UNDERSTANDING THE ADOPTION OF USE CASE NARRATIVES IN THE UNIFIED MODELING LANGUAGE

This research examines the adoption of Use Case Narratives within the Unified Modeling Language (UML).Using the Technology Acceptance Model (TAM) as a framework, practitioners with UML experience were asked questions to measure their Perceived Ease of Use and Perceived Usefulness of Use Case Narratives and their Intentions to Adopt them. We extend Perceived Usefulness in the context of UML adoption to address the question “usefulness for what purpose(s)?” Generally, we find that TAM explains Use Case Narrative acceptance. More importantly, we find that Perceived Usefulness is explained by usefulness for specific software development tasks. This research provides three main contributions, beginning with an improved understanding of the role of Use Case Narratives in UML projects. Second, the study extends TAM by explaining how a technology is used rather than simply whether it is used. Third, this study provides a framework for future studies into other UML diagrams

Success Factors Impacting Artificial Intelligence Adoption --- Perspective From the Telecom Industry in China

As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding the external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The results indicate that compatibility, relative advantage, complexity, managerial support, government involvement, and vendor partnership are significantly related to AI adoption. Managerial capability impacts other organizational capabilities and innovation attributes of AI, but it is indirectly related to AI adoption. Market uncertainty and competitive pressure are not significantly related to AI adoption, but all the external environment factors positively influence managerial capability. The study provides support for firms\u27 decision-making and resource allocation regarding AI adoption. In addition, based on the resource-based view (RBV), this article conducts study 2 which explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from telecom companies in China. The results indicate that at the firm level, the customer value and operational expenses are significantly related to sustainable growth. Also, at the industry level, industry investment significant impacts sustainable growth. Study 2 provides insights for practitioners the way to keep sustainable growth

Factors Influencing Farmers’ Adoption of Best Management Practices: A Review and Synthesis

Best management practices (BMPs) for reducing agricultural non-point source pollution are widely available. However, agriculture remains a major global contributor to degradation of waters because farmers often do not adopt BMPs. To improve water quality, it is necessary to understand the factors that influence BMP adoption by farmers. We review the findings of BMP adoption studies from both developed and developing countries, published after (or otherwise not included in) two major literature reviews from 2007 and 2008. We summarize the study locations, scales, and BMPs studied; the analytical methods used; the factors evaluated; and the directionality of each factor’s influence on BMP adoption. We then present a conceptual framework for BMP adoption decisions that emphasizes the importance of scale, the tailoring or targeting of information and incentives, and the importance of expected farm profits. We suggest that future research directions should focus on study scale, on measuring and modeling of adoption as a continuous process, and on incorporation of social norms and uncertainty into decision-making. More research is needed on uses of social media and market recognition approaches (such as certificate schemes and consumer labeling) to influence BMP adoption

Quantifying discrepancies in opinion spectra from online and offline networks

Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as the source for accurate public opinion mining.Comment: 10 pages, 4 figure

Information Trustworthiness and Information Adoption in Social Media Marketing: Contextualization of Ewom and Its Implications For Marketers

Social media platforms have exposed consumers to a large amount of either accurate information or misleading information. The quick spread of information through electronic word-of-mouth on social media networks has made it difficult for consumers to distinguish between marketer-generated content and user-generated content. This study aims to identify the factors that influence consumers when making purchasing decisions and to establish a comprehensive framework for consumers in the digital marketing. The study aimed to investigate how technology acceptance, electronic word-of-mouth (eWOM), and perceived risk affect information adoption by users in social media marketing. The study collected data from 213 social media users in Semarang via an online survey and used partial least squares structural equation modeling (PLS-SEM). The findings showed that information trustworthiness and information adoption were intermediaries between information quality, usefulness, perceived risk, argument quality, and information adoption. The study suggests that the quality and usefulness of the information are significant factors that affect the adoption of information. For social media marketers, providing high-quality and balancing useful information can increase consumer chances of adoption, thereby leading to purchase intention. The findings highlight for the marketers to ensure that the information provided is of high quality and relevant to the target audience. Keywords: digital marketing, social media, information adoption, electronic word-of- mouth, trus

Predictors of Sustainable Energy Technology Adoption Behavior in South-Western Nigeria

This study focuses on the predictors of sustainable energy technology (SET) adoption behavior in south-western Nigeria. Although the extant literature is gorged with plethora of studies on sustainable energy technology adoption, studies that were conducted in a typical emerging economy like Nigeria in general and south-west Nigeria in particular are grossly under-researched and under-reported. The main objective of this study is to empirically investigate the predicting factors that influence the adoption of sustainable energy technology in south-western Nigeria. Based on the foregoing, the study adopted quantitative design and quota sampling as the research design and sampling method respectively. Questionnaire was the research instrument. The validity and the reliability of the research instrument were tested using construct validity and composite validity respectively. Hypothesized relationships were tested using structural equation modeling. It was found that performance expectancy, perceived value and effort expectancy have significant effect on the intention to adopt sustainable energy technology, while social influence, facilitating condition and intrinsic motivation do not. Also, it was revealed that there is a positive and significant relationship between intention to adopt sustainable energy technology and the actual adoption of sustainable energy technology. It was concluded that the study provided empirical support that Unified theory of acceptance and use of technology (UTAUT) provides a robust and comprehensive theoretical framework to predict, explain and describe sustainable energy technology adoption behaviour in a typical developing country context like Nigeria. The marketers of SET products should use price as their unique selling proposition to attract customers. Also, the quality of the SET products should conform with the expected performance of the product. Also, the SET marketers should endeavour that expected efforts of the prospective SET products consumers are met adequately since social influence, facilitating conditions and intrinsic motivation did not have significant effect on adoption intentions for SET. Keywords: Sustainable energy technology, Adoption behavior, Intention to adopt, Unified theory of acceptance and use technology, Structural equation modeling, Nigeria. DOI: 10.7176/JESD/11-8-07 Publication date: April 30th 202

A Longitudinal Model of Post-Adoption Phenomena and Its Empirical Test in the Context of Social Games

It is widely accepted that initial adoption is critical to innovation success. A less recognized argument in the information System (IS) field is that post-adoption use of an innovation is equally important, if not more important than its initial acceptance. Drawing on the popular Unified Theory of Acceptance and Use Technology (UTAUT) model (Venkatesh et al. 2003) while adopting the Integrative Framework of Technology Use (IFTU) (Kim and Malhotra, 2005) paradigm, the present study proposes and tests a general modeling approach for one type of modern internet innovations – social games. To this end, we develop testable hypotheses which will be tested in order to support our claims. A research design based on the model is proposed, and theoretical contributions are provided

Goal and scope in life cycle sustainability analysis: the case of hydrogen production from biomass.

The framework for life cycle sustainability analysis (LCSA) developed within the project CALCAS (Co-ordination Action for innovation in Life-Cycle Analysis for Sustainability) is introducing a truly integrated approach for sustainability studies. However, it needs to be further conceptually refined and to be made operational. In particular, one of the gaps still hindering the adoption of integrated analytic tools for sustainability studies is the lack of a clear link between the goal and scope definition and the modeling phase. This paper presents an approach to structure the goal and scope phase of LCSA so as to identify the relevant mechanisms to be further detailed and analyzed in the modeling phase. The approach is illustrated with an on-going study on a new technology for the production of high purity hydrogen from biomass, to be used in automotive fuel cells

Barriers, trategies, and best practices for BIM Adoption in Quebec prefabrication small and medium-sized enterprises (SMEs)

Prefabricated construction has long faced problems due to the industry’s fragmentation. Building Information Modeling (BIM) has thus appeared as an efficient solution to provide a favorable environment for efficient completion of projects. Despite its benefits, implementing BIM successfully in small and medium-sized enterprises (SMEs), which represent the vast majority of manufacturers in Quebec, requires deep risk analysis and rigorous strategies. Hence, this work aims to study BIM implementation barriers, strategies, and best practices in wood prefabrication for SMEs through a literature review, semi-structured interviews, and an online survey. After qualitative content analysis, 30 critical barriers, 7 strategic milestones, and 31 best practices to maximize BIM benefits were revealed. One of the critical barriers concerns the effort required to develop BIM software libraries and programs to translate information from the BIM model to production equipment. Among the best strategies, it is essential to start by analyzing the current business model of the SMEs and to appoint a small BIM committee whose main responsibilities are management, coordination, and modeling. The prevalent best practices were to support the implementation team and encourage communication and collaboration. Previous studies show that BIM is not fully exploited in prefabrication for various reasons. This study highlights the critical barriers, strategies, and best practices for BIM adoption and proposes a framework for BIM implementation in prefabrication SMEs in Quebec, Canada. It also provides a summary of current knowledge and guidelines to promote BIM adoption in this sector

Factors Influencing the Adoption of Learning Management Systems by Medical Faculty

Despite recommendations by the Association of American Medical Colleges regarding the adoption of technology in medical universities, faculty are still reluctant to adopt new learning technologies. The purpose of this qualitative interview study was to determine the factors existing in the adoption of learning management technology among late adopters within the faculty of colleges labeled as comprehensive academic medical centers. Using the Everett Rogers diffusion of innovations theory as its framework, this study sought to ascertain the factors late adopters identify as preventing them from adopting technology and to determine what measures they suggest to increase technology adoption among their peers. This qualitative study used interviews of participants identified as late adopters and subsequent document analysis to provide evidence for the factors identified. Using in vivo coding, data were organized into 5 themes: factors, learning management systems, demographics, general technology, and solutions. Results showed that late adopters avoided adopting learning management technology for several reasons including training, time, ease of use, system changes, lack of technical support, disinterest, and the sense that the technology does not meet their needs. Recommended solutions offered by faculty included varied times for trainings, peer mentoring, and modeling learning management system use among faculty. Understanding these factors may contribute to social change by leading to more rapid adoption and thus introducing efficiencies such that faculty can dedicate more time to medical instruction. It also may aid other universities when considering the adoption of a learning management system