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This paper examines the framing of digital transformation. The research questions are specified as follows: what are the different types of framing strategies in response to digital transformation? How do the strategies differ across organizations? Theoretically, the authors draw on the framing perspective to emphasize the use of linguistic frames in shaping innovation and change processes. Empirically, the authors choose to study the Taiwanese sectors, including publicly governed entities, traditional private business or technology-based ventures.

The authors’ approach combines topic modeling and qualitative analysis. Using data collected from newspaper and magazine articles, the authors employ topic modeling to generate a set of distinctive framings that Taiwanese actors typically adopt to motivate and justify their digital move. The authors also conduct personal interviews to qualitatively complement the authors’ topic modeling analysis and to identify the rationale behind the linguistic framings and the strategic differences brought about by the various organizations.

The authors identify five topics that the Taiwanese actors commonly used in the framing of digital transformation. These topics or frames are labeled as cross-domain coordination, market demand, intelligent technology, global trend and competition and digital innovation. The practical use of the framings is contingent on organizational characteristics. Furthermore, the authors show how the framings can be classified as either positive framing (e.g. winning the next war) or negative framing (e.g. innovate or die), generally applicable to organizations around the world struggling to cope with digital disruption.

The authors’ study has two research implications. First, the authors extend the appreciation of the digital transformation from the usual concern with technological and business model innovations to linguistic or framing practices. Second, the authors enrich the framing analysis by emphasizing a practice or contingency perspective based on sector difference. The findings are subject to the limitations of the choice of only established and reputable media outlets, the diatextual reading and filtering of useful articles for topic modeling analysis and the use of world frequency to account for frame significance.

The authors shift actors' attention from improving technical efficiency to acquiring linguistic resources in the pursuit of digitalization. For example, framing the digital transformation in terms of creating a market orientation calls for not only real consumer power but also strategic discursive competence that enables the move to change. The findings also point out that practitioners can enlarge the scope of their agency rather than being trapped in the habituated routine of practices. Despite social embeddedness, organizations are more often widely connected and built enough to call for more of the cognitive frames to appeal to heterogeneous stakeholders.

The authors study contributes to the literature by developing a linguistic or socio-cognitive view of digital transformation strategy that is capable of expanding organizational attention toward change and innovation. The authors explore menus of strategic frames employed by actors in response to digital transformation. We also address the application of a machine-learning tool such as topic modeling to explore the socio-cognitive dimensions of digital transformation. Furthermore, the analysis leads us to identify the outcomes or effects – either positive or negative – that move beyond the particular Taiwanese case to explain the framing of digital transformation in general.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.