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Consumers display complex shopping behaviors in the multichannel environment, which includes traditional retail stores and the internet. The purpose of this paper is to examine the effects of the customer-sales associate relationship, customers’ receptiveness to online store shopping, and their interaction effects on the customer’s attitude toward multichannel shopping behavior when the firm decides to establish an online store as the online channel. The authors also examine how customers’ multichannel shopping behavior affects their future spending intentions.

Survey data were collected by soliciting 231 customers who purchased cosmetics in department stores within the past three months. Subjects were asked to give their overall evaluation of their offline and online shopping experiences in the last three months.

Results show that the customer-sales associate relationship significantly reduces customers’ attitude toward searching offline but purchasing online. Receptiveness to online store shopping has significant effects on customers’ attitude toward multichannel shopping behaviors regardless of whether they search or purchase via the online channel. The customer-sales associate relationship also moderates the relationship between customers’ receptiveness to online store shopping and multichannel shopping behaviors. Finally, unlike other types of online and offline multichannel shoppers who display higher future spending intentions when the physical store decides to open an online store, those who prefer physical stores for both information searching and product purchasing display lower spending intentions.

To the best of the authors’ knowledge, this paper is the first to use customer-sales associate relationships to investigate consumers’ attitude toward multichannel shopping behavior. The findings provide meaningful implications for service providers that use sales associates to increase consumers’ value via face-to-face service, but find it challenging to go online.

As existing studies show the accuracy of sampling methods depends heavily on the evaluation metric in web accessibility evaluation, the purpose of this paper is to propose a sampling method OPS-WAQM optimized for Web Accessibility Quantitative Metric (WAQM). Furthermore, to support quick accessibility evaluation or real-time website accessibility monitoring, the authors also provide online extension for the sampling method.

In the OPS-WAQM method, the authors propose a minimal sampling error model for WAQM and use a greedy algorithm to approximately solve the optimization problem to determine the sample numbers in different layers. To make OPS-WAQM online, the authors apply the sampling in crawling strategy.

The sampling method OPS-WAQM and its online extension can both achieve good sampling quality by choosing the optimal sample numbers in different layers. Moreover, the online extension can also support quick accessibility evaluation by sampling and evaluating the pages in crawling.

To the best of the authors’ knowledge, the sampling method OPS-WAQM in this paper is the first attempt to optimize for a specific evaluation metric. Meanwhile, the online extension not only greatly reduces the serious I/O issues in existing web accessibility evaluation, but also supports quick web accessibility evaluation by sampling in crawling.