Decision Support Systems最新文献_第10页

Selecting textual analysis tools to classify sustainability information in corporate reporting 选择文本分析工具，对企业报告中的可持续发展信息进行分类

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-11 DOI: 10.1016/j.dss.2024.114269

Frederik Maibaum , Johannes Kriebel , Johann Nils Foege

{"title":"Selecting textual analysis tools to classify sustainability information in corporate reporting","authors":"Frederik Maibaum , Johannes Kriebel , Johann Nils Foege","doi":"10.1016/j.dss.2024.114269","DOIUrl":"10.1016/j.dss.2024.114269","url":null,"abstract":"<div><p>Information on firms' sustainability often partly resides in unstructured data published, for instance, in annual reports, news, and transcripts of earnings calls. In recent years, researchers and practitioners have started to extract information from these data sources using a broad range of natural language processing (NLP) methods. While there is much to be gained from these endeavors, studies that employ these methods rarely reflect upon the validity and quality of the chosen method—that is, how adequately NLP captures the sustainability information from text. This practice is problematic, as different NLP techniques lead to different results regarding the extraction of information. Hence, the choice of method may affect the outcome of the application and thus the inferences that users draw from their results. In this study, we examine how different types of NLP methods influence the validity and quality of extracted information. In particular, we compare four primary methods, namely (1) dictionary-based techniques, (2) topic modeling approaches, (3) word embeddings, and (4) large language models such as BERT and ChatGPT, and evaluate them on 75,000 manually labeled sentences from 10-K annual reports that serve as the ground truth. Our results show that dictionaries have a large variation in quality, topic models outperform other approaches that do not rely on large language models, and large language models show the strongest performance. In large language models, individual fine-tuning remains crucial. One-shot approaches (i.e., ChatGPT) have lately surpassed earlier approaches when using well-designed prompts and the most recent models.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114269"},"PeriodicalIF":7.5,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167923624001027/pdfft?md5=778287af14f22b6f2973f34c9352e358&pid=1-s2.0-S0167923624001027-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141414917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unraveling juxtaposed effects of biometric characteristics on user security behaviors: A controversial information technology perspective 揭示生物识别特征对用户安全行为的并列影响：有争议的信息技术视角

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-10 DOI: 10.1016/j.dss.2024.114267

Jing Zhang , Zilong Liu , Xin (Robert) Luo

{"title":"Unraveling juxtaposed effects of biometric characteristics on user security behaviors: A controversial information technology perspective","authors":"Jing Zhang , Zilong Liu , Xin (Robert) Luo","doi":"10.1016/j.dss.2024.114267","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114267","url":null,"abstract":"<div><p>Biometric authentication has become ubiquitous and profoundly impacts decision-making for both individuals and firms. Despite its extensive implementation, there is a discernible knowledge gap in understanding the nuanced influence of biometric characteristics on user security behaviors. To advance this line of research, we embrace the controversial information technology framework to delve into the juxtaposed nature of biometric characteristics, wherein they concurrently yield benefits and raise concerns that manifest in opposing effects on users' switching behavior. Adopting a sequential mixed methods approach, we first conducted semi-structured interviews that uncovered three key biometric characteristics and identified two benefits and two concerns associated with them. A follow-up survey was conducted to explore the interplay between each identified construct. The results emphasize the pivotal role of biometric characteristics in shaping user security behavior. Our research contributes to theoretical understanding by scrutinizing user behaviors vis-à-vis biometric authentication through a controversial IT perspective.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114267"},"PeriodicalIF":7.5,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic product competitive analysis based on online reviews 基于在线评论的动态产品竞争分析

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-10 DOI: 10.1016/j.dss.2024.114268

Lu Zheng , Lin Sun , Zhen He , Shuguang He

{"title":"Dynamic product competitive analysis based on online reviews","authors":"Lu Zheng , Lin Sun , Zhen He , Shuguang He","doi":"10.1016/j.dss.2024.114268","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114268","url":null,"abstract":"<div><p>Competitive intelligence is vital for enterprises to survive in the market. Recently, online reviews have gained popularity among enterprises and researchers as a means to acquire timely and precise competitive insights. However, extant studies overlook the evolution of competitive information because they do not account for the variation of online reviews and products. In this research, we propose a method for dynamic competitive analysis by concentrating on the changes in products and online reviews. First, products and their related online reviews are analyzed via Dynamic Topic Model to derive product features mentioned in different slices. Second, we use sentiment analysis to estimate product performance and transfer the results into a product competitive relation network. Third, we implement competitive analysis from the perspectives of products and markets based on competitiveness propagation. By tracking the evolution of competitive relations among products, we discover competitors and glean more competitive insights. Lastly, a case study of laptops is used for validation. Experimental results indicate that our method is effective in capturing evolving and potential competitive relations among products.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114268"},"PeriodicalIF":7.5,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From engagement to retention: Unveiling factors driving user engagement and continued usage of mobile trading apps 从参与到留存：揭示驱动用户参与和持续使用移动交易应用程序的因素

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-10 DOI: 10.1016/j.dss.2024.114265

Sajani Thapa , Swati Panda , Ashish Ghimire , Dan J. Kim

{"title":"From engagement to retention: Unveiling factors driving user engagement and continued usage of mobile trading apps","authors":"Sajani Thapa , Swati Panda , Ashish Ghimire , Dan J. Kim","doi":"10.1016/j.dss.2024.114265","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114265","url":null,"abstract":"<div><p>The popularity of online mobile trading has led to an increase in the development of mobile stock trading applications. Despite this increase in popularity, there is a dearth of empirical studies that examine the factors influencing the continued usage intention of these applications (hereafter, apps). Drawing on stimulus-organism-response (S-O-R) theory, this paper investigates the features of stock trading apps that generate consumer engagement and consequently, continued app usage intention. In study 1, through semi-structured interviews, we establish four key drivers of customer engagement with stock trading apps, and two possible moderators influencing the relationship between customer app engagement and continued usage intention. In study 2, we examine these key drivers by surveying stock trading app users from three different Facebook stock trading communities. The results confirm that the social presence and security features of these apps are significantly associated with consumer stock trading app engagement. We also find that fear of uncertainty and perceived corporate hypocrisy weaken the effect of customer app engagement on continued app usage intention. The study findings add to the literature on app usage and customer engagement and provide insights for fintech service companies to help them understand the factors that enhance consumer engagement with these apps.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114265"},"PeriodicalIF":7.5,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decomposing the hazard function into interpretable readmission risk components 将危险函数分解为可解释的再入院风险成分

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-08 DOI: 10.1016/j.dss.2024.114264

James Todd, Steven E. Stern

{"title":"Decomposing the hazard function into interpretable readmission risk components","authors":"James Todd, Steven E. Stern","doi":"10.1016/j.dss.2024.114264","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114264","url":null,"abstract":"<div><p>Hospital decision-makers use predictive models to proactively manage risk of readmission for discharged patients. While predictions from classification models are easily integrated into decision-making processes, it is unclear how to best integrate predictions of the evolution of risk from time-to-event models. We propose a method for summarising predictions of risk over time that produces interpretable components for use in a variety of decision-making processes. The proposed method summarises predictions of risk over time (hazard functions) by approximating them with a parametric smoother. The components of the smoothed approximation can then serve as the basis for decision-making. To demonstrate the proposed summarisation method, we apply it in the specific case of a previously published model for patients discharged from a large teaching hospital on the Gold Coast, Australia. In this context, we describe how the summaries produced by the method could be used to estimate time until a patient reaches a stable, persistent risk level or to stratify patients according to risks of readmission in excess of patient-specific baselines. Our method is anticipated to be valuable in and outside of healthcare for settings where the evolution of risk is important, with specific examples including post-transplantation risk and reinjury risks.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114264"},"PeriodicalIF":7.5,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167923624000976/pdfft?md5=cb8f1fab985f1a894cd6378e54f73ce8&pid=1-s2.0-S0167923624000976-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influentials, early adopters, or random targets? Optimal seeding strategies under vertical differentiations 影响者、早期采用者还是随机目标？垂直差异下的最佳播种策略

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-06-05 DOI: 10.1016/j.dss.2024.114263

Fang Cui , Le Wang , Xin (Robert) Luo , Xueying Cui

{"title":"Influentials, early adopters, or random targets? Optimal seeding strategies under vertical differentiations","authors":"Fang Cui , Le Wang , Xin (Robert) Luo , Xueying Cui","doi":"10.1016/j.dss.2024.114263","DOIUrl":"https://doi.org/10.1016/j.dss.2024.114263","url":null,"abstract":"<div><p>Product seeding, defined as the act by which firms send products to selected customers and encourage them to spread word of mouth, is a critical decision support strategy for the success of new products. Using multiple agent-based simulation techniques, we investigated the relative importance of three widely adopted seeding strategies (seeding influentials, early adopters, and random targets) in a competitive market in which products are vertically differentiated in terms of quality and brand strength. We found robust evidence that the finding of an optimal seeding strategy depends on consumers' propensity to spread negative WOM. When negative WOM propensity is low, seeding influentials outperform seeding early adopters or random targets. When negative WOM propensity is high, decision-making about an optimal seeding strategy relies on the relative quality and brand strength of the product and the focal firm's objective. In particular, if a product's relative quality is low, seeding early adopters is the optimal seeding strategy in terms of both market share (MS) and net present value (NPV); if the product's relative quality is equal, seeding early adopters is most effective for increasing MS, while seeding influentials is the best for increasing NPV; and if the product's relative quality is high, seeding influentials is the optimal strategy, except that for products with strong brand strength and firm aims at maximizing the MS growth. We conclude the paper by discussing its theoretical contributions and managerial relevance for decision support.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"183 ","pages":"Article 114263"},"PeriodicalIF":7.5,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141324894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cyber resilience framework for online retail using explainable deep learning approaches and blockchain-based consensus protocol 使用可解释的深度学习方法和基于区块链的共识协议的在线零售网络弹性框架

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-05-24 DOI: 10.1016/j.dss.2024.114253

Karim Zkik , Amine Belhadi , Sachin Kamble , Mani Venkatesh , Mustapha Oudani , Anass Sebbar

{"title":"Cyber resilience framework for online retail using explainable deep learning approaches and blockchain-based consensus protocol","authors":"Karim Zkik , Amine Belhadi , Sachin Kamble , Mani Venkatesh , Mustapha Oudani , Anass Sebbar","doi":"10.1016/j.dss.2024.114253","DOIUrl":"10.1016/j.dss.2024.114253","url":null,"abstract":"<div><p>Online retail platforms encounter numerous challenges, such as cyber-attacks, data breaches, device failures, and operational disruptions. These challenges have intensified in recent years, underscoring the importance of prioritizing resilience for businesses. Unfortunately, conventional cybersecurity methods have proven insufficient in thwarting sophisticated cybercrime tactics. This paper proposes a novel resilience strategy that leverages Explainable Deep Learning technologies and a Blockchain-based consensus protocol strategy. By combining these two approaches, our strategy enables rapid incident detection, explains the features and related vulnerabilities that are used, and enhances decision-making during cyber incidents. To validate the efficacy of our approach, we conducted experiments using NAB datasets, preprocessed and trained the data, and performed an experimental study on real online retail architectures. Our results demonstrate the effectiveness of the proposed framework in supporting business and operation continuity and creating more efficient cyber resilience strategies that will enhance decision-making capabilities.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"182 ","pages":"Article 114253"},"PeriodicalIF":7.5,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141134035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Supporting organizational decisions on How to improve customer repurchase using multi-instance counterfactual explanations 利用多实例反事实解释为组织决策提供支持：如何提高客户回购率

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-05-24 DOI: 10.1016/j.dss.2024.114249

André Artelt , Andreas Gregoriades

{"title":"Supporting organizational decisions on How to improve customer repurchase using multi-instance counterfactual explanations","authors":"André Artelt , Andreas Gregoriades","doi":"10.1016/j.dss.2024.114249","DOIUrl":"10.1016/j.dss.2024.114249","url":null,"abstract":"<div><p>Improving customer repurchase intention constitutes a key activity for maintaining sustainable business performance. Returning customers provide many economic and other benefits to businesses. In contrast, attracting new customers is a process that is associated with high costs. This work proposes a novel counterfactual explanations methodology that utilizes textual data from electronic word of mouth to recommend business changes that can improve customers' repurchase behavior. Counterfactual explanation methods gained considerable attention because their logic aligns with human reasoning and the fact that they can recommend low-cost actions on how to turn an unfavorable outcome into a favorable. Most counterfactual explanation methods however recommend actions that can change the outcome of individual instances (i.e. one customer) rather than a group of instances. Therefore, this work proposes a multi-instance counterfactual explanation method that recommends optimum changes to an organization's practices/policies that increase repurchase intention for many customers or customer segments.</p><p>The proposed methodology utilizes topic modeling to extract customer opinions from online reviews' text and use topics as features to train a binary classifier that predicts customer revisit intention. Multi-instance counterfactual explanations are computed for all or different groups of non-revisiting customers, recommending optimum business changes that can increase revisit intention. The proposed methodology is empirically evaluated through a case study on the restaurant revisit problem and compared against a prominent alternative from the literature. The results show that the method has better performance to the alternative method and produces recommendations that are actionable and abide by the customer-repurchase literature.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"182 ","pages":"Article 114249"},"PeriodicalIF":7.5,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141134242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Focusing on the fundamentals? An investigation of the relationship between corporate social irresponsibility and data breach risk 关注根本问题？企业社会责任与数据泄露风险之间的关系调查

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-05-23 DOI: 10.1016/j.dss.2024.114252

Junmin Xu , Wei Thoo Yue , Alvin Chung Man Leung , Qin Su

{"title":"Focusing on the fundamentals? An investigation of the relationship between corporate social irresponsibility and data breach risk","authors":"Junmin Xu , Wei Thoo Yue , Alvin Chung Man Leung , Qin Su","doi":"10.1016/j.dss.2024.114252","DOIUrl":"10.1016/j.dss.2024.114252","url":null,"abstract":"<div><p>In an era of growing social activism, companies engaged in socially irresponsible practices are increasingly vulnerable to data breaches, resulting in substantial reputational and financial losses. This study examines how corporate social irresponsibility (CSI) influences a company's data breach risk. We argue that CSI has an impact on data breach risk by influencing the intentional behaviors of both employees and external hackers. Given that CSI is a broad concept and can take on various forms, we further examine whether some forms of CSI pose a more significant threat than others. Our empirical analysis of data breaches in publicly listed US firms from 2005 to 2017 indicates that compared to the forms of CSI that violate broader social norms (e.g., environmental damages), CSI activities that jeopardize a company's economic value delivery (e.g., product deficiencies) play a more dominant role in driving data breach risk. Furthermore, we find that corporate social responsibility (CSR) can have a dual impact on moderating the relationship between CSI and data breaches. While CSR often helps mitigate CSI-induced data breach risk, this risk is heightened when both CSR and CSI relate to a firm's economic value delivery. This study provides critical insights into how companies can navigate complex data breach risk by managing their social performance.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"182 ","pages":"Article 114252"},"PeriodicalIF":7.5,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141130365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain as a trust machine: From disillusionment to enlightenment in the era of generative AI 作为信任机器的区块链：生成式人工智能时代从幻灭到启迪

IF 7.5 1区计算机科学

Decision Support Systems Pub Date : 2024-05-22 DOI: 10.1016/j.dss.2024.114251

Shaokun Fan , Noyan Ilk , Akhil Kumar , Ruiyun Xu , J. Leon Zhao

{"title":"Blockchain as a trust machine: From disillusionment to enlightenment in the era of generative AI","authors":"Shaokun Fan , Noyan Ilk , Akhil Kumar , Ruiyun Xu , J. Leon Zhao","doi":"10.1016/j.dss.2024.114251","DOIUrl":"10.1016/j.dss.2024.114251","url":null,"abstract":"<div><p>Since the Economist magazine heralded blockchain as “the trust machine” in 2015, the blockchain paradigm has experienced crests and falls, including a recent phase of disillusionment due to its failure to meet the high expectations, e.g., to revolutionize record keeping, data management, and workflow, envisioned during its early history. However, despite the waning interest in this technology in some quarters, its deployment has become ever more essential in areas such as decentralized finance (DeFi), Non-fungible Tokens (NFTs), and other application domains beyond cryptocurrencies. In particular, recent advancements in Artificial Intelligence (AI) surrounding Large Language Models (LLM) offer new opportunities for blockchain adoption where trust and reliability become critical. As the blockchain technology transitions from a stage of disillusionment to one of enlightenment, anticipation is building for its mainstream adoption, with focused endeavors towards removing adoption barriers across diverse business contexts, exemplified by studies included in this special issue on <em>Blockchain Technology and Applications</em>. In this paper, we first survey the current state of the blockchain technology and then highlight its potential for enhancing trust and accountability in emerging phenomena such as AI generated content (AIGC). We conclude by introducing the papers included in the special issue.</p></div>","PeriodicalId":55181,"journal":{"name":"Decision Support Systems","volume":"182 ","pages":"Article 114251"},"PeriodicalIF":7.5,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141143867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0