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Advances in material agency driven by artificial intelligence (AI) have facilitated breakthroughs in material adaptivity enabling smart objects to autonomously provide individualized smart services, which makes smart objects act as social actors embedded in the real world. However, little is known about how material adaptivity fosters the infusion use of smart objects to maximize the value of smart services in customers' lives. This study examines the underlying mechanism of material adaptivity (task and social adaptivity) on AI infusion use, drawing on the theoretical lens of social embeddedness.

This study adopted partial least squares structural equation modeling (PLS-SEM), mediating tests, path comparison tests and polynomial modeling to analyze the proposed research model and hypotheses.

The results supported the proposed research model and hypotheses, except for the hypothesis of the comparative effects on infusion use. Besides, the results of mediating tests suggested the different roles of social embeddedness in the impacts of task and social adaptivity on infusion use. The post hoc analysis based on polynomial modeling provided a possible explanation for the unsupported hypothesis, suggesting the nonlinear differences in the underlying influencing mechanisms of instrumental and relational embeddedness on infusion use.

The formation mechanisms of AI infusion use based on material adaptivity and social embeddedness help to develop the business strategies that enable smart objects as social actors to exert a key role in users' daily lives, in turn realizing the social and economic value of AI.

This study advances the theoretical research on material adaptivity, updates the information system (IS) research on infusion use and identifies the bridging role of social embeddedness of smart objects as agentic social actors in the AI context.

The study aimed to investigate the relationship between the intention to avoid food waste (IAFW) and the use of food-sharing technologies, such as internet platforms and mobile applications. The study utilized a model based on the theory of planned behavior (TPB) as an extension of the unified theory of acceptance and use of technology (UTAUT2).

An online platform tool (Prolific), and online self-report questionnaires were used to gather empirical data on 309 individuals. These data were then analyzed using two-step structural equation modeling.

The model explained 76% of the variance in user adoption of food-sharing mobile applications and internet platforms, supporting seven out of the nine tested hypotheses. Effort expectancy, social influence and IAFW were found to be the significant determinants of the behavioural intention to use food-sharing mobile applications and internet platforms (BITA). IAFW partially mediated the relationship between perceived behavior control and BITA. Age played a moderator role between the adoption of food-sharing mobile applications and internet platforms. However, IAFW did not play a mediating role between environmental concerns and BITA. The facilitating condition construct had an insignificant impact on BITA.

The current study was affected by some limitations. First, the data may not be considered as statistically representative because they were gathered online. However, the varied sociodemographic backgrounds of the respondents would boost the reliability of the findings. However, it would be prudent to use caution when extrapolating these findings to other contexts and cultures. Second, environmental concerns and perceived behavior control related to the avoidance of food waste behavior, as well as other factors that affect technology acceptance, may alter with time. Data from cross-sections may cause difficulties in following such changes. Thus, we recommend that longitudinal research studies aimed at building on our findings should be conducted. A qualitative study may help gain deeper insights into the relationship between IAFW related behavior and the adoption of various technologies to share leftover food, thereby revealing further details regarding different perspectives held by various respondents.

The positive relationship between environmental concerns and IAFW underlines the significance of investing in this area to raise social awareness and public concern for environmental safety. Additional initiatives aimed at increasing public concern regarding environmental issues may increase the overall IAFW. Instead of concentrating on a single source pertaining to the avoidance of food waste, the government and policy regulations should focus on regulating and eliminating waste from all sources that generate waste. The adoption of technology to share leftover meals may be influenced by social factors. Increased advertising for food-sharing mobile apps and online platforms may persuade more users to join. Additionally, building additional platforms and mobile apps in these fields with friendlier interactions may improve the cyber environment, making it easier for people to use them. By providing information, tools and assistance to promote the reduction of food wastage, policymakers may create interventions that enhance public perception and behavior toward the reduction of food waste. In conclusion, the findings of our study indicated that the social impact and ease of use are important factors in determining the adoption of food-sharing technology. Cooperation with social influencers, policymakers and developers may lead to the development of user-friendly technology that may improve accessibility to food-sharing technology.

In order to encourage the adoption of food-sharing technology among various age groups, policymakers may create initiatives that take the specific requirements and traits of each group into consideration. Policymakers and governments may also create legislation and regulations that are tailored to guarantee food safety and health security for users of food-sharing technology, such as instructions for handling and storing food as well as safeguards against food fraud and contamination.

This study addressed practical issues related to managing and reducing household food wastage through social sharing via mobile applications and internet platforms. The proposed model, which integrated TPB with UTAUT2 in the context of food wastage and technology acceptance, contributes to the current body of knowledge.

The escalating levels of greenhouse gas emissions have become a growing global concern, with household energy consumption emerging as a significant contributor. To develop effective public policies, it is crucial to understand the energy-saving behavior of households. This study delves into the determinants of energy-saving practices in a developing country.

The authors chose a multivariate probit model, as it allowed to look after possible correlations among seven energy-saving practices within households.

The findings underscore the significant influence of sociodemographic variables, such as gender, civil status, income and education, on energy-saving practices. Furthermore, the authors discovered that households where the head actively volunteers in social organizations are more likely to adopt energy-saving behaviors. Additionally, internet access positively contributes to pro-environmental behavior. This research reveals that certain energy-saving practices are interconnected, acting as complements or substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior. The authors contribute to literature evidencing that certain energy-saving practices are not independent of each other, they are rather complementary and, in some cases, substitutes.

Recommendations for public policy include prioritizing education in rural areas to boost energy-saving practices, improving Internet access in nonurban regions and promoting citizen involvement in social organizations to enhance environmental awareness and encourage energy-saving behavior.

Previous studies have overlooked these interdependencies, highlighting the necessity of a system of equations to yield more efficient estimates by considering correlations between error terms.

The agricultural extension system in Indonesia has experienced its ups and downs in line with the sociopolitical dynamics of the country. This study examines the impact of access to agricultural extension on the adoption of technology and farm income of smallholder farmers in Banten, Indonesia.

This study uses a quasi-experimental research design to estimate the impact outcomes at the farm level, with methods that form part of the counterfactual framework.

Estimation results show that farming experience, off-farm income, irrigation, group membership, mobile phones and livestock ownership significantly affect extension access. The results of this main study show the important role of extension access to technology adoption and agricultural income. These studies found consistently positive and statistically significant effects of access to extension services on technology adoption and farm income.

The consistent positive and significant effect of extension access implies that public investment by the government in agricultural extension can optimize the potential impact on technology adoption and agricultural income, which also affects the distribution of the welfare of rural smallholder farmers.

Agricultural extension as a key to increasing technology adoption. However, the impact of access to agricultural extension in Indonesia has received less attention in terms of adoption and farm income.

This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge.

The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice.

The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy.

The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange.

The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange.

This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

Post-harvest losses are becoming a huge issue worldwide and are predominantly severe in developing countries. Seeking ways to control post-harvest losses is important because losses decrease farm income by more than 15% for approximately 480 million small-scale farmers.

The study engaged Wave 4 (2018/2019) of the Living Standards Measurement Studies–Integrated Survey on Agriculture, to examine the impact of soil technology such as fertilisers, herbicides, pesticides and certified crops on post-harvest losses in Nigeria. The study engaged descriptive statistics, logit regression and propensity score matching (PSM) to analyse the data.

The study found that approximately 38% of the household harvest was lost along the value chain. In addition, the results showed that among the indicators of soil technology, crop certification has a significant impact on the reduction of post-harvest losses. The implication is that from the nearest neighbour and kernel-based matching, the use of certified crops by households contributed to 1.62 and 1.36% reduction in post-harvest losses, respectively. In contrast, pesticide, herbicide and fertiliser use had no significant impact on post-harvest losses.

One of the limitations is that this study applied the PSM, the model did not account for endogeneity. Therefore, in examining this concept, further studies should consider applying other impact model such as the difference-in-difference to account for endogeneity.

While previous studies have examined how ICT adoption, storage mechanisms and value chain among others help to minimise post-harvest losses, the aspect of how soil technology can reduce post-harvest losses has been a subject of exclusion in the extant literature. This study empirically examines the impact of soil technology adoption on post-harvest losses in Nigeria.

This paper argues that through information and communication technology (ICT) adoption, the youth will be engaged in all nodes of the agricultural value chains, thereby improving the level of employment and reducing post-harvest losses. The study examines the determinants of ICT adoption among the youth. In addition, it estimates the impact of ICT adoption on youth employment in agriculture towards the actualisation of the Sustainable Development Goals (SDGs), particularly SDG-8, to promote inclusive and sustainable economic growth, productive employment and decent work for all.

The study engages data from Wave 4 (2018/2019) of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The logit regression, the propensity score matching and the inverse probability weighted regression adjustment are used as the estimation techniques.

The study underscores that educational level, access to electricity, location, age and income are significant determinants of ICT adoption among the youth. The findings also show that the youth's average weekly engagement in agricultural activities is about 24 h. In addition, the result reveals that ICT adoption can increase youth agricultural employment by approximately 21%. The mean difference indicates that those with access to ICT participate in agricultural activities more than their counterparts without ICT access by 29.46%.

One of the limitations of the study is that some of the variables such as insecurity, social protection/safety nets, that may have a significant influence on youth agricultural participation where not included in the model due to data constraint. As a recommendation for further studies, given data availability, such variables should be considered when examining youth-agricultural employment nexus.

Since ICT adoption has a significant impact on agricultural employment, this study proposes improved infrastructure facilities such as reliable power supply, lowering the cost of mobile and data subscriptions and better education facilities should be prioritised at all localities. This will enable the youth to embrace agriculture and help improve their socioeconomic welfare and livelihood.

Using Wave 4 of the LSMS-ISA, logit regression, propensity score matching and the inverse probability weighted regression adjustment, makes this study one of the very few to examine the impact of ICT adoption on agricultural employment among the youth in Nigeria. It implies that this study has provided empirical evidence and expanded the frontiers of knowledge on the extent to which ICT adoption influences youth agricultural employment in Nigeria.

This paper investigates the ways digital media applications in rural areas have transformed the influence of social networks (SN) on farmers' adoption of various climate change mitigation measures (CCMM), and explores the key mechanisms behind this transformation.

The study analyzes data from 1,002 farmers’ surveys. First, a logit model is used to measure the impact of SN on the adoption of different types of CCMM. Then, the interaction term between digital media usage (DMU) and SN is introduced to analyze the moderating effect of digital media on the impact of SN. Finally, a conditional process model is used to explore the mediating mechanism of agricultural socialization services (ASS) and the validity of information acquisition (VIA).

The results reveal that: (1) SN significantly promotes the adoption of CCMM and the marginal effect of this impact varies with different kinds of technologies. (2) DMU reinforces the effectiveness of SN in promoting farmers' adoption of CCMM. (3) The key mechanisms of the process in (2) are the ASS and the VIA.

This study shows that in the context of DMU, SN’s promotion effect on farmers' adoption of CCMM is strengthened.

This study firstly aims to prepare a hierarchical structure of the barriers contributing to digital exclusion of women. Secondly, the study aims to understand the inter-relationship of the barriers by converting them into a cyclic flow.

Systematic review was conducted through Web of Science and EBSCO Host Discovery Services with keywords: “digital divide” OR “digital gap” OR “digital inequality” OR “online difference” AND gender AND wom?n AND factors OR “demographic factors” OR “socio-economic” OR determinants OR reasons OR causes OR influences. Review was conducted of articles published in English language after 2012. Systematic literature review was conducted in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Framework 2020. Authors reviewed 21 reports.

This research found absence of education as the root of digital exclusion of women in the hierarchy of barriers. The cyclic flow of barriers displayed that how ill education of women lead to financial and psychological dependence of women on men, creating a hurdle in women empowerment. To break the cycle of digital exclusion, women education is must not only on primary basis but their tertiary education is important too.

This study makes an important contribution by ranking those barriers in a pyramid hierarchy and depicting their inter relation by framing a cyclic structure. This study provides suggestions to remove those barriers and ultimately break their chain to provide digital inclusive society for women.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.