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Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
THE SIGNIFICANCE OF BUSINESS INTELLIGENCE IN DECISION MAKING
IN E-COMMERCE ORGANIZATIONS: AN EMPIRICAL STUDY
Rabee Ali Zaker
51
Dr. A. A. Ansari
52
ABSTRACT
Business decisions are very crucial for any organization irrespective of its industry. Decisions related to the product, services
and its improvements are totally based on the feedback of the consumers, and even promotional efforts are directly related
with addressing right and relevant consumers. All these decisions or corrective actions can be done properly within the
organization if correct and timely feedback or information is given to the decision makers.
This study is based on e-commerce organizations with respect to application of Business intelligence tools. Purpose of this
study is to explore significance of Business intelligence in decision making in e-commerce organizations. Effectiveness can be
achieved in e-commerce organization by applying Business intelligence tools.
KEYWORDS
Business Intelligence, E-Commerce, Decisions, Inventory etc.
INTRODUCTION
E-commerce denotes the use of Internet in business transactions towards sale and purchase of goods and services. This also
includes post sale support services. This business concept is not new but the new aspect is the use of technology in the sale and
purchase transactions of products and services. The same is known as E-commerce, which reaches to global customers. Once
products or services has been bought or sold, this does not mean end of E-commerce, it is rather a continuous process that is to be
followed on regular basis. Now most of the business houses are having its own website and offers products and services through
internet portal. This means that business organizations are depending upon internet commerce heavily. In order to perform their
marketing activities through E-commerce it is very important to have data related to customers or own target customers. Data is
very important for implementing E-commerce in any organization, as it is the basic kind of information that keeps circulating
within the organization. Organizations collect data decoded information and take business decisions based on the extracted
information of the same data. It is a normal process of taking decision that involves collection of data, evaluation of data, and
analysis of the data. Based on extracted information, the decisions in the respective organization would be taken depending on
future course of action. There are many systems related to data like: data warehousing and Enterprise Resource Planning (ERP),
which are in use in most of the organizations nowadays. According to Wixom & Watson, 2001 these systems have progressed
tremendously in the last few years through making ample amounts of information accessible using data marts and data
warehouses. These systems and technology facilitate analyzing the data as per the requirements of the business concerned.
Decision-making becomes easier for the organizations through these systems and technological advancements. Right Decision
making totally depends on using the data effectively. If data have not been used effectively as right data, in right form, at right
time etc, decision will not be correct for the business organization and there might be adverse impact in the business. So right
decision is depending on effective use of data, moreover, the effective use of data is based on Business Intelligence.
Business Intelligence is a new concept in E-commerce business. In according with Olszak and Ziemba, 2006 Business intelligence
by definition is simply used to create knowledge to enable business decision making. As the name suggests, BI corresponds to
business and similar to many terminology in this area. So far, it has no standard definition like in many scientific terms. However,
most of the Business Intelligence literature has come from and within the business world, the IT industry, and vendors (Arnott, D.,
Gibson, M., and Jagielska I., 2004). As per Anderson, D., Fries, H., and Johansson, P. 2008, ―Business Intelligence is a set of
technologies and processes that use data to understand and analyze organization performance‖. Bisignani, D., and Brizee, A., 2010
explained Business Intelligence as ―the use of information to drive business insight‖. Based on the aforementioned definitions the
authors would like to add to its meaning that, the BI is an approach or a technique that provides a basis for the decision makers
through facilitating right information in a right form and in a right quality and even at a right time.
RESEARCH OBJECTIVES / HYPOTHESES
The need for the study is to highlight the significance of business intelligence in E-commerce organizations.
51
Ph.D. Scholar, Department of Commerce & Business Studies, JMI University, New Delhi, India, rabeeali2012@gmail.com
52
Professor, Department of Commerce & Business Studies, JMI University, New Delhi, India, aaansari54@gmail.com
Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
OBJECTIVES OF STUDY
To investigate the use of BI in E-commerce-based organizations.
To investigate the utilization of Business Intelligence (in terms of decision-making) to attain a more effective E-
commerce.
To achieve that, the work states the following hypotheses:
Hypothesis 1
H0: There is no impact on quality of information through using Business Intelligence tools.
H1: There is impact on the quality of information through using Business Intelligence tools.
Hypothesis 2
H0: There is no impact on decision making through using Business Intelligence tools.
H1: There is impact on decision making through using Business Intelligence tools.
REVIEW OF THE LITERATURE
The scope of this research has been consolidated through scanning the available literature. The nature of the study is to analyze the
participation of Business Intelligence in effective management of E-commerce. The authors have referred to many journals,
books, articles published by different authors on the same topic, which gave deep understanding of key terms and the utility of
Business Intelligence.
E-commerce
―Dot com‖ is a term associated with modern business organizations names. These various organizations differ from each other in
vision and mission, yet they are all share the ―dot com‖ label. However, in today‘s world we are more associated with
organizations having ―dot com‖ in their names. They are nothing but different organizations, which may or may not have physical
existence but they are available on the internet. So these organizations are intrinsically internet-based organizations which
facilitate sale and purchase of goods and services through internet only. This sale and purchase of online is called online transition
or E-commerce. In E-commerce, business transactions happen through network telecommunication upon the cyber world. It is
buying and selling of products and services through computer networks that include the internet. It is doing business electronically
(Rhodes, Carter, 1998).
Key Drivers of E-commerce
Key drivers of E-commerce can be used to measure stages of advancement of E-commerce in respective countries. These drivers
can be considered as criteria of E-commerce comparison or assessment. Amongst these are technological factors, Political factors
(like role of government in initiatives and funding to support e-commerce), Social factors (like IT education and training that
enable increasing potential buyer through E-commerce), and Economical factors (like commercial health of the country
concerned). Further, there exists some organizational culture in the E-commerce organizations world.
Business Intelligence
The term Business Intelligence is associated with software terminology. It‘s like an umbrella term that helps collecting of d ata,
analysis of data, and presentation of information related to the business. Business Intelligence contains different programs and
software that helps business extraction of data besides its information analytics. As such, the same can be exploited to become
significant for business organizations. As per Negash 2004, BI gave understanding of the capabilities of the organization that
exists within the organization. Those capabilities can be known through the trends, future directions in the markets, regulatory
environment (which is basically external business environment and the technologies as well). Arnott et al. 2004 explained the role
of business intelligence as to extract the main information or central information of the business and utilizing data to get the said
information. This is a kind of support in decision making to help managers. Koronios and Yeoh 2009 explained to business
intelligence as a set of tools and technologies that are being utilized to collect the information, integrate the information and
facilitate different kind of data‘s that are required in the organization for the decision making.
Key Components of Business Intelligence Systems
As per Olszak and Ziemba 2006, key components of business intelligence systems include: (a) data warehouses, (b) Extract-
Transform-Load (ETL) tools, (c) Online Analytical Processing (OLAP) techniques, and (d) data mining. Cella, Golfarelli and
Rizzi, 2004, suggested that business intelligence system components are used to support a set of managerial decision-making
Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
actions. Olszak and Ziemba 2007, elucidated that this involves several issues such as: Collection of Data supported by data
warehousing system, Analysis of Data supported by the use of on-line analytical products, as well as Producing of Reports
supported by data mining component of business intelligence systems.
Applications of Business Intelligence Tools in E-commerce
This comprehends but not limited to the following (Olszak & Ziemba, 2007).
Gaining better understanding of buying patterns among different segments of customers.
Creating data-driven promotions that are targeted based on customer behavior.
Tracking the sales and performance margin of different products, allowing inventory and marketing to focus on
higher value items.
Targeting marketing and relationship management to attract the most valuable customers.
Utilization of Business Intelligence Tools in Decision Making in E-Commerce Industry
Organizations dealing in E-commerce business get better understanding of buying patterns of their customers with the help of BI
tools. Such information become as a basis towards knowing their needs for better services. With the help of information provided
by BI tools, organization can take right decisions that help achieving customer satisfaction. Once the customers‘ behaviors are
known to the E-commerce-based organizations with the help of BI tools, organizations get help in their promotions targeting to
right customer segments with the help of data-driven promotion.
With the help of BI tools, organizations can take decisions related to sales i.e. whether there is need to boost the sales in the target
market or segment, or whether there is need to take decisions related to the performance of products from their margin point of
view. Margin is that part of the revenue, which comes after the deduction of variable cost from the sales revenue. So whether there
were sufficient margin of profit in the particular product or not, such case can be manage through effective decisions.
There are certain decisions that are related to the inventory management of the particular product. Inventory management is
concerned with categorization of inventory in different standard category such as ‗A‘ category, ‗B‘ category and ‗C‘ category.
Hereby, ‗A‘ category stands for high value products, ‗B‘ is moderate and ‗C‘ is less value product. As far as management of
inventory is concerned it is ‗A‘ category items that are in less quantity compared to ‗B‘ category inventory and ‗C‘ category items.
‗C‘ category items are large in quantity compared to ‗B‘ and ‗A‘ category. So these decisions and management can be done
properly by taking right decision of procurement which can be made easily by BI tools. It is business decisions that help running
business effectively and on the other hand, it is BI tools that help management taking right decision with the help of right
information provided by BI tools at right time and in right form as well.
RESEARCH METHODOLOGY
Both primary and secondary data types in this work have been utilized. Secondary data have been collected through books and
journals, whereas primary data have been collected from E-commerce-based organizations. First, list of organizations has been
created as a field, and simple random sampling technique has been applied to choose samples from this field. Thirty organizations
have been chosen for sampling, and there were 4 employees from each organization have been approached. Sample size of all
organizations was therefore 120. Tools of data collection were questionnaires only.
ANALYSIS AND DISCUSSION
The frequency chart and chi square test for testing hypothesis are exhibited below:
Table-1: The Number of Respondents
non BI users
12 respondents
10%
BI users
108 respondents
90%
Sources: Authors Compilation
Out of 120 samples, 12 i.e. 10% respondents responded as non user of modern tools of business intelligence, rather they use their
IT department for the collection of data and analysis of the same, which is a traditional approach. On the other hand there are 108
respondents i.e.90% respondents use BI tools for the management of their data and extracting vital information to bring the
difference in the business operation and growth.
Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
Hypothesis Test Findings
Hypothesis 1
H0: There is no impact on quality of information by using business intelligence tools
H1: There is impact on the quality of information by using business intelligence tools.
Table-2: Case-Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
User * Response
120
100.0%
0
.0%
120
100.0%
Sources: Authors Compilation
Table-3: User Response Cross tabulation
Count
Response
Total
Agree
Strongly Agree
User
Non User of BI Tools
6
6
12
Use BI Tools
0
108
108
Total
6
114
120
Sources: Authors Compilation
Table-4: Chi-Square Tests
Value
df
Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson Chi-Square
56.842a
1
.000
Continuity Correction
46.803
1
.000
Likelihood Ratio
31.008
1
.000
Fisher's Exact Test
.000
.000
Linear-by-Linear Association
56.368
1
.000
N of Valid Cases
120
Note: a. 1 cells (25.0%) have expected count less than 5.
The minimum expected count is .60.
b. Computed only for a 2x2 table
Sources: Authors Compilation
Since Sig<0.05 H0 is rejected which means there is an association or using tools of business intelligence for facilitation of right
data and information at right time and in right form is possible for BI users.
Hypothesis 2
H0: There is no impact on decision making by using business intelligence tools
H1: There is impact on decision making by using business intelligence tools.
Table-5: Case-Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
User * Response
120
100.0%
0
.0%
120
100.0%
Sources: Authors Compilation
Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
Table-6: User Response Cross Tabulation
Sources: Authors Compilation
Table-7: Chi-Square Tests
Value
df
Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson Chi-Square
18.305a
1
.000
Continuity Correction
9.548
1
.002
Likelihood Ratio
9.530
1
.002
Fisher's Exact Test
.009
.009
Linear-by-Linear Association
18.153
1
.000
N of Valid Cases
120
Note: a. 2 cells (50.0%) have expected count less than 5.
The minimum expected count is .20.
b. Computed only for a 2x2 table
Sources: Authors Compilation
Since Sig<0.05 H0 is rejected which means there is an association or data and information provide by business intelligence tools
is required for right decision making.
CONCLUSION AND SUGGESTIONS
Most of the respondents are using BI tools for managing their data and achieving effectiveness in decision-making. The same has
been shown in the pie chart exhibited in Figure-1 above, showing the two categories of respondents; BI users and non-BI users.
Two hypotheses have been developed and tested to know whether there is similarity in opinion or not of both groups regarding the
use of BI. It has been found that there is Impact on quality of information through using BI tools for the same. The title of this
paper, which is focused on decision-making, is directly linked with the stated relevant hypothesis. Outcome of hypotheses test
suggests that there is impact on decision making by using BI tools for the same. This implies that though there are some of the
respondents who are not using BI but still they believe that there is addition in the quality of information through applying BI.
Decision-making becomes easier and more effective through information provided by BI. So it is advisable that using BI will be
very much beneficial to even those who are not using BI in their organization.
REFERENCES
1. Olszak, C.M., Ziemba, E., (2003), ―Business intelligence as a key to management of an enterprise‖, Informing Science,
Retrieved scholarsbank.uoregon.edu.
2. Anderson, D., Fries, H., Johansson, P., (2008), ―Business intelligence: The impact on decision support and decision
making processes‖. Retrieved from http://hj.diva-portal.org
3. Arnott, D., Gibson, M., Jagielska I., (2004): ―evaluating the intangible benefits of business intelligence: review &
research agenda‖ paper presented at the IFIP TC8/WG8.3 International Conference.
4. Bell, C., Smith, T., (2007): critical evaluation of information sources, Viewed on September 07, 2015
http://libweb.uoregon.edu.
5. Bisignani, D., Brizee, A., (2010): Annotated bibliographies, Purdue online writing lab, Viewed on September 09, 2015
http://owl.english.purdue.edu.
Count
Response
Total
Agree
Strongly Agree
User
Non User of BI Tools
2
10
12
Use BI Tools
0
108
108
Total
2
118
120
Volume 4, Number 4, October – December’ 2015
ISSN (Print):2319-9016, (Online):2319-9024
PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
International Journal of Information Technology & Computer Sciences Perspectives © Pezzottaite Journals.
6. Koronios, A., and Yeoh, W., (2010), Critical success factors for business intelligence systems, Journal of Computer
Information Systems, Retrieved from http://iacis.org.
7. Negash, S., (2004), Business Intelligence. Communications of the Association for Information Systems, Retrieved from
http://site.xavier.edu
8. Olszak, C.M., and Ziemba, E., (2006), Business intelligence systems in the holistic infrastructure development
supporting decision-making in organizations, Interdisciplinary Journal of Information, Knowledge and Management, 1,
47- 58.
9. Olszak, C.M., and Ziemba, E., (2007), Approach to building and implementing business intelligence systems,
Interdisciplinary Journal of Information, Knowledge and Management, Vol. 2, Retrieved from http://www.ijikm.org
10. Wixom, B.H, (2007), the current state of business intelligence, Computer, 40(9), 96-99. Retrieved from
http://www.teradata.com
11. E. Rhodes, R. Carter, (1998), Electronic Commerce technologies and Changing Product Distribution, International
Journal of Technology Management, Vol. 15, No. (1/2) 31–48.
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