Yannian Wu, Euisoo Kim, James J. Zhang, Fengyan Li and Haixia Duan
Grounded in social cognitive theory, social exchange theory and “cognition-emotion-behavior intention” analysis framework, a theoretical model of cause-related sport marketing…
Abstract
Purpose
Grounded in social cognitive theory, social exchange theory and “cognition-emotion-behavior intention” analysis framework, a theoretical model of cause-related sport marketing (CRSM) affecting consumers’ purchase intentions was constructed through a case study. This model was then empirically validated to confirm CRSM's impact on consumers' purchase intentions.
Design/methodology/approach
This study embraces a mixed-methods approach that combines both qualitative and quantitative research methodologies to investigate the mechanisms through which CRSM influences consumers' purchase intentions.
Findings
The results indicate that: (1) consumers’ perception of CRSM has no direct impact on purchase intentions; (2) consumers’ perception of CRSM directly affects gratitude; (3) consumer gratitude acts as a complete mediator between perceived CRSM and purchase intentions.
Originality/value
These findings shed light on the role of gratitude in CRSM and offer practical guidance for sports enterprises in improving their philanthropic marketing strategies.
Details
Keywords
The purpose of this paper is to design and implement a novel type of PCI eXtension for Instruments (PXI) bus‐based airborne data transfer equipment (DTE) test system.
Abstract
Purpose
The purpose of this paper is to design and implement a novel type of PCI eXtension for Instruments (PXI) bus‐based airborne data transfer equipment (DTE) test system.
Design/methodology/approach
First, the basic principle of PXI bus is introduced in detail. Then, the hardware and software are developed for the PXI bus‐based airborne DTE test system. Based on the description of the basic conceptions of rough set theory, a novel hybrid approach for fault diagnosis in PXI bus‐based airborne DTE test system is proposed, which is based on rough set theory, genetic algorithm and neural network. Combining with rough set theory, genetic algorithm is used to compute the reductions of the decision table. Subsequently, the condition attributes of decision table are regarded as the input nodes of neural network and the decision attributes are regarded as the output nodes of neural network correspondingly.
Findings
The exact application results are also presented to verify the feasibility and effectiveness of the developed PXI bus‐based airborne DTE test system, and the test results can also be saved automatically. The exact application results show that the various faults within the PXI bus‐based airborne DTE test system can be located on board level, and the newly developed airborne DTE test system is also easy to be extended and upgraded.
Practical implications
The proposed hybrid rough set theory, genetic algorithm and neural network approach could reduce the number of attributes in the decision table, simplify the structure of neural network and improve the ability of generality. The airborne DTE test system is also capable of different unit under test (UUT), which can be selected by the definite operators at the start of the test, to ensure that failures and problems are handled automatically and without intervention. This newly developed PXI bus‐based airborne DTE test system can be located on board level, and it is also very easy to be extended and upgraded. Practical implementations show that hidden errors can be effectively detected by the developed PXI bus‐based airborne DTE test system. The proposed methodology can help improve the general performance of the airborne DTE test system, and the faults can be checked with minimum time and effort. This system can enhance the army combat capability efficiently.
Originality/value
This paper develops a novel type of PXI bus‐based airborne DTE test system. In particular, a hybrid approach for fault diagnosis in PXI bus‐based airborne DTE test system is proposed, which is based on rough set theory, genetic algorithm and neural network. This approach provides an effective way to diagnosis the faults of the airborne DTE test system.
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Keywords
Haixia Yuan, Kevin Lu, Ali Ausaf and Mohan Zhu
As an emerging video comment feature, danmaku is gaining more traction and increasing user interaction, thereby altering user engagement. However, existing research seldom…
Abstract
Purpose
As an emerging video comment feature, danmaku is gaining more traction and increasing user interaction, thereby altering user engagement. However, existing research seldom explores how the effectiveness of danmaku on user engagement varies over time. To address this research gap, this study proposes a comprehensive framework drawing on social presence theory and information overload theory. The framework aims to explain how the effectiveness of danmaku in increasing user engagement changes over shorter time intervals.
Design/methodology/approach
A research model was proposed and empirically tested using data collected from 1,019 movies via Bilibili.com, one of China’s most popular danmaku video platforms. A time-varying effect model (TVEM) was used to examine the proposed research model.
Findings
The study finds that the volume of danmaku and its valence exert a time-varying influence on user engagement. Notably, the study shows that danmaku volume plays a more substantial role in determining user engagement than danmaku valence.
Originality/value
This research offers theoretical insights into the dynamic impact of danmaku on user engagement. The innovative conceptualization and measurement of user engagement advance research on pseudo-synchronous communication engagement. Furthermore, this study offers practical guidelines for effectively managing danmaku comments on online video platforms.
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Qiuping Wang, Subing Liu and Haixia Yan
Due to high efficiency and low carbon of natural gas, the consumption of natural gas is increasing rapidly, and the prediction of natural gas consumption has become the focus. The…
Abstract
Purpose
Due to high efficiency and low carbon of natural gas, the consumption of natural gas is increasing rapidly, and the prediction of natural gas consumption has become the focus. The purpose of this paper is to employ a prediction technique by combining grey prediction model and trigonometric residual modification for predicting average per capita natural gas consumption of households in China.
Design/methodology/approach
The GM(1,1) model is utilised to obtain the tendency term, then the generalised trigonometric model is used to catch the periodic phenomenon from the residual data of GM(1,1) model for improving predicting accuracy.
Findings
The case verified the view of Xie and Liu: “When the value of a is less, DGM model and GM(1,1) model can substitute each other.” The combination of the GM(1,1) and the trigonometric residual modification technique can observably improve the predicting accuracy of average per capita natural gas consumption of households in China. The mean absolute percentage errors of GM(1,1) model, DGM(1,1), unbiased grey forecasting model, and TGM model in ex post testing stage (from 2013 to 2015) are 32.5510, 33.5985, 36.9980, and 5.2996 per cent, respectively. The TGM model is suitable for the prediction of average per capita natural gas consumption of households in China.
Practical implications
According to the historical data of average per capita natural gas consumption of households in China, the authors construct GM(1,1) model, DGM(1,1) model, unbiased grey forecasting model, and GM(1,1) model with trigonometric residual modification. The accuracy of TGM is the best. TGM helps to improve the accuracy of GM(1,1).
Originality/value
This paper gives a successful practical application of grey model GM(1,1) with the trigonometric residual modification, where the cyclic variations exist in the residual series. The case demonstrates the effectiveness of trigonometric grey prediction model, which is helpful to understand the modeling mechanism of trigonometric grey prediction model.