Initial customer relationship system efficiency evaluation

2010 ◽  
Author(s):  
Regina Jasilionienė ◽  
Rima Tamošiūnienė
Keyword(s):  
Customer Relationship ◽  
Efficiency Evaluation ◽  
System Efficiency

scholarly journals Improvement Social Customer Relationship for Community Enterprise through using Gamification

2020 ◽  
Vol 9 (4) ◽  
pp. 610-614
Keyword(s):  
Social Media ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Efficiency Evaluation ◽  
Acceptance Criteria ◽  
Community Enterprises

There are many types of community enterprise products in Thailand but not yet widely known, resulting in not many customers. In some cases, the existing customers have the opportunity to disappear because community entrepreneurs do not have marketing knowledge to help keep and maintain their customers. This paper proposes the development of gamification for improving the customer relationship management in community enterprises on social media such as Facebook. The results showed that the applied gamification for the community enterprise products has the highest level of efficiency evaluation and has the highest acceptance criteria while being used by experts and users. It can be said that Thai gamification on social media could be effectively used to support community enterprises in improving social customer relationship management and buying their products.

scholarly journals Investment Efficiency Evaluation of Customer Relationship Management System: Theoretical and Practical Aspects of Return on Investment Methodology Application

2011 ◽  
Vol 9 (3) ◽  
pp. 221-228
Author(s):  
Regina Jasilionienė ◽  
Rima Tamošiūnienė
Keyword(s):  
Customer Relationship Management ◽  
Business Strategy ◽  
Return On Investment ◽  
Relationship Management ◽  
Customer Relationship ◽  
Investment Efficiency ◽  
Efficiency Evaluation ◽  
Crm System ◽  
The Right ◽  
Financial Measurement

Customer relationship management (CRM) has been increasingly adopted by companies as the core of IT – driven business strategy and firms have started to invest in CRM. However, the rate of successful CRM implementations is about 30%. Many enterprises pursue expensive CRM initiatives without first understanding of the challenges and costs involved. This approach often results in CRM projects that fail to meet measurable benefit objectives. Evaluating costs and benefits associated with CRM systems acquiring and implementation and applying financial measurement methodologies can help a company make the right CRM investments solution and build a compelling justification for its CRM project. Return on investment (ROI) financial measurement methodology, its theoretical and practical aspects are analyzed in this study. Authors of this paper provide a detailed list of CRM cost categories, which can assist an organization to easily calculate its CRM system acquisition and ongoing spending. Also the authors of this paper present survey results of CRM system costs and investment efficiency evaluation in Lithuanian companies.

scholarly journals Operating system efficiency evaluation on the base of measurements analysis with the use of non-extensive statistics elements

2014 ◽  
Vol 14 (3) ◽  
Author(s):  
Paweł Dymora ◽  
Mirosław Mazurek ◽  
Kamil Zelazny
Keyword(s):  
Operating System ◽  
Long Range ◽  
Multifractal Analysis ◽  
Measurement Data ◽  
Database System ◽  
Efficiency Evaluation ◽  
System Efficiency ◽  
Major Goal ◽  
Self Similarity ◽  
Multifractal Spectra

AbstractThe major goal of this article was to evaluate the efficiency of Linux operating system using statistical self-similarity and multifractal analysis. In order to collect the necessary data, the tools available in Linux such as vmstat, top and iostat were used. The measurement data collected with those tools had to be converted into a format acceptable by applications which analyze statistical selfsimilarity and multifractal spectra. Measurements collected while using the MySQL database system in a host operating system were therefore analyzed with the use of statistical self-similarity and allowed to determine the occurrence of long-range dependencies. Those dependencies were analyzed with the use of adequately graduated diagrams. Multifractal analysis was conducted with the help of FracLab application. Two methods were applied to determine the multifractal spectra. The obtained spectra were analyzed in order to establish the multifractal dependencies.

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