Opportunities and challenges of blockchain for multi-sided platforms

Bendig, David; Charlet, Maximilian Article — Published Version Opportunities and challenges of blockchain for multi-sided platforms Electronic Markets Provided in Cooperation with: Springer Nature Suggested Citation: Bendig, David; Charlet, Maximilian (2025) : Opportunities and challenges of blockchain for multi-sided platforms, Electronic Markets, ISSN 1422-8890, Springer, Berlin, Heidelberg, Vol. 35, Iss. 1, https://doi.org/10.1007/s12525-025-00765-z This Version is available at: https://hdl.handle.net/10419/323626 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) Electronic Markets (2025) 35:25 https://doi.org/10.1007/s12525-025-00765-z RESEARCH PAPER Opportunities andchallenges ofblockchain formulti‑sided platforms DavidBendig1· MaximilianCharlet1 Received: 13 January 2024 / Accepted: 7 January 2025 © The Author(s) 2025 Abstract Blockchain appears promising in meeting the challenges of digital multi-sided platforms by limiting the power of centralized intermediaries. Research has addressed individual aspects of blockchain, including decentralized decision-making, trust mechanisms, and incentivization measures. A comprehensive overview of blockchain's concrete opportunities and challenges for multi-sided platforms can help research work toward a more holistic view. We aim to provide current knowledge on these nascent developments by performing a developmental literature review. We find that platforms can modularly adopt different technological and governance-related blockchain features. We develop a conceptual framework of eighteen opportunities and challenges of blockchain for multi-sided platforms. Last, we highlight mutual and sometimes contrary effects between these opportunities and challenges. Keywords Blockchain· Blockchain platform· Decentralized governance· Multi-sided platform· Network effects· Platform governance JEL Classification M150 Introduction “Twitter was so open early on that many saw its potential to be a decentralized internet standard […]. For a variety of reasons, all reasonable at the time, we took a different path and increasingly centralized Twitter. But a lot’s changed over the years,” says Jack Dorsey (2019), a founder of Twitter, 13years after the platform’s establishment. Today, Twitter, now known as X, is a highly centralized digital platform which regularly provokes criticisms concerning the platform operator’s exclusive decision-making on content moderation, user access, and interface restrictions in the platform’s ecosystem (Conger, 2022). Looking back a few years, this shift in perception is surprising. The term “Twitter revolution” once described how the public saw the platform as a means for free speech, democratization, and circumventing gatekeepers (Lim, 2012). Such a change in public perception of Twitter also impacts other platforms. For example, apartment-booking platforms, once celebrated for connecting people, are now pushed back by regulators (Rossi, 2023). Social media platforms, previously seen as global connectors, have been shaken by data leaks and privacy scandals (Conger, 2022). Electronic marketplaces, while enabling new markets for small businesses, are subject to competition investigations and the suspicion of unfair treatment of complementors (Wen & Zhu, 2019). These platforms, as well as others such as ridesharing apps like Uber, Didi, and Lyft, or food delivery services like Instacart and Deliveroo, are multi-sided platforms, acting as intermediaries to coordinate and match various user groups, facilitating transactions between them for a fee (Cennamo, 2021; Hagiu & Wright, 2015). Multi-sided platforms share inherent characteristics, including (indirect) network effects and cross-subsidization strategies (Rochet & Tirole, 2003). Indirect network effects is a term used to describe a situation whereby the value of a good for one user relies on the number of users of another group (de Reuver etal., 2017; Katz & Shapiro, 1985). The economic influence of multi-sided platforms is growing, and these platforms increasingly act Responsible Editor: Roger Bons * David Bendig [email protected] * Maximilian Charlet [email protected] 1 Institute forEntrepreneurship, University, ofMuenster, Geiststrasse 24-26, 48151Muenster, Germany Electronic Markets (2025) 35:25 25 Page 2 of 26 as “powerful engines of commerce” (Evans & Schmalensee, 2016, p. 3). In 2023, four of the five largest global companies in terms of market value were multi-sided platforms (Murphy & Tucker, 2023). Centralized platform orchestrators are responsible for the development and management of multi-sided platforms. Orchestrators make decisions on aspects like platform access, transaction rules, fee structure, promotion, coordination of complementors, and inclusion of third parties (Parker & Van Alstyne, 2008; Parker etal., 2017; Rietveld etal., 2019). In this way, platform orchestrators affect how humans interact, trade, and make decisions. These developments and the corresponding influence of platform orchestrators lead to concerns about whether centralized multi-sided platforms are becoming too powerful (Kamepalli etal., 2020). While centralized decision-making may be optimal for the platform company, it can negatively affect their user groups and other stakeholders (McIntyre etal., 2021; Subramanian, 2017; Zutshi etal., 2021). Interest in decentralized multisided platforms is growing. Decentralization refers to but is not limited to decision-making, rule setting, or data ownership (Chen etal., 2021). For example, Twitter founder Jack Dorsey funds the social platform Bluesky, a decentralized Twitter alternative driven by users and developers (Conger, 2022). An increasing number of platforms are adopting decentralized governance, often based on blockchain (Chen etal., 2021), a distributed ledger technology for recording transactions in a decentralized and permanent way (Lacity, 2022; Murray etal., 2021). Such platforms are characterized by community-wide voting processes, the integration of cryptocurrencies, and the decreased relevance of centralized intermediaries (Trabucchi etal., 2020). Weking etal. (2020) describe blockchain’s potential for “new ways of organizing economic activities, reduc[ing] costs and time associated with intermediaries, and strengthen[ing] the trust in an ecosystem of actors” (p. 285). The decreased relevance of centralized orchestrators is striking. Our understanding of the structures, dynamics, and economics of multi-sided platforms has been shaped by platforms with centralized orchestrators. The ongoing development of decentralized, blockchain-supported platforms challenges many of these assumptions, necessitating a better understanding of their implications for multi-sided platform research (Choi etal., 2020b; Trabucchi etal., 2020). In this context, information systems and multi-sided platform research communities can benefit from an understanding of how blockchain technology can apply for multi-sided platform research and how it can change our previous assumptions. Previous research published in special issues of Electronic Markets has analyzed, among other, strategies of multi-sided platforms (Abdelkafi etal., 2019), the impact of blockchain technology on networked businesses (Bons etal., 2020), the evolution of electronic marketplaces (Alt, 2020b), and the interactions of blockchain and electronic commerce (Madlberger etal., 2022). We follow the tradition of the journal investigating the potential and limits of blockchain technology for business models, networked businesses, and digital platform ecosystems (Alt, 2020a; Hein etal., 2020; Weking etal., 2020). In this article, we explore the impact of blockchain on multi-sided platforms. In our developmental literature review, we first develop a research framework to analyze the impact of blockchain on platforms. Second, we determine what the opportunities and challenges of blockchain for multi-sided platforms are, based on current research. We address two research questions: RQ 1: Which research framework is applicable for analyzing the impact of blockchain on multi-sided platforms? RQ 2:What are the opportunities and challenges of blockchain for multi-sided platforms? We find that there is no uniform blockchain platform archetype. Instead, platforms can utilize different sets of blockchain features. We develop a framework comprising four blockchain features and 18 opportunities and challenges for multi-sided platforms. Our results contribute to the multi-sided platform literature by providing a current state of knowledge on the impact of blockchain on multisided platforms, displaying the manifoldness of blockchain impact on multi-sided platforms, and sharpening platform executives’ understanding of the relevance, use cases and impact of individual blockchain features. The remainder of this paper proceeds with the proposed structure of Wolfswinkel etal. (2013) for a concept-centric literature review. In the background chapter, we provide an overview of multi-sided platforms and blockchain research, indicating the rationale for this literature review. In the method chapter, we describe the approach and process of the developmental literature review. Thereupon, we develop a research framework for our analysis. Then, we perform the textual analysis of the literature sample, analyzing opportunities and challenges for platforms. Last, we discuss and summarize our results, and provide an overview of the contributions and limitations of our approach. Background Multi‑sided platforms Our study contributes to analytical research regarding the value creation of intermediaries as they facilitate transactions between parties in competitive multi-sided markets (Evans, 2003; Hagiu, 2006; Katz & Shapiro, 1985; Rochet & Tirole, 2003). The term “multi-sided” refers to market Electronic Markets (2025) 35:25 Page 3 of 26 25 structures that bring two or more different user groups together for transactions. Common examples include hotel booking platforms (hotels and guests), search engines (web users and advertisers), or PC operating systems (users, hardware producers, and application developers) (Cennamo & Santalo, 2013; Cusumano etal., 2019; Seamans & Zhu, 2014). Due to advancements in information technology, many of these multi-sided markets emerge in the form of digital platforms, which we refer to as multi-sided platforms (Reimers etal., 2019). Multi-sided platform companies do not put emphasis on products in the conventional sense. Instead, they efficiently match different user groups to exchange goods and services, often digital, and levy a transaction fee from at least one of the user groups (Cusumano etal., 2019). Hagiu and Wright (2015) define the overarching characteristics of multi-sided platforms, namely their role of facilitating “direct interactions between two or more distinct sides,” whereby “each side is affiliated with the platform” (p. 5). Platform business models are characterized by indirect network effects, such as the positive feedback loop created by the fact that the attractiveness of a platform to one user group depends on the quantity of the other user group (Katz & Shapiro, 1985). A major stream in multi-sided platform research is the analysis of the role of centralized platform orchestrators, the entities that own, operate, govern, and strategically develop a platform (Adner, 2016). Orchestrators control the platform’s technology and make decisions regarding access, transaction rules, fee structure, promotion, coordination of complementors, and inclusion of third parties (Adner, 2016; Boudreau, 2017; Jacobides etal., 2018; Parker & Van Alstyne, 2008, 2013; Rietveld etal., 2019). Adner (2016) defines an orchestrator as an intermediary “to whose vision of structure and roles others defer. It sets, and often enforces, the governance rules, determines timing, and often reaps the lion’s share of gains after the ecosystem is aligned” (p. 48). The ways that orchestrators balance the platform’s business model to attract different user groups, support network effects, and solve the chicken-egg problem have been well-researched (Cennamo & Santalo, 2013; Eisenmann etal., 2011; Kapoor & Lee, 2013). McIntyre etal. (2021) describe how platform orchestrators capture value by optimizing “which side to charge, pricing strategy, switching costs, multi-homing costs, and crowdsourcing” (p. 9). Orchestrators make strategic decisions for platform development and budget allocation to establish trust and transparency among user groups and to incentivize users based on their relative price elasticities (Hein etal., 2020; Seamans & Zhu, 2014). Rietveld etal. (2019) and Parker and Van Alstyne (2008) find that orchestrators play a central role in managing value capture and creation in a platform’s ecosystem by selectively promoting particular complements. This way, orchestrators profoundly influence which complements succeed on a platform and the intensity of competition between complementors. Parker and Van Alstyne (2013) conclude that an orchestrator “acts as a self-interested social planner for [the platform’s] microeconomy, making choices that account for end-user consumption and developer production through cycles of recombinant innovation” (p. 3026). Researchers acknowledge that centralized orchestrator constructs can imply adverse outcomes for a platform, ecosystem dynamics, or user groups. Orchestrators can fail to stimulate and channel complementor engagement for platform development (Gawer & Cusumano, 2014; Wallbach etal., 2019). Analyses of the optimal degree of control of orchestrators compared to platform users yield differing results (Chen etal., 2021; Hagiu & Spulber, 2013; Zhao etal., 2022). Wen and Zhu (2019) observe that platform orchestrators’ strategic actions can reduce developer innovation and raise product prices. Parker etal. (2017) describe how orchestrators regularly absorb user innovation. Despite these findings, the underlying assumption of a central orchestrator remains unchanged in research, relying on platform concepts “in which a focal firm approaches the alignment of partners and secures its role in a competitive ecosystem” (Adner, 2016, p. 47). While research acknowledges theexistence of alternative platform models, “we tend to see an internal hierarchy of influence and contribution that maps on to members with more versus less influence on structure, choices, and timing of value creation” (Adner, 2016, p. 57). Research often implies that “all traditional multi-sided platforms rely on a central intermediary” (Trabucchi etal., 2020, p. 554). Consequently, centralized governance models shape our understanding of multi-sided platforms, their underlying dynamics, and challenges (Tumasjan & Beutel, 2018). This consistent perspective is surprising, considering the business model’s challenges and a general trend in electronic markets and management research towards more decentralized forms of governance (Daiberl etal., 2019). For example, Zachariadis etal. (2019) note that “while the management literature emphasizes the need for approaches capable of agile orchestration of resources across time and space, a surprising degree of centralization characterizes the governance of digital platforms” (p. 114). Simultaneously, we observe the development of more decentralized platforms in terms of governance and technical infrastructure in practice (Trabucchi etal., 2020). Reasons for this development are manifold, for example, the user’s desire for joint innovation and fair value capture (Schmeiss etal., 2019). Furthermore, the emergence of blockchain technologically enables decentralization tendencies. Electronic Markets (2025) 35:25 25 Page 4 of 26 Blockchain technology Blockchain is a distributed ledger technology for recording transactions in a decentralized and immutable way (Mohan, 2019). Lacity (2022) defines blockchain as “a meta-concept that refers to several concepts and technologies, including distributed ledgers, consensus algorithms, cryptoassets, and smart contracts” (p. 326). Unlike traditional ledgers, information is stored and updated decentralized, enabling a constant alignment of stored data via a consensus mechanism. This way, manipulation of transaction data is avoided, and trust is created without a mutually recognized middleman, like a bank, notary, or state institution (Shen etal., 2020; Wang etal., 2019). Technical implications of blockchain in information systems are described as far-reaching (Bons etal., 2020). Blockchain technology may revolutionize business operations widely due to its inherent technical features (Choi etal., 2020b). Blockchain also affects governance forms (Ziolkowski etal., 2020; Zutshi etal., 2021). Ying etal. (2018) describe the way blockchain’s security, reliability, transparency, and immutability are enabled by its technical features, but have the greatest effect on an organizational rather than a technical level. Ziolkowski etal. (2020) identify six challenges that arise with blockchain governance, half of those unique to the technology. Indeed, recent research outlines the relevance of better understanding the implications of governance aspects of blockchain in information systems research (Lacity, 2022). This includes the following: • Decision-making: Blockchain offers new ways to decentralize governance rights. Mueller-Bloch etal. (2022) describe the relevance of decentralized decision-making as crucial for replacing trusted intermediaries in information systems. Ziolkowski etal. (2020) outline decisionmaking challenges in blockchain governance that are novel and require more understanding. • Tokens: A major explanation for the initial success of blockchain-based cryptocurrencies is the ability to reward network contributors with newly issued tokens, motivating them to engage in value-enhancing activities (Lacity, 2022). Tokens are transferrable value units in a platform ecosystem for contributor incentivization, value exchange, or fundraising (Chod etal., 2021; Cong etal., 2022; Tönnissen etal., 2020). Drasch etal. (2020) suggest that while tokens can address chicken-and-egg problems in digital ecosystems, they can also negatively affect system usage. Beck etal. (2018) and Tönnissen etal. (2020) discuss existing research gaps in token-based ecosystems. • Trust: The trust function of blockchain is increasingly researched. Murray etal. (2021) analyze the impact of blockchain on the way market transactions are performed. Cho etal. (2021) show the potential of blockchain to increase tax compliance in online trades by deterring vendors’ misreporting. Feulner etal. (2022) analyze the potential of blockchain for platforms to transparently record the ownership of event tickets and limit ticket scalping. Blockchain‑supported multi‑sided platforms Research addresses the potential of blockchain to transform the processes and structures of multi-sided platforms (Lage etal., 2022; Trabucchi etal., 2020). Heinet al. (2019, 2020) identify blockchain as a push factor for incumbents’ decisions to adopt multi-sided platforms. Zutshi etal. (2021) analyze blockchain’s ability to enhance multi-sided platforms with analytics and automation applications, decentralized data infrastructure, and membership management tools. Weking etal. (2020) describe the potential of blockchain as platform infrastructure for multi-sided operations. Researchers analyze scenarios from single blockchain features enhancing multi-sided platforms to platforms run entirely by blockchain technology (Niu etal., 2021; Schmeiss etal., 2019). One challenge researchers face is the vagueness of the terms blockchain-enabled respectively blockchain platform. Pereira etal. (2019) differentiate between traditional centralized and blockchain-based platforms. Opposite to the former, blockchain-based platforms are characterized by community decision-making, permissionless entry rules, decentralized verification of transactions, and cryptocurrency instead of pricing-mechanism incentives. Lage etal. (2022) develop a taxonomy of blockchain platform archetypes. They differentiate between hosted, federated, and shared blockchain platforms, utilizing different amounts of blockchain components. Chen etal. (2021) discuss semi-decentralized platform governance structures as on Google’s Android platform. Zutshi etal. (2021) describe hybrid forms of platforms where orchestrators and user groups share governance. Blockchain’s relevance for multi-sided platforms is to a large degree its potential to replace the central intermediary role of platform orchestrators. As mentioned earlier, most platform researchers operate with an underlying assumption of a central intermediary. Zachariadis et al. (2019) highlight the potential governance implications of blockchain for current market-leading centralized platforms. Alt (2020a) presents “the question of whether platform providers are still necessary […,] pav[ing] the road towards completely decentralized blockchain-based electronic marketplaces or decentralized exchanges” (p. 184). Electronic Markets (2025) 35:25 Page 5 of 26 25 As blockchain-supported platforms develop, they give rise to this question: If blockchain can change major assumptions in multi-sided platform research, such as the role of a central orchestrator (Trabucchi etal., 2020), what is the technology’s impact on multi-sided platforms and on the prevailing scientific understanding? As Lacity (2022) notes, “[s]ome of our most revered theories need to be revisited because of blockchain” (p. 334). Previous researchers have reviewed existing literature on blockchain-based multi-sided platforms to create transparency in this nascent field. Perscheid (2021) analyzes 29 articles on blockchain’s disruptive innovation in platform markets. The author identifies differences between centralized and decentralized platforms but does not focus on multi-sidedness. Zutshi etal. (2021) analyze current findings regarding blockchain types, their value propositions, and their impact on digital platforms. They choose a technical focus instead of one based on multi-sided platform research. Kölbel etal. (2022) analyze 36 articles on blockchain-enabled marketplaces. They describe the current state of research in thematic categories including market environment and marketplace mediation design. Previous research addressing the impact of blockchain on multi-sided platforms, e.g., in the form of both opportunities and challenges, has thus far taken other lenses. Method This review aims to provide generalizable findings on the impact of blockchain on multi-sided platforms. Our literature sample consists of diverse studies with differing theoretical concepts and empirical methods. We conduct a developmental literature review to account for this diversity when selecting literature, analyzing contents, and generating new knowledge (Templier & Paré, 2015). Templier and Paré (2015) propose two major aspects for these types of reviews. First is a structured search approach for identifying and selecting a sample. Second is a concept-respectively framework-centric approach for analyzing and synthesizing the sample. We follow a structured process documented with logbooks to allow for transparent, reproducible, bias-free, and forward-looking conclusions. We utilize the adaptable guidance on developmental literature reviews for sample selection and analysis of Templier and Paré (2015) and Wolfswinkel etal. (2013) and develop an eight-step approach. As detailed by Wolfswinkel etal. (2013), these steps are not static but consist of iterative loops for continuous refinement of the sample and its analysis. The final sample was developed between the 5th of May 2022 and the 8th of May 2023. Thereupon, a phase of iterative conceptualization followed until we reached theoretical saturation on the 12th of November 2023. We provide a process overview in Fig.1. Sample selection Sample analysis Problem formulation 1Scopedefinition & literature search 2 Quality assessment 3Screening for inclusion & final sample selection 4 Iterations resulting in final end products Examples of iterative analysis Activities (selection) Step Iterative refinement of sample until final sampling (8th of May, 2023) Iterative conceptualization until theoretical saturation (12th of November, 2023) Primary explorative iteration (5th of May, 2022) Define criteria for inclusion/ exclusion of sample Select languages Determine appropriate sources for the sample Decide on specific search terms Identify fields of research (e.g., SJR sections) Open coding 5 Axial coding 6 Selective coding 7Result formulation and presentation 8 Fig. 4: Basic framework structure after open coding Fig. 5: Refined basic framework after axial coding Fig. 6: Framework of opportunities and challenges Explicate vaguely topic and scope of the review and progressively refine these Create a precise reference point and set logic for subsequent design decisions Implement quality measures to ensure evidence, validity, and significance of results Create general acceptance of findings, e.g., across research communities and geographies Exclude duplicates Define boundary conditions Test conditions with intercoder approach Analysis of abstracts and titles Analysis of forward and backward citations Discussion in cases of divergent judgements Increase abstraction level of findings Identify the main themes of categories (e.g., in the form of subcategories) Adapt framework with generated relations and subcategories Create a set of excerpts Systematically note down types of findings and iteratively develop overarching categories Develop mutually exclusive and collectively exhaustive basic framework Compare, relate, and link the identified categorizations with each other and the studied papers and excerpts Inductively create categories until state of theoretical saturation is reached, e.g., with the means of graphical matrices Develop a final conceptual framework Structure, present, and make sense of earlier findings and associated insights Formulate discussion, limitations, contributions, and conclusion of the work Develop corresponding graphs and visualizations for a transparent presentation of results Goal: Provide generalizable findings on the impact of blockchain on multi-sided platforms RQ 1: Which research framework is applicable for analyzing the impact of blockchain on multi-sided platforms? RQ 2: What are the opportunities and challenges of blockchain for multi-sided platforms? >80,000 articles (first database search) 15,532 articles downloaded on 16th of March 2023 (focussing on journals, after usingsearch terms, dropping ScienceDirect) 3,200 articles (applying SJR „Business, Management and Accounting” and “Economics, Econometrics and Finance” sections) 501 articles (SJR Ranking cutoff: 2.75 or higher) Test different quality filters includingvariousrankings 265 articles (after removing duplicates) Choose SJR and apply higher or lowercut-offs than 2.75 27 articles, representing the niche shaping of our work and its final sampling (after analysis of full texts and forward and backward citations) 72 articles (after reading abstracts and titles) Set of excerpts forall included articles Opportunity or challenge What?By? ConditionComponent Conceptual category Source P Opportunity Overcoming doubts of complementors to commit to and engage witha platform Allocating control points and responsibility in a decentralized way Control points need to enable equal or similar value capture and influence to design platform and interfaces Decisionmaking Complementor engagement Saadatmand et al. (2019) …… ………… … Table 1: 49 tabularentries Figs. 8, 9, 10: Case studies Fig. 11: Research gaps Fig. 7: Synthesized framework Fig. 2: Attribution of articles to categories Fig. 1 Iterative research design of sample selection and analysis for a developmental literature review, based on Wolfswinkel etal. (2013) and Templier and Paré (2015) Electronic Markets (2025) 35:25 25 Page 6 of 26 Sample selection Step 1: Problem formulation The basis of this review was the question of how the emergence of decentral blockchain technology impacts centralized multi-sided platforms. In an iterative process, this problem definition was refined into two consecutive research questions. These acted as reference points and set logic for subsequent research design decisions. First, we develop a research framework to analyze the impact of blockchain on platforms. In our second research question, we analyze concrete opportunities and challenges of these blockchain features for multi-sided platforms. Step 2: Scope definition andliterature search To ensure the quality and validity of findings, we limited our search process to peer-reviewed journal articles in English language and excluded other sources, e.g., grey literature (Wolfswinkel etal., 2013). We did not limit the literature review to a specific time frame, as relevant literature, due to the relative novelty of our research subject, started to develop in a manageable time frame of around ten years. We searched three scientific databases: EBSCOhost, Web of Science, and Scopus. Our iterative approach led to the exclusion of the ScienceDirect database due to the absence of exclusive findings. Initially using the search term “blockchain platform,” we iterated our search strategy to a final keyword set consisting of “blockchain” or “decentral governance” in combination with either “platform” or “market.” We searched the title and abstract of articles including the use of wildcard tokens (exemplary search string: “(blockchain* OR decentral* governance*) AND (platform* OR market*)”). A final search iteration resulted in 15,532 selected articles on the 16th of March 2023. We then limited our sample to articles published in journals listed in the “Business, Management and Accounting” and “Economics, Econometrics and Finance” sections of the SCImago Journal Ranking (González-Pereira etal., 2010). During the iteration phase, we discovered that only these categories provide valuable findings for answering our research questions. The two sections include, e.g., information systems, economics, and management journals. Step 3: Quality assessment Developmental literature reviews do not formally assess the quality of underlying studies. Nevertheless, there is a need to ensure the evidence, validity, and significance of the results (Templier & Paré, 2015). We utilized the SCImago Journal Ranking (SJR) to consider the weighted quality of an article’s journal (Alt etal., 2016). The rating of a journal represents its perceived quality based on the “number of citations and the prestige of the journals, in which a given journal’s articles are cited” (Krueger etal., 2021, p. 5). While the SJR approach has limitations, it is well-established in management and information systems research (Krueger etal., 2021; Teubner & Stockhinger, 2020). Furthermore, it fulfills expectations regarding acceptance across research communities and geographies, which is relevant due to the global nature of the research subject (Alt etal., 2016). The decision to only include research from journals ranked 2.75 or higher was based on two considerations. First, we chose to consider only above-average relevant results. Second, this approach enabled a meaningful manual analysis by keeping the number of analyzed articles manageable. The cutoff at 2.75 represented the upper third of all articles identified with an SJR rating of at least 1.0, namely, 501 articles. Please see Appendix 1 for a detailed list of the articles. Step 4: Screening forinclusion andfinal sample selection After eliminating duplicates, 265 articles remained. A challenge to researchers of multi-sided platforms is the prevailing ambiguity of their research subject. Various platform configurations and definitions hinder overarching findings and hypotheses in platform research (Abdelkafi etal., 2019). The term “platform” has different meanings in research streams like software development, mechanical engineering, or computer science. While the term “multi-sided platform” is clearly defined, some authors use other forms, including “digital platform” or just “platform.” To ensure we gathered all relevant results, we followed a precise approach. We included research on platforms that fulfill the conditions of a multi-sided platform, even when the concrete term was not used. Articles included in our research required the following boundary conditions building on established multi-sided platform research (Parker etal., 2017; Rochet & Tirole, 2006): (1) Platforms must be multi-sided, meaning they match two or more user groups. (2) Each user group must consist of multiple users. (3) Pure cryptocurrencies like bitcoin are not considered.1 (4) There is a clear comparison of platforms with and without blockchain technology, and the same goes for blockchain-principled governance. 1 Please note that lending or fintech platforms are considered in the review if they fulfill the listed criteria. Electronic Markets (2025) 35:25 Page 7 of 26 25 Conditions were tested in several rounds of manual reading by two researchers utilizing individual selection tables, in which they noted down the considerations for selection. We iteratively analyzed our samples’ titles, abstracts, full texts, and forward and backward citations and reached an inter-coder reliability of above 90 percent. When researchers came to different conclusions regarding the inclusion of articles, cases were individually discussed. Such cases included articles that analyze several platform types, some of which fulfill the conditions of a multi-sided platform while others do not, e.g., Shen etal. (2020). We included only findings that complied with our conditions. We included articles in which features such as decentralized platform governance were explicitly highlighted even if no blockchain features were mentioned, e.g., by Murray etal. (2021). The final sample of data selected for subsequent thorough textual analysis consisted of 27 articles and represented the niche shaping of our work (Wolfswinkel etal., 2013). Sample analysis While extracting, analyzing, and synthesizing data, researchers integrate prior knowledge, thoughts, and ideas, making a consistent, rigorous, and concept-centric approach relevant (Templier & Paré, 2015). To reach the desired level of objectivity, we applied the three iterative coding phases of Wolfswinkel etal. (2013). Our final framework and underlying conclusions are the result of this intertwined process, based on several rounds of going back and forth between articles, making notes, developing concepts based on inductive thinking, and investigating links between different articles (Wolfswinkel etal., 2013). Step 5: Open coding First, we marked findings and insights relevant to our problem formulation within the 27 articles of the sample, creating a substantial set of excerpts for each article. We then systematically noted the findings and iteratively developed overarching categories. This work resulted in a mutually exclusive and collectively exhaustive 2 × 2 framework structure differentiating between blockchain governance-related and technological features (y-axis) and between opportunities and challenges (x-axis, see Fig.3). The four categories represent the lowest categorizable common denominator structure of our findings regarding the diversity of our underlying data sample in terms of level of abstraction, underlying methods, and technical specifics as blockchain designs. Step 6: Axial coding In the axial coding phase, subcategories were identified and refined (Wolfswinkel etal., 2013). This process lowered the level of abstraction compared to the open coding phase. We derived four subcategories on the y-axis. These represent the main themes of our conceptual study. In contrast, our x-axis operationalization remained constant compared to the open coding phase, as it proved to be the most useful design even after further iteration. This refined 2 × 4 framework acts as conceptual frame for answering RQ 2 (see Fig.4). Step 7: Selective coding In the step of selective coding, the researcher immerses into the sub-categories based on the underlying literature, refines them, creates individual concepts, and develops relations between these concepts in an iterative process of “comparing, relating, and linking the identified categorizations with each other and the studied papers and excerpts” (Wolfswinkel etal., 2013, p. 7). Two researchers utilized a tabular framework (Table1) to systematically subsume the findings of underlying articles regarding our 2 × 4 coding (Fig.5). We documented 49 tabular entries, describing which concrete effects a blockchain feature causes in multi-sided platform settings (column “What”) and how the blockchain feature achieves this concretely (column “By”). These 49 entries represented the synthesis of the 27 articles regarding blockchain impacts. Based on the column “What” in our tabular framework, we inductively created 18 conceptual categories that describe what the four blockchain features improve, enable, or exacerbate in the context of multi-sided platforms. We developed these categories in a highly iterative process and with the means of several graphical matrices. This process ended with reaching theoretical saturation, meaning that all 49 content entries of our sample regarding the impact of blockchain features on multi-sided platforms were set into relation and mutually linked with each other (see Fig.2). Then, we answered RQ 2 with the summarizing overview in the form of Fig.6: Framework of blockchain opportunities and challenges for multi-sided platforms, which is derived in detail in the upcoming section “Analysis of opportunities and challenges.” Step 8: Result formulation andpresentation Last, the findings and associated insights are structured, presented, and conceptualized (Wolfswinkel etal., 2013). This is reached by inductively deriving findings from the results developed during the open, axial, and selective coding phases. To ensure that we “prefer the creativity of the data over the creativity of the researcher” (Wolfswinkel etal., 2013, p. 8), we followed in our discussion and conclusion section a transparent approach based on earlier findings. First, Electronic Markets (2025) 35:25 25 Page 8 of 26 we developed the main discussion regarding the two research questions strictly based on the results of steps 5 to 7. We then extended our analysis and developed a synthesized overview of mutual and sometimes contradictory influences between opportunities and challenges of blockchain features (Fig.7). First, this is performed by synthesizing our final framework of opportunities and challenges (Fig.6). In a second step we extended our analysis by utilizing additional academic articles and expert literature to develop three concise case studies on the blockchain-supported platforms Steemit, Mastodon, and TradeLens (Figs.8, 9, and 10). The cases were selected based on their relevance and available background information. Lastly, we included a graph providing a numerical analysis of our analyzed sample's absolute and relative numbers (Fig.11). We also included an overview table for all analyzed articles, including information on the type of blockchain, consensus mechanisms, smart contract use, and underlying case studies for all our samples (Appendix 1). We formulated potential promising future research based on these results in the last discussion step. Taking all these steps together, we followed the recommendation of Webster and Watson (2002) for developmental literature reviews to combine theoretical explanations, past empirical findings, and practical examples. RQ 1: Developing aresearch framework To investigate the impact of blockchain on multi-sided platforms, we develop a research framework to structure insights derived from our underlying literature sample. Previous platform research shows the relevance of defining a coherent level of abstraction to generate generalizable insights (Gawer, 2014; Gawer & Cusumano, 2014; Poniatowski etal., 2022; Templier & Paré, 2015). The level of abstraction in information system research describes the degree of detail when analyzing a system (Kaasbϕll, 1995; Poniatowski etal., 2022). A wide range of potential abstraction levels exist in platform research, e.g., ranging from holistically contrasting a centralized and a blockchain-based platform archetype to detailly analyzing the impact of blockchain on platforms based on detailed system components, e.g., the decentralized ledger, identity verification capabilities, or consensus mechanisms (see also Fig.3). As described in “Step 5: Open coding” and “Step 6: Axial coding” in the previous method section, we define a conceptual research framework by systematically noting findings from our sample and iteratively developing overarching, mutually exclusive, and collectively exhaustive categories to structure our findings on a coherent level of abstraction. Table 1 Tabular framework for analyzing and connecting the literature and creating conceptual categories (including example) Opportunity vs. challenge What? By? Condition Blockchain feature Conceptual category Source Pages Opportunity Overcoming doubts of complementors to commit to and engage with a platform Allocating control points and responsibility in a decentralized way Control points need to enable equal or similar value capture and influence to design platform and interfaces Decisionmaking Complementor engagement (O2) Saadatmand etal. (2019) 14, 15 Electronic Markets (2025) 35:25 Page 15 of 26 25 Wang etal. (2019) describe in their single-case study that unlike conventional platforms, those with blockchain background are incentivizing users not only economically but also psychologically, with measures aimed at self-fulfillment and social interaction, fulfilling the multi-dimensional motives of users. The authors note that such platforms should offer sufficient selection and secure, peer-to-peer and real-time transactions. Mohan (2019) argues that incentivizing users with tokens is relevant, but by itself insufficient for user motivation. He proposes a combination of reputation scoring and proof-ofvalue mechanisms to encourage users’ productive participation. Proof-of-value is defined as “secure consensus based on time and effort expended by humans in subjectively evaluating the contributions made by agents to the DC [decentralized cooperation] network” (Mohan, 2019, p. 10). The combination of reputation and tokens as rewards enables new ways to motivate and attract contributors. Challenge 3: Incumbents andveto players Emergent blockchain-supported multi-sided platforms compete with incumbents including centralized platforms. Incumbents can establish lock-in effects and high switching costs for their existing users (Schmeiss etal., 2019). Failed attempts like the TradeLens project prove that convincing users to switch to blockchain-supported platforms can be challenging (see “Case 3: TradeLens” in the discussion section). Mohan (2019) analyzes such participation dilemmas, in which many users would benefit from decentralized blockchain solutions. Nevertheless, benefitting from the current system and having little incentive to adopt a new one, different stakeholders may act as veto players. Niu etal. (2021) provide in their coopetition model a reason why brand-owning multinational firms may lack the incentive to support blockchain adoption when selling via platforms. They argue that if the costs of joining blockchainsupported platforms are large enough, brand-owning firms should refrain from participation in selling via blockchain platforms, even if other users profit from the new system. In their model, blockchain will make the brand-owning firm worse off in terms of competition levels and wholesaling, retailing, and tax-planning profits. Hojckova etal. (2020) describe similar challenges using the example of decentralized electric grid platforms. The authors argue that it is unlikely that existing centralized markets organically become decentralized with a bottom-up approach. Instead, the transition requires collaboration with established platform operators in charge of critical control points. They find that while “blockchain-based P2P [peer to peer] electricity trading is intended to disrupt the centralized character of the electricity sector, its realization still relies on accessing physical grid infrastructure typically owned and managed by incumbents” (Hojckova etal., 2020, p. 12), which may hinder decentralization attempts. Last, Chen etal. (2021) find that experienced platform leaders tend to avoid decentralization, raising “the concern that platforms led by experienced leaders may become overly centralized” (p.1324). Trust feature The third governance feature concerns trust. Mazzella etal. (2016) describe the relevance of trust for multi-sided platforms in the sharing economy. They highlight different trust dimensions relevant for platform users to reduce market failure likelihood, including trust in the platform’s ability to complete a transaction, in product or service quality, in user authenticity, and manageable risks. In traditional platform research, central orchestrators are responsible for creating trust between users, guaranteeing fulfillment of transactions, and ensuring users’ trust in the intermediary (Trabucchi etal., 2020). Such centralized design can present disadvantages regarding efficiency, cost, and the centralized risk of a single failure point (Ying etal., 2018; Zachariadis etal., 2019). Discussions around platform failure and the potential misuse of power by centralized platform orchestrators, including data breaches, indicate the topic’s relevance. Conversely, blockchain technology is described as having the potential to “create transparency and trust in an ecosystem that includes competitors and allows users to see which data are stored” (Hein etal., 2019, 2020, p. 643). Ying etal. (2018) argue that blockchain “replaces institution-based trust with democratization-based trust” (p. 3). This claim is based on blockchain’s inherent characteristics such as its distributed ledger function, its ability to record and verify data transparently and permanently, its democratic consensus mechanisms, and its self-executing smart contracts (Chen etal., 2021; Zachariadis etal., 2019). Next, we concisely describe findings regarding four opportunities and three challenges of blockchain in the field of trust. Opportunity 5: Trust inproduct orservice quality Xu and Choi (2021) analyze the effect of providing blockchain-verified product information on agency-sales-based online platforms. They show that authentic product provenance information, including carbon emission estimations, increases multi-sided platform profit due to the liberation of consumers from having to consult other sources. Conditions are that commission rates on the platforms and costs for blockchain technology are low. Furthermore, for detailed analysis, cross-channel effects must be considered (Xu & Choi, 2021). Tao etal. (2022) run a Stackelberg game model, finding that utilizing blockchain technology may increase product quality and decrease consumer pricing due to the Electronic Markets (2025) 35:25 25 Page 16 of 26 information verification effect. Results depend on the number of competing platforms, blockchain acceptance and quality sensitivity of consumers, and potentially lowered cost of products. Different combinations of these factors may lead to lower quality or higher consumer prices. Bauer etal. (2022) analyze blockchain certifications in multi-sided platform settings. They define blockchain certifications as “documentation of the history of an asset by multiple independent parties in a trusted manner” (p. 401). The authors, looking at technical and social subsystems of online car marketplaces, argue that traditional marketplaces work non-optimally due to information asymmetries. They show that blockchain certifications enable fairer sale prices for consumers by “decreasing the information gap (entropy) between buyers and sellers” (Bauer etal., 2022, p. 417) if product information is correct. Choi etal. (2020a) research the impact of product audit cost on full information disclosure. The authors say that if auditing costs are minor, complete product information should be disclosed. They also show that the disclosure of product information generally benefits the platform, the consumer, and the seller if the latter uses consignment schemes. Blockchain can enable “an increase of the optimal product information disclosure level, an increase of consumer surplus, and the likelihood of having the full product information disclosure” at platforms if the feature can “reduce the information auditing cost, increase the proportion of information-sensitive consumers and reduce demand volatility” (Choi etal., 2020a, p. 29). Shen etal. (2020) analyze the effect of blockchain-enabled quality disclosure on the likelihood of customers purchasing secondhand products on a platform compared to buying new products.3 The authors find that blockchain enables differentiated pricing strategies based on the uniqueness of products. With blockchain, secondhand products that are highly unique can sell for the same price as new products that are less unique because consumers can confidently evaluate product quality. Results do not apply when products are less unique. Additionally, the authors account for the effect of actual vs. perceived quality levels. For “high-quality and high-unique products (e.g., luxury products), implementing blockchain is recommended for both the platform and the supplier” (Shen etal., 2020, p. 9) at the expense of consumers’ welfare. Niu etal. (2021) describe how blockchain technology benefits sellers and buyers of brand products by removing customers’ uncertainty about product quality, and thereby increasing the market potential of sellers. Blockchain acts as proof of origin of products, enabling platforms to compete with brand manufacturers’ retail divisions. Shi etal. (2021) describe blockchain authentication for fighting counterfeit products on platforms like Alibaba or Amazon. For example, Alibaba uses an application in which information on products’ raw materials and logistics is retrievable for customers. Shen etal. (2022) find that the quality disclosure aspect of blockchain is a deterrent to counterfeiters of brand merchandise sold on platforms. If the proportion of inexperienced consumers (e.g., for newly introduced products) is large enough and costs are minor, consumer surplus and the profit of brand manufacturers grow, but the profits of imitators diminish. The authors also find that blockchain can decrease product quality, because manufacturers are losing the incentive to differentiate themself from imitators by providing better quality. Opportunity 6: Trust intransaction processes Tan and Saraniemi (2022) address the use of smart contracts in multi-sided platforms to conduct automatic transactions based on fulfillment of predefined conditions. The authors describe how “blockchain acts as an autonomous trusted escrow agent, managing the buyer-seller relationship so that the involved parties can trust in their exchange assets by gaining the economic benefits expected from the transaction” (p. 18). The authors additionally address blockchain’s ability to eliminate the risk of trusting a platform intermediary. “The mathematical and cryptography-driven exchange network could be used to replace some of the trusted agencies at a lower cost, and subsequently, this allows flat and agile business collaboration with less hierarchical and less bureaucratic middle management layers” (Tan & Saraniemi, 2022, p. 15). User trust is based on timestamped, immutable, and transparent transaction data. Similarly, Ying etal. (2018) describe the potential of blockchain to replace institutional intermediaries with nodes of a blockchain network, decreasing the risk of failure of a centralized intermediary. Ma and Hu (2022) analyze blockchain’s potential to increase platform users’ trust regarding product recycling. They describe a cooperation between a multi-sided platform and a blockchain technology service platform to “improve the recovery efficiency with the help of its blockchain technology” (p. 7). The authors find that “the adoption of blockchain can effectively improve brand goodwill, the recycling rate of waste products and demand” (Ma & Hu, 2022, p. 13). They find that blockchain adds the most value in reselling set-ups rather than using multi-sided platform-like agency models, except in scenarios involving medium to high commission rates. Schmeiss etal. (2019) describe that blockchain ledgers and smart contracts decrease information asymmetries when rewarding user contributions. This increases trust “that any interactions are securely executed and that conflicts of 3 Considering only the article’s first scenario with a decentralized, non-integrated supply chain due to the fit with the concept of multisided platforms. Electronic Markets (2025) 35:25 Page 17 of 26 25 interest can be resolved based on a common source of truth” (p. 133). This prevents unfair value capture of intermediaries and enables platform access for contributors who otherwise would not trust each other. These findings might not apply to overly complex or dynamic systems. Yu etal. (2021) describe the potential of blockchain to guarantee bank loans in multi-sided platform models. The multi-sided market that they analyze matches project developers with service providers. Traditionally, platforms guarantee bank loansthat project developers require to finance the facilitated services. Blockchain-based “customer undertaker guarantees” enable project developers to mortgage their assets via blockchain technology as collateral towards banks. This frees the platform from potential credit risk and opportunity costs, leading to higher efficiency and a pareto improvement. The findings are particularly valid if developers have low credit levels or a low opportunity cost. Tan (2022) evaluates the potential of blockchain-supported peer-to-peer trading of virtual objects like video game assets and upgrades, whose value can increase by use. Prior to blockchain, the downstream exchange of virtual objects could not be tracked, giving rise to such assets being heavily pirated. Consequently, developers of virtual objects often tried to prevent reselling. By tracking the origin of virtual goods and establishing blockchain-based chains of custody, developers in addition to resellers can profit from peer-to-peer resales of items. If virtual objects are subject to network effects such as upgrades, this can increase developers’ profits and consumers’ surplus, as resale ability justifies higher initial sales prices. Furthermore, the authors describe resale revenue-sharing options. Opportunity 7: Trust inusers Tan and Saraniemi (2022) describe how blockchain provides multi-sided platform users the trust that the products they buy exist and that the seller legally owns them. Choi etal. (2020b) state that both user authentication and storing user contribution data via blockchain address fake information issues and increase data analytics accuracy on platforms. Ying etal. (2018) discuss users’ concerns about sharing personal data when authenticating themselves on platforms, which is relevant for many multi-sided platform business models. Blockchain allows users to authenticate “without disclosing any sensitive information” (p. 3). Opportunity 8: Trust inaudit Tan and Saraniemi (2022) analyze increased transparency for investors when auditing blockchain-supported multisided platforms. On-chain governance allows to audit of critical features of multi-sided platform business models in real-time and to “alert investors about some risky blockchain projects that fail to satisfy the mechanisms enabling trust in blockchain exchange” (p. 24). Challenge 4: Data security Zachariadis etal. (2019) describe open, blockchain-supported platforms with high transparency regarding performed transactions. While these platforms enable, e.g., streamlined audits, inherent transparency can be a challenge if superior levels of data privacy are required. Similarly, Schmeiss etal. (2019) raise the concern that users may avoid blockchain-supported multi-sided platforms if they fear that sensitive data is transparently stored on blockchain, making it visible to competitors. Challenge 5: Platform profitability Liu etal. (2021) analyze decisions for or against blockchainbased product quality disclosure in multi-sided platform contexts. They describe how users’ decisions depend on the cost differences between blockchain adoption and ex-post information disclosure. The authors find no general advantage for blockchain disclosure. However, they describe potential scenarios in which “an increase in blockchain adoption further harms the platform’s payoff (…). The reason is that a large effort cost leads to low-quality transparency, resulting in ineffective service effort level and sales commission” (Liu etal., 2021, p. 3592). Challenge 6: Correctability andmoderation Zachariadis etal. (2019) explain that while blockchainsupported platforms can reduce the risk of a central system failure, this does not apply to smart contracts. In the case of erroneous smart contract design, such as for standardized platform processes, no flexible adjustment options exist. In their analysis of multi-sided platform governance, the authors conclude that “the in-principle efficiencies that could be achieved in processing smart contracts have yet to be realized in a way that would give regulated bodies […] the confidence to adopt DLT [distributed ledger technology] wholesale across their business” (Zachariadis etal., 2019, p. 115). Furthermore, they highlight risks of heavy misconduct when loopholes exist in the code of smart contract-run platforms. Technical architecture feature ofblockchain The last feature encompasses blockchain-based technical architecture. Centralized multi-sided platforms consist of a data architecture and solution framework with different service layers. The technical architecture of these platforms is characterized by proprietary data infrastructures like central databases (Pereira etal., 2019), and by services or workflows Electronic Markets (2025) 35:25 25 Page 18 of 26 that are, while often automated, easily modifiable by the platform orchestrator or other authorized actors (Ma & Hu, 2022; Tan & Saraniemi, 2022). Pereira etal. (2019) and Zachariadis etal. (2019) find that blockchain-supported platform architecture differs substantially from centralized architecture. Blockchain affects distributed data access, storing and verification, and the potential integration of smart contracts. Alt (2020a) contrasts centralized with blockchain-supported architectures and highlights potential differences in platforms’ front end, back end, and node structures. Blockchain-supported architectures are characterized by differences regarding, e.g., cost economics, efficiency dynamics, and technical requirements (Cong etal., 2022; Murray etal., 2021; Schmeiss etal., 2019). Next, we concisely describe findings regarding two opportunities and two challenges of blockchain in the field of technical architecture. Opportunity 9: Process efficiency Shi etal. (2021) use the example of the Xbox platform’s blockchain applications to illustrate how blockchain can decrease the manual effort and operational costs of payment processes. The blockchain solution “seamlessly connects all creators, developers and authors and enhances their experience by enabling fast, frictionless payment” (Shi etal., 2021, p. 13). Ying etal. (2018) find improved operational efficiency and user experience when introducing cryptocurrencies for payments on a platform. Opportunity 10: Data analytics Choi etal. (2020b) describe how blockchain-stored data leads to new methods for data analysis. The permanent nature of data records can enhance their collection and evaluability. Blockchain can address problems of missing data or data islands and avoids biased data which can result from censoring activities of centralized platforms. Challenge 7: Scalability Zachariadis etal. (2019) describe low-capacity of blockchain-supported platforms to perform high numbers of transactions. They state that validation processes suffer from “scalability issues [are] due to lack of consensus and governance structures” (Zachariadis etal., 2019, p. 115). Challenge 8: Technical skills anddebt Schmeiss etal. (2019) posit that complementors might hesitate to join a blockchain-supported platform as these can create substantial lock-in effects architecture-wise. Furthermore, they describe that blockchain-based technical architecture requires new capabilities for complementors like developer skills, standards, and interfaces. Discussion Previous research published in Electronic Markets has investigated the potential and limits of blockchain for digital and electronic markets’ business models (Alt, 2020a; Hein etal., 2020). Blockchain may enable fundamental changes in multi-sided platform markets, where it could replace the trusted intermediary role of central orchestrators (Alt, 2020a; Zachariadis etal., 2019). While blockchain-supported platforms are described as promising, we still need to know more about the technology’s concrete impact, for example, its inherent opportunities and challenges (Lacity, 2022). We perform a developmental literature review to inductively investigate findings from a selected sample of 27 articles. First, we define a research framework for our analysis that accounts for the differences in detail and technical specifications of the analyzed articles. We find that differentiating centralized from blockchain platforms is too abstract. Manifestations of blockchain features in a platform setting can take quite different shapes. Rather than assuming a uniform blockchain platform design, we define governance-related and technological blockchain features that platforms can adopt. While entirely centralized and entirely blockchain-based platforms exist, platforms can also adopt different sets of both centralized and blockchain-supported designs. We refer to these as blockchain-supported multi-sided platforms. Consequently, we focus our analysis on the impact of distinct blockchain features by sorting the different findings of our literature review into modular categories with the same level of abstraction. Second, we inductively develop 18 conceptual categories describing the different manifestations of blockchain features’ impact on multi-sided platforms. We identify ten opportunities indicating blockchain’s potential to enable new functionalities and solve existing challenges compared to centralized platforms. We identify eight new challenges, providing a nuanced picture of the potential of blockchain in multi-sided platforms. Within blockchain-supported multi-sided platforms, all or only a selected set of these opportunities and challenges can apply. Emphasizing this modular feature-based character of our findings, we answer the question which opportunities and challenges of blockchain impact multi-sided platforms. Contrary effects betweenblockchain opportunities andchallenges We extend our findings by highlighting mutual and sometimes contrary effects between opportunities and challenges of blockchain for multi-sided platforms. For example, in our analysis sectionwe find evidence that decentralized Electronic Markets (2025) 35:25 Page 19 of 26 25 decision-making can substantially improve the engagement of complementors, as they are integrated into platform governance, enabling fair value capture (Chod etal., 2021; Saadatmand etal., 2019). Then again, such decentralization may present profound challenges regarding the effectiveness and quality of decision-making processes within platforms (Tsoukalas & Falk, 2020; Zhao etal., 2022). We identify two blockchain-supported opportunities to improve the incentivization of user groups. However, such a positive effect may be impeded by centralized incumbents losing incentives on decentralized platforms. By synthesizing the 18 opportunities and challenges (see “Step 8: Result formulation and presentation”), we visualize that potentially contrary effects of opportunities and challenges are identifiable within all four blockchain features (Fig.7). We next analyze three relevant decentralized platforms in short case studies utilizing our framework of blockchain opportunities and challenges for multi-sided platforms (Fig.6). These findings, derived from expert and academic literature (see “Step 8: Result formulation and presentation”), visualize how opportunities and challenges of blockchain features can strive against each other within specific platform settings.4 Case 1: Steemit Steemit is a decentralized social media platform for creating and sharing content like blog posts, founded in 2016 (Li & Palanisamy, 2019). It operates a witness group of 21 members acting as a governance board that users elect. The platform issues different types of rewards for producers, curators, and authors, which are allocatedby a complex voting mechanism (“Opportunity 4: Plurality of incentives”) (Li & Palanisamy, 2019). Based on the weighted voting of users, which is proportional to the number of shares held by a user, contents are ranked, and producers are rewarded (“Opportunity 3: Token incentivization”) (Li & Palanisamy, 2019). This mechanism incentivizes the creation of high-quality content (“Opportunity 2: Complementor engagement”) (Zuckermann & Rajendra-Niccoluci, 2020). These opportunities are contrasted by challenges rooted in the platform’s blockchain design. Steemit has seen campaigns of dominant shareholders trying to use their market power, which is sustained by weighted voting mechanisms, to develop the platform toward their preferences. This includes systematically controlling the group of witnesses, the use of proxy electors, and the forming of value-transfer networks between witnesses and shareholders (“Challenge 1: Decision-making quality,” “Challenge 2: Decision-making flexibility,” and “Challenge 3: Incumbents and veto players”) (Zuckermann & Rajendra-Niccoluci, 2020). These governance issues, combined with the platform’s value proposition of having a solid censorship and content moderation resistance, have created several incidences of user misbehavior, including the use of bots that fraudfully promote low-value contributions (“Challenge 6: Correctability and moderation”) (Biggs, 2018; Li & Palanisamy, 2019). Case 2: Mastodon Mastodon, founded in 2016, is a blockchain-based microblogging platform similar to X. A significant feature of the platform is the ability of users to establish decentral themebased instances, which has led to an active ecosystem around both administrators and users (“Opportunity 2: Complementor engagement”) (Raman etal., 2019). In the past, the platform particularly benefitted from controversies around its centralized pendant X, leading temporarily to strong user growth (Wang etal., 2024). Governance Opportunities to improve/enable …Challenges regarding… Decisionmaking Incentivization Trust Technology Blockchain features Decentralized decision-making can enable improved platform performance (O1) and complementor engagement (O2), … but … may imply challenges for quality (C1) and flexibility (C2) of decision-making processes. Blockchain can enable incentivization with tokens (O3) and other means (O4), … … existing incumbents and veto players can hinder decentralization to protect currently advantageous market position (C3). Blockchain can increase the trust in platforms' products (O5), transaction processes (O6), users (O7), and auditing (O8), … … corresponding mechanisms may represent a challenge for data security (C4), platform profitability (C5), and correctability (C6). Technical architecture of blockchain can enable improved platform processes (O9) and new ways of data analytics (O10), … … there may exist challenges regarding platform scalability (C7) and required technical skills (C8). Technical Architecture Fig. 7 Comparison of opportunities and challenges of blockchain for multi-sided platforms (summary) 4 Steemit, Mastodon, and TradeLens underwent modifications in many aspects of their business models in different phases of their operations. The listed aspects may have been changed or are applicable only during specific time frames. Electronic Markets (2025) 35:25 25 Page 20 of 26 On the other hand, the platform has seen significant outages of technical instances, e.g., when users migrated in large numbers from centralized competitors to Mastodon (“Challenge 7: Scalability”) (Raman etal., 2019; York, 2022). The platform’s governance model hinders fast reaction and coordination to solve such instances leading to a decrease in user activity (Raman etal., 2019; Wang etal., 2024). Next to technical challenges, the platform governance generally appears too inflexible to adapt to growing user numbers and to keep them motivated to participate on the platform (“Challenge 1: Decision-making quality,” “Challenge 2: Decisionmaking flexibility”) (Raman etal., 2019; Wang etal., 2024). Such issues include ensuring sufficient content moderation as required by, e.g., European regulations (“Challenge 6: Correctability and moderation”) (York, 2022). These challenges, as well as the “established communities and clear audience engagement on Twitter, proved too significant to overcome” for Mastodon to become a full-fledged alternative to centralized microblogging platforms (“Challenge 3: Incumbents and veto players”) (Wang etal., 2024). Case 3: TradeLens In the case of TradeLens, industry incumbents Maersk and IBM tried to create a global blockchain-supported platform in the logistics sector from 2018 onwards (Tan & Saraniemi, 2022). Despite theoretical advantages for many users, including competitors of Maersk, the platform shut down in 2022 because of insufficient user acceptance (Jovanovic etal., 2022; Maersk, 2022). Expectations regarding the platform's value contribution were immense. TradeLens aimed to optimize the asset utilization of users (“Opportunity 1: Platform performance”) and to provide a variety of incentives for different user groups (“Opportunity 4: Plurality of incentives”) (Jovanovic etal., 2022). For the latter, a customer advisory board was implemented and tasked to align the diverse interests of complementors (“Opportunity 2: Complementor engagement”) (Jovanovic etal., 2022). The platform's design principles tried to enable ecosystem leverage and network effects in a market lacking these previously. Furthermore, the blockchain design of the Governance Opportunitiestoimprove/enable… Challenges regarding… Complementor engagement Decision-making quality Decision-making flexibility Decisionmaking O1 O2 C1 C2 Processefficiency Data analytics Scalability Technical skills &debt O9 O10C7 C8 Platform performance O1 Trust in audit Token incentivization Plurality of incentives Incumbents and veto players O3 O4 O8 C3 Incentivization Trust in users Trust in productor servicequality Trust in transaction processes Data securityPlatform profitability O5 O6 O7 C4 C5 Correctability & moderation C6 Trust Technology Blockchain features P l a t fo r m per f or f f m ance O 1 T rust i n a u d i t O 8 T r us t i n u s e r s T r us t i n p ro d u c t or se r vi c e q q u a l i t y y T r us t i n t r a n s ac t io n p roc p e s s es O 5 O 6 O 7 P r oc e s s ef f f f i f f c i e n c y Data a n a l y t i c s O 9 O 1 0 S calabi l i t y Te c h n i c a l s k i l l s & d e b t C 7 C 8 D ata se c u r i t y P l a tf o r m p ro fi tab i p l i t y y C 4 C 5 Techn. Arch. Note: Technical Architecture Fig. 8 Framework of blockchain opportunities and challenges for Steemit Governance Opportunitiestoimprove/enable… Challengesregarding… Compl Note: Technical Architecture ementor engagement Decision-making quality Decision-making flexibility Decisionmaking O1 O2 C1 C2 Processefficiency Data analytics Scalability Technical skills &debt O9 O10C7 C8 Platform performance O1 Trust in audit Token incentivization Plurality of incentives Incumbents and veto players O3 O4 O8 C3 Incentivization Trust in users Trust in product or servicequality Trust in transaction processes Data security Platform profitability O5 O6 O7 C4 C5 Correctability & moderation C6 Trust Blockchain features P l a t fo r m per f or ff m ance O 1 T r us t i n au d it O 8 T r us t i n u s e r s T r us t i n pro d u ct or se r vi c e q q u a l i t y y T r us t i n tr a n s ac t io n proc p e s s es O 5 O 6 O 7 To k en in c e n tiv i z a tio n P l u ra l i t y o f in c e ntive s O 3 O 4 P r oc e s s ef f ff i ff c i e ncy Data a n al y ti c s O 9 O 10 T e c h n i c al s k i ll s & debt C 8 D ata se c u r i ty P l a t fo r m p ro fi tab i p l i t y y C 4 C 5 Technology Techn. Arch. Fig. 9 Framework of blockchain opportunities and challenges for Mastodon Electronic Markets (2025) 35:25 Page 21 of 26 25 platform promised to enable an efficient data exchange for complementors (“Opportunity 9: Process efficiency”), to integrate visibility and immutability into transaction processes, to create trust between complementors (“Opportunity 6: Trust in transaction processes”), to establish a smooth and trustful compliance process (“Opportunity 8: Trust in audit”), and to allow “digitizing trade documentation, structuring data pipelines, enabling real-time information, and automating multi-party interactions” (“Opportunity 10: Data analytics”) (Jovanovic etal., 2022, p. 6). From the beginning, incumbents and other market participants were hesitant to join a platform that was developed by a current competitor (“Challenge 3: Incumbents and veto players”), among others, due to the fear that using the blockchain infrastructure could enable others to access businesssensitive proprietary data (“Challenge 4: Data security”) (Jovanovic etal., 2022). The customer advisory board could not address this issue accordingly. Project participants mentioned an irreconcilable tension between adequately addressing the concerns of complementors, which would, e.g., have required providing them with veto rights and the flexibility of an effective governance structure (“Challenge 2: Decision-making flexibility”) (Cecere, 2022). Lastly, potential users were deterred by the large necessary investment costs required to adopt decentralized technical infrastructure (“Challenge 8: Technical skills and debt”) (Cecere, 2022). All these challenges resulted in the platform failing to convince sufficient users and to overcome the chicken-egg challenge (Culot etal., 2024). Analyzing the three decentralized platforms with the means of our framework provides two major insights. First, the analysis makes even more visible that the identified blockchain opportunities and challenges dynamically affect each other in specific platform contexts within and across feature categories. When assessing the impact of blockchain on an individual platform, one needs to look at the respective applications and modes of operations of these features individually. Challenges do not necessarily need to apply in every setting, or they may be addressable with specific blockchain designs. At the same time, the potential opportunities do not automatically apply by the pure use of blockchain features but instead require a thought-out application. By combining theoretical explanations, past empirical findings, and practical examples, we conclude that blockchain does not entirely solve the challenges of centralized platforms but may substantially improve relevant areas (Webster & Watson, 2002). Simultaneously, we highlight new challenges associated with blockchainsupported multi-sided platforms, aiming to explain the gulf between their anticipated potential and their currently limited success in practice (Walsh etal., 2021; Webster & Watson, 2002). Second, we find an excellent fit for our conceptual framework (Fig.6) to address and incorporate the opportunities and challenges derived from analyzing the Steemit, Mastadon, and TradeLens cases. Our framework’s modular, feature-based character proves helpful in capturing the differing configurations of the analyzed cases. Gaps inliterature andfuture research A literature review should identify critical knowledge gaps (Webster & Watson, 2002). Our numerical analysis of 49 findings from 27 articles provides evidence that there is a strong focus of prior research on governance issues, opportunities of blockchain, and its trust feature (see Fig.11). Based on this analysis and the three prior short case studies (see “Step 8: Result formulation and presentation”), we first encourage future research focusing on the technical implications of blockchain for platforms. Different from earlier expectations of, e.g., Lacity (2022), our analysis shows that a surprising gap exists in this field. In such Governance Opportunities to improve/enable …Challengesregarding… Complementor engagement Decision-making quality Decision-making flexibility Decisionmaking O1 O2 C1 C2 Process efficiency Data analytics Scalability Technical skills &debt O9 O10C7 C8 Platform performance O1 Trust in audit Token incentivization Plurality of incentives Incumbents and veto players O3 O4 O8 C3 Incentivization Trust in users Trust in product or servicequality Trust in transaction processes Data security Platform profitability O5 O6 O7 C4 C5 Correctability& moderation C6 Trust Blockchain features De c i s i on - m a ki n g q u al i t y y C 1 Trust i n u s e r s T rust i n p ro d u c t or se r vi c e q q u al i t y y O 5 O 7 T o k e n in c e nti vi z ati on O 3 P l at fo r m p rofitab i p l i t y y C 5 C o r r e c tabi l i t y & m od e r a t i o n C 6 S calab i l i t y C 7 Technology Techn. Arch. Note: Technical Architecture Fig. 10 Framework of blockchain opportunities and challenges for TradeLens Electronic Markets (2025) 35:25 25 Page 22 of 26 context, we recommend future research at a lower level of abstraction, for example, contrasting different consensus mechanisms or comparing public and private blockchains regarding their applicability in platform contexts. Mainly but not exclusively for such technical aspects, we propose research that expands the analysis beyond peer-reviewed journals to uncover additional insights and perspectives, e.g., using grey literature. Then, we perceive future research to investigate the nuanced aspects of blockchain features with a stronger focus on potential challenges, such as blockchain-supported decision-making, as auspicious. Fields such as smart contracts and their potential adverse effects regarding transparency or limited correctability and moderation of contents deserve more attention and could spark promising research. Last, our case-based analysis provides evidence that contrary impacts between opportunities and challenges of blockchain are a significant factor in assessing the technology’s impact. Currently, most research, including that underlying this literature review, focuses on the thorough analysis of individual features, opportunities, or challenges. Our findings invite more research on the interactions between different elements, providing a holistic analysis of the impact of blockchain on multi-sided platforms. Contribution Our results contribute in three ways to the multi-sided platform literature. First, we provide the current state of knowledge regarding opportunities and challenges of blockchain for platforms by summarizing 49 findings from a transparently selected sample of 27 articles. We inductively synthesize the concrete mechanisms of four blockchain features to define 18 opportunities and challenges for platforms. By choosing a developmental literature review design, we generate overarching insights based on articles that apply various methods and analyze different blockchain designs. Our work acts as a contemporary knowledge base structuring scientific research at the interface of blockchain and multi-sided platforms, creating transparency in a developing research area, and providing insights into promising future research. Second, our work goes beyond synthesizing previous research and provides a well-rounded conceptual framework of the impact of blockchain on multi-sided platforms. The framework carves out the feature-based structure of blockchain-supported platforms and sheds light on the dynamic and potentially contrary effects of the identified opportunities and challenges. While we agree with other authors on the potential positive impacts blockchain can have on multi-sided Governance Complementor engagement Decision-making quality Decision-making flexibility Decis. Mak. O1 O2 C1 C2 Platform performance O1 Trust in auditO8 Inc. Trust in users O7 Correctability & moderation C6 Trust Technology Token incentivization Plurality of incentives Incumbents and veto players O3 O4 C3 Trust in product or service quality Trust in transaction processes Data security Platform profitability O5 O6 C4 C5 Process efficiency Data analytics Scalability Technical skills & debt O9 O10C7 C8 2 4 4 1 534 8521 11 3 21 1 1 49 findings overall 34 findings relatedtoopportunities 15 findings related to challenges 11 findings related to Decision Making, thereof 54,6% are opportunities 12 findings related to Incentivization, thereof 66,7% are opportunities 21 findings related to Trust, thereof 81% are opportunities 5findings related to Technology, thereof 60% are opportunities 10,2% of findings relatedtoTechnology features 89,8% of findings relatedtoGovernance features Techn. Arch. Note: Technical Architecture Fig. 11 Numerical analysis of features, opportunities, and challenges Electronic Markets (2025) 35:25 Page 23 of 26 25 platforms, we elucidate both positive and negative potential impacts of blockchain. Taking these aspects together, we conceptually shed light on the multi-facetedness of opportunities and challenges of blockchain for multi-sided platforms. Last, our literature review is valuable for platform practitioners. We address the issue of resistance from executives regarding blockchain adoption by analyzing three case studies of relevant decentralized platforms (Walsh etal., 2021). Our findings provide practitioners with a starting point when considering the application of blockchain features and offer transparency about blockchain's potential. Our framework can act as atemplate to provide insights into which blockchain features may be value-adding for particular circumstances. This can increase executives' understanding of the relevance and impact of specific blockchain features for their platforms, thus addressing initial resistance to the technology. Limitations As with any scientific study, this literature review has inevitable limitations. First, while our approach to identifying relevant articles is based on the transparent, reproducible, and robust process of Templier and Paré (2015) and Wolfswinkel etal. (2013), there inevitably remains the risk of any selection process potentially excluding work from our analysis (Templier & Paré, 2015). While we focus consciously on peer-reviewed academic articles, this can imply e.g., excluding grey literature, which has the potential to uncover additional insights and perspectives. Second, we only analyze articles published in journals with an SJR rating of 2.75 or above. While the reason we did so was to ensure academic quality, a higher (lower) cutoff would have resulted in more selective (comprehensive) analysis coverage. Last, while the proposed framework of blockchain features enables clear, generalizable, and meaningful insights, an alternative design, such as differentiating various blockchain types, could offer additional levels of analysis. Conclusion Decentralized, blockchain-supported multi-sided platforms have the potential to address the shortcomings and challenges of centralized platforms. We investigate the multifaced aspects of this potential through a developmental literature review. Our research design allows to synthesize articles with diverse methodological and thematic backgrounds, enabling unique insights into the current state of research. Instead of assuming a uniform blockchain platform design, we find that platforms can modularly adopt blockchain features in four overarching categories. When investigating the impact of blockchain on multisided platforms, we inductively identify ten opportunities and eight challenges. Thereupon, we develop a conceptual framework for platforms utilizing governance and technology features of blockchain. While we can confirm earlier findings on blockchain's potentially positive impacts on multi-sided platforms, our research design enables us to highlight mutual and sometimes contrary effects between the identified opportunities and challenges. This way, we provide an explanation for the gulf between the anticipated potential of blockchain-supported multi-sided platforms and their limited observed success. Last, we show that previous research has focused, among others, on governance designs and that further relevant aspects, including the technical implications of blockchain, deserve more attention. Our results contribute to information systems literature by providing a current state of knowledge about the impact of blockchain on multi-sided platforms, uncovering the multifaced and sometimes contrary aspects of blockchain's impact with the means of a conceptual framework, and sharpening executives’ understanding of the relevance and impact of technological and governance blockchain features. Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1252502500765-z. Funding Open Access funding enabled and organized by Projekt DEAL. Declarations Conflict of Interest All authors declare that they have no conflicts of interest. 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