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Public Transport Service Quality and Passenger Satisfaction: A Case of UPSRTC, Agra, India

Manoj Kumar1

SME,Cyient Insights, Hyderabad, 500032, TS, India

E-mail: manoj.kumar@cyient-insights.com

Vikas Anand2

Department of Financial Studies,

Global Institute of Management,

Amritsar, Punjab, India

E-mail: vikasanand_2001@yahoo.com

Anup Srivastava2

Department of Business Studies,

Lovely Professional University,

Phagwara, Punjab, India

E-mail: anupkumarsrivastava@yahoo.co.in

Abstract

Public services are offered by government to the public for their well-being and are offered to them on the basis of the principle of equality. This study measures the level of customer satisfaction with the quality of services offered by Uttar Pradesh State Public Transport Corporation (UPSRTC), Uttar Pradesh State in India. The study was conducted on over 2,000 passengers during June 2015 and October 2015. The various dimensions that are considered include safety, behavior, facilities, response to quarries, comfort, cost, availability etc. The study results reveal that while the passengers highly dissatisfied from attributes such as “Overall conditions of the buses” and “Behavior of the bus drivers and conductors”, the other attributes viz., “Cleanliness of bus stand amenities”, “Economy in travel by buses of UPSRTC” and “Comfort inside buses while travelling“ etc also contributed in overall high degree of dissatisfaction among them. The study concluded with the findings of highly dissatisfied customers of UPSRTC and many scopes of improvements in the services being offered by UPSRTC.

Keywords: Public Transportation, Services, Quality, Satisfaction, UPSRTC, India

1. Introduction

Transport facility is one of the important inputs for the overall economic development of the country. This is critical service when offered by the government to the public for the reason that the socio-economic development of heavily populated states like Uttar Pradesh (approximate population of the state is about 200 millions) depends largely on the public transportation system.

This study demonstrates how the data, collected through questionnaire based survey, can actually be used in measuring public transportation service quality.

2. Uttar Pradesh State Road Transport Corporation

UPSRTC, short for Uttar Pradesh State Road Transport Corporationandone of the largest in India, is a public sector passenger road transport corporation providing services in the state of Uttar Pradesh and its adjoining states in North of India. With a fleet size of around 8000 buses, it operates over 3.0 million kilometers catering to the travel needs of over 1.8 million passengers and earning more than Rs. 60 million per day as on date. (INR or Rs. is short for Indian currency name, Rupee. $1.00 = Rs. 66 or INR66.00 approximately as on date).

The UPSRTC corporate office is based out at Lucknow, which is the capital city of the Uttar Pradesh State in India. Due to the large geographic area and country’s largest population in the Uttar Pradesh state, the corporation has been divided into 19 regions for efficient functioning.Each region operates as urban and sub-urban transport services along with a regional workshop where major repair and maintenance work as well as assembly reconditioning work is performed on the buses operating from that region. Also, each region is further divided into transport operational units called depots. The total number of depots, at present, in the corporation is 108. Each depot has a depot workshop attached to it to provide supportive maintenance facilities. The location details of the various units of UPSRTC are shown in the Table 1 below:

Table 1: Locations of operations, UPSRTC

S. No.

Region

No. of Depots

S. No.

Region

No. of Depots

1

Agra

8

12

Lucknow

6

2

Ghaziabad

7

13

Faizabad

4

3

Meerut

4

14

Devipatan

3

4

Saharanpur

4

15

Chitrakoot

4

5

Aligarh

7

16

Allahabad

8

6

Moradabad

5

17

Azamgarh

7

7

Bareilly

4

18

Gorakhpur

6

8

Hardoi

5

19

Varanasi

7

9

Etawah

6

20

Noida

1

10

Kanpur

7

21

Lucknow

2

11

Jhansi

2

Total : 107

Source: UPSRTC website

While the main objectives of most private operators is to make profits rather than much of the social concerns, the public transportation system offers services to public keeping socio-economic developmental concerns in the mind. But, is UPSRTC, while offering such services, really able to satisfy the passengers? The answer to the question, through the analysis of this study, would not only help UPSRTC to understand in which areas the corporation needs to improve but also help them develop the strategies for eradicating the loopholes in the services.

3. Literature review

Satisfaction of the customers, an important term which is not only accepted as a measure of demand for the product or services being offered by firms but also drives the competitiveness of the firms. But this term means differently for service sector than for manufacturing sector, thus, making it difficult to measure customer satisfaction in service sector.

Andreassen (1995) discussed customer dissatisfaction with public transportation service such as bus, train or tram in and around the greater area of the capital of Norway. Using a data collected from 1,000 customers,study concluded that users have different preferences with respect to the frequency of uses (travel) of public transport.

Denson (2000) suggested that older riders (over 60 years of age) expect more from the service than young riders. This study also concluded that with regard to mobility and satisfaction, one might reasonably expect that riders with the greatest need for accessible transit will be more critical when the service fails to meet their mobility needs.

The exploratory research of Parasuraman, Zeithaml and Berry (1985) reported several insights and propositions concerning consumers’ perceptions and service quality. The research pointed out four key discrepancies in the services that affected the quality of service.

The study by Sai Kumar (2012) reveals that there is highest gap in comfort dimension and lowest gap in responsiveness and empathy dimensions. Further, a comparison made between the satisfaction of the respondents on the basis of gender and occupation, concludes that the satisfaction is different for male and female passengers as well as across occupations of the passengers.

In similar kind of study, Kumar and Anand (2014) explored what influences the decision makers to opt for certain class of services or products. They classified the factors most critical to satisfaction and decision making towards opting a service.

Kumar et. al. (2015) in their research concluded that it is also environment, in which people work, that plays major roles in overall satisfaction and hence performance and sense of responsibilities among employees.

A plethora of literatures on passenger satisfaction, perception and expectation is available but very few studies are conducted on Public Transport Facilities in India. In fact, not a single study was conducted on the Uttar Pradesh State Transport Corporation which offers the services to huge 200 million people in the state. Thus, need arises to study satisfaction level and quality of service as perceived by the passengers in the state and to explore into the factors that need be improved for better socio-economic conditions of the residents in the state.

3. Objectives of the study

The aim of this study is to determine the important factors and level of satisfaction perceived by customers concerning the quality of services provided by UPSRTC. The following are the main objectives of the study:

· To explore and understand the desirable service quality attributes

· To measure the satisfaction level of the passengers; and

· The critical factors impacting the passengers to opt for alternative transport solutions

4. Research methodology

4.1. Instrument development

In order to analyze the research objectives and measure the passengers' satisfaction the descriptive research design, the questionnaire based survey study is considered. Data was collected from primary as well as secondary sources. To measure the levels of passengers' satisfaction towards the quality of services offered by UPSRTC, a questionnaire was designed to collect primary data. Various attributes of service quality were included in questionnaire. Initially, a pilot survey was administered on a few respondents to improve the quality of questionnaire. This pilot study was encouraging and helped us to omit few and include some more important attributes which were missing in the original questionnaire. The improved questionnaire, later, was used to administer the survey on passengers (customers) of UPSRTC. Customers’ satisfaction was measured for attributes such as number of buses in operations, cleanliness, drivers’ attitude and behavior, safety, timings etc.Appendix 1represents the various attributes used in the survey.

4.2.Sample selection, procedure,anddata collection

For data collection it was decided to use judgmental sampling and the respondents were selected on the basis of judgments. Any respondents who were below 18 years of age or travelling a few times in the year were not considered for the study. Only passengers, who are regular commuters and using both UPSRTC buses and private or other state transport corporations' services, were only considered for the study.

The primary data is then collected through questionnaire which uses a 5–point scaling technique. A field survey is conducted at various bus stands in Agra district (rural as well as urban areas) to collect data. The following criterion was adopted in selecting passengers as sample of study:

a. The sample of study consisted randomly selected passengers from all the regions within Agra district

b. The sample of study free from any biasness such as gender, cast, religion etc and represents all the demographic classifications

c. If the age of passenger was below 18 years, they were omitted from being part of the sample. This ensures adulthood and maturity of the surveyed passengers

Initially, the survey was administered on 2000 passengers from Agra district. The selected passengers then were asked to fill-in questionnaire. The questions were explained to their best understanding. In case of any illiterate passengers, full assistance was given to them to understand the questions and their response were noted by surveyor onto questionnaire.

During final scrutiny, only 1542 questionnaires were found to be fully filled in (77%) and rest had either missing entries or multiple selections of answers within one question. Therefore, for final study purpose, 1500 randomly selected questionnaires (75% of total) were considered out of 1542 fully filled-in.

Therefore, the results of this study is based upon total sample size is of 1500 passengers representing both rural and urban areas of Agra district. The collected data was analyzed to examine the satisfaction of the passengers towards the service quality of UPSRTC in Agra district. The secondary data was collected from the UPSRTC website and their offices in Agra.

4.3.Analytical tool

The collected data sorted, tabulated and analyzed using statistical tools like mean, standard deviation, and factor analysis to make the study meaningful. To measure internal consistency of data, Cronbach’s Alpha was measure for reliability. Further, Kaiser-Meyer-Olkin (KMO) test was used to measure of sample adequacy. Later, Barlett’s test of sphericity and Factor Analysis were used for dimension reduction. Statistical software SPSS v.17 was used in this study.

5. Scope of study

The results of the study generate information, which can be used by UPSRTC towards improving the quality of services being offered to the passengers in the state.

6. Limitation of the study

The results of the study are, in majority, based on the primary data collected though a survey administered on the 1500 passengers using public transport facilities and services from UPSRTC. The study is limited by scopes in Agra district of Utter Pradesh State in India. This study further can be extended to other districts and regions in the state, excluding the certain imposed conditions in the survey (as mentioned in the sub-heading 3.2 of research methodology above), and also by introducing more attributes of services quality to deliver stronger results.

7. Analysis of the data

Before data analysis, all the service quality attributes (variables) were rearranged and tabulated. Later, each of these attributes was given a notation to make it easy to understand, analyze in SPSS and represent in the research report. Table 2 indicates notations used for the attributes:

Table 2: Attributes and notations

Attributes (Variables for measurement)

Notations

Number and General Availability of UPSRTC Buses

F1

Timings (Arrival, Departure and Travel) of Buses

F2

Overall Conditions of Buses

F3

Behaviour of Conductors and Drivers

F4

Overall Conditions of Bus Stands

F5

Cleanliness of Bus Stand Amenities

F6

Safety Inside Buses and Bus Stands

F7

Comfort Inside Buses While Travelling

F8

Travel By Buses is Economical

F9

Response to Telephonic Enquiry

F10

Seat Reservation Facilities

F11

Ease of Information Access (Offline and Online)

F12

Tourism Supports and Other Services

F13

Availability, Prices and Quality of Food, Snacks and Eateries

F14

Rate Buses as Compare to its Competitors

F15

Valid N (Listwise)

Source: Primary data

7.1.Descriptive statistics

Table 3 below represents the descriptive statistics of the primary data collected:

Table 3: Descriptive statistics

Descriptive Statistics

Attributes

N

Mean

Std. Deviation

Variance

Statistic

Statistic

Statistic

Statistic

F1

1500

1.68

.780

.608

F2

1500

1.67

.806

.649

F3

1500

3.59

1.055

.633

F4

1500

3.53

1.096

.803

F5

1500

1.81

.875

.765

F6

1500

3.48

1.044

.415

F7

1500

1.93

.990

.980

F8

1500

2.29

.935

.403

F9

1500

2.43

1.015

1.134

F10

1500

1.59

.756

.572

F11

1500

1.17

.389

.151

F12

1500

1.45

.657

.432

F13

1500

1.71

.918

.843

F14

1500

1.11

.866

1.136

F15

1500

2.36

1.419

2.013

Valid N (listwise)

1500

Source: Primary data

The results in the table above reveals that the highest variance (of 2.013) in response is seen in attribute F15 i.e. where respondents were asked to rate UPSRTC as compared to its peers (viz., private operators and trains etc). Overall, the respondents have fairly responded against each of the questions. It can be inferred from the above Table 3 that the responded shown primary concerns over attribute F3 (Overall conditions of the buses in operations, mean 3.59) followed by F4 (Behavior of the bus drivers and conductors, mean 3.53), F6 (Cleanliness of bus stand amenities, mean 3.48) and F9 (Economy in travel by buses of UPSRTC, mean 2.43).

7.2.Test of reliability: Cronbach’s Alpha

Due to the question of data reliability, a commonly accepted rule of thumb for minimum acceptable alpha value is 0.70 for questionnaire based survey studies. If the alpha value is greater than 0.7, data can be termed as “reliable”. The higher the value better is the reliability. Table 4 below represents the reliability test statistics of the primary data collected. The Cronbach’s alpha value is 0.977 which sufficiently meets the minimum requirement to move ahead for other tests such as KMO and Barlett’s.

Table 4: Reliability test – Cronbach’s alpha

Reliability Statistics

Cronbach's Alpha

Cronbach's Alpha based on standardized items

N of items

.977

.983

15

Source: Primary data

7.3. Kaiser-Meyer-Olkin test of adequacy and Barlett’s test of sphericity

To measure sample adequacy, KMO test and to measure strength of relationships among attributes (of correlation matrix), the Barlett’s test are applied to the data. Generally, a high value of KMO is considered good. Table 5 below represents the both tests’ statistics for the data. The KMO measure of sample adequacy in the present study is 0.929 which is of very high order and a good score to continue analyzing data. Furthermore, Barlett’s test of sphericity results a significance level of <0.001, a clear indication that Factor Analysis can be applied on the data.

Table 5: KMO and Barlett’s Tests

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy

.929

Bartlett's Test of Sphericity

Approx. Chi-Square

47728.244

DF

105

Sig.

0.000

Source: Primary data

7.4.Multi-collinearity: correlation analysis

The correlation analysis is performed on the data to test the problem of multi-collinearity. This problem is common in most survey based studies. It is assumed that this problem exists if the correlation between two or more attributes (variables) is more than 0.5 (correlation coefficient) and, if so, the data requires the factor analysis. Table 6 below represents the correlation analysis of the data. The correlation matrix in table 6 reveals that for almost all the attributes, the correlation coefficient is more than 0.5 and hence the data requires factor analysis to be performed.

Table 6: Correlation matrix

Correlation Matrixa

F1

F2

F3

F4

F5

F6

F7

F8

F9

F10

F11

F12

F13

F14

F15

Correlation

F1

1.0

.965

.900

.846

.925

.859

.909

.780

.905

.933

.748

.843

.900

.686

.747

F2

.965

1.0

.937

.820

.907

.876

.902

.797

.905

.925

.721

.860

.902

.662

.718

F3

.900

.937

1.0

.741

.864

.922

.883

.815

.875

.934

.687

.904

.925

.624

.680

F4

.846

.820

.741

1.0

.828

.712

.815

.593

.824

.799

.588

.684

.763

.873

.881

F5

.925

.907

.864

.828

1.0

.851

.948

.804

.928

.883

.732

.842

.933

.705

.783

F6

.859

.876

.922

.712

.851

1.0

.861

.770

.854

.909

.659

.958

.912

.626

.707

F7

.909

.902

.883

.815

.948

.861

1.0

.820

.959

.885

.721

.862

.911

.695

.783

F8

.780

.797

.815

.593

.804

.770

.820

1.0

.790

.794

.863

.801

.859

.381

.431

F9

.905

.905

.875

.824

.928

.854

.959

.790

1.0

.893

.726

.857

.901

.704

.790

F10

.933

.925

.934

.799

.883

.909

.885

.794

.893

1.0

.757

.886

.943

.659

.727

F11

.748

.721

.687

.588

.732

.659

.721

.863

.726

.757

1.0

.685

.776

.364

.411

F12

.843

.860

.904

.684

.842

.958

.862

.801

.857

.886

.685

1.0

.896

.578

.653

F13

.900

.902

.925

.763

.933

.912

.911

.859

.901

.943

.776

.896

1.0

.653

.719

F14

.686

.662

.624

.873

.705

.626

.695

.381

.704

.659

.364

.578

.653

1.0

.949

F15

.747

.718

.680

.881

.783

.707

.783

.431

.790

.727

.411

.653

.719

.949

1.0

a. Determinant = 1.312E-014

Source: Primary Data

8. Factor analysis

Factor analysis reduces the, comparatively, large number of attributes to a smaller number of factors, capable of explaining the observed total variances in all the attributes in the study. It takes qualitative observations against each of the attributes and resolves them into distinct pattern of occurrence.

8.1.Communalities

It measures the extent to which an attribute correlates with all other attributes. If the load for a particular attribute is less than 0.5, it might struggle significantly to load onto any factor during data reduction process. The Table 7 below represents the result of communalities in the data. This is the amount of variation extracted from each attribute. The extraction of factors is performed using Principal Component Analysis:

Table 7: Communalities

Communalities

Initial

Extraction

F1

1.000

.820

F2

1.000

.916

F3

1.000

.950

F4

1.000

.906

F5

1.000

.897

F6

1.000

.963

F7

1.000

.820

F8

1.000

.804

F9

1.000

.814

F10

1.000

.823

F11

1.000

.772

F12

1.000

.859

F13

1.000

.841

F14

1.000

.841

F15

1.000

.764

Extraction Method: Principal Component Analysis.

Source: Primary data

From the results above in the Table 7, it can be revealed that the attributes F6 (Cleanliness of bus stand amenities, 0.963), and F3 (Overall conditions of buses, 0.953) shown highest communalities followed by F2 (Timing of arrivals and departures, 0.916) and F4 (Behavior of bus drivers and conductors, 0.906).

8.2.Total variance explained

Further, the attributes were analyzed for Eigen-value, which is total variance explained by each factor. In other words, Eigen-value, for a given factor, measures the variance in all the attributes for which that factor is accounted for. The varimax rotation method was adopted to rotate the factor axes to maximize the variance of loading a factor in column in all the attributes. Table 8 below represents the results of total variance as explained by different attributes in the study. Extraction is done through Principal Component Analysis.

Table 8: Total variance explained by different variables

Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Var.

Cumu. %

Total

% of Var.

Cumu. %

Total

% of Variance

Cumulative %

1

12.257

81.713

81.713

12.257

81.713

81.713

8.216

54.776

54.776

2

1.281

8.543

90.255

1.281

8.543

90.255

5.322

35.480

90.255

3

.462

3.082

93.337

4

.225

1.497

94.834

5

.210

1.398

96.232

6

.125

.835

97.068

7

.110

.731

97.798

8

.086

.574

98.372

9

.067

.448

98.820

10

.041

.272

99.092

11

.040

.265

99.357

12

.034

.229

99.586

13

.023

.155

99.742

14

.021

.141

99.883

15

.018

.117

100.000

Extraction Method: Principal Component Analysis.

Source: Primary data

There are two variables which have Eigen-value more than 1.0 and cumulative variance explained by these two components is 90%. The sorted Eigen-value against the factor number is represented by the graph (Scree Plot) in Picture 1 below:

Figure 1: Scree Plot

The Scree plot graph above exhibits that two factors are able to explain all the attributes in the study for service quality assessment.

8.3.Component matrix

The component matrix, as shown in the Table 9 below, represents the correlation between the retained two factors. This solution is not as easy to interpret as rotated component matrix (in next sub-heading).

Table 9: Component Matrix

Component Matrixa

Component

1

2

F1

.959

-0.010

F2

.956

-0.047

F3

.942

-0.115

F4

.866

0.369

F5

.957

0.013

F6

.925

-0.086

F7

.959

0.001

F8

.838

-0.449

F9

.956

0.023

F10

.958

-0.072

F11

.771

-0.421

F12

.913

-0.157

F13

.963

-0.119

F14

.745

0.622

F15

.807

0.559

Extraction Method: Principal Component Analysis.

a. 2 components extracted

Source: Primary data

8.4.Rotated component matrix

Factor loading for each variable on the factors after rotation is shown in factor pattern matrix. Table 10 below represents the results in rotated component matrix. This matrix represents how the variables are weighted for each factor and the correlation between them. In this process, the SPSS was asked to suppress correlation below 0.3 so that the output is easy to understand by the removal of low correlation clutters in the results.

Table 10: Rotated Component Matrix

Rotated Component Matrixa

Component

1

2

F1

.768

0.574

F2

.788

0.543

F3

.818

0.480

F4

.465

0.819

F5

.753

0.591

F6

.787

0.493

F7

.762

0.582

F8

.938

F9

.746

0.598

F10

.805

0.524

F11

.868

F12

.821

0.430

F13

.837

0.490

F14

0.946

F15

.302

0.934

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization

a. Rotation converged in 3 iterations

Source: Primary data

The results in the table above show that there are 12 attributes loading onto factor one and 3 attributes loading onto factor two. Using extraction method of Principal Component Analysis and Varimax (Orthogonal) Rotations method with Kaiser Normalization, the factor analysis produced two factors. The entire rotation solution converged within 3 iterations. The component transformation matrix is discussed in the next sub-heading.

8.5.Component transformation matrix

This matrix describes the specific rotation applied to the factor solution. Table 11 represents the correlations among both the extracted factors. It does not require to be interpreted.

Table 11: Component transformation matrix

Component Transformation Matrix

Component

1

2

1

.795

0.607

2

-.607

0.795

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.

Source: Primary data

9.Results and discussions

Inline to the objectives of the study, the attributes were formulated to explore the passengers’ satisfaction level and critical factors in UPSRTC’s service quality. To make the study meaningful, the factor analysis, using SPSS, was applied on the data. Factor analysis extracted two critical factors from these attributes. These factors are able to explain 90% of the total variances in all the attributes. Following are the two factors along with grouped attributes:

9.1.Factor 1

It includes 12 attributes of service and these are “Number and General Availability of UPSRTC Buses”, “Timings (Arrival, Departure and Travel) of Buses”, “Overall Conditions of Buses”, “Overall Conditions of Bus Stands”, “Cleanliness of Bus Stand Amenities”, “Safety Inside Buses and Bus Stands”, “Comfort Inside Buses While Travelling”, “Economy in Travel By UPSRTC Buses”, “Response to Telephonic Enquiry”, “Seat Reservation Facilities”, “Ease of Information Access (Offline and Online)” and “Tourism Supports and Other Services”.

This factor can be renamed as “Main Factor” as it includes majority of the attributes to describe quality of services being offered by UPSRTC.

9.2. Factor 2

It includes 03 attributes of services viz., “Behaviour of Conductors and Drivers”, “Availability, Prices and Quality of Food, Snacks and Eateries” and “Rating UPSRTC as Compare to its Competitors”.

This factor can be named as “Secondary Factor” as it describes part of services quality.

10. Conclusion

The present empirical study attempts to explain the extent to which passengers are satisfied with the quality of the services being offered to public from the UPSRTC in Agra district of Uttar Pradesh State in India. It also attempts to penetrate into the critical attributes leading to high degree of dissatisfaction among the UPSRTC customers. The outcome of the study reveals that all the attributes, the satisfaction measurement parameters, can be grouped into two categories viz., Main and Secondary. The main category emerged out of the 12 critical attributes such as “Number and General Availability of UPSRTC Buses”, “Timings (Arrival, Departure and Travel) of Buses”, “Overall Conditions of Buses”, “Overall Conditions of Bus Stands”, “Cleanliness of Bus Stand Amenities”, “Safety Inside Buses and Bus Stands”, “Comfort Inside Buses While Travelling”, “Economy in Travel By UPSRTC Buses”, and “Response to Telephonic Enquiry” etc while the Second Category relates with the three attributes “Behaviour of Conductors and Drivers”, “Availability, Prices and Quality of Food, Snacks and Eateries” and “Rating UPSRTC as Compare to its Competitors”.

The result reveals that the passengers (respondents in the study) were highly dissatisfied with almost all the critical attributes of service quality from UPSRTC. This means UPSRTC, being public transport facility provider, needs to take strategic decisions of implementing improved quality in the services it is offering to public. Only such action will improve the satisfaction of passengers and hence social-economic conditions in the state.

11. References

11.1. Journal Article

[1] Kumar, M.; Anand, K., Shrivastava, A.;"Stress at Work & Employee's Satisfaction: Study on Private Institutions and Universities in Northern India", Pacific Business Review International, Volume 8, Issue 3, pp 51-56, (2015)

[2] Kumar, M.; Anand, V.;"Factors Affecting Taxpayers’ Decisions in Saving Tax by Investing in Tax Saving Bonds: A Study in U.P. State, India", Financial Assets and Investing, Volume 5, pp 22-40, (2014), doi:10.5817/fai2014-1-2

[3] Sai Kumar, K., "Expectations and Perceptions of Passengers on Service Quality with Reference to Public Transport Undertakings",The IUP Journal of Operations Management, Vol. XI, No. 3, pp. 67-81, (2012)

[4] Jen, W., Tu, R., & Lu, T., “Managing passenger behavioral intention: An integrated framework for service quality, satisfaction, perceived value, and switching barriers”, Transportation, Vol. 38 No. 2, pp. 321-342, (2011)

[5] Eboli, L. and Mazzulla, G., "Service quality aspects affecting customer satisfaction for bus transit", Journal of Public Transportation, Vol. 10 No. 3, pp. 21-34, (2007)

[6] Denson, C. R., “Public sector transportation for people with disabilities: A satisfaction survey”, Journal of Rehabilitation, Vol. 66, No. 3, pp. 29-37, (2000)

[7] Santos, J. Reynaldo A.; “Cronbach's Alpha: A Tool for Assessing the Reliability of Scales”, Journal of Extention, April 1999, Vol. 37, No. 2, (1999)

[8] T. W. Andreassen, "(Dis)satisfaction with public services: the case of public transportation", Journal of Services Marketing, Vol. 9, pp. 30-41, (1995)

[9] Parasuraman, A., Zeithaml, V. A. and Berry, L.L., "A conceptual model of service quality and its implication for future research", Journal of Marketing, Vol. 49, pp. 41-50, (1985)

[10] UPSRTC website http://www.upsrtc.com – accessed on October, 15, 2015

Appendix 1

Passenger Satisfaction Survey

Dear Passenger,

This survey is designated to evaluate customers' satisfaction towards UPSRTC services. Please read the below survey questions carefully and respond with your true/unbiased opinion.

1. How much satisfied are you with the number of buses and general availability of UPSRTC buses on the route to your destination [Attribute 1]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

2. How much satisfied are you with the timings (arrival, departure and travel) of buses from UPSRTC on the route to your destination [Attribute 2]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

3. How much satisfied are you with the overall conditions (e.g. window glasses, seats, noise, tyre, luggage carrier, shock absorber etc) of the UPSRTC buses [Attribute 3]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

4. How much satisfied are you with the behaviour of conductor and driver in the UPSRTC buses [Attribute 4]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

5. How much satisfied are you with the overall conditions (e.g. dust free, garbage free, floors, ambiance etc) of UPSRTC bus stands [Attribute 5]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

6. How much satisfied are you with the cleanliness of UPSRTC bus stand amenities (e.g. toilets, waiting area, drinking water facilities, cloak room etc) [Attribute 6]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

7. How much satisfied are you with the safety inside UPSRTC buses and bus stands [Attribute 7]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

8. How much satisfied are you with the comfort inside UPSRTC buses while travelling [Attribute 8]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

9. In your opinion, whether travel by UPSRTC buses is economical [Attribute 9]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

10. How much satisfied are you with the UPSRTC response to your telephone enquiry [Attribute 10]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

11. How much satisfied are you with the UPSRTC seat reservation facilities [Attribute 11]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

12. How much satisfied are you with the ease of booking tickets (online and offline) facilities [Attribute 12]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

13. How much satisfied are you with the tourism supports, facilities and other services (such as tie-ups with hotels, room-on-rent etc) at UPSRTC [Attribute 13]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

14. How much satisfied are you with the availability and prices of food, snacks and eateries at UPSRTC bus stands [Attribute 14]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

15. How much you rate UPSRTC buses as compare to its competitors (private or other state corporation buses) [Attribute 15]:

 Very Poor [1]

 Poor [2]

 Fair [3]

 Good [4]

 Very good [5]

Thank you for your time.

 
 

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