Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach

The adoption of innovative technology has always been a complex issue. The agriculture sectors of developing countries are following unsustainable farming policies. The currently adopted intensive farming practices need to replace with conservative agriculture practices (CAPs). However, the adoption...

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Main Authors: Naeem Hayat, Abdullah Al Mamun, Noorul Azwin Md Nasir, Ganeshsree Selvachandran, Noorshella Binti Che Nawi, Quek Shio Gai
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/9/9/289
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spelling doaj-7bbad1b5f8af4097a3dcb51a307ce36c2020-11-25T02:58:47ZengMDPI AGLand2073-445X2020-08-01928928910.3390/land9090289Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network ApproachNaeem Hayat0Abdullah Al Mamun1Noorul Azwin Md Nasir2Ganeshsree Selvachandran3Noorshella Binti Che Nawi4Quek Shio Gai5Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Pengkalan Chepa, Kota Bharu 16100, MalaysiaFaculty of Business and Management, UCSI University, Cheras, Kuala Lumpur 56000, MalaysiaFaculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Pengkalan Chepa, Kota Bharu 16100, MalaysiaFaculty of Business and Management, UCSI University, Cheras, Kuala Lumpur 56000, MalaysiaFaculty of Business and Management, UCSI University, Cheras, Kuala Lumpur 56000, MalaysiaFaculty of Business and Management, UCSI University, Cheras, Kuala Lumpur 56000, MalaysiaThe adoption of innovative technology has always been a complex issue. The agriculture sectors of developing countries are following unsustainable farming policies. The currently adopted intensive farming practices need to replace with conservative agriculture practices (CAPs). However, the adoption of CAPs has remained low since its emergence and reports have suggested that the use of CAPs is scant for sustainable farm performance. This article aims to study three scenarios: Firstly, the influence of personal and CAPs level factors on the intention to adopt CAPs; secondly, the influence intention to adopt CAPs, facilitating conditions and voluntariness of use on the actual use of CAPs; and thirdly, the impact of the actual use of CAPs on sustainable farm performance. This study is based on survey data collected by structured interviews of rice farmers in rural Pakistan, which consists of 336 samples. The final analysis is performed using two methods: (1) a well-established and conventional way of Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart PLS 3.0, and (2) a frontier technology of computing using an artificial neural network (ANN), which is generated through a deep learning algorithm to achieve maximum possible accuracy. The results reveal that profit orientation and environment attitude as behavioural inclination significantly predicts the intention to adopt CAPs. The perception of effort expectancy can significantly predict the intention to adopt CAPs. Low intention to adopt CAPs caused by the low-level trust on extension, low-performance expectancy, and low social influence for the CAPs. The adoption of CAPs is affected by facilitating conditions, voluntary use of CAPs, and the intention to adopt CAPs. Lastly, the use of CAPs can positively and significantly forecast the perception of sustainable farm performance. Thus, it is concluded that right policies are required to enhance the farmers’ trust on extension and promote social and performance expectation for CAPs. Besides, policy recommendations can be made for sustainable agriculture development in developing and developed countries.https://www.mdpi.com/2073-445X/9/9/289conservative agriculture practicesenvironmental performanceyield performancefinancial performancesustainable farm performance
collection DOAJ
language English
format Article
sources DOAJ
author Naeem Hayat
Abdullah Al Mamun
Noorul Azwin Md Nasir
Ganeshsree Selvachandran
Noorshella Binti Che Nawi
Quek Shio Gai
spellingShingle Naeem Hayat
Abdullah Al Mamun
Noorul Azwin Md Nasir
Ganeshsree Selvachandran
Noorshella Binti Che Nawi
Quek Shio Gai
Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
Land
conservative agriculture practices
environmental performance
yield performance
financial performance
sustainable farm performance
author_facet Naeem Hayat
Abdullah Al Mamun
Noorul Azwin Md Nasir
Ganeshsree Selvachandran
Noorshella Binti Che Nawi
Quek Shio Gai
author_sort Naeem Hayat
title Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
title_short Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
title_full Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
title_fullStr Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
title_full_unstemmed Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach
title_sort predicting sustainable farm performance—using hybrid structural equation modelling with an artificial neural network approach
publisher MDPI AG
series Land
issn 2073-445X
publishDate 2020-08-01
description The adoption of innovative technology has always been a complex issue. The agriculture sectors of developing countries are following unsustainable farming policies. The currently adopted intensive farming practices need to replace with conservative agriculture practices (CAPs). However, the adoption of CAPs has remained low since its emergence and reports have suggested that the use of CAPs is scant for sustainable farm performance. This article aims to study three scenarios: Firstly, the influence of personal and CAPs level factors on the intention to adopt CAPs; secondly, the influence intention to adopt CAPs, facilitating conditions and voluntariness of use on the actual use of CAPs; and thirdly, the impact of the actual use of CAPs on sustainable farm performance. This study is based on survey data collected by structured interviews of rice farmers in rural Pakistan, which consists of 336 samples. The final analysis is performed using two methods: (1) a well-established and conventional way of Partial Least Squares Structural Equation Modeling (PLS-SEM) using Smart PLS 3.0, and (2) a frontier technology of computing using an artificial neural network (ANN), which is generated through a deep learning algorithm to achieve maximum possible accuracy. The results reveal that profit orientation and environment attitude as behavioural inclination significantly predicts the intention to adopt CAPs. The perception of effort expectancy can significantly predict the intention to adopt CAPs. Low intention to adopt CAPs caused by the low-level trust on extension, low-performance expectancy, and low social influence for the CAPs. The adoption of CAPs is affected by facilitating conditions, voluntary use of CAPs, and the intention to adopt CAPs. Lastly, the use of CAPs can positively and significantly forecast the perception of sustainable farm performance. Thus, it is concluded that right policies are required to enhance the farmers’ trust on extension and promote social and performance expectation for CAPs. Besides, policy recommendations can be made for sustainable agriculture development in developing and developed countries.
topic conservative agriculture practices
environmental performance
yield performance
financial performance
sustainable farm performance
url https://www.mdpi.com/2073-445X/9/9/289
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