Search results for: supply demand model

Authors: Katie Wood

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Cyber criminals are constantly on the lookout for new opportunities to exploit organisation and cause destruction. This could lead to significant cause of economic loss for organisations in the form of destruction in finances, reputation and even the overall survival of the organization. Additionally, this leads to serious consequences on national security. The threat of possible cyber attacks places further pressure on organisations to ensure they are secure, at a time where international scale cyber attacks have occurred in a range of sectors. Stakeholders are wanting confidence that their data is protected. This is only achievable if a business fosters a resilient supply chain strategy which is implemented throughout its supply chain by having a strong cyber leadership culture. This paper will discuss the essential role and need for organisations to adopt a cyber leadership culture and direction to learn about own internal processes to ensure mitigating systemic vulnerability of its supply chains. This paper outlines that to protect national security there is an urgent need for cyber awareness culture change. This is required in all organisations, regardless of their sector or size, to implementation throughout the whole supplier chain to support and protect economic prosperity to make the UK more resilient to cyber-attacks. Through businesses understanding the supply chain and risk management cycle of their own operates has to be the starting point to ensure effective cyber migration strategies.

Keywords: cyber leadership, cyber migration strategies, resilient supply chain strategy, cybersecurity

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Authors: Kishore K. Pochampally

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The success of a supply chain heavily relies on the efficiency of the suppliers involved. In this paper, we propose a neural network approach to evaluate the efficiency of a supplier, which is being considered for inclusion in a supply chain, using the available linguistic (fuzzy) data of suppliers that already exist in the supply chain. The approach is carried out in three phases, as follows: In phase one, we identify criteria for evaluation of the supplier of interest. Then, in phase two, we use performance measures of already existing suppliers to construct a neural network that gives weights (importance values) of criteria identified in phase one. Finally, in phase three, we calculate the overall rating of the supplier of interest. The following are the major findings of the research conducted for this paper: (i) linguistic (fuzzy) ratings of suppliers such as 'good', 'bad', etc., can be converted (defuzzified) to numerical ratings (1 – 10 scale) using fuzzy logic so that those ratings can be used for further quantitative analysis; (ii) it is possible to construct and train a multi-level neural network in order to determine the weights of the criteria that are used to evaluate a supplier; and (iii) Borda’s rule can be used to group the weighted ratings and calculate the overall efficiency of the supplier.

Keywords: fuzzy data, neural network, supplier, supply chain

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Murad A. Bein

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This paper empirically examines the time-varying relationship and spillover effects between the international crude oil price and ten emerging equity markets, namely three oil-exporting countries (Brazil, Mexico, and Russia) and seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, and Slovakia). The results revealed that there are spillover effects from oil markets into almost all emerging equity markets save Slovakia. Besides, the oil supply glut had a homogenous effect on the emerging markets, both net oil-exporting, and oil-importing countries (CEE). Further, the time variance drastically increased during financial turmoil. Indeed, the time variance remained high from 2009 to 2012 in response to aggregate demand shocks (global financial crisis and Eurozone debt crisis) and quantitative easing measures. Interestingly, the time variance was slightly higher for the oil-exporting countries than for some of the CEE countries. Decision-makers in emerging economies should therefore seek policy coordination when dealing with financial turmoil.

Keywords: crude oil, spillover effects, emerging equity, time-varying, aggregate demand shock

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Authors: Jia-Chao Wang

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The cosmic microwave background radiation (CMB) freed during the recombination era can be considered as a photon source of small duration; a one-time event happened everywhere in the universe simultaneously. If space is divided into concentric shells centered at an observer’s location, one can imagine that the CMB photons originated from the nearby shells would reach and pass the observer first, and those in shells farther away would follow as time goes forward. In the Big Bang model, space expands rapidly in a time-dependent manner as described by the scale factor. This expansion results in an event horizon coincident with one of the shells, and its radius can be calculated using cosmological calculators available online. Using Planck 2015 results, its value during the recombination era at cosmological time t = 0.379 million years (My) is calculated to be Revent = 56.95 million light-years (Mly). The event horizon sets a boundary beyond which the freed CMB photons will never reach the observer. The photons within the event horizon also exhibit a peculiar behavior. Calculated results show that the CMB observed today was freed in a shell located at 41.8 Mly away (inside the boundary set by Revent) at t = 0.379 My. These photons traveled 13.8 billion years (Gy) to reach here. Similarly, the CMB reaching the observer at t = 1, 5, 10, 20, 40, 60, 80, 100 and 120 Gy are calculated to be originated at shells of R = 16.98, 29.96, 37.79, 46.47, 53.66, 55.91, 56.62, 56.85 and 56.92 Mly, respectively. The results show that as time goes by, the R value approaches Revent = 56.95 Mly but never exceeds it, consistent with the earlier statement that beyond Revent the freed CMB photons will never reach the observer. The difference Revert - R can be used as a measure of the remaining observable CMB photons. Its value becomes smaller and smaller as R approaching Revent, indicating a dwindling supply of the observable CMB radiation. In this paper, detailed dwindling effects near the event horizon are analyzed with the help of online cosmological calculators based on the lambda cold dark matter (ΛCDM) model. It is demonstrated in the literature that assuming the CMB to be a blackbody at recombination (about 3000 K), then it will remain so over time under cosmological redshift and homogeneous expansion of space, but with the temperature lowered (2.725 K now). The present result suggests that the observable CMB photon density, besides changing with space expansion, can also be affected by the dwindling supply associated with the event horizon. This raises the question of whether the blackbody of CMB at recombination can remain so over time. Being able to explain the blackbody nature of the observed CMB is an import part of the success of the Big Bang model. The present results cast some doubts on that and suggest that the model may have an additional challenge to deal with.

Keywords: blackbody of CMB, CMB radiation, dwindling supply of CMB, event horizon

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Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Mizan Ahmed, Srikanth Venkatesan

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Geological and tectonic framework indicates that Bangladesh is one of the most seismically active regions in the world. The Bengal Basin is at the junction of three major interacting plates: the Indian, Eurasian, and Burma Plates. Besides there are many active faults within the region, e.g. the large Dauki fault in the north. The country has experienced a number of destructive earthquakes due to the movement of these active faults. Current seismic provisions of Bangladesh are mostly based on earthquake data prior to the 1990. Given the record of earthquakes post 1990, there is a need to revisit the design provisions of the code. This paper compares the base shear demand of three major cities in Bangladesh: Dhaka (the capital city), Sylhet, and Chittagong for earthquake scenarios of magnitudes 7.0MW, 7.5MW, 8.0MW and 8.5MW using a stochastic model. In particular, the stochastic model allows the flexibility to input region specific parameters such as shear wave velocity profile (that were developed from Global Crustal Model CRUST2.0) and include the effects of attenuation as individual components. Effects of soil amplification were analysed using the Extended Component Attenuation Model (ECAM). Results show that the estimated base shear demand is higher in comparison with code provisions leading to the suggestion of additional seismic design consideration in the study regions.

Keywords: attenuation, earthquake, ground motion, Stochastic, seismic hazard

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Authors: Hussain Abdullah Al-Salamin, Elias Ogutu Azariah Tembe

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Supply chain (SC) is an operational research (OR) approach and technique which acts as catalyst within central nervous system of business today. Without SC, any type of business is at doldrums, hence entropy. SC is the lifeblood of business today because it is the pivotal hub which provides imperative competitive advantage. The paper present a conceptual framework dubbed as Homomorphic Conceptual Framework for Effective Supply Chain Strategy (HCEFSC).The term homomorphic is derived from abstract algebraic mathematical term homomorphism (same shape) which also embeds the following mathematical application sets: monomorphism, isomorphism, automorphisms, and endomorphism. The HCFESC is intertwined and integrated with wide and broad sets of elements.

Keywords: homomorphism, isomorphism, monomorphisms, automorphisms, epimorphisms, endomorphism, supply chain, operational research (OR)

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Authors: Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri, Aida Kazempour, Reza Tavakkoli-Moghaddam, Maryam Irani

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All over the world, natural disasters (e.g., earthquakes, floods, volcanoes and hurricanes) causes a lot of deaths. Earthquakes are introduced as catastrophic events, which is accident by unusual phenomena leading to much loss around the world. Such could be replaced by disasters or any other synonyms strongly demand great long-term help and relief, which can be hard to be managed. Supplies and facilities are very important challenges after any earthquake which should be prepared for the disaster regions to satisfy the people's demands who are suffering from earthquake. This paper proposed disaster response facility allocation problem for disaster relief operations as a mathematical programming model. Not only damaged people in the earthquake victims, need the consumable commodities (e.g., food and water), but also they need non-consumable commodities (e.g., clothes) to protect themselves. Therefore, it is concluded that paying attention to disaster points and people's demands are very necessary. To deal with this objective, both commodities including consumable and need non-consumable commodities are considered in the presented model. This paper presented the multi-objective multi-period mathematical programming model regarding the minimizing the average of the weighted response times and minimizing the total operational cost and penalty costs of unmet demand and unused commodities simultaneously. Furthermore, a Chebycheff multi-objective solution procedure as a powerful solution algorithm is applied to solve the proposed model. Finally, to illustrate the model applicability, a case study of the Tehran earthquake is studied, also to show model validation a sensitivity analysis is carried out.

Keywords: facility location, multi-objective model, disaster response, commodity

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Authors: M. Erol Genevois, D. Celik, H. Z. Ulukan

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Automated teller machines (ATMs) can be considered among one of the most important service facilities in the banking industry. The investment in ATMs and the impact on the banking industry is growing steadily in every part of the world. The banks take into consideration many factors like safety, convenience, visibility, cost in order to determine the optimum locations of ATMs. Today, ATMs are not only available in bank branches but also at retail locations. Another important factor is the cash management in ATMs. A cash demand model for every ATM is needed in order to have an efficient cash management system. This forecasting model is based on historical cash demand data which is highly related to the ATMs location. So, the location and the cash management problem should be considered together. Although the literature survey on facility location models is quite large, it is surprising that there are only few studies which handle together ATMs location and cash management problem. In order to fulfill the gap, this paper provides a general review on studies, efforts and development in ATMs location and cash management problem.

Keywords: ATM location problem, cash management problem, ATM cash replenishment problem, literature review in ATMs

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Authors: Timothy Akinwande, Eddie C. M. Hui

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Housing the urban poor has remained a challenge for many years across the world, especially in developing economies, despite the apparent research attention and policy interventions. It is apt to investigate the prevalent affordable housing (AH) provision challenges using unconventional approaches. It is pragmatic to thoroughly examine housing experts to provide supply-side solutions to AH challenges and investigate informal settlers to deduce solutions from AH demand viewpoints. This study being the supply-side investigation of an ongoing research, interrogated housing experts to determine significant expert solutions. Focus group discussions and in-depth interviews were conducted with housing experts in Nigeria. Through descriptive, content, and systematic thematic analyses of data, major findings are that deliberate finance models designed for the urban poor are the most significant housing finance solution in developing economies. Other findings are that adequately implemented rent control policies, deliberate PPP approaches like inclusionary housing and land-value capture, and urban renewal programmes to enlighten and tutor the urban poor on how to earn more, spend wisely, and invest in their own better housing will effectively solve AH finance challenges. Study findings are informative for the best approaches to achieve effective, affordable housing finance for the urban poor in Nigeria, which is indispensable for the achievement of sustainable development goals. This research’s originality lies in the exploration of experts’ opinions in relation to AH finance to produce an equation model of critical solutions to AH finance challenges. Study data are useful resources for future pro-poor housing studies. This study makes housing policy-oriented recommendations toward effective, affordable housing for the urban poor in developing countries.

Keywords: affordable housing, effective affordable housing, housing policy, housing research, sustainable development, urban poor

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Authors: D. Pérez, M. M. E. Alemany

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In this work a Framework to model the Supply Chain (SC) Collaborative Planning (CP) Process is proposed, and particularly its Decisional view. The main Framework contributions with regards to previous related works are the following, 1) the consideration of not only the Decision view, the most important one due to the Process type, but other additional three views which are the Physical, Organisation and Information ones, closely related and complementing the Decision View, 2) the joint consideration of two interdependence types, the Temporal (among Decision Centres belonging to different Decision Levels) and Spatial (among Decision Centres belonging to the same Decision Level) to support the distributed Decision-Making process in SC where several decision Centres interact among them in a collaborative manner.

Keywords: collaborative planning, decision view, distributed decision-making, framework

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Authors: Sumit Rahangdale

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This research paper is a comparative study of two BRTS cities of Madhya Pradesh (INDIA), Bhopal and Indore. Indore is the largest and most populous city of Madhya Pradesh, with heavy traffic, while Bhopal though being the capital of Madhya Pradesh is comparatively less developed and shows less traffic The cities show similarity in case of peri-urban nature, but variation is observed in transportation fare, where Indore has been able to reduce it but Bhopal couldn’t, one of the reason for it is the para-transit services. Indore can be considered as a successful model due to the low fares and can be implemented in other parts of the city. The research paper tries to identify relation of para-transit services with the peri-urban connectivity and provide a solution for the Bhopal case study.

Keywords: demand-supply-fare relationship, mobility and accessibility, paratransit, peri-urban connectivity

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Authors: Nina N. Serdar, Jelena R. Pejović

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This paper presents seismic risk assessment of two bridge structure, based on the probabilistic performance-based seismic assessment methodology. Both investigated bridges are tree span continuous RC curved bridges with the difference in column shapes. First bridge (type A) has a wall-type pier and second (type B) has a two-column bent with circular columns. Bridges are designed according to European standards: EN 1991-2, EN1992-1-1 and EN 1998-2. Aim of the performed analysis is to compare seismic behavior of these two structures and to detect the influence of column shapes on the seismic response. Seismic risk assessment is carried out by obtaining demand fragility curves. Non-linear model was constructed and time-history analysis was performed using thirty five pairs of horizontal ground motions selected to match site specific hazard. In performance based analysis, peak column drift ratio (CDR) was selected as engineering demand parameter (EDP). For seismic intensity measure (IM) spectral displacement was selected. Demand fragility curves that give probability of exceedance of certain value for chosen EDP were constructed and based on them conclusions were made.

Keywords: RC curved bridge, demand fragility curve, wall type column, nonlinear time-history analysis, circular column

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Authors: Adel Elomri

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The notion of carbon footprinting is ever more widespread as companies are becoming increasingly aware that tackling carbon emissions and being seen to do so is a key issue to face governments, customers and other stakeholders’ pressures towards delivering environmentally friendly services and activities. In this contest, many firms are taking self-initiatives to reduce their own carbon emissions while some other are constrained to obey to different regulations/policies (e.g. carbon tax or carbon Cap) designed by higher authorities targeting a low-carbon environment. Using buyer-vendor framework, this paper provides some insights on how effective are these self-initiatives and regulatory policies when only concerning firms at the individual level and not the whole supply chain they are part of. We show that when firms individually engage in reducing their direct carbon emissions either under self-initiatives or regulatory policy, an opposite expected outcome resulting in a higher global supply chain emission can occur. This effect is referred to as the carbon seesaw effect. Moreover, we show that coordinating or centralizing the supply chain -contrary to what one may think at first- is not often the appropriate solution to get rid of this effect.

Keywords: carbon emissions, supply chain coordination, EOQ, sustainable operations

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Authors: Payam Najafi, Behnam Ebrahimi, Hamid Montazerolghaem, Safoura Akbari-Alavijeh, Rasoul Tarkesh Esfahani

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The combination of work and study has been recently gained lots of attention due to the crucial demand of industries to skillfully trained youth. Nevertheless, the distance between university and industry makes this combination challenging. According to the OECD (2012), in most countries, there is a limited link between students’ field of study and their area of work while studying. On the other hand, high unemployment rates among the specialized workforce, which is common in developing countries, highlights the need to strengthen this relationship. Innovative Center of Isfahan Chamber of Commerce has defined a project called 'POUYESH', which helps students to find related work opportunities to their field of study as well as supporting industries to supply their needed workforce. The present research is sought to explore the effect of the running project as a model of combining work and study on the university-industry linkage.

Keywords: work and study, university-industry linkage, POUYESH project, field of study

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Authors: Addisu H. Addis, Hugh T. Blair, Paul R. Kenyon, Stephen T. Morris, Nicola M. Schreurs, Dorian J. Garrick

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Agent-based modeling (ABM) enables an in silico representation of complex systems and cap-tures agent behavior resulting from interaction with other agents and their environment. This study developed an ABM to represent a pasture-based beef cattle finishing systems in New Zea-land (NZ) using attributes of the rearer, finisher, and processor, as well as specific attributes of dairy-origin beef cattle. The model was parameterized using values representing 1% of NZ dairy-origin cattle, and 10% of rearers and finishers in NZ. The cattle agent consisted of 32% Holstein-Friesian, 50% Holstein-Friesian–Jersey crossbred, and 8% Jersey, with the remainder being other breeds. Rearers and finishers repetitively and simultaneously interacted to determine the type and number of cattle populating the finishing system. Rearers brought in four-day-old spring-born calves and reared them until 60 calves (representing a full truck load) on average had a live weight of 100 kg before selling them on to finishers. Finishers mainly attained weaners from rearers, or directly from dairy farmers when weaner demand was higher than the supply from rearers. Fast-growing cattle were sent for slaughter before the second winter, and the re-mainder were sent before their third winter. The model finished a higher number of bulls than heifers and steers, although it was 4% lower than the industry reported value. Holstein-Friesian and Holstein-Friesian–Jersey-crossbred cattle dominated the dairy-origin beef finishing system. Jersey cattle account for less than 5% of total processed beef cattle. Further studies to include re-tailer and consumer perspectives and other decision alternatives for finishing farms would im-prove the applicability of the model for decision-making processes.

Keywords: agent-based modelling, dairy cattle, beef finishing, rearers, finishers

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Authors: Abdelouahab Errida, Bouchra Lotfi, Elalami Semma

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In this paper, we try to address the topic of multiple change management by adopting an engineered research methodology, conducted within a Moroccan company during its implementation of several change projects that aim at improving its supply chain management performance. Firstly, we present the key concepts related to our research, namely change management, multiproject management and supply chain management. Then, we try to assess how the change management and multi-project management are applied in this company. Finally, we try to propose an approach that will help managers in dealing with multiple change projects. This approach proposes to integrate change management, project management and multi-project management for managing change projects according to three organizational levels: executive level, project portfolio level and change project level.

Keywords: change management, multi-project management, project management, change portfolio, supply chain management,

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Ahmed Barakat, Nourhan Ahmed Saad, Mahmoud Hammad

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Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: agriculture sector, cold chain management, export companies, non-traded goods, supply chain management

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Elucir Gir, Myllena Nilce de Freitas Surmano, Laelson Rochelle Milanês Sousa, Mayra Gonçalves Menegueti, Ana Cristina de Oliveira E Silva, Renata Karina Reis

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Objective: To analyze the factors associated with the worsening of the quality of life of health professionals in the Southeast region of Brazil during the COVID-19 pandemic and its associated factors. Method: Analytical cross-sectional study carried out with health professionals from the southeastern region of Brazil. Data collection took place through an online survey with a form stored on the Survey Monkey platform. Bivariate analysis was used, and the chi-square test was adopted, followed by the multiple binary logistic regression model based on the stepwise method. Results: 3,493 health professionals participated in the study. Factors associated with worsening quality of life were: Professional Category (Nursing assistant) [OR 1.851 (95%CI 1.035-3.311) p= 0.038]; types of people who provided care (people in general) [OR 1.445 (95%CI 1.072-1.945) p=0.015]; Supply of good quality PPE by the institution where he works (no) [OR 1.595 (CI 95% 1.144-2.223) p= 0.006] and Supply of good quality PPE by the institution where he works (in part) [OR 1.563 (CI 95% 1.257-1.943) p < 0.001]. Conclusion: The factors associated with the worsening of the quality of life of health professionals during the COVID-19 pandemic were: Professional Category (Nursing assistant); types of people who provided assistance (people in general); Supply of sufficient PPE by the institution where you work (no) and Supply of good quality PPE by the institution where you work (in part). Future studies should investigate to what extent QoL can be improved based on modifiable factors.

Keywords: COVID-19, quality of life, health professionals, respiratory infections

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Authors: Abel Sichinava

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The need for organ transplantation is vigorously increasing worldwide. The numbers on the waiting lists grow, but the number of donors is not keeping up with the demand even though there is a legal possibility of decreasing the gap between the demand and supply. Most countries around the globe are facing an organ donation problem (living or deceased); however, the extent of the problem differs based on how well developed a country is. The determining issues seem to be centered on how aware the society is about the concept of organ donation, as well as cultural and religious factors. Even if people are aware of the benefits of organ donation, they may still have fears that keep them from being in complete agreement with the idea. Some believe that in the case of deceased organ donation: “the brain dead human body may recover from its injuries” or “the sick might get less appropriate treatment if doctors know they are potential donors.” In the case of living organ donations, people sometimes fear that after the donation, “it might reduce work efficiency, cause health deterioration or even death.” Another major obstacle in the organ shortage is a lack of a well developed ethical framework. In reality, there are truly an immense number of people on the waiting list, and they have only two options in order to receive a suitable organ. First is the legal way, which is to wait until their turn. Sadly, numerous patients die while on the waiting list before an appropriate organ becomes available for transplant. The second option is an illegal way: seeking an organ in a country where they can possibly get. To tell the truth, in people’s desire to live, they may choose the second option if their resources are sufficient. This process automatically involves “organ brokers.” These are people who get organs from vulnerable poor people by force or betrayal. As mentioned earlier, the high demand and low supply leads to human trafficking. The subject of the study was the large number of society from different backgrounds of their belief, culture, nationality, level of education, socio-economic status. The great majority of them interviewed online used “Google Drive Survey” and others in person. All statistics and information gathered from trusted sources annotated in the reference list and above mentioned considerable testimonies shared by the respondents are the fundamental evidence of a lack of the well developed ethical framework. In conclusion, the continuously increasing number of people on the waiting list and an irrelevant ethical framework, lead people to commit to atrocious, dehumanizing crimes. Therefore, world society should be equally obligated to think carefully and make vital decisions together for the advancement of an organ donations and its ethical framework.

Keywords: donation, ethical framwork, organ, transplant

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Authors: Maximilian Richter

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Implementing shared autonomous electric vehicles (SAEVs) has many advantages. The main advantages are achieved when SAEVs are offered as on-demand services by a fleet operator. However, autonomous mobility on demand (AMoD) will be distributed nationwide only if a fleet operation is economically profitable for the operator. This paper proposes a microscopic approach to modeling two implementation scenarios of an AMoD fleet. The city of Zurich is used as a case study, with the results and findings being generalizable to other similar European and North American cities. The data are based on the traffic model of the canton of Zurich (Gesamtverkehrsmodell des Kantons Zürich (GVM-ZH)). To determine financial profitability, demand is based on the simulation results and combined with analyzing the costs of a SAEV per kilometer. The results demonstrate that depending on the scenario; journeys can be offered profitably to customers for CHF 0.3 up to CHF 0.4 per kilometer. While larger fleets allowed for lower price levels and increased profits in the long term, smaller fleets exhibit elevated efficiency levels and profit opportunities per day. The paper concludes with recommendations for how fleet operators can prepare themselves to maximize profit in the autonomous future.

Keywords: autonomous vehicle, mobility on demand, traffic simulation, fleet provider

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Authors: Z. Wang, F. Pashaei Kamali, J. A. Posada Duque, P. Osseweijer

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Globally, the aviation sector is seeking for sustainable solutions to comply with the pressure to reduce greenhouse gas emissions. Jet fuels derived from biomass are generally perceived as a sustainable alternative compared with their fossil counterparts. However, the establishment of jet biofuels supply chains will have impacts on environment, economy, and society. While existing studies predominantly evaluated environmental impacts and techno-economic feasibility of jet biofuels, very few studies took the social / socioeconomic aspect into consideration. Therefore, this study aims to provide a focused evaluation of social sustainability for aviation biofuels with a supply chain perspective. Three potential jet biofuel supply chains based on different feedstocks, i.e. sugarcane, eucalyptus, and macauba were analyzed in the context of Brazil. The assessment of social sustainability is performed with a process-based approach combined with input-output analysis. Over the supply chains, a set of social sustainability issues including employment, working condition (occupational accident and wage level), labour right, education, equity, social development (GDP and trade balance) and food security were evaluated in a (semi)quantitative manner. The selection of these social issues is based on two criteria: (1) the issues are highly relevant and important to jet biofuel production; (2) methodologies are available for assessing these issues. The results show that the three jet biofuel supply chains lead to a differentiated level of social effects. The sugarcane-based supply chain creates the highest number of jobs whereas the biggest contributor of GDP turns out to be the macauba-based supply chain. In comparison, the eucalyptus-based supply chain stands out regarding working condition. It is also worth noting that biojet fuel supply chain with high level of social benefits could result in high level of social concerns (such as occupational accident, violation of labour right and trade imbalance). Further research is suggested to investigate the possible interactions between different social issues. In addition, the exploration of a wider range of social effects is needed to expand the comprehension of social sustainability for biofuel supply chains.

Keywords: biobased supply chain, jet biofuel, social assessment, social sustainability, socio-economic impacts

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Authors: Saeedeh Imani Moqadam, Ilya Bobrov, Jérémy Epp, Nils Ellendt, Lutz Mädler

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High entropy alloys (HEAs), having adjustable properties and enhanced stability compared with intermetallic compounds, are solid solution alloys that contain more than five principal elements with almost equal atomic percentage. The concept of producing such alloys pave the way for developing advanced materials with unique properties. However, the synthesis of such alloys may require advanced processes with high cooling rates depending on which alloy elements are used. In this study, the micro spheres of different diameters of HEAs were generated via a drop-on-demand droplet generator and subsequently solidified during free-fall in an argon atmosphere. Such droplet generators can generate individual droplets with high reproducibility regarding droplet diameter, trajectory and cooling while avoiding any interparticle momentum or thermal coupling. Metallography as well as X-ray diffraction investigations for each diameter of the generated metallic droplets where then carried out to obtain information about the microstructural state. To calculate the cooling rate of the droplets, a droplet cooling model was developed and validated using model alloys such as CuSn%6 and AlCu%4.5 for which a correlation of secondary dendrite arm spacing (SDAS) and cooling rate is well-known. Droplets were generated from these alloys and their SDAS was determined using quantitative metallography. The cooling rate was then determined from the SDAS and used to validate the cooling rates obtained from the droplet cooling model. The application of that model on the HEA then leads to the cooling rate dependency and hence to the identification of process windows for the synthesis of these alloys. These process windows were then compared with cooling rates obtained in processes such as powder production, spray forming, selective laser melting and casting to predict if a synthesis is possible with these processes.

Keywords: cooling rate, drop-on-demand, high entropy alloys, microstructure, single droplet generation, X-ray Diffractometry

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Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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Human life, activity, and culture depend on the wider environment. Cities offer economic opportunities for goods and services, but cannot exist in environments without food, energy, and water supply. Technological innovation in energy supply and transport speeds up the expansion of urban areas and the physical separation from agricultural land. As a result, division of urban agricultural areas causes more energy demand for food and goods transport between the regions. As the energy resources are leaking all over the world, the impact on the environment crossing the boundaries of cities is also growing. While advances in energy and other technologies can reduce the environmental impact of consumption, there is still a gap between energy supply and demand by current technology, even in technically advanced countries. Therefore, reducing energy demand is more realistic than relying solely on the development of technology for sustainable development. The purpose of this study is to introduce the application of carbon footprint assessment in fields of urban planning and geography. In urban studies, carbon footprint has been assessed at different geographical scales, such as nation, city, region, household, and individual. Carbon footprint assessment for a nation and a city is available by using national or city level statistics of energy consumption categories. By means of carbon footprint calculation, it is possible to compare the ecological capacity and deficit among nations and cities. Carbon footprint also offers great insight on the geographical distribution of carbon intensity at a regional level in the agricultural field. The study shows the background of carbon footprint applications in urban planning and geography by case studies such as figuring out sustainable land-use measures in urban planning and geography. For micro level, footprint quiz or survey can be adapted to measure household and individual carbon footprint. For example, first case study collected carbon footprint data from the survey measuring home energy use and travel behavior of 2,064 households in eight cities in Gyeonggi-do, Korea. Second case study analyzed the effects of the net and gross population densities on carbon footprint of residents at an intra-urban scale in the capital city of Seoul, Korea. In this study, the individual carbon footprint of residents was calculated by converting the carbon intensities of home and travel fossil fuel use of respondents to the unit of metric ton of carbon dioxide (tCO₂) by multiplying the conversion factors equivalent to the carbon intensities of each energy source, such as electricity, natural gas, and gasoline. Carbon footprint is an important concept not only for reducing climate change but also for sustainable development. As seen in case studies carbon footprint may be measured and applied in various spatial units, including but not limited to countries and regions. These examples may provide new perspectives on carbon footprint application in planning and geography. In addition, additional concerns for consumption of food, goods, and services can be included in carbon footprint calculation in the area of urban planning and geography.

Keywords: carbon footprint, case study, geography, urban planning

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Authors: Suleiman Hassan Otuoze, Dexter Vernon Lloyd Hunt, Ian Jefferson

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Urbanization has continued to widen the gap between demand and resources available to provide resilient and sustainable transport services in many fast-growing developing countries' cities. Transport demand management is a decision-based optimization concept for both benchmarking and ensuring efficient use of transport resources. This study assesses the service quality of infrastructure and mobility services in the Nigerian cities of Kano and Lagos through five dimensions of quality (i.e., Tangibility, Reliability, Responsibility, Safety Assurance and Empathy). The methodology adopts a hybrid AHP-SERVQUAL model applied on questionnaire surveys to gauge the quality of satisfaction and the views of experts in the field. The AHP results prioritize tangibility, which defines the state of transportation infrastructure and services in terms of satisfaction qualities and intervention decision weights in the two cities. The results recorded ‘unsatisfactory’ indices of quality of performance and satisfaction rating values of 48% and 49% for Kano and Lagos, respectively. The satisfaction indices are identified as indicators of low performances of transportation demand management (TDM) measures and the necessity to re-order priorities and take proactive steps towards infrastructure. The findings pilot a framework for comparative assessment of recognizable standards in transport services, best ethics of management and a necessity of quality infrastructure to guarantee both resilient and sustainable urban mobility.

Keywords: transportation demand management, multi-criteria decision support, transport infrastructure, service quality, sustainable transport

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Authors: Samira Hamiditehrani

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Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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Authors: Hayder H. Kareem, Ayad K. Hussein, Aseel A. Alkatib

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Groundwater accumulated at geological formations constitutes a worldwide vital water resource component which can be used to supply agriculture, industry, and domestic uses. The subsurface environment is affected by human activities; consequently, planning and sustainable management of aquifers require serious attention, especially as the world is exposed to the problem of global warming. Establishing accurate and efficient groundwater models will provide confident results for the behavior of the aquifer's system. The new approach, 'Distributed Value Property Zones,' available in Visual MODFLOW, is used to reconstruct the subsurface zones of the Al-Najaf region aquifer, and then its effect is compared with those manual and automated (PEST) approaches. Results show that the model has become more accurate with the use of the new approach, as the calibration and results analyses revealed. The assessment of the Al-Najaf region groundwater aquifer has revealed a degree of insufficiency of the required pumping demand, which reflects dry areas in both of the aquifer's layers. In addition, with pumping, the Euphrates River loses water of 7458 m³/day to the aquifer, while without pumping, it gains 28837 m³/day from the rainfall's recharge. The distributed value property zones approach achieves a precise groundwater model to assess the state of the Al-Najaf region aquifer.

Keywords: Al-Najaf region, distributed value property zones approach, hydraulic conductivity, groundwater modelling using visual MODFLOW

Procedia PDF Downloads 171