Identifying market segments in beef: Breed, slaughter weight and ageing time implications

In this paper we propose a method to learn the reasons why groups of consumers prefer some beef products to others. We emphasise the role of groups since, from a practical point of view, they may represent market segments that demand different products. Our method starts representing people’s preferences in a metric space; there we are able to define a kernel based similarity function that allows a clustering algorithm to identify significant groups of consumers with homogeneous likes. Finally, in each cluster, we developed, with a support vector machine (SVM), a function that explains the preferences of those consumers grouped in the cluster. The method was applied to a real case of consumers of beef that tasted beef from seven Spanish breeds, slaughtered at two different weights and aged for three different ageing periods. Two different clusters of consumers were identified for acceptability and tenderness, but not for flavour. Those clusters ranked two very different breeds (Asturiana and Retinta) in opposite order. In acceptability, ageing period was appreciated in a different way. However, in tenderness most consumers preferred long ageing periods and heavier to lighter animal

ESSAYS ON NUDGING CUSTOMERS’ BEHAVIORS: EVIDENCE FROM ONLINE GROCERY SHOPPING AND CROWDFUNDING

The dissertation consists of three essays that employ predictive analytics, structural modeling techniques and field experiments to understand and nudge customers’ behaviors in two types of online engagement platforms. The first one is customers’ purchase behaviors in an online grocery store and the other is customer’ contribution behaviors in a reward-based crowdfunding platform. In both contexts, we study how to actively nudge their behaviors. In Chapter 2, we investigates how, when dealing with products that are available in limited quantities, customers may be nudged to purchase them. Specifically, our main problem is to identify targeted customers to receive the limited number of coupons. We develop a Support Vector Machines (SVM) based approach to rank order customers. We conduct a field experiment in an online grocery store to evaluate how well the identified customers are nudged through information and/or couponing. We find that, in terms of the successful nudges, our SVM-based approach performed better than other approaches

A framework for knowledge discovery within business intelligence for decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Business Intelligence (BI) techniques provide the potential to not only efficiently manage but further analyse and apply the collected information in an effective manner. Benefiting from research both within industry and academia, BI provides functionality for accessing, cleansing, transforming, analysing and reporting organisational datasets. This provides further opportunities for the data to be explored and assist organisations in the discovery of correlations, trends and patterns that exist hidden within the data. This hidden information can be employed to provide an insight into opportunities to make an organisation more competitive by allowing manager to make more informed decisions and as a result, corporate resources optimally utilised. This potential insight provides organisations with an unrivalled opportunity to remain abreast of market trends. Consequently, BI techniques provide significant opportunity for integration with Decision Support Systems (DSS). The gap which was identified within the current body of knowledge and motivated this research, revealed that currently no suitable framework for BI, which can be applied at a meta-level and is therefore tool, technology and domain independent, currently exists. To address the identified gap this study proposes a meta-level framework: - ‘KDDS-BI’, which can be applied at an abstract level and therefore structure a BI investigation, irrespective of the end user. KDDS-BI not only facilitates the selection of suitable techniques for BI investigations, reducing the reliance upon ad-hoc investigative approaches which rely upon ‘trial and error’, yet further integrates Knowledge Management (KM) principles to ensure the retention and transfer of knowledge due to a structured approach to provide DSS that are based upon the principles of BI. In order to evaluate and validate the framework, KDDS-BI has been investigated through three distinct case studies. First KDDS-BI facilitates the integration of BI within ‘Direct Marketing’ to provide innovative solutions for analysis based upon the most suitable BI technique. Secondly, KDDS-BI is investigated within sales promotion, to facilitate the selection of tools and techniques for more focused in store marketing campaigns and increase revenue through the discovery of hidden data, and finally, operations management is analysed within a highly dynamic and unstructured environment of the London Underground Ltd. network through unique a BI solution to organise and manage resources, thereby increasing the efficiency of business processes. The three case studies provide insight into not only how KDDS-BI provides structure to the integration of BI within business process, but additionally the opportunity to analyse the performance of KDDS-BI within three independent environments for distinct purposes provided structure through KDDS-BI thereby validating and corroborating the proposed framework and adding value to business processes

Food Innovation as a Means of Developing Healthier and More Sustainable Foods

The current demand for healthy and sustainable foods has encouraged the development of new alternatives, even in traditional products. Improved foods may be produced by reducing the amount of some ingredients, adding new ones, or replacing traditionally used ingredients for others. By reformulating their products, manufacturers can offer healthier choices for an ever-growing number of consumers interested in maintaining a balanced diet. In addition, market demand for more sustainable foods contributes to a lower environmental impact in their production. In this regard, current areas of interest include the production of foods using a lower amount of inputs, as well as the utilization of food by-products to improve the amount and quality of available foods. Another aspect to be considered is that not all consumers are willing to eat foods produced with new ingredients or novel technologies. Hence, the development of innovations in food products should take into account the influence of the so-called consumer food neophobia. For this reason, papers dealing with the consumer acceptance of these food innovations are also welcome. Thus, the aim of this Special Issue of Foods is to provide documents focused on the production of healthier and more sustainable foods by using novel ingredients, food by-products, or new production processes

Optimal Contracting and Vertical Coordination in the Beef Industry: An Assessment of Value-Based Pricing

This dissertation explores the nature and scope of vertical coordination in the U.S. beef industry. From the perspective of the incomplete contract theory of the industrial organization literature, this dissertation first provides a theoretical economic explanation for the traditional and emerging governance structure of the U.S. beef industry, and then explains why a complete vertical integration has not yet occurred in the beef sector. Analyzing the organizational details of this industry, the author argues that the degree of idiosyncrasy of transaction-specific investments by each of the vertically-related beef sectors is not high enough that transaction costs could be further reduced by vertical integration. The dissertation further examines optimal behavior of commercial cattle feeders under alternative cattle feeding contract provisions, and the implications for contract choice by cattle owners and feeders under traditional and value-based pricing methods for fed cattle. The author analyzes optimal incentive structures for cattle feeding contracts under alternative fed cattle pricing methods and risk preferences of cattle owners and feeders using a multitask principal-agent model. In order to evaluate the predictions of the model, a dynamic biophysical growth model for beef cattle from the animal science literature is employed to simulate feedlot and carcass performance outcomes of a large sample of feeder steers for various feeding strategies typically used by cattle feeders. The main results of this research are as follows. First, carcass yield- and quality-improving inputs are substitutes in the production technology of feedlots. Second, overall beef quality improves under grid pricing with optimal owner and feeder behavior. Third, the power of the optimal incentive scheme for cattle feeding is lower under value-based grid pricing than under traditional live- and dressed-weight pricing methods. Fourth, the power of the incentive scheme increases with the degree of cattle owners' risk aversion. Fifth, compared to traditional pricing methods, value-based grid pricing better aligns the incentives of cattle owners and feeders under feeding contract structures in current use (yardage-fee-plus-feed-cost contracts or cost-of-gain contracts). Sixth, asymmetry in the premium-discount structure in current grids and the additional risk associated with carcass yield and quality under grid pricing are the main reasons for continued use of live-weight pricing and apparent slowness to adopt grid pricing. Seventh, more balanced premiums and discounts in grid pricing may be required to achieve further expansion of grid pricing and overall improvement of beef quality and consistency. Eighth, if cattle feeders can limit the contract parameter space to traditional forms of contracts and owners choose the contract parameters, then typical forms of cattle feeding contracts can be rationalized by optimal behavior under plausible levels of risk aversion. Finally, the introduction of grid pricing decreases (increases) the tendency toward cost-of-gain (yardage-fee-plus-feed-cost) contracts in commercial cattle feeding

Research: South Dakota State University, Fall 2016

CONTENTS: Cattle primary host for new influenza virus [page] 1Statisticians evaluate probability models for crime scene evidence [page] 2Beef reproduction research to increase sperm, embryo survival [page] 4Chemicals in ice core reveal climate-changing events [page] 6New pediatric drug delivery method uses corn, milk proteins [page] 8Strategic application key to biochar application [page] 8Outstanding Scholars:Collaborative projects brings pioneer women to life [page] 9Nurses to learn substance abuse intervention technique [page] 9Dietitian targets weight management, goal-setting to improve health [page] 10Photovoltaic group helps Pakistani scientists harness sun\u27s energy [page] 10New capabilities will advance soybean nodule research [page] 11Understanding L1 elements in mouse can impact human health [page] 11https://openprairie.sdstate.edu/research_mag/1009/thumbnail.jp