A mindful product acceptance model

Ta, Anh; Prybutok, Victor R.

doi:10.1080/12460125.2018.1479149

Cited by 8 publications

(6 citation statements)

References 43 publications

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“…Subsequently the regression analysis confirmed that the intention-to-use of young farmers was significantly affected by organizational support, average annual turnover, perceived usefulness, perceived ease of use, and sense of trust, among which organizational support was the factor that exerted the most positive effect in encouraging young farmers to accept IoT technology. This result is consistent with conclusions of some articles (Alambaigi and Ahangari, 2015;Kabbiri et al, 2018;Kamrath et al, 2018;Ta and Prybutok, 2016). The conclusion that young farmers who receive support from family and fellow farmers are relatively willing to employ IoT technology particularly reflects Taiwan's agricultural structure and the close relationships between agricultural affairs, family affairs, and community affairs; accordingly, these results can clarify the focus of IoT marketing.…”

Section: Factors Affecting Young Farmers' Intention To Use Internet O...supporting

confidence: 89%

“…For example, the current study considered smart agriculture with the objective of exploring the scale of smallholder production and their average economic standard (Kabbiri et al, 2018). In addition, self-efficacy regarding technology, sense of trust, and perceived convenience are also critical factors to affect farmers to adopt computer systems (Amin and Li, 2014;Ta and Prybutok, 2016;Tubtiang and Pipatpanuvittaya, 2015). Regarding situated environment, analysis of external environments can be conducive to the quality of products and services as well as supply procedures, shipping services, reasonable prices, and appropriate promotion strategies all affect users' intention and enhance their perceptions of decision-making with innovative technology (Alambaigi and Ahangari, 2015;Amin and Li, 2014;Kabbiri et al, 2018;Ta and Prybutok, 2016;Tsai et al, 2014).…”

Section: Technology Acceptance Model In Agriculture Industrymentioning

confidence: 99%

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Implementation of Internet of Things depends on intention: young farmers’ willingness to accept innovative technology

Chuang

Wang

Liang

2020

IFAM

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Innovative applications of smart technology constitute a current trend in agricultural development. This study employed a technology acceptance model to explore the intention of young farmers to apply Internet of Things systems in field-level management of Taiwanese farms. An online questionnaire was used to collect data regarding farmers aged 45 years or younger who were currently engaged in agricultural production. Statistical analysis of 241 valid questionnaires revealed that young farmers’ intention to use innovative technologies was affected mainly by perceived organizational support, followed by average annual turnover, perceived usefulness, perceived ease of use, and sense of trust in the system supplier. This study suggests that agricultural administration agencies should consider farmers’ farming needs and intention to use; agencies should employ problem-solving and design thinking when developing smart agriculture policies. Insightful design of incentives and guidance measures enables young farmers to maximize achievement and to minimize effort.

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Section: Factors Affecting Young Farmers' Intention To Use Internet O...supporting

confidence: 89%

Section: Technology Acceptance Model In Agriculture Industrymentioning

confidence: 99%

Implementation of Internet of Things depends on intention: young farmers’ willingness to accept innovative technology

Chuang

Wang

Liang

2020

IFAM

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“…Most of the past studies have been done in the context of IT-related technologies. However, some studies have been conducted on the use of non-IT technologies such as apparel shopping [4,24], bottled water usage [25], acceptance of electric vehicles [23], intention to use YouBike system [26], outsourcing in organizational decision making [27], and acceptance of sustainability labels [28]. Therefore, TAM is the most appropriate model to predict customers' intention to use drone delivery.…”

Section: Theoretical Foundation: Technology Acceptance Modelmentioning

confidence: 99%

An Empirical Evaluation of Customers’ Adoption of Drone Food Delivery Services: An Extended Technology Acceptance Model

Waris¹,

Ali

Nayyar

et al. 2022

Sustainability

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A single technological advancement in the business sector tremendously changed customers’ lifestyles and consumption behavior. Drone technology is one of the main revolutions that increase business efficiency at a lower cost. However, the acceptance of emerging technologies is not rapid in developing markets. Therefore, this study aims to evaluate customers’ adoption of drone technology in the context of food delivery services. This study has used an extended technology acceptance model (TAM) to assess customers’ behavior. Product processing innovativeness, information processing innovativeness, and subjective norms have been added as additional constructs into TAM. The data of 354 customers from five different cities of Pakistan have been collected and analyzed through partial least square structural equation modeling (PLS-SEM). The results of the study revealed that all proposed hypotheses, except the positive influence of perceived ease of use on perceived usefulness, were accepted. Further, the results depict that perceived usefulness, subjective norms, and attitude were the major predictors of customers’ adoption of drone food delivery services. In addition to this, customers’ word of mouth has a greater influence and reach than other forms of marketing communication. Therefore, practitioners and marketers may consider hosting competition programs to experiment with drone food delivery systems to enhance the acceptance of this technology among the masses.

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“…The Cronbach alpha coefficient, factor loadings of the suconstructs of the main constructs, Eigenvalues, composite reliability (CR), percentage variance, and the average variance extracted are displayed in Table A3. For each of the factor loadings, the indicators surpassed the accepted threshold of 0.7 [138]. Results from Table A3 suggest that all constructs are reliable since, in the first phase of the study, the values for the Cronbach alpha coefficient and composite reliability are higher than the threshold of 0.7.…”

Section: Descriptive Statisticsmentioning

confidence: 89%

Ghanaian SMEs Amidst the COVID-19 Pandemic: Evaluating the Influence of Entrepreneurial Orientation

Anaba

et al. 2021

Sustainability

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Entrepreneurial orientation has recently been touted as a tool for solving enterprise failures in emerged and emerging economies especially during and after an epidemic. This study aims at understanding the impact of entrepreneurial orientation on enterprise performance in the Ghanaian food processing industry by assessing the mediating effects of innovation types and intellectual property. Data were collected from 702 owners/managers in the food processing industry via survey questionnaires. The data were analyzed using the partial least squares structural equation modeling (PLS-SEM) to test the hypothesis via the Smart PLS software. The findings show that entrepreneurial orientation, innovation types, and intellectual property positively and significantly influenced enterprise performance. Furthermore, the results indicated that the mediation effects of innovation types and intellectual property were full and partial, respectively. Useful policy implications are further proposed and discussed based on the study results.

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A mindful product acceptance model

Cited by 8 publications

References 43 publications

Implementation of Internet of Things depends on intention: young farmers’ willingness to accept innovative technology

Implementation of Internet of Things depends on intention: young farmers’ willingness to accept innovative technology

An Empirical Evaluation of Customers’ Adoption of Drone Food Delivery Services: An Extended Technology Acceptance Model

Ghanaian SMEs Amidst the COVID-19 Pandemic: Evaluating the Influence of Entrepreneurial Orientation

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