Analysis of the Effect for Customer Relationship Management on Digital Enterprises: Using Agent-Based Modeling

Introduction

Preserving a close relationship with customers and fulfilling their expectations are key issues in today's competitive market to promote business (Anshari et al., 2018). On the other hand, digital shopping in the field of electronic commerce is defined as shopping with the help of Internet technologies and tools. The successful digital shopping requires that sellers can create more economic benefits for customers than the traditional way. It is not enough to simply display products on a beautiful site, and use attractive photos (Zhang, 2017; Duarte et al., 2018).

Investigating the effect of the Internet on businesses in today's world is a part of the growing body of digital marketing and business literature. However, despite extensive research on the impact of the Internet on business, there is little knowledge of the complex relationship between digital enterprises and the electronic markets function (Thakur, 2018; Duarte et al., 2018). Although several studies have been conducted in the field of customer satisfaction and loyalty in business, the impact of standardization and customization on these variables has received less attention (Piccoli et al., 2017).

The customer not only provides the main capital and financial resources of the business through deposits, but also is the buyer of all business services and therefore, the customer is very important to the business. As having customer guarantees the business survival, customer relationship is a key element in maintaining a stable and successful relationship with the customer and the success of small and medium enterprises (Ritter & Geersbro, 2018). On the other hand, customers’ satisfaction with digital shopping and fulfilling their needs play a vital role in meeting business goals (Pozza et al., 2018). In other words, customer satisfaction with digital shopping services is the key to business growth (Ballestero et al., 2018). Hence, it is necessary to create an integrated departments of customer affairs in today's large business (Vanhanen et al., 2018).

The need for more accurate, faster and less risky decisions on the one hand and the complexity of issues, the diversity of decision-making criteria and the multiple choice of options on the other hand are caused by the current intense economic competition and increasing growth of technology (Fernández et al., 2018). Hence, more serious decision-making process is needed than ever before, and newer scientific techniques have been proposed in this regard. Customer relationship management systems clearly define all services and facilities and bring many benefits, including providing continuous information and services, reducing costs and increasing satisfaction. As a strategy of the process of gaining customers’ data and their needs, customer relationship management causes maximizing profitability, income, customer satisfaction with digital shopping services, through customer selection and adopting behaviors that lead to customer satisfaction, customer focus, and closer relationship with them (Ritter & Geersbro, 2018; Ballestero et al., 2018).

On the other hand, a “high volume of data” is generated on a daily basis by expanding and prevailing the Internet. Therefore, a system with high processing power is needed for processing this amount of data because current common systems are not capable of processing such large volumes of data, and on the other hand, the provision of high-processing systems is not feasible for business due to high costs. Extracting repetitive patterns over the past two decades, including the collection of repetitive samples from transactions and the sequence of repetition sequences, has attracted the interest of several research.

Indeed, factors such as acceptance of product price, consumers' advertising susceptibility, consumers' following tendency, customer motivational performance, price sensitivity, price of commodity, quality sensitivity, quality of commodity, have a special impact on consumer’s purchasing behavior (Zhang, 2017; Huiru et al., 2018).

The present study aims to investigate and analyze the effect of CRM dimensions on digital shopping in a digital store using statistical analysis and finally agent-based modeling (ABM) methodology. The dimensions of CRM examined in this study include the quality of information display and representation of CRM system, customer satisfaction with digital shopping services, the quality of optimal use of CRM system information resources, and the economic profitability of CRM system. Also, digital shopping stages include product review, product selection, payment, and receipt.