Analyzing AI's Influence on Value Creation in the Retail Supply Chain

This report examines the impact of artificial intelligence (AI) on value creation within the retail supply chain, aiming to identify new strategies for sustainable competitive advantages. The research includes an introduction to AI's influence on operational data and its application across various processes. The study utilizes both qualitative and quantitative data collection methods, including a literature review and analysis of technologies. The report addresses research objectives such as reviewing technologies for supply chain performance, developing a conceptual framework, and evaluating AI's contribution to value creation. The methodology involves grounded theory, with data collected from primary and secondary sources. Ethical considerations, including consent, anonymity, confidentiality, and data protection, are also discussed. The report concludes by emphasizing the crucial role of AI in organizational development and the need for adapting to technological advancements in supply chain management, providing insights into how AI is transforming the retail sector.

Proposal
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Table of Contents
Introduction......................................................................................................................................3
Conclusion.......................................................................................................................................9
REFERENCES..............................................................................................................................10
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Research title: Impact of artificial intelligence on the value creation in the
supply chain in Retail sector industry.
Introduction
The next wave of technological development is already making sense for operational data that is
streaming across plethora of device and various clod applications technology is advancing and is
applied across various processes, predicts and systems so that here can be early learning and
adaptation (Johnson and et. al., 2018). These developments have to be predicted by
organisations. Presently there is analysis of the role played by such artificial intelligence and
supply chain process of organisations that are part of retail sector. For this purpose there is need
to make detailed evaluation of the impact of artificial intelligence on the process of value
creation across the supply chain process in retail sector.
There is also evaluation of the impact of artificial intelligent on the value creation of supply
chain process in organisations (Hosny and et. al., 2018). With changing times and the changing
nature of external environment it has become very important to analyse such dynamic nature of
external environment that can lead to transformations in overall functioning. For this purpose
presently there will be use of qualitative and quantitative data method in order to collect the
relevant information across various platforms for the purpose of reaching to conclusions and
drawing suitable recommendations for retail sector organisations.
Overall Research Aim: “To analyse and evaluate the impact of AI on VC in the SC to find
new rules or even a theory to predict future mechanisms for sustainable competitive
advantages” A case study on retail industry.
Research Objectives:
1. To review the technologies for improving SC performance, especially value creation in
SC and concepts leading to sustainable competitive advantages.
2. To develop a conceptual framework with the purpose to explore scenarios towards future
SC performance mechanisms.
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3. To explore, analyse, and evaluate the contribution of artificial intelligence to value
creation in future supply chains.
Research questions:
1. What are various different types of technologies for improving SC performance,
especially value creation in SC and concepts leading to sustainable competitive
advantages?
2. What can be different conceptual frameworks to explore scenarios towards future SC
performance mechanisms?
3. What is the impact of AI application on the value creation of a supply chain?
Data Collection Methods
For the purpose of present research work there will be use of both primary and secondary form
of collecting data based on which further analysis is to be done to reach relevant conclusions. In
secondary form of information there is literature review which is developed in order to make
analysis of the information.
The technologies for improving Supply chain performance and value creation leading to
sustainable competitive advantages
As per view points of Bneton (2018), Artificial intelligence is affecting the overall functioning of
organisations. There are different sources of artificial intelligence that is affecting the preset
functions of supply chain & logistics in retail sector organisations. There are many organizations
that are making investments in artificial intelligent (Pandian, 2019). As per reports the state of
artificial intelligent is very important for various enterprises. Supply chain is one of top areas that
can be used by business organisations in the retail sector for the purpose of driving the overall
revenues for the investment in artificial technologies.
In retails sector organisations like Morrison’s, TECSO, Marks and Spencer there is use of
artificial intelligence for the purpose having rapid development that can enable organisations to
incorporate the process of artificial intelligence in the operations. Such as there is use of
graphical processing units that is part of expansion of CPU functionalities.
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Big data is also a part of supply chin and logistics that can be used for having significant volume
of power in processing overall activities of supply chain functions. In parts some of the years
data has emerged as a increasing pace of data creation and artificial intelligence in case of
macheb learning algorithms.
Artificial intelligent has lead to contextual intelligence that is providing the required level of
knowledge that is needed for the purpose of dealing with overall operations costs and also is
helping in the process of responding to customer more quickly. There is use of machine learning
technology so that there can be warehouse management, supply chain management and
collaborative techniques (Tuffnell and et. al 2019). It helps in two major aspects that include
intelligence robotic sorting. In retail industry this will help in high speed of sorting of parcels,
letters and palletized shipments. Another aspect is artificial intelligent that can help in proper
visual inspection so that there can be timely identification of damage so that timely corrective
actions can be taken (6 WAYS AI IS IMPACTING THE SUPPLY CHAIN, 2019).
Research data analysis methods
In research it is important to collect data and information so that objectives and aims are
being achieved. In this presented research topic, it is critically important to focus on which
methods are to be used to collect information. So, different types of data analysis methods are
being considered which are discussed below-
There are various types of statistical data analysis methods which are used within
research like descriptive research, grounded theory t test for differences and many more. As this
research focuses on impact of artificial intelligence on supply chain and value chain Grounded
theory has been used on the basis of information has been collected. Grounded theory is to be
defined as a theory which focuses and involves the gathering and Analysis of data. Main purpose
of this theory is to represent the integration of quantitative as well as qualitative perspective in
processes.
 Quantitative- It is a type of method which is used to collect information in the form of numerical
and statistical data. Also through obtaining of this quantitative information, both researcher and
investigator are equal to collect relevant and appropriate information about a topic.
 Qualitative- This is another approach of collecting credentials of a particular topic in which
theoretical information is being considered and collected by use of sources like newspaper
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articles, blogs and many more. Main benefit of using this method is that it helps them gathering
of credentials properly and within a timely manner. It is easy to use and also understandable by
others.
 Mixed- This is also to be viewed as an effective approach of collecting information and data. It
states about the using of both qualitative and quantitative approaches in order to gather the
credentials as well as data. So in this present research mixed approaches are being used through
which information has been applied to the specific topic.
 Primary data: It is a method in which there is first hand collection of information from
the neither sources that neither do not exist (Dubey and et. al 2021). There is collection of
raw form of information by the investigator from the target segment of respondents. It is
one of these suitable methods that can be applied in different courses of research work.
This method is highly reliable and authentic for the purpose of having authentic sources
of information.
 Secondary data collection: It is a method in which there is use of existing literature
sources for the purpose of data collection. This method will be used by researcher in
present course of research so that there can be relevant conclusion which are to be drawn
based on exiting literature sources, journal articles, books etc. all these will be required in
order to develop necessary conclusion and recommendations for the researcher.

From the above specified approaches, it is seen that mixed method is to be considered as the
best of collecting information. With the help of this method is able to obtain the information
related to artificial intelligence supply chain and value chain. Moreover it has also become
necessary to adopt the approach in most appropriate manner.
Ethical issues-
 Consent- It is a type of ethical issue in which it focuses on informing the participants about the
use of the information by applying implied and written form. In this presented research, this issue
is relevant to this research as because the field of area is about technology and where consent has
to be properly maintained in order to reduce the risk
 Anonymity- Anonymity is to be defined as a not disclosing the Identity of a person or individual
so that subject is not known to the researcher. This ethical issue is not relevant to presented
research as because it is necessary for associate to be aware about the identity of a participant so
that information is gathered properly and documentations are properly maintained.
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 Confidentiality- It is another ethical issue in which it focuses on keeping the privacy of a subject
in between the research researcher and participants. This issue is also relevant to the research as
because it is difficult to obtain information about supply chain of organisation and the field of
artificial intelligence for which confidentiality is important.
 Commercial sensitivity- It is another type of ethical issue in which insurance about
commercially sensitive credentials is being used in secured and protected way so that problem
will not occur in future interval. For example whenever a new work is published in the market no
other person and use it without the authorisation.This is also an issue which is relevant to the
research has because commercial sensitivity contact has been obtained in this research and proper
focus is required.
 Computer Misuse act- According to this act it is States about the restriction of assessing to
personal data information in an unauthorised way. This act is important which is being focused
by the researcher as because wide ranges of products are being stored in smart devices. The risk
can be reduced by using of different tools and software like antivirus, malware etc.It is important
to focus on this act so that difference undertaken in correct way.
 Data protection act- This is also the ethical issue which is to be properly so called as because it
aims towards the how personal credentials and data is being used by other people or enterprises
or government. This issue is related to the research because data is being used by research and it
is necessary to protect it from getting misused.This ethical issue can be solved by taking the
information and visiting to the researcher to making sure that information is used in appropriate
way.
 Deception- In this kind of ethical issue it is defined as providing incomplete or wrong
information to participants with motive of gaining more information on reading the research
subject of topic. This issue is applicable to some extent but I'm using it and continuous level can
lead to many problems. This is also connected with the research and deception has been avoided
by the researcher.
 Vulnerable participants- Vulnerable participants are those which includes teenager’s,students
children's etc. This ethical issue is not relevant to research because there are no such vulnerable
participants any function is being used through the professionals as well as external sources.
The above explained ethical issues are important to be considered by the researcher so
that it is easier to conduct the research of selected topic batter way and also it helps in
reducing the problem in future context. It is duty of a researcher to be well aware about how
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to deal with these issues on the basis of which objectives and aims are achieved within time
interval.
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Conclusion
From the above mentioned aspects it can be concluded that artificial intelligence is playing a
very crucial part in the overall development of organisations functioning. The changing external
environment has created a need to develop various measures to provide proper insights in the
process of supply chain management. These techniques have affected the process of
organisations to deal with the updated technologies of artificial intelligence and virtual learning
especially in this growing age of technological development. This research work is going to
facilitate in understand these concepts in detail in order to reach to relevant conclusions.
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REFERENCES
Books & Journal
Al-Turjman, F. ed., 2019. Artificial intelligence in IoT. Springer.
Dubey and et. al 2021. An investigation of information alignment and collaboration as
complements to supply chain agility in humanitarian supply chain. International Journal
of Production Research, 59(5), pp.1586-1605.
Hosny and et. al., 2018. Artificial intelligence in radiology. Nature Reviews Cancer, 18(8),
pp.500-510.
Johnson and et. al., 2018. Artificial intelligence in cardiology. Journal of the American College
of Cardiology, 71(23), pp.2668-2679.
Pandian, A.P., 2019. Artificial intelligence application in smart warehousing environment for
automated logistics. Journal of Artificial Intelligence, 1(02), pp.63-72.
Tuffnell and et. al 2019. Industry 4.0-based manufacturing systems: Smart production,
sustainable supply chain networks, and real-time process monitoring. Journal of Self-
Governance and Management Economics, 7(2), pp.7-12.
Online:
6 WAYS AI IS IMPACTING THE SUPPLY CHAIN, 2019 [online], available
throughhttps://supplychainbeyond.com/6-ways-ai-is-impacting-the-supply-chain/?
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