Mathematical modelling of the blood pressure signal

The objective of this work is to develop a model of the continuous arterial pressure signal provided by the arterial catheter, and to validate it against real data. The model involves a number of novel features not encountered in previous models of this form, namely terms to describe the arterial valve closing, the respiratory variations of blood pressure and heart frequency, and the dicrotic notch.. The focus of this project is to develop a simple mathematical model capable of describing the well-known blood pressure signal. The model will be verified by comparison with real data

Can brands claim ignorance? Unauthorized subcontracting in apparel supply chains

Unauthorized subcontracting—when suppliers outsource part of their production to a third party without the retailer’s consent—has been common practice in the apparel industry and is often tied to noncompliant working conditions. Because retailers are unaware of the third party, the production process becomes obscure and cannot be tracked. In this paper, we present an empirical study of the factors that can lead suppliers to engage in unauthorized subcontracting. We use data provided by a global supply chain manager with more than 30,000 orders, of which 36% were subcontracted without authorization. We find that the frequency of unauthorized subcontracting across factories has a pronounced bimodal distribution. Moreover, the degree of unauthorized subcontracting in the past is highly related to the probability of engaging in unauthorized subcontracting in the future, which suggests that factories behave as if they choose a strategic level of unauthorized subcontracting. At the order level, we find that state dependence (i.e., the status of an order carrying over to the next one) and price pressure are the key drivers of unauthorized subcontracting. Buyer reputation and lead time also play a role. Finally, we show that unauthorized subcontracting can be predicted correctly for more than 80% of the orders in out-of-sample tests and for about 70% of suppliers. This indicates that retailers can use business analytics to predict unauthorized subcontracting and help prevent it

Modelling the cardiovascular system for assessing the blood pressure curve

A four compartment model of the cardiovascular system is developed. To allow for easy interpretation and to minimise the number of parameters, an effort was made to keep the model as simple as possible. Using a standard method (Matlab function fminsearch) to calculate the parameter values led to unacceptable run times or non-convergence. Consequently we developed an algorithm which first finds the most important model parameters and uses these as a basis for a four stage process which accurately determines all parameter values. This process is then applied to data from three ICU patients. Good agreement between the model and measured arterial pressure is demonstrated in all cases

Mathematical modelling of the blood pressure signal

The objective of this work is to develop a model of the continuous arterial pressure signal provided by the arterial catheter, and to validate it against real data. The model involves a number of novel features not encountered in previous models of this form, namely terms to describe the arterial valve closing, the respiratory variations of blood pressure and heart frequency, and the dicrotic notch.. The focus of this project is to develop a simple mathematical model capable of describing the well-known blood pressure signal. The model will be verified by comparison with real data

Believing in Analytics: Managers’ Adherence to Price Recommendations from a DSS

Problem definition: We study the adherence to the recommendations of a decision support system (DSS) for clearance markdowns at Zara, the Spanish fast fashion retailer. Our focus is on behavioral drivers of the decision to deviate from the recommendation, and the magnitude of the deviation when it occurs. Academic/practical relevance: A major obstacle in the implementation of prescriptive analytics is users’ lack of trust in the tool, which leads to status quo bias. Understanding the behavioral aspects of managers’ usage of these tools, as well as the specific biases that affect managers in revenue management contexts, is paramount for a successful rollout. Methodology: We use data collected by Zara during seven clearance sales campaigns to analyze the drivers of managers’ adherence to the DSS. Results: Adherence to the DSS’s recommendations was higher, and deviations were smaller, when the products were predicted to run out before the end of the campaign, consistent with the fact that inventory and sales were more salient to managers than revenue. When there was a higher number of prices to set, managers of Zara’s own stores were more likely to deviate from the DSS’s recommendations, whereas franchise managers did the opposite and showed a weak tendency to adhere more often instead. Two interventions aimed at shifting salience from inventory and sales to revenue helped increase adherence and overall revenue. Managerial implications: Our findings provide insights on how to increase voluntary adherence that can be used in any context in which a company wants an analytical tool to be adopted organically by its users. We also shed light on two common biases that can affect managers in a revenue management context, namely salience of inventory and sales, and cognitive workload. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.1166

Modelling the cardiovascular system for assessing the blood pressure curve

A four compartment model of the cardiovascular system is developed. To allow for easy interpretation and to minimise the number of parameters, an effort was made to keep the model as simple as possible. Using a standard method (Matlab function fminsearch) to calculate the parameter values led to unacceptable run times or non-convergence. Consequently we developed an algorithm which first finds the most important model parameters and uses these as a basis for a four stage process which accurately determines all parameter values. This process is then applied to data from three ICU patients. Good agreement between the model and measured arterial pressure is demonstrated in all cases