THE GROCERY RETAILING SECTOR IN GERMANY: ECR ACTIVITIES IN COMPARISON TO THE USA

The German food retail sector and food manufacturers are in a state of transition due to a complex mix of technological and market forces. Competition continues to increase due to sluggish demand and increasing consumer mobility. The high degree of domestic and international concentration increases the intensity of competition. The top 20 food retailers obtain far more than two-thirds of total sales. Because of the increased competition among retailers, the number of retail stores will continue to decline. Food manufacturers fear the buying power of retailers in many ways. Distrust and struggle over the terms of trade characterize the relation between retailers and manufacturers. ECR activities in Germany lag behind relative to the US due to various cultural and procedural differences as well as strategic reasons. However, ECR provides a catalog of measures to achieve more efficiency and customer focus.Industrial Organization, Marketing,

DATA MINING: A SEGMENTATION ANALYSIS OF U.S. GROCERY SHOPPERS

Consumers make choices about where to shop based on their preferences for a shopping environment and experience as well as the selection of products at a particular store. This study illustrates how retail firms and marketing analysts can utilize data mining techniques to better understand customer profiles and behavior. Among the key areas where data mining can produce new knowledge is the segmentation of customer data bases according to demographics, buying patterns, geographics, attitudes, and other variables. This paper builds profiles of grocery shoppers based on their preferences for 33 retail grocery store characteristics. The data are from a representative, nationwide sample of 900 supermarket shoppers collected in 1999. Six customer profiles are found to exist, including (1) "Time Pressed Meat Eaters", (2) "Back to Nature Shoppers", (3) "Discriminating Leisure Shoppers", (4) "No Nonsense Shoppers", (5) "The One Stop Socialites", and (6) "Middle of the Road Shoppers". Each of the customer profiles is described with respect to the underlying demographics and income. Consumer shopping segments cut across most demographic groups but are somewhat correlated with income. Hierarchical lists of preferences reveal that low price is not among the top five most important store characteristics. Experience and preferences for internet shopping shows that of the 44% who have access to the internet, only 3% had used it to order food.Consumer/Household Economics, Food Consumption/Nutrition/Food Safety,

Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model

IntroductionPost-acute sequelae of COVID-19 seem to be an emerging global crisis. Machine learning radiographic models have great potential for meticulous evaluation of post-COVID-19 interstitial lung disease (ILD).MethodsIn this multicenter, retrospective study, we included consecutive patients that had been evaluated 3 months following severe acute respiratory syndrome coronavirus 2 infection between 01/02/2021 and 12/5/2022. High-resolution computed tomography was evaluated through Imbio Lung Texture Analysis 2.1.ResultsTwo hundred thirty-two (n = 232) patients were analyzed. FVC% predicted was ≥80, between 60 and 79 and <60 in 74.2% (n = 172), 21.1% (n = 49), and 4.7% (n = 11) of the cohort, respectively. DLCO% predicted was ≥80, between 60 and 79 and <60 in 69.4% (n = 161), 15.5% (n = 36), and 15.1% (n = 35), respectively. Extent of ground glass opacities was ≥30% in 4.3% of patients (n = 10), between 5 and 29% in 48.7% of patients (n = 113) and <5% in 47.0% of patients (n = 109). The extent of reticulation was ≥30%, 5–29% and <5% in 1.3% (n = 3), 24.1% (n = 56), and 74.6% (n = 173) of the cohort, respectively. Patients (n = 13, 5.6%) with fibrotic lung disease and persistent functional impairment at the 6-month follow-up received antifibrotics and presented with an absolute change of +10.3 (p = 0.01) and +14.6 (p = 0.01) in FVC% predicted at 3 and 6 months after the initiation of antifibrotic.ConclusionPost-COVID-19-ILD represents an emerging entity. A substantial minority of patients presents with fibrotic lung disease and might experience benefit from antifibrotic initiation at the time point that fibrotic-like changes are “immature.” Machine learning radiographic models could be of major significance for accurate radiographic evaluation and subsequently for the guidance of therapeutic approaches

THE GROCERY RETAILING SECTOR IN GERMANY: ECR ACTIVITIES IN COMPARISON TO THE USA

The German food retail sector and food manufacturers are in a state of transition due to a complex mix of technological and market forces. Competition continues to increase due to sluggish demand and increasing consumer mobility. The high degree of domestic and international concentration increases the intensity of competition. The top 20 food retailers obtain far more than two-thirds of total sales. Because of the increased competition among retailers, the number of retail stores will continue to decline. Food manufacturers fear the buying power of retailers in many ways. Distrust and struggle over the terms of trade characterize the relation between retailers and manufacturers. ECR activities in Germany lag behind relative to the US due to various cultural and procedural differences as well as strategic reasons. However, ECR provides a catalog of measures to achieve more efficiency and customer focus

DATA MINING: A SEGMENTATION ANALYSIS OF U.S. GROCERY SHOPPERS

Consumers make choices about where to shop based on their preferences for a shopping environment and experience as well as the selection of products at a particular store. This study illustrates how retail firms and marketing analysts can utilize data mining techniques to better understand customer profiles and behavior. Among the key areas where data mining can produce new knowledge is the segmentation of customer data bases according to demographics, buying patterns, geographics, attitudes, and other variables. This paper builds profiles of grocery shoppers based on their preferences for 33 retail grocery store characteristics. The data are from a representative, nationwide sample of 900 supermarket shoppers collected in 1999. Six customer profiles are found to exist, including (1) "Time Pressed Meat Eaters", (2) "Back to Nature Shoppers", (3) "Discriminating Leisure Shoppers", (4) "No Nonsense Shoppers", (5) "The One Stop Socialites", and (6) "Middle of the Road Shoppers". Each of the customer profiles is described with respect to the underlying demographics and income. Consumer shopping segments cut across most demographic groups but are somewhat correlated with income. Hierarchical lists of preferences reveal that low price is not among the top five most important store characteristics. Experience and preferences for internet shopping shows that of the 44% who have access to the internet, only 3% had used it to order food

Safety and Effectiveness of Mycophenolate Mofetil in Interstitial Lung Diseases: Insights from a Machine Learning Radiographic Model

Introduction: Treatment of interstitial lung diseases (ILDs) other than idiopathic pulmonary fibrosis (IPF) often includes systemic corticosteroids. Use of steroid-sparing agents is amenable to avoid potential side effects. Methods: Functional indices and high-resolution computed tomography (HRCT) patterns of patients with non-IPF ILDs receiving mycophenolate mofetil (MMF) with a minimum follow-up of 1 year were analyzed. Two independent radiologists and a machine learning software system (Imbio 1.4.2.) evaluated HRCT patterns. Results: Fifty-five (n = 55) patients were included in the analysis (male: 30 [55%], median age: 65.0 [95% CI: 59.7-70.0], mean forced vital capacity %predicted [FVC %pred.] +/- standard deviation [SD]: 69.4 +/- 18.3, mean diffusing capacity of lung for carbon monoxide %pred. +/- SD: 40.8 +/- 14.3, hypersensitivity pneumonitis: 26, connective tissue disease-ILDs [CTD-ILDs]: 22, other ILDs: 7). There was no significant difference in mean FVC %pred. post-6 months (1.59 +/- 2.04) and 1 year (-0.39 +/- 2.49) of treatment compared to baseline. Radiographic evaluation showed no significant difference between baseline and post-1 year %ground glass opacities (20.0 [95% CI: 14.4-30.0] vs. 20.0 [95% CI: 14.4-25.6]) and %reticulation (5.0 [95% CI: 2.0-15.6] vs. 7.5 [95% CI: 2.0-17.5]). A similar performance between expert radiologists and Imbio software analysis was observed in assessing ground glass opacities (intraclass correlation coefficient [ICC] = 0.73) and reticulation (ICC = 0.88). Fourteen patients (25.5%) reported at least one side effect and 8 patients (14.5%) switched to antifibrotics due to disease progression. Conclusion: Our data suggest that MMF is a safe and effective steroid-sparing agent leading to disease stabilization in a proportion of patients with non-IPF ILDs. Machine learning software systems may exhibit similar performance to specialist radiologists and represent fruitful diagnostic and prognostic tools