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 indicators, but with increased age, employment/shopping responsibilities, the preponderance of switchers diminishes and more deep green consumers appear. Deep green consumers tend to be both more information and variety seeking than the price conscious ones. Originality/value – By identifying demographic and other characteristics that are likely to qualify consumers as belonging to a specific segment, marketers of local and ecologically produced foods can better target and influence appropriate consumers.

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.

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