Explore the vast range of titles available.

Stock market analysis plays an indispensable role in gaining knowledge about the stock market, developing trading strategies, and determining the intrinsic value of stocks. Nevertheless, predicting stock trends remains extremely difficult due to a variety of influencing factors, volatile market news, and sentiments. In this study, we present a hybrid data analytics framework that integrates convolutional neural networks and bidirectional long short-term memory (CNN-BiLSTM) to evaluate the impact of convergence of news events and sentiment trends with quantitative financial data on predicting stock trends. We evaluated the proposed framework using two case studies from the real estate and communications sectors based on data collected from the Dubai Financial Market (DFM) between 1 January 2020 and 1 December 2021. The results show that combining news events and sentiment trends with quantitative financial data improves the accuracy of predicting stock trends. Compared to benchmarked machine learning models, CNN-BiLSTM offers an improvement of 11.6% in real estate and 25.6% in communications when news events and sentiment trends are combined. This study provides several theoretical and practical implications for further research on contextual factors that influence the prediction and analysis of stock trends.

PurposeVisual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology.Design/methodology/approachThis study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms.FindingsBased on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations.Research limitations/implicationsThis study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations.Practical implicationsThis study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals.Originality/valueThis study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

With the proliferation of big data and business analytics practices, data storytelling has gained increasing importance as an effective means for communicating analytical insights to the target audience to support decision-making and improve business performance. However, there is a limited empirical understanding of the relationship between data storytelling competency, decision-making quality, and business performance. Drawing on the resource-based view (RBV), this study develops and validates the concept of data storytelling competency as a multidimensional construct consisting of data quality, story quality, storytelling tool quality, storyteller skills, and storyteller domain knowledge. It also develops a mediation model to examine the relationship between data storytelling competency and business performance, and whether this relationship is mediated by decision-making quality. Based on an empirical analysis of data collected from business analytics practitioners, the results of this study reveal that the data storytelling competency is positively linked to business performance, which is partially mediated by decision-making quality. These results provide a theoretical basis for further investigation of possible antecedents and consequences of data storytelling competency. They also offer guidance for practitioners on how to leverage data storytelling capabilities in business analytics practices to improve decision-making and business performance.

This study presents a systematic approach that integrates the information adoption model (IAM) with topic modeling to analyze the digital voice of users in online open innovation communities (OOICs) and empirically examines the usefulness of UGC with large amounts of redundant information and varying content quality across two dimensions: information quality and information source credibility. A total of 61,227 bug comments were collected from the OOIC of Huawei EMUI and analyzed using binary logistic regression. The results show that information timeliness and completeness have a positive effect on the usefulness of UGC in OOICs; conversely, information semantics have a negative effect on the usefulness of UGC. Prior user experience has no influence on the usefulness of UGC in OOICs, while active user contribution has a positive effect on the usefulness of UGC. The results of this study offer several implications to researchers and practitioners, and thus could serve as a pivotal reference source for further investigation of potential determinants of UGC usefulness in OOICs.

Purpose Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology. Design/methodology/approach This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms. Findings Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations. Research limitations/implications This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations. Practical implications This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals. Originality/value This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

Mobile application development platforms (MADPs) vary in terms of their development capabilities and competency to fulfill the specific needs of organizations. Therefore, acknowledging the most appropriate MADP to adopt remains a challenging task for many organizations. Aiming to investigate the key factors of MADPs adoption in organizations, this study analyzed 1200 online evaluation reviews for six widely used MADPs posted by mobile applications developers. Based on the content analysis of online reviews, 26 factors emerged as significant contributors to the adoption decision of MADPs from the standpoint of developers. These factors were integrated into a conceptual framework of MADPs adoption based on the technology-organization-environment (TOE) framework. The results of this study indicate that in addition to the technological capabilities, the adoption decision of MADPs depends on several organizational and environmental factors. These results provide not only a theoretical foundation for further research on MADPs adoption but also offers actionable guidance for practical implementation.

To report several cases of hyperthyroidism in patients presenting with the unusual symptom of sleepwalking and to discuss the possible pathophysiologic basis for this novel association. After encountering and reporting the first case of new-onset somnambulism in a patient presenting with thyrotoxicosis at our institution, we routinely inquired about the sleep history of patients with thyrotoxicosis, questioning both the patients and family members when applicable. Those patients who actually had sleepwalking episodes coinciding with the onset of thyrotoxicosis underwent close follow-up, and the relationship between the sleepwalking and the results of thyroid function tests was analyzed. In addition, we reviewed the literature on psychiatric disorders and sleep problems, and the pathophysiologic rationale for a cause-and-effect relationship is discussed. We collected 8 cases of patients with new-onset sleepwalking episodes that coincided with the start of thyrotoxicosis. The disappearance of the sleepwalking with successful achievement of euthyroidism supports a cause-and-effect relationship. This hypothesis is further supported by the absence of a family history, the adult onset, and the relapse of sleepwalking in 2 of the patients when their thyrotoxicosis became poorly controlled as a result of noncompliance with medications and its subsequent disappearance with reachievement of euthyroidism. Of note, such a presentation was seen only in patients with thyrotoxicosis caused by diffuse toxic goiter or Graves' disease and never in patients with other causes of thyrotoxicosis. New-onset sleepwalking could be caused by thyrotoxicosis or, more specifically, by thyrotoxicosis resulting from diffuse toxic goiter. The mechanism is hypothesized to be related to the combination of prolongation of non-rapid eye movement sleep and the associated fatigue. Specific inquiry about this unusual presentation of thyrotoxicosis is encouraged, and more studies are needed to confirm and evaluate its extent.