Digital Transformation: Quo Vadit?

Abstract

Digital transformation (DT) has become an important theme in information systems (IS) and adjacent fields (Carroll et al. 2023; Hanelt et al. 2021; Kraus et al. 2021; Piccoli, Grover, and Rodriguez 2024; Schallmo et al. 2024; Van Veldhoven and Vanthienen 2022; Verhoef et al. 2021; Vial 2019). This is of course unsurprising given the widespread interest in how digital technologies occasion change in markets, societies at large, and the political landscape (Bareikytė et al. 2024; Cowburn 2024; Davidson et al. 2023; Faik, Barrett, and Oborn 2020; Majchrzak, Markus, and Wareham 2016; Tana, Breidbach, and Burton-Jones 2023). Coming to terms with these changes, their outcomes, and unintended consequences is, therefore, both important and timely. However, fully understanding these phenomena questions extant theories (Nambisan et al. 2017; Yoo 2013; Yoo, Henfridsson, and Lyytinen 2010; Yoo et al. 2024) and warrants us to pause and more carefully consider how IS as a field has tackled ‘DT’ and what challenges this entails (see also, Markus and Rowe 2021).

This special issue comes down to two motivations that made us organise and call for papers. One motivation is rooted in the abovementioned observations that cumulatively point to the diverse reverberations that digital technologies have across levels, processes, and actors altogether raising important questions for scholarship about DT (Baiyere et al. 2023; Yoo, Henfridsson, and Lyytinen 2010; Yoo et al. 2024). We, as a field, need to reflect on the implications of the assumptions shaping the narratives around DT. For example, DT has become shorthand for “change” driven by digital technology (see also, Markus 2004). Further, DT has also been discussed as being desirable to contemporary organisations, which implies that the discussion exhibits a favourability bias (Davidsson 2015, 2017). Revisiting underlying assumptions is important to avoid perceptions of DT as, for example, a ‘misnomer’ (Kane 2018). Put differently, revisiting these assumptions was one key aspect that we had in mind when we were working on the call for papers for this special issue, which emphasises ‘frontiers’ in research about DT. We wanted our special issue to foreground shifting baselines (Davison and Tarafdar 2018) where phenomena related to DT gradually overflow our conventional concepts and models and call for novel conceptualizations (Mousavi Baygi, Introna, and Hultin 2021). We sensed a need for studies and theorising that developed our understanding of DT in terms of its contents, levels of analysis, and processes that would contribute to widening our conceptual apparatuses and empirical accounts.

This leads to the second motivation. Given that our first motivation calls for plurality (Markus and Rowe 2023), it becomes critical to work toward a path of research where knowledge related to DT is systematically developed. More specifically, there is a need to engage with the plurality of DT literature with stringency. We argue that many problems result from the frequent yet somewhat uncritical adoption of the compound term ‘DT’, sidestepping to an extent engagement with theories that tackled either the ‘digital’ or the ‘transformation’ long before the term ‘DT’ was invented (Baiyere et al. 2023; Besson and Rowe 2012; Markus and Rowe 2021; Wessel et al. 2021). The problem is straightforward: as long as ‘DT’ remains loosely applied, these criticisms will persist and legitimately so (Markus and Rowe 2021; Rowe and Markus 2023). If we are to solve these problems, engaging with these criticisms and their implications must be a top priority for developing theories and constructs related to DT (see also, Rivard 2020; Suddaby 2010).

These motivations made us seek papers that specifically put ‘DT’ as a construct centre-stage and further developed its meaning, application, or impact. We asked authors to specify what DT means to them and to identify the frontiers their papers aimed to advance. In this editorial, we first explain a “stringency in plurality” approach to help advance research about DT and showcase the papers in the special issue in this context before providing an overview of each paper. We then highlight critical frontiers for future research advanced by these papers and offer additional frontiers based on our reflections from editing the special issue. As a result, we offer a research agenda to motivate deeper studies on how the field considers DT.

We hope this editorial, and the special issue will provide a fresh take that helps researchers conduct the next wave of DT research in a way that respects the plurality of the discourse while enabling a tradition of generating DT-related knowledge systematically.

IS and the associated transformations have imposed a ‘management puzzle’ (Rivard et al. 2004) upon organisations long before the term ‘DT’ was invented. Indeed, accounts of transformation loom large and have a long history in research associated with organisations. Economists have addressed industrial transformations from as early as the 1930s, explaining that general-purpose technologies required changes in industrial contexts that led to societal changes (Smil 2021; Wright 1997). For example, energy production has shaped people, societies, and businesses for centuries (Smil 2018). Management researchers started to consider organisational transformation in the second half of the twentieth century, with seminal works by Pettigrew (1985, 1987), Mintzberg (1979) and Mintzberg and Waters (1985) setting the stage for a debate about ‘radical organisation change’ (Anderson and Tushman 1986; Greenwood and Hinings 1996; Romanelli and Tushman 1994; Tushman and Romanelli 1985). This literature grew to become rich, diverse, and significant in size (see, e.g., Poole and Van De Ven 2021).

IS scholars have also conducted research on organisational transformation and change, as much of the literature on IT implementation (Berente and Yoo 2012; Lapointe and Rivard 2005; Rivard and Lapointe 2012) and IT-enabled organisational transformation (see; e.g., the overview in, Besson and Rowe 2012) show. Starting from seminal works in the early 1980s and 1990s on how IT might transform corporations (Hammer and Champy 1993; Kling 1980; Scott Morton 1991), over considerations of alignment of IT with strategy (Henderson and Venkatraman 1992, 1999), to practice-based studies of transformation (Barrett and Walsham 1999; Orlikowski 1996; Scott and Orlikowski 2022), this literature has developed nuanced accounts of organisational transformations rooted in IT. Notably, most of these works stem from a time and perspective when management considered IT a support function (albeit one with transformative impacts on organisations). It is important to stress that many of these insights remain valid in the digital age (Markus and Rowe 2021; Sebastian et al. 2017). The fact that data are now central to the business of many companies does not translate into a devaluation of these important earlier works. Conversely, ERP systems and the like support data generation in transactional systems that oftentimes serve as backbones to contemporary digital technologies (Sebastian et al. 2017). In turn, how and why earlier theoretical frameworks become extended or remain valid is, and remains, an important question for DT scholarship.

Just as the term ‘transformation’ has a history of being used in various disciplines related to management, so has the term ‘digital’ been used in different variations in IS and computer science. Managers, software developers, and researchers have been concerned with digitization for decades (Brennen and Kreiss 2016; Goblick and Holsinger 1967; Tilson, Lyytinen, and Sørensen 2010). Representing objects by encoding them as zeros and ones into software was central to the historical von Neumann architecture and became a driving force for modern corporations to seek efficiency gains (Alaimo and Kallinikos 2024; Baiyere et al. 2023; Faulkner and Runde 2019; Kallinikos 2006; Kallinikos, Aaltonen, and Marton 2013; Yoo, Henfridsson, and Lyytinen 2010; Yoo et al. 2024). Relatedly, these transformations can be seen to resemble ‘digitalization’; that is, the embedding of material technologies carrying digitization into sociotechnical contexts (Baiyere et al. 2023; Bharadwaj et al. 2013; Gray and Rumpe 2015). Organisational change and transformation resulting from digitalization also form a critical theme that IS researchers have tried to grapple with for many years (Rivard et al. 2004).

Against this background, well-known models of DT have emerged in research and practice that have shaped how we think of this phenomenon. Their value lies in establishing ‘DT’ as a topic and, in doing so, bringing the debate to where it is today. Perhaps the first model to have had a noteworthy impact is that of Vial (2019), who defines DT as a process that aims to enhance the operational efficiency of an entity, improve customer experience and develop new business models to increase competitiveness and create new revenue sources (see also, Fabian et al. 2024; Giessmann and Legner 2016; Schallmo, Williams, and Boardman 2017). In this model, digital technologies play a central role in creating and reinforcing disruptions in society and industry (see also, Verhoef et al. 2021). Organisations respond to these disruptions by strategically leveraging digital technologies to develop new products and services and remain competitive, while having to overcome barriers such as cultural resistance and obsolete systems (Vial 2019).

Hanelt et al. (2021) offer a model with a stronger emphasis on organisational change implied by DT. Hanelt et al.'s (2021) model is based on Pettigrew's (1985, 1987) work as these authors develop their framework of DT based on three key elements: contextual conditions, mechanisms, and outcomes. Companies are embedded in wider ecosystems interacting with contextual conditions, such as external and internal factors that shape DT (Hanelt et al. 2021). Mechanisms refer to the processes and actions that link these conditions to outcomes, such as the adoption of new technologies and reconfiguration of organisational structures (see also Iden and Bygstad 2024). Outcomes are the consequences of DT at different levels, including organisational performance, economic impact and broader societal effects (see also, Fabian et al. 2024). The Hanelt et al.'s model emphasises the dynamic and interconnected nature of DT, highlighting the need for continuous adaptation and alignment with digital ecosystems (Hanelt et al. 2021). The model represents an articulate account of how DT can be conceptualised as organisational change.

There are many other models of DT in IS and other domains. They all have their legitimate spaces in the debate. Our intent in highlighting two models in this editorial is not to devalue the others. Instead, we aimed to characterise the broad strokes of how DT is currently perceived by relying on two of the key papers that have played an important role in shaping this stream of research. It stands to reason that if we aim to develop insights about DT, we need to clarify how the phenomenon does or does not relate to these seminal advancements. DT research is not required to follow a ‘hard science’ trajectory with unified definitions and homogeneity in methods (Rowe and Markus 2023). Quite contrarily, diversity in theorising and studying DT is vital to the IS field. However, this is not synonymous with ‘anything goes’—there must be a way to sustain this plurality without risking opaqueness and lack of rigour. We turn to addressing this objective next.

Our aim in this section is to introduce a framework that appreciates the diversity inherent to current scholarship about DT while offering a means to advance research in a systematic manner. To these ends, we identify four dimensions of DT that become relevant once we think of DT as not only concerning organisations but also individuals and society at large. It is obvious that if we begin to conceive DT as phenomenon that is interconnected across different domains and levels, more than the dimensions below matter. This why the dimensions depicted below serve as starting point to drive DT research forward. Table 1 summarises the dimensions that we deem important in this regard: ‘distinctiveness’, ‘object(s)’, and ‘level(s) of analysis’, and ‘processual’ dimensions.

The rows in Table 1 suggest four ways of how to think about concisely developing new constructs related to DT, which is why we elaborate on each dimension in terms of its demands for construct clarity (Rivard 2014, 2020; Rowe and Markus 2023; Suddaby 2010). To do so we adopt Suddaby's (2010) four criteria for construct clarity. Definitions matter because without a clear and precise definition, it remains opaque what we mean when we speak of DT. While we do not need to agree on one definition, we argue that researchers should articulate the definition or meaning of DT from which their research draws. Scope conditions are central because few, if any, insights in the IS field are universal and law-like. Good research clarifies when the insights apply and when not. Relationships between constructs matter for clarifying the well-known ‘boxes and arrows’ and making clear how a focal study relates to earlier constructs. Finally, coherence means that conceptual arguments ought to be internally consistent. For example, coherence is at risk when a study is built on a process ontology yet includes entity-based arguments, even though research fields advance when individual studies use different ontologies than their predecessors (Thompson 2011).

Our stringency in plurality approach stems from our engagement with papers submitted to the special issue and our ongoing engagement in the debate about DT. While we hope the ideas articulated will foster future scholarship, we now shift focus to frontiers of DT that open new doors to different and relatively unexplored opportunities. In this Special Issue, we view frontiers as new horizons and opportunities to venture into relatively uncharted conceptual and empirical territories and specifically make a call for these kinds of papers. We approach the elaboration of the frontiers of DT research by first engaging with papers in the special issue and then synthesising these with our understanding of DT literature, thus presenting a research agenda that provides ample opportunities for scholars of DT.

We first turn to the papers in the special issue to outline their contributions to the DT discourse and the frontiers that they present (see Table 2 for a summary). Each paper highlights at least a frontier that should mobilise future research in potentially insightful avenues. In what follows, we present each paper and an overview of the boundaries identified by the authors illustrated in Table 2.

Our call for ‘stringency in plurality’ and our introduction to the papers of the special issue led us to outlining four additional frontiers that we hope will inform future research about DT. Our explication of these frontiers at this point matters because while we deem them important, they are not fully covered by our special issue. Specifically, we challenge four assumptions in proposing our frontiers. These assumptions are the (a) dominant change narrative, (b) technology imperative, (c) legacy-focused theorising and (d) behavioural scoping.

With DT all around us, it is important to ask where all this is going. Managers need to understand the phenomenon in all its facets, which calls on us researchers to be concise and clear about what we are finding and saying. This special issue and its editorial were intended to not only pause and reflect but also to act and drive forward research about DT. We explained dimensions that concern the IS field, introduced how the papers in this Special Issue speak to them and outlined where the debate could go next to tackle other challenges. While much remains to be done in these troubled times, this Special Issue marks an important milestone in research that is both empirically grounded and theoretically articulate.