Yankun Qi, Xiaoyu Li, Jinghui Liu, Hanqiu Li and Chen Yang
To systematically characterize and objectively evaluate basic railway safety management capability, creating a closed-loop management approach which allows continuous improvement…
Abstract
Purpose
To systematically characterize and objectively evaluate basic railway safety management capability, creating a closed-loop management approach which allows continuous improvement and optimization.
Design/methodology/approach
A basic railway safety management capability evaluation index system based on a comprehensive analysis of national safety management standards, railway safety rules and regulations and existing safety data from railway transport enterprises is presented. The system comprises a guideline layer including safety committee formation, work safety responsibility, safety management organization and safety rules and regulations as its components, along with an index layer consisting of 12 quantifiable indexes. Game theory combination weighting is utilized to integrate subjective and objective weight values derived using AHP and CRITIC methods and further combined using the TOPSIS method in order to construct a comprehensive basic railway safety management capability evaluation model.
Findings
The case study presented demonstrates that this evaluation index system and comprehensive evaluation model are capable of effectively characterizing and evaluating basic railway safety management capability and providing directional guidance for its sustained improvement.
Originality/value
Construction of an evaluation index system that is quantifiable, generalizable and accessible, accurately reflects the main aspects of railway transportation enterprises’ basic safety management capability and provides interoperability across various railway transportation enterprises. The application of the game theoretic combination weighting method to derive composite weights which combine experts’ subjective evaluations with the objectivity of data.
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Xusen Cheng, Jian Mou, Xiao-Liang Shen, Triparna de Vreede and Rainer Alt
Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process…
Abstract
Purpose
Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.
Design/methodology/approach
First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.
Findings
IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.
Originality/value
The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.
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Idrianita Anis, Lindawati Gani, Hasan Fauzi, Ancella Anitawati Hermawan and Desi Adhariani
This study aims to propose a solution to accelerate financing support low carbon (circular economy) transition. The authors developed a sustainability governance (SGOV) model and…
Abstract
Purpose
This study aims to propose a solution to accelerate financing support low carbon (circular economy) transition. The authors developed a sustainability governance (SGOV) model and a sustainability governance (SGOV) index as a proxy for the diffusion of sustainability innovation. This study investigates the effect of SGOV practices on profitability with the mediating role of operational efficiency.
Design/methodology/approach
The SGOV index consists of 32 and 122 sub-items, constructed using content analysis of annual and sustainability reports published by banks listed on the Indonesia Stock Exchange (IDX) from 2010 to 2020 (404 bank-year observations).
Findings
Banks are at a moderate level of sustainability innovation. They are prioritizing the balance aspects of financial, social and environmental. SGOV practice negatively affects profitability. However, operational efficiency plays a positive mediating role that is robust.
Research limitations/implications
The measurement of the SGOV index uses criteria that have not been tested in previous studies. There is the potential subjectivity in interpreting qualitative data, although this has been minimized by cross-checking the analysis of five raters.
Practical implications
This study gives feedback for the Indonesia sustainable finance (SF) journey phase I to proceed into SF journey phase II.
Social implications
The SGOV model can be applied in other industry sectors to know the readiness for entering low carbon (circular economy) transition.
Originality/value
The uniqueness of the scoring technique assuming a step-by-step innovation model to sustainable finance.
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This paper aims to offer a tutorial/introduction to new statistics arising from the theory of optimal transport to empirical researchers in econometrics and machine learning.
Abstract
Purpose
This paper aims to offer a tutorial/introduction to new statistics arising from the theory of optimal transport to empirical researchers in econometrics and machine learning.
Design/methodology/approach
Presenting in a tutorial/survey lecture style to help practitioners with the theoretical material.
Findings
The tutorial survey of some main statistical tools (arising from optimal transport theory) should help practitioners to understand the theoretical background in order to conduct empirical research meaningfully.
Originality/value
This study is an original presentation useful for new comers to the field.
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Jinbao Zhang, Yongqiang Zhao, Ming Liu and Lingxian Kong
A generalized distribution with wide range of skewness and elongation will be suitable for the data mining and compatible for the misspecification of the distribution. Hence, the…
Abstract
Purpose
A generalized distribution with wide range of skewness and elongation will be suitable for the data mining and compatible for the misspecification of the distribution. Hence, the purpose of this paper is to present a distribution-based approach for estimating degradation reliability considering these conditions.
Design/methodology/approach
Tukey’s g-and-h distribution with the quantile expression is introduced to fit the degradation paths of the population over time. The Newton–Raphson algorithm is used to approximately evaluate the reliability. Simulation verification for parameter estimation with particle swarm optimization (PSO) is carried out. The effectiveness and validity of the proposed approach for degradation reliability is verified by the two-stage verification and the comparison with others’ work.
Findings
Simulation studies have proved the effectiveness of PSO in the parameter estimation. Two degradation datasets of GaAs laser devices and crack growth are performed by the proposed approach. The results show that it can well match the initial failure time and be more compatible than the normal distribution and the Weibull distribution.
Originality/value
Tukey’s g-and-h distribution is first proposed to investigate the influence of the tail and the skewness on the degradation reliability. In addition, the parameters of the Tukey’s g-and-h distribution is estimated by PSO with root-mean-square error as the object function.
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Ying Liu, Chenggang Wang, Zeng Tang and Zhibiao Nan
The purpose of this paper is to examine the impacts of farmland renting-in on planted grain acreage.
Abstract
Purpose
The purpose of this paper is to examine the impacts of farmland renting-in on planted grain acreage.
Design/methodology/approach
A survey data of five counties were analyzed with the two-stage ordinary least squares model.
Findings
Households renting-in land trended to plant more maize, and the more land was rented by a household the more maize was planted, while wheat acreage showed non-response to farmland renting-in.
Practical implications
Overall, the analysis suggests that policy makers should be prepared for different changing trends of grain crop acreage across the nation as farmland transfer continues. Future research should pay attention to the effect of farmland transfer on agricultural productivity and rural household income growth.
Originality/value
As the Chinese Government is promoting larger-scale and more mechanized farms as a way of protecting grain security, it is important to understand whether farmland renting-in will reduce planted grain acreage. This study provides empirical evidence showing the answer to that question may differ across different regions and depend on the particular grain crop in question.
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Lin Li, Jiushan Wang and Shilu Xiao
The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.
Abstract
Purpose
The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.
Design/methodology/approach
The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle. Based on data mechanism models, it predicts the lifespan of key components, evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.
Findings
The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system, which helps operators to monitor the operation of vehicle online, predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.
Originality/value
This system improves the efficiency of rail vehicle operation, scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.