Measuring Service Quality Of Indian Railways Business Essay

Indian Railway is indeed the Lifeline of the Country with its admirable performance since the last 150 years. Indian Railways has 114,500 kilometers of total track over a route of 65,000 kilometers   and 7,500 stations. Indian Railways is the largest railway network in Asia and worlds largest railway system under a single management. IR employs approximately 1.5 million people, making itself the second largest commercial or utility employer in the world. The railways carry over 30 million passengers and 2.8 million tons of freight daily. Indian Railway is a major  means of transportation for long  freight movement in bulk, long distance passenger interchange, and  rapid transit in whole India.

Indian railways, being crucial services of Indian Economy, make it important to study its service quality. During the last decade, IR has witnessed significant developments including more reliance on technology, redesigning the berths and coaches management, use of self-service technologies, quality improvements in services etc. IR, thus, tried its sincere best to improve the attitude and satisfaction of the customers.  In this Present study an attempt is made to measure service quality of Indian railway through “RAILQUAL” model and link it with customer satisfaction.

Key Word: RAILQUAL, Service Quality & Indian Railways

Introduction

Services are becoming major driving force behind many country’s economies. Service quality is the decisive factor for any service organization to create the difference and obtain competitive advantage. Quality changes the nature of business competition and, perhaps more than any other factor, it dictated how companies make products or deliver services (Prasad and Shekhar, 2010). High levels of quality drive firm’s profitability (Parasuraman et al 1988; Rust and Oliver, 1994).

This study about the Indian railways is intended to give true picture of how Indian Railways has established itself after more than 150 years. Indian railways has undergone many changes since its first journey in 1853. It has adopted many new technologies and made many strategic moves to keep its several thousands of customers “on board”.

Indian railways has been used by majority of people throughout the nation across geographic boundaries and it has something to offer to every class of people. In spite of its several users, Indian railways has faced tough competition from other players in road transport and air transportation. It had to pass through many turbulent times and has, by making many smart moves, arisen out of the difficulties.

In spite of being an option without any narrow competitor (being a Government organization), the railway’s suffering calls for a research in terms of its customers attitude and preferences towards the organization. This can be judged to greater extent if the perceived quality of railways is measured and this is compared against the expected service quality of the customers. This gap in the perceived and actual quality can serve as a driver of customer satisfaction towards the railways and hence, their loyalty towards the service.

Literature review

Rust and Chung (2006) suggest that it is essential to understand the link between satisfaction and relationship formation in the service industry. Researchers have supported and widely agreed on SERVQUAL (developed by Parasuraman et al) as a reliable and effective tool to measure service quality. The main advantage of SERVQUAL is that it is reliable and valid across wide range of service industries. Allen and DiCesare (1976) considered that quality of service for public transport industry contained two categories: user and non – user categories. Under the user category, it consists of speed, reliability, comfort, convenience, safety, special services and innovations. For the non -user category, it is composed of system efficiency, pollution and demand.

Too and Earl (2010) observed that a key element in achieving sustainability’s triple-bottom-line goals is a good public transport system. Finland is arguably a leader in sustainable development and their sustainability indicators have always included the measurement of public transport service quality (Lyytimaki and Rosenstrom, 2008).

Sillock (1981) conceptualized service quality for public transport industry as the measures of accessibility, reliability, comfort, convenience and safety. Wang, Feng and Hsieh(2010) proposes an instrument based on SERVQUAL for measuring urban transport service quality from a stakeholder perspective. The proposed instrument is developed and tested through exploratory and confirmatory factor analyses.

Hu and Jen (2006) developed and tested a service quality scale designed for a city bus transit system in Taipei. 20 items and 4 dimensions viz. interaction with passengers, tangible service equipment, convenience of service and operating management support were finalized. Increase in ROI is the main force to improve quality in mass transit service (Pullen, 1993). Umar (2011) conducted a study in transport service quality in Nigeria where he concluded that safety and timeliness dimensions are the main driving forces in customer satisfaction of the transport. Shiralashetti and Hugar (2008) conducted a study to measure service quality perception towards KSRTC in Gadag district and suggested various measures to improve quality by making improvements on some focus areas and employing TQM. Eboli and Mazzulla(2007), in their study of bus transport, studied correlation between service quality attributes and identified more convenient attributes to improve service quality. Malik, Safwan and Sindhu(2011) conducted a study in Pakistan to reveal that customer satisfaction is also a function of employee satisfaction and former has high dependency on the later one.

Prasad and Shekhar(2010) presented a framework for assisting Railways to monitor and control the quality of services provided to passengers. This instrument, dubbed as RAILQUAL, is derived from Servqual and other parameters of rail transport quality. The central idea in this model, as in Servqual too, is that service quality is a function of the difference scores or gaps between expectations and perceptions. Maruvada and Bellamkonda (2010) applied Fuzzy set theory to evaluate service quality of Indian railways. They developed an architechture which incorporated fuzzy measurement of S-I (Satisfaction-Importance) degree. Rahaman and Rahaman (2009) developed model defining the relationship between overall satisfaction and service quality attributes. Geetika (2010) identified components of service quality of Indian Railways at railway platforms. Exploratory study was done and factor analysis was performed to identify various factors that are important for satisfaction with service quality.

In this paper, authors have tried to establish relationship between RAILQUAL dimensions and customer satisfaction. Difference between customer’s expected and perceived service was also found out. The research stands important to the decision makers in the reail department who can make necessary amendments in the IR to make customers satisfied and make IR a successful and more profitable organization.

Research Methodology

A descriptive research was carried out to find out the service quality of Indian railway. To measure Service quality we have adopted RAILQUAL scale which is derived from SERVQUAL and other parameters of rail transport quality, developed by Prasad and Shekhar. This scale contains forty-two Likert scale statements, and eight dimensions. The questionnaire was prepared using these two sets of this scale one for the Expected service quality and other for Perceived service quality. Other parameters like demographic components and some other basic questions were added to obtain required data to fulfill the objectives of the research. The survey was administered with mall intercept method at Ahmadabad Railway Junction to 250 Passengers. Some questionnaires were discarded because of invalid responses and final sample size considered was 197.

To find out the gap in service quality among different dimensions, mean score of Expected and Perceived Dimensions were calculated. The impact of RAILQUAL on satisfaction was assessed through multiple regression analysis.

To find out whether there is any difference in expectation of people based on their frequency of travel, perception of fares and the class by which they travel, ANNOVA was used.

Analysis of the data

Reliability analysis

We have adopted RAILQUAL questionnaire to measure the service quality of Indian railways. Adoption of this well established model calls for checking the reliability of its elements. To check the reliability, we have used the Cronbach’s alpha, inter item correlation and item to total correlation. These three measurements of reliability are used for all the 8 dimensions of the RAILQUAL (namely, assurance, empathy, reliability, responsible, tangibles, comfort, connection and convenience). The results of the reliability test are shown in table 1.

Table 1: Reliability of the RAILQUAL dimensions

Dimensions

Assurance

Empathy

Reliability

Responsiveness

Tangibles

Comfort

Connection

Cronbach’s appha

.884

.849

.837

.747

.928

.884

.868

The standard value of the Cronbach’s alpha is 0.7 i.e. a value of 0.7 or more is acceptable and the items are said to have good internal consistency and reliability can be considered good enough to carry out further research. Table 1 show that all the dimensions possess more than 0.7 which is good indicator.

Inter-item correlation shows that how item are internally correlated. Higher the correlation shows higher reliability. Inter-item correlation of 0.3 is acceptable as standard. Inter-item correlation of the all the dimensions found greater than 0.3 and it supports the conclusion of the Cronbach’s alpha about the reliability of the scale.

Item to total correlation measures that how an item is externally correlated with the other items. Item to total correlation of more than or equal to 0.5 suggests the adequate reliability of the scale. In our research we found that inter item correlation is more than 0.5 which is also supporting the results of other two measurements of reliability. Hence, the model is considered reliable to be used for further research.

Table 2: Gap scores

Dimension

Expected mean

Actual mean

Assurance

4.06

2.68

Empathy

3.99

2.64

Reliability

4.11

2.40

Responsiveness

4.31

2.50

Tangibles

4.36

2.69

Comfort

4.19

2.58

Connection

4.26

2.51

Convenience

4.26

2.50

Satisfaction mean is found to be 2.50 which is also nearby the actual mean of the individual dimensions. Highest expectations of the customers is seen towards the tangibles dimension i.e. customers are expecting more improvements in the appearances and the servicescapes of the railways, staff and platforms. Lowest expectations are there towards empathy dimension. Thus, customers are not carrying higher expectations towards care and understanding of the employees of Indian railways. Overall expectations, as seen from their means, is found to be not very high(nearer to 5) but is found to be little lower than extremely high expectations. Thus, it can be concluded that users of Indian railways are not carrying extremely high (and probably unrealistic) expectations.

In spite of that, the department has not been able to meet their requirements. The gap scores see differences of more than 1 point on each criterion. Highest gap is seen in responsiveness while lowest gap is seen in empathy dimension. Hence, the department is required to improve its services whereby they are required to give prompt services, show willingness to help people and enough staff is required to handle the customer’s requests.

Frequency of travel and customer expectations

Hypothesis

H0: There is no significant difference between customer’s Frequency of travel and Expectation from service

H1: There is significant difference between customer’s Frequency of travel and Expectation from service

Table 3: Frequency of travel

ANOVA test

Dimension

F value

Assurance

0.7580

Empathy

3.6111

Reliability

3.6124

Responsiveness

2.9719

Tangibles

2.2305

Comfort

2.9719

Connection

1.8726

Convenience

3.6124

Significant values in table 3 show that there is significant difference in expectations in different categories of frequency of travel. That is, customers with different frequencies of travel are carrying different expectations, especially on empathy, reliability, responsiveness, tangibles, and comfort and convenience dimensions at significance level of 0.1.

Perception of fare and customer expectations

Hypothesis

H0: There is no significant difference between customer’s Perception of fare and Expectation from service

H1: There is significant difference between customer’s Perception of fare and Expectation from service

Table 4: Perception for fare

ANOVA

Dimension

F

Assurance

1.3024

Empathy

0.4698

Reliability

1.1615

Responsiveness

1.3520

Tangibles

1.4981

Comfort

1.3520

Connection

1.5442

Convenience

1.1615

Table 4 shows that there is no difference in expectations of customers of different perceptions of fare. Those who see fares to be high carry same expectations as those of others who perceive fares to be lower (Significance level: 0.1).

Class of travel and customer expectations

Hypothesis

H0: There is no significant difference between customer’s Class of travel and Expectation from service

H1: There is significant difference between customer’s Class of travel and Expectation from service

Table 5: Class of travel

ANOVA test

Dimension

F

Assurance

0.7968

Empathy

1.4549

Reliability

0.2662

Responsiveness

0.3614

Tangibles

0.6111

Comfort

0.3614

Connection

0.7789

Convenience

0.2662

Table 5 shows that there is no difference in expectations of customers who visit in different classes of railways. All those who travel in general class, sleeper class, 1st class, 2 tier or 3 tier AC carry equal expectations (Significance level: 0.1).

Multiple regression model

Table 6: Model Summary

Model

R

R Square

Adjusted R Square

1

.881a

0.776

0.766

Table 7: Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

t

B

Std. Error

Beta

1

(Constant)

0.036

0.122

 

0.293

factor1

0.062

0.036

0.092

1.735

factor2

0.093

0.045

0.137

2.071

factor3

0.078

0.036

0.087

2.189

factor4

0.286

0.036

0.332

8.034

factor5

0.186

0.061

0.233

3.029

factor6

0.168

0.042

0.221

4.047

factor7

0.247

0.036

0.323

6.863

factor8

0.027

0.043

0.031

0.643

 

 

Results of the regression analysis show adjusted R square as 0.766 which means that around 76.6% of the service satisfaction can be explained using these 8 dimensions of service quality in railways. Model can be written as:

Satisfaction = 0.036 + .092(Assurance) + 0.137(Empathy) + 0.087 (Reliability) + 0.332 (Responsiveness) + 0.223(Tangibility) + 0.221(Comfort) + 0.323(Connection) + 0.031(Convenience).

Satisfaction is highly dependent on factors like Responsiveness(.332), Connection(.323), Tangibility(.223) and Comfort(.221)t while it’s found to be less dependent on Assurance, Reliability and Convenience. This results show that any change in the making service prompt, employees willingness to help customers, ease of access of stations, suitable timings of trains, frequency of trains, cleanliness and neat appearance of stations and staff and comfortable and smooth ride will have high positive impact on customer’s perception of satisfaction. While knowledge and courtesy of staff, complaint handling, ease of buying tickets and convenient office hours for ticket do not seem to have much impact on customer’s satisfaction.

Conclusion

The following points can be derived after doing extensive research on rail service quality of Indian Railways:

Highest expectations of the customers is seen towards the tangibles dimension i.e. customers are expecting more improvements in the appearances and the servicescapes of the railways, staff and platforms.

Lowest expectations are there towards empathy dimension. Thus, customers are not carrying higher expectations towards care and understanding of the employees of Indian railways.

Highest gap between expectation and perception is seen in responsiveness while lowest gap is seen in empathy dimension. Hence, the department is required to improve its services whereby they are required to give prompt services, show willingness to help people and enough staff is required to handle the customer’s requests.

There is significant difference in expectations in different categories of frequency of travel. That is, customers with different frequencies of travel are carrying different expectations, especially on empathy, reliability, responsiveness, tangibles, and comfort and convenience dimensions

There is no difference in expectations of customers of different perceptions of fare.

There is no difference in expectations of customers who visit in different classes of railways.

Around 76.6% of the service satisfaction can be explained using these 8 dimensions of service quality in railways

Satisfaction is highly dependent on factors like Responsiveness, Connection, Tangibility and Comfort while it’s found to be less dependent on Assurance, Reliability and Convenience.