Data and information management最新文献

{"title":"Task-specific algorithm advice acceptance: A review and directions for future research","authors":"Esther Kaufmann ,&nbsp;Alvaro Chacon ,&nbsp;Edgar E. Kausel ,&nbsp;Nicolas Herrera ,&nbsp;Tomas Reyes","doi":"10.1016/j.dim.2023.100040","DOIUrl":"10.1016/j.dim.2023.100040","url":null,"abstract":"<div><p>Due to digitalization resulting in artificial intelligence advice, there are increasing studies on advice taking, exploring individual and task-relevant factors associated with the acceptance of algorithm advice. However, to our notice, there are no reviews of studies on the acceptance of algorithm advice that focus explicitly on a task level that consider methodological features and provide a quantitative measure of algorithm acceptance. Our review closes these research gaps. We evaluated 44 studies, 122 tasks, and 89,751 participants. Our review shows that algorithm aversion is present in 75% of the 122 considered tasks. In addition, our quantified measures underscore some shortcomings by the underrepresented individual, task, or methodological characteristics—for example, the expertise of advice takers and longitudinal studies. Finally, we provide valuable recommendations to continue research on algorithm acceptance.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 3","pages":"Article 100040"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49403192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the joint effects of internal and external anthropomorphic cues of intelligent customer service bot on user satisfaction","authors":"Yuxin Hu ,&nbsp;Yongqiang Sun","doi":"10.1016/j.dim.2023.100047","DOIUrl":"10.1016/j.dim.2023.100047","url":null,"abstract":"<div><p>As one specific type of chatbot, Intelligent Customer Service Bot (ICSB) satisfies users by providing uninterrupted customer service and reducing response time. However, users still prefer to interact with humans rather than robots. In previous studies, scholars have focused more on enhancing the anthropomorphic characteristics of chatbot by treating anthropomorphic characteristics as a general concept. Few literatures have studied the influence of both external and internal features on user satisfaction and the possible interactive effects between the two dimensions of chatbot anthropomorphic cues. Therefore, this paper studies the main effects of internal anthropomorphic constructs (cognitive empathy and emotional empathy) and external anthropomorphic constructs (virtual appearance) of ICSB on user satisfaction, as well as the two-way and three-way interaction effects among them. With a scenario-based survey of 331 respondents, the results confirm the hypotheses about the main effects, the two-way and three-way interaction effects in the model.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 3","pages":"Article 100047"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42282953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Facebook's newsfeed algorithm shapes childhood vaccine hesitancy: An algorithmic fairness, accountability, and transparency (FAT) perspective","authors":"Eduardo D. Villacis Calderon ,&nbsp;Tabitha L. James ,&nbsp;Paul Benjamin Lowry","doi":"10.1016/j.dim.2023.100042","DOIUrl":"10.1016/j.dim.2023.100042","url":null,"abstract":"<div><p>Vaccine hesitancy is the delay or refusal of vaccination when vaccines are available. Over the last decade, many reports have suggested that the proliferation of vaccine disinformation and misinformation on social media has aggravated the vaccine-hesitancy problem. Access to vaccine dis(mis)information on social media is deemed partly responsible for the resurfacing of vaccine-preventable diseases (e.g., measles). Although studies have examined social media dis(mis)information, including that related to vaccines, the newsfeed algorithm, which determines the content social media users see, has received scant attention in the literature. We examine how people's perceptions of the fairness, accountability, and transparency (FAT) of the Facebook newsfeed algorithm influence their intention to vaccinate their children. We find that people's perceptions of the Facebook newsfeed algorithm's FAT increase their negative attitudes toward vaccination (fairness and transparency). However, they decrease users' perceptions of antivaccination norms on Facebook (fairness, accountability, and transparency). Negative attitudes toward vaccination decrease the intention to vaccinate, as do perceptions of Facebook antivaccination norms. Our findings demonstrate that to decrease the effectiveness of vaccine dis(mis)information, it is critical to educate the public about how social media newsfeed algorithms make content-display decisions.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 3","pages":"Article 100042"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45298835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding barriers affecting the adoption and usage of open access data in the context of organizations","authors":"Murat Tahir Çaldağ, Ebru Gökalp","doi":"10.1016/j.dim.2023.100049","DOIUrl":"https://doi.org/10.1016/j.dim.2023.100049","url":null,"abstract":"","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-AI interaction","authors":"Yongqiang Sun,&nbsp;Xiao-Liang Shen,&nbsp;Kem Z.K. Zhang","doi":"10.1016/j.dim.2023.100048","DOIUrl":"https://doi.org/10.1016/j.dim.2023.100048","url":null,"abstract":"","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 3","pages":"Article 100048"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49730447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Not transparent and incomprehensible: A qualitative user study of an AI-empowered financial advisory system","authors":"Hui Zhu ,&nbsp;Eva-Lotta Sallnäs Pysander ,&nbsp;Inga-Lill Söderberg","doi":"10.1016/j.dim.2023.100041","DOIUrl":"10.1016/j.dim.2023.100041","url":null,"abstract":"<div><p>AI-empowered and algorithm-driven automated financial advisory systems, also known as Robo-advisors, have been rapidly implemented by service providers and customers in financial service markets. Yet, few empirical studies investigate customers’ experience interacting with fully functional Robo-advisors in real-life scenarios. Also, it is still unknown how the design of the automated system can affect customers’ perception and adoption of this new technology. To mitigate these gaps, 24 participants with different levels of experience and understanding of financial investment were asked to use a Robo-advisor from a retail bank and perform the tasks. By conducting observations and retrospective post-test interviews, we find that participants do not fully perceive the social aspects supposed to be provided by Robo-advisors. The overarching problems are, among others, a lack of transparency and incomprehensible information. This results in distrust of the results generated by this system, which negatively affects customers’ adoption of the investment advice provided by the Robo-advisor. The potential of interactive data visualization is also detected. This work contributes to the understanding of customers regarding their perception and adoption based on their use of a functional Robo-advisor and proposes design takeaways for transparent and comprehensible automated advisory systems in financial service contexts.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 3","pages":"Article 100041"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48328584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data use policies on state COVID-19 dashboards in the United States: Key characteristics, topical focus, and identifiable gaps","authors":"Rong Tang, Zhan Hu, Yishan Zhang","doi":"10.1016/j.dim.2023.100050","DOIUrl":"https://doi.org/10.1016/j.dim.2023.100050","url":null,"abstract":"In this paper, we report the findings of an investigation into the data use policies published on the COVID-19 dashboards developed by the 50 state governments of the United States as well as the government of District of Columbia. Specifically, we examined the key attributes of the dashboard data notes, such as data source, update frequency, and data suppression disclaimers. We also studied the terms and phrases used, as well as topic themes of the data policy texts. Using a data policy analysis model, our results revealed a series of gaps and inconsistencies in the policy statements. Connecting these gaps and inconsistencies with potential problems that could violate individual Open Data Principles (ODP) and the FAIR principles, we made recommendations to help resolve these missing areas and fix the inconsistencies, so that open government data can be managed and used to further the very core of open data practice. Further research that we plan to carry out includes confirmation and validation of our analysis model and our approach of linking the examination and assessment of open data policy with ODP and the FAIR principles.","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135200197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic literature review on the factors influencing e-commerce adoption in developing countries","authors":"Saarah Hendricks,&nbsp;Samwel Dick Mwapwele","doi":"10.1016/j.dim.2023.100045","DOIUrl":"10.1016/j.dim.2023.100045","url":null,"abstract":"<div><p>E-commerce is a huge component of the digital economy as the business market landscape is now based on digital competition. E-commerce assists with national development through the creation of jobs and import tax. However, developing countries are lagging in e-commerce adoption due to internet challenges, trust, and security issues about online payment facilities. Despite these challenges, this study aimed at understanding the factors influencing e-commerce adoption in developing countries. The factors are built from the benefits and challenges of adoption. To address the research aim, the study identified the challenges and benefits of e-commerce adoption in developing countries using a systematic literature review methodology.</p><p>Systematic searches were carried out in 2021 in four databases (Ebsco host, ScienceDirect, SpringerLink, and Google Scholar) and Google Searches (for statistics). The included papers are 23 peer-reviewed studies and 2 reports published in English between 2014 and 2021. Thematic analysis was used to assess the papers and reports.</p><p>Our findings identified technology, environment, and customer trust as the main challenges affecting e-commerce adoption. The environment, organization, and performance are seen as benefits developing countries can leverage to boost e-commerce adoption. We found that all challenges and benefits are interconnected. However, e-commerce can only be adopted if those in management perceive and understand its benefits and values.</p><p>The research contributes to the theory by presenting a novel model of the factors influencing the adoption of e-commerce in developing countries and its ecosystem. Practically, having identified that the factors should be addressed collectively assists developing countries in identifying the strategies for eliminating e-commerce adoption challenges. The research contributes to SDG 8 and the body of knowledge on e-commerce adoption.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 1","pages":"Article 100045"},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925123000190/pdfft?md5=bb9ce3fecbb339d172499078e713ccd2&pid=1-s2.0-S2543925123000190-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44813257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging text mining approach to explore research roadmap and future direction of wrong-way driving crash studies","authors":"Boniphace Kutela ,&nbsp;Cecilia Kadeha ,&nbsp;Raynard Tom Magehema ,&nbsp;Raul E. Avelar ,&nbsp;Priyanka Alluri","doi":"10.1016/j.dim.2023.100044","DOIUrl":"10.1016/j.dim.2023.100044","url":null,"abstract":"<div><p>This study delves into the wrong-way driving (WWD) research performed in the United States over the past five decades. The study employs a text network to summarize and synthesize major themes, data sources, and collaboration efforts from 123 previously published WWD articles collected from various online databases. The analysis shows that the majority of WWD studies were conducted between 2014 and 2020. Throughout the entire period, the primary focuses have been on WWD countermeasures, freeways, exit ramps, contributing factors, driver behavior, and detection systems. Over time, there has been a noticeable shift in the key themes, whereby earlier studies focused on freeways and driver behaviors, while the latter delved into exit ramps, limited access, and contributing factors among others. Most studies were from Florida, Texas, Illinois, and Alabama, with little collaboration of researchers across the States, except for Alabama and Illinois. Further, across the four States, there observed variations in the interests. Studies from Texas and Florida were centered on WWD countermeasures, detection systems, and the use of connected vehicles, while Illinois and Alabama investigated WWD crashes on exit ramps and interchanges. Despite the development and deployment of various countermeasures, there is still a need to develop crash modification factors to examine the effectiveness of the countermeasures. Furthermore, as technology continues to advance, connected and autonomous technology is expected to play a significant role in mitigating the WWD problem. The findings are essential for transportation agencies to evaluate the mitigation efforts and direct resources toward the right course of action.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 1","pages":"Article 100044"},"PeriodicalIF":0.0,"publicationDate":"2023-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925123000189/pdfft?md5=9851afd2339ff43c9f5b67d1ceb73cab&pid=1-s2.0-S2543925123000189-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41925611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of big data on research methods in information science","authors":"Jin Zhang ,&nbsp;Dietmar Wolfram ,&nbsp;Feicheng Ma","doi":"10.1016/j.dim.2023.100038","DOIUrl":"10.1016/j.dim.2023.100038","url":null,"abstract":"<div><p>Social media platforms, search engine transaction logs, Web portal transaction logs, large text corpora, and other data sources offer users a variety of invaluable data sources. Data generated based on social media platforms and other data sources have become important sources of big data for researchers in information science. Big data provide not only challenges but also opportunities for information science. Emerging big data trends inevitably have an impact on research methods in information science. The authors of this paper discuss the impact of big data on research methods in information science.</p><p>This paper addresses these challenges and opportunities through the lens of research methods, ranging from data processing, to sampling, to information visualization, to temporal analysis, to sentiment analysis, to correlation, to cause-effect relationship, to data accessibility, to data privacy, and data ethics issues.</p><p>The discussions on related aspects of research methods provoke a healthy reflection and debate for the information science research community, which can help researchers in the field produce sound research designs for big data-oriented research studies and assist information practitioners in solving problems they face in the big data age.</p><p>Research methods are fundamental and essential for any research studies. Big data analysis has a natural relationship with research methods. The paper discusses an emerging and important research topic big data from the unique angle of research methods.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"7 2","pages":"Article 100038"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45161996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}