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Chapter 1: Introduction

Background of the study

There has been a shift in the perception of technology among individuals. The field of Artificial Intelligence is gaining increasing popularity as technology advances rapidly. The phenomenon has garnered considerable intrigue within the industry, prompting corporations to engage in efforts aimed at comprehending its potential applications. The term "intelligence" is frequently employed by individuals to denote an individual's capacity for analyzing, strategizing, problem-solving, and engaging in analogous cognitive activities. AI is frequently discussed as a distinct field within the realm of computer science

Problem Statement

Due to significant advancements in AI technology, retail establishments are now able to provide their clientele with a comprehensive automated shopping experience. Face recognition and computer vision represent instances of AI-enabled technologies that enable customers to bypass traditional checkout counters and directly access desired products.

Research Questions

  • What is the importance of artificial intelligence on the retail industry?
  • What is the impact of artificial intelligence on the retail industry in Malaysia?
  • What recommendations can be given?

Research Aim

The study will highlight and evaluate the impact of artificial intelligence on the retail industry in Malaysia

Research Objectives

The research objectives are as follows:-

  • To understand the importance of artificial intelligence on the retail industry
  • To analyze the impact of artificial intelligence on the retail industry in Malaysia
  • To provide suitable recommendations

Scope

The utilization of AI-enabled robots for the purpose of automating order fulfillment processes presents a cost-saving advantage for organizations by reducing reliance on human labor, while simultaneously enhancing productivity and precision. Consumers have the option to utilize AI-driven digital assistants to obtain tailored suggestions and information, hence facilitating their decision-making process over purchases. AI has the potential to enhance the check-out process as well. By utilizing artificial intelligence and facial recognition technologies, consumers are able to expedite their purchasing process, eliminating the need for queuing. This technology has the potential to apprehend shoplifters, thereby reducing instances of theft and enhancing the safety of clients within retail establishments.

Significance

. The primary objective of this field of study is to imbue computers with human-like capabilities in tasks such as reasoning, learning, and decision-making. Artificial intelligence has the capability to automate human capabilities as well. Artificial intelligence technologies are widely employed by numerous enterprises, particularly those engaged in advertising endeavours. The development of a marketing plan necessitates consideration of factors such as the preferences and desires of the target market, the accessibility of products or services, and the level of user-friendliness. There exist several distinct approaches to marketing, including cost leadership, differentiation, focus, collaboration, diversification, and direct marketing (Berdiyeva, Islam & Saeedi, 2021).

Chapter 2: Literature Review

THEORETICAL BACKGROUND

Lee et al. (2020) argues that the retail sector is currently undergoing a significant transformation due to the increasing integration of artificial intelligence in several aspects of the purchasing process. Artificial intelligence is significantly impacting various aspects of the retail industry, encompassing customer service, inventory management, and other relevant domains. The objective of this study is to examine the impact of artificial intelligence on the retail sector, encompassing its effects on both enterprises and consumers. The retail industry is experiencing significant impacts from AI since it enables the automation of various labor-intensive and manual processes that play a crucial role in ensuring the efficient operation of enterprises within this sector. The utilization of artificial intelligence in automating retail processes offers organizations the opportunity to achieve cost savings while simultaneously enhancing productivity, accuracy, and customer pleasure. AI-driven technologies such as chatbots, virtual personal assistants, and image recognition systems have emerged as valuable tools for automating jobs previously performed by human employees that were deemed monotonous, time-intensive, or both. The implementation of AI-powered automation in retail businesses has the potential to enhance efficiency and productivity, so enabling these establishments to allocate more attention towards strategic objectives while upholding consistent operational excellence (Yeo et al. 2020).

Variables

AI is also contributing to the enhancement of companies and consumers' experiences through the provision of customised product recommendations. The utilization of analytics driven by artificial intelligence holds the potential to enhance businesses' ability to effectively address the demands of their customers by identifying patterns in customer behavior. Ultimately, the integration of AI into automated processes has the potential to significantly enhance the management of supply chains in the retail industry, hence facilitating the more efficient and punctual delivery of items. AI is revolutionizing the retail sector through its ability to enhance customer experiences and streamline operational operations. Artificial intelligence enabled chatbots and virtual assistants have the capability to provide customized recommendations, address customer inquiries, and provide round-the-clock assistance. AI systems analyze customer behavior and past purchasing patterns in order to predict future consumer trends, hence facilitating the implementation of tailored marketing campaigns. Inventory management systems that utilize AI have the capability to optimize stock levels, hence mitigating the occurrence of stockouts and reducing surplus inventory. In addition, the use of AI-powered vision recognition technology has the opportunity for the establishment of cashier-less stores and seamless checkout processes (Berdiyeva, Islam & Saeedi, 2021).

Framework

positive impact AI

Figure: Theoretical Framework

The retail industry is currently witnessing a rapid revolution as a result of artificial intelligence thanks to the automation of several procedures that previously required manual effort and considerable labor to properly maintain a thriving business. Automating retail processes using AI helps save money, works faster and more accurately, and gives customers a better shopping experience overall. Several mundane tasks that were once handled by retail employees are progressively being delegated to AI-enabled technologies such as chatbots, virtual personal assistants, and image recognition systems. Artificial intelligence-driven automation in the retail sector helps boost efficiency and output. Therefore, business owners have the freedom to invest in strategic initiatives while still prioritizing operational efficiency and effectiveness (Alwi et al. 2023).

Consumers can now benefit from an AI-enhanced, fully automated purchasing experience. Facial recognition and computer vision are two examples of AI-powered technologies that might be used to quickly identify customers as they enter a store, allowing them to skip the lines and get their hands on the goods they came for. Robots powered by artificial intelligence might handle orders on their own, saving businesses money on human labor while improving productivity and accuracy. Customers can be helped to make educated selections with the assistance of AI-powered virtual assistants who provide individualized suggestions and direction regarding products.

The use of AI to manage stock levels in businesses is also on the rise. Predictive analytics is an AI-powered tool that helps businesses accurately estimate product demand and make timely modifications to stock levels. This helps stores improve their stock levels and avoid building up surplus goods at the same time. In addition, the usage of robots equipped with artificial intelligence might automate a variety of tasks, including inventory management and order fulfillment, reducing the need for human labor while simultaneously increasing efficiency (Berdiyeva, Islam & Saeedi, 2021). The primary goal is to improve the capabilities of artificial intelligence (AI) in terms of managing and carrying out decision-making processes. This will make it possible for us to take advantage of the potential benefits that AI provides in this area. Establishing operational procedures that are firmly rooted in the retail industry is a key component in the process of harnessing artificial intelligence (AI) to increase the performance of a business. Artificial intelligence (AI) has the potential to dramatically help enterprises by facilitating decision-making processes in crucial domains such as marketing, product development, and customer relationship management. These are all areas that are essential to the operation of a company. Due to the quick pace of technical breakthroughs in the digital sphere, it is now absolutely necessary for businesses to establish effective Artificial Intelligence Monitoring (AIM) systems in order to successfully monitor and upgrade their AI systems in a timely manner. This has become an absolute necessity for businesses (Lee & Tajudeen, 2020).

Inventory placement optimization is another area where artificial intelligence (AI) can be put to use. Using algorithms driven by artificial intelligence, retailers may determine where in a warehouse or store to best stock items. With this method, they are able to cut down on wait times and increase accessibility. The use of artificial intelligence (AI) for the goal of real-time inventory monitoring allows for earlier detection of stock depletion and subsequent action to replenish supplies. Chatbots powered by artificial intelligence are gaining popularity in the retail sector because they can respond quickly to customer enquiries with little to no human intervention. With the use of artificial intelligence, virtual assistants may provide shoppers with tailored suggestions and advice to help them find exactly what they need. AI-powered analytics could also help businesses gain a deeper understanding of their customers' needs and preferences, allowing them to better tailor their products and services to each individual (Lee & Tajudeen, 2020).

Several customer service tasks, such as order tracking and customer support, may be automated with the use of artificial intelligence technology. This change may shorten wait times for customers and increase their satisfaction. In addition, businesses can use AI-enhanced sentiment analysis to better understand how their customers feel about their interactions with them (Wong et al. 2022).

Gaps

There is a possibility that the application of AI in automation would improve the procedures of supply chains used by merchants. This will result in the timely and correct delivery of products to customers. Investigating the ways in which AI could be utilized to personalize and improve the shopping experience for each unique shopper presents a number of interesting research opportunities. Technologies based on AI such as face recognition and computer vision, make it feasible to quickly identify customers as soon as they enter a store. This enables businesses to better serve their customers. According to Yeo et al.' (2020) AI has the ability to enhance the quality of the shopping experience by making the environment more interesting. In addition, recommendation engines powered by AI can be of assistance to businesses in the process of creating individualized product recommendations to clients based on the customers' unique requirements and previous purchases. It is possible to utilize an AI-powered chatbot to immediately answer to enquiries from customers and make product recommendations. With the help of virtual assistants powered by AI, customers can get assistance locating the precise things they are looking for in the store.

Chapter 3: Methodology

Research Design

The study process has several steps, and each one explains how to gather, analyze, and evaluate information from different sources. There is a strong link between how the study was done and how reliable the results were. So, the investigation was done using an exploratory research strategy, which turned out to be very helpful because it allowed the researcher to use different ways to collect and analyze data, making it easier to come up with useful results.

Research Framework

Because raw data collection is so important to this study, quantitative research methods are often used. Using a survey questionnaire, the quantitative research method collects information from employees in global business organizations.

Research Approach

The study was planned by putting together a list of dependent and independent factors that tell us how to choose a framework that will help us reach our goals and objectives (Lee & Tajudeen, 2020).

Operationalization of the Variable

It can be said that using surveys can make it easier to gather information. Researchers can get information about how people use business tools by using this method of collecting data. To get results that match the study's goals and aims, it's important to use the right methods and techniques when analyzing poll questionnaire data. Also, researchers have chosen to use the Statistical Package for the Social Sciences (SPSS) to collect first-hand information through survey forms. This tool can show results in a table style, which makes it easier to figure out what the results mean.

POPULATION SAMPLE SIZE

The sample conditions set a specific limit that will be used to help choose between applicants. In this study process, the criteria for sampling are people who have a lot of experience and knowledge with business solutions that aim to improve performance. It is expected that using probability sampling to choose participants based on certain factors will be effective.

Data Collection

Primary data collection will be used. When incorporating primary and secondary data from diverse sources, it is imperative to consider ethical considerations throughout the research endeavor

Data Analysis

The data will be analyzed with the help of SPSS

Conclusion

. In order to maintain the integrity of a study and protect the privacy of participants, researchers must adhere to appropriate ethical guidelines. In this study, the researchers employed the principles outlined in the Data Protection Act 2018, which articulate each ethical obligation in an assertive manner. As a result of this legislation, individuals with expertise and the individuals who provide them with information may potentially safeguard their privacy. In order to address issues related to participation, a consent-based approach would be implemented to ensure that participants are not required to take any action.

References

Albahri, A. S., Alnoor, A., Zaidan, A. A., Albahri, O. S., Hameed, H., Zaidan, B. B., ... & Yass, A. A. (2022). Hybrid artificial neural network and structural equation modelling techniques: a survey. Complex & Intelligent Systems , 8 (2), 1781-1801.

Alwi, S., Salleh, M. M., Abu, M., Ismail, A. F., Abbas, M. S., & Fadzilah, A. H. H. (2023, May). Concept of Integration of Blockchain and Artificial Intelligence. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1160-1163). IEEE.

Berdiyeva, О., Islam, M. U., & Saeedi, M. (2021). Artificial Intelligence in Accounting and Finance: Meta-Analysis. International Business Review , 3 (1), 56-79.

bin Abdul Lasi, M., Halabi, K. N. M., Jantan, A. H., & Azahari, M. H. (2021). Marketing technologies and its effect towards online purchasing behaviour of fashion consumers in malaysia. Review of International Geographical Education Online , 11 (12), 908-916.

Lee, C. S., & Tajudeen, F. P. (2020). Usage and impact of artificial intelligence on accounting: Evidence from Malaysian organisations. Asian Journal of Business and Accounting , 13 (1).

Lee, K., Azmi, N., Hanaysha, J., Alzoubi, H., & Alshurideh, M. (2022). The effect of digital supply chain on organizational performance: An empirical study in Malaysia manufacturing industry. Uncertain Supply Chain Management , 10 (2), 495-510.

Nawi, N. C., Al Mamun, A., Md Nasir, N. A., & Rahman, M. K. (2023). Analyzing customer acceptance of the internet of things (IoT) in the retail industry. Journal of Ambient Intelligence and Humanized Computing , 14 (5), 5225-5237.

Rahman, M., Ming, T. H., Baigh, T. A., & Sarker, M. (2021). Adoption of artificial intelligence in banking services: an empirical analysis. International Journal of Emerging Markets .

Wong, L. W., Tan, G. W. H., Ooi, K. B., Lin, B., & Dwivedi, Y. K. (2022). Artificial intelligence-driven risk management for enhancing supply chain agility: A deep-learning-based dual-stage PLS-SEM-ANN analysis. International Journal of Production Research , 1-21.

Yeo, S. F., Tan, C. L., Kumar, A., Tan, K. H., & Wong, J. K. (2022). Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry. Technological Forecasting and Social Change , 177 , 121551. You Might Also Like:

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