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- International Journal of Management (IJM)
Volume 11, Issue 3, March 2020, pp. 439–448, Article ID: IJM_11_03_047
Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=11&IType=3
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ISSN Print: 0976-6502 and ISSN Online: 0976-6510
© IAEME Publication Scopus Indexed
EFFECTIVENESS OF ONLINE MARKETING
AND ITS DETERMINANTS: MARKETERS’
PERSPECTIVE
Veluchamy Ramanujam
Associate Professor, Bharathiar School of Management and Entrepreneur Development
(BSMED), Bharathiar University, Coimbatore, Tamil Nadu, India
Picthai Parthiban
Research Scholar, Bharathiar School of Management and Entrepreneur Development
(BSMED), Bharathiar University, Coimbatore, Tamil Nadu, India
Kasilingam Lingaraja
Assistant Professor, Department of Business Administration, Thiagarajar College
(Autonomous), Madurai, Tamil Nadu, India
ABSTRACT
The present study aims to the profile of the marketers, their e-marketing behavior
and its antecedents and the service quality in online marketing and the factors leading
to the successful implementation. And also the effectiveness of online marketing, its
determinants and its consequences, causes for service failure in online marketing and
the expected service quality in online marketing. In total 535 marketers were identified.
Out of the 535 marketers only 392 marketers responded the questionnaire given to them.
Hence the sample size of customers came to 392 had been used to collect the data. The
present study conclude that the level of EE adoption have a significant impact on the
rate of implementation of online marketing. The important antecedents to implement
online marketing are convenience, merchandize, interactivity, reliability, navigation,
and promotion.
Key Words: Online Marketing, Service Failure, Expected Service Quality
JEL Classification Code: M15, M31, O32, Z33
Cite this Article: Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja,
Effectiveness of Online Marketing and its Determinants: Marketers’ Perspective,
International Journal of Management (IJM), 11 (3), 2020, pp. 439–448.
http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=3
1. INTRODUCTION
On line communication can enhance efficiency in many ways. In the content of sales
performance and customer satisfaction, information flows facilitated by e-businesses can help
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- Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja
the sales volume by reacting customer directly and promptly whenever a new product is
introduced and by tapping into markets that were hitherto inaccessible on account of
distribution or other infrastructural constraints. The business can also enhance customer
satisfaction by providing information about products, trouble shooting, and service on line
furthermore, interested consumers who set can invoke a relationship with the unit on their own
accord. Both sales performance and customer satisfaction can benefit on these accounts. In the
context of relationship development, online communication can help a business increase the
intensity of and enrich the quality of, its interactions with partners and suppliers. In addition,
important product planning and inventory information can be shared on a regular, or even real-
time, basis, leading to more productive relationships. Also, when the business units systems
and online information repositories are integrated with those of its partners and suppliers, these
parties are likely to exhibit a greater commitment to their mutual relationship. Internal
administration covers processes related to financial and management accounting, travel
reimbursement, payroll, and employee benefits procession. The e-business adoption makes its
impact on order taking performance, procurement of materials and relationship development
also.
2. SCOPE AND NEED FOR THE STUDY
The proliferation of and rapid advances in technology – based systems, especially those related
to the interest, are leading to fundamental changes in how companies interact with one another
and with customers. Indeed, selling products and service via the internet is agreed to have
enormous potential, and e–commerce has received enormous pressure, speculation and
criticism. The internet technology has the potential to alter almost every aspect of business
operations. As a result, it is necessary to take a multidisciplinary approach for understanding
the marketers view on e-marketing since the e-marketers act as a intermediaries between the
customers and producers of goods and services. Since, the e-marketers, producers and
consumers are interlinked with each other’s, it is imperative to analyze the marketers’
perception on various aspects related to e-marketing and its impact. Hence, the present study
has made an attempt on these aspects.
3. STATEMENT OF THE PROBLEM
In the case of e-marketing, there is no direct personal meet of the marketers and consumers.
Hence, the marketers have to be careful in the determination of the customers’ expectations and
perception on various aspects related to the products and services in e-marketing. They should
be aware of the factors leading to their attitude towards e-marketing. At the same time, the
marketers should know their strengths and weakness in e-marketing. If not, there will be a lot
service failure. Nowadays, the management of service failure in e-marketing has received
increasing attention. Furthermore, despite the phenomenal growth in electronic commerce in
general and e-marketing in particular, research has yet to examine the role of service recovery
management. The e-marketing is subjected with some issues like credit card security, privacy,
on – time delivery and ease of navigation. The ability of the consumers to exit a relationship
with their marketers is very easy and frequent in e-marketing. Hence the service quality of the
marketers is an important as ever in this realm. Indeed, the technological changes in the world
lead to ever changing environment in the e-marketing. Hence, the marketers have to be vigilant
on knowing all these changes and prepare to accompany the changes in e-environment.
4. REVIEW OF LITERATURE
Ozment and Morash (2014) revealed that delivering quality in services has been shown to be
an important strategy for marketers who are typing to differentiate their service offering by
establishing customer value and satisfying customer needs. Bienstock et al., (2017) have shown
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- Effectiveness of Online Marketing and its Determinants: Marketers’ Perspective
that when a service provider and service customer are physically separated, it has a significant
impact in the criteria used to evaluate the service quality. The ability to handle question,
concerns, and frustrations from that customer is essential to the customer perception on e-
service quality. Mohr and Bitner (2015) demonstrated that service recovery has a direct
relationship with factors such as a trust, repurchase intention, commitment and word of mouth,
which all play a crucial role in success for e-retailers. Fram and Crady (2015) identified that
the ease of use in considered on one of the most important factors to customer on the internet.
This concept has been characterized as the customer ability to use as few “clicks” as possible.
It also includes the issue of navigation, effective search engines, the ability to easily change or
cancel an order, and the ability to inform customer of missing information. Pan et al,. (2017)
took an empirical study on the price dispersion in e-markets. They found that e-price dispersion
is persistent, even after controlling for e-toiler heterogeneity. They found evidence that e-
markets are not especially competitive from a pricing perspective. Alba and Hutchwison,
(2017) believed that price sensitivity would be lower e-than in traditional outlets when the non-
price attributes or quality attributes are of greater importance and when there is more product
differentiation among the choices. When the products are relatively comparable, then price, of
course, will play a greater role.
5. OBJECTIVES OF THE STUDY
1. To identify the success factors and the hurdles in their placement of online
marketing;
2. To evaluate the impact of service quality in online marketing, handless in it on the
overall effectiveness of online marketing.
6. RESEARCH METHODOLOGY
In the present study, research methodology covers the research design, locale of research,
sample and sampling, procedure and measurement variables, method of data collection, frame
work of analysis and limitations.
In the present study, the descriptive research design have been administered. Since this
research describes the characteristics of the marketers in e-marketing, it is concerned with
descriptive in nature. Meanwhile, this study analyze the e-marketing behavior and its
antecedents, e-services quality, service failure in e-marketing, its relationship with the profile
of the marketers, it seems to be diagnostic in nature. Besides, this present study is completely
based on determined objectives, research design, and data collection, processing of the collected
data and reporting. Hence it is descriptive in nature. The sampling framework consists of
determination of sample size and distribution of sample size. The sampled e-marketers have
been identified by the pilot study among 20 experienced and 20 lesser experienced marketers.
Since the population of the study is unknown, the sample size of the study is determined by
Z
2
n . Whereas n - Sample size; Z – 1.96 at five per cent level; σ - Standard deviation of
D
marketers’ attitude on e-marketing measured at five point scale in pilot study = 0.5899; and
1.96 0.5899
2
(D)- Error acceptance = 0.05. In the present study, n = 534.72=535
.05
marketers. In total, 535 marketers was identified by popular web service providers namely
Pronet, Satyam, Airtel and BSNL. All 535 marketers have been included as the sampled
marketers for the study.
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- Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja
7. DATA ANALYSIS AND INTERPRETATION
In the present study, the effectiveness of online marketing have been measured with the help of
eighteen performance variables. These are reduction in cost of product, increase in markets
share, customer satisfaction, strengthen business relationship, reduction in cost of transaction,
favorable works of mouth from marketers, retaining existing marketers, increase in sales
volume, marketers loyalty, strengthen the relationship among business partners, reduction in
cost of general management, attractive change in price, strengthen relationship with suppliers,
reduction in cost of co-ordination, increase in new marketers, increase in marketers enquiry,
reduction in cost of marketing and reduction in cost of acquiring new marketers. The marketers
are asked to rate the above said performance measures at five point scale from highly agree to
highly disagree. The scores assigned on the scales from 5 to 1 respectively. In order to identify
the in level of performance of the marketer in each performance measures, the mean score of
the performance measures have been calculated. The‘t’ statistics are also computed to show the
significant difference among the two group of marketers regarding their performance by e-
marketing.
TABLE .1
Variables in Effectiveness of Online marketing (EEM)
Mean scores among
Sl. marketers in
Variables in EEM t-statistic
No.
LE HE
1. Reduction in cost of production 2.4718 3.3091 -3.3667*
2. Increase in market share 2.9101 3.8426 -3.1982*
3. Customer satisfaction 2.6814 3.6517 3.5041*
4. Strengthen business relationship 2.9641 4.1109 3.6076*
5. Reduction in cost of transaction 2.8102 3.4517 2.7547*
6. Favorable words of month from marketers 2.4568 3.8196 4.1645*
7. Retaining of existing marketers 3.1142 3.8611 -2.9945*
8. Increase in sales volume 3.0681 4.2149 -3.4289*
9. Customer loyalty 2.2196 2.5768 -0.5268
Strengthen the relationship among business
10. 3.0414 3.6888 -2.1143*
partners
11. Reduction in cost of general management 3.2091 4.2674 -3.3771*
12. Attractive change in price 2.4511 3.4081 -3.4969*
13. Strengthen relationship with suppliers 3.1086 3.5696 -0.8044
14. Reduction in cost of co-ordination 2.8908 3.6017 -3.1965*
15. Increase in new marketers 2.7076 3.9114 -3.2569
16. Increase in cost of marketing 2.9114 3.8087 -3.1974*
17. Reduction in cost of marketing 2.4561 4.2086 -4.2065*
18. Reduction in cost of acquiring new marketers 2.8681 3.6085 -3.1664*
* Significant at 5 per cent level.
The important variables in EOM identified by LE marketers are reduction in cost of co-
ordination and retaining of existing marketers since their mean scores are 3.1086 and 3.1142
respectively. Among the HE marketers, these performance measures are, reduction in cost of
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- Effectiveness of Online Marketing and its Determinants: Marketers’ Perspective
general management and reduction in cost of marketing since its mean scores are 4.2674 and
4.2086 respectively. Regarding the perception on the variables in EEM, the significant
difference among the two group of marketers have been identified in the perception on
reduction in cost of production, increase in market share, customer satisfaction, strengthen
business relationship, reduction in cost of transaction, favorable words of month from
marketers, retaining existing marketers, increase in sales volume, strengthen the relationship
among business partners, reduction in cost of general management, attractive change in price,
reduction in cost of co-ordination, increase in marketers enquiry, reduction in cost of marketing
and reduction in cost of acquiring new marketers since their respective ‘t’ statistics are
significant at five per cent level which is similar to the findings of Donthu and Garcia (1999);
Jayawardhana (2004),
7.1. Association between Profile of Marketers and their view on IEEM
The profile of the marketers may be associated with their level of view on IEEM, the present
study has made an attempt to examine it with the help of one way analysis of variance. All the
eight profile variables and the sum IEEM are included for the present study. The result of one
way analysis of variance are shown in Table 2.
TABLE 2
Association between Profile of Marketers and their view on Effectiveness of Online marketing
F-Statistics in
Sl.
No Profile variables Marketers
. Efficiency Sales Relationship
Satisfaction
1. Type of markets 3.9841* 3.2117* 2.4563 2.2084
2. Age of markets 2.1171 2.9687* 2.6991* 2.9667*
3. Level of education 2.0996 2.2041 2.6979* 2.5984*
4. Personality score 2.8371* 2.0173 2.2626 2.2884
5. Number of products 2.6547* 2.7109* 2.7886* 2.8884*
6. Business turnover 2.6673* 2.1446 2.6979* 2.8983*
7. Market coverage 2.9084* 2.7971* 2.5171* 2.6868*
Technology readiness
8. 2.4117 2.2886 2.1887 2.3084
score
* Significant at five per cent level.
Regarding the view on efficiency, the significantly associating profile variables are type of
markets, personality score, number of products dealt, business turnover and market coverage
whereas in the view on sales, these profile variables are type of marketers, age of the marketers,
number of products dealt and market coverage. The significantly associating profile variables
regarding the iew on marketers satisfaction are age of marketers, level of education, number of
products dealt, business turnover, and market coverage whereas regarding the view on
relationship, these variables are age of marketers, level of education, number of products dealt,
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- Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja
business turnover and market coverage since their respective ‘F’ statistics are significant at five
per cent level.
7.2. Causes for Service Failure in Online marketing
It is important to analyze the various causes for service failure in online marketing for some
policy implications. Even though the variables related to service failure are too many, the
present study confine to 23 variables. The marketers are asked to rate the 23 variables at five
point scale from high agree to highly disagree. The mean score of each variable among the LE
and HE marketers has been computed separately. The ‘t’ test is used to find out the significant
difference among the two group of marketers.
TABLE 3
Variables in Causes of Service Failure (CSFA)
Mean score among
Sl.No. Variables in CSFA marketers in t – statistics
LE HE
1 Lack of personalized service 3.9845 3.1446 3.1285*
2 Poor presentation of product at site 3.7961 3.0891 3.1667*
3 Late delivery 3.8503 3.2662 2.9028*
4 Poor communication 3.6862 3.0117 2.5117*
5 Navigational problem at site 3.8908 3.0445 3.2016*
6 Difficulties in collection 3.9985 3.1408 3.3068*
7 Wrong size delivery 3.7501 3.1141 2.9604*
8 Credit card related problem 3.6568 2.9698 2.6771*
9 Insufficient information at site 3.8243 3.2646 2.6079*
10 Wrong product delivery 3.8334 3.1779 2.8011*
11 Credit card fraud 3.4548 3.8142 -1.0242
12 Poor customer support 3.8141 3.2645 2.4898*
13 Misrepresented merchandize 3.6173 3.7233 -0.2265
14 Delivery of damaged product 3.9694 3.7142 0.5046
15 Unfair return policies 3.6617 3.0466 2.4116*
16 E-mail address released to e-marketers 3.5844 3.6861 -0.3291
17 No delivery 3.4548 3.0961 1.1338
18 Mistake at website 3.8772 3.1042 3.1041*
19 Unclear return policies 3.7182 3.0545 2.8962*
20 Incorrect lost of products 3.8545 3.1546 3.0217*
21 Confusing account problem 3.9697 3.1025 3.4664*
22 Incorrect information at site 3.9908 3.0411 3.5086*
23 Discriminatory pricing 3.7141 3.0865 3.0241*
*Significant at five per cent level.
The Table 3 exhibits the mean of various variables related to service failure among the LE
and HE marketers and its respective‘t’ statistics. The highly viewed variables among the LE
marketers is difficulties in collection and incorrect information at site since its mean scores are
3.9985 and 3.9908 respectively. Among the HE marketers, these variables are credit card fraud
and delivery of damaged goods since their mean scores are 3.8142 and 3.7233 respectively.
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- Effectiveness of Online Marketing and its Determinants: Marketers’ Perspective
Regarding the perception on variables in service failure, the significant difference among LE
and HE marketers have been noticed in the case of 18 variables out of 23 variables since their
respective‘t’ statistics are significant at five per cent level. In total, the perception on variables
related to service failure is identified as higher among the LE marketers than the HE marketers.
7.3. Expected Service Quality (ESQ) in Online Marketing
The success of marketers in the online marketing rest on their service quality in the market. It
is called as expected service quality in online marketing. The marketers view on the expected
service quality needed by the marketers have been measured with the help of 22 variables. The
marketers are asked to rate these variables at five point scale according to the order of
importance. The mean of each variable among the LE and HE marketers have been computed
separately.
TABLE 4
Expected Service Quality (ESQ) by the Marketers
Mean score among marketers
Sl.No. Variables in ESQ in t – statistics
LE HE
1 Creativity 3.2334 3.8587 -2.9068*
2 Integration 3.1089 3.9082 -3.2309*
3 Accessibility 3.4144 3.9881 -2.6062*
4 Graphic design 3.0245 3.8568 -3.3565*
5 Purpose 3.2446 3.8085 -3.0314*
6 Speed 3.3081 3.9714 -2.4084*
7 Verbal expression 3.2469 3.8917 -2.5565*
8 Band width sensibility 3.4084 3.9649 -2.0211*
9 Customer service 3.8145 3.8802 -0.2446
10 Attention to detail 3.6673 3.9905 -0.8069
11 User friendliness 3.1782 3.9442 3.2091*
12 Information process 3.3084 3.6547 -0.9061*
13 Focus of message 3.6463 3.9345 -1.0234
14 Navigation and links 3.5088 3.9943 -1.4642
15 Distinctiveness 3.1177 3.8844 -2.9109*
16 Aesthetics 3.2671 3.9884 -2.9646*
17 Values 3.3082 3.8841 -2.3147*
18 Loyalty 3.3021 3.9049 -2.4889*
19 Alignment 3.0841 3.7764 -2.7023*
20 Human interactivity 3.8084 3.6844 0.2086
21 Layout 3.1773 3.8225 -2.9084*
22 Vision 3.2447 3.9664 -2.9611*
*Significant at five per cent level
The Table 4 illustrates the mean score of the variables in service quality among LE and HE
marketers and its respective‘t’ statistics. The highly viewed variables in expected service
quality of marketers (ESQ) among the LE marketers is customer service and human
interactivity since their respective mean scores are 3.8145 and 3.8084. Among the HE
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- Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja
marketers, these two variables are navigation and links; and attention to detail since their mean
scores are 2.9943 and 3.9905 respectively. Regarding the perception on variables in ESQ, the
significant difference among the LE and HE marketers have been noticed in the perception on
16 variables out of 22 variables in ESQ since their respective ‘t’ statistics are significant at five
per cent level.
7.4. Marketers view on IESQFs
The marketers view on important service quality needed b them are examined with the help of
the mean score of the five IESQFs . The score of each IESQFs is derived by the mean score of
the variables in it. The mean score of each IESQFs among the LE and HE marketers have been
computed separately. The ‘t’ test has been administered to find out the significant difference
among the two group of marketers regarding their view on IESQFs . The results are summarized
in Table 5.
TABLE 5
Marketers’ view on IESQFs
Mean score among marketers in
Sl.No. IESQFs t – statistics
LE HE
1 Design 3.1400 3.8828 -3.3891*
2 Functionality 3.3884 3.9611 -2.0128*
3 Content 3.5896 3.8996 -0.6965
4 Originality 3.4551 3.8059 -1.6081
5 Professionalism 3.1986 3.9032 -3.4548*
*Significant at five per cent level
The highly viewed IESQFs among the LE marketers is content and originality since their
mean scores are 3.5896 and 3.4551 respectively. Among the HE marketers, these are
functionality and professionalism since their mean scores are 3.8996 and 3.9032 respectively.
Regarding the perception on IESQFs, the significant difference among LE and HE marketers
have been noticed in the case of perception on design, functionality and professionalism since
their respective ‘t’ statistics are significant at five per cent level.
8. SUMMARY OF FINDINGS
1. Impact of Service quality of Effectiveness of Online Marketing: The significantly
influencing service quality factors on the level of effectiveness of online marketing as
per the view of LE are reliability, case of use, responsiveness, convenience,
creditability, access and security whereas as per the view of HE, these are
communication, personalization, convenience and continuous improvement.
2. Causes for Service Failure in Online Marketing: The causes for service failure in
online marketing is examined with the help of 23 variables. The highly viewed variables
in it by LE and HE are difficulties in collection and credit and fraud respectively. The
significant difference among the LE and HE have been noticed in their view on 18 out
of 23 variables. The important causes for service failure identified by the factor analysis
are navigation, delivery, customer service, sanity, collection and others.
3. Expected Service Quality in Online Marketing: The expected service quality in the
online marketing for the total success is studied with the help of 22 variables. The highly
viewed by LE and HE are human interactivity and navigation and links respectively.
The significant difference among LE and HE have been noticed in their view on 16 out
of 22 variables in it. The important expected service quality factors in online marketing
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- Effectiveness of Online Marketing and its Determinants: Marketers’ Perspective
identified by the factor analysis are design functionality, content, originality and
professionalism.
9. SUGGESTIONS
Based on the findings of the study, the following suggestions are drawn.
1. Response on Service Failure in Online Marketing: One of the important
determinants of the effectiveness of online marketing is the response on the service
failure among the marketers. The service failure of marketers is mainly caused by
the delivery problems and navigational problems. Hence, the marketers should
avoid these two problems in order to enrich their effectiveness. Apart from this, they
have to establish successful logistics plans and also the improved interaction
between service personnel and their online clientele. The personalized messages and
customized recoveries may provide a better customer trust and commitment.
2. Continuous Important in the Effectiveness of Online Marketing: The
effectiveness of online marketing is visible in the present study. But there is a need
for continuous enrichment in the effectiveness of online marketing. For that purpose,
the marketers are advised to develop the business model as per the requirement of
the present scenario. They are advised to frame the marketing strategies to enrich
their performance continuously.
10. CONCLUDING REMARKS
The present study conclude that the level of EE adoption have a significant impact on the rate
of implementation of online marketing. The important antecedents to implement online
marketing are convenience, merchandize, interactivity, reliability, navigation, and promotion.
The important service quality delivered by the marketers are reliability, ease to use,
communication, responsiveness, personalization, convenience, credibility, courtesy
continuous, improvement, access and security. The identified important hurdles in
implementation of online marketing agriculture inconvenience, risk, in store effect,
environment and cost. The narrated important effectiveness of online marketing are efficiency,
sales customer satisfaction and relationship. The service quality has a significant positive
impact on effectiveness whereas the hindless are having significant negative impact on
effectiveness in online marketing. If the marketers in online marketing overcome the hindless
is online marketing, they will succeed in the market since the scope of the online marketing is
higher.
REFERENCES
[1] Alba, J and Hutchwison, W., (2017). Dimension of Consumer Expertise. Journal of consumer
research, 13(4), 411-454.
[2] Bienstock, C., Mentzerand Bird, M., (2017). Measuring Physical Distribution Service Quality.
Journal of the Academy of Marketing Science, 25(1), 31-44.
[3] Collier, E., and Carol, C. Bienstak, (2016). Measuring Service Quality in E-Retailing. Journal
of Service Research, 8(3), 260-275.
[4] Donthu, N. and Garcia, A., (1999). The Internet Shopper. Journal of Marketing Research, May
– June, 52-58.
[5] Fram, H and Grandy, B., (2015). Internet Buyers: will the Suffers become Buyers?. Direct
Marketing, October, 63-65.
[6] Holloway, Betty B. and Sharon, E. Betty, (2013). Service Failure in Online Retailing: A
Recovery Opportunity. Journal of Service Research, 6(1), 92-105.
[7] Jayawardhena,C., (2004). Personal Values’ Influence in E-Shopping Attitude and Behaviour.
Internet Research, 14(2), 127-140.
http://www.iaeme.com/IJM/index.asp 447 editor@iaeme.com
- Veluchamy Ramanujam, Picthai Parthiban and Kasilingam Lingaraja
[8] Mohr, Loss, A. and Mary Jo Bitner, (2015). The role of Employee Efforts in Satisfaction with
Service Transactions. Journal of Business research, 32(3), 239-252.
[9] Pan, Xing, Brian, T. Ratchford and Venkatesh Shankar, (2017). Can Price Dispersion in
Online Market be Explained by Differences in E-Tailer Service Quality?. International Journal
of Marketing Management, 14(1), 106-111.
[10] Ramanujam, V., and Parthiban, P. (2019). A Study on Expected Service Quality Factors by
the Marketer in E-Marketing in India. International Journal of Engineering Technologies and
Management Research, 6 (11), 71-78.
[11] Reibstein, David, J., (2012). What Attracts Customer to Online Stores and What Keeps them
Coming Back. Journal of Academy of Marketing Science, 30(4), 465-473
[12] Slyworzkey, Achian and Morrism, D., (2011). The Rise of the Active Customer. Marketing
Management, 10(2), 22-26.
[13] Smith, Daniel, C., (2013). The Importance and Challenges of being Interesting. Journal of
Academy of Marketing Science, 31(3), 319-322.
[14] Wolfinberger, Mary F. and Mary C. Gilly, (2012). ComQ: Dimensionalizing, Measuring and
Predicting Quality of the E-tail Experience. Working Paper No. 02-100, Marketing science
institute, Cambridge, M.A.
[15] Yoo, Boonghee and Naveen Donthu, (2011). Developing a Scale to Measure the Perceived
Quality of an Internet Shopping Site (Sitequal). Quarterly Journal of Electronic Commerce,
2(1), 31-46.
[16] Zeithaml, Valaraie A., A. Parasuraman and Malhotra, A., (2012). Service Quality Delivery
through Websites: A Critical Review of Extent Knowledge. Journal of the Academy of
Marketing Science, 30(4), 363-375.
[17] Prof. Shrikant Waghulkar, Dr. Kumardatt Ganjre, Prof. Nitesh Behare and Prof. Niranjan
Diwan, 2017, A Feasibility Study For Online Marketing of Agricultural Greenhouse Products
W.R.T. Pune District, International Journal of Management, 8(1), pp. 98–110.
[18] R. Ramachandran and Dr. S. Sekar, (2014), A Study On Technology And Banking Service
Quality in Tiruchirappalli, International Journal of Marketing and Human Resource
Management (IJMHRM), Volume 5, Issue 6, November – December pp. 07-17
[19] R. Khader Mohideen and S. Abdul Rajak, 2016, A Study on The Determinants of Service
Quality In Airline Sector At Tiruchirappalli Airport, 7(2), pp. 510-515.
[20] Vibha, Abhay Shetty, B. Giridhar Kamath and Gopala Krishna. B, 2018, A System Dynamics
Model For Forecasting Service Quality, International Journal of Mechanical Engineering and
Technology, 9(8), pp. 326–338.
[21] Nur Hayati and Desi Novitasari, 2017, An Analysis of Tourism Service Quality Toward
Customer Satisfaction (Study on Tourists in Indonesia Travel Destinations to Bali).
International Journal of Marketing and Human Resource Management, 8(2), pp. 09–20.
[22] Reena (Ramneek Kaur) and Dr. Tejinder Sharma, (2014), Assessment of Service Quality- A
Conceptual Framework, International Journal of Marketing and Human Resource
Management (IJMHRM), Volume 5, Issue 1, January – February pp. 33-41
[23] Parul Gupta, R.K. Srivastava, (2011), Analysis of Customer Satisfaction in Hotel Service
Quality Using Analytic Hierarchy Process (Ahp), International Journal of Industrial
Engineering Research and Development (IJIERD), Volume 2, Issue 1, May – October, pp. 59-
68
http://www.iaeme.com/IJM/index.asp 448 editor@iaeme.com
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