Enhancement of radio spectrum data management for mobile broadband services via dashboard solution

Abstract

The purpose of this action research paper is to develop and enhance the data management platform on the radio spectrum data specifically for mobile broadband services. The proposed enhancement by developing the dashboard solution is with aim to improve the work and business process of Mobile Planning Department of Malaysian Communication and Multimedia Commission. The abundant of collective information related to radio spectrum is required to be properly managed that could benefit the users by improving the work quality and delivery. This study is consisting of two cycles of interventions. The study implemented the mix methods approach which are qualitative and quantitative methodologies. Qualitative methodology was being used for identifying the problem statements and to propose the possible intervention in first cycle of the study, whilst quantitative methodology was being used for both cycles of the study. Quantitative method is used to measures the impact of the interventions to the relevance officers as the respondents. For qualitative methodology, the thematic approach was chosen to the key personnel and was analysed by using Nvivo software. For quantitative methodology, the data collection is involved with the distribution of questionnaires through online platform to twenty respondents. The analysis of quantitative was using a t-test analysis to determine the p-value variation result to determine the impact and efficiency of the dashboard solution. The quantitative analysis was done by using SPSS software. The triangulation approach was then being used to combine the findings from qualitative and quantitative to generate a reliable outcome. First intervention was focus on developing and introduce the dashboard solution to the users while the second intervention was focus on improving, and addition of other data and information to the dashboard solution. In general, the findings shown pure results of which both interventions were statistically efficient, based from the Technology Acceptance Model’s variables.