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This paper addresses the growing fragmentation between traditional and digital service innovation (DSI) research and offers a unifying metatheoretical framework.

Grounded in service-dominant (S-D) logic's service ecosystems perspective, this study builds on an institutional and systemic, rather than product-centric and linear, conceptualization of value creation to offer a unifying framework for (digital) service innovation that applies to both physical and digital service provisions.

This paper questions the commonly perpetuated idea that DSI fundamentally changes the nature of innovation. Instead, it highlights resource liquification—the decoupling of information from the technologies that store, transmit, or process this information—as a distinguishing characteristic of DSI. Liquification, however, does not affect the relational and institutional nature of service innovation, which is always characterized by (1) the emergence of novel outcomes, (2) distributed governance and (3) symbiotic design. Instead, liquification makes these three characteristics more salient.

In presenting a cohesive service innovation framework, this study underscores that all innovation processes are rooted in combinatorial evolution. Here, service-providing actors (re)combine technologies (or more generally, institutions) to adapt their value cocreation practices. This research demonstrates that such (re)combinations exhibit emergence, distributed governance and symbiotic design. While these characteristics may initially seem novel and unique to DSI, it reveals that their fundamental mechanisms are not limited to digital service ecosystems. They are, in fact, integral to service innovation across virtual, physical and blended contexts. The study highlights the importance of exercising caution in assuming that the emergence of novel technologies, including digital technologies, necessitates a concurrent rethinking of the fundamental processes of service innovation.

Resilience while learning is the capacity to initiate, persist and direct effort toward learning when experiencing unpleasant affective states. The underlying mechanisms of resilience are emotional buffering and self-regulation when experiencing unpleasant affective states. The authors identified four factors that support resilience while learning: positive emotional engagement, creative problem-solving, learning identity and social support. The authors developed and tested scales and found evidence to support the four-factor model of resilience. The authors offer a person-centered approach to resilience in learning by conducting a latent profile analysis that tested the likelihood of resilience based on profiles of differences in scores on these factors under two affective conditions: (unpleasant) learning during frustration versus (pleasant) learning during progress. A quarter of individuals activated the four resilience factors in pleasant and unpleasant affective states, while 75% of participants saw decrements in these factors when faced with frustration. The results support a four-factor, person-centered approach to resilience while learning.

The authors develop and test a four-factor model of resilience and test the model in a group of 330 management undergraduate and graduate students. Each participant identified two learning episodes in their responses, one while frustrated and one while making progress, and ranked the level of intensity on the four resilience factors. Analysis on an additional 88 subjects provided additional support for the validation and reliability of scales.

Results revealed 2 latent profiles groups, with 25% of the sample associated with resilience (low difference on resilience factors between the two learning episodes) and 75% who remain susceptible to unpleasant emotions (high difference between the two learning episodes).

The study supports a person-centered approach to resilience while learning (in contrast to a variable centered approach).

The study provides a means to classify individuals using a person-centered, rather than a variable-centered approach. An understanding of how individuals buffer and self-regulate while experiencing unpleasant affect while learning can help educators, consultants and managers develop better interventions for learning.

This study addresses the growing concern over student success associated with increased dropout rates among undergraduate business students, and the failure of many management developments and executive training efforts. This study suggests that looking at specific variables may not provide insight into the complex relationship between learning outcomes and factors that support resilience in learning.

There is growing interest in understanding resilience factors from a person-centered perspective using analytical methods such as latent profile analysis. This is the first study to look at how individuals can be grouped into similar profiles based on four resilience factors.