Alley cropping systems as Ecological Focus Areas: A PLS-analysis of German farmers’ acceptance behaviour

Otter, Verena; Beer, Lara

doi:10.1016/j.jclepro.2020.123702

Cited by 10 publications

(8 citation statements)

References 33 publications

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“…This incurs a higher cost for the organization. This study results confirmed that perceived cost negatively affect behavioral intention, while this contradicts the previous study by Otter and Beer (2020) that identified an indirect relationship with intention via perceived usefulness. These negative influences on AI adoption intention among tourism and leisure companies in Malaysia as the results have negative beta value.…”

Section: Discussionsupporting

confidence: 65%

“…Notably, in the current extended model, the R 2 values of usage intention are 0.86, which is much greater than the values of 0.40 observed in the earlier TAM model (Sun & Zhang, 2006;Ventakatesh et al, 2003). Even this explanatory power is greater than the previously extended TAM studies for the dependent variable of behavioral intention (Otter & Beer, 2020;Zheng & Li, 2020). These results showed that as extended TAM can predict behavioral intention, the proposed model is generally comprehensive, adequate, accurate, and functional for understanding AI in the tourism sector.…”

Section: Discussionmentioning

confidence: 72%

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Intention to Adopt AI-Powered Online Service Among Tourism and Hospitality Companies

Alam

Masukujjaman

et al. 2022

International Journal of Technology and Human Interaction

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This study examines the factors affecting the adoption of artificial intelligence (AI) powered online service in the tourism and hospitality sector through an extension of the technology acceptance model (TAM) by including self-efficacy, subjective norms, technological knowledge, and perceived cost in the analysis. Data was collected from 336 respondents in Malaysia’s tourism and hospitality industry using the questionnaire survey. The empirical results confirmed that perceived usefulness, ease of use, attitude, cost, and technology knowledge significantly affected behavioral intention. Self-efficacy, perceived ease of use, and perceived usefulness affected the attitude towards AI. Attitude mediated the relationship between perceived ease of use and behavioral intention as well as the relationship between perceived usefulness and behavioral intention. This study contributes to enhancing AI's understanding of the tourism and hospitality industry context. This study also improves TAM by proposing a comprehensive model with cognitive external and technology-specific factors.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 72%

Intention to Adopt AI-Powered Online Service Among Tourism and Hospitality Companies

Alam

Masukujjaman

et al. 2022

International Journal of Technology and Human Interaction

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“…essential to evaluate the constructs' discriminant validity [98][99][100]. The cut-off scores should be smaller than 0.85 (more strict threshold) or 0.90 (more lenient threshold) to interpret the results [98,99].…”

Section: Plos Onementioning

confidence: 99%

Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling

et al. 2021

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Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients’ satisfaction relating to telemedicine adoption in rural public hospitals settings in Bangladesh through the adaptation of Expectation Disconfirmation Theory extended by Social Cognitive Theory. This research advances a theoretically sustained prediction model forecasting patients’ satisfaction with telemedicine to enable informed decision making. A research model explores four potential antecedents: expectations, performance, disconfirmation, and enjoyment; that significantly contribute to predicting patients’ satisfaction concerning telemedicine adoption in Bangladesh. This model is validated using two-staged structural equation modeling and artificial neural network approaches. The findings demonstrate the determinants of patients’ satisfaction with telemedicine. The presented model will assist medical practitioners, academics, and information systems practitioners to develop high-quality decisions in the future application of telemedicine. Pertinent implications, limitations and future research directions are endorsed securing long-term telemedicine sustainability.

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“…For example, this method is a full-fledged variance-based approach ideal for the linear, non-linear, recursive, and non-recursive structural model (Benitez, Henseler, Castillo, & Schuberth, 2020). This is a more suitable choice for explorative studies and highly complex casual (i.e., confirmatory and explanatory) models (Otter & Beer, 2021). PLS-SEM has distinctive features that do not follow the restrictive assumptions imposed by CB-SEM (Ali et al, 2018;Astrachan, Patel, & Wanzenried, 2014).…”

Section: Data Analysis and Resultsmentioning

confidence: 99%

“…This study measured the distinctiveness of a latent construct using the heterotrait-monotrait ratio (HTMT) criterion test. Literature indicates that the HTMT criterion is essential to evaluate the constructs' discriminant validity (Benitez et al, 2020;Hair Jr, Howard, & Nitzl, 2020;Otter & Beer, 2021). The cut-off scores should be smaller than 0.85 or 0.90 to interpret the results (Benitez et al, 2020;Hair Jr et al, 2020).…”

Section: Measurement Modelmentioning

confidence: 99%

Health Seekers’ Acceptance and Adoption Determinants of Telemedicine in Emerging Economies

Zobair

Sanzogni

Houghton

et al. 2021

AJIS

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This study investigates health seekers’ acceptance and adoption determinants of telemedicine services in a rural public hospital setting in an emerging economy using an adapted, extended Technology Acceptance Model. The present study pursued synthesising a plethora of existing literature and contextualised the significance of seven broad categories of potential determinants that significantly affect patients’ acceptance and adoption intentions: perceived usefulness, perceived ease of use, self-efficacy, service quality, privacy and data security, social influence, and facilitating conditions. The partial least square structural equation modeling technique was employed to test the conceptual model and research hypotheses. A cross-sectional survey was administered among 500 telemedicine users in randomly selected rural and remote areas of Bangladesh. Excluding self-efficacy and ease of use, five determinants expressively contributed to patients’ acceptance of telemedicine adoption, explaining 65% of the variance (R2) in behavioural Intention. The empirical findings have the quality of rigour obtained from rich data sets in health informatics and can contribute to build telemedicine into an institutionalised health infrastructure in Bangladesh and similar settings. Pertinent implications, limitations and future research directions were recommended to secure the long-term sustainability of telemedicine healthcare projects.

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Alley cropping systems as Ecological Focus Areas: A PLS-analysis of German farmers’ acceptance behaviour

Cited by 10 publications

References 33 publications

Intention to Adopt AI-Powered Online Service Among Tourism and Hospitality Companies

Intention to Adopt AI-Powered Online Service Among Tourism and Hospitality Companies

Forecasting care seekers satisfaction with telemedicine using machine learning and structural equation modeling

Health Seekers’ Acceptance and Adoption Determinants of Telemedicine in Emerging Economies

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