Competition, Strategy, and Innovation

The Impact of Trends in Business and the Consumer World

Rafał Śliwiński, Łukasz Puślecki, Rafał Śliwiński, Łukasz Puślecki

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000476996
• Edition: 1
• Topic: Betriebswirtschaft
• Subtopic: Internationale Wirtschaft

Understanding the latest trends and technologies and their impact on enterprises, organizations or state administrations is essential to successfully develop a business in the age of Industry 4.0.

This book presents a unique selection of topics and offers the reader an understanding of the implications of the newest technologies such as Artificial Intelligence (AI), Internet of Things (IoT), Augmented Reality (AR) and new trends like social media and sustainable competitiveness in business. It presents the impact of the newest trends on businesses, consumers, and the result on the economy. Contributions showcase the technical perspective of new technologies and provides an innovative and enriching perspective on the implementation of AI in e-commerce and the developmental barriers it can create, modern social media usage in enterprises, the newest trends in innovation management, sustainable competitiveness in the business context, the influence and effect of augmented reality, and the privacy problem of Internet of Things to consumers. This book illustrates how to develop innovation cooperation between business, academia and public institutions through the example of biopharmaceutical industry.

It will be of value to researchers, academics, professionals, and students in the fields of economics, management, international business.

Part I Strategy and Competitiveness

1 Artificial Intelligence: A Prerequisite for Competitive Advantage in E-Commerce

Rafał Śliwiński

DOI: 10.4324/9781003204343-1

Introduction

The subject of artificial intelligence (AI) has been known for decades. However, only in recent years has the emergence of the associated technologies, such as big data or the achievement of high-performance computer processors, influenced AI and its practical applications, leading to a spectacular victory for the computer (Google DeepMind) in 2016 on the Korean master, Lee Se-Dol, of the most difficult strategic game in the world, GO, and in 2014 on the Chinese world champion of GO, Kie Jie. Since then, the Google DeepMind algorithms have been improved several times (AlfaGo Lee, AlfaGo Master, AlfaGo Zero), and all the GO masters have been beaten by AI. Kie Jie’s post-defeat comment is highly telling; the seasoned player recounted that he had never before felt such psychological pressure during a game. This event opened the door for AI to enter the economic arena, showing the potential to replace lawyers, accountants, stock traders, and many other intellectual professions that have not been threatened by competition so far. It also paved the way for AI to penetrate e-commerce and traditional commerce. Thanks to AI, commercial solutions for acquiring new customers or increasing customer satisfaction with the purchasing process or with purchased items have been substantially improved, and it seems that traditional solutions in the field of marketing and sales techniques are not able to cope with modern AI solutions.

The literature on the subject quite selectively treats the areas of e-commerce and their links with AI. E-commerce firms engage in fierce competition with other e-commerce participants, and they also take up the fight against traditional trade stores, such as Walmart. The literature usually describes one aspect, but there is lack of broad overviews of solutions that will create a bigger picture of using AI to increase the competitiveness of e-commerce. For the above reasons, the purpose of this chapter is to show how an e-commerce company can increase its competitiveness through the use of AI. By grouping the benefits of using AI, we can help readers visualize the advantages a business can derive from this technology and how AI can strengthen or create a competitive edge. A scoping literature review was used to determine the scope of the body of literature (Munn et al., 2018). This type of review answers broad questions, especially in terms of issues that are still under-researched or at an early stage of research. The purpose of this scoping review is to provide an overview of the new methods of AI application to e-commerce with an in-depth analysis.

E-Commerce Competitive Advantage Thanks to AI

Retail e-commerce is expected to reach almost USD 6.5 billion globally in 2024, which is 55.5% more than in 2020 (Statista, 2021). In 2020, approximately 85% of all customer interactions were handled by AI, without human interference (Schneider, 2017). Furthermore, Servion predicts that by 2025, AI will handle 95% of all customer interactions (Nirale, 2018), including live phone calls and online calls, so realistic that it will be virtually impossible for customers to detect the bot. Commercial companies that are unable to prepare for this reality face serious risks of being left behind by their competitors. Prior research has confirmed a positive correlation between e-commerce and business performance, and the relationship between the use of modern technologies in e-commerce and positive business results (Jehangir et al., 2011; Syam & Sharma, 2018).

AI has made its way into e-commerce for good, and many researchers describe various aspects of this process (Kietzmann et al., 2018; Nadimpalli, 2017; Turban et al., 2018). Kumar et al. (2019) and Rossi (2016) describe ways AI helps customers by e.g. improving search results, helping buyers to understand their preferences, and serving as a personal assistant to shoppers. Many examples of AI in marketing are provided by Davis (2016), Davar (2018), and Venkatesan and Lecinski (2021). The use of chatbots in marketing is described by Mah (2016), among others. Salesforce’s AI Einstein Service facilitates sales transactions (Womack, 2016). Kohl (2016) describes the use of AI to boost customer engagement, which is particularly important since shopping is evolving to transactions that will take place without human interaction, with the use of technology, such as the Internet of Things (IoTs). IBM’s Watson AI is learning about people from their tweets. This will help companies predict consumer behavior, deciding what to offer and when (Russell, 2014). In general, AI is believed to have a big role in retailers’ future (Arthur, 2016).

The basic concept associated with AI is its ability to learn and, as a result, to innovate. Thanks to this skill, AI can find patterns of use of given products and, using accumulated knowledge that is often of a broader scope than their human counterparts, propose a creative innovation that meets the expectations of customers to a greater extent than before, and even propose a completely new solution that did not exist before, to a problem that human counterparts could not deal with. In addition, AI is better than humans at repetitive activities or activities that require patience. For this reason, in a trade where every customer expects to be served with enthusiasm and patience, AI alone can meet or surpass these customer expectations.

Another central concept in achieving a competitive advantage in trade thanks to AI is the network. An AI-powered network includes a group of subnets, supply chain networks, networks of Facebook customer accounts, purchase histories from trading partners, etc. These networks have at least five things in common. They consist of digital connections between network nodes, carry data, are shaped by increasingly powerful software algorithms, ignore traditional industry boundaries, and are becoming increasingly important to our economy and social system (Iansiti & Lakhami, 2020).

The competitive advantage in trade built thanks to AI can therefore be defined as, first, the ability to innovate based on the use of AI to improve the basic, useful properties of trade in the context of a product/service or process, and second, as the ability to shape and control networks based on the accumulation of quantities and the diversity of their transactions as well as using AI to analyze this data to capture key information that is used to expand business activities, both in scale and in scope. In the first sense, a competitive advantage means a better designed website or a well thought-out and effective purchase/sales process. It involves differentiation of products and services, adding features that give the firm an edge over the competition. A firm with competitive advantage thanks to AI sees a greater number of goods sold in a given period, a greater percentage of first-time buyers, increasing market share in trade in products of a given type, etc. In relation to sales management, the advantages of AI may include more effective sales analysis in terms of quantity, space, time, and connection with seemingly insignificant facts that a human would be unlikely to make. For instance, AI may associate an influx of arriving ferries with more customers for a beach goods store, quickly prompting a decision to increase store inventory and initiating a highly coordinated, strategic effort to maximize store sales. Such systems, capable of performing quick market analyses and choosing the proper course of action, allow firms to function better in the economic reality than they would with traditional analytics. Additionally, th...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Contents
• List of Tables
• List of Figures
• About the Contributors
• Strategy, Innovations, and Consumers Under the Influence of Megatrends
• Part I: Strategy and Competitiveness
• Part II: Consumer World
• Part III: Innovation
• Index