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The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

The current research aims to answer the following question: To what extent and under what conditions does hiring consultants to implement a customer relationship management (CRM) system produce performance gains for companies? To answer this question, this research delves into the critical interdependent roles of CRM consultant resources (CR) and user involvement (UI) in overcoming CRM’s technological and organizational implementation challenges.

A quantitative field study methodology was used to empirically test the research hypotheses. Cross-sectional data (N = 126) were collected from large client companies using CRM technology. Partial least squares-structural equation modeling was used to estimate the significance levels of the structural model.

The findings indicate that the extent to which CRM consultants improve CRM system quality (SQ) and, ultimately, firm performance, largely depends on UI, which acts as the key facilitating mechanism to cope with application complexity (APP) and requirements uncertainty (REQ).

This research probes into the largely unexplored interactions between CRM CR, UI, APP and REQ. Using these parameters, this model successfully predicts CRM SQ and firm performance.

The purpose of this paper is to explore the different human factor characteristics that are emphasized when co-creating value through digital service capabilities.

Empirical data are gathered from two small companies that deliver digital services and products in business-to-business markets.

The study highlights the role and importance of human factors as reflected in employees’ customer orientation while delivering digital service capabilities. The role of human factors also changes during the digital service production process.

Developing digital service capability is positively associated with value co-creation, but it requires new skills: firms need to evaluate their mechanisms for supporting continuous learning about the properties of digital technologies. To the authors’ knowledge, this is the first study to focus on the role of human factors in in developing digital service capabilities.