作者机构:
[Chen, Zhongwen] Hengyang Normal Univ, Coll Econ & Management, Hengyang 421002, Peoples R China.;[Shi, Yanlin] Macquarie Univ, Dept Actuarial Studies & Business Analyt, Sydney, NSW 2109, Australia.;[Shu, Ao] Hunan Univ, Business Sch, Changsha 410012, Peoples R China.
通讯机构:
[Ao Shu] B;Business School, Hunan University, Changsha 410012, China
关键词:
mortality rates;Lee-Carter model;time-varying coefficients;rotated age pattern;life expectancy
摘要:
Abstract: Influential existing research has suggested that rather than being static, mortality declines decelerate at young ages and accelerate at old ages. Without accounting for this feature, the forecast mortality rates of the popular Lee–Carter (LC) model are less reliable in the long run. To provide more accurate mortality forecasting, we introduce a time-varying coefficients extension of the LC model by adopting the effective kernel methods. With two frequently used kernel functions, Epanechnikov (LC-E) and Gaussian (LC-G), we demonstrate that the proposed extension is easy to implement, incorporates the rotating patterns of mortality decline and is straightforwardly extensible to multi-population cases. Using a large sample of 15 countries over 1950–2019, we show that LC-E and LC-G, as well as their multi-population counterparts, can consistently improve the forecasting accuracy of the competing LC and Li–Lee models in both single- and multi-population scenarios. Keywords: mortality rates; Lee–Carter model; time-varying coefficients; rotated age pattern; life expectancy
期刊:
IEEE Transactions on Engineering Management,2023年:1-19 ISSN:0018-9391
通讯作者:
Wang, ZR
作者机构:
[Liu, Xin] Hengyang Normal Univ, Coll Econ & Management, Hengyang 421007, Peoples R China.;[Wang, Zongrun; Zhou, Yanju] Cent South Univ, Sch Business, Changsha 410017, Peoples R China.;[Kumar, Ajay] EMLYON Business Sch, F-69130 Ecully, France.;[Biswas, Baidyanath] Trinity Coll Dublin, Trinity Business Sch, Dublin D02 F6N2, Ireland.
通讯机构:
[Wang, ZR ] C;Cent South Univ, Sch Business, Changsha 410017, Peoples R China.
关键词:
Analytical models;Big data analytics;Cognition;Costs;Data mining;data science in healthcare;Diseases;healthcare technology;Medical diagnostic imaging;Medical services;online medicine;PQDR-LDA model;text mining
摘要:
Disease information mining is one of the critical factors affecting users' perception of the disease and has attracted extensive attention from the information management community in recent years. If the mined disease information is incompatible with the disease information perceived by the user, it will eventually lead to the loss of users from the online medical consultation platform, degrading its operation and management. Using existing models to mine disease information leads to significant errors when users perceive the disease. Therefore, this research extends the latent Dirichlet allocation (LDA) and Twitter-LDA models to propose an intelligent topic model, PQDR-LDA. Compared with the Twitter-LDA model, the proposed model has a smaller perplexity value, stronger generalization ability, greater coherence value, lower correlation between topics, and stronger ability in extracting the disease information. It is found that the accuracy of disease diagnosis is very low, and the user's need for perceiving the disease will be reduced while using the traditional model to mine only the text of user questions on an online medical consultation platform. The accuracy of disease diagnosis does not decrease while only mining the doctor's reply text. Disease information that is more suitable for the consultation text can be obtained, which in fact cannot meet the user's real appeal for health, and reduces the users’ needs in perceiving the disease. These findings have important management implications for the platform's operation and decision-making. Besides, users will ask questions in more medical texts simultaneously, which makes things more complicated. Unique management insights are obtained based on the disease information mining of user consultation texts through multiple consultation texts and multiple doctor replies. IEEE
摘要:
Urban clusters are important carriers for cities to participate in international competition and cooperation, and a booster for urban sustainable development. This study measured the degree of urban clusters by utilizing the panel data of 278 cities in China during 2004-2016. Then, an extended meta-frontier data envelopment analysis (EM-DEA) model was applied to estimate the total-factor ecological performance (UTEP) and decompose it into two sub-index from the perspective of "resource conservation" and "environmental friendliness". On these bases, we employed a dynamic panel data approach to examine and demonstrate the relationship between urban cluster and UTEP in two dimensions, and further explored transmission channels of urban clusters on UTEP by adding the mediating effect. The results show that resource conservation increases first and then decreases with the increasing of urban clustering level, while environmental friendliness showed the opposite trend, making the latter become the main way for urban clusters to improve the UTEP. Industrial structure supererogation and rationalization are transmission channels for environmental friendliness rather than resource conservation in the way of improvement of UTEP. Technology innovation, as well as technology diffusion, also improves UTEP to some extent. In addition, urban clusters in eastern and central China have the greatest improvement in UTEP, while such effects are not the case in western China. Urban clusters in the second half sample period are more conducive to the improvement of the UTEP, with these potentially being the gains from the improvement of the level and quality of urban clusters.
期刊:
Journal of Electronic Commerce Research,2020年21(2):75-95 ISSN:1938-9027
通讯作者:
Wang, Yaoyu
作者机构:
[Li, Xinchen] Hengyang Normal Univ, Coll Econ & Management, Hengyang, Hunan, Peoples R China.;[Liao, Qinyu] Univ Texas Rio Grande Valley, Robert C Vackar Coll Business & Entrepreneurship, Brownville, TX USA.;[Luo, Xin (Robert)] Univ New Mexico, Anderson Sch Management, Albuquerque, NM 87131 USA.;[Wang, Yaoyu] Soochow Univ, Dongwu Sch Business, Suzhou, Jiangsu, Peoples R China.
关键词:
Social media;Cognitive reputation;Affective reputation;Interaction Experience;Utilitarian value;Hedonic value
摘要:
E-commerce enterprises use different social media channels to build their online reputation through customers' rich interaction experiences, but no study has differentiated the individual impact of consumer-to-consumer and business-to-consumer interaction features on e-commerce online reputations. This study investigates the linkage between five interaction characteristics, consumers' perceived values, and e-commerce online reputations. The results of our study show that only the perceived hedonic value has a significant influence on e-commerce online reputations. Perceived control, reciprocity, and responsiveness have a positive and significant influence on both perceived utilitarian value and perceived hedonic value. Sociability only shows a significant and negative influence on perceived utilitarian value. Personalization has a significant and positive influence on utilitarian value only. Perceived hedonic value mediates the influence of three interaction features (perceived control, reciprocity, and responsiveness) on both e-commerce cognitive and affective reputations. The implications of the study for research and practice are discussed.