SMM 210
Assessing Quality and Customer Satisfaction with service delivery of mobile telecommunication networks in the UK.
Dissertation Student Number: 0847416 Student Name: Vimal Gopal MBA International Business
Deadline: Monday 16th August 2010
Market Research on Service Quality and Customer Satisfaction
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ABSTRACT
Purpose - There are a lot of service quality dimensions derived from the Service
Quali Quality ty mo model delss and frame framewor works. ks. Th Thee aim aim of this this disse disserta rtati tion on is to find find out the the significance of these dimensions as perceived by the customers and compare it with the level of service offered by the UK’s Mobile Service Providers.
Review/Methodology Review/Methodology – A review was conducted on the relevant models and the gaps
were found using the Qualitative (Focus Group Interview) and Quantitative research (Questionnaire) methods.
Findings – Five attributes of service quality are found to be deemed with high
importance by the customers and lacks attention from the Mobile Service Providers.
Limitations/Implications – As this research has been conducted using limited time
and resources, the Mobile Networks could conduct research specific to their market potential and offered offe red service level.
Service Quality Quality,, custome customerr satisfa satisfacti ction, on, mob mobile ile telecom telecommun municat ication ion Keywor Keywords ds – Service networks, customer expectations and SERVQUAL
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Table of o f contents
INTRODUCTION............................ .................................. .................................. ................................ ...............................5 ...............5 1. INTRODUCTION............ 1.1. 1.2.
Background of the study……………………………………………....5
Overview of Telecommunications Market……………………...…....6 1.3.
The current state of telecommunication industry in the UK……….6 UK……….6
1.4.
Problem Identification & Purpose of the Study……………………..8
1.5.
Research Questions……………………………………………………9
1.6.
Research Objectives…………………………………………………...9
1.7.
Significance and Limitations of this dissertation……………………
10
2.
LITERATURE REVIEW.................... REVIEW.................................... ................................ ................................ .............................11 .............11
2.1.
Purpose of Literature review………………………………………….11
2.2.
Customer Psychology………………………………………………….11
2.3.
Role of Customer Satisfaction………………………………………...12
2.4.
Measuring Customer Satisfaction…………………………………….13
2.5.
Customer Satisfaction Indices (CSI) ……………………………………..13
2.6.
Disconfirmation Models………………………………………………..15
2.7.
Service Quality………………………………………………………….16
2.8.
Relationship Relationship between Service Quality and Customer Satisfactio Satisfaction…18 n…18
2.9.
Service Quality Dimensions……………………………………………19
2.10.
Service Quality Models…………………………………………………19
2.11.
SERVQUAL…………………………………………………………….20
2.12.
Gronroos’ Model of SERVQUAL……………………………………..23
2.13.
Addressing the Research Questions…………………………………...24
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METHODOLOGY.................................. .................................. ...............................26 .............26 3. RESEARCH METHODOLOGY.................. 3.1.
Research Purpose ……………………………………………………...26
3.2.
Research Philosophy…………………………………………………...26
3.3.
Research Approach……………………………………………………27
3.4.
Research Method ………………………………………………………27
3.5.
Operationalisation Operationalisation of Concepts………………………………………….30
3.5.1.
Minnesota Customer Satisfaction Index (MnCSI)…………..30 (MnCSI)…………..30
3.5.2.
Defining Hypothesis…………………………………………....32
3.5.3.
Disconfirmation Models……………………………………….33
3.5.4.
Over-all Satisfaction…………………………………………...33
3.5.5.
Procedures to test Hypotheses………………………………..34
3.6.
Sample Selection and Data Collection………………………………..37
3.7.
Reliability………………………………………………………………38
3.8.
Validity…………………………………………………………………39
4.
DATA ANALYSIS AND DISCUSSION………………………………….41
4.1. Introduction……………………………………………………………41 4.2. Demographic profile…………………………………………………..41 4.3. Assessing Customer Satisfaction with the Service Quality…………41 4.3.1.
Results of Minnesota Customer Satisfaction Index…………42
4.3.2.
Results of Disconfirmation Models and Over-all Customer Satisfaction Measure……………………………...43 4.3.2.1. Irrespective of cellular network……………………...43 4.3.2.2. With respect to cellular networks…………………....47
4.4.
Customer satisfaction with each service quality dimension………..57 dimension………..57
CONCLUSION................................ ................................ .............................65 .............65 5. SUMMARY AND CONCLUSION................
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BIBLIOGRAPHY............................... ................................ ................................ ................................ .........................69 .........69 6. BIBLIOGRAPHY...............
1. INTRODUCTION
1.1 Background to the study: During the last few years, the Telecom industry industry has experienced 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 organis ations are proposing various strategic methods to achieve effective Customer Satisfaction (CS) strategy decisions and eventually increase the CS success rates to sustain long term relationship with the profitable customers (Chien and Su, 2003; Gronroos, 1994). “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 custo mer centric, giving more importance importan ce to retaining old customer cus tomer 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 custome customerr loyalty loyalty and custome customerr retenti retention, on, each each of these these compani companies es is continua continually lly 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 organisations frequently adopt new measures to check if 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 make the right decision to increase customer satisfaction and eventually customer loyalty among 5|Page
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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 mobi le service providers provider s (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 According to the UK Mobile Operator Subscriber Data, Statistics and Market Share Share 2006 - 2008, there there are five primary primary cellular cellular network network operato operators rs in the UK: Vodafone, Telefonica O2, T-Mobile, Orange and 3 UK and it was reported to have 73.1 million cellular service subscribers 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 anticipated to achieve 126% by 2010 and gradually the total subscribers would also reach 78 million by 2010 (Telecoms Market Mark et 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 6|Page
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advances in technology and increased market turbulences turbulences have added a lot of value to the telecom industry (Lia and Whalley, 2002).
Recen Recently tly T-Mob T-Mobil ilee and Orang Orangee merge merged d becom becomin ing g a giant giant in the tele telecom com industry having 28.4 million customers and now they are the largest cellular service provider in the UK with an approximate of 37% of the entire mobile market (BBC News, 2009; The Register, 2010). 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 (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 (Mobile Virtual Network Operat Operator ors), s), the the mo mobil bilee data data traff traffic ic has has gradua gradually lly incre increase ased d 200 200% % in 200 2009 9 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 serv ice delivery delive ry necessitating ne cessitating the network netwo rk operators op erators to take precautions in order o rder to maintain their service se rvice delivery standards. stand ards.
The market share of mobile telecom industry in the UK as of September 2009:
Fig 1.3a Market Share of Mobile telecom industry in the UK
(Source: Guardian News, 2009)
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The Fig 1.3a indicate indicatess that, that, as of Septem September ber 2009, 2009, T-Mobil T-Mobilee / Orange 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%.
Thee tota Th totall num number ber of sub subscr scribe ibers rs for the the UK’s UK’s mo mobi bile le telec telecom om indus industr try y as on September 2009:
Fig 1.3b Number of subscribers for the UK’s mobile telecom industry
(Source: Guardian News, 2009)
The Fig 1.3b indicates that, as of September 2009, T-Mobile / Orange had 28.4 28.4 mill million ion custom customers ers being being the the highes highestt follo followe wed d by O2 havin having g 21.5 21.5 mill million ion customer, 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 dissati dissatisfie sfied d with with the serviceservice-avai availab labilit ility y and it’s it’s quality quality;; especial especially ly the network network coverage is a crucial concern to all of its consumers. (Telecom paper, 2009) Due to the existence of several MVNOs, 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 8|Page
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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 b ad at dealing d ealing with issues and complaints complaints compared with their successors British Gas.” (Xln Business Community, 2009). The customers don’t 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 Busine Business ss Commu Communi nity ty,, 200 2009) 9).. Th These ese situa situati tions ons creat createe a bad impre impressi ssion on in the the customer’s 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 analyse the level of customer satisfaction with regards to service delivery among different mobile service providers (Mobile (Mobile Telecommunica Telecommunication tion Networks) within the UK.
1.5 Research Questions: How the customers’ satisfaction with the service quality is described in the UK’s MTNs with and without respect to the customer’s service providers?
Whic Which h attr attrib ibut utes es of serv servic icee qual qualit ity y do the the cust custom omer erss perc percei eive ve to be of more ore importance that lacks attention from the service providers in the UK?
1.6 Research Objectives: To find out the level of customers’ satisfaction with the service quality offered to them by the UK’s MTNs with and without respect to which network customers subscribe to.
To
fi n d
out
which
dimensions
of
satisfied/dissatisfied with in the UK’s MTNs.
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service
quality
are
th e
customers
Market Research on Service Quality and Customer Satisfaction
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To identify the Service Quality dimensions that the customers perceive to be of high importance in the UK’s 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 o f this study would be b e helpful to the management manag ement of UK’s 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 dimens dimensio ions ns of servic servicee quali quality ty whic which h are are consi consider dered ed mo more re impor importan tantt from from the customer’s customer’s 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 a s share-holders share-h olders and an d investors inves tors which would help them provide prov ide useful useful sugg suggest estions ions to their their respect respective ive mob mobile ile service service provide providers rs to improv improvee their their service service deliver delivery y standard standards. s. The disserta dissertation tion enables enables the custome customers rs to analyze analyze the ratings of the various dimensions with respect to the service providers so that bringing in awareness among customers.
The limitatio limitations ns of this this dissert dissertatio ation n are that, the researc research h would would not have access access to every locality in the UK and as the research is mostly done in the city of London. But London, being a cosmopolitan cosmopolitan city, gives us a gist of UK and a right place to conduct the research. It doesn’t 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.
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2. 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, objectives, so that we can develop and refine the key area areass of our researc research h (Saun (Saunder derss et al, al, 200 2007). 7). To genera generate te and refine refine the research ideas the ‘Relevance Tree’ technique is used in this review of literature literature i.e. a broad concept is studied from the view of various authors via which a new subconc concep eptt is deve develo lope ped d and and as we proc procee eed d deep deep into into the the subj subjec ectt new new idea ideass are are formulated formulated (Saunders et al, 2007). The customer satisfaction is measured through the service service quality quality dimensi dimensions ons defined defined for that particular particular product product or service service.. These 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). 1 997). Understanding the psychology of customers plays a very important importan t role in determining their satisfaction satisf action over ov er a product or o r service. This Th is includ includes es desig designin ning g a produc productt accor accordin ding g to the needs needs of the custo custome mer. r. Th Thee satisfaction satisfaction of a customer starts well before manufacturing 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).
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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 Rejection – where the customer rejects the offer, Postponement 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 influencing the customer’s choice to purchase a product is very crucial (Lynch, 1992; Pizam Pizam and Ellis, 1999). Therefor Therefore, e, it is very essentia essentiall for us to know the custome customer r expectations and their requirements, to understand customer’s view and perspective about the quality of services and products they need (Pizam and Ellis, 1999).
2.3 Role of Customer Satisfaction: Custo Custome merr Sati Satisfa sfacti ction on (CS) (CS) is said said to be the the cust custom omer’ er’ss pos postt-pur purch chase ase evaluation of services or a product. When the CS level of an organisation is high, even even the marke markett share share and and profi profits ts of the the organi organisat satio ion n grow grow highe higherr leadi leading ng the the company company to a stronger stronger competitiv competitivee position position in the market market place place (Turky (Turkyilm ilmaz az 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 customer satisfaction and building great custome customerr experie experiences nces.. Custome Customerr care is therefo therefore re a key to gain the competi competitiv tivee advantage among the competitors (Lynch, 1992).
Satisf sfac acti tion on of cust custom omer erss also also happ happen enss to be the the chea cheape pest st mean meanss of “Sati promotion and therefore, customer satisfaction is recognized as of great importance import ance to all commercial firms because of its influence influence on repeat purchases and word-of mouth recommendations. recommendations.”” (Pizam and Ellis, 1999, p. 326). Hence, it becomes important important for the organisation to offer customers a good experience that exceeds their expectation and if the the custom customer erss have have bad experi experienc ences, es, then then the the reputa reputati tion on of the comp company any reduces rapidly due to word-of-mouth communication.
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Sati Satisfa sfacti ction on of custo custome mers rs over over a tele telecom commu munic nicat atio ion n produc productt can be two 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 on 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 customer satisfaction level based on the valuable feedback from the customers and identify identifying ing the custome customerr expecta expectation tionss (Crosby (Crosby,, 1991). 1991). The service service quality quality can be achieved only by knowing the customer’s 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: Expecta Expectancy ncy disconfi disconfirma rmation tion (Parasur (Parasurama aman n et al, 1988), 1988), Ass Assimi imilati lation on contrast contrast,, Compari Comparison son level level (Gronro (Gronroos, os, 2001), 2001), Value Value precept precept (Zeith (Zeithaml aml,, 1988), 1988), Cogniti Cognitive ve 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, However, among these, only two of them were widely accepted i.e. the expectancy disconfirmation disconfirmation theory and customer customer satisfaction satisfaction indices (Pizam and Ellis, 1999) because all the theories mentioned mentioned above use these two models as a common base (Parasuraman et al, 1988; Gronroos, 2001; Zeithaml, 1988; Kauppinen et al., 2007). Therefore, 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):
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This model focuses more on customer’s overall satisfaction with a product or the the serv servic ices es offe offere red d to them them till till date date and and it is base based d on a cumu cumula lati tive ve view view of satisfac satisfactio tion n (Turky (Turkyilma ilmazz and Ozkan, Ozkan, 2007). 2007). “The “The CSI model is a structur structural al mod model el 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 firm.” .” (Tur (Turky kyil ilma mazz and and Ozkan Ozkan,, 200 2007, 7, p. 673 673). ). It is equal equally ly impor importa tant nt to understand the customer perceived value and their expectations to attain high degree of customer satisfaction.
The Swedish Customer Satisfaction Barometer (SCSB) is reported to be the first national customer satisfaction index (NCSI) which was developed in 1989, then the mo mode dell was was follo followe wed d by the Germ German ans, s, they they name named d it as Germa German n Cust Custom omer er Barometer (Fornell, 1992).
The Americans adapted this model in 1993, it was developed by Claes Fornell, who who was was the the foun founde derr of SCSB SCSB and and they they name named d it as the the Am Amer eric ican an Cust Custom omer er Satisfaction 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, Ozkan, 2007; 2007; Fornell Fornell,, 1992). 1992). The Europea European n Organisa Organisatio tion n for Quality Quality (EOQ) (EOQ) and Europ Eu ropean ean Found Foundat ation ion for Quali Quality ty Manag Managem ement ent (EFQ (EFQM) M) joint jointly ly devel develope oped d the 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 ‘Corporate Image’ as a component 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 (MnCS (MnCSI) I).. Th Thee Mn MnCS CSII mo mode dell is speci specifi fical cally ly used used to evalu evaluat atee over-a over-all ll custo custome mer r sati satisf sfac acti tion on with with serv servic icee deli delive very ry of the the MT MTNs Ns on a sing single le scal scalee (Pos (Posit itiv ivel ely y Minnesota, 2007). This model uses the variables of disconfirmation models: both desire disconfirmation as well as expectation disconfirmation and it combines three question questionss which which includes includes the disconfi disconfirma rmation tion mod models els also (As discusse discussed d earlier earlier disconfirmation models are the second CSM tool which was widely accepted) It also 14 | P a g e
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gets more stable when there are three questions instead of one. In addition, it is compar comparati ative vely ly flexi flexibl blee and and best best suit suited ed for any num number ber of respo response nsess (Pos (Posit itive ively ly Minnesota, 2007).
2.6 Disconfirmation Models: According to Parasuraman et al. (1988), customer expectations are one of the most important factors of CS, as they play a major role of ascertaining customer satisfaction. satisfaction. Even the SERVQUAL SERVQUAL model uses the disconfirmation disconfirmation model as its base and it is basically used for conceptualizing conceptualizing service quality (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 - DesireDisconfi Disconfirma rmatio tion n mod model el and Expect Expectancy ancy disconfi disconfirma rmation tion mod model el (Pizam (Pizam and Ellis, Ellis, 1999; Parasuraman et al., 1988). The expectancy disconfirmation model states that quality is assessed by comparing comparing perceived and expected performance i.e. to examine if the customer customer expectations were met during the service delivery process (Oliver and DeSarbo, 1988; Kang and James, 2004).
Accordin According g to Oliver Oliver (1980), (1980), the expectan expectancy cy disconfi disconfirma rmatio tion n mod model el has got two internal attributes, which are known as positive disconfirmation and negative disconfirmation. If the performance of the product or service exceeds the customer expectations and when the customer is highly satisfied with the product or service delivere delivered, d, then it is called called as value value disconfi disconfirma rmatio tion. n. However However,, if the custome customer’s r’s expectations expectations are met and he/she is satisfied 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, expectations, then it is called negative disconfirmation disconfirmation (Oliver, 1980). This theory focuses more on the antecedents of satisfaction, which occurs at the initial stages of the service-delivery service-delivery process (Oliver, 1980; Oliver and DeSarbo, 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 15 | P a g e
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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 is defined as “a consumer’s judgment about an entity’s overall excellence or superiority.” (Kang and James, 2004, p. 267) This Th is term term is purely purely custo custome merr orien oriente ted. d. Hence Hence excel excellen lence ce in servi service ce requi require ress an understanding of customer needs and expectation (Edvardsson, 1998).
As there was an enormous growth in mobile 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 servi service ce quali quality ty in MT MTNs Ns can be perce perceive ived d throug through h the the techn technic ical al as well well as the the functional attributes of mobile services in which the technical attributes include the pricing/tariff plan, the network quality & data services and the functional attributes include the customer service quality and the billing system. “Overall perceptions of serv servic icee qual qualit ity y are are form formed ed by a cons consum umer er’s ’s eval evalua uati tion on of mu mult ltip iple le qual qualit ity y dimens dimensio ions. ns.”” (Kum (Kumar ar and Lim, Lim, 200 2008, 8, p. 569 569). ). Henc Hencee in order order to enhan enhance ce the the custo custome mer’s r’s perce perceiv ived ed value value and their their satis satisfac facti tion on level level,, it is impor importan tantt for for the organisations to create positive perceptions of service quality among its customers (Kumar and Lim, 2008).
Service quality enhances the organisation’s operational efficiency as well as improving improving the retention rate of its firm (Edvardsson, 1998). The customers assess the product quality qu ality in various tangible tang ible 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 (Parasuraman et al., 1985).
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Accordin According g to Parasur Parasurama aman n et al. (1985), as the services services being being intangib intangible le 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 to evaluate eva luate the service quality qu ality of an organisation. organisation .
Gronroos Gronroos (2001) (2001) introduc introduced ed the concept concept of Consum Consumer er Perceiv Perceived ed Quality Quality (CPQ), which evaluates to what extent the service delivered, meets the customer’s expectation. It compares the consumer’s expectations and the customer’s 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 that service quality and customer satisfaction are distinct conceptually but they are closely related constructs (Kang and James, 2004; Sureshchandar et al., 2002). A recent study has proved that “the CPQ influences profitability directly as well as indirectly ind irectly through thro ugh market share.” (Crosby, (Cro sby, 1991, p. 6). Hence it is equally important to take CPQ under consideration for this research.
According to Parasuraman et al. (1988), the long term and global evaluation of a service is related to the service quality perceived by the customers customers and the customer satisfaction satisfaction can be obtained by evaluating evaluating specific service transactions and they have also clearly pointed out that the customer experience with the provided service, influence the perceptions of service quality. Hence, it could be said that both service quality and CS are closely related terms.
2.8 Relationship between Service Quality and Customer Satisfaction: The relationship between service quality and customer customer satisfaction satisfaction has gained a 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 the curren currentt comp compet etiti itive ve marke market, t, the compa companie niess can sus sustai tain n its its compet competiti itive ve advantage by providing service quality of higher standards, which would result in satisfied customers (Sureshchandar et al, 2002).
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Customers are one of the important assets of an organisation as they are the only ones who keep the business running. As it was already discussed earlier that retai retainin ning g existi existing ng custo custome mers rs is mo more re essen essenti tial al than than genera generati ting ng new new ones, ones, it is important to have service quality in every stroke to 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 quality of service delivered, is the consumer’s commitment to renew/continue our service consistently in the future (Nguyen et al, 2007).
Figure 2.8: Five critical factors of customer perceived service quality
Source: (Sureshchandar et al., 2002)
The figure 2.8 indicates indicates the five critical factors of customer perceived service quality, quality, in which the core services refer to the content of the services i.e. the different features offered 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 s ervices refers to the systematizing s ystematizing and simplifying the systems, processes and the procedures. The tangibles 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
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improve the image of the company and also promote customer loyalty and overall customer satisfaction (Sureshchandar et al., 2002).
2.9 Service Quality Dimensions: According to Johnston (1995), it 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 to find out the determinants of service quality to define measures and control customer perceived service quality.
In 1980s, Parasuraman 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 to meet customer’s expectations. It is considered to be the most popular instrument, which is widely used by many researchers and practitioners to measure meas ure service quality qualit y (Sureshchandar et al., 2002). 20 02).
2.10 Service Quality Models: Many models were developed to capture the quality of service at different points of time to suit different business objectives ob jectives (Nitin et al, 2005). 200 5). 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 Parasuraman et al.’s al.’s (1985) (1985) GAP model. model. This This mod model el analyse analysed d the gaps between between the customers’ customers’ expected and perceived service forming a base for the SERVQUAL model with several dimensions like Tangibles, Tangibles, Reliability etc. However, 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
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next model designed designed by Haywoo Haywood d (1998) (1998) called called as ‘Attrib ‘Attribute ute ServQua ServQuall Mod Model’ el’ incorporated 3 attributes: ‘Physical facilities and process’, ‘People’s 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 customer’s 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.
Mean Meanwh whil ile, e, Cron Cronin in and and Tayl Taylor or (199 (1992) 2) deve develo lope ped d ‘SER ‘SERVP VPER ERF’ F’,, the the ‘Performance ‘Performance Only Model’ which states that the consumers’ 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 with perce percepti ption. on. But But the perce percepti ption on canno cannott alway alwayss be a prope properr servic servicee quali quality ty indicator because perceptions do change with time, and the organisation that provide unmatch unm atched ed service service excellen excellence ce always always lead lead even when when started started with with compara comparative tively ly lesser brand awareness and marketing system. The Mattson’s (1992) ‘Ideal Value Model’ calculates the Service Quality in comparison comparison with the Ideal Industry Standard Standard rather than the Customers’ perceptions. This model may strive to provide the best servi service ce in line line with with the techn technolo ologic gical al capab capabil ilit ity y but the innova innovati tion on may may not be focussed on the customer’s 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, Pivotal, Core and Peripheral. Oh (1999) depicted the importance importance of Customer Customer Value. Frost and Kumar (2000) proposed the ‘Internal ‘Internal Service Quality’ dimensions dimensions based on the GAP model for the Internal Customers of the organisation. In the ‘Internal Service Quality DEA model’ (Soteriou and Starvinide, 2000), the Data Envelope Analysis maps the depreciation in service quality from the client base to branches. Santos’ (2003) ‘e-Service ‘e-Service Quality’ is developed on the antecedents of service quality using ecommerce.
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2.11 SERVQUAL: SERVQUAL is a multiple item scale developed to measure the Service quality and this instrument instrument illuminates the different dimensions of customer’s customer’s perception and helps assessing the service quality (Parasuraman et al., 1985, 1988).
It has illuminated five dimensions via which customers perceive and assess service quality of the organisation organisation and each dimension has a sub-set called ‘items’ via which the dimensions are being measured (Parasuraman et al., 1988). The five dimensions are:
1. Tangibles: 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. 3. Responsiveness Responsiveness : Providing quick service and their willingness to help the customers. 4. Empathy: Caring for the customers with more individualised attention. 5. Reliability: Prov Provid idin ing g accu accura rate te serv servic icee and and perf perfor ormi ming ng the the prom promis ised ed commitments (Parasuraman et al., 1988).
The required data is collected via structured questionnaire or surveys from a sample of customers in which many questions are formulated based 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:
SERVQU SERVQUAL AL has overlook overlooked ed at som somee of the important important factors factors of service service quali quality ty such such as the the socia sociall respon responsi sibil bility ity of the organ organisa isati tion, on, core core servi service ce and standardisation of service delivery and there is also a general agreement towards the 22 item itemss scal scale, e, that that they they are are reas reason onab ably ly good good pred predic icto tors rs of serv servic icee qual qualit ity y
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(Sure (Sureshc shcha handa ndarr et al., al., 200 2002). 2). Mo Most st of the the resear research ch mo model delss till till date date have have used used SERVQUAL as its base for development (Sureshchandar et al., 2002).
The SERVQUAL SERVQUAL model has also been severely criticized in many cases. The contents of the service quality dimensions obtained obtained from the SERVQUAL model has not been accepted by everyone, as service quality is generally viewed as a multidimensional 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 funct functio ional nal attr attribu ibutes tes to predic predictt custom customer’ er’ss behavi behaviour our may may have have low predic predicti tive ve validity, the semantic differences are not being withstanded in each dimension, etc. (Kang and James, 2004; Sureshchandar et al., 2002). The criticisms criticisms also include “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 disadvantages it is advisable advisable to look into other models based on SERVQUAL.
In 1992, Cronin and Taylor developed the Performance only model, which they called it SERVPERF. It states that service quality can only be assessed by perceptions and it is not necessary to measure meas ure expectations (Cronin and Taylor, 1992). 1992) . The author views service quality as a link between purchase intentions and customer satisfaction and they challenged the SERVQUAL framework by Parasuraman et al. (198 (1985) 5),, that that perc percep epti tion onss are are the the only only pred predic icto tors rs of serv servic icee qual qualit ity y wher wheree as SERVQUAL model confuses consumer satisfaction with attitude of the consumers (Cronin and Taylor, 1992).
Similarly, 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 such as word-of-mouth communication and adverti advertisem sements. ents. It integra integrates tes the traditi traditional onal manager managerial ial framewo framework rk to the service service quality which comprises of three factors: image, traditional marketing activities and external influences and the model was called synthesized model of service quality (Brogowicz et al., 1990). 22 | P a g e
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Another study by Haywood-Farmer (1988) suggests that the attributes has to be separated into three groups: professional judgement, processes & facilities and consumer’s 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, Parasuraman et al. (1985) had stated that service quality cannot be assessed only with service outcomes but even the service 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 three attri attribut butes es i.e. i.e. necess necessar ary y from from the Eu Europ ropean ean perspe perspect ctive ive.. Mo Moreo reover ver,, the the G r on r oo s ’
ServQual
model
was
used
in
an
empirical
research
in
th e
telecommunications field, which had proved that Gronroos model is more appropriate to represent service quality in telecommunications industry (Kang and James, 2004).
2.12 Gronroos’ Model of SERVQUAL: It is a multi dimensional model. According to this model there are two service quality dimensions, dimensions, firstly the technical aspect (what kind of service is provided) and the functi functiona onall aspec aspectt (how (how is the the servi service ce being being provid provided) ed).T .They hey introd introduce uced d the corporate image concept, as one of the other important element in the perceived servi service ce-qu -qual ality ity mo model del,, as the the custo custome mers rs would would bring bring their their perce percepti ptions ons and past 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 wouldn’t bother much about the minor mistakes that happens and in case there is 23 | P a g e
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a negative image about the firm, then the mistakes would be magnified in their mind (Gronroos, 1994; Kang 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 Hence these these three three dime dimensi nsions ons (tech (technic nical al dime dimensi nsion, on, functi functiona onall dimens dimensio ion n and and corporate image) are considered the most important.
2.13 Addressing the Research Questions
As discussed earlier in the ‘current state of telecommunicatio telecommunication n industry in the UK’ UK’ and ‘Pro ‘Proble blem m Identi Identifi ficat catio ion’ n’ in the the intro introduc ducti tion on (sect (section ion 1.3 1.3 and 1.4), 1.4), the 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 customer’s switching intention.
At this juncture it 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 obtaine obtained d using using the followi following ng theoreti theoretical cal mod models els which which has been justified 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’ satisfaction with the service quality offered to them by the UK’s MTNs with and without respect to which network customers subscribe to. ii) The expectation disconfirmation model is used in order to find which dimensions of service quality the customers are satisfied or dissatisfied with in the UK’s MTNs. iii) The Gronroos’ Servqual model is used to identify the service quality dimensions that the customers perceive to be of high importance in the UK’s MTNs. 24 | P a g e
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The research question one: ‘How the customers’ satisfaction with the service quality is described in the UK’s MTNs with and without respect to the customer’s 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.
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3.1 Research Purpose: According According to Saunders et al. (2007), research is a systematic systematic or a step by step procedure to increase the knowledge of a new or an existing subject. The purpose of this research is to key out the main service quality dimensions/attributes dimensions/attributes as perceived by the customers and find out o ut how h ow satisfied satis fied they are with these th ese attributes and also als o to explore the reasons for their the intention intention to change their service providers (Saunders (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 their scien scientif tific ic explan explanati ations ons.. ‘Pheno ‘Phenomen menolo ologic gical’ al’ helps helps in trying trying to und unders erstan tand d 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 natura naturall scient scientist ist would would treat treat the world world (of natura naturall forces forces/thi /things ngs)) (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.
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According According to Saunders Saunders et al., (2007), there are two broad methods of reasoning: reasoning: deductive approach and inductive approach. The deductive approach is based on the topdown approach mode where a theory is developed and subjected to more observation after hypothesis as shown in the fig 4.3. It works from more general to specific reasoning (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 (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 Research 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 metho methods ds whic which h links links the data data to conce concepts pts (Neum (Neuman, an, 200 2006). 6). On the the other other hand, hand, qualitat qualitative ive analysi analysiss explain explainss the social social phenome phenomena na which which involve involve intervie interviews ws and observations from real life situations (Saunders et al., 2007) and the data here includes writ writte ten/ n/sp spok oken en word words, s, phys physic ical al obje object cts, s, soun sounds ds or visu visual al imag images es meas measur ured ed 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 following models as justified justified 28 | P a g e
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in the literature review: Gronroos’ SERVQU SERVQUAL AL model (Gronroos, (Gronroos, 1994) to evaluate CS with the Service Quality dimensions (functional dimensions, Technical dimension and Corporate Image); ‘Disconfirmation models’ to analyse and evaluate customer’s 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 custome customerr satisfac satisfactio tion n with with service service delivery delivery of the UK’s MTNs MTNs with with and without without respe respect ct to which which Mo Mobil bilee Tele Telecom com Netwo Network rk custo custome mers rs sub subscr scribe ibe to (Posi (Positi tivel vely y Minnesota, 2007).
According to Neuman (2006, pg. 412), “Researchers often combine focus group with with quantit quantitativ ativee research research,, and the procedur proceduree has its own specific specific strength strengthss 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 understanding of the subject in a bigger view and these strengths overwrites overwrites the weaknesses weaknesses which are: ‘polarization ‘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 somee more som more value value to the research research idea (Saunders (Saunders et al., al., 2007). 2007). The members 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 these attr attribu ibutes tes they they consid consider er the the balanc balancee betwe between en quali quality ty and cost cost as the the mo most st 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 Dimensions and its items (variables) (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.
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Table 3.4: Service Quality dimensions and its comprising items No.
of Service Quality Dimensions
Items 3
No.
of Service Quality Dimensions
TANGIBLES (TN)
Items 3
ASSURANCE (AR)
3
RELIABILITY (RE)
3
TECHNICAL QUALITY (TQ)
3
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, quality, the quantitative 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 perceptions 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 second section section consist consistss of disconfi disconfirma rmation tion measure measuress (desire (desire and expectation) derived from ‘Disconfirmation Models’, ‘Over-all customer satisfaction’ measure measure and ‘Servic ‘Servicee quality quality’’ dimensi dimensions ons derived derived from Gronroos Gronroos’’ SERVQU SERVQUAL AL model mod el and focus focus group group intervie interview w (VFM). (VFM). The third third section section includes includes all Service Service Quality dimensions and asks the customer to rate the importance of each dimension from their perspective, which is measured on a five-point likert scale ranging from ‘Least Important’ to ‘Most important’. The items in section 2 and 3 extensively analyzes the requirements 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: 30 | P a g e
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3.5.1 Minnesota Customer Satisfaction Index (MnCSI): This index may have up to 5 responses for 3 questions by which the customer satisfaction satisfaction levels are evaluated. The responses are measured using 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: Overall, how satisfied or dissatisfied you are with the services being provided by your network? How well does the service fulfil your expectations? To what 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 Question 1
1 Very
Question 2
dissatisfied Much worse Much better Equal than
Question 3
2 Dissatisfied
than
3 Neutral
4 Satisfied
5 Very
Satisfied to Bett Better er than than Much better
expectation
expected
than
expected expected expected Much worse Worse Worse than than Equal to my Bett Better er than than Much better than desired
desired
desire
desired
than desired
The table 3.5.1a indicates indicates the three questions with its corresponding corresponding values ranging between 1 and 5 where ‘1’ indicates the customer’s very dissatisfaction with the services and ‘5’ indicates the very satisfaction with the services.
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Then Th en the answe answers rs to these these three three questi questions ons are are then then calcu calcula lated ted using using this 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 in table 3.5.1b
Table 3.5.1b: Weight of each response Responses Weight •
1 0
2 8.32
3 16.65
4 24.97
5 33.30
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 81 - 1 00 61 - 8 0 51 - 6 0 31 - 5 0 Below 30
Description Very High Hi g h Fair Low 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 32 | P a g e
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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 tr ansformed 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 subscribe to.
Sub ub-H -Hyp ypot othe hese sess
Diss Dissat atis isffied ied wi with
H1a
Vodafone
H1b
O2
H1c
T-Mobile/Orange
H1d
3-Mobile
H2: Th Thee Discon Disconfir firmat mation ion models models impact impact the over-a over-all ll CS positi positive vely ly in UK’s UK’s 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 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 33 | P a g e
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DD
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Desire Di Disconfirmation
To what extent did the services you received from them match your desired set of ED
services? Expectation Disconfirmat mation How well does the service fulfil your expectations ? Both these variables are measured using a 5-point likert scale. For DD, the
scales vary from ‘Much worse than desired’ to ‘Much better than desired’. Similarly, Similarly, for ED the scales varied from ‘Much worse than expected’ to ‘Much better than expected’.
3.5.4 Over-all Satisfaction: It refers to the customer’s over-all judgement 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 sing le question, to which the respondents rate their over-all over-a ll satisfaction with service quality on the 5-point likert scale which vary from very dissatisfied to very satisfied.
Table 3.5.4: Variable for over-all Satisfaction Measure OCS OCS
Over Over-a -all ll Cust Custom omer er Sat Satis isfa fact ctio ion n
Overall, please rate how satisfied or dissatisfied you are with the services being provided by b y your network.
3.5.5 Procedures to test Hypotheses: The following describe how the research objectives are met and tested with the hypotheses.
Research Objective One (RO 1)
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To find out the level of customers’ satisfaction with the service quality offered to them by the UK’s 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 1
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 significance 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 customer’s dissati dissatisfac sfactio tion. n. Cut-off Cut-off point 4 is chosen chosen for OCS measure, measure, because because in over-al over-alll satisfaction scale, ratings from 1 to 3 indicates the customer’s 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 extracted from SPSS output.
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Step4: The null hypothesis is rejected under the following 2 conditions. Firstly, in case the mean mean differen difference ce is signifi significant cantly ly negative negative and secondly secondly,, if the confiden confidence ce interval is showing negative. It is not rejected if the mean difference is significantly positive or any value valu e under confidence confiden ce 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 the null hypothesis states that there is no significant relationship relationship between both the disconfirmation disconfirmation models (DD and ED) together and OCS.
The procedure to test these three models is mentioned below:
Step1: The Null hypothesis:
H0: DD ≤ 0 H1: DD > 0 H0: ED ≤ 0 H1: ED > 0
Vari Variab able le DD is is not not sign signif ific ican antl tly y gre great ater er than than 0 Vari Variab able le DD is is ssig igni nifi fica cant ntly ly grea greate terr tha than n0 Vari Variab able le ED is is not not sign signif ific ican antl tly y gre great ater er than than 0 Vari Variab able le ED is is sig signi nifi fica cant ntly ly grea greate terr tha than n0
Step2: Linear regression F test is conducted at significance level 0.05
Step3: p-value (critical value) is extracted from the SPSS output
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Step4: The null hypothesis is rejected under following two conditions: If the p-value is less than the significance value 0.05 and if the co-efficient is positive.
3.5.5c Research Objective Two (RO 2) To
fi n d
out
which
dimensions
of
service
quality
are
th e
customers
satisfied/dissatisfied with in the UK’s 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. OneSamp Sample le T test test is used used to verif verify y the the signi signific ficanc ancee of the mean mean differ differenc ences es with with significance level of 0.05 and test-value 3 in order to split the entire sample into satisfied satisfied and dissatisfied dissatisfied customers for each of the items in each dimension 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: Step3: Confiden Confidence ce interval intervalss and p-value p-value (Critic (Critical al value) value) is extracte extracted d from SPSS output.
Step4: The null hypothesis is rejected under the following two conditions: If the mean difference difference is significantly significantly negative and if the confidence interval is showing negative. It should not be rejected if the related related mean difference difference is significantly significantly positive or any value under confidence interval includes a positive value.
3.5.5d Research Objective Three (RO 3)
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What Service Quality dimensions dimensions do the customers customers perceive to be of high importance in the UK’s MTNs?
One-Sample T test is conducted at significance level 0.05 with a cut-off value 3 to split the service quality dimensions dimensions that are considered important by the customers customers from those that are unimportant. unimportant. Then each service quality dimension is ranked in an orde orderr of magn magnit itud udee to poin pointt out out the the impo import rtan ance ce of each each dime dimens nsio ion n from from the the customer’s point of view.
3.6 Sample Selection and Data Collection: According According to Neuman 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 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 one of the most active cell phone users (Clickz, 2005). From the sample frame of 78 million cellular service subscribers subscribers in the UK (Telecoms Market Research, 2008) , a sample size of 100 respondents respondents are selected due to the time and cost constraints. constraints. The time limit provided to complete this research was very less and using a larger sample size may require huge financia financiall resource resources, s, which which was unafford unaffordabl able. e. Two differe different nt types types of survey 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 is comprised for 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
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website website and the link > was sent to all the students of UEL via university’s webmail 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 questionnaires collected through various survey instruments, 17 are 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: Reliability 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 Cronbach’s 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 Where ‘K’ is is the number number of items items or comp componen onents ts in the quest questionn ionnaire aire and and
mean of
is the the
(Pallant, 2005).
With the help of reliability co-efficient Cronbach’s alpha we are checking the internal consistency of each scale.
Table 3.7: Results of Chronbach’s α test Service Quality
Chronbach’s α value
No. of items/components
Dimensions Tangibles
0.972
3
Reliability
0.963
3
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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
2010
Table 3.7 indicates that all the items under each dimension are above the minimum scale of 0.7. Hence these values indicate that all of these dimensions are reliable and internally consistent.
3.8 Validity: Validity is concerned with accuracy accuracy of the measurements. measurements. It is 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 author’s/researcher’s 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:
Accord According ing to Saund Saunders ers et al (2000) (2000) and and Malhot Malhotra ra et al., al., (2007) (2007) the the struc structur tured ed questionnaire must be pre-tested before final administration. Hence the preliminary 40 | P a g e
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draft of the questionnaire was pre-tested by the members of focus group interview to check check the clear clearnes nesss and signi signific ficanc ancee of the questi questions ons and it was was also also check checked ed 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 Saunders et al 2007), who had mentioned that it is adequate to have a minimum of ten members for the pre-t pre-tes estin ting. g. Befor Beforee givin giving g the questi questionn onnai aire re,, each each of these these memb members ers were 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.
4. DATA ANALYSIS AND DISCUSSION
4.1 Introduction: 41 | P a g e
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This chapter focuses on statistical analysis of quantitative data which was collecte collected d during during the process of surveyi surveying. ng. It compris comprises es of data data presenta presentation tion that covers demographic profile of respondents, measurement of customer satisfaction, custo custome merr satisf satisfac acti tion on with with diffe differen rentt servic servicee quali quality ty dimen dimensio sions ns and rela relati tive ve impor importan tance ce of those those dimens dimensio ions. ns. Th Thee discu discuss ssion ion includ includes es analy analysis sis of diffe differe rent nt hypotheses and their relative results and findings in order to answer the research questions.
4.2 Demographic profile: This shows 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 female respo responde ndent ntss and as menti mentione oned d previo previousl usly y in the resea research rch metho methodol dology ogy,, major majority ity of the respo responde ndent ntss are are young youngste sters, rs, betwe between en 21 – 30, 30, as they they are the the economi economicall cally y activeactive-grou group p constit constituti uting ng 77.1%, 77.1%, whilst whilst the rest rest constit constituti uting ng 22.9% 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 in the literature review and also mentioned in the sections 3.5.1, 3.5.3 and 3.5.4 of research methodology. Here Here the custo custome merr satisf satisfac acti tion on is asses assessed sed with with respec respectt to cellu cellula larr netwo network rk 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 mentioned earlier earlier in section 3.5.1. The raw data for this model was obtained from the structured questionnaire, which is based on 83 responses.
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Table 4.3.1: Customer satisfaction index using MnCSI Cellular Network MnCSI value Irre Irresp spec ecti tive ve of cell cellul ular ar 52.2
Description Fair
network Vodafone O2 T-Mobile / Orange 3-Mobile
Low Fair Fair Fair
46.3 54.8 51.5 51.3
The table 4.3.1 indicates the satisfaction index for all the four mobile service providers (Vodafone, O2, T-Mobile / Orange and 3-mobile) and also index for the total total samp sample le pop popula ulati tion on witho without ut respec respectt to whic which h netwo network rk the the sub subscr scrib iber er has subscribed to.
Firstly, Firstly, for all the mobile networks together the MnCSI value is 52.2, which is represented represented as ‘Fair’ as it is above the satisfactory index of 50. This result shows that in gene genera rall the the cust custom omer er sati satisf sfac acti tion on in the the UK’s UK’s cell cellul ular ar tele teleco com m marke arkett is substantially fair.
Secondly, The MnCSI value for Vodafone, O2, T-Mobile / Orange and 3Mobile 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-Mobi T-Mobile le / Orang Orangee and 3-Mobi 3-Mobile le.. Th Thee custom customer er satisf satisfac acti tion on index index gives gives the 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: The descriptive statistics for all three dimensions is mentioned below: 43 | P a g e
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Table 4.3.2.1a: Descriptive-statistics Descriptive-statistics of DD, ED and OCS One-Sample Statistics
N
Mean
Std. Deviation
83
2.98
1.126
.1 2 4
expectation 83
2.96
1.234
.1 3 5
D es i re
OCS
N
Mean
Std. Deviation
83
3 . 33
1.138
Std. Mean
Std. Mean .125
Error
Error
The details of this descriptive statistics is available in Appendix-E and the table 4.3.2.1a indicates 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
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Table 4.3.2.1c: Customer satisfaction rating irrespective of cellular network
1 12 15.7 7.2
DD ED OCS
2 18.1 19.3 18.1
3 39.8 28.9 22.9
4 20.5 25.3 38.5
5 9.6 10.8 13.3
In the fig 4.3.2.1b the x-axis indicates the measurement models: Desire Disconfi Disconfirma rmatio tion(DD n(DD), ), Expecta Expectatio tion n Disconfi Disconfirma rmation tion(ED (ED)) and Over-al Over-alll Custome Customer r 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. 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 Applying ED measure measure we could assess that 15.7% and 19.3% (a total of 35%) rated their satisfaction level as much worse than expected and worse than expected respectively. respectively. 28.9% of the respondents 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.
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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, one-sample t test is conducted to test their significance level. The result obtained from the test test is presen presente ted d in the the table table 4.3.2 4.3.2.1 .1d d below below and the descr descript iptiv ivee stati statisti stics cs is available in Appendix-E.
Table 4.3.2.1d: One-Sample T test for ED & DD irrespective of cellular network One-Sample Test
Test Value = 3 95% Confiden Confidence ce Interva Intervall of the Difference Mean t
df
Sig. (2-tailed) Difference
Lower
Upper
-.195
82
.8 4 6
- . 02 4
- .2 7
.22
expectation -. -.267
82
.7 9 0
- .03 6
- .3 1
.23
D es ire
The table 4.3.2.1d indicates indicates that, with the cut off point 3 the mean differences 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 more than the significance level of 0.05 and the upper limit of their confidence intervals provides a strong strong suppo support rt towar towards ds not rejec rejecti ting ng the the null null hypot hypothe hesis sis.. Th Ther erefo efore re with 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 that they were neither satisfied nor dissatisfied with the service delivery and 51.8% (38.5 + 13.3) rated that they 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, one-sample t test is conducted to test their significance level. The result obtained from the test is presented in the table 4.3.2.1e below.
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Table 4.3.2.1e: One-Sample T test for OCS irrespective of cellular network One-Sample Test
Test Value = 4 95% Confiden Confidence ce Interval Interval of Mean OCS
the Difference
T
df
Sig. (2-tailed) Difference
Lower
Upper
-5.401
82
.0 0 0
- .9 2
- .4 3
- .6 7 5
The table 4.3.2.1e indicates 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 it 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 UK’s 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, However, the overall satisfaction 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:
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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, one-sample t test is conducted to test their significance level. The result obtained from the test is presented in the table 4.3.2.2b below and the descriptive statistics is presented in Appendix-E.
Table Table 4.3.2. 4.3.2.2b: 2b: One One-Sa -Sample mple T test test to measur measuree OCS with with respec respectt to cellu cellular lar networks
One-Sample Test
Test Value = 4 Company df
Mean Sig. (2-tailed) Difference
Vodafon OCS -1.941 e
8
.0 3 8
O2
OCS -2.832
21
TMobile/ Orange
OCS -3.291
3-Mobile OC OCS -2 -2.364
t
95% Confiden Confidence ce Interval Interval of the Difference Lower
Upper
-.778
-1.70
- .1 5
. 01 0
-.682
-1.18
- . 18
32
.00 2
-.667
-1.08
- .2 5
18
. 03 0
-.632
-1.19
- .0 7
The Table 4.3.2.2b above shows that, having a cut off value 4, the mean differences for over-all customer satisfaction are -0.778, -0.682, -0.667 and -0.632 and their p-values are 0.038, 0.010, 0.002 and 0.030 for Vodafone, O2, T-Mobile / Orange and 3-Mobile respectively.
Thei Th eirr resp respec ecti tive ve p-va p-valu lues es show show that that all all of thei theirr mean mean sati satisf sfac acti tion on is significantly lesser than the cut off value 4 (as the p-value is less than 0.05 in all cases) and even all of their confidence intervals are negative, providing a strong supp suppor ortt to reje reject ct the the null null hypo hypoth thes esis is.. Th Ther eref efor ore, e, we can can conc conclu lude de with with 95% 95% confidence that, the customers of all the four service providers are 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.
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Table 4.3.2.2c: Mean satisfaction rating for Vodafone DD
ED
OCS
2.22
3 .1 1
3.22
Fig 4.3.2.2d: Satisfaction rating for Vodafone
Vodafone 5 4 3 Vodafone Mean Satisfaction
2 1 0 DD
ED
OCS
Thee table Th table 4.3. 4.3.2.2 2.2cc and the the fig 4.3.2. 4.3.2.2d 2d indic indicat atee the mean mean ratin ratings gs 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, one-sample t test is conducted to test their significance level. The result obtained from the test 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
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Test Value = 3 Company
95% Confidence Interval of the Difference
Vodafone
DD ED
t
df
Sig. (2-tailed)
Mean Difference
-2.800 .286
8 8
.023 .782
-.778 .111
Lower -1.42 -.79
Upper -.14 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 is 0.023 (less than 0.05) which implies that the mean is significantly lesser than the cut off value 3 which provides provides a strong support towards towards rejecting rejecting the null hypothesis. 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 customer’s 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 service providers. providers. There are many many inconsis inconsistenc tencies ies faced faced by its custo custome mers rs in term termss of softw softwar aree upd updat ates, es, proces processs delay delays, s, bad handof handoffs, fs, etc. etc. For For instance, Vodafone has still not attempted to take any measures to improve their servi service ce deli deliver very y stand standar ards, ds, as recent recently ly the compan company y has anger angered ed many many of its’ its’ customers because they failed to test the software updates before pushing it to the customers customers (Wattanajantra Wattanajantra,, 2010) Hence, 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 .3 2
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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 cust custom omer erss of O2 for for all all the the thre threee model odelss used used.. Th Thee mean mean rati rating ng for for desi desire re 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, one-sample t test is conducted to test their significance level. The result obtained from the test 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
O2
95% Confidence Interval of the Difference
DD ED
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t
df
Sig. (2-tailed)
Mean Difference
.370 .678
21 21
.715 .505
.091 .182
Lower
-.42 -.38
Upper
.60 .74
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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. 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 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 4.3.2.2a states that still the customers customers 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
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T-Mob -Mobiile/ Orang ange 5 4 3
T TMobile/Orange Mean Satisfaction
2 1 0 DD
ED
OCS
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, one-sample t test is conducted to test their significance level. The result obtained from the test 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
Test Value = 3 Company
95% Confidence Interval of the Difference t
df
Sig. (2-tailed)
Mean Difference
Lower
Upper
TMobile/
DD
-.297
32
.768
-.061
-.48
.35
Orange
ED
-.415
32
.681
-.091
-.54
.36
The mean differences for DD and ED are -0.061 and -0.091 respectively 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, significant, the corresponding upper limits of the confiden confidence ce interva intervals ls are positiv positivee (0.35 (0.35 and 0.36), 0.36), providin providing g a strong strong supp support ort to
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consider the null hypothesis. Hence, we can conclude with 95% confidence that, the custo custome merr sati satisfa sfact ctio ion n for T-Mo T-Mobi bile le / Oran Orange ge is at least least equal equal to the custo custome mers’ rs’ 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 customers 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
3.05
2.74
3.37
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, one-sample t test is conducted to test their
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significance significance level. The result obtained from the test is presented in the table 4.3.2.2m 4.3.2.2m below and the descriptive descrip tive statistics is presented pr esented in Appendix-E.
Table 4.3.2.2m: One-Sample T test to measure DD & ED for 3-Mobile
Test Value = 3 Company
3-Mobile
95% Confidence Interval of the Difference
DD ED
t
df
Sig. (2-tailed)
Mean Difference
.2 1 3 - .9 2 5
18 18
. 8 34 .3 67
.0 5 3 -.263
Lower
Upper
- .4 7 - .8 6
.57 .33
For 3-Mobile, the mean differences for DD and ED are 0.053 and -0.263 with pvalues 0.834 and 0.367 respectively. respectively. For DD measure, measure, the mean is significantly more than the cut off value 3, providing a strong support to consider the null hypothesis. hypothesis. In the case of ED measure the mean difference of -0.263 is not significant significant but however, the corresponding upper limit of the confidence confidence intervals is positive (0.33), providing a strong support to not to 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 the customers are not satisfied with the overall service quality provided by their network.
Though the services provided by O2, T-Mobile/Orange and 3-Mobile is at least equal to customer’s 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 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 55 | P a g e
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said ‘I need more call minutes and don’t need texts, but there is no plan where I can reduce reduce the text limit limit and increase increase the call call limit limit for the same amount I pay’ pay’ and the other said ‘I don’t need minutes and all I need is Data, but I have a plan where I pay unnecessarily for minutes which I don’t use’. The service providers don’t 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 p rovider has a 4G service. service .
The second hypothesis and its sub hypotheses are tested as per the procedure shown in section 3.5.5b in order to find the relationship between disconfirmation models mod els and Overall Overall satisfac satisfactio tion n measure measure. The detaile detailed d results results of this this regressi regression on analysis are presented in Appendix-G.
Table 4.3.2.2n: Result of regression analysis for Disconfirmation models
Unstandardized Co-efficients Models Beta
M1 (constant) DD ED
M2 (constant) DD 56 | P a g e
R
R²
Std Error of the Sig. F-Test Estimate
.9 2 8
.8 6 1
. 4 29
.652 .377 .563
.000 .000
.9 1 0 .587 .910
.8 2 9
. 4 74 .000
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M3 (constant) ED
.9 2 0
.8 4 7
2010
. 4 48
.810 .920
.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 it is significant as the P-value is also less than 0.05, 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 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 affec t the over-all customer satisfaction. s atisfaction.
Firstly, in model 1, the R (0.928) indicates that there exists a strong relationship between desire disconfirmation, expectation disconfirmation and over-all over- all satisfaction. satis faction. The R² (strength of the relationship): 0.861 shows that variations of about 86% in over-all customer satisfaction satisfaction are caused/explained caused/explained by DD & ED collectively. collectively. Hence we can concl conclude ude with with 95% confi confide dence nce that that desire desire disco disconfi nfirm rmat ation ion mo model del and and expectation disconfirmation model together impacts OCS significantly. The results of disco disconfi nfirm rmati ation on mo model delss for all all the the netwo network rk opera operator torss were were at least least equal 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 satisfaction level for disconfirmation 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 .
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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 UK’s cellular networks. So priority must be given to customers’ expectations than their desires. There Th erefor fore, e, all the servi service ce provid providers ers mu must st aim at deter determi mini ning ng what what exact exactly ly the 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-Sample T test is used to verify the significance of the mean differences. In this case, null hypothesis (H0) states that the customer satisfaction level is least equal to his/her expectation and the alternative hypothesis (H1) states that the customer satisfaction level is worse or much worse than their expectation. expectation. The results of this test are presented presented in Table 4.4a and it is tested as per the procedure presented in section 3.5.5c .
Table 4.4a: One-Sample T test for all the SERVQUAL dimensions
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One-Sample Test
Test Value = 3 95% Confiden Confidence ce Interval Interval of the Difference t
df
Mean Sig. (2-tailed) Difference
TN1
3.933
82
. 0 00
. 42 2
.2 1
.6 3
TN2
2.356
82
. 0 21
. 26 5
.0 4
.4 9
TN3
1.694
82
. 0 94
. 20 5
- .0 4
.4 5
RE1
5.524
82
. 0 00
.53 0
.3 4
.7 2
RE2
-3.484
82
. 0 01
- .4 1 0
- .6 4
- . 18
RE3
-2.373
82
. 0 20
- .2 8 9
- .5 3
- . 05
RP1
1.504
82
.1 3 7
.1 6 9
- .0 5
. 39
RP2
- .0 9 4
82
.9 26
- . 0 12
- .2 7
.2 4
RP3
-5.477
82
.0 0 0
- .6 1 4
- .8 4
- .3 9
EP1
.366
82
.7 1 5
.0 4 8
- .2 1
.3 1
EP2
2.556
82
.0 1 2
.3 2 5
.0 7
. 58
EP3
1.228
82
.2 2 3
.1 4 5
- .0 9
. 38
AR1
3.942
82
. 0 00
. 43 4
.2 1
.6 5
AR2
-1.341
82
. 1 84
- .1 6 9
- .4 2
.08
AR3
- .1 0 7
82
.9 1 5
- .0 1 2
- .2 4
.2 1
TQ1
-3.866
82
. 0 00
- .4 4 6
- .6 8
- .22
TQ2
1.341
82
. 1 84
. 16 9
- .0 8
.4 2
TQ3
3.203
82
. 0 02
. 32 5
.1 2
.5 3
CI1
1.341
82
.1 8 4
.1 6 9
- .0 8
. 42
CI2
1.706
82
.0 9 2
.1 9 3
- .0 3
. 42
CI3
1.454
82
.1 5 0
.1 6 9
- .0 6
. 40
VM1 -3.385
82
.0 0 1
- .3 9 8
- .6 3
- .1 6
VM2 1.382
82
.1 7 1
.2 0 5
- .0 9
. 50
Lower
Upper
Thee item Th itemss in the the tabl tablee 4.4a 4.4a are are indi indica cato tors rs of diff differ eren entt serv servic icee qual qualit ity y 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 much better than their expectation. Yellow represents those items in which the customer satisfaction level is at-least equal 59 | P a g e
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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 items in which either the mean difference difference or any one of their confidence confidence intervals 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
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12 10 8 12
6
Number of Item Items in in SERVQUAL dimensions
4
6
5
2 0 Better than than or or muchbetter better than expected
Equal to expectation
Worse Wor sethan / Much worse than expected
Therefore, we can conclude with 95% confidence that, the customer’s 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 its’ customers.
In order to find the importance of each of these dimensions as perceived by the custo custome mers, rs, they they were were also also asked asked to rate rate the impor importa tance nce of each each servi service ce quali quality ty dimension from their perspective (or point of view) on a five point likert scale. The values values ranged ranged from from ‘Leas ‘Leastt Im Impor porta tant’ nt’,, ‘Not ‘Not so impor importa tant’ nt’,, ‘Imp ‘Import ortant ant’, ’, ‘Very ‘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
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Descriptive Statistics
Std.
Std.
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 RELIABILITY 83 RESPONSIVENESS 83
2.76 3.93 3.98
1.100 1.124 .715
.121 .123 .079
EMPATHY ASSURANCE
2.98 3.40
.975 .855
.107 .094
83 83
Er r o r
In the table 4.4c, six dimensions have mean above ‘3’ and the remaining two have the mean below ‘3’. One-Sample T test is used in order to key out the important and unimportant dimensions dimensions with 0.05 as its significance level and 3 as its test-value. The results of this test are shown in the table 4.4d below. 4.4d below.
Table 4.4d: One-Sample T test for importance of service quality dimensions One-Sample Test
Test Value = 3 95% Confiden Confidence ce Interval Interval of the Difference t
df
Sig. tailed)
TECHNICAL QUALITY
11.871
82
.0 0 0
CORPORATE IMAGE
.283
82
VFM
17.886
TANGIBLES RELIABILITY
(2- Mean Difference
Lower
Upper
.928
.77
1.08
.7 7 8
.036
- .2 2
.29
82
.0 0 0
1.482
1.32
1.65
-1.996
82
.0 4 9
- .2 4 1
- .4 8
.00
7.521
82
.0 0 0
.928
.6 8
1.17
RESPONSIVENES 12.430 S
82
.0 0 0
.976
.82
1.13
EMPATHY
- .22 5
82
.8 2 2
- .0 2 4
- .2 4
.19
ASSURANCE
4.239
82
.0 0 0
.398
.2 1
.58
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The table 4.4d shows that all the dimensions dimensions are significantly 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 confidence intervals intervals include include a positive positive value and the other five 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 dimensions are perceived 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) is considered to be one of the most ost
import ortant
ser servic vice
qua quality
dimensio sions, ns,
whic hich
is
then
foll ollowed
by
Respo Responsi nsiven veness ess,, Tech Technic nical al Qual Quality ity,, Reli Reliabi abili lity ty,, As Assur suranc ance, e, Corpo Corporat ratee Im Image age,, Empathy and Tangibles. 63 | P a g e
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The satisfaction matrix displayed in Table 4.4f below is designed after a careful analysis of satisfied and dissatisfied dimension items of service quality in relation to the prioritized dimensions in order to analyze which of the items of service quality dimensions need more attention.
Table 4.4f: Satisfaction Satisfaction Matrix Better / Much
At-least equal to
Worse / Much
better than
expectation
worse than
VFM
VM2
expected V M1
Responsiveness
RP1, RP2
RP3
TQ2
TQ1
expected
Technical Quality
TQ3
Reliability
RE1
Assurance
AR1
RE2, RE3 AR2, AR3 CI1, CI2, CI3
Corporate Image 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 than expe expect cted ed (der (deriv ived ed from from Tabl Tablee 4.4a 4.4a), ), thre threee item itemss are are of high high degr degree ee of importance: TQ3, RE1 and AR1 while another three are considered to be of less importance: importance: EP2, TN1 and TN2. Hence, the focus on these particular attributes attributes could be shifted to those that are more significant but lacks attention.
Secondly, Secondly, out of the twelve dimension items that has CS at least equal to their expecta expectation tionss (derived (derived from Table 4.4a), 4.4a), six items items are consider considered ed very importa important: nt: VM2, RP1, RP2, TQ2, AR2 and AR3; while the remaining six items are of less
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importance: importance: CI1, CI2, CI3, EP1, EP3 and TN3. Hence the network providers need to maintai maintain n the same same service service delivery delivery standard standardss for these these attribut attributes es and eventua eventually lly 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 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 im portance and lacks attention by network providers
VM1 VM 1
How How eco econo nomi mica call is is the the call call cha charg rgee per per minu minute te? ?
RP3
Ability of the employees employees to communicate clearly clearly with the customers customers
TQ1
The ne network co coverage
RE2
Dependability and consistency consistency to resolve resolve customer issues (or complaints) complaints)
RE3
Ability to perform the service service request 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 collected in comparison 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, strategies, the hidden costs (fair usage guidelines, guidelines, starred conditions apply, etc) fuel the customers’ dissatisfaction. The incremental usage usage of Virtua Virtuall Network Networkss (MVNOs (MVNOs)) reasons reasons the signal signal and clarity clarity issues (Xln Business Community, 2010). Hence, there has to be some limits set for these MVNOs and gradually reduce their number in order to avoid capacity-crunch and by doing so even the switching attitude of the customers can be brought under control, as the cust custom omer er’s ’s may have have lim limited ited serv servic icee prov provid ider erss to choo choose se.. Howe Howeve ver, r, the the
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respon responsiv sivene eness, ss, depen dependa dabil bility ity and and consi consiste stency ncy facto factors rs are are with with respe respect ct to the particular network and still no network operator operato r has very satisfied satisfie d customers on those factors.
5. Summary & Conclusion
Thee main Th main purp purpos osee of this this diss disser erta tati tion on was was to measu easure re the the leve levell of cust custom omer er satisfaction with regards to service quality delivered by the UK’s MTNs with and without without respect to which which network network customer customer subs subscrib cribes es to; via four models: models: The MnCSI MnCSI mo mode del, l, Disco Disconfi nfirm rmati ation on mo model delss (Desi (Desire re & Ex Expec pectat tation ion)) and OverOver-al alll Custome Customerr satisfac satisfactio tion n mod model el that that was developed. developed. This This dissert dissertati ation on examine examined d the customer’s 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:
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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 custome customer’s r’s desire desire and expectatio expectation n but one model (OCS) (OCS) pointed pointed out that customer’s are dissatisfied. So considering the results of all the four models, we can conclude that customers are neither satisfied nor dissatisfied with the service quality delivered by cellular networks in the UK.
•
With With respe respect ct to cellu cellula larr netwo networks rks,, for the the custo custome mers rs of Vodaf Vodafone one,, their 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.
•
Thee OverTh Over-al alll custo custome merr satisf satisfac acti tion on has been been rated rated as dissa dissati tisfi sfied ed by the the customers of all the four networks. The ratings obtained are approximately same for all the four companies.
•
Regarding Regarding Customer-Satisf Customer-Satisfaction action with various service 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 customer’s 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 following five items as dissatisfied: RE2, RE3, RP3, TQ1 and VM1.
•
According to the customer’s 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.
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Most of the service quality dimension items which have been rated ‘satisfied’ by the customers cus tomers are a re less important to them, the m, while most of the service se rvice quality q uality dimension items which has been rated dissatisfied are more important to them.
•
Both the disconfirmation disconfirmation models (Desire and Expectation) Expectation) collectively impact OCS. However, ED impacts OCS stronger than DD in the UK’s cellular networks.
•
A significance matrix was developed to gather data on the most important dimensions dimensions that the respondent’s perceive and lacks attention from the service providers in the UK. It is found that some items under the ‘Value for Money’, ‘Resp ‘Respons onsive ivenes ness’ s’ and and ‘Tec ‘Techni hnical cal Qual Quality ity’’ are are highl highly y value valued d high high by the customers but the network providers have failed to achieve them.
Conclusion
The mobile networks in the UK must acquire superior measures to increase the quality of service in order to gain competitive advantage. The level of customer satisfaction delivered by the mobile networks in the UK is considerably low and not up to the mark. The process of amending the service 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 desire and expectat expectation. ion. The mean mean score score just meets the thresho threshold ld and signifi significant cant improvements have to be made on certain areas. As a result, it is highly essential for all the cellular cellular network network providers providers to underst understand and how the custome customers rs estimat estimatee the quality of services. This research has identified five key attributes of service quality
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which are considered to be of high importance by the customers and lacks attention from 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 dissertation has primarily measured and analyzed the customer customer satisfaction level with service quality in the UK’s cellular networks. Hence it is recommended that future research could:
•
Analyze customer customer satisfaction satisfaction in particular particular service areas such as Internet Services, Services, Video calls, SMS, MMS and other value added services.
•
Comp Compare are custo custome merr satisf satisfac acti tion on level level and and Serv Service ice quali quality ty with with the curre current nt 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.
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