The new era of mobile decision support systems

Introduction

The technological evolution in mobile computing and communication provides an exciting opportunity for a new class of decision support systems (DSS) known as Mobile Decision Support Systems (MDSS). These systems can be very beneficial to a range of application domains where complex and critical decisions are made under time pressure, decision-makers are on the move, and the environment is dynamic and uncertain. Examples include mobile healthcare, emergency management, mobile policing, mobile commerce and mobile banking. Access to up-to-date information and data on mobile devices can significantly enhance DSS and support mobility of decision-makers by accessing and/or analysing data where and when it is needed the most.

While the coming together of technology drivers has enabled the delivery of sophisticated real-time knowledge, the key questions of how this information is incorporated into the DSS and how it is processed to enable real-time decision-making onboard mobile devices have not been fully answered.

A historical overview of mobile decision support systems

Recent growth and advances in mobile computing and communication have revolutionized the way we live and access information. Today we are able to receive and process a vast amount of real-time data and situational information on mobile devices in a manner that has not been witnessed previously. Mobile devices in general are portable devices that are able to communicate with each other using wireless networks, Internet, or other protocols (Burstein et al., 2011). They can be classified into different categories. Among these categories, smartphones, PDAs and tablets are the most widely used devices to support mobile decision support systems as well as being greatly popular with general users (Burstein & Cowie, 2008, Carlsson et al., 2005). Smart phones enable the use of the Internet on the move and have introduced new perspectives on the use of mobile devices.

Although traditional DSS is often accommodated by desktop computers, Turban et al. (2005) predicted that the blooming of mobile technology and mobile devices would bring a lot more opportunities for DSS. One of the main benefits that mobile technology offers to decision support systems is the ability to retrieve real-time information anywhere, anytime (Van der Heijden & Junglas, 2006). Mobile DSS provides a ubiquitous working environment in situations that require high mobility.

MDSS has References (Basole & Chao, 2004; Ngai & Gunasekaran, 2007), proving to save time and increase productivity for those who need to make rapid decisions in real time (Carlsson et al., 2005). Mobile DSS applications all take advantage of mobile technology, wireless communication and location-aware features to deliver an easy way to access useful, real-time information on the move, which is critical for decision-makers (Delir Haghighi et al., 2012). Yet, to use the capabilities of mobile devices effectively and efficiently, there is a need for further research to establish appropriate principles, guidelines and methodologies. As Daniel Power in the invited paper suggests: ‘Researchers have much to learn about mobile decision support’ (p. 8).

Origins of this issue and the papers

The idea for this special issue originated from our prior research in context-aware decision support and the realisation of the rapidly increasing attraction of mobile decision support systems in a wide range of application domains. The offer to prepare a special issue of the Journal of Decision Systems was very timely for sharing our understanding of the theoretical and practical methods and techniques applied in current mobile DS. The aim was also to provide an opportunity for researchers to publicise their research studies and discuss open issues and future work. In this issue, the focus has been given to papers providing a broad analysis of the current state of mobile DSS, as well as those dealing with real-world applications and case studies of mobile and real-time decision support systems.

The special issue opens with an invited paper by Daniel Power, a prominent researcher in the DSS area. Professor Power is the editor of DSSResources.com, the most comprehensive web-based knowledge repository of decision support systems-related resources. His DSS News electronic newsletter also provides visionary insights into new opportunities in supporting better decision-making. It was most opportune to be able to gain the generous and kind support of Dan in our quest for mobile decision support opportunities. The paper is titled ‘Mobile decision support and business intelligence: an overview’ and it provides an interesting and inspiring review of the history of evolution of mobile computing technology and emergence of mobile DSS. This review also looks at the operational business intelligence and data-driven decision support, and cloud-based decision support and business intelligence.

The second paper, by Shijia (Caddie) Gao, titled ‘Mobile decision support systems: a literature review’ provide a comprehensive analysis of the current state of mobile decision support systems research. The paper identifies and analyses 32 articles in major Information Systems journals from 2002 to 2012 and finds interesting patterns with regard to research type, DSS factors, judgement and decision-making factors and types of mobile devices. The paper provides an important overview of the field to inspire future researchers to fill the gaps identified by this study.

The third paper describes a novel technique, contextual graph simulation, for mobile and real-time decision-making that takes into account the time dimension and context management. In this paper, titled ‘Representation of real-time decision making by contextual graphs based simulation’, Patrick Brézillon and Anissa Aroua present the Contextual-Graphs formalism and its implementation, and identify new aspects of contextual graph-based simulation by intelligent assistant systems. The authors discuss a workflow manager developed as part of the MICO (COgnitive MIcroscopy) project for improving the quality of breast cancer diagnosis. The workflow manager provides real-time decision support where the outcomes of any action can lead to changes in the context of decision-making. Mobility here is considered any changes in the play of contextual elements such as the actor, the task, the situation, and the environment.

The fourth paper is titled ‘Real-time management of chemotherapy toxicity using the Advanced Symptom Management System (ASyMS)’. In this paper, Julie Cowie, Lisa McCann, Roma Maguire, Nora Kearney, John Connaghan, Catherine Paterson, Jennifer Hughes and David Di Domenico discuss part of an ongoing study that aims to provide mobile decision support for patients who receive chemotherapy for breast or colorectal cancer. The ASyMS research involves using pre-programmed mobile phones. Patients daily enter the requested information on the mobile phones. They can receive evidence-based self-care advice on the phone. In case of critical symptoms, triage-level alerts are generated and received by the designated cancer specialists. This paper describes Phase III of the ASyMS study which aims to evaluate the impact of the system in a large-scale patient population.

Finally, Stanislaw Stanek, Jacek Namyslo and Stanislaw Drosio present a paper titled ‘Developing the functionality of a mobile decision support system’, which describes three motivating case studies of mobile decision support systems and discuss the good practices from these cases. The first case study focuses on the use of videoconferencing for mobile decision support systems and describes two interesting sample applications named eVideoHelpDesk and e-VideoBiznes. This case study is presented as a solution for improving communications in small- and medium-sized enterprises. The second case study discusses the Comarch Factoring Fraud Prevention system which performs data mining on large volumes of thematic data and is able to provide mobile risk management support to operational staff in different business sectors including banking or trade finance. The third case study, named JAŚMIN, is developed for providing decision support and effective communications in a military setting. In this setting, the aim is to increase data security and network reliability. The authors believe that this system has the potential to be exploited in business applications, particularly where a high level of security is required.

Acknowledgements

We would like to thank all the authors for their contributions and the reviewers for the time they put in reviewing the papers. We would also like to sincerely thank Dr Frédéric Adam, Editor-in-Chief of the JDS, for giving us the opportunity to publish this issue. We also thank Ciara Heavin, Managing Editor, for her invaluable help in preparation of this issue. The work on this special issue was partly supported by Australian Research Council funding (LP0453745).