scholarly journals The Underlying Drivers of Underprivileged Households’ Intention and Behavior towards Community Forestry Management: A Study Using Structural Equation Modelling and Artificial Neural Network Approach

2020 ◽  
Vol 12 (18) ◽  
pp. 7330
Author(s):  
Abdullah Al Mamun ◽  
Syed Ali Fazal ◽  
Muhammad Mehedi Masud ◽  
Ganeshsree Selvachandran ◽  
Noor Raihani Zainol ◽  
...  

In acknowledging the significant role of forestry on the environmental, social, and economic sustainability of local communities, this study focused on examining how different factors affect the intentional behavior towards community forestry among the poor households in Malaysia. Employing theory of planned behavior (TPB) in an expanded model, this study collected data from 420 underprivileged households from 10 states in Malaysia using a survey questionnaire. Final analysis is performed using two methods, one being the well-established, conventional way of partial least square–structural equation modelling (PLS-SEM); the other being a frontier technology of computing using artificial neural network (ANN), which is generated through a deep learning algorithm to achieve the maximum possible accuracy for each of the five scenarios aforementioned. The study found that perceived benefits (PB) and eco-literacy (EL) have a significant positive effect on the attitude towards environment (ATE) while normative belief (NB) and motivation (MO) have a significant positive effect on subjective norms (SUN). Perceived control (PC) has a significant positive effect on perceived behavioral control (PBC). ATE, SUN, and PBC have a significant positive effect on the intention towards community forestry (ITCF), whereas the ITCF has a significant positive effect on community forestry adoption behavior (CFAB). When formulating and enforcing carbon reduction and poverty elevating programs through community forestry, the Malaysian government should consider the perceptions of poor families and the prerogative from their special reference groups to enhance the perceived ability of the vulnerable groups for positive and effective pro-environmental behavior that can lead to sustainable forestry management.

Author(s):  
A. S. Albahri ◽  
Alhamzah Alnoor ◽  
A. A. Zaidan ◽  
O. S. Albahri ◽  
Hamsa Hameed ◽  
...  

AbstractTopical treatments with structural equation modelling (SEM) and an artificial neural network (ANN), including a wide range of concepts, benefits, challenges and anxieties, have emerged in various fields and are becoming increasingly important. Although SEM can determine relationships amongst unobserved constructs (i.e. independent, mediator, moderator, control and dependent variables), it is insufficient for providing non-compensatory relationships amongst constructs. In contrast with previous studies, a newly proposed methodology that involves a dual-stage analysis of SEM and ANN was performed to provide linear and non-compensatory relationships amongst constructs. Consequently, numerous distinct types of studies in diverse sectors have conducted hybrid SEM–ANN analysis. Accordingly, the current work supplements the academic literature with a systematic review that includes all major SEM–ANN techniques used in 11 industries published in the past 6 years. This study presents a state-of-the-art SEM–ANN classification taxonomy based on industries and compares the effort in various domains to that classification. To achieve this objective, we examined the Web of Science, ScienceDirect, Scopus and IEEE Xplore® databases to retrieve 239 articles from 2016 to 2021. The obtained articles were filtered on the basis of inclusion criteria, and 60 studies were selected and classified under 11 categories. This multi-field systematic study uncovered new research possibilities, motivations, challenges, limitations and recommendations that must be addressed for the synergistic integration of multidisciplinary studies. It contributed two points of potential future work resulting from the developed taxonomy. First, the importance of the determinants of play, musical and art therapy adoption amongst autistic children within the healthcare sector is the most important consideration for future investigations. In this context, the second potential future work can use SEM–ANN to determine the barriers to adopting sensing-enhanced therapy amongst autistic children to satisfy the recommendations provided by the healthcare sector. The analysis indicates that the manufacturing and technology sectors have conducted the most number of investigations, whereas the construction and small- and medium-sized enterprise sectors have conducted the least. This study will provide a helpful reference to academics and practitioners by providing guidance and insightful knowledge for future studies.


2021 ◽  
Author(s):  
Pragati Priyadarshinee

Abstract The article introduces a two-stage Structural equation modelling- Artificial Neural Network (SEM-ANN) model for the Smart city creation through Fog Computing (FC) and Internet of Things (IOT) by identifying the critical success factors in Indian context. The research article introduces a new factor Fog Computing (FC). Internet of Things (IoT) is again sub-divided into three more factors as Internet of People (IoP), Internet of Services (IoS) and Internet of Energy (IoE) as the independent variables. 13 Smart cities and 379 respondents are involved for this study. The data analysis is done through Structural equation modelling (SEM) and artificial neural network (ANN) which measures both the linear and non-linear relationships respectively. From Structural Equation Modeling (SEM) output, it is identified that Internet of Things (IOT), Internet of People (IOP) and Internet of Services (IOS) have some significant positive effect on Fog Computing (FC). Internet of Energy (IOE) has the negative effect on Fog Computing (FC) which is the only exception in the study for future research direction in this area. The SEM accepted variables are considered as the input for the next layer of ANN analysis that identified IOT has the major effect on Fog Computing (FC). A comparison is also done on SEM and neural network results. The outcome of the study will help more number of Smart City (SC) creations and will fulfil the target of 100 Smart city creation by Government of India taking forward towards a sustainable development.


2019 ◽  
Vol 8 (1) ◽  
pp. 35-45
Author(s):  
Esta Dewi Anggita ◽  
Abdul Hoyyi ◽  
Agus Rusgiyono

Poverty is a complex and multidimensional problem that links several dimensions. Statistical method that can explain the relationship between one latent variable with others is Structural Equation Modelling (SEM). The purpose of this study is to create a structural model of the relationship between education, health, economy and poverty in Indonesia in 2017 by using Structural Equation Modeling with Partial Least Square approach (SEM-PLS) based on predetermined indicators with the results of 11 valid indicators. Based on the model obtained, health has a significant positive effect on education, health and education have a significant positive effect on the economy and the economy has a significant negative effect on poverty. Segmentation based on the relationship of latent variables in structural models can be overcome by Finite Mixture Partial Least Square (FIMIX-PLS) so that it can identify poverty areas in each province in Indonesia with more homogeneous characteristics. The best segmentation result is number of segments (K) = 2 obtained based on the criteria of AIC, BIC, CAIC and Normed Entropy (EN) with an EN value of 0.964 which means the quality of segment separation is very good. Papua and West Papua provinces form one segment in segment 2, while 32 other provinces form one segment in segment 1.Keywords: Poverty, Structural Equation Modelling, Partial Least Square, Finite Mixture, Segmentation.


2020 ◽  
Vol 2 (2) ◽  
pp. 361
Author(s):  
Selvia Selvia ◽  
Rodhiah Rodhiah

This studies examines the effect of personality traits on brand loyalty through congruity and customer satisfaction as a mediating variables on the brand of Fore Coffee. This research design used quantitative methods with a descriptive approach. The sampling technique used purposive sampling, with 94 respondents which all of customers from Fore Coffee. Data were collected using questionnaire. The analysis used structural equation modelling (SEM) and SmartPLS 3 as a tool for analyzing data. The results of this study indicate that personality traits have a significant positive effect on consumer congruity on the Fore Coffee’s brand, personality traits have a significant positive effect on customer satisfaction on the Fore Coffee’s brand, personality traits directly have a significant positive effect on consumer brand loyalty on the Fore Coffee’s brand, congruity have a significant positive effect on consumer satisfaction on the Fore Coffee’s brand, congruity have a significant positive effect on consumer brand loyalty in the Fore Coffee’s brand, customer satisfaction does not have a significant effect on consumer brand loyalty on the Fore Coffee’s brand, congruity mediates the influences of personality traits on consumer brand loyalty on the Fore Coffee’s brand, and customer satisfaction does not mediate the influence of personality traits on consumer brand loyalty on the Fore Coffee’s brand. Penelitian ini meneliti pengaruh personality traits terhadap brand loyalty melalui congruity dan customer satisfaction sebagai variabel mediasi pada brand Fore Coffee. Desain penelitian ini menggunakan metode kuantitatif dengan pendekatan deskriptif. Teknik pengambilan sampel menggunakan purposive sampling, dengan responden sebanyak 94 yaitu seluruh konsumen dari Fore Coffee. Teknik pengambilan data dengan menggunakan kuesioner. Analisis yang digunakan adalah structural equation modelling (SEM) dan SmartPLS 3 sebagai alat untuk menganalisis data. Hasil penelitian ini menunjukkan bahwa personality traits berpengaruh positif signifikan terhadap congruity konsumen pada brand Fore Coffee, personality traits berpengaruh positif signifikan terhadap customer satisfaction konsumen pada brand Fore Coffee, personality traits secara langsung berpengaruh positif signifikan terhadap brand loyalty konsumen pada brand Fore Coffee, congruity berpengaruh positif signifikan terhadap customer satisfaction konsumen pada brand Fore Coffee, congruity berpengaruh positif signifikan terhadap brand loyalty konsumen pada brand Fore Coffee, customer satisfaction tidak berpengaruh signifikan terhadap terhadap brand loyalty konsumen pada brand Fore Coffee, congruity memediasi pengaruh personality traits terhadap brand loyalty konsumen pada brand Fore Coffee, dan customer satisfaction tidak memediasi pengaruh personality traits terhadap brand loyalty konsumen pada brand Fore Coffee.


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247582
Author(s):  
Ghazanfar Ali Abbasi ◽  
Lee Yin Tiew ◽  
Jinquan Tang ◽  
Yen-Nee Goh ◽  
Ramayah Thurasamy

In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model were extended with the inclusion of trust and personnel innovativeness. The model was further validated by introducing a new path model compared to the original UTAUT2 model and the moderating role of personal innovativeness between performance expectancy and price value, with a sample of 314 respondents. Contrary to previous technology adoption studies that used PLS-SEM & ANN as single-stage analysis, this study further enhanced the analysis by applying a deep learning-based dual-stage PLS-SEM and ANN method. The application of deep learning-based dual-stage PLS-SEM & ANN analysis is a novel methodological approach, detecting both linear and non-linear associations among constructs. At the same time, it is regarded as a superior statistical approach as compared to traditional hybrid shallow SEM & ANN single-stage analysis. Also, sensitivity analysis provides normalised importance using multi-layer perceptron with the feed-forward-back-propagation algorithm. Furthermore, the deep learning-based dual-stage PLS-SEM & ANN revealed that trust proved to be the strongest predictor in driving user intention. The introduction of this new methodology and the theoretical contribution opens the vistas of the extant body of knowledge in technology-adoption related literature. This study also provides theoretical, practical and methodological contributions.


2020 ◽  
Vol 49 (7) ◽  
pp. 1435-1449
Author(s):  
Genuine Narzary ◽  
Sasmita Palo

PurposeThe present study aims at investigating mediating–moderating effect of job satisfaction between structural empowerment and organisational citizenship behaviour.Design/methodology/approachThe study was conducted using standardised questionnaires. Responses were gathered from 178 auxiliary nurse and midwives working in primary health care centres in Chirang and Kokrajhar districts of Assam. Census method of data collection was adopted. The mediating–moderating effect of job satisfaction was assessed using the structural equation modelling.FindingsStructural equation modelling result shows that structural empowerment has significant and positive effect on job satisfaction (0.68) and organisational citizenship behaviour (0.37). Job satisfaction has significant and positive effect on organisational citizenship behaviour (0.39). Job satisfaction significantly mediates-moderates (0.23) between structural empowerment and organisational citizenship behaviour.Research limitations/implicationsGiven the only female auxiliary nurse and midwives and comparatively small sample obtained in this study, no attempt should be made to generalise these findings to other nurses or organisations. All data were obtained through a self-report survey, presenting a possibility for common method bias.Practical implicationsPromoting structural empowerment may help medical officer (supervisor) to increase auxiliary nurse and midwives’ level of job satisfaction and promote organisational citizenship behaviour.Originality/valueThis is the first study conducted on the mediating–moderating effect of job satisfaction on the relationship between structural empowerment and organisational citizenship behaviour among auxiliary nurse and midwives workings in rural and semi-urban areas in Assam (India).


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