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Abstract
Service operations worldwide are affected by the new
wave of quality awareness and importance. As a result,
service-based companies are obligated to provide
excellent services to their customers in order to have
sustainable competitive advantage especially in the
current trend of trade, liberalization and globalization.
Since service quality predominantly is about meeting
customers' needs and requirements and how well the
s e r v i c e l eve l d e l i ve re d m atc h e s c u sto m e r
expectations, delivering high quality services will
enable companies to achieve customer satisfaction
and, in turn, gain loyal customers. Moreover,
successful cellular companies of the future will be
those that will analyze markets based on customer
perceptions, design a service delivery system that will
meet customer needs, and enhance the level of
service performance in order to delight their
customers rather than merely satisfying them. In view
of this well-known belief, an attempt has been made in
the present study to measure service quality variation
in cellular companies under study across demographic
variables in Kashmir Valley with a view to offering
suggestions to make the overall services in cellular
companies more effective and efficient. The study is
based on data gathered from four hundred (400)
respondents; the results lead us to the conclusion that
service quality of Aircel and Airtel is comparatively
better than Vodafone and BSNL, and suggests
improvement in all dimensions to augment the quality
of cellular services. Finally, the study also brought to
light that there exists insignificant variation in service
quality on majority of demographic variables in all
cellular companies under reference.
Key words: Service Quality, Customer Satisfaction,
SERVQUAL, SERVPERF, Demographic Variables,
Cellular Companies and Kashmir Valley.
Variance in Service Quality acrossDemographic Variables: An Assessment of
Cellular Service Companies in Kashmir Valley
Mushtaq Ahmad BhatFozia Sajad
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
Introduction
In a very limited period, cellular services have become
an increasingly needed service with a very high
penetration rate in most of the countries. With the
extensive usage of mobile telecommunications, the
cellular services market is now recognized as the most
competitive part of the telecommunications sector.
The telecommunications sector is one of the most
important sectors of any economy and its contribution
remains the greatest to the GDP of the economy
(Ahluwalia, 1998). There are 4.7 billion mobile
customers across the globe with growth of around 20%
per annum over the last three years (Vodafone Group
Plc, 2010). The majority of customers are in emerging
markets such as India and China (Vodafone Group Plc,
2 0 1 0 ) . M o b i l e n e t w o r k s , p a r t i c u l a r l y 3 G
communication networks, are becoming critical
infrastructure and major factors in driving substantial
economic growth in developing countries. In 2009, the
'World Bank Information and Communications for
Development' report showed that wireless
connectivity in the telecommunications sector matters
a lot i.e. a 10% increase in mobile phone penetration
results in an increase of 0.81% in per capita GDP and a
10% increase in internet/broadband penetration
results in an increase of 1.38% in GDP (Wang, 2010). As
more and more people join the global information
society and high-speed communication networks
become indispensable infrastructure, the tracking and
measurement of developments in information and
communication technologies (ICT's) remain as
relevant as ever. According to International
Telecommunication Union (ITU) estimates, there will
be 6.8 billion mobile-cellular subscriptions by the end
of 2013, almost as many as the number of people on
the planet. While the ubiquitous availability of mobile-
telephone services is undeniable with close to 100 per
cent of the population covered by a mobile signal, not
everyone has a mobile phone.
Studies have shown that the rapid increase in mobile
penetration has contributed significantly to the
economic growth of nations. Fuss, Meschi and
Waverman (2005) considered 92 countries, both
developed and developing, to estimate the impact of
mobile phones on economic growth for the period
1980 to 2003; they found that a 10% difference in
mobile penetration levels over the entire sample
period implies a 0.6% difference in growth rates
between otherwise identical developing nations. The
effect of mobiles was twice as large in developing
countries as in developed ones (Waverman, 2005).
Research has repeatedly shown a positive relationship
of service quality with customer satisfaction (Danaher
and Mattesson, 1994; Kim, Park, and Jeong, 2004),
customer preference (Ranaweera and Neely, 2003),
profitability (Fornell, 1992; Danaher and Rust, 1996)
and competitiveness (Rapert and Wren, 1998). In light
of the above-mentioned research studies, it can safely
be argued that cellular companies can improve their
p r o f i t a b i l i t y, c u s t o m e r p r e f e r e n c e , a n d
competitiveness through excellent service quality.
Objectives of the Study
In view of the growing importance of service quality in
cellular service companies, an attempt has been made
in the present study, to measure service quality of
cellular companies under study, across demographic
variables in Kashmir Valley. Such an analysis will
provide cellular companies a quantitative estimate of
their services being perceived by their respective
customers and also to suggest, on the basis of study
results, ways and means for improving service quality
of cellular companies with a view to make overall
cellular services more effective and efficient.
52 53
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Abstract
Service operations worldwide are affected by the new
wave of quality awareness and importance. As a result,
service-based companies are obligated to provide
excellent services to their customers in order to have
sustainable competitive advantage especially in the
current trend of trade, liberalization and globalization.
Since service quality predominantly is about meeting
customers' needs and requirements and how well the
s e r v i c e l eve l d e l i ve re d m atc h e s c u sto m e r
expectations, delivering high quality services will
enable companies to achieve customer satisfaction
and, in turn, gain loyal customers. Moreover,
successful cellular companies of the future will be
those that will analyze markets based on customer
perceptions, design a service delivery system that will
meet customer needs, and enhance the level of
service performance in order to delight their
customers rather than merely satisfying them. In view
of this well-known belief, an attempt has been made in
the present study to measure service quality variation
in cellular companies under study across demographic
variables in Kashmir Valley with a view to offering
suggestions to make the overall services in cellular
companies more effective and efficient. The study is
based on data gathered from four hundred (400)
respondents; the results lead us to the conclusion that
service quality of Aircel and Airtel is comparatively
better than Vodafone and BSNL, and suggests
improvement in all dimensions to augment the quality
of cellular services. Finally, the study also brought to
light that there exists insignificant variation in service
quality on majority of demographic variables in all
cellular companies under reference.
Key words: Service Quality, Customer Satisfaction,
SERVQUAL, SERVPERF, Demographic Variables,
Cellular Companies and Kashmir Valley.
Variance in Service Quality acrossDemographic Variables: An Assessment of
Cellular Service Companies in Kashmir Valley
Mushtaq Ahmad BhatFozia Sajad
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
Introduction
In a very limited period, cellular services have become
an increasingly needed service with a very high
penetration rate in most of the countries. With the
extensive usage of mobile telecommunications, the
cellular services market is now recognized as the most
competitive part of the telecommunications sector.
The telecommunications sector is one of the most
important sectors of any economy and its contribution
remains the greatest to the GDP of the economy
(Ahluwalia, 1998). There are 4.7 billion mobile
customers across the globe with growth of around 20%
per annum over the last three years (Vodafone Group
Plc, 2010). The majority of customers are in emerging
markets such as India and China (Vodafone Group Plc,
2 0 1 0 ) . M o b i l e n e t w o r k s , p a r t i c u l a r l y 3 G
communication networks, are becoming critical
infrastructure and major factors in driving substantial
economic growth in developing countries. In 2009, the
'World Bank Information and Communications for
Development' report showed that wireless
connectivity in the telecommunications sector matters
a lot i.e. a 10% increase in mobile phone penetration
results in an increase of 0.81% in per capita GDP and a
10% increase in internet/broadband penetration
results in an increase of 1.38% in GDP (Wang, 2010). As
more and more people join the global information
society and high-speed communication networks
become indispensable infrastructure, the tracking and
measurement of developments in information and
communication technologies (ICT's) remain as
relevant as ever. According to International
Telecommunication Union (ITU) estimates, there will
be 6.8 billion mobile-cellular subscriptions by the end
of 2013, almost as many as the number of people on
the planet. While the ubiquitous availability of mobile-
telephone services is undeniable with close to 100 per
cent of the population covered by a mobile signal, not
everyone has a mobile phone.
Studies have shown that the rapid increase in mobile
penetration has contributed significantly to the
economic growth of nations. Fuss, Meschi and
Waverman (2005) considered 92 countries, both
developed and developing, to estimate the impact of
mobile phones on economic growth for the period
1980 to 2003; they found that a 10% difference in
mobile penetration levels over the entire sample
period implies a 0.6% difference in growth rates
between otherwise identical developing nations. The
effect of mobiles was twice as large in developing
countries as in developed ones (Waverman, 2005).
Research has repeatedly shown a positive relationship
of service quality with customer satisfaction (Danaher
and Mattesson, 1994; Kim, Park, and Jeong, 2004),
customer preference (Ranaweera and Neely, 2003),
profitability (Fornell, 1992; Danaher and Rust, 1996)
and competitiveness (Rapert and Wren, 1998). In light
of the above-mentioned research studies, it can safely
be argued that cellular companies can improve their
p r o f i t a b i l i t y, c u s t o m e r p r e f e r e n c e , a n d
competitiveness through excellent service quality.
Objectives of the Study
In view of the growing importance of service quality in
cellular service companies, an attempt has been made
in the present study, to measure service quality of
cellular companies under study, across demographic
variables in Kashmir Valley. Such an analysis will
provide cellular companies a quantitative estimate of
their services being perceived by their respective
customers and also to suggest, on the basis of study
results, ways and means for improving service quality
of cellular companies with a view to make overall
cellular services more effective and efficient.
52 53
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Literature Review
Quality Conceptualization
The changing paradigm of business has made the
provision of quality of services as top priority for
organizations. Researchers have emphasized distinct
conceptualizations of quality (Holbrook, 1994). In
operations management, reliability and fitness of use
define quality; whereas in marketing and economics,
attributes of products constitute quality. Crosby (1979)
defines quality of goods/services as conformance to
requirements. Requirements must be clearly stated so
that they cannot be misunderstood. Garvin (1983)
measures quality by counting the incidence of
―internal failures (those observed before a product
leaves the factory) and external failures (those
incurred in the field after a unit has been installed).
Juran (1974) defines quality as fitness for use, the
extent to which the product successfully serves the
purpose of the user usage. Similarly Ennew, Reed and
Binks (1993) express it as the ability of a service or a
product to perform its specified tasks. In all definitions,
the common aspect is the customers' needs and
expectations that define good quality. Quality has a
long term impact on customer sat isfact ion
(Omachonu, Johnson and Onyeaso, 2008). Atalik and
Arslan (2009) found that creating value and offering
quality services to customers creates loyal customers.
Quality is what a customer expects in the product/
service he/she is buying. If a customer expects
“excellence” in everything he/she purchases, then
his/her expectations are high. However, this could
prove to be elusive to a customer when he actually gets
a product/service that he has paid for. For instance, a
passenger travelling in an economy class on a flight
cannot expect service like a passenger who is travelling
in the first class. While the quality in tangible goods has
been described and measured considerably by
researchers, quality in services, on the other hand, has
largely remained much less researched due to its
peculiar nature. Thus instead of borrowing the
concept of quality from the manufacturing sector,
service marketing researchers based their own works
on developing a service quality concept on models
from consumer behaviour literature (Brown, and
Swartz, 1989). Parasuraman, Zeithaml, and Berry
(1985) also state that it may be inappropriate to use a
product-based definition of quality when studying the
service sector and, therefore, developed the
expression service quality.
Service Quality
Service quality has been described as a form of
attitude, related but not equivalent to satisfaction that
results from the comparison of expectations with
performance (Bolton and Drew, 1991; Cronin and
Taylor, 1992; Parasuraman, Zeithaml and Berry 1988;
Shepherd, 1999). Much of the initial work in defining
and assessing service quality has been conducted by
Parasuraman, et. al., (1985). Parasuraman, et. al.,
(1985) asserted that service quality can be assessed by
measuring the “discrepancies or gaps” between what
the customer expects and what the consumer
perceives he receives. In other words, they mean that
service quality as perceived by customers stems from a
comparison of what they feel service firms should offer
(i.e., from their expectations) with their perception of
the performance of the firm providing the services. In
line with the above research, Gronroos (1982)
developed a model in which he contended that
consumers compare the service they expect with
perception of the service they receive in evaluating
service quality. Similarly Johnston (1995) defined
service quality as customers' overall impressions of an
organization's service in terms of relative superiority
or inferiority. Lyord and Cheung (1998) asserted that
service quality should not only meet but also exceed
customers' expectations, and include a continuous
improvement process. Service quality arises from a
comparison of the difference between service
expectations developed before an encounter with the
service establishment and the performance
perceptions gained from the service delivery process
(Bloemer, Ruyter, and Peeters, 1998).
Further, Gronroos (2007) suggested that the quality of
service as perceived by customers is the result of an
evaluation process in which they compare their
perspective of service outcome against what they
expected. On the other hand, service quality means
zero defection (Reichheld and Sasser, 1990). Fogli
(2006) defined service quality as a global judgment or
attitude relating to a particular service, the customer's
overall impression of the relative inferiority or the
superiority of the organization and its services.
Similarly, Berry, Parasuraman, and Zeithaml, (1990)
pointed out that since customers are the “sole judge of
service quality”, an organization can build strong
reputation for quality service when it can constantly
meet customer service expectations. Likewise,
Howcorft (1991) defined service quality as meeting
customers' needs satisfactorily by matching their
expectations. Haddad, Fournier, and Potvin (1998)
defined service quality as the difference between the
actual performance of service and the customers'
expectation from the service. The customers'
perception of quality of service is based on the degree
of agreement between expectations and experiences
(Kandampully, 1998). Similarly, Lewis and Booms
(1983) stated that service quality is a measure of how
well the service level delivered matches customer
expectation. Delivering quality service means
conforming to customer expectation on a consistent
basis. Previous research studies on service quality
support this notion that perceived service quality
stems from customers' comparison of what they wish
to receive from firms and what they perceive actual
service performance to be – which is formed on the
basis of previous experience with a company, its
competitors, and marketing mix inputs (Sasser, Olsen
and Wyckoff, 1978; Gronroos, 1982; Lehtinen and
Lehtinen, 1982; and Parasuraman, et. al., 1985; 1988).
Service quality and customer satisfaction are
interlinked. Service quality helps the customer to
decide whether the services received justify the cost of
the service or not. Since customer satisfaction has
been considered to be based on the customer's
experience with a particular service encounter (Cronin
and Taylor, 1992), it is in line with the fact that service
quality is a determinant of customer satisfaction,
because service quality comes from outcome of the
services provided by the service provider.
Khan, M. A., (2010) adds to the service literature by
conducting an empirical study to examine the
dimensions of users' perceived service quality of
cellular mobile telephone operators in Pakistan by
using SERVQUAL dimensions as tangible, reliability,
assurance, empathy, responsiveness, and additional
dimensions of network quality and convenience. The
results of the study clearly indicate that the
dimensions of network quality, convenience, and
reliability are important aspects that need managerial
attention to attract and retain customers, and the
regulators in the telecommunications industry should
take appropriate measures in safeguarding customers'
interest. Communication and price were the most
influential and most preferential factors in selecting a
telecommunications service provider (Paulrajan and
Harish, 2011). However, product quality and
availability had a significant impact on consumer
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley54 55
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Literature Review
Quality Conceptualization
The changing paradigm of business has made the
provision of quality of services as top priority for
organizations. Researchers have emphasized distinct
conceptualizations of quality (Holbrook, 1994). In
operations management, reliability and fitness of use
define quality; whereas in marketing and economics,
attributes of products constitute quality. Crosby (1979)
defines quality of goods/services as conformance to
requirements. Requirements must be clearly stated so
that they cannot be misunderstood. Garvin (1983)
measures quality by counting the incidence of
―internal failures (those observed before a product
leaves the factory) and external failures (those
incurred in the field after a unit has been installed).
Juran (1974) defines quality as fitness for use, the
extent to which the product successfully serves the
purpose of the user usage. Similarly Ennew, Reed and
Binks (1993) express it as the ability of a service or a
product to perform its specified tasks. In all definitions,
the common aspect is the customers' needs and
expectations that define good quality. Quality has a
long term impact on customer sat isfact ion
(Omachonu, Johnson and Onyeaso, 2008). Atalik and
Arslan (2009) found that creating value and offering
quality services to customers creates loyal customers.
Quality is what a customer expects in the product/
service he/she is buying. If a customer expects
“excellence” in everything he/she purchases, then
his/her expectations are high. However, this could
prove to be elusive to a customer when he actually gets
a product/service that he has paid for. For instance, a
passenger travelling in an economy class on a flight
cannot expect service like a passenger who is travelling
in the first class. While the quality in tangible goods has
been described and measured considerably by
researchers, quality in services, on the other hand, has
largely remained much less researched due to its
peculiar nature. Thus instead of borrowing the
concept of quality from the manufacturing sector,
service marketing researchers based their own works
on developing a service quality concept on models
from consumer behaviour literature (Brown, and
Swartz, 1989). Parasuraman, Zeithaml, and Berry
(1985) also state that it may be inappropriate to use a
product-based definition of quality when studying the
service sector and, therefore, developed the
expression service quality.
Service Quality
Service quality has been described as a form of
attitude, related but not equivalent to satisfaction that
results from the comparison of expectations with
performance (Bolton and Drew, 1991; Cronin and
Taylor, 1992; Parasuraman, Zeithaml and Berry 1988;
Shepherd, 1999). Much of the initial work in defining
and assessing service quality has been conducted by
Parasuraman, et. al., (1985). Parasuraman, et. al.,
(1985) asserted that service quality can be assessed by
measuring the “discrepancies or gaps” between what
the customer expects and what the consumer
perceives he receives. In other words, they mean that
service quality as perceived by customers stems from a
comparison of what they feel service firms should offer
(i.e., from their expectations) with their perception of
the performance of the firm providing the services. In
line with the above research, Gronroos (1982)
developed a model in which he contended that
consumers compare the service they expect with
perception of the service they receive in evaluating
service quality. Similarly Johnston (1995) defined
service quality as customers' overall impressions of an
organization's service in terms of relative superiority
or inferiority. Lyord and Cheung (1998) asserted that
service quality should not only meet but also exceed
customers' expectations, and include a continuous
improvement process. Service quality arises from a
comparison of the difference between service
expectations developed before an encounter with the
service establishment and the performance
perceptions gained from the service delivery process
(Bloemer, Ruyter, and Peeters, 1998).
Further, Gronroos (2007) suggested that the quality of
service as perceived by customers is the result of an
evaluation process in which they compare their
perspective of service outcome against what they
expected. On the other hand, service quality means
zero defection (Reichheld and Sasser, 1990). Fogli
(2006) defined service quality as a global judgment or
attitude relating to a particular service, the customer's
overall impression of the relative inferiority or the
superiority of the organization and its services.
Similarly, Berry, Parasuraman, and Zeithaml, (1990)
pointed out that since customers are the “sole judge of
service quality”, an organization can build strong
reputation for quality service when it can constantly
meet customer service expectations. Likewise,
Howcorft (1991) defined service quality as meeting
customers' needs satisfactorily by matching their
expectations. Haddad, Fournier, and Potvin (1998)
defined service quality as the difference between the
actual performance of service and the customers'
expectation from the service. The customers'
perception of quality of service is based on the degree
of agreement between expectations and experiences
(Kandampully, 1998). Similarly, Lewis and Booms
(1983) stated that service quality is a measure of how
well the service level delivered matches customer
expectation. Delivering quality service means
conforming to customer expectation on a consistent
basis. Previous research studies on service quality
support this notion that perceived service quality
stems from customers' comparison of what they wish
to receive from firms and what they perceive actual
service performance to be – which is formed on the
basis of previous experience with a company, its
competitors, and marketing mix inputs (Sasser, Olsen
and Wyckoff, 1978; Gronroos, 1982; Lehtinen and
Lehtinen, 1982; and Parasuraman, et. al., 1985; 1988).
Service quality and customer satisfaction are
interlinked. Service quality helps the customer to
decide whether the services received justify the cost of
the service or not. Since customer satisfaction has
been considered to be based on the customer's
experience with a particular service encounter (Cronin
and Taylor, 1992), it is in line with the fact that service
quality is a determinant of customer satisfaction,
because service quality comes from outcome of the
services provided by the service provider.
Khan, M. A., (2010) adds to the service literature by
conducting an empirical study to examine the
dimensions of users' perceived service quality of
cellular mobile telephone operators in Pakistan by
using SERVQUAL dimensions as tangible, reliability,
assurance, empathy, responsiveness, and additional
dimensions of network quality and convenience. The
results of the study clearly indicate that the
dimensions of network quality, convenience, and
reliability are important aspects that need managerial
attention to attract and retain customers, and the
regulators in the telecommunications industry should
take appropriate measures in safeguarding customers'
interest. Communication and price were the most
influential and most preferential factors in selecting a
telecommunications service provider (Paulrajan and
Harish, 2011). However, product quality and
availability had a significant impact on consumer
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley54 55
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
perception in selecting a cellular mobile service
provider as consumers' perception widely varies in
accordance with the communication quality, call
service, facilities, price, customer care and service
provider's attributes. Further, OluOjo, (2010)
investigated the relationship between service quality
and customer satisfaction in the telecommunications
industry with a focus on Mobile Telecommunication
Network (MTN) Nigeria. The study revealed that
service quality has an effect on customer satisfaction
and that there is a positive relationship between
service quality and customer satisfaction. Likewise,
Nasser, Salleh, and Gelaidan, (2012) found that the
relationship between perceived value, perceived
quality and corporate image have a significant positive
influence on customer satisfaction.
According to Khan and Afsheen, (2012) price fairness,
customer services and coverage are major factors
which can highly affect customer satisfaction. Petzer
and Meyer, (2011) also aimed to determine different
generations' perceived quality of services and
satisfaction levels with services provided by cell phone
network service providers, as well as their behavioural
intentions towards these providers. The study results
of Petzer and Meyer (2011) found that young
generation Y consumers perceive the service quality
levels and service satisfaction levels of these providers
as significantly lower than other generations implying
that providers should strongly focus their efforts on
satisfying the needs and improving the service
satisfaction of young generation Y consumers in order
to retain them in the future.
Ode Egena, (2013) tried to measure customer
satisfaction with service delivery of mobile
telecommunications networks and found that the
respondents would likely stay with their telecom
service providers as long as the companies are able to
satisfy their changing needs and meet customer
requirements beyond expectations. Agyapong, G.
(2011) also attempted to examine the relationship
between service quality and customer satisfaction in
the utility industry (telecom) in Ghana and found that
service quality is a good predictor of customer
satisfaction.
From the above discussion, it is clear that service
quality revolves around customer expectations and
their perceptions of service performance. Hence, it is
characterized by the customers' perception of service
and the customers are the sole judges of the quality.
Parasuraman, Berry and Zeithmal, (1991) rightly
exp la ined that cons istent conformance to
ex p e c ta t i o n s b e g i n s w i t h i d e n t i f y i n g a n d
understanding customer expectations to develop
effective service quality strategies.
Research Hypotheses
Many researchers (Ahnand Lee, 1999; Wareham and
Levy, 2002; Madden, Coble, and Dalzell, 2004; Birke
and Swann; 2006; Clements and Abramowitz., 2006;
Andonova., 2006; Karaçuka, Nazif, and Haucap, 2012
and Olatokun and Nwone., 2013) have studied
variation in the quality of cellular services across
demographic variables. Although research has
suggested that demographic variables are significant
factors in perception of service quality (Webster, 1989
and Stafford, 1996), there has been little direct
analysis of those differences (Webster, 1989; Stafford,
1996). Atkin and LaRose (1999) in their study found
age, gender, education, occupation and income to be
antecedents in new media adoption. Moreover,
Clements and Abramowitz, (2006) in their study on the
development and adoption of broadband service
(household level analysis) concluded that income, age
and educational attainment do influence adoption of
broadband service. Likewise, Birke and Swann, (2006)
in their study on network effects and choice of mobile
phone operator, observed that the choice of mobile
phone operators is strongly coordinated within
households where gender differences in the use of
telecommunications products exist. Similarly,
Wareham and Levy, (2002) in their study also reported
that education is a steady indicator of wireless phone
diffusion because achieving higher education has a
positive association with being comfortable with
higher technology use. Scott (2004) also, in his study,
reports that educated people who used phones more
have a strong intention to use phones in future as well
and have a more positive attitude towards phones.
Olatokun and Nwone (2013) too, in their study on
influence of socio-demographic variables on users'
choice of mobile service providers, concluded that
categories in age, religion, occupation, monthly
income and expenditure on mobile services are
influenced by price, service quality, promotion and
brand image. Emphasizing the significance of
demographic factors on users' choice of telecom
operators, Karaçuka's, (2012) in his study on
consumer choice and local network effects in mobile
telecommunications, showed that being male rather
than female has a positive impact on choice of mobile
operator, while being married has a negative impact. In
line with the above research studies, the following
hypotheses have been framed to study variance in
service quality across demographic variables among
cellular service companies, under reference.
H1: Service quality varies significantly across all age
groups;
H2: Service quality varies significantly across all
gender groups;
H3: Service quality varies significantly across all
educational groups;
H4: Service quality varies significantly across all time
periods of network experience groups; and
H5: Service quality varies significantly across groups
with all connection types.
Sample Design
Since the present study aims at measuring service
quality variation in cellular service companies under
study across demographic variables in Kashmir Valley,
an attempt has been made to make the sample as
representative as possible. However, due to time and
financial constraints, the study is confined to district
Srinagar only. District Srinagar is further divided into
eight assembly constituencies and out of eight, four
assembly constituencies are selected for the present
study. The selected constituencies have a significant
relationship with the sampled companies in terms of
customer density, geographical presence and
competition. The study is further restricted to four
selective cellular service operators namely Airtel,
Vodafone, Aircel and BSNL. The decision regarding
sample organization has been made in view of the fact
that among the best cellular service providers Airtel,
Vodafone, Aircel and BSNL have maximum market
share as per TRAI report as on 31st January, 2013.
These service providers have greater customer base,
business operations, customer service centres and
retail outlets than any other cellular service provider in
district Srinagar. The size of the sample was limited to
four hundred (400) respondents selected from four (4)
cellular companies by following convenience sampling
method. All important demographic characteristics
like age, gender, level of education, time of network
experience and connection type were taken into
consideration while seeking the response from the
customers regarding their perception of service
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley56 57
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
perception in selecting a cellular mobile service
provider as consumers' perception widely varies in
accordance with the communication quality, call
service, facilities, price, customer care and service
provider's attributes. Further, OluOjo, (2010)
investigated the relationship between service quality
and customer satisfaction in the telecommunications
industry with a focus on Mobile Telecommunication
Network (MTN) Nigeria. The study revealed that
service quality has an effect on customer satisfaction
and that there is a positive relationship between
service quality and customer satisfaction. Likewise,
Nasser, Salleh, and Gelaidan, (2012) found that the
relationship between perceived value, perceived
quality and corporate image have a significant positive
influence on customer satisfaction.
According to Khan and Afsheen, (2012) price fairness,
customer services and coverage are major factors
which can highly affect customer satisfaction. Petzer
and Meyer, (2011) also aimed to determine different
generations' perceived quality of services and
satisfaction levels with services provided by cell phone
network service providers, as well as their behavioural
intentions towards these providers. The study results
of Petzer and Meyer (2011) found that young
generation Y consumers perceive the service quality
levels and service satisfaction levels of these providers
as significantly lower than other generations implying
that providers should strongly focus their efforts on
satisfying the needs and improving the service
satisfaction of young generation Y consumers in order
to retain them in the future.
Ode Egena, (2013) tried to measure customer
satisfaction with service delivery of mobile
telecommunications networks and found that the
respondents would likely stay with their telecom
service providers as long as the companies are able to
satisfy their changing needs and meet customer
requirements beyond expectations. Agyapong, G.
(2011) also attempted to examine the relationship
between service quality and customer satisfaction in
the utility industry (telecom) in Ghana and found that
service quality is a good predictor of customer
satisfaction.
From the above discussion, it is clear that service
quality revolves around customer expectations and
their perceptions of service performance. Hence, it is
characterized by the customers' perception of service
and the customers are the sole judges of the quality.
Parasuraman, Berry and Zeithmal, (1991) rightly
exp la ined that cons istent conformance to
ex p e c ta t i o n s b e g i n s w i t h i d e n t i f y i n g a n d
understanding customer expectations to develop
effective service quality strategies.
Research Hypotheses
Many researchers (Ahnand Lee, 1999; Wareham and
Levy, 2002; Madden, Coble, and Dalzell, 2004; Birke
and Swann; 2006; Clements and Abramowitz., 2006;
Andonova., 2006; Karaçuka, Nazif, and Haucap, 2012
and Olatokun and Nwone., 2013) have studied
variation in the quality of cellular services across
demographic variables. Although research has
suggested that demographic variables are significant
factors in perception of service quality (Webster, 1989
and Stafford, 1996), there has been little direct
analysis of those differences (Webster, 1989; Stafford,
1996). Atkin and LaRose (1999) in their study found
age, gender, education, occupation and income to be
antecedents in new media adoption. Moreover,
Clements and Abramowitz, (2006) in their study on the
development and adoption of broadband service
(household level analysis) concluded that income, age
and educational attainment do influence adoption of
broadband service. Likewise, Birke and Swann, (2006)
in their study on network effects and choice of mobile
phone operator, observed that the choice of mobile
phone operators is strongly coordinated within
households where gender differences in the use of
telecommunications products exist. Similarly,
Wareham and Levy, (2002) in their study also reported
that education is a steady indicator of wireless phone
diffusion because achieving higher education has a
positive association with being comfortable with
higher technology use. Scott (2004) also, in his study,
reports that educated people who used phones more
have a strong intention to use phones in future as well
and have a more positive attitude towards phones.
Olatokun and Nwone (2013) too, in their study on
influence of socio-demographic variables on users'
choice of mobile service providers, concluded that
categories in age, religion, occupation, monthly
income and expenditure on mobile services are
influenced by price, service quality, promotion and
brand image. Emphasizing the significance of
demographic factors on users' choice of telecom
operators, Karaçuka's, (2012) in his study on
consumer choice and local network effects in mobile
telecommunications, showed that being male rather
than female has a positive impact on choice of mobile
operator, while being married has a negative impact. In
line with the above research studies, the following
hypotheses have been framed to study variance in
service quality across demographic variables among
cellular service companies, under reference.
H1: Service quality varies significantly across all age
groups;
H2: Service quality varies significantly across all
gender groups;
H3: Service quality varies significantly across all
educational groups;
H4: Service quality varies significantly across all time
periods of network experience groups; and
H5: Service quality varies significantly across groups
with all connection types.
Sample Design
Since the present study aims at measuring service
quality variation in cellular service companies under
study across demographic variables in Kashmir Valley,
an attempt has been made to make the sample as
representative as possible. However, due to time and
financial constraints, the study is confined to district
Srinagar only. District Srinagar is further divided into
eight assembly constituencies and out of eight, four
assembly constituencies are selected for the present
study. The selected constituencies have a significant
relationship with the sampled companies in terms of
customer density, geographical presence and
competition. The study is further restricted to four
selective cellular service operators namely Airtel,
Vodafone, Aircel and BSNL. The decision regarding
sample organization has been made in view of the fact
that among the best cellular service providers Airtel,
Vodafone, Aircel and BSNL have maximum market
share as per TRAI report as on 31st January, 2013.
These service providers have greater customer base,
business operations, customer service centres and
retail outlets than any other cellular service provider in
district Srinagar. The size of the sample was limited to
four hundred (400) respondents selected from four (4)
cellular companies by following convenience sampling
method. All important demographic characteristics
like age, gender, level of education, time of network
experience and connection type were taken into
consideration while seeking the response from the
customers regarding their perception of service
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley56 57
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
quality in the cellular industry. All these aspects have
an important bearing on the user's evaluation of
cellular services. Effort was made to give a balanced
representat ion to the above demographic
characteristics to make the sample representative.
A sizeable number of respondents belonged to the age
group of up to 20 years (59.5%) followed by the age
group of 21-30 years (26.5%) whereas the age group of
above 30 years (14.25%) were the least. In terms of
gender, the sample has a greater number of males
(57.5% males and 42.5% females). The data further
shows that under-graduates were the largest number
of participants (36.25%) followed by post-graduates
(33%) and graduates (30.75%). Respondents with
network experience of more than a year were highest
in number (75%) followed by the respondents with
network experience of up to 7-12 months (14.5%)
whereas respondents with network experience of up
to 6 months were least in number (10.5%). As per
connection type, majority of the respondents in the
sample belonged to the prepaid category (79.5%)
followed by postpaid category (20.5%).
Data Collection
To achieve the objective of the study, data was
collected from both primary and secondary sources.
The study, however, is based on primary data gathered
through a self-developed questionnaire. The
questionnaire was designed in a structured objective
pattern focusing on the research objectives. In case
customers were unable to understand the
questionnaire or were illiterate, the investigator
herself filled up the questionnaire after seeking their
responses. Secondary data has been collected from
previous research findings, scholarly reports,
telecommunications reports and respective marketing
departments.
Research Instrument
Literature provides evidence of the availability of two
important/popular service quality measurement
instruments: SERVQUAL (Parasuraman, et. al., 1988)
and SERVPERF (Cronin and Taylor, 1992). The
SERVQUAL model developed by Parasuraman, (1985,
1988) consists of 22 items for assessing customer
perceptions and expectations regarding the quality of
service. A level of agreement or disagreement with a
given item is rated on a seven point Likert-type scale.
The level of service quality is represented by the gap
between perceived and expected service. The
SERVQUAL model is based on five service quality
dimensions, namely tangibles (physical facilities,
equipment and personnel appearance), reliability
(ability to perform the promised service dependably
and accurately), responsiveness (willingness to help
customers and provide prompt service), assurance
(knowledge and courtesy of employees and their
ability to gain trust and confidence) and empathy
(providing individualized attention to the customers).
SERVQUAL means service quality which is the
discrepancy between customer's expectations of
service offering and the customer's perceptions of the
service received (Parasuraman, et. al., 1988).
Despite its wide usage, the model has been criticized
by a number of researchers (Carman 1990; Babakus
and Boller 1992; Teas 1994). Criticism was directed at
the conceptual and operational base of the model -
mostly its validity, reliability, operationalization of
expectations, and dimensional structure. In other
words, criticism against the SERVQUAL model was
directed to the use of (P-E) gap scores, length of the
questionnaire, predictive power of the instrument,
etc. (Babukus and Boller, 1992; Cronin and Taylor,
1992; Teas, 1993, 1994; Dabholkar, Shepherd, and
Thorpe, 2000). As a result, Cronin and Taylor (1992 and
1994) proposed an alternate scale to SERVQUAL -
what is referred to as the 'SERVPERF' scale. They
argued that performance is the measure that best
explains customers' perceptions of service quality, so
expectations should not be included in the service
quality measurement instrument. Besides theoretical
arguments, Cronin and Taylor (1992) also provided
empirical evidence across four industries (namely
banks, pest control, dry cleaning and fast food) to
corroborate the superiority of their “performance-
only” instrument over disconfirmation based
SERVQUAL Scale. Under the SERVPERF, a higher
perceived performance implies higher service quality
and customer satisfaction (Jain and Gupta, 2004). It
eliminates the expectation on the twenty-two items
and measures only performance on the original
version of SERVQUAL dimensions i.e., tangibility,
reliability, responsiveness, assurance and empathy
(Bolton and Drew, 1991; Babakus and Boller, 1992;
Hartline and Ferrell, 1996). In equation form, the
SERVPERF can be expressed as:
KSQi =∑ Pij
J=1
Where:
SQi = perceived service quality of an
individual 'I'
K = number of service attributes / items
Pi = perception of individual 'I' with
respect to performance of a service
firm attribute 'j'
In terms of methodology, the SERVPERF scale
represents a marked improvement over the
SERVQUAL scale. Not only is the scale more efficient in
reducing the number of items to be measured by
about 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
and customer satisfaction measured through the use
of single-item scale. This explains the considerable
support that has emerged over time in favour of the
SERVPERF scale (Churchill and Suprenant, 1982;
Bolton and Drew, 1991; Babukus and Boller, 1992;
Boulding, Kalra, Staelin, and Zeithaml, 1993; Gotlieb,
Grewal, and Brown, 1994). Realizing the advantages of
the SERVPERF scale over SERVQUAL, researchers
have increasingly started making use of the
performance only measure of service quality (Brady
and Robertson, 1992; Cronin and Taylor, 1992, 1994;
Andaleeb and Basu, 1994; Cronin, Brady and Hult,
2000; Bigne, Moliner, and Sanchey, 2003; Duncan and
Elliot, 2004). Conceding its superiority, even Zeithmal
(one of the founders of the SERVQUAL scale) in a
recent study observed that, “Our result is incompatible
with both the one-dimensional view of expectations
and the gap formation for service quality.” Instead we
find that perceived quality is directly influenced only
by perceptions of performance (Jain and Gupta, 2004).
This admittance cogently lends a testimony to the
superiority of the SERVPERF scale.
Recognizing the superiority of SERVPERF over
SERVQUAL, the present study has also used modified
SERVPERF scale to measure the service quality of
cellular companies under study. This 27-item
SERVPERF has been modified to suit the context of
cellular customers. Modifying the original SERVPERF
was intended to improve the validity and reliability of
the instrument. The questionnaire was divided into
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley58 59
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
quality in the cellular industry. All these aspects have
an important bearing on the user's evaluation of
cellular services. Effort was made to give a balanced
representat ion to the above demographic
characteristics to make the sample representative.
A sizeable number of respondents belonged to the age
group of up to 20 years (59.5%) followed by the age
group of 21-30 years (26.5%) whereas the age group of
above 30 years (14.25%) were the least. In terms of
gender, the sample has a greater number of males
(57.5% males and 42.5% females). The data further
shows that under-graduates were the largest number
of participants (36.25%) followed by post-graduates
(33%) and graduates (30.75%). Respondents with
network experience of more than a year were highest
in number (75%) followed by the respondents with
network experience of up to 7-12 months (14.5%)
whereas respondents with network experience of up
to 6 months were least in number (10.5%). As per
connection type, majority of the respondents in the
sample belonged to the prepaid category (79.5%)
followed by postpaid category (20.5%).
Data Collection
To achieve the objective of the study, data was
collected from both primary and secondary sources.
The study, however, is based on primary data gathered
through a self-developed questionnaire. The
questionnaire was designed in a structured objective
pattern focusing on the research objectives. In case
customers were unable to understand the
questionnaire or were illiterate, the investigator
herself filled up the questionnaire after seeking their
responses. Secondary data has been collected from
previous research findings, scholarly reports,
telecommunications reports and respective marketing
departments.
Research Instrument
Literature provides evidence of the availability of two
important/popular service quality measurement
instruments: SERVQUAL (Parasuraman, et. al., 1988)
and SERVPERF (Cronin and Taylor, 1992). The
SERVQUAL model developed by Parasuraman, (1985,
1988) consists of 22 items for assessing customer
perceptions and expectations regarding the quality of
service. A level of agreement or disagreement with a
given item is rated on a seven point Likert-type scale.
The level of service quality is represented by the gap
between perceived and expected service. The
SERVQUAL model is based on five service quality
dimensions, namely tangibles (physical facilities,
equipment and personnel appearance), reliability
(ability to perform the promised service dependably
and accurately), responsiveness (willingness to help
customers and provide prompt service), assurance
(knowledge and courtesy of employees and their
ability to gain trust and confidence) and empathy
(providing individualized attention to the customers).
SERVQUAL means service quality which is the
discrepancy between customer's expectations of
service offering and the customer's perceptions of the
service received (Parasuraman, et. al., 1988).
Despite its wide usage, the model has been criticized
by a number of researchers (Carman 1990; Babakus
and Boller 1992; Teas 1994). Criticism was directed at
the conceptual and operational base of the model -
mostly its validity, reliability, operationalization of
expectations, and dimensional structure. In other
words, criticism against the SERVQUAL model was
directed to the use of (P-E) gap scores, length of the
questionnaire, predictive power of the instrument,
etc. (Babukus and Boller, 1992; Cronin and Taylor,
1992; Teas, 1993, 1994; Dabholkar, Shepherd, and
Thorpe, 2000). As a result, Cronin and Taylor (1992 and
1994) proposed an alternate scale to SERVQUAL -
what is referred to as the 'SERVPERF' scale. They
argued that performance is the measure that best
explains customers' perceptions of service quality, so
expectations should not be included in the service
quality measurement instrument. Besides theoretical
arguments, Cronin and Taylor (1992) also provided
empirical evidence across four industries (namely
banks, pest control, dry cleaning and fast food) to
corroborate the superiority of their “performance-
only” instrument over disconfirmation based
SERVQUAL Scale. Under the SERVPERF, a higher
perceived performance implies higher service quality
and customer satisfaction (Jain and Gupta, 2004). It
eliminates the expectation on the twenty-two items
and measures only performance on the original
version of SERVQUAL dimensions i.e., tangibility,
reliability, responsiveness, assurance and empathy
(Bolton and Drew, 1991; Babakus and Boller, 1992;
Hartline and Ferrell, 1996). In equation form, the
SERVPERF can be expressed as:
KSQi =∑ Pij
J=1
Where:
SQi = perceived service quality of an
individual 'I'
K = number of service attributes / items
Pi = perception of individual 'I' with
respect to performance of a service
firm attribute 'j'
In terms of methodology, the SERVPERF scale
represents a marked improvement over the
SERVQUAL scale. Not only is the scale more efficient in
reducing the number of items to be measured by
about 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
and customer satisfaction measured through the use
of single-item scale. This explains the considerable
support that has emerged over time in favour of the
SERVPERF scale (Churchill and Suprenant, 1982;
Bolton and Drew, 1991; Babukus and Boller, 1992;
Boulding, Kalra, Staelin, and Zeithaml, 1993; Gotlieb,
Grewal, and Brown, 1994). Realizing the advantages of
the SERVPERF scale over SERVQUAL, researchers
have increasingly started making use of the
performance only measure of service quality (Brady
and Robertson, 1992; Cronin and Taylor, 1992, 1994;
Andaleeb and Basu, 1994; Cronin, Brady and Hult,
2000; Bigne, Moliner, and Sanchey, 2003; Duncan and
Elliot, 2004). Conceding its superiority, even Zeithmal
(one of the founders of the SERVQUAL scale) in a
recent study observed that, “Our result is incompatible
with both the one-dimensional view of expectations
and the gap formation for service quality.” Instead we
find that perceived quality is directly influenced only
by perceptions of performance (Jain and Gupta, 2004).
This admittance cogently lends a testimony to the
superiority of the SERVPERF scale.
Recognizing the superiority of SERVPERF over
SERVQUAL, the present study has also used modified
SERVPERF scale to measure the service quality of
cellular companies under study. This 27-item
SERVPERF has been modified to suit the context of
cellular customers. Modifying the original SERVPERF
was intended to improve the validity and reliability of
the instrument. The questionnaire was divided into
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley58 59
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
two parts. The first part was designed to measure the
perception of customers regarding cellular services
provided by select cellular companies. The second part
of the questionnaire contained questions relating to
socio-demographic data about the respondents. The
researchers introduced the tool of measurement in
such a way that it briefly illustrated the topic of the
study and procedures of response. The measurement
grades were placed according to the 10-point Likert
scale. The scale was ordered regressively as Strongly
Agree (10) to Strongly Disagree (0). The study was
conducted in district Srinagar of Kashmir valley for four
months during the year 2013.
In order to analyze the collected data and confirm the
usefulness of the modified SERVPERF model to the
cellular companies' context, the statistical package for
the social science (SPSS-19) was used. The researcher
performed factor analysis on 27 items using the
Principal Component Analysis (PCA). Furthermore, the
construct validity was tested by applying Bartlett's Test
of Sphericity and the Kaiser–Mayer–Olkin measure of
sampling adequacy to analyze the strength of
association among variables. The result of Bartlett's
Test of Sphericity is 0.000, which meets the criteria of
value lower than 0.05 in order for the factor analysis to
be considered appropriate. Furthermore KMO
measure for sample adequacy for service quality
scores is 0.909 which exceeds satisfactory value of 0.6
(Tabachnik and Fidell, 2001) and revealed a Chi-Square
at 3731.731, (P≤0.000) which verified that correlation
matrix was not an identity matrix, thus validating the
suitability of factor analysis (Table 1.1).
Table: 1.1 - KMO and Bartlett's Test
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin measure of sampling adequacy 0.909
Bartlett’s Test of Spher icity (Approx. Chi-
Square)
3731.731
p-value 0.000*
*Significant at 1% level.
After these preliminary steps, factor analysis with
Principal Component Analysis as an extraction method
was performed using 400 questionnaires. To explore
the dimensionality of the twenty-seven (27) item
scale, the study used R-mode Principle Component
Analysis with a Varimax Rotation and Eigen value equal
to or more than 1, which extracted six factors with
explained variance of 55.921 percent in the data (Table
1.2). Most of the factor loading were greater than 0.50,
implying a reasonably high correlation between
extracted factors and the individual items. The
procedure resulted in six factors/dimensions totalling
27 items. These six factors are labelled as F1-'Network
quality'(excellent network coverage), F2-'Pricing'
(providing all the benefits for the price paid), F3-
'Reliability'(ability to perform the promised service
dependably and accurately), F4-'Assurance'
(knowledge and courtesy of employees and their
ability to inspire trust and confidence), F5-'Empathy'
(caring, individualized attention the firm provides to its
customers) and F6-'Responsiveness' (willingness to
help customers and provide prompt service). The first
factor (Network Quality) contains most of the items (8)
and explains most of the variance (12.402 percent) and
hence, is the important determinant of perceived
service quality dimensions in cellular services.
Table: 1.2 Summary of Results from Scale Purification: Dimensions, Factor Loadings,Communalities, Eigen Value, Explained Variance and Cronbach's Alpha
Items Factors Communalities
F1 F2 F3 F4 F5 F6
Emp 1 .100 .290 .170 .321 .627 -.061 616
Emp 2
.111
.057
-.045
.021
.812
.114
.691
Emp 3
.196
-.071
.372
.065
.593
.064
.432
Rel 4
.047
.037
.496
.219
.490
.101
.505
Rel 5
.069
.237
.488
.374
.191 -.047
.478
Rel 6
-.005
.211
.639
.243
.100
-.205
.580
NQ 7
.544
.209
.187
-.085
.284
.137
.481
Rel 8
.219
.237
.592
-.174
.304
.199
.481
NQ 9
.471
.039
.420
.306
.071
.187
.533
Rel 10
.421
.164
.425
.090
.067
.015
.397
Res 11
-.088
.177
.043
.366
-.033
.573
.623
Rel 12
.303
.061
.608
.108
-.063
.315
.563
NQ 13
.476
.393
.073
-.023
.082
.196
.666
Prc 14
.207
.639
.259
.074
.009
.183
.557
Prc 15
.130
.767
.117
.108
.028
.115
.645
Prc 16
.245
.742
.125
.195
.082
-.062
.675
Prc 17
.199
.664
.065
.107
.111
.164
.535
NQ 18
.608
.155
.150
.236
.126
.108
.499
NQ 19
.690
.281
-.029
.180
.079
-.031
.528
NQ 20
.604
.039
.236
.291
-.036
.265
.578
NQ 21
.533
.353
-.002
.206
.173
-.082
.488
NQ 22
.480
.128
.325
.347
.080
-.040
.481
Ass 23
.247
.156
.127
.658
.188
.089
.579
Ass 24
.317
.208
.136
.620
.183
.270
.653
Ass 25
.270
.112
.190
.657
.014
.280
.547
Res 26
.263
.104
.008
.051
.312
.697
.542
Res 27
.150
.395
.112
.321
.005
.484
.631
Eigen value
8.353
1.800
1.452
1.265
1.221
1.007
15.099
(Total)
Percentage (%) of Variance
12.402
11.080
9.435
8.877
7.893
6.233
55.921
Cronbach’s Alpha .801 .791 .768 .666 .737 .730 0.911
Number of Items 8 4 6 3 3 3 27
Cronbach's Alpha Test of Reliability
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley60 61
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
two parts. The first part was designed to measure the
perception of customers regarding cellular services
provided by select cellular companies. The second part
of the questionnaire contained questions relating to
socio-demographic data about the respondents. The
researchers introduced the tool of measurement in
such a way that it briefly illustrated the topic of the
study and procedures of response. The measurement
grades were placed according to the 10-point Likert
scale. The scale was ordered regressively as Strongly
Agree (10) to Strongly Disagree (0). The study was
conducted in district Srinagar of Kashmir valley for four
months during the year 2013.
In order to analyze the collected data and confirm the
usefulness of the modified SERVPERF model to the
cellular companies' context, the statistical package for
the social science (SPSS-19) was used. The researcher
performed factor analysis on 27 items using the
Principal Component Analysis (PCA). Furthermore, the
construct validity was tested by applying Bartlett's Test
of Sphericity and the Kaiser–Mayer–Olkin measure of
sampling adequacy to analyze the strength of
association among variables. The result of Bartlett's
Test of Sphericity is 0.000, which meets the criteria of
value lower than 0.05 in order for the factor analysis to
be considered appropriate. Furthermore KMO
measure for sample adequacy for service quality
scores is 0.909 which exceeds satisfactory value of 0.6
(Tabachnik and Fidell, 2001) and revealed a Chi-Square
at 3731.731, (P≤0.000) which verified that correlation
matrix was not an identity matrix, thus validating the
suitability of factor analysis (Table 1.1).
Table: 1.1 - KMO and Bartlett's Test
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin measure of sampling adequacy 0.909
Bartlett’s Test of Spher icity (Approx. Chi-
Square)
3731.731
p-value 0.000*
*Significant at 1% level.
After these preliminary steps, factor analysis with
Principal Component Analysis as an extraction method
was performed using 400 questionnaires. To explore
the dimensionality of the twenty-seven (27) item
scale, the study used R-mode Principle Component
Analysis with a Varimax Rotation and Eigen value equal
to or more than 1, which extracted six factors with
explained variance of 55.921 percent in the data (Table
1.2). Most of the factor loading were greater than 0.50,
implying a reasonably high correlation between
extracted factors and the individual items. The
procedure resulted in six factors/dimensions totalling
27 items. These six factors are labelled as F1-'Network
quality'(excellent network coverage), F2-'Pricing'
(providing all the benefits for the price paid), F3-
'Reliability'(ability to perform the promised service
dependably and accurately), F4-'Assurance'
(knowledge and courtesy of employees and their
ability to inspire trust and confidence), F5-'Empathy'
(caring, individualized attention the firm provides to its
customers) and F6-'Responsiveness' (willingness to
help customers and provide prompt service). The first
factor (Network Quality) contains most of the items (8)
and explains most of the variance (12.402 percent) and
hence, is the important determinant of perceived
service quality dimensions in cellular services.
Table: 1.2 Summary of Results from Scale Purification: Dimensions, Factor Loadings,Communalities, Eigen Value, Explained Variance and Cronbach's Alpha
Items Factors Communalities
F1 F2 F3 F4 F5 F6
Emp 1 .100 .290 .170 .321 .627 -.061 616
Emp 2
.111
.057
-.045
.021
.812
.114
.691
Emp 3
.196
-.071
.372
.065
.593
.064
.432
Rel 4
.047
.037
.496
.219
.490
.101
.505
Rel 5
.069
.237
.488
.374
.191 -.047
.478
Rel 6
-.005
.211
.639
.243
.100
-.205
.580
NQ 7
.544
.209
.187
-.085
.284
.137
.481
Rel 8
.219
.237
.592
-.174
.304
.199
.481
NQ 9
.471
.039
.420
.306
.071
.187
.533
Rel 10
.421
.164
.425
.090
.067
.015
.397
Res 11
-.088
.177
.043
.366
-.033
.573
.623
Rel 12
.303
.061
.608
.108
-.063
.315
.563
NQ 13
.476
.393
.073
-.023
.082
.196
.666
Prc 14
.207
.639
.259
.074
.009
.183
.557
Prc 15
.130
.767
.117
.108
.028
.115
.645
Prc 16
.245
.742
.125
.195
.082
-.062
.675
Prc 17
.199
.664
.065
.107
.111
.164
.535
NQ 18
.608
.155
.150
.236
.126
.108
.499
NQ 19
.690
.281
-.029
.180
.079
-.031
.528
NQ 20
.604
.039
.236
.291
-.036
.265
.578
NQ 21
.533
.353
-.002
.206
.173
-.082
.488
NQ 22
.480
.128
.325
.347
.080
-.040
.481
Ass 23
.247
.156
.127
.658
.188
.089
.579
Ass 24
.317
.208
.136
.620
.183
.270
.653
Ass 25
.270
.112
.190
.657
.014
.280
.547
Res 26
.263
.104
.008
.051
.312
.697
.542
Res 27
.150
.395
.112
.321
.005
.484
.631
Eigen value
8.353
1.800
1.452
1.265
1.221
1.007
15.099
(Total)
Percentage (%) of Variance
12.402
11.080
9.435
8.877
7.893
6.233
55.921
Cronbach’s Alpha .801 .791 .768 .666 .737 .730 0.911
Number of Items 8 4 6 3 3 3 27
Cronbach's Alpha Test of Reliability
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley60 61
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Cronbach's Alpha Test of Reliability is the most popular
estimate for measuring the internal consistency
(reliability) of items in a scale. In other words, it
measures the extent to which the responses collected
for a given item correlate with each other (Garson,
2002). The results of this test produce an α- score,
which is a number ranging between 0 and 1. According
to Garson (2002), the higher α -score is, the more
reliable the measured construct is. Furthermore,
according to Nunnally and Bernstein (1994), a score
exceeding 0.7 indicates high internal reliability of the
scale items, but there are still researchers who use
different cut-off α -scores like 0.8 or even 0.6 (Garson,
2002). However, the scores increase when the number
of items in a scale increases (Garson, 2002).
The reliability of the scale was also tested by using
Cronbach's Alpha (α) test. The present generated scale
achieved the scores of 0.911 (Table-1.2) which is highly
acceptable reliability coefficient (Nunnally, 1978). The
Cronbach's Alpha was also applied to each
factor/dimension which revealed an Alpha (α) score of
0.80 (network quality); 10.791 (pricing); 0.768
(reliability); 0.737 (empathy); 0.730 (responsiveness)
and 0.666 (assurance) which are all above 0.7 and are
highly reliable to measure the construct to which they
pertain except on assurance which is very close to 0.7
and can be regarded as pretty reliable.
Other Statistical Tools Used
For testing the various hypotheses set for the study,
various statistical tools and techniques were
employed. Common among these tools include
significance tests like students t-test and f-test. Data
gathered from respondents was processed and
analyzed with the help of SPSS 19.0 version. The
interpretation of data has been made on the basis of
mean and average scores. Keeping in view the control
variables in the study like gender and the connection
type, Student's t-Test was employed to test the
significance of means, if any. Variables like age, level of
education and time of network experience that were
more than two in number necessitated the use of f-test
to measure various statistical differences, if any.
Analysis
Service Quality in Cellular Companies
In line with the objectives, the present study seeks to
find out the service quality scores of customers of
different cellular companies. As mentioned earlier,
service quality was measured on a ten-point Likert
type (strongly disagree/ strongly agree) scale. To
measure the overall service quality of a sample
organisation, mean service quality scores on all
dimensions were calculated separately for each
service provider under study. The data in Table 1.4
presents information regarding the overall service
quality in cellular service companies. The table clearly
shows that all service providers, under reference, are
providing relatively better service quality to their
respective customers as the overall service quality
mean score is above 5. However, the overall service
quality score of Aircel is relatively high (6.19) followed
by Airtel (6.02), whereas service quality score of BSNL
(5.21) is the lowest followed by Vodafone (5.93).
Dimension-wise analysis in Table 1.4 clearly reveals
relatively better service performance of Aircel on
network quality with high service quality score of
(6.08) followed by Vodafone with the service quality
score of (5.83) while BSNL's service performance on
the said dimension is relatively poor with low service
quality score of (5.15) followed by Airtel with the
service quality score of (5.78). The data on pricing
dimension brings to light that the customers are
overall comfortable with the pricing option/best
pricing plans of Aircel followed by Airtel with the high
service quality scores of (6.24 and 5.96 respectively)
while Vodafone's and BSNL's performance on the said
dimension is relatively poor with low service quality
scores of (5.95 and 5.26 respectively). Further, the data
in Table 1.4 also reveals that both Airtel and Vodafone
have outperformed all other service providers under
reference on the reliability dimension with high
service quality scores (6.40 and 6.10 respectively)
whereas BSNL and Aircel have performed relatively
poor with low service quality scores of (5.24 and 6.4
respectively) on the said dimension. The service
quality score of Airtel on the assurance dimension has
been reported high at (6.35) followed by Aircel with
the service quality score of (6.34), while BSNL's
performance on the said dimension is reported
comparatively low with a low service quality score of
(5.45) followed by Vodafone with the service quality
score of (6.31). Service quality scores on the empathy
dimension evidences that both Aircel and Vodafone
have outperformed all other service providers under
reference with high service quality score of (6.38 and
6.19 respect ively) whi le Airte l and B S N L 's
performance on the said dimension is relatively low
with the low service quality scores of (6.07 and 5.40
respectively). On the responsiveness dimension,
Aircel's service quality score followed by Airtel are
comparatively high (5.73 and 5.58 respectively) while
BSNL's scores followed by Vodafone are relatively low
(4.79 and 5.25 respectively) on the same dimension.
Table: 1.4- Overall Comparative Service Quality Scores of Cellular Service Providers Averaged on all Dimensions
S.N. Dimensions Airtel N=(100)
Vodafone N=(100)
Aircel N=(100)
BSNL
N=(100)
1 Network quality 5.78 (3)
5.83 (2)
6.08 (1)
5.15 (4)
2
Pricing
5.96
(2)
5.95
(3)
6.24
(1)
5.26
(4)
3
Reliability
6.40
(1)
6.10
(2)
6.4
(3)
5.24
(4)
4
Assurance
6.35 (1)
6.31 (3)
6.34 (2)
5.45 (4)
5
Empathy
6.07
(3)
6.19 (2)
6.38 (1)
5.40 (4)
6
Responsiveness
5.58
(2)
5.25
(3)
5.73
(1)
4.79
(4)
Overall
(Averaged on all dimensions)
6.02
5.93
6.19
5.21
Rank 2 3 1 4
Note: Figures within parenthesis are ranks to each dimension across all service providers
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley62 63
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Cronbach's Alpha Test of Reliability is the most popular
estimate for measuring the internal consistency
(reliability) of items in a scale. In other words, it
measures the extent to which the responses collected
for a given item correlate with each other (Garson,
2002). The results of this test produce an α- score,
which is a number ranging between 0 and 1. According
to Garson (2002), the higher α -score is, the more
reliable the measured construct is. Furthermore,
according to Nunnally and Bernstein (1994), a score
exceeding 0.7 indicates high internal reliability of the
scale items, but there are still researchers who use
different cut-off α -scores like 0.8 or even 0.6 (Garson,
2002). However, the scores increase when the number
of items in a scale increases (Garson, 2002).
The reliability of the scale was also tested by using
Cronbach's Alpha (α) test. The present generated scale
achieved the scores of 0.911 (Table-1.2) which is highly
acceptable reliability coefficient (Nunnally, 1978). The
Cronbach's Alpha was also applied to each
factor/dimension which revealed an Alpha (α) score of
0.80 (network quality); 10.791 (pricing); 0.768
(reliability); 0.737 (empathy); 0.730 (responsiveness)
and 0.666 (assurance) which are all above 0.7 and are
highly reliable to measure the construct to which they
pertain except on assurance which is very close to 0.7
and can be regarded as pretty reliable.
Other Statistical Tools Used
For testing the various hypotheses set for the study,
various statistical tools and techniques were
employed. Common among these tools include
significance tests like students t-test and f-test. Data
gathered from respondents was processed and
analyzed with the help of SPSS 19.0 version. The
interpretation of data has been made on the basis of
mean and average scores. Keeping in view the control
variables in the study like gender and the connection
type, Student's t-Test was employed to test the
significance of means, if any. Variables like age, level of
education and time of network experience that were
more than two in number necessitated the use of f-test
to measure various statistical differences, if any.
Analysis
Service Quality in Cellular Companies
In line with the objectives, the present study seeks to
find out the service quality scores of customers of
different cellular companies. As mentioned earlier,
service quality was measured on a ten-point Likert
type (strongly disagree/ strongly agree) scale. To
measure the overall service quality of a sample
organisation, mean service quality scores on all
dimensions were calculated separately for each
service provider under study. The data in Table 1.4
presents information regarding the overall service
quality in cellular service companies. The table clearly
shows that all service providers, under reference, are
providing relatively better service quality to their
respective customers as the overall service quality
mean score is above 5. However, the overall service
quality score of Aircel is relatively high (6.19) followed
by Airtel (6.02), whereas service quality score of BSNL
(5.21) is the lowest followed by Vodafone (5.93).
Dimension-wise analysis in Table 1.4 clearly reveals
relatively better service performance of Aircel on
network quality with high service quality score of
(6.08) followed by Vodafone with the service quality
score of (5.83) while BSNL's service performance on
the said dimension is relatively poor with low service
quality score of (5.15) followed by Airtel with the
service quality score of (5.78). The data on pricing
dimension brings to light that the customers are
overall comfortable with the pricing option/best
pricing plans of Aircel followed by Airtel with the high
service quality scores of (6.24 and 5.96 respectively)
while Vodafone's and BSNL's performance on the said
dimension is relatively poor with low service quality
scores of (5.95 and 5.26 respectively). Further, the data
in Table 1.4 also reveals that both Airtel and Vodafone
have outperformed all other service providers under
reference on the reliability dimension with high
service quality scores (6.40 and 6.10 respectively)
whereas BSNL and Aircel have performed relatively
poor with low service quality scores of (5.24 and 6.4
respectively) on the said dimension. The service
quality score of Airtel on the assurance dimension has
been reported high at (6.35) followed by Aircel with
the service quality score of (6.34), while BSNL's
performance on the said dimension is reported
comparatively low with a low service quality score of
(5.45) followed by Vodafone with the service quality
score of (6.31). Service quality scores on the empathy
dimension evidences that both Aircel and Vodafone
have outperformed all other service providers under
reference with high service quality score of (6.38 and
6.19 respect ively) whi le Airte l and B S N L 's
performance on the said dimension is relatively low
with the low service quality scores of (6.07 and 5.40
respectively). On the responsiveness dimension,
Aircel's service quality score followed by Airtel are
comparatively high (5.73 and 5.58 respectively) while
BSNL's scores followed by Vodafone are relatively low
(4.79 and 5.25 respectively) on the same dimension.
Table: 1.4- Overall Comparative Service Quality Scores of Cellular Service Providers Averaged on all Dimensions
S.N. Dimensions Airtel N=(100)
Vodafone N=(100)
Aircel N=(100)
BSNL
N=(100)
1 Network quality 5.78 (3)
5.83 (2)
6.08 (1)
5.15 (4)
2
Pricing
5.96
(2)
5.95
(3)
6.24
(1)
5.26
(4)
3
Reliability
6.40
(1)
6.10
(2)
6.4
(3)
5.24
(4)
4
Assurance
6.35 (1)
6.31 (3)
6.34 (2)
5.45 (4)
5
Empathy
6.07
(3)
6.19 (2)
6.38 (1)
5.40 (4)
6
Responsiveness
5.58
(2)
5.25
(3)
5.73
(1)
4.79
(4)
Overall
(Averaged on all dimensions)
6.02
5.93
6.19
5.21
Rank 2 3 1 4
Note: Figures within parenthesis are ranks to each dimension across all service providers
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley62 63
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Service Quality Variation across
Demographic Variables
Service organizations need to provide consistent
service quality in order to maintain/increase their
profitability. In an attempt to study whether service
providers, under study, provide the same service
quality to all their customers, respondents were
divided into different groups, based on demographic
variables like age, gender, level of education, time of
network experience and connection type. Service
quality scores for different groups and for each service
provider were computed accordingly which are
presented below. T-Test and F-test were accordingly
performed to determine the level of significant
difference among all groups.
Service Quality Variation and Age
With a view to measure service quality variation, if any,
of different age groups of sample organizations,
respondents were categorized in three age groups viz.,
up to 20 years, 21-30 years, and above 30 years.
Service quality scores were calculated for each age
group of the respective service providers separately
followed by f-test which is presented in Table 1.5. The
data in the said table shows that there exists an
insignificant difference (P>0.05) in the overall quality
of services offered by Airtel and BSNL for all the three
age groups, whereas there exists a significant
difference in the overall quality of services offered by
Vodafone and Aircel as revealed by the p-value (p<
0.05).
From the analysis of data, it is further evident that the
service quality score of Airtel is comparatively high
(6.28) across all dimensions of service quality for all the stthree age groups (ranked 1 ) followed by Aircel (ranked
nd2 ) whereas the service quality scores of BSNL is
thlowest (ranked 4 ) across all the age groups, followed rdby Vodafone (ranked 3 ).
The dimension-wise analysis of the said table reveals
that the service quality scores of Airtel are relatively
high on the pricing dimension (6.62 and 5.86 st ndrespectively) in the 1 and 2 age groups followed by
empathy and reliability, whereas the company is
relatively low on network quality and responsiveness
dimensions. The service quality score of Airtel as rdreported by the 3 age group is relatively high on
network quality followed by reliability and assurance.
On the pricing dimension, the service quality score of
Vodafone is relatively high for all the three age groups,
followed by reliability and empathy dimensions.
However, it has scored relatively low scores in all the
three age groups as far as the responsiveness,
assurance and network quality dimensions are
concerned.
Aircel, on the other hand, has received the highest
scores on the pricing dimension for the first two age
groups i.e. up to 20 years and 21-30 years (6.78 and
6.37 respectively) followed by the empathy
dimension. On the reliability dimension, Aircel has st rdscored relatively high in the 1 and 3 age groups. As far
as the assurance and network quality dimensions are
concerned, all the three age groups have given low
scores. BSNL on the other hand, has received relatively
high scores on the pricing and reliability dimensions in st nd st ndthe 1 and 2 age groups (ranked 1 and 2
respectively) followed by the empathy dimension,
whereas it has scored relatively low on the assurance st nd and network quality dimensions in the 1 and 2 age
groups.
Service Quality Variation and Gender
The impact of gender differences, if any, of sample
organizations on service quality was also studied. The
gender-wise service quality scores of each service
provider are presented in Table 1.6 followed by t-test
to determine the level of significant difference. The
data in the said table brings to light that gender-wise,
there exists an insignificant difference (P>0.05) on
overall quality of cellular services among all cell phone
service providers under study, which means that
service providers do not consider gender while
providing cellphone services.
The table clearly reveals that Aircel evidences the
highest service quality scores across all dimensions in
both male and female categories, followed by Airtel nd(ranked 2 ) while Vodafone and BSNL have scored
rd thcomparatively low (ranked 3 and 4 respectively) in
both the above mentioned categories.
The dimensions-wise analysis of Airtel clearly shows
that it has scored the highest on the pricing dimension
for both the male and female categories, followed by ndthe reliability and empathy dimensions (ranked 2 and
rd3 respectively). However, it has scored low as far as
the assurance and network quality dimensions are
concerned (6.27, 6.17 and 6.00, 5.91 respectively).
Vodafone respondents on the other hand, have
different perceptions about the service quality
received from their provider. Analysis shows that
Vodafone has scored high on the pricing and reliability st nd dimensions (ranked 1 and 2 respectively) followed
by empathy and responsiveness, whereas it has scored
comparatively low on assurance and network quality
(5.83,6.08 and 5.49,5.80 respectively).
On the pricing dimension, Aircel has scored the highest
for both the male and female categories followed by
reliability, responsiveness and empathy dimensions nd rd th(ranked 2 , 3 and 4 respectively). However, it has low
scores as far as the assurance and network quality
dimensions are concerned (6.18, 5.34 and 6.27, 5.20
respectively).
stBSNL has been ranked 1 on pricing and reliability
dimensions by both male and female respondents. As
far as the empathy, responsiveness, assurance and
network quality dimensions are concerned it has
relatively low service quality scores.
Service Quality Variation and Education
With a view to study the service quality variation, if
any, of the sample organizations, at different levels of
education, respondents were grouped into three st nd levels viz., 1 level - up to secondary; 2 level -
rdGraduation; and 3 level - post-graduation. Service
quality scores at different levels of education were
calculated for each service provider separately
(presented in Table 1.7) followed by f-test. The analysis
in the table reveals that there exists an insignificant
difference (P>0.05) in the overall quality of service
among the different education groups among all the
service providers under study, which means that
service providers provide the same services to all
customers irrespective of their educational
background.
Moreover, the overall analysis shows that Airtel scores
are the highest on each dimension of service quality
for all educational groups, followed by Aircel and nd rdVodafone (ranked 2 and 3 respectively) whereas
BSNL scores are low among all educated groups as threported by the respective customers (ranked 4 ).
The dimension-wise analysis in the said table reveals
that Airtel has received the highest score on the pricing
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley64 65
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Service Quality Variation across
Demographic Variables
Service organizations need to provide consistent
service quality in order to maintain/increase their
profitability. In an attempt to study whether service
providers, under study, provide the same service
quality to all their customers, respondents were
divided into different groups, based on demographic
variables like age, gender, level of education, time of
network experience and connection type. Service
quality scores for different groups and for each service
provider were computed accordingly which are
presented below. T-Test and F-test were accordingly
performed to determine the level of significant
difference among all groups.
Service Quality Variation and Age
With a view to measure service quality variation, if any,
of different age groups of sample organizations,
respondents were categorized in three age groups viz.,
up to 20 years, 21-30 years, and above 30 years.
Service quality scores were calculated for each age
group of the respective service providers separately
followed by f-test which is presented in Table 1.5. The
data in the said table shows that there exists an
insignificant difference (P>0.05) in the overall quality
of services offered by Airtel and BSNL for all the three
age groups, whereas there exists a significant
difference in the overall quality of services offered by
Vodafone and Aircel as revealed by the p-value (p<
0.05).
From the analysis of data, it is further evident that the
service quality score of Airtel is comparatively high
(6.28) across all dimensions of service quality for all the stthree age groups (ranked 1 ) followed by Aircel (ranked
nd2 ) whereas the service quality scores of BSNL is
thlowest (ranked 4 ) across all the age groups, followed rdby Vodafone (ranked 3 ).
The dimension-wise analysis of the said table reveals
that the service quality scores of Airtel are relatively
high on the pricing dimension (6.62 and 5.86 st ndrespectively) in the 1 and 2 age groups followed by
empathy and reliability, whereas the company is
relatively low on network quality and responsiveness
dimensions. The service quality score of Airtel as rdreported by the 3 age group is relatively high on
network quality followed by reliability and assurance.
On the pricing dimension, the service quality score of
Vodafone is relatively high for all the three age groups,
followed by reliability and empathy dimensions.
However, it has scored relatively low scores in all the
three age groups as far as the responsiveness,
assurance and network quality dimensions are
concerned.
Aircel, on the other hand, has received the highest
scores on the pricing dimension for the first two age
groups i.e. up to 20 years and 21-30 years (6.78 and
6.37 respectively) followed by the empathy
dimension. On the reliability dimension, Aircel has st rdscored relatively high in the 1 and 3 age groups. As far
as the assurance and network quality dimensions are
concerned, all the three age groups have given low
scores. BSNL on the other hand, has received relatively
high scores on the pricing and reliability dimensions in st nd st ndthe 1 and 2 age groups (ranked 1 and 2
respectively) followed by the empathy dimension,
whereas it has scored relatively low on the assurance st nd and network quality dimensions in the 1 and 2 age
groups.
Service Quality Variation and Gender
The impact of gender differences, if any, of sample
organizations on service quality was also studied. The
gender-wise service quality scores of each service
provider are presented in Table 1.6 followed by t-test
to determine the level of significant difference. The
data in the said table brings to light that gender-wise,
there exists an insignificant difference (P>0.05) on
overall quality of cellular services among all cell phone
service providers under study, which means that
service providers do not consider gender while
providing cellphone services.
The table clearly reveals that Aircel evidences the
highest service quality scores across all dimensions in
both male and female categories, followed by Airtel nd(ranked 2 ) while Vodafone and BSNL have scored
rd thcomparatively low (ranked 3 and 4 respectively) in
both the above mentioned categories.
The dimensions-wise analysis of Airtel clearly shows
that it has scored the highest on the pricing dimension
for both the male and female categories, followed by ndthe reliability and empathy dimensions (ranked 2 and
rd3 respectively). However, it has scored low as far as
the assurance and network quality dimensions are
concerned (6.27, 6.17 and 6.00, 5.91 respectively).
Vodafone respondents on the other hand, have
different perceptions about the service quality
received from their provider. Analysis shows that
Vodafone has scored high on the pricing and reliability st nd dimensions (ranked 1 and 2 respectively) followed
by empathy and responsiveness, whereas it has scored
comparatively low on assurance and network quality
(5.83,6.08 and 5.49,5.80 respectively).
On the pricing dimension, Aircel has scored the highest
for both the male and female categories followed by
reliability, responsiveness and empathy dimensions nd rd th(ranked 2 , 3 and 4 respectively). However, it has low
scores as far as the assurance and network quality
dimensions are concerned (6.18, 5.34 and 6.27, 5.20
respectively).
stBSNL has been ranked 1 on pricing and reliability
dimensions by both male and female respondents. As
far as the empathy, responsiveness, assurance and
network quality dimensions are concerned it has
relatively low service quality scores.
Service Quality Variation and Education
With a view to study the service quality variation, if
any, of the sample organizations, at different levels of
education, respondents were grouped into three st nd levels viz., 1 level - up to secondary; 2 level -
rdGraduation; and 3 level - post-graduation. Service
quality scores at different levels of education were
calculated for each service provider separately
(presented in Table 1.7) followed by f-test. The analysis
in the table reveals that there exists an insignificant
difference (P>0.05) in the overall quality of service
among the different education groups among all the
service providers under study, which means that
service providers provide the same services to all
customers irrespective of their educational
background.
Moreover, the overall analysis shows that Airtel scores
are the highest on each dimension of service quality
for all educational groups, followed by Aircel and nd rdVodafone (ranked 2 and 3 respectively) whereas
BSNL scores are low among all educated groups as threported by the respective customers (ranked 4 ).
The dimension-wise analysis in the said table reveals
that Airtel has received the highest score on the pricing
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley64 65
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
dimension and received low scores on assurance,
responsiveness and network quality dimensions for all
educational groups. Among the graduate and post-
graduate respondents, Vodafone has received the
highest score on the pricing dimension followed by
reliability, empathy, responsiveness and assurance nd rd th thdimensions (ranked 2 , 3 , 4 and 5 respectively). On
the other hand, on the network quality dimension,
Vodafone has received a low score from all educational
groups.
The data for Aircel shows that it has received the
highest score from all educational groups on the
pricing dimension followed by the empathy dimension nd(ranked 2 ). Analyzing the responsiveness, assurance
and network quality dimensions, the data reveals low
scores among the secondary level and graduate rd th threspondents (ranked 3 , 4 and 5 respectively). BSNL
however, has received the highest score on the
reliability dimension among the secondary level and
post-graduate respondents followed by low scores on thassurance and network quality dimensions (ranked 5
thand 6 respectively).
Service Quality Variation and Time of
Network Experience
With a view to study the service quality variation if any,
with regard to time of network experience of the
sample organizations, respondents were divided into stthree groups, viz., up to 6 months (group 1 ), 7-12
nd rdmonths (group 2 ) and more than a year (group 3 ).
Service quality scores were calculated for each group
and for each service provider separately (presented in
Table 1.8) followed by f-test. From the analysis in the
table, it is quite evident that there exists an
insignificant difference (p >0.5) in the overall quality of
services among all service providers under study, in
terms of time of network experience for all the groups.
The data in Table 1.8 reveals that Airtel has received
the highest score on overall service quality (6.46)
followed by Aircel and Vodafone (6.34 and 6.11
respectively). BSNL, however, figures lowest on overall
service quality among all the three groups as disclosed
by the analysis (5.1). The dimension-wise analysis of
the said table shows that on the pricing dimension,
Airtel has scored the highest as reported by the three
groups of network experience, followed by reliability. nd rdIn the 2 and 3 group (network experience) Airtel has
received low scores as far as the responsiveness and
network quality dimensions are concerned. Vodafone
respondents on the other hand, have different
perceptions about their network experience. Analysis
shows that Vodafone has scored the highest on the
pricing dimension for all the three groups, followed by
reliability, empathy and responsiveness, whereas it
has scored comparatively low on assurance and
network quality.
Aircel has scored high on the pricing and empathy st nddimensions (ranked 1 and 2 respectively) as
nd rdreported by the 2 and 3 groups respectively.
However, it has scored relatively low in all the three
groups as far as the assurance and network quality th th dimensions are concerned (ranked 5 and 6
respectively).
BSNL has scored the highest on the reliability nd rddimension by the 2 and 3 groups of network
experience, followed by responsiveness, assurance nd rd thand network quality dimensions (ranked 2 , 3 and 4
strespectively) whereas in the group 1 , it has low scores
on assurance and network quality dimensions (ranked th th5 and 6 respectively).
Service Quality Variation and Connection
Type
With a view to study service quality variation if any,
with regard to connect ion type of sample
organizations, respondents were divided into two
groups, viz., prepaid and post-paid. Service quality
scores were calculated for each group and for each
service provider separately (presented in Table 1.9)
followed by t-test. Respondents of all the cell phone
service providing companies under study have
reported an insignificant difference (P>0.05) in the
overall quality of services for both the prepaid and
post-paid categories meaning thereby that all cell
phone service providers are delivering the same
service quality to both pre and post- paid customers.
The table clearly reveals that Airtel followed by Aircel
have received relatively high service quality scores stacross all dimensions of service quality (ranked 1 and
nd2 respectively) while Vodafone, followed by BSNL, rd thhave scored comparatively low (ranked 3 and 4
respectively) on all dimensions of service quality.
The dimension-wise analysis shows that in both the
groups i.e. prepaid as well as the post-paid group,
Airtel has received fairly high scores on the pricing
dimension, followed by the reliability dimension st nd(ranked 1 and 2 respectively) while it figures
relatively low on responsiveness, assurance and rd th thnetwork quality dimensions (ranked 3 , 4 and 5
respectively). Vodafone scores relatively high on the st ndpricing dimension in both the groups (ranked 1 and 2
respectively) followed by the empathy dimension
while it figures relatively low on responsiveness, rdassurance and network quality dimensions (ranked 3 ,
th th4 and 5 respectively).
Aircel has received the highest score on the pricing
dimension followed by empathy and responsiveness nd rddimensions (ranked 2 and 3 respectively). On the
assurance and network quality dimensions, it has
received low service quality scores (6.28, 6.32 and
5.98, 6.18) as is revealed by the analysis.
BSNL however, has scored the highest on the pricing
dimension for prepaid services, followed by low scores
on the network quality dimension on post-paid
services. However, post-paid users gave a high score on
the reliability dimension, followed by low scores on the
pricing dimension.
Conclusion and Managerial Implications
In this study, a scale for measuring the service quality
of cellular service companies was proposed through
exploratory factor analyses result ing in s ix
factors/dimensions namely: 'Network quality',
'Pricing', 'Reliability', 'Assurance', 'Empathy' and
'Responsiveness'. The first factor - Network quality -
followed by Pricing and Reliability contained most of
the elements (8, 4 and 6 respectively) and explained
most of the variance (12.402 percent, 11.080 percent
and 9.435 percent respectively); this clearly indicates
that the most important factor in predicting cellular
service quality evaluation is network quality, followed
by pricing and reliability. These research findings are in
harmony with the research findings of Cavana,
Corbett, and Lo, (2007), Khan (2010), OluOjo (2010),
Rakumar and Harish (2011), Siew, Ayankule, Hanisah
and Alan, (2011), Shahzad and Saima (2012) and Ode
Egana (2013). Along with the important findings
related to quality of cellular services, two more
dimensions i.e. network quality and pricing were
added to the original SERVPERF scale which is itself
another important contribution. At the same time, the
modified questionnaire can also provide guidelines
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley66 67
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
dimension and received low scores on assurance,
responsiveness and network quality dimensions for all
educational groups. Among the graduate and post-
graduate respondents, Vodafone has received the
highest score on the pricing dimension followed by
reliability, empathy, responsiveness and assurance nd rd th thdimensions (ranked 2 , 3 , 4 and 5 respectively). On
the other hand, on the network quality dimension,
Vodafone has received a low score from all educational
groups.
The data for Aircel shows that it has received the
highest score from all educational groups on the
pricing dimension followed by the empathy dimension nd(ranked 2 ). Analyzing the responsiveness, assurance
and network quality dimensions, the data reveals low
scores among the secondary level and graduate rd th threspondents (ranked 3 , 4 and 5 respectively). BSNL
however, has received the highest score on the
reliability dimension among the secondary level and
post-graduate respondents followed by low scores on thassurance and network quality dimensions (ranked 5
thand 6 respectively).
Service Quality Variation and Time of
Network Experience
With a view to study the service quality variation if any,
with regard to time of network experience of the
sample organizations, respondents were divided into stthree groups, viz., up to 6 months (group 1 ), 7-12
nd rdmonths (group 2 ) and more than a year (group 3 ).
Service quality scores were calculated for each group
and for each service provider separately (presented in
Table 1.8) followed by f-test. From the analysis in the
table, it is quite evident that there exists an
insignificant difference (p >0.5) in the overall quality of
services among all service providers under study, in
terms of time of network experience for all the groups.
The data in Table 1.8 reveals that Airtel has received
the highest score on overall service quality (6.46)
followed by Aircel and Vodafone (6.34 and 6.11
respectively). BSNL, however, figures lowest on overall
service quality among all the three groups as disclosed
by the analysis (5.1). The dimension-wise analysis of
the said table shows that on the pricing dimension,
Airtel has scored the highest as reported by the three
groups of network experience, followed by reliability. nd rdIn the 2 and 3 group (network experience) Airtel has
received low scores as far as the responsiveness and
network quality dimensions are concerned. Vodafone
respondents on the other hand, have different
perceptions about their network experience. Analysis
shows that Vodafone has scored the highest on the
pricing dimension for all the three groups, followed by
reliability, empathy and responsiveness, whereas it
has scored comparatively low on assurance and
network quality.
Aircel has scored high on the pricing and empathy st nddimensions (ranked 1 and 2 respectively) as
nd rdreported by the 2 and 3 groups respectively.
However, it has scored relatively low in all the three
groups as far as the assurance and network quality th th dimensions are concerned (ranked 5 and 6
respectively).
BSNL has scored the highest on the reliability nd rddimension by the 2 and 3 groups of network
experience, followed by responsiveness, assurance nd rd thand network quality dimensions (ranked 2 , 3 and 4
strespectively) whereas in the group 1 , it has low scores
on assurance and network quality dimensions (ranked th th5 and 6 respectively).
Service Quality Variation and Connection
Type
With a view to study service quality variation if any,
with regard to connect ion type of sample
organizations, respondents were divided into two
groups, viz., prepaid and post-paid. Service quality
scores were calculated for each group and for each
service provider separately (presented in Table 1.9)
followed by t-test. Respondents of all the cell phone
service providing companies under study have
reported an insignificant difference (P>0.05) in the
overall quality of services for both the prepaid and
post-paid categories meaning thereby that all cell
phone service providers are delivering the same
service quality to both pre and post- paid customers.
The table clearly reveals that Airtel followed by Aircel
have received relatively high service quality scores stacross all dimensions of service quality (ranked 1 and
nd2 respectively) while Vodafone, followed by BSNL, rd thhave scored comparatively low (ranked 3 and 4
respectively) on all dimensions of service quality.
The dimension-wise analysis shows that in both the
groups i.e. prepaid as well as the post-paid group,
Airtel has received fairly high scores on the pricing
dimension, followed by the reliability dimension st nd(ranked 1 and 2 respectively) while it figures
relatively low on responsiveness, assurance and rd th thnetwork quality dimensions (ranked 3 , 4 and 5
respectively). Vodafone scores relatively high on the st ndpricing dimension in both the groups (ranked 1 and 2
respectively) followed by the empathy dimension
while it figures relatively low on responsiveness, rdassurance and network quality dimensions (ranked 3 ,
th th4 and 5 respectively).
Aircel has received the highest score on the pricing
dimension followed by empathy and responsiveness nd rddimensions (ranked 2 and 3 respectively). On the
assurance and network quality dimensions, it has
received low service quality scores (6.28, 6.32 and
5.98, 6.18) as is revealed by the analysis.
BSNL however, has scored the highest on the pricing
dimension for prepaid services, followed by low scores
on the network quality dimension on post-paid
services. However, post-paid users gave a high score on
the reliability dimension, followed by low scores on the
pricing dimension.
Conclusion and Managerial Implications
In this study, a scale for measuring the service quality
of cellular service companies was proposed through
exploratory factor analyses result ing in s ix
factors/dimensions namely: 'Network quality',
'Pricing', 'Reliability', 'Assurance', 'Empathy' and
'Responsiveness'. The first factor - Network quality -
followed by Pricing and Reliability contained most of
the elements (8, 4 and 6 respectively) and explained
most of the variance (12.402 percent, 11.080 percent
and 9.435 percent respectively); this clearly indicates
that the most important factor in predicting cellular
service quality evaluation is network quality, followed
by pricing and reliability. These research findings are in
harmony with the research findings of Cavana,
Corbett, and Lo, (2007), Khan (2010), OluOjo (2010),
Rakumar and Harish (2011), Siew, Ayankule, Hanisah
and Alan, (2011), Shahzad and Saima (2012) and Ode
Egana (2013). Along with the important findings
related to quality of cellular services, two more
dimensions i.e. network quality and pricing were
added to the original SERVPERF scale which is itself
another important contribution. At the same time, the
modified questionnaire can also provide guidelines
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley66 67
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
through which service planners can design marketing
strategies that will help to improve the overall quality
of cellular services.
The analysis of service quality scores across all
demographic variables reveals that all service
providers under reference, are providing relatively
better service quality to their respective customers, as
their overall service quality mean score is above 5.
However, service quality of Aircel is the best (ranked st nd1 ) followed by Airtel (ranked 2 ) while the overall
thservice quality of BSNL is the poorest (ranked 4 ) with rdVodafone ahead (ranked 3 ). Further, the analysis of
service quality scores across demographic variables
also reveals that there exists an insignificant variation
(p>0.05) in service quality on nearly all demographic
variables in all cellular companies under reference,
meaning that cellular service operators provide the
same service quality to all customers alike and don't
differentiate their services on demographic basis.
Measuring service quality enables an organization to
know its position in the market and provides a strategic
advantage to enhance its competitiveness. It also
presents areas of strengths/ weaknesses that offer
opportunities to the organization to initiate an
appropriate response to focus and improve salient
attributes of customer perceived service quality. The
research instrument used in the present study, if
implemented in the right perspective, will surely go a
long way in identifying the area/s for improvement and
the area/s to be capitalized to meet/beat competition.
Mobile operators are vigorously investing in network
coverage, up-gradation and quality, competitive
pricing, and diversified offering to attract new/retain
existing customers. The results of this study
substantiate the response strategy of mobile phone
operators to enhance network quality, competitive
pricing and reliability dimensions that are vital to affect
the customers' perception of quality of cellular
services.
Tab
le 1
.5:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r A
ge
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Age
in Y
ears
Age
in Y
ears
Age
in Y
ears
Age
in Y
ears
Up
to
20
N=7
2
2
1-3
0
N=2
5
A
bo
ve 3
0
N=3
Up
to
20
N=6
0 2
1-3
0
N=3
6 A
bo
ve 3
0
N=4
U
p t
o 2
0
N=6
4
2
1-3
0
N=2
1
Ab
ove
30
N=1
5
Up
to
20
N=4
1
2
1-3
0
N=2
4
A
bo
ve 3
0N
=35
Net
wo
rk q
ual
ity
6
.08
(6)
5
.59
(6)
6
.81
(1)
5
.90
(6)
5.4
0
(5)
4.0
1
(5)
6
.24
(5)
5
.79
(5)
5
.37
(6)
5
.23
(6)
5.2
7
(5)
4.8
4(1
)
Pri
cin
g
6.6
2
(1)
5
.86
(1)
6
.46
(6)
6
.39
(1)
5.9
2
(1)
4.1
3
(2)
6
.78
(1)
6
.37
(1)
5
.39
(5)
5
.60
(1)
5.5
6
(2)
4.6
9(5
)
Rel
iab
ility
6
.50
(3)
5
.83
(3)
6
.66
(2)
6
.37
(2)
5.8
2
(2)
4.1
5
(1)
6
.67
(2)
6
.08
(4)
5
.46
(1)
5
.55
(2)
5.6
1
(1)
4.8
0(2
)
Ass
ura
nce
6
.40
(5
)
5.7
6
(5)
6
.64
(3)
6
.22
(5)
5.7
2 (4
) 4
.10
(4
)
6.5
6
(4)
6
.08
(4
)
5.4
0
(4)
5
.46
(5
) 5
.48
(4
) 4.7
8(3
)
Emp
ath
y
6.5
1
(2)
5.8
2
(2)
6.5
9 (5
)
6.3
3 (3
)
5.8
2 (2
)
4.1
2
(3)
6.6
7
(2)
6.1
8
(2)
5.4
1
(3)
5.5
4
(3)
5.5
5
(3)
4.7
6(4
)
Res
po
nsi
ven
ess
6
.47
(4
)
5.8
0
(4)
6.6
3 (4
)
6.3
1 (4
)
5.7
8 (3
)
4.1
2
(3)
6.6
4
(3)
6.1
1
(3)
5.4
2
(2)
5.5
2
(4)
5.5
5
(3)
4.7
8(3
)
Ove
rall
(ave
rage
d o
n a
ll d
ime
nsi
on
s)
6.4
3
5.7
7
6.6
3
6.2
5 5
.74
4.1
0
6.5
9
6.1
0
5.4
0
5.4
8 5.5
0
4.7
7
Me
an S
core
s (a
ve
rage
d
o
n a
ge g
rou
ps)
6.2
8
5.3
6
6.0
3
5.2
5
Ran
k
1
3
2
4
f-
Val
ue
2.0
54
4.6
92
4.2
80
1.1
07
p
-Val
ue
.13
4.0
11
*.0
17
*.3
35
No
te:
Fig
ure
s w
ith
in p
are
nth
esis
are
ra
nks
to
ea
ch d
imen
sio
n a
cro
ss a
ll se
rvic
e p
rovi
der
s *
Sig
nifi
can
t a
t 5
% L
evel
(p
<0.0
5)
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley68 69
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
through which service planners can design marketing
strategies that will help to improve the overall quality
of cellular services.
The analysis of service quality scores across all
demographic variables reveals that all service
providers under reference, are providing relatively
better service quality to their respective customers, as
their overall service quality mean score is above 5.
However, service quality of Aircel is the best (ranked st nd1 ) followed by Airtel (ranked 2 ) while the overall
thservice quality of BSNL is the poorest (ranked 4 ) with rdVodafone ahead (ranked 3 ). Further, the analysis of
service quality scores across demographic variables
also reveals that there exists an insignificant variation
(p>0.05) in service quality on nearly all demographic
variables in all cellular companies under reference,
meaning that cellular service operators provide the
same service quality to all customers alike and don't
differentiate their services on demographic basis.
Measuring service quality enables an organization to
know its position in the market and provides a strategic
advantage to enhance its competitiveness. It also
presents areas of strengths/ weaknesses that offer
opportunities to the organization to initiate an
appropriate response to focus and improve salient
attributes of customer perceived service quality. The
research instrument used in the present study, if
implemented in the right perspective, will surely go a
long way in identifying the area/s for improvement and
the area/s to be capitalized to meet/beat competition.
Mobile operators are vigorously investing in network
coverage, up-gradation and quality, competitive
pricing, and diversified offering to attract new/retain
existing customers. The results of this study
substantiate the response strategy of mobile phone
operators to enhance network quality, competitive
pricing and reliability dimensions that are vital to affect
the customers' perception of quality of cellular
services.
Tab
le 1
.5:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r A
ge
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Age
in Y
ears
Age
in Y
ears
Age
in Y
ears
Age
in Y
ears
Up
to
20
N=7
2
2
1-3
0
N=2
5
A
bo
ve 3
0
N=3
Up
to
20
N=6
0 2
1-3
0
N=3
6 A
bo
ve 3
0
N=4
U
p t
o 2
0
N=6
4
2
1-3
0
N=2
1
Ab
ove
30
N=1
5
Up
to
20
N=4
1
2
1-3
0
N=2
4
A
bo
ve 3
0N
=35
Net
wo
rk q
ual
ity
6
.08
(6)
5
.59
(6)
6
.81
(1)
5
.90
(6)
5.4
0
(5)
4.0
1
(5)
6
.24
(5)
5
.79
(5)
5
.37
(6)
5
.23
(6)
5.2
7
(5)
4.8
4(1
)
Pri
cin
g
6.6
2
(1)
5
.86
(1)
6
.46
(6)
6
.39
(1)
5.9
2
(1)
4.1
3
(2)
6
.78
(1)
6
.37
(1)
5
.39
(5)
5
.60
(1)
5.5
6
(2)
4.6
9(5
)
Rel
iab
ility
6
.50
(3)
5
.83
(3)
6
.66
(2)
6
.37
(2)
5.8
2
(2)
4.1
5
(1)
6
.67
(2)
6
.08
(4)
5
.46
(1)
5
.55
(2)
5.6
1
(1)
4.8
0(2
)
Ass
ura
nce
6
.40
(5
)
5.7
6
(5)
6
.64
(3)
6
.22
(5)
5.7
2 (4
) 4
.10
(4
)
6.5
6
(4)
6
.08
(4
)
5.4
0
(4)
5
.46
(5
) 5
.48
(4
) 4.7
8(3
)
Emp
ath
y
6.5
1
(2)
5.8
2
(2)
6.5
9 (5
)
6.3
3 (3
)
5.8
2 (2
)
4.1
2
(3)
6.6
7
(2)
6.1
8
(2)
5.4
1
(3)
5.5
4
(3)
5.5
5
(3)
4.7
6(4
)
Res
po
nsi
ven
ess
6
.47
(4
)
5.8
0
(4)
6.6
3 (4
)
6.3
1 (4
)
5.7
8 (3
)
4.1
2
(3)
6.6
4
(3)
6.1
1
(3)
5.4
2
(2)
5.5
2
(4)
5.5
5
(3)
4.7
8(3
)
Ove
rall
(ave
rage
d o
n a
ll d
ime
nsi
on
s)
6.4
3
5.7
7
6.6
3
6.2
5 5
.74
4.1
0
6.5
9
6.1
0
5.4
0
5.4
8 5.5
0
4.7
7
Me
an S
core
s (a
ve
rage
d
o
n a
ge g
rou
ps)
6.2
8
5.3
6
6.0
3
5.2
5
Ran
k
1
3
2
4
f-
Val
ue
2.0
54
4.6
92
4.2
80
1.1
07
p
-Val
ue
.13
4.0
11
*.0
17
*.3
35
No
te:
Fig
ure
s w
ith
in p
are
nth
esis
are
ra
nks
to
ea
ch d
imen
sio
n a
cro
ss a
ll se
rvic
e p
rovi
der
s *
Sig
nifi
can
t a
t 5
% L
evel
(p
<0.0
5)
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley68 69
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Tab
le 1
.6:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r G
en
de
r
Serv
ice
Qu
alit
y D
ime
nsi
on
s
Ce
ll P
ho
ne
Op
era
tors
Air
tel
V
od
afo
ne
A
irce
l
BS
NL
Gen
der
Gen
der
G
end
er
Gen
der
Mal
e
N=7
6
Fem
ale
N=2
4 M
ale
N=4
9 Fe
mal
e
N=5
1
Mal
e
N=6
0
Fem
ale
N=4
0
Mal
e
N=4
5
Fem
ale
N=5
5
Net
wo
rk q
ual
ity
6
.00
(6)
5
.91
(6)
5.4
9
(6)
5.8
0
(6)
5
.84
(6)
6
.27
(6)
5
.20
(6)
5
.03
(5)
Pri
cin
g
6.4
7 (1
)
6.3
1
(1)
6.0
0
(1)
6.2
6
(1)
6
.44
(1)
6
.55
(1)
5
.41
(1)
5
.16
(3)
Rel
iab
ility
6
.35
(3)
6
.30
(2)
5.9
9
(2)
6.1
8
(2)
6
.26
(3)
6
.53
(2)
5
.40
(2)
5
.22
(1)
Ass
ura
nce
6
.27
(5)
6
.17
(5)
5.8
3 (5
) 6
.08
(5
)
6.1
8
(5)
6
.45
(5
)
5.3
4
(5)
5
.13
(4
)
Emp
ath
y
6.3
6 (2
)
6.2
6 (3
)
5.9
4 (3
)
6.1
7
(3)
6.2
9
(2)
6.5
1
(3)
5.3
9
(3)
5.1
7
(2)
Res
po
nsi
ven
ess
6
.33
(4)
6.2
4 (4
)
5.9
2 (4
)
6.1
4
(4)
6.2
4
(4)
6.5
0
(4)
5.3
8
(4)
5.1
7
(2)
Ove
rall
(av
era
ged
on
all
dim
en
sio
ns)
6.2
9
6.1
9 5
.86
6.1
0
6.2
0
6.4
6
5.3
5
5.1
4
Me
an S
core
s (a
vera
ged
on
ge
nd
er)
6.2
4 5
.98
6.3
3
5.2
5
Ran
k
2 3
1
4
t-V
alu
e
.75
4 -1
.49
6
-.9
12
.4
64
p
-Val
ue
*.4
54
.13
8.3
64
.64
3
No
te:
Fig
ure
s w
ith
in p
are
nth
esis
are
ra
nks
to
ea
ch d
imen
sio
n a
cro
ss a
ll se
rvic
e p
rovi
der
s *
Insi
gn
ifica
nt
at
5%
Lev
el (
p>0
.05
)
Tab
le 1
.7:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r Le
vel o
f Ed
uca
�o
n
Serv
ice
Qu
alit
y
Dim
en
sio
ns
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Edu
ca�
on
leve
l
Edu
ca�
on
lev
el
Edu
ca�
on
leve
l
Edu
ca�
on
leve
l
Up to secondary
N=49
Gradua�on
N=45
Post-gradua�on
N=6
Up to secondary
N=16
Gradua�on
N=27
Post-gradua�on
N=57
Up to secondary
N=41
Gradua�on
N=27
Post-gradua�on
N=32
Up to secondary
N=39
Gradua�on
N=24
Post-gradua�on
N=37
Net
wo
rk q
ual
ity
6
.03
(6)
5
.76
(6)
7
.19
(6)
5
.57
(4)
6.0
4
(5)
5.4
8
(6)
5
.91
(6)
6
.09
(6)
6
.08
(5)
4
.98
(6)
5.0
6
(5)
5
.27
(4)
Pri
cin
g
6.5
4
(1)
6
.19
(1)
7
.36
(1)
5
.97
(2)
6.5
4
(1)
5.9
9
(1)
6
.26
(1)
6
.73
(1)
6
.56
(1)
5
.08
(4)
5.3
1
(1)
5
.45
(2)
Rel
iab
ility
6
.40
(3)
6
.15
(2)
7
.21
(5)
6
.07
(1)
6.3
6
(3)
5.9
6
(2)
6
.21
(2)
6
.56
(3)
6
.39
(3)
5
.13
(1)
5.2
6
(2)
5
.51
(1)
Ass
ura
nce
6
.32
(5
)
6.0
3
(5)
7
.26
(3)
5
.87
(3)
6.3
1 (4
) 5
.81
(5
)
6.1
3
(5)
6
.46
(5
)
6.3
4
(4)
5
.07
(5
) 5
.21
(4
)
5.4
1(3
)
Emp
ath
y
6.4
2
(2)
6.1
2
(3)
7.2
8 (2
)
5.9
7 (2
)
6.4
0 (2
)
5.9
2
(3)
6.2
0
(3)
6.5
9
(2)
6.4
3
(2)
5.0
9
(3)
5.2
6
(2)
5.4
5(2
)
Res
po
nsi
ven
ess
6
.38
(4
)
6.1
0
(4)
7.2
5 (4
)
5.9
7 (2
)
6.3
6 (3
)
5.9
0
(4)
6.1
8
(4)
6.5
4
(4)
6.3
9
(3)
5.1
0
(2)
5.3
4
(4)
5.4
5(2
)
Ove
rall
(ave
rage
d o
n a
ll
dim
en
sio
ns)
6.3
4
6
.05
7
.25
5
.90
6.3
3 5
.84
6
.14
6
.49
6
.36
5.0
7
5.2
2
5
.42
Me
an S
core
s (a
vera
ged
o
n le
vel o
f e
du
ca�
on
)
6.5
4
6.0
2
6.3
3
5.2
4
R
ank
1
3
2
4
f-
Val
ue
3.0
60
.81
9
.37
6
.08
7
p
-Val
ue
*
.05
1
.44
4
.68
7
.91
7
N
ote
: Fi
gu
res
wit
hin
pa
ren
thes
is a
re r
an
ks t
o e
ach
dim
ensi
on
acr
oss
all
serv
ice
pro
vid
ers
*In
sig
nifi
can
t a
t 5
% L
evel
(p
>0.0
5)
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley70 71
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Tab
le 1
.6:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r G
en
de
r
Serv
ice
Qu
alit
y D
ime
nsi
on
s
Ce
ll P
ho
ne
Op
era
tors
Air
tel
V
od
afo
ne
A
irce
l
BS
NL
Gen
der
Gen
der
G
end
er
Gen
der
Mal
e
N=7
6
Fem
ale
N=2
4 M
ale
N=4
9 Fe
mal
e
N=5
1
Mal
e
N=6
0
Fem
ale
N=4
0
Mal
e
N=4
5
Fem
ale
N=5
5
Net
wo
rk q
ual
ity
6
.00
(6)
5
.91
(6)
5.4
9
(6)
5.8
0
(6)
5
.84
(6)
6
.27
(6)
5
.20
(6)
5
.03
(5)
Pri
cin
g
6.4
7 (1
)
6.3
1
(1)
6.0
0
(1)
6.2
6
(1)
6
.44
(1)
6
.55
(1)
5
.41
(1)
5
.16
(3)
Rel
iab
ility
6
.35
(3)
6
.30
(2)
5.9
9
(2)
6.1
8
(2)
6
.26
(3)
6
.53
(2)
5
.40
(2)
5
.22
(1)
Ass
ura
nce
6
.27
(5)
6
.17
(5)
5.8
3 (5
) 6
.08
(5
)
6.1
8
(5)
6
.45
(5
)
5.3
4
(5)
5
.13
(4
)
Emp
ath
y
6.3
6 (2
)
6.2
6 (3
)
5.9
4 (3
)
6.1
7
(3)
6.2
9
(2)
6.5
1
(3)
5.3
9
(3)
5.1
7
(2)
Res
po
nsi
ven
ess
6
.33
(4)
6.2
4 (4
)
5.9
2 (4
)
6.1
4
(4)
6.2
4
(4)
6.5
0
(4)
5.3
8
(4)
5.1
7
(2)
Ove
rall
(av
era
ged
on
all
dim
en
sio
ns)
6.2
9
6.1
9 5
.86
6.1
0
6.2
0
6.4
6
5.3
5
5.1
4
Me
an S
core
s (a
vera
ged
on
ge
nd
er)
6.2
4 5
.98
6.3
3
5.2
5
Ran
k
2 3
1
4
t-V
alu
e
.75
4 -1
.49
6
-.9
12
.4
64
p
-Val
ue
*.4
54
.13
8.3
64
.64
3
No
te:
Fig
ure
s w
ith
in p
are
nth
esis
are
ra
nks
to
ea
ch d
imen
sio
n a
cro
ss a
ll se
rvic
e p
rovi
der
s *
Insi
gn
ifica
nt
at
5%
Lev
el (
p>0
.05
)
Tab
le 1
.7:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r Le
vel o
f Ed
uca
�o
n
Serv
ice
Qu
alit
y
Dim
en
sio
ns
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Edu
ca�
on
leve
l
Edu
ca�
on
lev
el
Edu
ca�
on
leve
l
Edu
ca�
on
leve
l
Up to secondary
N=49
Gradua�on
N=45
Post-gradua�on
N=6
Up to secondary
N=16
Gradua�on
N=27
Post-gradua�on
N=57
Up to secondary
N=41
Gradua�on
N=27
Post-gradua�on
N=32
Up to secondary
N=39
Gradua�on
N=24
Post-gradua�on
N=37
Net
wo
rk q
ual
ity
6
.03
(6)
5
.76
(6)
7
.19
(6)
5
.57
(4)
6.0
4
(5)
5.4
8
(6)
5
.91
(6)
6
.09
(6)
6
.08
(5)
4
.98
(6)
5.0
6
(5)
5
.27
(4)
Pri
cin
g
6.5
4
(1)
6
.19
(1)
7
.36
(1)
5
.97
(2)
6.5
4
(1)
5.9
9
(1)
6
.26
(1)
6
.73
(1)
6
.56
(1)
5
.08
(4)
5.3
1
(1)
5
.45
(2)
Rel
iab
ility
6
.40
(3)
6
.15
(2)
7
.21
(5)
6
.07
(1)
6.3
6
(3)
5.9
6
(2)
6
.21
(2)
6
.56
(3)
6
.39
(3)
5
.13
(1)
5.2
6
(2)
5
.51
(1)
Ass
ura
nce
6
.32
(5
)
6.0
3
(5)
7
.26
(3)
5
.87
(3)
6.3
1 (4
) 5
.81
(5
)
6.1
3
(5)
6
.46
(5
)
6.3
4
(4)
5
.07
(5
) 5
.21
(4
)
5.4
1(3
)
Emp
ath
y
6.4
2
(2)
6.1
2
(3)
7.2
8 (2
)
5.9
7 (2
)
6.4
0 (2
)
5.9
2
(3)
6.2
0
(3)
6.5
9
(2)
6.4
3
(2)
5.0
9
(3)
5.2
6
(2)
5.4
5(2
)
Res
po
nsi
ven
ess
6
.38
(4
)
6.1
0
(4)
7.2
5 (4
)
5.9
7 (2
)
6.3
6 (3
)
5.9
0
(4)
6.1
8
(4)
6.5
4
(4)
6.3
9
(3)
5.1
0
(2)
5.3
4
(4)
5.4
5(2
)
Ove
rall
(ave
rage
d o
n a
ll
dim
en
sio
ns)
6.3
4
6
.05
7
.25
5
.90
6.3
3 5
.84
6
.14
6
.49
6
.36
5.0
7
5.2
2
5
.42
Me
an S
core
s (a
vera
ged
o
n le
vel o
f e
du
ca�
on
)
6.5
4
6.0
2
6.3
3
5.2
4
R
ank
1
3
2
4
f-
Val
ue
3.0
60
.81
9
.37
6
.08
7
p
-Val
ue
*
.05
1
.44
4
.68
7
.91
7
N
ote
: Fi
gu
res
wit
hin
pa
ren
thes
is a
re r
an
ks t
o e
ach
dim
ensi
on
acr
oss
all
serv
ice
pro
vid
ers
*In
sig
nifi
can
t a
t 5
% L
evel
(p
>0.0
5)
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley70 71
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Tab
le 1
.8:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r Ti
me
of
Net
wo
rk E
xpe
rie
nce
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Up to 6
months
N=9
7-12 months
N=16
More than a
year
N=75
Up to 6
months
N=7
7-12 months
N=11
More than a
year
N=82
Up to 6
months N=12
7-12 months
N=13
More than a
year
N=75
Up to 6
months
N=14
7-12 months
N=18
More than a
year
N=68
Net
wo
rk q
ual
ity
6
.29
(6)
6
.26
(6)
5
.88 (5)
6
.07
(6)
5.6
5
(6)
5.6
1
(6)
5
.88
(6)
6
.19
(5)
6
.02
(5)
4
.71
(6)
4
.95
(4)
5.2
3(4
)
Pri
cin
g
6.7
9
(1)
6
.75
(1)
6
.32 (1)
6
.51
(2)
6.2
2
(1)
6.0
9
(1)
6
.43
(2)
6
.60
(1)
6
.48
(2)
4
.98
(1)
5
.09
(2)
5.3
8(2
)
Rel
iab
ility
6
.73
(2)
6
.69
(2)
6
.22 (2)
6
.54
(1)
6.0
3
(3)
6.0
5
(2)
6
.49
(1)
6
.50
(2)
6
.32
(3)
4
.95
(2)
5
.14
(1)
5.4
2(1
)
Ass
ura
nce
6
.60
(5
)
6.5
6 (5
)
6.1
4 (4)
6.3
8 (5
)
5.9
7
(5)
5.9
2
(5)
6.2
7
(5)
6.4
0
(4)
6.2
7
(4)
4.8
8
(5)
5.0
6
(3)
5.3
4(3
)
Emp
ath
y
6.7
1
(3)
6.6
7 (3
)
6.2
2 (2)
6.4
7 (3
)
6.0
7
(2)
6.0
2
(3)
6.3
9
(3)
6.5
0
(2)
6.3
6
(1)
4.9
4
(3)
5.0
9
(2)
5.3
8(2
)
Res
po
nsi
ven
ess
6
.68
(4
)
6.6
4 (4
)
6.1
9 (3)
6.4
6 (4
)
6.0
2
(4)
6.0
0
(4)
6.3
8
(4)
6.4
7
(3)
6.3
2
(3)
4.9
2
(4)
5.0
9
(2)
5.3
8(2
)
Ove
rall
(ave
rage
d o
n a
ll d
ime
nsi
on
s)
6.6
3
6.5
9
6.1
6 6
.40
5.9
9
5.9
4
6.3
0
6.4
4
6.2
9
4.8
9 5
.06
5.3
5
Me
an S
core
s (a
vera
ged
o
n n
etw
ork
exp
eri
en
ce)
6.4
6
6.1
1
6.3
4
5.1
Ran
k
1
3
2
4
f-
Val
ue
.99
9
.51
7
.01
9
.49
2
p
-Val
ue
*
.37
2
.56
7
.98
1
.61
3
N
ote
: Fi
gu
res
wit
hin
pa
ren
thes
is a
re r
an
ks t
o e
ach
dim
ensi
on
acr
oss
all
serv
ice
pro
vid
ers
*
Insi
gn
ifica
nt
at
5%
Lev
el (
p>0
.05
)
Tab
le 1
.9:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r co
nn
ec�
on
Typ
e
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Co
nn
ec�
on
typ
e C
on
nec
�o
n t
ype
C
on
nec
�o
n t
ype
C
on
nec
�o
n t
ype
Prepaid
N=90
Post-
paid
N=10
Prepaid
N=86
Post-
paid N=14
Prepaid
N=83
Post-
paid N=17
Prepaid
N=59
Post-
paid
N=41
Net
wo
rk q
ual
ity
5
.95
(5)
6
.24
(6)
5
.69
(6)
5.3
7
(6)
5
.98
(5)
6
.18
(5)
5
.17
(6)
5
.01
(4)
Pri
cin
g
6.3
9 (1
)
6.7
5
(1)
6
.19
(1)
5.7
9
(1)
6
.48
(1)
6
.49
(1)
5
.47
(1)
4
.99
(5)
Rel
iab
ility
6
.30
(2)
6
.69
(2)
6
.17
(2)
5.5
4
(5)
6
.38
(2)
6
.28
(4)
5
.46
(2)
5
.07
(1)
Ass
ura
nce
6
.21
(4)
6
.56
(5)
6
.02
(5)
5.5
7
(4)
6
.28
(4
)
6.3
2
(3)
5
.37
(5
)
5.0
3
(3)
Emp
ath
y
6.3
0 (2
)
6.6
7 (3
)
6.1
3 (3
)
5.6
3
(2)
6.3
8
(2)
6.3
6
(2)
5.4
3
(3)
5.0
3
(3)
Res
po
nsi
ven
ess
6
.27
(3)
6.6
4 (4
)
6.1
1 (4
)
5.5
8
(3)
6.3
5
(3)
6.3
2
(3)
5.4
2
(4)
5.0
4
(2)
O
vera
ll (a
vera
ged
on
all
dim
en
sio
ns)
6.2
3
6.5
9 6
.05
5.5
8
6.3
0
6.3
2
5.3
8
5.0
2
Me
an S
core
s (a
vera
ged
o
n c
on
ne
c�o
n t
ype
)
6.4
1
5.8
1 6
.31
5
.2
Ran
k
1
3 2
4
t-
Val
ue
.5
17
-.
02
1 .0
57
.8
71
p
-Val
ue
*
.60
7
.98
3
.95
4
.38
6
N
ote
: Fi
gu
res
wit
hin
pa
ren
thes
is a
re r
an
ks t
o e
ach
dim
ensi
on
acr
oss
all
serv
ice
pro
vid
ers
*In
sig
nifi
can
t a
t 5
% L
evel
(p
>0.0
5)
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley72 73
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Tab
le 1
.8:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r Ti
me
of
Net
wo
rk E
xpe
rie
nce
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Tim
e o
f n
etw
ork
exp
erie
nce
Up to 6
months
N=9
7-12 months
N=16
More than a
year
N=75
Up to 6
months
N=7
7-12 months
N=11
More than a
year
N=82
Up to 6
months N=12
7-12 months
N=13
More than a
year
N=75
Up to 6
months
N=14
7-12 months
N=18
More than a
year
N=68
Net
wo
rk q
ual
ity
6
.29
(6)
6
.26
(6)
5
.88 (5)
6
.07
(6)
5.6
5
(6)
5.6
1
(6)
5
.88
(6)
6
.19
(5)
6
.02
(5)
4
.71
(6)
4
.95
(4)
5.2
3(4
)
Pri
cin
g
6.7
9
(1)
6
.75
(1)
6
.32 (1)
6
.51
(2)
6.2
2
(1)
6.0
9
(1)
6
.43
(2)
6
.60
(1)
6
.48
(2)
4
.98
(1)
5
.09
(2)
5.3
8(2
)
Rel
iab
ility
6
.73
(2)
6
.69
(2)
6
.22 (2)
6
.54
(1)
6.0
3
(3)
6.0
5
(2)
6
.49
(1)
6
.50
(2)
6
.32
(3)
4
.95
(2)
5
.14
(1)
5.4
2(1
)
Ass
ura
nce
6
.60
(5
)
6.5
6 (5
)
6.1
4 (4)
6.3
8 (5
)
5.9
7
(5)
5.9
2
(5)
6.2
7
(5)
6.4
0
(4)
6.2
7
(4)
4.8
8
(5)
5.0
6
(3)
5.3
4(3
)
Emp
ath
y
6.7
1
(3)
6.6
7 (3
)
6.2
2 (2)
6.4
7 (3
)
6.0
7
(2)
6.0
2
(3)
6.3
9
(3)
6.5
0
(2)
6.3
6
(1)
4.9
4
(3)
5.0
9
(2)
5.3
8(2
)
Res
po
nsi
ven
ess
6
.68
(4
)
6.6
4 (4
)
6.1
9 (3)
6.4
6 (4
)
6.0
2
(4)
6.0
0
(4)
6.3
8
(4)
6.4
7
(3)
6.3
2
(3)
4.9
2
(4)
5.0
9
(2)
5.3
8(2
)
Ove
rall
(ave
rage
d o
n a
ll d
ime
nsi
on
s)
6.6
3
6.5
9
6.1
6 6
.40
5.9
9
5.9
4
6.3
0
6.4
4
6.2
9
4.8
9 5
.06
5.3
5
Me
an S
core
s (a
vera
ged
o
n n
etw
ork
exp
eri
en
ce)
6.4
6
6.1
1
6.3
4
5.1
Ran
k
1
3
2
4
f-
Val
ue
.99
9
.51
7
.01
9
.49
2
p
-Val
ue
*
.37
2
.56
7
.98
1
.61
3
N
ote
: Fi
gu
res
wit
hin
pa
ren
thes
is a
re r
an
ks t
o e
ach
dim
ensi
on
acr
oss
all
serv
ice
pro
vid
ers
*
Insi
gn
ifica
nt
at
5%
Lev
el (
p>0
.05
)
Tab
le 1
.9:
Co
mp
ara�
ve S
erv
ice
Qu
alit
y Sc
ore
as
pe
r co
nn
ec�
on
Typ
e
Serv
ice
Qu
alit
y D
ime
nsi
on
s
C
ell
Ph
on
e O
pe
rato
rs
Air
tel
Vo
daf
on
e
Air
cel
BS
NL
Co
nn
ec�
on
typ
e C
on
nec
�o
n t
ype
C
on
nec
�o
n t
ype
C
on
nec
�o
n t
ype
Prepaid
N=90
Post-
paid
N=10
Prepaid
N=86
Post-
paid N=14
Prepaid
N=83
Post-
paid N=17
Prepaid
N=59
Post-
paid
N=41
Net
wo
rk q
ual
ity
5
.95
(5)
6
.24
(6)
5
.69
(6)
5.3
7
(6)
5
.98
(5)
6
.18
(5)
5
.17
(6)
5
.01
(4)
Pri
cin
g
6.3
9 (1
)
6.7
5
(1)
6
.19
(1)
5.7
9
(1)
6
.48
(1)
6
.49
(1)
5
.47
(1)
4
.99
(5)
Rel
iab
ility
6
.30
(2)
6
.69
(2)
6
.17
(2)
5.5
4
(5)
6
.38
(2)
6
.28
(4)
5
.46
(2)
5
.07
(1)
Ass
ura
nce
6
.21
(4)
6
.56
(5)
6
.02
(5)
5.5
7
(4)
6
.28
(4
)
6.3
2
(3)
5
.37
(5
)
5.0
3
(3)
Emp
ath
y
6.3
0 (2
)
6.6
7 (3
)
6.1
3 (3
)
5.6
3
(2)
6.3
8
(2)
6.3
6
(2)
5.4
3
(3)
5.0
3
(3)
Res
po
nsi
ven
ess
6
.27
(3)
6.6
4 (4
)
6.1
1 (4
)
5.5
8
(3)
6.3
5
(3)
6.3
2
(3)
5.4
2
(4)
5.0
4
(2)
O
vera
ll (a
vera
ged
on
all
dim
en
sio
ns)
6.2
3
6.5
9 6
.05
5.5
8
6.3
0
6.3
2
5.3
8
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Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley72 73
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Table: 1.10 Hypothesis Tes�ng: Service Quality Variance Across Demographic Variables
Hypothesis Statements Operators F/T- value P- Value Status
H 1 Service quality varies
significantly among all age
groups.
Airtel 2.054 .134 Rejected
Vodafone 4.692* .011* Accepted
Aircel 4.280* .017* Accepted
BSNL 1.107 .335 Rejected
H 2 Service quality varies
significantly among all
gender groups.
Airtel .754 .454 Rejected
Vodafone -1.496 .138 Rejected
Aircel -.912 .364 Rejected
BSNL .464 .643 Rejected
H 3 Service quality varies
significantly among all
educa�onal groups.
Airtel 3.060 .051 Rejected
Vodafone .819 .444 Rejected
Aircel .376 .687 Rejected
BSNL .087 .917 Rejected
H 4
Service quality varies
significantly among network
experience groups.
Airtel
.999
.372
Rejected
Vodafone
.517
.567
Rejected
Aircel
.019
.981
Rejected
BSNL
.492
.613
Rejected
H 5
Service quality varies
significantly among all
connec�on types groups.
Airtel
.517
.607
Rejected
Vodafone
-.021
.983
Rejected
Aircel
.057
.954
Rejected
BSNL .871 .386 Rejected
References
• Ahluwalia, J. S., (1998), “Total Quality Management”, New Delhi, India.
• Ahn, L., and Lee, M., (1999), “An Econometric Analysis of the Demand for Access to Mobile Telephone
Networks,” Information Economics and Policy, Vol. 11, Pp. 297-305.
• Andonova, A., (2006), “Mobile Phones: The Internet and the Institutional Environment,” Telecommunications
Policy, Vol. 30, Pp. 29-45.
• Atkin, D. J., and Larose, R., (1999), “An Analysis of the Information Services Adoption Literature,” In Hanson, J.
(Ed.), Advances in Telematics Vol. 2, Pp. 91-110.
• Atalik O., and Arslan M., (2009), “A Study to Determine the Effects of Customer Value on Customer Loyalty in
Airline Companies operating: Case of Turkish Air Travelers”, International Journal of Business and
Management, Vol. 4 No. 6, Pp. 154-162.
• Agyapong, G. K, Q., (2011), “The Effect of Service Quality on Customer satisfaction in the Utility Industry: A
Case of Vodafone (Ghana)”, International Journal of Business and Management, Vol. 6, No. 5, Pp. 203-210.
• Andleeb, S. S., and Basu, A. K., (1994), “Technical Complexity and Consumer Knowledge as Moderators of
Service Quality Evaluation in the Automobile Service Industry,” Journal of Retailing, Vol.70, No.4, Pp.367-381.
• Bloemer, J., Ruyter, K. D., and Peeters, P., (1998), “Investing Drivers of Bank Loyalty: The Complex Relationship
between Image, Service Quality and Satisfaction”, International Journal of Bank Marketing, Vol. 16, No. 7, Pp.
276-286.
• Bitner, M. J., and Hubert, A. R., (1994), “Encounter Satisfaction versus Overall Satisfaction versus Quality”, in
Rust, R.T., and Oliver, R.L., (Eds), Service Quality: New Directions in Theory and Practice, Sage Publications,
London, Pp. 72-94.
• Birke, D., And Swann, P., (2006), “Network Effects and Choice of Mobile Phone Operator, Journal of
Evolutionary Economics,” Vol. 16, Pp. 1-2.
• Babukus, E., and Boller, G. W., (1992), “An Empirical Assessment of SERVQUAL Scale”, Journal of Business
Research, Vol. 24, No. 3, Pp. 253-268.
• Bolton, R. N., and Drew, J. H., (1991), “A Longitudinal Analysis of the Impact of Service Changes on Customer
Attitudes”, Journal of Marketing, Vol. 55, Pp. 1-9.
• Boulding, W., Kalra, A., Staelin, R., and Zeithaml, V., (1993), “A Dynamic Process Model of Service Quality: From
Expectations to Behavioral Intentions”, Journal of Marketing Research, Vol. 30, (February), Pp. 7-27.
• Brady, M. K., Robertson, C. J., (2002), “Performance-only Measurement of Service Quality: A Replication and
Extension”, Journal of Business Research, Vol. 55, No.1, Pp.127-139.
• Bigne, E., Moliner, M. A., and Sanchey, J., (2003), “Perceived Quality and Satisfaction in MultiService
Organizations: The Case of Spanish Public Services”, Journal of Service Marketing, Vol. 17, No.4, Pp. 420-442.
• Berry, L. L., Parasuraman, A., and Zeithaml, V. A., (1990), “Five Imperatives for Improving Service Quality”, Sloan
Management Review, Vol. 31, (summer) Pp. 29-38.
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley74 75
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Table: 1.10 Hypothesis Tes�ng: Service Quality Variance Across Demographic Variables
Hypothesis Statements Operators F/T- value P- Value Status
H 1 Service quality varies
significantly among all age
groups.
Airtel 2.054 .134 Rejected
Vodafone 4.692* .011* Accepted
Aircel 4.280* .017* Accepted
BSNL 1.107 .335 Rejected
H 2 Service quality varies
significantly among all
gender groups.
Airtel .754 .454 Rejected
Vodafone -1.496 .138 Rejected
Aircel -.912 .364 Rejected
BSNL .464 .643 Rejected
H 3 Service quality varies
significantly among all
educa�onal groups.
Airtel 3.060 .051 Rejected
Vodafone .819 .444 Rejected
Aircel .376 .687 Rejected
BSNL .087 .917 Rejected
H 4
Service quality varies
significantly among network
experience groups.
Airtel
.999
.372
Rejected
Vodafone
.517
.567
Rejected
Aircel
.019
.981
Rejected
BSNL
.492
.613
Rejected
H 5
Service quality varies
significantly among all
connec�on types groups.
Airtel
.517
.607
Rejected
Vodafone
-.021
.983
Rejected
Aircel
.057
.954
Rejected
BSNL .871 .386 Rejected
References
• Ahluwalia, J. S., (1998), “Total Quality Management”, New Delhi, India.
• Ahn, L., and Lee, M., (1999), “An Econometric Analysis of the Demand for Access to Mobile Telephone
Networks,” Information Economics and Policy, Vol. 11, Pp. 297-305.
• Andonova, A., (2006), “Mobile Phones: The Internet and the Institutional Environment,” Telecommunications
Policy, Vol. 30, Pp. 29-45.
• Atkin, D. J., and Larose, R., (1999), “An Analysis of the Information Services Adoption Literature,” In Hanson, J.
(Ed.), Advances in Telematics Vol. 2, Pp. 91-110.
• Atalik O., and Arslan M., (2009), “A Study to Determine the Effects of Customer Value on Customer Loyalty in
Airline Companies operating: Case of Turkish Air Travelers”, International Journal of Business and
Management, Vol. 4 No. 6, Pp. 154-162.
• Agyapong, G. K, Q., (2011), “The Effect of Service Quality on Customer satisfaction in the Utility Industry: A
Case of Vodafone (Ghana)”, International Journal of Business and Management, Vol. 6, No. 5, Pp. 203-210.
• Andleeb, S. S., and Basu, A. K., (1994), “Technical Complexity and Consumer Knowledge as Moderators of
Service Quality Evaluation in the Automobile Service Industry,” Journal of Retailing, Vol.70, No.4, Pp.367-381.
• Bloemer, J., Ruyter, K. D., and Peeters, P., (1998), “Investing Drivers of Bank Loyalty: The Complex Relationship
between Image, Service Quality and Satisfaction”, International Journal of Bank Marketing, Vol. 16, No. 7, Pp.
276-286.
• Bitner, M. J., and Hubert, A. R., (1994), “Encounter Satisfaction versus Overall Satisfaction versus Quality”, in
Rust, R.T., and Oliver, R.L., (Eds), Service Quality: New Directions in Theory and Practice, Sage Publications,
London, Pp. 72-94.
• Birke, D., And Swann, P., (2006), “Network Effects and Choice of Mobile Phone Operator, Journal of
Evolutionary Economics,” Vol. 16, Pp. 1-2.
• Babukus, E., and Boller, G. W., (1992), “An Empirical Assessment of SERVQUAL Scale”, Journal of Business
Research, Vol. 24, No. 3, Pp. 253-268.
• Bolton, R. N., and Drew, J. H., (1991), “A Longitudinal Analysis of the Impact of Service Changes on Customer
Attitudes”, Journal of Marketing, Vol. 55, Pp. 1-9.
• Boulding, W., Kalra, A., Staelin, R., and Zeithaml, V., (1993), “A Dynamic Process Model of Service Quality: From
Expectations to Behavioral Intentions”, Journal of Marketing Research, Vol. 30, (February), Pp. 7-27.
• Brady, M. K., Robertson, C. J., (2002), “Performance-only Measurement of Service Quality: A Replication and
Extension”, Journal of Business Research, Vol. 55, No.1, Pp.127-139.
• Bigne, E., Moliner, M. A., and Sanchey, J., (2003), “Perceived Quality and Satisfaction in MultiService
Organizations: The Case of Spanish Public Services”, Journal of Service Marketing, Vol. 17, No.4, Pp. 420-442.
• Berry, L. L., Parasuraman, A., and Zeithaml, V. A., (1990), “Five Imperatives for Improving Service Quality”, Sloan
Management Review, Vol. 31, (summer) Pp. 29-38.
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley74 75
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
• Brown, S. W., and Swartz, T. A., (1989), “A Gap Analysis of Professional Service Quality”, Journal of Marketing,
Vol. 53, (April), Pp. 92-100.
• Crosby, P. B., (1979), “Quality is Free. The Art of Making Quality Certain”, New York: New American Library, Vol.
12, Pp. 125-148.
• Carman, J. M., (1990), “Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL
Dimensions”, Journal of Retailing, Vol. 66, (spring), Pp. 33-35.
• Cronin and Taylor, S. A., (1992), “Measuring Service Quality: A Re-Examination and Extension”, Journal of
Marketing, Vol. 56 (July), Pp. 55-67.
• Cronin, J; Brady, M. K., and Hult, T.M. (2000), “Assessing the Effects of Quality, Value Environments,” Journal of
Retailing, Vol. 76, No. 2, Pp.193-218.
• Cavana, R.Y., Corbett L. M., and Lo, Y. L., (2007), “Developing Zones of Tolerance for Managing Passenger Rail
Services Quality”, International Journal of Quality and Reliability Management, Vol. 24, No.1, Pp.7-31.
• Churchill, G. A., and Supernant, C., (1982), “An Investigation into the Determinants of Customer Satisfaction”,
Journal of Marketing Research, Vol. 19 (November), Pp.491 504.
• Clements, M., and Abramowitz, A., (2006), “The Development and Adoption of Broadband Service: A th Household Level Analysis,” Paper Presented at the 35 Research Conference on Communication, Information
and Internet Policy, Arlington, VA, September.
• Danaher, P. J., and Mattesson, J., (1994), “Customer Satisfaction during the Service Delivery Process”,
European Journal of Marketing, Vol. 28, No. 5, Pp. 5-16.
• Danaher, P. J., and Rust, R. T., (1996), “Indirect Financial Benefits from Service Quality”, Quality Management,
Journal, Vol. 3, No. 2, Pp. 63-75.
• Dabholkar, P. A, Shepherd, D. C., and Thorpe, D. I., (2000), “A Comprehensive Framework of Service Quality: An
Investigation of Critical, Conceptual and Measurement Issues through a Longitudinal Study”, Journal of
Retailing, Vol. 76, No. 2, Pp. 139-173.
• Duncan, E., and Elliot, G., (2004), “Efficiency, Customer Service and Financial Performance among Australian
Financial Institutions”, The International Journal of Bank Marketing, Vol.22, No.5, Pp.319-342.
• Ennew, C. T., Reed, G. V., and Binks, M. R., (1993), “Importance-Performance Analysis and the Measurement of
Service Quality”, European Journal of Marketing, Vol. 27, No. 2, Pp. 59-70.
• Fuss, M., Meschi, M., and Waverman, L., (2005), “The Impact of Telecoms on Economic Growth in Developing
Countries, in Africa: The Impact of Mobile Phones”, the Vodafone Policy Paper Series, No. 2, Pp. 10-23.
• Festus, O., Maxwell, K. H., and Godwin, J. H., (2006), “Service Quality, Customer Satisfaction and Behavioral
Intentions in the Service Factory”, Journal of Services Marketing, Vol. 20, No. 1, Pp. 59-72.
• Fornell, (1992), “Customer Satisfaction: The Fundamental Basis for Business Survival”, Siebel Magazine, Vol.
51, Pp. 19-25.
• Fogli, L., (2006), “Customer Service Delivery”, Research and Best Practice, San Francisco: Jossey-Bass.
• Garvin, D. A., (1983), “Quality on the Line”, Harvard Business Review, No. 61 (September-October), Pp. 65-73.
• Gronroos, C., (1982), “Strategic Management and Marketing in the Service Sector”, Swedish School of
Economics and Business Administration, Helsinki.
• Gronroos, C. A., (1984), “Service Quality Model and its Marketing Implications” European Journal of
Marketing, Vol. 18, No. 4, Pp. 36-44.
• Gronroos, C., (1990), “Service Management Focus for Service Competition”, International Journal of Service
Industry Management, Vol. 1, No. 1, Pp. 6- 10.
• Gronroos, C., (2007), “Service Management and Marketing: Customer Management in Service Competition”,
third Edition, West Sussex: John Wiley and Sons, Ltd.
• Gotlieb, J., Grewal, D., and Brown, S.W., (1994), “Consumer Satisfaction and Perceived quality: Complimentary
and Divergent Constructs,” Journal of Applied Psychology, Vol. 79, No.6, Pp.875-885.
• Garson, D. A., (2002), “Guide to Writing Empirical Papers, Theses and Dissertations”, CRC Press, Grosuch, R. L.,
(1983), “Factor Analysis”, Hillsdale, N. J: Erlbaum.
• Holbrook, M. B., (1994), “The Nature of Customer Value”: An Axiology of Services in the Consumption
Experience.
• Hartline, M. D., and Ferrell, O. C., (1996), “The Management of Customer Contact Service Employees: An
Empirical Investigation”, Journal of Marketing, Vol. 69, (October), Pp. 52-70.
• Howcroft, J. B., (1991), “Customer Satisfaction in Retail Banking”, Service Industry Journal, (Jan), Pp. 11-17.
• Haddad, S., Fournier, P., and Potvin, L., (1998), “Measuring Lay People's Reception of the Quality of Primary
Health Services in Developing Countries: Validation of 20-Item Scale”, International Journal for Quality in
Health Care, Vol. 10, Pp. 93-104.
• Juran, J. M., (1974), “Quality Control Handbook”, Third Edition, McGraw-Hill, New York, Pp. 18-3.
• Jain, S. K., and Gupta, G., (2004), “Measuring Service Quality: SERVQUAL V/s SERVPERF Scales”, Vikalpa, Vol.
29, No. 2, Pp. 25-37.
• Johnston, R., (1995), “The Determinants of Service Quality: Satisfiers and Dissatisfiers”, International Journal
of Service Industry Management, Vol. 6, No. 5, Pp. 53-71.
• Jacoby, J., Jerry, C. O., and Rafael, A. H., (1973), “Price, Brand Name and Product Composition Characteristics as
Determinants of Perceived Quality”, Journal of Applied Psychology, Vol. 55, No. 6, Pp. 570-579.
• Kandampully, J., (1998), “Service Quality to Service Loyalty: A Relationship Which Goes Beyond Customer
Services”, Total Quality Management, Vol. 9, No. 6, Pp. 431- 443.
• Karaçuka, M., Nazif, A., and Haucap, J., (2012), “Consumer Choice and Local Network Effects in Mobile
Telecommunications in Turkey”.
• Khan, M, A., (2010), “An Empirical Assessment of Cellular Mobile Operators in Pakistan”, Journal of Asian Social
Sciences, Vol. 6, No. 10, Pp. 164-177.
• Khan, S., and Afsheen, S., (2012), “Determinants of Customer Satisfaction in Telecom Industry: A Study of
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley76 77
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
• Brown, S. W., and Swartz, T. A., (1989), “A Gap Analysis of Professional Service Quality”, Journal of Marketing,
Vol. 53, (April), Pp. 92-100.
• Crosby, P. B., (1979), “Quality is Free. The Art of Making Quality Certain”, New York: New American Library, Vol.
12, Pp. 125-148.
• Carman, J. M., (1990), “Consumer Perceptions of Service Quality: An Assessment of the SERVQUAL
Dimensions”, Journal of Retailing, Vol. 66, (spring), Pp. 33-35.
• Cronin and Taylor, S. A., (1992), “Measuring Service Quality: A Re-Examination and Extension”, Journal of
Marketing, Vol. 56 (July), Pp. 55-67.
• Cronin, J; Brady, M. K., and Hult, T.M. (2000), “Assessing the Effects of Quality, Value Environments,” Journal of
Retailing, Vol. 76, No. 2, Pp.193-218.
• Cavana, R.Y., Corbett L. M., and Lo, Y. L., (2007), “Developing Zones of Tolerance for Managing Passenger Rail
Services Quality”, International Journal of Quality and Reliability Management, Vol. 24, No.1, Pp.7-31.
• Churchill, G. A., and Supernant, C., (1982), “An Investigation into the Determinants of Customer Satisfaction”,
Journal of Marketing Research, Vol. 19 (November), Pp.491 504.
• Clements, M., and Abramowitz, A., (2006), “The Development and Adoption of Broadband Service: A th Household Level Analysis,” Paper Presented at the 35 Research Conference on Communication, Information
and Internet Policy, Arlington, VA, September.
• Danaher, P. J., and Mattesson, J., (1994), “Customer Satisfaction during the Service Delivery Process”,
European Journal of Marketing, Vol. 28, No. 5, Pp. 5-16.
• Danaher, P. J., and Rust, R. T., (1996), “Indirect Financial Benefits from Service Quality”, Quality Management,
Journal, Vol. 3, No. 2, Pp. 63-75.
• Dabholkar, P. A, Shepherd, D. C., and Thorpe, D. I., (2000), “A Comprehensive Framework of Service Quality: An
Investigation of Critical, Conceptual and Measurement Issues through a Longitudinal Study”, Journal of
Retailing, Vol. 76, No. 2, Pp. 139-173.
• Duncan, E., and Elliot, G., (2004), “Efficiency, Customer Service and Financial Performance among Australian
Financial Institutions”, The International Journal of Bank Marketing, Vol.22, No.5, Pp.319-342.
• Ennew, C. T., Reed, G. V., and Binks, M. R., (1993), “Importance-Performance Analysis and the Measurement of
Service Quality”, European Journal of Marketing, Vol. 27, No. 2, Pp. 59-70.
• Fuss, M., Meschi, M., and Waverman, L., (2005), “The Impact of Telecoms on Economic Growth in Developing
Countries, in Africa: The Impact of Mobile Phones”, the Vodafone Policy Paper Series, No. 2, Pp. 10-23.
• Festus, O., Maxwell, K. H., and Godwin, J. H., (2006), “Service Quality, Customer Satisfaction and Behavioral
Intentions in the Service Factory”, Journal of Services Marketing, Vol. 20, No. 1, Pp. 59-72.
• Fornell, (1992), “Customer Satisfaction: The Fundamental Basis for Business Survival”, Siebel Magazine, Vol.
51, Pp. 19-25.
• Fogli, L., (2006), “Customer Service Delivery”, Research and Best Practice, San Francisco: Jossey-Bass.
• Garvin, D. A., (1983), “Quality on the Line”, Harvard Business Review, No. 61 (September-October), Pp. 65-73.
• Gronroos, C., (1982), “Strategic Management and Marketing in the Service Sector”, Swedish School of
Economics and Business Administration, Helsinki.
• Gronroos, C. A., (1984), “Service Quality Model and its Marketing Implications” European Journal of
Marketing, Vol. 18, No. 4, Pp. 36-44.
• Gronroos, C., (1990), “Service Management Focus for Service Competition”, International Journal of Service
Industry Management, Vol. 1, No. 1, Pp. 6- 10.
• Gronroos, C., (2007), “Service Management and Marketing: Customer Management in Service Competition”,
third Edition, West Sussex: John Wiley and Sons, Ltd.
• Gotlieb, J., Grewal, D., and Brown, S.W., (1994), “Consumer Satisfaction and Perceived quality: Complimentary
and Divergent Constructs,” Journal of Applied Psychology, Vol. 79, No.6, Pp.875-885.
• Garson, D. A., (2002), “Guide to Writing Empirical Papers, Theses and Dissertations”, CRC Press, Grosuch, R. L.,
(1983), “Factor Analysis”, Hillsdale, N. J: Erlbaum.
• Holbrook, M. B., (1994), “The Nature of Customer Value”: An Axiology of Services in the Consumption
Experience.
• Hartline, M. D., and Ferrell, O. C., (1996), “The Management of Customer Contact Service Employees: An
Empirical Investigation”, Journal of Marketing, Vol. 69, (October), Pp. 52-70.
• Howcroft, J. B., (1991), “Customer Satisfaction in Retail Banking”, Service Industry Journal, (Jan), Pp. 11-17.
• Haddad, S., Fournier, P., and Potvin, L., (1998), “Measuring Lay People's Reception of the Quality of Primary
Health Services in Developing Countries: Validation of 20-Item Scale”, International Journal for Quality in
Health Care, Vol. 10, Pp. 93-104.
• Juran, J. M., (1974), “Quality Control Handbook”, Third Edition, McGraw-Hill, New York, Pp. 18-3.
• Jain, S. K., and Gupta, G., (2004), “Measuring Service Quality: SERVQUAL V/s SERVPERF Scales”, Vikalpa, Vol.
29, No. 2, Pp. 25-37.
• Johnston, R., (1995), “The Determinants of Service Quality: Satisfiers and Dissatisfiers”, International Journal
of Service Industry Management, Vol. 6, No. 5, Pp. 53-71.
• Jacoby, J., Jerry, C. O., and Rafael, A. H., (1973), “Price, Brand Name and Product Composition Characteristics as
Determinants of Perceived Quality”, Journal of Applied Psychology, Vol. 55, No. 6, Pp. 570-579.
• Kandampully, J., (1998), “Service Quality to Service Loyalty: A Relationship Which Goes Beyond Customer
Services”, Total Quality Management, Vol. 9, No. 6, Pp. 431- 443.
• Karaçuka, M., Nazif, A., and Haucap, J., (2012), “Consumer Choice and Local Network Effects in Mobile
Telecommunications in Turkey”.
• Khan, M, A., (2010), “An Empirical Assessment of Cellular Mobile Operators in Pakistan”, Journal of Asian Social
Sciences, Vol. 6, No. 10, Pp. 164-177.
• Khan, S., and Afsheen, S., (2012), “Determinants of Customer Satisfaction in Telecom Industry: A Study of
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley76 77
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Telecom Industry Peshawar”, Journal of Basic and Applied Scientific Research, Vol. 2, No. 12, Pp. 12833-12840.
• Kim, M., Park, M., Jeong, D., (2004), “The Effects of Customer Satisfaction and Switching Barrier on Customer
Loyalty in Korean Mobile Telecommunication Services”, Telecommunications Policy, Vol. 28, Pp. 145-159.
• Lehtinen, U., and Lehtinen, R. J.., (1982), “Service Quality: A Study of Quality Dimensions,” Unpublished
Working Paper, Helsinki: Service Management Institute, Finland OY.
• Lyord, W., Beverley, and Cheung, Y. P., (1998), “IT to Support Service Quality Excellence in the Australian
Banking Industry”, Managing Service Quality, Vol. 8, No. 5, Pp. 350-358.
• Lewis, R. C., and Booms, B. H., (1983), “The Marketing Aspects of Service Quality”, In Berry, L., Shostack, G. and
Upah, G., (Edition), Emerging Perspectives on Services Marketing, American Marketing Association, Chicago,
Vol. 2, Pp. 99-107.
• Monroe, Kent, B., and R. Krishnan., (1983), “The Effect of Price on Subjective Product Evaluations, Blacksburg”:
Virginia Polytechnic Institute, Working paper.
• McConnell, J. D., (1968), “Effect of Pricing on Perception of Product Quality”, Journal of Applied Psychology,
Vol. 52 (August), Pp.300-303.
• Madden, G., Coble, N., and Dalzell, B., (2004), “A Dynamic Model of Mobile Telephony Subscription
Incorporating a Network Effect,” Telecommunications Policy, Vol. 28, Pp. 133-144.
• MacStravic, S., (1997), “Questions of Value in Health Care”, Marketing Health Services, Chicago, Vol. 18, No. 4,
Pp. 50-3.
nd• Nunnaly, J. C., (1978), “Psychomatric Theory”, 2 edition, New York, NY: McGraw-Hill.
• Nunnally, J. C., and Bernstein, I. H., (1994), “Psychometric Theory”, New York: McGraw-Hill.
• Nasser, H. A., Salleh, S. B. M., and Gelaidan, H. M., (2012), “Factors Affecting Customer Satisfaction of Mobile
Services in Yemen”, Journal of Economics, Vol. 2, No. 7, Pp. 171-184.
• Olatokun, W., and Nwone, S. A., (2013), “Influence of Socio-Demographic Variables on Users” Choice of
Mobile Service Providers in Nigerian Telecommunication Market, International Journal of Computer and
Information Technology, Vol. 2, No.5
• OluOjo, (2010), “The Relationship between Service Quality and Customer Satisfaction in the
Telecommunication Industry: Evidence from Nigeria”, Broad Research in Accounting, Negotiation, and
Distribution, Vol. 1, No.1, Pp. 88-100.
• Ode Egena, (2013), “Customer Satisfaction in Mobile Telephony: An Analysis of Major Telecommunication
Service Providers in Nigeria”, Asian Journal of Management Research, Vol. 4, No. 1, Pp. 1-11.
• Omachonu V., Johnson, W. C. and Onyeaso, G., (2008), “An Empirical Test of the Drivers of Overall Customer
Satisfaction: Evidence from Multivariate Granger Causality”, Journal of Services Marketing, Vol. 22, No. 6, Pp.
434- 444.
• Parasuraman, A., Berry, L. L., and Zeithmal, V. A., (1991), “Refinement and Reassessment of the SERVQUAL
Scale”, Journal of Retailing, Vol. 67, Pp. 420-450.
• Parasuraman, A., Zeithaml, V., and Berry, L, L., (1985), “A Conceptual Model of Service Quality and its
Implications for Future Research”, Journal of Marketing, Vol. 49 (fall), Pp. 41-50.
• Parasuraman, A., Zeithaml V. A., and Berry, L. L., (1988), “SERVQUAL: A Multiple - Item Scale for Measuring
Consumer Perceptions for Service Quality”, Journal of Retailing, Vol. 64, No.1, (spring), Pp. 12-40.
• Paulrajan, R., and Rajkumar, H., (2011), “Service Quality and Customer Preferences of Cellular Mobile Service
Providers”, Journal of Technology and Innovation, Vol. 6, No. 1, Pp. 40-45.
• Petzer, D. J., and De Meyer, C. F., (2011), “The Perceived Service Quality, Satisfaction and Behavioral Intent
towards Cell phone Network Service Providers: A Generational Perspective”, African Journal of Business
Management, Vol. 5, No. 17, Pp. 7461-7473.
• Ranaweera, C., Neely, A., (2003), “Some Moderating Effects on the Service Quality: Customer Retention Link”,
International Journal of Operations and Production Management, Vol. 23, No. 2, Pp. 230-248.
• Rapert, M., and Wern, B., (1998), “Service Quality as a Competitive Opportunity”, The Journal of Services
Marketing, Vol. 12, No. 3, Pp. 223-235.
• Reichheld, F, F., Sassar, W. E., (1990), “Zero Defections: Quality Comes to Services”, Harvard Business Review,
(September – October), Pp. 105-11.
• Rajkumar and Harish, (2011), “Service Quality and Customer Preferences of Cellular Mobile Service Providers”,
Journal of Technology and Innovation, Vol. 6, No. 1, Pp. 40-45.
• Shepherd, C. D., (1999), “Service Quality and the Sales Force: A Tool for Competitive Advantage”, Journal of
Personal Selling and Sales Management, Vol. 19, No. 3, Pp. 73 82.
• Sasser, W. E., Olsen, R. P., and Wyckoff, D. D., (1978), “Understanding Service Operations”, in Management of
Service Operations Boston: Allyn and Bacon.
• Shahzad, and Saima., (2012), “Determinants of Customer Satisfaction in Telecom Industry, A Study of Telecom
industry Peshawar KPK Pakistan”, Journal of Basic and Applied Scientific Research, Vol. 2, No. 12, Pp.12833-
12840.
• Shapiro, Bensen, (1972), “The Price of Consumer Goods: Theory and Practice”, Cambridge, MA: Marketing
Science Institute, Working Paper.
• Siew, P., L., Ayankule, A., T., Hanisah, M., S., and Alan, G., D., (2011), “Service Quality and Customer Satisfaction
in a Telecommunication Service Provider, , International Conference on Financial Management and Economics
Vol. 11, Pp. 24-29.
• Stafford, M. R., (1996), “Demographic Discriminators of Service Quality in the Banking Industry”, The Journal of
Services Marketing, Vol. 10, No. 4, Pp. 6-22.
• Scotts, N., (2010), “New Research Findings Point to High Rates of Phone Use in No or Low Service Areas,”
Retrieved May 12, 2010, From Http://Www.Balancingact Africa.Com/News/Back/Balancing Act_203.Html.
• Teas, K. R., (1993), “Expectations, Performance Evaluation, and Consumers Perception of Quality,” Journal of
Marketing, Vol. 57 (October), Pp. 18-34.
• Teas, K. R., (1994), “Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of
Re-Assessment”, Journal of Marketing, Vol. 58, (January), Pp. 132-13.
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley78 79
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Telecom Industry Peshawar”, Journal of Basic and Applied Scientific Research, Vol. 2, No. 12, Pp. 12833-12840.
• Kim, M., Park, M., Jeong, D., (2004), “The Effects of Customer Satisfaction and Switching Barrier on Customer
Loyalty in Korean Mobile Telecommunication Services”, Telecommunications Policy, Vol. 28, Pp. 145-159.
• Lehtinen, U., and Lehtinen, R. J.., (1982), “Service Quality: A Study of Quality Dimensions,” Unpublished
Working Paper, Helsinki: Service Management Institute, Finland OY.
• Lyord, W., Beverley, and Cheung, Y. P., (1998), “IT to Support Service Quality Excellence in the Australian
Banking Industry”, Managing Service Quality, Vol. 8, No. 5, Pp. 350-358.
• Lewis, R. C., and Booms, B. H., (1983), “The Marketing Aspects of Service Quality”, In Berry, L., Shostack, G. and
Upah, G., (Edition), Emerging Perspectives on Services Marketing, American Marketing Association, Chicago,
Vol. 2, Pp. 99-107.
• Monroe, Kent, B., and R. Krishnan., (1983), “The Effect of Price on Subjective Product Evaluations, Blacksburg”:
Virginia Polytechnic Institute, Working paper.
• McConnell, J. D., (1968), “Effect of Pricing on Perception of Product Quality”, Journal of Applied Psychology,
Vol. 52 (August), Pp.300-303.
• Madden, G., Coble, N., and Dalzell, B., (2004), “A Dynamic Model of Mobile Telephony Subscription
Incorporating a Network Effect,” Telecommunications Policy, Vol. 28, Pp. 133-144.
• MacStravic, S., (1997), “Questions of Value in Health Care”, Marketing Health Services, Chicago, Vol. 18, No. 4,
Pp. 50-3.
nd• Nunnaly, J. C., (1978), “Psychomatric Theory”, 2 edition, New York, NY: McGraw-Hill.
• Nunnally, J. C., and Bernstein, I. H., (1994), “Psychometric Theory”, New York: McGraw-Hill.
• Nasser, H. A., Salleh, S. B. M., and Gelaidan, H. M., (2012), “Factors Affecting Customer Satisfaction of Mobile
Services in Yemen”, Journal of Economics, Vol. 2, No. 7, Pp. 171-184.
• Olatokun, W., and Nwone, S. A., (2013), “Influence of Socio-Demographic Variables on Users” Choice of
Mobile Service Providers in Nigerian Telecommunication Market, International Journal of Computer and
Information Technology, Vol. 2, No.5
• OluOjo, (2010), “The Relationship between Service Quality and Customer Satisfaction in the
Telecommunication Industry: Evidence from Nigeria”, Broad Research in Accounting, Negotiation, and
Distribution, Vol. 1, No.1, Pp. 88-100.
• Ode Egena, (2013), “Customer Satisfaction in Mobile Telephony: An Analysis of Major Telecommunication
Service Providers in Nigeria”, Asian Journal of Management Research, Vol. 4, No. 1, Pp. 1-11.
• Omachonu V., Johnson, W. C. and Onyeaso, G., (2008), “An Empirical Test of the Drivers of Overall Customer
Satisfaction: Evidence from Multivariate Granger Causality”, Journal of Services Marketing, Vol. 22, No. 6, Pp.
434- 444.
• Parasuraman, A., Berry, L. L., and Zeithmal, V. A., (1991), “Refinement and Reassessment of the SERVQUAL
Scale”, Journal of Retailing, Vol. 67, Pp. 420-450.
• Parasuraman, A., Zeithaml, V., and Berry, L, L., (1985), “A Conceptual Model of Service Quality and its
Implications for Future Research”, Journal of Marketing, Vol. 49 (fall), Pp. 41-50.
• Parasuraman, A., Zeithaml V. A., and Berry, L. L., (1988), “SERVQUAL: A Multiple - Item Scale for Measuring
Consumer Perceptions for Service Quality”, Journal of Retailing, Vol. 64, No.1, (spring), Pp. 12-40.
• Paulrajan, R., and Rajkumar, H., (2011), “Service Quality and Customer Preferences of Cellular Mobile Service
Providers”, Journal of Technology and Innovation, Vol. 6, No. 1, Pp. 40-45.
• Petzer, D. J., and De Meyer, C. F., (2011), “The Perceived Service Quality, Satisfaction and Behavioral Intent
towards Cell phone Network Service Providers: A Generational Perspective”, African Journal of Business
Management, Vol. 5, No. 17, Pp. 7461-7473.
• Ranaweera, C., Neely, A., (2003), “Some Moderating Effects on the Service Quality: Customer Retention Link”,
International Journal of Operations and Production Management, Vol. 23, No. 2, Pp. 230-248.
• Rapert, M., and Wern, B., (1998), “Service Quality as a Competitive Opportunity”, The Journal of Services
Marketing, Vol. 12, No. 3, Pp. 223-235.
• Reichheld, F, F., Sassar, W. E., (1990), “Zero Defections: Quality Comes to Services”, Harvard Business Review,
(September – October), Pp. 105-11.
• Rajkumar and Harish, (2011), “Service Quality and Customer Preferences of Cellular Mobile Service Providers”,
Journal of Technology and Innovation, Vol. 6, No. 1, Pp. 40-45.
• Shepherd, C. D., (1999), “Service Quality and the Sales Force: A Tool for Competitive Advantage”, Journal of
Personal Selling and Sales Management, Vol. 19, No. 3, Pp. 73 82.
• Sasser, W. E., Olsen, R. P., and Wyckoff, D. D., (1978), “Understanding Service Operations”, in Management of
Service Operations Boston: Allyn and Bacon.
• Shahzad, and Saima., (2012), “Determinants of Customer Satisfaction in Telecom Industry, A Study of Telecom
industry Peshawar KPK Pakistan”, Journal of Basic and Applied Scientific Research, Vol. 2, No. 12, Pp.12833-
12840.
• Shapiro, Bensen, (1972), “The Price of Consumer Goods: Theory and Practice”, Cambridge, MA: Marketing
Science Institute, Working Paper.
• Siew, P., L., Ayankule, A., T., Hanisah, M., S., and Alan, G., D., (2011), “Service Quality and Customer Satisfaction
in a Telecommunication Service Provider, , International Conference on Financial Management and Economics
Vol. 11, Pp. 24-29.
• Stafford, M. R., (1996), “Demographic Discriminators of Service Quality in the Banking Industry”, The Journal of
Services Marketing, Vol. 10, No. 4, Pp. 6-22.
• Scotts, N., (2010), “New Research Findings Point to High Rates of Phone Use in No or Low Service Areas,”
Retrieved May 12, 2010, From Http://Www.Balancingact Africa.Com/News/Back/Balancing Act_203.Html.
• Teas, K. R., (1993), “Expectations, Performance Evaluation, and Consumers Perception of Quality,” Journal of
Marketing, Vol. 57 (October), Pp. 18-34.
• Teas, K. R., (1994), “Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of
Re-Assessment”, Journal of Marketing, Vol. 58, (January), Pp. 132-13.
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 2016
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley78 79
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey
Dr. Mushtaq Ahmad Bhat is Associate Professor in the Department of Business & Financial Studies,
University of Kashmir, Srinagar, J&K. He has teaching experience of twenty-four years and has been
teaching Marketing Management, Services Marketing, Advertising & Sales Management, Consumer
Behaviour and Marketing Research. He has authored a book titled Marketing of Services in addition to
forty research papers published in Journals of national and international repute which among others
include Global Business Review, Management & Change, Abyigyan, Journal of Services Research, Asia-
Pacific Marketing Review, Pranjana-Journal of Management Awareness, Vision, Paradigm, Journal of
Business theory and Practice. He is a visiting faculty to a number of academic and training institutions. He
can be reached [email protected]
Ms Fozia Sajad is a registered Ph.D. Research Scholar in the Department of Business & Financial Studies,
University of Kashmir, Srinagar, J&K. She received her M.Phil. degree from the same institution in the year
2015. She has published three research papers in journals of national repute besides participating and
presenting research papers in two national seminars. She can be reached at [email protected]
• Taylor, S. A., and Baker, T. L., (1994), “An Assessment of the Relationship between Services and Customer
Satisfaction in the Formation of Consumer's Purchase Intentions”, Journal of Retailing, Vol. 70, Pp. 163-178.
• Takeuchi, H., and John A. Q., (1983), “Quality is More than Making a Good Product”, Harvard Business Review,
Vol. 61 (July-August), Pp 139-145.
• Vodafone Group Plc, (2010), Annual Report (Online). Retrieved from: www.vodafone.com/annual
_report10/index.html, (Accessed: 2 May 2011).
• Wells, W., and Prensky, D., (1996), “Consumer Behavior”, John Willy and Sons, USA, 411.
• Wang, J., (2010), “Mobile is Moving Africa”: African Telecoms., Pp. 11- 4.
• Waverman, L., (2005), “The Impact of Telecoms on Economic Growth in Developing Countries, in Africa: The
Impact of Mobile Phones”, the Vodafone Policy Paper Series, No. 2, Pp. 10-23.
• Wareham, J., and A. Levy, A., (2002), “Who will be the Adopters of 3G Mobile Computing Devices?, A Profit
Estimation of Mobile Telecom Diffusion”, Journal of Organizational Computing and Electronic Commerce, Vol.
12, No. 2, Pp.161-174.
• Webster, C., (1989), “Can Consumer be segmented on the Basis of their Service Quality Expectations?” Journal
of Service Marketing, Vol. 8, No. 2, Pp. 35-53.
• Zeithmal, V. A., and Bitner, M. J. (2003), “Service Marketing (3rd edition)”, New York, NY: The McGraw-Hill
Companies, Inc.
Variance in Service Quality across Demographic Variables:An Assessment of Cellular Service Companies in Kashmir Valley
ISSN: 0971-1023 | NMIMS Management ReviewVolume XXIX April-May 201680
Changes
cities of India, and therefore street
Contents
mall farmers. Majority of the
farmers (82%) borrow less than
Rs 5 lakhs, and 18% borrow
between Rs 5 – 10 lakhs on a
per annum basis. Most farmers
(65.79%) ar
** p < .01 + Reliability coefficie
** p < .01 + Reliability coefficie
References
Table 23: The Results of Mann-Whitney U Test for DOWJONES Index Daily ReturnsDr. Rosy Kalra
Mr. Piyuesh Pandey