中国科学院数学与系统科学研究院期刊网

25 December 2024, Volume 12 Issue 6
    

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  • Feipeng ZHANG, Yuhan MA, Di YUAN
    Journal of Systems Science and Information. 2024, 12(6): 709-731. https://doi.org/10.21078/JSSI-2024-0073
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    This study presents a comprehensive and innovative analysis of dynamic tail risk in the Chinese stock market utilizing the localizing conditional autoregressive expectiles (LCARE) model. We consider the dynamic changes in the tail distribution of stock market returns and the associated time-varying parameters, which is relatively rare in existing literature on tail risk in the Chinese stock market. We first determine homogeneous intervals through the local parametric approach (LPA) and then establish a CARE model with constant parameters within the homogeneous intervals. The lengths of the homogeneity intervals obtained through LPA provide strong evidence for the presence of potential structural changes in tail risk measurement. The efficacy of the LCARE model in predicting outcomes at various time scales has also been demonstrated effectively. The empirical evidence on portfolio strategies shows that the time-invariant portfolio protection (TIPP) strategy with time-varying multipliers, which is grounded in the LCARE framework, exhibits enhanced performance in comparison to other strategies. Thus, this study has the potential to serve as a valuable reference for government departments and investors seeking to assess and alert to the time-varying tail risk of the stock market across various market conditions and investment horizons.
  • Jinglin ZHAO, Muhammad HAFEEZ, Xiaoqin TONG
    Journal of Systems Science and Information. 2024, 12(6): 732-757. https://doi.org/10.21078/JSSI-2023-0040
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    In the context of the China-Pakistan Economic Corridor, this article evaluates how block chain technology might improve organizational performance (CPEC) through the sequential mediating role of artificial intelligence and environmental performance. Cross-sectional data were collected from one hundred respondents through a close-ended questionnaire-based survey of manufacturing companies, which was then analyzed using structural equation modeling, which structural equation modelling was used to analyze. The block chain technology benefits businesses in terms of the environment and economics. There is a focus on technology in every industry as the Industry 4.0 era gets underway. Block chain technology, a relatively new phenomenon, offers several opportunities for company operations improvement. Our findings showed that block chain technology favors the organizational performance through the sequential mediation of artificial intelligence and environmental performance, especially thanks to features like visibility, transparency, relationship management, and smart contracts. Also, it was discovered that block chain practices had a good relationship with both the environmental and economic paths to the firms' performance. At the same time, environmental performance is also positively correlated with the firm's economic well-being. The study found that improved economic and environmental performance were key drivers of increased organizational performance.
  • Chunmei HU, Jian YANG, Xiangchen YIN
    Journal of Systems Science and Information. 2024, 12(6): 758-774. https://doi.org/10.21078/JSSI-2023-0134
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    The growth of the Internet of Things (IoT) equipment business encourages the collection of large sizes of data. IoT data is being regarded as a new digital asset which contains valuable information. As a result, IoT data transactions are gaining in popularity, and data markets are starting to emerge. To support the smooth flow of data transactions, several academics offer market models and pricing techniques from various perspectives. However, the factors considered in the pricing model are still not comprehensive enough, and the willingness to sell of data providers has been ignored. Therefore, this paper investigates the pricing and profit maximization problems for the IoT data market who considers the willingness of data providers as well as data quality when purchasing data. Firstly, we analyze the factors that impact data providers' willingness to sell and give a definition of the willingness function. Secondly, we propose a data quality evaluation method and define a joint utility function based on data size and data quality. In addition, we build the profit function model of data market and give theoretical analysis. Finally, numerical experiments demonstrate that the suggested pricing mechanism can benefit the data market participants the most.
  • Abderrahmene HADJ BRAHIM, Hana ALI PACHA, Mohammed NAIM, Adda ALI PACHA
    Journal of Systems Science and Information. 2024, 12(6): 775-789. https://doi.org/10.21078/JSSI-2024-0054
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    In many applications of information processing, such as cryptography, generating random sequences presents many difficulties. In this paper, a new pseudo-random sequence is proposed, based on two chaotic systems, a logistic map and a seven-dimensional (7D) hyperchaotic system. The main process of the proposed generator is that it functions by using the logistic map to control the 7D hyperchaotic system, which exhibits random behavior to produce a pseudo-random sequence. Specifically, the logistic map is used to select one of the variables from the 7D hyperchaotic system. The variable selected at each iteration is used as a controller to fill the pseudo-random sequence, choosing from one of the other variables of the 7D hyperchaotic system. This means that in each iteration, the pseudo-random sequence takes a value from the 7D hyperchaotic system according to the logistic map and the selected variable of the 7D hyperchaotic system. This method allows the creation of a highly efficient pseudo-random generator through simple processes. Experimental and analysis results show that the proposed generator has good random characteristics, making it suitable for cryptography applications such as encryption algorithms.
  • N. SANDEEP, R. SURESH
    Journal of Systems Science and Information. 2024, 12(6): 790-803. https://doi.org/10.21078/JSSI-2024-0088
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    The Circular Manufacturing System (CMS) is a critical facet of the circular economy, embodying a closed-loop manufacturing model aligned with circular principles. This research area focuses on prolonging product life cycles and reducing energy and resource consumption. A recent literature review emphasized the need for clear definitions, scopes, and distinctions between CMS and other manufacturing paradigms like sustainable and green manufacturing. Although the 4Rs (Remanufacturing, Reuse, Reduce, Recycle) are commonly discussed in CMS contexts, a unified systemic approach is lacking. The study advocates for exploring CMS's foundational elements, refining performance metrics, and integrating it seamlessly into existing manufacturing systems. It also stresses the importance of analyzing business models, supply chains, and product design interdependencies using advanced technology. Advancements in these areas will enhance CMS theory and practice, aiding manufacturing firms in adopting circular economy principles effectively.
  • Lihui DENG, Shuyi DI, Yicheng LI
    Journal of Systems Science and Information. 2024, 12(6): 804-822. https://doi.org/10.21078/JSSI-2024-0038
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    Tourism destination branding is an important goal in the development of tourism industry, and brand image and brand loyalty are important components of destination brand equity. Based on analyzing the framework of influencing factors of brand image and brand loyalty in tourism destinations, this paper takes Xinjiang Production and Construction Corps of China as an example, and conducts an empirical study on the influencing mechanism of brand awareness, brand association, brand trust and perceived quality on brand image and brand loyalty in tourism destinations by constructing a structural equation model. We find that brand awareness, brand association, and perceived quality have positive effects on brand image and brand loyalty, and some of these effects are mediated by brand trust. In addition, we find that tourists' subjective experience, as reflected by tourists' age and frequency of travel, moderates each of the influences on brand image and brand loyalty differently. This study enriches the theory of tourism destination research and provides a basis for the improvement of tourism destination brand.