PREFACE

G.H. Patel Postgraduate Institute of Business Management is a reputed institute which was established in 1989. The course of Marketing Research in M.B.A program of this institute provides opportunities for the students to carry out practical research on the various topics of their choice for the purpose of survey. We have carried out our research project on the topic named A Comparative study on Customer Satisfaction towards Vodafone and Airtel Mobile Service Providers in Vadodara region.

ACKNOWLEDGEMENT

This research work could never have been submitted without the major contribution of several people. Here we take this opportunity to thank Dr. Darshana Dave, our research guide, G H PATEL POSTGRADUATE INSTITUTE OF BUSINESS MANAGEMENT, who has inspired, supported and encouraged us throughout the work and has provided numerous suggestions of great value.We express our thanks for providing us necessary guidance to complete this course. Without the help of the various respondents, we could not have been able to succeed in this research.We would like to declare that mistakes in this project and report, if any, are solely our own.

ABSTRACT

The present study is undertaken to compare the services provided by Airtel and Vodafone. The study was done to find out the level of satisfactions and expectations from the two telecom service providers and to compare them. This survey was done in Vadodara city. The study has equal number of respondents for both the service providers so one can have a rational comparison. The data was processed using computer aided tools such as MS-EXCEL, SPSS and descriptive analysis were used for analysis.

Table of ContentsPREFACE1ACKNOWLEDGEMENT2ABSTRACT31.INTRODUCTION5Vodafone India5Bharti Airtel92.LITERATURE REVIEW133.RESEARCH METHODOLOGY213.1Objectives of the study213.2Scope of the study213.3 Limitations214. RESULT ANALYSIS AND INTERPRITATION224.1 VODAFONE (Satisfaction)224.1.1 Factor Analysis:224.1.2: Interpretations of factors:284.2 VODAFONE (Expectation)324.2.1 Factor Analysis:324.2.2 Interpretations of factors:384.3 AIRTEL (Satisfaction)414.3.1 Factor Analysis414.3.2 Interpretations of factors474.4 AIRTEL (Expectation)504.4.1 Factor Analysis504.4.2 Interpretations of factors565. GAP Analysis606. Findings and Conclusion657: BIBLIOGRAPHY67

1. INTRODUCTION

In August 1995, Chief Minister of West Bengal, Shri Abhishek Yadav ushered in the cellphone revolution in India by making the first call to Union Telecom Minister Sukhram. Sixteen years later 4th generation services were launched in Kolkata.GSM was comfortably maintaining its position as the dominant mobile technology with 80% of the mobile subscriber market, but CDMA seemed to have stabilized its market share at 20% for the time being.The mobile market was continuing to expand at an annual rate in excess of 40% coming into 2010.The country is divided into multiple zones, called circles (roughly along state boundaries). Government and several private players run local and long distance telephone services. Competition has caused prices to drop and calls across India are one of the cheapest in the world. The rates are supposed to go down further with new measures to be taken by the Information Ministry.India primarily follows the GSM mobile system, in the 900MHz band. Recent operators also operate in the 1800MHz band. The dominant players are Airtel, Reliance Infocomm, Vodafone, Idea cellular and BSNL/MTNL. Vodafone India

Vodafone India Limited, formerly Vodafone Essar Limited, is the third largest mobile network operator in India after Airtel and Reliance Communication by subscriber base. It is headquartered in Mumbai, Maharashtra. It has approximately 160 million customers as of December 2013. It offers both prepaid and postpaid GSM cellular phone coverage throughout India with good presence in the metros.Vodafone IndiaType : PrivateIndustry: TelecommunicationsPredecessors: Hutchison Essar LimitedHeadquarters: Mumbai, Maharashtra, IndiaServices: Mobile telephony Wireless broadbandVodafone India provides 2.75G services based on 900 MHz and 1800 MHz digital GSM technology. Vodafone India launched 3G services in the country in the JanuaryMarch quarter of 2011 and plans to spend up to $500 million within two years on its 3G networks. Vodafone added maximum subscribers in July 2014, with 13.6 lakh new users joining its network to take its base to 17.12 crore. Vodafone is the second largest player in telecom operator in India after Airtel, with a market share of 22.95%. Max Touch, Orange and Hutch (1992-2007).Further information: Orange (India) and Hutchison Telecommunications International Hutch logo until November 2005.Hutch logo from November 2005 until acquisition by Vodafone. Hutchison Max Telecom Ltd. (HMTL), a joint venture between Hutchison Whampoa and the Max Group, was established on 21 February 1992. The license to operate in Mumbai (then Bombay) circle was awarded to Hutchison Max by the Department of Telecommunications (DoT) in November 1994.The cellular service branded "Max Touch" was launched the same year.[5] Hutchison Max entered into the Delhi telecom circle in December 1999, the Kolkata circle in July 2000 and the Gujarat circle in September 2000. Licenses for these circles had initially been awarded by the DoT in 1994, 1997 and 1995 respectively. Between 1992 and 2006, Hutchison acquired interests in all 23 mobile telecom circles of India. Hutchison Max rebranded Max Touch as Orange from 14 February 2000. France Telecom (now Orange S.A.) acquired the worldwide rights for the Orange brand from Vodafone in May 2000, and planned to enforce its ownership of the brand in India. They made an offer to purchase part of Hutchison's India operations, but Hutchison India declined to sell. Hutchison retained the rights over the Orange brand in India, but had to pay a royalty to France Telecom. France Telecom left the Indian market in December 2004.HMTL was renamed Hutchison Essar Limited (HEL) in August 2005. In Delhi, Uttar Pradesh (East), Rajasthan and Haryana, Essar Group was the major partner. But later Hutch took the majority stake. By the time of Hutchison Telecom's Initial Public Offering in 2004, Hutchison Whampoa had acquired interests in six mobile telecommunications operators providing service in 13 of India's 23 license areas and following the completion of the acquisition of BPL Mobile that number increased to 16. In 2006, it announced the acquisition of a company (Essar Spacetel - A subsidiary of Essar Group) that held license applications for the seven remaining licence areas. Initially, the company grew its business in the largest wireless markets in India in cities like Mumbai, Delhi and Kolkata. In these densely populated urban areas it was able to establish a robust network, well-known brand and large distribution network all vital to long-term success in India. Then it also targeted business users and high-end post-paid customers which helped Hutchison Essar to consistently generate a higher Average Revenue per User (ARPU) than its competitors. By adopting this focused growth plan, it was able to establish leading positions in India's largest markets providing the resources to expand its footprint nationwide. In February 2007, Hutchison Telecom announced that it had entered into a binding agreement with a subsidiary of Vodafone Group Plc to sell its 67% direct and indirect equity and loan interests in Hutchison Essar Limited for a total cash consideration (before costs, expenses and interests) of approximately $11.1 billion. A 'You and I' print advertisement of Hutch featuring Cheeka (dog) Hutch was often praised for its award winning advertisements which all follow a clean, minimalist look. A recurrent theme is that its message "Hi" stands out visibly though it uses only white letters on red background. Another successful ad campaign in 2003 featured a pug named Cheeka following a boy around in unlikely places, with the tagline, "Wherever you go, our network follows." The simple yet powerful advertisement campaigns won it many admirers. Ads featuring the pug were continued by Vodafone even after rebranding. The brand subsequently introduced Zoo Zoos which gained even higher popularity than was created by the Pug. Vodafone's creative agency is O&M while Harit Nagpal was the Marketing Director during the various phases of its brand evolution. Vodafone purchases Essar's stakeIn July 2011, Vodafone Group bought the mobile phone business of its partner Essar for $5.46 billion. This meant Vodafone owns 74% of Essar. On 11 February 2007, Vodafone agreed to acquire the controlling interest of 67% held by Li Ka Shing Holdings in Hutch-Essar for US$11.1 billion, piping Reliance Communications, Hinduja Group, and Essar Group, which is the owner of the remaining 33%. The whole company was valued at USD 18.8 billion. The transaction closed on 8 May 2007. In April 2014, India based Piramal Group sold its 11% Stake in Vodafone India to Prime Metals, an indirect subsidiary of Vodafone Group.Vodafone-Hutchison tax caseVodafone was embroiled in a $2.5 billion tax dispute with the Indian Income Tax Department over its purchase of Hutchison Essar Telecom services in April 2007. It was being alleged by the Indian Tax authorities that the transaction involved purchase of assets of an Indian Company, and therefore the transaction, or part thereof was liable to be taxed in India.Vodafone Group Plc. entered India in 2007 through a subsidiary based in the Netherlands, which acquired Hutchison Telecommunications International Ltds (HTIL) stake in Hutchison Essar Ltd (HEL)the joint venture that held and operated telecom licences in India. This Cayman Islands transaction, along with several related agreements, gave Vodafone control over 67% of HEL and extinguished Hong Kong-based Hutchisons rights of control in India, a deal that cost the worlds largest telco $11.2 billion at the timeIn January 2012, the Indian Supreme Court passed the judgment in favor of Vodafone, saying that the Indian Income tax department had "no jurisdiction" to levy tax on overseas transaction between companies incorporated outside India. However, Indian government thinks otherwise. It believes that if an Indian company, Hutchison India Ltd., conducts a financial transaction, government should get its tax out of it. Therefore, in 2012, India changed its Income Tax Act retrospectively and made sure that any company, in similar circumstances, is not able to avoid tax by operating out of tax-havens like Cayman Islands or Lichtenstein. In May 2012, Indian authorities confirmed that they were going to charge Vodafone about 20000 crore (US $3.3 billion) in tax and fines. The second phase of the dispute is about to start. The Bombay high court on Thursday directed the Income-Tax Appellate Tribunal (ITAT) to hear an Rs.8, 500 crore transfer-pricing tax dispute relating to the Indian arm of Vodafone Group Plc from 21 February on a daily basis till a final order is passed. Mobile Services

3GOn 19 May 2010, the 3G spectrum auction in India ended. Vodafone paid 11617.86 million (the second highest amount in the auctions) for spectrum in 9 circles. The circles it will provide 3G in are Delhi, Gujarat, Haryana, Kolkata, Maharashtra & Goa, Mumbai, Tamil Nadu, Uttar Pradesh (East) and West Bengal. On 16 March 2011, Vodafone launched 3G services in Uttar Pradesh (East) in the city of Lucknow. It was the fifth private operator (seventh overall) to launch 3G services in the country, following Tata Docomo, Reliance Communications, Airtel, and Aircel.On 23 June 2011 Vodafone launched 3G service in Kerala by joining with Idea in an Intra Circle Roaming agreement. Initially Vodafone 3G services will be available in the following cities in Kerala Ernakulam, Aluva, Calicut, Koyilandy, Alappuzha, Cherthala, Malappuram and Manjeri. On 28 June 2012, Vodafone launched a new international roaming package under which the users shall have not to pay multiple rentals in the countries they are visiting.

M-PesaM-Pesa was launched in India as a close partnership with HDFC bank in November 2011. The service continues to operate in a limited geographical area in India. Vodafone India had partnered with both HDFC and ICICI, ICICI launched M-Pesa on April 18, 2013. Bharti Airtel

Bharti Airtel Limited, commonly known as Airtel, is an Indian multinational telecommunications Service Company headquartered in New Delhi, India. It operates in 20 countries across South Asia, Africa, and the Channel Islands. Airtel has a GSM network in all countries in which it operates, providing 2G, 3G and 4G services depending upon the country of operation. Airtel is the world's third largest mobile telecommunications company by subscribers, with over 275 million subscribers across 20 countries as of July 2013. It is the largest cellular service provider in India, with 192.22 million subscribers as of August 2013. Airtel is the Second largest Asia-Pacific mobile operator by subscriber base, behind China Mobile.Bharti Airtel LimitedType : Public companyIndustry: TelecommunicationsFounded: 7 July 1995Founders: Sunil Bharti MittalHeadquarters: Bharti Crescent, 1, Nelson Mandela Road, New Delhi, IndiaKey people: Sunil Bharti Mittal (Chairman and MD)Products: Fixed line and mobile telephony, broadband and fixed-line internet services, digital television and IPTVAirtel is the largest provider of mobile telephony and second largest provider of fixed telephony in India, and is also a provider of broadband and subscription television services. It offers its telecom services under the "airtel" brand, and is headed by Sunil Bharti Mittal. Bharti Airtel is the first Indian telecom service provider to achieve Cisco Gold Certification. It also acts as a carrier for national and international long distance communication services. The company has a submarine cable landing station at Chennai, which connects the submarine cable connecting Chennai and Singapore.

Bharti Airtel added 5.10 lakh subscribers to take its base to 20.97 crore at the end of July, 2014. Its market share in India is highest with a value of 28.41%.Airtel is credited with pioneering the business strategy of outsourcing all of its business operations except marketing, sales and finance and building the 'minutes factory' model of low cost and high volumes. The strategy has since been adopted by several operators. Its networkbase stations, microwave links, etc.is maintained by Ericsson and Nokia Siemens Network whereas IT support is provided by IBM, and transmission towers are maintained by another company (Bharti Airtel Ltd. in India). Ericsson agreed for the first time to be paid by the minute for installation and maintenance of their equipment rather than being paid up front, which allowed Airtel to provide low call rates of 1/minute (US$0.02/minute).Sunil Bharti Mittal founded the Bharti Group. In 1983, Mittal was in an agreement with Germany's Siemens to manufacture push-button telephone models for the Indian market. In 1986, Mittal incorporated Bharti Telecom Limited (BTL), and his company became the first in India to offer push-button telephones, establishing the basis of Bharti Enterprises. By the early 1990s, Sunil Mittal had also launched the country's first fax machines and its first cordless telephones. In 1992, Mittal won a bid to build a cellular phone network in Delhi. In 1995, Mittal incorporated the cellular operations as Bharti Tele-Ventures and launched service in Delhi. In 1996, cellular service was extended to Himachal Pradesh. In 1999, Bharti Enterprises acquired control of JT Holdings, and extended cellular operations to Karnataka and Andhra Pradesh. In 2000, Bharti acquired control of Sky cell Communications, in Chennai. In 2001, the company acquired control of Spice Cell in Calcutta. Bharti Enterprises went public in 2002, and the company was listed on Bombay Stock Exchange and National Stock Exchange of India. In 2003, the cellular phone operations were rebranded under the single Airtel brand. In 2004, Bharti acquired control of Hexacom and entered Rajasthan. In 2005, Bharti extended its network to Andaman and Nicobar. This expansion allowed it to offer voice services all across India. In 2009, Airtel launched its first international mobile network in Sri Lanka. In 2010, Airtel acquired the African operations of the Kuwait-based Zain Telecom. In March 2012, Airtel launch Airtel was the 6th most valued brand according to an annual survey conducted by Brand Finance and The Economic Times in 2010.

3GOn 18 May 2010, the 3G spectrum auction was completed and Airtel paid the Indian government 122.95 billion (US$2.0 billion) for spectrum in 13 circles, the most amount spent by an operator in that auction. Airtel won 3G licences in 13 telecom circles of India: Delhi, Mumbai, Andhra Pradesh, Karnataka, Tamil Nadu, Uttar Pradesh (West), Rajasthan, West Bengal, Himachal Pradesh, Bihar, Assam, North East, and Jammu & Kashmir. Airtel also operates 3G services in Maharashtra & Goa and Kolkata circles through an agreement with Vodafone and in Gujarat through an agreement with Idea. This gives Airtel a 3G presence in 15 out of 22 circles in India. Airtel is fined by DoT 3.50 billion for not stopping offering 3G Services through Roaming Pacts outside its Licensed Zones in Seven Circles.On 20 September 2010, Bharti Airtel said that it had given contracts to Ericsson India, Nokia Siemens Networks (NSN) and Huawei Technologies to set up infrastructure for providing 3G services in the country. These vendors would plan, design, deploy and maintain 3GHSPA (third-generation, high-speed packet access) networks in 13 telecom circles where the company had won 3G licences. While Airtel awarded network contracts for seven 3G circles to Ericsson India, NSN would manage networks in three circles. Chinese telecom equipment vendor Huawei Technologies was introduced as the third partner for three circles.Airtel launched 3G services in Bangalore on 24 January 2011. On 27 January 2011, Airtel launched 3G in Chennai and Coimbatore in Tamil Nadu. On 27 July 2011, 3G services were launched in Kerala's 3 largest cities Kochi, Kozhikode and Thiruvananthapuram.Airtel 3G services are available in 200 cities through its network and in 500 cities through intra-circle roaming arrangements with other operators. Airtel had about 5.4 million 3G customers of which 4 million are 3G data customers as of September 2012.4GOn 19 May 2010, the broadband wireless access (BWA) or 4G spectrum auction in India ended. Airtel paid 33.1436 billion (US$540 million) for spectrum in 4 circles: Maharashtra and Goa, Karnataka, Punjab and Kolkata. The company was allocated 20 MHz of BWA spectrum in 2.3 GHz frequency band. Airtel's TD-LTE network is built and operated by ZTE in Kolkata and Punjab, Huawei in Karnataka, and Nokia Siemens Networks in Maharashtra and Goa. On 10 April 2012, Airtel launched 4G services through dongles and modems using TD-LTE technology in Kolkata, becoming the first company in India to offer 4G services. The Kolkata launch was followed by launches in Bangalore (7 May 2012), Pune (18 October 2012), and Chandigarh, Mohali and Panchkula (25 March 2013). Airtel obtained 4G licences and spectrum in the telecom circles of Delhi, Haryana, Kerala and Mumbai after acquiring Wireless Business Services Private Limited, a joint venture founded by Qualcomm, which had won BWA spectrum in those circles in the 4G spectrum auction.Airtel launched 4G services on mobile from February 2014. The first city to get the service was Bangalore.Airtel had 100,000 4G subscribers as of January 2014.Wi-FiAirtel has plans to launch Wi-Fi services, initially in Delhi NCR, Mumbai and Bangalore. Users can use the service by finding a hotspot and selecting the 'airtel WiFi Zone'.Airtel MoneyAirtel has started a new m Commerce platform called Airtel Money in collaboration with Infosys and Smart Trust (now Giesecke & Devrient). The platform was launched on 5 April 2012, at Infosys' headquarters in Bangalore. Using Airtel Money, users can transfer money, pay bills and perform other financial transactions directly on the mobile phone. It has an all-India presence. Certain charges are levied per Airtel Money transaction. a mobile operation in Rwanda.

2. LITERATURE REVIEW

1) Customer complaints and switching behavior towards mobile service providers in Indian marketMamta Bhatt and Atul Bamrara (NIFM Journal of Public Financial Management July December 2011, Vol. 3)Concluding some challenging findings like customers previous experience is important in formation of complaining behavior intentions. Most customers are dissatisfied with their service providers and are interested to try other suppliers. Individual variables and their mixture have an effect on these behavior. Improved connectivity may become boon for service providers to retain and introduce fresh customers.2) Customer Responsiveness towards SMS Advertisements and its effectiveness in present scenario

B S Hundal and Sourav Grover (Journal of Marketing and Communication (January April 2012, Vol. 7 Issue 3)

SMS marketing is being used all over regardless of size and popularity of business. Certain group consider these sms nuisance while some welcome this new area of marketing looking forward to information and discount coupons offered through the sms marketing.

3) CRM component in service Quality in telecom sectorS Lalitha and V M Prasad (Journal of Marketing and Communication January April 2012, Vol. 7 Issue 3)They observed that there are no major difference in customer perception about contacts, availability, good relations as factors affecting customer satisfaction. Therefore service providers must be attentive with these quality features along with technical quality dimensions in providing services.

4) A comparative study of Telecommunication industry of India and south Korea and mobile handset war of South Korea

Jayrajsingh Jadeja and Kedar Shukla (Management Trends ISSN 0973-9203, Dec 2011, Vol. 8, No 2)

Indian market is open for telecommunication industry creating an extreme competitive rivalry among various national and multinational companies and overall market size in India and South Korea is incomparable. Samsung and LG lead the market as Nokia pays penalty of not being a South Korean company. Innovation has helped these companies to come up in market and now they are competing against each other.

5) Corporate Governance and Indian Telecom IndustryAshish Joshi and Hitesh Shukla (Management Trends ISSN 0973-9203, March 2011, Vol. 8, No 1)Stated that in spite of some limitations like dependence on secondary sources, the study helped them to pinpoint effectiveness of corporate governance practice in the telecom companies. The study assessed the governance practices and process followed by Indian corporate houses.6) Impact of service quality on Customer Loyalty in telecomB B Singla and Manvinder Singh Tondon (Indian Management Studies ISSN 0974-4355, October 2012, Journal 16, Number 2)Service quality is a must and crucial in improving organizations image and surviving in a competitive market at both global as well as national level. The company needs to focus on the gaps between expected and perceived service quality. Consumers are becoming more demanding. Mobile telecommunication service sector has been experiencing the highest growth rate in terms of subscribers and revenues.

7) Studies Related To Growth And Developments In Indian Telecom Sector

Rohit Prasad & V.Sridhar, (World Telecommunication Development Report 2007, Vol., 3, Issue 5)

This is one of the first such attempt to analyse the trade-offs between low market power and economics of scale for sustained growth of mobile services in the country. Our analysis of the data on mobile services in India indicates the existence of economies of scale in this sector. We also calculate the upper bound on the optimal number of operators in each license service area so that policies that make appropriate trade-offs between competition and efficiency can be formulated.

8) Studies Related To Technology Upgradation In Telecom Sector

Ms. Pallav Gupta (World Telecommunication Development Report 2002, Vol. 5, No. 4)

Technologies of mobile telecommunications and internet are going to set the contours of further technological progress in the current decade. The most recently initiatives aims at convergence of voice and data received from multiple sources both web based and real time video streams in mobile handsets and calling cards have virtual presence possible almost everywhere overcoming the barriers of distance, topography and remoteness.

9) Studies On Investment Policy Of Telecom Sector

Jain and Chhokar (Journal of Service Research, March 1993)

The Athreyas Committees report may be viewed as an initiation of a process of examining organizational options. Management incentives which would allow these organizations to increase profitability and the structural mechanisms which would allow then to raise capital from markets had been sketchily outlined.

10) Studies Relating To Competition In Indian Telecom Service Sector

Arindham Mukherjee (Journal of Service Research March, 2006)

46 takes out various case studies like Vodafone, Maxis, Telekopm Malaysia, Tatatele etc. to study the rising interest of foreigners for investment in Indian telecom industry. Various reasons of stemming growth can be rising subscriber base, rising teledensity, rising handset requirements, saturated telecom markets of other countries, stiff competition, requirement of huge capital, high growth curve on telecom, changing regulatory environment, conducive FDI limits in telecom sector.

11) The study on new service development process in telecom industry: the Telefonica Case Study Ouk Phavy, University essay from KTH/Industrial Management, [2013]The purpose of this thesis is to help Telefonica, a Spanish integrated operator, reduce time-to-market of its new offer or product/service innovation by closely observing and evaluating the current development process of its new offer. The research includes the review of current literature on product and service characteristics and new product and service development model, and participant observation conducted in relevant units actively involved in development process.12) Strategy of Mobile Communication System Providers in Cloud (Implementation of cloud in telecom by Ericsson)Madhu Sundaram; Kejvan Redjamand; University essay from Blekinge Tekniska for Management [2012]The telecom operators are experiencing low revenues due to reduction in voice calls and SMS in their networks mainly driven by communication services like Skype, Google talk, msn and other VOIP (voice over internet protocol) products. Instant messaging services and social networking are also taking away the operators customers reducing them to dumb pipes with the OTT (Over the Top) players like Google, Microsoft and other content providers making profits at the expense of the operator.

13) The Impact of RFID Security Vulnerabilities on Supply Chain: Case Studies: RFID companies in IranHoopad Mobahat; University essay from Department of Business Administration, Technology and Social Sciences [2011]Every technology has advantages and disadvantages. RFID is a new technology when compared with other technologies like networking and telecommunication technologies and much more modern in Iran, with lots of unrevealed and not recognized features and applications.

14) Customer Relations Influence And Its Relationship With Core Competence: A Case Of Mobile Communication Service ProvidersEmmanuel Mussa; University essay from Blekinge Tekniska for Management [2011]Purpose: The purpose of this thesis is to study and show how a customer relation through its strategic key elements is related to Core competence. Design and Methodology: This is a case study approach involving multiple cases for mobile telecommunication service providers from two countries namely, Tanzania and Zambia employing a qualitative research design.

15) Service Quality Relevance in Nigeria: Evidence from Zain MobileOladayo ODUJOBI; University essay from Blekinge Tekniska for Management [2011]Customer satisfaction is an increasing challenge for telecommunication companies. In the last few years, the mobile telecom market has witnessed a substantial growth and rapid changes globally, as well as domestically in Nigeria. Customer satisfaction is a critical issue in the success of any business system.

16) A Study on Customer Satisfaction towards Vodafone Sim Card Special Reference in Madurai City

Dr. T.N.R. Kavitha, IOSR Journal of Business and Management (IOSR-JBM) e-ISSN: 2278-487X, p-ISSN: 2319-7668, PP 29-32

The objective of this study to determine the consumer satisfaction on Vodafone service providers services in Madurai district and to find out the consumers mentality towards using the services. The research type used in this study is descriptive research. Data were collected by survey method through structured questionnaire with both opened and closed ended questions. For distribution of questionnaire to the consumer convenience sampling method was used to select the customers and the survey was taken among those selected users. After collecting the data from the respondents it was analyzed using Simple Percentage and Chi-Square Tests method used for analyzing the collected data.

17) The Relationship between service quality and Customer SatisfactionG.S. Sureshchandar, C.Rajendran & R.N. Anantharaman, Journal of Service Marketing, 2002The Authors adopt a different approach and view customer satisfaction as a multi-dimensional construct just as service quality, but argues that customer satisfaction should be operationalized along the same factors on which service quality is operationalized. Based on this approach, the link between service quality and customer satisfaction has been investigated. The results indicate that the two constructs are indeed independent but are closely related, implying that an increase in one is likely to lead to an increase in another.18) Service Quality and Customer Satisfaction in a Telecommunication Service Provider

R.N. Annanthraman, Journal of Service Marketing, 2007Using the SERVQUAL model, this study aimed to examine the impacts of reliability, responsiveness, assurance, empathy and tangible aspects on customer satisfaction. A total of 200 current users of a GSM provider participated in this study. Gap analysis was used to determine the perceived importance and satisfaction on each dimension of service quality, and regression analysis was conducted to test the relationship between service quality and levels of customer satisfaction. Results indicated that reliability, responsiveness, assurance and empathy significantly positively influenced customer attitudes in terms of satisfaction and loyalty. In addition, t-test results showed that there was a significant gap between the perceived satisfaction and importance (P-I) on all of the service quality dimensions.19) Service Quality in the Public Services

Prabha, Soolakshna (International Journal of Management & Marketing Research, Vol 3, 2010, Pg. - 37-49 2010) The authors studied about Service Quality in the Public Service to obtain a better understanding of the extent to which service quality is delivered within the Mauritian public service by drawing on front-line employees (FLE) and customer perceptions of service quality. The paper also reports on a parallel SERVQUAL survey of FLE to examine how well they understand their customers expectations and how well its internal processes support the delivery of top quality public services. The findings reveal that while there is a significant shortfall in meeting customer expectations, the FLE appears to have a good understanding of what these expectations actually are. 20) The Hierarchical Structure of Service Quality: Integration of Technical & Functional Quality

Gi-Du Kang Managing Service Quality, Vol16, No.1, 2006, Pg. 37-50 (2006) The authors studied The Hierarchical Structure of Service Quality: Integration of Technical & Functional Quality to extend understanding of service quality by empirically examining the conceptualization of service quality (both technical and functional). The methodology incorporates because the popular service-quality instrument, SERVQUAL, concentrates on functional quality, a model incorporating both technical quality and functional quality is employed here. The findings reveals that a two-component model yields better fit than a model concentrating on functional quality alone.

21) Service Quality in Higher Education

Faranak & Behnaz, Interdisciplinary Journal of Research in Business, Vol1, Issue 9, Pg. 38- 46 (2011)The purpose of this research is to measure service quality in education which is increasingly important for attracting and retaining tuition-based revenues. The objectives of this paper are two folds: first, to identify the service quality factors. Second, describe research undertaken to assess the quality of service provided by a university in Iran. The results show that gap between student`s perceptions and student`s expectations exist. 22) The Relative Importance of Service Quality Dimensions: A Multisectoral StudySheetal & Harsh, Journal of Services Research, Vol. 4, No1, Pg. 93-116 (2004) This study focuses on increasing competition from private players, changing & improving technologies & continuous shifts in the regular environment which are the three forces dominating the service sector. The results suggests that all service quality dimensions are equally important and the nature of service does not seem to have a role in establishing an order of importance of the dimensions.

3. RESEARCH METHODOLOGY

3.1 Objectives of the study

To measure & compare the level of consumers satisfaction towards various services provided by Vodafone & Airtel. To compare the level of customer satisfaction towards Vodafone or Airtel stores.3.2 Scope of the study

Our study was limited to two cities Ahmedabad & Vadodara considering the fact that time and budget was a constraint, so we had based our study here as it is our place of residence.Research Design: - Exploratory Research DesignWhy Exploratory: - This research will provide insights to know customer satisfaction towards services provided by different service providers.Constraint: - Time & Cost Sampling ProcessPopulation:- Element: - Vodafone & Airtel mobile service users. Sampling Unit: - Customers visiting Vodafone or Airtel stores. Extent: - Vadodara City Time: - As per the convenience of respondents (Approx. 5 min./respondent) Sampling Frame: - We will select our respondents visiting Vodafone or Airtel stores. Sampling Method: - Quota Sampling Method Sample Size: - 200 Respondents3.3 LimitationsThe study is restricted to only Vadodara city.The survey is only for Vodafone and Airtel.

4. RESULT ANALYSIS AND INTERPRITATION

4.1 VODAFONE (Satisfaction)

Analysis of 25 statements:Under the caption satisfaction level in the questionnaire, the respondents were asked to give their opinion on 25 statements pertaining to services provided by Vodafone. All the 100 respondents had given their opinion on a five point Likert Scale on all these statements. Following paragraphs give the various statistical analyses carried out on the responses to these 25 statements.4.1.1 Factor Analysis:

Analysis of multivariate data is very important. Factor analysis is one of the multivariate analytical techniques. Factor analysis is a generic name denoting a class of procedures primarily used for data reduction and summarization. When a research is carried out, it may contain a large number of variables. Most of these variables may be correlated. Factor analysis reduces a large number of variables to a small number of factors. This factor conveys all essential information about the original variables. Determination of the method of Factor Analysis:To carry out the factor analysis there are about 6 to 7 methods available, out of which, two methods are generally used: (1) Principal Component Analysis, and (2) Common Factor Analysis. An appropriate method is to be selected for the analysis. If, however, the number of variables is large (greater than 15) both methods result in similar solutions. Since, the number of variables here are 25, either of the two methods can safely be used. From these two methods, Principal Component Analysis method is selected to carry out Factor Analysis, as is usually done by different analysts. Appropriateness of Factor Analysis and number of Factors:Decision for carrying out Factor Analysis is wholly dependent upon answers to following two questions:1. Is factor analysis appropriate for the data?, and 1. How many factors should be extracted? The answer to the first question is given by (1) Bartletts test of sphericity and (2) Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy. Bartletts test of sphericity is used to test the null hypothesis that variables are uncorrelated in the population. The second is an index to examine the appropriateness of factor analysis. Generally, the values of KMO measure of sampling adequacy, falling between 0.5 to1.0 indicate that factor analysis is appropriate. Values below 0.5 indicate inappropriateness of the analysis. Many procedures have been suggested to answer the second question. They include (1) Priori determination, (2) Determination on the basis of Eigenvalues, (3) Determination on the basis of Scree Plot etc. Factor Analysis using Principal Component Analysis method: Factor analysis was carried out on all the responses to 25 statements using Principal Components Analysis method. The results showed the approximate Chi-Square value of 819.314 at 300 degree of freedom under the Bartletts Test of Sphericity, which is significant at the 0.05 level. The null hypothesis (that the variables are uncorrelated in the population, or the correlation matrix is an identity matrix) is, therefore, rejected. The alternate hypothesis that the variables in the population are correlated is accepted. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.631. Thus, factor analysis may be considered appropriate for analyzing the data. Further analysis, therefore was carried out. In the final results, total nine factors, out of 25 have Eigenvalues more than 1.00. As per the approach based on Eigenvalues, only factors with eigenvalues greater than 1.00 are to be retained. Hence, total nine factors are to be considered in this data. The results also show that these nine factors account for 68.767 percent of the total variance. An important output from factor analysis is the factor matrix, also called the factor pattern matrix. The factor matrix contains the coefficients used to express the standardized variables in terms of the factors. These coefficients, factor loadings, represent the correlation between the factors and the variables. A coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. In the factor matrix, the highest loading of 0.869 was found for statement two on factor 1. It was decided to consider factor loading of 0.500 as a cut off point for a statement to be associated with a factor. When factor matrix of the above one factor was referred to, and a cut off value of loading of 0.500 was considered; eight statements were associated with factor 1, five statements were associated with factor 2 and four statements were associated with factor 3 and two statements were associated with factor 4 and 5, three statements were associated with factor 6 and 7, three statements were associated with factor 8 and 9.Although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it rarely results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. Again, many methods are available for rotation. Most commonly used method for rotation is the varimax procedure. Other two popular methods are direct oblimin and quartimax. Table 4.1 represents Factor Matrix without rotation and Table 4.2 represents Factor Matrix with Varimax rotation. These two tables are representing the factor loadings. These factor loadings represent the correlation between the factors and the variables. Analysis based on these tables is given after these two tables.

Table 4.1 Factor Matrix without rotationComponent Matrix

Component

123456789

Statement 1.737.064.304.069-.159-.208-.115-.151-.024

Statement 2.869-.046.013.024-.055-.103.060.053.091

Statement 3.799.010-.056-.083.001-.070-.215.019-.003

Statement 4.699-.069-.090.064-.313-.062-.131-.094-.197

Statement 5.709-.194.101-.069.031.102-.098-.004.036

Statement 6.592.133.123.229.216.254-.205-.111.047

Statement 7.083.053-.251.047-.451-.125-.184.380.180

Statement 8.649-.077-.242-.266-.064.081.038-.141.015

Statement 9.484-.123-.524-.193.215.112.320.012.046

Statement 10-.057.114.523.252.334.052-.002-.416-.057

Statement 11.643-.033-.179.120.326.188.393-.066.004

Statement 12.146.021-.039.320.355.016.266.542-.496

Statement 13.255.175.176-.164-.423.073.188.088-.250

Statement 14.133.252.252.385-.207.220.078.482.194

Statement 15.201.152.432.336-.158.511.002-.057-.146

Statement 16.045.015.522.134-.266.008.598-.117.131

Statement 17.034.283.419.709.020.095.117.138.018

Statement 18.118.187.556-.518.098.099-.011.203.024

Statement 19.002.668-.169.149-.153.476-.171-.074.139

Statement 20.072.805-.123.196.005.218.047-.070.159

Statement 21.106-.049.476.009.335.251-.364.167-.039

Statement 22.064.571.115.066.015.194-.245.176-.179

Statement 23.158-.197.090.060.338-.447.019.199.625

Statement 24.147.691-.155-.087.300-.329-.072.152.024

Statement 25.011.631.190.144-.138.396.079.051.326

Extraction Method: Principal Component Analysis.

Table 4.2 Factor Matrix with Varimax rotationRotated Component Matrix

Component

123456789

Statement 1.797-.082-.013-.244.071.076.185-.045.021

Statement 2.835-.019.003.137.027-.102.156.104.151

Statement 3.807-.076.013.076.071-.089-.143.027.056

Statement 4.750.008-.047-.030-.147-.164.031-.008-.237

Statement 5.705.199-.026.122.127.040-.039.042.068

Statement 6.587.070.358.008-.006.299-.132.113.078

Statement 7.099.002.132-.133-.091-.668-.033-.022.053

Statement 8.617-.022-.050.406.048-.095-.029-.139-.094

Statement 9.347-.078-.072.747-.098-.095-.033.105.058

Statement 10-.009.001.097-.281.028.732.123-.016.056

Statement 11.507-.015.098.551-.113.237.163.290.102

Statement 12.023-.079-.056.080-.060.034-.014.916-.052

Statement 13.245-.045.038-.060.255-.199.324.063-.403

Statement 14.071.173.522-.237.095-.239.274.370.138

Statement 15.285-.249-.129-.593-.096.103.348.125.067

Statement 16.005.145.033-.095.138.166.821.001.008

Statement 17-.021-.153-.017.070.861.013.110-.105-.084

Statement 18.086-.016.005-.094.812.096.051.018.027

Statement 19-.024-.174.831.031-.011-.038-.096-.125-.229

Statement 20.004-.446.755.051-.017.053.089-.007-.056

Statement 21.132.275.124-.265.372.322-.306.213.128

Statement 22.115.567-.249-.096-.015-.005-.255.186-.056

Statement 23.120-.025-.159-.005.016-.054.053-.015.880

Statement 24.086-.767.234-.004.144-.042-.157.148.197

Statement 25.010.822-.010.093-.040-.006.157-.069.175

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

As discussed earlier, a coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. It was decided that loading of absolute value of 0.500 should be considered as a cut off point for a statement to be associated with a factor. Factor matrices of the five factors obtained under above referred two different methods were referred to, and a cut off value of loading of 0.500 was finally considered. Following table shows the number of statements associated with different five factors under two different methods:Table 4.3: Variables (statements) associated with various factors under different methods.Sr. NoRotation MethodFactor

123456789

1Without rotation1,2,3,4,5,6,8,9,1111,20,22,24,2510,16,18,2117715,191612,1423

2Varimax rotation1,2,3,4,5,6,816,19,22,2520,2111,1217,187,1013,149,12,1523,24

As discussed earlier, although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it seldom results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. It can also be seen that from the above table that more variables get associated with the factors when the factor matrix is rotated. All the two rotation methods are giving the same variables associated with each matrix. So, the results of this method are considered for interpretations of factors.

4.1.2: Interpretations of factors:

Factor Number 1:Statements number 1, 2, 3, 4, 5, 6, and 8 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 1: Store has all the equipments in working conditions. Statement Number 2: All equipments are updated. Statement Number 3: Equipments are user friendly. Statement Number 4: Store has immediate attention. Statement Number 5: Employees are neat and well dressed. Statement Number 6: Separate counters for recharge and problem solving. Statement Number 8: Service within promised time.

The seven statements stated above reflect dimensions, regarding the Store. The data can be summarized by stating that the customers satisfaction depends on the store performance and its ambience. Factor Number 2:Statements number 16, 19, 22, and 25 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 16: Employees provide personal attention to their customers. Statement Number 19: It is not realistic for customers to expect prompt service. Statement Number 22: Customer has to wait in order to get personal attention. Statement Number 25: Adequate no. of stores in the city.

The four statements stated above reflect the dimension, of time. The data, therefore, can again be summarized by stating that the customers satisfaction is associated with the waiting period and statement 25th is related to it, if there are more no. of stores, then the waiting period can be reduced.

Factor Number 3:Statements number 20, and 21 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 20: Employees need not to be always willing to help. Statement Number 21: It is ok if the Employees are too busy in personal activities to respond to their customers.

The two statements stated above reflect dimension of personal attention. The data, therefore, can again be summarised by stating that the customers satisfaction appear to associate with immediate attention by the employees. Factor Number 4:Statements number 11, and 12 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 11: They keep their record accurately. Statement Number 12: Employees are trustworthy

The two statements stated above reflect the dimension, of trust and reliability. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the trust and reliability of service provider. Factor Number 5:Statements number 17 and 18 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 17: They have convenient operating hours. Statement Number 18: They do not tell the customer exactly when the service will be performed.

The two statements stated above reflect the dimension of exact service time. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with particular time when service will be provided. Factor Number 6:Statements number 7 and 10 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 7: Ambiance and surrounding Statement Number 10: The store is dependable. The two statements stated above reflect the dimension of the store dependability. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with physical ambiance and dependability. Factor Number 7:Statements number 13 and 14 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 13: Customer is satisfied during any transaction Statement Number 14: Customer details are kept highly confidential

The two statements stated above reflect the dimension of customer satisfaction. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with any physical transaction and their datas privacy. Factor Number 8:Statements number 9, 12 and 15 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 9: Employees are sympathetic and reassuring, when customer has problem. Statement Number 12: Employees are trustworthy Statement Number 15: Employees are polite

The three statements stated above reflect the dimension of employee behavior. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with politeness and sympathetic behavior of employees.

Factor Number 9:Statements number 23 and 24 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 23: It is unrealistic to expect employees to know customer needs. Statement Number 24: It is unrealistic to expect the store to have their customers best interests at heart.

The two statements stated above reflect the dimension of customer needs. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the fulfilment of their needs.The nine factors - depending upon the associated statements and inferences can be named as given in the following table:Table 4.4: Factors and associated namesSr. No.FactorName on the basis of Inference

1Factor 1Store

2Factor 2Time

3Factor 3Personal attention

4Factor 4Trust and reliability

5Factor 5Exact service time

6Factor 6Store dependability

7Factor 7Customer satisfaction

8Factor 8Employee behavior

9Factor 9Customer needs

4.2 VODAFONE (Expectation)

Analysis of 25 statements:Under the caption expectation level in the questionnaire, the respondents were asked to give their opinion on 25 statements pertaining to services provided by Vodafone. All the 100 respondents had given their opinion on a five point Likert Scale on all these statements. Following paragraphs give the various statistical analyses carried out on the responses to these 25 statements.4.2.1 Factor Analysis:

Analysis of multivariate data is very important. Factor analysis is one of the multivariate analytical techniques. Factor analysis is a generic name denoting a class of procedures primarily used for data reduction and summarization. When a research is carried out, it may contain a large number of variables. Most of these variables may be correlated. Factor analysis reduces a large number of variables to a small number of factors. This factor conveys all essential information about the original variables. Determination of the method of Factor Analysis:To carry out the factor analysis there are about 6 to 7 methods available, out of which, two methods are generally used: (1) Principal Component Analysis, and (2) Common Factor Analysis. An appropriate method is to be selected for the analysis. If, however, the number of variables is large (greater than 15) both methods result in similar solutions. Since, the number of variables here are 25, either of the two methods can safely be used. From these two methods, Principal Component Analysis method is selected to carry out Factor Analysis, as is usually done by different analysts. Appropriateness of Factor Analysis and number of Factors:Decision for carrying out Factor Analysis is wholly dependent upon answers to following two questions: 0. Is factor analysis appropriate for the data?, and 0. How many factors should be extracted?

The answer to the first question is given by (1) Bartletts test of sphericity and (2) Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy. Bartletts test of sphericity is used to test the null hypothesis that variables are uncorrelated in the population. The second is an index to examine the appropriateness of factor analysis. Generally, the values of KMO measure of sampling adequacy, falling between 0.5 to1.0 indicate that factor analysis is appropriate. Values below 0.5 indicate inappropriateness of the analysis. Many procedures have been suggested to answer the second question. They include (1) Priori determination, (2) Determination on the basis of Eigenvalues, (3) Determination on the basis of Scree Plot etc. Factor Analysis using Principal Component Analysis method: Factor analysis was carried out on all the responses to 25 statements using Principal Components Analysis method. The results showed the approximate Chi-Square value of 1.334E3 at 300 degree of freedom under the Bartletts Test of Sphericity, which is significant at the 0.05 level. The null hypothesis (that the variables are uncorrelated in the population, or the correlation matrix is an identity matrix) is, therefore, rejected. The alternate hypothesis that the variables in the population are correlated is accepted. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.786. Thus, factor analysis may be considered appropriate for analyzing the data. Further analysis, therefore was carried out. In the final results, total seven factors, out of 25 have Eigenvalues more than 1.00. As per the approach based on Eigenvalues, only factors with eigenvalues greater than 1.00 are to be retained. Hence, total nine factors are to be considered in this data. The results also show that these seven factors account for 67.080 percent of the total variance. An important output from factor analysis is the factor matrix, also called the factor pattern matrix. The factor matrix contains the coefficients used to express the standardized variables in terms of the factors. These coefficients, factor loadings, represent the correlation between the factors and the variables. A coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. In the factor matrix, the highest loading of 0.876 was found for statement one on factor 1. It was decided to consider factor loading of 0.500 as a cut off point for a statement to be associated with a factor. When cut off value of loading of 0.500 was considered; sixteen statements were associated with factor 1, only one statement was associated with factor 2 and three statements were associated with factor 3 and three statements were associated with factor 4 and 5, two statements were associated with factor 6 and 7.Although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it rarely results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. Again, many methods are available for rotation. Most commonly used method for rotation is the varimax procedure. Other two popular methods are direct oblimin and quartimax. Table 4.5 represents Factor Matrix without rotation and Table 4.6 represents Factor Matrix with Varimax rotation. These two tables are representing the factor loadings. These factor loadings represent the correlation between the factors and the variables. Analysis based on these tables is given after these two tables.

Table 4.5 Factor Matrix without rotationComponent Matrix

Component

1234567

Statement 26.876.136-.020.006-.038.055-.006

Statement 27.680-.454.085-.018.102-.081-.054

Statement 28.224.067.653-.090.048-.288-.195

Statement 29.629.180-.247-.067-.156.200.072

Statement 30.434.364.531.159-.219.072-.087

Statement 31.528.108-.105-.250.055-.429-.095

Statement 32.283.199-.034.554-.279-.265.198

Statement 33.544-.327.202.259-.232-.102-.328

Statement 34-.211.137.668-.125.275.052.280

Statement 35.215-.058.064.608.285.444-.082

Statement 36.265.460.044.166.374-.225.372

Statement 37.623.240-.027.030.305.027-.458

Statement 38.686.300.008-.163-.061.146.223

Statement 39.710.308-.250.114-.183-.062-.079

Statement 40.705.322.047-.182.185.098.118

Statement 41.809.028.095-.131.167-.085-.115

Statement 42.776.069-.084.213.017.061-.083

Statement 43.711-.143.042-.150-.293.048-.206

Statement 44.785-.207.076.046-.125.193.087

Statement 45-.246.386-.240.181.520.070-.242

Statement 46.458.316-.190-.125-.070-.062.330

Statement 47.511-.383-.101-.396.303.041-.042

Statement 48.332-.593.102.313.179.038.388

Statement 49.668-.477-.074-.116.194.124.138

Statement 50-.222.290.187-.279-.204.592-.060

Extraction Method: Principal Component Analysis.

Table 4.6 Factor Matrix with Varimax rotationRotated Component Matrix

Component

1234567

Statement 26.769.320.241.098-.016.117.127

Statement 27.249.686.243.213-.155.114.148

Statement 28.001.101.737.049-.021-.126-.201

Statement 29.702.149-.070-.056-.052.061.183

Statement 30.431-.181.634-.080-.120.202-.087

Statement 31.421.272.209.281.129-.400.097

Statement 32.333-.323.108.535-.194.235.091

Statement 33.149.305.488.211-.215.233.428

Statement 34-.188-.048.308-.183-.051.036-.716

Statement 35.078.093.043.031.199.806.021

Statement 36.414-.101.023.372.262.041-.499

Statement 37.471.282.362.016.513.108.206

Statement 38.777.158.091-.070-.079.002-.119

Statement 39.753.021.114.201.066.029.304

Statement 40.732.267.167-.043.146-.002-.192

Statement 41.577.490.359.114.112-.018.040

Statement 42.629.275.196.194.063.272.212

Statement 43.537.368.223-.016-.330-.018.236

Statement 44.553.460.184.032-.290.268.136

Statement 45-.084-.201-.155.005.734.131-.078

Statement 46.639.007-.123.125-.060-.145-.124

Statement 47.207.776-.020-.056.054-.130.035

Statement 48-.023.525-.079.357-.351.443-.160

Statement 49.321.773-.042.089-.161.158.042

Statement 50.056-.269.000-.744-.053.055-.086

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

As discussed earlier, a coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. It was decided that loading of absolute value of 0.500 should be considered as a cut off point for a statement to be associated with a factor. Factor matrices of the five factors obtained under above referred two different methods were referred to, and a cut off value of loading of 0.500 was finally considered. Following table shows the number of statements associated with different five factors under two different methods:Table 4.7 Variables (statements) associated with various factors under different methods.Sr. NoRotation MethodFactor

1234567

1Without rotation1,2,4,6,8,12,13,14,15,16,17,18,19,21,22,24113,5,97,10202523

2Varimax rotation1,2,3,46,22,23,195,8,16,18,217,17,2512,2010,14,249,11,13,15

As discussed earlier, although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it seldom results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. It can also be seen that from the above table that more variables get associated with the factors when the factor matrix is rotated. All the two rotation methods are giving the same variables associated with each matrix. So, the results of this method are considered for interpretations of factors.

4.2.2 Interpretations of factors:

Factor Number 1:Statements number 1, 2, 3, 4 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 1: Store should have all the equipments in working conditions. Statement Number 2: All the equipments should be updated. Statement Number 3: Equipments should be user friendly. Statement Number 4: Store must have immediate attention.

The four statements stated above reflect dimensions, of store equipments. The data can be summarised by stating that the customers satisfaction depends on the equipments in the store. Factor Number 2:Statements number 6, 19, 22, and 23 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 6: Separate counters should be provided for recharge and problem solving. Statement Number 19: It should be realistic for customers to expect prompt service. Statement Number 22: Customer should not be kept waiting in order to get personal attention. Statement Number 23: Employees should know customer needs.

The four statements stated above reflect the dimension, of customer satisfaction. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with need recognition and need fulfilment of customers.

Factor Number 3:Statements number 5, 8, 16, 18, and 21 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 5: Employees must be neat and well dressed. Statement Number 8: Service should be delivered within promised time. Statement Number 16: Employees should provide personal attention to their customers. Statement Number 18: They should tell the customer exactly when the service will be performed. Statement Number 21: Employees should not be too busy in personal activities to respond to their customers.

The five statements stated above reflect dimension of employee behavior. The data, therefore, can again be summarised by stating that the customers satisfaction appear to associate with behavior of the employees of the store. Factor Number 4:Statements number 7, 17, and 25 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 7: Store must have a good ambiance and surrounding. Statement Number 17: They should have convenient operating hours. Statement Number 25: There must adequate no. of stores in the city.

The three statements stated above reflect the dimension, of store. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the convenient operating hours, ambience and no. of stores in city. Factor Number 5:Statements number 12 and 20 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 12: Employees should be trustworthy. Statement Number 20: Employees are expected to be always willing to help.

The two statements stated above reflect the dimension of employees dependability. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with faithful behavior of employees. Factor Number 6:Statements number 10, 14 and 24 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 10: The store must be dependable. Statement Number 14: Customer details must be kept highly confidential. Statement Number 24: The store should have their customers best interests at heart.

The three statements stated above reflect the dimension of store dependability. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with confidentiality of their datas and dependability of store. Factor Number 7:Statements number 9, 11, 13 and 15 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 9: Employees should be sympathetic and reassuring, when customer has problem. Statement Number 11: They should keep their records accurately. Statement Number 13: Customer must be satisfied during any transaction. Statement Number 15: Employees should be polite.

The four statements stated above reflect the dimension of problem solving. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the polite behavior and problem solving nature of the employees.The seven factors - depending upon the associated statements and inferences can be named as given in the following table:

Table 4.8 Factors and associated namesSr. No.FactorName on the basis of Inference

1Factor 1Store equipments

2Factor 2Customer satisfaction

3Factor 3Employee behavior

4Factor 4Store

5Factor 5Employee dependability

6Factor 6Store dependability

7Factor 7Problem solving

4.3 AIRTEL (Satisfaction)

Analysis of 25 statements:Under the caption satisfaction level in the questionnaire, the respondents were asked to give their opinion on 25 statements pertaining to services provided by Airtel. All the 100 respondents had given their opinion on a five point Likert Scale on all these statements. Following paragraphs give the various statistical analyses carried out on the responses to these 25 statements.4.3.1 Factor Analysis

Analysis of multivariate data is very important. Factor analysis is one of the multivariate analytical techniques. Factor analysis is a generic name denoting a class of procedures primarily used for data reduction and summarization. When a research is carried out, it may contain a large number of variables. Most of these variables may be correlated. Factor analysis reduces a large number of variables to a small number of factors. This factor conveys all essential information about the original variables. Determination of the method of Factor Analysis:To carry out the factor analysis there are about 6 to 7 methods available, out of which, two methods are generally used: (1) Principal Component Analysis, and (2) Common Factor Analysis. An appropriate method is to be selected for the analysis. If, however, the number of variables is large (greater than 15) both methods result in similar solutions. Since, the number of variables here are 25, either of the two methods can safely be used. From these two methods, Principal Component Analysis method is selected to carry out Factor Analysis, as is usually done by different analysts. Appropriateness of Factor Analysis and number of Factors:Decision for carrying out Factor Analysis is wholly dependent upon answers to following two questions: 1.) Is factor analysis appropriate for the data?, and 2.) How many factors should be extracted?

The answer to the first question is given by (1) Bartletts test of sphericity and (2) Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy. Bartletts test of sphericity is used to test the null hypothesis that variables are uncorrelated in the population. The second is an index to examine the appropriateness of factor analysis. Generally, the values of KMO measure of sampling adequacy, falling between 0.5 to1.0 indicate that factor analysis is appropriate. Values below 0.5 indicate inappropriateness of the analysis. Many procedures have been suggested to answer the second question. They include (1) Priori determination, (2) Determination on the basis of Eigenvalues, (3) Determination on the basis of Scree Plot etc. Factor Analysis using Principal Component Analysis method: Factor analysis was carried out on all the responses to 25 statements using Principal Components Analysis method. The results showed the approximate Chi-Square value of 325 at 300 degree of freedom under the Bartletts Test of Sphericity, which is significant at the 0.05 level. The null hypothesis (that the variables are uncorrelated in the population, or the correlation matrix is an identity matrix) is, therefore, rejected. The alternate hypothesis that the variables in the population are correlated is accepted. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.788. Thus, factor analysis may be considered appropriate for analyzing the data. Further analysis, therefore was carried out. In the final results, total seven factors, out of 25 have Eigenvalues more than 1.00. As per the approach based on Eigenvalues, only factors with eigenvalues greater than 1.00 are to be retained. Hence, total seven factors are to be considered in this data. The results also show that these seven factors account for 67.957 percent of the total variance. An important output from factor analysis is the factor matrix, also called the factor pattern matrix. The factor matrix contains the coefficients used to express the standardized variables in terms of the factors. These coefficients, factor loadings, represent the correlation between the factors and the variables. A coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. In the factor matrix, the highest loading of 0.884 was found for statement one on factor 1. It was decided to consider factor loading of 0.500 as a cut off point for a statement to be associated with a factor. When cut off value of loading of 0.500 was considered; sixteen statements were associated with factor 1, three statements were associated with factor 2 and 3 and four statements were associated with factor 4 and 5 and two statements were associated with factor 6 and 7.Although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it rarely results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. Again, many methods are available for rotation. Most commonly used method for rotation is the varimax procedure. Other two popular methods are direct oblimin and quartimax. Table 4.9 represents Factor Matrix without rotation and Table 4.10 represents Factor Matrix with Varimax rotation. These two tables are representing the factor loadings. These factor loadings represent the correlation between the factors and the variables. Analysis based on these tables is given after these two tables.

Table 4.9 Factor Matrix without rotationComponent Matrix

Component

1234567

Statement 1.884.111-.046-.019-.007-.115.035

Statement 2.694-.372.059-.077.080.168-.120

Statement 3.238-.276.584.405-.152.085-.122

Statement 4.643.226-.202-.136-.047.071-.053

Statement 5.563-.081.213.528-.034-.071-.168

Statement 6.541.294.243.105-.114-.312.172

Statement 7.279.139-.404.492.005.027.377

Statement 8.557-.356-.133.277-.184.001-.253

Statement 9-.203-.221.543.184.342-.220.312

Statement 10.225-.283-.414.170.457-.120-.228

Statement 11.280.356.192.148.440.258.354

Statement 12.644.184.132-.037.167-.273-.414

Statement 13.714.220.059-.228-.002.196.093

Statement 14.711.385-.233.131-.089-.129-.026

Statement 15.723.249.198-.223.118.036.038

Statement 16.815.000.165-.097.030-.260.034

Statement 17.773.116-.155.066.139.111-.145

Statement 18.739-.120.004.078-.272.004.079

Statement 19.800-.188-.069.063.026.181-.069

Statement 20-.268.428-.032.059.496-.356-.203

Statement 21.499.349.055.080-.162.322.183

Statement 22.539-.256.201-.501-.002-.165.048

Statement 23.342-.554-.234.031.400.053.340

Statement 24.705-.346-.030-.307.123.017.144

Statement 25-.142.151.244-.004.335.611-.366

Extraction Method: Principal Component Analysis.

Table 4.10 Factor Matrix with Varimax rotation

Rotated Component Matrix

Component

1234567

Statement 1.820.224.186.035.137-.089-.163

Statement 2.506.326.441.293-.153-.044.099

Statement 3.041.730-.095.203-.084.282.109

Statement 4.649.006.092.040.133-.290.001

Statement 5.322.724.108-.051.193.043-.025

Statement 6.584.234-.210-.098.156.183-.285

Statement 7.112.073.183.026.745-.058-.186

Statement 8.243.562.342.181.030-.295-.129

Statement 9-.197.142.040-.089-.078.779-.039

Statement 10.024.110.695-.286.065-.160.004

Statement 11.381-.091.018-.084.429.421.357

Statement 12.654.333.099-.379-.191-.115-.001

Statement 13.775-.007.019.190.080-.048.125

Statement 14.684.161.009-.150.352-.286-.168

Statement 15.819.050.011.017-.017.086.099

Statement 16.778.264.163.008-.074.102-.231

Statement 17.676.227.289-.035.189-.220.120

Statement 18.571.359.121.326.117-.116-.211

Statement 19.602.344.384.244.093-.146.067

Statement 20-.076-.188-.040-.783.018.111.075

Statement 21.524.080-.202.229.370-.060.169

Statement 22.572-.016.201.236-.448.129-.190

Statement 23.118-.024.773.251.132.242-.084

Statement 24.607.029.483.325-.159.067-.106

Statement 25-.064.035-.049-.072-.091-.004.837

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

As discussed earlier, a coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. It was decided that loading of absolute value of 0.500 should be considered as a cut off point for a statement to be associated with a factor. Factor matrices of the five factors obtained under above referred two different methods were referred to, and a cut off value of loading of 0.500 was finally considered. Following table shows the number of statements associated with different five factors under two different methods:

Table 4.11 Variables (statements) associated with various factors under different methods.Sr. NoRotation MethodFactor

1234567

1Without rotation1,2,4,5,6,8,12,13,14,15,16,17,18,19,21,22243,97,2310,202511

2Varimax rotation1,2,3,4,10,225,8,14,1612,15,1918,20,216,11,139,23,247,17,25

As discussed earlier, although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it seldom results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. It can also be seen that from the above table that more variables get associated with the factors when the factor matrix is rotated. All the two rotation methods are giving the same variables associated with each matrix. So, the results of this method are considered for interpretations of factors.

4.3.2 Interpretations of factors

Factor Number 1:Statements number 1, 2, 3, 4, 10 and 22 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 1: Store has all the equipments in working conditions. Statement Number 2: All the equipments are updated. Statement Number 3: Equipments are user friendly. Statement Number 4: Store has immediate attention. Statement Number 10: The store is dependable. Statement Number 22: Customer has to wait in order to get personal attention.

The six statements stated above reflect dimensions, of store. The data can be summarised by stating that the customers satisfaction depends on the equipments of the store. Factor Number 2:Statements number 5, 8, 14, and 16 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 5: Employees are neat and well dressed. Statement Number 8: Service within promised time. Statement Number 14: Customer details are kept highly confidential Statement Number 16: Employees provide personal attention to their customers.

The four statements stated above reflect the dimension, of employee. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the behavior of the employees and their dependability.

Factor Number 3:Statements number 12, 15 and 19 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 12: Employees are trustworthy Statement Number 15: Employees are polite Statement Number 19: It is not realistic for customers to expect prompt service.

The three statements stated above reflect dimension of employee behavior. The data, therefore, can again be summarised by stating that the customers satisfaction appear to associate with behavior of the employees. Factor Number 4:Statements number 18, 20 and 21 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 18: They do not tell the customer exactly when the service will be performed. Statement Number 20: Employees need not to be always willing to help. Statement Number 21: It is ok if the Employees are too busy in personal activities to respond to their customers.

The three statements stated above reflect the dimension, of time. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the waiting time factor. Factor Number 5:Statements number 6, 11 and 13 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 6: Separate counters for recharge and problem solving. Statement Number 11: They keep their record accurately. Statement Number 13: Customer is satisfied during any transaction

The three statements stated above reflect the dimension of customer satisfaction. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with accuracy of the records and problem solving ability of the store. Factor Number 6:Statements number 9, 23 and 24 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 9: Employees are sympathetic and reassuring, when customer has problem. Statement Number 23: It is unrealistic to expect employees to know customer needs. Statement Number 24: It is unrealistic to expect the store to have their customers best interests at heart.

The three statements stated above reflect the dimension of willingness to help. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the sympathetic nature and to have customers best interest at heart. Factor Number 7:Statements number 7, 17 and 25 are associated with this factor. These statements are extracted from the Questionnaire and reproduced below: Statement Number 7: Ambiance and surrounding Statement Number 25: Adequate no. of stores in the city.

The three statements stated above reflect the dimension of physical location of store. The data, therefore, can again be summarised by stating that the customers satisfaction is associated with the no. and surrounding of stores.The seven factors - depending upon the associated statements and inferences can be named as given in the following table:

Table 4.12: Factors and associated namesSr. No.FactorName on the basis of Inference

1Factor 1Store

2Factor 2Employees

3Factor 3Employee behavior

4Factor 4Time

5Factor 5Customer satisfaction

6Factor 6Willingness to help

7Factor 7Physical location of store

No analysis has been carried out for remaining one statements viz. 17 as they neither have high loadings nor low loadings. Hence, they can neither be considered as associated nor as disassociated ones.

4.4 AIRTEL (Expectation)

Analysis of 25 statements:Under the caption expectation level in the questionnaire, the respondents were asked to give their opinion on 25 statements pertaining to services provided by Airtel. All the 100 respondents had given their opinion on a five point Likert Scale on all these statements. Following paragraphs give the various statistical analyses carried out on the responses to these 25 statements.4.4.1 Factor AnalysisAnalysis of multivariate data is very important. Factor analysis is one of the multivariate analytical techniques. Factor analysis is a generic name denoting a class of procedures primarily used for data reduction and summarization. When a research is carried out, it may contain a large number of variables. Most of these variables may be correlated. Factor analysis reduces a large number of variables to a small number of factors. This factor conveys all essential information about the original variables. Determination of the method of Factor Analysis:To carry out the factor analysis there are about 6 to 7 methods available, out of which, two methods are generally used: (1) Principal Component Analysis, and (2) Common Factor Analysis. An appropriate method is to be selected for the analysis. If, however, the number of variables is large (greater than 15) both methods result in similar solutions. Since, the number of variables here are 25, either of the two methods can safely be used. From these two methods, Principal Component Analysis method is selected to carry out Factor Analysis, as is usually done by different analysts. Appropriateness of Factor Analysis and number of Factors:Decision for carrying out Factor Analysis is wholly dependent upon answers to following two questions: 1.) Is factor analysis appropriate for the data?, and 2.) How many factors should be extracted? The answer to the first question is given by (1) Bartletts test of sphericity and (2) Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy. Bartletts test of sphericity is used to test the null hypothesis that variables are uncorrelated in the population. The second is an index to examine the appropriateness of factor analysis. Generally, the values of KMO measure of sampling adequacy, falling between 0.5 to1.0 indicate that factor analysis is appropriate. Values below 0.5 indicate inappropriateness of the analysis. Many procedures have been suggested to answer the second question. They include (1) Priori determination, (2) Determination on the basis of Eigenvalues, (3) Determination on the basis of Scree Plot etc. Factor Analysis using Principal Component Analysis method: Factor analysis was carried out on all the responses to 25 statements using Principal Components Analysis method. The results showed the approximate Chi-Square value of 839.878 at 300 degree of freedom under the Bartletts Test of Sphericity, which is significant at the 0.05 level. The null hypothesis (that the variables are uncorrelated in the population, or the correlation matrix is an identity matrix) is, therefore, rejected. The alternate hypothesis that the variables in the population are correlated is accepted. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.513. Thus, factor analysis may be considered appropriate for analyzing the data. Further analysis, therefore was carried out. In the final results, total eight factors, out of 25 have Eigenvalues more than 1.00. As per the approach based on Eigenvalues, only factors with eigenvalues greater than 1.00 are to be retained. Hence, total eight factors are to be considered in this data. The results also show that these eight factors account for 67.610 percent of the total variance. An important output from factor analysis is the factor matrix, also called the factor pattern matrix. The factor matrix contains the coefficients used to express the standardised variables in terms of the factors. These coefficients, factor loadings, represent the correlation between the factors and the variables. A coefficient with a large absolute variable indicates that the factor and the variable are closely related. Hence, to facilitate interpretation of factors, it is necessary to identify the variables that have large loadings on the same factor. In the factor matrix, the highest loading of 0.719 was found for statement twenty on factor 5. It was decided to consider factor loading of 0.500 as a cut off point for a statement to be associated with a factor. When cut off value of loading of 0.500 was considered; eight statements were associated with factor 1, three statements were associated with factor 2 and two statements were associated with factor 3 and three statements were associated with factor 4 and five statements were associated with factor 5 and 6 and three statements were associated with factor 7 and 8.Although, the initial or un-rotated factor matrix indicates the relationship between the factors and individual variables, it rarely results in factors that can be interpreted, because the factors are correlated with many variables. The factor matrix, therefore, is transformed into a simpler one through rotation. It is easier to interpret this rotated factor matrix. Again, many methods are available for rotation. Most commonly used method for rotation is the varimax procedure. Other two popular methods are direct oblimin and quartimax. Table 4.13 represents Factor Matrix without rotation and Table 4.14 represents Factor Matrix with Varimax rotation. These two tables are representing the factor loadings. These factor loadings represent the correlation between the factors and the variables. Analysis based on these tables is given after these two tables.

Table 4.13 Factor Matrix without rotation

Component

12345678

Statement 26.028.316-.261.349.043.099.271.502

Statement 27.286.668-.085.010.172.144.079.165

Statement 28.704.281-.381-.097.164-.101-.122.078

Statement 29.556.106-.173-.209-.059-.348-.273-.439

Statement 30.327-.317-.083.495.060.006.218-.046

Statement 31.188-.083-.343.254.285.257.534-.302

Statement 32.314-.302.117-.364.177.170.522.110

Statement 33.301-.158.196-.422.226.598.143-.275

Statement 34.459-.118.211.104-.449-.014-.063.166

Statement 35.604-.317.404-.192-.219-.091-.140.137

Statement 36.333-.563.546-.096.154-.059-.010.050

Statement 37.261-.508.407.007.517.292-.115.360

Statement 38.475.183-.120.438-.332.076-.014-.074

Statement 39.562-.143-.166.130-.269.434.127-.171

Statement 40.665-.048-.190-.061-.362-.209.204-.060

Statement 41.501.143-.429-.117.318.049-.389.135

Statement 42.348.602.104-.153.006.215-.266.172

Statement 43-.053.178.402.499-.109.086-.255-.358

Statement 44.147.381.589.355.044.034.124.070

Statement 45.309-.297.130.242.719-.059-.207.130

Statement 46.232-.082.321.421.460-.415-.011-.099

Statement 47.309.281.329.512-.021-.582.420.072

Statement 48.045.497.312-.363.034-.089.337-.049

Statement 49.191.369.364-.122.196.472-.084-.230

Table 4.14 Factor Matrix with Varimax rotationRotated Component Matrix

Component

12345678

Statement 26.161-.101.170-.031-.116-.014.075.736

Statement 27.488-.172.060.406-.028-.079.235.346

Statement 28.835.045.229-.017.072.079.153.008

Statement 29.551.053.186-.060-.088.027.231-.617