Integrating the protection motivation model with place attachment theory to examine rural residents’ intentions toward low-carbon behaviors: Empirical evidence from Iran
{"title":"Integrating the protection motivation model with place attachment theory to examine rural residents’ intentions toward low-carbon behaviors: Empirical evidence from Iran","authors":"Ali Mokhtari Karchegani , Moslem Savari","doi":"10.1016/j.rineng.2025.107180","DOIUrl":null,"url":null,"abstract":"<div><div>The continuous rise in carbon emissions has intensified climate change, generating widespread concern across all sectors of society. Although rural areas are typically regarded as less industrialized, they contribute substantially to carbon emissions through traditional practices such as deforestation and biomass burning. Existing research identifies Protection Motivation Theory (PMT) as one of the predominant frameworks for understanding low-carbon behavior. However, PMT does not account for the significance of individuals’ emotional ties to place, conceptualized by Place Attachment Theory (PAT), which can provide critical insights into the behavioral intentions of rural populations. To address this gap, the study aimed to develop an extended PMT model incorporating PAT as an additional construct. This research employed a questionnaire survey and utilized structural equation modeling (SEM) for analysis. The study targeted all villagers in Sistan and Baluchestan province, Iran. Following the Krejcie and Morgan (1970) sampling table, a sample of 383 individuals was selected through a multistage stratified cluster sampling method. Data analysis was conducted using the PLS-SEM approach. The findings revealed that the original PMT model accounted for only 59.9 % of the variance in villagers’ intentions to engage in low-carbon behaviors, whereas the extended PMT model, incorporating PAT, enhanced the explanatory power by an additional 27.7 %. The theoretical framework established in this study offers a valuable reference for future investigations into the low-carbon behavioral intentions of rural populations. Moreover, the insights gained can assist policymakers in designing effective conservation policies that align with local community values while safeguarding environmental and social well-being.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107180"},"PeriodicalIF":7.9000,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590123025032359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The continuous rise in carbon emissions has intensified climate change, generating widespread concern across all sectors of society. Although rural areas are typically regarded as less industrialized, they contribute substantially to carbon emissions through traditional practices such as deforestation and biomass burning. Existing research identifies Protection Motivation Theory (PMT) as one of the predominant frameworks for understanding low-carbon behavior. However, PMT does not account for the significance of individuals’ emotional ties to place, conceptualized by Place Attachment Theory (PAT), which can provide critical insights into the behavioral intentions of rural populations. To address this gap, the study aimed to develop an extended PMT model incorporating PAT as an additional construct. This research employed a questionnaire survey and utilized structural equation modeling (SEM) for analysis. The study targeted all villagers in Sistan and Baluchestan province, Iran. Following the Krejcie and Morgan (1970) sampling table, a sample of 383 individuals was selected through a multistage stratified cluster sampling method. Data analysis was conducted using the PLS-SEM approach. The findings revealed that the original PMT model accounted for only 59.9 % of the variance in villagers’ intentions to engage in low-carbon behaviors, whereas the extended PMT model, incorporating PAT, enhanced the explanatory power by an additional 27.7 %. The theoretical framework established in this study offers a valuable reference for future investigations into the low-carbon behavioral intentions of rural populations. Moreover, the insights gained can assist policymakers in designing effective conservation policies that align with local community values while safeguarding environmental and social well-being.