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As Singapore, Dubai and the US race ahead in digital finance, Prof. Yulin Fang, Professor of Innovation and Information Management from HKU Business School, highlights that Hong Kong must move faster or risk falling behind. In his recent commentary in Ta Kung Pao, Web3 should be the core engine powering Hong Kong’s international financial centre upgrade.

In the highly competitive mobile market, third-party vendors located outside the purview of hosting mobile platforms are becoming major suppliers of functional tool kits for mobile app development and innovation. Mobile app developers, however, face the uncertainty of whether and how to use third-party software development kits (SDKs) from these external vendors to create more appealing and engaging mobile apps. This study examines the extent to and conditions under which third-party SDK utilization affects mobile app market performance. Drawing on the platform ecosystem literature and boundary object theory, we contextualize the boundary-spanning practice in mobile app development as the extent to which developers utilize third-party SDKs and theorize the performance impact of third-party SDKs. Moreover, the boundary-spanning perspective leads us to examine how the performance impact of third-party SDKs varies across tool types versus platform types, the evolution of platform boundaries, and levels of app developers’ platform-specific experience. By conducting difference-in-differences-style analyses on a longitudinal data set of 335,958 multihoming mobile apps released on Apple App Store and Google Play Store, our study reveals that utilizing more third-party SDKs is positively associated with daily active users of mobile apps. This positive impact is limited to tool-type third-party SDKs, however, and is attenuated by platform updates and app developers’ platform-specific experience. This study contributes to the platform-based software innovation and platform governance literature and provides managerial implications for app developers, platform managers, and third-party SDK providers.

Digital platforms strive to filter out consumer reviews that are manipulated, which has become a common and increasingly vexing problem that can take anywhere from days to months to detect. Yet little is known about the consequences of such reviews on product market performance. Using data from the Apple App Store, we examine how the app’s ranking changes when it receives manipulated reviews that are later filtered out by Apple. Our findings reveal that both one-star and five-star manipulated reviews have a significant positive effect on app rankings within a week of posting. The positive effect of one-star manipulated reviews is particularly surprising, as it contradicts the expected effect of organic negative reviews and the intent behind using such reviews to harm competitors. We also explore how these effects evolve over time, shedding light on the role of filtering policies in mitigating distortions related to review manipulation. Results show that these effects become negative as platforms filter out manipulated reviews, but this process can take as long as six months to fully materialize. These findings highlight the need for digital platforms to increase their investment to promptly and accurately control review manipulation for the welfare of both businesses and users on the platform. To the best of our knowledge, this study is one of the first to empirically analyze the short-term and long-term effects of manipulated reviews on product sales, which provides crucial managerial implications for practitioners.

Although hospital-affiliated online health communities (OHCs) provide enormous potential for health promotion, their application can create uncertainty and complexities for existing off-line healthcare systems in terms of quality and equity concerns. Understanding how and why physicians’ off-line care quality and equity may change after joining an OHC is a critical yet underexplored question, particularly for patients with low socioeconomic status (SES), who are more likely to be impacted by such changes. This study seeks to quantify these effects using operation-level inpatient data along with the correlated activities of physicians and patients in an OHC sourced from a prominent hospital. Our empirical results show that physicians’ OHC participation is associated with a 3.87% (4.63%) reduction (increase) in the relative risk (safety) of mortality (recovery) for patients who engage in the community. To understand the mechanisms of change, we find that the enhancement of patient care continuity is a key mechanism through which OHC participation may improve off-line service quality. Study results also provide evidence of partial mediation for management and relational continuity in the process chains of OHC outcomes. Additionally, the impact of OHC participation is found to be far more pronounced for patients with low SES, suggesting that OHCs can promote the equity of off-line care quality. This study further tests how community activities along with the ladder of OHC interactions between physicians and patients affect off-line healthcare outcomes. It adds to the literatures on OHC, healthcare operations management, and public health as well as offers practical implications for service operations of online health platforms.

The past few years have seen what can almost be described as the meteoric rise of generative artificial intelligence (AI). From writing, design, application development to customer service, marketing, financial analysis, and medical assistance, more and more companies have introduced generative AI into at least one part of their operations.

Artificial intelligence (AI) technologies, represented by generative AI and machine learning, are reshaping industries with unprecedented speed and potential. Reports indicate that AI is expected to elevate productivity by 33% and redefine the global competitive landscape and economic growth (see Note 1).

Against the backdrop of the global Web 3.0 wave, which is driving the continued expansion of the virtual asset market and reshaping the international financial order, building a balanced and sound local Web 3.0 ecosystem has already become a pivotal lever for a breakthrough in Hong Kong’s financial development.

Artificial intelligence (AI) technology has been developing in leaps and bounds in recent years. Reams of academic studies have shown that human-AI collaboration is conducive to enhancing efficiency and creativity across different work settings.

Blockchain technologies have catalyzed the rise of decentralized autonomous organizations (DAOs), which operate in an incentive network fueled by crypto tokens. In essence, these tokens are imbued with either payment rights (i.e., transactional tokens) or ownership rights (i.e., governance tokens). The decentralized organizational paradigm dismantles the traditional management structure and bring new research opportunities to Operations Management (OM). While the performance of DAOs has been largely examined in current OM literature, the effectiveness of their internal incentive mechanisms—specifically the one that uses ownership as rewards to promote user contributions—remains unclear. Focusing on DAO-enabled virtual communities, we seek to examine whether decentralized ownership provides stronger incentives for user behaviors, such as creation and curation, in comparison to traditional monetary rewards through the lens of psychological ownership theory. We obtained data from Steemit that captures the reward, creation, curation and transaction behaviors of 98,000 users from May 2017 to April 2019. By leveraging the “power-up” action as a shock that increases user ownership shares, we established a quasi-experimental setting. Employing the PSM-DID model, we found that the use of governance tokens is associated with enhanced creation and curation efforts but declined creation novelty, compared to the use of transactional tokens. Our additional analyses further reveal that the incentive effects of governance tokens diminish over time. However, upon the recurrence of the intended choice, these effects become reinforced. Notably, we find that governance token ownership is more strongly associated with curation efforts for users with weaker social ties. Conversely, for users with high reputation scores, their content creation behaviors are less strongly associated with governance token ownership. This study contributes to the burgeoning discourse on blockchain and cryptocurrency from an operational perspective, providing valuable insights for the design of incentive mechanisms in DAOs and advancing our understanding of operational efficiencies and stakeholder engagement in decentralized structures within Operations Management.

In the burgeoning marketplaces of digital assets, non-fungible tokens (NFTs) revolutionize digital asset ownership and intellectual property (IP) protection, but high minting costs create barriers to marketplace entry and growth. This study examines the impact of “lazy minting,” a new NFT production method introduced by major NFT marketplaces to lower minting costs by deferring blockchain certification until the first sale. In response to the call for further research on emerging technologies in operations management, we explore how this policy affects the net sales performance of existing sellers in the NFT marketplaces. Based on transaction cost economics (TCE) and the literature about different IP protection methods, we distinguish between lazy- and regular-minted NFTs by their differential transaction costs and utilize the staggered difference-in-differences (DID) method to conduct our analysis. We find that lazy minting adoption significantly boosts the net sales performance of existing sellers. This is attributed to their cost-adaptive IP protection behavior. Specifically, they achieve this by minting more NFTs with a larger proportion of style-consistent NFTs through lazy minting, while strategically employing regular minting for style-breaking NFTs, which is contingent upon their reputation. Our study has important theoretical and practical implications for operations management under the emerging technological revolution.