product adoption
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Author(s):  
Zhu Zhang ◽  
Xuan Wei ◽  
Xiaolong Zheng ◽  
Qiudan Li ◽  
Daniel Dajun Zeng

Detecting product adoption intentions on social media could yield significant value in a wide range of applications, such as personalized recommendations and targeted marketing. In the literature, no study has explored the detection of product adoption intentions on social media, and only a few relevant studies have focused on purchase intention detection for products in one or several categories. Focusing on a product category rather than a specific product is too coarse-grained for precise advertising. Additionally, existing studies primarily focus on using one type of text representation in target social media posts, ignoring the major yet unexplored potential of fusing different text representations. In this paper, we first formulate the problem of product adoption intention mining and demonstrate the necessity of studying this problem and its practical value. To detect a product adoption intention for an individual product, we propose a novel and general multiview deep learning model that simultaneously taps into the capability of multiview learning in leveraging different representations and deep learning in learning latent data representations using a flexible nonlinear transformation. Specifically, the proposed model leverages three different text representations from a multiview perspective and takes advantage of local and long-term word relations by integrating convolutional neural network (CNN) and long short-term memory (LSTM) modules. Extensive experiments on three Twitter datasets demonstrate the effectiveness of the proposed multiview deep learning model compared with the existing benchmark methods. This study also significantly contributes research insights to the literature about intention mining and provides business value to relevant stakeholders such as product providers.


2021 ◽  
Vol 13 (9) ◽  
pp. 5084
Author(s):  
Lan-Lan Wan ◽  
Hong-Youl Ha

Marketing literature emphasizes the importance of green product adoption for environmental sustainability. However, consumers’ evaluations of the key factors (for adopting green products) differ in critical ways. Drawing on a consumer–marketing interface, this study uses a binary logit model to investigate how consumers adopt two different types of products (e.g., glass and electronic). The results show that the impacts of the twelve factors behind consumer adoption of green products vary widely between glass and electronic products. Specifically, the analysis identifies four factors (eco-labeling, peer groups, cultural values, and environmental awareness) that have no influence on consumer adoption intentions. It also shows that males are more likely to have positive adoption intentions than females for both glass and electronic products. The authors conclude this paper by discussing the implications of these important findings for research and practice.


Author(s):  
Daoyan Jin ◽  
Hallgeir Halvari ◽  
Natalia Maehle ◽  
Christopher P. Niemiec

Curiosity has a powerful influence on consumer behaviour, and previous research has tended to focus on how curiosity affects the desire to obtain curiosity-relevant, unknown information. Yet an interesting question, which was the focus of the present research, concerns the effect of incidental curiosity on intention to obtain curiosity-irrelevant, unknown information. A set of three experiments provided systematic support for the hypotheses that incidental curiosity will increase the intention to obtain curiosity-irrelevant, unknown information (both product-related and self-related) in a way that is serially mediated by the perceived value of curiosity-relevant, unknown information and the perceived value of curiosity-irrelevant, unknown information. As such, this research offers important theoretical contributions to the literatures on curiosity and information ignorance, and it has implications for new product adoption and self-tracking behaviour.


2021 ◽  
Vol 251 ◽  
pp. 01080
Author(s):  
Han Pan ◽  
Wu Xin ◽  
Yuping Li

Beginning in the 1970s, academia began to study consumer innovation and used it as an important indicator for predicting consumers’ new product adoption behavior. This article makes a more comprehensive summary and evaluation of the definition of consumer innovation from three aspects (innate innovativeness; special fields innovativeness; actualized innovativeness), summarizes the relationship between the three innovations, and builds a consumer innovation integration model.


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