Ubiquitous Decision Support Systems Research Articles

Understanding continued ubiquitous decision support system usage behaviour

With the recent surge in the use of ubiquitous computing devices, users are carrying their own ubiquitous decision support systems (UDSS) and making important decisions using them. UDSS enables decision makers to access mobile networks to acquire information at anytime, anywhere. However, there have been few studies investigating why UDSS users intend to use the systems continuously, as there would be a large number of elements to take into consideration. The specific factors of the UDSS that this study focuses on include the connectivity and context-awareness function, which were not considered in previous research on the adoption of UDSS. Accordingly, this study empirically explores this research question by using the scanphone-based ubiquitous delivery system (UDS), which many delivery service providers have been adopting recently as a form of the ubiquitous decision support system (UDSS). The results reveal that connectivity, context-awareness function, and perceived values play meaningful roles in the UDSS. Based on these results, this study suggests implications and directions for future research to enable the planning and realization of the future UDSS.

The impact of ubiquitous decision support systems on decision quality through individual absorptive capacity and perceived usefulness

PurposeThe purpose of this study is to examine a mobile delivery system as a working ubiquitous decision support system (UDSS) and determine whether it would improve decision quality.Design/methodology/approachUbiquitous mobility and context awareness are the two core functions of the UDSS. Hence the authors examined how they might influence individual absorptive capacity and perceived usefulness. Moreover the authors investigated how individual absorptive capacity and perceived usefulness might be related to decision quality. A total of 174 completed questionnaires were collected from delivery workers, and a financial incentive was provided to participants. To test the hypotheses the research model was analysed with the partial least square method.FindingsThe results reveal that all paths are statistically valid. Individual absorptive capacity and perceived usefulness were positively influenced by ubiquitous mobility and context awareness. In addition individual absorptive capacity and perceived usefulness have positive effects on decision quality.Research limitations/implicationsThis research model did not consider all the capabilities enabled by the UDSS. Future study should pay attention to nomadicity, proactiveness, invisibility, and portability as relevant antecedents within the model.Originality/valueIn the field of IS studies the impact of the UDSS on users' decision quality has remained unclear to date. The authors adopted a mobile delivery system as a working UDSS and applied it in their study. Thereby the authors found the mediating effects of perceived usefulness and absorptive capacity under a ubiquitous environment.

Ubiquitous decision support systems and their impact on users’ online decision-making

Ubiquitous decision support systems and their impact on users’ online decision-making

Unleash the power of mobile word‐of‐mouth

PurposeThis study aims to examine the effects of system and information characteristics in developing users' perceptions towards ubiquitous decision support systems (UDSS).Design/methodology/approachThe research model is empirically examined with survey data from 218 mobile users who have adopted a UDSS, i.e. mobile Dianping.com. A structural equation modelling approach is employed to assess the hypotheses.FindingsThe findings demonstrate that system characteristics of wireless networks, mobile devices and mobile applications significantly predicted system quality, which in turn determined system usefulness. Localisation, immediacy and customisation of mobile word‐of‐mouth were the major predictors of information quality, which in turn determined information usefulness.Originality/valueThis study contributes to our current understanding of ubiquitous commerce, especially mobile word‐of‐mouth, by presenting an integrated research framework, identifying system and information characteristics that are specific to the ubiquitous era, extending system quality and system usefulness from a single system to a combination of systems, and empirically examining the crossover effects between system and information factors.

MIS and Illusions of Control: An Analysis of the Risks of Risk Management

Dysfunctional MIS is an important topic but one that has received comparatively little attention in the literature. This discussion paper attaches new literature to the subject. The new literature centres upon the epistemological status of certain forms of MIS. More specifically, it is argued that MIS, based upon metonymy (part for whole substitution), can seriously mislead managers because the representation gets mistaken for the reality. The demonstration is based on high level risk registers. Risk registers were selected for analysis because they are ubiquitous and important decision support systems. In theory, diligent use of risk registers should virtually eliminate unpleasant surprises. In practice, the result may be an illusion of control. Analysis draws upon sociology and psychology to explain why this may be so.

Context-prediction performance by a dynamic Bayesian network: Emphasis on location prediction in ubiquitous decision support environment

Ubiquitous decision support systems require more intelligent mechanism in which more timely and accurate decision support is available. However, conventional context-aware systems, which have been popular in the ubiquitous decision support systems field, cannot provide such agile and proactive decision support. To fill this research void, this paper proposes a new concept of context prediction mechanism by which the ubiquitous decision support devices are able to predict users’ future contexts in advance, and provide more timely and proactive decision support that users would be satisfied much more. Especially, location prediction is useful because ubiquitous decision support systems could dynamically adapt their decision support contents for a user based on a user’s future location. In this sense, as an alternative for the inference engine mechanism to be used in the ubiquitous decision support systems capable of context-prediction, we propose an inductive approach to recognizing a user’s location by learning a dynamic Bayesian network model. The dynamic Bayesian network model has been evaluated with a set of contextual data from undergraduate students. The evaluation result suggests that a dynamic Bayesian network model offers significant predictive power in the location prediction. Besides, we found that the dynamic Bayesian network model has a great potential for the future types of ubiquitous decision support systems.

A NEED-AWARING MULTI-AGENT APPROACH FOR AD HOC NEED IDENTIFICATION AND GROUP FORMATION IN NOMADIC COMMUNITY COMPUTING

Researchers have proposed community computing for facilitating both group formation and group decision making. However, legacy community computing systems do not support group needs identification for ad hoc group formation, which is a key feature of ubiquitous decision support systems and services. In this article, we describe a multi-agent-based methodology that both enables nomadic community computing and supports ad hoc needs identification and group formation. Our approach uses needs awareness through a Rescorla-Wagner model of association theories and need reasoning by rough set theory. With a focus on supporting decision making within a relatively small-sized group of multiple individuals in a community, the methodology addresses the following three characteristics: (1) ad hoc group formation; (2) context-aware group needs identification; and (3) implementation of mobile devices working indoors and outdoors. We develop a prototype system, NAMA-US, to show the feasibility of the ideas proposed in this article.

UbiDSS: a proactive intelligent decision support system as an expert system deploying ubiquitous computing technologies

Abstract Many industries have deployed expert systems (ESs) to provide support for solving complicated and specialized problems since 1980. Because ESs are originally designed for generating feasible alternatives in an automated manner, users, especially decision makers, expect ESs to make decisions proactively and intelligently by automatically detecting users' contextual data. In other words, decision makers require decision support systems (DSSs) to be reinforced with proactive and intelligent ESs that can utilize contextual data. Meanwhile, ubiquitous technology-based applications currently only provide limited personalization services that use the user's context and preferences; in other words, these systems do not fully make use of sophisticated decision making capabilities. Hence, this paper describes how decision making and context-aware computing are jointly used to establish ubiquitous computing technology-based applications. To do so, we propose an amended DSS paradigm, Context-Knowledge-Dialogue-Data-Model (CKDDM). This model describes what may be considered for future DSSs when we regard ubiquitous computing technology as an inevitable effect that changes how decision making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems (ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, Context-Aware Multi Agent System-My Optimization (CAMA-myOpt) has been implemented as an illustrative example system.