In addition, I would like to sincerely thank my classmates for their helpful comments and fair criticism throughout the research project. The main objective of this research paper is to study the AI tools to improve the online shopping application with the aim of improving the customer attitude towards AI in the application.
INTRODUCTION
- Introduction
- Research Background
- Problem Statement
- Research Objectives
- Research Questions
- Scope of Study
- Significant of the Study
- Chapter Layout
- Summary
In addition, this study will provide suggestions for the AI system developers in online shopping applications. In addition, they can also focus on the expectations of consumers towards AI in the online shopping application.
LITERATURE REVIEW
- Introduction
- Underpinning Theory
- Technology Acceptance Model (TAM)
- Artificial Intelligence
- Online Shopping Application
- Shopee
- Lazada
- Malaysian Customer Attitude
- Review of Variables
- Dependent Variable – Attitude
- Independent Variable – Perceived Usefulness
- Independent Variable – Perceived Ease of Use
- Independent Variable – Perceived Trust
- Independent Variable - Perceived Performance/ Quality
- Proposed Research Framework
- Hypothesis of the Study
- Summary
Finally, this study also favors the government's ability or capacity to identify systems related to AI in the e-commerce industry. Not only that, but since online shopping is also growing tremendously and bringing a huge impact on the economy, this study can support the government to improve the AI systems in the online shopping application for the sake of improving user experience and more profit to obtain.
RESEARCH METHODOLOGY
Introduction
In addition, participant selection, data collection and data analysis are also discussed as study phases in this chapter. Subsequently, the role of the researcher in qualitative research related to reflexivity will also be discussed.
Research Design
Furthermore, it includes the information or data required for the research approach used along with the justification for its implementation. In addition, it is important to apply appropriate data analysis tools and appropriate research design along with data collection instruments (Sukamolson, 2007).
Data Collection Methods
- Primary Data
Sampling Design
- Target Population
- Sampling Location
- Sampling Elements
- Sampling Techniques
- Sampling Size
Sampling techniques can be divided into two main categories: probability sampling and non-probability sampling (Barratt & Kirwan, 2009). Non-probability sampling which was applied in this research as it is a quick, easy and cost effective method of data collection. Furthermore, (Roscoe, 1975) proposes some general rules for determining sample size.
In addition, the rules state that the sample size greater than 30 and less than 500 is appropriate for the majority of the study.
Research Instrument
- Questionnaire Design
- Pilot Test
Part A of the survey questionnaire contains a total of seven questions asking about respondents' gender, age group, highest grade or school level, and most commonly used online shopping application. Part B of the survey questionnaire consists of six categories, including both dependent and independent variables. Pilot testing can be described as a rehearsal of the research that allows the researcher to test the research approach through a smaller number of test participants.
Besides that, Cronbach's Alpha had been used to examine the internal reliability of the pilot test and it had been categorized into 4 categories by (Zikmund et al., 2013) as shown in Table 3.1. After the respondents completed the questionnaire, the reliability test was additionally tested through the Statistical Package for the Social Science (SPSS) to examine the reliability and validity. According to Table 3.2, there are 4 constructs with good reliability, as the value of Cronbach's Alpha is between 0.70 and 0.80.
Construct Measurement
- Scale Management
- Nominal Scale
- Ordinal Scale
- Interval Scale
- Ratio Scale
BI2 In the future, I intend to use online shopping application that contains AI on a regular basis. On top of that, 4 types of measurement scales were used in this research regarding consumer attitudes toward AI in online shopping applications. The ordinal scale is used e.g. to ask respondents how often they buy via the online shopping application each month as shown in Table 3.5.
Shopping on an online shopping app powered by artificial intelligence is a good idea. Shopping on an online shopping app powered by artificial intelligence is a smart idea. The ratio question in this survey includes the amount you spend on an online shopping app in a month.
Data Processing
- Collection
- Preparation
- Input
- Processing
- Output
- Storage
Data preparation is the process of sorting and filtering raw data to remove unnecessary data. The raw data is converted into machine-readable data and then fed into the processing unit. Moreover, it is the first stage where raw data becomes valuable or useful information.
Data were coded with specific numbers to simplify for the researchers to enter a significant amount of raw data into the SPSS system. The output stage is when the data is transmitted and displayed to the user in a readable form. All information must be saved for future use after the successful processing of data, as the data is properly stored so that it can be easily accessed in the future.
Data Analysis
- Descriptive Analysis
- Reliability Test
- Inferential Analysis
- Multiple Regression Analysis
Inferential statistics includes varieties of statistically significant tests that researchers are able to draw conclusions about the sample data. On top of that, Multiple Regression Analysis through SPSS had been used in this study. Multiple regression analysis is known as the highly flexible system that is able to investigate the relationship between the independent variables and a particular dependent variable (Aiken et al., 2003).
Moreover, in multivariate regression analysis, an attempt had been developed with the intention of synchronizing the variability of independent variables in the dependent variable (Ünver & Gamgam, 2008). In this study, the dependent variable is consumer attitudes towards AI in online shopping applications, while the independent variables are perceived usefulness, perceived ease of use, perceived trust, and perceived performance to build the equation. In addition, a researcher can interpret the key variable influencing Malaysian consumer attitudes towards AI by using the .
Conclusion
DATA ANALYSIS
Introduction
Respondents Demographic Profile
Central Tendencies of Variables
Scale Measurement
- Internal Reliability Analysis
Pearson Correlation Analysis
Multiple Linear Regression
- Test of Significant
Conclusion
DISCUSSION AND CONCLUSION
Introduction
Discussion on 1 st Research Objective
First, there are 80% of respondents who have chosen Shopee as their most used online shopping application, while the remaining 20% of respondents have chosen Lazada as their most commonly used online shopping application. Besides that, followed by the frequency of using online shopping applications to buy, there are 29% of the respondents selected several times a month to buy through online shopping application. In addition, 18% of respondents are selected several times a year, and the remaining 10% of respondents are selected several times a week.
Apart from that, the survey questionnaire also asked about the amount spent monthly on online shopping apps. In short, the result obtained from figure 5.2 illustrates that Shopee is currently the most popular online shopping application in Malaysia, and the majority of the consumers spend more than RM100 monthly on those online shopping applications. In short, the majority of respondents prefer AI-assisted assistance in online shopping applications.
Discussion on 2 nd Research Objective
Furthermore, the result showed that there are 92% of the respondents who chose yes, while the remaining 8% of the respondents chose no. In addition, the results interpreted from Chapter 4 show that perceived ease of use, perceived trust and perceived performance have a significant positive relationship with consumers' attitude. However, there is one variable that is considered that usability has no significant relationship with consumers' attitude.
In short, according to the results, a modified TAM model had been developed to investigate consumer attitudes towards AI.
Discussion on 3 rd Research Objective
- Relationship between Perceived Usefulness and Attitude
- Relationship between Perceived Ease of Use and Attitude
- Relationship between Perceived Trust and Attitude
- Relationship between Perceived Performance and Attitude
This result was supported by a study conducted by (Indarsin & Ali, 2017) where the population of the study is the regular customers of Ikens group wholesalers who have downloaded the Ikens wholesale mobile application. The study also mentioned that perceived ease of use has six dimensions, including ease of learning, control, clarity, flexibility, ability to become skilled, and ease of use. In summary, the result of the study shows that perceived ease of use has a positive effect on attitude toward using a mobile shopping application.
This result is supported through research conducted by (Suleman, 2018) to examine factors such as trust in the attitudes and intentions of consumers who purchase. In addition, the study has 74 respondents in the whole city of Jakarta from Indonesia and applied purposive sampling in the survey method. In short, the result of the study showed that the relationship between attitude and perception of product quality with recycled content is positive.
Implications of the Study
- Theoretical Implications
- Managerial Implications
Moreover, the online shopping app developer should ensure that AI will make the consumer or user effort-free rather than increasing the burden to use it by improving tracking and logistics through AI, such as providing tracking in real time and informing the customer when the parcel has left. station. On this account, the online shopping app developer can use the AI tool to detect the fake reviews along with fighting it for the sake of increasing the consumer trust towards the online shopping app. Liu et al., 2008) found that the performance offered is one of the factors that influence online shopping satisfaction.
As an illustration, the developers can improve the search engine by filtering the price and image search engine for AI tools, since AI is a fundamental tool for any search engine to be used today. Therefore, the developers need to improve the algorithms and apply AI to provide accurate search results. Not only that, but this study also shows the importance of promoting the AI system in Malaysia.
Limitations of the Study
- Limited Framework
- Limited Outcomes in Quantitative Research
- Imbalance Sample Size
Recommendations for Future Research
- Extend the Framework
- Apply Both Quantitative and Qualitative Research
- Enlarge the Sample Size
Conclusions
Consumer Attitudes Toward Online Shopping: The Effects of Trust, Perceived Benefits, and Perceived Internet Quality. Implementation of artificial intelligence in the healthcare sector in the United Arab Emirates: an extended model of technology acceptance. Analysis of perceived usefulness, perceived ease of use and perceived risk of online shopping in the era of the Covid-19 pandemic.
A Study on Factors Affecting Consumers' Attitude towards Online Shopping and Online Shopping Intent in Bangkok, Thailand. Exploring the adaptation of artificial intelligence to the whistleblowing practice of internal auditors in Malaysia. As Southeast Asia's largest e-startup platform it is using AI to improve the online shopping experience.
I am currently researching on "Using Artificial Intelligence in Online Shopping Application: Malaysian Customer Attitude." The purpose of this survey is to investigate the factors influencing Malaysian customers' attitudes towards the use of artificial intelligence in online shopping applications. The use of artificial intelligence in online shopping applications allows me to find the best deals.
