In most countries, Small Medium Enterprise (SMEs) are known as main players in generating domestic-led investment and stimulate economic expansion. They are vital for economic growth and innovation, poverty reduction, local employment and development, and social cohesion. However, in the current digitally-connected trading economy, SMEs have face many new challenges that change the way SMEs business-to-business (B2B) trading operates. Among these challenges ARE the level of B2B e-commerce implementation and utilization that able to facilitate B2B trading process. However, the implementation of B2B e-commerce is being categorized as a system with high degree of difficulty since it involves complexity of the multiple relationships and interactions between trading partners. The interactions are not just complicated by their volume and variation in processes, but also by the complexity inherent in the dependencies exist between different trading parties. Based on this, for SMEs to partake in the B2B e-commerce activities, they need to have attained some reasonable level of maturity or readiness measurement in order to participate in B2B e-commerce initiatives. To overcome this, the robust multidimensional B2B e-commerce maturity application to assess the e-readiness level is needed. This paper describes the development of B2B e-Commerce Maturity Application (BeMA) which involves several distinct sequential exploratory stages. In order to ensure its validity and practicality, the application was evaluated by 35 selected SMEs. Based on the evaluation results, all respondents were agreed on the model usefulness and its practicality. The research believes that the model will provide practical guidance for SMEs to clearly define appropriate method of measuring e-readiness and the recommendation approaches to improve their B2B e-commerce maturity level.
<p>Crowdsourcing is a process where a company outsources a task to a large group of the digital worker through an online platform. In Malaysia, the crowdsourcing ecosystem comprises of three key role players which are job providers, platforms and digital workers. The cycle starts when a job issued by the job providers. Then the platform advertises it to the digital workers who registered themselves in the system. The digital worker is an individual having different skills, knowledge, experiences and education level. Those who are interested and has the capabilities to complete it will pull the job based on the first come first serve basis. Basically, the aim of the platform is to ensure that the tasks are taken immediately and completed within a given time by the right skill of the digital worker. However, the platform does not have a structured mechanism to classify the type of task that would confirm the task match to the digital worker. Tasks are given based on digital worker skills and knowledge. A comprehensive mechanism to define and describe the task properties is important. Apart from enabling the determination of the remuneration value, it will also specify skill required and their level of competency. To solve that issues, this paper present the flow and process development and measured the relationships between the types of tasks and the digital workers in alluvial chart apps prototype. 76% of respondents agreed that the alluvial chart shows a comprehensive relationship. As a conclusion, this study defined the comprehensive relationships among the variables will facilitate a platform to match between digital workers to the tasks.</p>
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