Search results

There are many cases where top management either missed or almost missed detecting or interpreting a major change in the environment that might have led them to a major setback. We propose a model of sensing in hierarchical organizations that describes a sequence of sensing and detecting changes in the environment, followed by successive stages of perception, interpretation, and finally action. We model an organization as a complex signal detection system, where the flow of information among members of the organization is constrained by two elements: the structure of the organization, which is defined by who reports to whom, and the attentional and cognitive limitations of the individuals. We infer the probability of sensing over time for different levels of environmental shocks and different organizational structures. By focusing on the (un)reliability of sensing and the information flow in different organizational structures, we are able to provide preliminary analysis of the trade-offs among cognitive limitations, speed of detection, modes of information flow, and the resulting performance measure of delay, false-alarms, and true detections.

The purpose of this paper is to show that maintenance performance is potentially better predictable from recording routines.

An attempt is made to observe an effect of a policy. Maintenance cases seem exceptional because of the efficiently obtainable evidence about policy violations which potentially provides access to the counterfactual reality to be avoided by the decision maker. The approach followed in this work is to use maintenance policy compliance to observe the effect of a maintenance policy.

Conventional maintenance scorecards are not geared to accommodate maintenance performance predictions. The proposed alternative representation of maintenance performance indicators much better accommodates maintenance performance predictions.

This work focuses on the operationalisation and the sampling procedure of maintenance performance indicators; the selection of a predictive model is not considered.

This work demonstrates that maintenance decision makers have the possibility to observe the effects of their policy, which potentially enables them to better control their objectives. This work provides guidelines to construct performance indicators that much better accommodate maintenance performance predictions than conventional maintenance performance indicators.

The approach to make the effects of maintenance policy compliance observable is an original contribution to normative decision theory. To construct a maintenance scorecard that accommodates maintenance performance predictions is an original contribution to the field of maintenance performance measurement.

The recent surge in behavioral studies on the coordination mechanisms in supply chains (SCs) and advanced methods highlights the role of SC coordination (SCC) and behavioral issues associated with improving the performance of the operations. This study aims to critically review the behavioral aspect of channel coordination mechanisms.

Following a systematic literature review methodology, the authors adopt a combination of bibliometric (to reflect the current state of the field), content (using Leximancer data mining software to develop thematic maps) and theory-oriented qualitative analyzes that provide a holistic conceptual framework to unify the literature’s critical concepts.

The analysis confirms the plethora of risk-oriented publications, demonstrating that the second largest category of studies is concerned with social preferences theory. Most studies were based on experiments, followed by analytical modeling, revealing the impact of heuristics and individual preferences in SC decisions and suggesting promising managerial and theoretical avenues for future research.

The study sheds light on behavioral decision theories applied to SC coordination by categorizing the literature based on the adopted theories. The methodological contributions include using automated content analysis and validating the outcome by interviewing leading scholars conducting active research on “behavioral operations management and SC contracts.” The authors also propose several directions for future research based on the research gaps.

This research aims to create a methodology that integrates optimization techniques into preliminary cost estimates and predicts the impacts of design alternatives of steel pedestrian bridges (SPBs). The cost estimation process uses two main parameters, but the main goal is to create a cost estimation model.

This study explores a flexible model design that uses computing capabilities for decision-making. Using cost optimization techniques, the model can select an optimal pedestrian bridge system based on multiple criteria that may change independently. This research focuses on four types of SPB systems prevalent in Egypt and worldwide. The study also suggests developing a computerized cost and weight optimization model that enables decision-makers to select the optimal system for SPBs in keeping up with the criteria established for that system.

In this paper, the authors developed an optimization model for cost estimates of SPBs. The model considers two main parameters: weight and cost. The main contribution of this study based on a parametric study is to propose an approach that enables structural engineers and designers to select the optimum system for SPBs.

The implications of this research from a practical perspective are that the study outlines a feasible approach to develop a computerized model that utilizes the capabilities of computing for quick cost optimization that enables decision-makers to select the optimal system for four common SPBs based on multiple criteria that may change independently and in concert with cost optimization during the preliminary design stage.

The model can choose an optimal system for SPBs based on multiple criteria that may change independently and in concert with cost optimization. The resulting optimization model can forecast the optimum cost of the SPBs for different structural spans and road spans based on local unit costs of materials cost of steel structures, fabrication, erection and painting works.

The authors developed a computerized model that uses spreadsheet software's capabilities for cost optimization, enabling decision-makers to select the optimal system for SPBs meeting the criteria established for such a system. Based on structural characteristics and material unit costs, this study shows that using the optimization model for estimating the total direct cost of SPB systems, the project cost can be accurately predicted based on the conceptual design status, and positive prediction outcomes are achieved.

This paper explores the impact of both government subsidies and decision makers' loss-averse behavior on the determination of transportation build-operate-transfer (BOT) concession periods based on cumulative prospect theory (CPT). The prospect value of a transportation project under traffic risk can be formulated according to the value function for gains and losses and the decision weight for gains and losses. As an extra income for investors, government subsidy is designed for highly risky aspects of BOT transportation projects: uncertain initial traffic volumes and fluctuating growth rates.

A decision-making model determining the concession period of a transportation BOT project is proposed by using the Monte-Carlo simulation method based on CPT, and the effects of risky behaviors of private investors on concession period decision making are analyzed. A subsidy method related to the internal rate-of-return (IRR) corresponding to a specific initial traffic volume and growth rate is proposed. The case of an actual BOT highway project is examined to illustrate how the method proposed can be used to determine the concession period of a transportation BOT project considering decision makers' loss-averse behavior and government subsidy. Contingency analysis is discussed to cope with possible misestimating of key factors such as initial traffic volume and cost coefficients. Sensitivity analysis is employed to investigate the impact of CPT parameters on the concession period decisions. An actual BOT case which failed to attract private capital is introduced to show the practical application. The results are then interpreted to conclude this paper.

Based on comparisons drawn between a concession period decision-making model considering the psychological behaviors of decision makers and a model not considering them, the authors conclude that the concession period based on CPT is distinctly different from that of the loss-neutral model. The concession period based on CPT is longer than the loss-neutral concession period. That is, loss-averse private investors tend to ask for long concession periods to make up for losses they will face in the future. Government subsidies serve as extra income for investors, allowing appointed profits to be secured sooner. For the benefit side of contingency variables, the normal state of initial traffic volume, average annual traffic growth rate and bias degree and the government subsidy need to be paid close attention during the project life span. For the cost side of contingency variables, the annual operating cost variable has a significant impact on the length of predicted concession period, while the large-scale cost variable has minor impact.

With an actual BOT highway project, the determination of transportation BOT concession periods based on the psychological behaviors of decision makers is analyzed in this paper. As the psychological behaviors of decision makers heavily impact the decision-making process, the authors analyze their impacts on concession period decision making. Government subsidy is specifically designed for various states of initial traffic volume and fluctuating growth rates to cope with corresponding high risks and mitigate private investors' loss-averse behaviors. Contingency analysis and sensitivity analysis are discussed as the estimated values of parameters may not be authentic in actual situations.

The purpose of this paper is to introduce an effective methodology of obtaining Perot-optimal solutions when combining system dynamics (SD) and multi-objective optimization (MOO) for supply chain problems.

This paper proposes a new approach that combines SD and MOO within a simulation-based optimization framework for generating the efficient frontier for supporting decision making in supply chain management (SCM). It also addresses the issue of the curse of dimensionality, commonly found in practical optimization problems, through design space reduction.

The integrated MOO and SD approach has been shown to be very useful for revealing how the decision variables in the Beer Game (BG) affect the optimality of the three common SCM objectives, namely, the minimization of inventory, backlog, and the bullwhip effect (BWE). The results from the in-depth BG study clearly show that these three optimization objectives are in conflict with each other, in the sense that a supply chain manager cannot minimize the BWE without increasing the total inventory and total backlog levels.

Having a methodology that enables effective generation of optimal trade-off solutions, in terms of computational cost, time as well as solution diversity and intensification, assist decision makers in not only making decision in time but also present a diverse and intense solution set to choose from.

This paper presents a novel supply chain MOO methodology to assist in finding Pareto-optimal solutions in a more effective manner. In order to do so the methodology tackles the so-called curse of dimensionality by reducing the design space and focussing the search of the optimization to regions of inters. Together with design space reduction, it is believed that the integrated SD and MOO approach can provide an innovative and efficient approach for the design and analysis of manufacturing supply chain systems in general.

The purpose of this paper is to illustrate the value of extended time span coverage of state longitudinal education and workforce data system to inform and improve the effectiveness of future high impact expenditure decisions.

It used an analytical 29-year data file created by the author that links seven already-in-place education and workforce administrative record sources. Relying on the path dependency theory, multi-level mixed-effect logistic and multi-level mixed-effect linear regression models are used to test three hypotheses.

The findings are consistent with the hypotheses: inclusion of the multiple steps along a post-secondary education pathway and prior job histories are both critical to understanding workforce outcomes mechanisms; it takes time for the employment outcome effect to be evident and strong following education attainment.

The study concludes with research limitations and implications for decision makers to call for retaining and investing in administrative records with extended time span coverage, particularly for the already-in-place historical administrative records.

The paper is one of the first to demonstrate the value of extended time span coverage in a longitudinal state integrated data system through econometric modeling, using longitudinally integrated data linking seven administrative records covering continuously for 29 years. No matter for prior education or employment pathway, it is only through extended time span coverage that employment outcomes can be well measured and the rich nuances interpreting the mechanisms of education return on investment can be revealed.

We propose an information-based view of the dynamics of network positions and use it to explain why bridging positions become stronger. We depart from previous network dynamics studies that implicitly assume that firms have homogenous information about the network structure. Using network experiments with both students and managers, we vary a firm's network horizon (i.e., how much information a firm has about the network structure) and the network horizon heterogeneity (i.e., how this information is distributed among the firms within the network). Our results indicate that firms with a higher network horizon occupy a stronger bridging position, especially under conditions of high network horizon heterogeneity. At a more general level, these results provide an indirect validation of what so far has been an untested assumption in interfirm network research, namely that firms are aware of their position in the overall network and consciously attempt to improve their position.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.