Blockchain network as a platform: conceptualising its adapted layered architecture design

Digital platform as an organising logic has prominently reshaped the innovation activities in many sectors. Previous studies have extensively investigated the digital platforms from two views: economic view (i.e. as a sided marketplace) and engineering view (i.e. as an innovation infrastructure). Blockchain – a digital artefact that connects the distributed ledgers – resembles great overlaps and specifics to digital platforms. Building on this aspect, I first demarcate the Blockchain Product as a Platform (BPaaP) informed by the economic view and the Blockchain network as a platform (BNaaP) inspired by the engineering view. Given the scant of research around BNaaP, this research aims to depict the BNaaP’s architectural design by drawing on the layered design of digital technologies. Using Ping An Group as a case, this research applies the thematic analysis method in analysing online open data. As the main contribution, this research proposes the Adapted Layered Architecture of BNaaP that consists of (1) three design layers (foundation layer, interaction layer, and application layer); (2) adapted business scenarios; and (3) environmental factors. The suggested architectural design implies the BNaaP’s internal synergistic collaboration among layers and the external adaptability to different business contexts. Overall, this research provides a novel angle to understand the Blockchain phenomenon and brings insightful implications to Blockchain practitioners

Seeding innovation on nascent platforms: evidence from Amazon Alexa

Growing complementary innovations has always been a prominent concern for nascent platforms. With high uncertainty on the prosperity of the platform, complementors often hesitate to contribute innovation on the platform. This research studies complementor seeding strategy, which we define as “platform owners selectively fund third-party development of complementary innovation to elevate platform value”. We explore a mixed-methods design to examine Amazon Alexa’s seeding strategy from 2015 to 2021. Our preliminary findings reveal that complementor seeding could be conceptualized as a layered structure where the seeds are endorsed to grow innovation in platform applications, platform enablers, and platform foundation. Besides, a nascent platform will benefit from a shorter development window for seeding indirect complementary innovations that can give rise to undulating waves of innovation on the platform. Overall, this study contributes novel insights to digital innovation management on nascent platforms. </p

Human prejudice to the healthcare social robot and the impact of human personality: an experiment of the online mental counseling

Robots have vastly influenced the healthcare practices. Ample studies have investigated the use of industrial robots, while leaving social robots an under-explored area. This research investigates human’s prejudicial attitude on the social robots that conduct online mental counseling services. 80 participants are recruited, who have been told to receive counseling services either delivered by a human counselor or a robotic counselor. Given that the actual counseling services are all completed by the same human profession with carefully maintained quality consistency, the participants’ diverged counseling satisfaction becomes a substantial proxy for their prejudiced attitudes on the robotic counselor. With significant lower counseling satisfaction, participants in the robot group particularly show bias on the "helpfulness", "support", and "inclusion" of counseling services. Furthermore, the personality trait of “openness” is found to significantly narrow the magnitude of human bias on social robot. Overall, this research contributes profound insights to post-Covid healthcare research and practices

Human prejudice to the healthcare social robot and the impact of human personality: an experiment of the online mental counseling

Robots have vastly influenced the healthcare practices. Ample studies have investigated the use of industrial robots, while leaving social robots an under-explored area. This research investigates human’s prejudicial attitude on the social robots that conduct online mental counseling services. 80 participants are recruited, who have been told to receive counseling services either delivered by a human counselor or a robotic counselor. Given that the actual counseling services are all completed by the same human profession with carefully maintained quality consistency, the participants’ diverged counseling satisfaction becomes a substantial proxy for their prejudiced attitudes on the robotic counselor. With significant lower counseling satisfaction, participants in the robot group particularly show bias on the "helpfulness", "support", and "inclusion" of counseling services. Furthermore, the personality trait of “openness” is found to significantly narrow the magnitude of human bias on social robot. Overall, this research contributes profound insights to post-Covid healthcare research and practices

Seeding innovation on nascent platforms: evidence from Amazon Alexa

Growing complementary innovations has always been a prominent concern for nascent platforms. With high uncertainty on the prosperity of the platform, complementors often hesitate to contribute innovation on the platform. This research studies complementor seeding strategy, which we define as “platform owners selectively fund third-party development of complementary innovation to elevate platform value”. We explore a mixed-methods design to examine Amazon Alexa’s seeding strategy from 2015 to 2021. Our preliminary findings reveal that complementor seeding could be conceptualized as a layered structure where the seeds are endorsed to grow innovation in platform applications, platform enablers, and platform foundation. Besides, a nascent platform will benefit from a shorter development window for seeding indirect complementary innovations that can give rise to undulating waves of innovation on the platform. Overall, this study contributes novel insights to digital innovation management on nascent platforms. </p

User-AI intimacy in digital health

AI-enabled technologies have increasingly been used as alternative tools for enhancing self-mental healthcare. While there are divergent views on the existence and implications of the intimacy that users may perceive towards AI applications as a result of interacting with them, the rapid development and prevalent use of AI in digital health underscore the urgent need to understand how users may perceive feelings of intimacy towards AI applications. In this study, we draw on the theory of the psychology of intimacy and a mixed-method analysis of 4,754 user reviews collected from Wysa—an AI-driven digital health application. The paper develops a conceptual model of User-AI intimacy in digital health, built on five interconnected mechanisms - topical content of self-disclosure, experiential outcomes of self-disclosure, emotional attitudes towards AI, cognitive positioning of AI, and AI technological affordances - and on their co-constitutive relationship. The model shows how mechanisms interact to transform intimate interactions into intimate relationships. The paper discusses the temporal and anthropomorphic conditions of the model and explains how it contributes novel insights to intimacy theory and to the development and management of AI healthcare applications in mental health.</p

Seeding for quality of platform complements: evidence from Amazon’s Alexa ecosystem

An important objective for digital platform governance is to ensure the creation of high-quality complements. For nascent platforms, complements are typically the main force in attracting early adopters and, consequently, further improving platform’s attractiveness to potential complementors. In this research-in-progress paper, we study seeding – direct financial support to selected complements by the platform owner – as an indirect governance mechanism in motivating the complement quality improvement in general. The dataset consists of 499 connected home complements on Amazon’s Alexa platform that were released during the first three years after the platform launch. The preliminary findings reveal that complements launched after platform owner’s seeding actions generally show better quality. Such a quality improvement effect seems to be reinforced if the platform owner can conduct repetitive seeding on the same complement. However, the effectiveness of repetitive seeding may vary depending on the investment and the maturity of the target complement’s business

Comparing platform owners' early and late entry into complementary markets

Research on platform owners’ entry into complementary markets points in divergent directions. One strand of the literature reports a squeeze on post-entry complementor profits due to increased competition, while another strand observes positive effects as increased customer attention and innovation benefit the complementary market as a whole. In this research note, we seek to transcend these conflicting views by comparing the effects of the early and late timing of platform owners’ entry. We apply a difference-in-differences design to explore the drivers and effects of the timing of platform owners' entry using data from three entries that Amazon made into its Alexa voice assistant’s complementary markets. Our findings suggest that early entry is driven by the motivation to boost the overall value creation of the complementary market, whereas late entry is driven by the motivation to capture value already created in a key complementary market. Importantly, our findings suggest that early entry, contrary to late entry, creates substantial consumer attention that benefits complementors that offer specialized functionality. In addition, they also suggest that complementors with more experience are more likely to benefit from the increased consumer attention. We contribute to platform research by showing that the timing of the platform owner’s entry matters in a way that potentially can reconcile conflicting findings regarding the consequences of platform owners' entry into complementary markets. </p

Comparing platform owners' early and late entry into complementary markets

Research on platform owners’ entry into complementary markets points in divergent directions. One strand of the literature reports a squeeze on post-entry complementor profits due to increased competition, while another strand observes positive effects as increased customer attention and innovation benefit the complementary market as a whole. In this research note, we seek to transcend these conflicting views by comparing the effects of the early and late timing of platform owners’ entry. We apply a difference-in-differences design to explore the drivers and effects of the timing of platform owners' entry using data from three entries that Amazon made into its Alexa voice assistant’s complementary markets. Our findings suggest that early entry is driven by the motivation to boost the overall value creation of the complementary market, whereas late entry is driven by the motivation to capture value already created in a key complementary market. Importantly, our findings suggest that early entry, contrary to late entry, creates substantial consumer attention that benefits complementors that offer specialized functionality. In addition, they also suggest that complementors with more experience are more likely to benefit from the increased consumer attention. We contribute to platform research by showing that the timing of the platform owner’s entry matters in a way that potentially can reconcile conflicting findings regarding the consequences of platform owners' entry into complementary markets. </p

Platform owner information capability in digital platform ecosystem: an empirical investigation

The prominence of complementary innovation in digital platform ecosystems has made information-driven decision-making a central concern to platform owners (Cusumano et al. 2020). There are ample successful cases such as Google Android and Tencent, while many platforms ceased due to the misunderstanding of platform complementors or misinterpreting ecosystem-related factors. For example, Atari made a huge mistake of not noticing and responding correctly to the flood of low-quality games, and thus dragged platform complementors into an uncontrollable price competition and vitally curbed complementor innovation (Miric et al. 2019; Wareham et al. 2014). In contrast, when Apple gained knowledge of third-party developers’ jailbreaking iPhones, it reacted by introducing a Software Development Kit (SDK) for developers in 2008, giving rise to one of the first mobile application platform ecosystems (Eaton et al. 2015)