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1 – 10 of over 5000Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv
The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems…
Abstract
Purpose
The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.
Design/methodology/approach
Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.
Findings
Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.
Originality/value
The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.
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Haotian Xu, Jingcheng Wang, Hongyuan Wang, Ibrahim Brahmia and Shangwei Zhao
The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.
Abstract
Purpose
The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.
Design/methodology/approach
Motivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved.
Findings
The proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions.
Originality/value
The new method concerning design POCF has better plants compatibility and less validation conditions.
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The aggregate index and per capita index have different meanings for some countries or regions. CO2 emissions per capita matters for China because of its huge population…
Abstract
Purpose
The aggregate index and per capita index have different meanings for some countries or regions. CO2 emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO2 emissions per capita. In this study, mathematical formulas will be derived and verified.
Design/methodology/approach
First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.
Findings
The CO2 emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO2 decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO2 emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO2 emission intensity target and economic growth target, the growth rate of per capita CO2 emissions must fall within the range of [−0.92%, 6.1%].
Originality/value
Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.
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Katarzyna Czernek-Marszałek, Patrycja Klimas, Patrycja Juszczyk and Dagmara Wójcik
Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological…
Abstract
Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.
This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.
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The purpose of this paper is to examine the influence of perceived information and entertainment value, perceived credibility and perceived value on Generation Y consumers’ usage…
Abstract
Purpose
The purpose of this paper is to examine the influence of perceived information and entertainment value, perceived credibility and perceived value on Generation Y consumers’ usage frequency of online consumer reviews.
Design/methodology/approach
The paper proposes and tests, with structural equation modelling analysis of moment structures, a research model using data from a large sample of Generation Y consumers.
Findings
The results confirm that Generation Y consumers perceive online reviews to be informative, entertaining, credible and valuable, and that they frequently consult such reviews. More specifically, the empirical analysis confirms that perceived information value, perceived entertainment value and perceived credibility significantly influenced the perceived value that Generation Y attach to online consumer reviews, which, in turn, was a significant predictor of their usage frequency of such reviews.
Practical implications
The results highlight the strategic importance of integrating online consumer reviews into the marketing communication mix when targeting Generation Y, together with the necessity of having filtering mechanisms to ensure that only authentic reviews are published and the need to implement tactics to ensure that such reviews are informative and entertaining and, consequently, of value.
Originality/value
This study contributes to marketers’ comprehension of strategically using online consumer reviews when targeting the Generation Y segment.
Propósito
El objetivo de esta investigación es examinar la influencia del valor de la información, del valor del entretenimiento, la credibilidad y el valor percibido en la frecuencia de uso de las revisiones online de los consumidores por parte de los consumidores de la Generación Y.
Diseño/metodología/enfoque
Este documento propone y contrasta, a través de los modelos de ecuaciones estructurales (AMOS), un modelo de investigación que utiliza datos de una gran muestra de consumidores de la Generación Y.
Resultados
Los resultados ponen de relieve la importancia estratégica de integrar las reseñas de consumidores en línea en la combinación de comunicaciones de comercialización al dirigirse a la Generación Y, junto con la necesidad de disponer de mecanismos de filtrado para garantizar que sólo se publiquen reseñas auténticas y la necesidad de aplicar tácticas para asegurar que dichas reseñas sean informativas y entretenidas y, por consiguiente, de valor.
Implicaciones prácticas
Los resultados destacan la importancia estratégica de integrar las revisiones de los consumidores en línea en el mix de comunicación de marketing cuando se dirigen a la Generación Y, junto con la necesidad de contar con mecanismos de filtrado para garantizar que solo se publiquen revisiones auténticas y también se implementen tácticas para garantizar que las reseñas sean informativas y entretenidas y, en consecuencia, de gran valor.
Originalidad/valor
Este trabajo ayuda a los especialistas de marketing a comprender como pueden utilizar estratégicamente las opiniones de los consumidores online para dirigirse a los consumidores de la Generación Y.
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Qiyuan Chen, Zebing Wei, Xiao Wang, Lingxi Li and Yisheng Lv
The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic…
Abstract
Purpose
The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic agents’ trajectories are influenced by physical lane rules and agents’ social interactions.
Design/methodology/approach
In this paper, the authors propose the social relation and physical lane aggregator for multimodal motion prediction, where the social relations of agents are mainly captured with graph convolutional networks and self-attention mechanism and then fused with the physical lane via the self-attention mechanism.
Findings
The proposed methods are evaluated on the Waymo Open Motion Dataset, and the results show the effectiveness of the proposed two feature aggregation modules for trajectory prediction.
Originality/value
This paper proposes a new design method to extract traffic interactions, and the attention mechanism is used in each part of the model to extract and fuse different relational features, which is different from other methods and improves the accuracy of the LSTM-based trajectory prediction method.
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