The world is facing a digital transformation (DT) triggered by the intensified prevalence and use of digital technologies that are fundamentally changing organizations and economies. Today’s information age is dependent on different technologies based on the development of big data, algorithms, cloud computing, and social networks (Acs et al., 2022), and the market success of many businesses-whose competitive advantage mostly relies on digital technologies-is highly conditioned by their participation in digital platforms (Lafuente et al., 2022). However, the notion of DT is both theoretically and empirically underspecified (van Meeteren et al., 2022). Firms realize the potential of DT, but they can hardly tackle the challenges or achieve the maximum benefits of DT (Ellström et al., 2022). More literature is needed to uniformly define DT and help governments and private sectors develop the knowledge and abilities needed to rapidly adapt to the disruptive changes faced by businesses as a result of DT (Kraus, et al., 2021a). Although the term DT is frequently used in business research and marketing, scholars disagree on a common definition (Siachou et al., 2021). DT is not limited to particular innovative businesses such as digital start-ups and high-tech giants; it is rather a process that embraces companies of all sizes from diverse industries (Bresciani et al., 2021). For instance, for small and medium-sized enterprises (SMEs), an approach that reduce the underlying complexity of DT projects into manageable and easy-to-understand steps, rather than abstract frameworks, is highly demanded (Barann et al., 2019).

Casual everyday language is not precise enough for formal empirical research; a scientific field must develop artificial languages to increase the precision of empirical testing (Wacker, 2004). For example, Vial (2019) uses semantic analysis to build a conceptual definition of DT based on literatures on Information Systems and suggests it can be replicated in other disciplines where DT is relevant.

The discussion around DT in business and management is still open (Bresciani et al., 2021). According to Vial's (2019) call, this study aims at building a concise and clear concept of DT using existing definitions in the academic literature to provide appropriate and consistent measurable properties (Wacker, 2004), especially for the business and management domains.

A concise and clear concept of DT can help the consolidation of future applied research on business models and the design of structured frameworks for adapting business processes to digitalization. Moreover, conceptual clarity on DT is essential for equipping scholars and social planners with valid measurement instruments to strengthen research and policy action plans. For instance, governments should develop policies that facilitate the digitalization of society and economic activities (Lafuente et al., 2022), therefore, they have the responsibility of designing digital infrastructures and regulations that increase the efficiency of digital markets (Acs et al., 2022).

The research question of this proposal is the following: is the business literature sufficient to develop a conceptual definition of DT based on previous definitions?

2. Theoretical framework

The rise of smart devices and social media platforms has led to drastic changes in the way customers communicate with businesses, and in customers’ expectations to businesses’ response times and multi-channel availability (Schallmo et al., 2017). In 2005, just 500 million devices were connected to the Internet; 10 years later there were 8 billion; by 2030, it’s estimated that 1 trillion devices will be connected (WEF, 2016). Digital technologies are becoming an integral part of individuals’ lives and organizations’ work routines, and digitalization is continuously impacting the economy and society (Gimpel et al., 2018). Digitalization is the cause of large-scale transformations across multiple aspects of business, providing unparalleled opportunities for value creation (Weinelt, 2016). Research has shown that technology itself is only a part of the complex puzzle organizations need to solve to remain competitive in a digital world (Vial, 2019). The journey to digital maturity requires a whole-hearted commitment from a company’s leadership and sustained investment in people, capabilities, technology, and cultural change (Catlin et al., 2015).

According to Matarazzo et al. (2021) , research focused on DT in SMEs and how digitalization may change the entire process of consumer value creation is still limited, but they identify digitalization as a prerequisite for DT. Autio et al. (2018) associate transformative effects and business model (BM) innovation with digitalization; Verhoef et al. (2021) reserve these characteristics for DT. Kane et al. (2015) find the advantages of digitalization strategic, and not merely technological.

In general, there is frequent interchangeability between terms associated to DT (e.g., DT, digitalization, and business process reengineering) as well as a variety of variables, characteristics, and constructs affecting the conceptualization of DT (e.g., type of organization, industry, areas where digital information applies, organizations’ legacy and capabilities, organizations’ BM, and organizations’ experience with information technology and systems) (Siachou et al., 2021). Although digital changes have been thoroughly investigated by academics, DT, digitalization, and digitization are terms that are often used interchangeably by management scholars (Caputo et al., 2021).

Amongst other definitions, the term DT is used today to signify the transformational or disruptive implications of digital technologies for businesses (Jafari-Sadeghi et al., 2021). For Legner et al. (2017) , DT describes the changes brought about by information technologies as a means to automatize tasks. However, Andriole (2017) said that DT is not a software upgrade or a supply chain improvement project, but a planned digital shock to what there may be a reasonably functioning system.

There is currently no commonly accepted definition for the term DT (Schallmo et al., 2017). Vial (2019) reveals that circularity, unclear terminology, and the conflation of concepts and their impacts-among other challenges-hinder the conceptual clarity of DT. Proposing a novel definition is only the first step toward developing a better understanding of the phenomenon (Trischler & Li-Ying, 2022). The challenges of DT have gained attention from both academics and practitioners (Favoretto et al., 2021).

DT initiatives have been thoroughly investigated in this recent period (Gregurec et al., 2021) even though a formal concept remains undefined. Although definitions are never complete, unequivocal, or fully formalized, that does not mean that any or all definitions should be equally acceptable (Wacker, 2004). It is often the case that satisfying definitions cannot be found about words or concepts that are rarely used or have been newly created (Li et al., 2020). The meanings of those expressions are usually consulted from the immediate local context, on dictionaries, research documents, or the web to support interpretations and compare them to more global contexts (Ishiwatari et al., 2019).

In the case of formal conceptual definitions, few terms are preferred to convey the essence of the concept (Wacker, 2004). Li et al. (2020) propose to explicitly decompose the meaning of words into semantic components for definition generation. Wierzbicka (1996) proposes that different languages share a set of atomic concepts that cannot be further decomposed, i.e., semantic primitives by which all complex concepts can be semantically composed. Primitive terms have also been described in academic circles as terms that are not defined but are assumed to be understood by the academic field (Wacker, 2004).

3. Methodology

To build a manageable, easy-to-understand formal conceptual definition of digital transformation, Wolfswinkel et al.'s (2013) five-stage process is proposed to conduct a rigorous literature review. This process allows to (1) define the scope of the review; (2) search the literature; (3) select the final sample; (4) analyze the corpus; and (5) present the findings (Vial, 2019). Web of Science and Scopus databases are used for the initial queries as recommended by Tijjani et al. (2020) . To confirm the inclusion of all the relevant studies, the results were also cross-validated (Fakhar Manesh et al., 2021) in Google Scholar. The analysis consisted of the collection of definitions of DT and other related concepts.

After analyzing the existing definitions of DT in the academic literature, 17 unique definitions were selected. Since academic journals are not the only sources of knowledge (Mohammed et al., 2015), other professional sources such as SAP Insights (2021) and PwC (2013) were also accessed which provided an integrative view of the state of the art on DT (Kraus, et al., 2021b). Exploring those sources allowed to obtain the practitioners’ point of view.

Following Ishiwatari et al. (2019) , whose experiment is intended to describe unfamiliar words, phrases, polysemous words, rarely used idioms, or emerging entities (such as DT) through the Oxford dictionary, a “dataset newly created” from Wikipedia was also used. Finally, following Gadetsky et al. (2018) , who collects a dataset of definitions using OxfordDictionaries.com API, definitions in the Oxford Dictionary (n.d.), Wikipedia (n.d.), and Cambridge Dictionary (n.d.) were also collected by relating term searches to digital transformation.

A clear, concise definition of DT was derived using semantic decomposition (Akmajian et al., 2017), a process that aims at breaking down groups of words, single words or even morphemes into a series of primitives (Vial, 2019). Rules for formal conceptual definitions imply that a concept must be defined using primitive and derived terms to assure that terms are assumed to be known by individuals (Wacker, 2004).

4. Results

After following the five-stage process for a rigorous literature review, 19 unique definitions of DT were found. Although, this relatively small number reflects an overall enthusiasm toward the phenomenon of DT at the expense of conceptual clarity. Some of these definitions were created by research groups while others considered parts of previously published definitions. The definition by Barann et al. (2019) , considers DT “as the continuous digitalization process of a company, which uses digital and data-driven innovation to improve existing processes, change distinct BM elements, or reinvent its BM entirely”. Other definitions were built by combining existing pieces of knowledge (Wang et al., 2017), since “the term DT is used today to signify the transformational or disruptive implications of digital technologies for businesses and society” (Jafari-Sadeghi et al., 2021; Matt et al., 2016; Nambisan et al., 2018).

Academic journals are not the only sources of knowledge (Mohammed et al., 2015). Two definitions were retrieved from professional sources; PwC (2013) describes DT “as the fundamental transformation of the entire business world through the establishment of new technologies based on the internet with a fundamental impact on society as a whole”. SAP Insights (2021) indicates that DT “involves integrating digital technologies and solutions into every area of a business. This is as much a cultural change as a technological one as it requires organizations to make fundamental shifts in the ways they operate and how they deliver customer experiences and benefits. Digital solutions also help increase the workforce and can lead to business process and business model transformation”.

The Oxford Dictionary (n.d.) search retrieved no exact match for “digital transformation” in Academic English. The Cambridge Dictionary (n.d.) search suggested “digitalisation” for digital transformation, among other words, while the Wikipedia (n.d.) dataset referred the result to “digitization”.

The 19 definitions of DT retrieved for this research were analyzed to determine the essence of DT concepts by following the Wacker (2004) guidelines for conceptual definitions (Table 1).

Each definition was, then, broken down into its constituents in order to identify their primitives, following the semantic decomposition process described by Vial (2019) . Those primitives were (1) the target entity, i.e., the unit of analysis affected by DT; (2) the scope, i.e., the extent of the changes taking place within the target entity’s properties; (3) the means, i.e., the elements involved in creating the change within the target entity (4) the expected outcome, i.e., innovation of the BM (see Table 2). A conceptual definition of DT was finally derived from the resulting properties. DT is defined “as a process that aims to improve society by triggering significant changes to the enterprise business model using digital technologies”.