A meta-analysis of the impact of TOE adoption on smart agriculture SMEs performance
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| 发表在: | PLoS One vol. 20, no. 2 (Feb 2025), p. e0310105 |
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Public Library of Science
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| 在线阅读: | Citation/Abstract Full Text Full Text - PDF |
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| 001 | 3163165227 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0310105 |2 doi | |
| 035 | |a 3163165227 | ||
| 045 | 2 | |b d20250201 |b d20250228 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Nagy, Adrian | |
| 245 | 1 | |a A meta-analysis of the impact of TOE adoption on smart agriculture SMEs performance | |
| 260 | |b Public Library of Science |c Feb 2025 | ||
| 513 | |a Evidence Based Healthcare Journal Article | ||
| 520 | 3 | |a BackgroundAgricultural SMEs face distinct challenges due to factors such as weather, climate change, and commodity price changes. Technology has become essential in helping SMEs overcome these challenges and grow their businesses. The relationship between technology and SMEs in the agriculture sector covers various aspects, such as using hardware and software, digital applications, sensors, and e-commerce strategies to be examined in further depth through literature study.Problem statementThe implementation of the TOE (technology, organization, and environment) framework in smart agriculture faces several challenges. To overcome these challenges, an integrated approach is needed that involves technological capacity building, organizational management changes, and adequate policy and infrastructure support to help SMEs in the agricultural sector develop their businesses.ObjectivesThis research aims to demonstrate and identify how TOE plays an important role in the performance of SMEs, particularly with regard to agriculture in order to improve agricultural productivity, efficiency, and sustainability while enabling access to broader markets in several countries. This study employs a meta-analysis method using a quantitative approach taken by each publication, which typically used SEM.MethodsPRISMA technique was used to examine evidence from clinical trials, and clinical significance was determined using the GRADE approach. Statistical analysis was performed using the Fisher test to combine the results of several studies and Cohen’s approach to interpreting effect sizes.FindingsThe results of this study are in line with the findings of 27 previous studies which showed a direct positive relationship between TOE construction and the performance of agricultural SMEs, with variables including technological factors, organizational factors, environmental factors, and SME performance. The synergy between technology adoption by agricultural SMEs and Industry 4.0 can increase connectivity and automation in the agricultural sector. However, it is important to remember that adopting TOE to realize the smart agriculture concept has its own challenges and risks, such as resource management (technology), good organizational management (organization), and internal and external organizational environments (environments), including intense competitionResearch implicationTOE adoption improves access to information about competitors and customers, providing practitioners and decision-makers with a clearer understanding. It enables focus on factors with a significant impact on TOE adoption, so that they are more independent in developing effective business concepts that are adaptive to the era of agricultural technology 4.0. | |
| 653 | |a Capacity development | ||
| 653 | |a Clinical trials | ||
| 653 | |a Climate change | ||
| 653 | |a Agricultural industry | ||
| 653 | |a Agricultural production | ||
| 653 | |a Agricultural technology | ||
| 653 | |a Agriculture | ||
| 653 | |a Digital agriculture | ||
| 653 | |a Industry 4.0 | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Automation | ||
| 653 | |a Resource management | ||
| 653 | |a Internet of Things | ||
| 653 | |a Access to information | ||
| 653 | |a Technology adoption | ||
| 653 | |a Business competition | ||
| 653 | |a Sensors | ||
| 653 | |a Impact analysis | ||
| 653 | |a Statistical methods | ||
| 653 | |a Electronic commerce | ||
| 653 | |a Industrial applications | ||
| 653 | |a Meta-analysis | ||
| 653 | |a Environmental factors | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Tumiwa, Johan | |
| 700 | 1 | |a Fitty Arie | |
| 700 | 1 | |a Erdey László | |
| 700 | 1 | |a Anas Ratib Alsoud | |
| 700 | 1 | |a Al-Dalahmeh, Main | |
| 773 | 0 | |t PLoS One |g vol. 20, no. 2 (Feb 2025), p. e0310105 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3163165227/abstract/embedded/BH75TPHOCCPB476R?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3163165227/fulltext/embedded/BH75TPHOCCPB476R?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3163165227/fulltextPDF/embedded/BH75TPHOCCPB476R?source=fedsrch |