Customer Relationship Management Systems Research Articles

Understanding salespeople's resistance to, and acceptance and leadership of customer-driven change

Salespeople's responses to change have been extensively examined in the context of sales literature, sales force automation (SFA), customer relationship management (CRM) systems, and other sales technologies. The majority of sales technology changes were typically organization driven. In contrast, during the COVID-19 pandemic, salespeople faced changing sales processes that were increasingly customer-driven. We seek a deeper understanding of salespeople's acceptance of customer-driven change and interview 38 sales professionals to enhance our understanding of salespeople's perceptions and behaviors. Our findings show an increase in the use of technology, increased marketing-sales integration, and shifts in sales processes and organizations. We identify three profiles of salespeople: those that resist change, accept change, and lead change. We find differences in salespeople driven by their perceptions of customer environments and their capabilities, sales management function, and organization factors relevant in defining attitude toward change. We consequently derive implications for theory and practice.

Implementing a digital public health project - lessons learned?

Abstract The demand for the digitalisation of public health has been ongoing for more than a decade. The COVID-19 pandemic was the tipping point that accelerated the ideation, implementation, and scale-up of such public health projects. Despite the well-needed push, the same challenges that face every similar implementation will nonetheless be the same if not accentuated. The scope of the presentation is to highlight the difficulties and facilitators that such implementations and evaluations bring forward. We will also see what we can learn as public health professionals to ensure that present and future information systems are well-planned. We have to ensure that they do not succumb to the pressure of well-intended stakeholders who are yearning for such solutions to help their business workflows. This presentation will be enhanced with the lessons learned from implementing, monitoring, and following up on Malta's national contact tracing app and Customer Relationship Management systems based on Microsoft Dynamics 365 technologies that tackled the Test, Track and Trace workflows that were integral to the COVID response in Malta.

A Modular Approach to Customer Relationship Management (CRM) Systems

Customer loyalty within the service industry is critical. A customer relationship management (CRM) system allows for good management of all the transactional data and interactions between the customer and the organization. Readily available CRM systems offer a fixed collection of features in their application packages. Through our project, we aim to provide customizable features for individual organizations. Different modules were created for various needs identified in the CRM markets: leads display screens, email/website leads integration, statistical display, social media integrations, and email marketing. CRM was implemented using a web application deployed on the organization’s server, which has helped 4 organizations with 1000+ leads collectively till now.

Evaluating Electronic Customer Relationship Management System Success: The Mediating Role of Customer Satisfaction

This study evaluated the relationships among variables in electronic customer relationship management (e-CRM) success. The purpose of this paper is to examine the effect of technological readiness, privacy, COVID-19, customer pressure, trust, level of service quality, and customer satisfaction. Quantitative research methods were applied in examining the causal associations among the primary variables of the study. We used a sample approach called purposive sampling. Data was obtained from 390 completed questionnaires collected from employees, who took part in CRM technology activities, working in Jordanian firms. Data was analyzed via AMOS software version 22, and hypotheses were examined by applying structural equation modelling (SEM). Results revealed that technological readiness, COVID-19, customer pressure, and customer satisfactions had a positive effect on e-CRM success system. Moreover, the study showed that technological readiness, privacy, and level of service quality positively affected customer satisfaction. Additionally, the mediation of customer satisfaction on the association between trust and success of e-CRM system, and also between level of service quality and e-CRM system success, was demonstrated. Practical implications: In practice, this study can help managers and practitioners in implementing e-CRM systems. Moreover, it can drive further empirical studies on the relations among technological readiness, privacy, COVID-19, customer pressure, trust, and level of service quality, besides customer satisfaction. Only few studies had looked into the variables in the success of e-CRM system, in emerging industries of developing countries, specifically, among technological readiness, privacy, COVID-19, customer pressure, trust, level of service quality, and customer satisfaction. These gaps were addressed in this study. The current model is also relatively constrained, so it may be expanded in further studies. For instance, the construct of culture might be incorporated to the model to make it more thorough in its examination of the topic at issue.

Electronic Customer Relationship Management (E-CRM) Berbasis Web Pada Nada Salwa Tour & Travel Jambi

Nada Salwa Tour & Travel is one of the service businesses engaged in travel. Where the current system has problems in getting new customers, improving customer relationships, and retaining customers. Based on the existing problems, Nada Salwa Tour & Travel requires a web-based Electronic Customer Relationship Management (E-CRM) system that can help Nada Salwa Tour & Travel and its customers establish good relationships. The purpose of this research is to analyze the service relationship between the company and its customers and to design a prototype of a web-based Electronic Customer Relationship Management (E-CRM) system to create a better relationship between the company and its customers through features on the website. The author does object-oriented design including Use Case diagrams, activity diagrams, class diagrams, display designs, database structure tables. The result of this research is a prototype of a web-based E-CRM system that can help solve the problems that exist in Nada Salwa Tour & Travel.

Efficient customer relationship management systems for online retailing: The investigation of the influential factors

AbstractIn business processes, gaining customer satisfaction is vital for online retailing. In this way, it is necessary to identify the important factors for attracting and retaining customers in online retailing. Many factors are involved in efficient customer relationship management (CRM) systems. Their efficient implementation needs a deep focus on key customers, proper organization, knowledge management, technology, market, sales, ordering, support, and many other factors. Therefore, this paper examines the effective factors (including innovation management, market knowledge, competitive intelligence, entrepreneurship management, stakeholder management, project management, and business project management) on the efficiency of the CRM systems for online retailing. The data were collected from Digikala employees in Iran. Based on Morgan's table (Table A2 (Appendix)), 248 samples were randomly selected, and questionnaires were sent to employees, where 234 were fully answered. Research data and assumptions were evaluated using SPSS and PLS software. Research findings showed that innovation management (ß = .390, t = 6.426, p < .001), market knowledge (ß = .296, t = 4.864, p < .001), and competitive intelligence (ß = .115, t = 2.190, p < .005) directly impact the efficient CRM systems for online retailing. Stakeholder management (ß = .283, t = 9.713, p < .001), project management (ß = .229, t = 5.458, p < .001), and business project management (ß = .544, t = 11.351, p < .001) are also effective through the mediator variable of entrepreneurial management (ß = .143, t = 2.314, p < .005) on the efficient CRM systems for online retailing.

Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM

To create a personalized E-CRM recommendation system, the electronic customer relationship management system needs to investigate low accuracy and lack of personalization through applied hybrid recommendation system techniques such as fuzzy and AHP. The main purpose of this research is to enhance the accuracy and deep understanding of common recommendation techniques in E-CRM. The fuzzy and AHP techniques have been used in the current study to the available information of objects and to extend recommendation areas. The findings indicate that each of these strategies is appropriate for a recommendation system in a technological environment. The present study makes several noteworthy contributions to the fuzzy Analytic Hierarchy Process (AHP) and has the maximum accuracy of any of these approaches, with 66.67% of accuracy. However, AHP outperforms all others in terms of time complexity. We advocate the concept and implementation of an intelligent business recommendation system dependent on a hybrid approval algorithm that serves as a model for E–CRM recommendation systems. This recommendation system's whole design revolves on the hybrid recommendation system. The systems additionally incorporate the recommendation modules and the recommendation measurement updating framework. The recommendation modules include the formulation and development of material recommendation algorithms, element collaborative filtering recommendation algorithms, and demography-based recommendation algorithms.

A Comparative Analysis of the Acquisition Transaction of Management Information Systems through Virtual and Face-to-Face Negotiations—The Perspective of Green IT Industry in Poland

The COVID-19 pandemic that began in 2020 has significantly impacted businesses, regardless of size or industry. The hybrid and remote working models have moved all meetings with potential and existing suppliers to an online environment. This also applies to small- and medium-sized enterprises (SMEs), which have had to adapt themselves to the new situation and implement the solutions necessary to survive on the market. On the other hand, clients have become more aware of the environment and its changes. Customers are trying to be more eco-friendly, by choosing and moving towards Green IT. Thus, this needs to be considered. The acquisition of management information systems (MIS) in the pandemic era is based only on virtual meetings. The main goals of this paper were the identification of the changes in the negotiations caused by the COVID-19 pandemic, the transformation of this process into virtual environment, discussion of the possibility of using Green IT in addition to Management Information Systems, and the changes caused by the pandemic. The article was prepared based on the results of qualitative research using the case study method. The comparative analysis includes purposely selected cloud-based Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems’ acquisition processes, presented from the clients’ perspective. The research was conducted in 2021, based on the authors’ practical experience, and presents four cases. This research illustrates the negotiations concerning an acquisition transaction pre-pandemic and during the pandemic. Finally, the conclusions and main differences caused by the pandemic in the acquisition transaction process of management information systems (MIS) are presented.

Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions

Customer churn describes terminating a relationship with a business or reducing customer engagement over a specific period. Customer acquisition cost can be five to six times that of customer retention, hence investing in customers with churn risk is wise. Causal analysis of the churn model can predict whether a customer will churn in the foreseeable future and identify effects and possible causes for churn. In general, this study presents a conceptual framework to discover the confounding features that correlate with independent variables and are causally related to those dependent variables that impact churn. We combine different algorithms including the SMOTE, ensemble ANN, and Bayesian networks to address churn prediction problems on a massive and high-dimensional finance data that is usually generated in financial institutions due to employing interval-based features used in Customer Relationship Management systems. The effects of the curse and blessing of dimensionality assessed by utilising the Recursive Feature Elimination method to overcome the high dimension feature space problem. Moreover, a causal discovery performed to find possible interpretation methods to describe cause probabilities that lead to customer churn. Evaluation metrics on validation data confirm the random forest and our ensemble ANN model, with %86 accuracy, outperformed other approaches. Causal analysis results confirm that some independent causal variables representing the level of super guarantee contribution, account growth, and account balance amount were identified as confounding variables that cause customer churn with a high degree of belief. This article provides a real-world customer churn analysis from current status inference to future directions in local superannuation funds.

Rancangan Arsitektur Sistem Informasi E-Customer Relationship Management Menggunakan Metode Enterprise Unified Process

Customer Relationship Management (CRM) is a management that discusses the handling of the relationship between customers and the company. In the Power Kitchen where one of the company's equipment in the city of Surabaya has problems related to handling complaints from customers. So we need a CRM system to build relationships with customers. Therefore, the Power Kitchen company needs a CRM system to make it easier for companies to handle complaints from customers. This research uses the Enterprise Unified Process method which is a framework for the software process used. This research has resulted in the form of recommendations for system architecture models to achieve company goals and service relationships between companies and customers.

DEEPER UNDERSTANDING OF CUSTOMER NEEDS UTILIZING CUSTOMER RELATIONSHIP MANAGEMENT

Customer relationship management (CRM) helps firms adjust goods and services to customer needs. This article attempts to analyze narratively how a company's ability to maintain customer loyalty affects its financial health. Businesses must cultivate client loyalty and retention. Customer service may distinguish a company's offerings, keep consumers delighted, and improve sales and profits. Companies with loyal, satisfied customers do well. Loyal clients are inclined to speak positively about the firm and may try to recruit new customers. Customer satisfaction helps both the organization and the consumers. Businesses provide additional incentives and prizes for recurrent purchases to maintain consumer loyalty and reliability. This article finds that CRM is one of the most significant business tools since it helps companies better understand their customers and establish effective CRM systems. A customer-driven company strategy may be a response to mass advertising. Businesses respond to each customer's needs and preferences. CRM is the practice of a company actively pursuing customer relationships. Existing customers must be kept. CRM aims to enhance profitability and sales while also increasing a company's reputation with customers. Customer and corporate advantages will be explored. Repeat consumers are more likely to get long-term relationship advantages. Customers who like an organization's goods and services spend a lot of money on them.

Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods

The diversity of data collected on both social networks and digital interfaces is extremely increased, raising the problem of heterogeneous variables that are not often favourable to classification algorithms. Despite the significant improvement in machine learning (ML) and predictive analysis efficiency for classification in customer relationship management systems (CRM), their performance remains very limited by heterogeneous data processing, class imbalance, and feature scales. This impact turned out to be more important for simple ML methods which in addition often suffer from over-fitting. This paper proposes a succinct and detailed ML model building process including cross-validation of the combination of SMOTE to balance data and ensemble methods for modelling. From the conducted experiments, the random forest (RF) model yielded the best performance of 0.86 in terms of accuracy and f1-scoreusing balanced data. It confirms the literature summary about this topic which shows that RF was among the most effective algorithms for customer predictive classification issues. The constructed and optimized models were interpreted by Shapley values and feature importance analysis which shows that the “age” feature was the most significant while “HasCrCard” was the less one. This process has proven effective in bridging previously reported research gaps and the resulting model should be used for supporting bank customer loyalty decision-making.

PECULIARITIES OF USING ERP- AND CRM-SYSTEMS FOR AUTOMATION OF ENTERPRISE MANAGEMENT

This publication is devoted to the problem of informatization and automation of management at the enterprise. The study found that the use of innovative systems is becoming increasingly popular in the Ukrainian market. Automation plays a crucial role in ensuring the growth of efficiency indicators of economic activity, but among domestic enterprises, there is a problem in choosing the use of a particular information system. This article describes the main advantages and disadvantages of ERP and CRM systems. Approaches to definitions are defined, and the concepts of ERP and CRM as methodologies of effective resource planning and system of automation of interaction with clients are revealed. A comparative analysis of ERP and CRM systems is carried out. The main functions of CRM systems are studied, among which: are the formation of a single information client base; working time management; optimization of communications within the company; sales planning. The place of the customer in the customer relationship management system is determined. The main modules of the ERP system are analyzed, namely: finance, personnel, sales, procurement, production, logistics, service, research and development, and assets. A detailed description of the functional solution when using the resource management system is given. The main tools of ERP and CRM systems are identified. As a result of the analysis of the modern market of information systems the main suppliers of software products and their weight in the given market segment are defined. A number of software products of ERP and CRM systems popular in Ukraine have been studied. The level of implementation of CRM systems by industry structure is determined. It is established that the maximum result from the implementation of CRM systems is possible only when they are implemented together with the integrated internal ERP system.

Using Class Membership based Approach to Improve Predictive Classification in Customer Relationship Management Systems

Recently, the diversity of data collected on both social networks and digital interfaces is extremely increased. This diversity of data raises the problem of heterogeneous variables that are not favourable to classification algorithms. Although machine learning and predictive analysis have significantly improved the efficiency of the classification in customer relationship management (CRM) systems, their performance remains very limited by heterogeneous data processing. In this paper, we propose a new predictive classification approach well adapted for targeting actual CRM systems. Our approach consists of preprocessing each type of feature and constructing a reduced array. From this reduced array, the class membership computations become very faster and perform the predictive targeting of a new instance great accurately. The results of the experiments carried out on four types of data from the CRMs showed that the proposed algorithm is a good tool for strengthening these systems not only to optimize their loyalty actions but also to efficiently acquire new customers.

Implementation of Customer Relationship Management (CRM) at Giant Supermarket Pagar Alam Lampung WEB-Based

Giant Supermarket Pagar Alam Lampung is a company engaged in the sale of goods in Bandar Lampung. In marketing its products, it is still done by distributing sales catalogs and advertisements, so that many consumers cannot find out information about the stock of goods available at Giant Supermarket Pagar Alam Lampung. Consumers must come directly, if consumers want to get information or want to make purchases of goods, and do not improve sales and marketing strategies. CRM is a type of management that specifically discusses the theory of handling the relationship between a company and its customers, with the aim of increasing the value of the company in the eyes of its customers. CRM design will be discussed about ordering goods, purchase transactions, and service to consumers. The purpose and benefits of this research is to implement CRM in order to improve information services and customer satisfaction for Giant Supermarket Pagar Alam Lampung. The results of this study are a Customer Relationship Management (CRM) system in sales at Giant Supermarket Pagar Alam Lampung, this system can improve the company's service to customers through the sales provided, and this system can display information on goods sold, and can facilitate Giant Supermarket Pagar Alam Lampung in sales reporting.

Query Execution Time Analysis Using Apache Spark Framework for Big Data: A CRM Approach

Customer Relationship Management (CRM) is a systematic way of working with current and prospective customers to manage long-term relationships and interactions between the company and customers. Recently, Big Data has become a buzzword. It consists of huge data repositories, having information collected from online and offline resources, and it is hard to process such datasets with traditional data processing tools and techniques. The presented research work tries to explore the potential of Big Data to create, optimise and transform an insightful customer relationship management system by analysing large amount of datasets for enhancing customer life cycle profitability. In this research work, a dataset, “Book Crossing” is used for Big Data processing and execution time analysis for simple and complex SQL queries. This research tries to analyse the impact of data size on the query execution time for one of the majorly used Big Data frameworks, namely Apache Spark. It is a recently developed in-memory Big Data processing framework with a SPARK SQL module for efficient SQL query execution. It has been found that Apache-Spark gives better results with large size datasets compare to small size datasets and fares better as compared to Hadoop, one of the majorly used Big Data Frameworks (based on qualitative analysis).

Evaluating breast biopsy practice and breast biopsy marker utilisation in the clinical setting.

Breast Screen Australia and Breast Screen Aotearoa guidelines recommend breast biopsy marker (BBM) use in indicated patients. This study aims to evaluate breast biopsy practice and BBM utilisation by modality. An online survey was disseminated to radiologists who identified 'breast imaging' as their area of practice in the Royal Australian and New Zealand College of Radiologists (RANZCR) customer relationship management system. Survey questions addressed participant demographics and factors relating to BBM use. Most respondents (72%) place between 1 and 4 BBMs per week. Almost all (99%) respondents perform ultrasound-guided biopsy of the breast or axillary nodes, with 85% performing stereotactic or tomosynthesis-guided breast biopsy and 27% performing MRI-guided breast biopsy. BBM utilisation differs by modality, with 97% respondents always placing a BBM post-MRI-guided breast biopsy, 50% always placing a BBM post-stereotactic-guided biopsy and 3% always placing a BBM post-ultrasound-guided breast biopsy. Almost all radiologists perform breast biopsy using ultrasound, stereotactic/tomosynthesis or MRI guidance. BBM utilisation varies by modality, with 72% of respondents placing between 1 and 4 clips per week. Reasons for placing or not placing BBM aligned with prior studies. This is the first study to evaluate the number of breast biopsies performed by radiologists on a weekly or monthly basis, providing a useful platform for comparison in the local setting.

AI and digitalization in relationship management: Impact of adopting AI-embedded CRM system

The purpose of this study is to determine the impact of adopting a artificial intelligence-embedded customer relationship management (CRM) system for business-to-business relationship management. After reviewing the literature and considering the theory, a conceptual model was developed. The model was validated using the PLS-SEM technique with 312 responses from 14 firms in the B2B context. The study finds that an AI-embedded CRM system has a significant positive impact towards B2B relationship satisfaction and firm performance. Also, the study highlights that there is a negative impact of the moderator ‘technology turbulence’ on the relations of ‘automated decision making’ and ‘operational efficiency’ with ‘B2B relationship satisfaction’, whereas there is a positive impact of moderator ‘leadership support’ on ‘B2B relationship satisfaction’ and ‘firm performance’. There is presently no study on the impact of AI-CRM in the B2B context. Also, the study contributes to the existing literature by incorporating the moderator impact of ‘technology turbulence’ and ‘leadership support’ in the context of AI-embedded CRM systems for B2B relationship management.

DEVELOPMENT AND IMPLEMENTATION OF CUSTOMER RELATIONSHIP INFORMATION MANAGEMENT SYSTEM

The article analyzes the state of the problem of developing and implementing a customer relationship management system. Features of the concept of "customer relationship management system" are considered. The authors performed an analysis of the developed system and its implementation in the field of professional development of IT professionals. Possibilities of intensification of information process development in the field of professional development of IT specialists are shown and analyzed. A database has been developed to solve the problem of software in the field of professional development of IT professionals.

INFORMATION TECHNOLOGIES IN SYSTEM OF CUSTOMER RELATIONSHIP MANAGEMENT

In article CRM systems are analyzed. The concept and principles of their work are presented. Process of introduction of CRM systems is analyzed. In addition, the article presents the concept of CRM-system. In modern business, the need to automate various processes has become commonplace. It is becoming increasingly difficult to keep warehousing or accounting without the use of specialized software. Sales representatives use special programs to place and send orders to the office via tablet or mobile phone, quite a large number of orders come from the site in the form of ready-to-process documents. However, customer relationships, especially in small and medium-sized businesses, are often conducted without the introduction of automation and sufficient attention to accounting. At the same time, each sales manager works as he sees fit, records calls, other types of interaction with customers at his own discretion, or refuses to record at all. way out of this situation – automation and standardization of customer relationship management, ie the introduction of CRM-system. Customer Relationship Management (CRM) is software that helps you successfully monitor, organize, and schedule customer service. CRM-systems help sales departments by telling managers what to do: respond to a new request, call the customer, plan the transaction. Robots themselves send emails and text messages to customers when the application is in the desired status, automatically launch ads and more. CRM allows you to not lose orders from new customers, systematize the work of managers and control it, find points for optimization and further growth of the company. CRM system standardizes and automates processes in the sales department.