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The way organizations cope with uncertainty in strategic decision making is prominently discussed. Concepts such as heuristics and simple rules are gaining increasing attention in strategic management research. However, despite their importance, little is known how heuristics and simple rules operate. Our qualitative study reveals that, first, strategic decisions consist of three basic elements: single rules, rule patterns, and emotional handling. Second, we find that firms develop generalizable rule patterns which follow a sequential order of inter-linked rules. Based on the findings we introduce the concept of organizational heuristics as inter-linked rule patterns drawing on organizational experience.

The chapter offers complete details of the latest SGL version particularly suitable for dealing with large security systems and emerging crisis situations. It describes main types of constants representing information, physical matter or both and five very different and specific types of variables operating in fully distributed spaces and even being mobile themselves when serving spreading algorithms. Also given full repertoire of the language operations, called rules, which can be arbitrarily nested and carry different navigation, creation, processing, assignment, control, verification, context, exchange, transference, echoing, timing and other loads. The rules equally operate with local and remote values, process both, matter and distributed networked knowledge, and can express active graph-based patterns navigating, matching, conquering and changing distributed environments. Elementary programming examples in SGL are also provided.

Addresses the problem of sequencing a set of PCBs on a single assembling machine. Considers two objectives, namely minimizing tardiness and minimizing the set‐ups. Reduces component change‐overs by exploiting the similarity between PCBs. Proposes a new measure to sequence the PCBs, taking care of both the objectives. Develops a heuristic for solving the bi‐criteria problem. The proposed method performs better than the existing heuristics for the comparable situation of sequencing in a single machine job‐shop.

Machine scheduling plays an important role in most manufacturing industries and has received a great amount of attention from operation researchers. Production scheduling is concerned with the allocation of resources and the sequencing of tasks to produce goods and services. Dispatching rules help in the identification of efficient or optimized scheduling sequences. The purpose of this paper is to consider a data mining‐based approach to discover previously unknown priority dispatching rules for the single machine scheduling problem.

In this work, the supervised statistical data mining algorithm, namely Bayesian, is implemented for the single machine scheduling problem. Data mining techniques are used to find hidden patterns and rules through large amounts of structured or unstructured data. The constructed training set is analyzed using Bayesian method and an efficient production schedule is proposed for machine scheduling.

After integration of naive Bayesian classification, the proposed methodology suggests an optimized scheduling sequence.

This paper analyzes the progressive results of a supervised learning algorithm tested with the production data along with a few of the system attributes. The data are collected from the literature and converted into the training data set suitable for implementation. The supervised data mining algorithm has not previously been explored in production scheduling.

Purpose – The goal of this chapter is to contribute toward an understanding of Hayek's book “The Sensory Order.” It focuses on his concept of dispositions which influence perception as well as action. The dichotomy between the phenomenal and the scientific world which Hayek stresses throughout his works is based on the existence of such dispositions.

Approach – Hayek's cognitive writings such as The Sensory Order, “Rules, Perception and Intelligibility” (1963), “The Theory of Complex Phenomena” (1964), and “The Primacy of the Abstract” (1969) are the main resources to explain his cognitive theory.

Findings – Hayek's concept of dispositions facilitates re-interpretation of the term “dispersed knowledge.” Also, Hayek's Theory of Cultural evolution is seen as an evolution of dispositions, which stands in line with his view on the concurrent development of mind and culture.

Import of findings – The chapter offers a cognitive interpretation of Hayek's theory of government, depicting governmental action and rule-setting as spontaneous as well as deliberate processes.

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately.

Hyperlink indicators along with URL-based features are used to build the identification model. In the proposed approach, very simple rules are first extracted based on individual features to provide meaningful and easy-to-understand rules. Then, the F-measure score is used to select high-quality rules for identifying phishing websites. To construct a reliable and promising phishing website identification model, the selected rules are integrated using a simple neural network model.

Experiments conducted using self-collected and benchmark data sets show that the proposed approach outperforms 16 commonly used classifiers (including seven non–rule-based and four rule-based classifiers as well as five deep learning models) in terms of interpretability and identification performance.

Investigating patterns of phishing websites based on hyperlink indicators using the efficient rule-based approach is innovative. It is not only helpful for identifying phishing websites, but also beneficial for extracting simple and understandable rules.

The traditional models of real estate market have several sources of imprecision, such as transitions between submarkets, generating difficulties in property valuation. The purpose of this paper is to examine an alternative to improve mass appraisal models, using fuzzy rules.

Fuzzy rule‐based systems (FRBS) are able to generate flexible systems and may be useful in considering vagueness or imprecision presents in real estate market. An application to the housing market of Porto Alegre (Brazil), with more than 30,000 apartments, transacted in 1998‐2001, illustrates the fuzzy system, comparing with traditional hedonic regression model.

The results have indicated the potential of fuzzy rules to use in mass appraisal.

This paper presents a procedure to develop mass appraisal models using FRBS.

Construction resources are often limited, and there is a need to ensure resources are carefully allocated to avoid resource wastage and/or project delay. While mathematical and heuristic models were developed to resolve the conflicts between activities, none of them has been proven to be totally satisfactory. The aim of this paper is to explore this.

In this paper, a novel heuristic method known as a pull‐driven approach (PDA) is proposed; and this approach encourages a lean consideration of resource supply and partnering between activities. Two case studies are presented to illustrate how PDA can be applied. A comparison with another heuristic approach, namely the ranked positional weight method is conducted to illustrate the efficiency of the proposed approach.

Using the PDA approach, all the activities strive to find matching partners to pull resources to their sides. The resources are, therefore, no longer passively pushed to a single activity with high ranking but a combination of activities that can demonstrate their superiority in resource utilisation will actively win the necessary resources.

This approach has an ability to deal with intermittent activities and locate the lean (no‐waste) supply level of each resource.