Expected Impact of Adoption Precision Agriculture in Algeria According to Algerian Agricultural Engineers

2.1 Research framework and hypotheses

The implementation of precision agriculture can be explained through a comprehensive theoretical framework that combines the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT).

This hybrid methodology offers a comprehensive framework to analyze the factors influencing technological adoption in agricultural settings.

1. Technology Acceptance Model (TAM): The TAM asserts that the adoption of new technologies is fundamentally influenced by two cognitive factors: Perceived Usefulness (PU), which measures the extent to which a technology improves performance, and Perceived Ease of Use (PEOU), which indicates the level of effort required for its implementation. These constructs influence engineers' beliefs on adoption, which in turn affects their behavioral intentions and actual adoption behavior.
2. Innovation Diffusion Theory (IDT): IDT broadens the adoption framework by highlighting the significance of innovation attributes, such as compatibility (congruence with established values and practices), complexity (perceived ease of use), trialability (capacity for experimentation with the technology), and observability (visibility of outcomes). These variables collectively affect the speed and probability of adoption among various user demographics.
3. Integrated TAM-IDT Framework: The proposed model integrates TAM and IDT principles to offer a thorough explanation of PA adoption. TAM's Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) encapsulate the cognitive assessment of a technology's usefulness and usability, whereas IDT's compatibility, complexity, trialability, and observability pertain to the perceptual evaluation of innovation characteristics.

In this context, Behavioral Attitude characterized as the engineer's perceived significance of adapting to precision agriculture functions as a vital mediator connecting these perceptual elements to actual adoption results.

This model posits that the adoption of precision agriculture is dependent on the interaction of perceived advantages, compatibility with existing agricultural methods, ease of implementation, and the visibility of results, with Behavioral Attitude serving a crucial mediating function.

Research hypothesis

Based on the empirical coefficients illustrated in the structural model (Figure 1), the following hypotheses are established to examine the interactions within the integrated TAM-IDT framework:

TAM-oriented Hypotheses:

- H1: Perceived Utility (PU) positively influences Engineers Behavioral Attitude toward the adoption of Precision Agriculture.

- H2: Perceived Ease of Use (PEOU) positively influences Engineers Behavioral Attitude toward the adoption of Precision Agriculture.

- H3: Perceived Utility (PU) exerts a direct beneficial influence on the opinion about the future increase of the adoption of Precision Agriculture.

- H4: Perceived Ease of Use (PEOU) exerts a direct beneficial influence on the future increase in the adoption of Precision Agriculture.

Hypotheses based on IDT:

- H5: Compatibility positively affects engineers' behavioral attitude towards the adoption of Precision Agriculture.

- H6: Compatibility exerts a beneficial influence on the opinion about the future increase of the adoption of Precision Agriculture.

- H7: Complexity adversely affects engineers’ behavioral attitude towards the adoption of Precision Agriculture.

- H8: Complexity adversely affects engineers on the opinion about the future increase of the adoption of Precision Agriculture.

- H9: Trialability positively affects engineers’ behavioral attitude towards the adoption of Precision Agriculture.

- H10: Trialability positively affects engineers on the opinion about the future increase of the adoption of Precision Agriculture.

- H11: Observability has a good effect on engineers' behavioral attitude towards the adoption of Precision Agriculture.

- H12: Observability exerts a beneficial influence on the opinion about the future increase of the adoption of Precision Agriculture.

Attitude as a mediating factor:

- H13: The behavioral attitude of Engineers positively impacts on the opinion about the future increase of the adoption of Precision Agriculture.

This hypothesis will be empirically evaluated using structural equation modeling and statistical analysis.

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Figure 1. Theoretical framework

Source: The Researcher

2.2 Research method

This research was performed from June to September 2020 among Algerian agricultural experts possessing either an engineering or a master's degree in disciplines like crop production, plant protection, soil and water management, agricultural machinery, and agricultural economics.

A total of 1,503 engineers were contacted via multiple channels, including direct interviews with professionals from national and regional agricultural institutions, telephone communication organized by the National Institute of Extensive Crops, and email correspondence with agricultural directorates and consultancy firms. Further outreach was conducted via professional networks encompassing universities, research institutions, and private enterprises, in addition to verified contacts on LinkedIn, Twitter, and Facebook.

Of all those approached, 563 consented to participate. Following the application of eligibility criteria and the exclusion of incomplete replies, 329 valid questionnaires were retained for analysis. The sample size was deemed representative of the national population of agricultural engineers (162,565), satisfying the criteria of a 5% margin of error and a 95% confidence level.

The survey instrument comprised 22 items examining factors that affect the adoption of precision agriculture technologies. The questionnaire underwent evaluation by academic specialists for clarity and comprehensiveness, followed by a pilot test with engineers from Sidi Bel Abbes to enhance the items. The completed instrument exhibited robust reliability, evidenced by a Cronbach’s Alpha of 0.916. The Cronbach’s alpha coefficients for the variables are presented in Table 1. Data were analyzed with SPSS software (version 26), employing both descriptive and inferential statistical methods to evaluate the research hypotheses.

In Table 1, content validity was additionally corroborated by professional evaluations from professors at the University Djilali Liabes (Sidi Bel Abbes) and the University Ibn Khaldoun (Tiaret).

Table 1. Cronbach’s alpha coefficients for research variables

Source: The Researcher

A comprehensive review of the literature on precision agriculture was conducted, encompassing its conceptual frameworks, international adoption patterns, and associated impact.

A survey was then developed to assess the perception of Algerian agricultural engineers regarding the feasibility of these frameworks within the Algerian agricultural context. The survey also solicited their viewpoint on the significance of adopting precision agriculture and their future outlook on its potential in Algeria.

The results indicated that Algerian agricultural engineers consider it imperative to adopt precision agriculture in Algeria, perceiving it as a future-oriented development. The positive impacts of precision agriculture, as categorized by respondents, were grouped into five overarching groups.

4.1 Improvements in economic efficiency and productivity

The most significant effects, as perceived by Algerian agricultural engineers, are those on productivity and profitability.

They anticipate that precision agriculture will lead to an expansion in the area cultivated of agricultural land being cultivated, in accordance with the perspectives articulated by agricultural engineers in the Islamic Republic of Iran in the study undertaken by Tohidyan Far and Rezaei-Moghaddam [7].

The study by Koutsos and Menexes [8] also supports this claim, as it found that American agricultural producers have a favorable attitude towards precision agriculture. According to their research, precision agriculture will increase the profitability of Algerian agriculture. This assertion is further substantiated by the findings of Fabiani et al. [6], who demonstrated that precision agriculture leads to a reduction in production costs. This claim is corroborated by the studies of Lowenberg-DeBoer [9] and McBratney et al. [10].

These studies also posit that precision agriculture facilitates agricultural work, in accordance with the results of Thompson et al. [11] in their study on the perceptions of agricultural producers. Furthermore, the results of Groher et al. [12] demonstrate that the adoption of precision agriculture This adoption has been shown to reduce the physical demands of agricultural work and to decrease the time required for its execution [13]. The utilization of agricultural robots has also been demonstrated to reduce the time required for agricultural work [14].

The development of a database to monitor the condition of the land and the effects of the different agricultural works is one of the effects mentioned by the Algerian agricultural engineers, and it is an effect to which they refer [14].

4.2 Ecological factors and resource optimization

Parihar et al. [15] demonstrated in their study on the effect of precision agriculture that it leads to efficiency in water consumption, while Jochinke et al. [16] demonstrated that it increases the efficiency of pest, disease and weed control. Algerian agricultural engineers identified the reduction of water use as the most significant impact on this axis, with the efficiency of disease and pest management and control and the efficiency of weed control ranking second and fourth, respectively.

The preservation of surface and groundwater, along with their reduction in pollution, was identified as the second most significant impact. This finding aligns with the results reported in the study by Tohidyan Far and Rezaei-Moghaddam [7].

The preservation of soil from pollution, erosion, and compression ranked fifth. This finding is in line with the studies conducted by Ahmad and Mahdi [17]. The list of impacts continues with similar findings, as outlined in the work by Bora et al. [18].

4.3 Chemical use and environmental impact

Numerous studies have indicated the role of precision agriculture and its techniques in increasing the efficiency of fertilizer and pesticide use. For instance, a study by Cao et al. [19] examined the role of precision agriculture in increasing the efficiency of fertilizer use even in small fields. Similarly, a study by Jensen et al. [20] explained its effect on reducing fertilizer use, and study of Koutsos and Menexes [8] shows that precision agriculture increases the efficiency of agricultural pesticide use, and Batte and Ehsani [21] demonstrated the benefit of using precision pesticide spraying machines in reducing the cost of agricultural inputs.

The Algerian agricultural engineers identified the enhancement of fertilizer efficiency as the primary effect in this axis, the augmentation of pesticide efficiency as the secondary effect, and the reduction in input costs as the tertiary effect.

4.4 Impact on the efficiency of agricultural machinery

The Algerian agricultural engineers identified the reduction in the depreciation rate of agricultural machinery as the most significant effect in this axis, and Gusev et al. [22] noted a comparable effect, while they regarded the enhancement in the efficiency of energy consumption as the secondary effect. In this axis, Bora et al. [18] identified a similar effect in their study, while the reduction of greenhouse gas emissions was the third effect in this axis, as Ahmad and Mahdi [17] indicated.

4.5 Socio-economic impacts and social equity

Ofori and El-Gayar [23] indicated through their analysis of publications about precision agriculture on social media platforms that the attitude towards it is positive among young people, as they indicated that it can lead to an increase in the number of jobs, while Tohidyan Far and Rezaei-Moghaddam [7] indicated that agricultural engineers in the Islamic Republic of Iran believe that precision agriculture has a positive impact on immigration and workers' income.

In contrast, Algerian agricultural engineers identified the increasing trend of youth entering the agricultural sector as the most significant impact of precision agriculture in this axis. The impact of precision agriculture in reducing internal migration was ranked second, followed by the impact on increasing workers' income in third place. The impact of limiting migration abroad was ranked fourth, and the impact of increasing job opportunities in the center was ranked fifth.

4.6 Comprehensive education and practical training

Adoption of precision agriculture technology integrates effortlessly into existing farming operations, reducing disruption while enhancing established values and practices. Which highlighting the necessity for explicit demonstrations of concrete advantages, including enhanced efficiency, financial returns, and sustainability improvements. Training programs, demonstration farms, and extension services can function as essential tools to enhance behavioral attitudes by rendering the benefits apparent and relatable. Technology vendors must build solutions that correspond with local agricultural systems and articulate their benefits clearly to mitigate adoption reluctance. The image demonstrates that the transition from perception to adoption is not merely technological but also behavioral, necessitating interventions that address both engineers practical requirements and psychological motivations.