20,682 research outputs found

    A novel integrated fuzzy DEA–artificial intelligence approach for assessing environmental efficiency and predicting CO2 emissions

    No full text
    Undesirable output of industrial economic activities—carbon dioxide (CO2) and other pollutants—has been become global concern because of their harmful effects on the climate, especially for environmentally sustainable production systems which attempts to generate less undesirable outputs, as well as achieve higher levels of production and economic growth. This study proposes a novel environmental efficiency data envelopment analysis (DEA) in conjunction with predicting artificial intelligence algorithms. The proposed model—fuzzy undesirable slacks-based measure DEA model (FUNSBM)—measures environmental efficiency in terms of the directional distance function and weak disposability, and its combined approaches (artificial neural network (ANN), ANN + particle swarm optimization (PSO) and artificial immune system (AIS)) predict optimal values of inefficient decision-making units (DMUs) so that they become more efficient considering the possible reduction of CO2 emissions in their production process. The FUNSBM model is applied to a dataset of 30 Iranian forest management units. The findings show that almost 47% DMUs are operating at low efficiency levels with a weak efficiency dispersion; however, these inefficient DMUs could improve their efficiency border via following the combined approaches. This analysis shows that the FUNSBM-AIS approach, by 53% reduction of CO2 emission, is the best approach to predict and/or control CO2 emission in optimal way while FUNSBM-ANN and FUNSBM-ANN + PSO are reduced CO2 emission by 15% and 32%, respectively. As the major conclusion, the FUNSBM-AIS approach exhibits a high degree of reliability to predict the lowest amount of CO2 emission and can help improve the inefficient DMUs by following their predicted optimal values

    La eficiencia técnica del sector manufacturero en la zona económica 2 de Ecuador

    No full text
    Technical efficiency is an economic tool used to determine the use of business resources to improve their productive capacity. The objective was to establish the relationship between production factors and technical efficiency. The methodology for the analysis of the information obtained was the data envelopment analysis (DEA) supported by the location and urbanization indexes. As results, it was evidenced that the highest constant return (CRS) is in the year 2016 and reaches 0.77046 and, the most representative variable return (VRS) is presented in the year 2018 with 0.97901. The average location index is 27.8402. Ultimately, through an econometric model, the direct relationship between the variables is obtained, to obtain a more concrete support in the results of the investigation. In conclusion, all the companies are in the province of Pichincha exclusively and technical efficiency has a direct relationship with the capital incurred (Ci) and the raw material (Mp) in addition to the location and urbanization indices.La eficiencia técnica es una herramienta económica utilizada para determinar el uso de los recursos empresariales para mejorar su capacidad productiva. El objetivo fue establecer la relación existente entre los factores de la producción y la eficiencia técnica. La metodología para el análisis de la información obtenida se utilizó el análisis envolvente de datos (DEA) apoyado en los indicies de localización y de urbanización. Como resultados se evidencio que el rendimiento constante (CRS) más alto se lo ubica en el año 2016 y llega a 0,77046 y, el rendimiento variable (VRS) más representativo se presenta en el año 2018 con 0,97901. El índice de localización promedio es de 27,8402. En última instancia a través de un modelo econométrico se obtiene la relación directa entre las variables, para obtener un soporte más concreto en los resultados de la investigación. En conclusión, todas las empresas se ubican en la provincia de Pichicha exclusivamente y la eficiencia técnica tiene una relación directa con el capital incurrido (Ci) y la materia prima (Mp) además de los índices de localización y urbanización

    Optimization of Construction Projects Time-Cost-Quality-Environment Trade-off Problem Using Adaptive Selection Slime Mold Algorithm

    Get PDF
    In order to address optimization problems, artificial intelligence (AI) is employed in the construction industry, which aids in the growth and popularization of AI. This study utilizes a Hybrid algorithm called Adaptive Selection Slime Mold Algorithm (ASSMA), which combines the Tournament Selection (TS) and Slime Mould Algorithm (SMA) to address the four-factor optimization problem in projects. This combination will improve the original algorithm's performance, speed up result finding and achieve good convergence via Pareto Front. Hence, efficient resource management must be comprehended in order to optimize the time, cost, quality and environmental impact trade-off (TCQE). Case studies are used to illustrate the capabilities of the new model, and ASSMA results are compared to those of the data envelopment analysis (DEA) method used by the previous researcher. To improve the suggested model's superiority and effectiveness, it is compared to the multiple-target swarm algorithm (MOPSO), multi-objective artificial bee colony (MOABC) and non-dominant sort genetic algorithm (NSGA-II). Based on the overall results, it is clear that the ASSMA model illustrates diversification and offers a robust and convincing optimal solution for readers to understand the potential of the proposed model

    An empirical investigation of the relationship between integration, dynamic capabilities and performance in supply chains

    Get PDF
    This research aimed to develop an empirical understanding of the relationships between integration, dynamic capabilities and performance in the supply chain domain, based on which, two conceptual frameworks were constructed to advance the field. The core motivation for the research was that, at the stage of writing the thesis, the combined relationship between the three concepts had not yet been examined, although their interrelationships have been studied individually. To achieve this aim, deductive and inductive reasoning logics were utilised to guide the qualitative study, which was undertaken via multiple case studies to investigate lines of enquiry that would address the research questions formulated. This is consistent with the author’s philosophical adoption of the ontology of relativism and the epistemology of constructionism, which was considered appropriate to address the research questions. Empirical data and evidence were collected, and various triangulation techniques were employed to ensure their credibility. Some key features of grounded theory coding techniques were drawn upon for data coding and analysis, generating two levels of findings. These revealed that whilst integration and dynamic capabilities were crucial in improving performance, the performance also informed the former. This reflects a cyclical and iterative approach rather than one purely based on linearity. Adopting a holistic approach towards the relationship was key in producing complementary strategies that can deliver sustainable supply chain performance. The research makes theoretical, methodological and practical contributions to the field of supply chain management. The theoretical contribution includes the development of two emerging conceptual frameworks at the micro and macro levels. The former provides greater specificity, as it allows meta-analytic evaluation of the three concepts and their dimensions, providing a detailed insight into their correlations. The latter gives a holistic view of their relationships and how they are connected, reflecting a middle-range theory that bridges theory and practice. The methodological contribution lies in presenting models that address gaps associated with the inconsistent use of terminologies in philosophical assumptions, and lack of rigor in deploying case study research methods. In terms of its practical contribution, this research offers insights that practitioners could adopt to enhance their performance. They can do so without necessarily having to forgo certain desired outcomes using targeted integrative strategies and drawing on their dynamic capabilities

    A TOPSIS and DEA Based Approach to Evaluate the Operational Efficiency of Sponge City

    Get PDF
    As an innovative means to promote low-carbon and ecological development of cities, sponge cities have attracted extensive attention from industry and scholars. Measuring the operation efficiency of a sponge city can effectively measure whether the current input and output are reasonable, whether the management and operation are scientific, etc., which can find out the weaknesses in the current process and management. This paper proposes an evaluation method of interval cross-efficiency combined with TOPSIS and DEA to measure the operating efficiency of a sponge city. Specifically, an evaluation system, that includes three inputs and six outputs, is established at first from the perspective of input and output. Secondly, due to the uncertainty of the natural environment, two DEA models of benevolent and aggressive models are adopted to obtain the cross-efficiency interval value of a sponge city. Next, the cross-efficiency interval values are aggregated based on TOPSIS, and then, the descending principle is introduced to rank sponge cities to obtain the optimal operation efficiency cities. Finally, a case is used to verify the effectiveness of the proposed method. The research idea of this paper is clear, the research method is simple, and the research results can provide a basis for building an efficient and high-level sponge city

    Performance Assessment of Malaysian Fossil Fuel Power Plants: A Data Envelopment Analysis (DEA) Approach

    Get PDF
    This paper investigated the performance of Malaysian power plants from the year 2015 to 2017 using Malmquist Total Factor Productivity (TFP) index, which is based on Data Envelopment Analysis (DEA). This approach offers substantial advantages as compared to other existing methods as it can measure productivity changes over time for a variety of inputs and outputs. Moreover, it comprises two primary components: the technical efficiency change and the technological change indexes that provide clearer insight into the factors that are responsible for shifts in total factor productivity. This study uses a single input, installed generation capacity (MW), and two outputs, average thermal efficiency (%) and average equivalent availability factor (%). These output-input data included ten main power plants: TNB Natural Gas, SESB Natural Gas, SESB Diesel, SEB Natural Gas, SEB Coal, SEB Diesel, IPP Semenanjung Natural Gas, IPP Semenanjung Coal, IPP Sabah Natural Gas, and IPP Sabah Diesel. The results have two significant implications for fossil fuel power plants in Malaysia. First, technological change was the primary factor in boosting the TFP performance of the fossil fuel power plants in Malaysia. Meanwhile, the decline in TFP performance in Malaysian fossil fuel power plants may be attributed, in part, to a lack of innovation in technical components as the results found that the average technical efficiency changes in 2015 – 2016 were at 146% and then dropped significantly to 2% in 2016 – 2017. Second, the average scale efficiency changes rose dramatically from -53% to 3% providing a significant contribution to the improvement of technical efficiency changes. The fossil fuel power plants become efficient as the power plants’ size increases. This indicates that the size of a power plant positively impacts the performance of the TFP

    Lancaster Stem Sammon Projective Feature Selection based Stochastic eXtreme Gradient Boost Clustering for Web Page Ranking

    Get PDF
    Web content mining retrieves the information from web in more structured forms. The page rank plays an essential part in web content mining process. Whenever user searches for any information on web, the relevant information is shown at top of list through page ranking. Many existing page ranking algorithms were developed and failed to rank the web pages in accurate manner through minimum time feeding. In direction to address the above mentioned issues, Lancaster Stem Sammon Projective Feature Selection based Stochastic eXtreme Gradient Boost Clustering (LSSPFS-SXGBC) Approach is introduced for page ranking based on user query. LSSPFS-SXGBC Approach has three processes for performing efficient web page ranking, namely preprocessing, feature selection and clustering. LSSPFS-SXGBC Approach in account of the numeral of operator request by way of an input. Lancaster Stemming Preprocessed Analysis is carried out in LSSPFS-SXGBC Approach for removing the noisy data from the input query. It eradicates the stem words, stop words and incomplete data for minimizing the time and space consumption. Sammon Projective Feature Selection Process is carried out in LSSPFS-SXGBC Approach to select the relevant features (i.e., keywords) based on user needs for efficient page ranking. Sammon Projection maps the high-dimensional space to lower dimensionality space to preserve the inter-point distance structure. After feature selection, Stochastic eXtreme Gradient Boost Page Rank Clustering process is carried out to cluster the similar keyword web pages based on their rank. Gradient Boost Page Rank Cluster is an ensemble of several weak clusters (i.e., X-means cluster). X-means cluster partitions the web pages into ‘x’ numeral of clusters where each reflection goes towards the cluster through adjacent mean value. For every weak cluster, selected features are considered as the training samples. Subsequently, all weak clusters are joined to form the strong cluster for attaining the webpage ranking results. By this way, an efficient page ranking is carried out through higher accurateness and minimum time consumption. The practical validation is carried out in LSSPFS-SXGBC Approach on factors such ranking accurateness, false positive rate, ranking time and space complexity with respect to numeral of user query

    The Effects of Judicial Reorganization of Companies on the cost of credit in Brazil and its social impacts

    Get PDF
    The present study aims to analyze whether the institute of judicial reorganization of companies has viability in the context of Economic Analysis of Law, taking into account its reflexes on the cost of credit in Brazil and consequently on society as a whole. The method of approach followed was empirical-dialectical, using bibliographic and legislative research. In conclusion, it was verified that the institute of judicial reorganization of companies, in the current national scenario, does not have viability in face of the theoretical framework of Economic Analysis of Law, considering that it provides short-term benefits only to those who participate directly in its process

    Government spending and tax revenue decentralization and public sector efficiency : do natural disasters matter?

    Get PDF
    We assess notably how do extreme events affect the public sector efficiency of decentralized governance. Hence, we empirically link the public sector efficiency scores, to tax revenue and spending decentralization. First, we compute government spending efficiency scores via data envelopment analysis. Second, relying on panel data and impulse response approaches, we estimate the effect of decentralization on public sector efficiency and how extreme natural disasters mediate this relationship. The sample covers 36 OECD countries between 2006 and 2019. Our results show that tax revenue decentralization decreases public sector efficiency, while spending decentralization and a regional authority index are positively related to public sector efficiency, both for local projections and panel analysis. For instance, efficiency rises by 10 percent following a spending decentralization shock (reaching over 20 percent after 4 years). Nevertheless, in cases of natural disasters, spending decentralization reduces public sector efficiency. Specifically, in the presence of most extreme natural disasters, the improvement in public sector efficiency after a spending decentralization shock is smaller than in their absence. Moreover, extreme natural disasters also deteriorate the negative effect of tax revenue decentralization on public sector efficiency. These results suggest that sub-national discretionary spending and tax revenue responses might be less fruitful when such extreme events occur.info:eu-repo/semantics/publishedVersio

    Technological drivers of dry port efficiency in Brazil

    Get PDF
    Purpose: Identify the scale efficiency of dry ports in Brazil and its main technological drivers. Design/methodology/approach: This paper uses the Data Envelopment Analysis (DEA) model in two stages. The first stage of the DEA was used to measure the efficiency of the dry ports. In the second stage, the Bootstrap Truncated Regression (BTR) was applied to explore the relationship between efficiency and the factors analyzed. The inputs, outputs, and contextual variables for this analysis were extracted from the secondary database provided by Revista Tecnologística. Findings: In the first analysis stage, a high level of idleness was verified in the operations. The contextual variables in the second stage were significant: Certification, Warehouse Management System (WMS), Barcode, and Radio Frequency Identification (RFID). Results corroborate the positive impact of Information Technology (IT) coordination processes on logistics performance. Practical Implications: Results show that dry ports operate below their technical and operational capacity and that the sector's lack of regulation in Brazil can facilitate and encourage the use of ports and marine terminals by importers and exporters. Originality: Application of two-stage DEA measures efficiency as a sectoral benchmarking tool
    corecore