Applied Stochastic Models in Business and Industry最新文献

Industrial statistics grew up in an era when manufacturing was the primary engine of commerce. Today, the driver is information technology. This paper discusses how statisticians need to adapt to contribute to this new business model, with particular emphasis upon computational advertising, autonomous vehicles, operations management, and large language models. Remarkably, many of our old tools are still relevant, even as the new problem space poses fresh research challenges for our employment and educational systems.

The incidence of allergic rhinoconjunctivitis due to pollinosis is increasing in Western countries. The first-line therapy (No-AIT) typically involves the administration of antihistamines and corticosteroid sprays to manage symptoms. Immunotherapy represents an alternative treatment option, as it promotes desensitization to allergens. However, it is associated with significant costs. Currently, two types of allergen immunotherapy (AIT) are prescribed: subcutaneous immunotherapy and sublingual immunotherapy. This article compares these two therapeutic options with No-AIT. The comparison is conducted through a cost-effectiveness analysis (CEA), which evaluates health-related outcomes by estimating the incremental cost per unit of change in a composite outcome that combines morbidity and quality-of-life metrics. To perform the analysis, we developed a realistic multistate model describing the progression of a cohort of patients undergoing the three therapeutic approaches. The model was designed to be sufficiently flexible to account for treatment-related challenges commonly observed in real-world settings, which are often inadequately represented in randomized controlled trials. By employing a novel two-dimensional framework, we tracked the proportion of the cohort transitioning between health states during each cycle while simultaneously capturing the origin and destination of each transition. This approach enabled the integration of structural features that are typically overlooked, such as early treatment discontinuation, transition rewards, nonstationarities associated with the usual termination of immunotherapy after three years, and differential protection against severe complications (e.g., asthma) depending on whether immunotherapy was completed or not. Deterministic simulations were conducted using standard input parameters, supplemented by probabilistic simulations to generate CEACs for each of the three strategies. The results from our model indicate that AIT is not cost-effective unless the payer exhibits a moderately high willingness-to-pay. These findings have important implications for the pharmaceutical industry involved in the production of AIT drugs.

As industries increasingly outsource their Maintenance, Repair, and Overhaul (MRO) programs to third-party service providers, Original Equipment Manufacturers (OEMs) seek to expand their market share by providing comprehensive MRO packages along with the original products at a bundled price. This study introduces a bargaining model that jointly optimizes pricing, maintenance policies, and OEM's market coverage, considering participants' gain/loss behaviors within the Full-Service Product System (FSPS) contracts framework. We first provide closed-form analysis for various scenarios in a one-on-one bargaining negotiation, resulting in significant computational efficiency and insightful managerial implications. It also enables us to expand the problem to multiple contracts and develop an algorithm that simultaneously optimizes client density, profitability, pricing and MRO policies. The findings indicate that when players' profits fall short of their reference point, a more loss-averse approach results in increased personal profit and less favorable outcomes for the opponent. We further enrich our findings by conducting a sensitivity analysis of the parameters affecting the pricing, MRO policies, and market coverage.

In this paper, we study the optimal design problem for constant-stress accelerated degradation tests using a new class of Wiener processes that effectively capture the positive relation between the drift rate and the volatility. Under the $��D�$-, $��A�$-, and $��c�$-optimality criteria, both the test stress levels and the allocation of test units at each stress level are explicitly determined. We provide a numerical example using carbon-film resistor data to validate our theoretical findings and perform a simulation study to highlight the advantages of our proposed designs. The numerical results suggest that the proposed designs outperform existing designs in terms of estimation accuracy.

We investigate two asymmetric loss functions, namely linear exponential (LINEX) loss and power divergence loss for optimal spatial prediction with area-level data. With our motivation arising from the real estate industry, namely in real estate valuation, we use the Zillow Home Value Index (ZHVI) for county-level values to show the change in prediction when the loss is different (asymmetric) from a traditional squared error loss (symmetric) function. Additionally, we discuss the importance of choosing the asymmetry parameter and propose a solution to this choice for a general asymmetric loss function. Since the focus is on area-level data predictions, we propose the methodology in the context of conditionally autoregressive (CAR) models. We conclude that the choice of the loss functions for spatial area-level predictions can play a crucial role and is heavily driven by the choice of parameters in the respective loss.

This study delves into the comparison of two parallel systems, each composed of multiple component types following the scale models with a shared baseline distribution. Under some assumptions imposed on the baseline distribution, it is shown that a restricted version of the $��p�$-larger order between the scale parameter vectors implies the hazard rate order between the system lifetimes, provided that the allocation vectors of the two systems are the same. Additionally, we explore scenarios where one system embodies heterogeneous scale parameters, whereas the other adopts homogeneous ones, examining the hazard rate order between their lifetimes. For the case when the scale vectors of the two systems are the same, it is shown under some assumptions on the baseline distribution that the weak supermajorization order between the allocation vectors results in the reversed hazard rate order between the system lifetimes. Under more restrictions on the allocation vectors, an extension of this result to the likelihood ratio order is also established. Our discussion also highlights the fulfillment of these assumptions by well-known lifetime distributions such as Feller-Pareto, generalized gamma, power-generalized Weibull, exponentiated Weibull, and half-normal distributions. The findings of this work contribute to addressing gaps in the understanding of stochastic orderings between parallel systems and further refine prior research in this domain. Furthermore, the results provide a foundation for practical applications, such as optimizing resource allocation and reliability assessment in engineering and operational contexts.