IMPACT OF ICTS USAGE ON SMALLHOLDER FARMER’S ADAPTATION STRATEGIES: A STRUCTURAL EQUATION MODELING STUDY IN NIGER STATE

The study was conducted in Kontagora Local Government Area of Niger State between June and August 2021. The objective of this study was to find out the impact of ICTs on adaptation strategies of the smallholder farmers. The study used a multiple-stage random sampling technique to randomly select 240 respondents. The levels were determined using frequency and percentages of summated scores by categorization into high moderate and low using range. The impacts of ICTs on adaptation strategies were determined using structural equation modeling (IBM SPSS Amos 20). The study revealed high-level adaptation strategies (M=3.69) and a moderate level of ICTs (M=3.51). The study also revealed the impact of ICTs on adaptation strategies. The impact of radio (β= 0.355, CR = 4.145, P =.001), mobile (β=.322, CR= 4.111, P=.000), television, (β=.211, CR=3.717, P=.000) on adaptation strategies were positive and statistically significant. The study recommended planned interventions should be undertaken to bring those responsible for adaptation policy and planning (particularly National Adaptation Plans) together with ICT/telecommunications agencies for more effective planning and implementation.


INTRODUCTION
The application of Information and Communication Technology (ICT) across different sectors of the global economy has become a game changer in boosting work efficiency and productivity.The agriculture sector in the global economy is one of the industries experiencing tremendous ICT application in all spheres of its operations.ICT is an umbrella term that includes radio, television, mobile phone, internet, etc.The ICTs increase productivity, access to markets, and adaptability to weather conditions in agriculture (Salampasis and Theodoridis, 2013).More effective interventions are needed in agriculture because rising food prices pushed over 40 million people worldwide into poverty since 2010 (Stein, 2011).The growing global population which is expected to reach 9 billion by 2050, has heightened the demand for food and placed pressure on already-resources (Ghose, 2014).Even after years of industrialization and growth in services, agriculture still accounts for one-third of the gross domestic product and three-quarters of employment in Nigeria (Obasan and Adediran, 2011).
Over 60 percent of the labour force in countries with per capita incomes in the range of US$ 400 to 1,800 range works in agriculture (World Bank, 2019).The arid-north region of Nigeria is already experiencing extreme heat and reduced rainfall as a result of climate change, while the Sahel region receives less than 10 inches of rain per year, which is 25% less than thirty years ago (Chukwuezie et al., 2016).According to the intergovernmental panel on climate change (IPCC) the situation might worsen by 2100, when worldwide rainfall will have decreased below 10%.The agriculture sector has experienced a new technological revolution for the past ten years (Ali et al., 2016).Compared to a decade earlier, this new technological revolution, has the potentials to respond to farmers' needs accurately and swiftly.Daum (2020) observed that in recent years, ICTs had become one of the main driving tools used by farmers to manage the essential factors of production in agriculture.ICT applications have the potential to identify and find solutions to some of the numerous problems faced in the field of agriculture, which includes prolonged droughts, pest and disease outbreaks, seasonality and spatial dispersion of farming; high transaction costs and information asymmetry (Anh et al., 2019).Information and communication technologies have had an increasing impact on economic and social development over the past two decades, resulting from their capacity to generate and disseminate information, to facilitate the coordination of different actors in and beyond government, and to make government, business, and development processes are more efficient (Ali et al., 2016).These three capacities are as relevant to climate change adaptation as they are to other fields.
However, the extent of experience in deploying ICTs for adapting to climate change is currently less than in other development fields, such as health and education (Creech & Parry, 2014).ICTs also have a complex relationship with sustainability and with the underlying cause of climate change (Papa et al., 2015).This relationship can be described in terms of the effects of ICTs.The ICTs can play an important role in increasing productivity through intensive agriculture (Rengaraj & Shibu, 2022).Conducting impact studies and sharing pilot project information is critical to success with ICTs as more specific lessons and impacts are learned (Wroński, 2019).The pace at which ICT application is growing in every sector of the world has triggered the development of different ICT applications in agro climatology to aid the rapid access to information by farmers.
The specific objectives of this study are to: determine the level of ICTs usage (mobile, radio, and television) and adaptation strategies; examine the impact of ICTs usage on smallholder farmers' adaptation strategies.

Research Framework
This study is based on the proposed framework shown in Figure 1.The framework considers the impact of ICTs (radio, mobile phone, and television) on adaptation strategies of smallholder The third stage, 4 wards were selected.In the fourth stage, 240 farmers were selected purposively who were using ICTs in farming activities as shown in Table 1 below: The data were collected through questionnaires and interview method.Firstly, the level of adaptation strategies was determined using frequency and percentages of summated scores by categorization into high moderate, and low range.The level of ICTs as perceived by individual farmers was to provide a true picture of what is on the ground at the time of conducting this study.In addition, the impact of predictor variables on the outcome variables (ICTs on adaptation strategies) was determined using structural equation modeling (IBM SPSS Amos 20).The first step was to evaluate the measurement model's validity, followed by a test of the structural model.Confirmatory factor analysis (CFA) was used in the first stage.Its purpose is to see if the measurement model is correct.The measuring model's validity must meet two criteria: acceptable degrees of Goodness-of-Fit (GOF) and construct validity (Hair et al., 2010).Some of the commonly used goodness-of-fit indices include normed Chi-square x 2 =d f, comparative fit index (CFI), adjusted goodness-of-fit index (AGFI), non-normed fit index (NNFI), goodness-of-fit index (GFI), normed fit index (NFI), parsimonious goodness-of-fit index (PGFI), the root mean square error of approximation (RMSEA), and.Standardized factor loadings, average variance extracted (AVE), and construct reliability are three construct validity metrics to consider (CR).
The structural model was estimated once the measurement model was validated.Running SEM and collecting the GOF indices using the same assessment criteria as CFA was the second stage.The path coefficients, as well as structural equation fit, were then interpreted (R 2 ).The goodness-of-fit indices for the model are X 2 = 1258.541,df = 624, p = 0.000, CFI = 0.915, RMSEA = 0.053 (90 percent confidence for RMSEA = 0.041-0.048)and normed x 2 = 2.13.CFI values of 0.9 are generally regarded as acceptable (Hair and Patel, 2014).The RMSEA should be between 0.03 and 0.08, and a normed Chi-square of 3 or less is associated with better fit (Hair et al., 2010).

Variable Measurement and Estimation Procedures
Structural equation modeling (SEM) was used to estimate the interrelationships among constructs in the conceptual model.Even though the focus was on the fundamental features of ICTs radio, mobile phone, and adaptation strategies.The goal of the estimation was to figure out the ICTs usage of farmers to gauge the impacts on adaptation strategies.Respondents were asked how they agreed or disagreed on a five-point Likert scale as indicated in Table 2.

Level of Adaptation Strategies
Table 1 indicates that the majority of the respondents were given more priority to irrigation as an adaptation practice towards climate change (M = 4.65), followed by cover coping (M = 4.50), drought-resistant varieties, and Organic matter all at moderate levels.Therefore, this can be attested that smallholder farmers had played a significant role in the use of adaptation practices towards climate change impact in the study area as the overall mean score signified a high level of adaptation strategies (M=3.96).This result is consistent with the previous findings of Jha et al. (2018) on the use of adaptation practices to cope with climate change impacts.(Gangopadhyay et al., 2019).The use of ICTs helps one to acquire necessary technical skills and knowledge towards a logical and progressive attitudinal change which may result in improved performance of farmers' productivity (Sima et al., 2020).
Mobile phones reduced the gap between farmers and extension research centers as he communicates directly with the extension agent on the issue of adaptation and other related agricultural practices.Chhachhar et al. (2014) revealed that the internet, mobile phones, radio, and television were the most important tools of communication providing knowledge and information to farmers about agriculture.3 show a good fit.All standardized factor loadings that are statistically significant should be at least 0.5 (Hair et al., 2010).This level of loading suggests that the observed indicators are strongly linked to the structures with which they are associated.It also contributes to construct validity (Hair et al., 2010).In our model, all standardized factor loadings are significant.The bulk of factor loadings are more than 0.5, CR stands for convergent validity.Strong reliability is indicated by a CR of 0.7 or higher.Most of the constructs in our model have CR values larger than 0.7.A CR of less than 0.7 is acceptable if the research is exploratory in nature (Hair & Patel, 2014).Average Variance Extracted (AVE) is another convergent validity indicator, and convergence is good when the AVE is 0.5 or more (Hair et al., 2010).The AVE values for all constructs in our model are greater than 0.5, as shown in Table 3, which is acceptable.The other relevant indicators (factor loadings) are within acceptable bounds, meaning that convergent validity is acceptable.Discriminant validity of the construct is achieved when the square root of the AVE is greater than the correlation between the constructs (Afthanorhan, 2014).The degree to which a test or measure diverges from (i.e., does not correlate with) another measure whose underlying construct is conceptually unrelated to it (Hair et al., 2010).
As depicted in Table.The structural model's results show that it fits well.The relative x 2 (Chisq/df) is 2.444 (achieved), which is below the acceptance level of 5.0; other fit indices include AGFI = 0.834 (not achieved), GFI = 0.834 (not achieved), CFI = 0.919 (achieved), IFI = 0.916 (achieved), TLI = 0.933 (achieved), and RMSEA = 0.638 (achieved).As previously stated (Hair et al. 2010).The goodness-of-fit indices of the correlation output structural model are shown in Table 5 below.CR = 4.145,P =.001;β=.322,CR= 4.111,P=.000;β=.211,CR=3.717,P=.000).The findings reliably support the conceptual model, with all estimated path coefficients being statistically significant.For our primary construct, adaptation strategies, the squared multiple correlations (R 2 ) is 56.1%.That signifies the important factors in our model can account for over 56.1% of the variation in adaptation strategies.In other words, the influence of the predictor variable on the outcome variable in this study has been confirmed.This revealed that radio was a favorite tool of communication which broadcasts many adaptation programs while television also contributed much in disseminating information about climate change adaptation as well in the area.Mobile phones reduced the gap between farmers and Extension Agents.Farmers got the latest information from the metrological department for weather conditions before taking any adaptation measures in their farms.
According to the findings of this study, the predictor variable has contributed to the outcome variable in a relative sense as shown in Table 6 below.More work is needed to engage strategically with the private ICT sector, to review where privately motivated interests in applications could directly or serendipitously enhance adaptation while also delivering commercial value.
(iii) The Government and NGOs should sensitize the farmers on the benefits of using ICTs and ICT education in the schools and colleges/universities should be made compulsory to address the shortage of ICT skills.Adaptation Plans should be seen as a window of opportunity for the inclusion of ICT-relevant interventions.Preparation for these should include a capacity-building programme to review where and how investments in ICTs might be best integrated.

Fig
Fig 2. Research Framework

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ii) Involve the private sector more extensively in planning and implementation: With Public-Private Partnership (PPP) ICT infrastructure should be developed across the country to ensure access to ICT technologies.Accessible telecoms and power infrastructure in rural areas should be developed to use ICTs in agriculture.

Table 2 . Indicator Variables in the Model Observed.
RD= Radio, MP=Mobile phone, TV= Television, AD= Adaptation

Table 3 : Factor loadings, Average Variance Extracted and Construct Reliability Constructs Items Factor Loading CR (Above 0.6) AVE (Above 0.5)
CR=Construct reliability, AVE= Average Variance Extracted

Table 4 . Discriminant Validity of the Constructs
Note:

Table 6
summarizes the results of the structural model with a structural path estimate of a significant effect of ICTs on adaptation strategies.The standardized coefficients are (β= 0.355,

Table 6 : Regression Results
In this respect, the current study concludes that smallholder's adaptation strategies towards climate change in Kontagora were encouraged due to exposure to ICTs which positively contributed towards smallholder adaptation practice.The ICTs created awareness to smallholder farmers on various adaptation practices towards climate change impact on farming activities.The identification of the importance of ICTs can enable the policymakers in creating climate change adaptation options.Therefore the following recommendation were made (i) Build capacity for integrating ICTs into national strategic adaptation plans: Planned interventions should be undertaken to bring those responsible for adaptation policy and