scholarly journals Gas vs Electric: Sustainability Performance of Heating Fuel Options in the NIST NZERTF

2020 ◽  
Author(s):  
David Webb ◽  
Joshua Kneifel
Keyword(s):  
Sustainability Performance ◽  
Heating Fuel

scholarly journals Sustainability Assessment of Public Transport, Part I—A Multi-Criteria Assessment Method to Compare Different Bus Technologies

2021 ◽  
Vol 13 (2) ◽  
pp. 825
Author(s):  
Jonas Ammenberg ◽  
Sofia Dahlgren
Keyword(s):  
Fossil Fuels ◽  
Sustainability Assessment ◽  
Public Procurement ◽  
Assessment Method ◽  
County Level ◽  
Participatory Process ◽  
Problem Context ◽  
The Public ◽  
Sustainability Performance ◽  
Sustainability Assessments

This article departs from the perspective of Swedish regional transport authorities and focuses on the public procurement of bus transports. Many of these public organizations on the county level have the ambition to contribute to a transition involving the continued marginalization of fossil fuels and improved sustainability performance. However, there are several renewable bus technologies to choose between and it can be difficult to know what alternative (or combination) is preferable. Prior research and the authors’ experiences indicate a need for improved knowledge and supportive methods on how sustainability assessments can support public procurement processes. The purpose of this article is to develop a multi-criteria assessment (MCA) method to support assessments of public bus technologies’ sustainability. The method, which was established in an iterative and participatory process, consists of four key areas and 12 indicators. The article introduces the problem context and reviews selected prior research of relevance dealing with green or sustainable public procurement and sustainability assessments. Further on, the process and MCA method are presented and discussed based on advice for effective and efficient sustainability assessments. In the companion article (Part II), the MCA method is applied to assess several bus technologies involving biodiesel, biomethane, diesel, electricity, ethanol and natural gas.

Beyond Bounded Rationality: CEO Reflective Capacity and Firm Sustainability Performance

2021 ◽  
pp. 1-38
Author(s):  
Yingya Jia ◽  
Anne S. Tsui ◽  
Xiaoyu Yu
Keyword(s):  
Decision Making ◽  
Bounded Rationality ◽  
Three Dimensional ◽  
Strategic Decision ◽  
Future Research ◽  
Sustainability Performance ◽  
Business Executives ◽  
Dimensional Measure ◽  
Reflective Capacity ◽  
Mediating Mechanisms

ABSTRACT Optimal or rational decision making is not possible due to informational constraints and limits in computation capability of humans (March & Simon, 1958; March, 1978). This bounded rationality serves as a filtering process in decision making among business executives (Hambrick & Mason, 1984). In this study, we propose the concept of CEO reflective capacity as a behavior-oriented cognitive capability that may overcome to some extent the pervasive limitation of bounded rationality in executive decision-making. Following Hinkin's (1998) method and two executive samples, we developed and validated a three-dimensional measure of CEO reflective capacity. Based on two-wave surveys of CEOs and their executive-subordinates in 213 Chinese small-medium sized firms, we tested and confirmed three hypotheses on how CEO reflective capacity is related to a firm's sustainability performance (including economic, societal, and environmental dimensions) through the mediating mechanisms of strategic decision comprehensiveness and CEO behavioral complexity. We discuss the contribution of this study to the literature on the upper echelons and information processing perspectives. We also identify the implications for future research on strategic leadership and managerial cognition in complex and dynamic contexts.

scholarly journals Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)

2021 ◽  
Vol 13 (7) ◽  
pp. 3870
Author(s):  
Mehrbakhsh Nilashi ◽  
Shahla Asadi ◽  
Rabab Ali Abumalloh ◽  
Sarminah Samad ◽  
Fahad Ghabban ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Sustainability Assessment ◽  
Regression Trees ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Sustainability Performance ◽  
Learning Techniques ◽  
Self Organizing

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment.

scholarly journals An integrated fuzzy intuitionistic sustainability assessment framework for manufacturing supply chain: a study of UK based firms

2021 ◽  
Author(s):  
Alok Choudhary ◽  
Arijit De ◽  
Karim Ahmed ◽  
Ravi Shankar
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Mixed Method ◽  
Sustainability Assessment ◽  
Assessment Framework ◽  
Mixed Method Approach ◽  
Sustainability Performance ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Topsis ◽  
Method Approach

AbstractThe increasing importance of sustainability has put pressure on organisations to assess their supply chain sustainability performance, which requires a holistic set of key performance indicators (KPIs) related to strategic, tactical and operational decision making of firms. This paper presents a comprehensive set of KPIs for sustainable supply chain management using a mixed method approach including analysing data from the literature survey, content analysis of sustainability reports of manufacturing firms and expert interviews. A 3-level hierarchical model is developed by classifying the identified KPIs into key sustainability dimensions as well as key supply chain decision-making areas including strategic, tactical and operational. A novel multi-attribute decision-making (MADM) based sustainability assessment framework is proposed. The proposed framework integrates value focussed thinking (VFT), intuitionistic fuzzy (IF) Analytic Hierarchy Process (AHP) and IF Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The novelty of the research lies in (1) using a rigorous mixed method approach for KPIs identification and industrial validation (2) the development of a novel integrated intuitionistic sustainability assessment framework for decision making and (3) the innovative application of the proposed framework and associated methodologies in the context not explored before. The practical data on the performance ratings of various KPIs were obtained from the experts and a novel intuitionistic fuzzy TOPSIS was applied to benchmark the organisations for their sustainability performance. Furthermore, the case study shows the applicability of the proposed framework to evaluate and identify the problem areas of the organisations and yield guidance on KPIs by recognising the most significant areas requiring improvement. This research contributes to the practical implication by providing an innovative sustainability assessment framework for supply chain managers to evaluate and manage sustainability performance by making informed decisions related to KPIs.

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