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• Social anxiety affects traditional taxi services. • Social pressure and norms have a strong influence on transition intention. • Perceived control over technology is a key driver of actual behavioral change. • Habitual behavior plays a moderating role in the adoption of new technologies. • Passengers' transition behavior is driven by their perception of technology control. Robotaxi services integrate autonomous driving technology with traditional online ride-hailing and can meet the increasing demand for urban transportation. This study analyzed the factors influencing passengers' intentions to transition from traditional ride-hailing to robotaxi services. Using the stimulus-organism-response framework and theory of planned behavior, we examined social anxiety (social environment anxiety, social performance concern, and stranger interaction avoidance) and technological factors (perceived technical safety and perceived operational safety) as external stimuli affecting individuals' internal states and behaviors. Data from 510 valid questionnaires collected in China's first-tier cities (Beijing, Shanghai, Guangzhou, and Shenzhen) revealed that social anxiety and perceived safety significantly affected transition intentions. Among the social anxiety variables, social environment anxiety had the strongest influence, followed by social performance concerns and stranger interaction avoidance. Additionally, travel habits emerged as a significant moderator between subjective norms and transition intentions and between perceived behavioral control and both transition intentions and behaviors. The classification of user groups based on levels of social anxiety and travel habits provided valuable insights; for instance, passengers with high social anxiety and weak travel habits were more inclined to transition to robotaxi services. These findings offer practical implications for urban planners and robotaxi service providers to address transportation challenges in rapidly urbanizing areas. [ABSTRACT FROM AUTHOR]

• Geriatric nurses acknowledged the potential benefits of AI in improving diagnostic accuracy, personalized care, continuous monitoring, and data pattern insights. • Challenges and barriers to AI adoption included workflow integration issues, cost concerns, resistance to change, data privacy risks, and fears of diminishing human elements of care. • Ethical considerations centered on safeguarding patient data, preserving the patient-nurse relationship, and the need for clear ethical guidelines and policies. • Nurses expressed cautious optimism towards AI adoption, emphasizing the importance of addressing practical challenges while maintaining the human touch. • Comprehensive training, user-centered design, ethical frameworks, and strategies to overcome financial barriers are crucial for successful AI implementation in geriatric care. This phenomenological study explored the perspectives of geriatric nurses on the adoption of artificial intelligence (AI) in elderly care. Thematic analysis of semi-structured interviews with 17 nurses revealed perceived benefits, challenges, ethical considerations, and practical implications. Participants acknowledged AI's potential for improving diagnostic accuracy, personalized care, continuous monitoring, and data pattern insights. However, concerns were raised regarding workflow integration, cost barriers, resistance to change, data privacy, diminishment of human elements, and the need for ethical guidelines. A cautious optimism was expressed, emphasizing the importance of addressing practical challenges, maintaining the human touch, and fostering a collaborative approach. The findings highlight the need for comprehensive training, user-centered design, ethical frameworks, and strategies to overcome financial and implementation barriers. Future research should focus on evaluating the impact of AI implementation on patient outcomes and nursing experiences. [ABSTRACT FROM AUTHOR]

This exploratory study delves into the factors influencing digital technology adoption and the dynamics of its institutionalization within the Thai maritime industry, a key sector underpinning Thailand's economic expansion. Data was collected through semi-structured interviews with executive leaders from seven Thai shipowners, utilizing a snowball sampling method. The study reveals that digital technology adoption is driven by a complex interplay of factors including reliable IT infrastructure, perceived technological benefits, organizational culture, top management support, IT skills and support, legal, regulatory, and policy requirements, social pressure influence, and varying degrees of government support. Additionally, the institutionalization of such technologies within the maritime sector is heavily reliant on well-defined organizational rules and the establishment of trust in technological advancements. These findings not only enrich the theoretical landscape regarding digital adoption but also offer practical insights for industry stakeholders, paving the way for more nuanced interventions and policy formulations aimed at enhancing digital integration in this traditionally conservative sector. [ABSTRACT FROM AUTHOR]

This research intends to assess the influence of innovation and strategic planning on MSME performance, utilizing technology adoption as a moderator. The work fills the gap in previous research by integrating these four aspects, which have not been fully explored together before. Using a quantitative methodology, this study focuses on MSMEs in the Jakarta region. The researcher adopted the snowball sampling technique, seeking the cooperation of research participants to identify suitable subjects for further inquiry. Friends operating MSME firms were requested to disseminate questionnaires to their contacts, leveraging personal ties with these business owners. A total of 220 surveys were successfully conducted. The results reveal that innovation has a considerable negative influence on MSME performance. Conversely, strategic planning favourably improves MSME performance, according with past studies. Additionally, technology adoption mitigates the harmful effects of innovation on MSME performance and improves the influence of strategic planning on performance improvement. This study contributes to the understanding of MSME success by evaluating the combined effects of innovation, strategic planning, and technology adoption. It fills a gap in existing research by merging these factors and studying their interaction. The findings give useful insights for policymakers, business owners, and researchers seeking to promote the sustainability and competitiveness of MSMEs in Indonesia, particularly in Jakarta. Moreover, the study shows the importance of strategic planning and technology adoption as tools to minimize the detrimental impact of innovation on MSME performance, presenting practical implications for MSME development strategies. [ABSTRACT FROM AUTHOR]

Output uncertainty is a major concern for industries prone to exogenous, persistent and large fluctuations in output, such as agriculture, wind and solar power generation, while technology adoption aimed at mitigating output uncertainty can improve social welfare. This paper constructs a competitive market model with random output fluctuations to examine the scale of technology adoption at the long-term equilibrium and its comparison with the social optimum. We show that the First Welfare Theorem no longer holds in general, and depending on the characteristics of the demand function, the scale of technology adoption in the competitive market may be greater or less than the socially optimal scale. • We consider technology adoption aimed at mitigating output uncertainty in the competitive market. • We show that the First Welfare Theorem no longer holds in general. • We show that the scale of technology adoption in the competitive market may be too high or too low. [ABSTRACT FROM AUTHOR]

Antimicrobial use (AMU) data are essential to monitor the effect of AMU reduction strategies in animal health. The use of technology and herd recording software to record AMU will be vital to scale the collation of these data in the future. The aim of this study was to determine the barriers and facilitators to Irish dairy farmers recording their AMU using a herd recording software and sharing AMU data. Thirty-three Irish dairy farmers involved in a study on AMU monitoring were asked to record their AMU using a herd recording software over a 12-mo period. At the end of the 12-mo period, 10 of these farmers were selected to take part in semi-structured interviews exploring their opinions on recording AMU, the use of herd recording software, and sharing AMU data. Interviews were transcribed and qualitatively analyzed using inductive thematic analysis. Several barriers and facilitators to farmers recording their AMU using a herd recording software and sharing AMU data were identified. Barriers included the age and generation of the farmer, farm infrastructure, a lack of training and education, a lack of knowledge around the benefits of digital data, a lack of incentive to digitize records, and a fear of repercussions. Facilitators identified by the farmers included the benefits of having instantly available data for making herd management decisions, reduced paperwork, increased organization for inspections, and a potential positive effect on the image of the dairy industry. To increase the uptake of new technology to record AMU at farm-level, farmers will need support in terms of education and training around the software available to them and reassurance around the perceived risks of repercussions with sharing data in a digital format. [ABSTRACT FROM AUTHOR]

This study examines the adoption of a new preventive treatment for HIV called preexposure prophylaxis (PrEP) in a nation-wide network of US physicians. We compare the structure of these networks across nine multi-state census regions, and assess geographic variations in network structure. Within these networks, we measured the adoption threshold associated with physician adoption of PrEP. The low threshold values that we observe are consistent with the hypothesis that slow PrEP adoption is the result of a lack of knowledge and exposure among physicians. Regression results demonstrate the mix of market, epidemiological, and socio/cultural factors that shape adoption thresholds. • The structural topologies of the physician networks vary dramatically between census regions. • Thresholds for PrEP adoption were low, suggesting that its slow adoption may have been due to a lack of physician knowledge. • Physicians' adoption thresholds were conditioned by both social and epidemiological factors. [ABSTRACT FROM AUTHOR]

As part of its efforts to secure a 'net-zero society', the UK government will take a strategic decision on the role of hydrogen in decarbonising homes within the next years. While scholars have recently advanced the social science research agenda on hydrogen technology acceptance, studies are yet to engage with the prospective dynamics of adopting 'hydrogen homes'. In response, this study examines the perceived adoption potential of hydrogen heating and cooking technologies, as evaluated through the eyes of consumer. Engaging with behavioural and market acceptance, this research draws on data from a broadly nationally representative online survey to examine the influence of safety, technological, economic, environmental, and emotional factors on the domestic hydrogen transition in the UK context. The analysis follows a multi-stage empirical approach, integrating findings from partial least squares structural equation and necessary condition analysis to crystallise insights on this emergent subject. At this juncture, perceived adoption potential may hinge primarily on emotional, environmental, safety, and to a lesser extent, technological perspectives. However, consumers have an expressed preference for hydrogen heating over hydrogen cooking, with perceived boiler performance emerging as a necessary condition for enabling adoption potential. At the formative phase of the transition, risks associated with energy insecurity and fuel poverty exceed concerns over purchasing and running costs. Nevertheless, economic factors remain less critical during the pre-deployment phase of the innovation-decision process. Across the full sample, simple slope analysis highlights the moderating effects of gender, age, and housing tenure. Moreover, statistically significant differences from both a sufficiency- and necessity-based perspective are detected between male property owners aged 55+ and female mortgage owners 18–34 years old. By bridging the knowledge gap between social acceptance and adoption intention, this contribution reinforces the need for consumer engagement in the hydrogen economy, advocating for more fine-grained, mixed-methods analyses of technology acceptance dynamics to support decarbonisation strategies. [Display omitted] • Economic factors constrain the perceived adoption potential of hydrogen homes. • The emotional dimension of hydrogen acceptance is highly influential. • Perceived adoption potential is contingent on safety and environmental perspectives. • Gender, age, and housing tenure status are potentially powerful moderators. • The role of hydrogen cooking warrants justification ahead of policy decisions. [ABSTRACT FROM AUTHOR]

Information technology infrastructure (ITI) has gone through an exponential change due to the rapid evolution of digital technologies during the past few years. It is therefore relevant to identify the factors that push organizations towards the adoption of new technologies. This paper considers a specific case study of the higher education institutions (HEI) to present (i) the motivational factors that push HEIs toward the adoption of new technologies, and (ii) the key challenges HEIs face in the adoption of these technologies. The data was gathered after conducting 17 open-ended interviews with practitioners working at HEIs in Finland and Pakistan. Data analysis identified 10 motivational factors and 41 challenges faced by HEI in the adoption of the latest technologies. Furthermore, the data was further classified to identify broad themes and categories representing the challenges and motivation factors. [ABSTRACT FROM AUTHOR]

Video consultations and telemedicine play a key role in healthcare. It is crucial to assist institutions in identifying which patients are more likely to use them, increasing the adoption rate. Even though Artificial Intelligence models are important, certain cases require a human centric approach to inform patients and doctors, ensuring trust in the tools provided. This can be achieved through interpretable Machine Learning models and Statistical Analysis. In this paper we show that even though the accuracy of the Machine Learning models used (Decision Trees, Logistic Regression, and Random Forest) was between 84%-89% on the training set and 69%-76% on the test set the models lacked good ability to identify the users. Afterwards, additional statistical analysis evidenced that the main driver to use video consultations in a sample of participations with a higher-than-average education is the presence of one or more chronic diseases. [ABSTRACT FROM AUTHOR]

The accelerated rate of technological progress has significantly altered how individuals and or-ganizations interact with technology. Understanding the process of technology adoption has be-come crucial for remaining competitive in a world that is becoming increasingly digital. This entry provides an overview of numerous technology adoption models, shedding light on the factors that influence the adoption of new technologies by individuals and organizations. This entry examines the Technology Acceptance Model (TAM) is examined, with an emphasis on perceived utility and usability. Focusing on performance expectation, effort expectation, social influence, and facilitat-ing conditions, the Unified Theory of Acceptance and Use of Technology (UTAUT) is presented. In addition, the Technology-Organization-Environment (TOE) Framework is discussed, taking in-to account the three factors that influence adoption decisions. The Innovation Adoption Lifecycle is investigated, with the characteristics and motivations of various adopter categories highlighted. Individual, organizational, and external factors that influence the adoption of technology are also examined. The entry concludes by addressing the challenges and limitations of existing models and highlighting the importance of technology adoption research in influencing the future of soci-ety and business. [ABSTRACT FROM AUTHOR]

Online Food Delivery (OFD) is a service innovation that significantly impacts current technological developments in the food and beverage sector. This paper aims to review the academic literature on OFD services systematically. This study reviews all literature published from 2017 until 2022. Literature is classified based on the context, the theory, and the factors influencing the adoption of OFD. The results of this study indicate that twenty-one factors have a dominant influence on OFD adoption. These factors are classified into three categories, namely individual factors, technological factors, and external factors. This study highlights that individual factors are the most commonly used factors for OFD adoption. This study outlines directions for future research and allows a detailed view of consumer behavior in OFD businesses. [ABSTRACT FROM AUTHOR]

Due to the COVID-19 epidemic in March 2020, the government is mandated that schools in Indonesia implement School from Home (SFH) and use online instruction. A community-based learning platform called Zedemy was created during the COVID-19 pandemic to connect social media with online learning environments. The use of Zedemy has yet to be prevalent among teachers and students in Indonesia, as shown by the number of participants, 329 for all courses at Zedemy in 2021. This study used the UTAUT approach to assess user interest and acceptability based on users' voluntariness in utilizing Zedemy as an online learning tool during the COVID-19 epidemic. Surveys were sent to Zedemy users who have used at least one other online learning platform. The data will next be examined using the SmartPLS 3 tool and the SEM method. The findings showed that variables such as performance expectancy, effort expectation, social influence were affecting the behavioral intention of the user, meanwhile facilitating conditions was affecting the use behavior of the user. This research also found that moderating variables may have an impact on the model. [ABSTRACT FROM AUTHOR]

The exponential increase in smartphone and internet utilization in Indonesia offers immense potential for the uptake of mobile payment services. This article explores the critical factors driving the adoption of mobile payment services in the Indonesian context by establishing a conceptual model encompassing personal, technological, and social aspects. Additionally, the study examines potential differences in adoption behavior between male and female users. To achieve these objectives, an empirical survey was conducted, collecting 277 valid questionnaires from GoPay users in Indonesia. The proposed model was analyzed using the path analysis method to measure the relationships between variables. The results indicate that perceived usefulness, social influence, perceived need for minimalism, and security awareness are all crucial determinants of users' intentions to use the service. However, gender differences were found to have little moderating influence on the adoption process. This research offers a comprehensive framework for examining the key factors affecting technological acceptance, benefiting both academicians and practitioners by providing an integrated perspective on the factors influencing users' intentions to use mobile payment services. [ABSTRACT FROM AUTHOR]

• Expected utility theory is not appropriate for understanding the behavior of low-income farmers. • Lexicographic ordering has the advantages of procedural rationality and the behavioral focus on thresholds. • Lexicographic ordering is readily adaptable to the narrative that low income farmers put safety first. • Focusing on safety does not imply avoidance of variance-increasing techniques. As Richard Day explained, expected utility theory suffers from procedural irrationality. This and other problems are illustrated here in the context of decision-making among low-income farmers. Farmers in developing countries are commonly thought to underinvest in modern techniques because their low incomes make them especially risk averse. In addition to the procedural leap of faith, highly restrictive assumptions are needed to apply expected utility theory to the problem. Nor does expected utility theory, as usually prescribed, fit the narrative of loss aversion. The reader is introduced to a procedurally rational substitute called lexicographic safety first. The model is illustrated for the case of rice fertilization in the Philippines, and policy implications are drawn. To illustrate the potential appeal of lexicographic ordering for other applications involving thresholds, a lexicographic model of rational addiction is also provided. [ABSTRACT FROM AUTHOR]

• The study aims to explore the determinants affecting the purchase intention of electric motorcycles. • The study extended the Unified Theory of Acceptance and Use of Technology (UTAUT) by considering national culture to analyze the purchase intention of electric motorcycles. • The results showed that the model could explain 63.6% of the variance in the purchase intention of electric motorcycles. • Performance expectancy, effort expectancy, social influence, facilitating conditions, power distance, and long-term orientation significantly affected purchase intention, while uncertainty avoidance, collectivism, and masculinity were insignificant. • Performance expectancy, effort expectancy, and social influence were found to mediate the relationship between national culture and the purchase intention of electric motorcycles. Migration to electric motorcycles is urgent to reduce air pollution and prevent climate change. However, the adoption rate of electric motorcycles in Indonesia remains very low compared to the number of conventional motorcycles. This study aims to explore the determinants affecting the purchase intention of electric motorcycles. Because every country has a different culture, the key contribution of our research is developing a model to investigate the purchase intention by integrating national culture into the Unified Theory of Acceptance and Use of Technology (UTAUT). This study also investigates the direct and indirect effects of national cultural constructs such as power distance, uncertainty avoidance, collectivism, masculinity, and long-term orientation on purchase intention. This study used a survey and a non-probability method, especially convenience sampling, and obtained 936 valid responses. This study used the confirmatory factor analysis to analyze the construct validity and reliability and the partial least square–structural equation model to test its hypotheses. The results showed that the model could explain 63.6% of the variance in the purchase intention of electric motorcycles. Performance expectancy, effort expectancy, social influence, facilitating conditions, power distance, and long-term orientation significantly affected purchase intention, while uncertainty avoidance, collectivism, and masculinity were insignificant. Performance expectancy, effort expectancy, and social influence were found to mediate the relationship between national culture and the purchase intention of electric motorcycles. The study provides better suggestions to manufacturers and the Government to make more efficient planning and policies by considering the factors influencing purchase intentions. [ABSTRACT FROM AUTHOR]

• This study explores the impact of consumers' contextual reasons (i.e., reasons for and against) on the acceptance of autonomous vehicles (AVs) and investigates how technology readiness influences consumer behavior. • It emphasizes the crucial roles of consumers' technological readiness and social influence in the behavioral reasoning processes related to AV adoption. • For business practitioners and marketers, the findings offer guidelines for developing marketing strategies tailored to individual consumers' adoption levels. The main goal of this study was to investigate the impact of four dimensions of technological readiness on the adoption of autonomous vehicles (AVs): Discomfort, insecurity, optimism, and innovativeness. This study confirmed that reasons for (against) adoption of technology are also important determinants of the intention to use AVs with the moderating effect of social influence on technological readiness and reasons for (against) adoption AVs are also investigated. Thus, this research adds to the existing literature on AVs adoption by establishing the important roles of consumers' technological readiness and social influence through their behavioral reasoning processes. For business practitioners and marketers, the findings provide guidelines for developing marketing strategies that fit an individual customers' level of adoption. [ABSTRACT FROM AUTHOR]

Solar cooking is a sustainable way of cooking and heating that use direct energy from the sun. Despite the introduction of solar cookers in Tanzania, various challenges have hindered the adoption of this technology. This study aims to explore the level of awareness of solar cooking technology among community members, and the main barriers confronting its usage, while exploring factors that can strengthen its adoption in Tanzania. The study is informed by semi-structured questionnaires, in-depth interviews, and a review of relevant documents. The collected quantitative data were subjected to descriptive statistics, while qualitative data were brought under thematic analysis. The study found a good level of understanding and awareness of solar cooking technology among researched communities. Nevertheless, higher prices, poor designs, limited access, weather dynamics were found among factors discouraging successful adoption. Moreover, solar cooking adoption is incentivized by the relief from costs of using of conventional fuels such as fuelwood. The study concludes that solar cooking technology bears a great potential of environmentally friendliness, long term cost saving with zero operational costs, and protects the health of the users from some harmful cooking fuels. This study recommends more efforts to promote the domestic use of solar cooking through education to individuals in the communities and policy interventions to increase its adoption rate in Tanzania. • Awareness and preferences of community influenced adoption solar cookers. • The high costs of solar cookers have resulted in a lower adoption rate in Tanzania. • Some types of solar cookers are slower in cooking compared to fuelwood. • Integrating solar cooking into policymaking can increase adoption rate. [ABSTRACT FROM AUTHOR]

Empirical evidence identifies shortages of specialized labor as one of the main obstacles to technology adoption. In this paper, we explain this phenomenon by developing a model in which firms require specialized labor to produce with a new (more efficient) technology. We assume that the cost of specializing labor increases with the efficiency gains that can be attained through the new technology. This reveals two opposing effects on the endogenous share of specialized labor. On the one hand, there is a wage effect by which efficiency gains widen the wage gap between specialized and unspecialized workers, raising the share of specialized labor. On the other hand, there is a learning effect by which efficiency gains increase specialization costs, reducing the share of specialized labor. We show the learning effect will dominate when products are sufficiently differentiated. [ABSTRACT FROM AUTHOR]

Improved rice varieties (IRVs) play a significant role in establishing food security and improving livelihood in the Global South since its introduction in the 1960s. However, the adoption of new IRVs has remained relatively low. This low adoption poses a challenge to rice-producing and consuming countries as they are increasingly threatened by production shortages, malnutrition, and poor rice quality. Many empirical studies have attempted to identify the determinants influencing the adoption of IRVs by distinguishing the characteristics between adopters and non-adopters. This review showed a consensus on the important determinants influencing the adoption of IRVs in the Global South. Findings synthesized from 99 studies suggested that variables (farm size, education, information access and farm location) examined extensively are not necessarily the most important determinants of adoption when undertaking a weighted analysis. Terrain, source of seed and technology-related attributes (perceived yield, maturity, ease of use, marketability and technical efficiency) are more important determinants of adoption, with determinants changing according to adoption type (probability or intensity of adoption), variety type and region. The recommendations for future adoption studies include: incorporating more technology-specific variables, increasing research for overlooked regions and variety types, shifting away from predominant static analysis by capturing the dynamics of the adoption process, and considering the potential biases in analyses. This review will facilitate the development of targeted interventions and policies that promote IRV adoption in the Global South. [ABSTRACT FROM AUTHOR]

Precision livestock farming (PLF) technologies have been widely promoted as important tools to improve the sustainability of dairy systems due to perceived economic, social, and environmental benefits. However, there is still limited information about the level of adoption of PLF technologies (percentage of farms with a PLF technology) and the factors (farm and farmer characteristics) associated with PLF technology adoption in pasture-based dairy systems. The current research aimed to address this knowledge gap by using a representative survey of Irish pasture-based dairy farms from 2018. First, we established the levels of adoption of 9 PLF technologies (individual cow activity sensors, rising plate meters, automatic washers, automatic cluster removers, automatic calf feeders, automatic parlor feeders, automatic drafting gates, milk meters, and a grassland management decision-support tool) and grouped them into 4 PLF technology clusters according to the level of association with each other and the area of dairy farm management in which they are used. The PLF technology clusters were reproductive management technologies, grass management technologies, milking management technologies, and calf management technologies. Additionally, we classified farms into 3 categories of intensity of technology adoption based on the number of PLF technologies they have adopted (nonadoption, low intensity of adoption, and high intensity of adoption). Second, we determined the factors associated with the intensity of technology adoption and with the adoption of the PLF technology clusters. A multinomial logistic regression model and 4 logistic regressions were used to determine the factors associated with intensity of adoption (low and high intensity of adoption compared with nonadoption) and with the adoption of the 4 PLF technology clusters, respectively. Adoption levels varied depending on PLF technology, with the most adopted PLF technologies being those related to the milking process (e.g., automatic parlor feeders and milk meters). The results of the multinomial logistic regression suggest that herd size, proportion of hired labor, agricultural education, and discussion group membership were positively associated with a high intensity of adoption, whereas age of farmer and number of household members were negatively associated with high intensity of adoption. However, when analyzing PLF technology clusters, the magnitude and direction of the influence of the factors in technology adoption varied depending on the PLF technology cluster being investigated. By identifying the PLF technologies in which pasture-based dairy farmers are investing more and by detecting potential drivers and barriers for the adoption of PLF technologies, the current study could allow PLF technology companies, practitioners, and researchers to develop and target strategies that improve future adoption of PLF technologies in pasture-based dairy settings. [ABSTRACT FROM AUTHOR]

We investigate how information networks influence smallholder farmers' learning and decisions that lead to the adoption of improved pulse varieties in two Ethiopian villages. Using data from a mixed methods study (snowball sampling, egocentric networks, unstructured interviews, and focus group discussions), we find that farmers with more connections had adoption rates that were more strongly associated with their relative positions in the network than farmers with fewer connections. All other factors being equal, a one-percentage-point increase in centrality is associated with a 22-percentage-point increase in the adoption of new pulse varieties. This finding offers additional insights into the role that social networks may play in technology adoption as well as the measurement of network effects. • We studied how smallholders' information networks impact decision-making, leading to adopting improved pulse varieties. • Using snowball sampling and egocentric networks, we found a link between information access inequality, diffusion, and influence of central farmers. • Farmers more connected in networks have better access to information leading to higher adoption rates compared to those with slightly lower centrality. [ABSTRACT FROM AUTHOR]

To understand the preference for heating and cooling technology (HCT) adoption and promote appropriate HCTs, this study conducts a comprehensive spatiotemporal analysis of HCT adoption in 300,043 houses between 2011 and 2019 across 108 city councils in New South Wales, Australia. First, this study establishes a driving indicator system with respect to demographics, economy, and environment. Next, this study employs a three-dimensional trend analysis to create spatial distribution trend maps and uses Moran's I to analyse spatial autocorrelations via ArcGIS to examine the spatiotemporal aspects of technology adoption. The results indicate that, over time, HCT adoption has stabilised and air conditioning is expected to continue as the primary choice in the future. Spatially, despite disparities in HCT adoption across cities, air conditioning remains the predominant choice. This study then uses ordinary least squares, geographically weighted regression and multiscale geographically weighted regression (MGWR) to establish the relationships between the driving indicators and HCT adoption rates via ArcGIS, with the results of the MGWR being the most significant. The MGWR results indicate significant impacts at various spatial scales. Among the 20 parameters examined, 16 exhibited significant effects, with the economic and environmental indicators having the most pronounced impacts. The MGWR results also emphasise the significance of socioeconomic contexts in different cities. In general, to encourage technology adoption, it is crucial to reduce adoption costs, increase green energy efficiency standards, and promote industrial upgrading. The results of this study can predict HCT adoption and offer valuable insights for future technology promotion recommendations. [Display omitted] • The preference for HCT adoption was investigated from spatiotemporal perspective. • Comprehensive driving indicator system was established from three dimensions. • Economic and environmental indicators drove HCT adoption more. • HCT promotion strategies were promoted considering the spatiotemporal impacts. • The significance of social-economic contexts in different cities was emphasized. [ABSTRACT FROM AUTHOR]

This study focuses on the importance of water management in agriculture, considering both economic and environmental aspects. We aim to assess the eco-efficiency of farms by incorporating water-related indicators into performance evaluations. These eco-efficiency scores are further decomposed into water conservation efficiency (WCE) and water use efficiency (WUE). This paper uses a combination of Data Envelopment Analysis (DEA) and econometric analysis to calculate efficiency scores and identify the factors that influence efficiency for small-scale greenhouse farms in Crete (Greece) from 2009 to 2013. Findings reveal that: i) the average technical efficiency (TE) score for the sample is 0.891, indicating a relatively high level of efficiency; ii) the scores for WCE and WUE are 0.180 and 0.174 on average, respectively, suggesting room for improvement in managing water resources; iii) farmers who adopt alternative irrigation technology demonstrate higher technical efficiency compared to the overall sample, while non-adopters show even higher levels of efficiency. Moreover, non-adopters have been found to exhibit relatively better water conservation and use efficiency, indicating that adopters need to adjust their irrigation management practices and fine-tune the system's settings. Lastly, the findings suggest that utilizing more advanced irrigation technologies can enable farmers to effectively counteract the detrimental effects of aridity in managing water resources. • The analysis focuses on the eco-efficiency of farms, particularly regarding water loss and conservation practices. • Water use efficiency is decomposed into technical efficiency and water conservation efficiency. • Results show that adopters exhibit higher levels of technical efficiency compared to the pooled sample. • The findings indicate that advanced irrigation technologies help farmers manage water more effectively in arid conditions. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is revolutionizing healthcare by introducing novel treatments and applications, thereby transforming the sector. However, the complexity, ambiguity, and inherent risks associated with AI can create tensions for healthcare workers that may result in stress, anxiety, and discomfort when they make decisions. These tensions are paradoxical in nature as they may present conflicting demands that can persist over time and develop into seemingly irrational situations. Understanding how these paradoxical tensions affect healthcare workers' responses to AI is crucial in addressing their concerns. This study investigates the role of paradoxical tensions and the paradoxical mindset in shaping healthcare workers' responses to AI. The study examines how these two factors influence individuals' intention to adopt AI systems and tools and evaluates the users' satisfaction with them. Using a quantitative survey design, data were collected from 357 healthcare workers. The results, based on regression analysis, indicate that paradoxical tensions positively influence both individuals' intention to adopt AI systems and tools and their satisfaction with the current use of AI systems and tools. The results also indicate that the paradoxical mindset positively mediates these relationships. • This paper investigates the adoption of and satisfaction with AI systems and tools in healthcare using paradox theory. • This study surveyed 357 physicians and nurses working in Swedish healthcare. • Learning, performing, belonging, and power tensions positively influence individuals' intentions and attitudes toward AI. • Paradoxical mindset mediates the relationship between paradoxical tensions and individuals' responses toward AI. [ABSTRACT FROM AUTHOR]

Farmers face challenges ranging from fractured landholdings to climate change, yet they often have limited adoption of technology that could help cope with these adversities. As such, understanding farmers' adoption of technology is critical to developing farmer livelihoods in the context of changing global pressures. This research studies the technology and behavior change decisions of farmers in Cambodia through a survey of 109 farmers growing different types of crops and that have a variety of technical change opportunities. The study uses double hurdle modeling with a fractional logistic regression approach and discusses the results in the context of the theory of planned behavior. Results demonstrate that growing rice or cashews, extension services, risk aversion, indebtedness, experiencing crop loss, and having negative perspectives about climate change were positively significantly related to production behavior change while age and owning livestock were negatively significantly related to behavior change. The results suggest that agricultural technology could be made more accessible regardless of production type and developed with special attention towards climate change effect mitigation strategies. • Study builds understanding of farmer decision-making about change and technology adoption in rural Cambodia. • Quantitative survey of 109 farmers analyzed with a double hurdle with fractional logistic model.. • Differentiated adoption behavior between producer groups, with rice and cashew farmers more likely to adopt technology. • Risk averse farmers and farmers concerned with effects of climate change more likely to adopt technology. • Findings provide insights into shaping extension services and equitable technology development. [ABSTRACT FROM AUTHOR]