BUS 625 Week 4 Response to Discussion 2 Guided Response: Your initial response should be a minimum of 300 words in length. Respond to at least two of your classmates by commenting on their posts. Though two replies are the basic expectation for class discussions, for deeper engagement and learning, you are encouraged to provide responses to any comments or questions others have given to you.  Below there are two of my classmate’s discussion that needs I need to response to their names are Umadevi Sayana and Britney Graves Umadevi Sayana TuesdayMar 17 at 7:50am Manage Discussion Entry Twitter mining analyzed the Twitter message in predicting, discovering, or investigating the causation. Twitter mining included text mining that designed specifically to leverage Twitter content and context tweets. With the use of text mining, twitter was able to include analysis of additional information that associates to tweets, which include hashtags, names, and other related characteristics. The mining also employs much information as several tweets, likes, retweets, and favorites trying to understand the considerations better. Twitter using text mining was successful in capturing and reflecting different events that relate to other conventional and social media. In 2013, there were over 500 million messages per day for twitter and became impossible for any human to analyze. It became important than to develop computer-based algorithms, including data mining. Twitter implements text mining in analyzing the sentiment that associates with twitter messages. It based on the analysis of the keyword that words are having a negative, positive, or neutral sentiment (Sunmoo, Noémie& Suzanne,  (Links to an external site.)n.d). Positive words, for example like great, beautiful, love, and negative words of stupid, evil, and waste, do regularly have lexicons. Using text mining, Twitter was able to capture sentiments by capturing many dictionary symbols. Moreover, the sentiment applied to abbreviations, emoticons, and repeated characters, symbols, and abbreviations. The sentiments on topics of economics, politics, and security are usually negative, and sentiments related to sports are harmful. Twitter also used text mining to collect and analyze for topic modeling techniques over time. To pull out the data from Twitter, TwitterR used. “Someone well versed in database architecture and data storage is needed to extract the relevant information in different databases and to merge them into a form that is useful for analysis” ( Sharpe, De Veaux & Velleman, 2019, p.753). It provides the interface that connects to Twitter web API; retweetedby/ids also used combined with RCurl package in finding out several tweets that retweeted. Text mining is also used in Twitter to clean the text by taking out hyperlinks, numbers, stop words, punctuations, followed by stem completion. Text mining also implemented for social network analysis. Web mining focus on data knowledge discovery .

1. BUS 625 Week 4 Response to Discussion 2
Guided Response: Your initial response should be a minimum of
300 words in length. Respond to at least two of your classmates
by commenting on their posts. Though two replies are the basic
expectation for class discussions, for deeper engagement and
learning, you are encouraged to provide responses to any
comments or questions others have given to you.
Below there are two of my classmate’s discussion that needs I
need to response to their names are Umadevi Sayana
and Britney Graves
Umadevi Sayana
TuesdayMar 17 at 7:50am
Manage Discussion Entry
Twitter mining analyzed the Twitter message in predicting,
discovering, or investigating the causation. Twitter mining
included text mining that designed specifically to leverage
Twitter content and context tweets. With the use of text mining,
twitter was able to include analysis of additional information
that associates to tweets, which include hashtags, names, and
other related characteristics. The mining also employs much
information as several tweets, likes, retweets, and favorites
trying to understand the considerations better. Twitter using
text mining was successful in capturing and reflecting different
events that relate to other conventional and social media. In
2013, there were over 500 million messages per day for twitter
and became impossible for any human to analyze. It became
important than to develop computer-based algorithms, including
data mining. Twitter implements text mining in analyzing the

2. sentiment that associates with twitter messages. It based on the
analysis of the keyword that words are having a negative,
positive, or neutral sentiment (Sunmoo,
Noémie& Suzanne, (Links to an external site.)n.d). Positive
words, for example like great, beautiful, love, and negative
words of stupid, evil, and waste, do regularly have lexicons.
Using text mining, Twitter was able to capture sentiments by
capturing many dictionary symbols. Moreover, the sentiment
applied to abbreviations, emoticons, and repeated characters,
symbols, and abbreviations.
The sentiments on topics of economics, politics, and security
are usually negative, and sentiments related to sports are
harmful. Twitter also used text mining to collect and analyze for
topic modeling techniques over time. To pull out the data from
Twitter, TwitterR used. “Someone well versed in database
architecture and data storage is needed to extract the relevant
information in different databases and to merge them into a
form that is useful for analysis” ( Sharpe, De Veaux &
Velleman, 2019, p.753). It provides the interface that connects
to Twitter web API; retweetedby/ids also used combined with
RCurl package in finding out several tweets that retweeted. Text
mining is also used in Twitter to clean the text by taking out
hyperlinks, numbers, stop words, punctuations, followed by
stem completion. Text mining also implemented for social
network analysis.
Web mining focus on data knowledge discovery of data from
blogs, online mailing lists, social media, including the structure
analysis, content, and usage. Web mining aim in extracting and
analyzing the information that is useful from the content of the
web through several techniques from data mining, natural
language processing, machine learning. In Twitter, web mining
is used in selecting keywords, importing the data, preparing,
analyzing, and interpreting the data. For example, a web content
mapping for physical activity includes searching for keywords
like body fat, body mass index, appetite, obesity, overweight,
and importing data in searching the Twitter database specifying

3. a period. The preparation of data includes cleaning the
extraneous words and analyze the data by calculating frequency
vectors that result in terms like circumference, supplements,
calculator, and height. The web mining method on Twitter is
also used in social media to study health behaviors. It is
essential to understand the behaviors that are difficult due to the
complexity. The web mining in twitter help to reveal the
situational context of before and after the physical activity
(Sunmoo, Noémie& Suzanne, (Links to an external site.)n.d).
The analysis provides the situational context purposes like build
muscle, time with words like now, today, social context, words
like gym, environmental with water trial. Tweets capture the
detailed fair information measurement as several calories
burned. Web mining content also used to track the mobility
changes of the microblogging context. It relates to the fact in
which the user is no longer bound to the computer while
generating microblogging content (Mathieu & Derek, n.d). Web
mining helps to find the effect of mobility level on features of
the user in the dataset of their followers, followees, and recent
100 recent posted tweets using Twitter User API. It allows us to
identify a total number of followees and followers in the
Twitter applications and web pages.
Twitter got benefitted with the text and web mining that help to
achieve a large number of customers that ta re satisfied and
increase customer loyalty. Mining help in overcoming risk
factors and display hidden profitability (Maningo, 2020).
Mining helps the reduction of client’s involvement with proper
extraction and analysis of client data. It helps Twitter to
identify customer groups to market the different products
according to the niche.
References:
Mathieu, P. & Derek, R. (n.d). The effect of Mobile platforms
on Twitter content generation.
file:///C:/Users/TZ97TH/Downloads/2798-14225-1-PB.pdf
Maningo, J. (2020, February 6). How to Use Twitter for Data
Mining. https://www.quickstart.com/blog/how-to-use-twitter-

4. for-data-mining/ (Links to an external site.)
Sharpe, N. D., De Veaux, R. D., & Velleman, P. F.
(2019). Business statistics (4th ed.). https://www.redshelf.com
Sunmoo, Y., Noémie, E., & Suzanne, B. (Links to an external
site.) (n.d). A Practical Approach for Content Mining of Tweets.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694275/
Britney Graves
WednesdayMar 18 at 4:48pm
Manage Discussion Entry
Before we can understand how a company benefits from text
mining, it’s essential to know what that is and how it can be
used. Text mining is using text to obtain quality information
instead of relying on trends and relationships that are solely
from numbers. This type of data can provide a diverse set of
data because every person has different experiences and insight
that they can bring to a company’s attention. Chase Bank uses
text data by analyzing call center transcripts and tracking and
responding to online reviews and being active on Twitter and
other social media. Chase Bank’s twitter account is
continuously asking for feedback, and responding to tweets left
my customers regardless of if customers are satisfied or not.
Now, Chase can gather this information, turn it into numbers,
and can see a visual representation of text. (Bennett,
2017)Explains that “The process by which text mining solves
the problems of structure and scale is where data science comes
in. The basic approach is to turn text into numbers so that we
can use machines to analyses the large volumes of documents
and discover insights through mathematical algorithms” (p. 3).
Text mining can provide equally important information by being
equated into numbers.
Web mining has a lot of benefits as well because it allows
companies to find and use information from the web to predict
behavior and improve customer relations. For example, how
often customers are clicking hyperlinks, how often they visit

5. websites, and the content of web pages. Chase Bank uses this
information every time they send out an email with a promotion
or a new product and attach a hyperlink. How many customers
are click this link? Are more people clicking the email link or
the texted link? While this doesn’t seem like important
information, knowing this data can help Chase Bank recreate its
business plan to make a shift from an email hyperlink to a text
message. Through web mining, Chase Bank may discover that
people are near a specific area code are searching for the
nearest location; therefore, they can see there is a demand for
their services.
Reference
Bennett, F. (2018, July 15). What is text mining and how can it
be used to create value for business? Retrieved March 17, 2020,
from https://www.mastodonc.com/2017/04/12/what-is-text-
mining-and-how-can-it-be-used-to-create-value-for-business/
BUS 625 Week 4 Response to Discussion 1
Guided Response: Your initial response should be a minimum of
300 words in length. Respond to at least two of your classmates
by commenting on their posts. Though two replies are the basic
expectation for class discussions, for deeper engagement and
learning you are encouraged to provide responses to any
comments or questions others have given to you.
Below there are two of my classmate’s discussion that needs I
need to response to their names are Lisa Schreiner and Robert
Mcalexander
Lisa Schreiner
SaturdayMar 14 at 9:18am
Manage Discussion Entry
1. Volume: It refers to the incredible amount of data that is

6. generated each second from multiple sources such as cell
phones, social media, online transactions, etc.
2. Velocity: It refers to the speed at which the data is generated,
collected, and analyzed.
3. Variety: If refers to the different types of data such as
structured, semi-structured and unstructured data. Structured
data has a fixed format and size, semi-structured data has a
structure but cannot be stored in a database, unstructured data
does not have any format and or hard to analyze.
4. Veracity: It is the trustworthiness of data in terms of quality
and accuracy. Extracting loads of data is not useful if the data is
messy and poor in quality.
Netflix collects big data for competitive advantage by tracking
the types of shows or movies people watch. According to Dans
(2020), “the company began to verify when it used to send
DVDs by mail, then it began to replace this with streaming. An
approach that provides superior data and instantaneous
feedback, as well as setting it apart from the competition” (para.
3). The velocity or speed at which the data collects through the
internet is in real time with a click of the mouse or remote
control button. The variety of data collects in a structured
manner by genre, frequency, and time of day. The structured
data allows quick algorithms to run in the background and
suggest specific viewing options on the account in an instant.
The veracity or quality and accuracy of the data collection
provides a level of detail with no external or human influence to
interpretation leading to clean data in the warehouse. “Netflix’s
success proves this: if we consistently resort to data analysis, a
greater percentage of our decisions will be better made, the
risks we take will be more balanced, and the results will be
better” (Dans, 2020, para. 5). Netflix has provided me with
many successful viewing suggestions during personal use
proving the data mining and analysis techniques work.
The values of data mining in a business is to provide
correlations, patterns or trends in the market products or

7. services. The data use can increase the marketing strategy by
defining the target market for cost effectiveness and
maximizing profits. Fraud detection is a valuable purpose for
many businesses such as banks, credit card companies,
insurance, retail, and more. Minimizing losses due to fraud
increases value in a product or service providing protection.
Data analysis adds value to decision-making in organizations
and personal practices through process improvement,
identifying successful offerings for further expansion, or
unsuccessful offerings to cut the losses.
Challenges in managing a data mining project include
unstructured data, unclean data, data protection and security,
ensuring questions to answer are specific, and willing to work
with others – this is a team effort. Unstructured and dirty data
leads to unreliability. The errors can manifest from
measurements, quantification, or simple human keying
mistakes. Protection and security of data is the forefront of
every person and business due to the ease and speed of
obtaining information through technology. Acquiring
permission to pull data for analysis is challenging in this
environment. Questions must be specific for the process
otherwise the database is too large providing unreliable and
possible duplication in output. Data mining is a team effort.
One must be willing to work and share knowledge and findings
across levels to provide reliable conclusions.
References
Dans, E. (2020, January, 15). Netflix: Big Data And Playing A
Long Game Is Proving A Winning Strategy.
https://www.forbes.com/sites/enriquedans/2020/01/15/netflix-
big-data-and-playing-a-long-game-is-proving-a-
winningstrategy/#2ec78c7a766e (Links to an external site.)
Sharpe, N. D., De Veaux, R. D., & Velleman, P. F.
(2019). Business statistics (4th ed.). https://www.redshelf.com

8. Robert Mcalexander
SundayMar 15 at 8:05am
Manage Discussion Entry
Good morning everyone!
Provide an example of a company that is collecting big data for
competitive advantage. Explain how each of the three Vs,
outside the volume, is helping the company achieve competitive
advantage.
Big Data: The collection and analysis of data sets so large and
complex that traditional methods typically brought to bear on
the problem would be overwhelmed.
A standard example of a company that uses big data would be
our friends over at Amazon. All the data that comes in on a
daily basis surely helps them to sustain their competitive
advantage here in the United States, and it also helps them to
seek one on a global level. When looking at the four “V’s” of
big data, the first one seems rather obvious. With the number
of users on a daily basis, there has to be overwhelming
quantities of data continuously streaming in. Amazon will also
receive quite a variety of data even when just looking at one
user. Think of all the different types of services Amazon
offers. They can track down what you are listening to, what
you are watching, what you are eating, what you like to wear,
your favorite games or hobbies, and much more simply from
your search/buy history. This variety can help them to better
tailor their user interface to each individual by making
suggestions based on data they have collected. The next aspect
of big data to look at would be the velocity of the data. Again
even just breaking this down on a single user basis, there is so
much data coming in all at once just through a few clicks. So
when you take that and multiply I by the hundreds of millions
of users that frequent these services on the daily, that is a lot of
data at a high rate. The final aspect of big data would be the
veracity, or the quality of the data. This is where I feel Amazon
would have trouble sorting through the quantity of data they

9. receive. But with all of their services they surely have the
opportunity to gather extremely high quality data.
Explain the values of data mining in a business and at least
three challenges in managing a data mining project.
One of the best values that comes from data mining is the
ability to make an accurate forecasts on demand. By tracking
trends in data, Amazon can be much better prepared and provide
the end user with the highest quality services. But by doing
this, there will inevitably be massive challenges associated with
it. Three significant challenges would be the infrastructure,
responsiveness, and finally using the data gathered.
Infrastructure would be a major piece of this equation. You
would need to have a sufficient hardware, software, and
manpower in order to accurately gather and use all the data.
The next challenge would be the time taken to respond. This
will by no means be a quick turnaround. “This can be a time-
consuming part of the process and is also likely to be a team
effort. Investigating missing values, correcting wrong and
inconsistent entries, reconciling data definitions, and merging
data sources are all challenging issues.” (Sharpe 753) The final
challenge that Amazon would face would be on actually using
the valuable data. Being able to make decisions based on the
data found will again take time and by then the information
could be deemed irrelevant.
Govindarajan. V.G. (2018 February 2) Can anyone stop amazon
from winning the industrial internet? The Challenges for
industrial giants. Retrieved from: https://hbr.org/2018/02/can-
anyone-stop-amazon-from-winning-the-industrial-
internet (Links to an external site.)
Sharpe, N. D., De Veaux, R. D., & Velleman, P. F.
(2019). Business statistics (4th ed.). Retrieved
from: https://platform.virdocs.com/r/s/0/doc/509177/sp/680467
83/mi/291160736?cfi=%2F4%2F2%5BP70010159890000000000
0000000C2CE%5D%2F28%5BP70010159890000000000000000

10. 0C3F3%5D%2F6%5BP700101598900000000000000000C3F6%5
D%2F8%5BP700101598900000000000000000C3FD%5D%2F2
%5BP700101598900000000000000000C3FE%5D (Links to an
external site.)
BUS 624 Week 4 Response Discussion 1
Guided Response: Respond to at least two of your peers’ posts
(as well as any comments made by your instructor) in a
substantive manner and provide information or concepts that
they may not have considered. Each response should have a
minimum of 100 words. Support your position by using
information from the week’s readings. You are encouraged to
post your required replies earlier in the week to promote more
meaningful and interactive discourse in this discussion forum.
Below there are two of my classmate’s discussion that needs I
need to response to their names are Mark Zuniga and Lisa James
Mark Zuniga
MondayMar 16 at 10:41pm
Manage Discussion Entry
Did Mr. Higgins infringe on Ms. Garner’s Patent? Is Ms.
Garner’s patent valid?
I would rule in favor of Mr. Higgins not infringing on Ms.
Garner’s patent as the patent is not valid. The patent is not valid
as the process of keeping tabs of customers and the shopping
behaviors is not a new process or idea. Mr. Higgins explains
that his company has used this method for customers of shoes
and upon expanding to an online presence, the same methods
are the same. Ms. Garner is trying to state that there is a
different between applying these methods in a building and
online but the result is the same for the customer. As these
characteristics are demonstrated prior by the company Mr.
Higgins works for, there is no infringement.
Does Ms. Garner’s patent meet the requirements of being novel,
non-obvious, and having utility? Explain why or why not.

11. Ms. Garner’s patent does not meet novel and non-obvious
requirements. As a novelty is the invention being new and truly
different from previous actions in the field, keeping tabs on
customer behaviors and trends is not new in the retail industry
(Langvardt et al., 2019). Non-obvious requires the invention to
not be obvious to people in the same field of reasonable skills,
marketing and analytics are specific job titles to help keep tabs
on customers (Langvardt et al., 2019). The idea of providing
products based on customer preferences is not a new idea for
business and does not allow this idea alone to be patented. The
patent does meet utility as this is useful in a business setting
(Langvardt et al., 2019).
Resources
Langvardt, A. W., Barnes, A. J., Prenkert, J. D., McCrory, M.
A., & Perry, J. E. (2019). Business law: The ethical, global, and
e-commerce environment (17th ed.). Retrieved
from https://www.vitalsource.com (Links to an external site.)
McGraw Hill. (n.d.). YBTJ_intellectual_click_arg (Links to an
external site.) (Links to an external site.) [Video clip].
In Intellectual property: Click here, get sued [Video file].
Retrieved
from http://www.viddler.com/embed/37be50a1/?f=1&autoplay=
0&player=full&disablebranding=0 (Links to an external site.)
McGraw Hill. (n.d.). YBTJ_intellectual_click_prof_def (Links
to an external site.) (Links to an external site.) [Video clip].
In Intellectual property: Click here, get sued [Video file].
Retrieved
from http://www.viddler.com/embed/8fc0ee71/?f=1&autoplay=0
&player=full&disablebranding=0 (Links to an external site.)
McGraw Hill.
(n.d.). YBTJ_intellectual_click_prof_plaint (Links to an
external site.) (Links to an external site.) [Video clip].
In Intellectual property: Click here, get sued [Video file].
Retrieved
from http://www.viddler.com/embed/eef250e4/?f=1&autoplay=0
&player=full&disablebranding=0 (Links to an external site.)

12. McGraw Hill. (n.d.). YBTJ_intellectual_click_react_def (Links
to an external site.) (Links to an external site.) [Video clip].
In Intellectual property: Click here, get sued [Video file].
Retrieved
from http://www.viddler.com/embed/c0e674c8/?f=1&autoplay=
0&player=full&disablebranding=0 (Links to an external site.)
McGraw Hill.
(n.d.). YBTJ_intellectual_click_react_plain (Links to an
external site.) (Links to an external site.) [Video clip].
In Intellectual property: Click here, get sued [Video file].
Retrieved from
http://www.viddler.com/embed/36326200/?f=1&autoplay=0&p
Lisa James
TuesdayMar 17 at 3:42pm
Manage Discussion Entry
Did Mr. Higgins infringe on Ms. Garner’s Patent?
Mr. Higgins did not infringe on Ms. Garner’s patent based on
the fact that her idea was not new and was utilized in stores and
online prior to her gaining patent on it. Even though the law
does allow for the “first to file rule” the patent still must be
unique (Langvardt, Barnes, Prenkert, McCrory, & Perry, 2019).
Mr. Higgins argument that the profiling of customer
preferences is the basis of customer service is valid and there is
no difference between utilizing the practice in store as there is
online.
Is Ms. Garner’s patent valid?
No, the patent is not valid because it would not because it does
not meet the basic requirements of being novel, non-obvious,
and having utility
Does Ms. Garner’s patent meet the requirements of being novel,
non-obvious, and having utility? Explain why or why not.
Her patent does not meet any of these requirements. For a
patent to be novel, it must be a new and completely different
from anything else in the relevant filed. Langvardt, Barnes,

13. Prenkert, McCrory, & Perry (2019) state that, “The America
Invents Act provides that a patent cannot be granted if any of
these events occurred before the patent applicant filed his, her,
or its patent application: the invention was already patented; the
invention was already in public use, on sale, or otherwise
available to the public; or the invention had already been
described in a printed publication” (pg 289). Because stores
were already utilizing this method in their brick and mortar
locations, it would not be considered novel. The patent is also
not non-obvious as to qualify for this distinction the idea must
not be obvious to those in the same field. Mr. Higgins’ store
and other locations have been using a variation of this for year.
I would agree that the patent has utility, as it is helpful and
useful for various locations.
Resources
Langvardt, A. W., Barnes, A. J., Prenkert, J. D., McCrory, M.
A., & Perry, J. E. (2019). Business law: The ethical, global, and
e-commerce environment (17th ed.). Retrieved from
https://www.vitalsource.com
BUS 624 Week 4 Response Discussion 2
Guided Response: Respond to at least two of your peers’ posts
(as well as any comments made by your instructor) in a
substantive manner and provide information or concepts that
they may not have considered. Each response should have a
minimum of 150 words. Support your position by using
information from the week’s readings. You are encouraged to
post your required replies earlier in the week to promote more
meaningful and interactive discourse in this discussion forum
Below there are two of my classmate’s discussion that needs I
need to response to their names are David Geusen and Kyle
Jablonski

14. David Geusen
WednesdayMar 18 at 7:29pm
Manage Discussion Entry
Over the course of the MBA program I have selected the
Philippines for my Walmart Case Study. Walmart's introduction
into the Philippines will have many hurdles that require detailed
planning and research. In my prior classes, I have discussed the
cultural issues including demographical and employee
management differences. After now reviewing the surface of
legal aspects in business, I know now that there are many legal
issues that arise as well.
Some legal issues that Walmart in the Philippines may
encounter is rights to intellectual property. An example would
be Walmart's trademark logo. When an American trademark
owner goes global, the owner runs the risk of other businesses
using their trademark freely and without consent (Langvardt,
Barnes, Prenkert, McCrory, and Perry, 2019). To avoid this,
Walmart would need to register their trademark in the nation of
the Philippines to be protected.
Another foreseeable issue is contracts. Contracts are used
everyday in business and when Walmart enters the Filipino
market, they will need to understand the laws the govern them.
An issue could arise if Walmart has employment contracts used
for the United States and they adopt the same techniques in the
Philippines. Employment labor contracts in the Philippines must
have clearly stated terms and clauses as well as be a dual
language contract (Dezan Shira & Associates, 2018). By
interpreting Book IV of the Civil Code of the Philippines,
Walmart will be better prepared when entering the country.
References:
Dezan Shira & Associates (2019). Philippine Labor Contracts:
What You Need to Know.
Langvardt, A. W., Barnes, A. J., Prenkert, J. D., McCrory, M.
A., & Perry, J. E. (2019). Business law: The ethical, global, and
e-commerce environment (17th ed.). Retrieved from

15. https://www.vitalsource.com
Kyle Jablonski
The country that I chose for my Walmart case study was South
Korea. The cultural difference between South Korea and
Walmart is primarily due to the perception of what Walmart is
and the shopping behaviors of the general public. According to
Renee Kim (2008), “Korean consumers viewed Wal-Mart as a
store to visit when they needed to purchase large nonfood
products and to see a variety of products, including foreign
products. They prefer to visit local domestic supermarkets for
food purchases and daily use items. Korean consumers also
like to shop daily, instead of weekly or biweekly, and purchase
small packages, given their small houses with limited storage
and freezing spaces” (P. 5). Walmart did not change how and
adjust to South Korean culture. In order to adjust to the Korean
market place, Walmart needs to restructure how their products
are sold. Instead of focusing on large bulk and low cost.
Purchasers should focus on quality instead of quantity and
offering smaller quantities instead of big bulky items. This
would allow consumers to shop for what they are accustomed
to.
The legal issues that Walmart may face in South Korea are
importation legal issues. Even though there is the “US-Korea
Trade Agreement,” Walmart imports products to distribute in
their stores. If importers and exporters are not aware of the laws
and regulations on how South Korea stances on each country
Walmart does business there could be an issue. A way of
combating this is to work with local merchants as much as
possible. Also designating an entire department on knowing the
import laws of where all of the Walmarts of the world would
help alleviate this issue tremendously.

16. References:
Cascio, W. F., & Aguinis, H. (2019). Applied psychology in
talent management (8th ed.). Retrieved
from https://www.vitalsource.com (Links to an external site.)
Kim, R. (2008) Wal-Mart Korea: Challenges of Entering a
Foreign
Market, Journal of Asia-Pacific Business. Retrieved
from https://www.tandfonline.com/doi/pdf/10.1080/1059923080
2453604 (Links to an external site.)