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Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
Turnitin uk originality report
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Turnitin uk originality report

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Turnitin uk originality report

Turnitin uk originality report

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  • 1. 3/8/13 TurnitinUK Originality Report TurnitinUK Originality Report Assessing Quality and Customer Satisfaction with service delivery of mobile telecommunication networks in the UK. by VIMAL VIJAYA SARATHY From Dissertation (Postgraduate Dissertation - 2009-10) Processed on 16-08-10 7:51 AM BST ID: 7309325 Word Count: 15833 Similarity Index 13% Similarity by Source Internet Sources: 4% Publications: 2% Student Papers: 12% sources: 1% match (student papers from 01/09/09) 1 Submitted to University of East London on 2009-09-01 1% match (student papers from 04/12/06) 2 Submitted to University of Greenwich on 2006-12-04 < 1% match (student papers from 18/05/09) 3 Submitted to Middlesex University on 2009-05-18 < 1% match (student papers from 26/08/09) 4 Submitted to Heriot-Watt University on 2009-08-26 < 1% match (Internet from 21/4/10) 5 http://www.ida.liu.se/~steho/und/htdd01/1080140401.pdf < 1% match (Internet from 22/2/10) 6 http://scholar.lib.vt.edu/theses/available/etd-02082006- 210252/unrestricted/RMThompson_dissertation.pdf < 1% match (student papers from 14/09/09) 7 Submitted to University of Hull on 2009-09-14 < 1% match (Internet from 2/5/10) 8 http://www.surveymonkey.com/s/SGVRP5X < 1% match (student papers from 05/04/07) 9 Submitted to University of Greenwich on 2007-04-05 < 1% match (student papers from 30/07/10)file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 1/45
  • 2. 3/8/13 TurnitinUK Originality Report 10 Submitted to Kaplan Professional School of Management on 2010-07-30 < 1% match (student papers from 22/09/09) 11 Submitted to Middlesex University on 2009-09-22 < 1% match (Internet from 7/6/10) 12 http://ccsenet.org/journal/index.php/ijbm/article/viewFile/5495/4962 < 1% match (student papers from 30/01/08) 13 Submitted to University of Lancaster on 2008-01-30 < 1% match (Internet from 17/3/10) 14 http://dspace.fsktm.um.edu.my/bitstream/1812/595/2/Microsoft%20Word%20- %20CHAPTER%201.doc%20amed%201.pdf < 1% match (publications) 15 International Journal of Bank Marketing, Volume 21, Issue 5 (2006-09-19) < 1% match (Internet from 17/6/10) 16 http://media.wiley.com/product_ancillary/49/14051002/DOWNLOAD/Chapter9.pdf < 1% match (publications) 17 Journal of Services Marketing, Volume 16, Issue 4 (2006-09-19) < 1% match (student papers from 10/12/07) 18 Submitted to Coventry University on 2007-12-10 < 1% match (student papers from 17/09/09) 19 Submitted to Coventry University on 2009-09-17 < 1% match (Internet from 24/5/10) 20 http://www.sagepub.com/upm-data/11886_Chapter_3.pdf < 1% match (publications) 21 International Journal of Contemporary Hospitality Management, Volume 11, Issue 7 (2006- 09-19) < 1% match (Internet from 12/4/10) 22 http://repository.tamu.edu/bitstream/handle/1969.1/2426/etd-tamu-2005A-COMG- Lertban.pdf;?sequence=1 < 1% match (publications) 23 Journal of Services Marketing, Volume 22, Issue 7 (2008-10-12) < 1% match (student papers from 02/05/06) 24 Submitted to De Montfort University on 2006-05-02 < 1% match (student papers from 02/03/10) 25file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 2/45
  • 3. 3/8/13 TurnitinUK Originality Report Submitted to London School of Commerce on 2010-03-02 < 1% match (student papers from 22/05/08) 26 Submitted to University of East London on 2008-05-22 < 1% match (student papers from 16/05/07) 27 Submitted to University of Greenwich on 2007-05-16 < 1% match (student papers from 18/05/10) 28 Submitted to University of East London on 2010-05-18 < 1% match (student papers from 03/08/10) 29 Submitted to University of Bradford on 2010-08-03 < 1% match (student papers from 06/04/09) 30 Submitted to University of Northumbria at Newcastle on 2009-04-06 < 1% match (student papers from 25/02/05) 31 Submitted to University of Glamorgan on 2005-02-25 < 1% match (student papers from 01/04/08) 32 Submitted to University of Portsmouth on 2008-04-01 < 1% match (student papers from 24/02/08) 33 Submitted to The Robert Gordon University on 2008-02-24 < 1% match (Internet from 20/5/09) 34 http://www.pafis.shh.fi/graduates/josnwa05.pdf < 1% match (student papers from 10/03/09) 35 Submitted to Oxford Brookes University on 2009-03-10 < 1% match (student papers from 06/02/10) 36 Submitted to University of Gloucestershire on 2010-02-06 < 1% match (student papers from 04/09/09) 37 Submitted to The University of Manchester on 2009-09-04 < 1% match (student papers from 18/01/06) 38 Submitted to University of Ulster on 2006-01-18 < 1% match (student papers from 14/08/10) 39 Submitted to University of Glasgow on 2010-08-14 < 1% match (Internet from 10/5/10) 40 http://etd.lib.metu.edu.tr/upload/12605141/index.pdffile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 3/45
  • 4. 3/8/13 TurnitinUK Originality Report < 1% match (student papers from 19/11/07) 41 Submitted to Bournemouth University on 2007-11-19 < 1% match (student papers from 27/08/09) 42 Submitted to Glasgow Caledonian University on 2009-08-27 < 1% match (student papers from 26/03/08) 43 Submitted to University of Greenwich on 2008-03-26 < 1% match (Internet from 22/7/10) 44 http://www.posey.com/files/MK1414.pdf < 1% match (Internet from 14/4/09) 45 http://www.ida.liu.se/~steho/und/htdd01/1080160104.pdf < 1% match (student papers from 09/09/08) 46 Submitted to Sheffield Hallam University on 2008-09-09 < 1% match (student papers from 15/04/08) 47 Submitted to University of Huddersfield on 2008-04-15 < 1% match (student papers from 08/04/08) 48 Submitted to Coventry University on 2008-04-08 < 1% match (student papers from 22/09/09) 49 Submitted to University of Northumbria at Newcastle on 2009-09-22 < 1% match (student papers from 19/11/07) 50 Submitted to Bournemouth University on 2007-11-19 < 1% match (student papers from 13/05/10) 51 Submitted to Brunel University on 2010-05-13 < 1% match (student papers from 16/10/07) 52 Submitted to University of Stirling on 2007-10-16 < 1% match (student papers from 14/08/10) 53 Submitted to University of Leicester on 2010-08-14 < 1% match (student papers from 25/01/05) 54 Submitted to University of Northumbria at Newcastle on 2005-01-25 < 1% match (student papers from 15/04/10) 55 Submitted to University of Greenwich on 2010-04-15 < 1% match (student papers from 12/08/10) 56file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 4/45
  • 5. 3/8/13 TurnitinUK Originality Report Submitted to Royal Holloway and Bedford New College on 2010-08-12 < 1% match (student papers from 13/03/08) 57 Submitted to University of Huddersfield on 2008-03-13 < 1% match (student papers from 23/07/10) 58 Submitted to Buckinghamshire Chilterns University College on 2010-07-23 < 1% match (student papers from 22/04/08) 59 Submitted to University of Southampton on 2008-04-22 < 1% match (Internet from 10/9/08) 60 http://www-csc.dg.com/csc/plus/DGUX-4.asp < 1% match (student papers from 13/09/07) 61 Submitted to University of Lancaster on 2007-09-13 < 1% match (student papers from 24/04/09) 62 Submitted to University of Strathclyde on 2009-04-24 < 1% match (student papers from 16/08/10) 63 Submitted to University of Warwick on 2010-08-16 < 1% match (student papers from 31/08/07) 64 Submitted to University of Northumbria at Newcastle on 2007-08-31 < 1% match (Internet from 6/5/10) 65 http://intranet.cs.man.ac.uk/Intranet_subweb/library/3yrep/2008/5731213.pdf < 1% match (Internet from 24/5/10) 66 http://ecommons.txstate.edu/cgi/viewcontent.cgi?article=1017&context=anthroptad < 1% match (Internet from 20/3/09) 67 http://www.diva-portal.org/diva/getDocument?urn_nbn_se_umu_diva-1745-2__fulltext.pdf < 1% match (Internet from 9/8/10) 68 http://bes.tkk.fi/en/publications-002/papers/paper_66/out/ < 1% match (Internet from 23/1/07) 69 http://www.qualityindicators.ahrq.gov/news/AHRQ_QI_RAHM_Draft.pdf < 1% match (Internet from 22/2/09) 70 http://www.telecomsmarketresearch.com/resources/UK_Mobile_Operator_Subscriber_Statistics.shtml < 1% match (student papers from 28/08/08) 71 Submitted to University of Durham on 2008-08-28file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 5/45
  • 6. 3/8/13 TurnitinUK Originality Report < 1% match (student papers from 28/02/10) 72 Submitted to University of Leicester on 2010-02-28 < 1% match (student papers from 29/07/10) 73 Submitted to London School of Commerce on 2010-07-29 < 1% match (student papers from 28/05/10) 74 Submitted to London School of Commerce on 2010-05-28 < 1% match (student papers from 13/05/10) 75 Submitted to Southampton Solent University on 2010-05-13 < 1% match (student papers from 11/05/09) 76 Submitted to University of Hull on 2009-05-11 < 1% match (student papers from 00/00/00) 77 /paperInfo.asp?r=24.2006643414076&svr=5&session- id=50af39bb1c63ace578f5306b0a83b37d&lang=en_us&oid=5862715 < 1% match (Internet from 9/5/10) 78 http://www.pafis.shh.fi/graduates/agyasa05.pdf < 1% match (Internet from 11/1/10) 79 http://bloodpressurenormalrange.info/?m=20091208 < 1% match (Internet from 6/7/09) 80 http://www.isobd.org/artifacts/Volume_III_Issue_III.pdf < 1% match (publications) 81 Journal of Services Marketing, Volume 11, Issue 1 (2006-09-19) < 1% match (student papers from 03/05/10) 82 Submitted to University of Greenwich on 2010-05-03 < 1% match (student papers from 23/08/08) 83 Submitted to University of Leicester on 2008-08-23 < 1% match (student papers from 29/08/08) 84 Submitted to University of Birmingham on 2008-08-29 < 1% match (student papers from 26/03/08) 85 Submitted to University of Greenwich on 2008-03-26 < 1% match (student papers from 02/05/07) 86 Submitted to University of East London on 2007-05-02 < 1% match (student papers from 31/07/08)file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 6/45
  • 7. 3/8/13 TurnitinUK Originality Report 87 Submitted to University of Hull on 2008-07-31 < 1% match (student papers from 06/12/09) 88 Submitted to University of Strathclyde on 2009-12-06 < 1% match (student papers from 23/04/10) 89 Submitted to University of Brighton on 2010-04-23 < 1% match (student papers from 09/03/06) 90 Submitted to University of Derby on 2006-03-09 < 1% match (student papers from 07/04/08) 91 Submitted to Bournemouth University on 2008-04-07 < 1% match (student papers from 04/02/10) 92 Submitted to North East Wales Institute of Higher Education on 2010-02-04 < 1% match (student papers from 20/04/10) 93 Submitted to Heriot-Watt University on 2010-04-20 < 1% match (student papers from 31/03/10) 94 Submitted to University of Hertfordshire on 2010-03-31 < 1% match (student papers from 17/10/07) 95 Submitted to University of Southampton on 2007-10-17 < 1% match (student papers from 02/09/09) 96 Submitted to The Robert Gordon University on 2009-09-02 < 1% match (student papers from 25/04/08) 97 Submitted to Napier University on 2008-04-25 < 1% match (student papers from 13/06/08) 98 Submitted to University of Wales Institute, Cardiff on 2008-06-13 < 1% match (student papers from 13/05/09) 99 Submitted to Bath Spa University College on 2009-05-13 < 1% match (student papers from 30/01/08) 100 Submitted to University of Northumbria at Newcastle on 2008-01-30 < 1% match (student papers from 14/10/09) 101 Submitted to Kingston University on 2009-10-14 < 1% match (student papers from 12/08/10) 102 Submitted to Holborn College on 2010-08-12file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 7/45
  • 8. 3/8/13 TurnitinUK Originality Report < 1% match (student papers from 18/11/09) 103 Submitted to Oxford Brookes University on 2009-11-18 < 1% match (student papers from 03/05/07) 104 Submitted to Leeds Metropolitan University on 2007-05-03 < 1% match (student papers from 09/01/08) 105 Submitted to Cardiff University on 2008-01-09 < 1% match (student papers from 13/01/10) 106 Submitted to Bolton Institute of Higher Education on 2010-01-13 < 1% match (student papers from 11/01/10) 107 Submitted to Bolton Institute of Higher Education on 2010-01-11 < 1% match (student papers from 14/05/08) 108 Submitted to University of Greenwich on 2008-05-14 paper text: 261. INTRODUCTION 1.1 Background to the study: During the last few years, the Telecom industry has experienced an enormous growth across the world and there has been a rapid growth in the wireless technology (Bharat Book Bureau, 2008). According to an industry market study, by 2013 the telecommunications industry is anticipated to attain revenue of $2.7 trillion with an average growth rate of 10.3 percent an year (Bharat Book Bureau, 2008). In the present dynamic and interactive market place, the organisations are proposing various strategic methods to achieve effective Customer Satisfaction (CS) strategy decisions and eventually increase the CS success rates to sustain 103long term relationship with the profitable customers (Chien and Su, 2003; Gronroos, 1994). 12"Loyal customers are reported to have higher customer retention rates, commit a higher share of their category spending to the firm, and are more likely to recommend others to become customers of the firm." (Keiningham et al., 2007, p. 362). Hence the organisations are becoming more customer centric, giving more importance to retaining old customer as the business would end up spending an approximate of five times more in attracting new customers than retaining the existing customers in terms of time, money and resources (Reichheld, 1996; Pizam and Ellis, 1999). As the growth of the organisation and its survival in the market is driven by customer loyalty and customer retention, each of these companies is continually improving on their service quality standards to survive in this highly competitive market (Keiningham et al., 2007). Hence, in order to maintain these service quality standards, organisations frequently adopt new measures to checkfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 8/45
  • 9. 3/8/13 TurnitinUK Originality Report 3if the customers are satisfied with the service quality provided. For e.g. by conducting customer surveys and analysing the acquired data statistically, which would help them 83make the right decision to increase customer satisfaction and eventually customer loyalty among their customers (SPSS White Paper, 1996). Organisations adopt both quantitative and qualitative methodologies to evaluate CS and the data obtained from these measures provide constructive feedback to help the organisation know the satisfactory level of its customers with its products, which would help the organisation to: i) take reliable steps to improve the quality of service, ii) adding more value to its customers and iii) achieving high customer satisfaction rates (Amaratunga et al., 2002). 1.2 Overview of the UK Telecommunications Market: Telecommunications is one of the best growing sectors of the UK economy. The competition developed strongly in 1984 after the privatisation of British Telecom (BT) and as of 2004, the UK had an approximate of 170 fixed telecommunications provider and 59 mobile service providers (CWU research, 2004). The market for fixed telephone network has been declining since the evolution of mobile / cellular phone networks and in 2003 due to flat call volumes and pricing competition, it fell by £400m (CWU research, 2004). Eventually, the consumers preferred the cellular phone networks as the mode of communication which was faster and easier than the fixed telephones (CWU research, 2004). According to the 70UK Mobile Operator Subscriber Data, Statistics and Market Share 2006 - 192008, there are five primary cellular network operators in the UK: 76Vodafone, Telefonica O2, T-Mobile, Orange and 3 UK and it was reported to have 73.1 million cellular service 19subscribers in the last quarter of 2007, which represents almost 9% of the total European mobile subscriber market and another statistical report from IE market research Corp reveals that the wireless market is anticipated to achieve 126% by 2010 and gradually the total subscribers would also 75reach 78 million by 2010 (Telecoms Market Research, 2008). 1.3 The current state of telecommunication industry in the UK: Today, the telecommunication industry has undergone a rapid transformation creating a lot of new challenges for infrastructure and service providers. The rapid advances in technology and increased market turbulences have added a lot of value to the telecom industry (Lia and Whalley, 2002). Recently T-Mobile and Orange merged becoming a giant in thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 9/45
  • 10. 3/8/13 TurnitinUK Originality Report telecom industry having 28.4 million customers and now they are the largest cellular service provider in the UK with an approximate of 9437% of the entire mobile market (BBC News, 2009; The Register, 2010). The 3G network is up to 40 times faster in data than the 2g or the GSM networks. This high connection speed adds on more features such as sending Pictures, MMS (Multimedia Messaging Service) or video clips and also promotes high quality sound (Robins, 2003). However this rapid growing mobile market is expected to face capacity-crunch i.e. due to the increasing existence of several MVNOs, the mobile data traffic has gradually increased 200% in 2009 and according to the reports of Ofcom, few service providers such as O2 are about to hit that capacity (Xln Business Community, 2010). Hence, this capacity- crunch may bring down the quality of service delivery necessitating the network operators to take precautions in order to maintain their service delivery standards. The 28market share of mobile telecom industry in the UK as of September 2009: Fig 1.3a 28Market Share of Mobile telecom industry in the UK (Source: Guardian News, 2009) The Fig 1.3a indicates that, as of September 2009, T-Mobile / Orange had 37% of market share being the highest, followed by O2 with 28%, Vodafone with 23% and 3-mobile with the least at 5.8%. The total number of subscribers for the UKs mobile telecom industry as on September 2009: Fig 1.3b Number of subscribers for the UKs mobile telecom industry (Source: Guardian News, 2009) The Fig 1.3b indicates that, as of September 2009, T-Mobile / Orange had 28.4 million customers being the highest followed by O2 having 21.5 million customer, Vodafone with 17.7 million customers and 3-mobile having the least at 4.5 million customers. 1.4 Problem Identification & Purpose of the Study: Though majority of the customers for UK mobile telecommunication networks use all of their mobile services like text, data and mobile internet services, they are dissatisfied with the service-availability and its quality; especially the network coverage is a crucial concern to all of its consumers. (Telecom paper, 2009) Due to the existence of several MVNOs (Mobile Virtual Network Operator), customers switch to different service providers frequently and they are also concerned about the self- regulatory schemes by their network providers (Telecom paper, 2009). Customers are known to have reported that there is no network clarity and coverage. They are not being told if they would have network coverage in their area before they could sign a contract with the company and they are unhappy with the after sales service that is being provided to them (Poulter, 2009). "A study on 5,000 people revealed the telecom giants are nearly twice as bad at dealing with issues and complaints compared with their successors British Gas." (Xln Business Community, 2009). The customers dont get reliability and assurance in the services they are being offered, as they have to go through a sequence of inconsistencies such as waiting in long queues to speak to representative, incompetent employees who do not understand the correct issue that is being faced and bear with their rude behaviour at times (Xln Business Community, 2009). These situations create a bad impression in the customers mind and lead them to change the service provider. Also, this word of mouth communication can spoil the image or reputation of the company. Hence the main research aim of this study would be: To measure and critically 7analyse the level of customer satisfaction with regards to service delivery among different mobile service providers (Mobile Telecommunication Networks) within thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 10/45
  • 11. 3/8/13 TurnitinUK Originality Report UK. 1.5 Research Questions: How the customers satisfaction with the service quality is described in the UKs MTNs with and without respect to the customers service providers? Which attributes of service quality do the customers perceive to be of more importance that lacks attention from the service providers in the UK? 1.6 Research Objectives: To find out the level of customers 4satisfaction with the service quality offered to them by the UKs MTNs with and without respect to which network customers subscribe to. 33To find out which dimensions of service quality are the customers satisfied/dissatisfied with in the UKs MTNs. To identify the Service Quality dimensions that the customers perceive to be of high importance in the UKs MTNs. 1.7 Significance and Limitations of this dissertation: This study is significant in various ways to business consultants and business partners. The results and findings of this study would be helpful to the management of UKs cellular service providers, as it provides a reliable scientific measure to evaluate customer satisfaction level with the services delivered by them. It will reveal the 11dimensions of service quality which are considered more important from the customers perspective, which would provide them with a priceless empirical support to make right strategic decisions in the required areas of operations and over-all it would act as reliable guide to improve their service delivery standards and create customer-value. This dissertation would provide enormous valuable information to business partners such as share-holders and investors which would help them provide useful suggestions to their respective mobile service providers to improve their service delivery standards. The dissertation enables the customers to analyze the ratings of the various dimensions with respect to the service providers so that bringing in awareness among customers. The limitations of this dissertation are that, the research would not have access to every locality 74in the UK and as the research is mostly done in the city of London. But London, being a cosmopolitan city, gives us a gist of UK and a right place to conduct the research. It doesnt allow us to conduct the analysis on large samples, which is a prerequisite to have more reliability on surveys (Saunders et al., 2007). But, as the MTNs are a public service and have millions of users, the samples are obtained from a much diversified respondents to obtain the best possible results. 842. LITERATURE REVIEW 2.1 Purpose of Literature review: The literature review aims at critically exploring the existing knowledge and theories that are relevant to the research objectives, so that we can develop and refine the key areas of our research (Saunders et al, 2007). To generate and refine the research ideas the Relevance Tree technique is used in this review of literature i.e. a broad concept is studied from the view of various authors via which a new sub-concept is developed and as we proceed deep into the subject new ideas are formulated (Saunders 87et al, 2007). The customer satisfaction is measured through thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 11/45
  • 12. 3/8/13 TurnitinUK Originality Report service quality dimensions defined for that particular product or service. These dimensions are based on different models created by academics which I critically analyse in the literature and adopt those that best suit the aim of this dissertation. 2.2 Customer Psychology: A Customer is usually the final user of any product where the purpose of it being made gets fulfilled (Hayes, 1997). Understanding the psychology of customers plays a very important role in determining their satisfaction over a product or service. This includes designing 31a product according to the needs of the customer. The satisfaction of a customer starts well before manufacturing the product rather than the moment after sale. During the service encounters the customers values, perceptions, beliefs and expectations motivate them to choose one service provider rather than another (Lynch, 1992; Pizam and Ellis, 1999). At any point of sale, there are four options available for the customer to choose: Purchase – where the customer is convinced to buy a product or service, Rejection – where the customer rejects the offer, Postponement – where the customer is partly convinced and postpones the offer to think at a later date and substitution – where the customer compares the product with other contemporary offers. Hence influencing the customers choice to purchase a product is very crucial (Lynch, 1992; Pizam and Ellis, 1999). Therefore, 88it is very essential for us to know the customer expectations and their requirements, to understand customers view and perspective about the 104quality of services and products they need (Pizam and Ellis, 1999). 2.3 Role of 46Customer Satisfaction: Customer Satisfaction (CS) is said to be the customers post-purchase evaluation of services or a product. When the CS level of an organisation is high, even the market share and profits of the organisation grow higher leading the company 82to a stronger competitive position in the market place (Turkyilmaz and Ozkan, 2007). The customer satisfaction is built on the varied experiences, positive and negative that the customer has come across at different points of time (Satari, 2007). The impact of customer care in service quality system would maximize profits and help the organisations grow by providing 54customer satisfaction and building great customer experiences. Customer care is therefore a key to gain the competitive advantage among the competitors (Lynch, 1992). 21"Satisfaction of customers also happens to be the cheapest means offile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 12/45
  • 13. 3/8/13 TurnitinUK Originality Report promotion and therefore, 14customer satisfaction is recognized as of great importance to all commercial firms because of its influence on repeat purchases and word-of mouth recommendations." (Pizam and Ellis, 1999, p. 326). Hence, it becomes important for the organisation to offer customers a good experience that exceeds their expectation and if the customers have bad experiences, then the reputation of the company reduces rapidly due to word-of-mouth communication. Satisfaction of customers over a telecommunication product can be two dimensional: i) It can be component specific – i.e. service specific, over the MMS services, 3G services, speed etc. and ii) It can be product specific – satisfaction 7on the overall performance and responsiveness of the mobile service provider (Cronin and Taylor, 1992). These dimensions require us to measure the satisfaction level of the customers in different particular components as well as on the whole. 2.4 Measuring Customer Satisfaction: In order to take managerial decisions, the CS needs to be measured in an organisation and this Customer Satisfaction Measurement (CSM) is used to determine the 10customer satisfaction level based on the valuable feedback from the customers and identifying the customer expectations (Crosby, 1991). The service quality can be achieved only by knowing the customers total needs or customer expectations and with the help of this data, the service standards and processes may be altered to achieve customer satisfaction (Crosby, 1991). After in depth research on CSM, nine distinct theories were developed such as: Expectancy disconfirmation (Parasuraman et al, 1988), Assimilation contrast, Comparison level (Gronroos, 2001), Value precept (Zeithaml, 1988), Cognitive dissonance, Equity, Generalised negativity, Contrast and Attribution (Kauppinen et al., 2007). Most of these theories were based on cognitive psychology, but they were developed with no empirical research. However, among these, only two of them were widely accepted i.e. the expectancy disconfirmation theory and customer satisfaction indices (Pizam and Ellis, 1999) because all the theories mentioned above use these two models as a common base 17(Parasuraman et al, 1988; Gronroos, 2001; Zeithaml, 1988; Kauppinen et al., 2007). Therefore, we would review the customer satisfaction indices and disconfirmation models which would form the crux of this study. 2.5 Customer Satisfaction Indices (CSI): This model focuses more 48on customers overall satisfaction with a product or the services offered to them till date and it is based on a cumulative view of satisfaction (Turkyilmaz and Ozkan, 2007).file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 13/45
  • 14. 3/8/13 TurnitinUK Originality Report 18"The CSI model is a structural model based on the assumptions that customer satisfaction is caused by some factors such as perceived quality (PQ), perceived value (PV), expectations of customers, and image of a firm." (Turkyilmaz and Ozkan, 2007, p. 673). The Swedish Customer Satisfaction Barometer (SCSB) is reported to be the first national customer satisfaction index (NCSI) which was developed in 1989, then the model was followed by the Germans, they named it as German Customer Barometer (Fornell, 1992). The Americans adapted this model in 1993, it was developed by Claes Fornell, who was the founder of SCSB and they named it as the 43American Customer Satisfaction Index (ACSI). The ACSI is a cause and effect model using the responses from the respondents to form a Multi-Equation Econometric model. The responses were collected according to different variables in a 0-100 scale (Turkyilmaz and Ozkan, 2007; Fornell, 1992). The 25European Organisation for Quality (EOQ) and European Foundation for Quality Management (EFQM) jointly developed the European Customer Satisfaction Index (ECSI) in 1999. Then gradually many other countries followed the CSI model (Turkyilmaz and Ozkan, 2007). The ECSI model included the Corporate Image as a component on top of the ASCI model. But, these indices do not measure the CS levels for specific components and overall CS together (Turkyilmaz and Ozkan, 2007). The Workforce Centre developed the Minnesota Customer Satisfaction Index (MnCSI). The MnCSI model is specifically used to evaluate over-all customer satisfaction with service delivery of the MTNs on a single scale (Positively Minnesota, 2007). This model uses the variables of disconfirmation models: both desire disconfirmation as well as expectation disconfirmation and it combines three questions which includes the disconfirmation models also (As discussed earlier disconfirmation models are the second CSM tool which was widely accepted) It also gets more stable when there are three questions instead of one. In addition, it is comparatively flexible and best suited for any number of responses (Positively Minnesota, 2007). 2.6 Disconfirmation Models: 9According to Parasuraman et al. (1988), customer expectations are one of the most important factors of CS, as they 13play a major role of ascertaining customer satisfaction. Even the SERVQUAL model uses the disconfirmation model as its base and it is basically used for conceptualizing service quality 29(Parasuraman et al., 1988). The disconfirmation model was tested and confirmed in a lot of studies conducted across the world and there are two different types of disconfirmation models - Desire-Disconfirmation model and Expectancy disconfirmation model (Pizam andfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 14/45
  • 15. 3/8/13 TurnitinUK Originality Report Ellis, 1999; Parasuraman et al., 1988). The expectancy disconfirmation model states that quality is assessed by comparing perceived and expected performance i.e. to examine if the customer expectations were met during the service delivery process (Oliver and DeSarbo, 1988; Kang and James, 2004). According to Oliver (1980), the expectancy disconfirmation model has got two internal attributes, which are known as positive disconfirmation and negative disconfirmation. 29If the performance of the product or service exceeds the customer expectations 24and when the customer is highly satisfied with the product or service delivered, then it is called as value disconfirmation. However, if the customers expectations are met and he/she is satisfied with the product or services offered, then it is positive disconfirmation and finally if the product or service perceived is below his/her expectations, then it is called negative disconfirmation (Oliver, 1980). This theory focuses more on the antecedents of satisfaction, which occurs at the initial stages of the service-delivery process (Oliver, 1980; Oliver and DeSarbo, 1988; Kang and James, 2004). Recently Khalifa and Liu (2002) built a theory that embedded both desire as well as expectancy disconfirmation theory. They have proved that both these factors impact the over- all customer satisfaction, as they both are of cognitive standards and it is hard to evaluate which one of these factors explains CS better. 2.7 Service Quality: Service Quality means the service that meets all the customers expectation and satisfies their needs and requirements or it 45is defined as "a consumers judgment about an entitys overall excellence or superiority." (Kang and James, 2004, p. 267) This term is purely customer oriented. Hence excellence in service requires an understanding of customer needs and expectation (Edvardsson, 1998). As there was an enormous growth in 7mobile telecommunications market in the last few years, the customers are more conscious about the quality of services being offered to them (Kumar and Lim, 2008). According to Kumar and Lim (2008), the service quality in MTNs can be perceived through the technical 47as well as the functional attributes of mobile services in which the technical attributes include the pricing/tariff plan, the 23network quality & data services and the functional attributes include the 23customer service quality and the billing system.file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 15/45
  • 16. 3/8/13 TurnitinUK Originality Report 23"Overall perceptions of service quality are formed by a consumers evaluation of multiple quality dimensions." (Kumar and Lim, 2008, p. 569). Hence in order to enhance the customers perceived value and their satisfaction level, it is important for the organisations to create positive perceptions of service quality among its customers (Kumar and Lim, 2008). Service quality enhances the organisations operational efficiency as well as improving the retention rate of its firm (Edvardsson, 1998). The customers assess the product quality in various tangible ways such as its colour, style and feel. But in most of the cases only few of these tangibles exist and meet the customers expectation 37(Parasuraman et al., 1985). According to Parasuraman et al. (1985), as the services being 1intangible in nature, most of it cannot be measured and their heterogeneous nature makes them vary from time to time and customer to customer. Hence because of these natures, it becomes hard 13to evaluate the service quality of an organisation. Gronroos (2001) introduced the concept of Consumer Perceived Quality (CPQ), which evaluates to what extent the service delivered, meets the customers expectation. It compares the consumers expectations and the customers perception of service received. According to this theory, over- all satisfaction of the customer with the organisation is based on every encounter or experience he had with that organisation. Hence they claim 17that service quality and customer satisfaction are distinct conceptually but they are closely related constructs 3(Kang and James, 2004; Sureshchandar et al., 2002). A recent study has proved that "the CPQ influences profitability directly as well as indirectly through market share." (Crosby, 1991, p. 6). Hence it is equally important to take CPQ under consideration 3for this research. According to Parasuraman et al. (1988), the long term and global evaluation of a service 61is related to the service quality perceived by the customers and the customer satisfaction can be obtained by evaluating specific service transactions and they have alsofile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 16/45
  • 17. 3/8/13 TurnitinUK Originality Report clearly pointed out that the customer 54experience with the provided service, influence the perceptions of service quality. Hence, 85it could be said that both service quality and CS are closely related terms. 2.8 Relationship between 52Service Quality and Customer Satisfaction: The relationship between service quality and customer satisfaction has gained 50a lot of attention in the last few years and they are considered to be the two core components that frame a crux of the marketing theories (Sureshchandar et al, 2002). In the current competitive market, the companies can sustain its competitive advantage by providing service quality of higher standards, which would 31result in satisfied customers (Sureshchandar et al, 2002). Customers are 73one of the important assets of an organisation as they are the only ones who keep the business running. As it was already discussed earlier 95that retaining existing customers is more essential than generating new ones, 108it is important to have service quality in every stroke 102to build a long term relationship with the customers, which adds more value to the consumers as well as the company (Nguyen et al, 2007). Based on the 7quality of service delivered, is the consumers commitment tofile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 17/45
  • 18. 3/8/13 TurnitinUK Originality Report renew/continue our service consistently in the future (Nguyen et al, 2007). Figure 2.8: Five 4critical factors of customer perceived service quality Source: (Sureshchandar et al., 2002) The figure 2.8 indicates the five 15critical factors of customer perceived service quality, in which the core services refer to the content of the services i.e. the different features 15offered in a service. The human element of services refers to the empathy, assurance, reliability and responsiveness i.e. includes the factors that affect the human behaviour. Standardisation of services refers to the systematizing and simplifying the systems, processes and the procedures. The 71tangibles refer to the physical facilities available, equipments and the appearance of their workers and finally the social responsibility refers to encouraging ethical behaviour in every aspect, which would improve the image of the company and also promote customer loyalty and overall customer satisfaction (Sureshchandar et al., 2002). 2.9 10Service Quality Dimensions: According to Johnston (1995), 90it is crucial to identify the determinants of service quality before we proceed with the service research. Hence this becomes a central concern, as it is necessary 33to find out the determinants of service quality to define measures and control customer perceived service quality. In 1980s, 42Parasuraman et al. (1985, 1988, 1994) developed the SERVQUAL model to determine what service quality meant to the consumers, followed by the measures they developed strategies 31to meet customers expectations. It is considered to be the most popular instrument, which is widely used by many researchers and practitioners to measure service quality (Sureshchandar et al., 2002). 2.10 Service Quality Models: Many models were developed tofile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 18/45
  • 19. 3/8/13 TurnitinUK Originality Report capture the quality of service at different points of time to suit different business objectives (Nitin et al, 2005). The earliest ones were that of Gronroos, (1984) Technical and Functional Quality Model where the perceived quality was compared with the Expected Service with reference to the Functional and Technical dimensions. The next popular model was 49Parasuraman et al.s (1985) GAP model. This model analysed the gaps 21between the customers expected and perceived service forming a base for the SERVQUAL model with several dimensions like Tangibles, Reliability etc. However, the SERVQUAL model has been subjected to a lot of criticisms and there have been many scholars who had tried to modify or restructure this model conceptually (Kang and James, 2004). The next model designed by Haywood (1998) called as Attribute ServQual Model incorporated 3 58attributes: Physical facilities and process, Peoples Behaviour and Professional Judgement into the SERVQUAL components. Haywood (1998) also said that all the three attributes needs to have a balance and if not leads to fall in quality. The Synthesized ServQual Model by Brogwicz et al. (1990) explained the importance of the customers perception of the brand and image before even the product launched. This model added up the Company Image component and its elements to the SERVQUAL model. Meanwhile, 9Cronin and Taylor (1992) developed SERVPERF, the Performance Only Model which states that the consumers perceptions on the brand actually predict the service quality and the perception index is a worthy indicator of the Service Quality. It also criticises that the SERVQUAL model mixes satisfaction with perception. But the perception cannot always be a proper service quality indicator because perceptions do change with time, and the organisation that provide unmatched service excellence always lead even when started with comparatively lesser brand awareness and marketing system. The Mattsons (1992) Ideal Value Model calculates the Service Quality in comparison with the Ideal Industry Standard rather than the Customers perceptions. This model may strive to provide the best service in line with the technological capability but the innovation may not be focussed on the customers requirements. The IT Alignment Model (Berkley and Gupta, 1994) introduced Information Technology for improving the service quality. Meanwhile, Dabholkar (1996) introduced the Attribute and Overall Affect Model which examines the technology used self service options to minimize labour costs. The PCP Attribute (Philip and Hazzlet, 1997) egg prioritized the dimensions as Pivotal, Core and Peripheral. Oh (1999) depicted the importance of Customer Value. 27Frost and Kumar (2000) proposed the Internal Service Quality dimensions based on the GAP model for the Internal Customers of the organisation. In thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 19/45
  • 20. 3/8/13 TurnitinUK Originality Report 27Internal Service Quality DEA model (Soteriou and Starvinide, 2000), the Data Envelope Analysis maps the depreciation in service quality from the client base to branches. 37Santos (2003) e-Service Quality is developed on the antecedents of service quality using e- commerce. 2.11 53SERVQUAL: SERVQUAL is a multiple item scale developed to measure the Service quality and this instrument illuminates the different dimensions of customers perception and helps assessing the 1service quality (Parasuraman et al., 1985, 1988). It has illuminated five dimensions via which customers perceive and assess service quality of the organisation and each dimension has a sub-set called items via which the dimensions are being measured 86(Parasuraman et al., 1988). The five dimensions are: 1. 13Tangibles: This includes the physical facilities available, equipments and the appearance of their workers. 2. Assurance: This includes the courteous nature and the product knowledge of the employees and also if they are confident and trust worthy. 643. Responsiveness: Providing quick service and their willingness to help the customers. 4. Empathy: Caring for the customers with more individualised attention. 5. Reliability: Providing accurate service and performing the promised commitments (Parasuraman et al., 1988). The required 57data is collected via structured questionnaire or surveys from a sample of customers in which many questions are formulatedfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 20/45
  • 21. 3/8/13 TurnitinUK Originality Report 72based on the key service quality dimensions (Parasuraman et al., 1988, 1994). Before reviewing other models based on SERVQUAL, it is better to look into the advantages and disadvantages of SERVQUAL. Advantages and Disadvantages of SERVQUAL: SERVQUAL has overlooked at some of the 15important factors of service quality such as the social responsibility of the organisation, core service and standardisation of service delivery and 17there is also a general agreement towards the 22 items scale, that they are reasonably good predictors of service quality (Sureshchandar et al., 2002). Most of the research models till date have used SERVQUAL as its base for development (Sureshchandar 9et al., 2002). The SERVQUAL model has also been severely criticized in many cases. The contents of the service quality dimensions obtained from the SERVQUAL model has not been accepted by everyone, as 100service quality is generally viewed as a multi-dimensional construct and it focuses mainly on the service delivery aspects and there are many additional factors also to be considered for e.g. Considering only the functional attributes to predict customers behaviour may have low predictive validity, the semantic differences are not being withstanded in each dimension, etc. 3(Kang and James, 2004; Sureshchandar et al., 2002). The criticisms also 5include "the use of difference scores, dimensionality, applicability and the lack of validity of the model, especially with respect to the dependence or independence of the five main variables" (Kang and James, 2004, p. 267). Hence considering all these criticisms that SERVQUAL is renowned for its widespread use by other researchers and scholars and it also has got lot of disadvantages it is advisable to look into other models based on SERVQUAL. 9In 1992, Cronin and Taylor developed the Performance only model, whichfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 21/45
  • 22. 3/8/13 TurnitinUK Originality Report they called it SERVPERF. It states that service quality can only be assessed by perceptions and it is not necessary to measure expectations (Cronin and Taylor, 1992). The author views service quality as a link between purchase intentions and customer satisfaction and they challenged the SERVQUAL framework 101by Parasuraman et al. (1985), that perceptions are the only predictors of service quality where as SERVQUAL model confuses consumer satisfaction with attitude of the consumers 1(Cronin and Taylor, 1992). Similarly, Brogowicz et al. (1990) argued that there are many chances for the service quality gap to occur well before the customer experiences the service, as the customer may learn through various ways 50such as word-of-mouth communication and advertisements. It integrates the traditional managerial framework to the service quality which comprises of three factors: image, traditional marketing activities and external influences and the model was called 27synthesized model of service quality (Brogowicz et al., 1990). Another study by Haywood-Farmer (1988) suggests that the attributes has to be separated into three groups: professional judgement, processes & facilities and consumers behaviour and each of the attributes comprises of various factors. It also states that all the three groups must be given equal importance, in case if any one of the attribute is given more importance than others, then it may lead to a disaster (Haywood-Farmer, 1988). Similarly, 26Parasuraman et al. (1985) had stated that service quality cannot be assessed only with service outcomes but even the 26service delivery process needs to be evaluated, the SERVQUAL is composed of only functional dimension of service quality and they lack technical dimension and corporate image. Both these dimensions are inter correlated. The attributes of functional quality refers to the American perspective of service quality but however according to the European perspective, the service quality needs two more attributes in addition, which are technical quality and the corporate image (Kang and James, 2004). The Gronroos SERVQUAL model includes all the three attributes i.e. necessary from the European perspective. Moreover, the Gronroos ServQual model was used in an empirical research in the telecommunications field, which had proved 5that Gronroos model is more appropriate to represent service quality in telecommunications industryfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 22/45
  • 23. 3/8/13 TurnitinUK Originality Report 105(Kang and James, 2004). 2. 12 Gronroos Model of SERVQUAL: It is a multi dimensional model. According to this model there are 5two service quality dimensions, firstly the technical aspect (what kind of service is provided) and the functional aspect (how is the service being provided). They introduced the corporate image concept, as one of the other important element 98in the perceived service-quality model, as the customers would bring their perceptions and past experiences with the firm in each encounter with the organisation (Kang and James, 2004). If a positive image about the firm is created in the mind of a customer, then they wouldnt bother much about the minor mistakes that happens and in case there is a negative image about the firm, then the mistakes would be magnified in their mind (Gronroos, 1994; 89Kang and James, 2004). In the mobile telecommunications industry the customers look for both – How they are being served (functional dimension) as well as the nature of services and service outcomes which constitute the technical dimension (Kang and James, 2004). Hence these three dimensions (technical dimension, functional dimension and corporate image) are considered the most important. 2.13 Addressing the Research Questions As discussed earlier in the current state of telecommunication industry in the UK and Problem Identification in the introduction (section 1.3 and 1.4), the network operators are likely to face capacity crunch which induces network coverage and clarity issues. This in turn shall reduce the service quality standards to a new low. Moreover, even the reliability, assurance and responsiveness factors are not addressed with proper concern increasing the customers switching intention. At this juncture 49it is important to know the service quality dimensions valued more by the customers and to give more attention towards those in order to achieve positive customer service experience. These problems led to the main research objectives specified. Based on the reviewed literature the research objectives can be obtained using the following theoretical models which has been justified in this chapter: i) The MnCSI model, Disconfirmation models (both desire and expectation) and over-all satisfaction measure is used to assess and describe the level of customers 4satisfaction with the service quality offered to them by the UKs MTNs with and without respect to which network customers subscribe to. ii) The expectation disconfirmation model is used in order to find which 7dimensions of service quality the customers are satisfied or dissatisfied with in thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 23/45
  • 24. 3/8/13 TurnitinUK Originality Report UKs MTNs. iii) The Gronroos 13Servqual model is used to identify the service quality dimensions that the customers perceive to be of high importance in the UKs MTNs. The research question one: How the customers satisfaction with the service quality is described in the UKs MTNs with and without respect to the customers service providers? is answered by critically analysing the results obtained from the first research objective and the research question two: Which attributes of service quality do the customers perceive to be of more importance and lacks attention from the service providers in the UK? is answered by critically analysing the results obtained from objectives two and three. 3. RESEARCH 1METHODOLOGY 3.1 Research Purpose: According to Saunders et al. (2007), research is a systematic or a step by step procedure to increase the knowledge of a new or an existing subject. The 41purpose of this research is to key out the main service quality dimensions/attributes as perceived 7by the customers and find out how satisfied they are with these attributes and also to explore the reasons for their the intention to change their service providers (Saunders et al., 2007). 3.2 Research Philosophy: Research philosophy brings up different philosophical assumptions and beliefs that would support this research and help us selecting the appropriate research strategy and phenomenon. It has two core traditions: Positivism and phenomenological approach (Saunders et al., 2007). Positivism deals with the fundamental laws perceived by us and their scientific explanations. Phenomenological helps in trying to understand a particular phenomenon (Saunders et al., 2007). The three main characteristics of positivism are: ? The explanations and knowledge attained in this method are similar to that of natural science. ? The hypothetico deductive methodology which is followed by positivism is same as natural science. ? It treats its subject matter (i.e. mobile telecom networks in UK, in this study) just like how a natural scientist would treat the world (of natural forces/things) (Saunders et al., 2007). Hence, it implies that positivism deals with observable social reality. So, this research is built on this approach as it involves customer perceptions and identifying relationships through different theoretical frameworks. 13.3 Research Approach: According to Saunders et al., (2007), there are two 92broad methods of reasoning: deductive approach and inductive approach. The deductive approach is based on the top-down approach mode where 1a theory is developed and subjected tofile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 24/45
  • 25. 3/8/13 TurnitinUK Originality Report more observation after hypothesis as shown in the fig 4.3. It works from more general to specific reasoning 91(Saunders et al., 2007). Conversely, the inductive approach is based on the bottom-up approach model i.e. the theory is developed based on the data collected during research. However, the deductive approach is also said to have degrees of uncertainty 36(Saunders et al., 2007) and moreover, as this research is based on theoretical considerations, our research employs the deductive approach. Fig 3.3: Deductive Approach THEORY HYPOTHESIS OBSERVATION CONFIRMATION 3.4 43Research Method: There are two different groups of research methods: quantitative and qualitative. In quantitative analysis, we obtain statistical data that represents the concepts empirically. This data is further measured using the quantitative statistical methods which links the data to concepts (Neuman, 2006). On the other hand, qualitative analysis explains the social phenomena which involve interviews and observations from real life situations (Saunders et al., 2007) and the data here includes written/spoken words, physical objects, sounds or visual images measured simultaneously while collecting the data (Neuman, 2006). This research uses both quantitative as well as qualitative methods to get accurate results. The quantitative measurement uses the following models as justified in the literature review: Gronroos SERVQUAL model (Gronroos, 1994) to evaluate CS with the Service Quality dimensions (functional dimensions, Technical dimension and Corporate Image); Disconfirmation models to analyse and evaluate customers desires and expectations both with and without respect to their service provider (Oliver 1980; Parasuraman et al., 1988) and the MnCSI model to evaluate the over-all customer satisfaction with service delivery of the UKs MTNs with and without respect to which Mobile Telecom Network customers subscribe to (Positively Minnesota, 2007). According to Neuman (2006, pg. 412), "Researchers often combine focus group with quantitative research, and the procedure has its own specific strengths and weaknesses". The strengths are: the lively setting that allows respondents to express their opinions or ideas freely and interpretation of ideas is facilitated (Neuman, 2006). This helps in bridging rich ideas and data in a continuing and interactive manner via which we could have a better understanding of the subject in a bigger view and these strengths overwrites the weaknesses which are: polarization effect and limitation in the number of topics discussed in a session (Neuman, 2006). Hence focus group interview is the chosen Qualitative method as the research also includes quantitative measurement. The focus group interview uses the Delphi technique to refine the research ideas. This process involves employing a group of people who can contribute some more value to the research idea (Saunders et al., 2007). The members of the group were initially briefed about the research idea and were asked to suggest other important elements to measure the service quality. According to respondents, among these attributes they consider the balance between quality and cost as the most important. It was then derived as another dimension to the Gronroos SERVQUAL model called as Value for Money (VFM). This focus group interview lasted for 60 minutes and the details of which is described in Appendix-A. All the Service Quality Dimensions and its items (variables) used are listed in table 3.4. Each dimension is represented with indicators as shown in the table below. For e.g., Tangibles is TN, Reliability is RE, etc. A set of 3 items were added for every dimension based on its properties except VFM which has 2 items. The items/variables under each dimension are defined in the Appendix-H. Table 3.4: Service Quality dimensions and its comprising items No. of Service Quality Dimensions No. of Service Quality Dimensions Items Items 3 TANGIBLES (TN) 3 ASSURANCE (AR) 3 RELIABILITY (RE) 3 TECHNICAL QUALITY (TQ) 3file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 25/45
  • 26. 3/8/13 TurnitinUK Originality Report RESPONSIVENESS (RP) 3 CORPORATE IMAGE (CI) 3 EMPATHY (EP) 2 VFM (Value for Money) (VM) According to Neuman (2006), structured questionnaire is the most viable option for quantitative measurement to get precise information in all respective areas and also because of its ease of use nature. Since this research analyses several areas of service quality, the quantitative method is used via closed- ended survey or structured questionnaire designed based on all the items mentioned in Table: 3.4 to evaluate customer satisfaction with service delivery. A questionnaire was deployed for capturing the 10perceptions of customers about their mobile service provider. The questionnaire consists of three sections with several items as represented in Appendix-B: The first section includes age, sex and service provider to get variety of responses, and help us set a pattern for that specific group. The pattern analysis helps in satisfying the needs of specific groups in the society. The second section consists of disconfirmation measures (desire and expectation) derived from Disconfirmation Models, Over-all customer satisfaction measure and Service quality dimensions derived from Gronroos SERVQUAL model and focus group interview (VFM). The third section includes all Service Quality dimensions and asks the customer to rate the importance of each dimension from their perspective, which is 63measured on a five- point likert scale ranging from Least Important to Most important. The items in section 2 and 3 extensively analyzes the requirements of all groups of customers ranging from basic to advanced mobile services as well as the after sales service provided by their service provider. 3.5 Operationalisation of Concepts: 3.5.1 Minnesota Customer Satisfaction Index (MnCSI): This index may have up to 5 responses for 3 questions by which the customer satisfaction levels are evaluated. The responses are measured 56using a likert scale of 1 to 5 i.e. 1 being least satisfied and 5 being highly satisfied. The three questions asked to the customers are: 7Overall, how satisfied or dissatisfied you are with the services being provided by your network? How well does the service fulfil your expectations? To 8what extent did the services you received from them match your desired set of services? The questions mentioned above are rated on a five point likert scale i.e. each response would have a value from 1 to 5. Table 3.5.1a: Measuring MnCSI model on 5-point Likert scale RESPONSES 1 2 3 4 5 Question 1 Very dissatisfied Dissatisfied Neutral Satisfied Very Satisfied Question 2 Much worse Much better Equal to Better than 68Much better than expected than expected expectation expected thanfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 26/45
  • 27. 3/8/13 TurnitinUK Originality Report expected Question 3 8Much worse than desired Worse than desired Equal to my desire Better than desired Much better than desired The table 3.5.1a indicates the three questions with its corresponding values ranging between 1 and 5 where 1 indicates the customers very dissatisfaction with the services and 5 indicates the very satisfaction with the services. Then the answers to these three questions are then calculated using this formula (Positively Minnesota, 2007): Further, it is calculated using the following procedure: ? ? Step A: Frequency of each scale has to be found for all three answers. Step B: The weight of each response must be calculated as shown 69in table 3.5.1b Table 3.5.1b: Weight of each response Responses 1 2 3 4 5 ? Step C: The frequency of each response obtained from the customer is then multiplied with the response weight for all the three answers. ? Step D: The Sum of the values for all three answers is then evaluated ? Step E: The total sum is divided by (sample size-1) i.e. in our case it is 4. The Minnesota Customer Satisfaction index is evaluated using these steps. Then a description for customer satisfaction level is given to the derived value as shown in the table below: Table 3.5.1c: Description for each MnCSI value MnCSI Value Description 81-100 Very High 61-80 High 51-60 Fair 31-50 Low Below 30 Very Low Table 3.5.1c indicates that MnCSI value between 81-100 is marked Very High implying the high level of customer satisfaction, and subsequently low as the range decreases until Below 30 which is marked Very Low implying the low level of customer satisfaction level (Positively Minnesota, 2007). 3.5.2 Defining Hypothesis: Now we explain how the research objectives are transformed into hypotheses and executed. The following hypotheses are being used for this study: H1: Customers dissatisfied with services offered by cellular network in the UK with and without respect to which cellular network customers subscribe to. Sub-Hypotheses H1a H1b H1c H1d Dissatisfied with Vodafone O2 T- Mobile/Orange 3-Mobile H2: The Disconfirmation models impact the over-all CS positively in UKs MTNs. H2a: Expectancy disconfirmation impacts the over-all CS positively. H2b: Desire disconfirmation impacts the over-all CS positively. 3.5.3 Disconfirmation Models: As justified in the literature review we use both desire as well as expectation disconfirmation models to measure satisfaction. The table 3.5.3 shows the indicators for these variables. Table 3.5.3: Variables for Disconfirmation models DD ED Desire Disconfirmation To 8what extent did the services you received from them match your desired set of services? Expectation Disconfirmation How well does the service fulfil your expectations? Both these variables are measured using a 5-point likert scale. For DD, the scales vary 11from Much worse than desired to Much better than desired. Similarly, for ED the scales variedfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 27/45
  • 28. 3/8/13 TurnitinUK Originality Report 11from Much worse than expected to Much better than expected. It refers to the customers over-all judgement on the service quality delivered by their service provider. Here, we use only one indicator as shown in table 3.5.4 below, using a single question, to which the respondents rate their over-all satisfaction with service quality on the 5 3-point likert scale which vary from very dissatisfied to very satisfied. Table 3.5.4: Variable for over-all Satisfaction Measure OCS Over-all Customer Satisfaction Overall, please rate how satisfied or dissatisfied you are with the services being provided by your network. 3.5.5 Procedures to test Hypotheses: hypotheses. The following describe how the research objectives are met and tested with the Research Objective One (RO 1) To find out the level of customers 4satisfaction with the service quality offered to them by the UKs MTNs with and without respect to which network customers subscribe to. The procedure outlined for MnCSI model (as described in section 3.5.1) is used. 3.5.5a Testing Hypotheses 1a to 1d (as mentioned in 3.5.2) under RO 201 One-Sample T test is used to test hypothesis H1a to H1d with and without respect to the subscribed cellular network. Cut-off points 3 and 4 are chosen for disconfirmation measure and Over-all customer satisfaction measure respectively with 40significance level of 0.05. The null hypothesis assumes that customers are satisfied for both with respect to and irrespective of cellular network. We take 3 as the cut-off value for DD and ED because in disconfirmation scales, any rating between 3 and 5 indicates that the customer is satisfied. However, 1 and 2 indicates the customers dissatisfaction. Cut-off point 4 is chosen for OCS measure, because in over-all satisfaction scale, ratings from 1 to 3 indicates the customers dissatisfaction and ratings 4 and 5 indicate that the customer is satisfied with the service delivery. Procedure to test first hypothesis: Step1: The Null hypothesis: H0: x ≥ 3 (Equal to / Better than desired or expected) H1: x < 3 (Worse than / Much worse than desired or expected) H0: x ≥ 4 (Satisfied / Very Satisfied) H1: x < 4 (Neither dissatisfied nor satisfied, dissatisfied / very dissatisfied) Step2: One- Sample T test is conducted at significance level 0.05 Step3: The t-statistics, confidence intervals and p- value (Critical value) is extracted from SPSS output. Step4: The null hypothesis is rejected under the following 2 conditions. Firstly, in case the mean difference is significantly negative and secondly, if the confidence interval is showing negative. It is not rejected if the mean difference is significantly positive or any value under confidence interval includes a positive value. 3.5.5b Testing Hypothesis two and sub hypotheses (as mentioned in 3.5.2) Here a linear regression is used as each sub hypothesis involves one independent and one dependent variable. The three models that have to be tested are as follows: M1: Over-all CS = n + ED + DD + x M2: Over-all CS = n + DD + x M3: Over-all CS = n + ED + x Where n is a constant and x is the error-term and here 38the null hypothesis states that there is no significant relationship between both the disconfirmation models (DD andfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 28/45
  • 29. 3/8/13 TurnitinUK Originality Report ED) together and OCS. The procedure to test these three models is mentioned below: Step1: The Null hypothesis: H0: DD ≤ 0 Variable DD is not significantly greater than 0 H1: DD > 0 Variable DD is significantly greater than 0 H0: ED ≤ 0 Variable ED is not significantly greater than 0 H1: ED > 0 Variable ED is significantly greater than 0 Step2: Linear regression F test is conducted at significance level 0.05 Step3: p-value (critical value) is extracted from the SPSS output Step4: The null hypothesis is rejected under following two conditions: If the 6p-value is less than the significance value 0.05 and if the co-efficient is positive. 3.5.5c Research Objective Two (RO 2) 33To find out which dimensions of service quality are the customers satisfied/dissatisfied with in the UKs MTNs? As discussed earlier in Research Method (in section 3.4), customer satisfaction is measured for four service quality dimensions: functional, technical, image and VFM dimensions. Items under each dimension are defined in Appendix-H. One 34-Sample T test is used to verify the significance of the mean differences with significance level of 0.05 and test-value 3 in order to split the entire sample into satisfied and dissatisfied customers 81for each of the items in each dimension of service quality. The following procedure is being used: Step1: The Null hypothesis: H0: x ≥ 3 (Equal / better than expected) H1: x < 3 (Worse than / Much worse than expected) Step2: One-Sample T test is conducted at significance level 0.05 Step3: Confidence intervals and p-value (Critical value) is extracted from SPSS output. Step4: The null hypothesis is rejected under the following two conditions: If the mean difference is significantly negative and if the confidence interval is showing negative. It should not be rejected if the related mean difference is significantly positive or any value under confidence interval includes a positive value. 3.5.5d Research Objective Three (RO 3) What Service Quality dimensions do the customers perceive to be of high importance in the UKs MTNs? One-Sample T test is conducted at significance level 0.05 with a cut-off value 3 to split the service quality dimensions that are considered important by the customers from those that are unimportant. Then each service quality dimension is ranked in an order of magnitude to point out the importance of each dimension from the customers point of view. 3.6 Sample Selection and Data Collection: According to Neuman (2006), the sample size for focus group interview must range from 6 to 12 people. Hence, initially a sample size of 12 respondents are selected to conduct a focus group interview, the selection was based on purposive sampling method because the respondents had to pass the eligibility criteria before they could participate (Neuman, 2006). All the respondents were students doing their masters and they all were mobile telecom users, who had wide subject knowledge regarding the quality concerns in mobile telecom networks in the UK. The data was also collected via structured questionnaire which targeted only the mobile telecom users. In this survey-process, emphasis was given to include people of all groups within the UK (age groups, sex, etc), but more attention was given to the younger generation and student sector, as they are considered to be 25one of the most active cell phonefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 29/45
  • 30. 3/8/13 TurnitinUK Originality Report users (Clickz, 2005). From the sample frame of 78 million cellular service subscribers in the UK (Telecoms Market Research, 2008), a sample size of 100 respondents are selected due to the time and cost constraints. The time limit provided to complete this research was very less and using a larger sample size may require huge financial resources, which was unaffordable. Two different types of survey instruments are used here for the collection of data. Firstly, out of the total sample size of 100 respondents, 33 respondents responded via simple random sampling method. This method was chosen because the population comprises of mobile service providers in the UK, each constituting a stratum. All these respondents were students of UEL using UK cellular service. The survey was hosted on survey monkey website and the link <http://www.surveymonkey.com/s/SGVRP5X> was sent to all the students of UEL via universitys webmail and the link was also posted on several social networking sites such as Facebook, Twitter and Orkut. Secondly, the remaining 67 respondents were selected randomly using the personal contact approach from different areas of London (Stratford, Bow Road, East Ham and Barking). In this method, the respondents from the different areas are approached in person and they are explained in detail about this survey. Out of the total 100 questionnaires collected through various survey instruments, 17 1are partially filled and hence it is being rejected for data analysis. Overall there are 83 questionnaires that are usable for further analysis. 3.7 Reliability: 97Reliability refers to the consistency of measurements. A test is considered reliable, if the test yields similar results repeatedly for similar set of inputs. In this study we use the 14Cronbachs Alpha test is used to assess the internal consistency of the chosen likert scale and measure reliability of different service quality dimensions. It is calculated using the formula mentioned below Where K is the 21number of items or components in the questionnaire and (Pallant, 2005). is the mean of With the help of reliability co-efficient Cronbachs alpha we are checking the internal consistency of each scale. Table 3.7: Results of Chronbachs α test Service Quality Chronbachs α value No. of items/components Dimensions Tangibles 0.972 3 Reliability 0.963 3 Responsiveness 0.967 3 Empathy 0.975 3 Assurance 0.964 3 Technical-Quality 0.966 3 Corporate Image 0.981 3 VFM(Value for Money) 0.930 2 Importance of dimensions 0.973 8 Table 3.7 indicates that all the items under each dimension are 1above the minimum scale of 0.7. Hence these values 1indicate that all of these dimensions are reliable and internally consistent. 3file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 30/45
  • 31. 3/8/13 TurnitinUK Originality Report 106.8 Validity: Validity is concerned with accuracy of the measurements. It 9is one of the most important factors for an experimental research. In other words, it is about testing the data analysis procedure, if it is measuring in a right way and in an accurate manner. Validity is of two types: Internal and external validity (Saunders et al., 2007). To ensure validity in this research, there were many steps taken: All the relevant theoretical frameworks, models and literature were examined in an exhaustive manner i.e. viewed from different authors/researchers perspective. Most of the questions are based on the theoretical frame works and literature, except the service quality dimension- VFM (Value for Money) derived from the focus group interview. Still to ensure criterion validity, the structured questionnaire was compared with other validated SERVQUAL models, which are similar to the one created. Pilot testing: According to 47Saunders et al (2000) and Malhotra et al., (2007) the structured questionnaire must be pre-tested before final administration. Hence the preliminary draft of the questionnaire was pre-tested by the members of focus group interview to check the clearness and significance of the questions and it was also checked thoroughly by 3 employees and 2 managers who work for different mobile telecom networks in the UK. Most of the parameters and wordings were changed based on their advice, so that respondents can understand the questions clearly. Then it was pre-tested to a sample size of ten telecom users who were selected through simple random method. This sample size was suggested by Fink (2003b in 48Saunders et al 2007), who had mentioned that it is adequate to have a minimum of ten members for the pre-testing. Before giving the questionnaire, each of these members were described about the purpose of the questionnaire and ensured confidentiality and anonymity. It was also ensured that the questionnaire was filled by the mobile telecom users of UK only, in both via e-survey as well as personal contact approach. 324. DATA ANALYSIS AND DISCUSSION 4.1 Introduction: This chapter focuses on statistical analysis of quantitative data which was collected during the process of surveying. It comprises of data presentation that covers demographic profile of respondents, 32measurement of customer satisfaction, customer satisfaction with different service quality dimensions and relative importance of those dimensions. The discussion includes analysis of different hypotheses and their relative results and findings 11in order to answer the research questions. 4. 2 Demographic profile: Thisfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 31/45
  • 32. 3/8/13 TurnitinUK Originality Report 67shows the demographic grouping of all the respondents who participated in the surveying process. It indicates that among the total of 83 respondents more than half are males i.e. 67.5% are male respondents and the remaining 32.5% are the female respondents and as mentioned previously in the research methodology, majority of the respondents are youngsters, between 21 – 30, as they are the economically active-group constituting 77.1%, whilst the rest constituting 22.9% includes respondents of age group below 20, 31 – 50 and above 51. 4.3 Assessing Customer Satisfaction with the Service Quality: To assess customer satisfaction with service quality four different measures are used namely: MnCSI model, Desire and Expectation Disconfirmation models and Over-all Satisfaction. All these models are supported by theory 96in the literature review and also mentioned in the 60sections 3.5.1, 3.5. 3 and 3.5.4 of research methodology. Here the customer satisfaction is assessed with respect to cellular network and irrespective of cellular network. 4.3.1 Results of Minnesota Customer Satisfaction Index The result for MnCSI model was arrived from the formula and steps that was mentioned earlier in section 3.5.1. The raw data for this model was obtained from the structured questionnaire, which is based on 83 responses. Table 4.3.1: Customer satisfaction index using MnCSI Cellular Network MnCSI value Description Irrespective of cellular 52.2 Fair network Vodafone 46.3 Low O2 54.8 Fair T-Mobile / Orange 51.5 Fair 3-Mobile 51.3 Fair The table 4.3.1 indicates the satisfaction index for all the four mobile service providers (Vodafone, O2, 19T-Mobile / Orange and 3-mobile) and also index for the total sample population without respect to which network the subscriber has subscribed to. Firstly, for all the mobile networks together the MnCSI value is 52.2, which is represented as Fair as it is above the satisfactory index of 50. This result shows that in general the customer satisfaction in the UKs cellular telecom market is substantially fair. Secondly, The MnCSI value for Vodafone, O2, 19T-Mobile / Orange and 3-Mobile were 46.3, 54.8, 51.5 and 51.3 respectively. This implies that Vodafone has got considerably low customer satisfaction with service quality, but it is fair for O2, T-Mobile / Orange and 3- Mobile. The customer satisfaction index gives the perception of a customer over the mobile service providers. The satisfaction score reflects the past experiences of the customer with the providers, both positive and negative and the result draws on the average of their experiences. Hence, we could say that except Vodafone customers, the individual experiences of customers of all other networks have been fair with their respective service providers. 4.3.2 Results of Disconfirmation Models and Over-all Customer Satisfaction Measure: 4.3.2.1 Irrespective of cellular network: Table 4.3.2.1a: Descriptive-statistics of DD, ED and OCS 66One-Sample Statistics N Mean Std. Deviation Std. Mean Desire 83 2.98 1.126 .124 expectation 83 2.96 1.234 .135 Errorfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 32/45
  • 33. 3/8/13 TurnitinUK Originality Report 78N Mean Std. Deviation Std. Mean OCS 83 3. 33 1. 138 .125 Error The details of this descriptive statistics is available in Appendix-E and the table 4.3.2.1a indicates the ratings by the 83 respondents for all the three measures i.e., for DD measure the customers mean rating was 2.98 with standard deviation (SD) of 1.126, for ED measure the customers mean rating was2.96 with SD of 1.234 and for OCS measure, the customers mean rating was 3.33 with SD of 1.138, being the highest. The mean rating for ED and DD measures are very close to the cut-off value 3 and for OCS measure, it was below the cut-off value 4 and has a wider deviation than the other two attributes (ED & DD). Fig 4.3.2.1b: Customer satisfaction rating irrespective of cellular network Table 4.3.2.1c: Customer satisfaction rating irrespective of cellular network 1 2 3 4 5 DD 12 18.1 39.8 20.5 9.6 ED 15.7 19.3 28.9 25.3 10.8 OCS 7.2 18.1 22.9 38.5 13.3 In the fig 4.3.2.1b the x-axis indicates the measurement models: Desire Disconfirmation(DD), Expectation Disconfirmation(ED) and Over-all Customer Satisfaction(OCS) and the y-axis indicates Percentage(%) of customer satisfaction rating, the details of these frequencies is given in Appendix-C and the table 4.3.2.1c indicates that applying DD measure we could assess that 12% and 18.1% (a total of 30.1%) rated their satisfaction level as much worse than desired and worse than desired respectively. 39.8% of the respondents rated that the service delivery is equal to what they desire and 30.1% (20.5 + 9.6) rated that the services were better than or much better than what they desired. Applying ED measure we could assess that 15.7% and 19.3% (a total of 35%) rated their satisfaction level as 11much worse than expected and worse than expected respectively. 28.9% of the respondents rated that the service delivery is equal to what they expected and 36.1% (25.3 + 10.8) rated that the services were better than or much better than what they expected. The first hypothesis and its sub hypotheses are tested as per the procedure shown in section 3.5.5a in order to verify if the mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.1d below and the descriptive statistics is available in Appendix-E. Table 4.3.2.1d: 39One-Sample T test for ED & DD irrespective of cellular network 6One-Sample Test Test Value = 3 95% Confidence Interval of the Difference Mean t df Sig. (2-tailed) Difference Lower Upper Desire -.195 82 .846 -.024 -.27 .22 expectation -.267 82 .790 -.036 -.31 .23 The table 4.3.2.1d indicates that, with the cut off point 3 the mean differences are -0.24 and -0.36 for DD and ED respectively and the observed significance level (p-value) being 0.846 and 0.790 for DD and ED respectively, which are morefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 33/45
  • 34. 3/8/13 TurnitinUK Originality Report 40than the significance level of 0.05 and the upper limit of their confidence intervals provides a strong support towards not rejecting the null hypothesis. Therefore with 95% confidence it can be concluded that the provided services are at least equal to their desire and expectation. Applying OCS measure we could assess that 7.2% and 18.1% (a total of 25.3%) rated their satisfaction level as very dissatisfied and dissatisfied respectively. 22.9% of the respondents rated 62that they were neither satisfied nor dissatisfied with the service delivery and 51.8% (38.5 + 13.3) rated that 99they were satisfied / very satisfied with the services. The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if the mean value is significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.1e below. Table 4. 3.2.1e: 39One-Sample T test for OCS irrespective of cellular network 22One-Sample Test Test Value = 4 Mean T df Sig. (2-tailed) Difference 95% Confidence Interval of the Difference Lower Upper OCS -5. 401 82 .000 -.675 -.92 -.43 The table 4.3.2.1e indicates that, with the cut off point 4, the mean difference for OCS measure is -.675 and the observed significance level (p-value) being .000, which means that the mean is significantly lesser than 4. This provides a strong support towards rejecting the null hypothesis. Therefore with 95% confidence 3it can be concluded that customers are not over-all satisfied with the service delivery from their service providers irrespective of cellular networks in the UK however, they are at equal to their desire and expectation. The CS in general with the UKs cellular network is deemed to be fair as obtained from the MnCSI value which is 52.2, slightly greater than the satisfaction index of 50. It is at least equal to the customers desire and expectation. However, the overallfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 34/45
  • 35. 3/8/13 TurnitinUK Originality Report 3satisfaction of the customers with the service quality of the operators is significantly low. 4.3.2.2 With respect to cellular networks: The details of frequencies with respect to cellular network is available in Appendix-D 4.3.2.2a Testing significance of the OCS measures for all cellular networks: The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if those mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.2b below and the descriptive statistics is presented in Appendix-E. Table 4.3.2.2b: One-Sample T test to measure OCS with respect to cellular networks Company Vodafon e 20One-Sample Test Test Value = 4 t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Lower Upper OCS -1. 941 8 .038 -.778 -1.70 -.15 O2 OCS -2.832 21 .010 -.682 -1.18 -.18 T- Mobile/ Orange OCS -3.291 32 .002 -.667 -1.08 -.25 3-Mobile OCS -2.364 18 .030 -.632 -1.19 -.07 The Table 4.3.2.2b above shows that, having a cut off value 4, the mean differences for over-all customer satisfaction 1are -0. 778, -0. 682, -0. 667 and -0. 632 and their p-values 1are 0. 038, 0. 010, 0. 002 and 0. 030 for Vodafone, O2, 19T-Mobile / Orange and 3-Mobile respectively. Their respective p-values show that all of their mean satisfaction is significantly lesser than the cut off value 4 79(as the p-value is less than 0.05 in all cases) and even all of their confidence intervals are negative, providing a strong support to reject the null hypothesis. Therefore, we can conclude with 95% confidence that, the customers of all the four service providersfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 35/45
  • 36. 3/8/13 TurnitinUK Originality Report 42are not satisfied with the service quality provided by each of these companies and moreover, the over-all satisfaction of the customers is very much worse with service quality of Vodafone than the other cellular networks because it holds the highest negative mean difference. Vodafone: Table 4.3.2.2c: Mean satisfaction rating for Vodafone DD ED OCS 2.22 3.11 3.22 Fig 4.3.2.2d: Satisfaction rating for Vodafone The table 934.3.2.2c and the fig 4.3.2.2d indicate the mean ratings of the customers of Vodafone for all the three models used. The mean rating for desire disconfirmation and expectation disconfirmation are 2.22 and 3.11 respectively and the mean for over-all satisfaction is 3.22. The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if those mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.2e below and the descriptive statistics is presented in Appendix-E. Table 4.3.2.2e: One-Sample T test to measure DD & ED for Vodafone Company 35Test Value = 3 95% Confidence Interval of the Difference t df Sig. (2-tailed) Mean Difference Lower Upper Vodafone DD -2. 800 8 .023 -.778 -1.42 -.14 ED .286 8 .782 .111 -.79 1.01 The Table 4.3.2.2e above indicates that the mean differences using DD and ED for Vodafone are -.778 and .111 respectively. The p value for DD measure 29is 0. 023 (less than 0.05) which implies that the mean is significantly lesser than the cut off value 3 which provides a strong support towards rejecting the null hypothesis. The p value or significance for ED is 0.782 and as the mean is more than the test-value 3, the null hypothesis is being considered positive in this case. Hence, we can conclude with 95% confidence that, the customer satisfaction for Vodafone is at least equal to their expectation and worse than the customers desire. With the evidence obtained from section 4.3.2.2a, the over-all satisfaction of the customers is much worse than all other service providers and even the satisfaction index in Table 4.3.1, indicated that the CS is considerably low (with MnCSI value of 46.3) only for Vodafone, whereas all other networks had their satisfaction index above 50, which indicates that CS is fair for all other service providers. There are many inconsistencies faced by its customers in terms of software updates, process delays, bad handoffs, etc. For instance, Vodafone has still not attempted to take any measures to improve their service delivery standards, as recently the company has angered many of its customers because they failed to test the software updates before pushing it to the customers (Wattanajantra, 2010) Hence,file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 36/45
  • 37. 3/8/13 TurnitinUK Originality Report Vodafone has to take some serious measures in order to build their service delivery standards and customer satisfaction level. O2: Table 4.3.2.2f: Mean satisfaction rating for O2 DD ED OCS 3.09 3.18 3.32 Fig 4.3.2.2g: Satisfaction rating for O2 The table 4.3.2.2f and the fig 4.3.2.2g indicate the mean ratings of the customers of O2 for all the three models used. The mean rating for desire disconfirmation and expectation disconfirmation are 3.09 and 3.18 respectively and the mean for over-all satisfaction is 3.32. The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if those mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.2h below and the descriptive statistics is presented in Appendix-E. Table 4.3.2.2h: One-Sample T test to measure DD & ED for O2 Test Value = 3 Company 695% Confidence Interval of the Difference t df Sig. (2-tailed) Mean Difference Lower Upper O2 DD ED .370 .678 21 21 .715 .505 .091 .182 -.42 -.38 .60 .74 The p-values are 0.715 and 0.505 for DD and ED respectively, which are more than 0.05 (significance level) which implies that the mean is significantly more than the cut off value 3. The mean differences using DD and ED measures are 0.091 and 0.182 respectively. Hence the null hypothesis is being considered positive in both the cases. Hence, we can conclude with 95% confidence that, the customer satisfaction for O2 is at least equal to the customers expectation and desire. Even the satisfaction index in Table 4.3.1, indicated that the CS is fair for O2. However, the evidence obtained from section 4.3.2.2a states that still the 4customers are not satisfied with the overall service quality provided by their network. T – Mobile / Orange: Table 4.3.2.2i: Mean satisfaction rating for T – Mobile / Orange DD ED OCS 2.94 2.91 3.33 Fig 4.3.2.2j: Satisfaction rating for T – Mobile / Orange The table 4.3.2.2i and the fig 4.3.2.2j indicate the mean ratings of the customers of T- Mobile / Orange for all the three models used. The mean rating for desire disconfirmation and expectation disconfirmation are 2.94 and 2.91 respectively and the mean for over-all satisfaction is 3.33. The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if those mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.2k below and the descriptive statistics is presented in Appendix-E. Table 4.3.2.2k: One-Sample T test to measure DD & ED for T-Mobile/Orange Company Test Value = 3file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 37/45
  • 38. 3/8/13 TurnitinUK Originality Report 16t df Sig. (2-tailed) 95% Confidence Interval of the Difference Mean Difference Lower Upper T- DD -.297 32 .768 -.061 -.48 .35 Mobile/ Orange ED -.415 32 .681 -.091 -.54 .36 The mean differences for DD and ED are -0.061 and -0.091 respectively but however the p- values are 0.768 and 0.681 which are more than 0.05 (significance level). Here though the mean differences are not significant, the corresponding upper limits of the confidence intervals are positive (0.35 and 0.36), providing a strong support to consider the null hypothesis. Hence, we can conclude with 95% confidence that, the customer satisfaction for T-Mobile / Orange is at least equal to the customers expectation and desire. Even the satisfaction index in Table 4.3.1, indicated that the CS is fair for T-Mobile/Orange. However, the evidence obtained from section 4.3.2.2a states that still the 4customers are not satisfied with the overall service quality provided by their network. 3 – Mobile: Table 4.3.2.2l: Mean satisfaction rating for 3-Mobile DD ED OCS Fig 4.3.2.2m: Satisfaction rating for 3-Mobile The table 4.3.2.2l and the fig 4.3.2.2m indicate the mean ratings of the customers of 3- Mobile for all the three models used. The mean rating for desire disconfirmation and expectation disconfirmation are 3.05 and 2.74 respectively and the mean for over-all satisfaction is 3.37. The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify if those mean values are significant or not, 2one-sample t test is conducted to test their significance level. The result obtained from the 2test is presented in the table 4.3. 2.2m below and the descriptive statistics is presented in Appendix-E. Table 4.3.2.2m: One-Sample T test to measure DD & ED for 3-Mobile Company Test Value = 3 44t df Sig. (2-tailed) 95% Confidence Interval of the Difference Mean Difference Lower Upper 3- Mobile DD .213 18 .834 .053 -.47 .57 ED -.925 18 .367 -.263 -.86 .33 For 3-Mobile, the mean differences for DD and ED are 0.053 and -0.263 with p-values 0.834 and 0.367 respectively. For DD measure, the mean is significantly more than the cut off value 3, providing a strong support to consider the null hypothesis. In the case of ED measure the mean difference of -0.263 is not significant but however, the corresponding upper limit of the confidence intervals is positive (0.33), providing a strong support to not 38to reject the null hypothesis i.e., satisfaction level is at least equal to expectation. Hence, we can conclude with 95% confidence that, the customer satisfaction for 3-Mobile is at least equal to the customers desire and expectations. Even the satisfaction index in Table 4.3.1, indicated that the CS is fair for 3-Mobile. However, the evidence obtained from section 4.3.2.2a states that still thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 38/45
  • 39. 3/8/13 TurnitinUK Originality Report 4customers are not satisfied with the overall service quality provided by their network. Though the services provided by 25O2, T-Mobile/Orange and 3- Mobile is at least equal to customers desire and expectation, the Over-all Customer Satisfaction with service delivery is considerably low. This could be very low because of the following reasons: i) The customers are very diversified with varied requirements on the Value Added Services (Mobile Internet – 3G, e-mail services, News Updates, etc) and the Tariff plans (Free Local Minutes/Texts Limits, Data Limits) etc, virtually having to customize the plans to suit their particular needs. The people interviewed in the focus group emphasized that they do not get the plan customized, for eg. One respondent said I need more call minutes and dont need texts, but there is no plan where I can reduce the text limit and increase the call limit for the same amount I pay and the other said I dont need minutes and all I need is Data, but I have a plan where I pay unnecessarily for minutes which I dont use. The service providers dont usually let the customers decide on what and exactly how much they want of these services, letting down their satisfaction at the very stage of purchase. ii) There exists a severe inconsistency between physical hardware capability and the service capability. The technology is rapidly growing to enable supreme features in the handsets but the service providers are unable to cope up with that growth. For eg. The latest handsets are capable of transferring data at 7.2 Mbps while the real time 3G speed is much lesser than 1 Mbps. The revolutionary 4G featured handsets Evo and i phone 4G has no better use in the market where no provider has a 4G service. The second hypothesis and its sub hypotheses are tested as per the procedure shown in section 3.5.5b 24in order to find the relationship between disconfirmation models and Overall satisfaction measure. The detailed results of this regression analysis are presented in Appendix-G. Table 4.3.2.2n: Result of regression analysis for Disconfirmation models Models Unstandardized Co-efficients Beta R R² Std Error of the Estimate Sig. F-Test M1 (constant) DD ED .652 .377 .563 .928 .861 .429 .000 .000 M2 (constant) DD .587 .910 .910 .829 .474 .000 M3 (constant) ED .810 .920 .920 .847 .448 .000 The Table 4.3.2.2n, points out that in the first model, DD & ED together affect customer satisfaction positively, as the coefficients are greater than zero i.e. .377 and .563 for DD and ED respectively and 24it is significant as the P-value is also less than 60.05, hence the null hypothesis is being rejected. In the second model, the co-efficient is greater than zero (.910) and it is significant as the P-value is .000. In the third model again the co-efficient is greater than zero (.920) and it is also significant, as the P-value is .000. Hence we can conclude that all the three models significantly and positively affect the over-all customer satisfaction. Firstly, in model 1, the R (0.928) indicates that there exists a strong relationship between desire disconfirmation, expectation disconfirmation and over-all satisfaction. The R² (strength of the relationship): 0.861 shows that variations of about 86% in over-all customer satisfaction are caused/explained by DD & ED collectively. Hence we can conclude with 95% confidence that desire disconfirmation model andfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 39/45
  • 40. 3/8/13 TurnitinUK Originality Report expectation disconfirmation model together impacts OCS significantly. The results of disconfirmation models for all the network operators were at least equal to the customers desire and expectation except Vodafone, as their service quality was worse than what they desired though it is at least equal to their expectation. Hence, if the satisfaction level for disconfirmation models had been better than or much better than desired or expected, then definitely the customers overall satisfaction with the service delivery would have resulted positive. Secondly, in models 2 & 3 (Table 4.3.2.2n) both the P-values are .000 (less than 0.05) and R values are .910 and .920 for DD & ED respectively, which shows that both these models impact OCS. The outputs for R² (strength of the relationship) are .829 and .847 for DD & ED respectively, which shows that variations of about 83% and 85% in over-all customer satisfaction are caused by DD and ED respectively. Hence, it is validated that ED impacts OCS stronger than DD in the UKs cellular networks. So priority must be given to customers expectations than their desires. Therefore, all the service providers must aim at determining what exactly the customers expect from them in order to keep their customers overall satisfied with their service delivery and eventually gain customer loyalty. 4.4 Customer satisfaction with each service quality dimension A detailed descriptive statistics is found in Appendix-F which has got customer satisfaction ratings for all the four service quality dimensions. One 34-Sample T test is used to verify the significance of the mean differences. In this case, null hypothesis (H0) 55states that the customer satisfaction level is least equal to his/her expectation and the alternative hypothesis (H1) 55states that the customer satisfaction level is worse or much worse than their expectation. The results of this test are presented in Table 4.4a and it is tested as per the procedure presented in section 3.5.5c. Table 4.4a: 39One-Sample T test for all the SERVQUAL dimensions 16One-Sample Test Test Value = 3 t df Sig. (2-tailed) 95% Confidence Interval of the Difference Mean Difference Lower Upper TN1 3.933 82 .000 .422 .21 .63 TN2 2.356 82 .021 .265 .04 .49 TN3 1.694 82 .094 .205 -.04 .45 RE1 5.524 82 .000 .530 .34 .72 RE2 -3.484 82 .001 -.410 -.64 -.18 RE3 -2.373 82 .020 -.289 -.53 -.05 RP1 1.504 82 .137 .169 -.05 .39 RP2 -.094 82 .926 -.012 -.27 .24 RP3 -5.477 82 .000 -.614 -.84 -.39 EP1 .366 82 .715 .048 -.21 .31 EP2 2.556 82 .012 .325 .07 .58 EP3 1.228 82 .223 .145 -.09 .38 AR1 3.942 82 .000 .434 .21 .65 AR2 -1.341 82 .184 -.169 -.42 .08 AR3 -.107 82 .915 -.012 -.24 .21 TQ1 -3.866 82 .000 -.446 -.68 -.22 TQ2 1.341 82 .184 .169 -.08 .42 TQ3 3.203 82 .002 .325 .12 .53 CI1 1.341 82 .184 .169 -.08 .42 CI2 1.706 82 .092 .193 -.03 .42 CI3 1.454 82 .150 .169 -.06 .40 VM1 -3.385 82 .001 -.398 -.63 -.16 VM2 1.382 82 .171 .205 -.09 .50 The items in the table 4.4a are indicators of different service quality dimensions used in this research and the details of what each indicator stands for is available in Appendix- H. In the table 4.4a, three different colour codes are given for each item under the service quality dimensions. Green represents those items in which the customer satisfaction level is better than or muchfile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 40/45
  • 41. 3/8/13 TurnitinUK Originality Report better than their expectation. Yellow represents those items in which the customer satisfaction level is at- least equal to their expectation and Red represents those items in which the customer satisfaction level is worse than or much worse than their expectation. The Table 4.4a shows that both the mean difference and confidence intervals (both lower and upper) are negative for six items, they are: RE2, RE3, RP3, TQ1 and VM1. For these items the customer satisfaction level is worse or much worse than their expectation. According to Borzorgi M. M. (2007), the customers mainly look for technical quality and reliability than the others in the public sector industry. However, the results show that two items of reliability and one item of Technical quality have been rated very poor by the customers. Hence, the network providers must focus on developing their technical quality in terms of network coverage and reliability by resolving the customers issues on time. There are twelve items in which either the mean difference or any one of their confidence intervals include a positive value, which means that customer satisfaction level is at-least equal to their expectation, they are: TN3, RP1, RP2, EP1, EP3, AR2, AR3, TQ2, CI1, CI2, CI3 and VM2. The remaining six items includes TN1, TN2, RE1, EP2, AR1 and TQ3 in which both the mean difference as well as confidence intervals are positive, which states that the customer satisfaction level is better than or much better than their expectation. As presented in the fig 4.4b below, precisely six of the items under different service quality dimension had their means significantly equal to the test-value 3. Twelve items were rated equal to expectation and eight items were rated below the test-value 3. Over-all eighteen items have been given a satisfaction rating as at-least equal to or better than their expectation Fig 4.4b: Satisfaction level with the SERVQUAL dimensions Therefore, we can conclude with 95% confidence that, the customers are dissatisfied with the 5 items of service quality dimension (RE2, RE3, RP3, TQ1 and VM1) and at-least satisfied with 18 items of service quality (TN1, TN2, TN3, RE1, RP1, RP2, EP1, EP2, EP3, AR1, AR2, AR3, TQ2, TQ3, CI1, CI2, CI3 and VM2). Though these items meet the customers expectation in order to create a tremendous (Wow!) experience, the organisations have to develop strategies to go an extra mile and diversely satisfy 51its customers. In order to find the importance of each of these dimensions as perceived by the customers, they were also 51asked to rate the importance of each service quality dimension from their perspective (or point of view) 3on a five point likert scale. The values ranged from Least Important, Not so important, Important, Very Important and Most Important. A descriptive statistics of all the dimensions and its corresponding substituted values is given in the table 4.4c below. Table 4.4c: Descriptive Statistics for importance of service quality dimensions Descriptive 65Statistics Std. Std. Error N Mean Deviation Mean TECHNICAL 83 3. 93 .712 .078 QUALITY CORPORATE 83 3.04 1.163 .128 IMAGE VFM 83 4.48 .755 .083 TANGIBLES 83 2.76 1.100 .121 RELIABILITY 83 3.93 1.124 .123 RESPONSIVENESS 83 3.98 .715 .079 EMPATHY 83 2.98 .975 .107 ASSURANCE 83 3.40 .855 .094 In the table 4.4c, six dimensions have mean above 3 and the remaining two have the mean below 3. 22One-Sample T test is used in order to key out thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 41/45
  • 42. 3/8/13 TurnitinUK Originality Report important and unimportant dimensions with 0.05 as its significance level and 3 as its test-value. The results of this test 59are shown in the table 4.4d below. Table 4. 4d: One -Sample T test for importance of service quality dimensions 30One-Sample Test Test Value = 3 95% Confidence Interval of the Difference t df Sig. (2- tailed) Mean Difference Lower Upper TECHNICAL QUALITY CORPORATE IMAGE 11.871 82 .000 .928 .77 1.08 .283 82 .778 .036 -.22 .29 VFM 17.886 82 .000 1.482 1.32 1.65 TANGIBLES -1.996 82 .049 -.241 -.48 .00 RELIABILITY 7.521 82 .000 .928 .68 1.17 RESPONSIVENES S 12.430 82 .000 .976 .82 1.13 EMPATHY -.225 82 .822 -.024 -.24 .19 ASSURANCE 4.239 82 .000 .398 .21 .58 The table 4.4d shows 3that all the dimensions are significantly important to the customers. However, when it comes to the degree of importance for each service quality dimension, Tangibles, Empathy and Corporate Image are significantly less important to the respondents than the others because: either the mean difference or any one of their confidence intervals include a positive value and the other 80five dimensions of service quality (Technical Quality, VFM, Reliability, Responsiveness and Assurance) have been rated with high degree of importance as it has got positive mean difference as well as positive confidence intervals. The rankings as to which dimensions 10are perceived to be more important than the others is shown in Table 4.4e. These rankings are given to the service quality dimensions with respect to their mean difference values i.e., the dimension with the highest mean difference would be ranked one and correspondingly, the dimension with the lowest mean difference would be ranked last. Table 4.4e: Prioritized Service quality dimensions Service Quality Dimensions Rankings (Ascending Order) VFM (Value for Money) 1 Responsiveness 2 Technical Quality 3 Reliability 4 Assurance 5 Corporate Image 6 Empathy 7 Tangibles 8 Table 4.4e indicate that VFM (Value for Money) 41is considered to be one of the most important service quality dimensions, which is then followed by Responsiveness, Technical Quality, Reliability, Assurance, Corporate Image, Empathy and Tangibles. The satisfaction matrix displayed in Table 4.4f below is designed after a careful analysis of satisfied and dissatisfied dimension items 77of service quality in relation to the prioritized dimensions in order to analyzefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 42/45
  • 43. 3/8/13 TurnitinUK Originality Report which of the items of service quality dimensions need more attention. Table 4.4f: Satisfaction Matrix Better / Much better than expected At-least equal to expectation Worse / Much worse than expected VFM VM2 VM1 Responsiveness RP1, RP2 RP3 Technical Quality TQ3 TQ2 TQ1 Reliability RE1 RE2, RE3 Assurance AR1 AR2, AR3 Corporate Image CI1, CI2, CI3 Empathy EP2 EP1, EP3 Tangibles TN1, TN2 TN3 The Table 4.4f indicates the following: Firstly, out of the six dimension items that has CS much better than or better than expected (derived from Table 4.4a), three items are of high degree of importance: TQ3, RE1 and AR1 while another three are considered to be of less importance: EP2, TN1 and TN2. Hence, the focus on these particular attributes could be shifted to those that are more significant but lacks attention. Secondly, out of the twelve dimension items that has CS at least equal to their expectations (derived from Table 4.4a), six items are considered very important: VM2, RP1, RP2, TQ2, AR2 and AR3; while the remaining six items are of less importance: CI1, CI2, CI3, EP1, EP3 and TN3. Hence the network providers need to maintain the same service delivery standards for these attributes and eventually increase it in order to achieve competitive advantage. Finally, under the dimension items that has CS worse than or much worse than expected (derived from Table 4.4a), all the items are considered very important VM1, RP3, TQ1, RE2 and RE3. Hence, the attributes of service quality those customers perceive to be of high importance and lacks attention from the service providers in the UK are mentioned in the table 4.4g below: Table 4.4g: The Service quality dimension items and their description which are considered to be of high importance and lacks attention by network providers VM1 How economical is the call charge per minute? RP3 TQ1 RE2 RE3 Ability of the employees to communicate clearly with the customers The network coverage Dependability and consistency to resolve customer issues (or complaints) Ability to perform the service request on time The description for each item is derived from the Appendix-H. This gives the operators a note on what to concentrate to improve their CS scores. The most important factor, Value for Money on how economical the charges are; is mainly collected in comparison with other service providers, but the complaint is that, the operators do not price the components equally, for e.g. if the call cost is low, the data charge is high, and if both are low the roaming charges soar. Even if these are considered to be business strategies, the hidden costs (fair usage guidelines, starred conditions apply, etc) fuel the customers dissatisfaction. The incremental usage of Virtual Networks (MVNOs) reasons the signal and clarity issues (Telecompaper, 2009). Hence, there has to be some limit set for these MVNOs. However, the responsiveness, dependability and consistency factors are with respect to the particular network and still no network operator has very satisfied customers on those factors. 5. Summary & Conclusion The main purpose of this dissertation was to 36measure the level of customer satisfaction with regards to service quality delivered by the UKs MTNs with and without respect to which network customer subscribes to; via four models: The MnCSI model, Disconfirmation models (Desire & Expectation) and Over-all Customer satisfaction model that was developed. This dissertation examined the customers satisfaction level with several service quality dimensions and also finds the dimensions that the customers perceive to be of very important. Data for analysis was derived from Eighty three (83) survey responses. The following summary of major findings & conclusions are based on the data analysis and the discussions made: ? Irrespective of cellular network in the UK, three models (MnCSI, DD and ED) indicated that Customer Satisfaction is fair and at-least equal or equal to the customers desire and expectation but one model (OCS) pointed out that customers are dissatisfied. So considering the results of all the four models, we can conclude that customers are neither satisfied nor dissatisfied with the 15service quality delivered by cellular networks in the UK. ? With respect to cellular networks, for thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 43/45
  • 44. 3/8/13 TurnitinUK Originality Report customers of Vodafone, their satisfaction level is worse than desired and at-least equal to expectation. For the customers of O2, their satisfaction level is at-least equal to desire and expectation. For the customers of T-Mobile/Orange, their satisfaction level is at-least equal to desire and expectation and for the customers of 3-Mobile, their satisfaction level is at-least equal to desire and expectation. ? The Over-all customer satisfaction has been rated as dissatisfied by the customers of all the four networks. The ratings obtained are approximately same for all the four companies. ? Regarding Customer-Satisfaction with various 107service quality dimensions, the customer s satisfaction level is better than expectation for the following six items of service quality dimensions: TN1, TN2, RE1, EP2, AR1 and TQ3. The customers satisfaction level is at-least equal to expectation for the following twelve items: TN3, RP1, RP2, EP1, EP3, AR2, AR3, TQ2, CI1, CI2, CI3 and VM2. The customers rated the following five items as dissatisfied: RE2, RE3, RP3, TQ1 and VM1. ? According to the customers priority, VFM is the most important dimension followed by Responsiveness, Technical Quality, Reliability, Assurance and Corporate Image, which scores the least importance. Tangibles and Empathy are unimportant to the customers. ? Most of the service quality dimension items which has been rated satisfied by the customer are less important to the them, while most of the service quality dimension items which has been rated dissatisfied are more important to them. ? Both the disconfirmation models (Desire and Expectation) collectively impact OCS. However, ED impacts OCS stronger than DD in the UKs cellular networks. ? A significance matrix was developed to gather data on the most important dimensions that the respondents perceive and lacks attention from the service providers in the UK. It is found that some items under the Value for Money, Responsiveness and Technical Quality are highly valued high by the customers but the network providers have failed to achieve them. Conclusion The cellular networks in the UK must acquire superior 13service quality measures in order to gain competitive advantage. Most of the 4customers are not satisfied with service quality delivered by the cellular networks in the UK, or that their satisfaction level is considerably low. The process of amending the 1service quality standards begins from identifying the customers needs and then taking required actions to satisfy them. However, all the network providers have problems in identifying their customers needs. In most cases, the service quality provided is at least equal to the customers desire and expectation. The mean score just meets the threshold and significant improvements have to be made on certain areas. 1As a result, it is highly essential for all the cellular network providers to understand how the customers estimate thefile:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 44/45
  • 45. 3/8/13 TurnitinUK Originality Report 1quality of services. This research has identified five key attributes of 10service quality which are considered to be of high importance by the customers and lacks attention by network providers, they are: pricing issues, communication problems, network coverage and lack of ability to resolve complaints and service requests on time. Hence, it is crucial for the network service providers to concentrate on these five areas to improve their service standards and eventually gain competitive advantage. Recommendations for Future Research This dissertation has primarily measured and analyzed the customer satisfaction level with service quality in the UKs cellular networks. Hence it is recommended that future research could: ? Analyze customer satisfaction in particular service areas such as Internet Services, Video calls, SMS, MMS and other value added services. ? Compare customer satisfaction level and Service quality with the current technology (3G network) and the upcoming technology (4G network). ? Analyze customer satisfaction with fixed line services for e.g. with BT (British Telecom) customers. ? Verify the models and theories used in this dissertation with different industry settings. Finally, this study comprises a mixture of both qualitative as well as quantitative models. Therefore, it is recommended that other models and approaches could be used for a similar study and the results could be compared. Weight 0 8.32 16.65 24.97 33.30 The descriptive statistics for all three dimensions is mentioned below: 3.05 2.74 3.37 3.5.4 Over-all Satisfaction:file:///C:/Users/Acid/Documents/BACK UP/Dissertation/TurnitinUK_Originality_Report_7309325.html 45/45

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