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Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

This study aims to explore challenges and opportunities in the digitalization of the business-to-business (B2B) customer journey in different buying situations. It also investigates where in the customer journey digital marketing is most efficient.

This research adopts a single case study approach to examine a B2B company that implemented digitalization in its customer journey in different buying situations. Data were collected through semistructured interviews, complemented by internal documents and information from the company’s website and social media, to identify reasons for and against the decision to digitalize the B2B customer journey.

Digitalization can offer firms a cost-effective and value-creating way to interact with customers in a B2B context. The B2B buying situation, however, plays a significant role in decisions on how to implement digitalization. Moreover, in the prepurchase phase, digital marketing is more effective in building awareness; in the purchase phase, personal selling is more effective in addressing customers’ needs.

The use of a single case study cannot produce results directly generalizable to other contexts. However, the findings are applicable to the digitalization of B2B customer journeys in similar industrial contexts.

To successfully implement digitalization in the customer journey, B2B firms should choose digital tools according to different buying situations and phases in the customer journey, segment buyers by their needs rather than individual characteristics and integrate the sales and marketing functions.

This study contradicts prior research that claims that digital marketing can be used in a similar way in both B2B and business-to-consumer contexts. It further shows that the relevant demarcation is not between personal sales and digitalization but between automated digital marketing and individualized personal sales, regardless of medium.