risky manner. In contrary to that lenient management induces higher risk tolerance level among employee and therefore, provision for dealing with wrong doer at workplace should be formulated accordingly.

Basically, the top management through their actions and initiatives can exhibit their commitment towards safety and hence management commitment (F1) stimulates the organization as a whole to make safety as top priority.

When performing routine task, like maintenance and repair, employee takes procedural shortcuts ignoring inherent hazards of doing so due to excessive familiarity or repetition of the job (F30) and resulting higher risk tolerance level.

Experience from Indian mining industry also shows that the mining companies providing better welfare amenities are having better safety culture and workers tend to take less risk at workplace because of better risk perception and which eventually reduces the risk tolerance of individuals.

Family responsibility of a married person motivates him to take less risk at workplace and hence married persons have lower risk tolerance level than unmarried person with comparatively less responsibility. So, deployment of married persons at risky job is more preferrable than the unmarried.

Motivational measures (F16) like safety incentives as cash rewards enhance positive attitudes towards safety, which eventually lower the risk tolerance level among employees and thereby enhance the safety performances of an individual, a group, or the organization as a whole. In contrast, if production incentives are more frequently adopted for improving production, employees will gradually develop a sense of ignorance towards safety, which eventually will increase the risk tolerance.

Overconfident individuals (F25) may take higher risks without proper assessment of the situation or identification of hazards and make irrational decisions. Therefore, if management observes such an instinct in any individual, they should not be deployed in any risky job. There have been a lot of studies (macro and micro analysis) conducted in the past by various researchers to improve the safety standard of an organization. Safety is given the most important concern by majority of individual or organizations, but mostly the safety protocols are not followed seriously at an individual or organisational level due to many reasons like a culture of denial, peer pressure, work load and time constraint, safety culture within the organization, a lack of proper supervision, overconfidence, acceptance of wrong practices in general, acceptance of less than adequate design, overtrust on the equipment, etc. There have been a lot of cases in the past where accidents occured due to individuals’ unsafe behavior and resulted in fatalities.

Safety professionals and organizations with limited resources and time are suggested to focus first on these 10 critical influential factors for reducing the individuals’ risk tolerance. Safety policy makers must consider these critical factors while framing policies for raising safety standards. In a similar way, the organizational risk profiling (5 class labels) and risk classification system (3-way risk classification system) will be utilized for finding the critical groups having high risk tolerance and also for knowing the nature of risk being taken respectively. Organisational risk profiling will help organisation in deployment of right person at right position which basically means engagement of less risk tolerant employee in comparatively more risky job and more risk tolerant employee in less risky job. It will also help management identify critical groups with high risk tolerance and treat them in order to engage them in safe behaviour. The study is limited to Indian conditions so the local factors depending upon manpower, region etc might vary but the critical factor analysis suggested in this study is applicable in every conditions. The accuracy of the study can be further improved by increasing the sample size.

In future more detailed study could be done for identifying the exhaustive list of factors and also other techniques may be utilized for finding the significant factors among all. The five-way class label used in the study for organizational risk profiling may include smaller denominations for assessing the frequency more precisely. Similarly, the 3-way risk classification system may be improved by including more sub classification for deeper understanding or by further subdividing it based on the severity of the risk. This will enable the managers to act accordingly and help reduce accidents and improve the mine safety by engaging employees in safer behavior.

Author contribution statement

Deepak Kumar: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Ram Madhab Bhattacharjee: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Data will be made available on request.

Declaration of interest’s statement

The authors declare no competing interests.