RELATION BETWEEN ZONE OF TOLERANCE AND ...2013/07/10 · The zone of tolerance (ZOT) is defined as “the difference between desired service and the level of service considered adequate”

Asia Pacific Journal of Marketing & Management Review__________________________________________ ISSN 2319-2836 Vol.2 (7), July(2013) Online available at indianresearchjournals.com

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RELATION BETWEEN ZONE OF TOLERANCE AND IMPORTANCE OF

SERVICE QUALITY ATTRIBUTES: AN EMPIRICAL STUDY

COMMERCIAL BANKS

HAVINAL VEERABHADRAPPA*; DR. SIRIGERI JAYANNA**;

UDAY KOKATNUR***

*PROFESSOR,

INDUSTRIAL AND PRODUCTION ENGINEERING DEPARTMENT,

R Y M ENGG COLLEGE, BELLARY, KARNATAKA, INDIA,

** PROFESSOR,

DEPT. OF MANAGEMENT STUDIES,

VSK UNIVERSITY, BELLARY, KARNATAKA, INDIA,

*** ASSOCIATE PROFESSOR,

KLE COLLEGE OF ENGINEERING, BELGAUM, KARNATAKA,

_____________________________________________________________________________________

ABSTRACT

In ever increasing intense competition, providing service quality is vital for banks to compete.

The of this study is to identify the service quality dimensions, establish the zone of tolerance

based on the minimum and desired service and to explore the relation between the height, width

of tolerance zone and the importance of service quality attributes. The responses from five

hundred customers of the commercial banks on perception of service quality, importance,

minimum and desired level of service of twenty two attributes of service quality are used to

identify the five dimensions of service quality. The height and width of tolerance zone are then

established. The study reveals that the perceived service with respect to all the service quality

attributes is within the tolerance zone. It is also observed from the study that there is positive

correlation between importance of service quality attributes and the height of tolerance zone,

negative correlation between importance of service quality attributes and the width of tolerance

zone

KEYWORD: Service quality, zone of tolerance, desired service, minimum service. _____________________________________________________________________________________

Introduction

Today‟s customers of banking services are more aware of quality than ever. The customers are

becoming more sophisticated in their needs and are increasingly demanding higher standard of

service. Service quality is defined as the conformance of services to the customer‟s specifications

and expectations. The customer lays the level of quality of services he expects and anything

below this is not acceptable. In simple words, he establishes a range of acceptable service

quality. This range is known as zone of tolerance.

The zone of tolerance (ZOT) is defined as the range of customer perceptions of a service

between desired as acceptable standards (Zathaml et al., 1993). It is the range of service

performance that the customer considers satisfactory. Performance above this zone is seen as

delighting and below this zone as dissatisfying. Customer may accept variations within this range


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of performance. Any decrease or increase within this area will have marginal effect on

perceptions. When performance moves outside this range, it will have real effect on perceived

service quality.

If a customer‟s zone of tolerance is wide, then the customer may be less sensitive to the service

experience, thus increasing the likelihood of a satisfactory or acceptable outcome. Conversely, if

a customer‟s zone is narrow, then he or she may be highly sensitive to the service experience,

with a greater likelihood of dissatisfying or delighting outcomes. That is to say, the width of the

zone of tolerance may vary from customer to customer.

The tolerance zone can be established by customer‟s expectations for a set of service attributes.

When service rendered effectively occurs, the customer evaluates the level of services received

or perceived, through his or her own expectations. Zeithaml and Bitner (2003), reported that

zone of tolerance is narrow for those attributes that the customers find more important. That is,

the more important the attributes are, the closer the limits of desired service (DS) and minimum

service (MS) while zone of tolerance is wider for those attributes which the customers find less

important as in figure 1. The tolerance zone height (Alt Z) is the average between the desired

service (DS) and minimum service (MS) for each attribute. The width of tolerance zone (Larg Z)

of an attribute corresponds to the difference between the level of desired service (DS) and the

minimum service (MS). Algebraically, for a sample size „n‟, the average values of Alt Z and

Larg Z can be computed as

(1)

(2)

Tolerance zone

Zone Height

Zone Height

Tolerance zone

Attributes More important Less Important

Minimum service

Desired service

Zone width

Minimum Service

service

Desired service

Zone width

Figure 1 Relation between Importance and Expectations

Source: Adopted from Zeithaml and Bittner (2003)

E

x

P

e

c

t

a

t

i

o

n


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Review of literature

SERVQUAL and SERVPERF Models

Measuring quality of services might be difficult because of intangible nature of services. The

most widely used models in service quality in the banking sector are SERVQUAL and

SERVPERF models. According SERVQUAL model, developed by Parasuraman (1985, 1988),

service quality can be measured as a difference between customer‟s expectations of the service to

be rendered and their perceptions of the actual performance of the service. SERVQUAL is based

on five dimensions namely Tangible, Reliability, Assurance, Responsiveness and Empathy. Each

dimension is measured by four to five attributes. Mathematically, Service quality is measured as

(3)

Where

SQi = Perceived service quality of individual „i‟

k = number of attributes / items

P = Perception of individual „i‟ with respect to performance of a service firm attribute „j‟

E = Service quality expectation for attribute „j‟ that is relevant norm for individual „i‟.

Several issues have been raised with regard to use of ( P – E ) scores. Most studies have found a

poor fit between service quality measured through Parasuraman, Zeithaml and Berry (1988)

scale and the overall service quality measured through a single-item scale (Babacus and Boller

1992, Babakus and Mangold 1989; Finn and Lamb 1991 and Spreng and Singh 1993). Though

the „gap scores‟ is conceptually sensible, the ability of these scores to provide additional

information beyond that already contained in the perception component of the service quality

scale is under doubt (Babacus and Boller 1992). Teas ( 1993, 1994) observed that a ( P – E ) gap

of „-1‟ can be produced in six ways: P=1, E=2; P=2, E=3; P=3, E=4; P=4, E=5; P=5, E=6; P=6,

E=7 and these tied gaps cannot be trusted as implying equal perceived service quality shortfalls.

Brown, Peter and Churchil (1993) found different scores being beset with psychometric

problems and, therefore, cautioned the use of (P-E) score. Cronin and Taylor (1992, 1994)


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challenged the gap score approach and developed the SERVPERF scale which directly captures

customer‟s performance perceptions in comparison to their expectations of the service encounter

which can be expressed mathematically as follows.

(4)

Where, P = Perception of individual „i‟ with respect to performance of a service firm attribute

„j‟.

Babacus and Boller (1992), Brady at al. (2002), also proved that SERVPERF is better alternative

than SERVQUAL. Jain and Guptha (2004), reported that SERVPERF was more strongly

correlated with overall service quality than SERVQUAL. Beerli et al. (2004), Wang et al.

(2003), Lee and Hwan (2005), Zahoor (2011), Mensah (2010) and Suleman (2011) reported that

SERVPERF is better alternative than SERVQUAL as it reduces the amount of data needed to

measure service quality. Since Service quality attributes are not expected to be equally important

across service industries, it has been suggested to include importance weights in the service

quality measurement scales. Hence the service quality is measured as:

(5)

Where Wij is the weighting factor, i.e., importance of attribute „j‟ to an individual „i‟

Though, on theoretical grounds, addition of weights makes sense (Bolton and drew, 1991), not

much improvement in the measurement potency of either scale has been reported after inclusion

of weights. Hence, the present study uses the un-weighted SERVPERF scale to measure the

service quality of banking services based on the perceptions of service.

Zone of tolerance

The zone of tolerance (ZOT) is defined as “the difference between desired service and the level

of service considered adequate” (Zeithaml et al., 1993). The ZOT model recognises that

consumer enter service encounters with different expectation levels, desired service is “the level

of service the customer hopes to receive and the adequate service is “the level the customer will

accept (Zeithaml et al., 1993). The difference between these two expectation standards is the

zone of tolerance. The customer satisfaction will result as long as customer perception of service

performance, fall in this zone of tolerance. Zeithaml et al., (1993) reported that ZOT varies

across customers and can expand /contract with the same customer. They also propose that

adequate service expectations are subject to change, while desired service expectations are

relatively enduring.

Poiesz and Bloomer (1991) proposed that the zone of tolerance can be used as unifying construct

between expectations, performance and outcomes. Johnston (1995) theoretically examined the

relationship between involvement and ZOT, as well as the impact of various service

performances out comes upon ZOT. He reported that “width of ZOT is inversely proportional to

the degree of involvement”. That is to say high involvement generates narrower ZOT, while low


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involvement generates a wider ZOT. Zeithaml et al., (1993) and Johnston (1995) propose that (i)

performance below the customers adequate expectations level (below ZOT) will generate

dissatisfaction, (ii) Performance within ZOT may go unnoticed by the customer, and (iii)

performance above the customers adequate expectations level (above the ZOT)will generate

“delight”, or what Zeithaml termed as a “Customer franchise”, It is important to note that

disagreement exists in whether perceived service quality should be measured using a

performance based frame work or with a standards (or norms) based framework. Teas and

Decarlo (2004) reported that performance based frame works specify perceived performance

without any comparative referents, while standard based frameworks specify a relative or

comparative performance conceptualization of perceived quality. Parasuraman et al., (1994)

from his study of 3069 customers, urged that norms-based (such as ZOT) would be more useful

because of the measurement of more precise information about customer perceptions across the

multiple expectation levels. Teas and Teas and Decarlo (2004) in their study of student‟s

perception of a university found that performance based models offered more explanatory power

than ZOT regarding the relationship between perceived quality and purchase intensions. They

also found that ZOT offered superior performance when evaluating the linkage between

perceived quality and satisfaction. They provided support for the ZOT as a useful managerial and

research tool for better understanding how customer perceptions of quality impact satisfaction

with service?

Walker and Baker (2000), proposed that the width of ZOT varies for essential versus less

essential service quality components, They also reported that the width of ZOT would be

influenced by the degree of customer experience with the service, as well as the number of

competitive alternatives the customers perceived. They found that ZOT is narrower for

experienced customers „because they have increasingly demanding expectations‟. In addition

Walker and Baker (2000) found no support for Zeithaml et al., (1993) proposition that the

presence of readily available alternatives would narrow the ZOT. Walker and Baker (2000)

attributed this finding to the stability of the desired expectations standard. Sachdev and Verma

(2004) conducted study on banking, insurance, fast food and beauty-saloon services. They found

that in case of banking, the perceived service performance is below „would be „level of

performance in four of five service quality dimensions. That is, the banking services even do not

perform at the adequate level in respect of reliability, responsiveness, assurance and empathy.

Banks seem to have performed better in case of „tangibles‟ dimension.

Objectives of the Study

The objectives of the study are summarized below.

1. To identify the service quality factors / dimensions of selected commercial banks

using SERVPERF scale.

2. To Establish zone of tolerance using minimum and desired service of service quality

attributes.

3. To explorer the relations between the importance of service quality attributes, height

and width of tolerance zone

Methodology


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Research methodology is a blue print of the way in which the research is going to be conducted.

It enlightens the methods to be followed in research activities. It includes research design, locale

of research, sampling framework, collection of data, framework for analysis and limitations.

Research Design

The present study describes the perception of service, minimum and desired service of each

attribute / item of service quality dimensions of the selected commercial banks. The mean of

desired and minimum service are used to determine the tolerance zone for each service quality

attributes.

Locale of Research

The present study is conducted in Bellary city including the suburban areas of the city. As no

exclusive study on service quality in commercial banks is carried out in this area and the

customer belonging to this area may reveal their opinions on service quality which are versatile

in nature, this area is selected. More over the researcher is familiar with the culture, language,

local dialect and infrastructure facilities available in this area, which is highly essential for the

response on the questionnaire.

Sample and Data Collection

The relevant literature and survey developed by the past studies provided the basis for

development of self administered questionnaire. After review of the literature twenty two

variables / attributes (table 8) of service quality (Parasuraman et al., 1885, 1988, 1994; Cronin

and Tailor, 1994) were used to develop questionnaire. Methodologically the SERVPERF scale

represents marked improvement over the SERVQUAL scale. Not only is the scale more efficient

in reducing the number of items to be measured by 50 percent, it has also been empirically found

superior to the SERVQUAL scale for being able to explain greater variance in the overall service

quality measured through the use of single-item scale (Sanjay and Gupta, 2004). Also when

applied in conjunction with SERVQUAL scale, the SERVEPERF measure has outperformed the

SERVQUAL scale (Babakus and Boller, 1992; Cronin and Taylor, 1994; Dhabolkar et al., 2000).

The present study adopted SERVPERF scale to measure the service quality.

The questionnaire consists of two sections: Demographic profile of the customers and twenty

two items/attributes (listed in table 7) about five dimensions service quality for assessing

perception of customers, minimum service and the desired service of each service quality

attribute. For each statement, the respondent indicates his or her opinion on a five point Likert-

scale ranging from “Strongly Disagree” (1) and “Strongly Agree” (5) for perception of service

quality. For each item customers are also asked to give the rating for minimum and desired

service on a five point Likert-scale.

Pretesting of the questionnaire was conducted on a random sample of 50 bank customers. The

pretest was conducted to obtain feedback to improve the content of questions, instructions,

clarity and layout of the questions. Furthermore, pretesting of the questionnaire also assessed the

reliability and the likely response rate. Some minor wording modifications to the questionnaire

were made as a result of this process.


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The non-probability sampling strategy called „Convenient sampling‟ was adapted to collect the

data. A convenience sampling is available to the researcher by virtue of its accessibility (Bryman

and Bell, 2003). Data from five hundred customers of five public sector banks namely State bank

of India, State bank of Mysore, State bank of Hyderabad, Canara bank and Syndicate bank, and

five private sector banks namely Axis bank, ICICI, SUCO bank, Ing. Vysya and Karnataka bank,

arriving to the banks from 10-30 A.M to 5.00 P. M, from Monday to Friday and from 10-30 A.M

to 1.00 P. M on Saturday are collected.

Data Analysis and Findings

It is very important to categorize the respondent‟s demographic profile because it gives a broad

picture and helps bankers to analyze the demographic factors which influence and are associated

with satisfaction level. 60.8 percent of the respondents are males and 39.2 percent of the

respondents are females.23 percent of the respondents are below 35 years age, 47, 30 percent of

the respondents are 35 to 55 year and above 55 years respectively. 70.4 percent of the

respondents are from urban and 29.6percent from rural.19.8 percent of the respondents have

studied up to 7th

standard, 63.2 percent of the respondents have education between 7th

standard to

PUC, 36.8 percent of the respondents are graduates and above. 23.6 percent of the respondents

have annual income of less than 1 lakh, 64.2 percent of the respondents have annual income

between 1 to 5 lakh and 35.8 percent of the respondents have annual income of more than 5 lakh.

15.2 percent of the respondents are employees, 50.6 percent of the respondents are businessman

and others accounts for 34.2 percent.

Table1 Demographic Profile of Respondents

S. No Characteristics Numbers Percentage

1 Gender Male

Female

Total

304

196

500

60.80

39.20

100

2 Age (years) Below 35

35 to 55

Above 56

Total

115

235

150

500

23.00

47.00

30.00

100

3 Nativity Urban

Rural

Total

352

148

500

70.40

29.60

100

4 Education Below 7th

standard

7th

std to PUC

Degree and above

Total

99

217

184

500

19.8

63,2

36.8

100

5 Annual

income (Rs.)

Below 1 lakh

1 to 5 Lakh

Above 5 Lakh

Total

118

203

179

500

23.60

40.60

35.80

100


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6 Occupation Employee

Business

Others

Total

76

253

171

500

15.20

50.60

34.20

100

Source: Primary data

The important service quality factors are identified using twenty two variables/attributes of

service quality with factor analysis. Before conducting factor analysis, validity of data for factor

analysis is examined with the help of Kaiser-Meyer-Olkin measure of sampling adequacy and

Bartletts test of sphericity. The KMO measure of sampling adequacy (0.649) reported in table 1

is greater than the minimum required (Nunnally, 1978). The Chi-square is significant even at

zero level. These two confirm the validity of data for factor analysis.

Table 2 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .649

Bartlett's Test of

Sphericity

Approx. Chi-Square 10651.056

Degree of freedom 231.000

Significance. .000

Table 3 Mean importance, mean of minimum, desired service, perception,

height (Alt Z) and width (Larg Z) of tolerance zone

Item

Mean

importance

Mean

Minimum

Service

(MS)

Mean

Desired

service

(DS)

Mean

Perception

Alt Z

Larg Z

E1 3.360 2.86 4.34 4.72 3.5999 1.4812

E2 3.334 2.87 4.37 4.30 3.6200 1.5022

E3 3.341 2.87 4.37 4.63 3.6221 1.5011

E4 3.332 2.86 4.37 4.34 3.6150 1.5131

E5 3.321 2.86 4.38 4.18 3.6212 1.5232

E6 3.313 2.85 4.37 3.50 3.6111 1.5215


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E7 3.300 2.85 4.37 3.43 3.6100 1.5223

E8 3.273 2.85 4.38 3.29 3.6153 1.5311

E9 3.262 2.86 4.39 3.21 3.6250 1.5324

E10 3.271 2.87 4.38 3.36 3.6252 1.5119

E11 3.212 2.86 4.37 3.67 3.6152 1.5128

E12 3.222 2.87 4.41 3.07 3.6431 1.5443

E13 3.196 2.87 4.42 3.46 3.6455 1.5499

E14 3.202 2.87 4.40 3.40 3.6350 1.5300

E15 3.223 2.87 4.42 4.36 3.6457 1.5502

E16 3.194 2.88 4.42 4.26 3.6511 1.3289

E17 3.183 2.87 4.41 3.46 3.6429 1.5431

E18 3.186 2.82 4.37 3.38 3.5949 1.5500

E19 3.198 2.82 4.36 3.23 3.5928 1.5451

E20 3.275 2.86 4.42 3.14 3.6412 1.5618

E21 3.224 2.87 4.43 3.30 3.6535 1.5624

E22 3.203 2.87 4.42 3.66 3.6453 1.5549

Table 4 Ranking items

in descending order

of Alt Z

Table 5 Ranking

items in ascending

order of Larg Z

Table 6 Ranking items

in the descending order

of important

Item Alt Z Rank Item

Larg Z Rank Item Mean

Importance

Rank

E21 3.6535 1 E16 1.3289 1 E1 3.360 1

E16 3.6511 2 E1 1.4812 2 E3 3.341 2

E15 3.6457 3 E3 1.5011 3 E2 3.334 3

E13 3.6455 4 E2 1.5022 4 E4 3.332 4


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E22 3.6453 5 E10 1.5119 5 E5 3.321 5

E12 3.6431 6 E11 1.5128 6 E6 3.313 6

E17 3.6429 7 E4 1.5131 7 E7 3.300 7

E20 3.6412 8 E6 1.5215 8 E20 3.275 8

E14 3.6350 9 E7 1.5223 9 E8 3.273 9

E10 3.6252 10 E5 1.5232 10 E10 3.271 10

E9 3.6250 11 E14 1.5300 11 E9 3.262 11

E3 3.6221 12 E8 1.5311 12 E21 3.224 12

E5 3.6212 13 E9 1.5324 13 E15 3.223 13

E2 3.6200 14 E17 1.5431 14 E12 3.222 14

E8 3.6153 15 E12 1.5443 15 E11 3.212 15

E11 3.6152 16 E19 1.5451 16 E22 3.203 16

E4 3.6150 17 E13 1.5499 17 E14 3.202 17

E6 3.6111 18 E18 1.5500 18 E19 3.198 18

E7 3.6100 19 E15 1.5502 19 E13 3.196 19

E1 3.5999 20 E22 1.5549 20 E16 3.194 20

E18 3.5949 21 E20 1.5618 21 E18 3.186 21

E19 3.5928 22 E21 1.5624 22 E17 3.183 22


Table 7 Ranking of items based on three measurement scales

Item Item Description Ranking

based on

Importance

Ranking

based on

Alt Z

Ranking

based on

Larg Z

E1 Prompt service 1 20 2

E2 Communicate what is to be served 3 14 4


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E3 Always willing to help customer 2 12 3

E4 Respond to customer request 4 17 7

E5 Never being too busy to respond to

customer‟s request

5 13 10

E6 Clarity of facilities 6 18 8

E7 Decoration of facilities 7 19 9

E8 Efficacious work environment 9 15 12

E9 Visually appealing equipments 11 11 13

E10 Complementary equipments 10 10 5

E11 Feeling of security 15 16 6

E12 Knowledgeable employees 14 6 15

E13 Friendliness of employees 19 4 17

E14 Consistently courteous with

customers

17 9 11

E15 Individual attention, understand

customer specific needs

13 3 19

E16 Customers best interest in heart 20 2 1

E17 Services as per the promise 22 7 14

E18 Provide right service at first time 21 21 16

E19 Precision in filing system 18 22 16

E20 Absence of error in service delivery 8 8 21

E21 Sincere in solving problems 12 1 22

E22 Precision in account statements 16 5 20


The factor analysis results in five factors known as service quality dimensions. These are termed

as Tangibles (E6 to E10), Reliability (E17 to E22), Responsiveness (E1 to E5), Assurance (E11 to

E14) and Empathy (E15 to E16). These five factors account for 72.6% of variance. The reliability

is tested using coefficient alpha (Cronbach, 1951). On analysis, the alpha values are found

greater than (0.7), the cut off recommended by Nunnally (1978). Hence the reliability analysis


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predicted the trustworthiness of the data obtained from the questionnaire and the data was used

for further analysis.

The mean of importance, minimum and the desired service along with the standard deviations

are listed in table 3. The tolerance zone height (Alt Z) and width of tolerance zone (Larg Z) are

computed using equations 1 and 2 as reported in table 3. The mean importance varies from 3.183

(for „Services as per the promise‟) to 3.360 (for Prompt service). The minimum service varies

from 3.82 to 3.87 and the desired service varies from 4.34 to 4.43.

The service quality attributes are ranked using the three measurement scales namely Alt Z, Larg

Z and importance. The results are shown in table 4, 5 and 6. Table 7 gives the ranking of each

service quality attribute using the three measurement scale. Table 3 reveals that the customers

are getting the service much above the minimum level of service with respect to all the service

quality attributes as their perception are within the desired and minimum service levels. The

perception of item number „E11‟ i.e., „feeling of security‟ is above the desired level of service.

Hence the customers are delighted with respect to this service quality attribute.

The degree of correlation between the measurements used can be compared by the ranking made

by the three measurement scales. A coefficient „1‟ indicates a degree of 100% alignment, „-1‟

indicates complete miss-alignment. the correlation between the ranking using the three

measurement scales is carried as given in table 8.The spearman‟s test reveals positive correlation

coefficient (0.40) among the ranking the by importance and the ranking by height of tolerance

zone. That is to say, the height of tolerance zone is proportional to the importance of the service

quality attributes. Negative correlation is observed (-0.355) between the width of tolerance zone

and the importance of the service quality attributes. That means the width of tolerance zone has

inverse behaviour with the importance of the service quality attributes. The test also reveals that

the height and width of tolerance zone are inversely related as correlation coefficient is negative

(-0.241).

Table 8 Spearman coefficient of correlation

Ranking Importance Alt Z Larg Z

Importance 1.000 0.400 -0.355

Alt Z 0.400 1.000 -0.241

Larg Z -0.355 -0,241 1.000

Conclusions

The aim of this study was to assess the service quality based on the zone of tolerance. The study

aims at exploring the service quality with respect to which the customers are dissatisfied,

satisfied and delighted. Five dimensions of service quality namely Tangibles, Reliability,

Responsiveness, assurance and Empathy are derived from twenty two attributes/items of service

quality using factor analysis.


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It is observed from the study that the mean importance of the service quality attributes varies

from 3.183 to 3.360, the height of tolerance zone varies from 3.5928 to 3.6535 and the width of

tolerance zone varies from 1.3289 to 1.5624.

The study reveals that the perceived service with respect to all the service quality attributes is

within the tolerance zone. Hence the service provided by the banks is acceptable to customers.

The customers are delighted with respect to the service quality attribute „Feeling of security‟ as

its perceived service is above the desired level of service. It is also observed from the study that

the height of tolerance zone is proportional to the importance of the service quality attributes and

width of tolerance zone has inverse behaviour with the importance of the service quality

attributes.

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RELATION BETWEEN ZONE OF TOLERANCE AND ...2013/07/10 · The zone of tolerance (ZOT) is defined as “the difference between desired service and the level of service considered adequate”

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