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Exploring purchasing preferences: local and ecologically labelled foods

Purpose – The growing presence of foods that are labelled “locally/ecologically produced” leads to the question of how many consumers consider the impact of their food purchases. Do they value local/ecologically-produced food sufficiently to drive their purchasing behaviour, even if such foods are more costly? Can consumer segments be identified and, if so, what are their characteristics? This paper aims to focus on these questions. Design/methodology/approach – In an exploratory study, the authors surveyed over 400 students from a public university in California asking them to select between apples based on a combination of price, origin and presence/absence of an ecological indicator. The authors collected information on their shopping attitudes, their affinity for international trade and demographic identifiers. Findings – Evidence is found for three consumer segments: the deep green, the price conscious and switchers. The latter are the most prevalent category across demographic and attitudinal indica...

Facets of the p -cycle polytope

Abstract The purpose of this study is to provide a polyhedral analysis of the p -cycle polytope, which is the convex hull of the incidence vectors of all the p -cycles (simple directed cycles consisting of p arcs) of the complete directed graph K n . We first determine the dimension of the p -cycle, polytope, characterize the bases of its equality set, and prove two lifting results. We then describe several classes of valid inequalities for the case 2 p n , together with necessary and sufficient conditions for these inequalities to induce facets of the p -cycle polytope. We also briefly discuss the complexity of the associated separation problems. Finally, we investigate the relationship between the p -cycle polytope and related polytopes, including the p -circuit polytope. Since the undirected versions of symmetric inequalities which induce facets of the p -cycle polytope are facet-inducing for the p -circuit polytope, we obtain new classes of facet-inducing inequalities for the p -circuit polytope.

TestAnt: An ant colony system approach to sequential testing under precedence constraints

We consider the problem of minimum cost sequential testing (diagnosis) of a series (or parallel) system under precedence constraints. We model the problem as a nonlinear integer program. We develop and implement an ant colony algorithm for the problem. We demonstrate the performance of this algorithm for special type of instances for which the optimal solutions can be found in polynomial time. In addition, we compare the performance of the ant colony algorithm with a branch and bound algorithm for randomly generated general instances of the problem. The ant colony algorithm is particularly effective as the problem size gets larger.

Optimal keyword bidding in search-based advertising with target exposure levels

Search-based advertising has become very popular since it provides advertisers the ability to attract potential customers with measurable returns. In this type of advertising, advertisers bid on keywords to have an impact on their ad’s placement, which in turn affects the response from potential customers. An advertiser must choose the right keywords and then bid correctly for each keyword in order to maximize the expected revenue or attain a certain level of exposure while keeping the daily costs in mind. In response to increasing need for analytical models that provide a guidance to advertisers, we construct and examine deterministic optimization models that minimize total expected advertising costs while satisfying a desired level of exposure. We investigate the relationship between our problem and the well-known continuous non-linear knapsack problem, and then solve the problem optimally by utilizing Karush–Kuhn–Tucker conditions. We present practical managerial insights based on the analysis of both a real-life data from a retailer and a hypothetical data.

A Spreadsheet Scenario Analysis Technique That Integrates with Optimization and Simulation

Scenario analysis is a widely used technique, and business students should be proficient in running scenarios through a spreadsheet model. We propose 10 desirable properties for a scenario analysis technique, and show that the Microsoft Excel Scenario Manager tool satisfies only one of them. We provide a tutorial for a better technique that can be programmed into an existing spreadsheet in a matter of minutes. We show how to integrate the technique with the Excel Solver to allow for rapid optimization of multiple scenarios and with the Crystal Ball add-in for Monte Carlo simulation to enable simulation of multiple scenarios. Our undergraduate and MBA students are able to learn the technique with little difficulty.

Optimal Keyword Bids in Search-Based Advertising with Stochastic Advertisement Positions

US expenditures on search-based advertising exceeded

Optimum service capacity and demand management with price incentives

12 billion in 2010. Advertisers bid for keywords, where bid price determines ad placement, affecting click-through and conversion rates. Advertisers must select keywords, allocating each a proportion of their fixed daily budget. In this paper, we construct a stochastic model for the selection and allocation process. We provide analytical results for the single-keyword problem and examine the multiple-keyword problem numerically. We investigate trade-offs between keywords given varying levels of risk and return. We show the implications of enforcing a probabilistic budget constraint. Our paper provides a critical analysis of the advertiser’s problem that may guide future research.

An ant colony algorithm for the sequential testing problem under precedence constraints

Service firms periodically face fluctuating demand levels. They incur high costs to handle peak demand and pay for under-utilized capacity during low demand periods. In this paper, we develop a mixed integer programming (MIP) model based on the real life experience of a Brazilian telecommunications firm. The model determines the optimum staffing requirements with different seniority levels for employees, as well as the distribution and balancing of workload utilizing flexibility of some customers in their service completion day. The proposed MIP uses monetary incentives to smooth the workload by redistributing some of the peak demand, thereby increasing capacity utilization. Due to the intractable nature of optimizing the proposed MIP model, we present a heuristic solution approach. The MIP model is applied to the case of the examined Brazilian Telecommunications firm. The computational work on this base case and its extensions shows that the proposed MIP model is of merit, leading to approximately seventeen percent reduction in the base case operating costs. Extensive computational work demonstrates that our heuristic provides quality solutions in very short computational times. The model can also be used to select new customers based on the workload, the revenue potential of these new customers and their flexibility in accepting alternate service completion dates. The generic structure of the proposed approach allows for its application to a wide variety of service organizations facing similar capacity and demand management challenges. Such wide applicability enhances the value of our work and its expected benefits.

UCSF Increases Consumer Value Through Optimal Vendor-Show Scheduling

We consider the problem of minimum cost sequential testing of a series (parallel) system under precedence constraints that can be modeled as a nonlinear integer program. We develop and implement an ant colony algorithm for the problem. We demonstrate the performance of this algorithm for special type of instances for which the optimal solutions can be found in polynomial time. In addition, we compare the performance of the algorithm with a special branch and bound algorithm for general instances. The ant colony algorithm is shown to be particularly effective for larger instances of the problem.

Solving the Traveling Circus Problem by Branch & Cut

The University of California San Francisco (UCSF) spends approximately