Arash Khosravi

Toward software quality enhancement by Customer Knowledge Management in software companies

Abstract Customer Knowledge Management (CKM) plays an important role in the production of high quality software products. As CKM in Enterprise Software (ES) development is still immature, this raises questions on how CKM enablers can be used to help ES development companies improve their software quality. In this study, Human, Organizational and Technological CKM enablers were identified from the literature. The weights of these factors were determined by experts from the ES development companies. Based on the most important factors, a theoretical model was developed. The proposed model was evaluated by distributing a survey questionnaire to decision-makers in ES development companies. The results showed that “Customer Involvement” together with “Trust” were the most influential factors, followed by “CRM Technology Infrastructure” and “Cross-Functional Cooperation”. In addition, there was no impact from “Organizational Training”, “Customer Knowledge Map”, and “CKM Strategy Development”. The results also revealed that the impact of CKM on software quality is significant. The proposed model in this study can be used as a guideline for the successful application of CKM in ES development companies to improve the software quality.

Examining antecedents of knowledge-sharing factors on research supervision: An empirical study

The use of an effective supervision mechanism is crucial between a student and supervisor. The essential knowledge shared and transferred between these two parties must be observed and understood very well in order to ensure that students are produced at good level of quality for future professional knowledge workers. The aim of this study was to conduct an assessment of the impact of individual, organisational and technical factors on knowledge sharing in a research supervision domain. In order to achieve this aim, a specific research model was developed. This model was based on systematically analysing and extracting all the knowledge-sharing impact factors and then choosing the more iterative and adaptable ones, according to research supervision models. These factors categorized to individual, organizational and technological factors. To effectively evaluate the research model, a quantitative research method was adopted. Data was collected by a survey of 150 students from the Faculty of Computing at Universiti Teknologi Malaysia. The Smart PLS tool was used for data analysis. In sum, the results of this research show that the individual factor in the research supervision domain – namely, the ability of students to share knowledge – in addition to technological factors – specifically, IT systems – have the greatest impact on knowledge sharing in the supervision process. In addition, it was shown that organisational factors including the culture of the university, social networks, and supervisor support have a positive impact on knowledge sharing in research supervision. However, when compared with individual and technical factors, the effect of organisational factors on knowledge sharing in research supervision was not particularly strong in the case of this study. A positive relationship did not exist between the learning strategy and knowledge sharing in research supervision. This study is among the first of its kind to empirically examine the antecedent factors of knowledge sharing in the context of research supervision.