Organizational Decision Support Systems Research Articles

Top Management's Role in Promoting Decision Support Systems Efficiency

Despite overwhelmingly positive reviews for decision support systems, the IS literature has produced inconsistent results regarding the role of top management and the effectiveness of these systems. IS researchers are concerned with there being a widening gap between research and practice, leading to the current study, focusing on the relevance of these two constituencies. This study employs the Delphi methodology in relation to Saudi Arabia to investigate the reality of the decision support systems in governmental organizations and the diverse issues related to making effective use of them by increasing the role of top management. The findings revealed that there is an absence of a role for IT in the decision-making process, and that there is a lack of robust data warehouse systems capable of supporting organizations' top management with high-quality information. The study revealed various required reforms of various governmental and institutional arrangements and obligational aspects of the efficiency of decision support systems.

BIMp-Chart—A Global Decision Support System for Measuring BIM Implementation Level in Construction Organizations

Building Information Modeling (BIM) is recognized as one of the most significant technological breakthroughs in the Architecture, Engineering, and Construction (AEC) industry. The pace of implementation of BIM in AEC has increased during the past decade with an enhanced focus on sustainable construction. However, BIM implementation lags its potential because of several factors such as readiness issues, lack of previous experience in BIM, and lack of market demand for BIM. To evaluate and solve these issues, understanding the current BIM implementation in construction organizations is required. Motivated by this need, the main objective of this study is to propose a tool for the measurement of BIM implementation levels within an organization. Various sets of indexes are developed based on their pertinent Critical Success Factors (CSFs). A detailed literature review followed by a questionnaire survey involving 99 respondents is conducted, and results are analyzed to formulate a BIMp-Chart to calculate and visualize the BIM implementation level of an organization. Subsequently, the applicability of the BIMp-Chart is assessed by comparing and analyzing datasets of four organizations from different regions, including Qatar, Portugal, and Egypt, and a multinational organization to develop a global measurement tool. Through measuring and comparing BIM implementation levels, the BIMp-Chart can help the practitioners identify the implementation areas in an organization for proper BIM implementation. This study helps understand the fundamental elements of BIM implementation and provides a decision support system for construction organizations to devise proper strategies for the effectual management of the BIM implementation process.

A Fuzzy Inference-Based Facility Prioritization Decision Support System for Complex Hierarchical Organizations

ABSTRACT Safeguarding limited resources for an organization's most critical assets can be difficult when decision-makers at different corporate hierarchy levels have different objectives and needs. Prioritizing resources in a manner that aligns with the organization's strategic goals requires expertise and knowledge at all corporation levels. DePalmer et al. (2021) explored the opportunity to quantify the relationship between facilities and the operations they support using a Mamdani fuzzy inference system. This research extends the previous work by incorporating multi-level perspectives of the facilities and the operations they support outside of the tactical campus. Additionally, the authors simulated various risk attitudes to investigate how subjective inputs at the tactical level can affect strategic-level outputs. This research produces a framework that aggregates junior-level facility knowledge depth with the breadth of senior-level operational and strategic knowledge to support decision-making for facility project prioritization. An additional prediction boundary is created from the risk attitude variance and can give portfolio managers data-driven tools for quality control of risk profiles at individual campus locations.

Estimating transportation-related CO2 emissions of European city tourism

The present study develops a methodology to assess transportation-related CO2 emissions of European city tourism. In doing so, not only is travel distance considered, but also the chosen transportation modes and the particularities of the different cities’ source markets. The major contribution of this study is the implementation of this learning methodology into a decision support system for destination management organizations of cities. Based on a sample from 2018 of 48 European cities with at least 40 source markets, the range of aggregate transportation-related CO2 emissions of European city tourism is estimated. Moreover, a longitudinal analysis of the exemplary city of Vienna covering the period of 1990 to 2018 is carried out. Finally, some policy recommendations of how destination management organizations can contribute to make the estimated transportation-related CO2 emissions even more precise and on how to make European city tourism more environmentally sustainable are drawn.

Complexity drivers in engineering design

PurposeIn the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.Design/methodology/approachThe proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.FindingsAn analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.Originality/valueThe originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.

Agent Based Simulation on Task Workflow Oriented Self-Organization of Cellular Organizational Network

Modeling self-organization is a critical problem in computational analysis of organizational dynamics and decision support system. Task workflow oriented self-organization shows different characteristics from completely self-organization mechanism. Towards this end, a task workflow oriented self-organization model is constructed to analyze the internal mechanism and performance under different task requirement environments. The cellular organizational network is used to model the relationship structure of cellular work groups. The Agent Based Simulation (ABS) is used to simulate the whole activity self-organization process and individual behaviors driven by task workflow. The model is examined through for simulation experiments. Experimental results shows the difference of the organizational performance according to different task requirements, which exhibits potential application in task workflow oriented organization design and optimization.

Patterns of business intelligence systems use in organizations

Business intelligence (BI) is often used as the umbrella term for large-scale decision support systems (DSS) in organizations. BI is currently the largest area of IT investment in organizations and has been rated as the top technology priority by CIOs worldwide for many years. The most important use patterns in decision support are concerned with the type of decision to be supported and the type of manager that makes the decision. The seminal Gorry and Scott Morton MIS/DSS framework remains the most popular framework to describe these use patterns. It is widely believed that DSS theory like this framework can be transferred to BI. This paper investigates BI systems use patterns using the Gorry and Scott Morton framework and contemporary decision-making theory from behavioral economics. The paper presents secondary case study research that analyzes eight BI systems and 86 decisions supported by these systems. Based on the results of the case studies a framework to describe BI use patterns is developed. The framework provides both a theoretical and empirically based foundation for the development of high quality BI theory. It also provides a guide for developing organizational strategy for BI provision. The framework shows that enterprise and smaller functional BI systems exist together in an organization to support different decisions and different decision makers. The framework shows that personal DSS theory cannot be applied to BI systems without specific empirical support.

From the grid to the smart grid, topologically

In its more visionary acceptation, the smart grid is a model of energy management in which the users are engaged in producing energy as well as consuming it, while having information systems fully aware of the energy demand-response of the network and of dynamically varying prices. A natural question is then: to make the smart grid a reality will the distribution grid have to be upgraded? We assume a positive answer to the question and we consider the lower layers of medium and low voltage to be the most affected by the change. In our previous work, we analyzed samples of the Dutch distribution grid (Pagani and Aiello, 2011) and we considered possible evolutions of these using synthetic topologies modeled after studies of complex systems in other technological domains (Pagani and Aiello, 2014). In this paper, we take an extra important step by defining a methodology for evolving any existing physical power grid to a good smart grid model, thus laying the foundations for a decision support system for utilities and governmental organizations. In doing so, we consider several possible evolution strategies and apply them to the Dutch distribution grid. We show how increasing connectivity is beneficial in realizing more efficient and reliable networks. Our proposal is topological in nature, enhanced with economic considerations of the costs of such evolutions in terms of cabling expenses and economic benefits of evolving the grid.

A dynamic carsharing decision support system

This paper proposes a dynamic optimization–simulation model as a decision support system for one-way carsharing organizations. To reduce the vehicle imbalance in one-way systems, a Vehicle Relocation Optimization model is solved successively in a discrete event simulation. Each event is the arrival of a new user. The model is compared to an a priori benchmark model. Autoshare is chosen as a case study. Results show that increasing the reservation time (time between requesting and picking up a vehicle) from 0 to 30min reduces fleet size by 86%. The model captures a tradeoff between vehicle relocation hours and fleet size.

Strategic Decision Support Systems for Local Government: A Performance Management Issue? The Use of Information Systems on the Decision-making and Performance Management of Local Government

This paper aims to lay the grounds of a framework for further research on Decision Support Systems (DSS) in French local government organizations. A survey conducted in 2008 with 225 CIOs and executives in collaboration with the French Association of Management Control in French local government (AFIGESE) is used to analyze the maturity of implementation of these systems in French sub-national communities (cities and regions). Results show their importance for local public managers on decision making, performance, and management control. A literature review of the decision making process in the public sector and a theoretical framework on the design science of information systems is hence developed to provide the basis of a research program dedicated to the conception of DSS as IT artifacts for local governments.

MODSSO–A Manager-centric Global Decision Support System for Organizations

The goal of this paper is to describe a set of structured concepts for the design of software systems supporting the global decision process in an enterprise or organization. The concepts has as elements: i) each manager has available a decision dashboard to support, in a framework of decision theory, the flux of decision-making for which he or she is responsible; ii) the dashboards also allow managers crowdsourcing from non-managers different aspects of decision iii) the dashboards are connected in a conversational network; iv) this conversational network is so structured to support the global decision process of the organization. An example of implementation's architecture for the concept will be described.

Towards the Realization of an Integrated Decision Support Environment for Organizational Decision Making

Traditional decision support systems are based on the paradigm of a single decision maker working at a standalone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This article proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re-configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi-tier integration framework for consistent information exchange and sharing, seamless process co-ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations.

A decision support system for public research organizations participating in national research assessment exercises

AbstractWe are witnessing a rapid trend toward the adoption of exercises for evaluation of national research systems, generally based on peer review. They respond to two main needs: stimulating higher efficiency in research activities by public laboratories, and realizing better allocative efficiency in government funding of such institutions. However, the peer review approach is typified by several limitations that raise doubts for the achievement of the ultimate objectives. In particular, subjectivity of judgment, which occurs during the step of selecting research outputs to be submitted for the evaluations, risks heavily distorting both the final ratings of the organizations evaluated and the ultimate funding they receive. These distortions become ever more relevant if the evaluation is limited to small samples of the scientific production of the research institutions. The objective of the current study is to propose a quantitative methodology based on bibliometric data that would provide a reliable support for the process of selecting the best products of a laboratory, and thus limit distortions. Benefits are twofold: single research institutions can maximize the probability of receiving a fair evaluation coherent with the real quality of their research. At the same time, broader adoptions of this approach could also provide strong advantages at the macroeconomic level, since it guarantees financial allocations based on the real value of the institutions under evaluation. In this study the proposed methodology was applied to the hard science sectors of the Italian university research system for the period 2004–2006.

Aspectos relevantes dos SAD nas organizações: um estudo exploratório

A informação vem auxiliando as organizações a alcançarem seus objetivos num ambiente de crescente concorrência, exigindo delas rapidez, flexibilidade e alta percepção. A abrangência cada vez maior do uso dos Sistemas de Apoio à Decisão (SAD) como suporte na solução de problemas tem como proposta o processamento de informação para reduzir a incerteza e resolver conflitos. Este artigo tem como objetivo fazer uma investigação sobre os SAD nas organizações brasileiras. Para tal, foi conduzida uma pesquisa exploratória e descritiva, sobre o assunto, foram utilizados questionários que investigaram os SAD nas empresas brasileiras e aspectos relevantes destes sistemas.

An organizational decision support system for effective R&D project selection

Research and development (R&D) project selection is an important task for organizations with R&D project management. It is a complicated multi-stage decision-making process, which involves groups of decision makers. Current research on R&D project selection mainly focuses on mathematical decision models and their applications, but ignores the organizational aspect of the decision-making process. This paper proposes an organizational decision support system (ODSS) for R&D project selection. Object-oriented method is used to design the architecture of the ODSS. An organizational decision support system has also been developed and used to facilitate the selection of project proposals in the National Natural Science Foundation of China (NSFC). The proposed system supports the R&D project selection process at the organizational level. It provides useful information for decision-making tasks in the R&D project selection process.

A Web-based AHP approach to standardize the process of managing service-contracts

Despite the gainful use of the Web as a communication medium, recent research suggests that very little work has been done to leverage this new technology for enabling changes in the planning process. This paper, motivated by a situation at a Fortune 100 company, describes a prototype Web-based decision support system (DSS) for the management of service contracts, which are being increasingly purchased by a variety of businesses. The planning for spare parts needed to support service contracts is hampered by unpredictable and extremely low demands, thereby necessitating a subjective manual approach that is inherently non-standardized and non-coordinated among the various constituents of the organization. In this paper, we describe how a Web-based system can enable the standardization of the process of managing and supporting service contracts. In addition, our DSS supports geographically and functionally dispersed decision-making roles, thereby displaying characteristics of an organizational decision support system (ODSS).

Adoption of information quality management practices in US healthcare organizations

The growing acceptance of evidence‐based decision support systems in healthcare organizations has resulted in recognition of data quality improvement as a key area of both strategic and operational management. Information managers are faced with their emerging role in establishing quality management standards for information collection and application in the day‐to‐day delivery of health care. In the USA, rigid data‐based practice and performance standards and regulations related to information management have met with some resistance from providers. In the emerging information‐intensive healthcare environment, managers are beginning to understand the importance of formal, continuous data quality assessment in health services delivery and quality management. Variation in data quality management practice poses quality problems in such an environment, since it precludes comparative assessments across larger markets or areas, a critical component of evidence‐based quality assessments. In this study a national survey of health information managers was employed to provide a benchmark of the degree of such variation, examining how quality management practices vary across area indicators. Findings here suggest that managers continue to employ paper‐based quality assessment audits, despite nationwide mandates to adopt system‐based measures using aggregate data analysis and automated quality intervention. The level of adoption of automated quality management methods in this study varied significantly across practice characteristics and areas, suggesting the existence of data quality barriers to cross‐market comparative assessment. Implications for healthcare service delivery in an evidence‐based environment are further examined and discussed.

MACE: multi-agents coordination engine to resolve conflicts among functional units in an enterprise

The purpose of this paper is to study how a multi-agent-based coordination mechanism can resolve conflicts among functional units in an enterprise. In the era of information technology, characterized by web technology, intelligent agents demonstrate the best interests of a functional unit when engaged in the highly delicate coordination process of an enterprise. Thus, behavioral problems that occur while coordinating conflicts among functional units can be avoided effectively. Since there are a number of functional units in an enterprise, the multi-agents are utilized to support the agent-based coordination of conflicts among several functional units. This paper proposes a new type of multi-agent-based coordination engine termed MACE in which the information exchange between multi-agents is properly controlled via a complicated algorithm. To illustrate the performance of MACE, we devised a cooperative organizational decision support system (CODSS) and incorporated MACE into CODSS, yielding MACE_CODSS. The combined case of production and marketing was introduced and tackled by MACE_CODSS, obtaining the proper coordination results. To verify the improved performance of MACE, we implemented three types of coordination DSS: Joint_CODSS, Separate_CODSS, and None_CODSS. With 12 simulation periods and 100 simulation runs, we obtained comparative coordination results for each coordination type. Statistical tests revealed that the proposed MACE_CODSS produced the most desirable coordination results.

Organizational reconciliation and its implications for organizational decision support systems: a semiotic approach

This paper describes the key problems with the core concepts behind ODSS, and provides a critique from a theoretical perspective that draws on organizational theory and semiotics. We argue that any distinction between organizational decision support systems (ODSS) and other related systems such as DSS or group decision support systems (GDSS) should be based on the difference between the characteristics of groups and organizations. Our approach uses characteristics of communication within organizations to model information in order to support organizational level decisions. We illustrate the usefulness of this approach by examining a decision-making problem in the context of a British hospital.

Enterprise-wide DSS: Development Approaches and Outcomes

Soft systems methodologies and other participatory and “bottom-up” approaches have recently gained much attention in the information systems development literature with their focus on organizational versus technical aspects and their potential to increase the likelihood of systems success. This paper investigates the problem of information systems development in the context of enterprise-wide decision support systems (DSS). Larger and more complex enterprise-wide DSS are now required because of organizational changes and demands for more sophisticated information and technological advancements, including integrated systems, and open architectures. The paper compares the development of two organizational DSS in the same organization. The aim is to contrast aspects of the development approaches employed and the related degrees of success in outcomes. These case studies may provide insights for other organizations facing the challenges of developing successful enterprise-wide systems.