The growing awareness of the wide variation in health care prices, increased availability of price data, and increased patient cost sharing are expected to drive patients to shop for lower-cost medical services. We conducted a nationally representative survey of 2,996 nonelderly US adults who had received medical care in the previous twelve months to assess how frequently patients are price shopping for care and the barriers they face in doing so. Only 13 percent of respondents who had some out-of-pocket spending in their last health care encounter had sought information about their expected spending before receiving care, and just 3 percent had compared costs across providers before receiving care. The low rates of price shopping do not appear to be driven by opposition to the idea: The majority of respondents believed that price shopping for care is important and did not believe that higher-cost providers were of higher quality. Common barriers to shopping included difficulty obtaining price information and a desire not to disrupt existing provider relationships.
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http://dx.doi.org/10.1377/hlthaff.2016.1471 | DOI Listing |
PLoS One
January 2025
Faculty of Operation and Economics of Transport and Communications, Department of Economics, University of Zilina, Zilina, Slovakia.
The online environment has its own specifics, which shape the specific behavior of all market subjects, both customers and companies that trade electronically. The aim of the paper is to create, quantify and verify a conceptual comprehensive model of relationships between determinants that influence consumers when shopping online. The impetus for the conducted research was the discovery of the non-existence of a comprehensive model of online shopping behavior that reflects the specifics of the online environment.
View Article and Find Full Text PDFJ Environ Manage
January 2025
CEDON - Center for Economics and Corporate Sustainability, Faculty of Economics and Business, KU Leuven, Warmoesberg 26, B-1000, Brussel, Belgium.
Through a natural experiment setting in Hong Kong, this study examines the effects of financial incentives and nudges on consumer choices among three types of coffee cups: bring-your-own-cup (BYOC), shop-provided reusable cups, and disposable cups. Our dataset comprises 223 structured observations of coffee shops with 522 data points. The financial incentive-a direct price instrument set as a discount-is offered exclusively to customers who bring their own cups, while shop-provided (reusable) cups are not eligible.
View Article and Find Full Text PDFHeliyon
January 2025
UKM - Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, UKM, Bangi, Selangor Darul Ehsan, Malaysia.
Domestic e-retailers acknowledge logistics service quality (LSQ) as a critical success factor in business excellence. However, exponential growth in cross-border e-commerce (CBEC) requires a re-evaluation of the relationship between LSQ and consumers repurchase intention. By integrating the technology acceptance model, this study investigates the impact of LSQ on repurchase intention based on the LSQ (experience)-satisfaction-repurchase intention consequence chain.
View Article and Find Full Text PDFAppetite
January 2025
Tilburg University, Department of Communication & Cognition, P.O. Box 90153, 5000 LE, Tilburg, the Netherlands. Electronic address:
As food choices are increasingly made in contexts such as online supermarkets, nudging has been extrapolated to the digital sphere. Digitalization poses unique opportunities to enhance the promotion of healthier food choices online: Digital nudges can be delivered "just-in-time" (JIT), in response to the initial selection of an unhealthy product. Furthermore, digital JIT nudges can be personalized to match user characteristics of behavioral relevance, such as one's food and cognitive processing preferences.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Business and Commerce, Kansai University, Osaka, 5648680, Japan.
In field of location prediction, trajectory recognition is one of the most widely research issues. Since trajectory includes various information such as position, time, and speed, many scientific methods are applied to extracting meaningful features, and discovering valuable knowledges. This paper pays more attention on case study of in-store trajectory, and proposes a series of recurrent neural network (RNN) for location prediction based on trajectory.
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