Search results

The librarian and researcher have to be able to uncover specific articles in their areas of interest. This Bibliography is designed to help. Volume IV, like Volume III, contains features to help the reader to retrieve relevant literature from MCB University Press' considerable output. Each entry within has been indexed according to author(s) and the Fifth Edition of the SCIMP/SCAMP Thesaurus. The latter thus provides a full subject index to facilitate rapid retrieval. Each article or book is assigned its own unique number and this is used in both the subject and author index. This Volume indexes 29 journals indicating the depth, coverage and expansion of MCB's portfolio.

Decision support (DS), as a traditional management concept, have had a remarkable role in competitiveness or survival of organizations and nowadays, business intelligence (BI), as a brand modern impression, has various contributions in supporting decision-making process. Although, a variety of benefits are expected to arise from BI functions, researches, and models that determining the effect of BI functions on the decisional and organizational benefits are rare. The purpose of this paper is to study the relationship between BI functions, DS benefits, and organizational benefits in context of decision environment.

This research conducts a quantitative survey-based study to represent the relationship between BI capabilities, decision support benefits, and organizational benefits in context of decision environment. On this basis, the partial least squares (PLS) technique employs a sample of 228 firms from different industries located in Middle-East countries.

The findings confirm the existence of meaningful relationship between BI functions, DS benefits, and organizational benefits by supporting 15 out of 16 main hypotheses. Essentially, this research provides an insightful understanding about which capabilities of BI have strongest impact on the outcome benefits.

The results can provide effective and useful insights for investors and business owners to utilize more appropriate BI tools and functions to reach more idealistic organizational advantages. Also it enables managers to better understand the application of BI functions in the process of achieving the specified managerial support benefits.

Focuses on consulting experiences utilizing simulation approaches that capture decision‐making processes in formulations that are transparent to the general manager. Examines the dual benefit of modelling in terms of not only providing forecasts and an objective framework for quantitative evaluations, but also in the softer sense of building consensus in management teams. Casts these experiences against theories of effective group decision making, and other decision support examples which focus on the use of models. Reconciles the circumstances of the case with the conditions specified for effective group working and suggests that the greatest contribution may be made to consensus decision making when the whole modelling approach, not just access to model outputs, is integrated into the decision‐making process, and where the model complexity is commensurate with the task complexity and the task familiarity of the management group.

Computer‐aided decision‐support tools are part and parcel of the emergency planning and management process today. Much is dependent on using modern technology to gather and analyse data on damage assessment, meteorology, demography, etc. and provide decision support for prevention/mitigation, response and recovery. Diverse technologies are merged to provide useful functions to aid the emergency planner/manager. Complexities arise when attempting to link several streams of technology to achieve a realistic, usable and reliable decision‐support tool. This discussion identifies and analyses the challenging issues faced in linking two technologies: simulation modelling and GIS, to design spatial decision‐support systems for evacuation planing. Experiences in designing CEMPS, a prototype designed for area evacuation planning, are drawn on to discuss relevant managerial, behavioural, processual and technical issues. Focus is placed on modelling evacuee behaviour, generating realistic scenarios, validation, logistics, etc. while also investigating future trends and developments.

This article seeks to present a decision support model for improving supply chain performance. The model aims to provide a holistic view of the supply chain as an integrated system by analyzing inventory options to facilitate the decision‐making process by business partners in the system.

In recent years, organizations have focused on incorporating both internal and external business activities of their supply chain into an integrated system. The goal of integration of all supply chain activities is to maximize total systems performance while minimizing costs. Literature review and professional experience in the field provided the foundation for the model development in this research.

The article demonstrates the usefulness of a decision support model in analyzing and developing a cooperative environment among supply chain members in order to reduce the cost of inventory as well as the cost of goods sold. The effects of utilizing such tools as just‐in‐time and electronic business systems are illustrated and discussed.

The proposed model demonstrates disadvantages of individual optimization in an integrated supply chain system as well as the advantages of collaboration of supply chain members in finding the minimum cost. The model uses one manufacturer with multiple retailers and distributors. Future research in this area could expand the model to allow multiple manufacturers.

The decision support model allows decision makers along the supply chain to employ a series of what‐if analyses to evaluate different scenarios with regard to lowering the cost of products reaching the consumer.

The model developed in this paper provides the foundation for future research as well as support for decision making when various decision makers are involved.

Servitization of manufacturing is characterized by very complex decision processes within strongly unstable and uncertain decision contexts. Decision-makers are face situations of lack of internal and external information. The purpose of this paper is to develop a decision aid approach to support the management of servitization decision-making processes.

The scientific orientation of this research consists in working at improving the efficiency of the servitization decision-making process, by identifying factors of non-reliability, in order to propose remediation actions for the whole process. Improving the final decisions taken by the managers is considered as a consequence of the improvement of the decision-making process reliability. The method, based on modeling and evaluation, requires the specification of a decision process model for servitization, used as a basis to assess decision process reliability and diagnose the enterprise’s servitization decision system. Improving the final decisions made by the managers is considered as a consequence of the improvement of the decision-making process reliability.

Key added values: first, to formalize a servitization decision-making reference model; second, to specify a reliability assessment applied to the decision system; and third, to define a decision process reliability diagnosis procedure for servitization, illustrated in a case study.

A direct perspective is to complete the focus on procedural reliability, by taking into consideration the subjective rationality of decision-makers in the reliability assessment procedure. Additionally, this reliability assessment method and diagnosis could become the basis of a larger risk management approach for servitization.

The diagnosis procedure proposed in the paper is dedicated to generating practical results for enterprise decision-makers, consisting in recommendations for decision process improvements, in the context of servitization. The approach is illustrated through an industrial SME case study. The practical implications are highly contextualized.

The key originality of this research is to tackle servitization complexity with a decision system modeling and diagnosis orientation, including the formalization of the notion of “decision process reliability,” and the specification and implementation of a quantitative assessment procedure.

Expert systems (ES) design emulates expertise with the intention that the ES be used by non-experts. This study aims to predict end-user intention and use of ES by proposing a research model that extends the basic components of the unified theory of acceptance and use of technology (UTAUT) by including additional relevant factors to ES, including the expert domain, perceived relevance, reliability, quality of ES and management support, which directly and indirectly influence the end-user intention to use an expert system.

A structural equation model (SEM), using LISREL, was used to test the measurement and structural models using a sample of 205 end-users of expert systems in the USA. These users of expert systems come from a variety of domains. The factors include both internal and external factors for the individual level of analysis design of this study.

The results showed behavioral intention had the strongest effect on usage, followed by perceived relevance. With respect to the factors that impact intention, perceived relevance had the strongest total effect, followed by attitude. For attitude, effort expectancy had the strongest total effect, followed by management support and perceived relevance.

The results of this study should assist decision-makers in planning training and communications about the use of expert systems so that the expert systems will be used as intended.

The originality of this work resides in the addition of external factors to the UTAUT model that helps provide advice to practitioners in the support needed to insure expert system implementation success.

Model management systems (MMS) empower decision makers throughout the problem‐solving phases by providing operations research and management science (OR/MS) models as well as the knowledge to build or use such models. Managerial problem solving typically involves a wide range of modeling activities, i.e., definition, retrieval, modification, execution, modification, and integration of decision models. This research stems from the basic premise that, given the problem, decision aiding software such as MMS can reach its highest level of performance when the necessary modeling activities are adequately supported, subsequently enhancing the quality of the decisions made by the users. Reported in this paper are the results from an experiment involving two versions of MMS used by naïve modelers in two decision‐making settings. Through this study, we learn that the decision‐making behavior of software users, especially the way they develop their decision strategies, is considerably influenced by the capability of the software.

The purpose of this study is to develop an operational level decision support system model for air traffic controllers (ATCos) within the framework of the Flexible Use of Airspace (FUA) concept to enable more efficient use of airspace capacity. This study produces a systematic solution to the route selection process so that the ATCo can determine the most efficient route with an operational decision support system model using Dijkstra’s Shortest Path Algorithm.

In this study, a new decision support system model for ATCos in decision-making positions was recommended and used. ATCos use this model as a main model for determining the shortest and safest route for aircraft as an operational-level decision support system. Dijkstra Algorithm, used in the model, is defined step by step and then explained with the pseudocode.

It has been determined that when the FUA concept and DSS are used while the ATCo chooses a route, significant fuel, time and capacity savings are achieved in flight operations. Emissions resulting from the negative environmental effects of air transportation are reduced, and significant capacity increase can be achieved. The operational level decision support system developed in the study was tested with 55 scenarios on the Ankara–Izmir flight route compared to the existing fixed route. The results for the proposed most efficient route were achieved at 11.22% distance (nm), 9.36%-time (min) savings and 837.71 kg CO₂ emission savings.

As far as the literature is reviewed, most studies aimed at increasing airspace efficiency produce solutions that try to improve rather than replace the normal process. Considering the literature positioning of this study compared to other studies, the proposed model provides a new systematic solution to the problems that cause human-induced route inefficiency within the framework of the FUA concept.

In the past several decades, Taiwanese companies have been successful in the world market. However, knowledge about how these firms use information technology is very limited. Investigates the application of decision support systems (DSS) and executive information systems (EIS) in Taiwan. Two mail surveys were conducted to explore who used the system, where the systems were applied, what decision models were used and reasons for not using these systems. The results indicate that: more than 20 per cent of the firms already used DSS or EIS and an additional 37 per cent had plans to adopt them shortly; 87 per cent of the firms considered DSS and EIS to be important to their competitiveness; middle‐ and lower‐level managers were major DSS and EIS users; half of them used the system every day; the most troublesome problem in developing DSS/EIS was the difficulty in determining information requirements; and information aggregation and what‐if analysis were major functions for decision support. Furthermore, quantitative models were employed only in large and old companies. The most popular models included linear programming, PERT/CPM, and regression analysis, whereas the most popular domains for application were finance and production management.