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Quality management in supply chain: Strategic implications and the paradox of AI inspection 供应链质量管理:人工智能检测的战略意义和悖论
IF 2.5 4区 管理学
DECISION SCIENCES Pub Date : 2025-03-07 DOI: 10.1111/deci.70003
Jun Pei, Ruiqi Wang, Ping Yan, Yinliang (Ricky) Tan
{"title":"Quality management in supply chain: Strategic implications and the paradox of AI inspection","authors":"Jun Pei,&nbsp;Ruiqi Wang,&nbsp;Ping Yan,&nbsp;Yinliang (Ricky) Tan","doi":"10.1111/deci.70003","DOIUrl":"https://doi.org/10.1111/deci.70003","url":null,"abstract":"<p>Artificial intelligence (AI) has transformed the quality control process with <i>AI inspection</i> technology, which reduces the need for costly physical resources and mitigates retail returns. Despite its revolutionizing impact on supply chain quality management, there is a notable gap in research on the implications of a manufacturer's adoption of AI inspection. This article addresses this gap by presenting a two-stage model that explores the consequences of AI inspection adoption for a downstream manufacturer and an upstream supplier. Our results show that higher AI-based inspection accuracy may not always benefit the manufacturer. This is because when the supplier's traditional inspection accuracy falls within an immediate range, the manufacturer's incentive to improve AI inspection accuracy diminishes, and the positive effect of AI inspection on retail returns cannot fully offset the technology expense. Moreover, our study explores the dynamics of technology-sharing strategies between the manufacturer and supplier. Despite potential revenue gains, the manufacturer may hesitate to share technology due to the risk of increased defective products with lower AI inspection accuracy, leading to a paradox where profitability coexists with losses. Surprisingly, the successful collaborative technology-sharing strategy may paradoxically lead to reduced technology investment. This occurs because technology-sharing enables significant marginal cost savings in retail returns, rendering the manufacturer to achieve a comparable inspection level with lower investment. Overall, this research highlights that adopting AI inspection does not guarantee benefits for the supply chain members and can sometimes be detrimental. Our study offers strategic guidance for decision-makers in supply chain quality management.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 5","pages":"509-526"},"PeriodicalIF":2.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Working apart together: How outcome control supports operations when working from home 协同工作:在家工作时,结果控制如何支持运营
IF 2.5 4区 管理学
DECISION SCIENCES Pub Date : 2025-03-05 DOI: 10.1111/deci.70002
Henri C. Dekker, Melanie L. Feldhues, Nikolay Georgiev
{"title":"Working apart together: How outcome control supports operations when working from home","authors":"Henri C. Dekker,&nbsp;Melanie L. Feldhues,&nbsp;Nikolay Georgiev","doi":"10.1111/deci.70002","DOIUrl":"https://doi.org/10.1111/deci.70002","url":null,"abstract":"<p>Working from home (WFH) significantly impacts firms’ operations by introducing altered control challenges regarding the facilitating and influencing of decisions. WFH can drastically limit the control options that managers—according to organizational control theory—can rely on, particularly behavior control and informal control, shifting emphasis to outcome control. Yet, the effectiveness of outcome control can also be constrained in a WFH setting, potentially resulting in a control loss. We conducted a field study among all customer due diligence teams of Nordea bank, exploiting teams’ abrupt shift to WFH after the COVID-19 disruption to examine how team leaders’ (TLs') reliance on outcome control based on performance information supported remote team operations and performance. Multilevel analysis of survey data collected in May/June 2020 from both TLs and team members (TMs) matched with other firm data shows that TLs’ reliance on outcome control supported favorable changes in TMs’ task performance after shifting to WFH. This effect is mediated by changes in team communication effectiveness, which, supported by performance information, enabled TLs to better manage team operations conducted from home. Collectively, our findings highlight the role of outcome control in supporting WFH by enabling remote team operations and performance.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 5","pages":"471-488"},"PeriodicalIF":2.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Managing context in Six Sigma projects: New themes from a methods-only replication 管理六西格玛项目中的上下文:来自纯方法复制的新主题
IF 2.5 4区 管理学
DECISION SCIENCES Pub Date : 2025-02-05 DOI: 10.1111/deci.70000
Tim Baker, Thamer N. Almutairi, Xun Xu, Lizao Zhang, Phillip W. Witt
{"title":"Managing context in Six Sigma projects: New themes from a methods-only replication","authors":"Tim Baker,&nbsp;Thamer N. Almutairi,&nbsp;Xun Xu,&nbsp;Lizao Zhang,&nbsp;Phillip W. Witt","doi":"10.1111/deci.70000","DOIUrl":"https://doi.org/10.1111/deci.70000","url":null,"abstract":"<p>We conduct a methods-only replication of Nair, Malhotra, and Ahire's study by analyzing 13 Six Sigma (SS) projects from nine small- to medium-sized enterprises (SMEs). Nair et al. analyzed 10 SS projects from seven large firms and found support for three propositions associating themes (i.e., expanded scope of analysis, clarity of metrics, and cross-functional integration) contributing to SS project success, as well as 10 propositions associating project contextual factors, project management elements, and themes. Our replication provides support for two of the original propositions, partial support for five original propositions, and no support for five original propositions. Note that one of the 13 original propositions from Nair et al. could not be replicated given data restrictions. These replication results suggest that SS project success and their associations with project management elements and project context are contingent on firm size. Importantly, for SMEs, unlike larger firms, expanded scope of analysis, clarity of metrics, and cross-functional integration are not important contributing factors to SS project success in SMEs. Instead, we derived two new themes (i.e., time-to-completion and prioritization) and seven corresponding propositions that appear to better explain how SMEs can manage SS project context to improve SS project performance. These two new themes illustrate the need for SS project teams within SMEs to be amenable to (a) emphasizing quick wins and (b) being more selective in pursuing process drivers for improvement.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 4","pages":"383-397"},"PeriodicalIF":2.5,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mining social media data via supervised topic model: Can social media posts inform customer satisfaction? 通过监督主题模型挖掘社交媒体数据:社交媒体帖子是否能告知客户满意度?
IF 2.5 4区 管理学
DECISION SCIENCES Pub Date : 2025-01-15 DOI: 10.1111/deci.12660
Yinghui Huang, Mei Li, Fugee Tsung, Xiangyu Chang
{"title":"Mining social media data via supervised topic model: Can social media posts inform customer satisfaction?","authors":"Yinghui Huang,&nbsp;Mei Li,&nbsp;Fugee Tsung,&nbsp;Xiangyu Chang","doi":"10.1111/deci.12660","DOIUrl":"https://doi.org/10.1111/deci.12660","url":null,"abstract":"<p>Customer satisfaction is crucial for any firm. Traditional methods of measuring customer satisfaction, such as customer surveys, are resource-intensive despite their effectiveness. We develop an innovative approach that leverages social media posts to evaluate customer satisfaction. Specifically, we augment survey data with social media content and propose a supervised topic model to predict customer satisfaction. Method-wise, our model accommodates texts from various social media platforms, with or without explicit customer ratings. In addition, we address the challenges associated with integrating multiple data sources. To empirically validate our approach, we utilize data from various social media platforms combined with customer surveys from target firms in seven essential industries in Hong Kong. Our model exhibits higher prediction accuracy compared to baseline methods. This research provides a cost-effective and efficient tool for transforming vast amounts of social media posts into valuable insights on customer satisfaction.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 4","pages":"423-442"},"PeriodicalIF":2.5,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Exploring the cost–carbon trade-off in using a mixed fleet of hydrogen trucks and diesel trucks 探索使用氢燃料卡车和柴油卡车混合车队的成本-碳权衡
IF 2.5 4区 管理学
DECISION SCIENCES Pub Date : 2024-12-22 DOI: 10.1111/deci.12659
Siqiang Guo, Erhan Kutanoglu, Shadi Goodarzi, Manjeet Singh
{"title":"Exploring the cost–carbon trade-off in using a mixed fleet of hydrogen trucks and diesel trucks","authors":"Siqiang Guo,&nbsp;Erhan Kutanoglu,&nbsp;Shadi Goodarzi,&nbsp;Manjeet Singh","doi":"10.1111/deci.12659","DOIUrl":"https://doi.org/10.1111/deci.12659","url":null,"abstract":"<p>Hydrogen trucks (HTs) offer promising potential for decarbonizing the transportation sector. Based on current technologies, they have significant advantages over electric trucks (ETs) in terms of range, refueling time, and performance in cold conditions. However, HTs are costly, and there are insufficient hydrogen refueling stations (HRSs). Gradually integrating HTs into the existing diesel truck (DT) fleet is a practical approach for many freight logistics companies. In this article, we formulate a mathematical model to route a mixed fleet of HTs and DTs, and we propose an algorithm called the curve descent search (CDS) to generate the Pareto set based on cost and carbon emissions. We find that CDS can generate better Pareto sets compared to existing algorithms in the literature. We use CDS to comprehensively explore the cost–carbon trade-off in using a mixed fleet. This question differentiates our study from previous research and is motivated by discussions with one of the largest third-party logistics companies in North America. Detailed experiments reveal important managerial insights, such as: (1) Achieving a significant reduction in carbon emissions (e.g., a 30% reduction compared to the current diesel fleet) does not need a very dense refueling infrastructure; (2) The cost–carbon trade-off for mixed fleets is relatively insensitive to variations in customer density and demand, suggesting that HTs can be applicable across a wide range of scenarios (including different sectors or regions); and (3) Although ETs are cheaper to use compared to HTs, their shorter range limits their competitiveness in terms of decarbonization efficiency and customer service.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"56 4","pages":"341-360"},"PeriodicalIF":2.5,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Explanation seeking and anomalous recommendation adherence in human-to-human versus human-to-artificial intelligence interactions 在人与人和人与人工智能的互动中寻求解释和异常推荐的遵从性
IF 2.8 4区 管理学
DECISION SCIENCES Pub Date : 2024-11-21 DOI: 10.1111/deci.12658
Tracy Jenkin, Stephanie Kelley, Anton Ovchinnikov, Cecilia Ying
{"title":"Explanation seeking and anomalous recommendation adherence in human-to-human versus human-to-artificial intelligence interactions","authors":"Tracy Jenkin,&nbsp;Stephanie Kelley,&nbsp;Anton Ovchinnikov,&nbsp;Cecilia Ying","doi":"10.1111/deci.12658","DOIUrl":"https://doi.org/10.1111/deci.12658","url":null,"abstract":"<p>The use of artificial intelligence (AI) in operational decision-making is growing, but individuals can display algorithm aversion, preventing adherence to AI system recommendations—even when the system outperforms human decision-makers. Understanding why such algorithm aversion occurs and how to reduce it is important to ensure AI is fully leveraged. While the ability to seek an explanation from an AI may be a promising approach to mitigate this aversion, there is conflicting evidence on their benefits. Based on several behavioral theories, including Bayesian choice, loss aversion, and sunk cost avoidance, we hypothesize that if a recommendation is perceived as an anomalous loss, it will decrease recommendation adherence; however, the effect will be mediated by explanations and differ depending on whether the advisor providing the recommendation and explanation is a human or an AI. We conducted a survey-based lab experiment set in the online rental market space and found that presenting a recommendation as a loss anomaly significantly reduces adherence compared to presenting it as a gain, however, this negative effect can be dampened if the advisor is an AI. We find explanation-seeking has a limited impact on adherence, even after considering the influence of the advisor; we discuss the managerial and theoretical implications of these findings.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"653-668"},"PeriodicalIF":2.8,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12658","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fine-tuning of artificial intelligence managers' logic in a supply chain with competing retailers 在有竞争零售商的供应链中对人工智能管理人员的逻辑进行微调
IF 2.8 4区 管理学
DECISION SCIENCES Pub Date : 2024-11-12 DOI: 10.1111/deci.12657
Yue Li, Ruiqing Zhao, Xiang Li, Tsan-Ming Choi
{"title":"Fine-tuning of artificial intelligence managers' logic in a supply chain with competing retailers","authors":"Yue Li,&nbsp;Ruiqing Zhao,&nbsp;Xiang Li,&nbsp;Tsan-Ming Choi","doi":"10.1111/deci.12657","DOIUrl":"https://doi.org/10.1111/deci.12657","url":null,"abstract":"<p>Today, with the advance of artificial intelligence, companies in the real world are using AI as managers to make operational decisions, who can respond quickly to market shocks and whose logic can be fine-tuned to programmed pessimism/optimism, that is, underestimating/overestimating the market. The introduction of AI managers poses new challenges to supply chain management, and how to manage AI managers warrants further exploration. We investigate the optimal AI manager fine-tuning strategies in a supply chain consisting of one manufacturer and two competing retailers, each operated by an AI manager in the face of an uncertain market shock. We establish the manufacturer–retailer AI manager fine-tuning game, where the manufacturer and two retailers endogenously decide whether to fine-tune their AI managers' logic. The market may suffer an uncertain shock, and once the shock occurs, the AI managers' logic settings and price decisions can be quickly adjusted. We find that the manufacturer would never fine-tune the AI manager, while the retailers may fine-tune their AI managers to programmed optimism. Notably, AI manager's fine-tunability only benefits the retailers and harms the manufacturer, entire supply chain, consumers, and social welfare. To make AI manager's fine-tunability beneficial to all participants, that is, to reach a win–win–win situation, we design two incentive mechanisms, retailer pessimism incentive mechanism and mutual pessimism incentive mechanism (MPIM), where MPIM can lead to the win–win–win situation. Further, we endogenize the compensation, endogenous retailer pessimism compensation and endogenous mutual pessimism compensation, both achieving the win–win–win outcome. We also make several extensions and provide suggestions for supply chain firms to fine-tune their AI managers' logic.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"639-652"},"PeriodicalIF":2.8,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
AI in business research 商业研究中的人工智能
IF 2.8 4区 管理学
DECISION SCIENCES Pub Date : 2024-11-06 DOI: 10.1111/deci.12655
Zhi Cao, Meng Li, Paul A Pavlou
{"title":"AI in business research","authors":"Zhi Cao,&nbsp;Meng Li,&nbsp;Paul A Pavlou","doi":"10.1111/deci.12655","DOIUrl":"https://doi.org/10.1111/deci.12655","url":null,"abstract":"<p>Artificial intelligence (AI) has emerged as a pivotal force in modern business transformation, garnering widespread attention from both practitioners and academics. With a notable exponential increase in AI-related studies, we provide a research framework aiming to synthesize the existing literature on AI in the business field. We conduct a comprehensive review of AI research spanning from 2010 to 2023 in 25 leading business journals according to this review framework. Specifically, we review the literature from three research perspectives: (i) AI applications, (ii) human perceptions of AI, and (iii) AI behavior. We also identify five principal research questions and offer suggestions for future research directions.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"518-532"},"PeriodicalIF":2.8,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Voice or text? The role of physician media choice on patient experience in online medical communities 语音还是短信?医生媒介选择对在线医疗社区患者体验的作用
IF 2.8 4区 管理学
DECISION SCIENCES Pub Date : 2024-11-06 DOI: 10.1111/deci.12654
Anfei Xia, Sandun C. Perera, Muhammad U. Ahmed, Jianying Tang, Jian-Jun Wang
{"title":"Voice or text? The role of physician media choice on patient experience in online medical communities","authors":"Anfei Xia,&nbsp;Sandun C. Perera,&nbsp;Muhammad U. Ahmed,&nbsp;Jianying Tang,&nbsp;Jian-Jun Wang","doi":"10.1111/deci.12654","DOIUrl":"https://doi.org/10.1111/deci.12654","url":null,"abstract":"<p>Online medical communities (OMCs) are a type of online healthcare, in which physician-patient interaction can be comprised of a variety of media options such as pictures, text, and voice. These media formats are often used to create a personalized patient experience in AI-driven conversational healthcare platforms. To explore how physician media usage affects patient experience, we propose a counterfactual causal inference model using AI-driven data mining methods on 131,083 online consultation records and 7,666,111 messages sent by physicians from one of the largest OMCs in China. Our study reveals the negative impact of physician use of voice on patient experience, compared to text. Drawing upon social support theory, we identify the mechanism by which physician media usage for voice produces a negative effect. The findings indicate that the negative effect of physicians' voice-media usage occurs mainly in low-risk disease conditions, by weakening the role of professional and emotional support. In contrast, in high-risk disease conditions, voice-media usage strengthens the role of professional and emotional support in improving the patient's experience. Our study is one of the first to focus on the social support attributes of the different media formats used in OMCs. We use advanced AI text-analysis algorithms to extract features related to social support in physician-patient conversations, and thus contribute to the use of AI in feature extraction for research.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"620-638"},"PeriodicalIF":2.8,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unsupervised news analysis for enhanced high-frequency food insecurity assessment 用于加强高频率粮食不安全评估的无监督新闻分析
IF 2.8 4区 管理学
DECISION SCIENCES Pub Date : 2024-10-13 DOI: 10.1111/deci.12653
Cascha van Wanrooij, Frans Cruijssen, Juan Sebastian Olier
{"title":"Unsupervised news analysis for enhanced high-frequency food insecurity assessment","authors":"Cascha van Wanrooij,&nbsp;Frans Cruijssen,&nbsp;Juan Sebastian Olier","doi":"10.1111/deci.12653","DOIUrl":"https://doi.org/10.1111/deci.12653","url":null,"abstract":"<p>This article introduces an artificial intelligence (AI)-based system for forecasting food insecurity in data-limited settings, employing unsupervised neural networks for topic modeling on news data. Unlike traditional methods, our system operates without relying on expert assumptions about food insecurity factors. Through a case study in Somalia, we show that the method can yield competitive performance, even in the absence of traditional food security indicators such as food prices. This system is valuable in supporting expert assessments of food insecurity, unlocking a wealth of untapped information from news outlets, and offering a path toward more frequent and automated food insecurity monitoring for timely crisis intervention.</p>","PeriodicalId":48256,"journal":{"name":"DECISION SCIENCES","volume":"55 6","pages":"605-619"},"PeriodicalIF":2.8,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/deci.12653","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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