The Progress of Business Analytics and Knowledge Management for Enterprise Performance Using Artificial Intelligence and Man-Machine Coordination

The Progress of Business Analytics and Knowledge Management for Enterprise Performance Using Artificial Intelligence and Man-Machine Coordination

Qian Liu, Jiayi Li
Copyright: © 2022 |Pages: 21
DOI: 10.4018/JGIM.302642
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Abstract

This study aims to explore the integration of human-computer interaction (HCI) technology and platform ecosystem in artificial intelligence (AI) environment, thus providing a practical basis for the intelligent development of strategic management of platform ecosystem. With clothing e-commerce as an example, first, the business model of brand clothing is simply analyzed. Then, the fashion knowledge management method is adopted to build the fashion data warehouse. The platform intelligent clothing ecosystem is innovatively put forward through the research of business analytics and management mode of clothing e-commerce industry. The optimized genetic algorithm is used to solve the objective function of the model, and a flexible production scheduling model with multiple constraints and maximum cost-saving is established. Finally, the questionnaire results of voice interaction users are analyzed by HCI customer trust model.
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Introduction

The relationship among business ecosystems is similar to the interaction between biological and natural ecosystems. Enterprises should regard themselves as the constituent elements of the business ecosystem system (Rong et al., 2018). All the agents in the same business system will influence each other and form a complex and multi-faceted system through interaction. The system's main body includes enterprises, suppliers, government departments, operators, and stakeholders. Each participant has a very close relationship with the system, including its internal participants (Leminen et al., 2018; Lüftenegger et al., 2017). Small and medium-sized enterprises (SMEs) can gain benefits in the fierce market competition, suggesting that their ecological status differs from that of large enterprises. A dynamic process for enterprises to improve the niche in the business ecosystem is to compete with each other for ecological status (Banoun et al., 2016). In the same niche, two competing species cannot coexist for a long time. Niche is also the time and space position of all living things in the natural ecosystem, and technological niche and enterprise niche are crucial in the development of SMEs (Roundy et al., 2018).

Artificial intelligence (AI) is a technology making computers simulate human thinking processes and intelligent behavior. The principle of intelligence is realized through computers. Devices similar to human brain intelligence are obtained to enable computers to realize deeper applications (Lu et al., 2018). AI covers a wide range, including computer science, psychology, philosophy, and linguistics. It is almost all disciplines in natural science and social science, and its field has completely exceeded the scope of computer science. The relationship between AI and thinking science is the relationship between practice and theory. AI is at the technical application level of thinking science. It is to carry out logical thinking and consider image thinking and inspiration thinking so that AI can have a breakthrough development. Mathematics is also a basic science of many subjects, and it is involved in language and thinking. AI discipline also needs to use mathematical tools in the scope of standard logic and fuzzy mathematics. When mathematics enters the AI discipline, they can promote each other and develop faster (Raza & Khosravi, 2015; Zang et al., 2015). Human-computer interaction (HCI) technology in the AI field, such as interactive robots, has been applied in various fields, including medicine, military, and business. Shen et al. (2019) showed that the trend analysis of online to offline (O2O) development in different language regions was revealed through AI. HCI technology makes AI technology more humanized and improves its applicability in application fields (Rigas et al., 2014).

The development of science and technology promotes online shopping, bringing more convenience to the process of commodity exchange. More importantly, it greatly impacts consumers' shopping habits and changes people’s consumption behavior (Shen et al., 2018; Ding & Lu, 2017). E-commerce can be adopted to describe a place that uses different platforms for online shopping. As the media of e-commerce, the AI interactive design of the business website is a platform for building brand image, attracting users to browse the website, and cultivating customer loyalty (Zhao et al., 2017; Jahanshahi & Brem, 2017). However, there will be multiple problems accompanied by the convenience of interactive e-commerce in the AI environment, such as security and privacy, website stability, customer experience, and platform trust (Wan et al., 2018; Freathy & Calderwood, 2016).

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