مقاله انگلیسی رایگان در مورد سازمان ها و پذیرش فناوری اطلاعات سبز – IEEE

 

مشخصات مقاله
ترجمه عنوان مقاله مدلی برای قصد پذیرش فناوری اطلاعات سبز در زمینه سازمان ها
عنوان انگلیسی مقاله Model for the Intent to Adopt Green IT in the Context of Organizations
انتشار مقاله سال 2022
تعداد صفحات مقاله انگلیسی  22 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) JCR – Master Journal List – Scopus – DOAJ
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.342 در سال 2020
شاخص H_index 158 در سال 2022
شاخص SJR 0.927 در سال 2020
شناسه ISSN 2169-3536
شاخص Quartile (چارک) Q1 در سال 2020
فرضیه ندارد
مدل مفهومی دارد
پرسشنامه دارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مدیریت
گرایش های مرتبط مدیریت فناوری اطلاعات
نوع ارائه مقاله
ژورنال
مجله / کنفرانس دسترسی آی تریپل ای – IEEE Access
دانشگاه Administration Academic Unit, Universidad Católica de Cuenca, Ecuador
کلمات کلیدی فناوری اطلاعات سبز – سازمان – مدل پذیرش – مدل معادلات ساختاری
کلمات کلیدی انگلیسی Green IT – organization – adoption model – structural equation model
شناسه دیجیتال – doi
https://doi.org/10.1109/ACCESS.2022.3184727
کد محصول e16718
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
I. Introduction
II. Hypothesis Development
III. Research Methodology
IV. Data Analysis and Results
V. Discussion
VI. Research Contributions and Implications
VII. Conclusion
References

 

بخشی از متن مقاله:

Abstract

     In organizations, part of sustainability is manifested through green information technology (GIT) for the use of information technologies (IT) resources in a profitable and sustainable manner. The purpose of this study was to understand the social, individual, and contextual factors that drive actors belonging to the sector of organizations in the Latin American and Caribbean (LAC) context on the intention to adopt GIT to generate strategies that promote its application. A model resulting from the analysis and integration of adoption models was proposed, including the theory of planned behavior (TPB), norm activation theory (NAT), GIT adoption model (GITAM), and environmental sustainability variables. To determine the predictive factors, the research team collected data from organizations belonging to Mexico, Panama, Honduras, Colombia, Ecuador, Peru, Bolivia, and Chile, where information was collected from personnel at strategic, tactical, and operational levels. Data were collected from 562 informants from different productive and service sectors and analyzed using a structural equation model with the partial least squares technique. This research provided important insights into the most significant factors that determine intent towards GIT adoption. The model analyzed contextual variables of the organization or external drivers, such as the motivating forces of environmental sustainability and environmental, organizational, and technological contexts; and behavioral variables of internal organizational actors, such as awareness of the consequences, attribution of responsibility, motivation, attitude, assignment of responsibility, and internal IT enablers.

Introduction

     The greenhouse gas emissions produced by the use of information technologies worldwide would have increased from 1.6% in 2007 to 3.5% in 2020, reaching 14% by 2040 if necessary corrections are not taken [1]–[2][3]. As dependence on devices and IT services grows exponentially, the electric energy needed to produce and feed these devices has also reached a point where it has become an important contributor to carbon dioxide creation [4], [5], one of the main greenhouse gases, as well as the creation of other contaminants of global warming [6].

     Recently, an increasing number of organizations worldwide, have experimented with initiatives to reduce their impact on the environment and improve their green protection seals [7]. As information technologies have entered most, if not all, organizational processes [8], it is necessary to approach the problem with the intention of reducing contamination produced by the technology [9].

     On the other hand, strategic levels continue to put pressure on the parts of interest to improve efficiency in IT operations and activate environmental protection to mitigate contamination that the use of IT produces. Making IT ecological inside organizations has become one of an important consideration for improving environmental sustainability [10], [11].

Conclusion

     The study validated that the main objective had been fulfilled, proposed a model for the intention to adopt the GIT in the context of LAC organizations called GITL, and answered the research questions. In GITL, the parameters that validate the measurement model are satisfied, and the reflective values of the indicators are reliable. This implies that the instrument used is statistically valid and reliable and that the indicators contribute significantly to the latent variables; that is, each indicator is correlated with its own latent variable before the others. Structurally, the nine hypotheses are statistically supported.

     The model is highly predictive because GITL has predictive relevance for exogenous constructs over endogenous ones. In other words, GIT adoption intention can be predicted from attitude towards GIT, GIT drivers, motivation for GIT, and ascription of responsibility. In turn, ascription of responsibility from awareness of consequences. On the other hand, attitude towards GIT from organizational context, environmental context and technological context. Finally, environmental context from environmental sustainability motivating forces.

     In this study, external or contextual drivers were treated separately from the internal motivational and behavioral variables of organizational actors. The interrelation between them has not been explored, and future studies should examine such relationships, especially the impact of external drivers on internal motivation. Adopting the GIT is the decision made by individuals, as identified in previous studies.

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