The Next Frontiers of Digital Innovation Research
2024; Institute for Operations Research and the Management Sciences; Volume: 35; Issue: 4 Linguagem: Inglês
10.1287/isre.2024.editorial.v35.n4
ISSN1526-5536
AutoresYoungjin Yoo, Ola Henfridsson, Jannis Kallinikos, Robert Wayne Gregory, Gordon Burtch, Sutirtha Chatterjee, Suprateek Sarker,
Tópico(s)Innovation and Knowledge Management
ResumoFree AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookXLinked InEmail Go to SectionFree Access HomeInformation Systems ResearchAhead of Print The Next Frontiers of Digital Innovation ResearchYoungjin Yoo Corresponding Author Youngjin Yoo[email protected]http://orcid.org/0000-0001-8548-3475Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio 44106;Search for more papers by this author, Ola HenfridssonOla Henfridsson[email protected]Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146;Search for more papers by this author, Jannis KallinikosJannis Kallinikos[email protected]Libera Università Internazionale degli Studi Sociali "Guido Carli", 00197 Rome, Italy;Search for more papers by this author, Robert GregoryRobert Gregory[email protected]Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146;Search for more papers by this author, Gordon BurtchGordon Burtch[email protected]Questrom School of Business, Boston University, Boston, Massachusetts 02215;Search for more papers by this author, Sutirtha Chatterjee Sutirtha Chatterjee[email protected]https://orcid.org/0000-0001-8956-220XLee Business School, University of Nevada, Las Vegas, Nevada 89154;Search for more papers by this author, Suprateek Sarker Suprateek Sarker[email protected]http://orcid.org/0000-0002-8079-3121McIntire School of Commerce, University of Virginia, Charlottesville, Virginia 22903Search for more papers by this authorYoungjin Yoo Corresponding Author Youngjin Yoo[email protected]http://orcid.org/0000-0001-8548-3475Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio 44106;Search for more papers by this author, Ola HenfridssonOla Henfridsson[email protected]Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146;Search for more papers by this author, Jannis KallinikosJannis Kallinikos[email protected]Libera Università Internazionale degli Studi Sociali "Guido Carli", 00197 Rome, Italy;Search for more papers by this author, Robert GregoryRobert Gregory[email protected]Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146;Search for more papers by this author, Gordon BurtchGordon Burtch[email protected]Questrom School of Business, Boston University, Boston, Massachusetts 02215;Search for more papers by this author, Sutirtha Chatterjee Sutirtha Chatterjee[email protected]https://orcid.org/0000-0001-8956-220XLee Business School, University of Nevada, Las Vegas, Nevada 89154;Search for more papers by this author, Suprateek Sarker Suprateek Sarker[email protected]http://orcid.org/0000-0002-8079-3121McIntire School of Commerce, University of Virginia, Charlottesville, Virginia 22903Search for more papers by this authorPublished Online:4 Nov 2024https://doi.org/10.1287/isre.2024.editorial.v35.n41. Introduction At the dawn of the millennium, digital innovation emerged as a transformative promise. The unforeseen power and ubiquitous presence of digital technology engendered a compelling vision of individuals across society as potential creators who would not only enjoy their own digital experiences in everyday life (Yoo 2010), but also generate novel products. Yoo et al. (2010) associated this promise with the emergence of a new technical architecture, the Layered Modular Architecture (LMA), that established the conditions whereby the focus of value creation shifted from the control of corporates behind opaque walls into the hands of ordinary, yet savvy, individuals and entrepreneurs. Furthermore, they envisioned that this new technical architecture would bring a new organizing logic that was bound to challenge the traditional one that governed the industrial economy. Digital technology was no longer hidden in beige boxes in the back offices of large corporations. Rather, it was in the hands of people in their everyday contexts (Weiser 1991, Yoo 2010). The ubiquity of digital infrastructures (Tilson et al. 2010, Henfridsson and Bygstad 2013) and the availability of smartphones as a delivery mechanism (Lyytinen and Yoo 2002) radically lowered the entry barriers for entrepreneurs to pursue unprecedented market opportunities through digital innovation. The research commentary by Yoo et al. (2010) arguably served as a catalyst for the interest in digital innovation among IS scholars.1 Defining digital innovation as "the carrying out of new combinations of digital and physical components to produce novel products" (Yoo et al. 2010, p. 725), it offered two key ideas that enabled scholars to frame and study the unique nature and consequences of digital innovation. First, it described the specification of a technology architecture through which innovation is enabled and markets are transformed. In particular, the LMA advances the notion of four distinct layers—hardware, software, content, and network—as separate value spaces of innovation (cf. Henfridsson et al. 2018). Second, it put forward the incessant recombination as the driving force of digital innovation. Combined with the accessibility of digital technologies as the primary means of digital innovation and the historically low cost of capital, these two forces—the separation of four layers and recombination—allowed researchers to explore new forms of value creation far beyond the traditional vertical industrial and product boundaries. Some 15 years later, digital innovation has come of age. Consider how digital innovation has transformed industries, reshaped economies, and altered our lives and work. We navigate with Google Maps, share memories on Instagram, work remotely via Zoom, shop endlessly on Amazon, and stay connected through Facebook. From LinkedIn for professional networking to X (formerly Twitter) for real-time updates, from Dropbox for file storage to Venmo for seamless transactions, and from Fitbit for fitness to Headspace for mindfulness, digital tools permeate every aspect of our lives, reshaping the way we connect, learn, and grow. Apple, Google, Amazon, Microsoft, and Meta are among the world's most valuable companies, boasting trillions of dollars of market capitalization. The advent of the gig economy, fueled by companies like Uber, Airbnb, and Etsy, has disrupted traditional employment models and created new opportunities for millions of people worldwide. Most recently, hardware companies like Nvidia have enabled other companies to accelerate digital innovation further by supplying technologies that enable parallel computation. For the most part, the IS community has been at the forefront of researching this digital innovation revolution. Yet, it is clear that our current society does not readily map to the positive image envisioned by Yoo et al. (2010). Even though the past 15 years have indeed unleashed a wave of generative innovations, the lion's share of the value created has been captured by a handful of big tech platforms that have mastered and exploited the inner workings of digital infrastructure. Although we, people in our everyday contexts, enjoy free, convenient, and almost abundant digital services, we pay for these "free" services with the data we create through our attention and actions. The early promise of democratizing innovation through the unbounded generativity of digital technology has been tamed by the iron grip of the few companies, often referred to as the Magnificent Seven. The most recent court ruling on Google's monopoly case is just the tip of the iceberg (United States of America et al. v. Google LLC 2024). Moreover, as these technologies have expanded, concerns have emerged, in turn, about their unintended negative consequences for society, from the unsustainable level of electricity demands to power data centers and generative artificial intelligence (AI) (Watson et al. 2010) to the amplification of fake news (Muchnik et al. 2013, Kitchens et al. 2020) and declines in youth mental health associated with the use of social media platforms like Instagram and TikTok (Krasnova et al. 2015). Addressing the apparent chasm between the early vision of unbridled value creation of digital innovation and the reality 15 years later of the negative consequences of digital innovation is the grand challenge that the global information systems research community must confront. The power of digital innovation is too ubiquitous, its reach too pervasive, and its impact too consequential for our community to stand on the sidelines and passively document what happens. The urgency of this challenge serves as the impetus for this editorial. In this editorial essay, we take a step back to critically examine the current state of digital innovation to trace the root of both the positive and the negative consequences of digital innovation from multiple perspectives. In doing so, we revisit some of the early assumptions about the nature of digital innovation as they manifest in the literature, both explicitly and implicitly. We also reflect and draw upon more recent theoretical developments (Yoo et al. 2010, Kallinikos et al. 2013, Henfridsson et al. 2018, Faulkner and Runde 2019, Baskerville et al. 2020, Recker et al. 2021, Alaimo and Kallinikos 2022, Baiyere et al. 2023) and empirical studies (Huang et al. 2017, Svahn et al. 2017, Tumbas et al. 2018, Recker et al. 2021, Huang et al. 2022, Lehmann et al. 2022, Fürstenau et al. 2023, Ganguly et al. 2024, Lorenz et al. 2024). With a focus on architecture, externalities, or data, we now see an increasingly mature set of diverse, yet complementary, theoretical perspectives that help us offer a more balanced view of digital innovation and address the developments that keep changing the technical and institutional landscape in which it unfolds. The goal of this editorial essay, therefore, is to critically review the contours of the evolution of digital innovation research over the years and offer a set of entry points for IS scholars with diverse backgrounds to engage with this important intellectual challenge that our field should address. We attempt to clarify some key constructs underpinning our collective discourse on digital innovation and how they evolved. We also try to shed light on the inherent connections and tension between the two sides of value—creation and capture—which has not received much attention in the IS community. We do so in the spirit of advancing our collective understanding of this complex and dynamic phenomenon among the broader IS community, rather than closing down the discourse.2. Digital Innovation: Background, Current Status, and Limitations2.1. Background In the aftermath of the dot.com bubble, the world saw decisive and irreversible changes driven by digital technology. As observed by Friedman (2017), the launch and breakthrough of the iPhone, Hadoop, GitHub, Facebook, Twitter, YouTube, Android, Kindle, Airbnb, and IBM Watson, among many other significant innovations, roughly happened when internet users hit 1 billion in late 2006. Given these breathtaking innovations, the promises of the early visions of computing seemed to have finally arrived. Computers were no longer just tools for work in the office, but became integral parts of our daily lives (Weiser 1991, Dourish 2001, Yoo 2010). Until then, information technology (IT) was a tool to support business. IT had to align with the business to support its strategic goal (Henderson and Venkatraman 1999). To wit, IT was not the business; it was merely a tool to support it. However, all of that changed this century. Now, IT has become the business. It started with early digital native companies like Google, Amazon, and Facebook, selling digital goods. These digital goods were not subject to the economic rules of the physical goods of traditional firms (Shapiro and Varian 1999). Over time, however, the barrier between digital and physical goods blurred with the introduction of smartphones, the Internet of Things, and mobile communications. Given this historical context, scholars were confronted with the need to make sense of the new role of IT, which had become more pervasive and ubiquitous than ever before. Although the emergence of IT as the driving force of economic and societal transformations was a welcome development for IS scholars, it also presented significant challenges to those who historically focused on the role of IT within organizations. Although it was possible to offer partial explanations of the evolving landscape through the existing "IT" lens, the field needed new perspectives that would allow us to see the world in a fundamentally different way. The early digital innovation research was born out of this historical context.2.2. Current Status The term "digital" started to emerge in our discourse as a meaningful signifier some 15 years ago. Early works by Yoo et al. (2010), Yoo (2013), Faulkner and Runde (2013, 2019), Kallinikos et al. (2010, 2013), and Leonardi (2010) offer contributions that speak to digital innovation. This early body of work emphasizes reprogrammable, recombinable, ephemeral, and ambivalent characteristics of digital objects that enable the procrastinated and temporary binding of digital resources for new market offerings (Lehmann et al. 2022), generativity (Yoo et al. 2012, Fürstenau et al. 2023), rapid scaling (Huang et al. 2017), and, eventually, the establishment of digital platform ecosystems (Parker et al. 2016, Jacobides et al. 2018). A series of conceptual breakthroughs came when scholars began articulating digital objects' properties. Two contributions stand out. First, Faulkner and Runde (2013, 2019) conceptualize digital objects, such as software applications and data files, as essentially nonmaterial, bitstring-based objects that contrast with the spatial attributes associated with physical objects. Nonmaterial objects of this sort nonetheless have an enduring structure and are variously entangled with material bearers (e.g., hard-disks, CD-ROMs), through which they are stored, shared, and acted upon. Second, Kallinikos et al. (2010, 2013) elaborate on digital objects as editable, interactive, open, and distributed. These properties, Kallinikos and his coauthors claim, challenge the conventional notions of stability, boundedness, and closure that have characterized most artifacts in the past. Moreover, they suggest that digital objects are not only different from physical objects, but also from other types of symbolic or informational objects, such as texts, images, or sounds. Digital objects are not merely representations or carriers of information, but active agents that can manipulate, transform, and generate information through various computational processes. In parallel to these works seeking to define digital objects and their unique features, Yoo et al. (2010) expound on how embedding digital components into previously physical products changes the nature of products, value creation, and the organizing logic. Building on two foundational theories in computer science—von Neumann's theory of the stored-program computer (later known as von Neumann Architecture) (von Neumann 1945) and Claude Shannon's digital signal theory (Shannon 1948)—they highlight two critical separations in product architecture as a consequence of digital innovation. These separations give rise to two fundamental properties of digital technology. First, building on von Neumann's computing architecture, they propose that the separation of hardware and software leads to reprogrammability. This means that the functionality of a digital device can be changed by modifying its software without altering the physical hardware. Second, building on Shannon's digital signal theory, they propose that the separation between network and content leads all types of content—texts, images, and sound—to be homogenized into bits. The separation between data and content is a fundamental prerequisite of the ongoing data revolution, as it allows different types of data to be transmitted, stored, and processed and combined using the same digital infrastructure (Gleick 2011, Alaimo and Kallinikos 2024). Furthermore, Yoo et al. (2010) note the self-referential nature of digital technology; digital innovation requires digital technology. They argue that the self-referential nature of digital innovation creates a virtuous cycle through the positive externalities of the diffusion of digital technology. Observing the consequences of the infusion of layered modular architecture into previously nondigital products, Yoo et al. (2010) unravel the broader consequences of digital innovations. LMA's most crucial insight is that pervasive digitalization upends the long-held assumption of product design. With the proliferation of product-agnostic digital components and easily recombinable digital data objects, the very idea of a product as a fixed category is challenged. With the integration of software-enabled digital capabilities, things do not just become smarter and connected, but the boundaries between different products become blurred (Verganti 2009, Yoo et al. 2012, Wang 2021). Smartphones are not just smarter phones; the phone is one of many apps on a smartphone. A vehicle is now a "moving computing platform." Smartwatches and smart rings are wearable health devices that monitor our sleep, steps, heartbeats, breathing, and blood oxygen levels. No longer can firms apply existing mental models about product categories and industries to define what a product is and its value propositions (Kaplan and Tripsas 2008). Using generative, reprogrammable, and recombinable digital components, firms began looking for ways to discover hidden unmet needs to create new sources of customer value (Verganti 2009). This focus on value creation with digital innovations is a fundamental shift away from the traditional focus on value capture in the management literature. Ever since the seminal work of Teece (1986) on "profiting from technological innovations," an implicit assumption in the management literature has been that the value creation potential for a given product category is more or less known and fixed once a dominant design of the product is established (Murmann and Frenken 2006). Therefore, extant literature suggests that firms must focus on value capture by adding new features, improving the efficiencies of their operations, and increasing their market share (Anderson and Tushman 1990). Casual observations of digital innovations, however, challenge such an assumption. Digital innovations do not simply marginally improve a firm's ability to capture value. Instead, they disrupt the existing market by offering different value propositions. LMA provides a theoretical foundation for firms to explore these unforeseen value-creation opportunities (Henfridsson et al. 2018, Jacobides et al. 2018, Gregory et al. 2021, Wessel et al. 2021). Furthermore, such explorations of new value-creation opportunities radically increase knowledge heterogeneity, demanding different innovation practices (Lyytinen et al. 2016). Taken together, the term "digital" in early and subsequent work on digital innovation seems to have evolved to signify two separate, yet interrelated, departures from the previous ways of thinking about computer and communication technology. In the beginning, "digital" is used in contrast to "physical," marking a departure from industrial-age thinking, where physical assets were considered the primary sources of value creation (Penrose 1963, Porter 1985, Chandler 1990, Barney 1991). In this context, scholars suggest that digital assets have emerged as equally, if not more important, value-creating strategic assets for firms (Giustiziero et al. 2023). This perspective was driven by observing new market offerings providing seemingly boundless innovation opportunities (Yoo et al. 2012, Yoo 2013). Over time, however, scholars have started using "digital" in contrast to "IT" to signal the emergence of new technology in organizations. This encompasses concepts like the consumerization of IT (Gregory et al. 2018) and experiential computing (Yoo 2010). Here, digital technology signifies a broad shift in the role of technology within organizations, moving beyond the traditional IT function (Tumbas et al. 2018). This departure of digital from IT coincided with the rise of various initiatives often led by parties outside traditional IT organizations, such as digital ventures and customer experience teams. These initiatives include pilot projects with smart and connected products, apps linked to conventional offerings, and new business models such as subscriptions and ad-supported revenue. Through this evolution of the term "digital," we see an emerging consensus, whereby the term signifies the advent of digital resources and assets as unique sources of value creation via product innovation. As we stand now, we believe it is important to continue to build on the idea of "digital" as a meaningful signifier that implicates using various digital resources to create value, differentiating it simultaneously from physical and IT. It is equally important to note that the term digital does not necessarily signify different material capabilities per se, as others have suggested (Piccoli et al. 2022). Rather, it refers to the change in the role and the ownership of digital assets (even with the same material characteristics) and the shift in the locus of value creation processes.2.3. Limitations of Digital Innovation to Date Given the early excitement about the potential of distributed and generative digital innovation, mainly stressing the shift of the locus of value creation as a positive force for industrial organizing logic (Yoo et al. 2010), it is important to re-examine these early assumptions and projections to understand ways by which current economy and society do not necessarily map onto the reality envisioned. We see at least three distinct, yet related, aspects of digital innovation that can serve as entry points to understanding the limitations of digital innovation research (see Table 1). First, recombination in layered modular architecture turns out to be subject to far more centralized control than originally imagined. Consider that, in modular systems, control is codified in the interfaces between components (Baldwin and Clark 2000, Lee and Berente 2012), and whoever has control over significant boundary resources (Ghazawneh and Henfridsson 2013) will also dominate the value spaces related to layers of digital innovation (Woodard 2008, Um et al. 2023, Benzell et al. 2024). The centralized control of key digital resources involved in the distributed value creation process can lead to uneven value distribution among participating actors.Table 1. Re-examination of Early Assumptions and Visions of Digital InnovationTable 1. Re-examination of Early Assumptions and Visions of Digital InnovationKey ideasWe thought thenYes, butDistributed, generative, and recombinant innovation through LMAFour distinct layers creating separate value spaces with system-agnostic digital components, which enables distributed and generative innovation through recombinationsIndustry and product boundaries blurredShift of value creation from corporations to individuals and entrepreneursDisproportionate value capture by few big tech platformsCentralized control over key digital resourcesPositive network externalitiesPositive externalities driving innovationEnhanced platform capabilitiesNew form of externalities, data network effectNegative demand-side externalities (e.g., overcrowding, privacy concerns, entry barriers, and gatekeeping)Need for careful examination of centralized LMA used by dominant platformsData as the center stage of digital innovationHomogenization of all data as a part of LMA's content layerData as new economic resources through learning effectData as the medium or vehicle by which innovation occursCentrality of data in value creation; data as an independent value source rather than enablerPrivacy concerns and data exploitationData perform epistemic, semantic, and communicative functions with far-reaching work, industry, and structural implications Second, initially, the architectural view of digital innovation, represented by LMA, ran in parallel with the economic view of digital platform ecosystems, which view them as multisided markets (Rochet and Tirole 2003, Parker and Van Alstyne 2005). Over time, however, there is a growing convergence between the two perspectives as scholars increasingly draw on architectural and economic views on digital innovation (Van Alstyne et al. 2024). Early studies on digital innovation focused on the power of network externalities in the context of the supply side of platform ecosystems (Parker et al. 2016). This focus is often due to the visible and measurable impacts of supply-side growth, such as increased innovation, new product offerings, and enhanced platform capabilities. The supply side is frequently seen as the driver of network growth and value creation in digital ecosystems (Huang et al. 2017). However, the demand-side externalities, which have been less explored, can have profound implications, such as negative consequences associated with undesirable outcomes like overcrowding, gatekeeping, diminished user experience, and privacy concerns. Indeed, there is a growing concern among scholars and policymakers alike that the centralized nature of the current LMA needs to be carefully examined to address these negative externalities of digital innovations (Cennamo 2021, Van Alstyne et al. 2021, Cennamo et al. 2023, Jacobides et al. 2024). Third, data have become a critical frontier in digital innovation. Although the LMA provides a framework for understanding content and its intersections with other layers of digital innovation, there is a growing recognition that value creation does not necessarily happen via the recombination of system-agnostic components alone. Rather, data homogenization and the aggregation and recombination of different types of data enable these platforms to create and capture value along diverse value paths (Baskerville et al. 2020, Gregory et al. 2021, Alaimo and Kallinikos 2022). It is, therefore, not surprising that new perspectives centered around data and digital objects have emerged (Alaimo and Kallinikos 2024) alongside work on data network effects (Gregory et al. 2022). What connects these three aspects is the growing recognition of seemingly irreconcilable tension between digital innovation's incredible value creation possibilities and decisively distorted value distribution among participating actors. We believe these three aspects of digital innovation—recombinant innovation, network externalities, and data—offer potential entry points for IS scholars to address the grand challenge that our community faces.3. Digital Innovation: Moving Forward A central tension emerging from our reflection on the past 15 years is the irreconcilable chasm between the massive value created from distributed, generative, and recombinant innovations and the disproportionately uneven distribution of value created among actors. Thus, a compelling intellectual challenge that our field must confront is vigorous intellectual inquiries on how to resolve this tension efficiently, fairly, and sustainably. Our analysis highlights three aspects of digital innovation serving as complementary entry points to address this challenge: (a) the centralization of control over digital architectures, (b) the impact of negative externalities leading to market concentration, and (c) the emergence of data as a critical driver of value and organizational change (see Table 2). These three dimensions represent complex tensions between the architectural, economic, and epistemic dimensions of digital innovation. In what follows, we outline a set of research areas that we believe can serve as the frontiers of digital innovation research to resolve this tension in the years to come.Table 2. Emerging Research Themes and Example Research QuestionsTable 2. Emerging Research Themes and Example Research QuestionsResearch areasThemesExample research questionsArchitecturesNew organizational and institutional rearrangement of firmsWhat are the different forms of organizing, performing, and learning with deferred and temporary binding of digital resources?How do digital innovation reorder organizational, technological, and institutional arrangements at a macro level?How do organizations learn with massively parallelized and decentered organizational arrangements?Key interfaces and architectures are increasingly centralizedWhat are the governance mechanisms that favor (nearly) symmetric value capture in digital innovation?How can the benefits of modular recombination be leveraged within, and between, layers of digital architecture?What is the role of emerging technologies, such as blockchain technology, in governance models that combine value creation with decentralized control?Design choices and consequences in digital innovationsHow do new structural conditions of layered modular architecture interact with human design agency in reshaping digital innovation practices?What are the unintended consequences of digital innovation practices on individuals and society, including individual users' and workers' well-being and environments?ExternalitiesImpact of regulationsHow effective are different regulatory approaches in addressing negative externalities?Socio-technical governance mechanismsHow can decentralized technologies and governance structures mitigate market concentration and power issues?What novel mechanisms can address societal consequences like misinformation?How and why can platforms be designed to harness the positive aspects of network effects while mitigating m
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