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This paper aims to examine how customer participation in new service development (NSD) and customer relationship management (CRM) technology can improve the NSD performance of manufacturing firms. Additionally, the paper examines CRM technology usage to understand how it impacts new service performance both individually and jointly with customer participation in NSD.

This study is a survey of 216 manufacturing managers who are overseeing the development of new services at their organizations. For the analysis, structural equation modeling is used with Amos 22.0. Measures of all latent variables in the analysis pass the traditional tests for reliability, convergent validity and discriminant validity. Furthermore, the results of a common latent factor test for common method variance and Harman’s one-factor test indicate that common method bias is not a source of endogeneity in the model.

Customer participation has a positive effect on NSD performance. CRM technology usage also has a positive effect on NSD performance. The effect of customer participation on NSD performance is enhanced by CRM technology. The results of a post hoc analysis suggest that the usage of CRM technology has the most benefit for managing the technical aspects of customer participation.

This study has methodological limitations that may impact the generalizability of results. For instance, it is based on cross-sectional self-reported survey data, which is more subjective than longitudinal secondary data. Survey research lacks the depth and nuance of qualitative research designs, which are commonly employed to study NSD. In addition, this study focuses on large US manufacturing firms. The authors do not include small firms or international organizations in the sample. Despite these limitations, they believe the findings can provide significant contributions to the NSD literature.

Although prior research has shown that customer participation and CRM technology can individually influence new product development (NPD) performance, the results indicate they are equally effective factors in the development of new services. Furthermore, the authors show that customer participation can be enhanced via the use of CRM technologies. The interaction is more pronounced within the technical aspects of NSD.

This study contributes to the NSD literature, and it also has implications for managers leading NSD efforts in traditional tangible-product industries. The findings provide additional evidence that customer participation is an effective NSD strategy for manufacturing firms (Morgan et al., 2019). Furthermore, CRM technology is integral to NSD performance. CRM technology not only has a direct effect on NSD performance, but the interaction term of customer participation by CRM technology also has a positive effect on NSD performance.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.