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This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

Exploring the determinants of a winery brand reputation (BR) and how those determinants interact is vital for the sustainable development of wineries as well as the growth of the wine industry as a whole. This study aims to test an integrated model to better understand the observed measurement constructs of winery brand reputation, including collective reputation (CR), wine label (WL), expert opinion (EO), social media advertising (SMA) and consumer wine knowledge (CWK).

In-depth interviews, an expert panel review and a pilot study were conducted to examine and improve the observed variables. A questionnaire survey was conducted as the main data source for the study. A total of 616 valid questionnaire responses were collected from 102 cities in mainland China and Hong Kong, Macao and Taiwan from December 2021 to April 2022. Structural equation modeling was conducted for the data analysis.

This study supported 9 of the 18 proposed theoretical hypotheses. WL, EO and SMA had positive effects on BR. CWK was found to have a moderating effect on the relationship between expert opinions/social media advertising and brand reputation.

The results of this study can guide wine practitioners, researchers and administrators in brand development, label regulation and consumer education.

To the best of the authors’ knowledge, this is the first attempt to examine the determinants of winery brand reputation among Chinese wine consumers. This study explains the mechanism of winery brand reputation, demonstrating the dynamics and effects of the observed measurement constructs on brand reputation.