elk asia pacific journal of marketing and retail ......hotel services in bhubaneswar. this framework...

ELK ASIA PACIFIC JOURNAL OF MARKETING AND RETAIL MANAGEMENT

ISSN 0976-7193 (Print) ISSN 2349-2317 (Online) Volume 3 Issue 4 (2012)

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STUDY ON UNDERLYING KEY DIMENSIONS OF CUSTOMER PERCEPTION OF

SERVICE PROVIDED BY THE HOTELS IN BHUBANESWAR, ODISHA

Subrat Kumar Panigrahi

Lecturer in Marketing.

Rajdhani College of Engineering and

Management,

Bhubaneswar, Odisha

Subhashree Padhy

Lecturer in Marketing,

Rajdhani College of Engineering and

Management,

Bhubaneswar,Odisha

ABSTRACT

Keywords: Service Quality, Perception, Customer Satisfaction, SERVQUAL

Introduction:

Quality in service sustains the customer’s confidence and is essential for a competitive advantage.

Fulfilling the customer’s expectation by providing quality services forms a strong foundation for customer loyalty

and positive word-of-mouth advertisement about the service provider. Yet many companies are struggling to

improve the service quality, thereby wasting money on ill-conceived service management systems which lead to

customer’s dissatisfaction.

Providing an outstanding service quality is a strategy that is often utilized by marketers of hotel Industry.

Achieving a sustaining competitive advantage is a critical aspect to succeed in the market place. The decision

process of a customer starts when he/she recognizes a need for a specific product or service, in this case services

offered by a hotel. The need for a hotel service can be motivated by various reasons including tourism, business

deals, business entertainment and leisure. Services are “experiences”, and as such are more difficult to evaluate

before their consumption or purchase. If service expectations are met or exceeded, there is satisfaction; if experience

is below expectation, it leads to dissatisfaction. Achieving customer satisfaction allows increasing levels of

purchase repetition and loyalty.

Objectives:

en customer perception and overall customer satisfaction.

Research Hypothesis

Ha: There is a positive relationship between the level of customers’ perception on overall service provided by the

hotel and their level of satisfaction.

This study makes an attempt to provide a framework for assessing customer’s perception towards

hotel services in Bhubaneswar. This framework would enable managers to determine which dimension of

customer service has the greatest impact and how these dimensions are related to each other. Principal

Component Analysis has been used to find out the variables which are responsible for the choice behavior

of customer for hotels in Odisha. The result showed that “tangibility”, “accessibility”, “reliability”,

“promptness”, “response”, “security”, “assurance”, and “empathy” are the major dimensions of the

customers’ perceptions towards the service provided by the hotel. Moreover, it has been identified that

there exist a positive relationship between the overall customers’ perception toward the hotel service and

the customer satisfaction level.

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Literature Review:

As many industry sectors get matured, the individual businesses face increased competition; and so high

quality service has become an important weapon for gaining competitive advantage. Few would deny that

customers have become increasingly sensitized to service quality in the recent years (Lee & Hing 1995). The

hotel industry in India is certainly not exempt from either growing competition or rising customer expectations.

As the Indian tourism sector is getting more international exposure, the local and foreign customer expectations

regarding the luxury of five star hotels are increasing. Apart from the country’s beautiful natural environment,

the warm welcome of the local population and tourist souvenir is deeply influenced by the type of service that

they receive from the hotel where they lodge. Therefore hotels should strive for delivering quality service to

ensure customer satisfaction, which in turn ensures survival and profitability (Fowdar 2007). It is evident that

when customer’s perception of service quality is positive, the behavioral intentions are favourable, which

strengthens their relationship with the organization (Zeithml & Bitner 2003). On the other hand, when service

quality assessments are negative, the customer’s behavioral intentions are unfavorable (Kouthouris and

Alexandris 2005).

Quality refers to the ability of product or service to consistently meet or exceed customer expectations.

Stevenson (2002) and Schoenberger (1990) found twelve dimensions that customers associate with quality

products and services. These are: conformance to specification, performance, quick response, expertise, features,

reliability, durability, serviceability, aesthetics, perceived quality, humanity, and value. For the success of any

service organization, quality is a critical and of paramount importance to service providers (Bebko 2000), as

service is the intangible outcome of a tangible or intangible process. Service is becoming a commodity and quality

is becoming more critical in service organizations. That is why it can offer a source of competitive advantage

(Chowdhury, Iqbal & Miah 2010).

Quality and customer service have been identified as critical strategic issues for the organizations

(Donelley et al, 1995). As Wang, Lo and Hui (2003) mentioned, delivering quality service is essential for gaining

competitive advantages. A customer’s experience with individual service encounters affects his

satisfaction/dissatisfaction with the overall service experience (Johnston, 1995). Research has demonstrated the

strategic benefits of quality in contributing to market share and ROI, as well as lowering manufacturing costs and

improving productivity (Anderson and Zeithml, 1984; Garving, 1982). That is why delivering superior service

quality is a prerequisite for success and survival in today’s competitive business environment (Gilbert & Wong

2002).

The SERVQUAL measurement model (Parasuraman et al. 1988) is based on five dimensional model of

Service Quality. ‘Reliability’ refers to delivering on promises, ‘Responsiveness’ means being willing to help the

customer, ‘Assurance’ refers to inspiring trust and confidence in customers by the employees of the service

provider, ‘Empathy’ means treating customers individually, while ‘Tangible’ represents the physical aspects of

service. The questionnaire has been designed based on these dimensions.

Service quality, which refers to the quality of service delivered to the customers, has gained importance

in the light of increasing customers’ estimation and changing customer preference. External service quality

offered to customers is generally referred to as service quality. Providing high quality service enhances customer

retention rates, helps to attract new customers through positive word of mouth advertising, increases productivity,

leads to higher market share, and financial performance. Researchers have identified different dimensions to

measure External Service Quality (ESQ). Garnin (1984) measured the ESQ with the help of performance,

features, reliability, conformance, durability, serviceability, aesthetics and prestige. Driver and Johnson (2001)

estimated the ESQ with different dimensions namely alternativeness, care, courtesy, flexibility, reliability,

competence, integrity, access, availability and functionality.

Vanniarajan, Prabadevi and Shankari (2008) in their study on “Relative importance of servqual dimensions

in Indian service sector” threw light on the following findings: Reliability, responsiveness and Tangibility are

found to be most important servqual dimensions in hotel industries, whereas in banking industries Reliability and

Responsiveness are found the most important. The customers in the insurance sector treated all servqual




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dimensions in an equal manner. Reliability, Tangibility and Responsiveness are considered as the vital

SERVQUAL dimensions in the transport sector. In the education sector, Empathy is said to be the key servqual

dimension. Madhaviah (2007) in his empirical study evaluated the pros and con of the three SERVQUAL

models, namely, Perception minus Expectation model, the Ideal point model and the Performance based model,

and suggested the need for the development of an enhanced model for measuring service quality. Customers

in developing economies consider “technological factors” of service such as core service and systematization

of the service delivery as the key parameters in differentiating good and bad service while the “human factors”

appear to play a lesser role in discriminating.

Research Methodology:

For this research, a scale with 21 items was developed based on the relevant literature review. Of those,

two items were used to measure the satisfaction of customers and the remaining were to access the dimensions

of perception of customer on the service provided by the hotels. The researchers have adopted and modified

several dimensions of SERVQUAL, proposed by Parasuraman et al. (1988) such as Security and Promptness to

fit the settings of changing scenario of hotel industry.

A pretest of the questionnaire was conducted to assess the content validity of measurement scales. Content

validity can be evaluated by a panel of persons who judge whether a scale logically appears to reflect accurately

what it seeks to measure. Based on their suggestions, two scale items were re-worded because they contained

ambiguous meaning.

The final survey questionnaire consisted of 21 scale items out of this first 19 items were to measure

consumer’s perceptions of the service provided by the hotels and rest two items were to measure overall

perception and satisfaction. The first 19 items were related to 7 dimensions on perception of service

(promptness, accessibility, security, reliability, assurance, empathy and tangibility). The respondents were

requested to select the response that best indicates their experience on each statement, using 7 point Likert scale,

where 1 indicated strongly agree and 7 indicated and strongly disagree. Each question also allowed the

respondents to check “not applicable” if necessary.

Principal Component Analysis, Kaiser-Meyer-Olkin, Bartlett’s test of sphericity, Spearman Coefficient

of Correlation were used as statistical tools for the study. The data were analyzed using SPSS 16.0. Descriptive statistics

Classification Numbers Percent

Gender (n=50) Male 29 59 Female 21 41

Age 20-30 1 2

30-40 17 34

40-50 25 50

50 and above 7 14

On average, how often do you use to stay in hotel in a month

Once a month 23 46

Twice a month 11 22

Thrice a month 11 22

More than three times 1 2

+ Four Executives

The respondents in our study were

1. People who spend at least one night in any of the three hotels namely, Hotel Trident Hilton, Hotel Swasti




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Plaza, Hotel Crown in last three months.

2. Four executives of the hotel who were serving in these hotels for last 1 year.

The survey questionnaires were distributed to 62 respondents through email out of which 50 usable

questionnaire were collected. Resulting 80% of the response rate. The demographic characteristics of the

respondents are summarized in the above table.

Data Analysis: Table on correlation matrix (Table-1) provides all inter item correlation coefficients. This table contains

all Pearson coefficients of correlation between all pair of variables. On scanning the correlation coefficients it is

found that maximum of the correlation coefficient is more than .30 which is desirable to conduct factor analysis.

So there is no singularity in the data. The determinant value of the data is 5.271E-04 (which is 0.0005271) which

is greater than the necessary value of 0.00001. Therefore multi-co linearity was not a problem for the data in our

study.

Table for communalities (Table-2) shows the list of communalities of variables before and after extraction.

Principal component analysis works on the initial assumption that all variance is common; therefore before

extraction the communalities are all 1. 81.3% of variance is explained by the underlying factors.

KMO and Bartlett's Test (Table-3) shows Kaiser-Meyer-Olkin measure of sampling adequacy and

Bartlett’s test of sphericity. Here the value is .612 which is nearer to 1. It indicates that patterns of correlations

are relatively compact and so factor analysis should yield distinct and reliable factors. Bartelett’s measure tests

the null hypothesis in our study that the original correlation is an identity matrix. The significant test tells us

that the R matrix is not an identity matrix. (P-value <.05). Therefore there are some relationships exist among

the variables which we have included in the analysis. So factor analysis is appropriate.

Total variance table (Table-4) lists the Eigen values associated with each linear component before

extraction, after extraction and after rotation. Before extraction, SPSS has identified 19 linear components within

the data set. The eigenvectors associated with each factor represent the variance explained by that particular linear

component. It is clear from the Table-4 that first seven factors explain relatively large amounts of variance. Here

the factors whose Eigen value are greater than 1 are taken into consideration, and subsequent factors with only

small amount of variance are left. Before rotation factor 1 accounted for considerably more variance than the

remaining six (19.18% compared to 214.35%, 10.17%, 8.45%, 8.05%, 6.68%, 5.30%), however after extraction

it accounts for only 13.37%.

The first factor “tangibility” accounted for the largest proportion (19.18%) of the total explained

variance. So it was considered the most important factor. This factor was defined by 3 scale items related to

availability of modern equipments like internet, gym etc, visually appealing physical facilities, well dressed

employees. The second factor “accessibility” explained 14.35 percent of total variance. It was constructed by

again 3 scale items like access of the hotel, exact location and booking options. The third factor “Reliability” has

explained 10.17 percent of total variance and was constructed by 3 scale items i.e., promise keeping, courtesy,

and problem solving approach. The fourth factor “Promptness” has explained 8.45% of variance. It includes

variables like individual attention, prompt response, and willingness to help. The fifth factor “Security” accounted

for 8.45% of variance. It includes the aspects of privacy and security, the sixth factor “Assurance” explains 6.68%

of variance. It includes the variables like knowledge of employ, quality of service, confidence of customer. Finally

the 7th factor which explain least variance (5.30%) has included only one variable i.e, individual attention given

to the customer.

Spearman coefficient of correlation (Table-5) between customer perception and overall satisfaction

shows customer satisfaction level is positively correlated with the overall perception score which is significant.

(The correlation coefficient was 0.885, p<0.01). Figure 3 provides a scatter diagram which shows a positive

relation between customer perception and overall satisfaction.

The component matrix before rotation matrix (Table-6) contains the loadings of each variable onto each




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factor. There are less than 30 variables and average communalities is greater than 0.6. Therefore according to

Kaiser’s criterion SPSS extracted 7 factors.

Rotated component matrix (Table-7) shows the loading which is highest among all the factors for each

variable are retained. Here varimax rotation has been adopted which is requested through SPSS. The variables are

listed in the order of size of their factor loadings because we asked for the output to be sorted by size.

Deciding the no of factors:

The no of factors are also confirmed from the Scree plot diagram (figure-1). Which is the most reliable

technique (Hair, Black, Anderson, 2007)? Here the point of inflection starts after 7 points from left upper end

corner. The curve begins to tail after 7th point. So it is justified to retain only 7 factors.

Findings of the study:

The first issue addressed in this study was the key dimensions of customer perception of service, provided

by the hotels. The analysis identified total of 7 dimensions namely “Promptness” “Response”, “Accessibility”,

“Security”, “Reliability”, “Assurance”, “Empathy” and “Tangibility”. All the dimensions have their own unique

characteristics inherent in the respective environment.

First of all, the “Tangibility” dimension refers to the service variants which the customers can touch and

feel. This study reveals a great importance attached to this factor. Customer apparently wants to have the

sophisticated technology attached to their reach. They perceive some sort of superiority if these facilities are

available inside the hotel. Customers prefer cleanliness and neatly dressed employees.

In addition, hotel customers from outside the state or country face problems in reaching the hotel. The

easy way of communication is preferably through website, newspapers, magazines etc. Thus it is recommended

that hotels adopt the CRM service that handles queries from various channels.

Customers expect the hotel management to respond promptly to their queries, especially regarding foods,

locations, tourist places etc. another important facet of prompt responses is related to courtesy of the staff while

answering the queries of the customer. In India “Atithi Devo Vaba” is a proverb which says that guests should be

treated as god. So the kind of service inside the hotel should replicate the meaning. The time period to cater a

service should tactfully maintained keeping the customer personality in mind. There should be a willingness to

help the customer which should be reflected by the employees.

Nowadays the security has become an important threat for hotel customers. The customers are conscious

about their security. Though Odisha is not sensitive as compared to other states where some unusual threats are

encountered, the hotels need to show their sensitiveness towards security. Another facet of security is privacy.

Some customers are more sensitive towards maintaining their privacy inside their rooms which should be taken

care. The lack of security should not be a stumbling block in the growth of hotel industry now days.

Limitations and future Research Directions

Although there are notable contributions of this study especially for customer retention strategies, the

results of this study need to be viewed and acknowledged in the lights of its limitations. First, the sample size

was considerably low. Moreover, the study considers only the three prime hotels of Bhubaneswar City. Therefore,

future research should be conducted on a larger scale by considering a large sample size form all over Odisha to

authenticate the dimensions of customer perception toward the service received by the hotels. In future, other

variables i.e. Employee satisfaction, customer loyalty, customer retention should be included in the study to

validate the importance of service quality in the hotel industry in Odisha.

Conclusion:

With unlimited access to the information hotel customers have wide range of choices in selecting the

best hotels and services. Therefore, it is not easy for the hotels to gain and sustain competitive advantage based

solely on a cost leadership strategy in rival driven industry. Rather, the subtle difference in level of service quality




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increasingly become a key driving force in enhancing customer’s satisfaction and in turn expanding their customer

base. The finding of this study confirmed that there is a strong and positive relationship between the customer

perception and their level of satisfaction.

Service quality improvement initiatives should begin with defining the customers needs and

preferences. If hotels understand the dimensions of quality service, they can take appropriate actions to monitor

and enhance performance on those dimensions and remedy service failures. In order to maintain a high level of

overall service quality, the hotel should pay attention to all seven dimensions identified in this study. However

to strengthen competitiveness in the extremely competitive market, given limited organizational resources, it is

recommended that the hotels to focus particularly on four dimensions that is “Tangibility”, “Promptness”,

“Response”, “Accessibility” and “Reliability”.

More specifically, it is found the following managerial implications. First, the “Tangibility” dimension

indicates that the hotel customers seek sophisticated physically facilities. The failures of the hotel in delivering

the service in a timely manner often result from lack of up to date information regarding the facilities. Therefore

it is recommended that the hotels should integrate all the information available in the market and improve their

delivery performance.

References:

1) Anderson C., & Zeithaml, C 91985). Stage of Product life cycle, Business strategy and Business Performance, Academy of Management journal, 27 (March), 5-24

2) Bebko, C.P (2000), Service Intagibility and its impact of customer expectations of service quality.

Journal of Services marketing., 14(1), 9-26

3) Chowdhury, A.H.Iqbal, M.T., & Miah, M.K. (2010). A study of service quality Determinants of Private

Universities in Bangladesh using SERVQUAL. Journal of Knowledge Globalization, 3(1), 49-74.

4) Donnelley, M. Wisniewski, M. , Darlymple, J.F., &Corry A.C. (1995). Measuring Service Quality in

Local Government; The SERVQUAL Approach. International Journal of Public Sector Management,

8(7), 15-20.

5) Driver, C. and Johnson, R. (2001), “Understanding Service Customers – The value and hard and soft

attributes”, Journal of Services Research Vol. 4, No.2, pp. 130-139.

6) Fowdar, R.R.R. (2007). Developing a service quality questionnaire for the hotel industry in Mauritius

journal of vacation marketing, 13(1), 19-27.

7) Garvin, D. (1982). Quality of the line. Harvard Business Review, 61 (September – October). 65-73.

8) Gilbert, D., & Wong, R.K.C. (2003). Passenger expectations and Airline services: A Hong Kong based

study. Tourism Management, 24, 519-532.

9) Hair, Jr. J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2010) Multivairate Data Analysis, Edition , Mc

Graw Hill

10) Johnston, R. (1995), “The zone of tolerance: exploring the relationship between service transactions and

satisfaction with the overall service”, International Journal of Service

11) Industry Management, Vol. 6 No. 2, pp. 46-61.

12) Kouthouris, C. & Alexandris, K. (2005). Can Service Quality Predict customer satisfaction and

behavioural intentions in the sport tourism industry? An application of the SERVQUAL model in an

outdoor setting. Journal of Sport tourism, 10(2), 101-111

13) Lee, Y.L., & Hing, N. (1995). Measuring Quality of restaurant operations: an application of the

SERVQUAL instrument. International journal of Hosptiality Management, 14 (3/4), 293-310.

14) Madhaviah, C. (2007), “SERVQUAL measurement – A Critical review of selected models”, Synthesis,

Vol. 4 No1.

15) Parasuraman, A. Zeithmll V.A. and Berry, L. (1998), “SERVQUAL: A multiple item scale for measuring

customer perceptions of service quality” . Journal of Retailing Vol. 64. Mp 1. Pp 12-40




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16) Schoenberger, R.J (1990). Building a chain of customers Newyork: Free Press

17) Stevenson, W.J (2002). Operation Management. New York: Mc Grawhill/Irwin.

18) Tabassum, T. ,Rahman, T.; “An analysis of service Gap of luxurious hotels in Bangladesh using

SERVQUAL Model”; JM International Journal of Marketing Management. Vol-1, Issue V, PP 14-20.

19) Vanniarajan, Prabadevi P and Shankari L (2008), “Relative importance of servqual

20) dimensions in Indian service sector”, PES Business Review.

21) Wang, Y., Lo., H., & Hui, Y.V. (2003). The antecedents of service quality and product quality and their

influences on bank reputation; Evidence from the banking industry in china. Managing service quality,

13(1), 72-83

Annexure

FIGURE 1

SCREE PLOT:

FIGURE 2

3D PLOTS WITH RESPECT TO THE FACTOR SCORE




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FIGURE 3

CORRELATION SCATTER GRAM




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At the level of significance Alpha=0.050 the decision is to reject the null hypothesis of absence of correlation.

TABLE 1: Correlation Matrix

V1 V2 V3. V4. V5. VI5 V7. V8 Vg 1/10 V11 V12 V13 V14 V15 V16 V17 V18 V18

V1

11300 .058 .304 -.250 .271 .045 -.359 -.134 .085 -.150 -.008 -.024 .072 .0:35

-.104 .196 .073 -.085 -.280

V2. .058 11300 -.235 .340 -.285 - .188 .414 .286 -.120 .334 -.123 -.001 .360 .094 .236

.053 -.028 .219 .094

V3

.304 -.235 1.003 -.187 .639 .452 -.120 -.028 .240 -.255 -.042 .141 -.032 .C27 .038 .042

.306 -.143 -.005

V4

-.250 .340 -.187 11300 -.012 .018 .367 .291 -.103 .248 .151 .013 .14.0 .051 .454 .253 -.125 .146 .197

V5

.271 -.285 .539 -.012 11300 .398 -.090 -.049 .C63 -.078 .237 .348 -.025 .144 -.064 .149 .418 -.238 -.062

V6 .045 -.189 .452 .018 .389

1.00 -.014 -.286 .4:14 -.350 .015 -.105 -.253

.108 -.051 .080 .148 -.075 .101




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1.7

-.359 .414 -.120 .367 -.083

-.014 1.000 .348 -.294 .343 .125 .087 .300 .318 .118 .132 .123 .165 .125

va -.134 .285 -.039 .291 -.043 -.286 .348 11300 -.416 .637 .128 .167 .271 .227 .156 .236 .142 -.098 .013

Vg

.C85 -.120 .240 -.103 .053 .4:14 -.294 -.416 11300 ..4e2 -.118 -.113 -.228 .019 -.025 .025 -.047 .017 -.082

1/10

-.150 .334 -.255 .248 -.079 -.350 .343 .637 -.482 1000 .324 .295 .123 .038

.186 .028 .078 .032 -.041

V11 -.003 -.123 -.042 .151 .237 .016 .126 .128 -.118 .324 1.000 .534 .C69 .016 -.152 .378 .272 .112 -.117

V12

-.024 -.001 .141 .013 .348 -.105 .087 .167 -.113 .295 .534 1 DOD .132 .084

.027 .055 .189 .054 .138

V13 .072 .350 -.032 .140 -.025 -.253 .300 .271 -.223 .123 .059 .132 100) .301 .112 .120 -.0(6 .102 .030

V14

-.035 .034 .027 .051 .144 -.108 .318 .227 .019 -.033 .015 -.084 .301 1003 .124

.101 .264 -.177 -.124

V15 100 • -.104 .235 .030 .454 -.064 -.051 .119 .156 -.025 .185 -.152 .027 .112 -.124

0 .015 -.381 .256 .432

V16 -..1O5 -.063 -.042 .253 .149 .080 .132 .236 .025 .028 .378 .055 .120 1 01

•

.015 1.00 0 .268 .252 -.136

V17 .073 -.039 .306 -.125 .438 .148 .123 .142 -.047 .078 .272 .199 -.006 .264

.31 .258 10(0 -.105 -.202

V18 -.0E6 .219 -.143 .146 -.233 -.075 .165 -.096 .017 .032 .112 .054 .102 -.177 .255 .252 -.105 100) .016

V19 -.280 .034 -.005 .107 -.062 .101 .125 .013 ..082 -.041 -.117 .138 .030 -.124 .412

.136 -.202 .016 100)

TABLE -2

Communalities

Initial

Extrac

tion

The employees are never too busy to respond my request. 1.000 .813

The hotel gives customer individual attention. 1.000 .672

If I want I could easily contact a customer service representative any time. 1.000 .758

The quality of service I received was exactly the same as that I ordered. 1.000 .654

The website of the hotel showed me the exact location of the hotel. 1.000 .822




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The hotel offered multiple booking options. 1.000 .693

The management responded to my enquiry promptly. 1.000 .629

The physical facilities are visually appealing. 1.000 .722

The employees are well dressed and neat in appearance. 1.000 .569

The complementary modern equipments for supporting the hotel service for

adequate 1.000 .819

I feel secure inside the hotel 1.000 .742

I am confident that my privacy is been maintained inside the hotel. 1.000 .792

The employees give me prompt service. 1.000 .747

The employees are always willing to help me. 1.000 .726

When the hotel promises to do something by a certain time, it will do so. 1.000 .754

The employees instill confidence in customer. 1.000 .656

The employees are consistently courteous to customer. 1.000 .660

The employees have knowledge to answer customer's question. 1.000 .699

When a customer has a problem, the hotel will show a sincere interest in

resolving it. 1.000 .793

Extraction Method: Principal Component Analysis.

TABLE-3: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

. 6 1 2

Bartlett's Test of Sphericity Approx. Chi-Square

d f

S i g .

322.866

1 7 1

. 0 0 0

TABLE- 4: Total Variance

Com pone nt Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Varianc

e Cumula tive % Total

% of Varianc

e

Cumul ative

% Total

% of Varian

ce Cumul ative %

1 3.645 19.184 19.184 3.645 19.184 19.184 2.541 13.373 13.373 2 2.728 14.357 33.541 2.728 14.357 33.541 2.423 12.750 26.124

3 1.933 10.174 43.715 1.933 10.174 43.715 2.170 11.423 37.547




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4 1.607 8.459 52.174 1.607 8.459 52.174 1.757 9.245 46.791

5 1.531 8.059 60.234 1.531 8.059 60.234 1.713 9.017 55.808

6 1.270 6.684 66.917 1.270 6.684 66.917 1.693 8.909 64.717

7 1.009 5.309 72.227 1.009 5.309 72.227 1.427 7.510 72.227

8 .907 4.772 76.999 9 .776 4.083 81.082 10 .673 3.540 84.622

11 .586 3.085 87.707 12 .525 2.761 90.468 13 .435 2.290 92.758 14 .330 1.736 94.494 15 .283 1.491 95.984 16 .272 1.431 97.415 17 .206 1.085 98.500 18 .187 .984 99.483 19 .098 .517 100.000

Extraction Method: Principal Component Analysis.

TABLE- 5: Pearson coefficient of Correlation between customer perception and overall satisfaction

Correlations

Overall percept Overall satisfac

Overall percept Pearson Correlation 1 .816(*)

Sig. (2-tailed) . .025

N 50 50

Overall satisfac Pearson Correlation .816(*) 1

Sig. (2-tailed) .025 .

N 50 50

* Correlation is significant at the 0.05 level (2-tailed).

TABLE- 6: Component matrix before rotation Component

1 2 3 4 5 6 7

The complementary modern equipments for supporting the hotel service for adequate

.703 .252 -.160 -.203 -.293

.324

The physical facilities are visually appealing. .651 .340 -.106 .164 -.151 -.182 .297




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The management responded to my enquiry promptly. .626 .203 .150 .268 .269 -.149

The hotel gives customer individual attention.

.584 -.128

.369

.393 .155

The quality of service I received was exactly the same as that I ordered. .552

.480

.197

.280

The employees are well dressed and neat in appearance. -.550 -.137 .295

.337 .207

If I want I could easily contact a customer service representative anytime. -.490 .432 .395 .302 -.266

The employees are consistently courteous to customer. -.130 .760 -.135 .101 .165

The website of the hotel showed me the exact location of the hotel. -.373 .715 .329 .121 -.215

I feel secure inside the hotel .192 .610

-.537

.115 -.161

I am confident that my privacy is been maintained inside the hotel. .186 .515 .177 -.381 -.413

-.371

When the hotel promises to do something by a certain time, it will do so. .385 -.309 .642

-.254 .104 .127

When a customer has a problem, the hotel will show a sincere interest in resolving it. .218 -.294 .598

-.291 -.292 -.360

The hotel offered multiple booking options.

-.499 .167 .560

.214 -.107 .194

The employees are always willing to help me.

.142 .329 -.182 .607 .318 -.129 -.279

The employees instill confidence in customer.

.187 .414 .179 -.246 .583 .113

The hotel gives customers individual attention. -.375 .140 -.186 .233 -.392 .608 .202

The employees have knowledge to answer customer's question. .280 -.156 .234 -.324 .296 .589

The employees give me prompt service. .447 .164

.414

.364 -.462

TABLE -7: Rotated Component Matrix(a

Component

1 2 3 4 5 6 7




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……………………………………………………………………………………………………………………

The complementary modern equipments for

supporting the hotel service for adequate

The physical facilities are visually appealing.

The employees are well dressed and neat in appearance.

The website of the hotel showed me the exact

location of the hotel.

If I want I could easily contact a customer

service representative any time.

The hotel offered multiple booking options.

When the hotel promises to do something by a

certain time, it will do so.

When a customer has a problem, the hotel will

show a sincere interest in resolving it.

The employees are consistently courteous to

customer.

The employees give me prompt service.

The employees are always willing to help me.

The management responded to my enquiry

promptly.

The employees are never too busy to respond

my request.

I am confident that my privacy is been

maintained inside the hotel.

I feel secure inside the hotel

The employees have knowledge to answer customer's question.

The employees instill confidence in

customer.

The quality of service I received was exactly

the same as that I ordered.

The hotel gives customers individual

attention

.855

.814

-.638

.836

.802

.668

.814

.792

-.551

.779

.742

.519

.417

.851

.712

.701

.666

.504

.850

a Rotation converged in 18 iterations.


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