Adoption Tendencies Research Articles

Effective extension and access to education drive optimal adoption of climate-smart agriculture interventions in affected tidal floodplains: A case study

Developing countries with predominantly agricultural economies are particularly vulnerable to short-term climate variability and long-term climate change adversities. This provides the context for adopting climate-smart agricultural (CSA) practices to ensure consistent agricultural product supply and food security. Although concepts of CSA tools and strategies are well-established, their adoption trends in developing regions are still undesirable, with little to no empirical understanding of factors contributing to these trends. The current research aims to address this gap of knowledge by assessing the nature of climate change impacts, adaptation strategies, and socio-economic characteristics of the farmers influencing the adoption of CSA techniques in a rural cohort in Southwestern Bangladesh. Systematically designed interview schedules revealed that the most common and devastating consequences of climate change in the study area were increased infestation of pests and diseases. Other overlooked hazards including water-logging, cyclones and cold waves, are posing new threats to regional agriculture by changing conventional patterns. Contrary to the status quo, many CSA technologies, especially indigenous approaches, are widely and effectively adopted by farmers in the studied area to cope with climate change. These adoption tendencies and innovations in CSA were found to be significantly driven by factors such as extension and training programs, education of farmers, and dependence on on-farming income. The findings of the current study provide a preliminary analysis of the attitude, knowledge and trends of CSA technology adoption by farmers in a less-saline floodplain niche of a predominantly salinity-impacted coastal region. The study acts as a model for future relevant investigations and implementations for stakeholders with supply of inputs, technologies and expertise in finding sustainable solutions and appropriate extension for communities around the world confronted with similar challenges.

ChatGPT and generation ‘Z’: A study on the usage rates of ChatGPT

This study aims to elucidate the prevailing patterns in the utilization of technology, specifically chatGPT. It determines the influence of Generation ‘Z,’ students' perspectives, and adoption tendencies on the rate of chatGPT usage. Data were analyzed using a structural equation model (SEM) through Amos version 24, focusing on university students (n = 307). Findings showed a direct relationship among all variables: students' views, Generation Z's, and adoption tendencies. All three variables had a positive impact on chatGPT usage rates. Of all three independent variables, Generation ‘Z' had the most significant impact on chatGPT usage among university students. This study focused on students enrolled in public universities; future research could investigate the demographics of students attending private universities, specifically those in the twelfth grade and academics.

Factors associated with smallholders’ uptake of intercropping in Southeast Asia: A cross-country analysis of Vietnam, Laos, and Cambodia

While previous studies acknowledge intercropping as a climate-smart agricultural practice and confirm its prominence in developing countries, behavioral factors underlying farmers’ decision in intercropping adoption remain poorly understood. This study assesses and compares the heterogeneity in adoption of intercropping among smallholder farmers in Vietnam, Laos, and Cambodia, through the lens of climate change adaptation. A sample of 1017 smallholder farmers was recruited for a household survey across the three countries using a convenient sampling approach. Principle component analysis (PCA) was performed to identify the main dimensions of farmers’ perception towards climate change and adaptation. Next, generalized order logit regressions were employed to assess the association between farmers’ adoption tendency of intercropping and their perception of climate change and adaptation, perceived usefulness, perceived ease of intercropping, and socio-demographic characteristics. The study shows that perceived climate severity was negatively associated with intercropping adoption tendency in Vietnam and Laos (p < 0.001). In all studied countries, farmers who perceived a higher level of climate change impact were less interested in intercropping. Perceived ease and perceived usefulness of intercropping were positively related to farmers’ adoption of intercropping in the three countries (p < 0.001). Information acquisition on climate change adaptation reduced the willingness to intercrop in Vietnam (p < 0.001) but increased the adoption readiness in Laos (p < 0.001) and Cambodia (p < 0.1). Informal social support hampered readiness to adopt intercropping only in Vietnam (p < 0.001). Lastly, households with a home garden were more willing to adopt intercropping in Laos (p < 0.1) and Cambodia (p < 0.001), compared to households without a home garden. Policies focused on enhancing the perceived ease and benefits of intercropping, alongside improving the access and usability of information on climate change and adaptation, could incentivize adoption of intercropping among smallholder farmers,therefore strengthening their resilience against the impacts of climate change.

The economic constraints of adopting renewable energy in farming systems

The shift to renewable energy is considered one of the policies that encourage agricultural production and preserve the environment. This paper investigates the constraints that affect the adoption of renewable energy sources in developing countries. A questionnaire was designed to collect the data. The questionnaire's validity and reliability were measured. The questionnaire was distributed on 150 farms. The relative importance index was calculated for the different constraints and the structural equation modeling was used to measure the effect of different factors on the adoption of renewable energy sources. The results showed moderate tendencies of farmers to adopt renewable energy sources. The weight of the different constraints was very close showing that legal and economic constraints were in the first position, followed by infrastructure readiness, installation costs, and maintenance requirements. Keywords: Renewable energy, economic constraints, legal constraints, installation constraints, economic returns, adoption tendencies, farm size.

What Drives People’s Willingness to Adopt Autonomous Vehicles? A Review of Internal and External Factors

This article presents a state-of-the-art literature review to understand people’s perceptions and opinions of Autonomous Vehicles and the factors that influence their adoption. A strategic literature search was conducted to select articles for this review. Most of the articles were published since 2015 and they used a household questionnaire survey to collect data. Mostly, they used statistical and econometric methods to evaluate the factors that affect people’s intentions to adopt Autonomous Vehicles. The results show that psychological factors often appear as the most important internal factors of people’s willingness to adopt Autonomous Vehicles. Additionally, other internal factors such as the socioeconomic profile of individuals and their household, and knowledge and familiarity with Autonomous Vehicle technologies would affect adoption tendencies. User attributes also indirectly affect adoption of Autonomous Vehicles by influencing the psychological factors of users. We identify several critical external factors such as opportunities (e.g., safety and security, low congestion, energy use) and challenges (e.g., system failures, privacy breaches, and legal issues), while another influential group includes transportation factors (e.g., travel mode, distance, and time), urban form (e.g., urban/rural, density, land use diversity), affinity to new technology, and the institutional regulatory environment. We discuss some recommendations for policy makers, auto industries, and private stakeholders to formulate policies and strategies to increase the market share of Autonomous Vehicles. Finally, we identify some limitations of previous studies and provide a blueprint for future research on Autonomous Vehicle adoption.

Identifying the structure patterns to govern the performance of localization in regulating innovation diffusion

The macro social influence is recognized as a non-negligible ingredient in innovation propagation: more adopters in the network lead to a higher adoption tendency for the rest individuals. A recent study to incorporate such a crucial mechanism shows that sufficient intensity of macro-level social influence can cause a change from a continuous to discontinuous transition, further indicating the existence of a tricritical point. Although network localization strength determines the tricritical point, it remains unclear what network quantities govern the performance of localization in regulating innovation diffusion. To address this issue, we herein consider the model incorporating both the micro- and macro-levels social influence. We present a dynamic message-passing method to analytically treat both the outbreak threshold and recovered population, and validate the predictions through agent-based simulations. Extensive analysis on the classical synthetic networks shows that sparsely available connections, and relatively heterogeneous degree distribution, either assortative or extremely disassortative configurations are favorable for continuous transition. In such cases, the employed network can yield a strong localization effect so that the innovation is trapped in the configurations composed of the hubs with high non-backtracking centrality. We further explore the dependence of both tricritical point and localization strength on three structural quantities: network density, heterogeneity, and assortativity, which gives a clear physical picture of the joint effects of the three structure quantities on the localization strength. Finally, we conclude that the core-periphery structure, being sensitive to the change of the three structure quantities, essentially determines localization strength, and further regulates the phase transition.

The role of cognitive complexity and risk aversion in online herd behavior

This paper investigated the role of information related, social and customer characteristics in public information adoption tendencies of online customers to result in herding in e-commerce. E-commerce platforms contains numerous online reviews about products which have the potential to influence customers. We applied structural equation modeling and a 2 × 2 scenario experiment to empirically verify the effect of a few factors in creating online herding. Two levels of cognitive complexity (simple, complex) and risk aversion (risk averse, risk taker) formed the 2 × 2 factorial design. The study's primary finding was that a person with simple cognitive structure and risk avoidance tendency may exhibit higher intention to adopt public information and engage in herding. Information specific attributes contributed maximum towards information adoption and herding. Among sociological variables, only reputation concern significantly predicted both information adoption and herding. Theoretically, the study offered a framework to explore herding intentions online and augmented the observations from the information adoption model. The quality of concise information from credible sources significantly instigates adoption of public information contained in online reviews. From the perspective of marketers, having a better understanding of herding behaviors and its mechanisms can enable the e-commerce platform to reduce herding’s erosion on the wisdom of the crowd by optimizing its information structures (i.e., public information, private information, etc.).

The mediating effects of public genomic knowledge in precision medicine implementation: A structural equation model approach.

Precision medicine emphasizes predictive, preventive and personalized treatment on the basis of information gleaned from personal genetic and environmental data. Its implementation at health systems level is regarded as multifactorial, involving variables associated with omics technologies, public genomic awareness and adoption tendencies for new medical technologies. However, interrelationships of the various factors and their synergy has not been sufficiently quantified. Based on a survey of 270 participants involved in the use of molecular tests (omics-based biomarkers, OBMs), this study examined how characteristics of omics biomarkers influence precision medicine implementation outcomes (ImO) through an intermediary factor, public genomic awareness (represented by User Response, UsR). A structural equation modelling (SEM) approach was applied to develop and test a 3 latent variable mediation model; each latent variable being measured by a set of indicators ranging between three and six. Mediation analysis results confirmed a partial mediation effect (an indirect effect represented as the product of paths 'a' and 'b' (a*b)) of 0.36 at 90% confidence level, CI = [0.03, 9.94]. Results from the individual mediation paths 'a' and 'b' however, showed that these effects were negative(a = -0.38, b = -0.94). Path 'a' represents the effect of characteristics of OBMs on the mediator, UsR; 'b' represents the effect of the mediator, UsR on implementation outcomes, ImO, holding OBMs constant. The results have both theoretical and practice implications for biomedical genomics research and clinical genomics, respectively. For instance, the results imply better ways have to be devised to more effectively engage the public in addressing extended family support for extended family cascade screening, especially for monogenic hereditary conditions like BRCA-related breast cancer and colorectal cancer in Lynch syndrome families. At basic biomedical research level, results suggest an integrated biomarker development pipeline, with early consideration of factors that may influence biomarker uptake. The results are also relevant at health systems level in indicating which factors should be addressed for successful.

Role of networking capability, socio-economic and institutional characteristics on adoption tendencies of clean seed potato agri-enterprises in central Rift Valley, Kenya

Even though quality of seed is a major yield determinant in potato (Solanum tuberosum L.) production and global food security, inadequate availability of and access to high quality (certified) seed is a major challenge to potato producers in Sub-Saharan Africa. The objective of this study was to examine farmer’s adoption tendency towards decentralised clean seed potato multiplication agri-enterprise (CSPMAE) in Central Rift Valley, Kenya, which aids in implementation of stage matched entrepreneurial interventions. A cross-sectional survey was conducted using a semi-structured questionnaire on 54 seed potato producers and 192 non-seed potato producers, through multistage sampling. Ordered logistic regression analysis, based on the trans-theoretical model, revealed that household head, partner knowledge, gender, land size allocated for potato production, level of education, ownership of transport and/or storage facilities, frequency of interaction with certified seed potato producers and agricultural extension officers influenced adoption tendencies of CSPMAE, positively and significantly. Seed potato value chain stakeholder platforms, development workers and donors should prioritise their support for clean seed agri-enterprises to farmers with such traits. This is likely to lead to increased supply of access to clean seed, thereby improving potato yields in Kenya.

Role of networking capability, socio-economic and institutional characteristics on adoption tendencies of clean seed potato agri-enterprises in central Rift Valley, Kenya

Even though quality of seed is a major yield determinant in potato (Solanum tuberosum L.) production and global food security, inadequate availability of and access to high quality (certified) seed is a major challenge to potato producers in Sub-Saharan Africa. The objective of this study was to examine farmer’s adoption tendency towards decentralised clean seed potato multiplication agri-enterprise (CSPMAE) in Central Rift Valley, Kenya, which aids in implementation of stage matched entrepreneurial interventions. A cross-sectional survey was conducted using a semi-structured questionnaire on 54 seed potato producers and 192 non-seed potato producers, through multistage sampling. Ordered logistic regression analysis, based on the trans-theoretical model, revealed that household head, partner knowledge, gender, land size allocated for potato production, level of education, ownership of transport and/or storage facilities, frequency of interaction with certified seed potato producers and agricultural extension officers influenced adoption tendencies of CSPMAE, positively and significantly. Seed potato value chain stakeholder platforms, development workers and donors should prioritise their support for clean seed agri-enterprises to farmers with such traits. This is likely to lead to increased supply of access to clean seed, thereby improving potato yields in Kenya.

Structural equation modeling for three aspects of green business practices: a case study of Bangladeshi RMG's industry.

Green business (GB) had often been regarded as a pervasive trend that underlies the operations and performance of businesses. By portrayal of three aspects view of the green business, this paper evaluates green business approaches within the Bangladeshi ready-made garments (RMG) sector and provides a structured framework for the factors affecting the utilization of green business approaches. This study further evaluates how the environmental, societal, and economic impact derived green business practices. The framework is experimentally tested by the partial least square approach to structural equation modeling (PLS-SEM) concentrated on survey responses quantifying the green business practices within 40 RMG organizations situated in Dhaka and Chittagong, Bangladesh. The findings demonstrate that there is a positive relationship between environmental, social, and economic aspects. More specifically, the PLS-SEM estimation demonstrates that the interaction between environmental and economic sustainability has a substantial proportion of values towards profiling GB practice. Meanwhile, there is a vast gap for profiling the performances of environmental and economic aspects through social aspects within the RMG sectors of Bangladesh. Also, there is a significant difference between the predicted and factual green business adoption tendencies and views among different industrial enterprises, especially for waste management and water pollution based on the findings of the SEM-PLS model. Throughout the context of the rapid growth of socioeconomic development and new technological advancement, social level performance possess comparably weak influences of GB strategy on the within Bangladeshi RMG sectors. In the meantime, as the stricter law has a vital impact on the firm's strategies for becoming more environmentally friendly practices, it instituted as an essential variable for quantifying social sustainability. Moreover, the study recommends some suggestions emphasizing the part of the identified model in the context of encouraging business organizations to indulge in environment-oriented socio-economy actions and thus change the emphasis of potential GB study directions.

Farmer’s adoption tendency towards drought shock, risk-taking networks and modern irrigation technology: evidence from Zhangye, Gansu, PRC

PurposeThe purpose of this paper is to measure Farmer’s adoption tendency towards drought shock, risk-taking networks and modern irrigation technology.Design/methodology/approachBased on this assumption, this paper evaluated the data gathered from 498 household surveys of Zhangye, Gansu province, PRC, by using the binary probit model. First, the empirical data was analyzed for evaluating the impact of drought shock and risk-taking tendencies on the adoption of modern irrigation technology by farmers. Second, the authors introduced informal risk-bearing networks with formal risks. Final, based on the empirical results, the sustainability test, along with the marginal effect analysis and the degree of impact was carried out.FindingsThe results show that the drought shock has a significantly deferent effect on the modern irrigation technology of the farmers. The probability of using technology for each level of drought loss is reduced by 15.02%. The risk-taking network has a significant role in promoting the modern irrigation technology of farmers. The probability of adoption for each additional unit of rural household labor security supply, the likelihood of adoption by farmers increased 23.11%, the probability of approval for each level of relative support, and neighborhood assistance by farmers increased by 13.11% and 17.88% respectively. This study further revealed that insurance purchases enabled farmers to adopt new irrigation technology with the probability increased by 24.99%; easily available bank loans increased the probability of farmers using irrigation technology by 31.89%. From the perspective of interactions between farmers, the risk-taking network can alleviate the inhibitory effect of drought impact towards the adoption of irrigation technology. Among the control variables, the number of years of education, the age of farming, the degree of arable land, the distance from home to the market, and the price of water all has significant effects on the adoption of modern irrigation technology by farmers.Originality/valueThe novelty of the study is that it illustrated the interactive influence of drought shock and risk-taking networks on the farmer’s adoption tendencies of modern irrigation technologies, the inner relationship among drought impact, the risk-taking network and the farmer’s adoption behavior and provide an interactive relationship between the formal risk-taking network and the non-risk-taking network in farmer’s technology adoption.

Acceptance of Vehicle Automation: Effects of Demographic Traits, Technology Experience and Media Exposure

Transportation users are increasingly aware of a possible future where they may ride in or share the road with automated vehicles. However, even with recent technological advances, many are still hesitant to accept automated driving. This study explores effects of the following characteristics on acceptance: demographics including age, gender, level of education and income; experiences with technology in general, as well as technology in drivers’ current vehicles; and media exposure. Survey responses from 3505 adults in the United States indicate that younger age, a high level of education, positive affect for advanced driver assistance systems currently in use, and high self-rated early technology adoption tendency have significant influence on acceptance. Data reflecting time course and salience of media coverage on knowledge and attitudes, especially with high-profile events such as a fatal crash, is presented with implications around the need for balanced media reporting with more focus on the safety benefits.

Factors Affecting on Users’ Intentions toward 4G Mobile Services in Bangladesh

This study discusses the amalgamation of Technology Acceptance Model with the underlying 8 factors to investigate the intensity of users’ intentions towards 4G adoptions in Bangladesh. So, it has tried to list all the latest released facilities and the adoption tendency. A sample size of 119 respondents with random sampling as well as in-depth interviewing methods have used and collected primary data from different institutions across Bangladesh with a self-administered field survey questionnaire as well as having secondary sources from different webs, books, journals, annual reports, and unpublished research works. The SPSS and the 5-Point-Likert scale have used to validate the results. Also the tests include correlation, multiple regression technique, ANOVA, and co-efficient of variance have used. The study indicates that 36% respondents are positively prone to 4G (r2=.362, f=5.531, p=.000). Besides, among the 8 factors, the image has the greatest influence on it (β=.249, t=2.558, p=.012) followed by the variety of services (β=.189, t=1.608, p=.111), the perceived enjoyment (β=.148, t=1.803, p=0.109), the perceived ease of use (β=0.108, t=0.916, p=0.368), the personal Innovativeness (β=.098, t=.934, p=.352), and the network effects (β=.002, t=.025, p=.980). Conversely, the price (β=-.027, t=-.406, p=.685) and the perceived usefulness (β=-.069, t=-.629, p=.303) have a rare impact on it. However, with the outcomes, the telecommunication services providers will be able to accelerate the wining strategies at different levels in Bangladesh. As there are few studies published in this regard, future research is necessary to investigate the financial and industrial implications associated with it.

Influences of Value Perception on Farmers’ Technology Adoption Tendency and Conditional Response-Based on the Micro Data of 338 Farmers

From the “perception-action” perspective, based on the microscopic survey data from 338 farmer households, this paper measures the influences of farmers’ value perception on their tendency to adopt technologies using a combination of methods including the confirmatory factor analysis and multi-group structural equation model and further studies the response of each influence path on variables like the characteristics of the individual decision maker, topographic conditions, radiation circle, and whether the farmer has joined any agricultural organization. The results show that: (1) anticipated benefit and comprehensive value perception have significant positive influences on farmers’ tendency to adopt technologies; and cost and benefit risk perception have negative inhibitory effects on their adoption tendency; (2) The individual characteristics of the farmer household decision makers have a significant role in adjusting the perception of comprehensive technological value and its influence on the adoption tendency; (3) the influences that farmers’ knowledge of technology costs and benefits and their perception of health risks have on their adoption tendency show significant geographical responses; and (4) whether the farmers are members of agricultural organizations (leading enterprises) leads to large differences in the influences that farmers’ value perception has on their technology adoption tendency.

The Case of Legume-Cereal Crop Mixtures in Modern Agriculture and the Transtheoretical Model of Gradual Adoption

Mixed cropping (MC), the growing of two or more coexisting crops in one field, specifically the mix of cereal and grain legumes, can contribute to a more sustainable agricultural land use. Despite a variety of ecological benefits and promising grain productivity, applications are scarce among farmers in developed countries. In consideration of MC's potential this study interviews farm managers to profile characteristics of adopters. The transtheoretical model (TTM) is applied to capture adoption and adoption tendencies. The results point to a significant positive role of land owned vs. leased, adoption of reduced tillage and adoption intensity of legumes in general. The perception of technical barriers and the perception of MC's usefulness are also major drivers that proponents need to address. In general, the TTM provides a gradual measure of farmer's willingness to adopt, leading to more variance than binary classifications, which makes TTM especially useful to adoption research of marginalized ecological practices.

The Impact of Soil Erosion as a Food Security and Rural Livelihoods Risk in South Africa

&lt;p&gt;This study evaluates soil erosion/attrition as a major food security and rural livelihoods risk in South Africa, with the Upper and Lower Areas of Didimana, Eastern Cape Province, as a case study. The survey research method was adopted for the study. Farmers and extension officers’ behaviours relating to soil erosion control was negative even though the impact of erosion in the area was high. Approximately 75% of farmers indicated that they lose more than 21% of their crops yearly due to erosion and 55% said their crops and livestock, as well as their household feeding, suffer due to the problem. The results of the multiple linear regression analysis indicate that farm yield and farmers’ access to market are positively related to farmers’ adoption tendencies regarding erosion control, implying that farmers are more willing to adopt recommendations if their yields and access to market can increase. Similarly, age of farmers is positively related with erosion impact, indicating that older people have a higher tendency to cause erosion in the study area. This is true, as the area consists more of older people, who are generally known to resist change, thus low in adoption. Therefore, it is perceived that if farmers manage soil erosion appropriately, they will achieve higher yields. More so, pull factors like improved rural infrastructures and adequate agricultural incentives for youths are suggested to lure more youth in taking into farming in the study area.&lt;/p&gt;

Investigating Information Adoption Tendencies Based on Restaurants’ User-Generated Content Utilizing a Modified Information Adoption Model

Social media has boosted information sharing and user-generated content. Consequently, many restaurant goers rely on online reviews for dining recommendations. This study adds to the sparse literature on the influence of review extremeness, source credibility, website quality, and information usefulness on information adoption. Most notably, a modified information adoption model with the addition of website quality was tested in the context of restaurant review websites. Respondents answered survey questions based on what they saw in a simulated restaurant review website, which depicted one of eight scenarios. Results showed that the more negative a review, the more useful it is perceived to be. Perceived source credibility of the review writer was positively related to the perceived information usefulness. The only component of website quality that played a significant role in determining information adoption tendency of the review readers was the quality of the information disseminated in the website. Lastly, information usefulness also was positively related to information adoption.

User Adoption Tendency Modeling for Social Contextual Recommendation

Most of studies on the existing recommender system for Netflix-style sites (scenarios with explicit user feedback) focus on rating prediction, but few have systematically analyzed users’ motivations to make decisions on which items to rate. In this paper, the authors study the difficult and challenging task Item Adoption Prediction (IAP) for predicting the items users will rate or interact with. It is not only an important supplement to previous works, but also a more realistic requirement of recommendation in this scenario. To recommend the items with high Adoption Tendency, the authors develop a unified model UATM based on the findings of Marketing and Consumer Behavior. The novelty of the model in this paper includes: First, the authors propose a more creative and effective optimization method to tackle One-Class Problem where only the positive feedback is available; second, the authors systematically and conveniently integrate the user adoption information (both explicit and implicit feedbacks included) and the social contextual information with quantitatively characterizing different users’ personal sensitivity to various social contextual influences.

Louisiana crawfish farmer adoption of best management practices

This study investigated factors influencing the adoption of 18 best management practices in Louisiana crawfish aquaculture production based upon results of a farmer survey. Best management practices included in this survey are those that (1) are primarily vegetative; (2) address water management, including the irrigation system; and/or (3) address nutrient management. Probit results showed that land tenancy, whether a crop rotation was used, whether double cropping of crawfish with rice was practiced, farm size, portion of income from farming, and farmer age, education, risk preference, and technology adoption tendencies influenced best management practice adoption. Adoption rates varied widely, depending upon the best management practice, from 3% to 79%. The most frequently used best management practice was irrigation water management. Results provided information for targeting extension programs on the benefits of best management practice adoption.