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学者姓名：唐中君
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摘要 ：
New product development process is complex, involving many decisions that are based on incomplete and unrepresentative weak signal information. In this case, cognitive bias will affect decision-making significantly, leading to development failure. Therefore, we propose a weak signal evolution prediction method to enrich weak signal information and exclude unrepresentative weak signal information. Specifically, the weak signal evolution prediction method contains three parts. First, on the basis of matter-element extension model, the system diagram approach is used to construct evolutionary three-process prediction index system. Second, evolutionary matter elements, classical and joint domains, correlation functions, and weight coefficients are determined. Finally, the discriminant criterion is improved to divide the evolution evaluation stage, and then weak signal evolution prediction method is constructed on the foundation of improved matter-element extension model. We take perovskite photovoltaic cells as an example to verify the performance of the weak signal evolution prediction method proposed in this article. Results showed that the method proposed in this article has higher accuracy and applicability, which is more in line with practical situations. The research results further expand the matter element extension model, providing a new approach to reduce cognitive bias in the process of new product development for enterprises, and offering new insights for new product development. Meanwhile, this study also has shortcomings such as a limited research perspective and a single case selection.
关键词 ：
Asymmetric proximity Asymmetric proximity meaning construction meaning construction weak signal evolution weak signal evolution extension theory extension theory
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| GB/T 7714 | Zhao, Dongyuan , Tang, Zhongjun , Wang, Jing et al. A Predictive Method for Weak Signal Evolution During New Product Development Based on an Improved Matter-Element Extension Model [J]. | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT , 2024 , 71 : 8488-8502 . |
| MLA | Zhao, Dongyuan et al. "A Predictive Method for Weak Signal Evolution During New Product Development Based on an Improved Matter-Element Extension Model" . | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 71 (2024) : 8488-8502 . |
| APA | Zhao, Dongyuan , Tang, Zhongjun , Wang, Jing , Han, Zhongya , Sun, Fengxia , He, Duokui et al. A Predictive Method for Weak Signal Evolution During New Product Development Based on an Improved Matter-Element Extension Model . | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT , 2024 , 71 , 8488-8502 . |
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摘要 ：
Live streaming shopping, as a novel sales channel, has caught much attention from researchers and practitioners. Its unique features, such as the commission rate, fixed fee and number of followers of the live streamer, appear different from traditional wholesale-contract sales channels. But few studies have examined the impact of these factors on manufacturers' opening live streaming shopping channel decisions. To address this gap, we develop game theoretic models to examine whether a manufacturer should hire a live streamer to open a live streaming shopping channel on an e-commerce platform where the manufacturer's direct channel and third-party e-retailer co-exist. We consider the impact of the commission rate, fixed fee and number of followers of the live streamer on the operating decisions and profits of the manufacturer and e-retailer. Then we identify the threshold-conditions where the manufacturer and e-retailer are better off or worse off by opening a live streaming shopping channel. We show that opening a live streaming shopping channel may hurt or harm the manufacturer's profit, depending on the interaction of above three factors. The manufacturer may be willing to open a live streaming shopping channel when the commission rate and fixed fee are both small, or when the commission rate and number of followers are both large and the fixed fee is small. The e-retailer could also benefit from opening a live streaming shopping channel. These insights appear novel in the literature. We further show that opening a live streaming shopping channel could improve the consumer surplus. We extend our model to price competition to verify our main conclusions. These insights may help manufacturers decide whether or not to open live streaming shopping channels and help manufacturers and extant retailers develop optimal operating decisions and improve profits when participating in live streaming shopping.
关键词 ：
Game theory Game theory Live streaming shopping Live streaming shopping e-commerce e-commerce Supply chain Supply chain
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| GB/T 7714 | Zhang, Tao , Tang, Zhongjun . Should manufacturers open live streaming shopping channels? [J]. | JOURNAL OF RETAILING AND CONSUMER SERVICES , 2023 , 71 . |
| MLA | Zhang, Tao et al. "Should manufacturers open live streaming shopping channels?" . | JOURNAL OF RETAILING AND CONSUMER SERVICES 71 (2023) . |
| APA | Zhang, Tao , Tang, Zhongjun . Should manufacturers open live streaming shopping channels? . | JOURNAL OF RETAILING AND CONSUMER SERVICES , 2023 , 71 . |
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摘要 ：
Time-series clustering of view counts with changes in online time can identify animated series with similar evolutionary count patterns over time, which may help companies reduce their investment risk. For time-series data of animation view counts, most existing time-series clustering methods ignore both the local relationships within data and global relationships between data, making it challenging to identify animated series with similar evolutionary patterns. Therefore, we propose a two-stage deep graph clustering method that involves graph data construction and deep graph clustering. Specifically, graph data construction converts time-series data into graph data, while deep graph clustering uses a temporal convolutional network and graph convolutional network to learn features from the time-series data and graph data, respectively. The entire model is then trained end-to-end to complete the clustering task, utilizing a dual self-supervised module. This study utilizes two datasets to evaluate the clustering performance of our proposed model in comparison to baseline methods. The datasets consist of view count data from 185 animated series on Tencent Video from 2018 to 2022, as well as a public time-series BME dataset. The experimental results demonstrate that our model outperforms the baseline methods on both datasets. Additionally, through visualizing the identified three classes of evolutionary patterns, we propose new product development strategies for animation enterprises.
关键词 ：
GCN GCN Animation view counts Animation view counts Evolutionary patterns Evolutionary patterns Deep graph clustering Deep graph clustering Time-series clustering Time-series clustering
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| GB/T 7714 | He, Duokui , Tang, Zhongjun , Chen, Qianqian et al. A two-stage deep graph clustering method for identifying the evolutionary patterns of the time series of animation view counts [J]. | INFORMATION SCIENCES , 2023 , 642 . |
| MLA | He, Duokui et al. "A two-stage deep graph clustering method for identifying the evolutionary patterns of the time series of animation view counts" . | INFORMATION SCIENCES 642 (2023) . |
| APA | He, Duokui , Tang, Zhongjun , Chen, Qianqian , Han, Zhongya , Zhao, Dongyuan , Sun, Fengxia . A two-stage deep graph clustering method for identifying the evolutionary patterns of the time series of animation view counts . | INFORMATION SCIENCES , 2023 , 642 . |
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摘要 ：
5G mobile communication technology is anticipated to merge with many other sectors, spurring innovation and creating substantial ripple effects. Despite the significance of this advancement, current research provides limited knowledge of users' behavioral reactions to the affordances, values, and trust generated from 5G technology. To investigate this relationship, this study used the Stimulus-response theory and the consumption values theory. The empirical data was gath-ered from 373 consumers in China using a survey method. To validate the model's suggested relationships, the author utilized the partial least squares-structural equation modelling (PLS-SEM) technique. The finding designates that the affordances and purchase intention relationship was mediated by consumption values and trust. Given the significance of 5G technology and its potential, this study investigates what drives and deters consumers from obtaining 5G technology. Original findings insights on the role of affordances in developing marketing strategies and increasing consumer intentions to purchase 5G technology products.
关键词 ：
5G technology 5G technology Consumption values Consumption values User ?s intentions User ?s intentions Affordances Affordances Trust Trust
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| GB/T 7714 | Shah, Sayed Kifayat , Tang, Zhongjun , Olah, Judit et al. The relationship between 5G technology affordances, consumption values, trust and intentions: An exploration using the TCV and S-O-R paradigm [J]. | HELIYON , 2023 , 9 (3) . |
| MLA | Shah, Sayed Kifayat et al. "The relationship between 5G technology affordances, consumption values, trust and intentions: An exploration using the TCV and S-O-R paradigm" . | HELIYON 9 . 3 (2023) . |
| APA | Shah, Sayed Kifayat , Tang, Zhongjun , Olah, Judit , Popp, Jozsef , Acevedo-Duque, Angel . The relationship between 5G technology affordances, consumption values, trust and intentions: An exploration using the TCV and S-O-R paradigm . | HELIYON , 2023 , 9 (3) . |
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摘要 ：
提出并验证考虑消费动机和动态竞争的电影日需求预测模型.考虑非粉丝及粉丝型的消费动机,构建电影消费两阶段过程模型;融合该模型和Bass模型,考虑竞争导致市场潜量的动态性,考虑映前被关注度、口碑、节假日对票房的影响,提出电影日需求预测模型.利用2016 ～2017年上映的电影数据验证该模型,并与Bass模型对比分析.结果 显示,该模型预测效果优于Bass模型.因考虑竞争导致的动态市场潜量,考虑粉丝型消费者由续集效应及改编效应导致的动态市场潜量提升,该模型能显著提高预测准确度.利用映前被关注度和电影口碑数据,该模型能实现映前及上映早期的预测.该模型可推广至存在消费动机不同、市场动态竞争的其它短生命周期体验品的需求预测,是对Bass模型的改进.
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| GB/T 7714 | 唐中君 , 周亚丽 . 考虑消费动机和动态竞争的电影日需求预测模型 [J]. | 运筹与管理 , 2021 , 30 (6) : 172-180 . |
| MLA | 唐中君 et al. "考虑消费动机和动态竞争的电影日需求预测模型" . | 运筹与管理 30 . 6 (2021) : 172-180 . |
| APA | 唐中君 , 周亚丽 . 考虑消费动机和动态竞争的电影日需求预测模型 . | 运筹与管理 , 2021 , 30 (6) , 172-180 . |
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摘要 ：
基于信息收集的降低需求可变性两级供应链博弈研究
关键词 ：
STACKELBERG博弈 STACKELBERG博弈 库存决策 库存决策 需求可变性 需求可变性 信息收集 信息收集 决策科学 决策科学
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| GB/T 7714 | 禹海波 , 李欣 , 李健 et al. 基于信息收集的降低需求可变性两级供应链博弈研究 [J]. | 禹海波 , 2021 , 35 (3) : 229-240 . |
| MLA | 禹海波 et al. "基于信息收集的降低需求可变性两级供应链博弈研究" . | 禹海波 35 . 3 (2021) : 229-240 . |
| APA | 禹海波 , 李欣 , 李健 , 李泉林 , 唐中君 , 管理工程学报 . 基于信息收集的降低需求可变性两级供应链博弈研究 . | 禹海波 , 2021 , 35 (3) , 229-240 . |
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摘要 ：
新兴产业的发展伴随着不确定性和复杂性,风险贯穿于新兴产业的成长史.针对新兴产业发展过程中无标准参照的风险特性,构建了一个基于逼近理想标准参照值的"垂面"距离风险评估模型;考虑新兴产业成长及风险变化的速度"惯性",提出了一种基于变化速度特征的风险预警模型.以我国航天器制造业2006-2014年期间的数据为样本,对新兴产业的风险评估与预警进行了实证分析,结果表明:此期间,我国航天器制造业的四类风险演变状态呈现多阶段的具有差异性的特点,综合风险演化展现出无序混乱态势.此外,在航天器制造产业的未来发展进程中,其面临的四类风险中成长性风险最为突出,是预警的重点;技术风险和环境风险较为弱化,但仍需要适当监控;市场风险呈现无警信号,表明其市场前景依然乐观.
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| GB/T 7714 | 杨早立 , 綦萌 , 黄鲁成 et al. "距离"与"速度"视角下的新兴产业风险评估及其预警——以航天器制造产业为例 [J]. | 管理评论 , 2021 , 33 (7) : 43-53 . |
| MLA | 杨早立 et al. ""距离"与"速度"视角下的新兴产业风险评估及其预警——以航天器制造产业为例" . | 管理评论 33 . 7 (2021) : 43-53 . |
| APA | 杨早立 , 綦萌 , 黄鲁成 , 唐中君 . "距离"与"速度"视角下的新兴产业风险评估及其预警——以航天器制造产业为例 . | 管理评论 , 2021 , 33 (7) , 43-53 . |
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摘要 ：
基于存在潜伏期的仓室模型,依据消费者具有选择权和判断力的特性,首先提出了考虑人群非接触情形下的消费者涌现行为数理模型,并综合考虑消费者的冲动消费、人群间的交互行为等多种属性以刻画不同群体间的转移概率。其次,构建了数理模型的演化动力学方程,通过实例验证了数理模型的有效性。最后,运用该模型论证得到了短生命周期体验品的消费者涌现行为机理。
关键词 ：
仓室模型 仓室模型 消费者行为 消费者行为 涌现机理 涌现机理 涌现行为 涌现行为 短生命周期体验品 短生命周期体验品
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| GB/T 7714 | 唐中君 , 朱慧珂 . 短生命周期体验品的消费者涌现行为演化机理 [J]. | 工业工程与管理 , 2021 , 26 (05) : 59-67 . |
| MLA | 唐中君 et al. "短生命周期体验品的消费者涌现行为演化机理" . | 工业工程与管理 26 . 05 (2021) : 59-67 . |
| APA | 唐中君 , 朱慧珂 . 短生命周期体验品的消费者涌现行为演化机理 . | 工业工程与管理 , 2021 , 26 (05) , 59-67 . |
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摘要 ：
为获得改进的分类算法BP_Adaboost,利用思维进化算法(MEA)和列文伯格-马夸尔特算法(LM)结合改进的BP神经网络作为弱分类器,由改进的弱分类器集成得到MEA-LM-BP_Adaboost算法.提出了基于MEA-LM-BP_Adaboost算法的首轮融资时总票房分类预测方法,该方法包括变量选取及操作化处理、网络参数优化、MEA改进弱分类器、LM算法改进弱分类器、MEA-LM-BP_Adaboost算法的流程设计、待预测电影验证6个部分.选用2013～2018年的245部国产电影作为样本验证该预测方法和模型,测试集分类准确率可达73.3％.最后在模型准确率、稳定性、K折交叉验证3方面进行模型整体性能比较,结果表明本文提出的模型整体性能最好.
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| GB/T 7714 | 唐中君 , 王美月 , 周欣浩 et al. BP_Adaboost算法的改进及在首轮融资时总票房分类预测中的应用 [J]. | 科技促进发展 , 2021 , 17 (6) : 1158-1168 . |
| MLA | 唐中君 et al. "BP_Adaboost算法的改进及在首轮融资时总票房分类预测中的应用" . | 科技促进发展 17 . 6 (2021) : 1158-1168 . |
| APA | 唐中君 , 王美月 , 周欣浩 , 杨崇耀 . BP_Adaboost算法的改进及在首轮融资时总票房分类预测中的应用 . | 科技促进发展 , 2021 , 17 (6) , 1158-1168 . |
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摘要 ：
Purpose Because of short life cycle and fluctuating greatly in total sales volumes (TSV), it is difficult to accumulate enough sales data and mine an attribute set reflecting the common needs of all consumers for a kind of experiential product with short life cycle (EPSLC). Methods for predicting TSV of long-life-cycle products may not be suitable for EPSLC. Furthermore, point prediction cannot obtain satisfactory prediction results because information available before production is inadequate. Thus, this paper aims at proposing and verifying a novel interval prediction method (IPM). Design/methodology/approach Because interval prediction may satisfy requirements of preproduction investment decision-making, interval prediction was adopted, and then the prediction difficult was converted into a classification problem. The classification was designed by comparing similarities in attribute relationship patterns between a new EPSLC and existing product groups. The product introduction may be written or obtained before production and thus was designed as primary source information. IPM was verified by using data of crime movies released in China from 2013 to 2017. Findings The IPM is valid, which uses product introduction as input, classifies existing products into three groups with different TSV intervals, mines attribute relationship patterns using content and association analyses and compares similarities in attribute relationship patterns - to predict TSV interval of a new EPSLC before production. Originality/value Different from other studies, the IPM uses product introduction to mine attribute relationship patterns and compares similarities in attribute relationship patterns to predict the interval values. It has a strong applicability in data content and structure and may realize rolling prediction.
关键词 ：
Attribute relationship pattern Attribute relationship pattern Code category system Code category system Experiential product with short life cycle Experiential product with short life cycle Interval prediction Interval prediction Pattern network graph Pattern network graph Sales prediction Sales prediction
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| GB/T 7714 | Tang, Zhongjun , Wang, Tingting , Cui, Junfu et al. Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns [J]. | MANAGEMENT DECISION , 2021 , 59 (10) : 2528-2548 . |
| MLA | Tang, Zhongjun et al. "Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns" . | MANAGEMENT DECISION 59 . 10 (2021) : 2528-2548 . |
| APA | Tang, Zhongjun , Wang, Tingting , Cui, Junfu , Han, Zhongya , He, Bo . Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns . | MANAGEMENT DECISION , 2021 , 59 (10) , 2528-2548 . |
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