-Nowadays manufacturing industry is growing rapidly and large numbers of added value in business activities has been exercised. Supplier selection problem has improved in many areas by evaluation of supplier to increase supply chain performance. Supplier selection is one of the most important aspects in manufacturing industry. This paper suggest a combination techniques of Analytical Hierarchy Process (AHP) together with Supply Chain Operation Reference (SCOR) model to develop new decision support system (DSS) to the industry. There are four stages in supplier selection process which employed the norm stages of supplier selection process: data gathering, AHP calculation, SCOR evaluation, and implementation of decision making. Data analyzed was aligned with evaluation of data to synthesize of priorities and consistencies measurement. Organization"s decision maker would gain benefits and acquire competitive advantage providing DSS practitioners to achieve a success of the holistic approach in future decision support system.
Abstract. Small and Medium Enterprises (SMEs) in Malaysia have gained a prominent role as the significant contributor to the economic growth. However, the world nowadays is heading towards economic downturn. The stability of macroeconomic variables promotes profitability of SMEs which propels them to a stage where they can access financing for sustaining growth. Therefore, it is apparent that the behaviour of the macroeconomic variables plays a major part in determining the nation's backbone in surviving the economic downturn. The objective of this study is to evaluate the impact of macroeconomic variables on the profitability of SMEs in Malaysia using multiple regression analysis. The findings revealed that the exchange rate has a small positive impact on SME GDP growth rate (10.81%), the interest rate has a strong positive impact (60.74%), while the inflation rate has a strong negative impact (-53.89%). Therefore, it can be concluded that the interest rate and inflation rate have significant impacts on the profitability of SMEs in Malaysia.
Malaysia has set a target to become the first aerospace nation in South East Asia by 2030. In efforts to ensure industry players are able to achieve the target, the critical success factors (CSFs) that affecting the successful implementation of total quality management (TQM) in aerospace industry, especially in Malaysia, need to be identified and ranked. Ranking CSFs is a sensitive task that requires extra attention. Self-judgment, previous experiences and references by industry experts, including the existence of uncertainty in decision making, results in inaccurate ranking. Therefore, this study aims to prioritise (identify and rank) the CSFs for successful implementation of TQM in Malaysia aerospace industry (manufacturing sector). Through an in-depth review of the literature, 11 CSFs were identified and categorised into four main criteria. These criteria were analysed empirically using Fuzzy Analytic Hierarchy Process (FAHP) approach to rank the CSFs based on their relative importance weights. FAHP approach was used since the judgments from industry experts have been taken into account as recommended by National Aerospace Industry Coordinating Office (NAICO). The results showed that the main criterion for successful TQM implementation is culture and people with the highest weight of 0.434, followed by organising (0.296), systems and technique (0.151), and measurement and feedback (0.119). Therefore, the top management and decision makers need to give more attention on culture and people factors before implementing TQM which include employee involvement and role of quality department. However, the relationship between CSFs and the performance of TQM implementation need to be analysed further.
The relative risk of a disease is the observed probability that a member of an exposed group will develop the disease relative to the expected probability that a member of a susceptible group will develop the same disease. The estimation of relative risk is important for disease mapping; it is a method used to illustrate the geographical distribution of a disease occurrence for identifying areas that need more attention. Better estimates of risk would subsequently produce more accurate maps of disease risk. The study on relative risk estimation of leptospirosis in Malaysia is very scarce. Most of the related studies involved only the demographic of the disease. Furthermore, most of the mathematical modelling and statistical analyses used for disease transmission models have been deterministic; do not consider the potential of random effects. Thus, the objective of this study is to propose a discrete-time discrete-space stochastic model for relative risk estimation of leptospirosis in Malaysia based on a SIR-SI transmission model. The proposed model was demonstrated using Malaysia leptospirosis dataset (2012-2016) to estimate and analyse the expected relative risks of leptospirosis for all states. The results showed that the averages of estimated relative risks are between 0.340 and 2.898. Kelantan and Terengganu are the two most vulnerable states of leptospirosis for every epidemiology year from 2012 to 2016.
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