Protective behavior in ride-sharing through the lens of protection motivation theory and usage situation theory     

《International Journal of Information Management》2021

The frequent occurrence of security incidents in ride-sharing is a challenge for the survival of IT-enabled ride-sharing platforms. Passengers’ protective behavior is an effective means to alleviate this issue, with benefits to both the passengers and the platforms. This study explores the mechanisms of passengers’ protective behavior in the ride-sharing context by combining protection motivation theory (PMT) and usage situation theory. We test our hypotheses using data (n = 346) collected from a field survey based on a real scenario. The findings reveal that PMT and usage situation theory work well to explain passengers’ protective behavior during ride-sharing. This study explains the motivation behind passengers’ protective behavior in the ride-sharing context, extends the contents of PMT by exploring its antecedents, and extends the contents of usage situation theory by introducing a new dimension. Our findings can help ride-sharing platforms take appropriate strategies to improve passengers’ protective behavior.  相似文献   

The Mystery Room: discovering the flexibility of an information literacy-based educational escape room     

Glenn Koelling  Alyssa Russo 《Public Services Quarterly》2020,16(1):1-11

Abstract

The Mystery Room is an educational escape room based on information literacy and applied to multiple audiences, including first-year students and library student employees. In this article, we explain how we developed the game, its theoretical underpinnings, and why it’s a flexible workshop for a variety of audiences.  相似文献   

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws     

Edgardo Ferretti  Leticia Cagnina  Viviana Paiz  Sebastián Delle Donne  Rodrigo Zacagnini  Marcelo Errecalde 《Information processing & management》2018,54(6):1169-1181

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   

Information retrieval in the workplace: A comparison of professional search practices     

Tony Russell-Rose  Jon Chamberlain  Leif Azzopardi 《Information processing & management》2018,54(6):1042-1057

Legal researchers, recruitment professionals, healthcare information professionals, and patent analysts all undertake work tasks where search forms a core part of their duties. In these instances, the search task is often complex and time-consuming and requires specialist expertise to identify relevant documents and insights within large domain-specific repositories and collections. Several studies have been made investigating the search practices of professionals such as these, but few have attempted to directly compare their professional practices and so it remains unclear to what extent insights and approaches from one domain can be applied to another. In this paper we describe the results of a survey of a purposive sample of 108 legal researchers, 64 recruitment professionals and 107 healthcare information professionals. Their responses are compared with results from a previous survey of 81 patent analysts. The survey investigated their search practices and preferences, the types of functionality they value, and their requirements for future information retrieval systems. The results reveal that these professions share many fundamental needs and face similar challenges. In particular a continuing preference to formulate queries as Boolean expressions, the need to manage, organise and re-use search strategies and results and an ambivalence toward the use of relevance ranking. The results stress the importance of recall and coverage for the healthcare and patent professionals, while precision and recency were more important to the legal and recruitment professionals. The results also highlight the need to ensure that search systems give confidence to the professional searcher and so trust, explainability and accountability remains a significant challenge when developing such systems. The findings suggest that translational research between the different areas could benefit professionals across domains.  相似文献   

An extension of the technology acceptance model in the big data analytics system implementation environment     

Surabhi Verma  Som Sekhar Bhattacharyya  Saurav Kumar 《Information processing & management》2018,54(5):791-806

Research on the adoption of systems for big data analytics has drawn enormous attention in Information Systems research. This study extends big data analytics adoption research by examining the effects of system characteristics on the attitude of managers towards the usage of big data analytics systems. A research model has been proposed in this study based on an extensive review of literature pertaining to the Technology Acceptance Model, with further validation by a survey of 150 big data analytics users. Results of this survey confirm that characteristics of the big data analytics system have significant direct and indirect effects on belief in the benefits of big data analytics systems and perceived usefulness, attitude and adoption. Moreover, there are mediation effects that exist among the system characteristics, benefits of big data analytics systems, perceived usefulness and the attitude towards using big data analytics system. This study expands the existing body of knowledge on the adoption of big data analytics systems, and benefits big data analytics providers and vendors while helping in the formulation of their business models.  相似文献   

我国武术科研领域交叉学科研究动态——基于CNKI数据库的武术文献计量分析     

刘存忠 《广州体育学院学报》2019,(5):63-68

应用文献计量法对1988—2018年CNKI数据库武术交叉研究文献进行分析，以探析我国武术科研领域交叉学科研究动态。结果显示：我国武术科研领域交叉学科研究动态主要包括文化、运动人体科学、教育、健身养生、经济产业、历史、艺术和其它八个方向，数量占了武术研究文献总数近1/5，热点集中在武术文化、武术教育，其次为武术与经济产业、武术与养生健身，由热点转为冷门的是运动人体科学；各类基金支持的文献篇数占支持武术研究总数的近1/3，其中受国家社科基金支持的交叉研究文献比例更高。机构单位发文篇数主要集中在国家六大体育专业院校和河南省三所综合性大学；武术科研领域交叉学科研究未来的趋势包括政策导向发展、武术本源发展、与新兴事物交叉发展三个方面。  相似文献   

商业性档案培训服务SWOT分析     

孙大东  彭登辉 《档案与建设》2020,(2):18-21,44

随着档案行业的发展和市场经济的推动,商业性档案培训服务应运而生,并逐渐展示出了强大的活力,这无疑为档案事业的发展提供了新思路、新动力、新方法。文章运用SWOT分析法,对商业性档案培训服务内部的优势、劣势以及外部的机会、威胁因素进行分析,进而提出了相应的发展思路和建议,以期推动商业性档案培训服务能够突破传统思想束缚、完善运营机制,使之成为档案事业发展的新增长点。  相似文献   

协同搜索过程中用户交流内容与模式研究     

张璐  张鹏翼  刘畅 《图书情报知识》2020,(3):51-62

[目的/意义]旨在分析协同搜索用户在信息搜索任务过程中的交流内容与模式,从而理解协同搜索用户的关注重点与搜索过程。[研究设计/方法]基于书籍交互检索平台(CLEF-Social Book Search)设计实验,共招募18名被试完成两种搜索任务,通过录音记录对话并对其进行编码和分析,总结交流内容特征和模式。结合任务类型、认知类型组合、服务器记录的搜索交互行为日志以及问卷收集的搜索体验进行了探索分析。[结论/发现]从交流内容上看,协同搜索用户主要理解与评判书目信息、商讨搜索任务计划;比起认知类型不同的用户,相同认知类型的用户在操作交互方面交流更多,在评判决策方面交流较少。交流模式依据讨论内容比重可分为理解评判型、评判主导型、均衡交流型三种,评判主导型用户的任务完成满意度最高。[创新/价值]协同搜索用户的交流反映出搜索过程中需要与同伴商讨协同的焦点,也是需要系统提供协助的重点,给协同搜索系统设计提供一定参考。本研究针对协同搜索的交流内容设计的编码系统对相关的协同交流研究也有借鉴意义。  相似文献   

Using an interactive platform to recognize the intersection of social and spatial inequalities     

Lisa Poling  Travis Weiland 《Teaching Statistics》2020,42(3):108-116

With the creation of interactive tasks that allow students to explore spatial ways of knowing in conjunction with their other ways of knowing the world, we create a space where students can make sense of information as they organize these new ideas into their already existing schema. Through the use of a Common Online Data Analysis Platform (CODAP) and data from Public Use Microdata Areas (PUMA), students can explore the communities in which they live and work, critically examining opportunities and challenges within a defined space.  相似文献   

Neural embedding-based indices for semantic search     

Fatemeh Lashkari  Ebrahim Bagheri  Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755

Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献