Drivers Of Adoption Research Articles

The role of Video on Demand in stimulating broadband adoption

In this paper we study the role of Video on Demand services (VOD) as drivers of broadband adoption. While the research literature has highlighted the importance of digital content, such as applications and Internet platforms, as a driver of broadband adoption, no studies have yet explored the specific contribution of VOD. We developed a worldwide database of VOD services launch by country since 2012 (including Netflix, Amazon Prime, Apple TV+, Disney+, Paramount+, and HBO Max) and explored their contribution as contributors to broadband adoption during the period. To do so, we relied on several empirical specifications including instrumental variables to control for reverse causality between broadband adoption and VOD services availability. Our results confirm that VOD services have been a key contributor to the increase of broadband connectivity, also helping to narrow down the digital divide especially in developing nations. In addition, VOD service offers have been associated with the gradual increase in the purchasing of broadband higher speed plans. Finally, there is a significant and positive increase in consumer surplus associated with the launch of VOD offers. This evidence points to the impact of VOD services on the digital economy as a stimulus for consumer acquisition of broadband services and therefore as a contributor to the revenues of broadband service providers.

Analyzing the drivers of blockchain adoption for supply chain in Pakistan

Purpose In recent years, technological advancement has played a crucial role in the growth of emerging economies. However, as with any novel technological development, there are often concerns and hesitations surrounding its implementation. This study aims to investigate the factors influencing blockchain adoption and usage. Thereby evaluating its impact on supply chain performance. Design/methodology/approach This is a deductive research based on the modified form unified theory of acceptance and use of technology, which is a persuasive model that has been used in numerous studies on the acceptance and usage of information technology systems. For this study, valid data was collected from 129 management-level supply chain professionals and policymakers working in diverse manufacturing industries. The collected data was used for testing hypotheses by deploying the structural equation modeling technique. Findings The findings of this study reveal that facilitating conditions and technology readiness highly are key influencers for organizations to implement this disruptive technology. Moreover, blockchain adoption and usage can significantly enhance supply chain performance. Originality/value Blockchain technology is a novel and promising disruptive technology that industries are looking forward to adopting and using. For the policymakers and supply chain strategists working in a developing country, this study offers a comprehensive viewpoint on the swift acceptance and usage of blockchain technology to facilitate supply chain operations.

Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour

Drawing on the Theory of Planned Behaviour (TPB), this study investigates the relationship between the perceived benefits, strengths, weaknesses, and risks of generative AI (GenAI) tools and the fundamental factors of the TPB model (i.e., attitude, subjective norms, and perceived behavioural control). The study also investigates the structural association between the TPB variables and intention to use GenAI tools, and how the latter might affect the actual usage of GenAI tools in higher education. The paper adopts a quantitative approach, relying on an anonymous self-administered online questionnaire to gather primary data from 130 lecturers and 168 students in higher education institutions (HEIs) in several countries, and PLS-SEM for data analysis. The results indicate that although lecturers' and students' perceptions of the risks and weaknesses of GenAI tools differ, the perceived strengths and advantages of GenAI technologies have a significant and positive impact on their attitudes, subjective norms, and perceived behavioural control. The TPB core variables positively and significantly impact lecturers' and students’ intentions to use GenAI tools, which in turn significantly and positively impact their adoption of such tools. This paper advances theory by outlining the factors shaping the adoption of GenAI technologies in HEIs. It provides stakeholders with a variety of managerial and policy implications for how to formulate suitable rules and regulations to utilise the advantages of these tools while mitigating the impacts of their disadvantages. Limitations and future research opportunities are also outlined.

A sentiment analysis approach for understanding users’ perception of metaverse marketplace

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace's revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding security and privacy within the Metaverse, pointing to a critical area for development and assurance. The study also reveals a substantial neutral sentiment, reflecting users’ cautious but interested stance, particularly regarding the marketplace's role in investment and passive income opportunities. This balanced view underscores the evolving nature of user perceptions in this emerging field. Theoretically, the research enriches the discourse on technology adoption, particularly in virtual environments, by highlighting perceived benefits and enjoyment as significant adoption drivers. These insights are invaluable for stakeholders in the Metaverse Marketplace, guiding the development of more secure, engaging, and user-friendly platforms. While providing a pioneering perspective on Metaverse user perceptions, the study acknowledges its limitation to Twitter data, suggesting the need for broader research methodologies for a more holistic understanding.

Modelling the relationship between circular economy barriers and drivers for sustainable construction industry

Circular economy (CE) is an emerging concept in the construction industry that focuses on maintaining materials in a continuous cycle to maximize their value. Although previous studies have explored CE in different contexts, there is a lack of studies investigating the relationship between CE barriers and drivers in developing countries. To address this gap, this study aims to identify a list of barriers and drivers of CE adoption and investigate their relationship. The literature review classifies 21 barriers into four constructs, including market policy and technology-related, legal and institutional, supply chain-related, and product design and waste management barriers. Through a questionnaire-based survey with respondents mainly from the Ghanaian construction industry, the research uncovers the most critical barriers within each construct and identifies 13 out of 16 drivers to be critical for CE implementation. The relationship between CE barriers and drivers is found to be significant and substantial, as demonstrated by the path coefficient (β = 0.723) and the p-value (<0.05). This study's outcomes offer both theoretical and practical implications for academic and industry practitioners, empowering them to craft evidence-based strategies that facilitate successful CE adoption in developing nations.

Adoption determinants of improved cassava varieties and intercropping among East and Central African smallholder farmers

AbstractA key constraint to cassava productivity in Africa is the lack of adoption of improved cassava varieties tolerant to pests and diseases. To understand the drivers of adoption behavior, we examine the simultaneous adoption of improved cassava varieties and intercropping by 1200 smallholder farmers in Malawi, Tanzania, and Uganda. Using a linear model, we find that varietal characteristics, such as yield and early maturity, are critical drivers of adoption. Access to extension and credit is associated with an increase in the attractiveness of yield‐improving characteristics. We conclude that a more targeted extension approach would increase technology adoption in these countries.

Examining user behavior with machine learning for effective mobile peer-to-peer payment adoption

Disruptive innovations caused by FinTech (i.e., technology-assisted customized financial services) have brought digital peer-to-peer (P2P) payments to the fore. In this challenging environment and based on theories about customer behavior in response to technological innovations, this paper identifies the drivers of consumer adoption of mobile P2P payments and develops a machine learning model to predict the use of this thriving payment option. To do so, we use a unique data set with information from 701 participants (observations) who completed a questionnaire about the adoption of Bizum, a leading mobile P2P platform worldwide. The respondent profile was the average Spanish citizen within the framework of European culture and lifestyle. We document (in this order of priority) the usefulness of mobile P2P payments, influence of peers and other social groups such as friends, family, and colleagues on individual behavior (that is, subjective norms), perceived trust, and enjoyment of the user experience within the digital context and how those attributes better classify (potential) users of mobile P2P payments. We also find that nonparametric approaches based on machine learning algorithms outperform traditional parametric methods. Finally, our results show that feature selection based on random forest, such as the Boruta procedure, as a preprocessing technique substantially increases prediction performance while reducing noise, redundancy of the resulting model, and computational costs. The main limitation of this research is that it only has a place within the sociocultural and institutional framework of the Spanish population. It is therefore desirable to replicate this study by surveying people from other countries to analyze the effects of the institutional environment on the adoption of mobile P2P payments.

Behavioural drivers of long-term land leasing adoption: application of an extended theory of planned behaviour

AbstractIncreasing agricultural productivity while also protecting the environment, requires careful stewardship of the most important resource in production – land. Most land in Northern Ireland is controlled via owner occupation and granting access to others is a matter for careful consideration. Proprietorial caution, combined with custom and values attributed to land in the region has resulted in a pattern of tenure dominated by short-term rental agreements called conacre. An insecure, short-term land rental system, such as the conacre may be a disincentive to farmers in their decision-making around investing in land management and development, consequently resulting in reduced farm-level sustainability. In this study, we analysed the psychological and behavioural factors influencing farmers’ intention to take up long-term land leasing in Northern Ireland. To achieve our objective, we employed a mixed-methods approach and statistically analysed our quantitative data using an extended theory of planned behaviour (TPB) approach in a structural equation modelling framework. The results of our analyses showed that attitude, perceived behavioural control, subjective norm and perceived risk were statistically significant determinants of farmers’ intention to adopt long-term land leasing. The study results have important implications for the design of effective policies aimed at encouraging long-term land leasing through behavioural change to ensure sustainable agricultural production and effective land management.

From intentions to actions: unveiling the socio-psychological drivers of solar home system adoption in developing nations

ABSTRACT In the face of an expanding global population and the diminishing reservoirs of natural resources, humanity stands at a critical juncture necessitating timely decisions for a secure and sustainable future, ensuring an uninterrupted supply of green energy. The imperative calls for comprehensive implementations across societal echelons, garnering support from all stakeholders. This study explores the adoption dynamics of solar housing systems (SHS) by investigating the direct impact of associated effort and performance expectancy, incorporating an econometric perspective. Additionally, it scrutinizes the moderating effect of buyer awareness regarding these systems. Utilizing 205 survey responses, the research employs econometric analysis to underscore the pivotal roles of performance expectancy, effort expectancy, and buyer knowledge in shaping SHS adoption in Pakistan. The findings not only offer valuable insights into the dynamics of fostering environmentally conscious practices at an individual level but also contribute to the broader understanding of sustainable energy adoption from an econometric standpoint. This research holds practical implications for policymakers and stakeholders engaged in promoting greener initiatives, providing a foundation for informed decision-making in the pursuit of a sustainable energy future.

Sustainable Shift: Analyzing Drivers for Low-Carbon Transportation Adoption in California’s Heavy-Duty and Off-Road Sectors

The transportation sector stands out as a major challenge for California’s transition to a more sustainable transportation system, as it accounts for most of the greenhouse gas emissions. This underscores the urgency for government agencies to take decisive action in promoting the adoption of low-carbon transportation (LCT) within the heavy-duty vehicle (HDV) and off-road equipment (ORE) sectors. This study employs content analysis to investigate the impact of behavioral factors, specifically awareness and impression, on LCT adoption within these sectors. The analysis results are refined using a generative artificial intelligence (AI) tool. The results indicate that awareness about LCT, in conjunction with factors such as government incentives and environmental considerations, positively influences the likelihood of adopting LCT. Moreover, the findings highlight the significant impact of financial barriers on small-fleet organizations, reflecting the inherent challenges these entities may encounter in adapting to significant changes. Conversely, technical barriers are particularly notable for adopters and larger organizations. These insights provide valuable guidance for government agencies to develop targeted strategies, including mandates and incentives, tailored to the specific needs of organizations within the HDV and ORE sectors. By addressing these barriers and fostering a supportive environment for sustainable practices, policymakers can accelerate California’s transition toward a greener transportation landscape.

Drivers of wearable fitness technology adoption for health care: an investigation through organismic integration and regulatory focus theory

PurposeIn the prior literature, the motivation to adopt wearable fitness technology (WFT) has been linked with either intrinsic or extrinsic. However, how the subcategories of extrinsic motivations (identified, introjected and external) affect the consumers’ WFT adoption decision remains sparse. Furthermore, do regulatory focus (prevention vs promotion) and gender differences the effects of different motivations on WFT adoption is almost unknown in the health-care marketing literature. This study aims to fill the above-mentioned gap and to unfold the WFT adoption beyond the traditional motivation by incorporating the organismic integration theory (part of self-determined theory) and regulatory focus theory.Design/methodology/approachThis study used a questionnaire-based survey. Using the “AMOS” survey, questionnaire responses of 641 respondents were analyzed and validated by using structural equation modeling. All the variables were adopted from the literature.FindingsThe results show that intrinsic, identified and external motivations have the greatest impact on consumers’ decisions, while introjected motivation was not significant directly. The moderation effects of regulatory focus are significant in such a way that prevention focus influences the introjected motivation and promotion focus affects the external motivation and WFT adoption decision. Furthermore, the findings on gender moderation suggest that women are more intrinsically motivated, and men are more externally motivated for WFT adoption.Practical implicationsThe new insights and contributions of this study provide a better understanding of WFT adoption and help sellers develop more effective marketing strategies.Originality/valueThis study incorporates subcategories of extrinsic motivations to provide a deeper understanding of consumers’ behavior. Furthermore, this study applies a unique framework of organismic integration theory to consumers’ WFT adoption. It is also among very few research that investigate regulatory focus and gender impact on consumers’ WFT adoption.

CONSUMER ADOPTION OF MOBILE PAYMENT IN THE KINGDOM OF SAUDI ARABIA AN EMPIRICAL STUDY

Objective: The rapid stride in mobile payment adoption has transformed the payment practices in the 21st Century. Admittedly, m-payment practice has become more intense due to the surge in usage of internet, mobile devices (smart phones), accelerated further by the spread of the Covid-19 Pandemic. Against such a backdrop, it is the need of the hour to investigate: Why are people starting to use mobile payments more and how will that affect their purchasing habits? The study's intention is to add to what's already been written on electronic banking and mobile banking specifically. The study provides a report on m-banking's development, assesses the potential for its adoption, and identifies potential avenues for expansion in Saudi Arabia. They aid Saudi Arabian banking decision-makers in locating and developing strategies for supplying m-banking services that will help them keep their competitive edge. Methods: While electronically distributed surveys can reach more people more quickly and for less money, this method also has the potential to introduce bias into the sample by excluding people who don't have access to the internet. In addition, the data acquired from the respondents in many mobile payment and mobile banking studies can enhance selection bias. Researchers used both paper-print and online survey methods to disseminate survey instruments, reducing selection bias and increasing response rates. Other potential sources of common method bias (CMB) include the retrospective nature of the survey, the use of a commonly used scale format for constructs, and the fact that respondents were asked to provide information about both the independent and dependent variables in the same question. As a result, SEM has emerged as the gold standard in the field of theory testing, especially as it pertains to studies of IS/IT adoption. Statistical modelling with structural equation modelling (SEM) was chosen as the advanced inferential analytic technique for this study. Aim: The present study also aims to identify the perceived risk, trust, self-efficacy, past experience, attitude, anxiety, and customer support associated with the mobile payment. Lastly, this study will be a path-breaking one because of its intended contribution to the policy-makers and to the society at large in the Kingdom of Saudi Arabia. Needless to say, outcome of the study was providing managerial inputs to various mobile payment platforms. Results: Consumers' intent to utilize mobile banking was strongly correlated with their level of trust and Application of Mobile Banking. In similar way Self-efficacy directly and positively related to the consumer intention towards mobile banking adoption. In the same ways, past experience directly and positively related to the consumer intention towards mobile banking adoption. In the same way, there is a positive and direct relationship between customer intention and the use of mobile banking. Lack of a causal relationship between attitude and consumer desire to use mobile banking. Perceived risk not directly and positively related to the consumer intention towards mobile banking adoption Anxiety not directly and positively related to the consumer intention towards mobile banking adoption. Conclusion: This study intends to identify the various drivers of mobile payment adoption by examining how consumers' spending habits have changed in response to the popularity of mobile payment systems and the relationship between various payment mechanisms. The study's primary aim is to establish precisely the point when mobile payments will become the norm can replace debit and credit card transactions. Besides transaction activities, online payment channels are enhancing mobile payment adoption and lead to increase in the online transactions, local penetration further escalating increased transaction activities.

Assessing and prioritizing crucial drivers for CloudIoT-based healthcare adoption: an analytic hierarchy process approach

Assessing and prioritizing crucial drivers for CloudIoT-based healthcare adoption: an analytic hierarchy process approach

Legal implications of automated suspicious transaction monitoring: enhancing integrity of AI

The fast-paced advances of technology, including artificial intelligence (AI) and machine learning (ML), continue to create new opportunities for banks and other financial institutions. This study reveals the barriers to trust in AI by prudential banking supervisors (compliance with regulations). We conducted a qualitative study on the drivers for adoption of explainability technologies that increase transparency and understanding of complex algorithms (some of the underpinning legal principles in the proposed EU AI Act). By using human-centred and ethics-by-design methods coupled with interviews of the key stakeholders from Eastern European private and public banks and IT AI/ML developers, this research has identified the key challenges concerning the employment of AI algorithms. The results indicate a conflicting view of AI barriers whilst revealing the importance of AI/ML systems in banks, the growing willingness of banks to use such systems more widely, and the problematic aspects of implementing AI/ML systems related to their cost and economic efficiency. Keeping up with the complex regulation requirements comes at a significant cost to banks and financial firms. The focus of the empirical study, stakeholders in Ukraine, Estonia and Poland, was chosen because of the fact that there has been a sharp increase in the adoption of AI/ML models in this jurisdiction in the context of its war with Russia and the ensuing sanctions regime. While the “leapfrogging” AI/ML paths in each bank surveyed had its own drivers and challenges, these insights provide lessons for banks in other European jurisdictions. The analysis of four criminal cases brought against top banks and conclusions of the study indicate that the increase in predicate crimes for money laundering, constantly evolving sanctions regime along with the enhanced scrutiny and enforcement action against banks are hindering technology innovation and legal implications of using AI driven tools for compliance.

Adoption Model Choice Affects the Optimal Subsidy for Residential Solar

Understanding the adoption patterns of clean energy is crucial for designing government subsidies that promote the use of these technologies. Existing work has examined a variety of adoption models to explain and predict how economic factors and other technology and demographic attributes influence adoption, helping to understand the cost-effectiveness of government policies. This study explores the impact of adoption modeling choices on optimal subsidy design within a single techno–economic framework for residential solar PV technology. We applied identical datasets to multiple adoption models and evaluated which model forms appear feasible and how using different choices affects policy decisions. We consider three existing functional forms for rooftop solar adoption: an error function, a mixed log-linear regression, and a logit demand function. The explanatory variables used are a combination of net present value (NPV), socio-demographic, and prior adoption. We compare how the choice of model form and explanatory variables affect optimal subsidy choices. Among the feasible model forms, there exist justified subsidies for residential solar, though the detailed schedule varies. Optimal subsidy schedules are highly dependent on the social cost of carbon and the learning rate. A learning rate of 10% and a social carbon cost of USD 50/ton suggest an optimal subsidy starting at USD 46/kW, while the initial subsidy is 10× higher (USD 540/kW) with a learning rate of 15% and social carbon cost of USD 70/ton. This work illustrates the importance of understanding the true drivers of adoption when developing clean energy policies.

Risk aversion, impatience, and adoption of conservation agriculture practices among smallholders in Zambia

Sustainable agricultural practices such as conservation agriculture have been promoted in southern Africa for nearly three decades, but their adoption remains low. It is of policy interest to unpack behavioural drivers of adoption to understand why adoption remains lower than anticipated. This paper assesses the effects of risk aversion and impatience on the extent and intensity of the adoption of conservation agriculture using panel data collected from 646 households in 2021 and 2022 in Zambia. We find that 12% and 18% of the smallholders were impatient and risk averse, respectively. There are two main empirical findings based on panel data Probit and Tobit models. First, on the extensive margin, being impatient is correlated with a decreased likelihood of adopting combined minimum-tillage (MT) and rotation by 2.9 percentage points and being risk averse is associated with a decreased propensity of adopting combined minimum tillage (MT) and mulching by 3.2 percentage points. Being risk averse is correlated with a decreased chance of adopting basins by 2.8 percentage points. Second, on the intensive margin, impatience and risk aversion are significantly correlated with reduced adoption intensity of basins, ripping, minimum tillage (MT), and combined MT and rotation by 0.02–0.22 ha. These findings imply a need to embed risk management (e.g., through crop yield insurance) in the scaling of sustainable agricultural practices to incentivise adoption. This can help to nudge initial adoption and to protect farmers from yield penalties that are common in experimentation stages.

Drivers of Organic Rice Adoption Among Smallholder Farmers: Implications for Sustainable Development

Drivers of Organic Rice Adoption Among Smallholder Farmers: Implications for Sustainable Development

Strategic enablers: Unveiling crucial drivers for managerial adoption of electronic resources planning

The rapid growth of the information technology industry has spurred corporate process digitalization. This study aims to examine how the Unified Theory of Acceptance and Use of Technology’s (UTAUT) major tenets – performance expectancy and effort expectancy – and trust affect managers’ acceptance of new e-fulfillment services. This study also considers Hofstede’s cultural dimension of long-term orientation as the major variable influencing management’s acceptance of the new fulfillment platform. This study employed a quantitative research methodology with a simple random sampling of 248 Indonesian Logistic Association members from various industries. The research finding shows that only effort expectancy does not significantly affect managers’ e-fulfillment platform usage. Both effort expectancy and performance expectancy have a significant impact on employee trust in using the new technology. In addition, performance expectancy, customer trust, and long-term orientation positively affect the managerial adoption of e-fulfillment services. The study also shows a full mediation effect of customer trust in the relationship of effort expectancy to managerial adoption and a partial mediation effect in the influence of performance expectancy into managerial adoption of electronic resources planning with trust as a mediating variable. AcknowledgmentThis study is conducted with the support from the Ministry of Education, Culture, Research, with the Contract No. 1170/LL3/AL.04/2023; 0059-RD-LPPM-UMN/P-JD/V/2023.

Understanding the drivers of rural household scaling up of integrated crop-livestock-forestry systems. A systematic review and bibliometric analysis

This literature review focuses on the drivers of Integrated Crop-Livestock-Forestry Systems (ICLFS) adoption by small farmers. It has enabled us to identify current trends and analyze the various drivers of adoption and knowledge gaps. According to the PRISMA literature review protocol, 1,352 scientific publications have been selected and analyzed after a Scopus database search. Data analysis was carried out in two steps. A systematic review was performed with the metadata of scientific publications using the Biblioshiny package of R 4.3.1 software. Then, the 42 most relevant publications were used for a brief narrative synthesis. The results showed that between 2003 and 2023, publications were made in 587 different sources. 73% of publications were scientific articles. 91% of publications were written by an average of 05 co-authors. The effectiveness of Integrated Crop-Livestock-Forestry Systems (ICLFS) practices, the production of organic matter and the effects on farmers’ livelihoods are the research topics considered. Five categories of factors were identified to facilitate the adoption of ICLFS by small farmers: (i) farmer profile, (ii) farm characteristics, (iii) economic factors, (iv) institutional factors and (v) biophysical factors. Policy orientations are the most decisive of all the factors identified, followed by the establishment of extension systems and social networks between farmers. This paper makes three main recommendations. Firstly, it recommends the implementation of collaborative research frameworks between West African researchers and those from East Africa, Asia and South America, who have more experience in this area. In addition, this study suggests that future research on the adoption of ICLFS should take into account herd mobility issues in the adoption process. Finally, it suggests that ICLFS should be taken into account in development policies and implemented through action research projects, mostly in West Africa.

Healthy people, soils, and ecosystems: uncovering primary drivers in the adoption of regenerative agriculture by US farmers and ranchers

As regenerative agriculture grows in popularity, policy and decision-makers have become interested in its practices. Yet, little is known about those factors driving its adoption among farmers and ranchers. To better understand these drivers, we conducted semi-structured interviews with 31 farmers and ranchers across the United States (US) who self-identified as practitioners of regenerative agriculture. In doing so, we asked about relational values, which reflect one’s perspectives around the links between humans and nature. We also asked about economic and environmental drivers for adoption. In the analysis, we used qualitative coding to identify the range of values and factors driving adoption across our sample. We found that 1) improving the health of people, soils, and ecosystems - through farming practices and related social configurations - was a primary driver for adoption, 2) that relative economic privilege, particularly across two extremes - privileged idealism and less privileged necessity - correlated with most drivers for adoption, 3) that a shift away from industrial agriculture was at once a moral, economic, and environmental imperative for many practitioners, and 4) a systems view of social-ecological relationships was seen as a key to adoption and societal transitions. While our sample represents only a narrow segment of the regenerative agriculture movement in the US, our findings can serve as a useful starting point for understanding the drivers for its adoption. Our findings may also inform conversations on regenerative agriculture’s potential to support food-related sustainability transitions. The discussion situates our work amidst sustainable agriculture and social movement studies, questions of equity in food systems transitions, and the benefits of studying values in developing policy-relevant solutions.