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The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

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.