Sustainable Supply Chain Analytics: Grand Challenges and Future Opportunities

Over the last few years, the pressure for decreasing environmental and social footprints has motivated supply chain organizations to significantly progress sustainability initiatives. Since supply chains have implemented sustainability strategies, the volume of economic, environmental and social data has rapidly increased. Dealing with this data, business analytics has already shown its capability for improving supply chain monetary performance. However, there is limited knowledge about how business analytics can be best leveraged to grow social, environmental and financial performance simultaneously. Therefore, in reviewing the literature around sustainable supply chain, this research seeks to further illuminate the role business analytics plays in addressing this issue. A literature survey methodology is outlined, scrutinizing key papers published between 2012 and 2016 in the research fields of Information/Computing Science, Business and Supply Chain Management. From examination of 311 journal papers, 39 were selected as meeting defined criteria for further categorization into three distinct research groups including: (a) sustainable supply chain configuration; (b) sustainable supply chain implementation; (c) sustainable supply chain evaluation. The issues involved within each grouping are identified and the business analytics processes (i.e. prescriptive, predictive, prescriptive analytics) to specifically address them are discussed. This wide-ranging review of sustainable supply chain analytics can assist both scholars and practitioners to better appreciate the current grand challenges and future research opportunities posed by this area

Designing a conceptual framework for strategic selection of Bushfire mitigation approaches

Fires are an important aspect of environmental ecology; however, they are also one of the most widespread destructive forces impacting natural ecosystems as well as property, human health, water and other resources. Urban sprawl is driving the construction of new homes and facilities into fire-vulnerable areas. This growth, combined with a warmer climate, is likely to make the consequences of wildfires more severe. To reduce wildfires and associated risks, a variety of hazard reduction practices are implemented, such as prescribed burning (PB) and mechanical fuel load reduction (MFLR). PB can reduce forest fuel load; however, it has adverse effects on air quality and human health, and should not be applied close to residential areas due to risks of fire escape. On the other hand, MFLR releases less greenhouse gasses and does not impose risks to residential areas. However, it is more expensive to implement. We suggest that environmental, economic and social costs of various mitigation tools should be taken into account when choosing the most appropriate fire mitigation approach and propose a conceptual framework, which can do it. We show that applying GIS methods and life cycle assessment we can produce a more reasonable comparison that can, for example, include the benefits that can be generated by using collected biomass for bioenergy or in timber industries. This framework can assist decision makers to find the optimal combinations of hazard reduction practices for various specific conditions and locations

Profit, planet and people in supply chain: grand challenges and future opportunities

Recent pressure from governments and customers on supply chain organizations to consider environmental and social issues has increased dramatically. The challenge ahead for supply chain managers is how to grow business profit while protecting the planet and respecting people’s rights. The significance of this issue motivates researchers in the fields of “sustainability” and “supply chain” to further integrate these concepts. To identify affected areas, and how sustainability influences them, this research has employed a literature survey of related papers published between 2012 and 2016 within 16 A* indexed journals that are relevant to Information and Computing Science, Transportation/Freight Services and Manufacturing Engineering. Findings show that sustainable supply chain network structure, impact factors, relationship integration and performance evaluation are the main research topics in these streams. The role of decision-making tools within each discipline, the key methodologies and techniques are discussed. Generally speaking, primary challenges in the sustainable supply chain domain devolve from use of inadequate decision-making tools and inappropriate information systems. The holistic picture presented in this paper is important for helping scholars, system developers, and supply chain analysts to become more aware of current grand challenges and future research opportunities within this field.N/

Sustainable supply chain analytics: Grand challenges and future opportunities

Over the last few years, the pressure for decreasing environmental and social footprints has motivated supply chain organizations to significantly progress sustainability initiatives. Since supply chains have implemented sustainability strategies, the volume of economic, environmental and social data has rapidly increased. Dealing with this data, business analytics has already shown its capability for improving supply chain monetary performance. However, there is limited knowledge about how business analytics can be best leveraged to grow social, environmental and financial performance simultaneously. Therefore, in reviewing the literature around sustainable supply chain, this research seeks to further illuminate the role business analytics plays in addressing this issue. A literature survey methodology is outlined, scrutinizing key papers published between 2012 and 2016 in the research fields of Information/Computing Science, Business and Supply Chain Management. From examination of 311 journal papers, 39 were selected as meeting defined criteria for further categorization into three distinct research groups including: (a) sustainable supply chain configuration; (b) sustainable supply chain implementation; (c) sustainable supply chain evaluation. The issues involved within each grouping are identified and the business analytics processes (i.e. prescriptive, predictive, prescriptive analytics) to specifically address them are discussed. This wide-ranging review of sustainable supply chain analytics can assist both scholars and practitioners to better appreciate the current grand challenges and future research opportunities posed by this areaN/

Extended Sustainable Supply Chain: Pathways to Sustainability through Consumer Behavior Change

University of Technology Sydney. Faculty of Engineering and Information Technology.In today's growing economy, overconsumption and overproduction have accelerated environmental deterioration worldwide. Consumers, through unsustainable consumption patterns, and producers, through production based on traditional resource depleting practices, have contributed significantly to the socio-environmental problems. Consumers and producers are linked by supply chains, and as the idea of sustainable development has become seen as a way to reverse socio-environmental degradation, it has also started to sprout in research on supply chains. We look at the evolution of research on sustainable supply chains and show that it is still largely focused on the processes and networks that involve the producer and the consumer, hardly taking into account consumer behavior and its influence on the performance of the producer and the supply chain itself. We conclude that we cannot be talking about sustainability, without extending the supply chains to account for consumers' behavior and their influence on the overall system performance. In Chapter 2, a conceptual framework is proposed to explain how supply chains can become sustainable and how their economic and socio-environmental performance can be improved by motivating consumer behavior toward green consumption patterns, which, in turn, motivates producers and suppliers to change their operations. In the thesis we focus on agro-food production-consumption, which is an important element of the sustainability agenda. The current intense food production-consumption is one of the main sources of environmental pollution and contributes up to 25-30% of anthropogenic greenhouse gas emissions. Organic farming is a potential way to reduce environmental impacts by excluding synthetic pesticides and fertilizers from the process. Organic food has important environmental and health benefits, decreasing the toxicity of agricultural production, retaining carbon, and improving overall soil quality, and generally the resilience of farming. Despite the recorded 20% growth in organically managed farmland, its global land area is still far less than could be expected, only 1.4%. Increasing consumers’ demand for organic food reinforces the rate of organic farming adoption and the level of farmers' risk acceptance when transitioning to organic. […

PROFIT, PLANET AND PEOPLE IN SUPPLY CHAIN: GRAND CHALLENGES AND FUTURE OPPORTUNITIES

Recent pressure from governments and customers on supply chain organizations to consider environ-mental and social issues has increased dramatically. The challenge ahead for supply chain managers is how to grow business profit while protecting the planet and respecting people’s rights. The significance of this issue motivates researchers in the fields of “sustainability” and “supply chain” to further integrate these concepts. To identify affected areas, and how sustainability influences them, this research has employed a literature survey of related papers published between 2012 and 2016 within 16 A* indexed journals that are relevant to Information and Computing Science, Transportation/Freight Services and Manufacturing Engineering. Findings show that sustainable supply chain network structure, impact factors, relationship integration and performance evaluation are the main research topics in these streams. The role of decision-making tools within each discipline, the key methodologies and techniques are discussed. Generally speaking, primary challenges in the sustainable supply chain domain devolve from use of inadequate decision-making tools and inappropriate in-formation systems. The holistic picture presented in this paper is important for helping scholars, system developers, and supply chain analysts to become more aware of current grand challenges and future research opportunities within this field

DAESim: A dynamic agro-ecosystem simulation model for natural capital assessment

Threats to sustainable food production are accelerating due to climate change, population growth, depletion of natural capital, and global market instability. This causes significant risks to farmers, consumers, and financial and policy institutions. Understanding agro-ecosystems, and how varying management styles can impact their performance is critical to future wellbeing. To better understand and manage agricultural production, we have developed a dynamic simulation model that accounts for the core natural capital components of agro-ecosystems, including climate, soil, carbon, water, nitrogen, phosphorus, microorganisms, erosion, crops, farm animals and plants. Dynamic Agro-Ecosystem Simulation (DAESim) model can be used to simulate dynamics of soil health and project it into the future to assess vulnerabilities and resilience. This knowledge can inform and guide investment decisions by financial institutions, insurance companies, farmers, and governmental agencies. Here, we describe the basic model structure, sensitivity, and calibration results. We then run a few scenarios to demonstrate the model's ability to analyze alternative agro-ecosystem management options

Machine-assisted agent-based modeling: Opening the black box

While agent-based modeling (ABM) has become one of the most powerful tools in quantitative social sciences, it remains difficult to explain their structure and performance. We propose to use artificial intelligence both to build the models from data, and to improve the way we communicate models to stakeholders. Although machine learning is actively employed for pre-processing data, here for the first time, we used it to facilitate model development of a simulation model directly from data. Our suggested framework, ML-ABM accounts for causality and feedback loops in a complex nonlinear system and at the same time keeps it transparent for stakeholders. As a result, beside the development of a behavioral ABM, we open the ‘blackbox’ of purely empirical models. With our approach, artificial intelligence in the simulation field can open a new stream in modeling practices and provide insights for future applications

Battery and hydrogen-based electric vehicle adoption: A survey of Australian consumers perspective

Electric vehicles (EV) are a promising alternative for the current fossil-fuel-based vehicles. However, as of 2020, the share of EV sales was only 4.6 % globally, and 1 % in Australia. It is important to identify factors that promote or hinder consumer intentions of EV adoption. In addition, there are a few types of EVs, each with different advantages and disadvantages creating consumer segmentation. This study considered battery-powered EV and hydrogen fuel cell EV and sought to understand which factors influence the preferences for one of the two types of vehicles. We designed a survey on individual perceptions toward EV and collected data of 1735 consumers in Australia. Participants had a mean age of 44.9 years (SD = 16.71) and 41 % of them were males. The median daily traveling distances was 8.7 km, and 74 % of them reported using a personal car for commuting. The results show that the safety concern has a stronger impact on adoption intention than the purchase cost and perceived benefits. Age and consumers' current mode of transportation play a significant role in EV adoption intentions. In addition, the results indicate that preference for BEV is significantly affected by BEV range sufficiency, tolerability in battery charging time, and fear of hydrogen explosion, whereas the key preference factors for FCEVs is their longer driving range, and fear of battery explosion. Besides, the results reveal that part-time employees are more likely to prefer BEV than full-time workers. On the other hand, apartment residents tend to prefer FCEV more than people living in a house. Furthermore, female is more likely to still undecided than males whether they prefer BEV or FCEV