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To date, many of the models and theories that seek to explain problem solving and decision making, have tended to adopt an overly reductionist view of the processes involved. As a consequence, most theories and models have proved unsuitable in providing managers with a practical explanation of the dynamics that underpin problem solving. A substantial part of a manager’s time is taken up with problem solving and decision making issues. The question of whether managers possess the necessary problem solving skills, or have access to “tools”, which can be used to manage different types of problems, has become an issue of some importance for managers and organisations alike. This paper seeks to contribute to the current literature on problem solving and decision making, by presenting a conceptual model of problem solving, which is intended to assist managers in developing a more holistic framework for managing problem solving issues.

This study aims at determining the factors that favor a systematic approach to deal with complex operational and strategic problems. Management literature on problem-solving makes a clear distinction between either fixing a problem temporarily by eliminating its symptoms or solving it by diagnosing and altering underlying causes. Adopting a cognitive perspective of the dual-processing theory, this study labels these two approaches intuitive problem-solving and systematic problem-solving (SPS). While the superior effectiveness of SPS in fostering organizational learning is widely documented, existing literature fails to provide an overview of the conditions that support the adoption of SPS.

This paper presents a systematic literature review to shed light on the main supporting factors of SPS in operational as well as strategic domains.

Seven supporting factors of SPS (namely, nature of the problem, time availability, information availability, collaborative culture, transformational leadership, organizational learning infrastructure and environmental dynamism) are first identified and then discussed in an integrative model.

This work is an original attempt to inclusively address organizational, environmental and problem nature-related factors that favor SPS adoption. By determining the SPS supporting factors, this study highlights why many organizations fail or struggle to implement and sustain SPS over time.

This paper aims to introduce a practical expert decision support system (EDSS) for performing location analysis and making real estate location decisions in the organization’s facility and real estate management (FREM) department in presence of several decision criteria, under risk and uncertainty. This tool is particularly useful for making strategic decisions in facility planning, portfolio management, investment appraisal, development project evaluations and deciding on usage possibilities in an unbiased, objective manner.

The proposed EDSS uses fuzzy logic and uncertainty theory as two of the most useful tools to deal with uncertainties involved in the problem environment. The system performs an unbiased mathematical analysis on the input data provided by the decision-maker, using a combination of Analytical Hierarchy Process (AHP) and Global Criterion Method; determines a suitable compromise level between the objectives; and delivers a set of locations that complies best with the outlined desires of the management as the final solution. The application of the system is tested on a real case and has delivered satisfactory results.

The proposed EDSS took the defined objectives, the list of alternative locations, and their attributes as the required input for problem-solving, and used a combination of AHP, Possibilistic approach, and global criterion method to solve the problem. The delivered outcome was a set of proper locations with the right attributes to meet all objectives of the organization at a satisfactory level, confirmed by the problem owners.

The application of such a system with such a degree of preciseness and complexity has been very limited in the literature. The system designed in this study is an Industry 4.0 decision making tool. For designing this system several body of knowledge are used. The present study is particularly useful for making strategic decisions in the domains of portfolio management, investment appraisal, project development evaluations and deciding on property usage possibilities. The proposed EDSS takes the information provided by the experts in the field (through qualitative and quantitative data collecting) as the inputs and operates as an objective decision-making tool using several bodies of knowledge considering the trends and developments in the world of FREM. The strong scientific method used in the core of the proposed EDSS guarantees a highly accurate result.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Introduction Consider a hi‐fi loudspeaker manufacturing company acquired on the brink of insolvency by an American multinational. The new owners discover with growing concern that the product range is obsolete, that manufacturing facilities are totally inadequate and that there is a complete absence of any real management substance or structure. They decide on the need to relocate urgently so as to provide continuity of supply at the very high — a market about to shrink at a rate unprecedented in its history.

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.

We extend the classical garbage can model to examine how individual differences in ability and motivation will influence organizational performance. We find that spontaneous coordination provided by an organized anarchy is superior when agents are equally competent. The Weberian bureaucracy of planned coordination is effective when problems require specialist knowledge. However, errors in matching problems to specialized agents are a central challenge for bureaucracies. Actual organizations, therefore, combine elements of organized anarchies and bureaucracies. Heterogeneous motivation compounds coordination problems, but is usually less important than competence. Our findings point to matching and interactive learning as fruitful areas for further study.

The multiple objective decision making problem arises when two or more non‐comparable objective functions are to be simultaneously optimised. There is a definite trend towards utilising interactive techniques for solving the multiple objective decision making problem. Interactive techniques allow the involvement of the DM throughout the decision process. In this paper we first provide a brief overview of multiple objective decision making, and then give a survey of literature dealing with interactive multiple objective decision making from 1965 to 1988.

Do managers have the creative and innovative ability needed for their organisations to survive in an increasingly competitive environment? A study of 200 managers from eight companies gives an answer to this question. If intuition is an indication of creativity and innovation, we find that almost 25 per cent of all managers were primarily intuitive when solving problems and making decisions. The concept of intuition and other decision functions is based on Jung’s typology. Is intuition in managers an important asset to their organisations? An investigation of problem‐solving and decision‐making styles of 33 managers related to organisational effectiveness throws some light on this question. What is called the “creative‐innovative” decision‐making style was found in 23 per cent of the managers. This article suggests that intuition as decision‐making style appears to be related to organisational effectiveness. Several managers are intuitive. Whether the intuitive managers are more effective than others remains to be seen.