Hasimah Sapiri

Prioritizing the causes and correctors of smoking towards the solution of tobacco free future using enhanced analytic hierarchy process

This paper presents a method for prioritizing the causes and correctors of smoking habits in Malaysia. In order to identify the driving forces that causes (initiation factors) smoking habits and its correctors (anti-smoking strategies), a method called Enhanced Analytic Hierarchy Process (EAHP) is employed. The EAHP has advantages over normal Analytic Hierarchy Process (AHP) based on its capability to eliminate inconsistency (consistency ratio > 0.1) in evaluating expert’s judgment. Based on the Theory of Triadic Influence, the identified initiation factors were personal beliefs and values, personal psychological, family influence, psychosocial influence, culture and legislative. There are five anti-smoking strategies that have been implemented in Malaysia, namely packaging and labelling, pricing and taxation, advertising, smoke-free legislation and education and support. Findings from the study shows that psychosocial influence was considered as the initiation factor of smoking among Malaysian adults, an...

A Framework of Multi-method Modelling Using System Dynamics and Enhanced Analytic Hierarchy Process Towards the Solution for Tobacco Endgame

Tobacco endgame is hotly debated worldwide as one of the effort by the World Health Organization Framework Convention on Tobacco Control (WHO FCTC) towards tobacco-free future. Tobacco epidemic involve dynamic interrelationships between multi-disciplinary elements. Hence, it become increasingly difficult to identify the root of the problem in order to solve the issues. System dynamics (SD) has been recognized with its ability to capture the flow and feedback as well as the dynamic relationships between components in a system under study. The holistic view offered by SD will portray the impact of anti-smoking strategies implementation. In order to identify the driving forces in tobacco epidemic, Enhanced Analytic Hierarchy Process (EAHP) has advantages over normal Analytic Hierarchy Process (AHP) based on its capability to eliminate inconsistency in prioritizing the driving forces in tobacco epidemic which is the initiation factors of smoking. SD and EAHP have different strengths and weaknesses, therefore, integrating both modelling approaches will provide more realistic projections of a tobacco control system. This paper uses SD and EAHP to model the complexity of the problem and to identify the dominant linkages between the initiation factors and anti-smoking strategies in assessing the effectiveness of anti-smoking strategies that have been implemented in Malaysia. We proposed a multi-method modelling framework that served as a basis in understanding the complexity of tobacco epidemic due to the interconnections of multiple elements that may range from qualitative to quantitative aspects. Also, we describe the potential benefits of integrating SD and EAHP in demonstrating the interaction between the smoking causes (initiation factors) and its corrector (anti-smoking strategies).

A dynamic modelling framework towards the solution of reduction in smoking prevalence

This paper presents a hypothetical framework towards the solution for reduction in smoking prevalence in Malaysia. The framework is design to assist in decision making process related to reduction in smoking prevalence using SD and OCT. In general, this framework is developed using SD approach where OCT is embedded in the policy evaluation process. Smoking prevalence is one of the determinant which plays an important role in measuring a successful implementation of anti-smoking strategies. Therefore, it is critical to determine the optimal value of smoking prevalence in order to trim down the hazardous effects of smoking to society. Conversely, smoking problem becomes increasingly complex since many issues that ranged from behavioral to economical need to be considered simultaneously. Thus, a hypothetical framework of the control model embedded in the SD methodology is expected to obtain the minimum value of smoking prevalence which the output in turn will provide a guideline for tobacco researchers as we...

An overview of modelling approaches and potential solution towards an endgame of tobacco

A high number of premature mortality due to tobacco use has increased worldwide. Despite control policies being implemented to reduce premature mortality, the rate of smoking prevalence is still high. Moreover, tobacco issues become increasingly difficult since many aspects need to be considered simultaneously. Thus, the purpose of this paper is to present an overview of existing modelling studies on tobacco control system. The background section describes the tobacco issues and its current trends. These models have been categorised according to their modelling approaches either individual or integrated approaches. Next, a framework of modelling approaches based on the integration of multi-criteria decision making, system dynamics and nonlinear programming is proposed, expected to reduce the smoking prevalence. This framework provides guideline for modelling the interaction between smoking behaviour and its impacts, tobacco control policies and the effectiveness of each strategy in healthcare.

A new method for starter sets generation by fixing any element

A new permutation technique based on distinct starter sets was introduced by employing circular and reversing operations. The crucial task is to generate the distinct starter sets by eliminating the equivalence starter sets. Meanwhile new strategies for starter sets generation without generating its equivalence starter sets were developed and more efficient in terms of computation time compared to old method. However all these algorithms have limitations in terms of fixing element to construct the first set (starter set) to begin with. It would be interesting to derive new strategy by fixing an element in any position. A new method is developed for starter sets generation namely STARSET1 based on circular where any element can be selected randomly to be fixed. The result showed that no redundancy of starter sets is occurring and no equivalence starter sets are obtained.

The dynamic model on the impact of biodiesel blend mandate (B5) on Malaysian palm oil domestic demand: A preliminary finding

Over the last ten years, world biofuels production has increased dramatically. The biodiesel demand is driven by the increases in fossil fuel prices, government policy mandates, income from gross domestic product and population growth. In the European Union, biofuel consumption is mostly driven by blending mandates in both France and Germany. In the case of Malaysia, biodiesel has started to be exported since 2006. The B5 of 5% blend of palm oil based biodiesel into diesel in all government vehicles was implemented in February 2009 and it is expected to be implemented nationwide in the nearest time. How will the blend mandate will project growth in the domestic demand of palm oil in Malaysia? To analyze this issue, a system dynamics model was constructed to evaluate the impact of blend mandate implementation on the palm oil domestic demand influence. The base run of simulation analysis indicates that the trend of domestic demand will increase until 2030 in parallel with the implementation of 5 percent of biodiesel mandate. Finally, this study depicts that system dynamics is a useful tool to gain insight and to experiment with the impact of changes in blend mandate implementation on the future growth of Malaysian palm oil domestic demand sector.