Electronic Health Record Systems Investment Valuation: A System Dynamics Approach

Implementing Electronic Health Record (EHR) systems is on the agenda for most of the healthcare organizations in the next few years. Decision makers need to do a cost-benefit analysis to value EHR investments. The major question for decision makers is what the benefits of such systems are. We propose the use of System Dynamics (SD) to measure the benefits of EHR systems. A System dynamics approach as a predictive tool maps complex relationships among the healthcare processes into a model by which one can dynamically measure the effect of any changes in the parameters over time. The System dynamics model’s objective is to analyze the impact of EHRs in a healthcare setting during and after its implementation. Simulation of EHR implementations using system dynamics model produces useful data on the benefits of EHRs that are hard to obtain through empirical data collection methods. The results of an SD model then can be transformed into economic values to estimate financial indices

A Decision Support System for Rice Cultivation on Acid Sulfate Soils in Malaysia

Ameliorative steps to put acid sulfate soils into productive use can be organized by a decision support system. The model uses microeconomic analysis to get an optimal rate of lime and fertilizer in maximizing profit. A glasshouse experiment was conducted on an acid sulfate soil in Malaysia to get the potential yield. A field trial was conducted for validation purposes. The recommended rate of fertilizer application of 150-200 kg ha-1 N. 20-30 kg ha-1 P and 150-200 kg ha-1 K were applied during the critical stage of the rice growth. Field Adjusting Factor (FAF) of 0.40 has been found and this was used to analyze the production function. Using TableCurve 3D software. an equation for production function was established. Validation using experimental data showed that the equation has a good capability. shown by the value of p>0.2 (t-test) and MEE of 2%. The model. named as RiCASS (Rice Cultivation on Acid Sulfate Soil) was developed and successfully simulatedthe maximal profit under 4 different scenarios. The recommended rate of lime (GML) was 6.5 t ha-1 for maximal profit and 2.5- 3.0 t ha-1 for the farmers, practice. Keywords: Acid sulfate soil. decision support system. field adjusting factor. lime. ric

Predicting Performance - A Dynamic Capability View

Emerald has removed the embargo period across all journals. The full text of the article may therefore become visible within your IR as soon as the final version has been published in the journal.Production planning and resource allocation are ongoing issues that organisations face on a day-to-day basis. The study addresses these issues by developing a dynamic performance measurement system (DPMS) to effectively re-deploy manufacturing resources, thus enhancing the decision-making process in optimising performance output. The study also explores the development of dynamic capabilities through exploitation of the organisational tacit knowledge. The study was conducted using 6-stage action research for developing DPMS with real-time control of independent variables on the production lines to study the impact. The DPMS was developed using a hybrid approach of discrete event simulation (DES) and system dynamics (SD) by using the historical as well as live data from the action case organisation. Through the development of DPMS and by combining the explicit and tacit knowledge, this study demonstrated an understanding of using cause and effect analysis in manufacturing systems to predict performance. Such a DPMS creates agility in decision making and significantly enhances the decision-making process under uncertainty. The research also explored how the resources can be developed and maintained into dynamic capabilities to sustain competitive advantage. The present study provides a starting-point for further research in other manufacturing organisations to generalise findings. The originality of the DPMS model comes from the approach used to build the cause and effect analysis by exploiting the tacit knowledge and making it dynamic by adding modelling capabilities. Originality also comes from the hybrid approach used in developing the DPMS

Unifying business objects and system dynamics as a paradigm for developing decision support systems

Due to the market-driven nature of modern organisations, it is important that they can easily adapt to changing business needs. In order to be able to do so, organisations need to employ information systems that exhibit the important characteristic of adaptability. Change, however, is risky because it encompasses unpredictable behaviours. Organisations, in order to minimise this risk, employ decision support systems (DSS) techniques that enable predictions to be made. This paper describes a simulation methodology, based on the combination of business objects and system dynamics that assists organisations in predicting future behaviours. The methodology eliminates the need for duplicate models of enterprise operation and simulation, and introduces a framework that enables the unification of the two in a single model

Hybrid Model for It Investment Analysis: Application to Rfid Adoption in the Retail Sector

One of the major obstacles in Information Technology (IT) adoption is its return on investment analysis. IT benefits in organizations are hard to measure and are usually realized over time. System dynamics approach has been used in IT literature to identify the impact of IT on business processes. Given benefits of any IT system in organizations, however, there is a high degree of uncertainty in achieving such benefits. Managerial flexibility in decision making process of implementing a new IT helps managers to overcome this uncertainty over time. Traditional cost benefit analysis such as NPV that is typically used to value any technology is unable to value managerial flexibilities while real options theory offers a model that can value a new investment as uncertainties about the system decreases over time. In this dissertation, we are proposing a new hybrid model for IT return on investment (ROI) that combines system dynamics and real options as two major techniques in economics of IT. This robust hybrid model takes advantages of both techniques while overcoming their weaknesses. We propose a systems dynamic solution to simulate the way an IT influences and improves an organization to be able to estimate the parameters used in the real options model. The hybrid model is used to find the best time for investing in item-level RFID in the retail sector.The results of return on investment analysis on item-level investment show that the variable cost of investment that is the tag prices dominates the return on investment. Other factors such as product unit price and consequently type of retail stores are important as well. The system dynamics simulation provided some major parameters of the real options model such as the expected payoffs and volatility of the expected payoffs that were hard to find in the literature.Business Administration (MBA

Activity-Based Costing in Supply Chain Cost Management Decision Support Systems

Activity-based costing and management (ABC/M) is an accounting and management approach that enhances the level of understanding about business operation costs, especially the overhead costs. ABC/M generates more reliable and precise cost information compared to those of traditional cost accounting (TCA) systems. The integration of ABC/M in supply chain (SC) mathematical decision support models can elucidate the managerial aspects of ABC/M more as an accounting and management tool. Most of the supply chain (SC) order management decision support systems (DSSs) developed so far are based mainly on the material flow and capacity constraints without considering the profitability factor. This thesis first presents a profitable-to-promise (PTP) multi-objective mixed-integer programming (MIP) model which considers profitability in order to effectively manage order acceptance decisions in supply chains, subject to capacity constraints by using ABC/M. The proposed model fulfills a desirable amount of orders completely and accepts a selective number of orders partially having the objective of minimizing the amount of residual capacity and increasing the profitability simultaneously. Because of the common disadvantages that traditional operations research (OR) approaches have such as, complexity in modeling, impossibility of integrating qualitative factors, and inability of on-time model result analysis, the thesis presents a new generic DSS modeling methodology with system dynamics (SD) and based on ABC/M cost structure. The approach presented results a novel real-time cost monitoring and analysis system. SD is a dynamic simulation approach with learning ability to investigate the status changes in the system that correspond to the system variables’ changes as well as their interactions amongst them. Subsequently, the thesis elaborates on both models by integrating them and introducing them as hybrid (MIP-SD) decision support system. In the hybrid system, MIP model generates the order management policy and SD model monitors the cost behavior of each implemented policy during the implementation process. The main purpose is to show how ABC/M acts as a common cost accounting, information, and managerial approach to synchronize the two mentioned models and to introduce the combination as a hybrid DSS system. In general, the approach provides the order fulfillment optimal mix aligned with the implementation strategy considering the factors such as, minimizing the residual capacity, considering the customer satisfaction level, selling price, the cost of resources incurred for each order fulfillment policy, and the share of each product and/or order from manufacturing overhead costs. Such an approach can assists management to analyzing and foreseeing the consequences and outcome of each order fulfillment strategy chosen besides finding the optimal order fulfillment combination