*4.3. Factors Predicting the Rural Residents' Motivations Towards Deforestation*

**Control Beliefs (cbi) x Power of Control Factors (pci) Correlations Coefficients (r) Β—Coefficients t-Values**  Legislations insufficient x without legislation 0.501 \*\* 0.401 \*\* 5.425 Training of personnel unsuited x without proper training 0.405 \*\* 0.170 \*\* 2.305 \*\* significant for *p* ≤ 0.01. *4.3. Factors Predicting the Rural Residents' Motivations Towards Deforestation*  The components of the theory of planned behavior—attitude, DN, and perceived The components of the theory of planned behavior—attitude, DN, and perceived behavior control—had shown strong associations with behavioral intention. Furthermore, the sums of all three products (∑bie<sup>i</sup> , ∑nbimci, and ∑cbip<sup>i</sup> ) had a positive correlation with behavioral intention. Since all the variables had positive Pearson 's correlation coefficients with behavioral intention (significant level of all variables = *p* ≤ 0.01), none of the variables was excepted from the linear regression analysis that was proposed to explain the behavioral intention (Table 6).

behavior control—had shown strong associations with behavioral intention. Furthermore, **Table 6.** TPB (Theory of planned behavior) model explaining the Pearson's correlation coefficients.


\*\* significant for *p* ≤ 0.01. \* significant for *p* ≤ 0.05.

**BI** 3.32 0.740 1.000

**ATT** 3.53 0.621 0.611 \*\* 1.000 **∑bsioei** 11 2.388 0.276 \*\* 0.413 \*\* 1.000 **DN** 3.14 0.770 0.511 \*\* 0.326 \*\* 0.222 \*\* 1.000 **∑dnbiirwi** 10.00 4.211 0.508 \*\* 0.359 \*\* 0.333 \*\* 0.455 \*\* 1.000 **PBC** 3.29 0.785 0.539 \*\* 0.334 \*\* 0.113 \* 0.391 \*\* 0.204 \*\* 1.000 **∑cbipci** 11.442 3.067 0.458 \*\* 0.291 \*\* 0.310 \*\* 0.197 \* 0.381 \*\* 0.508 \*\* 1.000 \*\* significant for *p* ≤ 0.01. \* significant for *p* ≤ 0.05. Through the evaluation of multiple linear regression, all possible models to explain Through the evaluation of multiple linear regression, all possible models to explain behavioral intention were examined. (Table 7). "The standardized regression coefficients (and t-values) of so-called basic model, having as explanatory variables attitude, descriptive norm, and perceived behavioral control, demonstrated that all of three variables had high explanatory power in behavioral intention variation. The basic model was also statistically significant (*<sup>p</sup>* <sup>≤</sup> 0.01) and explained 56% (R<sup>2</sup> = 0.552) of the total variation of the intention".

behavioral intention were examined. (Table 7). "The standardized regression coefficients


However, attitude was the most powerful component to explain the behavior intentions with highest β = 0.436, followed by descriptive norms β = 0.256 and perceived behavioral control β = 0.295 (Figure 7). *Sustainability* **2021**, *13*, x FOR PEER REVIEW 13 of 18

**Figure 7.** β-coefficient explaining the factors affecting behavioral intention. **Figure 7.** β-coefficient explaining the factors affecting behavioral intention.

**5. Discussion**  Ajzen's theory of planned behavior suggests that attitude, norms, and perceived Other analyzed models had the explanatory power in explaining the total variation of the behavioral intention (R<sup>2</sup> ranking between 0.576 and 0.343).

### behavioral control are better predictors to explain an individual's behavior [51]. In this **5. Discussion**

research, a preliminary exploration of behavior toward economic incentive for deforestation in the study region was conducted using the theory of planned behavior as a framework for structuring our analysis. The findings of the study suggest that the level of education influenced respondent's behavioral intention to deforest for economic incentive. The present study explored that attitude, descriptive norm, and perceived behavior control may be good predictors to investigate the behaviors. The analysis of the regression models has demonstrated that attitude was the major factor to explain behavioral intention. Perceived behavioral control was followed closely Ajzen's theory of planned behavior suggests that attitude, norms, and perceived behavioral control are better predictors to explain an individual's behavior [51]. In this research, a preliminary exploration of behavior toward economic incentive for deforestation in the study region was conducted using the theory of planned behavior as a framework for structuring our analysis. The findings of the study suggest that the level of education influenced respondent's behavioral intention to deforest for economic incentive. The present study explored that attitude, descriptive norm, and perceived behavior control may be good predictors to investigate the behaviors.

by descriptive norms, which verified the high power of influence. The PBC generally has the characteristic of high power, which is confirming by the other studies [73–79]. Besides these components, intention to deforest with small-scale agriculture was also high because of unsuited law effort in the region. With regards to belief-based evaluation, the major item explaining the attitude was food for family, followed by an increased livelihood. In the context of Pakistan, the The analysis of the regression models has demonstrated that attitude was the major factor to explain behavioral intention. Perceived behavioral control was followed closely by descriptive norms, which verified the high power of influence. The PBC generally has the characteristic of high power, which is confirming by the other studies [73–79]. Besides these components, intention to deforest with small-scale agriculture was also high because of unsuited law effort in the region.

influence of these two factors is due to rural residents' reliance on natural resources. Interestingly, *tourism* was not perceived as an important factor. This could be due to mostly residents want to focus on agricultural activities and especially on family food. Descriptive norms were highly influenced by the respondent's behavior toward other people. Unlike other studies that stated perceived behavioral control might be a good predictor of behavior (e.g., [80–83], we found that people's perception of law enforcement did not affect their behavior. Rural resident's view of law enforcement might not be sufficient to avoid negative behavior, as the activities carried out involve the use of resources vital to the livelihoods of local communities [9,84–86]. Regarding that most rural residents are involved in agrarian activities, their main complaint was that they were prohibited from substituting secondary forests for small-With regards to belief-based evaluation, the major item explaining the attitude was food for family, followed by an increased livelihood. In the context of Pakistan, the influence of these two factors is due to rural residents' reliance on natural resources. Interestingly, *tourism* was not perceived as an important factor. This could be due to mostly residents want to focus on agricultural activities and especially on family food. Descriptive norms were highly influenced by the respondent's behavior toward other people. Unlike other studies that stated perceived behavioral control might be a good predictor of behavior (e.g., [80–83], we found that people's perception of law enforcement did not affect their behavior. Rural resident's view of law enforcement might not be sufficient to avoid negative behavior, as the activities carried out involve the use of resources vital to the livelihoods of local communities [9,84–86].

scale agriculture, which impeded their work and livelihood. This feeling was expressed in negative attitudes toward forest conservation, as well as negative behavior, as some of the residents replacing secondary forests with small-scale farming. Regarding that most rural residents are involved in agrarian activities, their main complaint was that they were prohibited from substituting secondary forests for smallscale agriculture, which impeded their work and livelihood. This feeling was expressed in

Deforestation by residents of the area is a great challenge for forest management

the livelihoods of inhabitants.

negative attitudes toward forest conservation, as well as negative behavior, as some of the residents replacing secondary forests with small-scale farming.

Deforestation by residents of the area is a great challenge for forest management because reconciling land use and preservation of ecosystems inside the region requires a preventative measure to ensure the protection of remaining fragments without affecting the livelihoods of inhabitants.

The current research did not deal with all of the theory of planned behavior components (particularly, exclude the actual behavior and SN and explore the general element of PBC and DN related to the economic incentive for deforestation), attempting to prevent the use of the basic theory of planned behavior framework and complete analysis of structural equations modeling or multivariate regression. However, it identifies areas to be addressed by forestry managers to change the behavior of residents in relation to important conservation issues of deforestation.

There should be a prosecution of corrupt government officials in charge of the forestry laws and policies along with illegal loggers. Environmental awareness should be made accessible to the general public about the devastating consequences of deforestation on people and society at large. The government should embark on a program of tree planting by enlightening the public to fathom that we have only one earth. Government, Nongovernmental organizations, and spirited individuals should organize an enlightenment program on the impacts of climate change. The government should add more effort to the poverty eradication program, and the educated unemployed youths should be accorded employment. To curb the rate of deforestation, a skills training system should be coordinated for rural women dwellers and the uneducated youth. In conclusion, therefore, it is necessary to recognize and introduce successful ways of addressing the daily needs of the communities. The emphasis needs to be placed on seeking alternative energy sources, sustainable agricultural practices, diversifying income sources, and supporting rural development for young people and disadvantaged community members. In order to allow communities to engage actively in decision-making processes aimed at conserving the forest and improving the livelihoods of rural communities, forestry education and extension should be geared toward institutional strengthening at the local level.

### **6. Conclusions**

The economic benefits include the provision of subsidies for forest products, an enhanced system of taxes on exploited forest goods, the procurement of well-monitored hunting licenses, alternative job opportunities, credit provision, and a limited ban on round log exports in northern areas of Pakistan. The study suggests that the level of education influenced the respondent's behavioral intention to deforest for economic incentive. The attitude, descriptive norm, and perceived behavior control may be good predictor to investigate the behaviors. Besides these components, the intention to deforest with small-scale agriculture was also high because of unsuited law efforts in the region. As far as outcome evaluation is concerned, 94% of the participants perceived that provide food to family is an important or very important component of livelihood. Socio-economic factors that affect the forest, such considerations are profoundly rooted in the everyday needs of the communities as regards forest products that meet the increasing population rather than knowledge of the degradation and its implications of forest resources.

However, insufficient legislation demonstrated a major factor that is affecting the perceived power of control. Both the Pearson correlation coefficient and the regression analysis demonstrated that insufficient legislation as well as unsuited training demonstrates that Human activities are environmentally hazardous in combination with our daily work and actions at home, in industry, and even in agriculture, endanger the stability of the climate and the ecological balance. All these human actions endanger nature. Adequate economic incentives can be an important tool for reducing deforestation.

**Author Contributions:** S.U., A.A., R.S.N. and M.M.W. conceptualized the idea of the study design; R.S.N. and W.A. contributed to data collection and formal analysis; S.U., A.A. and R.S.N. performed the statistical analysis and wrote the manuscript; S.U., R.S.N. and M.M.W. edited and reviewed the manuscript; T.G. supervised and gave the conceptual insight. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study has not received any funding.

**Acknowledgments:** Authors acknowledge the efforts of Central Karakoram National Park and staff for helping in data collection.

**Conflicts of Interest:** The authors declared no conflict of interest.
