Level Of Technology Adoption Research Articles

Green Agricultural Technology and Food Security: Implications for Nigeria

This study investigates the relationship between green agricultural technology adoption and food security in Nigeria, addressing a critical gap in understanding how sustainable agricultural practices can contribute to alleviating food insecurity in developing countries. Using a quantitative cross-sectional design, data were collected from 132 farmers across different agro-ecological zones in Nigeria. The study employed exploratory factor analysis and structural equation modeling to examine the factors influencing green technology adoption and their impact on food security. The results reveal a strong positive relationship between green agricultural technology adoption and food security levels (β = 0.29, p < 0.001). Adoption factors were found to have a significant positive effect on food security (β = 0.668, p = 0.012), underscoring the importance of addressing barriers to technology adoption. Interestingly, environmental factors showed a small negative effect on food security (β = -0.126, p = 0.039), suggesting potential short-term trade-offs between environmental sustainability and immediate food security needs. Four distinct factors influencing green agricultural technology adoption were identified: technology-specific aspects, environmental considerations, policy or institutional factors, and social or cultural aspects. These findings provide a comprehensive framework for understanding the complex dynamics of sustainable agriculture adoption in Nigeria. The study contributes to the growing body of literature on sustainable agriculture in developing countries and offers valuable insights for policymakers and practitioners. It highlights the potential of green agricultural technologies to enhance food security while also emphasizing the need for balanced approaches that consider both short-term food production needs and long-term environmental sustainability.

Economic Impact of Biotech and Nanotech Approaches in Chickpea (Cicer arietinum L.) Cultivation

Background: Chickpea cultivation plays a vital role in India's agricultural economy, yet it faces challenges like low yields, high input costs, and environmental concerns. Emerging biotechnological and nanotechnological approaches offer potential solutions to enhance productivity and sustainability in legume cultivation. This study evaluates the economic and environmental impacts of these technologies in comparison to conventional farming methods. Methods: A cost-benefit analysis was conducted for chickpea cultivation using both conventional and biotech/nanotech methods across key input categories. A regression model was developed to assess the impact of factors like farm size, irrigation access, and labour costs on profitability. Additionally, a scenario analysis was performed to project economic and environmental outcomes under varying levels of technology adoption. Results: Biotech/nanotech methods demonstrated a significant yield increase of 33% (1.6 tons/hectare vs. 1.2 tons/hectare), resulting in a 60% higher net return (₹48,800 vs. ₹30,500 per hectare). The cost-benefit ratio (CBR) improved from 2.03 (conventional) to 2.56 (biotech/nanotech). Environmental savings amounted to ₹1,800 per hectare through reduced pesticide and water usage. Scenario analysis showed that high adoption rates (90%) could lead to additional revenue of ₹17,000 per hectare and environmental savings of ₹16,200. These results indicate that biotech and nanotech approaches can significantly improve the economic and environmental sustainability of chickpea farming in India.

Technology adoption, competitiveness and new market access among SMEs in Ghana: What are the limiting factors?

A total of 300 SMEs including beneficiaries and non-beneficiaries of the Presidential Business Development Support initiative were surveyed in Ghana using structured interview questionnaires. The survey objectives were to (i) investigate the extent of adoption of emerging technologies including the Internet of Things (IoTs), Artificial Intelligence (AI), e-Commerce, Mobile Banking and Social Media among SMEs in Ghana; (ii) identify the main barriers to adoption of emerging technologies; and (iii) explore any association between the level of technology adoption by SMEs and access to new markets. Close to 60% of the beneficiary SMEs had adopted less sophisticated technologies such as social media, mobile banking and e-commerce as compared to 50% adoption among non-beneficiaries. Overall, less than 5% of the SMEs surveyed were using sophisticated technologies such AI and IoTs. This study adopted the Technological-Organizational-Environmental (TOE) framework to identify barriers to technology adoption. The top five barriers to technology adoption by the SMEs identified from this study are: (i) lack of finance, (ii) insufficient government support, (iii) lack of absorptive capability, (iv) insufficient demand and (v) poor technology enabling infrastructure. The beneficiary SMEs had better access to sub-regional (West Africa), regional (Africa) and international markets than the non-beneficiaries. Logit regression results showed that the most significant factors positively influencing technology adoption are Education, Marketing Skills, Human Resource Skills, Gender, Market Opportunities and Financial Improvement. There was a positive but weak correlation between technology adoption and access to new market opportunities.

Dampak Digitalisasi Terhadap Pertumbuhan UMKM di Negara Berkembang

Digitalization has become a crucial factor in enhancing the competitiveness and growth of Micro, Small, and Medium Enterprises (MSMEs) in developing countries, particularly within the ASEAN region. This study aims to explore the impact of digitalization on MSME growth in Indonesia, the Philippines, and Vietnam through a Systematic Literature Review (SLR) approach. These three countries were selected due to their substantial economic potential and evolving levels of technology adoption, yet each faces unique challenges in digital transformation. The study analyzes literature on the role of digitalization in improving market access, operational efficiency, and MSME financing, identifying key drivers and barriers specific to each country. Findings reveal that digitalization significantly contributes to enhancing productivity and sustainability for MSMEs, though challenges related to infrastructure, digital literacy, and regulatory frameworks present notable obstacles. This review aims to provide insights for policymakers and MSME stakeholders in optimizing digitalization strategies to foster economic growth in ASEAN.

The Non-Linear Impact of Industry 4.0 on Carbon Emissions in China’s Logistics Sector

This study investigates the impact of Industry 4.0 on carbon emissions within China’s logistics sector, focusing on its potential to support global carbon reduction goals. Utilizing panel data from 30 Chinese provinces between 2011 and 2019, this research employed an Industry 4.0 index alongside IPCC guidelines to estimate logistics emissions. Through fixed effects and dynamic panel models, this study indicated an inverted U-shaped relationship among the development of Industry 4.0 and carbon emission management. Industries move to emitting more pollution to provide their required needs to all but once technologies advance, drastic decreases in combustion and emissions take place as the industries move more towards conservation and the integration of information continues to improve. This study investigates the non-linear impact of Industry 4.0 on carbon emissions in China’s logistics sector. Utilizing panel data from 30 Chinese provinces between 2011 and 2019, the research employs a dynamic panel model to quantify the relationship between Industry 4.0 adoption and carbon emissions. The findings reveal an inverted U-shaped relationship, with emissions initially increasing by 10% at lower levels of technology adoption before decreasing by 15% as the Industry 4.0 index reached higher levels. This study provides empirical evidence supporting the strategic deployment of Industry 4.0 technologies to achieve sustainable logistics growth. Key policy implications and future research directions are discussed.

Estimating probability of default via delinquencies? Evidence from European P2P lending market

The unprecedented growth of the financial sector's digital transformation opens wide areas to the scaling up of finance in innovative and knowledge-based projects. Improving risk management takes centre stage in the acceleration of this process. This study uses loan-book data from the peer-to-peer (P2P) lending market to empirically investigate the determinants of default risk. Using the loan-book database covering the period from 2014 to 2020, we examine multiple factors related to the default risk of loans issued by P2P lending platforms. The results indicate that a higher interest rate and higher stock market returns increase the probability of default in the P2P lending market. Results are robust to additional tests based on endogeneity correction, the LASSO method and sampling bias. The severity of the impact of market returns and interest rates is found to be significantly different based on the levels of financial technology (FinTech) adoption and banking sector distress. Increases in the market interest rate are found to boost the sensitivity of P2P loan defaults to stock market volatility. This study contributes to existing literature on risk management models with its consideration of country-specific factors, paving the way to future best practices in the market.

Typologies of South African small-scale farmers and their risk perceptions: an unsupervised machine learning approach

PurposeSmall-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.Design/methodology/approachA cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.FindingsAccording to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.Originality/valueThis is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

Determinants Of Adoption Of Soil Conservation Technologies Among Smallholder Farmers In Izzi Local Government Area Of Ebonyi State, Nigeria

The study examined the determinants of adoption of soil conservation technologies among smallholder farmers in Izzi Local Government Area, Ebonyi State, Nigeria. Multistage sampling technique was used to select 160 respondents for the study. Data collected with the aid of structured questionnaire were analyzed using descriptive and inferential statistics. Results showed that farmers in the area had average age of 47 years and operated on 1.5 hectares of land with an average farm income of ₦152,125. Further analysis revealed that the smallholder farmers had an adoption index of 2.21 which implied that they used at least two (2) soil conservation technologies with an average source of information of 2.72 showing that they got information on soil conservation technologies from at least three different sources. Furthermore, results revealed erosion, deforestation, reduced soil fertility and indiscriminate bush burning as the forms of soil degradation existing in the area while adopted coping strategies were crop rotation, use of organic manure, intercropping practices, appropriate use of fertilizer, use of mixed cropping system and planting of trees. The results of OLS multiple regression analysis showed that the coefficient of multiple determination (R2 ) of the regression model was 0.760. This implies that seventy-six percent (76%) of the variations in level of soil conservation technology adoption were accounted for by the independent variables socio-economic characteristics of the smallholder farmers included in the model. The result of factor analysis identified social, institutional and economic factors as constraints militating against adoption of soil conservation technologies among the smallholder farmers in the study area. The rejected hypothesis concluded that there is a significant relationship between the socioeconomic characteristics of smallholder farmers and their adoption of soil conservation technologies in the area. Based on the findings, the study recommends; that local government authorities and NGOs working in areas that are prone to soil fertility losses should introduce programmes that will train and promote soil conservation technologies to be adopted by farmers to improve productivity; provision of Infrastructural facilities such as good road network to ensure easy movement of agricultural inputs to the farmers field; and Agricultural extension services which are saddled with the responsibility of disseminating timely, complete actionable information should be re-positioned and strengthened to ensure smallholder farmers access to information, through appropriate channels.

Pendampingan Penggunaan Layanan Perbankan Digital Pada Nasabah BANK BPD Bali Capem PUSPEM BADUNG

Abstract Assistance with Digital Banking Services Usage at Bank BPD Bali Capem Puspem Badung identifies low levels of digital technology adoption among customers as a major challenge. Despite Bank BPD Bali’s commitment to regional economic development and providing inclusive banking services, many customers still rely on cash transactions and physical visits to the branch. This Internship Program aims to enhance understanding and usage of digital banking applications through intensive support. This approach includes direct education on how to use the app, its benefits, and technical problem- solving. Results show an improvement in customers' understanding and skills in using digital services, but challenges related to digital literacy still need to be addressed. The program demonstrates effectiveness in increasing digital service adoption, supporting Bank BPD Bali’s goal of delivering more efficient and high-quality banking services, and contributing to the economic development of Bali. Evaluation and the development of a structured monitoring system are necessary to ensure the program’s sustainability and effectiveness in the future. Kata Kunci: digital banking, customer assistance, digital literacy, technology adoption

Adoption of Artificial Intelligence Chatbot Technology in Academic Activities of Jakarta Students: Ease of Use

Artificial Intelligence (AI) Chatbot technology has garnered significant attention recently as an innovative solution for various needs, from learning to counseling. However, its adoption among university students remains a crucial research area. This study aims to understand the usage patterns of university students in Jakarta regarding Chatbot technology, focusing on usage frequency, ease of use, and factors influencing adoption. Conducted from March to May 2024, the research involved 100 students from various Jakarta universities, selected through convenience sampling to capture diverse characteristics. Data collection methods included document studies and questionnaires. The analysis identified the level of Chatbot technology adoption among Jakarta students and the factors influencing it. Results indicate a high frequency of Chatbot use, with perceived usefulness, ease of use, and comfort being the primary drivers of adoption and positive attitudes toward this technology. This study provides significant insights for companies developing Chatbot technology, offering an in-depth understanding of students' preferences and behaviors. These insights can guide companies in creating more effective marketing strategies and enhancing Chatbot design and functionality to be more user-friendly and aligned with user expectations, thereby increasing adoption rates and user satisfaction.

Farm Typology to Enhance Rice Technologies Adoption in Ethiopia

The aim of this study is to conduct a review of farm typology in order to improve the adoption of rice technologies in Ethiopia. Rice production has experienced significant growth in the country, with the cultivated area expanding from 33,820 hectares in 2013 to 60,000 hectares in 2022. However, the adoption level of rice technologies remains low, posing a challenge to meet the increasing demand that is currently being met through rice imports. To address this issue, the government has developed a national rice production strategy and flagship programs at the national level. Furthermore, understanding the characteristics of farmers is crucial for the successful implementation of these initiatives, as farmers are heterogeneous in terms of their resources, preferences, and objectives. Consequently, the adoption rate of rice technologies varies among farmers, leading to different demands for agricultural advisory services. To develop effective farm typologies, it is important to identify the key drivers of technology adoption, such as farm size, risk exposure, human capital, labor availability, credit access, and access to commodity markets. While there are various theories available for studying farm typology, the sustainable livelihood theory is particularly comprehensive in creating effective typologies. These theories employ both quantitative and qualitative approaches. In conclusion, conducting a farm typology study specific to rice cultivation is crucial for enhancing the adoption level of rice technologies.

EVALUATION OF NIGERIAN CASHLESS PAYMENT POLICY AND ITS IMPACT ON ECONOMIC GROWTH: A SYNTHETIC REVIEW

This study aimed to provide a comprehensive analysis of the existing literature on the impact of cashless payment policy on economic growth in Nigeria. The paper is designed to provide a first broad overview for academic researchers and provide a practical financial policy for determining the impact of cashless payment policy on economy growth. This study conducted a critical literature review (survey) on the relation between cashless payment policy and economic growth. This research was explorative, descriptive and was based on documentary review. The study applied qualitative text data analysis approach and examined documents and systematically interprets the information so as to allow the researcher to draw inference about the issues of interest. Thus, the identified articles were screened using the content-centric analysis technique so as to align with the objective of the study by searching for suitable keywords in line with the theme of the study. Hence, the study was carried out systematically through an article search engine using the keywords "cashless policy" and "economic growth,". Having evaluated the outcome of several study from the review, the study finds that virtually all the studies agreed that cashless payment policy has significant impact on economy growth of a country. However, due to different economic structure and levels of technology adoption as well as other related factors as explained in this study, the positive impact of cashless payments on economy growth in Nigeria may not be generalizable to European countries and other member countries such as G7, G20, OECD and CPMI as reviewed in the study.

The role of agglomeration in digitalisation and productivity: an empirical examination of manufacturing SMEs in South Korea

ABSTRACT This study examines the relationship between regional agglomeration and the digitalisation of manufacturing small and medium enterprises (SMEs), and how this interplay affects their productivity. Using two analytical models, we investigate the correlation of regional agglomeration factors such as industrial specialisation, related and unrelated variety, urbanisation economies and the spatial concentration of suppliers with SMEs' digitalisation level in South Korea. Our findings indicate that related variety within regional agglomerations positively influences digital innovation, facilitating knowledge spillovers particularly beneficial for SMEs with higher levels of digitalisation. The study reveals a differentiated impact of agglomeration economies on SMEs based on their digital maturity. While high-level digitalised enterprises benefit from related variety and urbanisation economies, those in the initial stages of digital adoption gain proximity to digital technology suppliers. The 2SLS models further demonstrate that digitalisation significantly enhances productivity across all levels of digital technology adoption among SMEs. This study emphasises the conditional nature of the effects of regional agglomeration on digitalisation and productivity, advocating for nuanced support strategies that cater to the varying digital maturity stages of SMEs, which are valuable for policymakers and business leaders in fostering a supportive regional ecosystem that propels SMEs towards greater productivity in the digital economy.

Pengaruh Sosial dan Nilai Harga terhadap Behavioral Intention to Use QRIS serta dampaknya pada Use Behavior: Studi Empiris pada UMKM Sektor Kuliner Kota Pekanbaru

The presence of QRIS payment technology in the digitalization era shows that there is a level of technology adoption that originates from the intensity of behavior of MSME players as users of digital payment services. The aim of this research is to explore the role of social influence and price values on interest in using QRIS for MSMEs in the Culinary Sector in Pekanbaru City. This research uses quantitative descriptive methods. Empirical data was collected through questionnaires from 340 respondents who are MSME owners. Analyzed using SmartPLS 4.0 based on the SEM-PLS method. The research results concluded that social influence and price value influenced behavioral intentions to use QRIS, then behavioral intentions to use QRIS influenced usage behavior. Therefore, this study is consistent with the efforts of the government and Bank Indonesia to accelerate the implementation of digital payments in the development of the MSME digitalization program.

Survey of farm, parlour and milking management, parlour technologies, SCC control strategies and farmer demographics on Irish dairy farms

BackgroundThis cross-sectional study describes a survey designed to fill knowledge gaps regarding farm management practices, parlour management practices and implemented technologies, milking management practices, somatic cell count (SCC) control strategies, farmer demographics and attitudes around SCC management on a sample of Irish dairy farms.ResultsWe categorized 376 complete responses by herd size quartile and calving pattern. The average respondent herd was 131 cows with most (82.2%) operating a seasonal calving system. The median monthly bulk tank somatic cell count for seasonal calving systems was 137,000 cells/ml (range 20,000 – 1,269,000 cells/ml), 170,000 cells/ml for split-calving systems (range 46,000 – 644,000 cells/ml) and 186,000 cells/ml for ‘other’ herds (range 20,000 – 664,000 cells/ml). The most common parlour types were swing-over herringbones (59.1%) and herringbones with recording jars (22.2%). The average number of units across herringbone parlours was 15, 49 in rotary parlours and two boxes on automatic milking system (AMS) farms. The most common parlour technologies were in-parlour feeding systems (84.5%), automatic washers on the bulk tank (72.8%), automatic cluster removers (57.9%), and entrance or exit gates controlled from the parlour pit (52.2%). Veterinary professionals, farming colleagues and processor milk quality advisors were the most commonly utilised sources of advice for SCC management (by 76.9%, 50.0% and 39.2% of respondents respectively).ConclusionsIn this study, we successfully utilised a national survey to quantify farm management practices, parlour management practices and technology adoption levels, milking management practices, SCC control strategies and farmer demographics on 376 dairy farms in the Republic of Ireland. Rotary and AMS parlours had the most parlour technologies of any parlour type. Technology add-ons were generally less prevalent on farms with smaller herds. Despite finding areas for improvement with regard to frequency of liner changes, glove-wearing practices and engagement with bacteriology of milk samples, we also found evidence of high levels of documentation of mastitis treatments and high use of post-milking teat disinfection. We discovered that Irish dairy farmers are relatively content in their careers but face pressures regarding changes to the legislation around prudent antimicrobial use in their herds.

Farm Women Participation in Natural Resource Conservation: Technology Adoption Study in Semi-Arid Regions of India

Background: Semi-arid regions (SARs) of India are characterized by limited rainfall and often prone to droughts. These regions typically receive moderate to low levels of precipitation, making agriculture and water availability significantly challenging. In India, 55% of population is engaged in agriculture and its allied activities. Despite making a significant contribution to livelihoods, the sector continues to face challenges as soil degradation and resource depletion have reduced crop and livestock outputs. To mitigate the effects of land degradation and conserve rainwater, government has taken significant measures to make natural resource conservation a priority throughout the country. To conserve the natural resources, women are always playing an important role as they are always involved in agricultural activities. Methods: The study was undertaken to investigate the role of women in Soil and Water Conservation (SWC) in 3 SARs of India. The purposive sampling was done as watershed beneficiaries were selected as sample respondents. Result: The results revealed that majority of women (55%) had a medium level of technology adoption. Multiple regression analysis revealed that women’s age, education, farming experience, risk bearing, social participation and cost-effectiveness were influencing the adoption of SWC technologies in watersheds. The correlation analysis reflected that out of sixteen factors, eleven factors namely age, education, farming experience, land holding, risk bearing, social participation, agro advisory and weather advisory, skill development, ease of use and cost effectiveness significantly affected the adoption of SWC technologies.

Enhancing Dairy Farm Welfare: A Holistic Examination of Technology Adoption and Economic Performance in Kahramanmaraş Province, Turkey

Technology and innovations have significant potential to enhance farm productivity, profitability, and economic sustainability. This study comprehensively investigates the relationship between technology adoption and economic performance within dairy farming. First, it seeks to clarify how socio-economic, information-seeking, behavioral factors and technical efficiency influence the level of technology adoption in dairy farms. It also compares the economic indicators of dairy farms depending on their technology adoption levels and evaluates whether technology adoption affects dairy farms’ technical, allocative, and economic efficiency. The data were collected from 188 dairy farmers in Kahramanmaraş Province in the East Mediterranean Region of Turkey in 2022. The results reveal that dairy farms’ technology adoption levels are influenced by income, household size, investment, ownership of cultured cattle breeds, Chamber of Agriculture membership, contact frequency with private veterinarians and other farmers, perceived ease of use, perceived usefulness, and technical efficiency. Farms with high-level technology adoption demonstrate increased profitability and efficiency scores, highlighting the positive correlation between technology adoption and farm efficiency. Policymakers should focus on training and support programs for dairy farmers to optimize technology use and input management. They can also promote resource-efficient farming and provide financial incentives for sustainable practices and dairy technologies.

Trade and technology adoption in distorted economies

This paper examines how labor market imperfections distort firm-level technology choices and alter the gains from trade in developing countries. Motivated by evidence that firms using modern technologies are disproportionately exposed to labor market distortions, we introduce firm-level technology choices and labor market distortions into an otherwise standard quantitative trade model. We then provide formulas for the welfare and labor productivity gains from trade liberalization, highlighting the role of distortions and technology choice. Our quantitative analysis reveals that labor market distortions provide a possible explanation for the inefficiently low levels of modern technology adoption in developing countries. Moreover, labor market distortions erode one-third of the potential labor productivity gains from trade liberalization among low-income countries.

Impact Assessment and Upliftment of Poor and Marginal Tribal Farmers of Chhattisgarh State through Quality Seed Production in Chickpea (Cicer arietinum L.)

The study was carried out in districts of Chhattisgarh plains and plateau by conducting front line demonstrations (FLD’s) and tribal Sub Plan (TSP) of chickpea at different locations of farmer’s field to promote the cultivation and adoption of improved package of practice from 2018-19 to 2022-23. The seeds of improved varieties and balanced fertilizers were the part of technological package supplied to the demonstration plot as against control. All the demonstrations were conducted by following participatory approach. Results revealed that improved varieties and balanced fertilization increased yield as compared to the farmer’s practice. In demonstration plots C: B ratio was also higher as compared to control ones. It can be concluded from the findings that use of improved technologies can reduce the technology gap to a considerable extent resulting in increased productivity of rapeseed in the district. It needs the efforts of both extension and farmers to enhance adoption level of location and crop specific technologies among farmers for bridging these gaps. Therefore, the farmers’ need to provide proper technical support and guidance through various improved agronomic practices for better production and productivity in the district.

Adapting to climate change accounting for individual beliefs

As the climate changes, efficient climate policy requires a better understanding of how individuals adapt. Despite extensive research on various climate adaptation frictions, including financial and technological constraints, models of adaptive decision-making assume that agents have perfect information and accurate beliefs about climate. Combining rural household data in Bangladesh with a meteorological measure of dryness, this paper studies the role of individual drought beliefs and their accuracy in irrigation decisions as a key adaptive margin. In a theoretical model, I introduce a behavioral friction to document how heterogeneous beliefs differentially influence responsiveness to the same meteorological signal in dryness. The empirical analysis reveals an asymmetric response to dry shocks in irrigation conditional on the accuracy of prior beliefs. A counterfactual analysis shows lower technology adoption levels and higher monetary losses when beliefs are inaccurate.