Impacts of the COVID-19 pandemic on household food waste behaviour: A systematic review.

Food waste has adverse economic, social, and environmental impacts and increases the prevalence of food insecurity. Panic buying at the beginning of the COVID-19 outbreak raised serious concerns about a potential rise in food waste levels and higher pressure on waste management systems. This article aims to investigate the impact of COVID-19 on food waste behaviour and the extent to which it occurs using the systematic review method. A total of 38 articles were identified and reviewed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The findings showed that the COVID-19 pandemic led to reductions in household food waste in most countries. Several changes in shopping and cooking behaviours, food consumption, and managing inventory and leftovers have occurred due to COVID-19. Based on these insights, we predicted that some desirable food-management habits would be retained, and others would roll back in the post-COVID-19 world. The review contributes to the food waste literature by offering a comprehensive overview of behavioural changes during the COVID-19 pandemic and future research directions.

Supply chain resilience reactive strategies for food SMEs in coping to COVID-19 crisis.

BACKGROUND: The ability of small- and medium-sized enterprises in the food industry (FSMEs) in cultivating resilience against the COVID-19 pandemic is vital food security. However, there is limited supply chain resilience literature to guide FSMEs in overcoming disruptions caused by pandemic. SCOPE AND APPROACH: This review aims to provide a broad view of SCRes reactive strategies for FSMEs in dealing with crises in the context of COVID-19. Attention is given to the literature on resilience in other types of supply chain and situated in the context of food settings. The factors are monitored or controlled to contribute to FSME resiliency.Key findings and conclusion: Four quadrants, i.e., (1) rapid with low cost, (2) rapid with high cost, (3) slow with low cost and (4) slow with high cost, are offered based on the limitations and the time needed to react, and the strategies of each quadrant are explained in depth. This review also provides a better understanding of and guidance on reactive strategies for SCRes as options for FSMEs in dealing with the COVID-19 pandemic. This review suggests future directions as extensions based on the logical flow of this review.

A causal eco-industrial park hierarchical transition model with qualitative information: Policy and regulatory framework leads to collaboration among firms.

Eco-industrial parks promise to reduce environmental and social impacts and improve the economic performance of industrial parks. However, the transition from industrial parks to eco-industrial parks is still not well understood. This study contributes to developing valid hierarchical eco-industrial park transition attribute sets with qualitative information, as prior studies lack an exploration of the attributes in the transition of eco-industrial parks in Hungary. In nature, eco-industrial park transition attributes have causal and hierarchical interrelationships and are described with qualitative information. The assessment involves an analysis of the industrial symbiosis principles by using linguistic preferences. However, multiple attributes are involved in the assessment; therefore, this study proposes the Delphi method to develop a valid attribute set and applies fuzzy set theory to translate qualitative information into crisp values. The fuzzy decision-making trial evaluation laboratory method is used to visualize the attributes' causal interrelationships under uncertainties. The results indicate that the policy and regulatory framework leads to collaboration among firms in the eco-industrial park transition model. In practice, price reforms, management commitment, strategic planning, cognitive barriers and the integration of external information are the practical criteria for improvement. Theoretical and practical implications are also discussed.

A deep convolutional neural network for the automatic segmentation of glioblastoma brain tumor: Joint spatial pyramid module and attention mechanism network.

This study proposes a deep convolutional neural network for the automatic segmentation of glioblastoma brain tumors, aiming sat replacing the manual segmentation method that is both time-consuming and labor-intensive. There are many challenges for automatic segmentation to finely segment sub-regions from multi-sequence magnetic resonance images because of the complexity and variability of glioblastomas, such as the loss of boundary information, misclassified regions, and subregion size. To overcome these challenges, this study introduces a spatial pyramid module and attention mechanism to the automatic segmentation algorithm, which focuses on multi-scale spatial details and context information. The proposed method has been tested in the public benchmarks BraTS 2018, BraTS 2019, BraTS 2020 and BraTS 2021 datasets. The Dice score on the enhanced tumor, whole tumor, and tumor core were respectively 79.90 %, 89.63 %, and 85.89 % on the BraTS 2018 dataset, respectively 77.14 %, 89.58 %, and 83.33 % on the BraTS 2019 dataset, and respectively 77.80 %, 90.04 %, and 83.18 % on the BraTS 2020 dataset, and respectively 83.48 %, 90.70 %, and 88.94 % on the BraTS 2021 dataset offering performance on par with that of state-of-the-art methods with only 1.90 M parameters. In addition, our approach significantly reduced the requirements for experimental equipment, and the average time taken to segment one case was only 1.48 s; these two benefits rendered the proposed network intensely competitive for clinical practice.

A simple method for increasing levels of high-density lipoprotein cholesterol: a pilot study of combination aerobic- and resistance-exercise training.

Evidence suggests that physical activity has a beneficial effect of elevated high-density lipoprotein cholesterol (HDL-C) on reducing coronary artery risk. However, previous studies show contrasting results for this association between different types of exercise training (i.e., aerobic, resistance, or combined aerobic and resistance training). The aim of this study was to determine which type of exercise training is more effective in increasing HDL-C levels. Forty obese men, age 18-29 yr, were randomized into 4 groups: an aerobic-training group (n = 10), a resistance-training group (n = 10), a combined-exercise-training group (n = 10), and a control group (n = 10). After a 12-wk exercise program, anthropometrics, blood biochemical variables, and physical-fitness components were compared with the data obtained at the baseline. Multiple-regression analysis was used to evaluate the association between different types of exercise training and changes in HDL-C while adjusting for potential confounders. The results showed that with the control group as the comparator, the effects of combined-exercise training (ß = 4.17, p < .0001), aerobic training (ß = 3.65, p < .0001), and resistance training (ß = 2.10, p = .0001) were positively associated with increase in HDL-C after adjusting for potential confounders. Our findings suggested that a short-term exercise program can play an important role in increasing HDL-C levels; either aerobic or resistance training alone significantly increases the HDL-C levels, but the improvements are greatest with combined aerobic and resistance training.

Nexus amongst environmental regulations, carbon emission intensity and technological innovation in China's construction industry.

China's construction industry confronts with the dilemma of carbon emissions in adjusting the environmental regulations. Many studies are neglected on discovering the potential nexus amongst environmental regulations (ERs), technological innovation (TI) and CEI (CEI) and ignores the relationships amongst TI for reducing CEI. To mitigate this gap, this study bridges institutional theory to integrate the practices in the construction industry. This study applies a panel dataset on the construction industry from 30 provinces during 2004-2018 and uses it with a two-step system-generalised method of moments for analysis. The proposed method enables the prevention of the interference of the heteroscedasticity problem and improves certain analytical efficiency. The results are as a guideline for policymakers in rechecking the policies and regulations adequacy. The findings indicate that (1) the forced emission reduction effect is proven by command-and-control and market-based ERs, which can inhibit CEI; (2) voluntary ERs have an inverted U-shaped nexus with CEI; in other words, the green paradox effect shifts to the forced emission reduction effect once the intensity of voluntary ERs increases; and (3) market-based and voluntary ERs reduce CEI effectively by using TI as the mediator in construction industry.

Identifying the evolution of ecological poverty alleviation efficiency and its influencing factors: evidence from counties in Northeast China.

Ecological poverty alleviation (EPA) is an effective strategy to address the vicious circle of poverty and environmental destruction in poor areas. However, it remains controversial whether this strategy has really succeeded in this respect. Previous research investigated the impact of a certain factor on EPA, and only few studies integrated them to explore their differential effects, thereby overlooking the complexity of EPA. Therefore, this study quantified the overall efficiency of the EPA strategies of 28 poor counties in three provinces of Northeast China from 2005 to 2018 by using a super-efficiency slacks-based measure model. This model can take into account undesirable outputs; as such, it has significant advantages in measuring the coordination among economic and social development and environmental protection. The Tobit model was used to explore the factors influencing EPA efficiency. The results show that, first, the majority of counties investigated had an EPA efficiency below the overall national average. Second, as for the factors influencing EPA efficiency, it was found that (1) GDP per capita and investment in environmental governance favored EPA efficiency, as they are conducive to stimulating regional consumption dynamics and achieving green economic development; (2) science and technology expenditure and urbanization were not conducive to EPA efficiency; and (3) industrial structure and trade had insignificant effects on EPA efficiency, due to the small scale of industry and the inadequacy of the policy system. This study assessed EPA efficiency from a holistic perspective, and addressed the controversies over EPA's influencing factors, thereby providing an effective method to conduct regional EPA assessment and improve EPA performance in poor regions of China.

Resource saving and carbon footprint reduction potential of urban symbiosis strategy in express packaging waste recycling network.

The booming express delivery industry corresponds to the environmental challenges caused by massive express packaging waste (EPW). An efficient logistics network is necessary link to support EPW recycling. This study, therefore, designed a circular symbiosis network for EPW recycling based on urban symbiosis strategy. The treatment of EPW in this network includes reuse, recycling and replacing. An optimization model with multi-depot collaboration combining material flow analysis and optimization methods was developed and a hybrid non-dominated sorting genetic algorithm-II (NSGA-II) was designed as technical support for designing the circular symbiosis network while quantitatively assessing the economic and environmental benefits of the network. The results show that the designed circular symbiosis option has better resource saving and carbon footprint reduction potential than both the business as usual option and circular symbiosis option without service collaboration. In practice, the proposed circular symbiosis network can save EPW recycling costs and reduce carbon footprint. This study provides a practical guideline for the application of urban symbiosis strategies to help urban green governance and the sustainable development of express companies.

A circular waste bioeconomy development model in the Ecuadorian fishery industry: the impact of government strategy on supply chain integration and smart operations.

This study develops a set of measures to address the interrelationship among circular waste-based bioeconomy (CWBE) attributes, including those of government strategy, digital collaboration, supply chain integration, smart operations, and a green supply chain, to build a circular bioeconomy that feeds fish waste back into the economy. CWBE development is a potential solution to the problem of waste reuse in the fish supply chain; however, this potential remains untapped, and prior studies have failed to provide the criteria to guide its practices. Such an analytical framework requires qualitative assessment, which is subject to uncertainty due to the linguistic preferences of decision makers. Hence, this study adopts the fuzzy Delphi method to obtain a valid set of attributes. A fuzzy decision-making trial and evaluation was applied to address the attribute relationships and determine the driving criteria of CWBE development. The results showed that government strategies play a causal role in CWBE development and drive digital collaboration, smart operations, and supply chain integration. The findings also indicated that smart manufacturing technology, organizational policies, market enhancement, supply chain analytics, and operational innovation are drivers of waste integration from fisheries into the circular economy through waste-based bioeconomy processes.

Uncovering four domains of energy management in palm oil production: a sustainable bioenergy production trend.

This study aims to identify current and future research trends in sustainable bioenergy production. The systematic review is conducted using a social network analysis method. The data were collected from the Web of Science and Scopus database (2010-2021). Out of the 1747 articles reviewed, 100 were found to be relevant for thematic analysis. The results uncovered four domains of palm oil biodiesel production for sustainable energy management: (1) renewable energy, (2) biodiesel, (3) bioenergy, and (4) life cycle assessment. This study has proposed a sustainable bioenergy production framework based on the four main domains. The framework sheds light on the future of sustainable bioenergy production. The findings indicate the potential growth of the research topic, including sustainable bioenergy, palm oil biodiesel, energy management, and carbon emissions reduction. Future research must incorporate the energy management framework to design a sustainable energy management ecosystem strategy. In addition, the industry must comply with the international sustainability standard and sustainable development goals to manage the energy supply chain and consistency of palm oil biodiesel production.

Understanding barriers and motivations in solid waste management from Malaysian industries: a comparative analysis.

The objective of this study is to explore the similarities and differences in the barriers and motivations between the plastic and resins and food and beverages industries as these two industries are the major contributors of solid waste in Malaysia. Prior studies are lacking with regard to explaining the barriers and motivations in solid waste management from the Malaysian context. This study is focused on 10 firms from the plastics and resins industry and 9 from the food and beverages industry in Malaysia. Through Rasch measurement theory, the results indicate that the barriers of lack of skills and qualifications and lack of closed-loop control and the motivations of cost savings and a business model are performed differently. The findings further confirm that the lack of skills and qualifications is a more difficult barrier to overcome than the lack of closed-loop control, while the motivation factor of a business model is more difficult to achieve than cost savings. In terms of practical contribution, this study provides results that can help policy makers in Malaysia to close the gaps present regarding the adoption of solid waste management practices and to devise appropriate incentives. The study also supports managers of companies in regard to working on the most pressing hindering and promoting factors in the field of solid waste management.

Developing a hierarchical framework for assessing the strategic effectiveness of sustainable waste management in the Somaliland construction industry.

This study contributes to develop a hierarchical framework for assessing the strategic effectiveness of waste management in the construction industry. This study identifies a valid set of strategic effectiveness attributes of sustainable waste management (SWM) in construction. Prior studies have neglected to develop a strategic effectiveness assessment framework for SWM to identify reduce, reuse, and recycle policy initiatives that ensure waste minimization and resource recovery programs. This study utilizes the fuzzy Delphi method to screen out nonessential attributes in qualitative information. This study initially proposes a set of 75 criteria; after two rounds of assessment, consensus regarding 28 criteria is achieved among experts, and the 28 criteria are validated. Fuzzy interpretive structural modeling divides the attributes into various elements. The modeling constructs a six-level model that depicts the interrelationships among the 28 validated criteria as a hierarchical framework, and it finds and ranks the optimal drivers for practical improvement. This study integrates the best-worst method to measure the weights of different criteria in the hierarchical strategic effectiveness framework. The findings reveal that waste management operational strategy, construction site waste management performance, and the mutual coordination level are the top aspects for assessing strategic effectiveness in the hierarchical framework. In practice, the waste reduction rate, the recycling rate, water and land usage, the reuse rate, and noise and air pollution levels are identified to assist policymakers in evaluation. The theoretical and managerial implications are discussed.

Understanding the barriers to sustainable solid waste management in society 5.0 under uncertainties: a novelty of socials and technical perspectives on performance driving.

This study contributes to identifying a valid and reliable set of barriers to sustainable solid waste management framework rooted in society 5.0 perspectives in Taiwan. The SSWM-related causal interrelationships within the proposed hierarchical structure, and critical barriers for the practical improvement and enhancement of SSWM performance are identified as preference enriching both literature and practices. In nature, the hierarchical structure is with the causal interrelationships under uncertainties. The perspective empowers the creation of a new biosphere based on technological progress, but in the sustainable solid waste management field, it is difficult to encounter and shape the systematized processes due to barriers and challenges. To address this shortcoming, this study evaluates the technical challenges faced in the field of sustainable solid waste management toward society 5.0. The valid attributes are usually described the qualitative information. The fuzzy Delphi method is applied to acquire the valid and reliable attributes. Fuzzy decision-making trial and evaluation laboratory experiment is to visualize the causal interrelationships among the attributes. Choquet integral with respect to the nonadditive attributes over the valid set provides an overall perspective function. The results establish an understanding of sustainable solid waste management barriers in the perspectives under uncertainties. Community uncertainty, policy and regulation problems, city architecture, and technology interaction are the factors that influence sustainable performance. In practices, (1) diverse disciplines and sectors in local, national, and global communities; (2) a lack of mobility and reliability; (3) mass production and mass consumption; (4) an insufficient level of artificial intelligence application; and (5) failures related to data management and security hinder the improvement of sustainable solid waste management toward society 5.0. The social and technical perspectives are indicated as the top priorities to improve SSWM performance.

Solid waste material reuse analysis: filling the road subgrade with riverway silt and sediment.

This study proposes to explore solid waste material (SWM) reuse of the riverway silt and sediment, and examines the impacts of chemical composition on road construction through sensitivity analysis. Considering the characteristics of silt mixture, it is necessary to investigate the modified materials to improve the mechanical feasibility for subgrade filling. In this study, the water content of riverway silt and sediments was found to be important to determine the selection and content of modified materials. Specifically, the riverway silt and sediment with low water content could be improved effectively with 6 to 8% lime. Compared to the original sludge, the improved mixture had better particle size and permeability, and the carrying capacity also grew 2 to 3 times. On the other hand, the reuse of riverway silt and sediment with high water content over 40% was provided with multiple schemes. Among them, the modification scheme of construction waste or garbage slag showed well mechanical properties and environmental benefits in the sensitivity analysis, especially for the high water content sludge modified by the mixture of garbage slag and lime. The California bearing ratio (CBR2.5) was 2 to 5 times higher than the original silt, which would promote the reuse of multiple solid wastes in road construction. Finally, this study puts forward engineering measures to prevent heavy metals from polluting the water and soil environment by silt-improved soil roadbeds, and the improved riverway silt and sediment roadbeds were proved to be safe and reliable for the environment during service.

An optimum balance among the reduction in ordering cost, product deterioration and carbon emissions: a sustainable green warehouse.

This study involves an optimum balance between ordering cost reduction and product deterioration in controllable carbon emissions for a sustainable green warehouse. The sensitivity analysis is to simulate the impact of those attributes. Industries are foraging to find a proper balance between the use of fossil fuels and reducing carbon emissions, as burning fossil fuels is also indispensable for industrialization. Carbon can emit through inevitable logistic activities in the chains (e.g., lighting, heating, air-conditioning, product deterioration). An industry always attempts to curb those emissions through energy-efficient green technology. The green warehouse is a popular store system in present supply chains to limit the carbons. Product deterioration, particularly for perishable items, is also important for a practitioner to decide how to preserve a perishable product for maximum shelf-life. There is a common tendency among industries to increase order frequencies and volumes in search of a better preservation strategy, increasing the ordering cost and the probability of carbon emissions due to increased transportation. A realistic mathematical model is proposed based on those decision parameters by a sensitivity analysis to demonstrate the impacts. The results showed an increase of 46.30% profit is achieved when all three proposed reduction attributes, but shortages are considered. This improvement is significant without shortage, whereas the increased profit is 94.75%.

Consumption-based CO2 emissions accounting and scenario simulation in Asia and the Pacific region.

This study uses a consumer-based accounting approach to evaluate the CO2 emission factors of 17 countries in Asia and the Pacific region by including all emissions in the supply chain from commodity location to final consumption location in country consumption patterns. In addition, the number of emissions connected with each country's consumption of products and services in Asia and the Pacific region has received little attention. This study contributes to understanding the effects of countries' consumption of products and services on carbon emission peaks and formulates efficient carbon mitigation plans for governments and decision-makers. Accelerating economic growth and industrialization have posed significant challenges to global carbon mitigation efforts and climate change responses. The Monte Carlo simulation technique was used to create a dynamic scenario simulation model to investigate possible future peaks in the carbon emissions of countries in Asia and the Pacific region while taking into account factor uncertainties. The results show that total consumption-based CO2 emissions are remarkable in three Asian countries, including China (387,451.95 metric tons Mt CO2), Japan (185,259.60 Mt CO2), and India (100,720.46 Mt CO2). In South Korea, Brunei, and Taiwan, annual consumption emissions are 1.77, 1.62, and 1.49 tons of CO2 per person, respectively. In terms of final consumption, the household sector is the most noteworthy contributor to consumption-based emissions, accounting for 27-56%. The household sector probably peaks at 19.7 Gt CO2 as per the dynamic scenario simulation. For the three other types of final demand, government expenditure will possibly reach a maximum of 44.0 Gt CO2 in the next 30 years, while capital formation will probably reach its highest emission level at 149.5 Gt CO2.

Inventory decisions on the transportation system and carbon emissions under COVID-19 effects: A sensitivity analysis.

The COVID-19 pandemic has created multiple problems in the existing transportation system. The contribution of this study is to guide logistics managers as they make ordering decisions within a disrupted transportation system. In the overall supply chain system, inventory decisions have been either compromised or challenged. Traditional inventory decisions that consider preplanned transportation facilities (and speeds) are currently becoming obsolete, predominantly in post-COVID times due to delays in the delivery of products and higher delivery costs. Therefore, businesses such as retailers must align ordering and pricing decisions to maintain a sustainable profit. To address this issue, this study investigates optimum inventory decisions under the pandemic's effects while considering the transportation cost as proportional to COVID-19 intensity. This study also considers product deterioration, time-dependent holding costs, price-dependent demands, and carbon emissions from vehicle operation and intends to establish a harmonious relationship among these attributes. The optimization of green technology investment is studied to reduce emissions due to transportation. Some theoretical derivations and numerical examples are given, and they are followed by a sensitivity analysis to extract important managerial insights into the effect of COVID-19. The manager can set an optimal selling price and the cycle length by carefully planning the number of trips in considering the rate of the outbreak and its effect on the increasing transportation cost.

Importance-performance analysis of municipal solid waste management in uncertainty.

The aim of this study was to evaluate and position the perceptions of importance and performance of municipal solid waste management aspects and criteria. The study results propose dependence relations among four aspects and 33 criteria pertaining to metropolitan Taipei. Evaluation was based on linguistically described preferences and multiple aspects and criteria analysis; in particular, applied fuzzy set theory was used to evaluate linguistic vagueness, and the analytic network process was applied for dependence relations among the aspects and criteria. In order to compile managerial implications and concluding remarks, importance-performance analysis was conducted, using several mathematical techniques applied to the objectives as well as the participation and input of professionals and academicians. Overall results and concluding remarks are discussed.

Using hybrid method to evaluate the green performance in uncertainty.

Green performance measure is vital for enterprises in making continuous improvements to maintain sustainable competitive advantages. Evaluation of green performance, however, is a challenging task due to the dependence complexity of the aspects, criteria, and the linguistic vagueness of some qualitative information and quantitative data together. To deal with this issue, this study proposes a novel approach to evaluate the dependence aspects and criteria of firm's green performance. The rationale of the proposed approach, namely green network balanced scorecard, is using balanced scorecard to combine fuzzy set theory with analytical network process (ANP) and importance-performance analysis (IPA) methods, wherein fuzzy set theory accounts for the linguistic vagueness of qualitative criteria and ANP converts the relations among the dependence aspects and criteria into an intelligible structural modeling used IPA. For the empirical case study, four dependence aspects and 34 green performance criteria for PCB firms in Taiwan were evaluated. The managerial implications are discussed.

Exploring food waste during the COVID-19 pandemic among Malaysian consumers: The effect of social media, neuroticism, and impulse buying on food waste.

The amount of food being thrown away despite being in an edible condition has become alarming in countries with populations with medium and high incomes. Changes in consumer behaviour, such as overbuying, are some of the major impetuses of food waste. This study aimed to examine the relationship between food waste and social media usage, neuroticism, and impulse buying. The mediating role of impulse buying and the moderating role of neuroticism on food waste during the coronavirus (COVID-19) pandemic were also uncovered in this study. A self-administered online survey was distributed to a total of 274 consumers who had experienced a lockdown during the COVID-19 outbreak and were also regular buyers of food. Empirical findings supported the fact that social media usage, neuroticism, and impulse buying were positively related to food waste. Impulse buying mediates the relationship between social media usage and food waste, as well as between neuroticism and food waste. The study results also revealed that neuroticism positively moderates the relationship between social media usage and food waste. This paper offers new insights into efforts for sustainable food consumption to tackle the issue of food waste.