Uncertainty Management

Following uncertainty management theory, we argue that when people face increased uncertainty, fairness becomes more important to them and judgments of fairness affect their reactions more strongly. The organizational field study reported here examines the effects of uncertainty about performance standards and appropriate behaviors on the relationship between fairness and job satisfaction. Results reveal that uncertainty moderates the positive relationship between fairness perceptions and job satisfaction such that the more uncertain people are about performance standards and appropriate behaviors, the stronger the relationship between fairness and job satisfaction. Further results reveal a significant moderating effect of uncertainty specifically for procedural fairness and interactional fairness. We discuss the implications of our findings for the uncertainty management model.

Our modern world and digital technology are evolving at an unimaginable pace, which has greatly impacted healthcare. However, some populations such as the Deaf may not fully incorporate this evolution due to differences in culture, health disparities, varying communication methods, and uncertainty management choices. Therefore, the overall objective of this research is to assess the potential impact of the digital technology on Deaf healthcare access and their resulting health. The objectives of the study are: (a) to assess the utilization patterns of online health information seeking by the Deaf; and (b) to examine the relationship between healthcare satisfaction and online health information seeking. To examine the objectives I propose a single research question: What is the relationship among patient satisfaction, language concordance, and online health information seeking by the Deaf? The study proposes to administer an initial pretest via an in-person, cross-sectional survey to help inform the participants of the purpose of the focus group and to gather some background information and their feelings towards certain topics. It also proposes conducting an in-person focus group with pretest participants and an in-person interview with a key informant of the Deaf community to better understand the pretest answers. In the results I discovered the participants usually seek to reduce or manage uncertainty through family, friends, doctors, or printed materials instead of the internet.

It is recognised that nowadays, users interact with large amounts of data that exist in disparate forms, and are stored under different settings. Moreover, it is true that the amount of structured and un-structured data outside a single well organised data management system is expanding rapidly. To address the recent challenges of managing large amounts of potentially distributed data, the vision of a dataspace was introduced. This data management paradigm aims at reducing the complexity behind the challenges of integrating heterogeneous data sources.Recently, efforts by the Linked Data (LD) community gave rise to a Web of Data (WoD) that interweaves with the current Web of documents in a way that it is useful for data consumption by both humans and computational agents. On the WoD, datasets are structured under a common data model and published as Web resources following a simple set of guidelines that enables them to be linked with other pieces of data, as well as, to be annotated with useful meta data that help determine their semantics. The WoD is an evolving open ecosystem including specialist publishers as well as community efforts aiming at re-publishing isolated databases as LD on the WoD, and annotating them with meta data.The WoD raises new opportunities and challenges. However, currently it mostly relies on manual efforts for integrating the large amounts of heterogeneous data sources on the WoD. This dissertation makes the case that several techniques from the dataspaces research area (aiming at on-demand integration of data sources in a pay-as-you-go fashion) can support the integration of heterogeneous WoD sources. In so doing, this dissertation explores the opportunities and identifies the challenges of adapting existing pay-as-you-go data integration techniques in the context of LD. More specifically, this dissertation makes the following contributions: (1) a case-study for identifying the challenges when existing pay-as-you-go data integration techniques are applied in a setting where data sources are LD; (2) a methodology that deals with the ''schema-less'' nature of LD sources by automatically inferring a conceptual structure from a given RDF graph thus enabling downstream tasks, such as the identification of matches and the derivation of mappings, which are, both, essential for the automatic bootstrapping of a dataspace; and (3) a well-defined, principled methodology that builds on a Bayesian inference technique for reasoning under uncertainty to improve pay-as-you-go integration. Although the developed methodology is generic in being able to reason with different hypothesis, its effectiveness has only been explored on reducing the uncertain decisions made by string-based matchers during the matching stage of a dataspace system.

Situational awareness and prediction are essential elements of information fusion. Both involve various types of uncertainty and require a sound automated inferential process. Probabilistic ontologies support uncertainty management in se-mantically aware systems, and facilitate modular, interoperable systems. This paper describes the process of developing a probabilistic ontology for a Maritime Domain Awareness application. The ontology was created to support identification of ships behaving suspiciously enough to be declared ships of interest. The original model was expanded in two ways: to provide reasons for declaring a ship as being of interest, and to include individual crew member associations. The latter is achieved by supporting inferences about a person's close relations, group associations, communications, and background influences to assess his likelihood of having terrorist links.

Home > Journal of Property Investment & Finance > Volume 24 issue 5 > Addressing risk and uncertainty in property... ... Icon: Abstract. Icon: Backfiles. Icon: Print. Icon: Reprints & permissions. ... The authors thank the German Federal Office for Building and Regional ...

This study investigated the use of uncertainty management tools within the construction sector in Nigeria.
The objectives were to evaluate the level of use of uncertainty management tools and techniques and to
determine the factors responsible for the low knowledge and misconception of uncertainty within the
construction sector. Views from project managers obtained from two sub-sectors, the real estate and the oil
and gas was evaluated. Finding of the study revealsa low level of use of uncertainty management tools and
techniques due to the lack of clear understanding of uncertainty and its management parameters. Further
finding identifies the type of project management practice in use, and over reliance on the use of
deterministic approach as factors responsible for the low knowledge of uncertainties. The challenge
therefore is how to improve the state of misconception among practitioners and to explore refinements to
the traditional project management framework. To develop appropriate knowledge about uncertainty
management, the notion that uncertainty management is about creating previously unknown information,
must be repealed to embrace approaches encouraging information sharing, learning, and competence. The
study provides an insightful perspective into understanding uncertainty in projects;and highlight possible
refinements to extant project management practice in order to enhance uncertainty management within the
construction sector.

Context-sensing for context-aware HCI challenges the traditional sensor fusion methods with dynamic sensor configuration and measurement requirements commensurate with human perception. The Dempster-Shafer theory of evidence has uncertainty management and ...

This study examined openness and topic avoidance in interpersonal communication about ovarian cancer. Guided by the uncertainty management theory, the researchers analyzed qualitative data from 28 ovarian cancer patients/survivors and found openness and topic avoidance to be complex communication behaviors which are connected to patients/survivors' uncertainty. Participants appraised uncertainty about disease prognosis and effectiveness of treatments as a threat; thus, they avoided topics such as treatment side effects and fears about death and disease recurrence to manage such uncertainty. Furthermore, findings showed that communication about ovarian cancer is layered with degrees of openness and avoidance relative to respective audiences and changing illness trajectories. Overall, the findings indicate connections between interpersonal communication about ovarian cancer and uncertainty management practices, suggesting that intervention efforts should help cancer patients/survivors and relational others practice sensitivity when discussing topics such as death and dying.

Abstract: There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the ...