Optimizing green supply chain with artificial intelligence promoting sustainable development and increasing the green purchasing trend of

ĐẠI HỌC KINH TẾ THÀNH PHỐ HÒ CHÍ MINHBÁO CÁO TÔNG KÉT ĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024 OPTIMIZING GREEN SUPPLY CHAIN WITH ARTIFICIAL

ĐẠI HỌC KINH TẾ THÀNH PHỐ HÒ CHÍ MINH

BÁO CÁO TÔNG KÉT

ĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG

“NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024

OPTIMIZING GREEN SUPPLY CHAIN WITH ARTIFICIAL

PURCHASING TREND OF YOUNG PEOPLE IN HO CHI

MINH CITY

TP Hồ Chí Minh, tháng 2/2024

In the context of the current digital era, Artificial Intelligence (AI) has become a

key factor in promoting sustainable development and environmental progress, with a

global and unique impact, especially in Ho Chi Minh City (Vietnam) However, the

specific research model to explore the potential impact of Artificial Intelligence on

evidence on the relationship between them

Intelligence: Promoting Sustainable Development and increasing the Green Purchasing Trend of Young People in Ho Chi Minh City” to identify a researchmodel Specific research to explore the potential impact of Artificial Intelligence on

evaluate green purchasing intention of young consumers in Ho Chi Minh City

significant influence on green purchasing intention of young people in Ho Chi Minh

optimize the effectiveness of Green Supply Chain Management in the context of

strongly developing AI technology

Keywords: Artificial Intelligence, Green Supply Chain Management, Sustainable Development, Green Brand Image, Environmental Knowledge, Green Product, Environmental Concern

2.1.8 Green Purchasing Intention 9

2.2.1 Organizational information processing theory (OIPT) 9

2.3 Research hypotheses and proposed model 11

3.3.4 Questionnaire design and data collection methods 24

4.2 EFA exploratory factor analysis and Cronbach ’ s Alpha reliability

4.5 Testing results and post-quantitative research model 44

5.3 Directions for continued research and expansion 49

-8-LIST OF PICTURES

Picture 4.4-4 Summary of regression model (GSCM - GBI) 41-42

Picture 4.4-6 Regression coefficients (GSCM - GBI) 42

Picture 4.4-8 ANOVA regression analysis (GP, GBI, CA, EK, EC - GPI) 43

LIST OF TABLES

Table 4.2-1 Summary table of results of EFA analysis and first

34-37

Cronbach’s Alpha test

38-39

Table 4.5 Results of testing the model’s hypotheses 45

GPI Green Purchasing Intention

GSCM Green Supply Chain Management

KMO Kaiser - Meyer - Olkin

OIPT Organizational information-processing theory

TPB Theory of Planned Behaviour

CHAPTER 1: OVERVIEW OF THE RESEARCH TOPIC 1.1 Overview of research topic

1.1.1 The need of the research

strategy, but also an opportunity to emphasize sustainable development in production,

Management not only helps reduce negative impacts on the environment but alsocontributes to building a sustainable development ecosystem At the same time, this

creates many business opportunities, meeting the growing market demand for green

products and services (J Sarkis el al., 2010)

business optimization but also brings many benefits and positive impacts on the

environment

Changes in Green Supply Chain Management not only have a profound impact

on the consumption behavior of young people in Ho Chi Minh City but also put

from product origin to production and transportation, facing young people, it becomes

impact on the environment and society (T Y Choi et al 2019)

Understanding the correlation between Artificial Intelligence and Green SupplyChain Management and how it affects youth consumption behavior becomes important

combined with AI not only optimizes business operations but also creates innovation in

development of appropriate policies and educational programs to encourage green

consumption behavior in the community, especially among young people, contributing

to building a sustainable future for Ho Chi Minh City and the whole country

1.1.2 Research issue

difficult due to the lack of models and evidence on the relationship between AI factors

affecting Green Supply Chain Management, as well as other factors such as:

Product

To optimize the effectiveness of Green Supply Chain Management, it is

green products This requires a comprehensive research model that continuously collects data from AI information sources to analyze, predict and evaluate the potential impact

1.2 Research content

L2.L Research questions

potential?

Management impact consumers' Green Purchasing Intention?

1.2.2 Research objectives

Intelligence, Green Supply Chain Management, Environmental Knowledge,

Suggestions and recommendations for administrators and businesses in Vietnam

concerns for the environment and intention to use green products in the digital era.especially AI technology.

1.2.3 Objectives and scope of the research

1.2.3 1 Objectives of the research

Young people aged 18-30 years old are living, studying and working in Ho ChiMinh City This is a group of people who have a positive awareness of environmental

protection, easily adapt to digital technology and can make their own purchasingdecisions

change and the impact of human activities on the environment They tend to look forproducts and services that aim to protect the environment and reduce negative impacts

environmentally friendly packaging of Vietnamese youth in Hanoi" by Pham Thu

Young people often adopt new technology quickly, and the majority of green

products are often related to advanced technologies For example, electric vehicles,energy-saving appliances, and consumer assistance applications make shopping for

green products more attractive to them Based on the research paper "Shopping and

consumption." by Calafell, G., Banqué, N., & Viciana, s (2019)

the environment and resource protection more important and accessible to young people.According to Wang, s T (2014) mentioned in the research article "Consumer

characteristics and social influencing factors on green purchase intention", this has

consumers are willing to pay a higher price for products from brands that have a positive

impact on society and environmental protection Businesses' commitment to

Vietnamese consumers.

Financial capacity: Although not all young people are financially well off, a

proportion often have the financial capacity to purchase greener products This may

involve working in technology, finance, or other fields with a stable income

1.2.3.2 Scope of the research

Space: Survey of young people in Ho Chi Minh City, Vietnam

proposed solutions in the future

1.2.4 Research Methodology

1.2.4.1 Data collection

selected subjects to determine the urgency of the topic

Secondary data: Document sources are collected from publications of articles,

works,

1.2.4.2 Research Methods

Qualitative research: The team conducted focus group interviews with young

the interview, the team supplemented, adjusted and completed the research model, and

built a questionnaire for the research topic

research to test the scale and suitability of the research model Questionnaire is a tool to

collect data The questionnaire includes 36 questions Each question is measured on a

5-level Likert scale The sampling method in this research is a convenience samplingmethod

1.2.5 Research content

The content of the research article on the topic "Optimizing Green Supply Chain with Artificial Intelligence: Promoting Sustainable Development and increasing the Green Purchasing Trend of Young People in Ho Chi Minh City" is

published through the following sections:

Summary of topic

Chapter 1: Overview of research topic: Urgency of the topic; issues needing

practical significance

proposed research models

Chapter 3: Research design: Research process design; how to design and analyze

qualitative research results; Design research samples, quantitative questionnaires and

Chapter 4: Research results: Descriptive statistics; test the reliability of the scale;

EFA exploratory factor analysis; Pearson correlation; testing research models and

research results; Propose management implications for businesses; present limitations

L2.6 Significance in science and practice

In terms of theory and practice, the above research has made meaningfulcontributions to science and practice:

I.2.6 J Significance in science

model and tested the interaction between variables In addition, the research updates

evaluating the ability to integrate and apply Artificial Intelligence in management,

monitoring and optimization processes In addition, the research results build a scientific

1 2.6 2 Significance in practice

regulations From there, promote sustainable development to ensure environmental

for sustainable development, providing information for organizations to build a green

economy Thanks to that, businesses create a green brand image by understanding the

to customers

CHAPTER 2: LITERATURE REVIEW 2.1 Some basic concepts

2.1.1 Artificial intelligence

(2002), it can be understood that Artificial Intelligence is defined as the use ofcomputers

to reason, recognize patterns, and learn or understand certain behaviors from experience,

acquire and retain knowledge, and develop different forms of reasoning to solve

problems in decision-making situations in which optimal solutions or accuracy is too

expensive or difficult to produce The real purpose of Artificial Intelligence is to imitatethe human brain and perform human-like decision making in different situations (De

Sousa Jabbour et al., 2018; Deshpande et al., 2018) Therefore, AI must be able to learn

and understand new concepts, learn from its own experiences, perform inferences, draw

modeling, robotics, machine learning, data mining, neural networks, mobile algorithms,

2002)

In most of the current research, Artificial Intelligence has been widely accepted

as a decision support tool, but there is still a limited amount of research on the

application of Artificial Intelligence in Management, supply chain (GSCM) When

exploring this topic, the research article by Surajit Bag and Dhamija (2019) mentioned

that the application of Artificial Intelligence in logistics and supply chain management

is to help administrators solve problems related to supply chain network design,

chain adaptability and alignment

2.1.2 Green Supply Chain Management (GSCM)

practice have been highlighted in previous literature In 2005, Zhu et al proposed a four­

procurement, green manufacturing, green distribution and green logistics are important

aspects of GSCM practices that manufacturing industries need to achieve sustainable performance.

2.1.3 Green Brand Image

According to Keller (1993), consumers often perceive a brand based on their

that are associated with environmental concerns and commitments Martinez studies,

2015; Mourad & Ahmed, 2012; Yadav et al., 2016 often consider green brand image as

an association network theory that contributes to explaining the outcome variable(s)

(such as green brand preference, trust, loyalty, and image), company) Sometimes, a

used functional or emotional benefits as antecedent variables in their research before

al., 2017)

2.1.4 Environmental Concern

According to Alibeli and Johnson, environmental concern is the degree to which

At the same time, Diamantopoulos et al (2018) observe that environmental concern is

purchasing intention Consumers have a higher level of concern for the environment

2.1.5 Customer Attitude

According to Fazio, attitude is the interaction in memory between a specific

object and an overall evaluation of that object Attitudes have the ability to reveal a

focused on the relationship between attitudes and behavioral intentions Irlandconcluded that consumers’ purchase intentions depend on their environmental attitudes

purchase intention of consumers who will pay for green products

2.1.6 Environmental Knowledge

person’s ability to understand and evaluate issues surrounding consumption behavior

that may positively or negatively affect the environment (Haron el al., 2005) Previous

literature shows that general environmental knowledge positively influences consumers'

beliefs and attitudes toward environmentally friendly products (Choi and Johnson, 2019;

attitudes into consistent actions For example, Pothitou et al (2016) argue that people

2.1.7 Green Product

product Some people define green product as “product that do not pollute the earth ordeplete natural resources and can be recycled or conserved/’ It is a product whose

ingredients or packaging are more environmentally friendly in minimizing its impact on

the environment On the other hand, green product is product that incorporate strategies

or content that recycle, reduce packaging, or use less toxic materials to reduce the impact

on the natural environment (Chen & Teck Chai, 2010)

2.1.8 Green Purchasing Intention

Nik Abdul et al 's (2009) research on green purchase intention is a person'swillingness to prioritize environmentally friendly products over other conventional

products when considering purchase Similarly, Chen and Chang (2012) defined green

purchase intention as the likelihood that a consumer will purchase a specific productbased on environmental needs “Green purchasing”, is choosing to purchase products

throughout the life cycle of production, transportation, use and recycling or disposal.The main goal is to reduce negative impacts on the environment, while sourcing and

relatively complex (Shah, 2002)

2.2 Related theories

2.2.1 Organizational information processing theory (O1PT)

Organizational information processing theory (OIPT) - developed by Thompson

in 1967 - posits that an organization develops within a system, integrating many internal

and external processes that are characterized by complexity and uncertainty This theoryprovides a solid basis for explaining the concept and organizational behavior of firms

and the level of interdependency between sub-units As the volume of data managed by

participation of a number of internal and external entities (Galbraith, 1977; Srinivasan

performance and enhance a company's competitive advantage (Bartnik and Park, 2018; Dubey et al., 2019b)

In the field of supply chain management, information processing capabilities

appropriate technology (Srivastava and Singh, 2020) Many studies have addressed the

role of technological infrastructure as a mechanism that can enhance the information processing capacity of organizations (Galbraith, 1974) In this regard, the authors assert that the use of AI technology can help organizations cultivate and exploit additional

In green supply chain management, supply chain operations depend on a number ofuncertain conditions that change with customer demand and the unpredictability of

ability to process information effectively and make decisions about the implementation

organizational complexity In this regard, the implementation of AI has the potential to

improvement

2.2.2 Theory of Planned Behavior (TPB)

Reasoned Action (TRA), is one of the most widely studied and applied models by social

psychologists to predict behavioral intentions Intention here is understood as a

conscious action plan, specifically including a behavior and the motivation to perform

it There are many studies describing intentions and generally suggest that intentions arethe most reliable predictor of behavior and fully mediate the effects of attitudes, social

stereotypes, and perceived behavioral control In the context of TPB intention is considered the leading predictor of human behavior, which plays an important role

Picture 2.2.2 Model of the Theory of Planned Behavior (Hung et al., 2010)

Rezai and colleagues applied TPB to the research of green food consumption in

as well as Paul and colleagues have demonstrated that promoting this intention can

Jones and colleagues along with Sutton defined it as the ability to maintain resources orelements of significant value in the physical environment

2.3 Research hypotheses and proposed model

2.3.1 Research hypotheses

2.3.1.1 Hypothesis HI

2020 research states that the GSCM system is a very dynamic and complex system Itinvolves many criteria that require expert decisions Industry 4.0 technologies, such asloT, can be used to collect data from different points, and Artificial Intelligence can be

items This is helpful in building relationships with green customers, green suppliersand partners This brings great value in supply chain coordination and collaborative

demand planning in green supply chains At the same time, it solves many GSCMproblems that traditional analysis models fail Genetic algorithms can be used in green

installation, and material handling problems in GSCM Al-based technological support

will help managers come up with appropriate strategies and action plans (Min, 2010; Dwivedi et al., 2019)

Hl: Artificial Intelligence has a positive relationship with Green Supply Chain Management.

2 3 1.2 Hypothesis H2

(GSCM) is a vital factor that plays a decisive role in the development of businessreputation The application of Green Supply Chain Management practices, such asenvironmentally friendly products and services, has significantly enhanced its overall

perception of a business and begin to notice that the business pays more attention to the

natural environment Additionally, Aslam et al (2019) conducted a research

GSCM activities have a positive and significant relationship with corporate image

H2: Green Supply Chain Management has a positive relationship with Green Brand Image.

2.3 ì.3 Hypothesis H3

through brand positioning is as important as quality and profitability Saha and Darnton

The authors cite a definition from Chen and Chang, that “green purchaseintention" is the likelihood of consumers purchasing specific products or brands due to

their environmental needs In the context of environmental management, the

purchase intention Therefore, the authors propose the hypothesis:

H3: Green Brand Image has a positive relationship with Green Purchasing Intention.

2.3 J.4 Hypothesis H4

Environmental Concern plays an important role in research on environmental

attitudes Hanson reports that environmental concern has a positive effect on green

H4: Environmental Concern has a positive relationship with Green Purchasing Intention.

2.3.1.5 Hypothesis H5

concerns about environmental issues lead to green shopping intentions In this context:

change the intention to use environmentally friendly products Environmental concerns

have positively changed young adults' purchasing decisions toward green shopping

intentions Consumers who intend to pay more attention to the ecological environment

will be more willing to buy green products Therefore, the authors propose the

indicator and influence on green purchase intention Similarly, L Wang et al (2020)

analyzed the demographic influence of consumers' purchases and their intentions

towards choosing green products Therefore, the authors propose the hypothesis:

H6: Environmental Knowledge has a positive relationship with Green Purchasing Intention.

2.3.1.7 Hypothesis H7

Rising environmental issues have changed consumer purchasing intentions.There are products that are harmful to the environment, and there are products that areenvironmentally friendly In this context: Tan et al (2019) listed the factors that change

intentions The world has faced a lot of damage to the environment due to

environmentally harmful products The long-term widespread use of green products by

environmentally friendly products Environmental knowledge provided by world

forums plays a role in protecting the environment Furthermore, Cai et al (2017) linkretailers and eco-label reputation and its impact on purchase intention of green products

the environment Although the intention to purchase green products has increasedpositively in developed and developed countries, where the public consumes a lot ofgreen products Therefore, the authors propose the hypothesis:

H7: Green Product have a positive relationship with Green Purchasing Intention.

2.3.2 Proposed research model

Picture 2.4.2 Proposed research model

CHAPTER 3: RESEARCH DESIGN 3.1 Research Process

Figure 3.1 Framework

Includes 7 steps:

framework for the research article

set of qualitative interview questions

Step 4: Qualitative interview to synthesize opinions and propose quantitative questions

Step 6: Synthesize quantitative data and run tests through the application SPSS 26.0

3.2 Qualitative research

3.2 L Objectives

Qualitative research to help the team have an overview of the relationship

between AI and Green Supply Chain Management affecting green purchasing intention

intelligence is developing strongly Through this, the authors hope to be able to collectmore suitable variables to complete the research model through in-depth interview methods

3.2.2 Methods of implementation

conducted interviews with subjects with experience in the field and potential target

groups The interviews were conducted by the following two methods:

• For the In-depth Interview method:

researching

Contact and interview via online platform, thereby synthesizing information anddrawing conclusions for the research article

• For focus group interview method:

Contact and interview respondents based on the available questionnaire, therebysynthesizing information and drawing conclusions for the research article

3.2.2.1 Number of survey samples

• For experts:

Limited

This interview aims to clearly understand how the potential of artificial

intelligence tools has affected Green Supply Chain Management in businesses, therebyaffecting the Green Consumption Intention of customers Ho Chi Minh City youth

Then, synthesize the opinions and continue to perfect the research model

• For focus group interviews:

15 students from 5 universities in Ho Chi Minh City were divided into 5 smallgroups and conducted in-depth interviews

The questions revolve around factors that affect their Green Purchase Intention:

products and what is their attitude

3.2.2.2 Sampling method

Qualitative research was conducted with in-depth interviews with 02 experts and

performed purposive sampling

3.2.2.3 Model approach

Due to the lack of time for the interview subjects, the authors were unable to meet

directly with groups and experts Therefore, the interview was conducted in the form of

to be confidential and are recorded with the permission of the groups of respondents andexperts

3.2.3 Qualitative research results

3.2.3.1 For expert interviews

• Evaluation of Artificial Intelligence tools:

AI plays an important role in enhancing decision-making and implementing

dashboard information applications in the field of Green Supply Chain Management

However, successful implementation and use requires a combination of expertise,

and devices

Ms N.M.T.N said, “AI creates and simulates the Green Supply ChainManagement system This helps businesses test strategies and make different decisions

without directly implementing them Thereby, helping businesses predict changes in

Regarding the AI dashboard, Mr H.M.C emphasized the ability to visualize data

overview of environmental, production and transportation performance, with real-time data collection capabilities

• Evaluation of Green Supply Chain Management:

collaboration to address consumers' environmental concerns, is increasingly important

creates many economic, social and brand benefits for businesses

Innovation in the production process

On the other hand, Mr H.M.C shared more to meet consumers’ growing concerns

actions they are taking to protect the environment, this could be through product labels,

website information or customer engagement programs.”

• Evaluation of Green Brand Image:

This concern influences brand image, aids in attracting talent and partners, and

meets market requirements However, simply creating an Environmental Image without

reputation and image

Ms N.M.T.N said: "The issue of communication expressing a brand's image is

careful and pay attention to each step of implementation and product quality."

• Evaluation of Environmental Concern:

products are gradually changing and developing Therefore, environmental concern is

Vietnam

In general, it is the value and usefulness of the product that matters The

positive view of how Vietnamese consumers can contribute to protecting the

environment through their purchasing decisions

• Evaluation of Environmental Knowledge:

Experts also gave similar opinions about limited information: One challenge to

online information sources, consumers are increasingly accessing to learn more and

• Evaluation of Green Product:

purchasing decisions

Experts agree that in purchasing decisions, despite increased environmental

concerns, product value and utility still play an important role If a green product meets

both of these factors, it can boost consumers' purchasing decisions

3.2.3.2 For focus group interviews

• Evaluation of AI Tools:

When asked about AI artificial intelligence tools, most respondents shared that

GPT Chat is the favorite and frequently used AI tool of the majority of respondents

Most respondents thought ofChat GPT when asked about the most popular tool recently

and needed time to think Because the respondents in this group are still students who

have not yet worked and have not had any actual observations in the business They

believe that AI is very versatile and can support businesses in processing data, solving

• Evaluation of Green Supply Chain Management:

Similar to the above question, the respondents are still people who have not

about the concept of "Green Supply Chain Management" but mostly in theory throughtheir studies at school, in reality how Green Supply Chain Management is being

implemented in enterprises which they still do not understand clearly

• Evaluation of Green Brand Image:

demonstrate professionalism, honesty and put customers’ interests first T.H (student, 19

years old) said: "After the pandemic, in addition to the application of technology,

health issues When choosing products with reputable brands, labeled "green", "clean"

and made from natural ingredients, priority is given This greatly increases the likelihood that customers will know about the product if the business allows consumers

to believe, feel and experience it as advertised.”

• Evaluation of Environmental Concern:

With the cun-ent state of environmental pollution, respondents all believe that

reasonably: not cutting down forests to cause climate change, managed in the right placeaccording to regulations to protect a clean and green environment

• Evaluation of Customer Attitude:

The majority of respondents agree that consumers will have positive attitudestowards green products when they believe that green products are safe, healthy and good

for their health

• Evaluation of Environmental Knowledge:

To the question about environmental knowledge, respondents had different

confident that they know how to properly classify recyclables, and respondents know

sites Although their environmental knowledge varies, they are generallyenvironmentally aware and know that purchasing environmentally friendly products andpackaging will have a positive impact

• Evaluation of Green Product:

Regarding the question about how do you think green products will benefitconsumers: the majority of respondents agree that green products improve satisfaction

following answer: "My family specializes in using products and bags made of paper,

wood, paper straws items that are recyclable.” mechanism for use Recycling andreusing products such as paper and bamboo bags to replace single-use products will

unfriendly products contributes to reducing family spending.”

• Evaluation of Green Purchasing Intention:

Regarding the future question, do you intend or want to buy green products? Is

there anything that is preventing you from buying green products? All respondents want

conventional products to buy products that both protect their health and theenvironment,

in which the important factor is good product quality

3.2.4 Results

the authors exploited and collected information from the respondents' multi-dimensional perspectives to supplement and complete the research article From there, synthesize it

Chain Management have a direct impact on a business’s Green Brand Image but will not

intention, however it can be affected by external factors

3.3 Quantitative research

The authors research on the impact of the relationship between Artificial

green purchasing intention of young people who are studying and working, job in HoChi Minh City This place is an ideal location for this research because it is where many

job opportunities in Vietnam In addition, in Ho Chi Minh City, there are many people

authors selected young people who are studying and working in Ho Chi Minh City, and

have purchased green products, as the main research subjects in the overall study

3.3.1 Number of survey samples

to satisfy both formulas:

Formula 1: For EFA exploratory factor analysis: Based on research by Hair et al

in 2006, to use factor analysis, the minimum sample size is 5 times the total number of

observed variables This is an appropriate sample size for research using factor analysis:

n=5*m, where n is the sample size, m is the number of questions in the article

Tabachnick and Fidell, 1996, the minimum sample size must be calculated according to

the formula: n=50 + 8 * m, where n is the sample size , m is the number of independent

variables (m is different from formula 1)

based on the stated sample size calculation, the minimum number of samples is:

Formula 1: n = 5 * m

With m = 36 we have n = 5 * 36 = 180

Formula 2: n = 50 + 8 * m

With m = 5, we have n = 50+ 8*5 = 90

To satisfy the above two formulas, the sample size is n > 180

previous studies and their own ability to conduct surveys, using the convenience

met the requirements

So the sample size is n = 203

3.3.2 Sampling method

The authors chose a non-random sampling method including 2 methods:

Convenience sampling method: conducting an online survey (specifically via the

survey research site "khaosat.me") for young people studying and working in Ho Chi

Minh City, has the advantage of ease of access and quick collection of information

generalizability of results

Snowball sampling method: The authors expanded participation in the survey by

asking those who initially participated to send the survey to their relatives and friends

-people in the same group of subjects that the authors are researching Initially, part of

the participating group was selected by random method, while later participants were

introduced by people in the first part This helped significantly increase the number of

survey participants

3.3.3 Model approach

The authors’ sample approach was to conduct an online survey because of travel

difficulties To do this, the authors designed a clear survey questionnaire and sent it to survey participants through the research page

This form of online survey has saved time and brought high efficiency in data

that contained false information or did not fully meet the research's criteria

3.3.4 Questionnaire design and data collection methods

• The questionnaire consists of 4 parts:

Introduction: state the objectives and meaning of the survey to the surveyor This

value

stop and not participate in the survey

Main question part: statements are measured using a 5-point Likert scale

Likert scale with five levels from 1 to 5 respectively as follows:

• Expressing and coding the scale:

The research ’’Optimizing Green Supply Chain with Artificial Intelligence: Promoting Sustainable Development and increasing the Green Purchasing Trend

of Young People in Ho Chi Minh City” proposed a scale consisting of 8 components

Artificial Intelligence (AI) (4 observed variables)

Green Supply Chain Management (4 observed variables)

4

in electronic devices of green supply chain processes AI4

Green Supply Chain Management

5

6

In the market, businesses have cross-functional collaborations to

7

In the market, businesses have built projects to convert production

8

In the market, businesses have measures to promote senior

management's commitment to environmental issues GSCM4

Green Brand Image

12 To implement a green supply chain, businesses are honest GBI4

Environmental Concern

14 People need to understand the laws of nature and act reasonably ECI

16

Being the master of the world, humans have the right to use natural

18

Customer Attitude

19 I think that purchasing green product is advantageous CAI

20 I think that purchasing green product is a good idea CA2

Environmental Knowledge

22

I know that purchasing environmentally friendly products and

24

Table 3.3.4 Scale coding table

25 I understand environmental phrases and symbols on product packaging EK4

26 I am confident that I know how to properly sort rccyclablcs EK5

27 I am very knowledgeable about environmental issues EK6

30 The green product continues to improve its development over time GP3

Green Purchasing Intention

35

The price ofgreen products had to increase quite a bit before I switched

36

I am willing to pay a higher price for green products than conventional

3.3.5 Data analysis method

All response data will be analyzed with the support of IBM SPSS 26 software

4- Descriptive statistics of the sample

+ EFA factor analysis

+ Pearson correlation analysis

3.3.5.1 Clean data

The purpose is to eliminate invalid survey samples, including those with

incomplete answers, answers with at least two options, or do not belong to the survey object.

entering incorrect, missing or redundant data In addition, the authors created frequency

tables for all variables, proofread, and eliminated observational samples with irregular

scores to find outlier values and eliminate them

3.3.5.2 Descriptive statistics

Descriptive statistics help summarize and describe the basic characteristics of

data and provide simple, complex information for general assessment of survey

participants Parameters after descriptive statistics such as minimum value (min),

3.3.5.3 EFA exploratory factor analysis

number) of observable variables and unobservable variables Factor analysis operates

on the principle of measurability and the reduction of variables that share common,

The criteria used for evaluation in EFA analysis are as follows:

degree of contribution of the observed variable to the factor If the sample size is 100,

loadings < 0.5 when analyzing EFA will be eliminated (Hair el al., 1998) In addition,Communalities value > 0.5 is accepted

KMO coefficient (Kaiser - Meyer - Olkin): The KMO value must be 0.5 or

higher (0.5 < KMO < 1) If this value is less than 0.5, factor analysis is not suitable forthe research data set (Kaiser, 1974)

Bartlett's test of sphericity: used to see whether the observed variables in the

factor are con*elated with each other or not The Bartlett test has statistical significance

of less than 0.05 (sig Bartlett’s Test < 0.05), proving that the observed variables arecorrelated with each other in the factor (Nguyen Dinh Tho, 2011)

EFA analysis With this criterion, only factors with Eigenvalue > 1 will be retained in

Total Variance Explained - Total Variance Explained - "Cumulative Percent" >

60% shows that the EFA models are appropriate This value represents how much the

Dinh Tho, 2011)

3.3.5.4 Test the reliability of the scale (Cronbach's Alpha)

To evaluate the suitability ofthe child variable with the parent factor, the research

tested the scale using Cronbach's Alpha index This index will help check whether theobserved variables of the parent factor are reliable or good This test reflects the level ofclose correlation between observed variables in the same factor

+ Cronbach's Alpha index > 0.6: the scale is considered reliable

+ Cronbach's Alpha index is in the range [0.6 - 0.95]: the scale has good reliability

3.3.5.5 Pearson correlation analysis

99% confidence with Sig values (2-tailed) of all variables is less than 0.01,

inferring there is a correlation Thus, regression analysis is appropriate The value of the

coefficients are positive (Hoang Trong and Chu Nguyen Mong Ngoc (2008, page 237))

3.3.5.6 Regression analysis

Use the correlation coefficient (r) to test the correlation between group

r>0 represents a positive correlation, ifr<0 represents a negative correlation, if r=0 then

the two variables do not have a linear correlation

Use the sig value of the correlation coefficient to evaluate the tightness of the

correlated

The R2 coefficient is adjusted to determine the appropriateness of the model, the

T-test is used to reject the hypothesis of regression coefficients The general rule is 0

Variance exaggeration index VIF to check multicollinearity If VIF > 2, be careful

in interpreting the regression coefficients

Hypothesis testing and partial regression coefficient pi indicate the effect ofone- unit changes in that independent variable on the average value of the dependent variablewhen the effects of other independent variables are excluded.

CHAPTER 4: RESEARCH RESULTS 4.1 Descriptive statistics

Table 4.1 Descriptive statistics (Source: Authors)

4.1.1 Age

Of the total 203 samples processed, people aged 18-22 years old accounted for a

businesses related to the fields of production, transportation, and distribution, they will have special interest in GSCM to be able to protect the environment and resonate with

Management Practices, and Financial Performance: A Sophisticated Empirical Study.”

by Alghababsheh, M., Butt, A s., & Moktadir, M A (2022) From the consumer's

pay more attention to green products that both protect the environment and are healthy for their health According to the research paper “The Impact of Customer-Oriented

Satisfaction” by Chavez, R., Yu, w., Feng, M., & Wiengarten, F (2016)

4.1.2 Gender

Results from the chart show that the number of survey participants who were

and women tend to learn, have understanding and are interested in the impact of AI and

found that perspective in the research of Touboulic and Walker (2015)

4.1.3 Occupation

Regarding employment structure, the majority of survey participants are

studying Meanwhile, only 19.7% of respondents are still going to school and not

employed people often have a high level of contact and awareness about the

environment, AI technology as well as green supply chain activities in businesses

4.1.4 Educational level

graduated from high school only accounted for 7.4% of the total 203 respondents The

total of 163 people The reason for this difference could be explained by the fact that the

of university students to participate In addition, the survey is aimed at the group of

Graduate/Master's degrees, accounting for 12.3% with a total of 25 people

4.1.5 Income

Regarding monthly income, the majority of surveyors concentrated on income

participants This income level is suitable for a number of students living with family orrelatives, the expenses incurred do not include accommodation and living expenses like

students living far away from family The income level from 3 million VND to 5 millionVND (19.2%) is also quite suitable for the student segment who can work part-time and

be supported by their families In addition, a small number of 4th year students have an

- Below 3 million VND: 59 people

- From 3 million VND to under 5 million VND: 39 people

- From 5 million VND to under 7 million VND: 38 people

4.2 EFA exploratory factor analysis and Cronbach ’ s Alpha reliability assessment

Exploratory factor analysis (EFA) is used to check and eliminate inappropriate

Meyer-Olkin (KMO) scale is > 0.6 and the significance level of the Bartlett Test is <

the factor analysis model must have factor loading > 0.6, Eigenvalue > 1, Commonalities

> 0.5 and Total Explained Variance - "Proportion” Cumulative Percent > 60% If a

variable does not meet these criteria, it will be eliminated from factor evaluation

dependent variable to identify inappropriate observed variables The scale is considered