A hybrid novel approach for evaluation of resiliency and sustainability in construction environment using data envelopment analysis, principal component analysis, and mathematical formulation

Mohammadnazari, Zahra; Aghsami, Amir; Rabbani, Masoud

doi:10.1007/s10668-022-02210-z

Cited by 13 publications

(4 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DMUs). DEA is a non-parametric method based on linear programming that is used for performance assessment of different environments like care unit (Taghipour et al ., 2023, Mehdizadeh-Somarin et al ., 2022; Torabzadeh et al ., 2022; Samieinasab et al ., 2022), bank (Aghakarimi et al ., 2023), factory (Mahboobi et al ., 2020), construction sites (Mohammadnazari et al. , 2023), retail store (Barros and Alves, 2004) and the semiconductor industry (Chen and Chen, 2007).…”

Section: Methodsmentioning

confidence: 99%

Evaluating and improving the performance of retailers' branches by considering resilience, sustainability and sales-marketing

Aghakarimi

Karimi

Aghsami

et al. 2023

IJPPM

Self Cite

View full text Add to dashboard Cite

PurposeConsidering the direct impact of retailers' performance on the economy, this paper aimed to propose a comprehensive framework to evaluate the performance of different branches of a retailer.Design/methodology/approachThrough a case study, the weights of indicators were calculated by the best-worst method (BWM) and the branches' performance was appraised using data envelopment analysis (DEA).FindingsThe branches were ranked in terms of performance, and sensitivity analysis and statistical tests were conducted to realize the weaknesses and strengths of the branches. Then, some strategies were proposed using strengths, weaknesses, opportunities and threats (SWOT) analysis to improve the performance of the weak branches.Originality/valueThis paper contributes to previous studies on the evaluation of retailers' performance by proposing a triple framework based on resilience, sustainability and sales-marketing indicators. This paper focused on branches' operations and branches' optimization by improving performance in terms of these three indicators. This paper also offers a qualitative and quantitative analysis of retailers' performance, which has received less attention in previous studies.

show abstract

Section: Methodsmentioning

confidence: 99%

Evaluating and improving the performance of retailers' branches by considering resilience, sustainability and sales-marketing

Aghakarimi

Karimi

Aghsami

et al. 2023

IJPPM

Self Cite

View full text Add to dashboard Cite

show abstract

“…The strength of PCA lies not only in its ability to streamline complex datasets, but also in its ability to shed light on the dynamics of economic activity, population growth, and their collective impacts on environmental indicators such as carbon dioxide emissions and energy consumption. Through a detailed study of variance interpretation, factor loading and weighted composite model construction, this approach not only reveals the main drivers of environmental change, but also provides a quantifiable framework for policy analysis and strategic planning [2]. The validation of the applicability of PCA through KMO and Bartlett's test further reinforces its importance in environmental policy planning, providing policy makers with a refined perspective to identify, prioritise and address key levers for achieving sustainable environmental outcomes.…”

Section: Introductionmentioning

confidence: 91%

Study on the Impact of Population and Economic Activities on Environmental Indicators through Pca

Zhang,

Yan,

2024

TEBMR

View full text Add to dashboard Cite

Principal Component Analysis (PCA) is applied in environmental policy planning to effectively identify and assess key factors affecting carbon peaking and emissions reduction. By analysing multidimensional data covering GDP, population, average temperature, oil consumption and price, and CO2 emissions, PCA reveals complex correlations of environmental challenges. Preliminary regression analyses expose complex relationships between variables, with a particular focus on anomalous oil consumption data for 2020, emphasising the importance of precise analytical methods.The PCA highlights the significant impacts of economic activity, population and oil-related factors on environmental indicators by simplifying the high-dimensional data, retaining the key information, and extracting the principal components with the highest variance.The KMO and Bartlett test confirms the applicability of PCA, with variance interpretation and dendrograms guiding principal component selection to ensure adequate retention of data information. This approach enabled precise identification of factors affecting environmental indicators, construction of a weighted composite model to quantitatively analyse environmental impacts on a yearly basis, and strengthened the understanding of the overall role of population and economic activities on the environment. Overall, the application of PCA highlights its key role in refining complex environmental data, clarifying the drivers of carbon emissions and energy consumption, and in the development of targeted environmental policies, enriching the environmental planning toolkit and demonstrating the contribution of statistical techniques to environmental governance.

show abstract

“…Market competition is the competition between supply chain and other supply chains, and a weak link will destroy the competitiveness of the whole chain (Esmaeili et al, 2023). Therefore, it is of great practical significance to study supplier selection and evaluation based on supply chain environment (Mohammadnazari et al, 2023).…”

Section: Literature Reviewmentioning

confidence: 99%

Supplier Evaluation in Supply Chain Environment Based on Radial Basis Function Neural Network

Liu,

Yu,

Kim

2024

International Journal of Information Technology and Web Engineering

View full text Add to dashboard Cite

The comprehensive evaluation and selection of suppliers under the environment of supply chain management has become a key factor affecting the success of supply chain. How to select suppliers and the strategic partnership between suppliers under the environment of supply chain management has become an important challenge. To solve this problem, this paper takes the supplier evaluation and selection of Guangzhou Automobile Toyota Company as the research object, constructs the index system of supplier comprehensive evaluation and selection, uses the RBF neural network algorithm to establish the supplier evaluation and selection model, and makes an experimental study. The results show that radial basis function neural network is a local approximation network, which has a unique and definite solution to the problem, and there is no local minimum problem in BP network. It is a method that enables enterprises and suppliers to have a clear understanding and seek further promotion together. The research provides theoretical data support for enterprise managers to make decisions.

show abstract

A hybrid novel approach for evaluation of resiliency and sustainability in construction environment using data envelopment analysis, principal component analysis, and mathematical formulation

Cited by 13 publications

References 46 publications

Evaluating and improving the performance of retailers' branches by considering resilience, sustainability and sales-marketing

Evaluating and improving the performance of retailers' branches by considering resilience, sustainability and sales-marketing

Study on the Impact of Population and Economic Activities on Environmental Indicators through Pca

Supplier Evaluation in Supply Chain Environment Based on Radial Basis Function Neural Network

Contact Info

Product

Resources

About