4.7 Article

Triple bottom line accounting for optimizing natural gas sustainability: A statistical linear programming fuzzy ILOWA optimized sustainment model approach to reducing supply chain global cybersecurity vulnerability through information and communications technology

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 142, Issue -, Pages 1931-1949

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2016.11.089

Keywords

Triple bottom line; Sustainability; Supply chain management; Information and communications technology; Risk; Security

Ask authors/readers for more resources

In this paper, we employed triple bottom line (TBL) accounting and considered threats to cybersecurity in the context of natural gas and global supply chain sustainability. The global supply chain is a diverse assortment of contingent claims contracts and relationships that span the world. It contains both risks and benefits. In this study, consideration is given to the balance of consequences. We propose a sustainable economic model that preserves the positive dynamics of capitalism and accounting principles while improving collaboration between industry, landowners, and environmentalists to optimize return on profits for companies, provide royalties to landowners, and satisfy the planet's environmental concerns. Our TBL approach supports the need to preserve the best qualities of free enterprise and market driven regulation profits while also providing social and environmental benefits. Our proposed approach is novel and may be helpful for decision makers in all sectors, from public to private. We have endeavored to make sufficiently objective and appropriate conclusions that guide how the model can be used in other sectors or by other decision makers. This review has several aims. First, we aim to understand the technical application of TBL optimization and to associate it with the use of mathematical and statistical analysis. Second, we present a fuzzy integrated linguistic operator weighted average application to better understand TBL and to strengthen the argument for its use. Finally, we debate issues inherent in applying analyses of this type with regard to stakeholder viewpoints and objectivity. (C) 2016 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Computer Science, Artificial Intelligence

A distributed problem-solving framework for probabilistic software effort estimation

Parag C. Pendharkar, James A. Rodger

EXPERT SYSTEMS (2012)

Article Computer Science, Artificial Intelligence

A fuzzy linguistic ontology payoff method for aerospace real options valuation

James A. Rodger

EXPERT SYSTEMS WITH APPLICATIONS (2013)

Article Computer Science, Artificial Intelligence

A fuzzy nearest neighbor neural network statistical model for predicting demand for natural gas and energy cost savings in public buildings

James A. Rodger

EXPERT SYSTEMS WITH APPLICATIONS (2014)

Article Automation & Control Systems

Decision making using a fuzzy induced linguistic ordered weighted averaging approach for evaluating risk in a supply chain

James A. Rodger, Pankaj Pankaj, Stephen P. Gonzalez

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2014)

Article Computer Science, Information Systems

A STUDY ON EMOTION AND MEMORY IN TECHNOLOGY ADOPTION

James A. Rodger, Stephen P. Gonzalez

JOURNAL OF COMPUTER INFORMATION SYSTEMS (2014)

Article Computer Science, Artificial Intelligence

Longitudinal Study of a Website for Assessing American Presidential Candidates and Decision Making of Potential Election Irregularities Detection

Justin Piper, James A. Rodger

Summary: This study employs word sense disambiguation to examine voter intentions in the 2016 Presidential election. Using a developed website, the authors analyze candidates' assets and competencies in eligibility, education, and experience. Data envelope analysis is used to determine underlying word instances for elected and successful outcomes. The findings also extend to potential election fraud detection in the 2020 Presidential election using Benford's Law, shedding new light on word sense disambiguation literature.

INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS (2022)

Article Computer Science, Information Systems

A Model for Examining Challenges and Opportunities in Use of Cloud Computing for Health Information Systems

Ahmad Al-Marsy, Pankaj Chaudhary, James Allen Rodger

Summary: The adoption of cloud computing in Health Information Systems (HIS) requires consideration of financial performance, IT operational excellence, and security challenges, with a proposed model for executive management to make informed decisions.

APPLIED SYSTEM INNOVATION (2021)

Article Information Science & Library Science

Information Systems Capabilities and Their Effects on Competitive Advantages: A Study of Chinese Companies

Ganesh D. Bhatt, Ziping Wang, James A. Rodger

INFORMATION RESOURCES MANAGEMENT JOURNAL (2017)

Article Green & Sustainable Science & Technology

Relative evaluation of probabilistic methods for spatio-temporal wind forecasting

Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad

Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

Comparison of ethane recovery processes for lean gas based on a coupled model

Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang

Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

A novel deep-learning framework for short-term prediction of cooling load in public buildings

Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu

Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China

Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang

Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.

JOURNAL OF CLEANER PRODUCTION (2024)

Article Green & Sustainable Science & Technology

Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor

Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He

Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.

JOURNAL OF CLEANER PRODUCTION (2024)