The Effectiveness of Visualization Techniques for Supporting Decision-Making

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique\u27s strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization approach for a specific data type poses a significant research challenge. Our findings will help both professionals and researchers determine the most successful visualization approach for different data types, as well as identify topics for future study in the field of data visualization

A Conceptual Model for Network Decision Support Systems

We introduce the concept of a network DSS (NWDSS) consisting of fluid, heterogeneous nodes of human and machine agents, connected by wireless technology, which may enter and leave the network at unpredictable times, yet must also cooperate in decision-making activities. We describe distinguishing properties of the NWDSS and propose a 3-tier conceptual model comprised of digital infrastructure, transactive memory systems and emergent collaborative decision-making. We suggest a decision loop of Sense-Analyze-Adapt-Memory leveraging TMS as a starting point for addressing the agile collaborative requirements of emergent decision-making. Several examples of innovative NWDSS services are presented from Naval Postgraduate School field experiments

Unleashing Crowd Wisdom: Leveraging Cognitive Memory Structures to Increase Quality of User-Generated Content

In recent years, online information sharing platforms have opened new opportunities for people to share information and experiences with each other and with organizations that sponsor these platforms. Increasingly, data consumers, both at the organizational and at the individual level, hope to use these User-Generated Content (UGC) in their decision making. However, recent studies uncovered significant challenges associated with the interfaces used to collect high-quality UGC. While many aspects of the information quality (IQ) of UGC have been studied, the role of data structures in gathering UGC and the nature of shared content have yet to receive attention. UGC is created on online platforms with varying degrees of data structure, ranging from unstructured (e.g., open box fields) to highly structured formats (e.g., rigid and specific forms). Despite much research on UGC, we have little understanding of the appropriate degree of data structures in data collection and its impact on the quality of information. Moreover, we know that most of the produced UGC originates in the declarative memory of the contributors. Psychology literature shows that different types of memory are stored and managed differently, and that they are retrieved accordingly. Thus, we argue that the information collection interface for retrieving and collecting each type of memory should be aligned with the way that it was stored. Therefore, we posit that designing interfaces with sensitivity to human memory structures should result in improvements of the IQ of UGC. We conducted several experiments to examine differently-designed information collection interfaces for different types of information. We evaluated both data creators’ and data consumers’ perceived quality of information collection, at the individual level. The findings support our claims of the importance of these factors for information quality. This research demonstrates a connection between information system interface design and human memory, which eventually could result in changes to best practices in interface design. This could, in turn, lead to improved interaction between participants and organizations, including enhanced data creators’ self-expression, improved users’ attitudes toward UGC systems, and increased value-add from organizations’ use of UGC

EXPLORING AIRPORT NAVIGATION CHALLENGES FACED BY AIRLINE TRAVELERS WITH HIDDEN DISABILITIES

In this paper, the Servicescape theory was employed as the conceptual framework to (a) investigate the live airport experiences of passengers with an HD and (b) understand the negative experiences of passengers within the airport\u27s physical environment. The authors collected the electronic word-of-mouth statements of 203 travelers from the TripAdvisor website. The data generated were analyzed using thematic analysis. Common themes found from the analysis included (1) human interaction, (2) services, and (3) terminal design. This paper offers insight into airport navigational challenges faced by travellers with an HD at various stages within the airport. These findings have practical implications for airport operators and decision-makers implementing a Hidden Disability Assistance Program. The results may help airport operators, including airlines, understand passenger-customer interaction issues. Findings may equally help airport operators, while addressing identified challenges, to offer appropriate support effectively and efficiently to travellers with an HD when transiting through airports

Generative AI in Idea Development: The Role of Numeric and Visual Feedback

Human creativity is a crucial factor in developing innovative ideas. Many ideas are being generated, but only a few receive feedback, as creating feedback is a costly and time-consuming effort in innovation. While feedback promises higher idea quality, previous work requires human experts with domain expertise. Generative AI could provide automated feedback and is expected to transform creative work. This short paper presents an experimental series in which we let humans collaborate with generative AI to develop ideas. Based on dual-coding and media synchronicity theory, we conceptualize numerical and visual feedback to overcome cognitive barriers. We manipulate feedback modalities and timing to personalize the interaction. Our contributions provide evidence on when and why specific co-creative arrangements between humans and generative AI are favorable

Learning Model for Local Wisdom-based Prophet's Hadith Translation

Google Translate is a famous translation machine among students. It is just that in the Arabic-Indonesian translation, they still need to re-edit the translation. This means that there is a problem with the quality of the machine translation results, so the accuracy still needs to be improved. Therefore, it is essential to research Arabic-Indonesian translation learning. The purpose of this study is to describe the forms of Arabic-Indonesian machine translation errors. In addition, this study also offers the Ngalodern method, Indonesian local wisdom, so that students can improve the quality of Arabic-Indonesian translation. The method used in this research is descriptive analysis and uses an eclectic combination of theories to achieve the objectives of this study. There are three stages of this research. First, providing data through selected questionnaires and interviews. Second, the data analysis uses the translational equivalent method to determine the exact equivalent of meaning, while the distributional method is used to describe the level of grammatical errors. Third, is the presentation of data in the form of a table of the percentage of errors in translation cases in the field of Islam. Ngalodern, Indonesian local wisdom as an effort to improve the quality of Arabic-Indonesian translation is described descriptively. There are two findings from this research namely, The first is a description of translation errors at the level of morphemes, words, phrases, and clauses. Second, Ngalodern learning on Arabic-Indonesian translation with critical literacy based on the Sundanese culture in the field of education. In conclusion, Ngalodern learning can improve the learner's ability to edit Arabic-Indonesian machine translation results