In today’s multichannel retail environment, consumers’ experiences in one channel influence their perceptions of another channel. Specifically, consumer evaluations of a firm’s online store have been found to be influenced by consumer interactions with the firm’s in-store personnel. This paper is among the first to address this assumption and test it empirically. Drawing upon the analogical transfer paradigm, we propose hypotheses and accordingly model in-store personnel’s competence and friendliness as determinants of online store usefulness, online store enjoyment, and online store value. Using consumer data collected from two Dutch multichannel retailers, we test this model with partial least squares modeling. The results provide clear support for the model and confirm that consumers may use characteristics of in-store personnel as analogies when evaluating a firm’s online store. Implications for research and retail managers are discussed.
Medical imaging practice changed dramatically with the introduction of digital imaging. Although digital imaging has many advantages, it also has made it easier to delete images that are not of diagnostic quality. Mistakes in imaging—from improper patient positioning, patient movement during the examination, and selecting improper equipment—could go undetected when images are deleted. Such an approach would preclude a reject analysis from which valuable lessons could be learned. In the analog days of radiography, saving the rejected films and then analyzing them was common practice among radiographers. In principle, reject analysis can be carried out easier and with better tools (ie, software) in the digital era, provided that rejected images are stored for analysis. Reject analysis and the subsequent lessons learned could reduce the number of repeat images, thus reducing imaging costs and decreasing patient exposure to radiation. The purpose of this study, which was conducted by order of the Dutch Healthcare Inspectorate, was to investigate whether hospitals in the Netherlands store and analyze failed imaging and, if so, to identify the tools used to analyze those images.
