Modeling passengers’ perceptions of intercity train service quality for regular and special days

Hadiuzzaman, Md.; Malik, Djamaludin; Barua, Saurav; Qiu, Tony Z.; Kim, Amy

doi:10.1007/s12469-019-00213-0

Cited by 8 publications

(15 citation statements)

References 26 publications

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“…Thus, we emphasize the point that corruption is a social phenomenon, that is self-annihilating as economy develops at a higher pace, than the average growth rate across the world. That is why, it is important to try to focus on economic development, what will eventually reduce the corruption level in a country (Huang et al, 2019;Hadiuzzaman et al, 2019;Jasti et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Investigating the relation of GDP per capita and corruption index

Moiseev¹,

Mikhaylov²,

Varyash³

et al. 2020

JESI

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The paper is devoted to modelling the corruption perception index in panel data framework. As corruption index is bounded from below and above, traditional econometric multiple regression will produce a bad quality model. In order to correct that, we propose a mathematical framework for modelling bounded variables implementing a logistic function. It is shown that corruption is best explained by GDP per capita and all other major macroeconomic indicators cannot add any statistically significant improvement to the models' accuracy. Thus, we assume, that society wealthiness facilitates the reduction of corruption acts. Indeed, if some individual lives in a society that does not experiences almost any shortage of resources of whatever kind, the less interested this person is in getting wealthier by applying some corruption schemes. These methods are rather popular in less wealthy countries, where temptation to engage into corruption is higher, since it can drastically increase individual's utility function. Therefore, in this research we assert, that the growth of wealth in a society makes corruption recede and not the other way around (reducing corruption helps increase GDP per capita). However, the most counterintuitive finding of this research is the fact, that GDP per capita, adjusted by purchasing power parity, produces the model of a worse quality then just using plain GDP per capita. This fact can be tentatively explained by the flaws in the methodology of calculating these adjustments, since the basket of goods varies drastically across the countries.

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Section: Discussionmentioning

confidence: 99%

Investigating the relation of GDP per capita and corruption index

Moiseev¹,

Mikhaylov²,

Varyash³

et al. 2020

JESI

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“…Paper proposes the implementation the concept of TBL in Russian companies for increasing level of environment, social and corporate governance and business performance (EBITDA) (Lopatin, 2020 country, Russian business aims to implement these standards in various geographies, for instance, in Africa, where it promotes best practices, especially in public transport sector (Aleshin, 2019;Szlosarek et al, 2019;Covic and Voss, 2019;Dorantes-Argandar et al, 2019;Iliopoulou et al, 2019;Huang et al, 2019;Hadiuzzaman et al, 2019;Jasti et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Triple bottom line and corporate social responsibility performance indicators for Russian companies

Varyash¹,

Mikhaylov²,

Moiseev³

et al. 2020

JESI

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develops the 3-overlapping-circles sustainability model in the context of CSR performance indicators. The data in this study represents scores of 34 major Russian companies, which operate domestically and abroad, in particular, in developing regions like Africa. The mathematical methods like regression has approved the link between environmental innovations and ESG level. It is the first empirical research using this approach for analysis of CSR performance indicators in Russia, because the same data was unavailable before. The paper suggests that environmental innovations and ESG level is linked to Russian largest companies. If business is stimulated towards environmental innovations and R&D. It gives more projects and make the ESG level higher. Paper proposes the concept of TBL in Russian companies for increasing level of ESG and business performance (EBITDA). Understanding how 3-overlapping-circles model implementation can improve CSR performance indicators is a significant question. In addition, we analyzed regression of CSR performance indicators in 2018 year for Russian large companies to find the optimal solution.

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“…For example, de Oña et al used a three-point semantic scale (poor, fair, and good) for obtaining passengers' perception of performance and used a numeric 10 point scale for collecting information about the importance of SQ attributes [21]. Other studies asked passengers to select the attributes they considered as important sparing them from the tedious routine of having to rate all the SQ attributes individually [16], [22]- [26]. Moreover, researchers using decision trees reduced the dependent and explanatory variables in a semantic scale (POOR, FAIR, and GOOD) for ease of modeling [13], [15].…”

Section: Survey Methodologymentioning

confidence: 99%

“…The different types of neural networks employed in SQ studies and often compared to each other or other techniques include ANN [37], comparison between ANN and DT [36] comparison between ANFIS and PNN [24], comparison between PNN, PRNN, and GRNN [25] and ANFIS [22].…”

Section: Neural Networkmentioning

confidence: 99%

A Review of Methodological Approaches and Modeling Techniques in Service Quality Evaluation of Surface Transportation during the Last Decade

Islam

2021

J. eng. adv.

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During the duration of the last decade, a growing interest has been noticed among transport practitioners and researchers to better understand the concept of service quality in the field of surface transportation and identify important service quality (SQ) attributes of different transportation services since these results have implications for transport managers. Due to advancements in computer technology and the availability of software packages, researchers are better able to extract meaningful results from passengers’ opinions collected through stated preference surveys and communicate their findings to transport managers looking to ameliorate SQ to boost ridership on a limited budget. Since the concept of SQ is itself complex owing to the nature of the service itself compared to a tangible product and characteristics of SQ attribute, different advanced modelling techniques based on multivariate analysis, machine learning, and artificial intelligence paradigms have become popular tools among researchers. This paper aims to summarize the trends of the SQ research in the field of surface transportation during the last decade with a focus on the methodological approaches and modelling techniques and delineate future directions for research in this field.

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Modeling passengers’ perceptions of intercity train service quality for regular and special days

Cited by 8 publications

References 26 publications

Investigating the relation of GDP per capita and corruption index

Investigating the relation of GDP per capita and corruption index

Triple bottom line and corporate social responsibility performance indicators for Russian companies

A Review of Methodological Approaches and Modeling Techniques in Service Quality Evaluation of Surface Transportation during the Last Decade

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