Search

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]

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]

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]

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]

We study the role of social learning in the diffusion of cash crops in a resettled village economy in Brazil. We combine detailed geo-coded data on farming plots with dyadic data on social ties among settlers, and we leverage the variation in network formation induced by the landless workers' movement land occupation. By using longitudinal data on farming decisions over 15 years, we find evidence of significant peer effects in the decision to farm new cash fruits (pineapple and passion fruit). Our results suggest that social diffusion is heterogeneous along observed plot and crop characteristics, i.e. farmers growing water-sensitive crop are more likely to respond to the actions of peers with similar water access conditions. [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]

Industry 4.0 (I4.0) is a transformative industrial paradigm that encompasses a set of technologies and principles that are increasingly essential for companies operating in the automotive sector. By embracing the principles and implementing the associated I4.0 technologies, automotive companies have the potential to improve their overall business performance, foster greater collaboration within the supply chain (SC) ecosystem and thereby strengthen their competitive edge. These technologies drive innovation, enabling the development of sustainable solutions and the alignment of products with ever-evolving customer demands. Therefore, this study explores the complex interplay between I4.0 technologies and business performance by providing insights from a multi-case study in the automotive sector. As the exploratory nature of this research is driven by the exploration of pathways, topics such as the implementation of I4.0 technologies, their impact on business performance and current important industry issues such as reshoring and the circular economy (CE) were also discussed. A research protocol was developed and semi-structured interviews were conducted with senior managers from six leading European automotive suppliers. The results show how significant improvements in business performance can be achieved by implementing advanced I4.0 technologies aimed at automating processes and making production lines more flexible. This led to improvements in productivity and product quality, while reducing production costs through the strategic use of available data. Furthermore, European automotive suppliers are engaging in collaborative initiatives with other SC actors to stay abreast of emerging innovation trends, to meet customer needs and to help share knowledge and resources. Overall, the implementation of I4.0 technologies leads directly and indirectly to more sustainable production and efficient resource management, as I4.0 technologies are designed to be energy efficient and reduce emissions. [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]

• 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]

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]

Government of India has adopted policies to grow the share of electric vehicles (EVs) to 'de-carbonize' India's transport sector and reduce import dependence for oil. For the lower-middle income economy two-wheelers play a significant role in the private vehicle market. This paper focuses on the effectiveness of some of the demand incentives; roles of infrastructure, market visibility; and peer effects on acceptance of electric two-wheelers in India. It utilizes a discrete choice survey to collect responses from Indian residents. Respondents in six different choice scenarios chose between two categories of petrol vehicles and an EV. Results from the random-parameter logit model indicate that price, refueling time, availability of infrastructure, vehicle taxes, and fuel prices are significant determinants of two-wheeler choice. Further, estimates suggest that consumers are willing-to-pay INR 567 to save in fuel cost by INR 1 per 100 kms, INR 997 for every percentage point reduction in taxes, INR 316 to save an additional minute of charging time, and INR 879 to increase the charging infrastructure by an additional percentage point. Government policies involving price subsidies, preferential tax treatments and improvements in infrastructure should continue. Differential pricing of petrol and electricity can also make electric two-wheelers more attractive. • Stated discrete choice survey on electric two-wheeler preference in India. • Infrastructure development is imperative to promote electric vehicles. • Differential tax treatments and fuel pricing can be favorable for demand. • Purchase subsidies help in bridging price gap and boost demand. • Long-term cost savings by electric vehicles should be promoted to boost demand. [ABSTRACT FROM AUTHOR]

Collaborative robots (cobots) allow for combining complementary strengths of humans and robots. However, this close human-cobot interaction creates a highly complex socio-technical system. This is a key adoption and integration challenge as it complicates an understanding of dependencies between cobots and their surrounding workplace: while a cobot needs to fit to the product to be manipulated, the human operator and the workplace, those three domains also need to be adjusted to allow for a successful cobot use. This paper presents a matrix-based approach to analyze dependencies between the four domains; (1) cobot, (2) product, (3) human/operator, and (4) workplace. [ABSTRACT FROM AUTHOR]

Machine learning (ML) gives organizations the power to predict the future, and this has become a core element of modern enterprises. Three contexts, grounded in the technology-organizational-environmental (TOE) framework, were scrutinized to explain ML adoption. Data collected from 319 firms are used to test conceptual model. Additionally, this study investigates the use of process sophistication and mimetic pressures as moderators. The significance of the technological, organizational, and environmental contexts for ML adoption is confirmed. Furthermore, the moderator influence of mimetic pressures and process sophistication between the technological and organizational context and ML adoption was confirmed. [ABSTRACT FROM AUTHOR]

Recent years have seen increased levels of adoption of Enterprise Collaboration Systems (ECS) in organisations. However, to date, there are limited in-depth studies that provide empirically derived insights into Adoption Supporting Measures (ASM) in the context of ECS. The aim of the study presented in this paper is to identify, analyse and classify ASM for ECS from the organisational perspective and the company staff responsible for managing the ECS implementation. The study follows a qualitative and interpretative research design based on the analysis of company case studies. Through a process of inductive coding of six industry case studies we identified and described 41 different ASM in the context of ECS. These 41 ASM were further analysed and classified into seven categories and related subcategories. The resulting classification is visualised and discussed. The findings presented in this paper serve as an essential intermediate step for further in-depth investigations to understand contextual variations in ECS adoption and how these may vary over the life of an ECS project. [ABSTRACT FROM AUTHOR]

The concept of transforming maritime industry into a digital platform with real-time communication has rapidly emerged within industry discussions. A big part of the topic was tied around blockchain technology that due to its decentralization feature can simplify the complexity of the supply chain network and interconnect its actors. Nevertheless, only a few studies have investigated the feasibility in detail, yet not covered limitations other than those generally discussed. The purpose of the study is to identify and summarize the challenges of blockchain implementation in the maritime industry and within maritime ports. Based on the literature and previous research findings, 18 challenges to the blockchain implementation were identified and categorized into four dimensions: human factor, operational, organizational, and technological. The findings show that different priorities among ports, low level of digitalization, scalability of blockchain systems, and unwillingness to change business routine are important challenges. [ABSTRACT FROM AUTHOR]

Digital product passports (DPPs) may help bridge prevailing information gaps along value chains, and thus support actors' sustainable product management (SPM) decisions by providing needed product life cycle data. However, different factors influence their successful adoption. This paper provides empirical insights into the perceived potential of DPP adoption in SPM. The focus was placed on DPPs for electric vehicle batteries. Research entailed conducting stakeholder online focus group workshops, expert interviews, follow-up stakeholder consultations, and subsequent qualitative content analysis. Diffusion of innovation (DOI) theory and the technology-organization-environment (TOE) framework were used as theoretical basis. The results illustrate stakeholder perspectives on DPP use in SPM support, as well as stakeholder classification based on innovation adopter categories of DOI theory. Furthermore, DPP adoption barriers, enablers and drivers are presented and discussed in the context of the TOE framework and DOI theory. This paper adds to the literature on digitalization as an enabler of SPM and circular value chains, and to the field of innovation adoption and diffusion in the context of DPPs. As the identified DPP adoption factors help support the uptake of DPPs in facilitating SPM, it is also of clear practical relevance. [ABSTRACT FROM AUTHOR]

• This study produces predictive models for MaaS use by applying artificial neural network (ANN) analysis. • MaaS use models are developed separately for social, general, and work trips. • The cross industry standard process and data mining framework is followed in designing ANN-based predictive models. • Different sets and combinations of socio-economic, personal travel and Covid-19 related factors are key predictors of MaaS use for social, general, and work trips. • Findings can inform strategies and policies to promote MaaS use. Mobility as a Service (MaaS) has gained popularity as a means of sustainable urban transport which makes the understanding of MaaS use critical for its design and promotion. Studies have contributed to the growing understanding of MaaS, its design features, and consumers' willingness to pay for MaaS in general, without recourse to the differences in traveling for work, social and general purposes. This paper develops and tests models to predict MaaS use by applying artificial neural network analysis, following the cross industry standard process and data mining framework. It also estimates separate models for social, general, and work trips, using 33 input variables reflecting network externality, transaction cost, behaviour, institutional, environmental concern, personal travel, and socio-economic factors. Data are collected from a survey of 331 Australians. The study reveals different sets of socio-economic factors, the impact of Covid-19, and personal travel factors as key predictors of MaaS use for general, social, and work trips with an average prediction accuracy of 68%, 68%, and 75% respectively. The findings can be used to inform strategies and policies on how to attract a user base with respect to socio-economic and personal travel factors for promoting MaaS use. [ABSTRACT FROM AUTHOR]

Electrification of the transport sector is expanding in both developing and developed countries in response to air pollution and climate change. Indonesia, the world's 10th biggest CO 2 emitter having the world's third largest two-wheeler market, aims to deploy 2.1 million electric two-wheelers by 2025 and is developing electric vehicle policies. This study designs a consumers' choice model for buying a scooter in Jakarta, Indonesia, and simulates the effects of two supportive policies to expand electric two-wheelers (providing subsidies and building charging infrastructure) using a discrete choice experiment. We calculate the budget required for these subsidies. The results show that people in Jakarta highly prefer electric scooters and consider their environmental impacts. A 20% subsidy increases the estimated annual market share of new electric scooter sales to 10%. In addition to a 20% subsidy, building charging infrastructure for electric scooters to the same level as conventional gas stations leads to estimated new sales of electric scooters reaching 21%. This study suggests the need to develop comprehensive policy packages to successfully deploy electric two-wheelers in Jakarta and provides reference data to improve the efficiency and effectiveness of related policies. [ABSTRACT FROM AUTHOR]

• We evaluate rainwater harvesting (RH) and fertilizer micro-dosing (FMD) impacts. • We assess combined RH-FMD on many dimensions of sustainability in Tanzania. • Food security can increase with combined RH-FMD in households in humid regions. • No effect found on food security in dry regions but a decrease in the economic pillar. • RH-FMD should be promoted in humid rather than dry regions of East Africa. Food insecurity and poverty are of major concern for farmers and rural households in Tanzania. Innovations to increase the sustainability of households must be carefully investigated by integrating, in the analysis, the effect on crop yields with a holistic view on the overall sustainability and its components. Rainwater harvesting and fertilizer micro-dosing can increase food security, particularly in water-limited contexts, but they can also significantly increase labor requirements and the availability and use of water resources in villages and watersheds. The purpose of this study was to quantify the impacts of rainwater harvesting and fertilizer micro-dosing on environmental, social and economic sustainability of households in two regions in Tanzania – semi-arid Dodoma and semi-humid Morogoro. We selected and calculated 40 sustainability indicators for 892 households in 2013 and 2016, and we applied Difference-in-Difference Propensity Score Matching to identify relative changes in household sustainability. We show that in the dry region of Dodoma, economic sustainability increased less for adopters of the innovations in comparison to non-adopters between the years 2013 and 2016, with 6 percentage points and 11 percentage points respectively. In contrast, in the humid region, the adoption of innovations increased food security by 14 percentage points compared to 6 percentage points in the case of non-adoption. These results highlight that innovations must fit the context and should not be scaled without prior analysis of multiple impact dimensions as they may trigger significant trade-offs. By moving the focus from field to farm scale, this study contributes to providing a more rigorous assessment of the spillover effects that in-field innovations can have on the overall sustainability of households, which is a prerequisite for the advancement of sustainable intensification of agricultural production in the region. [ABSTRACT FROM AUTHOR]

As global demand for animal products is projected to increase significantly by 2050, driven by population growth and increased incomes, smart livestock technologies are essential for improving efficiency, animal welfare, and environmental sustainability. Conducted within the unique agricultural context of Japan, characterized by small-scale, family-run farms and strong government protection policies, our study builds upon traditional theoretical frameworks that often oversimplify farmers' decision-making processes. By employing a scoping review, expert interviews, and a Modified Grounded Theory Approach, our research uncovers the intricate interplay between individual farmer values, farm management policies, social relations, agricultural policies, and livestock industry trends. We particularly highlight the unique dynamics within family-owned businesses, noting the tension between an "advanced management mindset" and "conservatism." Our study reveals that technology adoption is a sequential and iterative process, influenced by technology availability, farmers' digital literacy, technology implementation support, and observable technology impacts on animal health and productivity. These insights highlight the need for tailored support mechanisms and policies to enhance technology uptake, thereby promoting sustainable and efficient livestock production system. • Unveils complex factors influencing the adoption of smart livestock technologies • Highlights the unique dynamics in family-owned businesses • Demonstrates the sequential and iterative nature of technology adoption • Presents a pioneering methodology combining review, expert interviews, and Modified Grounded Theory Approach (M-GTA) [ABSTRACT FROM AUTHOR]

Although skepticism is involved in technical change and scientific revolutions, surprisingly, the literature lacks a systematic analysis of the different forms, causes, and roles of skepticism in the diffusion of innovation. This paper defines, identifies and models different types and causes of skepticism and their role in technology adoption. The paper identifies and studies: skepticism involving the characteristics of the technology and the producer; skepticism that induces to disbelieve market signal; and comparative skepticism i.e., skepticism produced by an unbalance relationship between the perceived complexity of the problem and the solution. Among the theoretical findings of the paper and regarding skepticism on market signals, we found that the non-differentiability and oscillation of diffusion rates occur if individuals use the information on diffusion rates as proxy of the probability of technology working and modify this probability according to their skepticism. • Although scepticism is involved in technical change, general analysis of the different forms, causes and role of scepticism in innovation diffusion do not exist. • We developed a dynamic model of decision-making and innovation diffusion that incorporates technology diffusion and trust/scepticism. • Scepticism modifies market signals. • The model contributes to understanding mechanisms behind technology adoption and diffusion: adoption delay, adoption without social interaction, and oscillation of diffusion rates. [ABSTRACT FROM AUTHOR]

Environmental consciousness and digital competence are sought-after characteristics of managers by many organisations today. The digital expertise of organisations is considered a critical capability that drives their digitalisation strategies. Also, values and beliefs towards environmental sustainability influence their attitudes towards achieving environmental performance. By integrating the three 'big' adoption theories of DoI, TAM and UTAUT, along with decision-making literature, this study empirically investigates the effects of the digital expertise and environmental consciousness of managers on their intention to adopt Industry 4.0 technologies. We used an online survey with 172 managers from Australian firms using the PLS-SEM method for data analysis. The results show that managers' environmental consciousness and digital expertise significantly and positively affect their intention to adopt Industry 4.0 technologies. Their perceived usefulness of technologies partially mediates the relationships between digital expertise and intention to adopt and between environmental consciousness and intention to adopt. The mediation roles of perceived ease of use, perceived visibility and social influence were not empirically confirmed. Integrating adoption theories with domain-specific knowledge-based decision-making is a novel theoretical approach adopted in the study. The key contribution is to the Industry 4.0 technology adoption literature by empirically confirming the effects of domain-specific knowledge expertise and environmental consciousness on the intention to adopt. Its practical implications lie in the confirmation that organisations benefit from their investment in the digital skill development of managers and environmentally conscious managers. • Digital competence and environmental consciousness are sought-after characteristics. • Technology adoption and decision-making literature are integrated. • Managers' environmental consciousness increases their intention to adopt technologies. • Managers' digital expertise positively affects their technology adoption intentions. • Demonstrated usefulness of technology mediates managers' technology adoption intentions. [ABSTRACT FROM AUTHOR]

The purpose of this study is to propose the theoretical model of artificial intelligence-based touchless technology adoption, in the context of facial recognition systems (FRSs) adoption by business event attendees. This research combines constructs of technology adoption and privacy-personalization paradox models with the construct derived from the contemporary context of perceived health risk at events. The study used a survey research design with a mental simulation that introduced an FRS to respondents via a video clip. The results of structural equation modeling based on 199 responses show that performance expectancy and trust in the system positively impact the intention to use FRSs at business events. While lacking direct effects on the adoption intention, effort expectancy demonstrates a significant influence on performance expectancy, and perceived personalization serves as a significant predictor of trust in the system. Perceived health risks of attending a business event did not reveal statistically significant effects on performance expectancy and intention to use FRSs. However, further investigation shows that perceived health risk moderates the effects of privacy concerns on trust and intention to use FRSs. • Effort expectancy positively affected performance expectancy of FRSs of attendees of business events. • Perceived performance expectancy and trust in the system positively and significantly affected intention to use the FRS. • Perceived personalization had positive significant large effect on trust in FRSs. • Perceived health risk has moderating effect on nonlinear relationships between privacy concerns and intention to use FRSs. • Perceived health risk has moderating effect on nonlinear relationships between privacy concerns and trust in FRSs. [ABSTRACT FROM AUTHOR]

In recent years, advancements in machine learning (ML) have facilitated the utilisation of big data across various academic disciplines. Nonetheless, these techniques still require a high-level of programming and data science expertise, making them inaccessible to many researchers and hindering the potential for knowledge advancements. This paper presents a framework for identifying the adoption of Industry 4.0 (I4.0) technologies among European firms that have undergone restructuring events. Existing studies on I4.0 adoption rely on diverse data sources at different levels of aggregation (e.g., countries, sectors, firms), spanning various time periods and technological domains. While this diversity often complicates result comparison, it also drives researchers and institutions to explore new data sources to assess technology adoption. Our identification methodology is based on the implementation of ML techniques using STATA, a well-established and user-friendly statistical software. We offer a step-by-step guide based on recently developed commands, allowing for comparison of model performance and analysis of model features. Our findings underscore the potential of ML algorithms as a robust tool for collecting new firm-level data on I4.0 adoption. Specifically, we observe that business restructuring events predicted as I4.0-related conform to adoption patterns identified in prior studies, across countries, sectors and over time. • This study presents machine learning models to predict Industry 4.0 adoption. • A methodology is presented to explore the application of data science techniques in social sciences. • The machine learning implementations are based on a set of recent commands for STATA. • Eurofound's data on 23,618 restructuring events were used to predict technology adoption from textual descriptions. • Predicted adoption patterns conform to those observed across European countries, sectors, and over time. [ABSTRACT FROM AUTHOR]

To effectively integrate clean energy resources into the supply chain (SC) and optimize energy consumption, the digitalization of renewable energy supply chain (RESC) plays a vital role in the future. Nonetheless, society must accept these emerging RE technologies to transition successfully into mainstream energy resources. The Internet of Things (IoT) technology can resolve the challenges facing RESC (solar energy) to achieve sustainable development strategies. This study examines how IoT adoption affects the sustainability of the RESC. The sample size consisted of 175 active companies in the RESC in Iran, and a standard questionnaire is distributed among them using a simple random method. Structural equation modeling was used to investigate the hypothesis. We evaluated the questionnaire's discriminative validity, computed composite reliability, and computed Cronbach's alpha to determine its validity and reliability. The results revealed that our research validates six hypotheses about the relevance between lean and eco-friendly actions, SC integration, performance perceived benefit, expenses, peers and government support, and IoT adoption. The findings also suggest adopting IoT technology as a broad-based strategy to attain sustainability in the energy context. As a result of its transparency, immutability, and security features, IoT presents a viable option for RESC sustainability. [Display omitted] • Digitalizing the renewable energy supply chain with IoT technology to achieve the sustainable performance. • Explanation the relationship between IoT adoption and sustainable performance in renewable energy sector. • IoT arises as a driver for the sustainable energy supply chain due to its immutability and transparency features. • IoT influences the link between green practices, integration, and external support and the sustainable performance. [ABSTRACT FROM AUTHOR]

Knowledge-based virtual shopping agents, that advise their users about which products to buy, are well used in technical markets such as healthcare e-commerce. To ensure the proper adoption of this technology, it is important to consider aspects of users' psychology early in the software design process. When traditional adoption models such as UTAUT-2 work well for many technologies, they overlook important specificities of the healthcare e-commerce domain and of knowledge-based virtual agents technology. Drawing upon health information technology and virtual agent literature, we propose a complementary adoption model incorporating new predictors and moderators reflecting these domains' specificities. The model is tested using 903 observations gathered through an online survey conducted in collaboration with a major actor in the herbal medicine market. Our model can serve as a basis for many phases of the knowledge-based agents software development. We propose actionable recommendations for practitioners and ideas for further research. [ABSTRACT FROM AUTHOR]

This study introduces a new adoption model for assessing the quality of experience (QoE) of radiologists using AI-based medical imaging technology. While AI has increasingly been used by radiologists for screening, diagnosis, and classification of medical images, previous investigations have primarily focused on metrics such as effectiveness, efficiency, and satisfaction. This research expands the evaluation criteria to include user experience and user interface (UX/UI) factors, integrating them within the broader QoE. QoE is conceptualized as a multifaceted construct influenced by both human and system factors, which affect cognitive perception, including hedonic and pragmatic aspects. Data were collected from 159 hospital radiologists with prior experience in using AI technology in medical imaging systems through a structured questionnaire. The data were then analyzed using structural equation modeling principles. The findings suggest that contextual content, human factors, and system characteristics significantly influence cognitive perception, which in turn affects the adoption and utilization of AI in medical imaging. This adoption model captures the radiologists' integration of AI throughout various stages of radiological procedures, including scheduling, scanning, acquisition, interpretation, reporting, and communication. The study also highlights the importance of data collection, storage, and sharing practices in compliance with privacy policies. [ABSTRACT FROM AUTHOR]

The study was conducted on 125 US based high-tech firms from software engineering, hardware production, biotechnology, and telecommunications. Senior-level executives, including CEOs, board members, and CTOs, provided insights through structured questionnaires. Key findings indicate that AI adoption significantly enhances organizational capabilities in terms of employees' innovation, creativity, and experimentation. Moreover, AI adaptation positively impacts decision making thus yielding more accurate and timely valuable decisions. These findings contribute to both theoretical understanding and managerial practice by guiding strategic investments in AI technologies, fostering innovation, and advocating for ethical AI deployment practices. Future study should examine longitudinal impacts across industries and regions to optimize benefits and minimize risks in digital transformation efforts. It should also integrate qualitative methods for deeper insights and appropriate AI governance systems. [ABSTRACT FROM AUTHOR]

Virtual economies with 3D assets have been studied for decades, often in the context of entertainment, but the concept of the metaverse as a workplace platform has only recently begun to take hold. This research addresses a gap in our understanding of how the enhanced ability for impression management in the metaverse workplace may relate to worker well-being and equity. We explore how demographics and previous virtual meeting (VM) experiences relate to people's valuation of self-presentation in the metaverse, reflected by willingness to pay for avatar customizations in a work context. Survey responses from a general population of adults (n = 553) suggest that the valuation of avatar customization in the metaverse workplace was predicted by VM fatigue, gamers' propensity to purchase virtual items, and demographics. People of color and women exhibited higher intentions to purchase avatar customization in the metaverse workplace. These results support the reasoning that the demand for impression management in the metaverse workplace will likely motivate avatar customization, and that gamers are likely to be the early adopters of paid avatar customization options in the non-game metaverse. This study contributes to an understanding of the role avatar customization has for a self-presentation strategy to meet norms in the future metaverse workplace. We discuss implications of VM fatigue and self-presentation concerns from the perspective of an equitable avatar-mediated workplace. • Zoom fatigue is associated with a greater appreciation for avatar customization in the future of the virtual workplace. • People of color exhibited a stronger preference for avatar customization in the virtual workplace compared to Whites. • The inclination to purchase in-game items forecasts future behaviors of customizing avatars in a professional environment. • Customizing avatars in the virtual workplace reflects motivations for impression management and strategic self-presentation. [ABSTRACT FROM AUTHOR]

Technology adoption has acquired significant research interest, resulting in an expanding volume of literature. However, there is a scarcity of studies using scientometrics and detailed content analysis due to limited quantitative research over time. Consequently, this paper conducts a comprehensive review of 124 peer-reviewed articles to explore and characterize the developmental trajectory of construction-related technology acceptance and adoption literature. The research analyzes aspects such as annual publication trends, citation distributions, scientific collaboration, source citations, and literature content. The outcomes of this paper deepen new researchers' understanding of technology adoption literature, assist practitioners in evaluating emerging technologies, and identify promising domains for future studies. [Display omitted] • Conducting Scientometric analysis on technology adoption in the construction industry. • Visualizing collaboration and citation networks of technology adoption publications. • Performing content analysis and social network analysis on the extracted publications. • Mapping knowledge gaps and directions for developing new technology adoption studies. [ABSTRACT FROM AUTHOR]

In recent years, the rapid advancement of artificial intelligence (AI) technologies has significantly impacted various sectors, including public governance at the local level. However, there exists a limited understanding of the overarching narrative surrounding the adoption of AI in local governments and its future. Therefore, this study aims to provide a comprehensive overview of the evolution, current state-of-the-art, and emerging trends in the adoption of AI in local government. A comprehensive scientometric analysis was conducted on a dataset comprising 7112 relevant literature records retrieved from the Scopus database in October 2023, spanning over the last five decades. The study findings revealed the following key insights: (a) exponential technological advancements over the last decades ushered in an era of AI adoption by local governments; (b) the primary purposes of AI adoption in local governments include decision support, automation, prediction, and service delivery; (c) the main areas of AI adoption in local governments encompass planning, analytics, security, surveillance, energy, and modelling; and (d) under-researched but critical research areas include ethics of and public participation in AI adoption in local governments. This study informs research, policy, and practice by offering a comprehensive understanding of the literature on AI applications in local governments, providing valuable insights for stakeholders and decision-makers. • Maps the landscape of artificial intelligence (AI) adoption in local government (LG) • Advancements in the last decades brought the Blooming Era of AI adoption in LG • Main AI adoption purposes: decision support, automation, prediction, service delivery • Main AI adoption areas: planning, analytics, security, surveillance, energy, modelling • Under-researched but critical areas: responsibility and ethics of AI adoption in LG [ABSTRACT FROM AUTHOR]

Drawing on the diffusion of innovations theory, this study focuses on two critical aspects of information communication technology (ICT) adoption in the restaurant industry, thus contributing empirically and conceptually to the hospitality literature. The perceived advantages and disadvantages of such adoption are examined through the views of restaurant operators in Vietnam, an emerging economy boasting a growing food and beverage industry. Using a questionnaire eliciting quantitative and qualitative data, 492 usable responses were gathered. Quantitatively, the analysis revealed the significance of intangible and tangible elements of ICT uptake, supporting the proposed hypotheses. Indeed, while advantages underscored marketing/promotion and sales, time and financial investments were key disadvantages. The qualitative analysis uncovered nine conceptual dimensions. Among others, the 'inspirational ICT' dimension positions technology as a resource booster, while the 'human-technology boundaries' dimension suggests challenges related to users' perceptions, generational divide, and preferences. A resulting theoretical framework highlights practical and theoretical implications. • Examines the advantages/disadvantages of technology adoption among restaurants. • Chooses a mixed methods approach and exploratory design. • Identifies various factors and dimensions with practical and conceptual value. • Develops a conceptual framework illuminating the study's key themes. • Investigates restaurant managers operating in an emerging economy. [ABSTRACT FROM AUTHOR]

This study employs microdata from the China Labor-force Dynamics Survey to investigate the influence of foreign language proficiency on the adoption of Internet technology within households. The results indicate that householders who are proficient in foreign languages are more likely to adopt Internet technology at home than those who lack such knowledge. The greater the foreign language proficiency of the householder, the greater the likelihood of Internet technology adoption. Further analyses indicate that the positive effect of foreign language proficiency on the Internet technology adoption of the household in China is more pronounced in male-headed households, in urban areas, and in eastern and central regions. This study also identifies three potential mechanisms by which foreign language proficiency influences household Internet technology adoption: the information effect, the trust effect, and the income effect. These findings contribute to the understanding of the role of language proficiency in technology adoption at the household level, offer new insights into the positive outcomes of foreign language education in China, and encourage measures to reduce digital inequality among households through language learning. • We examine the impact of foreign language proficiency on Internet technology adoption of the household in China. • Householders proficient in a foreign language have a significantly increased probability of the Internet use at home. • The impact is more pronounced in male-headed households, in urban areas, and in eastern and central regions. • Three potential mechanisms of the impact are information, trust, and income effects. [ABSTRACT FROM AUTHOR]

Technology adoption has recently gained more attention due to its significant impact on smart systems' user retention. Many procedures in education, business, and private life are anticipated to evolve and change shortly due to the use of 5/6 technology. This article specifically highlights the significance of deploying 5/6G technology in libraries to allow the development of creative, clever, and improved services backed by new digital technologies. It could start a revolution in smart libraries and change how they are run now. According to our best knowledge, this is the first attempt that enriches our understanding of 5/6G and its adoption intentions in libraries using a combined SF-AHP and PLS path modeling. As per Spherical fuzzy AHP, all variables except social influence were the most important factors predicting adoption intention for 5G- and 6G-based services from experts' point of view. The structural equation modeling (SEM) method showed that all of our conceptual model variables, including perceived performance expectancy, perceived effort expectancy, and perceived attitude towards using 5/6G, positively impacted adoption intention in the library. At the same time, perceived social influence did not affect adoption intention (5/6G). One explanation is that there is still some ambiguity about what "5/6G technologies" entail and the minimal carrying out of the technology we bring into the survey by libraries at this time. Furthermore, we did not account for variations in each librarian's function. It is conceivable that the work spent on such technologies was exaggerated or unclearly by those not directly engaged in their implementation. • This research enriches knowledge of 5&6G and its adoption intentions in smart libraries. • To our knowledge, 5G and 6G have not been studied using UTAUT with SEM and SF-AHP methods in library contexts. • Results showed PPE, PEE, and PATU positively impacted the library's intention to adopt 5G and 6G. • Our study did not find support for the Perceived Social Influence (PSI) variable, which may have influenced the findings. [ABSTRACT FROM AUTHOR]

Although SMEs' innovation adoption has been widely studied, little research has explored how SMEs strategize a continuously evolving technology in a complex institutional context over time. Drawing from institutional perspectives, our case study, based on 44 interviews and field observation, seeks to analyze how institutional forces interact with the Wi-Fi adoption process at three small organizations with different innovation statuses. Results reveal the significance of institutional forces in shaping small organizations' technology adoption process. At the knowledge stage, institutional forces stem from the champion's advocacy and institutional pressures. At the persuasion and implementation stages, they are embedded in organizations' actions in following the institutional trend and complying with institutional norms. At the confirmation stage, they can be observed in organizations' shaping institutional changes or leapfrogging institutional trends. These insights challenge and extend the traditional linear perspective of innovation diffusion and contribute to the literature on technology adoption, digital transformation, innovation leapfrogging, institutional theory, and SMEs. Managerially, we propose three strategic responses (i.e., trend reformulation, service differentiation, complete transformation) that urge SMEs to utilize leapfrogging effects of technologies to renovate their innovation status. • Institutional forces are significant in shaping small organizations' technology adoption. • Unexpected leapfrog effects reshape SMEs' innovation status. • We propose an alternative view of the linear perspective of Rogers' Diffusion of Innovation. • Regardless of their original innovation status, SMEs can take advantage of leapfrog effects. • Late adopters and laggards can omit intermediate technology and become innovators. [ABSTRACT FROM AUTHOR]

Information problems are pervasive in developing economies and can hinder productivity growth. This paper studies how much rural producers in developing countries can learn from their own cultivation experience, i.e. learning by doing, to redress important information gaps about imperfectly known input technologies. First, I build a theoretical model which links learning by doing in one period to improved input choices in the next period, and show that this can be impeded by uncertainty about what is being observed due to noisy cultivation signals and by uncertainty about what to infer about market varieties due to imperfect variety integrity. Second, I apply this framework to cotton farmers in Pakistan, where farmers have imperfect information prior to cultivation about the extent to which their seeds have pest resistant biotechnology. The results suggest that farmers are unable to learn by doing about this aspect of their seeds due to a high degree of noise in cultivation signals. The paper highlights the potential difficulties in parsing out and processing information from cultivation experience alone and therefore of learning by doing by rural producers in a development context. [ABSTRACT FROM AUTHOR]

• Latrine adoption and use among peers increases household latrine use. • Peer effects are consistently strong influences on latrine use behavior over time. • Female latrine use is influenced by latrine use among other women. • Male latrine use is influenced by latrine use among women. • Policy efforts increase latrine adoption, but use behavior is not always sustained. One third of the world's population lacks access to improved sanitation facilities with ramifications for health, human well-being, and economic development. Although household latrines offer a relatively cheap technological solution, initiatives for universal coverage have fallen short of their goals. In this paper, we analyze a unique panel dataset to examine policies and peer effects as drivers of household sanitation behaviors over time. Our data include nearly 1000 rural Indian households across 39 villages surveyed at five time points over a 14-year period during which two distinct sanitation policy interventions occurred. Using spatial data on household locations to define peer reference groups, we estimate how the sanitation behaviors of neighbors influence latrine use, both at the household level and by gender. We find evidence that, while external interventions can be effective in increasing latrine use in the short term, sustained household latrine use consistently depends on neighbors' behavior. We also examine within- and across-group peer influences by examining patterns of latrine use among adult women and men. We find clear evidence that latrine use by neighboring women positively influences sanitation behaviors for both women and men, while latrine use among neighboring men has imprecisely estimated and small positive effects on men's behaviors and no effect on women's behaviors. These finding suggest that peer influences represent an important mechanism underlying household sanitation behavior, and policies that leverage these social effects, such as investments expanding women's access to sanitation and other drivers of behavior change, may be more effective and sustainable. [ABSTRACT FROM AUTHOR]