The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

A likelihood ratio test for bimodality in two-component mixtures with application to regional income distribution in the EU

We propose a parametric test for bimodality based on the likelihood principle by using two-component mixtures. The test uses explicit characterizations of the modal structure of such mixtures in terms of their parameters. Examples include the univariate and multivariate normal distributions and the von Mises distribution. We present the asymptotic distribution of the proposed test and analyze its finite sample performance in a simulation study. To illustrate our method, we use mixtures to investigate the modal structure of the cross-sectional distribution of per capita log GDP across EU regions from 1977 to 1993. Although these mixtures clearly have two components over the whole time period, the resulting distributions evolve from bimodality toward unimodality at the end of the 1970s.     

TAX POLICY AND INCOME INEQUALITY IN THE UNITED STATES, 1979–2007

This paper assesses the effects of U.S. tax policy reforms on inequality over around three decades, from 1979 to 2007. It applies a new method for decomposing changes in government redistribution into (1) a direct policy effect resulting from policy changes and (2) the effects of changing market incomes. Over the period as a whole, the tax policy changes increased income inequality by pushing up the income share of high‐income earners (the top 20%). (JEL H23, H31, H53, P16)     

Ideal Values and Counter‐ideal Values as Two Distinct Forces: Exploring a Gap in Organizational Value Research

Motives and values at work have long been key topics of business and management studies. In a focused review of the literature on the nature of human values, this paper identifies a disconnect with the literature on human motivation, despite the otherwise inherent relatedness of the two fields. Specifically, extant theory and research have conceptualized values generally in terms of ideals, namely desired end‐states that individuals strive to approach. Although values, by this definition, express motivational concerns, theories of human motivation suggest that there are two forces to consider, i.e. approach and avoidance motivation. By applying this ‘two forces’ perspective to value research, this paper identifies a gap in the literature on values: namely, the idea that individuals are also influenced by counter‐ideal values, i.e. end‐states that they deliberately seek to avoid. The identification of this gap opens up new opportunities for value research in general and organizational value research in particular. To pave the way for future research, this paper critically discusses the few studies that have taken first steps in that direction and outlines research questions that may follow for issues such as employer branding and person–organization fit. This paper closes by providing suggestions on how to tackle the issue in organizational practice.     

The invisible body of queer youth: identity and health in the margins of lesbian and trans communities

How does complexity in gender and sexual identity construction and partnering practices generate unique vulnerabilities for queer-identified youth? We present two case studies from an ongoing ethnographic study of LGBTQ youth development: "Samantha," a queer-identified woman partnered with a transgender man, and "Reid," a queer-identified transgender man who has declined medical gender transitioning and who partners with lesbians and gay men. We consider the implications of these youths' locations on the margins of both lesbian and transgender communities and the challenges in providing health care and support services for queer-identified youth.     

Supply Chain Conflict Due to Store Brands: The Value of Wholesale Price Commitment in a Retail Supply Chain*

Store brands are of increasing importance in retail supply chains, often causing channel conflict, as the retailer's product directly competes with the manufacturer's national brand. Extant research on the resulting channel interactions either assumes the national brand manufacturer can credibly commit to maintaining a wholesale price or that he lacks such ability. However, these two scenarios imply very different supply chain interactions, as only a national brand manufacturer with commitment ability can strategically adjust a national brand wholesale price to prevent a store brand introduction by the retailer. We specifically analyze the impact of this assumption on the manufacturer, the retailer, and the customers. We determine when long‐term contracts that provide the manufacturer with such commitment ability can improve supply chain profitability.     

Time series models associated with Mittag-Leffler type distributions and its properties

ABSTRACT

We have provided a fractional generalization of the Poisson renewal processes by replacing the first time derivative in the relaxation equation of the survival probability by a fractional derivative of order α(0 < α ? 1). A generalized Laplacian model associated with the Mittag-Leffler distribution is examined. We also discuss some properties of this new model and its relevance to time series. Distribution of gliding sums, regression behaviors, and sample path properties are studied. Finally we introduce the q-Mittag-Leffler process associated with the q-Mittag-Leffler distribution.     

Segmentation,alignment and statistical analysis of biosignals with application to disease classification

We present a novel methodology for a comprehensive statistical analysis of approximately periodic biosignal data. There are two main challenges in such analysis: (1) the automatic extraction (segmentation) of cycles from long, cyclostationary biosignals and (2) the subsequent statistical analysis, which in many cases involves the separation of temporal and amplitude variabilities. The proposed framework provides a principled approach for statistical analysis of such signals, which in turn allows for an efficient cycle segmentation algorithm. This is achieved using a convenient representation of functions called the square-root velocity function (SRVF). The segmented cycles, represented by SRVFs, are temporally aligned using the notion of the Karcher mean, which in turn allows for more efficient statistical summaries of signals. We show the strengths of this method through various disease classification experiments. In the case of myocardial infarction detection and localization, we show that our method compares favorably to methods described in the current literature.