Impact of Artificial Intelligence on Value Creation in Retail Supply Chain

ENGINEERING
POST GRADUATE RESEARCH PROPOSAL 2020/2021
1. Student name:
2. Student number:
3. Date:
4. Course:
5. Supervisor:
6. Objectives of the proposed study (including provisional title)
a. Provisional Title: Impact of artificial intelligence on the value creation in the supply
chain in Retail sector industry.
b. Research Question:
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?
c. 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.
3. To explore, analyse, and evaluate the contribution of artificial intelligence to value creation in
future supply chains
d. Relation of the topic to your course:
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.
7. The Context
a. Abstract:
It analysed 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.
b. Background Literature:
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.
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).

c. 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/?
8. Research design (including methods) or critical approach:
a. Methodology:
The research methodology is an particular technique used in order to identify, choose and
evaluate the required data and information about the particular topic. For this research both
primary and secondary research is taken into consideration.
b. Data Collection Techniques:
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.
c. Participants or Host Organisation: SC
d. Data Analysis Technique(s):
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