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Customer referral programs (CRPs) are considered an effective means of customer acquisition through which firms stimulate existing customers to refer services and products to potential new customers. Digitalization and technological developments have led to the common practice of using digital devices like smartphones or laptops to create and submit customer referrals. This is the first study to investigate the influence of submission devices in CRPs from both the sender's and receiver's perspective. Based on four experiments, we demonstrate that smartphone‐generated referrals are shorter and less positive than those composed on laptops/PCs. These differences in text length and valence negatively influence receiver responses, leading to lower purchase intentions due to the perceived usefulness of the referral mediating this relationship. Our findings underscore the important role of submission devices for online referral behavior and contribute to the growing body of research on device‐mediated consumer behavior, offering crucial insights to optimize the promotion and design of CRPs. [ABSTRACT FROM AUTHOR]

Biosimilar development refers to the process of creating a biologic drug that is similar to an existing approved biologic drug, also known as a reference drug. Due to the complex nature of biologics drugs and the inherent variability in their manufacturing process biosimilars are not identical but highly similar to the reference drug in terms of quality, safety, and efficacy. Efficacy and safety trials for biosimilars involve large numbers of patients to confirm comparable clinical performance of the biosimilar and the reference product in appropriately sensitive clinical indications and for appropriate sensitive endpoints. The objective of a biosimilar clinical data is to address slight differences observed at previous steps and to confirm comparable clinical performance of the biosimilar and the reference product. In recent years with advances in big data computing, there has been increasing interest to incorporate the totality of information from different data sources (e.g. Real World data and published literature) in design and conduct of clinical trial to support regulatory objectives. The biosimilar development is an ideal framework for utilization of Real-World Evidence in design of trials as potentially large amount of data are available for the reference dug. Hence there may be an opportunity to use RWD in establishing, improving or validating equivalence margins (EQM) for biosimilar designs, specifically in the case there is no historical published data in the intended sensitive population. In this article, we propose a variation of matching method that seems promising to identify the matched set from a real-world data for which the effect size of targeted endpoint would be comparable to historical data. We believe this is a reasonable approach because in design stage, we can view covariates and secondary endpoints as data feature that can be used in a matching method. This approach was illustrated through a case study which indicated the estimate of the primary endpoint is within 1% of published results and thus RWD may be used to justify or estimate the equivalence margin. To ensure consistent results we recommend using this approach in different indications and endpoint scenarios. Thus utilization of RWD/RWE can provide an important opportunity to increase access to biologic therapies, reducing cost by repurposing existing data. [ABSTRACT FROM AUTHOR]

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