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Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

Polymethyl methacrylate (PMMA) is a remarkable biocompatible material for bone cement and regeneration. It is also considered 3D printable but requires in-depth process–structure–properties studies. This study aims to elucidate the mechanistic effects of processing parameters and sterilization on PMMA-based implants.

The approach comprised manufacturing samples with different raster angle orientations to capitalize on the influence of the filament alignment with the loading direction. One sample set was sterilized using an autoclave, while another was kept as a reference. The samples underwent a comprehensive characterization regimen of mechanical tension, compression and flexural testing. Thermal and microscale mechanical properties were also analyzed to explore the extent of the appreciated modifications as a function of processing conditions.

Thermal and microscale mechanical properties remained almost unaltered, whereas the mesoscale mechanical behavior varied from the as-printed to the after-autoclaving specimens. Although the mechanical behavior reported a pronounced dependence on the printing orientation, sterilization had minimal effects on the properties of 3D printed PMMA structures. Nonetheless, notable changes in appearance were attributed, and heat reversed as a response to thermally driven conformational rearrangements of the molecules.

This research further deepens the viability of 3D printed PMMA for biomedical applications, contributing to the overall comprehension of the polymer and the thermal processes associated with its implementation in biomedical applications, including personalized implants.