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The customer relationship management (CRM) technology adoption process in small- and medium-sized enterprises (SMEs) is an under-researched area and the purpose of this paper is to extend the knowledge and offer greater understanding of the CRM adoption process through an empirical study in the USA.

In this study it is hypothesized that the likelihood of CRM technology being adopted is dependent on management characteristics, organizational characteristics and management's perception of CRM technology. To investigate the proposed model a survey of SMEs in the retail, manufacturing and services sectors was conducted in Southern California, USA.

The results indicate that management characteristics significantly influence a firm's perception of CRM technology specifically innovativeness and positive attitude to CRM. Organizational characteristics such as the employee, information technology (IT) resources, a firms’ innovativeness influence the likelihood that CRM technology will be adopted and the extent to which CRM technology will be implemented.

First, the industries focused on were in retail, manufacturing and services. Second, the sample was geographically specific to Southern California. Third, the sample size in this study was relatively small, although it is within the testable range. Finally, only one respondent was surveyed from each firm.

Management regardless of gender, age or education level, must be supportive, innovative and have a positive attitude towards the new IT application, as positive perception will likely to lead to decision to adopt. In addition, there must be innovation within the organization and the firm must have the ability to absorb knowledge and to use it. There must be an availability of IT resources, both infrastructure and skills to support the change.

The results of this study have implications for CRM adoption in SMEs. More importantly, they suggest a framework which demonstrates the necessary linkage between organizational characteristics and CRM adoption process.

The aim of this paper is to use an innovation decision process to examine CRM technology adoption in small to medium-sized enterprises and its intrinsic link to the nature of the organisation and the individuals within it.

A survey was administered to SMEs in Southern California to measure the organisational characteristics, specifically management characteristics, employee characteristics, IT resources and firm characteristics. The perception of CRM, decision to adopt CRM, and extent of CRM implementation were also measured. Previously validated instruments were used where required. The data were analysed using multivariate and logistic regression.

The results indicate that management's innovativeness affects the firm's perception of CRM systems, but age, education and gender do not. The decision to implement a CRM system is influenced by management's perception of CRM, employee involvement, the firm's size, its perceived market position, but not the industry sector. However, the number and types of CRM features implemented are affected by management's perception of CRM, employee involvement, the firm's size, the industry sector, but not its perceived market position.

This study is specific to Southern California and the sample size is relatively small, although sufficient for this analysis. The study should be replicated in more diverse geographic settings with a larger sample.

The study provides evidence of the need for management to be supportive of innovation and technology, to evaluate the available resources (IT knowledge, skills, infrastructure) within the organisation, to recognise the importance of employees' contributions, and to be aware of the features appropriate to their company's size and industry sector before undertaking CRM technology adoption.

The findings from this study extend the understanding of CRM adoption in SMEs and help in building a greater understanding of the factors associated with such adoption. It will be of great value to owners/managers in SMEs who are considering adopting CRM.

The aim of this research is to gain a clearer understanding of information technology (IT) adoption in small and medium‐sized enterprises (SMEs) by analysing and contrasting the current literature. Whilst describing how and why SMEs acquire IT, the paper also seeks to highlight the enablers as well as the inhibitors that influence the adoption process.

The method was a review of literature including empirical research and case studies related to IT adoption from various databases such as Business Premier, Science Direct, JStor and Emerald Insight. Supporting material was accessed from reference books regarding similar concepts and theories.

The literature suggests that SMEs adopt IT for many reasons. In general, the majority of the changes result from pressures from both internal and external sources. In addition to these drivers, there are factors that influence the process either directly or indirectly. Based on these different perspectives the paper proposes a conceptual framework that is composed of those perspectives that are relevant to the adoption of IT in SMEs.

This conceptual framework for the IT adoption process is based on the existing literature. It is open to and requires empirical testing to determine its relevance and validity in a practical setting.

The paper demonstrates the process of IT adoption in SMEs by combining perspectives from the literature. The framework will help adopters gain a practical overview of the IT adoption process in SMEs.

Customer relationship management (CRM) is an information system that tracks customers' interactions with the firm and allows employees to instantly pull up information about the customers such as past sales, service records, outstanding records and unresolved problem calls. This paper aims to put forward strategies for successful implementation of CRM and discusses barriers to CRM in e‐business and m‐business.

The paper combines narrative with argument and analysis.

CRM stores all information about its customers in a database and uses this data to coordinate sales, marketing, and customer service departments so as to work together smoothly to best serve their customers' needs.

The paper demonstrates how CRM, if used properly, could enhance a company's ability to achieve the ultimate goal of retaining customers and gain strategic advantage over its competitors.

The purpose of this paper is to develop a conceptual framework to check if an organization is ready to adopt an AI-integrated CRM system. The study also analyzes different situations which can provide a comprehensive check list in the form of indicators that could provide a signal indicating whether the organization is ready to adopt an AI-integrated CRM system by capturing actionable and appropriate data.

The paper is a general review, and appropriate literature has been used to support the conceptual framework.

The key findings of this study are the different indicators that make up the conceptual framework. This framework can help organizations to check at a glance whether they are ready to adopt AI-integrated CRM system in their organizations. Specifically, it has been identified that different approaches are needed to tackle various types of customer data so that those may be made fit and actionable for appropriate utilization of AI algorithms to facilitate business success of an organization.

The paper has elaborately discussed the different approaches to be undertaken to calibrate and reorient the various kinds of actionable data and the contemplated challenges one would face in doing so. This would help the practitioners that how the data so captured can be made fit for action and utilization toward application of AI technologies integrated with existing CRM system in an organization.

This study is claimed to be a unique study to provide a conceptual framework which could help arranging and rearranging of captured data by an organization for making the data fit and ready for use with the help of AI technologies. This successful integration of AI with CRM system can help organizations toward taking quick and automated decision-making without much intervention of human beings.