1.INTRODUCTION

Service sector gives large contribution in the economic development of the country (Daniel and Harrington, 2007)¹. Service sector largely contributes in the wealth creation of a country which is assessed by measures like GDP. In India also, service sector plays a major role in the economic development and has the maximum contribution in GDP. The entire electricity service sector flourishes on the pillars of quality of its services (Singh et al., 2017; Singh et al., 2016)^2,3.

Service quality has become the foremost concern for the service sector. Service quality fuses competition into the market driven by service industry. In today’s world, entire service sector has dire need of good service quality as customers have become more aware and concerned about the quality of service for which they are spending money (Satapathy, 2014; Singh et al., 2017)^4,5. Despite having electricity supply, people are more concerned with the quality of power being supplied (Saini and Kapoor, 2012; Kapoor and Saini, 2007; Saini et al., 2011; Saini and Kapoor, 2010; Saini and Beniwal, 2018)^6-10. Service means deeds, processes and performances provided or coproduced by one entity or person for another entity or person (Zeithaml et al., 2013)¹¹. Services can be characterized by following properties: (i) Intangibility (ii) Heterogeneity and (ii) (iii) Perishability. On account of these properties, measurement of quality of services is not an easy job as it can’t be touched, stored or weighed (Parasuraman, Zeithaml, and Berry, 1985)¹².

Service quality has been defined by many researchers. Service quality is defined by Reeves and Bednar (1994)¹³ as excellence, value, conformance to specifications and meeting or exceeding customers’ expectations. Service quality is also defined in terms of difference between customers’ expectations and the perceived service. More the perceived service lags behind the expected service, poorer is the service quality leading to more customer dissatisfaction. Customer expectations arise from the predictions about what they like to get during the transaction with company. To study the service quality, Parasuraman, Zeithaml and Berry developed SERVQUAL model in 1985 which identifies gap between the expectations and perceptions (Parasuraman, Zeithaml, and Berry, 1985)¹². This model is also known as ‘GAP’ model. SERVQUAL model has become the favourite choice of researchers and academicians in different fields (Carman, 1990)¹⁴, and it has also become a standard for measuring service quality (DeMoranville and Bienstock, 2003)¹⁵.

SERVQUAL model consists of basically five dimensions but it has been extended to ten dimensions, namely, tangibility, responsiveness, reliability, communication, empathy, accessibility, credibility, assurance, courtesy and security. This model measures the gap between what customers expect from company on these dimensions and what they experience. In this modern world, customers’ expectations are rising continuously but company is not performing upto the mark leading to widening gap between actual services provided and the expectations. This situation has created an alarming stage for the service firms to improve their services so that they can win in the Indian marketplace.

In this paper, SERVQUAL model has been utilized to assess the service quality of electric utility company of Haryana. In this model, there are 50 items in pair, i.e., each pair for each expectation and corresponding perception.The model collects the responses from the customers on five-point Likert scale varying from ‘highly agree’ to ‘highly disagree’. It measures the gap between mean value of expectations and mean value of perceptions for different items. This gap determines whether the customer will be satisfied or dissatisfied. This work employs paired t-test to test whether the gap between customer expectations and perceptions is significant or not.This analysis provides the dimensions on which company’s performance is not upto the mark, causing large gap between expectations and perceptions.

2.LITERATURE REVIEW:

Service quality is a well explored field of research; still it can be further prospected for dwelling into the methods for prosperity of service industry. Numerous models have been proposed for service quality analysis (Seth et al., 2004)¹⁶. There is plethora of studies and concentrating on the analysis of service quality in different service sectors like banking, health, travel, electricity etc. Few significant studies related to service quality of electricity distribution sector are briefed here.

Satapathy (2014)⁴ proposes a new model for service quality enhancement. Author explores about scope of service quality and customer satisfaction in the electricity industry using a questionnaire based survey. In this paper, author shows a direct and positive relationship between the seven dimensions of the service quality model for electricity utility services. Gunatilake et.al. (2012)¹⁷ perform an experiment in Madhya Pradesh, India and show that if the service quality in terms of hours of supply, power quality and other services’ quality drops, then willingness of the customers to pay bill also decreases. Likewise, good service quality in all terms enhances their willingness to pay. Thus, good service quality indirectly also guarantees about minimum losses to the electricity utilities (Saini, 2018)¹⁸. Daniel et al. (2010)¹⁹ show the importance of customer satisfaction by employing a model called SERVQUAL model for measuring the service quality in grocery stores. Authors show some gap in SERVQUAL performance and show the necessary improvements for good quality of service.

Chodzaza et al. (2003)²⁰ assess the service quality of the public electricity utility organisation in Malawi and the resultant loyalty and satisfaction of industrial customers in Malawi. Authors determine the customer dissatisfaction using the relationship between service quality, customer satisfaction and customer loyalty. Achchuthan et al. (2014)²¹ use the SERVQUAL model having five dimensions (tangibility, empathy, responsiveness, reliability and assurance) with 21 items in total for the measurement of service quality of Ceylon Electricity Board in Sri Lanka. Andaleeb et al. (2012)²² examine the impact of service quality on the post-complaint satisfaction of electricity customers. They perform the regression analysis and find the dimension of empathy as the most effective dimension in impacting the customers’ satisfaction level. They also suggest different control mechanisms which can play a great role in establishing the service justice to the legitimate customers and increasing the customers’ post-complaint satisfaction. Manjunath et al. (2013)²³ show that service quality of the services offered by the electricity company decides the consumer behaviour towards electricity consumption and the company. And consumer behaviour positively affects power consumption, load forecasting and bill collection.

Sharma (2010)²⁴ proposes a reliable tool having seven dimensions for assessment of quality of services provided by DHBVN to South Haryana. This assessment tool can be used by policy makers of DHBVN and other suppliers in retail electricity supply industry for monitoring and improvement of service quality keeping in view the perceptions of their customers. Despite of these studies, there is lack of study aimed at the service quality analysis of the services offered by UHBVN supplying electricity to North Haryana. Such kind of study can easily help the policy makers to focus on the areas where the company services do not conform to the customers’ expectations leading to bad consumer perceptions and resultant losses in the system (Saini et al., 2016; Saini, 2017)^25,26. For this purpose, the present study has been undertaken.

3.OBJECTIVES OF THE STUDY:

The main purpose of this paper is the assessment of service quality of utility company in Haryana. SERVQUAL model has been chosen for the analysis of service quality. According to SERVQUAL model, service quality is a function of gap in customer expectations and their perceptions regarding the services of utility company. Focussing on this fact, following objectives have been framed for this study:

1. To assess the customer expectations regarding service quality of electricity distribution company in Haryana.

2. To assess the customer perceptions regarding service quality of electricity distribution company in Haryana.

3. To analyse the gap between customer expectations and perceptions regarding service quality of electricity distribution company in Haryana.

4.RESEARCH HYPOTHESES:

This study aims at service quality analysis of utility company using SERVQUAL model which revolves around the gap between expectations and perceptions. Therefore, following hypotheses have been framed for this work.

H_o :There is no gap between customer expectations and perceptions regarding service quality of utility company.

H₁: There is significant gap between customer expectations and perceptions regarding service quality of utility company.

H₀:refers to null hypothesis and H₁ gives alternative hypothesis. There is mutual exclusion between null and alternative hypotheses. In this work, t-test is used for hypothesis testing.

5.RESEARCH METHODOLOGY:

Exploratory cum descriptive research design has been adopted in this study. Survey has been carried out in Sonepat district of Haryana State. Thus, respondents comprise of residents of Sonepat belonging to different demographic profile.

Sample size:

In this study, stratified random sampling has been used for the selection of respondents. There are six divisions in Haryana State, out of which, survey of Rohtak division has been presented in this study. Further, there are six districts in Rohtak division which act as six strata. According to stratified random sampling, Sonepat district is randomly chosen among six strata. Total population for all divisions is taken as 500. Here, population means electricity connections. Thus, the survey population for Sonepat district is calculated using equation (1) as per stratified random sampling:

Domestic connections of Sonepat district

Sample size=--------------------------------------------X 500 (1)

Total domestic connections of Rohtak division

There are 282148 domestic connections in Sonepat district and total number of domestic connections in Rohtak division is 940496. Thus, equation (1) gives sample size of 150 connections. As population comprises electricity connections, 150 electricity customers are asked to fill the questionnaire.

Table 1. Demographic profile of respondents

Variable	Category	Frequency	Percent
Age	18-30 years	29	19.3
	30-40 years	43	28.7
	40-50 years	49	32.7
	50-60 years	19	12.7
	Above 60 years	10	6.7
Gender	Male	129	86.0
	Female	21	14.0
Category	General	87	58.0
	OBC	49	32.7
	SC/ST	14	9.3
Education	Illiterate	5	3.3
	Matric	17	11.3
	Upto 10+2	39	26.0
	Graduate	56	37.3
	Post Graduate/ Above	28	18.7
	Others	5	3.3
Monthly Income	UptoRs. 10000	38	25.3
	Rs. 10000-50000	80	53.3
	Rs. 50000-100000	26	17.3
	Above Rs. 100000	6	4.0
Locality	Rural	81	54.0
	Urban	69	46.0
Employment	Self-employed	69	46.0
	Government Job	45	30.0
	Private Service	26	17.3
	Unemployed	7	4.7
	NGO Worker	3	2.0
	Others	0	0.0

Data Collection Method:

This study covers the analysis of primary data which were collected using well-structured questionnaire. The questionnaire consists of three sections: (i) demographic profile, (ii) expectation and (iii) perception. Demographic profile asks the respondents’ personal information like age, gender, category, education, monthly income, locality, and type of employment. Questionnaire is designed on the basis of SERVQUAL model. It comprises of ten dimensions of SERVQUAL model, i.e., tangibility, empathy, responsiveness, reliability, communication, security, courtesy, credibility, competence and accessibility. Both expectation and perception section include five questions each for each dimension. The responses are collected on 5-point Likert scale (1 – highly disagree, 2 – disagree, 3 – neither agree nor disagree, 4 – agree and 5 – highly agree). Collected data has been analysed using SPSS (version 20.0) software.

6.DATA ANALYSIS:

Demographic Profile of Respondents:

Demographic profile of customers like age, gender, education, income, category, type of employment has significant impact on customer expectations and perceptionsregarding the service quality of utility company.For instance, highly educated customer will expect more from the utility company. Likewise education, all demographic characteristic affect the customers’ expectation and perception differently. Therefore, there is need to study the demographic profile of respondents as a primary concern. 150 customers of utility companyhave been selected as respondents in this study.Table 1 describes the demographic profile of respondents comprising of their age, gender, category, education, monthly income, locality and type of employment. Out of 150 respondents, maximum respondents (32.7%) are of age group 40-50 years followed by age group 30-40 years (28.7%), age group 18-30 years (19.3%) and age group 50-60 years (12.7%). Most of the respondents (86%) are male and only 14% respondents are female. 58%respondents belong to general category and 32.7% respondents belong to OBC category. Rest of the respondents are of SC/ST category. Maximum respondents, i.e., 37.3% are graduate and 26% respondents have studied upto 10+2. 11.3% respondents are matric passed and 3.3% respondents are illiterate also. 18.7% respondents are post-graduate/above whereas 3.3% respondents have another qualification. Locality-wise, 54% respondents account for rural residents and 46% respondents account for urban residents. Among all respondents, 25.3% and 53.3% respondents are earning upto Rs. 10,000 and upto Rs. 50,000 respectively in a month. 17.3% respondents have monthly income between Rs. 50,000 and Rs. 1,00,000 and 4% respondents have above Rs. 1,00,000. 46% respondents do their own business and 30% are Government employees. 17.3% respondents work in private companies and 2% respondents are NGO workers. All the respondents have different profile which has implications on what they expect from company and how they perceive the services of company.

Table 2. Reliability analysis

Dimensions	No. of Items	Cronbach’s Alpha
Dimensions	No. of Items	Expectation	Perception
Tangibility	5	0.880	0.852
Empathy	5	0.722	0.781
Responsiveness	5	0.734	0.751
Reliability	5	0.784	0.798
Communication	5	0.763	0.746
Security	5	0.723	0.838
Courtesy	5	0.779	0.828
Credibility	5	0.731	0.89
Competence	5	0.741	0.828
Accessibility	5	0.822	0.783
Overall	50	0.884	0.841

Table 3.Descriptive statistics of expectation and perception values for SERVQUAL dimensions

Statements				Expectation				Perception
				Mean			SD	Mean			SD
Tangibility
The company has modern tools and technology.				4.560			0.573		2.273		0.874
The company has well managed offices.				4.607			0.590		2.280		0.836
Forms (for new connections, load change etc.) are simply written in regional languages.				4.620			0.487		2.393		1.117
The records (of electricity connection, bills and meter, etc.) are maintained properly.				4.640			0.522		2.453		0.987
Wires are well organized on electric poles.				4.500			0.610		2.133		1.028
The company has modern tools and technology.				4.560			0.573		2.273		0.874
Empathy
Employees personally attend the customers for their queries and complaints.				4.547			0.551		2.427		0.992
Company staff has operating hours suitable to customer’s needs.				4.467			0.609		2.507		0.974
Rural customers get subsidies in electricity bill.				4.327			0.916		2.853		1.095
Company motivates the customers to use energy saving bulbs, fans and other products.				4.580			0.571		2.940		1.076
The bill collection centers are near to the customer’s residence.				4.440			0.690		2.773		1.112
Responsiveness
There are not long queues at bill collection centers.			4.680			0.468		2.687			1.088
Employees quickly respond to customers’ complaints.			4.793			0.406		2.607			1.016
Every electricity office has helpdesk for enquiry.			4.713			0.454		3.860			0.927
Company gives information in advance for power cuts.			4.713			0.548		3.673			1.223
Customers get the satisfactory service in the first visit to the company office.			4.680			0.594		3.900			0.888
Reliability
Employees give reliable answers to customers’ enquiries.			4.480			0.501		2.453		1.059
The company provides correct electricity bills.			4.480			0.552		2.740		1.065
Customers get full voltage all the time.			4.467			0.575		2.613		1.054
Company gives 24 hours supply.			4.207			0.846		2.507		1.110
Meter reader honestly notes correct reading from the meter.			4.567			0.511		2.887		1.150
Communication
Prior information about due date of bill is given to customers through phone.			4.400			0.543		3.627		1.218
Company provides toll-free numbers for enquiries.			4.527			0.527		3.820		0.812
Employees communicate with customers in regional language.			4.393			0.601		3.887		0.574
Company runs awareness programs through advertisement, social media and newspapers.			4.353			0.592		3.693		0.948
Company gives notice before disconnection of meter.			4.440			0.549		3.853		0.937
Security
Customers are secured in all financial transactions.		4.460			0.500			2.547		1.078
Employees show ID proof while visiting to customer premises (for meter reading etc.).		4.427			0.679			2.247		0.983
Company does timely maintenance of transformers.		4.440			0.524			2.293		1.040
Supply lines are far from the reach of customers.		4.433			0.618			2.240		1.028
Company properly seals the electricity meters.		4.480			0.564			2.580		1.255
Courtesy
Employees behave respectfully with the customers.		4.460			0.500			2.560		1.059
Behavior of the employees is same with all the customers.		4.440			0.596			2.713		1.107
At the entrance of electricity office, ramps are available for the physically challenged customers.		4.480			0.552			2.347		1.017
Expertise staff is available to properly deal with physically challenged (deaf, dumb, blind) customers.		4.520			0.564			2.433		1.064
Customers get new connection with less formalities.		4.440			0.511			2.167		1.058
Credibility
Company does repairing of equipments without charging money from customers.		4.327			0.573			3.320		1.045
The supply is restored within the minimum time.		4.440			0.585			3.293		1.144
Electricity bills are provided by the company at the time of meter reading.		4.413			0.626			3.227		1.124
Customers have secured toll free number/online facility to report against employees.		4.320			0.669			3.260		1.184
Electricity meter runs at normal speed.		4.453			0.551			3.353		0.984
Competence
Billing is done on monthly basis.		4.340			0.731			3.493		1.122
Employees ensure the safety of customers after repairing and maintenance work.		4.467			0.501			3.280		1.159
Customers get the electricity bill at least 7 days before due date.		4.513			0.501			3.373		1.090
Major equipments (like transformer) are replaced without any delay.		4.467			0.501			3.080		1.184
Company takes strict actions for theft complaints.		4.487			0.642			3.327		1.033
Accessibility
Employees are available in any emergency conditions.	4.427				0.496			2.093		0.780
Bill correction procedures are easy for customers.	4.427				0.496			2.180		0.997
Customers have facility of online complaint registration.	4.447				0.525			2.620		1.097
Customers get the online facility to apply for new connections.	4.447				0.585			2.313		0.898
Company provides facility to pay the bill through various modes (cash, cheques, online and drafts).	4.407				0.519			2.860		1.187

Reliability Analysis:

Reliability of the survey instrument has been checked by calculating the Cronbach coefficient alpha (Cronbach, 1951)²⁷. This coefficient is used to assess the internal consistency of the items. For the instrument to be considered valid for survey, Cronbach alpha should be more than 0.70 (Nunally, 1978)²⁸. Therefore, reliability coefficient’s value has been computed for all ten dimensions of SERVQUAL model in case of both customer expectations and perceptions. The reliability of all dimensions is shown in Table 2. As, it is observed from Table 2, that all dimensions under expectation have value of alpha above than 0.70; same applies for perception also. Overall reliability coefficient in case of expectation and perception is also high. Thus, the designed instrument is considered valid for doing the survey and collecting reliable data for analysis.

Descriptive analysis:

Descriptive analysis of the data through SPSS (version 20.0) software gives mean and standard deviation of customers’ expectations and perceptions towards each statement. Table 3 presents the descriptive statistics of the responses collected from respondents using SERVQUAL based questionnaire. Almost all the statements of every dimension have mean value of expectation higher than 4. This shows that customers irrespective of their demographic profile have high expectations from the company with respect to every dimension. But the customers’ perceptions are not that much high. Customers have comparatively good value of perception (i.e., above 3) with respect to following dimensions: communication, credibility and competence. For dimension of responsiveness, customers’ perception is slightly higher than other dimensions (tangibility, empathy, reliability, security, courtesy and accessibility). These observations show that company’s performance is not remarkably good with regard to different dimensions of SERVQUAL model.

Table 4. Paired t-test for SERVQUAL dimensions

Dimensions	Gap (P-E)		t-value	Df	Sig.
Dimensions	Mean	Std. Deviation	t-value	Df	Sig.
Tangibility	-2.279	0.412	32.053	149	0.000
Empathy	-1.772	0.383	25.058	149	0.000
Responsiveness	-1.370	0.534	24.225	149	0.000
Reliability	-1.800	0.490	23.309	149	0.000
Communication	-0.647	0.335	10.690	149	0.000
Security	-2.067	0.500	26.130	149	0.000
Courtesy	-2.024	0.516	26.258	149	0.000
Credibility	-1.100	0.496	13.671	149	0.000
Competence	-1.144	0.543	15.093	149	0.000
Accessibility	-2.018	0.468	29.98	149	0.000

Table 4 shows the gap between mean value and standard deviation of customer expectations and perceptions on different dimensions. Gap between expectations and perceptions assesses service quality of the company. As gap is calculated as the difference between perception and expectation and listed in Table 4, all dimensions have negative gap. This shows that customers’ expectations are very high as compared to their perceptions towards company’s performance.

They do not get the services as expected from the company on all dimensions. In other words, it is analysed that the customers are not satisfied with the company services. Among all ten dimensions, there is lowest gap (-0.647) with regard to communication services. Different dimensions, arranged sequentially according to the increasing gap are as follows: communication (-0.647), credibility (-1.100), competence (-1.144), responsiveness (-1.370), empathy (-1.772), reliability (-1.800), accessibility (-2.018), courtesy (-2.024), security (-2.067) and tangibility (-2.279).

This sequence has highest performing dimension first, followed by less performing dimensions. Thus, tangibility is the weakest dimension of the company’s services and communication is the strongest dimension.

Hypothesis Testing:

To prove the hypothesis, paired t-test is performed in SPSS on the mean values of customers’ expectations and perceptions of all the respondents. Table 4 gives t-value, df and significance value for all dimensions. This test has been performed considering 0.05 significance value. All the dimensions have significance value smaller than 0.05. This observation infers that the mean value of perceptions and expectations have significant difference between them. In other words, it is understood that the gap between expectations and perceptions is significant for all dimensions. This proves that alternative hypothesis, H₁, is accepted thus rejecting the null hypothesis, H₀.

7.CONCLUSION:

From this study, it is concluded that there is huge gap between customers’ expectations and perceptions towards the company’s services. The customers’ expectations and perceptions have been analysed on ten different dimensions of SERVQUAL model. On all the dimensions, customers’ expectations are higher than their perceptions leading to large negative gaps. The dimension of communication has lowest gap and the dimension of tangibility has maximum gap. For testing the hypotheses, paired t-test is performed. The result of t-test reveals that the gap between expectations and perceptions is significantly high. Observations of this study highlight the dimensions of SERVQUAL model upon which the company’s performance is lagging and is not meeting the customer’s expectations.

8.PRACTICAL IMPLICATIONS:

This work helps the distribution company to study the customers’ expectations and perceptions on different dimensions. This study provides the clear view of what items customers expect the most and what items they expect the least from the company. The analysis would facilitate the company to explore about the weakest dimension and would also provide the clear vision of estimates about how much the company is lagging on different dimensions. Thus, it would help in deciding the management strategies which could aim the minimum gap between customers’ expectations and the company’s services. Also, the company can prioritize their efforts first towards their weakest dimensions of service quality.

9.LIMITATIONS OF THE STUDY:

This study covers analysis of primary data collected from the customers of one distribution company, UHBVN, at district level only. More comprehensive view can be taken by surveying more districts served by UHBVN.This study can also be extended to other distribution companies so that performance of different distribution companies can be compared with respect to different dimensions. Analysis over the complete State can bring out the dimensions on which all the distribution companies in the State need to be worked upon to improve their service quality.

10. REFERENCES:

1. Daniel CN and Berinyuy LP. Using the SERVQUAL model to assess service quality and customer satisfaction: An empirical study of grocery stores in Umea. Master Thesis, Umea University, 2010.

2. Singh R, Satpal and Saini S. Sustainable Growth of Indian Power Sector: A Scenario. Proceedings in: Second National Conference on Recent Trends in Computing and Communication Technologies. 2017; 122-124.

3. Singh R, Satpal and Saini S. Power Sector Development in Haryana, International Journal of Science, Technology and Management. 2016; 5: 278-285.

4. Satapathy S. An analysis for service quality enhancement in electricity utility sector of India by SEM. Benchmarking: An International Journal. 2014; 21(6): 964 – 986.

5. Singh R, Satpal and Saini S. Significance of spreading awareness among energy consumers. Proceedings in: Second National Conference on Recent Trends in Computing and Communication Technologies. 2017; 155-157.

6. Saini MK and Kapoor R. Multiwavelet transform based classification of PQ events. International Transactions on Electrical Energy Systems. 2012; 22(4):518-532.

7. Kapoor R and Saini MK. A new signal processing technique for power system disturbance detection and classification. Institution of Engineers India Part-EL. 2007; 88: 9-14.

8. Saini MK et al. PQ events classification and detection – a survey. 2^ndIEEEInternational Conference on Sustainable Energy and Intelligent system, Chennai. 2011; 490-495.

9. Saini MK and Kapoor R. Classification of nonlinear power quality events based on multiwavelet transform. International Journal of Nonlinear Science. 2010: 10(3): 279-286.

10. Saini MK and Beniwal R. Recognition of Multiple PQ issues using Modified EMD and Neural Network Classifier. Iranian Journal of Electrical and Electronics Engineering. 2018, Accepted.

11. Zeithaml VA et al. Service Marketing: Integrating Customer Focus Across The Firm (6th ed.). McGraw-Hill Education, New York. 2013.

12. Parasuraman A, Zeithaml VA and Berry LL. A Conceptual Model of Service Quality and Its Implications of Future Research. Journal of Marketing. 1985; 49: 41-50.

13. Reeves CA and Bednar DA. Defining Quality: Alternatives and Implications. The Academy of Management Review. 1994; 19(3): 419-445.

14. Carman, JM. Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL Dimensions. Journal of Retailing. 1990; 66(1): 33-55.

15. DeMoranville CW and Bienstock CC. Question Order Effects in Measuring Service Quality. International Journal of Research in Marketing. 2003; 20(3): 217-231.

16. Seth N and Deshmukh SG. Service quality models: a review. International Journal of Quality and Reliability Management. 2005; 22(9): 913-949.

17. Gunatilake H et al. Valuing Electricity Service Attributes - A Choice Experiment Study in Madhya Pradesh, India. ADB Economics Working Paper Series, 2012.

18. Saini S. Scenario of Distribution Losses – A Case Study From Haryana. International Journal of Research in Economics and Social Science. 2018; 8(1): 163-175.

19. Daniel PW and Harrington JW. Services and Economic Development in the Asia-Pacific, Ashgate. 2007;

20. Chodzaza GE and Gombachika SH. Service quality, customer satisfaction and loyalty among industrial customers of a public electricity utility in Malawi. International Journal of Energy Sector Management. 2013; 7(2): 269-282.

21. Achchuthan S et al. Service Quality Dimensions of Electricity Services: Evidence from Electricity Board in Sri Lanka. Asian Social Science. 2014; 10(17): 194-203.

22. Andaleeb SS et al. Customer Satisfaction with Complaint Resolution in the Power Sector in a Developing Economy. Journal of Nonprofitand Public Sector Marketing. 2012; 24(3): 181-201.

23. Manjunath M et al. Consumer Behaviour towards Electricity – a field study. Energy Procedia. 2014; 54: 541-548.

24. Sharma H. Modeling Customer Perceived Service Quality for Electricity Supply in South Haryana. International Journal of Business and Management Science. 2010; 3(1): 73-91.

25. Saini S, Singh R and Satpal. Determinant of Electricity Theft – A Case Study of Charkhi-Dadri. Proceedings in: Sixth International Conference on Advanced Computing and Communication Technologies. 2016; 300-307.

26. Saini S. Social and behavioral aspects of electricity theft: An explorative review. International Journal of Research in Economics and Social Sciences. 2017; 7(6): 26-37.

27. Cronbach LJ. Coefficient Alpha and the Internal Structures of Tests. Psychometrika. 1951; 16(3): 297-333.

28. Nunnally JC. Psychometric Theory. McGraw-Hill, New York. 1978.

Received on 29.01.2018 Modified on 11.02.2018

Asian Journal of Management. 2018; 9(1):702-708.

DOI: 10.5958/2321-5763.2018.00109.9