Background - Handling non-observed activities pose major challenges to the governments and other stakeholders. Non-observed activities refer to underground activities, illegal activities, informal sector and any other activities that result in goods or services consumed by the household. The impact of these non-observed activities shows that the volume of people involved in the informal sector will rapidly increase. Informal economic activities are technically illegal yet are not intended as antisocial, thereby remaining acceptable to many individuals within the society. This research aimed to identify the factors that lead to entrepreneurial necessity and opportunity. Methods - The data of 51 respondents who were employed as informal entrepreneurs in Klang Valley areas in Malaysia was collected with the use of a questionnaire and convenient and proportionate sampling techniques. The data were analysed using SPSS software. Results - The two primary drivers of informal entrepreneurial activity were necessity and opportunity. The inability to find a formal job was an example of being driven by necessity. Meanwhile, individuals that are driven by opportunity chose to work independently in these informal sectors. Between necessity and engagement, refinement acted as a mediator. Often, necessity and opportunity do not automatically translate into successful entrepreneurship; further refinement is required in terms of market potential, technology usage, location preferences, and capital requirements. Improved refinement results in increased entrepreneurial engagement. Conclusions - The role and contribution of the informal sector entrepreneurship in economic development need to be evaluated and not just observed as an opportunity for individuals who choose this type of career. Therefore, further research is required in a wider variety of contexts to evaluate whether the same remains true in different populations. The results of this study can be useful for the government to set policies to encourage the transition of informal to formal entrepreneurships in Malaysia.
In the original particle swarm optimisation (PSO) algorithm, the particles' velocities and positions are updated after the whole swarm performance is evaluated. This algorithm is also known as synchronous PSO (S-PSO). The strength of this update method is in the exploitation of the information. Asynchronous update PSO (A-PSO) has been proposed as an alternative to S-PSO. A particle in A-PSO updates its velocity and position as soon as its own performance has been evaluated. Hence, particles are updated using partial information, leading to stronger exploration. In this paper, we attempt to improve PSO by merging both update methods to utilise the strengths of both methods. The proposed synchronous-asynchronous PSO (SA-PSO) algorithm divides the particles into smaller groups. The best member of a group and the swarm's best are chosen to lead the search. Members within a group are updated synchronously, while the groups themselves are asynchronously updated. Five well-known unimodal functions, four multimodal functions, and a real world optimisation problem are used to study the performance of SA-PSO, which is compared with the performances of S-PSO and A-PSO. The results are statistically analysed and show that the proposed SA-PSO has performed consistently well.