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Topic review
Updated time: 30 Jun 2021
Submitted by: Mosayeb Dashtpeyma
Definition: Learning about the new concept of bioenergy supply chain resilience is necessary to have continues development in renewable energy industries. In this regard, realizing the relevant research gap(s), suggestion(s), future directions, etc. play the undeniable roles in optimizing the quality and quantity of managerial and non-managerial performance in the relevant fields.
Entry Collection : Environmental Sciences
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Topic review
Updated time: 21 Aug 2021
Submitted by: Abdelrahman Zaky
Definition: Bioethanol has many environmental and practical benefits as a transportation fuel. It is one of the best alternatives to replace fossil fuels due to its liquid nature, which is similar to the gasoline and diesel fuels traditionally used in transportation. In addition, bioethanol production technology has the capacity for negative carbon emissions, which is vital for solving the current global warming dilemma. However, conventional bioethanol production takes place based on an inland site and relies on freshwater and edible crops (or land suitable for edible crop production) for production, which has led to the food vs. fuel debate. Establishing a coastal marine biorefinery (CMB) system for bioethanol production that is based on coastal sites and relies on marine resources (seawater, marine biomass and marine yeast) could be the ultimate solution. In this paper, we aim to evaluate the environmental impact of using seawater for bioethanol production at coastal locations as a step toward the evaluation of a CMB system. Hence, a life cycle assessment for bioethanol production was conducted using the proposed scenario, named Coastal Seawater, and compared to the conventional scenario, named Inland Freshwater (IF). The impact of each scenario in relation to climate change, water depletion, land use and fossil depletion was studied for comparison. The Coastal Seawater scenario demonstrated an improvement upon the conventional scenario in all the selected impact categories. In particular, the use of seawater in the process had a significant effect on water depletion, showing an impact reduction of 31.2%. Furthermore, reductions were demonstrated in natural land transformation, climate change and fossil depletion of 5.5%, 3.5% and 4.2%, respectively. This indicates the positive impact of using seawater and coastal locations for bioethanol production and encourages research to investigate the CMB system.
Entry Collection : Environmental Sciences
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Topic review
Updated time: 01 May 2021
Submitted by: Thyago Nepomuceno
Definition: Conditional Frontier Analysis is part of the Nonparametric Robust Estimators proposed to overcome some drawbacks in the traditional Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH) measures for the technical efficiency. In special, this methodology extends the nonparametric input/output production technology to robustly account for extreme values or outliers in the data, and allow measuring the effect of external environmental variables on the efficiency of Decision Making Units (DMUs).
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Topic review
Updated time: 27 Apr 2021
Submitted by: Jamilya Nurgazina
Definition: "Distributed Ledger Technology (DLT) is a term used to represent a digital network of distributed models, consisting of blockchain-based ledgers, and collaborating on shared tasks and activities. Blockchain technology is a data structure, composed of “blocks”, that are cryptographically linked together in a chained sequence using cryptographic hashes, secured against manipulations. Due to wider functionality, DLT is a commonly used term for a computer-based system consisting of distributed ledger-based data structures, which can provide increased levels of trust, service availability, resiliency, and security of digital systems, as well as distributed storage, computation, and control."
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Updated time: 21 Nov 2021
Submitted by: Hisham Alidrisi
Abstract: Manufacturing Innovation Index (GGMII) was developed by formulating an input-oriented data envelopment analysis model. Criteria such as the value added to the gross domestic product (GDP), corresponding CO2 emissions, and unemployment rates were examined in order to represent the economic, environmental, and social dimensions of SD, respectively. Other scientific and technological dimensions were also considered. The data corresponding to all ten of the criteria were collected from World Bank Open Data.
Entry Collection : Environmental Sciences
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Topic review
Updated time: 30 Apr 2021
Submitted by: Thyago Nepomuceno
Definition: In the simple words of Peter Drucker, efficiency is doing things right while effectiveness is doing the right things. Efficient and Effective Rankings are ranking classifications for Decision-Making Units (DMUs) based on a combination of the efficiency score (obtained by parametric or non-parametric Data Envelopment Analysis frontier estimations) with a multiple effectiveness measure (often obtained using a Multicriteria Decision Analysis). This study aims at providing a non-compensatory ranking classification combining Conditional Frontier Analysis with the PROMETHEE II methodology for the multidimensional efficiency and effectiveness analysis of Police. The results on Pernambuco (Brazil) Police departments offer interesting perspectives for public administrations concerning prioritizations of units based on the mitigation of resources and strategic objectives.
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Topic review
Updated time: 12 Aug 2021
Submitted by: Jacinto Jardim
Definition: Entrepreneurship education (EE) is par excellence a field for advancing and developing societies, a trigger for economic growth, social cohesion, organizational success, and personal fulfillment.
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Topic review
Updated time: 25 May 2021
Submitted by: Golshan Madraki
Definition: Graphs are powerful tools to model manufacturing systems and scheduling problems. The complexity of these systems and their scheduling problems has been substantially increased by the ongoing technological development. Thus, it is essential to generate sustainable graph-based modeling approaches to deal with these excessive complexities. Graphs employ nodes and edges to represent the relationships between jobs, machines, operations, etc. Despite the significant volume of publications applying graphs to shop scheduling problems, the literature lacks a comprehensive survey study. We proposed the first comprehensive review paper which 1) systematically studies the overview and the perspective of this field, 2) highlights the gaps and potential hotspots of the literature, and 3) suggests future research directions towards sustainable graphs modeling the new intelligent/complex systems. We carefully examined 143 peer-reviewed journal papers published from 2015 to 2020. About 70% of our dataset were published in top-ranked journals which confirms the validity of our data and can imply the importance of this field. After discussing our generic data collection methodology, we proposed categorizations over the properties of the scheduling problems and their solutions. Then, we discussed our novel categorization over the variety of graphs modeling scheduling problems. Finally, as the most important contribution, we generated a creative graph-based model from scratch to represent the gaps and hotspots of the literature accompanied with statistical analysis on our dataset. Our analysis showed a significant attention towards job shop systems (56%) and Un/Directed Graphs (52%) where edges can be either directed, or undirected, or both. Whereas 14% of our dataset applied only Undirected Graphs, and 11% targeted hybrid systems, e.g., mixed shop, flexible and cellular manufacturing systems which shows potential future research directions.
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Topic review
Updated time: 23 Jun 2021
Submitted by: Sehrish Atif
Definition: Industry 4.0 (I4.0) technologies have been highlighted in recent literature as enablers of servitisation. Simultaneously, businesses are advised to implement a circular economy (CE) to bring new opportunities. However, it is pertinent to mention that little attention has been given to assess the role of I4.0 in adopting the CE and servitisation in a fully integrated manner. This research fills this gap by developing a conceptual framework through a systematic literature review of 139 studies investigating the relationship between the I4.0, CE, and servitisation. This study identifies the impact of these variables on a firm’s operational and financial performance (revenue stream, growth, and profitability). Our research findings advocate that adopting I4.0 technologies to the business and manufacturing model enables sustainability, energy and resource efficiency while enhancing performance and offering innovative products through smart services. Thus, firms must systematically adopt I4.0 technologies to support a CE model that creates value through servitisation. This study identifies the research gaps that are unexplored for practitioners and future researchers while providing insight into the role of I4.0 in implementing CE in the servitisation business model.
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