Abstract:

The mobile health platforms offer users lots of exercise courses. And the platforms often employ recommender systems to enhance users' awareness of fitness exercise courses， helping them better manage their personal health. Recommender systems can predict the users’ preferences based on their historical data and recommend suitable fitness courses. One of the key objectives of deploying recommender systems is to earn higher commission fees from course providers. However， if the systems intensify market competition and subsequently reduces course sales， platform’s commission fees will correspondingly decline. This potential decrease in platform fees may prevents deploying recommender systems.The impact of recommender systems on the competitive market environment remains ambiguous. While enhancing product visibility， they also intensify competition among substitutable products. In the mobile health platforms， recommender systems increase user awareness of course offerings and expand the pool of potential customers， but they also heighten the competition among course providers. Course providers must adjust their business strategies according to the market shifting caused by recommender systems. Apart from attracting users， they need set reasonable prices to expand potential market from the extra exposure provided by the recommender system. Cost strategy of providers is intricately linked to the product price strategy. Effective cost control enhances the market competitiveness of products. A low-cost approach to producing fitness courses makes it more feasible to lower sales prices. Such low-price courses are more likely to be recommended but not necessarily favored by users. Conversely， high-quality fitness courses resulting from high-cost strategies offer greater value to users. High-cost courses provide users more health benefits， but their corresponding high selling prices reduce the likelihood of obtaining additional exposure from recommender systems. Three questions are primarily investigated： Under what conditions does a platform have the incentive to deploy a recommender system？ How does the recommender system affect market price competition and course providers' sales profits under different cost strategies？ And under various levels of user awareness and market conditions， how should course providers decide their cost strategies？The results show that　（1） Regardless of whether course providers adopt a high- or low-cost strategy， deploying a recommender system can enhance platform profits. （2） When providers uniformly adopt a high-cost strategy， the recommender system intensifies price competition among them， but simultaneously increases user demand and provider profits. （3） When providers uniformly opt for a low-cost strategy， the recommender system mitigates price competition among them. The systems may not necessarily increase user demand but can still enhance provider profits. （4） The choice of cost strategy for providers is jointly influenced by user characteristics and market conditions. When the degree of course mismatch， production costs， user health value conversion coefficients， or market cognitive levels are high， providers should choose a high-cost strategy. Conversely， when users gain a high fixed health value from courses， adopting a low-cost strategy is beneficial to provider profits.

Key words: mHealth platforms, course recommender system, price competition, cost strategy