An architecture for organisational decision support

The Decision Support (DS) topic of the Network Enabled Capability for Through Life Systems Engineering (NECTISE) project aims to provide organisational through-life decision support for the products and services that BAE Systems deliver. The topic consists of five streams that cover resource capability management, decision management, collaboration, change prediction and integration. A proposed architecture is presented for an Integrated Decision Support Environment (IDSE) that combines the streams to provide a structured approach to addressing a number of issues that have been identified by BAE Systems business units as being relevant to DS: uncertainty and risk, shared situational awareness, types of decision making, decision tempo, triggering of decisions, and support for autonomous decision making. The proposed architecture will identify how either individuals or groups of decision makers (including autonomous agents) would be utilised on the basis of their capability within the requirements of the scenario to collaboratively solve the decision problem. Features of the scenario such as time criticality, required experience level, the need for justification, and conflict management, will be addressed within the architecture to ensure that the most appropriate decision management support (system/naturalistic/hybrid) is provided. In addition to being reliant on a number of human factors issues, the decision making process is also reliant on a number of information issues: overload, consistency, completeness, uncertainty and evolution, which will be discussed within the context of the architecture

Urban management revolution: intelligent management systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated transparent and open decision making mechanism. The paper emphasises the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This paper introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The paper discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This paper also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities

Implikasi Sistem Pendukung Manajemen Terhadap Lingkungan Organisasi.

ABSTRAK Computer applications for management support are on the rise. The microcomputer revolution made computer available on many managers\u27 desks. Managers may now access thousands of databases and computerized analysis in their decision making. Corporate are developing distributed systems that enable easy accessibility to data stored in multiple locations. Various information systems are being integrated with each other and/or with other automated systems. Managers can make better decisions because they have more accurate information at their fingertips. Decision Support Systems, Group Decisions Support Systems, Executive Information Systems, Expert Systems, and Artificial Neural Networks, collectively called Management Support Systems (MSS), are the major technologies behind this developments. Introduction of MSS may create a significant change in organization and this article discusses the implications of implementing MSS in organizations. Key word: Manajement Support Systems, Network, Rekayasa ulan

Knowledge network modelling to support decision-making for strategic intervention in IT project-oriented change management

This is the Accepted Manuscript version of an article published by Taylor & Francis in Journal of Decision Systems on 20 March 2014, available online: http://www.tandfonline.com/doi/abs/10.1080/12460125.2014.886499.This paper focuses on knowledge management to enhance decision support systems for strategic intervention in information technology (IT) project-oriented change management. It proposes a model of change management knowledge networks (CMKNM) to support decision by tackling three existing issues: insufficient knowledge traceability based on the relationships between knowledge elements and key factors, lack of procedural knowledge to provide adequate policies to guide changes, and lack of ‘lessons learned’ documentation in knowledge bases. A qualitative method was used to investigate issues surrounding knowledge mobilisation and knowledge networks. Empirical study was undertaken with industries to test the CMKNM. Results are presented from the empirical study on the key factors influencing knowledge mobilisation in IT project-oriented change management, knowledge networks and connections. The CMKNM model allows key knowledge mobilisation factors to be aligned with each other; it also defines the connections between knowledge networks allowing knowledge to be mobilised by tracing knowledge channels to support decision.Peer reviewe

Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes. View Full-Tex

Expert vs. Management Support Systems: Semantic Issues

Expert systems hold great promise for technical application areas such as medical diagnosis or engineering design. They are, we argue, less promising for management applications. The reason is that managers are not experts in the sense of possessing a formal body of knowledge which they apply. The limitations of artificial intelligence approaches in managerial domains is explained in terms of semantic change, motivating attention towards management (decision) support systems

Capability of APSIM-Oryza to stimulate lowland rice-based farming systems under nitrogen treatments in a tropical climate

Rice is the most important crop in Asia and the staple food for most of the world’s population. Due to the overwhelming importance of this crop, modelling rice-based farming systems will provide valuable help to compare experimental research findings across regions, extrapolate field experimental data to wider environments, develop management recommendations and decision-support systems, explore effects of climate change and adaptation options, and prediction of crop yield. There is an increasing demand for the capability to simulate rice-based cropping systems, especially in Asia. Such a system capability will allow expanded investigation of nitrogen dynamics, crop sequencing, intercropping, crop residue management and soil and water management. Incorporation of the ORYZA2000 rice model(Bouman and van Laar, 2006) into APSIM (Agricultural Production Systems Simulator (APSIM-Oryza) together with recent work on carbon and nitrogen dynamics in transitional flooded/non-flooded systems(Gaydon et al., 2009) has facilitated long-term simulation of lowland rice-based farming systems scenarios. However, the capability of APSIM-Oryza to simulate rice-based crop sequences involving other crops has undergone limited testing to this point and under a variety of crop management practices and cropping systems. In this paper, we detail testing of the APSIM-Oryza simulation model against an experimental dataset involving lowland rice-rice-soybean crop rotation in West Nusa Tenggara Province(NTB) Indonesi

Simulation based decision support for strategic communication and marketing management concerning the consumer introduction of smart energy meters

Communication and marketing professionals make strategic decisions in highly complex and dynamic contexts. These decisions are highly uncertain on the outcome and process level when, for example, consumer behaviour is at stake. Decision support systems can provide insights in these levels of uncertainty and the professional process of decision making. However, literature describing decision support tools for strategic communication and marketing management that provide clear insights in uncertainty levels is lacking. This study therefore aims at developing a consumer behaviour simulation module as an important element of such a future decision support tool. The consumer behaviour simulation we propose in this paper is based on data collected from a survey among 386 households with which a behavioural change model was calibrated. We show how various decision scenarios for strategic communication and marketing challenges can be explored and how such a simulation based decision support system can facilitate strategic communication and marketing management concerning the introduction of a smart energy meter

Use and effectiveness of decision support systems (DSS): Study of the Saudi private sector

In the industrialized world today, management is characterized by extensive use of computers to manage rapid change, information overload, and complex decision-making. Literature suggests that Decision Support Systems, computer packages offering information retrieval, problem-structuring models, decision alternatives, and other types of decision support, are effective extensions of human decision-making and offer substantial benefits to organizations utilizing them. In spite of overwhelmingly positive reviews for DSS, empirical literature has produced inconsistent results regarding DSS effectiveness, and definitions of “effectiveness” and of DSS itself are varied and sometimes contradictory. Distinguishing DSS from MIS (management information systems) and other types of managerial computer support has proven to be an essential part of DSS research. An additional gap in DSS research to date is that little is known about DSS use in developing countries and the potential of DSS to improve decision-making and overall organizational effectiveness. The present empirical study surveyed one member from each of Saudi Arabia\u27s largest corporations to determine to what extent DSS has been incorporated into the companies\u27 decision-making procedures. A second purpose was to determine decision-makers\u27 perceptions of the effectiveness of DSS in terms of their decision processes (time savings, availability of more alternatives, cognitive effort) as well as decision outcomes (decision accuracy and overall quality). The research revealed a high degree of use and enthusiasm for DSS, but revealed gaps in Saudi utilization of the systems. The research identified specific obstacles to more pervasive adaptation and enjoyment of benefits, including a lack of research stemming from researchers\u27 misperceptions of the private sector\u27s interest in and ability to understand Decision Support Systems

An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure