Multiple criteria decision analytical tools in assessing risk for green growth: the case of oil palm biomass in Malaysia

The heightening world issues arises from climate change and energy security has created a strong resonance for sustainable development. The utilisation of biomass resources is amongst one of the best strategies to counter carbon emission and energy security issues for waste-to-wealth. Over the last decade, the Malaysian government has shown its clear intent to be a front-runner in the green economy through its various green economy policies and programs, particularly focus on oil palm biomass industry. However, it is observed that the diffusion rate of the industry remains relatively slow as compared to other developing countries such as Thailand and Philippine. Literature, anecdotal evidence, and advocates as well as businesses have identified that one of the non-technical factors that contribute to this problem is financing difficulties. The complication of biomass value chain creation often engaged with high risk profile, capital intensive and long payback period which is unfavourable for financing based on conventional risk assessment. Thus, this research focusses on developing a full range risk assessment model in aiding the industry stakeholder to comprehend the risk profile in managing and mitigating risk in biomass value chain in Malaysia. Multiple decision analytical tools have been employed and developed to integrate non-quantitative factors in risk assessment and design risk mitigation strategy based on the strengths and preferences of different stakeholders’ role. The outputs can serve as policy recommendation to aid the authorities and policy makers to undertake policy reviews to effectively spur the biomass industry for green growth. Furthermore, financier and investor are recommended to utilise the information to enhance its financing decision, to offer financial products that customised the need of sustainable projects without losing great business opportunity. Last but not least, the framework also offers industry stakeholders a practical decision analysis and making tool to integrate preferences as well as quantitative information to mitigate risks before any losses in venturing into the biomass industry occurred

Multiple criteria decision analytical tools in assessing risk for green growth: the case of oil palm biomass in Malaysia

The heightening world issues arises from climate change and energy security has created a strong resonance for sustainable development. The utilisation of biomass resources is amongst one of the best strategies to counter carbon emission and energy security issues for waste-to-wealth. Over the last decade, the Malaysian government has shown its clear intent to be a front-runner in the green economy through its various green economy policies and programs, particularly focus on oil palm biomass industry. However, it is observed that the diffusion rate of the industry remains relatively slow as compared to other developing countries such as Thailand and Philippine. Literature, anecdotal evidence, and advocates as well as businesses have identified that one of the non-technical factors that contribute to this problem is financing difficulties. The complication of biomass value chain creation often engaged with high risk profile, capital intensive and long payback period which is unfavourable for financing based on conventional risk assessment. Thus, this research focusses on developing a full range risk assessment model in aiding the industry stakeholder to comprehend the risk profile in managing and mitigating risk in biomass value chain in Malaysia. Multiple decision analytical tools have been employed and developed to integrate non-quantitative factors in risk assessment and design risk mitigation strategy based on the strengths and preferences of different stakeholders’ role. The outputs can serve as policy recommendation to aid the authorities and policy makers to undertake policy reviews to effectively spur the biomass industry for green growth. Furthermore, financier and investor are recommended to utilise the information to enhance its financing decision, to offer financial products that customised the need of sustainable projects without losing great business opportunity. Last but not least, the framework also offers industry stakeholders a practical decision analysis and making tool to integrate preferences as well as quantitative information to mitigate risks before any losses in venturing into the biomass industry occurred

Prioritization of sustainability indicators for promoting the circular economy: The case of developing countries

The concept of the circular economy has gained well-recognition across the world for the past decades. With the heightening risk of the impact of climate change, resource scarcity to meet the increasing world population, the need to transition to a more sustainable development model is urgent. The circular economy is often cited as one of the best solutions to support sustainable development. However, the diffusion of this concept in the industrial arena is still relatively slow, particularly in the developing country, which collectively exerts high potential to be the world’s largest economies and workforce. It is crucial to make sure that the development of these nations is sustainable and not bearing on the cost of future generation. Thus, this work aims to provide a comprehensive review of the circular economy concept in developing country context. Furthermore, a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the circular economy. The results revealed that improvement in economic performance and public acceptance are they key triggers to encourage stakeholders for sustainable development. The outcomes serve as a reference to enhance the overall decision-making process of industry stakeholders. Local authorities can adopt the recommendations to design policy and incentive that encourage the adoption of circular economy in real industry operation to spur up economic development, without neglecting environmental well-being and jeopardizing social benefits

Adaptive Analytical Approach to Lean and Green Operations

Recent problems faced by industrial players commonly relates to global warming and depletion of resources. This situation highlights the importance of improvement solutions for industrial operations and environmental performances. Based on interviews and literature studies, manpower, machine, material, money and environment are known as the foundation resources to fulfil the facility's operation. The most critical and common challenge that is being faced by the industrialists is to perform continuous improvement effectively. The needs to develop a systematic framework to assist and guide the industrialist to achieve lean and green is growing rapidly. In this paper, a novel development of an adaptive analytic model for lean and green operation and processing is presented. The development of lean and green index will act as a benchmarking tool for the industrialist. This work uses the analytic hierarchy process to obtain experts opinion in determining the priority of the lean and green components and indicators. The application of backpropagation optimisation method will further enhance the lean and green model in guiding the industrialist for continuous improvement. An actual industry case study (combine heat and power plant) will be presented with the proposed lean and green model. The model is expected to enhance processing plant performance in a systematic lean and green manner

Prioritization of sustainability indicators for promoting the circular economy: The case of developing countries

The concept of the circular economy has gained well-recognition across the world for the past decades. With the heightening risk of the impact of climate change, resource scarcity to meet the increasing world population, the need to transition to a more sustainable development model is urgent. The circular economy is often cited as one of the best solutions to support sustainable development. However, the diffusion of this concept in the industrial arena is still relatively slow, particularly in the developing country, which collectively exerts high potential to be the world’s largest economies and workforce. It is crucial to make sure that the development of these nations is sustainable and not bearing on the cost of future generation. Thus, this work aims to provide a comprehensive review of the circular economy concept in developing country context. Furthermore, a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the circular economy. The results revealed that improvement in economic performance and public acceptance are they key triggers to encourage stakeholders for sustainable development. The outcomes serve as a reference to enhance the overall decision-making process of industry stakeholders. Local authorities can adopt the recommendations to design policy and incentive that encourage the adoption of circular economy in real industry operation to spur up economic development, without neglecting environmental well-being and jeopardizing social benefits

Adaptive Analytical Approach to Lean and Green Operations

Recent problems faced by industrial players commonly relates to global warming and depletion of resources. This situation highlights the importance of improvement solutions for industrial operations and environmental performances. Based on interviews and literature studies, manpower, machine, material, money and environment are known as the foundation resources to fulfil the facility's operation. The most critical and common challenge that is being faced by the industrialists is to perform continuous improvement effectively. The needs to develop a systematic framework to assist and guide the industrialist to achieve lean and green is growing rapidly. In this paper, a novel development of an adaptive analytic model for lean and green operation and processing is presented. The development of lean and green index will act as a benchmarking tool for the industrialist. This work uses the analytic hierarchy process to obtain experts opinion in determining the priority of the lean and green components and indicators. The application of backpropagation optimisation method will further enhance the lean and green model in guiding the industrialist for continuous improvement. An actual industry case study (combine heat and power plant) will be presented with the proposed lean and green model. The model is expected to enhance processing plant performance in a systematic lean and green manner

Prevalence and Risk Factors of Human Papillomavirus (HPV) Infection in Southern Chinese Women – A Population-Based Study

Background: Persistent high-risk type Human papillomavirus (HPV) infection is recognized as a necessary cause of cervical cancer. This study aimed to compare the HPV prevalence and risk factors between women residing in Hong Kong (HK) and Guangzhou (GZ) region of China. Methodology/Principal Findings: A total of 1,570 and 1,369 women were recruited from HK and GZ, respectively. The cytology samples were collected and tested for HPV infection. The overall and type-specific HPV prevalence and the potential risk factors for acquisition of HPV infection were studied. Women with normal cytology in the GZ cohort had significantly higher HPV prevalence (10%) than those in the HK cohort (6.2%, p<0.001). The patterns of the age-specific HPV prevalence were also different between the two cohorts. In the HK cohort, women at the age of 20-29 years old had the highest prevalence and a second peak was observed in the age of ≥60 years old. In the GZ cohort, the highest HPV prevalence was also observed in 20-29 years old but declined as the age increased and a second peak was not seen. HPV16 and HPV52 were the most common high-risk types found in the HK and GZ cohorts, respectively. Age was the most consistently observed independent risk factor for HPV infection in the HK, while the number of sexual partners had association in the GZ cohort. Conclusions/Significance: Our study provides the current status and the epidemiological characteristics of HPV prevalence in Southern Chinese women. The results strongly suggested that population education and the effective cervical cancer screening would be vital in the prevention of cervical cancer. © 2011 Liu et al.published_or_final_versio

A Perspective on Post-Pandemic Biomass Supply Chains:Opportunities and Challenges for the New Norm

Since the dawn of the COVID-19 pandemic, we have seen increasing disruption in several economic sectors, especially the energy sector. This has forced decision-makers in the energy sector to reconsider how should the sector operate. With stumbling crude oil prices, it is evident that there is a need for a radical change in the way energy resources are utilized. This is where renewable energy supply chains such as biomass supply chains can play an important role. Biomass supply chains have been identified as a potential answer to the current issues faced by the energy sector that is still heavily reliant on fossil fuel. As such, this paper aims to examine the current challenges faced by biomass supply chains. Alongside this, potential opportunities that may arise for biomass supply chains in a post-COVID-19 world are also discussed with a specific focus on how the resiliency of biomass supply chains in six areas (i.e., supply availability, digitalization and automation, collaboration within the supply chain, community-focused energy production, social challenges and opportunities, and policy) can be improved in the post-pandemic scenario. [Image: see text

A novel risk assessment model for green finance: The Case of Malaysian Oil Palm Biomass Industry

The last few decades have witnessed dynamic changes across the world, with millions of people lifted out of poverty and standard of living has improved in many developing countries, including in Malaysia. However, these achievements have come at a significant cost to the environment and sustainable development. In the face of pressing economic and environmental challenges, concerted efforts have been made to promote green growth as a new source of economic growth. Several policies and strategies have been formulated to promote green growth in Malaysia, and the country has made significant strides in moving its society towards more sustainable consumption and production patterns. However, the green industry still faces significant challenges, hindering progress towards sustainable development. The perceived high risks of green-related projects are often cited by investors and industry players as one of the factors contributing to the slow growth of green industries in developing countries including Malaysia. Therefore, it is imperative that these risk factors are identified and evaluated in a comprehensive manner so that industry players can address these risks by putting in place appropriate risk management and mitigation measures. In this study, we employ the analytic network process (ANP) approach to assess, evaluate, and prioritize risks commonly associated with the oil palm biomass industry. The results indicate that financing risk appears to be as a major concern for the industry, followed by technology risk and supply chain risk. These findings provide useful insights for the industry’s stakeholders to understand risk factors affecting the biomass industry in Malaysia and develop a basis for putting in place risk management and mitigation strategies more effectively. © 2018, Springer Nature Singapore Pte Ltd