/desautels/channels_item/400 en /desautels/node/1099155 <h4><b>Congratulations to the 不良研究所 Desautels professors who received 2023 SSHRC Insight Grants.</b></h4> <hr /> <p>The Social Sciences and Humanities Research Council of Canada (SSHRC) is the federal research funding agency that promotes and supports research and training in the humanities and social sciences.</p> <p>聽</p> Mon, 08 Apr 2024 15:04:00 +0000 不良研究所 /desautels/node/357117 <h4><b>Congratulations to the 不良研究所 Desautels professors who received 2023 SSHRC Insight Grants.</b></h4> <hr /> <p>The Social Sciences and Humanities Research Council of Canada (SSHRC) is the federal research funding agency that promotes and supports research and training in the humanities and social sciences.</p> Thu, 28 Sep 2023 13:21:50 +0000 不良研究所 /desautels/node/151055 <p><strong>Authors:</strong> <a href="/desautels/warut-khern-am-nuai"><b>Warut Khern-am-nuai</b></a>,<b> <a href="/desautels/hyunji-so">Hyunji So</a></b>,<b> <a href="/desautels/maxime-cohen">Maxime C. Cohen</a></b> and Yossiri Adulyasak</p> <p><strong>Publication:</strong> <i>Manufacturing &amp; Service Operations Management</i>, Forthcoming</p> <p><b>Abstract</b>:</p> <p>Restaurant review platforms, such as Yelp and Tripadvisor, routinely receive large numbers of photos in their review submissions. These photos provide significant value for users who seek to compare restaurants. In this context, the choice of cover images (i.e., representative photos of the restaurants) can greatly influence the level of user engagement on the platform. Unfortunately, selecting these images can be time consuming and often requires human intervention. At the same time, it is challenging to develop a systematic approach to assess the effectiveness of the selected images. In this paper, we collaborate with a large review platform in Asia to investigate this problem. We discuss two image selection approaches, namely crowd-based and AI-based systems. The AI-based system we use learn complex latent image features, which is further enhanced by transfer learning to overcome the scarcity of labeled data. We collaborate with the platform to deploy our AI-based system through a randomized field experiment to carefully compare both systems. We find that the AI-based system outperforms the crowd-based counterpart and boosts user engagement by 12.43%-16.05% on average. We then conduct empirical analyses on observational data to identify the underlying mechanisms that drive the superior performance of the AI-based system. Finally, we infer from our findings that the AI-based system outperforms the crowd-based system for restaurants with a (i) longer tenure on the platform, (ii) limited number of user-generated photos, (iii) lower star rating, and (iv) lower user engagement during the crowd-based system.</p> <div class="bl-tpl"><a class="button--outline" href="https://ttps://dx.doi.org/10.2139/ssrn.3808667" target="_blank">More details</a></div> <p> Wed, 23 Aug 2023 16:05:32 +0000 不良研究所 /desautels/node/79909 <h4>Congratulations to the Desautels professors who received 2020 SSHRC Insight Grants and Insight Development Grants.</h4> <hr /> <h5>SSHRC Insight Grants</h5> <ul> <li>Professor <a href="/desautels/laurent-barras">Laurent Barras</a> (with Professor <a href="/desautels/david-schumacher">David Schumacher</a>)</li> <li>Professor <a href="/desautels/sebastien-betermier">Sebastien Betermier</a></li> <li>Professor <a href="/desautels/lisa-cohen">Lisa Cohen</a></li></ul> Tue, 23 Feb 2021 23:02:04 +0000 不良研究所