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

被引:21
|
作者
Hayat, Naeem [1 ]
Al Mamun, Abdullah [2 ]
Nasir, Noorul Azwin Md [1 ]
Selvachandran, Ganeshsree [2 ]
Nawi, Noorshella Binti Che [2 ]
Gai, Quek Shio [2 ]
机构
[1] Univ Malaysia Kelantan, Fac Entrepreneurship & Business, Kota Baharu 16100, Kelantan, Malaysia
[2] UCSI Univ, Fac Business & Management, Kuala Lumpur 56000, Malaysia
关键词
conservative agriculture practices; environmental performance; yield performance; financial performance; sustainable farm performance; INFORMATION-TECHNOLOGY; CONSERVATION TECHNOLOGIES; ADOPTION BEHAVIOR; PLANNED BEHAVIOR; UNIFIED THEORY; AGRICULTURE; ACCEPTANCE; MANAGEMENT; DETERMINANTS; INTENTION;
D O I
10.3390/land9090289
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:37
相关论文
共 50 条
  • [31] Technological environment and sustainable performance of oil and gas firms: a structural equation modelling approach
    Akhimien, Okharedia Goodheart
    Adekunle, Simon Ayo
    [J]. FUTURE BUSINESS JOURNAL, 2023, 9 (01)
  • [32] Predicting mobile government service continuance: A two-stage structural equation modeling-artificial neural network approach
    Xiong, Li
    Wang, Houcai
    Wang, Chengwen
    [J]. GOVERNMENT INFORMATION QUARTERLY, 2022, 39 (01)
  • [33] Identifying the factors affecting strategic decision-making ability to boost the entrepreneurial performance: A hybrid structural equation modeling - artificial neural network approach
    Feng, Jiaying
    Han, Ping
    Zheng, Wei
    Kamran, Asif
    [J]. FRONTIERS IN PSYCHOLOGY, 2022, 13
  • [34] Predicting CHF using artificial neural network
    Xiao, G
    Su, GH
    Liu, RL
    Jia, DN
    [J]. MULTIPHASE FLOW AND HEAT TRANSFER, 1999, : 125 - 129
  • [35] Cryptocurrency Adoption among Saudi Arabian Public University Students: Dual Structural Equation Modelling and Artificial Neural Network Approach
    Alomari, Ali S. A.
    Abdullah, Nasuha L.
    [J]. HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES, 2023, 2023
  • [36] The Underlying Drivers of Underprivileged Households' Intention and Behavior towards Community Forestry Management: A Study Using Structural Equation Modelling and Artificial Neural Network Approach
    Al Mamun, Abdullah
    Fazal, Syed Ali
    Masud, Muhammad Mehedi
    Selvachandran, Ganeshsree
    Zainol, Noor Raihani
    Gai, Quek Shio
    [J]. SUSTAINABILITY, 2020, 12 (18)
  • [37] A novel approach to predicting human ingress motion using an artificial neural network
    Kim, Younguk
    Choi, Eun Soo
    Seo, Jungmi
    Choi, Woo-sung
    Lee, Jeonghwan
    Lee, Kunwoo
    [J]. JOURNAL OF BIOMECHANICS, 2019, 84 : 27 - 35
  • [38] Clearness index predicting using an integrated artificial neural network (ANN) approach
    Kheradmand, Saeid
    Nematollahi, Omid
    Ayoobi, Ahmad Reza
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 58 : 1357 - 1365
  • [39] Using artificial neural network approach for modelling rainfall–runoff due to typhoon
    S M CHEN
    Y M WANG
    I TSOU
    [J]. Journal of Earth System Science, 2013, 122 : 399 - 405
  • [40] Predicting freshwater production in seawater greenhouses using hybrid artificial neural network models
    Panahi, Fatemeh
    Ahmed, Ali Najah
    Singh, Vijay P.
    Ehtearm, Mohammad
    Elshafie, Ahmed
    Haghighi, Ali Torabi
    [J]. JOURNAL OF CLEANER PRODUCTION, 2021, 329