Optimal delivery service strategy for Internet shopping with time-dependent consumer demand

https://doi.org/10.1016/j.tre.2005.03.007Get rights and content

Abstract

This study attempts to optimize a delivery service strategy for Internet shopping by considering time-dependent consumer demand, demand–supply interaction and consumer socioeconomic characteristics. A nonlinear mathematical programming model is formulated for solving the optimal number and duration of service cycles for discriminating strategy by maximizing profit subject to demand–supply interaction. An example is employed to demonstrate the application of the model. Results suggest that discriminating service strategy is a better strategy in response to time-dependent consumer demand than uniform strategy. Finally, the proposed model is demonstrated to yield more profit than models that do not consider variations in consumer demand or demand–supply interaction.

Introduction

Electronic data interchange (EDI) and related technologies have made it more efficient to transmit information to suppliers. At the same time, information flow-based Internet shopping has markedly improved consumer service by reducing order processing time and providing delivery information. Since real-time consumer demand is processed via the Internet, operator inventory costs are reduced by ordering goods from wholesalers or manufactures and shipping them directly to consumers. However, high order frequency and small order quantity that characterize consumer Internet shopping behavior make it expensive to deliver goods to individual consumers (Huppertz, 1999). With fixed transportation costs for each shipment, the average logistics cost per item decreases with increasing shipment size. Therefore, a larger quantity of goods will accumulate with longer shipping cycles, which also results in an increased delay in receiving ordered goods, thus reducing consumer intention to shop via the Internet. The above process involves a trade-off between consumer demands and operator logistics costs.

The goal of delivery strategies is to reduce logistics costs and satisfy consumer needs. A crucial factor in optimizing a delivery service strategy is consumer demand. The assumption of constant demand is highly controversial, since in reality demand varies with time, space, and consumer socioeconomic characteristics. For example, peak demand for food products is likely to occur at lunchtime. Serving consumers via uniform shipping cycles without considering variations in cumulative quantities ordered during each shipping cycle may result in high logistics costs under time-dependent consumer demand. Conversely, shipping cycle has a dramatic influence on consumer intention to shop via the Internet because it determines delay in receiving ordered goods. When a consumer orders goods from an Internet store, they typically receive delivery information with respect to each service cycle, which is posted on the Internet. Upon the completion of the service cycle, the goods ordered during that cycle are shipped to consumers. Thus, service cycles coincide with shipping cycles for Internet store operators. In addition to time-dependent consumer demand, consumer demand for Internet shopping is also characterized by socioeconomic characteristics, and temporal and spatial variations. Even when served by the same service cycles, consumers with different characteristics perceive Internet shopping differently, which may further influence consumer demand for Internet store goods and, thus, profit. In summary, how to determine an optimal delivery service strategy for Internet shopping by considering demand–supply interaction, time-dependent consumer demand and consumer characteristics has become important.

Previous empirical studies have investigated the impacts of delivery-related issues on consumer satisfaction with Internet shopping (e.g., Rabinovich, 2004, Esper et al., 2003, Rabinovich and Bailey, 2004). Studies of consumer choices between shopping modes focused primarily on investigating the influences of demand and supply attributes on consumer intention to shop via the Internet (e.g., Sim and Koi, 2002, Bhatnagar and Ghose, 2004). Some studies have quantified consumer demand for Internet store goods and costs under different shipping strategies (Khouja, 2001, Hsu et al., 2003, Chen, 2001). However, few have integrated issues such as consumer socioeconomic characteristics, time-dependent consumer demand, demand–supply interaction and the 24-h nature of Internet shopping into their models.

Discriminating service strategy proposed in this study differs significantly from the traditional and typical uniform service strategy in which all consumers are served according to the same delivery cycle. Periods with considerable consumer demand suggest that frequent and short service cycles are suitable and may stimulate consumer demand for Internet store goods because of reduced delay in receiving ordered goods; this perspective also implies that long service cycles are suitable when demand is very low. Such an approach would reduce logistics costs and boost profit. The Internet store in this study is assumed to operate as a retailer, ordering a batch of goods from wholesalers or manufactures and distributing these goods to consumers. Delay in receiving ordered goods is determined here as the time between consumers ordering and receiving goods, and depends on delivery cycles which include lead time for processing and handling.

This study explores how to optimize a delivery service strategy for Internet shopping in terms of service cycle frequency and duration by considering time-dependent consumer demand and demand–supply interaction. The model applies mathematical programming methods and compares profit between using discriminating and uniform service strategies thereby identifying the optimal strategy for Internet store operators. This study uses R-company selling flowers via the Internet in Taiwan, as an example to demonstrate the application of the model.

The remainder of this paper is organized as follows. Section 2 reviews the literature on Internet shopping and physical distribution problems. Section 3 formulates the consumer choice probability model for Internet shopping and aggregates consumer demand for Internet store goods in each service cycle. Nonlinear programming problems are formulated in Section 4 for determining the optimal number and duration of service cycles for discriminating service strategy and uniform service strategy by maximizing Internet store profit subject to demand–supply equality. In Section 5, a case study and numerical examples are presented to demonstrate the application of the model and the effects of changing in key parameters on the optimal solution. Finally, Section 6 presents a summary of study findings and conclusions.

Section snippets

Literature review

The major issues related to Internet shopping have been extensively examined in numerous studies, including marketing, pricing and payment, etc. (e.g., Pavitt, 1997, Reynolds, 1997, Kiang et al., 2000, Peterson et al., 1997). O’Cass and Fenech (2003) examined Internet user adoption of the Web for retail/purchase behavior. Burke (1997) noted that the home-shopping system eliminated drive time and checkout time and enabled shoppers to access distant stores and showed the retailing technology is

Consumer demand for Internet store goods

Three key groups of factors influence shopping behavior, namely goods characteristics, shopping mode attributes, and consumer characteristics (Salomon and Koppelman, 1988). Generally, goods that require detailed examination before purchase are considered inappropriate for Internet markets (Liang and Huang, 1998). Thus, the goods discussed here are those that are appropriate for Internet markets. This study designs a consumer choice probability model for choosing between Internet and

Mathematical programming models for the optimal service cycles

The discussions completed to date deal with dynamic and time-sensitive consumer demand, and demonstrate how service cycle duration influences consumer demand for Internet store goods. This section further investigates how consumer demand for goods from Internet stores influences logistics costs for Internet store operators. Moreover, this study devises a mathematical programming model for determining the optimal number and duration of service cycles during the entire study period by considering

Numerical example

A case study is presented to demonstrate the application of the proposed model using data available from R-company selling flowers via the Internet in Taiwan. For simplicity, this study merely chose six cities from all of the cities currently served by R-company as study zones, and assumed one operating day, namely 24 h, as the study period, with the unit of time for study being 1 h. Base values for parameters in the utility were calibrated using data collected via street interviews conducted at

Conclusions

Recent studies have investigated Internet shopping carriers and provider issues and their effects on consumer services and operating strategies. Most of these empirical studies dealt these issues by collecting empirical data and testing hypotheses. This study further develops a mathematical programming model that can determine the optimal number and duration of service cycles for Internet shopping by exploring demand–supply interaction and time-dependent consumer demand. This study shows how

Acknowledgement

The authors would like to thank the National Science Council of the Republic of China for financially supporting this research under Contract No. NSC 93-2416-H-009-005.

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