Applying the health action process approach model (goodness) in explaining micro savings behavior

سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 47

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شناسه ملی سند علمی:

JR_IJNAA-15-12_003

تاریخ نمایه سازی: 17 تیر 1403

چکیده مقاله:

In this research, the fit of the model according to the GOF criterion shows a strong fit for this model. Also, based on the standardized root mean square residual index (SRMR), which has recently become more preferred, the acceptable fit of this model has been confirmed. The findings showed that firstly, there is a significant correlation between the constructs of the health action process approach model and micro-savings behavior among the study participants. Secondly, the constructs of action self-efficacy, outcome expectations and risk awareness were able to predict ۶۲% of the variance of behavioral intention, and also, the intention with the mediation of planning together with maintenance self-efficacy and recovery self-efficacy, ۵۹% of the behavior variance. They predicted small savings. Conclusion: In this study, we found that intention, action self-efficacy, planning and self-efficacy play a role as the most important determining factors in the adherence to savings in the target community. It was found that HAPA is useful in determining the predictors of adherence to savings among people. It is promising to design intervention programs to improve the level of adherence to savings by considering these factors. Macro policymakers and market leaders, especially financial businesses, should focus on the self-efficacy and planning of people in designing such interventions so that they can change the financial behavior of customers for the benefit of savings for themselves and their customers.

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نویسندگان

Sajjad Khazaei

Department of Business Management, Faculty of Management and Economics, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran

Hosein Vazifehdust

Department of Business Management, Faculty of Management and Economics, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran

Mohammad Bameni Moghadam

Department of Statistics, Faculty of Mathematics and Computer Statistics, Allameh Tabatabai University, Tehran, Iran

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