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Discusses decisions faced by marketing managers and whether answers to some important questions can be successfully answered. Examines marketing information systems (MIS) components – the data bank, the model bank, the measurement statistics bank, and the system user interface. Posits that there are economic benefits derived from making ‘better’ marketing decisions that result in larger monetary payoffs to the firm. Suggests a systematic impact study be based on analysis of the various steps that have to be taken in constructing a decision model. States MIS aids the marketing manager in specifying the decision model and in implementing this model. Concludes the MIS designer should look at each step in the construction of the decision model in order to estimate the potential impact of the change.

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.

Explains that the focus of decision theory is on the mathematical models. These may be probability based; loss functions or other forms of statistical representations of judgements. Yet, much of decision theory does not lie entirely within any one discipline: it draws on psychology, economics, mathematics, statistics, social sciences and many other areas of study. Investigates investors’ perceptions and attitudes towards real estate. Highlights the important difference between theoretical exposure levels and pragmatic business considerations. Suggests a prescriptive model to explore judgements, beliefs and preferences of decision makers and to inform decision making. Examines the concept of risk and its place in developing a prescriptive model. Maintains that a decision must be judged on factors other than the risk of a single outcome.

Takes the view that managerial decisions are made in a diversity of organizational settings which can best be explained and evaluated in the context of conceptual interdisciplinary decision‐making models, and that such models constitute an appropriate vehicle for explaining the eclectic aspects of managerial decision making in all types of formal organization. Presents a typology of conceptual decision‐making models and evaluates their similarities and differences along with their respective efficacies in various managerial decision‐making contexts. Advances the process model of managerial decision making as the ideal choice for decisions which have significant long‐term consequences for the whole organization.

It should be re‐emphasized, however, that the [Vroom‐Yetton] model is explicitly normative in character in that it specifies what leaders should do in various organizational circumstances — rather than attempting to summarize what leaders do do and what the effects of those actions are. Thus, if the assumptions in the model about the outcomes which result from various leader behaviors are incorrect, the model will lead to faulty behavioral prescriptions.

Marketing management presents challenging ground for the integrated use of intelligent agents. The design of a strategic marketing plan presents a natural division of four distinct yet independent decision problems. Concurrent execution of these four functions can yield a significant decrease in time‐to‐market for new products, and turnaround time for modified products. Electronic information is a two‐edged sword. On the one hand, it results in information overload, taxing the decision‐ making process. On the other hand, the electronic nature of these vast information flows makes them accessible to intelligent agents who can improve the decision‐making process. This paper presents the problem of information overload and decision‐making complexity in marketing management. In it, we present a blackboard‐based agent architecture that allows individual agents to proceed toward their given goals yet react opportunistically to developments reported by other marketing agents. We present the blackboard model of problem solving, and discuss why it is well suited to support multiple marketing agents. CMA, a multi‐agent model for concurrent marketing analysis, is discussed and the agent architecture required for creating a cooperating society of marketing agents is presented.

Although there are many models of decision making, there are few attempts to match the appropriate decision strategy with different situations. After reviewing and comparing six contemporary decision‐making models, a framework and propositions are developed that match strategies with circumstances. The article concludes with a discussion of theoretical and practical application of the proposed contingency model decision making.

The study examines the effects of organisational size on elementary school principals′ instructional leadership decisions to allocate teachers to groups of students. More specifically, the study tested the invariance of a personnel allocation decision‐making model for principals from three categories of California district and school sizes, using the LISREL methodology. The results confirmed the fit of the proposed model to the data across schools of all sizes and in small and medium school districts. In large school districts, however, the proposed model did not fit the data. A specification search to determine the model that describes this organisational context indicated that political bargaining with parents and teachers over the allocation of teachers and students is a less important decision input for principals in large school districts.

The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the IoT-enabled Context-aware BPM (IoT-CaBPM) framework to bridge from the IoT infrastructure to context-aware business processes.

Motivated by the “Three Waves” of BPM research, IoT-enabled context-awareness is, therefore, expected to be achieved for enhancing the business process design, which pilots a new wave of BPR (Business Process Redesign/Reengineering) to enable the business process coevolve with IoT and analytics. This paper reports an illustrative case study of BPR in a Chinese bulk port, one of the hub seaports that widely adopted IoT technologies over the last few years.

The IoT implementation and data analytics has increased the efficiency and improve the monitoring effectively. The proposed IoT-CaBPM framework availably helps to identify and match nodes of IoT devices, business decisions and analytic models in order to redesign a business process towards context-aware variability. As IoT is rapidly becoming the new dominant IT paradigm is moving towards mature implementation in various industries, the corresponding BPR must be planned and executed strategically for achieving better benefits.

Despite some research extend BPM standard by integrating IoT devices as a sort of resources or report generically that the ports operations are affected by IoT, there is still a lack of layers from the IoT infrastructure to context-aware business processes. An industrial BPR case with business models in detail is also a lack for presenting the specific implications and effectiveness of the adoption of such technologies. This paper fills in this gap.

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.