Adoption Decisions Research Articles

The adoption non-adoption dichotomy: Why do smallholder producers dis-adopt improved chicken breeds?

Adopting agricultural technologies is crucial to improve productivity and livelihoods in developing countries. While much research has focused on adoption decisions, understanding dis-adoption, when farmers stop using technology, is equally important. Studies on agricultural technology adoption often treat dis-adopters (those who initially adopted but later discontinued to use) and never-adopters (those who never adopted) as the same, using binary models to analyze farmers' decisions. We argue that a better understanding of these decisions can be achieved by separately analyzing 'never-adoption', 'dis-adoption', and 'adoption.' Using nationally representative data from three African countries, Ethiopia, Nigeria, and Tanzania, we developed a multinomial logit model to analyze the adoption of improved chicken breeds. Our findings show that dis-adopters of improved chicken are different from never-adopters. Factors associated with dis-adoption include gender and education of household heads, access to training and extension services, breeding and culling practices, access to markets, use of complementary inputs, production objectives, landholding size, income diversity, and access to finance. Policies and strategies that aim to enhance sustained adoption and use of improved chicken breeds should promote a bundle of technologies, including tailored training, women empowerment, locally adapted and farmer-preferred chicken breeds, complementary inputs and services, innovative marketing strategies, and delivery models for bundles of technologies.

Self-Owned or Outsourced? The Impact of Farm Machinery Adoption Decisions on Chinese Farm Households’ Operating Income

Using farm machinery plays a significant role in easing the issue of slowing growth of operating income among farm households in China. Drawing data from CFPS2018, this study adopts a multinomial endogenous switching regression (MESR) to analyze the factors influencing farm households’ choices regarding self-owned farm machinery and outsourced machinery services, as well as their subsequent impact on operating income. The results of the study show that the characteristics of the head of household, family, village, and region have a significant impact on the farm households’ selection of whether to use self-owned machinery or outsourced services. Furthermore, the exclusive use of self-owned farm machinery and the combined use of both self-owned and outsourced machinery substantially enhance farm households’ operating income. An additional analysis indicates that these two types of machinery are complementary, and their combined use generates a superimposed effect that further boosts income. These findings suggest that the combined use of self-owned and outsourced machinery is optimal for farm households who wish to expand their operating income.

Comparative safety outcomes of leadless versus transvenous cardiac pacemaker: a systematic review and meta-analysis

Abstract Introduction Leadless Cardiac Pacemakers (LCP) have emerged as a promising alternative to Transvenous Pacemakers (TVP) for managing bradyarrhythmias, especially in cases where TVP options are limited, such as venous access issues in haemodialysis patients or high infection risk individuals. However, long-term safety data, including mortality and hospitalisation rates, are lacking, hindering informed clinical adoption decisions. Purpose This systematic review and meta-analysis compares safety endpoints of LCP with TVP. Methods A systematic search of PubMed, Medline, Embase, Scopus, Web of Sciences, and gray literature was conducted following PRISMA guidelines from release of the Micra LCP to market until May 15, 2023. Meta-analysis was performed using RevMan 5.4. Results Twenty-four studies including data from 33,450 patients (12,802 LCP, 20,648 TVP) were evaluated. The mean age of the population was 77.5 ± 10.6 years, with a mean left ventricular ejection fraction (LVEF) of 58.6 % ± 6.7. Follow-up durations ranged from 6 to 36 months. Compared to TVP, the LCP was associated with significantly fewer overall complications, major complications, acute, mid-term complications, hospitalisations, re-interventions, and device dislodgements (p<0.05). Mortality, tricuspid regurgitation, pacemaker-induced cardiomyopathy, and heart failure hospitalisation rates did not significantly differ. Although LCP showed higher cardiac injury risk, no significant difference in cardiac tamponade rates was observed (Figure 2). LCP exhibited increased vascular-related complications but decreased lung injury, endocarditis, device, and pocket-related issues. Conclusion In the largest review of LCPs, we report that LCP is associated with significantly lower rates of overall complications compared to conventional TVP. This knowledge is critically important as more LCPs enter clinical practice and serves as a baseline against which future data can be evaluated. Nevertheless, proper skill training may help to mitigate the risk of vascular and cardiac injury. These findings underscore the importance of conducting randomized controlled trials to comprehensively evaluate the safety of LCP compared to TVP.Cardiac complication

Store Advertising Strategy In Tuban In Increasing Product Appeal

Advertising strategy of Ceker Gobyozz Byozz Tuban Shop and its impact on business growth. Using the Diffusion of Innovation Theory by Everett M. Rogers, this study identifies how innovation in products and advertising strategies can be applied to small businesses. This shop utilizes the trend of spicy food that is popular among young people as the main innovation, accompanied by promotions through social media such as Instagram, Facebook, and WhatsApp, as well as print media in the local community. This strategy is implemented in stages, starting from word-of-mouth (WOM) promotion to the use of more modern media. The results of the study show that a well-integrated advertising strategy can significantly increase the number of visitors. This shop is able to attract around 50-70 visitors per branch per day, with a total turnover of 120 million rupiah per month. In addition, involvement in the local community accelerates the diffusion of innovation and helps the shop reach a wider market. Consumer adoption decisions are influenced by product quality and positive experiences at the shop, which creates customer loyalty. In conclusion, an innovative and targeted advertising strategy is the key to the success of Ceker Gobyozz Byozz Shop, providing important insights for small businesses in developing their businesses through effective promotions.

The adoption of Best Management Practices: empirical evidence from oil palm farming in rural Ghana

ABSTRACT Purpose We examine how farmer characteristics, farm, institutional, perception and shock factors influence the adoption of the Best Management Practices (BMPs). A thorough understanding of how relevant drivers affect the adoption decision of diverse BMPs can contribute to the development of evidence-based policies. Approach We use a household survey of 1031 smallholder oil palm farmers in the forest zones of Ghana to assess the determinants of farmers’ adoption decisions. We employ a seemingly unrelated regression (SUR) model after a principal component analysis is used to extract five latent components. Findings Our findings indicate that different farmer characteristics, farm, institutional, perception and shock factors have differential associations with the adoption of diverse BMPs. Key among these are the positive perception of BMPs, access to mills, perception of soil fertility and pests and diseases. Practical implications Specific BMPs must be tailored to meet the prevailing individual socio-economic characteristics and challenges of farmers to facilitate their adoption and scale-up. Educational programmes and dissemination of information by extension agents and research institutions are needed in the promotion of BMPs to enhance effective uptake. Theoretical implication The paper contributes to the growing literature especially on the uptake of diverse management practices, utilizing both behavioural and socio-economic theories underpinning adoption, thus providing empirical evidence that adoption is influenced by both behavioural and socio-economic factors. Originality/value In the bid to increase agricultural productivity, while preserving ecosystem services, the adoption of sustainable management practices remains key for all stakeholders and policy makers. This paper presents credible information for policy makers in Ghana and Africa in designing polices to influence their adoptions.

Adoption of Lean Construction and AI/IoT Technologies in Iran’s Public Construction Sector: A Mixed-Methods Approach Using Fuzzy Logic

The construction sector in Iran faces substantial inefficiencies, including high material wastage, posing environmental and economic risks. This study investigated the adoption of Lean Construction (LC) practices and AI/IoT technologies in Iran’s public construction sector using a mixed-methods approach. This research examined the organizational, technical, and infrastructural factors across four key provinces—Tehran, Isfahan, Khorasan Razavi, and Fars—and employed fuzzy logic to address the uncertainties in adoption decisions. Data from 28 key stakeholder interviews were analyzed using Python 3.9, with libraries such as Pandas 1.3.3, NumPy 1.21.2, and skfuzzy 0.4.2 for the statistical analysis and NVivo 12 for the thematic coding. The analysis revealed that organizational readiness and leadership support were the critical drivers of adoption, particularly in Isfahan and Khorasan Razavi, which exhibited the highest adoption likelihood scores (0.5000). Tehran and Fars showed slightly lower scores due to regulatory barriers and financial limitations. The findings highlight the need for targeted leadership training, regulatory reforms, and infrastructure investments to accelerate the adoption of these technologies. This study aligned with the Sustainable Development Goals (SDG 9: Industry, Innovation, and Infrastructure and SDG 11: Sustainable Cities and Communities) by offering practical recommendations for advancing sustainable practices in Iran’s construction sector. The insights provided have broader implications for other developing economies facing similar challenges, contributing to global efforts toward sustainable development.

Exploring consumers’ innovative products adoption process: based on technology readiness and value-based adoption

ABSTRACT This study seeks to empirically verify whether technology readiness composed of facilitating factor and inhibiting factor, affects consumer’s decision on innovation adoption. In addition, in an attempt to explore the mediation mechanism, the study sought to confirm whether technology readiness impacts consumers’ adoption decision through the dual paths, employing double sided perceptions with regards to perceived benefits and perceived sacrifices of the innovation. Finally, the study examines the moderating effect of psychological distance on the relationships between perceived benefits (and sacrifices) and adoption intention. Result of the study revealed that innovativeness affects the intention to adopt innovative products. Perceived benefits (and sacrifices) mediated the relationship between technology readiness and the intention to adopt innovative products. Finally, the study confirmed that the psychological distance moderates the relationship between perceived benefits (and sacrifices) and the intention to adopt innovative products.

Data analytics-driven innovation: UTAUT model perspectives for advancing healthcare social work

In today’s dynamic and increasingly complex healthcare landscape, leveraging data analytics in decision-making processes has become indispensable for fostering innovation and enabling more effective, data-driven approaches to healthcare delivery. This study explores the factors influencing the adoption of data analytics techniques in healthcare social work practice. It is guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) model and is aligned with key principles of open innovation dynamics. The analysis, conducted through binary logistic regression, revealed that facilitating conditions, effort expectancy, and self-efficacy are the most influential predictors of healthcare social workers’ intention to adopt data analytics. This underscores the critical role of organizational support, perceived ease of use, and individual confidence in fostering the adoption of innovative data-driven practices within healthcare social work. The results also indicate that social influence has a limited impact on shaping adoption decisions. The study’s findings have significant practical implications for healthcare decision-makers, social workers, and other stakeholders aiming to advance service delivery and improve patient outcomes through innovative data-driven solutions.

Development of an Evaluation Instrument on Artificial Intelligence Search Tools for Evidence Synthesis

What Was the Question? There are conflicting calls for evidence synthesis producers to adopt or avoid recent Artificial Intelligence (AI) technologies. Our question was: How do we evaluate rapidly evolving AI tools to enhance the production of evidence syntheses and maintain quality standards? What Did We Do? To advance information retrieval science for producing evidence syntheses at Canada’s Drug Agency (CDA-AMC), the Research Information Services team developed a process to evaluate promising AI search tools. We inventoried 51 tools in the fall of 2023, established selection criteria, assessed specific attributes, and built a standalone instrument to support continuous monitoring and evaluation of new tools. What Did We Find? Rapid development of AI search tools requires a flexible evaluation instrument to inform adoption decisions and enable comparison between tools. We identified mandatory and desirable characteristics for suitable AI tools to assist with information retrieval tasks conducted by CDA-AMC. This work enabled the development of a flexible instrument to evaluate novel AI search tools for evidence synthesis. What Does This Mean? CDA-AMC operationalized a replicable process to monitor and evaluate AI search tools. Our approach to evaluating AI technologies will advance information retrieval methods by CDA-AMC, and our evaluation instrument will assist any evidence synthesis producer interested in adopting AI search tools.

Drivers of Electric Vehicle Adoption in Nigeria

Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source in place of traditional fossil fuels and incorporating sophisticated navigation and autopilot systems. These vehicles align with multiple Sustainable Development Goals (SDGs) by offering a more environmentally sustainable alternative to internal combustion engine vehicles (ICEVs). Despite their potential, the adoption of EVs in developing nations such as Nigeria remains constrained. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework is expanded in this study by including important enablers such as poor infrastructure, problems with affordability, and government support in the broader category of facilitating conditions. Additionally, it scrutinizes variables such as trust, performance expectations, social influences, and network externalities to identify the primary determinants influencing Nigerian consumers' propensity to adopt EVs. Results show that the percentage increase of H6 (facilitating conditions → behavioral intentions) compared to H5 (network externalities → behavioral intentions) is approximately 32.35%, indicating that traditional drivers significantly influence individuals' willingness to purchase EVs and are particularly strong factors in adoption decisions. The paper concludes with a discussion of these findings and proposes strategies for future research to further explore the barriers and drivers of EV adoption in Nigeria.

Impact of heterogenous capabilities on export performance amid the digital transformation

We investigate the effects of adopting digital technology on export performance of Korean manufacturing firms amidst the digital transformation. We recognize firm-level capabilities should be closely associated with adoption of rapidly progressing digital technology but also with export performance. And our data indicates that the most common purpose of digital technology adoption is to launch new products to the market. Hence, we consider that technology adoption is a strategic and purposeful decision to gain competitive edge mostly by producing new product, and treating technology adoption exogenous can be misleading. Due to the endogeneity and selection issues in technology adoption, the endogenous switching regression is applied to this study as Coad et al. (2020). On technology adoption decision, we find external innovative resources from strategic alliance in addition to internal innovative capabilities stand out. Given technology adoption decision, internal capabilities like patent rights and international affiliation are complementary factors to export growth. The treatment effect analysis has implications as follows: the result on contribution of technology adoption to export growth for actually adopting firms is rather small, and shows heterogenous innovation, organizational, and external capabilities are still critical factors as much as new products embedding high-end digital technology; the result on non-adopting firms indicates potential of advanced digital technology to improve export performance by helping to produce such new products if they were actually capable to do it. In sum, our findings provide another evidence that structurally positive interaction between innovative activities and export performance as Aw et al. (2011), since adoption of digital technology to products itself is innovative in the digital transformation. Furthermore, the result is consistent with the capability theory in that heterogenous innovative and complementary capabilities determine strategic technology adoption and export performance simultaneously. Finally, our findings indicate that the digital transformation might be still at the early stage. The fact that Korean firms have adopted advanced digital technology mainly for new products can be interpreted as an indicator of early development stage of transformation, since firms concentrate on product innovation than process innovation to gain competitive edge at the early stage (Utterback and Abernathy, 1975). Thus, we expect that further evolution of digital transformation can facilitate process innovation, then contribute to firm performance by improving cost efficiency that should be tackled in the upcoming study.

Microalgae-Based Crop Support Technologies Show Multifaceted Promise Well-Suited to Looming Threats

This review summarises the available evidence on the prospects for using microalgae or their extracts to support crop production. The evidence is limited but suggests technological promise in several distinct ways, namely, higher core productivity, enhanced resilience to biotic and abiotic stresses, and better-quality produce. The different efficacy pathways of these microalgal technologies were examined to assess their scope to help address key farmer priorities. Their scope to help farmers face climate change and land degradation was a particular focus, given the magnitude of these threats. These microalgal technologies are framed in terms of their pertinence to farmer priorities due to the centrality of farmers to food systems. Notably, farmers’ technology adoption decisions are key to food system outcomes. The findings reported suggest that these crop support technologies could potentially deliver major benefits to farmers, consumers, and the environment. For the moment, however, this emerging literature remains largely neglected. Possible reasons for this are considered, as are potential ways forward. The review focuses particularly on the two most researched and widely available microalgae, the genera Arthrospira and Chlorella, in the interest of highlighting options farmers could adopt rapidly while research on the wider body of microalgae-based crop technologies continues.

Pathways to adoption and mitigation: A dynamic perspective on good agricultural practices in Rural Malawi

Many researchers have noted the limited adoption of farming management practices that should increase the resilience of smallholder farmers to weather shocks and mitigate their impact on the changing climate in sub-Saharan Africa. In this paper, we evaluate the dynamics of adopting “good agricultural practices” in Malawi, using data from a three-wave panel collected as part of an impact assessment of the Sustainable Agricultural Production Programme, funded by the International Fund for Agricultural Development. In addition to project impacts, we also evaluate additional mechanisms though which farmers may learn about the costs and benefits of different practices. We also evaluate the extent to which climatic conditions – such as being located in drought-prone or heavy rainfall areas – drive adoption decisions. Given the three waves of data, we first look at the range of adoption pathways observed, through the use of an adoption pathway trees. We identify six pathways, noting that adoption is not continuous for a large percentage of households. We then run a multinomial logit to assess the factors that increase the likelihood of falling into different adoption categories vis-a-vis remaining a never adopter. Results suggest that learning through information dissemination, such as through the SAPP project, and wider learning opportunities significantly increased the likelihood of pursuing different adoption pathways, while climatic conditions and learning through observing have limited impacts. On the other hand, for land-intensive management practices, being located in drought-prone areas or being located in areas prone to heavy rainfall increased the likelihood of pursuing different adoption pathways, as did greater ability to learn by observing. Learning by information sharing had limited impacts for land-intensive adoption pathway decisions. Overall, results suggest that information dissemination is important, though the mechanism differs by type of practice promoted. Flexibility in adoption status is an attribute of this system and there is a need to identify and promote practices that are both flexible and increase resilience to climate change.

A Review of IT Investment in Firms: What Can We Do in the New Era

Many studies on IT investment in companies have been conducted in the past, but our team combined them by summarizing the latest research. Compared to previous work, we revise a larger universe of firm IT investment, focus on more recent IT investment researches, refine the focus of current researchers pay attention to and address the problem of insufficient reference for enterprise practice. Through a review of the literature to synthesize the understanding of IT investment to (i) IT investment performance, (ii) IT adoption decision, (iii) IT governance, and (iv) IT labor (worker), we could highlight the research gaps that we encountered. Finally, based on the current research conclusions, we give practical suggestions from the early, middle and late stages of IT investment. This study contributes to the growing amount of literature on IT investment, both academically and practically.

An economic test for an unlawful agreement to adopt a third-party’s pricing algorithm

SUMMARY Artificial intelligence has helped fuel a growing market in the supply of pricing algorithms by software developers. While there is an efficiency rationale for outsourcing pricing, anticompetitive concerns have been expressed when competitors in a market adopt the same pricing algorithm. These concerns have resulted in private litigation claiming a third-party company (who developed the pricing algorithm) and firms (who adopted it) had an unlawful agreement. This study develops an empirical test for determining whether firms’ adoption decisions are coordinated. If adoption decisions are coordinated then adopters’ average price is increasing in the number of adopting firms, while if adoption decisions are independent then adopters’ average price does not depend on the number of adopting firms. This test could provide economic evidence to support a claim of an unlawful agreement between a third-party developer and adopting firms.

The Impact of Data Privacy on Users' Smartphone App Adoption Decisions

Rich user information is gained through user tracking and power mobile smartphone applications. Apps thereby become aware of the user and their context, enabling intelligent and adaptive applications. However, such data poses severe privacy risks. Although users are only partially aware of them, awareness increases with the proliferation of privacy-enhancing technologies. How privacy literacy and raising privacy concerns affect app adoption is unclear; however, we hypothesize that it leads to a lower adoption rate of data-heavy smartphone apps, as non-usage often is the user's only option to protect themselves. We conducted a survey (N=100) to investigate the relationship between privacy-relevant app- and publisher characteristics with the users' intention to install and use it. We found that users are especially critical of contentful data types and apps with rights to perform actions on their behalf. On the other hand, the expectation of a productive benefit induced by the app can increase the app-adoption intention. Our findings show which aspects designers of privacy-enhancing technologies should focus on to meet the demand for more user-centered privacy.

Is adoption of modern dairy farming technologies interrelated? A case of smallholder dairy farmers in Meru county, Kenya

Attempts have been made to promote the adoption of modern dairy farming technologies (MDFT). However, the adoption of these technologies largely remains underutilized. This study aimed to analyze the determinants of the adoption of MDFTs in Meru County. Using purposive and proportionate sampling techniques from 355 smallholder dairy farmers in Meru County, Kenya, this study analyzed the factors that facilitate or impede the adoption of MDFTs. We use a Multivariate probit (MVP) to evaluate adoption decisions by dairy farm households facing multiple MDFTs. The results reveal a significant correlation among the eight MDFTs suggesting that modern technologies are interrelated. The MVP model results indicate that household income, education level, number of extension contacts, access to credit, farmer group membership, farming experience and livestock monetary value had positive effect on the adoption of MDFTs. Education level and extension contacts had a positive influence on the adoption of fodder establishment and preservation technologies. Farming experience in dairy farming had a positive effect on the adoption of well-structured and clean sleeping areas, and the growth of Rhodes grass. Household income had a positive effect on the growth of Rhodes grass and feed mixture. This work illustrates a need for a policy implication and insight into a need for the county government and private milk processing companies to increase extension frequency to enhance the adoption of MDFTs. Additionally, there is a need to increase access to affordable credit, this should be considered by the government by establishing strengthening a smallholder low-interest and efficient local credit schemes and institutions.

Examining the Impact of Vulnerability and the Law of Justice on the IFRS Adoption Decision

We investigate the impact of vulnerability and the law of justice indicators on the decision to adopt International Financial Reporting Standards (IFRS) by 133 countries. Applying robust Logit and Probit models to 2021 cross-sectional data, we find that the absence of corruption, state illegitimacy, a well-functioning civil justice system, and insufficient public services are helpful for IFRS adoption. On the other hand, results show that a country’s uneven economic development and human rights violations are detrimental to IFRS adoption. Our research confirms that requiring higher standards for financial and accounting reporting in the media, allocating sufficient budget amounts to support an equitable civil justice system, and coordinating efforts to reduce or eliminate economic inequality may help IFRS adoption. We argue that highlighting the positive benefits of IFRS adoption and the commensurate constructive policy outcomes may add the emphasis needed to convince governmental leaders to move toward IFRS adoption.

Does non-farm employment influence a farmer’s decision to adopt hybrid rice seeds or improved variety?

Purpose. The study aims to examine the effect of non-farm employment decisions on the adoption decision of rice hybrid seeds or improved variety in Vietnam. Methodology / approach. This study uses panel data from the Vietnam Access to Resources Household Survey (VARHS) 2008–2016 dataset. The study uses the correlated random effect Probit model with the Mundlak approach to control unobserved heterogeneity of panel data and the endogenous switching Probit model (ESPM) to solve the endogeneity problem and self-selection of the non-farm participation variable. Results. There has been increasing interest that the development of rural non-farm employment has effects on agricultural production as well as agricultural growth. However, still relatively poor understanding of how non-farm participation affects the farmers’ decision to adopt modern technologies in the face of market failure. Our findings indicate that non-farm employment has a positive effect on the adoption of rice hybrid seeds or improved varieties in Vietnam. The value ATT is predicted from the endogenous switching Probit model, which implies that farm households who engage in non-farm employment had a 35.1 % of probability of modern varieties adoption, vs. 19.0 % in the sample overall. Originality / scientific novelty. This study adds evidence from a developing country (using the example of Vietnam) to the broader literature on the role of non-farm employment participation on farmers’ adoption behaviour under market imperfections. In addition, the research addresses the limitations of unobserved heterogeneity of an unbalanced panel by applying the Mundlak approach and contributes to the literature by controlling the endogenous problem and self-selection problem of non-farm participation by using the endogenous switching Probit model. Practical value / implications. Based on the empirical results of this paper, some policy implications are provided to develop the rural non-farm sector and to diffuse modern technologies among rural farmers.

A decision support framework for best-fitting blockchain platform selection in sustainable supply chains under uncertainty

Despite blockchain’s potential to enhance visibility and traceability in sustainable supply chains (SCs), its adoption is complex due to the various criteria (e.g., interoperability and cost) required for the best-fitting platform selection. This study aims to investigate conflicting criteria in the blockchain technology (BT) platform selection process for decision-making under uncertainty. We propose a three-phase decision support framework to study BT adoption considering technological, organizational, and environmental contexts. In the first phase, after exploring the evaluation criteria from multiple contexts, the developed framework incorporates uncertainty and reliability to deal with the BT platform evaluation problem. Then, fuzzy cognitive map modeling, advanced by a Z-number-based inference system, is introduced to model the causal relationships between criteria. This is followed by implementing a hybrid learning algorithm to assess the impact of each criterion on adoption decisions. Finally, the fuzzy combined compromise solution embedded in the framework prioritizes BT platforms to identify the most suitable ones for sustainable SC. The findings imply that performance efficiency, implementation costs, maintainability and operability can significantly affect the BT platform selection decisions. The outcomes offer more stable, reliable, and distinguishable solutions for the proposed problem compared to the traditional approaches. The results introduce Hyperledger and R3 Corda as the best-fitting platforms for adoption based on the identified criteria.