Organizational Reasons For Decision Aid Implementation

Although substantial research efforts have been devoted to determining the reasons for the success and failure of decision aids in organizations, little has been done to examine the reasons why an organization chooses to implement the technology. We propose that understanding the relationship between decision aids and organizational reasons for implementation can assist in achieving a higher level of congruence between the organizations’ goals and the technology. This paper proposes and empirically tests a framework that categorizes four primary reasons – improved decision-making, improved financial outcomes, improved communication processes, and improved learning/training processes. The results support the four proposed dimensions and provide a structure to the multitude of potential reasons for developing and implementing decision aid technology.  The framework can be used by organizational managers in the initial stages of implementing a decision aid technology as well as during the functional stages of the decision aid to assess the initial and ongoing contribution the decision aid is making toward meeting organizational goals

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The effect of computer -mediated communication on group decisions: An experimental study of order effects

Group work, although an essential component of contemporary business, is a costly activity. Advances in information technology have made computer-mediated, virtual meetings a practical alternative to the traditional meeting. However, past research indicates that computer-mediated meetings may not be a wholly equivalent substitute for traditional meetings. This study relies on theories of belief revision and group decision-making to examine whether communication setting affects group belief revision performance in a business task. The belief-adjustment model is a theory of belief revision that predicts a measurable effect on a final decision according to the order of information. Research utilizing the model indicates that although order effects are a pervasive judgment bias, situational factors, such as group work, can temper the effect. Prior research has not addressed whether this benefit holds in a computer-mediated setting. This study posits that computer-mediated groups cannot be assumed to retain the positive belief revision patterns of face-to-face groups, resulting in order biases. Secondary hypotheses explore reasons why the belief revision patterns of face-to-face and virtual groups are expected to differ. An experiment is conducted with a 2 x 2 factorial design obtained by crossing communication setting with evidence order. The results indicate that face-to-face groups exhibit few order effects while the decisions of computer-mediated groups were strongly biased by order. This implies that the benefits of group work cannot be expected to transfer to a computer-mediated setting. Findings on the secondary hypotheses were generally inconsistent with expectations, suggesting that other factors not measured in this study impact group belief revision. This study contributes to the literature by examining how group decisions are changed when the group operates in a computer-mediated setting. The prevalence of, and emphasis on, group work in contemporary organizations is not likely to diminish; the increasing dispersion of organizations has intensified the desire for supportive technology. Studying the differences between face-to-face groups and computer-mediated groups can provide clues into what factors are the most influential in group settings

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press