Young people’s behaviour intentions towards reducing PM2.5 in China: Extending the theory of planned behaviour

Ru, Xingjun; Qin, Haibo; Wang, Shanyong

doi:10.1016/j.resconrec.2018.10.019

Cited by 189 publications

(108 citation statements)

References 65 publications

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“…A large number of meta-analytic reviews have confirmed that individual BI and actual behavior can be well explained and predicted by TPB [26,27,28,29]. TPB is also used to investigate individual pro-environmental behavior, such as pollution reduction intention [20,30], choice of travel mode [31,32], energy-saving behavior [33,34,35], domestic waste sorting, and recycling behavior [36,37,38,39,40]. While exploring the influencing factors of an individual’s intention and behavior, these studies also confirm the applicability of TPB in the field of pro-environmental behavior.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

“…PMO can also significantly increase the proportion of interpretation variance in the original TPB model [31,35,51]. Ru et al [20] and Wan et al [18] added PMO to TPB to analyze young people’s intention to reduce PM2.5 and staff to classify takeaway waste. Their results show that PMO has a significant positive impact on pro-environmental BI.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

“…Although scholars such as Zhang et al [2] and Wan et al [18] conducted a survey to reveal the factors influencing students’ behavior of MSWS on university campuses in Beijing and Hong Kong, respectively, the scope of these studies is limited to college students. In fact, young people include mainly individuals between 15 and 30 years old [19,20], and this group has a broader range and a more decentralized education level than the college students group. Furthermore, young people include individuals of different genders, household registrations and income levels, and what is not yet clear is whether there are differences between different groups.…”

Section: Introductionmentioning

confidence: 99%

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Factors Influencing Young People’s Intention toward Municipal Solid Waste Sorting

Shen

et al. 2019

IJERPH

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With the rapid growth of urban economy and population in China, the output of municipal solid waste (MSW) has dramatically increased becoming a constant threat to residents’ living environment and health. The classification intention of residents plays a pivotal role in solving the problem of MSW disposal. While numerous studies have examined the classification behavior of MSW from the perspective of ordinary residents and households, few studies have attempted to understand young people’s sorting intention. The novelty of this research is to explore the determinants that affect young people’s intention toward municipal solid waste sorting (MSWS) by extending the predictive factors of environmental concern and personal moral obligation into the theory of planned behavior (TPB). A sample of 524 young respondents from Hebei Province in China were used to conduct a structural equation model (SEM) validation. The empirical results revealed that, according to the rankings of significance, personal moral obligation, perceived behavioral control, and subjective norm had positive influences on young people’s intention toward MSWS, while attitude and environmental concern did not. Furthermore, the multi-group comparison showed that, compared with the male and rural group, the intention of female and urban respondents to classify MSW was not affected by subjective norms. Some targeted managerial implications were ultimately proposed to promote young people’s intention toward MSWS. This study contributes to the existing knowledge system of MSWS by revealing the classification intention of young people as a group. The findings and implications provide the government with useful insights for encouraging young people to actively participate in MSWS.

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Factors Influencing Young People’s Intention toward Municipal Solid Waste Sorting

Shen

et al. 2019

IJERPH

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“…Regarding sustainability and the environment, the TPB has been successfully applied in identifying the factors that determine sustainable behaviour in various fields: (a) Reducing contamination and natural resource conservation, such as the intentions to adopt a search engine that promotes sustainable water management [32], using biodiesel by car drivers [33] reducing fine particulate matter emissions [34] and willingness to pay for air quality improvement [35]; (b) recycling and reusing, such as people's intention to separate waste at home [36], reducing waste [37], recycling plastic waste [38], paper waste [39], electrical and electronic waste [40] and industry intentions to recycle food waste [41]; (c) purchasing intention of green products [42], traceable products [43], choosing a sustainable restaurant [15] and staying in green hotels [44].…”

Section: The Theory Of Planned Behaviourmentioning

confidence: 99%

About Intentions to Donate for Sustainable Rural Development: An Exploratory Study

Pérez

Egea

2019

Sustainability

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The Theory of Planned Behaviour (TPB) was used to investigate factors affecting the intention of citizens to donate money altruistically for sustainable rural development projects in Spain. To achieve this aim, individuals’ attitudes, subjective norms and perceived behavioural control have been considered; also, Azjen’s model was further extended to include additional elements: Moral norms, past behaviour, knowledge and some background factors. Respondents completed an online questionnaire assessing domains elaborated in the extended TPB model. Hierarchical multiple regression analysis revealed support for the model. Attitudes, injunctive norms, perceived behavioural control, moral norms, past behaviour, crowdfunding knowledge, age and employment condition were found to have positive and significant influence on intentions to donate. Theoretical and applied implications of the results are discussed, highlighting important considerations for public policy.

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“…To reduce the social desirability bias, we assured the respondents that their personal information was strictly confidential (Ru, Wang, & Yan, 2018; Wang et al ., 2020). Meanwhile, we also told them that their responses would only be used for research purpose and the data would be kept private (Ru, Qin, & Wang, 2019; Shi, Wang, & Zhao, 2017; Sun & Wang, 2020).…”

Section: Methods and Datamentioning

confidence: 99%

Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era

Wang¹,

Yu²,

Hu³

et al. 2020

Brit J Educational Tech

Self Cite

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The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the penetration rate of intelligent tutoring systems and the enthusiasm of faculty to use are still relatively low. This research examined the determinants of the willingness of faculty to use intelligent tutoring systems. Innovation diffusion theory was the theoretical basis of this research and it was adapted by incorporating perceived trust and experience. To gather data, a cross‐sectional questionnaire survey was performed and structural equation modeling was employed to analyze the data. The findings indicated that relative advantage, compatibility, perceived trust and experience are the contributing determinants of the willingness of faculty to use intelligent tutoring systems, while complexity has no significant effect. Meanwhile, complexity is significantly negatively affected by experience and compatibility. Relative advantage is significantly positively affected by perceived trust but not by complexity. Based on the research findings, relevant recommendations for encouraging faculty to use intelligent tutoring systems were proposed.

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Young people’s behaviour intentions towards reducing PM2.5 in China: Extending the theory of planned behaviour

Cited by 189 publications

References 65 publications

Factors Influencing Young People’s Intention toward Municipal Solid Waste Sorting

Factors Influencing Young People’s Intention toward Municipal Solid Waste Sorting

About Intentions to Donate for Sustainable Rural Development: An Exploratory Study

Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era

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