Learning,signaling, and convincing: The role of experimentation in the business modeling process

This study examines experimentation in the business modeling process, unpacking three different roles of experimentation: learning, signaling, and convincing. Learning is an inherent role of experimentation, as managers typically experiment to engage with the environment and to obtain knowledge. This study uncovers another set of roles, which have a symbolic nature. These roles show that experimentation is not just a learning process, but also a strategic legitimation process, aimed at enacting the environment. Experimentation serves the purpose of signaling to potential customers and other stakeholders, and of convincing them to embrace the business model. Furthermore, this study shows that experimentation takes two forms—purposeful interactions and experimental projects—and that these forms can support the different roles of experimentation.     

Max‐infinitely divisible models and inference for spatial extremes

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max‐stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max‐infinitely divisible processes, which extend max‐stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max‐infinitely divisible models, which relax the max‐stability property but remain close to some popular max‐stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max‐stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student‐t copula process and its max‐stable limit, even for large block sizes.     

论适应性表征及其方法论意义

适应性是主体适应其环境的特性,是物理演化系统和生物演化系统的本质属性,反映在认知上就是适应性表征。适应性表征也因此成为知识显现的方式和创造的核心,具有协调性、匹配性、互补性、模拟性和类比性,其表现方式有直接具象表征、间接具象表征、直接抽象表征和间接抽象表征,分别对应于经验主义、建构经验主义、理性主义和科学实在论。适应性表征的实现是通过科学理论核心概念的变化、定律的凝练、理论的更替、模型推理和世界观的改变展开的,具有经验上的适当性。这种经验适当性不仅是感知层次的体验,更是一种认知模式。在认知意义上,经验也是基于心理模型的,心理建模的路径有思想语言、心理表象、心理命题、思想实验和心理模拟推理。这种基于心理建模的适应性表征为科学认知和科学发现提供了有益的方法论。     

Modeling Finite‐Time Failure Probabilities in Risk Analysis Applications

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time‐dependent critical risk level within a finite‐time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.     

Evaluation of Proactive and Reactive Strategies for Polio Eradication Activities in Pakistan and Afghanistan

Only Pakistan and Afghanistan reported any polio cases caused by serotype 1 wild polioviruses (WPV1s) in 2017. With the dwindling cases in both countries and pressure to finish eradication with the least possible resources, a danger exists of inappropriate prioritization of efforts between the two countries and insufficient investment in the two countries to finish the job. We used an existing differential‐equation‐based poliovirus transmission and oral poliovirus (OPV) evolution model to simulate a proactive strategy to stop transmission, and different hypothetical reactive strategies that adapt the quality of supplemental immunization activities (SIAs) in response to observed polio cases in Pakistan and Afghanistan. To account for the delay in perception and adaptation, we related the coverage of the SIAs in high‐risk, undervaccinated subpopulations to the perceived (i.e., smoothed) polio incidence. Continuation of the current frequency and quality of SIAs remains insufficient to eradicate WPV1 in Pakistan and Afghanistan. Proactive strategies that significantly improve and sustain SIA quality lead to WPV1 eradication and the prevention of circulating vaccine‐derived poliovirus (cVDPV) outbreaks. Reactive vaccination efforts that adapt moderately quickly and independently to changes in polio incidence in each country may succeed in WPV1 interruption after several cycles of outbreaks, or may interrupt WPV1 transmission in one country but subsequently import WPV1 from the other country or enable the emergence of cVDPV outbreaks. Reactive vaccination efforts that adapt independently and either more rapidly or more slowly to changes in polio incidence in each country may similarly fail to interrupt WPV1 transmission and result in oscillations of the incidence. Reactive strategies that divert resources to the country of highest priority may lead to alternating large outbreaks. Achieving WPV1 eradication and subsequent successful OPV cessation in Pakistan and Afghanistan requires proactive and sustained efforts to improve vaccination intensity in under‐vaccinated subpopulations while maintaining high population immunity elsewhere.     

Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights

Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments.     

Human Agency in Disaster Planning: A Systems Approach

Current approaches to risk management place insufficient emphasis on the system knowledge available to the assessor, particularly in respect of the dynamic behavior of the system under threat, the role of human agents (HAs), and the knowledge available to those agents. In this article, we address the second of these issues. We are concerned with a class of systems containing HAs playing a variety of roles as significant system elements—as decisionmakers, cognitive agents, or implementers—that is, human activity systems. Within this family of HAS, we focus on safety and mission‐critical systems, referring to this subclass as critical human activity systems (CHASs). Identification of the role and contribution of these human elements to a system is a nontrivial problem whether in an engineering context, or, as is the case here, in a wider social and public context. Frequently, they are treated as standing apart from the system in design or policy terms. Regardless of the process of policy definition followed, analysis of the risk and threats to such a CHAS requires a holistic approach, since the effect of undesirable, uninformed, or erroneous actions on the part of the human elements is both potentially significant to the system output and inextricably bound together with the nonhuman elements of the system. We present a procedure for identifying the potential threats and risks emerging from the roles and activity of those HAs, using the 2014 flooding in southwestern England and the Thames Valley as a contemporary example.     

口感预测型食品物性仿生检测系统

针对目前在使用质构仪进行食品物性检测时，存在的检测数据准确性较差，操作系统功能单一，测试结果与口感 评价间无关联性分析等缺点，提出了基于六自由度并联机器人的口感预测型仿生检测系统。设计了仿生咀嚼检测平台； 利用数理统计原理和最小二乘法建立了物性检测数据与口感评价之间的数学模型，实现了仿生检测系统的口感预测功 能。实验结果表明，利用数学模型获得的口感预测值与人口感评价结果之间的误差小于9%，满足实际应用的需要，验 证了口感预测数学模型构建的正确性及口感预测功能的可行性。     

A Study of Interval Censoring in Parametric Regression Models

Parametric models for interval censored data can now easily be fitted with minimal programming in certain standard statistical software packages. Regression equations can be introduced, both for the location and for the dispersion parameters. Finite mixture models can also be fitted, with a point mass on right (or left) censored observations, to allow for individuals who cannot have the event (or already have it). This mixing probability can also be allowed to follow a regression equation.Here, models based on nine different distributions are compared for three examples of heavily censored data as well as a set of simulated data. We find that, for parametric models, interval censoring can often be ignored and that the density, at centres of intervals, can be used instead in the likelihood function, although the approximation is not always reliable. In the context of heavily interval censored data, the conclusions from parametric models are remarkably robust with changing distributional assumptions and generally more informative than the corresponding non-parametric models.     

Risk of Legionellosis in residential areas around farms irrigating with municipal wastewater

The conservation of freshwater is of both global and national importance, and in the United States, agriculture is one of the largest consumers of this resource. Reduction of the strain farming puts on local surface or groundwater is vital for ensuring resilience in the face of climate change, and one possible option is to irrigate with a combination of freshwater and reclaimed water from municipal wastewater treatment facilities. However, this wastewater can contain pathogens that are harmful to human health, such as Legionella pneumophila, which is a bacterium that can survive aerosolization and airborne transportation and cause severe pneumonia when inhaled. To assess an individual adult's risk of infection with L. pneumophila from a single exposure to agricultural spray irrigation, a quantitative microbial risk assessment was conducted for a scenario of spray irrigation in central Illinois, for the growing seasons in 2017, 2018, and 2019. The assessment found that the mean risk of infection for a single exposure exceeded the safety threshold of 10^–6 infections/exposure up to 1 km from a low-pressure irrigator and up to 2 km from a high-pressure irrigator, although no median risk exceeded the threshold for any distance or irrigator pressure. These findings suggest that spray irrigation with treated municipal wastewater could be a viable option for reducing freshwater consumption in Midwest farming, as long as irrigation on windy days is avoided and close proximity to the active irrigator is limited.