Linking Heuristic-Systematic Processing to Adoption of Behavior

This study sets out to draw connections among key components within three conceptual models: the Risk Information Seeking and Processing model, the Heuristic-Systematic Model, and the Theory of Planned Behavior. Specifically, it proposes and tests the theoretical linkages among heuristic and systematic information processing, depth of processing, attitude stability, and behavioral intention. Archival data drawn from a panel survey that concerns health risks from drinking municipal tap water are used for theory testing. Findings reveal that systematic processing is positively related to number of strongly held behavioral beliefs, strength of belief outcome evaluations, and strength of cognitive structure--all indicated depth of processing, and that heuristic processing is negatively related to all three measures. Cognitive structure and attitude toward the behavior appear to be consistent in direction and strength. Attitude toward the behavior, subjective norms, and alternative behavior are positively related to behavioral intention. An anticipated positive relationship between perceived behavioral control and behavioral intention was not found. Finally, theoretical and practical implications of the findings are discussed

Parsing Argumentation Structures in Persuasive Essays

In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed model globally optimizes argument component types and argumentative relations using integer linear programming. We show that our model considerably improves the performance of base classifiers and significantly outperforms challenging heuristic baselines. Moreover, we introduce a novel corpus of persuasive essays annotated with argumentation structures. We show that our annotation scheme and annotation guidelines successfully guide human annotators to substantial agreement. This corpus and the annotation guidelines are freely available for ensuring reproducibility and to encourage future research in computational argumentation.Comment: Under review in Computational Linguistics. First submission: 26 October 2015. Revised submission: 15 July 201

From Death Notification Through the Funeral: Bereaved Parents’ Experiences and their Advice to Professionals

Parents who experience the sudden death of a child will interact with many professionals in the period immediately following the death notification through to the funeral. The way these professionals respond to the parents during this critical period may be perceived as helpful, and thus support them in beginning the process of managing the trauma and starting a healthy grieving process. It may also be perceived as unhelpful, though, and contribute to more prolonged and complicated grieving. This article identifies the interventions that a sample of 20 parents who had experienced the sudden death of a child found helpful with different aspects of grieving. Specific advice is given to police, nurses, doctors, coroners, social workers, crisis counselors, funeral directors, and chaplains or clergy

Distributed Learning System Design: A New Approach and an Agenda for Future Research

This article presents a theoretical framework designed to guide distributed learning design, with the goal of enhancing the effectiveness of distributed learning systems. The authors begin with a review of the extant research on distributed learning design, and themes embedded in this literature are extracted and discussed to identify critical gaps that should be addressed by future work in this area. A conceptual framework that integrates instructional objectives, targeted competencies, instructional design considerations, and technological features is then developed to address the most pressing gaps in current research and practice. The rationale and logic underlying this framework is explicated. The framework is designed to help guide trainers and instructional designers through critical stages of the distributed learning system design process. In addition, it is intended to help researchers identify critical issues that should serve as the focus of future research efforts. Recommendations and future research directions are presented and discussed

Business Intelligence & Analytics and Decision Quality - Insights on Analytics Specialization and Information Processing Modes

Leveraging the benefits of business intelligence and analytics (BI&A) and improving decision quality does not only depend on establishing BI&A technology, but also on the organization and characteristics of decision processes. This research investigates new perspectives on these decision processes and establishes a link between characteristics of BI&A support and decision makers’ modes of information processing behavior, and how these ultimately contribute to the quality of decision outcomes. We build on the heuristic–systematic model (HSM) of information processing, as a central explanatory mechanism for linking BI&A support and decision quality. This allows us examining the effects of decision makers’ systematic and heuristic modes of information processing behavior in decision making processes. We further elucidate the role of analytics experts in influencing decision makers’ utilization of analytic advice. The analysis of data from 136 BI&A-supported decisions reveals how high levels of analytics elaboration can have a negative effect on decision makers’ information processing behavior. We further show how decision makers’ systematic processing contributes to decision quality and how heuristic processing restrains it. In this context we also find that trustworthiness in the analytics expert plays an important role for the adoption of analytic advice

Using a Modified Heuristic-Systematic Model to Characterize Information Seeking on the Internet

This study combines two major theories in communication research, Palmgreen and Rayburn\u27s Expectancy-Value approach to media gratifications (1985) and Eagly and Chaiken\u27s Heuristic-Systematic Model (1989), in order to identify the relationships between information seeking tendencies, channel beliefs about specific websites, and website usage for accurate information. Taking a page from schema theory (Rumelhart, 1980), it was expected that individuals who use the Internet frequently to find accurate information have a set of beliefs concerning what a good or bad website has on it. To this end, a study of 130 undergraduate college students was completed. The study had an added experimental manipulation which varied the domain extension and authority of the website given for the task. The analyses performed showed that when given a task of finding accurate information, a higher capacity to understand information predicted which characteristics of a website were highly valued and how likely a given website was to have those characteristics. This in turn predicted website usage. Furthermore, websites with official domain extensions (e.g., .gov) were considered more likely to have desirable characteristics, more likely to contain accurate information than websites with non-official domain extensions (e.g., .com), and were more likely to be used. The study also offers a model of how information seeking, domain extension, and channel beliefs lead to website use