Risk Factors Assessment of Musculoskeletal Disorders among Professional Vehicle Drivers in India Using an Ordinal Priority Approach

Abstract

Professional driving involves sitting in uncomfortable positions, navigating difficult terrain and roads, and occasionally conducting small repairs and other auxiliary transportation duties while at work for long periods. Drivers who engage in these activities may develop a variety of musculoskeletal disorders (MSDs). MSDs in professional drivers are accompanied by several risk factors. In this study, the various risk factors for MSD have been identified through the literature reviews, discussions with professional drivers, and consultations with ergonomics specialists. This study employed the ordinal priority approach (OPA), a multi-criteria decision-making (MCDM) technique, to rank the identified risk variables for MSD in order of importance. The same OPA method has also been used to identify the group of professional drivers who use eight different types of vehicles and are more likely to develop MSDs. The analyses findings show that the five main risk factors for MSDs among drivers are prolonged sitting, restricted posture, working hours, alcohol consumption, and uncomfortable seating. Additionally, among all drivers regarded as professionals, truck drivers are found to be the most at risk. For the study’s conclusions to be validated, a sensitivity analysis was also carried out. The results of this study are anticipated to help formulate strategies for lowering these hazards through the ergonomic design of drivers’ cabins by automobile OEMs (Original Equipment Manufacturers) and vehicle scheduling by concerned transportation organizations to reduce driver tiredness.

1. Introduction

A crucial component of people’s daily life is transportation. Professional drivers play a significant role in the transportation system, and their dependability and productivity are key factors in the system’s effectiveness [1]. Professional drivers are individuals who must operate a vehicle as part of their line of work, such as bus, taxi, or truck drivers [2]. Professional driving is a stressful job that is made more unpleasant by things such as bad weather, the speed, intensity, and density of the traffic flows, traffic jams, unreliable transportation schedules, unclear holidays, convoluted routes, etc. [3]. Drivers are exposed to activities that increase their risk of lower back pain and other spinal injuries, such as prolonged sitting, whole-body vibrations, uncomfortable postures, etc. Due to the aforementioned, professional drivers are always at risk for occupational diseases, such as oncologic diseases, dysmetabolic disorders, gastrointestinal issues, musculoskeletal system mobility-related complications, and cardiovascular complications [1]. The most frequent occupational injuries among professional drivers are musculoskeletal disorders (MSDs) of the neck, back, and upper extremities [4]. Along with experiencing physical discomfort, drivers who miss work owing to injuries brought on by MSDs also incur financial losses. Studies have shown that 33% of all workplace illnesses and injuries are caused by MSDs [5]. These illnesses’ onset is largely linked to a variety of work-related causes, which can be divided into three categories: individual factors, work-related psychosocial factors, and work-related physical factors or occupational factors [6]. The high prevalence of musculoskeletal injuries has been attributed to occupational factors, such as whole-body vibration and extended sitting [7], as well as psychosocial issues [8]. With almost 296 million registered vehicles, India has the third-largest road network in the world [9] and relies heavily on professional drivers for both public transportation and freight movement. In order to protect the health of professional drivers, it is necessary to address MSDs and their consequences. The objectives of this study are to identify the risk factors for MSDs in driving jobs, rate them, and identify the group of vehicle drivers who are most at risk as a result of these risk factors.

There are seven sections in the paper. Based on a review of the research and discussions with specialists in the fields of ergonomics, medicine, and professional driving, Section 2 lists every risk factor for MSD. The OPA approach is described in Section 3. The approach for ranking the MSD variables and various driving contexts is described in Section 4. The sensitivity analysis is presented in Section 5, and Section 6 outlines the conclusion and potential future research topics. Section 7 closes the work by providing research implications covering theoretical, practical, or methodological contributions of the present study.

2. Identification of MSDs’ Risk Factors

Drivers of tractors, buses, trucks, heavy machinery (such as cranes, excavators, and earthmovers), and cars who are frequently subjected to whole-body vibrations were the subjects of certain epidemiological investigations by Gallais and Griffin [10]. When compared to other industrial and agricultural drivers, they found that automobile drivers had substantially lower levels of whole-body vibration. The postural tension caused by a taxi cab’s restricted leg movement or flexibility has been demonstrated to increase the incidence of musculoskeletal problems in drivers [11]. Additionally, the urban area’s extremely congested traffic conditions and frequent stops put drivers under a lot of physical strain [12]. Some research [13,14] discovered a connection between workplace characteristics such as repetitiveness and static posture, as well as musculoskeletal problems, and individual aspects such as gender. Smoking is frequently cited as a contributing factor to back and neck discomfort, in addition to work-organizational and psychosocial issues, but excessive alcohol intake has been shown to have a protective effect [15]. Additionally, other research claimed that the most important risk factors for lower back and neck pain were personal, occupational, and psychological factors [16,17].

Truck drivers perform additional tasks such as loading and unloading the vehicle and getting in and out of the vehicle, which results in muscular injury, according to Sekkay et al. [18]. Numerous factors, including lengthy driving hours [19], insufficient rest, worn-out driving seats [20,21], poor driving posture [22], and whole-body vibration [23], have been linked to these muscle ailments. Furthermore, numerous research [8,24,25,26] revealed that truck, bus, and taxi drivers experienced lower back pain as a result of extended driving, as well as physical and psychological issues. Due to the adoption of poor body posture while driving, the lower back is the predominant region of the body for musculoskeletal diseases when compared to other sections of the body. According to the research, drivers are particularly vulnerable to developing WMSD due to extended sitting positions, lengthy workdays, continual smoking, vibration, and psychosocial factors [21,24]. Job support has only a weak correlation with musculoskeletal discomfort [27,28], whereas job discontent and stress at work [8,27,29] are important risk factors for musculoskeletal injury. Discovered a substantial correlation between taxi drivers’ lower back pain (LBP) and body mass index (BMI).

Twenty MSD risk factors associated with driving were found after a thorough assessment of the literature and discussions with experts, as shown in

Table 1. MSDs risk factors identified from the literature.

S. No	MSDs Risk Factors	References
1	Gender	Raanaas and Anderson [29]; Berrones-Sanz and Araiza-Diaz [30]
2	Ethnicity	Raanaas and Anderson [29]; AL-Dubai et al. [31]
3	BMI	Raanaas and Anderson [29]; Bovenzi et al. [32]; AL-Dubai et al. [31]; Nahar et al. [33]; Borle et al. [34]; Bhaumik and Anjenaya [20]; Mozafari et al. [35].
4	Less physical exercise	Raanaas and Anderson [29]; AL-Dubai et al. [31]; Wanamo et al. [36]; Wang et al. [37].
5	Age	Bovenzi et al. [32]; Ahmad et al. [38]; Borle et al. [34]; Mehta et al. [25]; Bhaumik and Anjenaya [20]; Goon et al. [26]; Mozafari et al. [35].
6	Alcohol consumption	AL-Dubai et al. [31]; Wanamo et al. [36]; Sekkay et al. [18].
7	Smoking	AL-Dubai et al. [31]; Wang et al. [37]; Tamrin et al. [24].
8	Restricted posture	Bulduk et al. [39]; Srivastava and Kiran [40]; Hoy et al. [41]; Agarwal et al. [42]; Mehta et al. [25]; Robb and Mansfield [21].
9	Repetitiveness	Bulduk et al. [39].
10	Vibration	Bulduk et al. [39]; Bovenzi et al. [32]; Funakoshi et al. [43]; Srivastava and Kiran [40]; Sekkay et al. [18]; Shaik et al. [44]; Mehta et al. [25]; Robb and Mansfield [21].
11	Uncomfortable seat	Serrano-Fernández et al. [12]; Wanamo et al. [36]; Tamrin et al. [24]; Bhaumik and Anjenaya [20].
12	Increased number of working hours	Serrano-Fernández et al. [12]; Ahmad et al. [45]; Abledu et al. [28]; Srivastava and Kiran [40]; Wang et al. [37]; Nahar et al. [33]; Shaik et al. [44]; Mehta et al. [25]; Bhaumik and Anjenaya [20]; Raanaas and Anderson [29].
13	Physical loading	Bovenzi et al. [32]; Wanamo et al. [36]; Srivastava and Kiran [40].
14	Prolonged sitting	Srivastava and Kiran [40]; Tamrin et al. [24]; Gallais and Griffin [10]; Robb and Mansfield [21].
15	Years of experience	Wang et al. [37]; Wanamo et al. [36]; Nahar et al. [33]; Mehta et al. [25]; Bhaumik and Anjenaya [20].
16	Less no. of sleeping hours	Wang et al. [37]; Sekkay et al. [18].
17	Less no. of breaks	Ahmad et al. [38]; Wanamo et al. [36].
18	Job stress	Bulduk et al. [37]; Funakoshi et al. [43]; Chen et al. [8]; Ahmad et al. [38]; Abledu et al. [28]; Ads et al. [46]; Tamrin et al. [24]; Mehta et al. [25].
19	Job support	Raanaas and Anderson [29]; Bovenzi et al. [32].
20	Job dissatisfaction	Chen et al. [8]; Abledu et al. [28].

. As stated in

Table 2. The hierarchical structure of MSDs’ risk factors.

Sr. No.	Main Factor	Sub-Factor	Notation
1	Individual factors (IF)	Gender	GE
		Ethnicity	ET
		BMI	BM
		Less physical exercise	LP
		Age	AG
		Alcohol consumption	AC
		Smoking	SM
2	Occupational factor (OF)	Restricted posture	RP
		Repetitiveness	RE
		Vibration	VI
		Uncomfortable seat	US
		Increased number of working hours	WH
		Physical loading	PL
		Prolong sitting	PS
		Years of experience	YE
		Less no. of sleeping hours	SH
		Less no. of breaks	LB
3	Psycho-social factor (PF)	Job stress	JST
		Job support	JS
		Job dissatisfaction	JD

, they were divided into three major categories: individual factors (IF), occupational factors (OF), and psychosocial factors (PF).

3. Description of the OPA Methodology

The best weights and ranks for the risk factors for MSDs are determined in this study using the ordinary priority approach (OPA). The rating of professional drivers who are more susceptible to MSD risk factors uses the same methodology. The most recent method for resolving MCDM issues that may be used for both individual and group decision-making is the ordinal priority approach (OPA), which was put forth by Ataei et al. [9]. OPA determines the weight of experts, criteria, sub-criteria, and alternatives in a straightforward manner. Sadeghi et al. [47] reported the following advantages of OPA over other MCDM tools.

• The OPA method does not require a pairwise comparison matrix and instead uses the order of criteria and alternatives.
• The OPA method does not require a decision-making matrix.
• The OPA method does not require normalization practice
• OPA method does not require the averaging practice for accumulation of the experts’ instead uses a mathematical model for the same.
• OPA concurrently evaluates the rank of alternatives, the weight of experts, and the weight of attributes.

Mahmoudi and Javed [48] provided the essential sets, indexes, variables, and parameters associated with the OPA, which are shown in

Table 3. Sets, parameters, and variables for OPA.

Sets
L	Set of experts
M	Set of criteria
N	Set of alternatives
Parameters
l	Index of experts (1…a)
m	Index of criteria (1…b)
n	Index of criteria (1…c)
Variable
Z	Objective function
$W_{lmn}^{\left(r\right)}$	Importance of nth alternative based on mth criteria by lth expert at rth rank
$B_{lmn}^{\left(r\right)}$	The nth alternative is based on mth criteria by lth expert at rth rank

.

Here, n alternatives are ranked according to the following steps (Ataei et al. [49])

• Ranking of the criteria by each of the experts
• Ranking of the experts based on the organizational chart, educational level, background, experience, etc.
• Ranking of the alternatives by each expert based on each criterion

In

Table 4. Experts and details.

Expert	Designation	Experience (in Years)	Specialization	Rank
Exp-1	Deputy General manager	21	Design Engineer	1
Exp-2	Professor	21	Human factors& Ergonomics	2
Exp-3	Professor	18	Human factors& Ergonomics	3
Exp-4	Assistant Manager	8	Design Engineer	4
Exp-5	Assistant Manager	6	Design Engineer	5

, $B_{lmn}^{\left(r\right)}$ is the nth alternative centered on mth criteria by experts l at rth rank. Moreover, $W_{lmn}^r$ is the importance value of nth alternative centered on mth criteria by experts l at rth rank. The ranking of alternatives centered on each criterion is shown by Equation (1)

$$B_{lmn }^1\ge B_{lmn}^2 \ge B_{lmn}^3 \ge \dots .. \ge B_{lmn}^r \ge B_{lmn}^{r+1} \ge \dots \dots \ge B_{lmn}^c\hspace{1em}\hspace{1em}\forall l, m, n$$

(1)

The only logical assumption of $B_{lmn}^r$ ≥ $B_{lmn}^{r+1}$_lmn is that $W_{lmn}^r$ should be considerably greater than $W_{lmn}^{r+1}$. Hence, Equation (2) holds.

$$W_{lmn}^1 \ge W_{lmn}^2 \ge W_{lmn }^3\ge \dots .. \ge W_{lmn}^r \ge W_{lmn}^{r+1} \ge \dots \dots \ge W_{lmn }^{c-1}\ge W_{lmn}^c\hspace{1em}\forall l, m, n$$

(2)

As such, the importance weight difference in successive rank, Equation (2), can be modified and written as Equation (3)

$$\begin{gathered} W_{lmn}^1-W_{lmn}^2 \ge 0 \\ {W}_{lmn}^2-W_{lmn}^3 \ge 0 \\ {W}_{lmn}^{r }-W_{lmn}^{r+1} \ge 0 \\ {W}_{lmn}^{c-1}-W_{lmn}^c \ge 0 \end{gathered}$$

(3)

Multiplying both sides of Equation (3) by l, m, and r, it will be modified to generate Equation (4)

$$l\left(m\left(r\left(W_{lmn}^r-W_{lmn}^{r+1}\right)\right)\right) \ge 0\hspace{1em}\hspace{1em}\forall l, m, n, \mathrm{and} r$$

(4)

Equations (1)–(4) can be used for prioritizing and evaluating the importance and weight of the alternatives. Moreover, the same method can be utilized for the criteria and experts. Ataei et al. [49] have suggested the following steps for the ordinal priority approach (OPA) in detail.

Step 1: Selecting the decision criteria.

The criteria, as well as their sub-criteria, are specified and included in the decision-making process as per analyst opinion.

Step 2: Designating and ranking the experts.

The ranking of the experts who participate in the decision-making process (single or group) may include several factors such as their education level and year of experience.

Step 3: Ranking of criteria.

At this stage, experts are asked to prioritize the criteria based on their experience. Experts have the liberty to include or exclude any criteria in the ranking process and mathematical model.

Step 4: Ranking of alternatives in each criterion.

In this stage, experts prioritize each alternative in each criterion according to their expertise. In the case of group decision-making, experts prioritize each alternative by taking each criterion into consideration.

Step 5: Solving of mathematical model for optimal weights.

The mathematical model, which was developed based on steps 1 and 2 shown in Equation (5), is solved to obtain the optimal weight of the criteria.

$$\begin{array}{ll}\mathrm{Max} Z& \\ Z\ge l \left(m \left(r\left(W_{lmn}^r \ge W_{lmn}^{r+1}\right)\right)\right)& \forall l, m, n, \mathrm{and} r\\ Z\ge lmn{W}_{lmn}^c& \forall l, m, n{\displaystyle \sum }_{l=1}^a{\displaystyle \sum }_{m=1}^b{\displaystyle \sum }_{n=1}^c{W}_{lmn}=1 \end{array}$$

(5)

$W_{lmn} \ge 0$, Where Z doesn’t have any restriction on its sign.

Step 6: Evaluation of the weight of criteria, alternatives, and experts.

Based on the results of the mathematical model in Equation (5), the weights of criteria, alternatives, and experts are calculated based on Equations (6)–(8).

$$W_l={{\displaystyle \sum }}_{m=1}^b{{\displaystyle \sum }}_{n=1}^c{W}_{lmn}\hspace{1em}\hspace{1em}\forall l$$

(6)

$$W_m={{\displaystyle \sum }}_{l=1}^a{{\displaystyle \sum }}_{n=1}^c{W}_{lmn}\hspace{1em}\hspace{1em}\forall m$$

(7)

$$W_n={{\displaystyle \sum }}_{l=1}^a{{\displaystyle \sum }}_{m=1}^b{W}_{lmn}\hspace{1em}\hspace{1em}\forall n$$

(8)

4. Implementation of the Methodology

Three primary categories—individual (IF), occupational (OF), and psycho-social—were used to classify the twenty MSD risk variables that were found in the literature (PF). A panel of five experts provided the input data for the rankings of risk factors and potential solutions (Refer Appendix A and Appendix B). The professors who were selected were actively involved in the MCDM research projects. Additionally, some of them focus on ergonomics and know the difficulties that drivers confront, which are described in the literature. Since they were managers of logistics firms that previously used professional drivers, the Deputy General Managers, Assistant Managers, and Managers were chosen for the study on professional drivers. They were the ones who were most familiar with the driver’s issues and who understood the seriousness of such circumstances.

The experts were ranked keeping in mind their experience and education level. The details of the experts and their ranking are presented in Table 4.

Further, the category of professional drivers considered in this study who are vulnerable to MSD risk is shown in

Table 5. Category of professional drivers.

Category	Notation
Cab Driver	A
Heavy machinery driver	B
Bus driver	C
Auto-rickshaw driver	D
E-rickshaw driver	E
Tractor driver	F
Truck driver	G
Two-wheeler taxi driver	H

.

The ideal weight of the risk factors for MSD was then computed using the OPA methods described in Section 3. The severity of each risk factor for each group of professional drivers was ranked by experts, and this ranking was utilized to determine the best weight of the alternatives. The risk variables for MSDs and the various professional driver groups were then rated according to their ideal weights. The ideal weight of the primary risk variables was eventually calculated using the optimal weight of the sub-risk factors.

Table 6. Prioritization of MSDs’ risk factor based on experts’ opinion.

Priority Order	Experts
	1	2	3	4	5
1	PS	AC	RE	PS	RP
2	RP	SM	WH	RP	US
3	US	WH	AG	WH	PS
4	WH	PS	RP	US	AG
5	SH	SH	VI	SH	VI
6	LB	LB	PS	AG	WH
7	LP	JST	US	VI	RE
8	AG	AG	PL	LP	PL
9	RE	GE	YE	LB	LP
10	PL	US	SH	PL	SH
11	VI	VI	BM	RE	LB
12	BM	RP	LP	BM	JST
13	ET	RE	GE	SM	SM
14	JST	PL	AC	JST	AC
15	AC	YE	SM	ET	BM
16	SM	JS	ET	GE	JS
17	JS	JD	LB	JS	JD
18	JD	BM	JST	YE	YE
19	GE	LP	JD	AC	GE
20	YE	ET	JS	JD	ET

displays the input information connected to each expert’s ranking of the risk factors for MSDs.

Subsequently, experts were also asked to prioritize the different professional driver groups according to each MSDs’ risk factor. The opinion of expert1 related to this prioritization is shown in

Table 7. Ranking of different professional driver groups based on the opinion of Expert-1.

Expert	Risk Factor	Professional Driver Groups
		First Priority	Second Priority	Third Priority	Fourth Priority	Fifth Priority	Sixth Priority	Seventh Priority	Eight Priority
Exp-1	Gender	G	C	A	B	F	D	E	H
	Ethnicity	G	C	A	B	F	D	E	H
	BMI	B	C	F	G	A	D	E	H
	Less physical exercise	G	C	B	A	F	D	E	H
	Age	A	G	C	B	F	D	E	H
	Alcohol consumption	G	B	C	D	E	A	F	H
	Smoking	G	C	A	B	D	E	F	H
	Restricted posture	G	C	A	B	D	E	F	H
	Repetitiveness	A	G	C	D	E	B	F	H
	Vibration	B	F	G	C	D	A	E	H
	Uncomfortable Seat	A	G	C	D	E	B	F	H
	Increased number of working hours	A	C	G	B	D	E	F	H
	Physical loading	G	B	F	D	E	A	C	H
	Prolong sitting	G	A	C	D	E	B	F	H
	Years of experience	B	G	C	A	F	D	E	H
	Less no. of Sleeping hours	G	A	B	C	D	E	F	H
	Less no. of breaks	G	A	C	B	D	E	F	H
	Job stress	G	C	A	B	D	E	F	H
	Job support	A	C	D	E	G	B	F	H
	Job dissatisfaction	G	A	C	B	D	E	F	H

.

Similarly, the ranking of professional driver groups based on the severity of each MSDs’ risk factors by other experts was also obtained. By using the input data from Table 6 and Table 7, the linear mathematical model was solved, and computed the optimal solution of the model’s variable, such as the importance weight of MSDs’ risk factors and the weight of different categories of professional drivers and experts using Equations (6)–(8) described in Section 3. The degree of significance of the experts is represented by the sum of weight related to decision-making experts. Hence, the importance weight of experts is $W_1=0.438$,$W_2=0.219$, $W_3=0.146$, $W_4=0.109$, and $W_5=0.087,$ respectively. In addition to this, the ratio of the optimal weight of each risk factor and the aggregate weight of each expert displayed in

Table 8. Importance value of each risk factor from the perspective of each expert.

Expert	Degree of the Significance of Criteria
	GE	ET	BM	LP	AG	AC	SM	RP	RE	VI	US	WH	PL	PS	YE	SH	LB	JST	JS	JD
Exp-1	0.0146	0.0214	0.0232	0.0397	0.0347	0.0185	0.0174	0.1390	0.0309	0.0253	0.0927	0.0695	0.0278	0.2780	0.0139	0.0556	0.0463	0.0199	0.0164	0.0154
Exp-2	0.0309	0.0139	0.0154	0.0146	0.0347	0.2780	0.1390	0.0232	0.0214	0.0253	0.0278	0.0927	0.0199	0.0695	0.0185	0.0556	0.0463	0.0397	0.0174	0.0164
Exp-3	0.0214	0.0174	0.0253	0.0232	0.0927	0.0199	0.0185	0.0695	0.2780	0.0556	0.0397	0.1390	0.0347	0.0463	0.0309	0.0278	0.0164	0.0154	0.0139	0.0146
Exp-4	0.0174	0.0185	0.0232	0.0347	0.0463	0.0146	0.0214	0.1390	0.0253	0.0397	0.0695	0.0927	0.0278	0.2780	0.0154	0.0556	0.0309	0.0199	0.0164	0.0139
Exp-5	0.0146	0.0139	0.0185	0.0309	0.0695	0.0199	0.0214	0.2780	0.0397	0.0556	0.1390	0.0463	0.0347	0.0927	0.0154	0.0278	0.0253	0.0232	0.0174	0.0164

indicates the degree of significance of each risk factor.

The ranking of factors given by the experts shows the significance of the criteria. Therefore, the weight of the criteria obtained after solving the linear mathematical model is listed in

Table 9. Priority weight and ranking of criteria/risk factors.

Sr. No	Risk Factor	Symbol	Priority Weight	Rank
1	Gender	GE	0.0195	16
2	Ethnicity	ET	0.0182	17
3	BMI	BM	0.0214	15
4	Less physical exercise	LP	0.0305	12
5	Age	AG	0.0475	8
6	Alcohol consumption	AC	0.0752	4
7	Smoking	SM	0.0450	9
8	Restricted posture	RP	0.1156	2
9	Repetitiveness	RE	0.0650	6
10	Vibration	VI	0.0339	11
11	Uncomfortable seat	US	0.0722	5
12	Working hour	WH	0.0852	3
13	Physical loading	PL	0.0277	13
14	Prolonged sitting	PS	0.1823	1
15	Year of experience	YE	0.0177	18
16	Less no. of sleeping hour	SH	0.0491	7
17	Less no. of breaks	LB	0.0384	10
18	Job stress	JST	0.0238	14
19	Job support	JS	0.0163	19
20	Job dissatisfaction	JD	0.0154	20

.

Similarly, the degree of significance of different categories of professional drivers is indicated by the ratio of the optimal weight of the category of professional drivers to the aggregate weight of each expert (

Table 10. Importance value of each alternative from the perspective of each expert.

Experts	Degree of the Significance of Alternatives
	A	B	C	D	E	F	G	H
Exp-1	0.2118	0.1101	0.1681	0.0908	0.0628	0.0498	0.2909	0.0156
Exp-2	0.1582	0.1024	0.1438	0.0813	0.0567	0.1215	0.1898	0.1462
Exp-3	0.0893	0.3397	0.1038	0.0687	0.0364	0.1220	0.2113	0.0289
Exp-4	0.1976	0.1398	0.1850	0.0942	0.0596	0.0571	0.2511	0.0156
Exp-5	0.1713	0.1762	0.1835	0.0911	0.0624	0.0707	0.2175	0.0272

). Furthermore, the rank of the category of professional drivers suggested by the experts determines the importance weight of the different categories of professional drivers. As a result, the importance weight of each category of professional drivers is determined after solving the mathematical model, and the ranking of the category of professional drivers based on their importance weight is listed in

Table 11. Priority weight and ranking of alternatives.

Sr. No	Alternatives	Symbol	Priority Weight	Rank
1	Cab drivers	A	0.1771	2
2	Heavy machinery drivers	B	0.1510	4
3	Bus drivers	C	0.1566	3
4	Auto rickshaw drivers	D	0.0859	5
5	E- rickshaw drivers	E	0.0572	7
6	Tractor drivers	F	0.0787	6
7	Truck drivers	G	0.2463	1
8	Two-wheeler taxi drivers	H	0.0472	8

.

The importance weight of the sub-factors determines the weight of the main factors. Finally, the weight of individual factors, occupational factors, and psycho-social factors are obtained, as shown in

Table 12. Priority weight and ranking of main criteria.

Sr. No.	Main Factors	Priority Weight	Rank
1	Individual factors (PF)	0.2572	2
2	Occupational factors (OF)	0.6872	1
3	Psycho-social factors (PF)	0.0556	3

.

Table 12 shows that out of three main factors, ‘occupational factors (OF)’ appears to be the most important, followed by ‘individual factors’ and ‘psycho-social factors.’ Moreover, Table 9 reveals that the sub-factor ‘prolonged sitting (PS)’ and ‘job dissatisfaction (JD)’ are the most important and least important MSDs risk factors, respectively.

OPA suggested that occupational factor is the top-ranked MSDs risk factor, and this finding is supported by the studies conducted by other researchers [50,51,52], in which they also found that occupational factors such as non-neutral posture, repetition, vibration, weightlifting, etc. strongly elevates the MSD risk. Results from Table 11 reveal that the significance of the MSDs risk factors is the maximum among truck drivers and the minimum among two-wheeler taxi drivers. The results also show that the significance of MSDs risk factors among cab drivers is next to that of truck drivers. These results are in line with the results of studies conducted by previous researchers [4,53,54].

5. Sensitivity Analysis

One cannot completely rule out the potential that a change in the rank of the experts will affect the ranking of the sub-factors. As a result, sensitivity analysis is carried out to assess the impact of a change in the experts’ ranking on the weight of the risk factors for MSDs, as well as to check the reliability and robustness of the ranking of the factors. It is carried out by exchanging the expert ranks of every single person. The possible combination of a different set of experts’ ranks is evaluated by using a relation n(n − 1), where ‘n’ represents the number of experts in the group decision-making process. Accordingly, the possible combination of experts’ ranking is shown in

Table 13. Variation in expert’s ranking.

Experts	The Possible Combination of Experts’ Rank
	R-01	R-02	R-03	R-04	R-05	R-06	R-07	R-08	R-09	R-10	R-11	R-12	R-13	R-14	R-15	R-16	R-17	R-18	R-19	R-20
Exp-1	1	1	1	1	2	2	2	2	3	3	3	3	4	4	4	4	5	5	5	5
Exp-2	2	3	4	5	3	4	5	1	4	5	1	2	5	1	2	3	1	2	3	4
Exp-3	3	4	5	2	4	5	1	3	5	1	2	4	1	2	3	5	2	3	4	1
Exp-4	4	5	2	3	5	1	3	4	1	2	4	5	2	3	5	1	3	4	1	2
Exp-5	5	2	3	4	1	3	4	5	2	4	5	1	3	5	1	2	4	1	2	3

.

Table 13 represents the change in the ranking of experts, and the corresponding proportionate change in the weights and rank of different categories of professional drivers is calculated as shown in

Table 14. Variation in weight of categories of professional drivers.

Run	Variation in Weight of Categories of Professional Drivers
	${\mathit{W}}_{\mathit{A}}$	${\mathit{W}}_{\mathit{B}}$	${\mathit{W}}_{\mathit{C}}$	${\mathit{W}}_{\mathit{D}}$	${\mathit{W}}_{\mathit{E}}$	${\mathit{W}}_{\mathit{F}}$	${\mathit{W}}_{\mathit{G}}$	${\mathit{W}}_{\mathit{H}}$
R-01	0.1771	0.1510	0.1566	0.0859	0.0572	0.0787	0.2463	0.0472
R-02	0.1804	0.1512	0.1624	0.0874	0.0587	0.0734	0.2479	0.0387
R-03	0.1862	0.1455	0.1658	0.0887	0.0590	0.0686	0.2534	0.0328
R-04	0.1737	0.1713	0.1560	0.0857	0.0560	0.0753	0.2507	0.0312
R-05	0.1705	0.1659	0.1659	0.0876	0.0587	0.0781	0.2321	0.0413
R-06	0.1820	0.1522	0.1697	0.0896	0.0584	0.0703	0.2450	0.0328
R-07	0.1458	0.2219	0.1421	0.0809	0.0503	0.0912	0.2336	0.0342
R-08	0.1643	0.1495	0.1515	0.0839	0.0560	0.0945	0.2245	0.0759
R-09	0.1801	0.1568	0.1706	0.0895	0.0583	0.0717	0.2394	0.0336
R-10	0.1459	0.2237	0.1432	0.0811	0.0500	0.0916	0.2304	0.0341
R-11	0.1564	0.1661	0.1466	0.0822	0.0540	0.0997	0.2184	0.0767
R-12	0.1676	0.1651	0.1640	0.0868	0.0581	0.0832	0.2244	0.0507
R-13	0.1444	0.2262	0.1437	0.0811	0.0499	0.0924	0.2277	0.0346
R-14	0.1559	0.1672	0.1472	0.0823	0.0539	0.0999	0.2169	0.0767
R-15	0.1632	0.1735	0.1616	0.0859	0.0572	0.0859	0.2215	0.0512
R-16	0.1781	0.1566	0.1697	0.0891	0.0581	0.0744	0.2357	0.0384
R-17	0.1550	0.1686	0.1475	0.0823	0.0539	0.1004	0.2153	0.0770
R-18	0.1629	0.1742	0.1620	0.0860	0.0571	0.0860	0.2206	0.0512
R-19	0.1754	0.1616	0.1683	0.0886	0.0575	0.0760	0.2339	0.0387
R-20	0.1433	0.2259	0.1433	0.0810	0.0498	0.0939	0.2255	0.0374

and

Table 15. Modified ranking of different categories of professional drivers due to change in experts’ rank.

Run	Variation in the Rank of Different Categories of Professional Drivers
	${\mathit{W}}_{\mathit{A}}$	${\mathit{W}}_{\mathit{B}}$	${\mathit{W}}_{\mathit{C}}$	${\mathit{W}}_{\mathit{D}}$	${\mathit{W}}_{\mathit{E}}$	${\mathit{W}}_{\mathit{F}}$	${\mathit{W}}_{\mathit{G}}$	${\mathit{W}}_{\mathit{H}}$
R-01	2	4	3	5	7	6	1	8
R-02	2	4	3	5	7	6	1	8
R-03	2	4	3	5	7	6	1	8
R-04	2	3	4	5	7	6	1	8
R-05	2	4	3	5	7	6	1	8
R-06	2	4	3	5	7	6	1	8
R-07	3	2	4	6	7	5	1	8
R-08	2	4	3	6	8	5	1	7
R-09	2	4	3	5	7	6	1	8
R-10	3	2	4	6	7	5	1	8
R-11	3	2	4	6	8	5	1	7
R-12	2	3	4	5	7	6	1	8
R-13	3	2	4	6	7	5	1	8
R-14	3	2	4	6	8	5	1	7
R-15	3	2	4	5	7	6	1	8
R-16	2	4	3	5	7	6	1	8
R-17	3	2	4	6	8	5	1	7
R-18	3	2	4	6	7	5	1	8
R-19	2	4	3	5	7	6	1	8
R-20	3	1	4	6	7	5	2	8

.

Subsequently, the proportionate change in the weights and ranking of the factors due to the change in the rank of experts was calculated as represented in

Table 16. Variation in criteria weight due to change in expert’s ranking.

Risk Factors	R-01	R-02	R-03	R-04	R-05	R-06	R-07	R-08	R-09	R-10	R-11	R-12	R-13	R-14	R-15	R-16	R-17	R-18	R-19	R-20
GE	0.019	0.018	0.018	0.018	0.018	0.018	0.019	0.023	0.018	0.020	0.024	0.019	0.020	0.024	0.019	0.019	0.024	0.019	0.019	0.020
ET	0.018	0.018	0.018	0.019	0.016	0.018	0.018	0.017	0.017	0.018	0.016	0.016	0.017	0.016	0.016	0.017	0.016	0.016	0.017	0.017
BM	0.021	0.021	0.022	0.022	0.020	0.022	0.023	0.020	0.021	0.023	0.020	0.020	0.023	0.020	0.020	0.021	0.020	0.020	0.021	0.023
LP	0.030	0.032	0.033	0.032	0.030	0.032	0.029	0.025	0.031	0.028	0.024	0.028	0.028	0.024	0.028	0.030	0.023	0.027	0.030	0.027
AG	0.048	0.050	0.047	0.053	0.057	0.050	0.066	0.048	0.052	0.066	0.052	0.057	0.068	0.052	0.059	0.052	0.053	0.060	0.054	0.068
AC	0.075	0.056	0.046	0.041	0.057	0.046	0.041	0.132	0.046	0.041	0.132	0.076	0.041	0.132	0.076	0.055	0.132	0.076	0.055	0.047
SM	0.045	0.036	0.032	0.029	0.037	0.033	0.030	0.072	0.033	0.030	0.072	0.046	0.030	0.072	0.046	0.038	0.072	0.046	0.038	0.033
RP	0.116	0.145	0.140	0.129	0.176	0.141	0.114	0.090	0.151	0.114	0.085	0.167	0.119	0.085	0.164	0.146	0.088	0.164	0.145	0.116
RE	0.065	0.058	0.052	0.084	0.060	0.050	0.139	0.063	0.051	0.138	0.081	0.059	0.138	0.081	0.068	0.051	0.081	0.068	0.056	0.138
VI	0.034	0.036	0.035	0.037	0.043	0.039	0.044	0.034	0.041	0.045	0.036	0.043	0.046	0.037	0.044	0.041	0.037	0.045	0.042	0.046
US	0.072	0.086	0.083	0.077	0.094	0.076	0.064	0.057	0.081	0.064	0.054	0.091	0.065	0.053	0.089	0.079	0.054	0.088	0.077	0.064
WH	0.085	0.077	0.080	0.088	0.072	0.085	0.103	0.090	0.083	0.104	0.095	0.074	0.104	0.096	0.077	0.084	0.096	0.077	0.086	0.104
PL	0.028	0.029	0.029	0.029	0.030	0.029	0.031	0.026	0.029	0.031	0.026	0.030	0.031	0.026	0.030	0.029	0.027	0.030	0.029	0.031
PS	0.182	0.182	0.208	0.189	0.141	0.208	0.138	0.137	0.194	0.138	0.120	0.126	0.131	0.120	0.117	0.187	0.116	0.117	0.182	0.127
YE	0.018	0.017	0.016	0.018	0.017	0.017	0.022	0.019	0.017	0.022	0.020	0.018	0.022	0.020	0.018	0.017	0.020	0.018	0.017	0.022
SH	0.049	0.046	0.049	0.046	0.040	0.049	0.040	0.049	0.047	0.040	0.047	0.040	0.039	0.047	0.039	0.047	0.046	0.039	0.046	0.039
LB	0.038	0.037	0.037	0.035	0.033	0.034	0.029	0.038	0.032	0.028	0.036	0.032	0.027	0.036	0.031	0.032	0.035	0.031	0.032	0.027
JST	0.024	0.023	0.023	0.021	0.024	0.023	0.020	0.028	0.023	0.020	0.028	0.025	0.020	0.028	0.025	0.023	0.028	0.025	0.023	0.021
JS	0.016	0.016	0.016	0.016	0.017	0.016	0.015	0.017	0.016	0.015	0.016	0.017	0.016	0.016	0.017	0.017	0.016	0.017	0.016	0.016
JD	0.015	0.016	0.015	0.015	0.016	0.015	0.015	0.016	0.015	0.015	0.016	0.016	0.015	0.016	0.016	0.015	0.016	0.016	0.015	0.015

and

Table 17. Variation in criteria rank due to change in expert’s ranking.

Risk Factor	R-01	R-02	R-03	R-04	R-05	R-06	R-07	R-08	R-09	R-10	R-11	R-12	R-13	R-14	R-15	R-16	R-17	R-18	R-19	R-20
GE	16	16	17	18	16	16	17	15	16	17	15	16	17	14	16	16	14	16	16	17
ET	17	17	16	16	19	17	18	18	17	18	19	20	18	19	20	18	19	20	18	18
BM	15	15	15	14	15	15	14	16	15	14	17	15	14	17	15	15	17	15	15	14
LP	12	12	11	11	13	12	13	14	12	12	14	13	12	15	13	12	15	13	12	12
AG	8	7	7	6	6	6	5	9	5	5	8	7	5	8	7	6	8	7	7	5
AC	4	6	8	8	7	8	8	2	8	8	1	4	8	1	5	5	1	5	6	7
SM	9	11	12	13	10	11	11	5	10	11	6	8	11	6	8	10	6	8	10	10
RP	2	2	2	2	1	2	3	4	2	3	4	1	3	4	1	2	4	1	2	3
RE	6	5	5	4	5	5	1	6	6	1	5	6	1	5	6	7	5	6	5	1
VI	11	10	10	9	8	9	7	11	9	7	11	9	7	10	9	9	10	9	9	8
US	5	3	3	5	3	4	6	7	4	6	7	3	6	7	3	4	7	3	4	6
WH	3	4	4	3	4	3	4	3	3	4	3	5	4	3	4	3	3	4	3	4
PL	13	13	13	12	12	13	10	13	13	10	13	12	10	13	12	13	13	12	13	11
PS	1	1	1	1	2	1	2	1	1	2	2	2	2	2	2	1	2	2	1	2
YE	18	18	18	17	17	18	15	17	18	15	16	17	15	16	17	17	16	17	17	15
SH	7	8	6	7	9	7	9	8	7	9	9	10	9	9	10	8	9	10	8	9
LB	10	9	9	10	11	10	12	10	11	13	10	11	13	11	11	11	11	11	11	13
JST	14	14	14	15	14	14	16	12	14	16	12	14	16	12	14	14	12	14	14	16
JS	19	19	19	19	18	19	19	19	19	19	18	18	19	18	18	19	18	18	19	19
JD	20	20	20	20	20	20	20	20	20	20	20	19	20	20	19	20	20	19	20	20

.

Table 13 and Table 15 show that the occupation of “truck driving” and the risk sub-factor of “prolonged sitting” maintained the top rank even when the rank of experts shifted from 1 to 5. Additionally, “two-wheeler taxi driving” and “work unhappiness” had the lowest rankings across all types of experts’ rankings. Because the top- and bottom-ranked sub-factors remain the same even when the expert ranks vary, sensitivity analysis supports the robustness and reliability of the weight and ranking that was produced.

Figure 1, Figure 2 and Figure 3 illustrate the variance in the optimal weight and ranking of several categories of professional drivers during sensitivity analysis accordingly. These figures also indicate the results of the sensitivity analysis.

6. Conclusions and Future Scope

MSDs among professional drivers of different types of vehicles hasalways been a major concern for ergonomists, engineers, and other professionals. In the present study, a relatively new MCDM method, i.e., OPA, was employed to compute the weight of the MSD risk factors associated with professional drivers. In addition, the different categories of professional drivers were also ranked based on the risk factors to identify the risky drivers among all categories of commercial vehicles. The results of the present study led to the following conclusions:

• Among the three main categories of MSD risk factors, occupational factors (OF) are the most important, followed by individual factors (IF) and psycho-social factors (PF).
• The rank of the significance of the different sub-factors of the occupational factors (OF) for MSDs is: PS > RP > WH > US > RE > SH > LB > VI > PL > YE.
• The order of importance of the various sub-factors of the individual factors (IF) for MSDs is: AC > AG > SM > LP > BM > GE > ET.
• The order of importance of the various sub-factors of the psycho-social factors (PF) for MSDs is JST > JS > JD.
• Among the drivers of different types of vehicles, truck drivers are at the highest risk of MSDs, followed by cab drivers, bus drivers, heavy machinery drivers, auto-rickshaw drivers, tractor drivers, E- rickshaw drivers, and two-wheeler taxi drivers.

This research provides useful information to ergonomists/human factor engineers, automobile designers, transport planners, and other stakeholders in the transportation business on the significance of the various MSD risk factors that may lead to injuries to drivers. In terms of limitations, it is emphasized that this research does not determine the importance of the combined effect of the various MSDs risk factors. Further, it involved only a few experts in providing feedback during data collection. In addition, it determined the significance of the MSDs risk factors for drivers of only eight different types of vehicles.

The future scope of this research includes analysis of the interaction between the various MSD risk factors, incorporation of a bigger group of experts, and implementation of other statistical techniques such as factor analysis and structural equation modeling for validation of the results.

7. Research Implications

Musculoskeletal diseases are now a widespread health issue among employees in general and professional drivers in particular since they spend so much time at work and sitting in uncomfortable positions while driving. In order to reduce the hazards involved; it is important to study the characteristics that may contribute to MSDs in professional drivers. These factors include gender, ethnicity, BMI, age, and others. In order to effectively manage them and reduce the danger of acquiring MSDs, it has been attempted to identify and prioritize the major MSD risk factors that may cause MSDs in professional drivers.

Mitigating the risk cannot be achieved until the severity and criticality of involved factors are identified, which can easily be achieved by implementing multi-criteria decision-making (MCDM) techniques.Thus, in this study, initially, the MSD risk factors have been identified through the literature and discussions with the experts, and subsequently, the ordinal priority approach (OPA), which is an MCDM technique, has been employed to rank them. The same OPA method has also been used to identify the group of professional drivers who drive eight different types of vehicles and are more likely to develop MSDs. Based on the results of the present study, the decision makers of the transportation companies may understand the relative importance of the various MSD risk factors and may formulate effective strategies to prevent the risk of developing MSDs among professional drivers, which may ensure their better health conditions and may also help in the economic growth of the companies.