Adoption Of Behaviors Research Articles

Investigating the adoption of building information modeling of small-medium sized organizations in the construction industry: from a configuration perspective

ABSTRACT Building Information Modeling (BIM) is considered to be one of the most promising innovations in the construction industry, and the building industry is beginning to use and benefit from it. However, the full adoption of BIM in the construction industry is still challenging as small and medium-sized organizations (SMOs) are lagging in BIM adoption. Although existing studies have explored many influencing factors of BIM adoption, most of them are focused on a single relationship and cannot explain why certain factor that works for one organization fails in others. This study aims to respond to the research gap in previous studies on BIM adoption in SMOs by highlighting the importance of the combination of influencing factors rather than single correlations, thereby clarifying the realization mechanisms of BIM adoption in SMOs. Using the qualitative comparative analysis (QCA) approach and fsQCA3.0, this study connects the factors from technological, organizational, and environmental aspects under the technology-organization-environment (TOE) framework, five configurations leading to the high BIM adoption and two configurations leading to the low BIM adoption are identified with 36 SMO cases through the configurational lens. As one of the earliest attempts to investigate SMOs’ BIM adoption decisions using the QCA method, this study expects to offer a holistic understanding of BIM adoption in SMOs and contribute to the full BIM diffusion in the construction industry by providing valuable suggestions to industry practitioners. Highlights BIM adoption in SMOs results from a combination of technological, organizational, and environmental conditions, and no necessary conditions lead to BIM adoption behavior. More than one configuration is leading to high or low BIM adoption in SMOs. Under specific contexts, BIM capability can substitute for financial capability, while financial capability will substitute for government pressure. When conditions are missing on both the technological and organizational aspects, government or market pressure alone cannot lead to BIM adoption behavior in SMOs.

The impact of vertical and horizontal pressures on policy diffusion: evidence from APLS adoption in China

This study examines the diffusion of governmental self-regulation policy, specifically the Administrative Power List System (APLS) in China, which has received less focus than economic or social policies within horizontal and vertical pressure frameworks. By employing event history analysis and case studies, the research compares local government adoption behavior before and after the central intervention. The findings reveal that, in the absence of strong central directives, local governments are often reluctant to replicate neighboring policies, as they strive for distinctiveness in their innovations. However, once the central government issues mandates, local governments quickly adapt and implement practices observed elsewhere. The study also highlights significant vertical influences from provincial and county governments. During the exploration stage, top-down pressure from provincial governments enhances municipal adoption, although this influence is eventually surpassed by central mandates. Bottom-up learning from county-level pilot programs significantly improves adoption efficiency, especially when local governments face pressure for rapid implementation. This study contributes to the policy diffusion literature by analyzing the diffusion of governmental self-regulation policy and highlighting the mixed impacts of horizontal and vertical pressures on policy learning and adoption, with central intervention playing a crucial role.

Adoption and User Behaviour Towards Digital Payments by Millennial

The rapid adoption of digital payment systems has transformed the financial landscape, particularly among millennials, who are at the forefront of this technological shift. This study explores the adoption and user behaviour of digital payment methods among millennials in India. The research aims to identify the key factors influencing the decision to use digital payments, including convenience, security, trust, and government initiatives. Additionally, it examines how socio-cultural influences, mobile payment applications, and peer networks impact the payment choices of this demographic. Through a survey of 250 millennials, the study reveals that ease of use, trust in security features, and promotional incentives are the primary drivers of digital payment adoption. It also identifies challenges such as concerns over data privacy and digital literacy. The findings suggest that while millennials are increasingly adopting digital payment systems, their behaviour is shaped by a complex interplay of technological, economic, and social factors. The study provides insights into strategies for improving the digital payment ecosystem and encourages further research into the evolving behaviour of young consumers.

Can farmers’ adoption of conservation tillage achieve sustainable agricultural production targets? Evidence from the Jianghan Plain, Hubei, China

ABSTRACT As a major agricultural country, China is under threat from land degradation because of long-term high-carbon-emission land use patterns. Conservation tillage (CT) technologies are expected to restore soil fertility, transform agricultural production models, and improve sustainability. However, the impacts of farmers’ CT adoption on achieving sustainable agricultural development remain unclear. To investigate the heterogeneous ecological effects resulting from farmers’ adoption of CT technologies, this study estimates the ecological effects of CT and examines the differences in these effects across different technologies, utilizing survey data from 1,449 farmers in the rural Jianghan Plain of China. The results show that farmers’ technology perceptions, previous adoption behaviour, and collective economic conditions significantly affect their CT adoption behaviour. The agricultural eco-efficiency in the Jianghan Plain is only 0.65. After removing bias from self-selection and unobservable factors, the ecological effect of CT adoption was 8.43%. The four different CT technologies evaluated in this study were found to increase agricultural eco-effects and achieve sustainable agriculture. However, the agricultural eco-effects of different CT technologies vary, indicating heterogeneity. Finally, policies that include implementing different combinations of CT models according to local conditions, technical training, and establishing subsidies for CT adoption are highly recommended.

Examining Gender Disparities in Traditional Retailers' Intentions to Embrace Digital Technology in Saudi Arabia

This study aims to examine the factors influencing digital technology adoption among retail businesses in Saudi Arabia, with a focus on understanding gender-specific differences. Employing a cross-sectional design, data were collected from 291 owners and managers using an online survey. A convenience sampling technique was utilized to gather responses. The study investigated four primary constructs: intention to use digital technology, attitude toward digital technology, perceived ease of use, and perceived usefulness. Data analysis was conducted using structural equation modeling with SmartPLS software version 4. The findings reveal significant relationships among the constructs. Perceived ease of use was found to significantly influence perceived usefulness, which in turn positively affected both attitudes toward digital technology and intentions to use it. The study also highlighted that perceived usefulness has a substantial impact on intention to use digital technology, with attitudes toward technology playing a critical mediating role. Notably, gender-specific differences were observed in the impact of perceived ease of use on attitudes toward digital technology, which was significant for males but not for females. Tailored marketing and training strategies that address these differences are essential for enhancing digital technology adoption in the retail sector. These insights contribute to a deeper understanding of technology adoption behaviors and offer practical implications for improving technology integration. Received: 10 September 2024 / Accepted: 27 October 2024 / Published: 05 November 2024

Prevalence of Infertility, its Risk Factors and Child Adoption Behavior in Ambala, India

Prevalence of Infertility, its Risk Factors and Child Adoption Behavior in Ambala, India

Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model

This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformation and innovation, empirical research on the adoption of these systems remains scarce. To fill this gap, this study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model, surveying 300 employees from both large and small enterprises in South Korea. The findings reveal that effort expectancy and social influence significantly influence employees’ behavioral intention to use generative AI systems. Specifically, effort expectancy plays a critical role in the early stages of adoption, while social influence, including support from supervisors and peers, strongly drives the adoption process. In contrast, performance expectancy and facilitating conditions show no significant impact. The study also highlights the differential effects of age and work experience on behavioral intention and usage behavior. For older employees, social support is a key factor in technology acceptance, whereas employees with more experience exhibit a more positive attitude toward adopting new technologies. Conversely, facilitating conditions are more critical for younger employees. This study contributes to the understanding of the interaction between various factors in AI technology adoption and offers strategic insights for the successful implementation of AI systems in Korean companies.

Narrowing the gaps between perception and adoption behavior of integrated pest management by farmers: Incentive and challenge

Integrated Pest Management (IPM) is an important strategy in global agriculture, aimed at maintaining the growth trend of food production without compromising environmental integrity or human health. Despite various measures taken by the government to encourage farmers to adopt IPM technologies, the adoption rate of IPM in China remains insufficient. This study finds that the number of farmers who adopt IPM to a high degree is significantly lower than those who view IPM as a win-win solution for profits and the environment. To address the gap between attitudes and behaviors, this research utilizes data from a survey of 480 households in Dengkou County, Inner Mongolia, China, employing structural equation modeling to analyze the impact of farmers' perceived factors on IPM adoption rates. Additionally, a generalized linear mixed model is used to assess farmers' attitudes toward financial subsidies, while an Ordered Logit model conducts an empirical analysis of the factors influencing barriers to IPM adoption. The findings indicate that: (1) Farmers' overly optimistic expectations regarding the initial costs of IPM hinder their adoption; (2) Farmers who are skeptical about the economic benefits of IPM demonstrate greater interest in cash subsidies; (3) Land characteristics and farmer attributes influence farmers' evaluations of barriers to IPM adoption. To develop reasonable and effective policies aimed at narrowing the adoption gap for IPM, it is essential to thoroughly understand the characteristics of farmers and their perceptions of IPM, and to design incentive measures that account for group differences. Findings of the study provide information regarding the IPM adoption gap among farmers in China, thereby offering practical insights and empirical evidence to assist policymakers in developing appropriate policies. It also provides a framework for countries in similar situations globally to examine and address the adoption gap.

Understanding What Drives the Adoption of Data Analytics Among Academic Leaders and Supervisors in a Jewish Higher Education Institution

This study explores the determinants influencing the adoption of Big Data Analytics (BDA) within the Jewish higher education system centered in the Northwestern United States of America, emphasizing the impact of six key factors: Absorptive Capacity, Technological Resource Competency, Competition Intensity, Complexity, Compatibility, and Relative Advantage, alongside participants' age. Utilizing a quantitative methodology, the research surveyed 64 managerial role employees across the academic institution. Results from multiple regression analysis indicate a statistically significant relationship between these factors and the behavioral intention toward BDA adoption, with Compatibility emerging as the predominant predictor. This finding underscores the critical role of perceived consistency with existing needs and practices in influencing BDA adoption intentions. Moreover, Marketing Department Leadership exhibited significantly lower ratings in both Absorptive Capacity and behavioral intention toward BDA adoption based on a MANOVA analysis compared to other types of academic institutional leaders, suggesting a discrepancy in recognizing and leveraging new external information for competitive advantage within this group. The study concludes with recommendations for higher education institutions aiming to transition towards data-driven decision-making, highlighting the importance of fostering an organizational culture that values data literacy and aligns BDA initiatives with institutional goals. Limitations and directions for future research are also discussed, advocating for a broader investigation into behavioral intentions and the potential benefits of applying the Decomposed Theory of Planned Behavior in understanding BDA adoption.

Demystification of Readiness, Security, and Technological Enhancements in the Adoption of a Cashless Economy

The adoption of a cashless economy was accelerated globally by the devastating impact of the COVID-19 pandemic. Brunei Darussalam was not excluded from this trend, as pandemic-related restrictions were implemented to ensure the safety of its population. In light of the COVID-19 crisis, this research paper examines the factors influencing the readiness and acceptance of a cashless economy among working society in Brunei Darussalam. The integrated concepts of the Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) are applied to examine perceptions impacting their acceptance and readiness to continue adopting a cashless economy. The methodology includes a literature review and the use of secondary data from government reports and industry publications. A quantitative approach is employed, utilizing an online survey to collect non-probability samples from 212 respondents. The main instruments used in the survey are structured questionnaires. The study’s findings show that factors such as the assessment of payment modes, technological development, digital literacy, knowledge, regulatory policies, and security concerns significantly affect working society’s perceptions, readiness, and acceptance of a cashless economy. These results provide insights for policymakers and stakeholders on the key factors influencing continued cashlessness adoption and shaping societal behavior towards cashless payments.

Does peer conformity have moderating effects on university students’ consumptive behavior? A focus on self-concept, economic literacy, and e-money adoption

The study explores the moderating role of peer conformity on the relationship between self-concept, economic literacy, and e-money adoption with the consumptive behavior of university students, specifically those receiving the KIP Kuliah scholarship in Indonesia. Data were collected through an online survey of 328 students and analyzed using Moderated Regression Analysis (MRA). The results indicated that the relationship between self-concept and consumptive behavior, as well as e-money adoption and consumptive behavior, was significantly strengthened by peer conformity. However, the effect of economic literacy on consumptive behavior was not moderated by peer conformity. These findings suggest that while self-concept and e-money adoption are influenced by peer conformity, economic literacy operates independently of peer conformity. The importance of fostering economic literacy and a critical self-concept among students to mitigate the effects of peer pressure on consumption was highlighted in this research. The findings reveal that peer conformity strengthens the effect of self-concept and e-money adoption on consumptive behavior, but does not moderate the impact of economic literacy. The research highlights the need for fostering economic literacy and critical self-concept to reduce the influence of peer conformity on student consumption decisions. Further research should expand the scope beyond KIP Kuliah students to include a broader student population.

Discovering Islamic marketing potential in shaping blockchain-­based halal logistic services: a bibliometric analysis

Purpose This paper aims to examine the Islamic marketing literature to uncover potential customer adoption behaviours and enhance the effectiveness of blockchain-based halal logistics services in catering to customer demands. The findings of this paper provide substantial contributions to the realms of both halal logistics services and Islamic marketing literature, delineating future paths for research. By delving into halal logistics practices, integration procedures and service provider performance, this paper assists stakeholders in enhancing halal logistics services to meet the changing demands of customers effectively. Design/methodology/approach This paper uses a systematic review incorporating bibliometric analysis to examine past and contemporary research topics, selecting and appraising contributions while analysing and consolidating data. A methodical approach has been used to identify, assess and incorporate pertinent studies on Islamic characteristics, traceability technology, blockchain integration and halal logistics practices. Findings After screening and analysing 139 selected documents with the VOS viewer, it is evident that among a 1,000 keywords, 15 stand out in terms of frequency and link strength. The research highlights the considerable academic interest in themes such as “blockchain”, “halal logistics” and “supply chain”, underscoring their importance. The findings of this paper help bridge the gap in Islamic marketing by linking technology with religious values. It suggests that the integration of blockchain technology in halal logistics enhances operational efficiency while aligning with both operational and Islamic marketing principles, promoting ethical conduct and transparency as key enablers. Practical implications The theoretical significance of this paper lies in establishing a correlation among three key research domains: technology, symbolised by blockchain; customer-centric operations, incorporating the halal supply chain and logistics within Islamic marketing. The outcomes reflect consumer behaviour and Shariah compliance. This integration has the potential to introduce innovative theoretical frameworks that encompass religious ethics in marketing, logistics and technological advancements. Originality/value This paper comprehensively analyses the intersection between blockchain technology, halal logistics, supply chain management and Islamic marketing. The paper has comprehensively analysed previous studies and outlined the future research path for blockchain technology in halal logistics and its application in Islamic marketing literature.

Factors shaping innovative behavior: A meta‐analysis of technology adoption studies in agriculture

AbstractThis study conducts a meta‐regression analysis to synthesize the marginal effects of 12 factors that frequently appear in empirical studies examining farmer's technology adoption behavior. The analysis includes 187 observational studies on technology adoption in agriculture, which are published in 32 peer‐reviewed journals in the broader field of agricultural economics, covering farmer's adoption in 47 countries for a diverse range of agricultural technologies. Using this broad meta‐dataset, we investigate whether each of the 12 determinants has a true effect on technology adoption rates and examine whether Type I and Type II publication bias are present in the adoption literature. Our results reveal that while most determinant factors significantly affect adoption rates, their marginal effects are generally of small magnitude and vary considerably by technology type and country group. Additionally, our results provide evidence of the presence of Type I publication bias in half of the factors considered and Type II publication bias in nearly all, underscoring the need for caution when interpreting results in the adoption literature by researchers and policymakers. Overall, the findings highlight the critical need for proactive measures to address publication bias and promote more transparent and credible research practices in agricultural economics.

Exploring the Role of Tourist Pro-Environmental Behavior in Autonomous Vehicle Adoption: A TPB and PLS-SEM Approach

As businesses and governments increasingly explore innovative strategies to promote pro-environmental behavior, autonomous vehicles (AVs) have emerged as a key initiative for fostering sustainable communities. However, the specific norms—personal, descriptive, and subjective—that influence behavioral intentions regarding AV adoption remain underexplored. This research addresses this gap by integrating the extended theory of planned behavior (TPB) with pro-environmental variables to examine both direct and indirect influences on behavioral intentions. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the proposed model was validated with data from 516 domestic Chinese tourists. The findings highlight that subjective norms and trust significantly shape positive intentions toward adopting autonomous vehicles. Furthermore, environmental knowledge and concerns exert a significant indirect impact on these intentions, underscoring the complex interplay of factors that drive pro-environmental behavior. These results provide valuable insights for policymakers and practitioners aiming to enhance the acceptance of AVs in China and offer a foundation for future research on the role of norms in technology adoption.

Investigating the determinants of user adoption behavior in the context of conflicting health information: a DEMATEL-ISM model approach

PurposeThe purpose of this paper is to investigate the factors influencing user adoption behavior in the context of conflicting health information, thereby contributing to the understanding of users' information decision-making and adoption processes within intricate information environments. Furthermore, this research endeavors to offer guidance for mitigating the adverse effects of contradictory health information on users' cognitive perceptions.Design/methodology/approachFirst, this study used literature coding to identify factors that influence user adoption behavior in the context of conflicting health information. Secondly, we utilized the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to unveil the key influencing factors based on centrality and causality. Lastly, utilizing the Interpretive Structural Model (ISM), we constructed the multilevel hierarchical structure model of influencing factors to delineate the relationships among factors across different levels.FindingsThe key causal factors influencing user adoption behavior in the context of conflicting health information include user basic characteristics, experience accumulation, and information type. The key result factors consist of psychological emotion, perceived trade-offs, and the source credibility. The significant elements include users' psychological emotions, perceived trade-offs, emotional support, source credibility, and informational support. Furthermore, user adoption behavior in the context of conflicting health information is a manifestation of the interplay among surface-level, mid-level, and deep-level factors.Research limitations/implicationsTheoretically, this paper enriches the existing relevant theoretical framework and offers a novel perspective for further investigation into user adoption behavior concerning conflicting health information. Practically, this study extracts factors that can influence user adoption behavior in the context of conflicting health information which is an essential reference value for guiding and optimizing user adoption behavior.Originality/valueThis paper expands the system of factors influencing user adoption behavior in the context of conflicting health information from individual, information and social perspectives. Utilizing DEMATEL quantitative analysis and ISM multilevel hierarchical models, this research examines and illustrates the significance of the influencing factors and their interrelationships.

Dissemination dynamics based on delayed behavior on double-layer networks

Adoption behavior spreads socially due to a variety of variables, and the classic dynamic model is insufficient to fully understand the impact of psychological elements on humans. To illustrate the intricacy of personal decision-making and information dissemination, this paper presents the psychological mechanism of latency. This research analyzes the dynamic process on double-layer networks using an edge division theory based method. The simulation results show the phenomena of phase transition. Global outbreak is possible when latency behavior is weak; global outbreak did not happen when latency behavior becomes strong. There is good agreement between the theoretical analysis and experimental simulation results. It is extremely important for the study of psychology, sociology, and dynamics.

Adoption of green production technologies by farmers through traditional and digital agro-technology promotion–An example of physical versus biological control technologies

Traditional and digital agro-technology promotion are two critical methods for disseminating agricultural technology information, which effectively encourages farmers to employ green production technologies. This paper empirically examines the effects of traditional and digital agro-technology promotion on the adoption of green production technologies by 619 apple producers in the primary apple production area of Guanzhong Plain, China, using micro-survey data. The study's findings suggest that both promotion models significantly influence the adoption of green production technologies by farmers. This conclusion remains valid after the instrumental variables approach and a series of robustness tests are implemented to address endogeneity concerns. The heterogeneity analysis revealed that the impact of the two promotion modes on the adoption behavior of green production technologies by farmers varied by scale. Specifically, digital agro-technology promotion had a greater impact on the adoption of physical control technologies by small-scale farmers, while traditional agro-technology promotion had a greater impact on the adoption of biological control technologies by large-scale households. In addition, the technological differences between traditional agrotechnology promotion and digital agrotechnology promotion result in clear complementary and substitution effects. The two modes of promotion have evident complementary effects for biological control technologies. The two modalities of promotion for physical control technologies exhibit complementary effects between social communication-type promotions and traditional agro-technology promotions, as well as substitution effects between short-video promotions and traditional agro-technology promotions.

The power of electronic Word of Mouth in inducing adoption of emerging technologies

This study examines the influence of electronic Word-of-Mouth (eWOM) on consumer expectations and intentions to adopt emerging technologies, specifically focusing on cryptocurrency payment methods. Employing the Elaboration Likelihood Model (ELM), the research utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (PLS-MGA) to analyze data from a diverse sample of 505 respondents sourced from MTurk. The findings reveal that the quality, consistency, and volume of eWOM significantly shape consumer expectations. Notably, the two-sidedness of online reviews does not have any substantial impact on both expectations and adoption behaviors toward cryptocurrency payment methods. Furthermore, factors such as the time spent online, and the frequency of online shopping were found to partially moderate the effects of eWOM on adoption behavior. This research contributes pioneering insights into the role of eWOM in influencing consumer attitudes towards cutting-edge technologies, extending existing knowledge beyond traditional consumer decisions to include technological adoption, particularly in digital finance. This offers valuable implications for technology firms and digital marketers aiming to harness eWOM to promote new technological solutions.

Open Government Data Intention-Adoption Behavioural Model for Public Sector Organisations: A Technological Innovation Perspective

The objective of this research is to examine an open government data (OGD) intention-adoption behavioural model for the public sector organisations (PSOs), since examining the model is expected to lead to a better understanding of how to realise this technological innovation among PSOs on a large scale to excavate its innovative value. In this respect, we proposed a theoretical model to explore the factors that affect OGD adoption behaviour based on three dimensions of the TOE (technology, organisation, and environment) framework. The model was then analysed after collecting the survey data from 249 PSOs in Pakistan using a purposive sampling technique. The findings unfolded that the factors, except centralisation and civil society participation, framed in technology dimension (data resource, dataset quality, perceived benefits), organisation dimension (data-driven culture, digitisation capacity, need for transparency), and environment dimension (compliance pressure, political leadership commitment) affect the PSOs’ OGD adoption intention. Cumulatively, the intention to adopt OGD was found to have a significant positive impact on OGD adoption behaviour. Based on the TOE framework, the model, with the addition of adoption intention as a significant positive factor in adoption behaviour, bears a crucial theoretical and practical contribution in the context of OGD. Doi: 10.28991/ESJ-2024-08-05-04 Full Text: PDF

Determinants of digital technology adoption in innovative SMEs

Despite the increasing adoption of digital technology, small and medium enterprises (SMEs) continue to lag behind larger firms. This study integrates the technology, organization, and environment (TOE) framework with Rogers’ diffusion of innovation (DOI) theory to investigate the factors influencing SMEs’ digital technology adoption. Data from 419 SMEs was analyzed using partial least squares structural equation modelling (PLS-SEM), followed by artificial neural network (ANN) analysis to rank the importance of the variables identified.The PLS-SEM results show that technological, organizational, and environmental factors directly impact adoption. The supported variables include adoption costs, top management support, human resources, digital culture, and trading partner pressure. Some factors indirectly impact adoption through top management support. This study also found that SMEs’ international orientation moderates the relationship between digital culture and adoption behavior. The ANN results identify that the most important predictors, ranked from the most to the least influential, are digital culture, international orientation, top management support, trading partner pressure, human resources, and adoption costs.This research contributes to the theoretical discourse on technology adoption by integrating the TOE framework with Rogers’ DOI theory. It highlights that no single TOE element functions in isolation. The findings provide practical guidance for SME managers, stressing the need to improve organizational factors, such as, human resources, digital culture, and top management support. Governments may use these findings to identify ways to support SMEs’ digital technology adoption, particularly by offering subsidies to reduce costs, which remain a barrier.