Zhengxiang Wu, Tingting Guo and Baoku Li
The purpose of this paper is to investigate the effect of framing idle item recycling appeals as gains or losses on influencing consumers' idle item recycling intention by…
Abstract
Purpose
The purpose of this paper is to investigate the effect of framing idle item recycling appeals as gains or losses on influencing consumers' idle item recycling intention by assessing the mediating role of perceived impact and the moderating role of product attachment.
Design/methodology/approach
In total, three experiments were conducted to gather data. The assumed hypotheses were verified using analysis of variance (ANOVA) and bootstrap analysis.
Findings
Study 1 illustrated that loss-framed messages are more persuasive than gain-framed messages for less-involved consumers in idle item recycling, whereas message framing shows no significant difference in more-involved consumers' intention. Study 2 suggested that perceived impact tends to increase less-involved consumers' recycling intention when the message is framed as loss. Study 3 demonstrated that less-involved consumers would react to idle item recycling messages when they are strongly attached to a product. Further, gain-framed messages are more efficacious than loss-framed messages in influencing more-involved consumers' recycling intention when they are strongly attached to a product.
Originality/value
Previous research focuses on promoting waste recycling behavior initiated by local, city or national governments. This study provides some of the first evidence on the influence mechanism of message framing on consumers' idle item recycling intention and offers insights into companies to develop effective advertising strategies for idle item recycling management.
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Keywords
Zibo Li, Zhengxiang Yan, Shicheng Li, Guangmin Sun, Xin Wang, Dequn Zhao, Yu Li and Xiucheng Liu
The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.
Abstract
Purpose
The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.
Design/methodology/approach
In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.
Findings
Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.
Research limitations/implications
With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.
Originality/value
Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.
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Yin Shi, Liping Ding, Chenchen He, Fan Zhang, Zumeng Zhang and Qiyao Dai
This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of…
Abstract
Purpose
This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of clean energy in China.
Design/methodology/approach
This study contained a sample of 653 households in 8 provinces/regions by stratified, and random sampling in rural China. Descriptive analysis, exploratory factor analysis and confirmatory factor analysis techniques have been used for analytical purposes.
Findings
The empirical results indicate that financial incentive and social interaction have positive effects on rural residents’ adoption willingness, while village leaders’ engagement can indirectly influence their adoption willingness through social interaction and residents’ cognition.
Research limitations/implications
This study mainly considers external and internal factors but ignores the effect of technical factors. In addition, the samples are just selected from the residents who have adopted solar PV.
Practical implications
This study is expected to be useful for the government, regulators, village leaders, village leaders and other institutions.
Originality/value
This study conducts a systematic analysis and clarifies the relationship between factors (external and internal) and rural residents’ adoption willingness. The village leaders’ engagement is first added to the conceptual model as an external factor, which is very essential in rural residents’ adoption in China.