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This study aims to examine the effects of network externalities and diffusion of innovation on users’ perceived usefulness and perceived enjoyment, and in turn subjective well-being and intention to use in the smart living context.

To explore different types of smart living services, the data collected come from surveying 512 users of smart home services and 570 users of smart living apps. Structural equation modeling is used to analyze the data, and post hoc interviews are conducted to provide insights into our conceptual model of smart living services.

Compatibility and perceived service complementarity are the most influential determinants of users’ perceived usefulness and perceived enjoyment toward smart living services. Perceived usefulness has a greater impact on users’ intention to use and their subjective well-being than perceived enjoyment. Interestingly, perceived enjoyment exerts a stronger influence on subjective well-being than on intention to use.

This study is one of the first to provide empirical evidence in the context of smart living services, contributing to transformative service literature by extending the understanding of technology use and its influence on user well-being into a less explored service context. This study also advances users’ intention to use and subjective well-being of technology adoption in the service context by integrating perspectives from network externalities and diffusion of innovation.

Data quality assurance (DQA) is essential for enabling the sharing and reuse of research data, especially given the increasing focus on data transparency, reproducibility, credibility and validity in research. Although the literature on research data curation is vast, there remains a lack of theory-guided exploration of DQA modeling in research data repositories (RDRs).

This study addresses this gap by examining 12 distinct cases of DQA-related knowledge organization tools, including four metadata vocabularies, three metadata schemas, one ontology and four standards used to guide DQA work in RDRs.

The study analyzed the cases utilizing a theoretical framework based on activity theory and data quality literature and synthesized a model and a knowledge artifact, a DQA ontology (DQAO, Lee et al., 2024), that encodes a DQA theory for RDRs. The ontology includes 127 classes, 44 object properties, 7 data properties and 18 instances. The article also uses problem scenarios to illustrate how the DQAO can be integrated into the FAIR ecosystem.

The study provides valuable insights into DQA theory and practice in RDRs and offers a DQA ontology for designing, evaluating and integrating DQA workflows within RDRs.

This study aimed to analyze how online management response strategies affect observers’ purchase intentions, considering the moderation of complainant communication and failure severity.

A survey was conducted with 671 Brazilian consumers, and the data were analyzed using partial least squares structural equation modeling.

The results show that quick and personalized responses increase the satisfaction of observers, who recognize the company’s competence and commitment. Clarity in communication with the complainant proved to be relevant, especially in the relationship between personalization and satisfaction, enhancing the effects of personalized webcare. For responsiveness, the moderating impact was less significant. The severity of the fault only had a significant effect on the relationship between personalization and satisfaction, suggesting that the impact of personalization is reduced in situations of greater severity.

This study reinforces the importance of adjusting webcare strategies according to context, prioritizing personalization in simple interactions and increasing efficiency in more critical situations. Companies must adapt their communication to the expectations of observers in order to maximize satisfaction and purchase intentions.

This study contributes to the literature by approaching online communication as a triad involving company-customers-observers, demonstrating how elements of online interactions moderate the effects of two important managerial response strategies on potential consumers’ purchase intentions.