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The purpose of this paper is to model the relationship between student performance, student attitudes, and computer laboratory environments.

Data were collected from 234 college students enrolled in courses that involved the use of a computer to solve problems and provided the laboratory experience by means of formal closed laboratory classes. The a priori proposed model that student performance can be explained by perceptions of the computer laboratory environment and attitudes towards computer was tested using structural equation modeling.

The proposed model was determined to fit the data reasonably well. These results indicate that student performance scores can be explained by perceptions of the computer laboratory environment and attitudes toward computers.

The theoretical and practical implications of the model concerning student performance within the framework of educational management are discussed.

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 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 purpose of this paper is to examine the factors associated with franchisors going public using signaling theory. Listing on the stock market is a sign that the business concept has reached a threshold level of acceptance and success. To increase the relevance of this study to practitioners, the authors focus on franchising-specific controllable variables.

This study uses a sample of 2,134 franchisors from US drawn from a survey by Entrepreneur magazine during the years 2015–2016. Binominal logistic regression models are used for analysis of the data.

Findings indicate that time to franchise, international operations, franchise association affiliation, disclosure and extent of top management commitment are factors positively related to the likelihood of a franchisor being publicly listed.

Study findings are based on a sample of franchisors from North America, where financial markets are well developed, and due caution should be exercised before generalizations are made to other contexts. A major implication of this study is that signaling theory may provide an important supplement to the already well-entrenched resource-scarcity and agency theoretic explanations in franchising research.

While signaling theory is growing in importance in the franchising literature, this study is the first to uncover the relationship between company signals and initial public offering.