The objective of this study is to investigate a very common phenomenon in an important emerging country, namely the spike in demand at the end of the sales period, known as the hockey stick phenomenon. The analysis will encompass the causes as well as the impacts of this phenomenon, in a way that allows alternative policies to be proposed that are able to provide a better financial result for the agents involved. Data collected from a Brazilian branch of a large multinational in the non-durable consumer goods industry and in semi-structured interviews conducted face-to-face with executives of 26 clients. After internal and external validation of the model, scenarios were generated to identify causes, impacts and alternative policies. The findings showed that the phenomenon negatively impacted the manufacturers financial performance in the long term and indicated requisite changes able to eliminate it. The study showed that companies should not assume the hockey stick phenomenon to be an exogenous problem; it showed that there are alternative policies; and it provided ideas regarding ways to carry out the change process. This is the first empirical study on the hockey stick phenomenon, a problem that affects diverse companies in emerging countries.
CO2 emission of industrial facilities is a major cause of climate change that affects the ecosystems, human beings and environment. Capture, Transport and Storage of CO2 (CTSC) is a novel technology of mitigating the impacts of climate change. The uncertainties concerning long term reliability of CTSC technology give rise to the significance of risk assessment for CTSC activities.
An enterprise information system, e.g. a system for Enterprise Resource Planning or Customer Relationship Management, is important for any organization to carry out its business activities. Even when the upstream activities of selection or development of such a system, its installation and appropriate user training are carried out effectively, the subsequent use of the system does not always result in meeting the expectations to carry out the work of the enterprise. Published literature is rich in covering the initial acceptance and adoption of such information systems, but is rather sparse in covering the dynamics of post-installation use of the systems. This is particularly so for the critical time period immediately after the system is installed when enterprises have the opportunity to take corrective actions, if needed. Our system dynamics model is an initial attempt to capture the complex dynamic interactions among the characteristics of the organization, business processes, users, the enterprise information system, and interventions by the organization. Our results show that the model can be used to understand the impact of organizational characteristics and interventions on profiles of system use and work done via the system after an enterprise information system is successfully installed.
The obesity trends in the U.S. and many other countries are alarming. Models that can assess the potential impact of alternative interventions are much needed in turning the obesity trend. The purpose of this research is to study the dynamics of obesity in the United States over time to build a generic system dynamics model that can be used for obesity policy analysis at multiple levels. The model is multi-level in the sense that it builds on individual level models for both childhood and adulthood to capture the energy balance and weight change throughout the life of individuals, and aggregates individual level models to population level trends. We discuss the application of simulated method of moments to the calibration of this model. This approach enables community, state, or national policy analysis building on a calibrated model and offers promising methodological advances in model calibration in the field of system dynamics.
This paper builds on a previously proposed approach where fuzzy logic is used to incorporate linguistic variables in system dynamics modeling. The motivation for this approach is to include vague yet dynamic variables that are combined in a meaningful way. The essence of our approach requires the definition of membership functions as representations of the degree to which specific variable attributes hold, the application of a max-min direct inference approach as a way to combine two or more fuzzy variables, and the use of a defuzzification method that captures (summarizes) the joint effect of the linguistic variables. The objective of this paper is to study the implications of using two alternative defuzzification methods (largest of maximum and center of area) and to highlight various interpretation and modeling challenges associated with each defuzzification method. For illustrative purposes we use a variant of a sales and service model that is based on the concepts of product diffusion, backlog accumulation and personnel adjustments and their respective existing modeling representations in the literature. In summary, based on our findings, by substituting the Max-Min operator and eliminating inconsistencies among the fuzzy rules, the defuzzified values behave reasonably for both defuzzfication methods.
Dissemination of system dynamics to project management practitioners is not as widespread as its use for project management theory building within the system dynamics community. This article presents a decision support and training project model built for a global consulting and engineering company. The simulation model comprises the most important work phases within the detail engineering phase of a large investment project in three offices. The model was validated using data from several past projects and in workshops with the company. A user interface was built to aid dissemination and use of the model. The purpose of the model is the bottleneck analysis and simulation of an ongoing engineering project, as well as the simulation of quality, scheduling, and profitability issues when outsourcing parts of the detail plant engineering.
Traditional independent project performance evaluations take time, disrupt business-as-usual, and report one-off performance based on the best data available at the time. The alternative approach for measuring project, programme or enterprise success performance tracking risks moving the focus of work from the technical end goal to the satisfaction of performance measures. In this research, we create and begin testing a method aimed at
Erythropoietic Stimulating Agents (ESAs), have been used in hemodialysis patients since 1988, largely eliminating the need for transfusions to correct the anemia of chronic renal failure. However, current ESA protocols lead to suboptimal anemia control. Questions about the safety of ESAs and clinically desirable hemoglobin levels remain open, despite a series of clinical trials. Moreover, ESAs are expensive: Medicare reimbursements for ESAs in 2008 approached two billion dollars. A process improvement project conducted at Mayo Clinic initiated in 2007 revealed that current ESA protocols lead to (undesirable) oscillations in hemoglobin levels. Recognizing the behavior as a system signature, we developed a bio-pharmacokinetic model of erythropoiesis. Using prior data for a specific patient, the model provides parameters for individualized ESA response profiles. Parameter values are then used to design dosing regimens that achieve the desired results. 650 patients are enrolled in this prototype information system. The percentage of patients who achieved target and stable hemoglobin levels has improved by 40%, ESA costs have been reduced by 35%, and anemia management resource requirements have been reduced by more than 50%. Indications that hospitalizations may have been reduced by 25% are currently under study. Commercial development is underway.