7Ps’ of Service marketing-Major Research Project

School of Studies in Management
Jiwaji University Gwalior
Major Reserach Project
On
“The relationship among the ‘7Ps’ of Service
marketing mix efforts toward customer in Banking
Sectors”
Submitted in partial fulfillment for the award of degree of
Master of Business Administration
of
School of Studies in Management Jiwaji University Gwalior
By
KULDEEP MATHUR
MBA IV SEM.
Roll. No. 16098002
Session 2016-18
June 2018

DECLARATION
I, Kuldeep Mathur student of Jiwaji University, Gwalior Batch in MBA,
hereby declare that, this Project Report under the title “7P’s of service marketing
in banking sector” is the record of my original work under the guidance of Dr.
Yogesh Upadhayay, Head of School of Studies in Management. This report
has never been submitted anywhere else for award of any degree or diploma.
Kuldeep Mathur
Roll No:16098002
MBA IV SEM

ACKNOWDLEGEMENT
It is a great opportunity & pleasure for me to express my profound gratitude
towards all the individuals who directly or indirectly contributed towards
completion of this report.
Working on this report was a great fun, excitement, challenges and a new
exposure in the field of Marketing. I am in debated to under whose guidance and
concern I am able to bring the report into its real shape.
I am thankful to Dr. Yogesh Upadhyay and all faculty members of Management
Department in providing me useful guidance for the completion of this report. I
convey my gratitude to all those who are directly or indirectly related in the
completion of this project report.
Kuldeep Mathur
Roll No:16098002
MBA IV SEM

Table of Content
Chapter Description Page No.
1. Abstract 1
2. Introduction 1
3. Literature review and hypotheses
development
3
3.1. Customer 3
3.2. Service marketing mix 4
3.2.1. Product 5
3.2.2. Price 5
3.2.3. Place 6
3.2.4. Promotion 7
3.2.5. People 7
3.2.6. Physical evidence 8
3.2.7. Process 8
4. Methodology 9
4.1. Measurement instrument 9
4.2. Sampling designing and data collection 9
5. Data analysis and findings 10
5.1. Scale validity and reliability 10
5.2. Structural model analysis 12
5.2.1. Model assessment 12
5.2.2. Main effects and path coefficients 22
6. Discussion and conclusion 22
7. Managerial implication 22
8. Limitations 23
9. References 24
10. Questionnaires 24

"This page [is] intentionally left blank."

1
1. Abstract
The primary aim of the study is to examine the effects of services marketing mix elements on Indian
customer for making the appropriate marketing mix strategy in banking services context. The study is
based on a sample of 72 customers of bank users in India who filled an online questionnaire. The paper
uses confirmatory factor analysis and structural equation modeling to analyse and confirm the conceptual
model proposed in the research. The paper finds that physical evidence, process, place, and people have a
positive and significant effect on customer. The study suggested an appropriate services marketing mix
strategy for Indian customer perspective in the context of banking services. The paper would help the
bankers to create marketing strategies and action plans to retain their existing customers and to attract
new customers. The paper is first of its kind to discuss the effects of ‘7Ps’ of services marketing mix
collectively on Indian customer. The results of the analysis indicated that managing the marketing mix
dimensions of product, price and promotion is of less importance except place than managing interactive
marketing dimensions such as people, physical evidence, and process.
2. Introduction
The competitive climate in the Indian financial market has changed dramatically over
the last few years. The expectations of the customers are changing. Indian banking
sector has also under-gone financial reforms since the 1990s Earlier, banks enjoyed a
protected market. After economic liberalisation, banks were exposed to free market
competition, advanced technological sophistication and changing customer dynamics.
Owing to the globalisation of markets, banking in India is experiencing internal turmoil.
Few Indian banks initiated experimenting with new innovative services by offering
online and mobile banking which provides 24 h service. Private sector banks and
foreign banks have also introduced some new innovative services. Banking firms have
become flatter and customer-centric now.
In recent years, there has been an increasing interest in the service marketing mix which aims
to achieve the maximum outcomes in terms of customer satisfaction and retention that allow
firms, including banks, to be competitive over time. During the past decade, marketers and
researchers have identified the importance of 7Ps of services marketing and customer
orientation for sustainable competitive advantage (Gronroos, 2004). Crisis in banking industry
have shown the need for sustainable and effective service marketing mix strategies. Krasnikov
(2009) suggested that a successful marketing mix approach can help banks to achieve better
customer service and support, greater efficiency and cost reduction. The major differ- ence
between services marketing mix and regular marketing is that instead of the traditional 4Ps i.e.
product, price, place, and promotion, there are three additional Ps consisting of people, physical
evidence, and process. It means that service marketing mix involves the 7Ps of marketing i.e.
product, price, place, promotion, people, physical evidence, and process. To a certain extent

2
managing services are more complicated then managing products. Products can be
standardised, to standardise a service is far more difficult as there are more input factors
involve, namely, physical evidence, process, and people. There is evidence to suggest that
managing the marketing mix (i.e. product, price, place, and promotion) is of less importance
than managing interactive marketing dimensions, namely, people, processes and physical
evidence. While the literature defines 7Ps of services marketing as being wide in scope and it
encompasses all of the dimensions, some dimensions are of more importance than others. In
such a situation, marketing is no longer a function of its own but rather it becomes part of the
various functions of the firm.
On the other hand, bank deals with providing services to satisfy customers' financial needs
and wants. Banks have to find out the financial needs of the customers and offer the services
which can satisfy those needs. Banks may also require satisfying the customers' financial and
other related needs and wants. The individuals and corporate bodies have certain needs in
relation to money commodity. To satisfy these financial needs, customers want specific
services. Wallis (1997) stated that “customers will seek out those financial products and
services which offer the best value for money”. Different banks offer different benefits by
offering various schemes which can take care of the wants of the customers. Service
marketing mix helps in achieving the organisational objectives of the bank. It is the
‘aggregate of functions’ which signify the totality of the marketing activity. This aggregate of
functions is the sum total of all individual activities consisting of an integrated effort to
discover, create, arouse and satisfy customer needs This means that each individual
function in the banking is a marketing function which contributes to the total satisfaction to
customers and the bank should ultimately develop integrated customer orientation approach.
Because firm cannot stay in business so long if it does not attract and hold enough
customers, no matter how efficiently it operates.
The literature review revealed that the concept of marketing mix and additional three P's
of services marketing have been defined by a large number of marketing researchers in
different contexts and along different industries. The importance of research on these P's
strategy is undoubted. However, empirical research on the 7P's of services marketing mix
in banking industry is unfortunately characterised by non-significant, contradictory and
confusing. Banking is such as industry that the degree of flexibility of the service
marketing mix is low, and the initiative of banks that present those services is less than
other industries. In addition, banking sector has been suffering in creating superior
individual service performance and direct relations with their customers (Shin and Elliott,
2001). A fundamental issue facing Indian banking is the question of how to coordinate the
different generic services marketing mix dimensions around the Indian customer. The
literature on services marketing strategy provides a magnitude of arguments for both the
standardisation and the adaptation of the different combination of 7Ps in various
financial services (Gronroos, 2004). Many researchers have also focused on a single
analysis of the influence of one marketing mix dimension on a firm's performance.
However, a marketing mix does not result in a single marketing ‘P’ strategy. It may be the

3
interplay of all 7P's elements at the same time. So there is a need to examine the
appropriate services marketing mix strategy for Indian customer perspective in banking
services. Therefore, the present study is expected to contribute to the literature on services
marketing mix as related to Indian customer in banking services. The primary aim of the
current study is to examine the effects of services marketing mix elements on Indian
customer for making the appropriate marketing mix strategy in the context of banking
services.
3. Literature review and hypotheses development
3.1.Customer
It was McCarthy (1960) who clarified that the customer is not a part of the marketing
mix; rather, he should be the target of all marketing efforts (Kotler, 2000). In order to
develop effective marketing strategies, the marketers need first to understand why
customers use services and how they choose among competing service suppliers. What
are their expectations at each step in service delivery? Finally, of course, they should
determine whether the experience of using the service and receiving its benefits has met
customers' expectations and left them satisfied and ready to repurchase in the future.
Indian customers also typically hold similar desired expectations across banking services.
A customer's desired service expectation from banks may be quick, convenient, value
added, low cost, with advanced technology, easy and smooth, safe and reliable through a
modern branch setting. Safe and reliable banking is the primary concern of all customers.
Marketers do not usually need to know the specifics of how physical goods are manufac-
tured—that responsibility belongs to the people who run the factory. However, the
situation is different in services because their customers are often involved in service
production and may have preferences for certain methods of service delivery, so that
marketers must understand the nature of the processes through which services are created
and delivered. Because designing a simple and seamless service delivery process support
firms to reduced the necessary time of delivering the service products. It has an important
role in shaping customers overall perception of service quality evaluation. This strategic
response of a firm can achieve the competitive advantage from its competitors and surpass
the competition. It significantly affects the creation and delivering of superior value,
customer satisfaction, competitive advantage, growth opportunity, and profitability of the
firm.
Due to a dynamic business environment, Indian banks have also started to adopt customer-
driven marketing strategies to address the rapid and changing needs of their customers. Thus,
banks have come to realise the importance of differentiating themselves from their
competitors on the basis of superior customer service and relying on effective service

4
marketing mix strategies instead of the traditional banking (Gronroos, 1982). But the ﬁrst
and most important step in applying any marketing strategy is to have a whole hearted
commitment to customer orientation. This means that the central focus of all the marketing
activities of a bank is customer. As a result, the notion of 7Ps of services marketing mix has
emerged as a key factor in modern banking and their customer analysis. Understanding and
gaining access to India's markets will also require careful analysis of customer perception
regarding services marketing mix.
3.2. Services marketing mix
The concept of the marketing mix was coined by Neil Borden in 1953 and then
formalised in his article ‘The concept of the Marketing mix’. McCarthy (1960)
‘4Ps’- product, price, place, and promotion. Alternative models of marketing mix
were also proposed around the same time. However, McCarthy's four Ps model has
dominated marketing thoughts, particularly in the goods marketing context For
service industries, it was observed that the traditional marketing mix was
inadequate because the original marketing mix was developed for manufacturing
industries. The marketing practitioners in the service sector found that the marketing
mix does not address their needs. They observed that the services have certain basic
characteristics which in turn, have marketing implications. For example there is a
problem as regard to maintaining the quality due to lack of standardisation. Also services
cannot be inventoried, patented or transferred. Services are basically different in
comparison to physical products. Therefore, the marketing models and concepts have to
be developed in direction of the service sector. Then, the marketing mix has extended
beyond the 4Ps for marketing of services. The three additional Ps are added to meet the
marketing challenges posed by the characteristics of services such as people, physical
evidence, and process. A number of marketing research studies supplements the
relevance of each of the ‘7Ps’ of services marketing mix.
On the other hand, Indian banking sector has been slow in adopting the modern
marketing knowledge to their advantage. There is no actual realisation that 7Ps of
services marketing can be of use to them. They are not even clear about the scope and
dimensions of marketing, as applicable to banking industry. But the present scenario
is totally changed because of fast-changing customer needs and intense competition
in the banking services. This business environment has created more diversiﬁed and
dynamic customer base. Customers now have a lot of options from which to opt, they
can easily switch over from one service provider to other who promises to offer better
services at lower costs. So the focus of banking services now has been completely
shifted from a transactional marketing approach to a customer oriented approach. In
this regard, services marketing mix can be a critical component in running a
successful business in today's economy. Because developing a complete marketing

5
mix is vital for any business. Without it, all efforts to achieve organisational goal are
likely to be haphazard and inefficient. This has resulted in banks becoming
increasingly engaged in marketing and planning activities in order to achieve certain
objectives such as attracting new customers or providing a superior service for high
net-worth clients or retaining valuable customers. These changes in the nature of
marketing activity have repercussions for service marketing mix decision making and
implementation. As marketing activities become more sophisticated in banking
sector, greater attention needs to be directed towards product, price, place,
promotion, people, physical evidence, and process.
3.2.1.Product
Product is anything which is offered to the market for exchange or consumption (Kotler,
2000). In goods marketing, there is a tangible component to which some intangibles like
style, after- sales-service, credit, etc. are integrated. In the case of services, the tangible
component is nil or minimal. A service is a bundle of features and benefits and these
have relevance for a specific target market. Since the products offered to the customers
of a bank are more or less standardised in nature, banks are feeling an increasing need to
design customised products/services to meet customer needs. Value added dimension
includes those features which are embedded in service itself as its characteristics. Bank's
product such as saving accounts, current accounts, fixed deposits, and investment
options are the primary component in this category. The bank marketing literature
indicates that the transaction context in banking services is mainly concerned with
product and then achieving organisational goals that emphasise product profitability.
Therefore, while developing a service product it is important that the package of
benefits in the service offer must have a customer's perspective. Hence, in the same
direction our first hypothesis states that:
H1. Product has a positive and significant effect on customer.
3.2.2. Price
Price could be considered as an attribute that must be scarified to obtain certain kinds of
products or services. In banking industry, price includes fees, bank charges, and interest
rates. If prices are not charged with fairness and competitiveness, it triggers customer
switching immediately in banking and other financial services. It means that perceptions
of price have a direct impact on customer satisfaction and customer loyalty.
Pricing is yet another strong variable of the marketing mix (Shanker, 2002). The
service pricing should be such as to provide value addition and quality indication to
the customers. Customers see price as a key part of the costs they must incur to obtain
wanted benefits. To calculate whether a particular service is worth it, they may go
beyond just money and also assess the outlays of their time and effort. Otherwise
customers have a lot of alternatives to choose in the market and can easily switch over

6
from one service provider to other who promises to offer better goods/services at lower
prices. Customers are becoming more price-sensitive and less loyal. Customer attrition
has become a real and pressing concern. There- fore, service marketers must not only
set prices that target customers are willing and able to pay as a low cost, but also
convey the message that they are getting more in using that particular product or
service. Many marketing researchers investigated that pricing is an important key
driver for different customer related variables such as, attraction, satisfaction, retention
and loyalty. Therefore, it is expected that:
H2. Price has a positive and significant effect on customer.
3.2.3.Place
A flurry of research has considered that services differ from products in terms of
characteristics such as, intangibility, inse- parability, perishability, and interactivity.
Hence, traditional distribution channels available for product marketing cannot be
used in services marketing (Gronroos, 1983). Services cannot be separated from
selling; it must be created and sold at the same time. The field of logistics has not
been recognised as an area of consideration for effective distribution of services
whether it is the question of locating a site for a new branch of a bank, location of
educational institutions, hotels, etc. In India, these logistical problems are always
overshadowed by govern- ment policy or interventions. There are guidelines
suggesting that to open a single branch in any urban area, a nationalised bank has to
first open a fixed number of branches in rural areas.
Over the last three decades, the proliferation of new information and communication
technologies in the banking sector has changed the way banks service their customers.
The increased availability of self-service technologies has enabled banks to pursue an
electro- nically mediated multi-channel strategy. Automated teller machines (ATMs)
have been considered as one of the most well-known and classic examples of self-
service technology application in the banking sector since 1960s. Now the banks are
able to deploy more and more ATMs and replace costly counter tellers in order to
improve cost efficiency. To enhance their customer service, attract new customers and
remain competitive in banking industry, all domestic as well as foreign banks in India
are establishing technology-driven delivery channels based branches near to customer.
In banking sector, customers choose different service delivery channels in a com-
plementary way such as, the bank's physical location, the opening hours, distance to
reach a bank, parking places, and ATM availability also argued that the large number of
branches and ATMs at various locations make the bank more approachable to the
customers. Consequently, the study states the following hypothesis:
H3. Place has a positive and significant effect on customer.

7
3.2.4.Promotion
It represents the communications that marketers use in marketplace including
advertising, public relations, personal selling and sales promotion (McCarthy, 1960). In
certain service industries it is not possible to use the conventional promotion tools with
success. For example, a bank may face difficulty to afford heavy promotional budgets
due to its small size of the operations. Therefore, promotional activities like community
relations, event management, media blitz, and corporate identity pro- grammes have
relevance and they should be used innovatively and effectively. The impact of
marketing communication on customer behavioural intentions such as, satisfaction,
loyalty, retention and among others. All the techniques and strategies of promotional
mix are used so that ultimately they induce the people to do business with a particular
firm. Indian Market Research Bureau, one of the largest market research consultancy
organisations, has conducted market research studies in the field of banking and
evaluated the bank's advertising and publicity and its image among the people. It reflects
a customer's overall perception about that firm. Hence, we put forward the following
hypothesis:
H4. Promotion has a positive and significant effect on customer.
3.2.5. People
Judd (1987) came out with another ‘P’, People. He even went further by recommending
that people power should be formalised, institutionalised and managed like the other
4Ps as a distinctive component of the market mix. Judd's argument was that it is the
employees of an organisation who represent the organisation to the customers. If these
employees are not given training in how to go about face-to-face customer contact, the
entire marketing effort may not prove to be effective. A service is a performance and it
is usually difficult to separate the performance from the people. The way service is
delivered by the people can be an important source of differentiation as well as
competitive advantage. These are the reasons why the ‘People’ element forms such an
important part of the 7Ps of services marketing mix.
In the case of banking, the service employee is often the primary contact point for the
customer whenever the customer interacts with the employee. Customers' perceptions
of the performance of service employees play an important role in customers'
evaluations of service quality. Therefore, the bankers' attention should be focused on
employee service quality and to develop of their services skills consistently. Many
consider personal interaction is a key driver among the dimensions of service quality
and merged together some of the SERVQUAL's items related to responsiveness,
assurance, and empathy. More specifically, it includes attitude, behaviour, expertise,
confidence, courtesy, and willingness to help of the employees toward customers. In

8
addition, customer-oriented service employees with a focus on showing personal
attention, interpersonal care, willing to help, politeness, and promptness behaviour are
likely to contribute significantly toward the strength of customer–employee
relationship. Thus, we propose the following hypothesis:
H5. People have a positive and significant effect on customer.
3.2.6.Physical evidence
Services are often intangible, and customers cannot assess their quality well. So
customers use the service environment as an important proxy for quality (Shanker,
2002). Service environ- ments, also called servicescape or physical evidence, relate to
the style and appearance of the physical surroundings and other experiential elements
encountered by customers at service delivery sites. Service firms need to manage
physical evidence carefully, because it can have a profound impact on customers'
impressions. The appearance of build- ings, landscaping, interior furnishing, equipment,
staff members' uniforms, signs, communication materials, and other visible cues all
provide tangible evidence of a firm's service quality.
The physical evidence is also important for banks because it conveys to the customers
an external image of the service package. If a bank wants to have user friendly, hi-tech
and efficient image, the branch infrastructure will have a comfortable seating, pleasant
lighting and temperature, computer systems with advanced technology and network
connectivity. The modern infrastructure with latest technology influences customers'
perceptions of the service provider and customers' behavioural intentions. Many
technological and structural changes have taken place within the global banking
environment to attract and retain the customers. In the post-liberalised economy, Indian
public and private sector banks have reformed their workplace layout to give a
comfortable, efficient and user-friendly image. Therefore, we hypothesise:
H6. Physical evidence has a positive and significant effect on customer.
3.2.7.Process
Processes are the architecture of services. Process describes the method and sequence in
services and creates the value proposition that has been promised to customers. In high-
contact services, customers themselves are an integral part of the opera- tion and the
process becomes their experience. Badly designed processes are likely to annoy
customers because they often result in slow, frustrating, bureaucratic and poor-quality
service delivery. The well designed process assures service availability, consistent
quality, total ease and convenience to the customers. As service cannot be inventoried, it
is essential to designed sound process management system which can balance service
demand with service supply in peak hours.

9
For service industries, such as banking, process is an important way of creating better
value-in-use (Zeithaml, 2008). The availability of advanced self-service technologies within
the financial industry has changed the way banks service their customers. The financial
service sector has used remote distribution channels such as the telephone or Internet to
reach more customers, cut out intermediaries, bring down overheads and increase
profitability Banking customers today can access a variety of services from their home,
office or elsewhere. But the processes involved in the banking services should be easy and
smooth, fast and accurate, and customer friendly. Businesses have moved from off-line to
on-line through electronic channels. This approach is commonly called ‘e-banking’ in terms
of banking services. Many authors argued that the accessibility of e-banking from any
location, at any time of the day, is an important factor for customers. In banking services,
customer satisfaction mainly depends on the process of service delivery. Therefore, we
hypothesis (Fig. 1):
H7. Process has a positive and significant effect on customer.
Fig. 1. The conceptual framework of the study.
4. Methodology
4.1.Measurement instrument
The survey instrument was developed based on an extensive review of the literature
and studied definitions. The constructs and their observable items are presented in
Table 1. The final set of 20 items was examined by an academic experienced in
questionnaire design. The final questionnaire consisted of three sections. In the first
section, questions were related to banking services in terms of 7P's of service
marketing toward customer. The second section contained questions regarding
demographic characteristics of the respondents such as gender, age, education,

10
profession and gross income per month. In the last, respondents were asked about
their bank name. All the items were put on a five-point Likert scale where a value of
1 expresses strongly disagree and a value of 5 expresses strongly agree.
4.2.Sampling design and data collection
Testing the suggested research hypotheses was accomplished through an online
convenience sample survey of bank customers of Gwalior city in India. There was a
note enclosed with the questionnaire that the customers have to share one of the
banking services experiences which is being operating by them frequently.72
respondents filled up the questionnaire online within the months of May–June,
2018. Total of 73 questionnaires were received out of which 72 were found to be
completely and accurately filled, the rest 1 were discarded due to incomplete
information. Respondents were the customers of different 19 banks.
These banks namely, State Bank of India (SBI), Central Bank of India (CBI), Vijay
Bank, Bank of India (BOI), Punjab National Bank (PNB), Canara Bank, Allahabad
Bank, Bank of Baroda (BOB), Union Bank of India (UBI), and United Commercial
Bank. Housing Development Finance Corporation (HDFC) Bank, Industrial Credit and
Investment Corporation of India (ICICI) Bank, Industrial Development Bank of India
(IDBI) Bank, Axis Bank, and Citi Bank, Yes Bank, Syndicate Bank, Canara Bank
etc. All 19 banks have the largest network of branches in India.
5. Data analysis and findings
All constructs in the research model are measured using multi-item scales. Scale items in the
questionnaire are measured with a 5-point Likert scale 1=strongly disagree and 5=strongly
agree presents all measures and reliabilities of scores. The regression analysis was
conducted to reveal how different factors affect the customer. A multi-correlation problem
was identified and minimized using the statistical choice methods (Nummenmaa et al.,
1996). As the conceptual model is relatively complex, the procedure using the IBM
SPSS statistics software 23.0 version.
5.1.Scale validity and reliability
Table 1
Variables and their observable indicators.
Variables Obserable variables
Product PRO1: innovative products/services.
PRO2: value added products/services.

11
Price PRI1: low cost.
PRI2: getting more.
Place PLA1: branch location convenience.
PLA2: easy availability of ATM.
Promotion PROM1: bank advertisement.
PROM2: social and cultural events.
PROM3: promotional strategies impact.
People PEO1: personal attention.
PEO2: politeness.
PEO3: willing to help.
PEO4: quick response.
Physical PHY1: modern infrastructure.
Evidence PHY2: advanced technology.
Process PROC1: easy and smooth.
PROC2: fast online services.
PROC3: services at your convenience.
Customer CUS1: overall products/services quality.
CUS2: safe and reliable
Table 2
Demographic breakdown of participants.
Category n Percentage(%)
Gender
Male 53 73.6
Female 19 26.3
Age
< 21 22 30.6
21–30 42 58.3
31–40 8 11.1
41–50 0 0.00
> 50 0 0.00
Education
Under graduate 17 23.6
Graduate 31 43.1
Post-graduate 22 30.6
Doctorate 2 2.8

12
Occupation
Service 11 15.3
Businessman 14 19.4
Professional 9 12.5
Self-employed 10 13.9
Student 28 38.9
Monthly
Income
<&10000 29 40.3
&11000 -
&20000
22 30.6
&21000 -
&30000
21 29.2
&31000 -
&40000
0 0.00
>&41000 0 0.00
Composite reliability (CR) and should be exceed the recommended threshold criterion of
0.70.
5.2.Structural model analysis
5.2.1.Model assessment
A comprehensive statistical technique for examining relations between observed and latent
variables. In the present study, the calculated values as multiple regression can affect
the results, the study examined the tolerance for multiple regression assessment. To
assess multiple regression issues of the study model, the latent variable scores
(calculated by SPSS) can be used as input for multiple regressions in IBM SPSS
software to get the tolerance.
Reliability
Scale: ALL VARIABLES
Combined Reliability Analysis
Reliability Statistics
Cronbach's
Alpha
Cronbach's Alpha
Based on Standardized
Items N of Items
.761 .757 8
Composite reliability (CR) and should be exceed the recommended threshold criterion of
0.70, the Reliability Statistics Table which provides the value for Cronbach alpha which in this

13
case is .761 and reflects high reliability of the measuring instrument. Furthermore, it indicates
high level of internal consistency with respect to the specific sample.
Regression
1. ProductCustomer
Model Summary
b
Model R
R
Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .222
a
.049 .036 .77193 .049 3.631 1 70 .061 1.399
a. Predictors: (Constant), TOTALPRO
b. Dependent Variable: TOTALCUS
This table provides the R and R2
values. The R value represents the simple correlation and is
.222 (the "R" Column), which indicates a high degree of correlation. The R2
value (the "R
Square" column) indicates how much of the total variation in the dependent variable Customer
can be explained by the independent variable Product . In this case, 4.9% can be explained,
The Durbin-Watson statistic is 1.399 which is between 1.5 and 2.5.
ANOVA
a
Model Sum of Squares df Mean Square F Sig.
1 Regression 2.163 1 2.163 3.631 .061
b
Residual 41.712 70 .596
Total 43.875 71
a. Dependent Variable: TOTALCUS
b. Predictors: (Constant), TOTALPRO
This table indicates that the regression model predicts the dependent variable significantly well.
Look at the "Regression" row and the "Sig." column. This indicates the statistical significance
of the regression model that was run. Here, p < 0.0005, which is less than 0.05, and indicates
that, overall, the regression model statistically significantly predicts the outcome variable (i.e., it
is a good fit for the data), Singinificant values is .061 whihic is >P Value, no significant effect
on Customer.
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
95.0% Confidence
Interval for B
B
Std.
Error Beta
Lower
Bound
Upper
Bound
1 (Constant) 6.814 1.391 4.900 .000 4.040 9.588
TOTALPRO .288 .151 .222 1.905 .061 -.013 .590

14
The Coefficients table provides us with the necessary information to predict satisfaction from
independent variables, as well as determine whether independent variables contribute
statistically significantly to the model (by looking at the "Sig." column). A multiple regression
analysis was conducted to verify this and explore the relationship between Prodcut and
Customer, the variability in different dimensions. Such analysis is appropriate in the case that
there is one predictor variables (product) and one response variable (customer). The regression
results shown in Table indicate that the independent variables have a significant.
2. PriceCustomer
Model Summary
b
Model R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .263
a
.069 .056 .76379 .069 5.209 1 70 .026 1.371
a. Predictors: (Constant), TOTALPRI
value (the "R
Square" column) indicates how much of the total variation in the dependent variable, Customer,
can be explained by the independent variable Price. In this case, 6.9% can be explained.
The Durbin-Watson statistic is 1.371 which is between 1.5 and 2.5.
ANOVA
a
1 Regression 3.039 1 3.039 5.209 .026
b
Residual 40.836 70 .583
Total 43.875 71
b. Predictors: (Constant), TOTALPRI
is a good fit for the data), Singinificant values is .026 whihic is >P, Value no significant effect
on Customer.
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
95.0% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 7.254 .970 7.477 .000 5.319 9.189

15
TOTALPRI .238 .104 .263 2.282 .026 .030 .447
analysis was conducted to verify this and explore the relationship between Pric and Customer,
the variability in different dimensions. Such analysis is appropriate in the case that there is one
predictor variables (price) and one response variable (customer). The regression results shown
in Table indicate that the independent variables have a significant.
3. PlaceCustomer
Model Summary
b
Model R
R
Square
Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
Durbin-
Watson
R Square
Change F Change df1 df2
Sig. F
Change
1 .162
a
.026 .012 .78122 .026 1.890 1 70 .174 1.352
a. Predictors: (Constant), TOTALPLA
value (the "R
can be explained by the independent variable Product . In this case, 2.6% can be explained.
The Durbin-Watson statistic is 1.352 which is between 1.5 and 2.5, Singinificant values is .174
whihic is >P Value no significant effect on Customer.
ANOVA
a
1 Regression 1.153 1 1.153 1.890 .174
b
Residual 42.722 70 .610
Total 43.875 71
b. Predictors: (Constant), TOTALPLA
is a good fit for the data).
Coefficients
a

16
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
95.0% Confidence Interval
for B
1 (Constant) 7.878 1.153 6.830 .000 5.577 10.178
TOTALPL
A
.171 .124 .162 1.375 .174 -.077 .419
analysis was conducted to verify this and explore the relationship between Place and Customer,
predictor variables (place) and one response variable (customer). The regression results shown
4. PromotionCustomer
Model Summary
b
Model R
R
Square
Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .296
a
.087 .074 .75630 .087 6.705 1 70 .012 1.378
a. Predictors: (Constant), TOTALPROM
value (the "R
whihic is <P Value, positive and significant effect on Customer.
ANOVA
a
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 3.835 1 3.835 6.705 .012
b
Residual 40.040 70 .572
Total 43.875 71
b. Predictors: (Constant), TOTALPROM

17
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
1 (Constant) 6.435 1.171 5.495 .000 4.099 8.770
TOTALPROM .218 .084 .296 2.589 .012 .050 .386
analysis was conducted to verify this and explore the relationship between Promotion and
there is one predictor variables (promotion) and one response variable (customer). The
regression results shown in Table indicate that the independent variables have a significant.
5. PeopleCustomer
Model Summary
b
Model R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .499
a
.249 .238 .68618 .249 23.183 1 70 .000 1.676
a. Predictors: (Constant), TOTALPEO
value (the "R
ANOVA
a
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 10.916 1 10.916 23.183 .000
b
Residual 32.959 70 .471
Total 43.875 71

18
b. Predictors: (Constant), TOTALPEO
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
1 (Constant) 3.803 1.177 3.230 .002 1.455 6.151
TOTALPE
O
.303 .063 .499 4.815 .000 .177 .428
analysis was conducted to verify this and explore the relationship between People and
there is one predictor variables (people) and one response variable (customer). The regression
results shown in Table indicate that the independent variables have a significant.
6. Physical evidenceCustomer
Model Summary
b
Model R
R
Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
Durbin-
Watson
R Square
Change F Change df1 df2
Sig. F
Change
1 .381
a
.145 .133 .73199 .145 11.885 1 70 .001 1.544
a. Predictors: (Constant), TOTALPHY
value (the "R
can be explained by the independent variable Product . In this case, 14.5.% can be explained.
ANOVA
a
Model
Sum of
Squares df
Mean
Square F Sig.

19
1 Regression 6.368 1 6.368 11.885 .001
b
Residual 37.507 70 .536
Total 43.875 71
b. Predictors: (Constant), TOTALPHY
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
1 (Constant) 6.065 .988 6.138 .000 4.094 8.036
TOTALPH
Y
.363 .105 .381 3.447 .001 .153 .573
analysis was conducted to verify this and explore the relationship between Physical evidence
and Customer, the variability in different dimensions. Such analysis is appropriate in the case
that there is one predictor variables (physical evidence) and one response variable (customer).
The regression results shown in Table indicate that the independent variables have a significant.
7. ProcessCustomer
Model Summary
b
Model R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .551
a
.303 .293 .66091 .303 30.446 1 70 .000 1.440
a. Predictors: (Constant), TOTALPROC

20
value (the "R
ANOVA
a
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 13.299 1 13.299 30.446 .000
b
Residual 30.576 70 .437
Total 43.875 71
b. Predictors: (Constant), TOTALPROC
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
1 (Constant) 4.215 .954 4.420 .000 2.313 6.116
TOTALPROC .374 .068 .551 5.518 .000 .239 .509
analysis was conducted to verify this and explore the relationship between Pric and Customer,
predictor variables (price) and one response variable (customer). The regression results shown
Correlations
Correlations

21
TOTAL
CUS
TOTAL
PRO
TOTAL
PRI
TOTAL
PLA
TOTAL
PROM
TOTAL
PEO
TOTAL
PHY
TOTALP
ROC
TOTALCUS Pearson
Correlation
1 .222 .263
*
.162 .296
*
.499
**
.381
**
.551
**
Sig. (2-tailed) .061 .026 .174 .012 .000 .001 .000
N 72 72 72 72 72 72 72 72
TOTALPRO Pearson
Correlation
.222 1 .161 .218 .080 .281
*
.221 .278
*
Sig. (2-tailed) .061 .177 .065 .504 .017 .062 .018
N 72 72 72 72 72 72 72 72
TOTALPRI Pearson
Correlation
.263
*
.161 1 .076 .008 .207 .290
*
.207
Sig. (2-tailed) .026 .177 .525 .949 .082 .013 .081
N 72 72 72 72 72 72 72 72
TOTALPLA Pearson
Correlation
.162 .218 .076 1 .222 .182 .200 .192
Sig. (2-tailed) .174 .065 .525 .061 .126 .092 .106
N 72 72 72 72 72 72 72 72
TOTALPROM Pearson
Correlation
.296
*
.080 .008 .222 1 .407
**
.408
**
.219
Sig. (2-tailed) .012 .504 .949 .061 .000 .000 .065
N 72 72 72 72 72 72 72 72
TOTALPEO Pearson
Correlation
.499
**
.281
*
.207 .182 .407
**
1 .535
**
.585
**
Sig. (2-tailed) .000 .017 .082 .126 .000 .000 .000
N 72 72 72 72 72 72 72 72
TOTALPHY Pearson
Correlation
.381
**
.221 .290
*
.200 .408
**
.535
**
1 .497
**
Sig. (2-tailed) .001 .062 .013 .092 .000 .000 .000
N 72 72 72 72 72 72 72 72
TOTALPROC Pearson
Correlation
.551
**
.278
*
.207 .192 .219 .585
**
.497
**
1
Sig. (2-tailed) .000 .018 .081 .106 .065 .000 .000
N 72 72 72 72 72 72 72 72
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Now let's take a close look at our results: the strongest correlation is between PEO and between PROC :
r = 0.585. It's based on N = 72 .and its 2-tailed significance, p = 0.000. This means there's a 0.000 probability
of finding this sample correlation -or a larger one- if the actual population correlation is zero.

22
¼
5.2.2.Main effects and path coefficients
The results indicated thatPromotion, People, Physical evidence had positive and
significant effect on customer. Thus H4, H5, H6 and H7 were accepted. However,
Product, Price, Place showed no significant effect on customer. Therefore, H1, H2
and H3 were rejected. And strongest correlation between People and process.
6. Discussion and conclusion
The purpose of the study was to demonstrate the most important elements of services
marketing mix that inﬂuence Indian customer and to determine the right services
marketing mix in the context of banking sector. The research emphasises the important
role of services marketing mix on banking industry. In bank marketing, little prior
research focuses on the relationship among the ‘7Ps’ of service marketing mix efforts
toward customer. The present study examined a model to explain the mentioned
relationship in the context of Indian banking customer. In other words, the effect of
individual ‘P’ of services marketing mix on customer was determined. Regressioon
analysis produce dimensions of product, price, place, promotion, people, physical
evidence, process, and customer.
7. Managerial implications
Indian banking industry has gone through the pre-independence, post-independence, pre-
nationalisation, nationalisation and post- liberalisation stages. Marketing was always
considered not to be a banker's cup of tea. But today, it is considered to be an integral
management function in the banking sector. And if a bank is functioning based on
marketing tools and techniques, it simply means that a bank's decisions are made through
the eyes of the customers of the bank. As banks do not provide tangible products, their
managers need to put a lot of emphasis on services marketing mix to acquire and retain
the customers. The study suggested that physical evidence, process, place and people are
the main services marketing mix elements in the context of bank services. Importantly,
right combination of services marketing elements can be used to create stronger customer-
ﬁrm relationships, as shown in the present study. All these are important for banks
because it helps customers to develop an image of the bank. This can be achieved by
attaching more importance to the indicators of these ‘Ps’. Moreover, there is a dire need to
improve banking services with modern infrastructure and advanced technology, followed
by easy and smooth banking process, fast online and other services at customer's
convenience. A user-friendly image of the bank can be built by its interior design with
a comfortable seating arrangement, pleasant lighting, temperature and cleanliness,
computer systems with advanced technology and network connectivity, and

23
convenient and easy accessible counters. Further, branch location and easy availability
of ATM machines should be considered in the view point of customer convenience by
the bankers. The convenience of the location of branches of the bank and its ATMs are
the dominant criterion both for subsequent satisfaction and selection of bank. A large
number of branches and ATMs at various locations make the bank more approachable
to the customers (Kranias and Bourlessa, 2013). Banks should also encourage
employees to develop friendship and long-term relationship with cusomers. It can be
achieved by listening to what customer has to say, pay personal attention to him.
Especially, in the case of Indian customers, they look for a personal attention in all
their transaction. To have a close relation with customers, the bank management has to
ensure that core service is delivered on the time with quick response. Because quick and
timely response is important for banking in order to create customer satisfaction and
loyalty. It can also be helpful to handle the possible conflicts between staff and
customer. The banks must undertake strategies, such as employees training to make
them courteous, caring and responsive. The speed in service delivery, courtesy and
helpfulness of bank staff are the most critical attributes that influence customers. In
general, customers look for an environment, where the employees listen to their
problems and show willingness to help them, and are polite to them. Customers feel
more satisfied when they get quick response to their problems. Ultimately, the findings
of the study indicated that the proper implementation of right services marketing mix
elements may be helpful for banks to attract new customers and retain old customers
which results in higher sales, market share, and profits. Because overall the banks are
delivering the identical products, charges are fixed and driven by marketplace. Thus,
banker tends to differentiate its firm from competitors through right services
marketing mix dimensions.
8.Limitations and future research directions
The study gauges the effect of ‘7Ps’ of services marketing mix on Indian customer in the
context of bank marketing. The research, however, is subject to some limitations. The
study results obtained by the convenience sampling method were difficult to generalise
to the population because it was a type of non- probability sampling. A more
representative sampling technique needs to be considered in future research to generalise
the findings of the study. The current study was primarily a cross- sectional due to time
and cost constraints, although a longitudinal study is recommended to monitor the
evolution of customer behaviour over time. It is important to note that the study is
limited to a sample size of 72 Indian customers. The larger sample sizes with foreign
customers residing and having bank accounts in India can be considered by future
researchers. The scope of the study is also limited to the number of banks (19) in the
research. The application of the services marketing mix elements identified in the study
cannot be generalised as we have taken only one industry (banking). To confirm its
applicability in other financial services like insurance, loans, share trading etc., the same
study should carry out in various other financial service based firms. There is obviously

24
opportunity for a similar study in different geographic locations. Finally, the future
research is recommended to measure the effect of identified services marketing mix
elements on bank performance.
9. References
Gronroos, C. (1983). The internal marketing function. marketing science, 83-104.
Gronroos, C. (2004). The relationship marketing process: communication, interaction, dialogue, value. J. Bus. Ind. Mark,
99-113.
Judd, V. C. (1987). Differentiate with the 5th P: People. Mark Manag, 241-247.
Kotler, P. (2000). Marketing Management. Millenium Edition Prentice-Hall of India.
Kranias, A., & Bourlessa, M. (2013). Investigating the relationship between service quality and loyalty in Greek banking
sector. Procedia Econ. Financ, 453-458.
Krasnikov, A., Jayachandran, S., & Kumar, V. (2009). The impact of customer relationship management implementation
on cost and profit efficiencies: evidence from the U.S. commercial banking industry. J. Mark., 61-76.
Kushwaha, G. S., & Agrawal, S. R. (2014). An Indian customer surrounding 7 P's of service marketing. Science dierect, 85-
96.
McCarthy, E. J. (1960). Basic Marketing: A Managerial Approach. Homewood.
Shanker, R. (2002). Services Marketing, The Indian Perspective. Excel Books.
Wallis, S. (1997). The financial system inquiry final report. AGPS.
Zeithaml, V. A., Bitner, M. J., & Pandit, D. D. (2008). Services Marketing, Integrating Customer Focus across the Firm. Tata
McGraw-Hill.

25

25
10. Procedure of Reliability and Regression analysis
Step 1: Select a base paper and create questionnaire on Google
Form.
Step 2: Create a Link of questionnaire and send it to different
customer of the Banking.
https://goo.gl/forms/POiI73Aa9afr7JoZ2

26
Step 3: Generate an Excel Sheet of the Responses, there is 72
respondent.
Step 4: Paste our responses in SPSS, in Date View section.

27
Step 5: Coding in of the data in Variable View.
Step 6: Change the Measures, Label and Value.

28
Step 7: Compute Variable, TransformCompute Variable
option available.
Step 8: All Compute Variable given in below table as
TOTALPRO….etc.

29
Step 9: Reliability Test ,AnalyzeScaleReliability Analysis
Step 10: Dialogue Box Open

30
Composite reliability (CR) and should be exceed the recommended threshold
criterion of 0.70, the Reliability Statistics Table which provides the value for
Cronbach alpha .761.
Step 11: Regression Analysis, AnalyzeRegressionLinear

31
Step 12: Dependent Customer and Independent 7P’s (Product,
Price, Place, Promotion, People, Physical evidence and Process)
Step 13: Dialogue Box Open

32
Step 14: Regression Analysis Output
values. The R value represents the simple
correlation and is .619 (the "R" Column), which indicates a high degree of
correlation. The R2
value (the "R Square" column) indicates how much of the total
variation in the dependent variable, Customer , can be explained by the
independent variable, 7P’s . In this case, 38.3% can be explained.
This table indicates that the regression model predicts the dependent variable
significantly well. How do we know this? Look at the "Regression" row and go to
the "Sig." column. This indicates the statistical significance of the regression
model that was run. Here, p < 0.0005, which is less than 0.05, and indicates that,
overall, the regression model statistically significantly predicts the outcome
variable (i.e., it is a good fit for the data).
The Coefficients table provides us with the necessary information to predict price
from income, as well as determine whether income contributes statistically
significantly to the model (by looking at the "Sig." column). Furthermore, we can
use the values in the "B" column under the "Unstandardized Coefficients"
column, as shown below:

33
The Coefficients part of the output gives us the values that we need in order to
write the regression equation. The regression equation will take the form:
Predicted variable (dependent variable) = slope * independent variable + intercept
11. Questionnaires
(Attached)

34

Questionnaire
* Required
An Indian customer surrounding 7P's of service marketing in
banking sectors.
1. Gender *
Mark only one oval.
Male
Female
2. Age *
Mark only one oval.
< 21
21 - 30
31 - 40
41 - 50
< 50
3. Education *
Mark only one oval.
Under graduate
Graduate
Post-graduate
Doctorate
4. Occupation *
Mark only one oval.
Service
Businessman
Professional
Self-employed
Student
5. Monthly Income *
Mark only one oval.
< 10000
11000 - 20000
21000 - 30000
31000 - 40000
> 41000

6. Which bank do you prefer? *
Instructions
1. Strongly disagree
2. Disagree
3. Neutral/Neither agree nor disagree
4. Agree
5. Strongly agree
7. 1. Innovative products/services. *
Mark only one oval.
1 2 3 4 5
Strongly disagree Strongly agree
8. 2. Value added products/services. *
Mark only one oval.
1 2 3 4 5
9. 3. Low cost. *
Mark only one oval.
1 2 3 4 5
10. 4. Getting more. *
Mark only one oval.
1 2 3 4 5
11. 5. Branch location convenience. *
Mark only one oval.
1 2 3 4 5
12. 6. Easy availability of ATM. *
Mark only one oval.
1 2 3 4 5

13. 7. Bank advertisement. *
Mark only one oval.
1 2 3 4 5
14. 8. Social and cultural events. *
Mark only one oval.
1 2 3 4 5
15. 9. Promotional strategies impact. *
Mark only one oval.
1 2 3 4 5
16. 10. Personal attention. *
Mark only one oval.
1 2 3 4 5
17. 11. Politeness. *
Mark only one oval.
1 2 3 4 5
18. 12. Willing to help. *
Mark only one oval.
1 2 3 4 5
19. 13. Quick response. *
Mark only one oval.
1 2 3 4 5

20. 14. Modern infrastructure. *
Mark only one oval.
1 2 3 4 5
21. 15. Advanced technology. *
Mark only one oval.
1 2 3 4 5
22. 16. Easy and smooth *
Mark only one oval.
1 2 3 4 5
23. 17. Fast online services. *
Mark only one oval.
1 2 3 4 5
24. 18. Services at your convenience. *
Mark only one oval.
1 2 3 4 5
25. 19. Overall products/services quality. *
Mark only one oval.
1 2 3 4 5
26. 20. Safe and reliable. *
Mark only one oval.
1 2 3 4 5
THANK YOU

Powered by
Thank You

7Ps’ of Service marketing-Major Research Project

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à 7Ps’ of Service marketing-Major Research Project

Similaire à 7Ps’ of Service marketing-Major Research Project (20)

Plus de KULDEEP MATHUR

Plus de KULDEEP MATHUR (20)

Dernier

Dernier (20)

7Ps’ of Service marketing-Major Research Project