The Effect of Inventory on Purchase Incidence: Empirical Analysis of Opposing Forces of Storage and Consumption

Behavioral studies and recent empirical research suggest higher levels of inventory on hand can lead consumers to increase consumption. Inventory on hand is therefore posited to exert two countervailing forces on the probability of purchase incidence. First, higher levels of inventory reduce the likelihood of purchase as the consumer feels less pressure to buy. At the same time however, theory suggests higher levels of inventory may drive up the rate of consumption, thereby increasing the probability of incidence. We develop an empirical model that explicitly captures these two effects. The elasticity of purchase incidence with respect to inventory derived from the model is shown to capture these opposing forces in a simple and intuitive way. The analytical expression allows calculation of a threshold below (above) which the net effect is positive (negative). The model is estimated on ten product categories from the Stanford Market Basket database and is shown to fit better than both the standard nested logit approach and an alternative formulation developed by Ailawadi and Neslin (1998). The threshold values have plausible magnitudes and are intuitive across categories: butter, margarine and crackers have relatively low thresholds implying that inventory build up does not drive consumption; ice cream and soft drinks have relatively large thresholds (below which the inventory pressure to consume more outweighs the effect to delay purchase). Implications for retail management are discussed. --Choice Models,Consumption,Inventory,Purchase Incidence

Abundance and Partitioning of OH in a High-pressure Magmatic System: Megacrysts from the Monastery Kimberlite, South Africa

Concentrations of OH, and major and trace elements were determined in a suite of mantle-derived megacrysts that represent the crystallization products of a kimberlite-like magma at ~5 GPa and ~1400–1100°C. OH concentrations, determined by single-crystal Fourier transform infrared spectroscopy, display the following ranges (ppmw H2O): olivine 54–262, orthopyroxene 215–263, garnet 15–74, clinopyroxene 195–620, and zircon 28–34. High OH concentrations in olivine imply mantle conditions of origin, with limited H loss during ascent. OH is consistently correlated with megacryst composition, exhibiting trends with Mg-number that are similar to those of other minor and trace elements and indicating a record of high-pressure magmatic evolution. H substitution is not coupled to minor elements in olivine, but may be in ortho- and clinopyroxene. The OH–Mg-number trends of garnet and clinopyroxene show inflections related to co-precipitation of ilmenite, suggesting minor element (Ti) influence on OH partitioning. During differentiation, relative OH enrichment in clinopyroxene and olivine is consistent with proportional dependence on water activity, whereas that in garnet suggests a higher power-law dependence and/or influence of temperature. Inter-mineral distribution coefficients for OH between cpx, opx, olivine and zircon are thus constant, whereas partitioning between these minerals and garnet shows a factor 4–10 variation, correlated regularly with composition (and temperature). Calculation of solid–melt partition coefficients for H at 5 GPa over a range of magmatic evolution from 1380 to 1250°C yields: ol 0·0053–0·0046, opx 0·0093–0·0059, cpx 0·016–0·013, gt 0·0014–0·0003, bulk (garnet lherzolite–melt) 0·0063–0·0051. These are consistent with experimental studies and similar to values inferred from mid-ocean ridge basalt geochemistry, confirming the moderate incompatibility of H in mantle melting

The Inter-Store Mobility of Supermarket Shoppers

The allegiance of a particular customer, and the distribution across customers of strength of affiliation to a store are important indicators of store health. It is therefore important to understand the extent and determinants of shopper mobility among competing retailers. While shoppers often patronize many stores, they typically have a primary affiliation to a “main store” that captures the majority of their purchases. We examine, in detail, the tendencies of shoppers to transition away from the current main store and adopt another in its place. That is, rather than study all types of store switching behavior, we focus on the decision to change primary allegiance. The model is established in a discrete time hazard framework and estimated as random-effects probit. Data from 548 households taking 88,945 shopping trips among five stores are used to calibrate the model. We find that state dependence is prevalent with nearly three quarters of the shoppers showing progressive attachment to their current main store. Interestingly, this finding is not simply driven by location (i.e., because shoppers are captive to a single store based on geographical distance). More likely, shoppers are unwilling to give up the benefits of store-specific knowledge of assortment, layout and prices. Second, the decision to transition from a current main store is not influenced by temporary price promotions on a common basket of items: Shoppers will cherry-pick, but this alone does not cause them to change primary allegiance. The majority of transitions occur across competing stores of the same price format, which suggests “format loyalty” is an important aspect of shopper behavior. After controlling for unobserved heterogeneity, we find little relationship between observable demographics and the transition probability. We do, however, find that shoppers who spend more per trip are less likely to change main stores, as are less frequent shoppers. Implications for retail management strategy are discussed

Smart Cities and M³: Rapid Research, Meaningful Metrics and Co-Design

The research described in this paper is undertaken under the banner of the smart city, a concept that captures the way urban spaces are re-made by the incursion of new technology. Much of smart is centred on converting everyday activities into data, and using this data to generate knowledge mediated by technology. Ordinary citizens, those that may have their lives impacted by the technology, usually are not properly involved in the ‘smartification’ process. Their perceptions, concerns and expectations should inform the conception and development of smart technologies at the same extent. How to engage general public with smart cities research is the central challenge for the Making Metrics Meaningful (MMM) project. Applying a rapid participatory method, ‘Imagine’ over a five-month period (March – July) the research sought to gain insights from the general public into novel forms of information system innovation. This brief paper describes the nature of the accelerated research undertaken and explores some of the themes which emerged in the analysis. Generic themes, beyond the remit of an explicit transport focus, are developed and pointers towards further research directions are discussed. Participatory methods, including engaging with self- selected transport users actively through both picture creation and programmatically specific musical ‘signatures’ as well as group discussion, were found to be effective in eliciting users’ own concerns, needs and ideas for novel information systems

The Indo-U.S. Library of Coude Feed Stellar Spectra

We have obtained spectra for 1273 stars using the 0.9m Coud\'e Feed telescope at Kitt Peak National Observatory. This telescope feeds the coud\'e spectrograph of the 2.1m telescope. The spectra have been obtained with the #5 camera of the coud\'e spectrograph and a Loral 3K X 1K CCD. Two gratings have been used to provide spectral coverage from 3460 \AA to 9464 \AA, at a resolution of $\sim$1\AA FWHM and at an original dispersion of 0.44 \AA/pixel. For 885 stars we have complete spectra over the entire 3460 \AA to 9464 \AA wavelength region (neglecting small gaps of $<$ 50 \AA), and partial spectral coverage for the remaining stars. The 1273 stars have been selected to provide broad coverage of the atmospheric parameters T$_{eff}$, log g, and [Fe/H], as well as spectral type. The goal of the project is to provide a comprehensive library of stellar spectra for use in the automated classification of stellar and galaxy spectra and in galaxy population synthesis. In this paper we discuss the characteristics of the spectral library, viz., details of the observations, data reduction procedures, and selection of stars. We also present a few illustrations of the quality and information available in the spectra. The first version of the complete spectral library is now publicly available from the National Optical Astronomy Observatory (NOAO) via FTP and HTTP.Comment: 18 pages, 6 figures, 4 table

Trends and Regional Variation in Hip, Knee and Shoulder Replacement

Analyzes patterns in underuse or overuse of joint replacements among Medicare beneficiaries by geographic regions and race/ethnicity. Explores underlying factors and highlights the need for physician and patient education and shared decision making

Neighborhood Social Capital and Social Learning for Experience Attributes of Products

Social learning can occur when information is transferred from existing customers to potential customers. It is especially important when the information that is conveyed pertains to experience attributes, i.e., attributes of products that cannot be fully verified prior to the first purchase. Experience attributes are prevalent and salient when consumers shop through catalogs, on home shopping networks, and over the Internet. Firms therefore employ creative and sometimes costly methods to help consumers resolve uncertainty; we argue that uncertainty can be partially resolved through social learning processes that occur naturally and emanate from local neighborhood characteristics. Using data from Bonobos, a leading U.S. online fashion retailer, we find not only that local social learning facilitates customer trial but also that the effect is economically important because about half of all trials were partially attributable to it. Merging data from the Social Capital Community Benchmark Survey, we find that neighborhood social capital, i.e., the propensity for neighbors to trust each other and communicate with each other, enhances the social learning process and makes it more efficient. Social capital does not operate on trials directly; rather, it improves the learning process and therefore indirectly drives sales when what is communicated is favorable