Digital platforms have emerged as an important technology underpinning the new economy. A key problem in such platforms concerns provisioning decisions for customer-service requests, in order to maximize the provider's revenue subject to resource availability. Provisioning is important to meet customer needs, and in turn, for customer retention. The service provisioning problem, in addition to being NP-hard, is further compounded by the fact that the timeframe to make provisioning decisions is short, and more importantly, varies considerably across different platform domains. Digital-platform customers often request bundled services and are sensitive to when tasks get completed. We describe a behavioral-economic model of this problem and develop a domain-independent solution featuring a judicious combination of optimization-backed rule-based approach. Through extensive computational results, we show how our approach has the potential for generalizability and tailorability across different domains in a seamless manner, thus offering the advantages proposed in the software-reusability literature. Implications to platform sustainability, reusable platform solutions and to practical approaches to real-time platforms are also provided.

数字平台已成为支撑新经济的重要技术。此类平台中的一个关键问题涉及客户服务请求的供应决策，以便根据资源可用性最大化供应商的收入。配置对于满足客户需求很重要，反过来，对于保留客户也很重要。服务供应问题，除了是 NP-hard 之外，由于做出配置决策的时间框架很短，更重要的是，在不同的平台域之间差异很大，这一事实进一步加剧了这一问题。数字平台客户通常要求捆绑服务，并且对任务何时完成很敏感。我们描述了这个问题的行为经济模型，并开发了一个独立于领域的解决方案，该解决方案以优化支持的基于规则的方法的明智组合为特色。通过广泛的计算结果，我们展示了我们的方法如何具有以无缝方式跨不同领域的通用性和可裁剪性的潜力，从而提供软件可重用性文献中提出的优势。对平台可持续性的影响，