What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing

Nowadays, online retailers are offering a variety of delivery options consisting of varying combinations of delivery attributes. This study investigates how consumers value these delivery attributes (e.g., delivery speed, time slot, daytime/evening delivery, delivery date, and delivery fee) when selecting a delivery option for their online purchases. Mental accounting theory is used to frame the research and to suggest how mental accounts for money, time, and convenience influence consumer preferences for online delivery options. Specifically, the results of a conjoint analysis show that the most important attribute in shaping consumer preferences is the delivery fee, followed by nonprice delivery attributes. For individual attributes, significant differences are found in consumer preferences between gender and income groups. Cluster analysis reveals three consumer segments that show distinct preference structures: We identify a "price‐oriented," a "time‐ and convenience‐oriented," and a "value‐for‐money‐oriented" consumer segment. This study has practical implications for online retailers when implementing suitable delivery strategies and designing effective delivery options to maximize consumer satisfaction

Farm-specific Adjustment Costs in Dutch Pig Farming

This paper develops a dynamic model of investment under rational expectations, assuming farm-specific production technologies and adjustment cost structures. The model distinguishes regimes of negative, zero and positive investments and maintains that it is optimal for a farmer not to invest for a range of shadow prices, depending on thresholds for positive and negative investments. The model is applied to a rotating sample of Dutch pig farms over the period 1980-1996. Farm-specific parameters of the adjustment cost function and production technology are obtained using Generalised Maximum Entropy estimation. Cluster analysis using the farm-specific adjustment cost parameters indicates that five groups of farms with distinct adjustment cost structures can be identified. A tobit regression analysis is used to explain the impact of different socio-economic factors on the size of the threshold between positive and negative investments