Analysis of Food Security Factors in Indonesia using SEM-GSCA with the Alternating Least Squares Method

Wardhani Utami Dewi, Khoirin Nisa, Mustofa Usman

Abstract


An economic recession, characterized by prolonged economic decline, increased unemployment, and decreased spending, is projected to occur globally in 2023, potentially impacting production capacity within the food sector. Experts have identified various contributing factors such as shifts in global trade dynamics and geopolitical tensions, highlighting the need to understand the broader global economic context leading to this recession. To achieve this goal, in this research SEM is used to analyze the relationship between variables that influence food security. Furthermore, GSCA is used to handle complex structural models and non-normal data distribution. Special considerations include the use of ALS methods to estimate parameters effectively and consistently. The findings of this research are the important role of availability, access and utilization in shaping food security in Indonesia, with a contribution of 98% of the overall influence shown by the model. These insights help governments design targeted interventions to improve food security, especially amidst challenges posed by a potential global economic downturn. Implementing strategies to increase availability, increase access and optimize utilization is very important in maintaining food security amidst economic uncertainty.

Keywords


Structural Equation Modeling; Generalized Structured Component Analysis; Alternating Least Squares.

Full Text:

DOWNLOAD [PDF]

References


Ahmed, Z., & Ambinakudige, S. (2023). Does land use change, waterlogging, and salinity impact on sustainability of agriculture and food security? Evidence from southwestern coastal region of Bangladesh. Environmental Monitoring and Assessment, 195(1), 74. https://doi.org/https://doi.org/10.1007/s10661-022-10673-w

Airola, A., & Pahikkala, T. (2018). Fast kronecker product kernel methods via generalized vec trick. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3374–3387. https://doi.org/10.1109/TNNLS.2017.2727545

Badan Pusat Statistika. (2022). Konsumsi Kalori dan Protein Penduduk Indonesia dan Provinsi. Badan Pusat Statistika Indonesia. https://webapi.bps.go.id/

Cho, G., & Choi, J. Y. (2020). An empirical comparison of generalized structured component analysis and partial least squares path modeling under variance-based structural equation models. Behaviormetrika, 47(1), 243–272. https://doi.org/10.1007/s41237-019-00098-0

Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2020). Cutoff criteria for overall model fit indexes in generalized structured component analysis. Journal of Marketing Analytics, 8(4), 189–202. https://doi.org/https://doi.org/10.1057/s41270-020-00089-1

Cho, G., Kim, S., Lee, J., Hwang, H., Sarstedt, M., & Ringle, C. M. (2022). A comparative study of the predictive power of component-based approaches to structural equation modeling. European Journal of Marketing. https://doi.org/10.1108/EJM-07-2020-0542

De Leeuw, J., Young, F. W., & Takane, Y. (1976). Additive structure in qualitative data: An alternating least squares method with optimal scaling features. Psychometrika, 41(4), 471–503. https://doi.org/10.1007/BF02296971

Denny, R. C. H., Marquart-Pyatt, S. T., Ligmann-Zielinska, A., Olabisi, L. S., Rivers, L., Du, J., & Liverpool-Tasie, L. S. O. (2018). Food security in Africa: a cross-scale, empirical investigation using structural equation modeling. Environment Systems and Decisions, 38(1), 6–22. https://doi.org/10.1007/s10669-017-9652-7

Fahad, S., Nguyen-Thi-Lan, H., Nguyen-Manh, D., Tran-Duc, H., & To-The, N. (2023). Analyzing the status of multidimensional poverty of rural households by using sustainable livelihood framework: policy implications for economic growth. Environmental Science and Pollution Research, 30(6), 16106–16119. https://doi.org/https://doi.org/10.1007/s11356-022-23143-0

Fakfare, P., Promsivapallop, P., & Manosuthi, N. (2023). Applying integrated generalized structured component analysis to explore tourists’ benefit consideration and choice confidence toward travel appscape. Technological Forecasting and Social Change, 188, 122321. https://doi.org/https://doi.org/10.1016/j.techfore.2023.122321

Galeana-Pizaña, J. M., Couturier, S., Figueroa, D., & Jiménez, A. D. (2021). Is rural food security primarily associated with smallholder agriculture or with commercial agriculture?: An approach to the case of Mexico using structural equation modeling. Agricultural Systems, 190, 103091. https://doi.org/https://doi.org/10.1016/j.agsy.2021.103091

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Canonical correlation: A supplement to multivariate data analysis. Multivariate Data Analysis: A Global Perspective, 7th Ed.; Pearson Prentice Hall Publishing: Upper Saddle River, NJ, USA. https://www.drnishikantjha.com/papersCollection/Multivariate Data Analysis.pdf

Hair Jr, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Black, W. C., & Anderson, R. E. (2018). Multivariate Data Analysis. https://doi.org/10.1002/9781119409137.ch4

Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069

Huang, W., Roscoe, R. D., Craig, S. D., & Johnson-Glenberg, M. C. (2022). Extending the Cognitive-Affective Theory of Learning with Media in Virtual Reality Learning: A Structural Equation Modeling Approach. Journal of Educational Computing Research, 60(4), 807–842. https://doi.org/10.1177/07356331211053630

Hwang, H., Sarstedt, M., Cheah, J. H., & Ringle, C. M. (2020). A concept analysis of methodological research on composite-based structural equation modeling: bridging PLSPM and GSCA. Behaviormetrika, 47, 219–241. https://doi.org/https://doi.org/10.1007/s41237-019-00085-5

Hwang, H., & Takane, Y. (2014). Generalized structured component analysis: A component-based approach to structural equation modeling. In Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling. https://doi.org/10.1201/b17872

Hwang, H., Takane, Y., & Jung, K. (2017). Generalized structured component analysis with uniqueness terms for accommodating measurement error. Frontiers in Psychology, 8(DEC). https://doi.org/10.3389/fpsyg.2017.02137

Jendryczko, D., & Nussbeck, F. W. (2022). Estimating and investigating multiple constructs multiple indicators social relations models with and without roles within the traditional structural equation modeling framework: A tutorial. Psychological Methods. https://doi.org/https://doi.org/10.1037/met0000534

Jung, K., Lee, J., Gupta, V., & Cho, G. (2019). Comparison of Bootstrap Confidence Interval Methods for GSCA Using a Monte Carlo Simulation. Frontiers in Psychology, 10, 24–25. https://doi.org/10.3389/fpsyg.2019.02215

Kementerian Pertanian. (2022). Statistik Ketahanan Pangan Tahun 2022. https://satudata.pertanian.go.id/assets/docs/publikasi/Statistik_Ketahanan_Pangan_2022.pdf

Lv, F., Deng, L., Zhang, Z., Wang, Z., Wu, Q., & Qiao, J. (2022). Multiscale analysis of factors affecting food security in China, 1980–2017. Environmental Science and Pollution Research, 29(5), 6511–6525. https://doi.org/10.1007/s11356-021-16125-1

Mai, Y., Zhang, Z., & Wen, Z. (2018). Comparing Exploratory Structural Equation Modeling and Existing Approaches for Multiple Regression with Latent Variables. Structural Equation Modeling, 25(5), 737–749. https://doi.org/10.1080/10705511.2018.1444993

Makkulau, Susanti Linuwih, Purhadi Purhadi, & Muhammad Mashuri. (2010). Pendeteksian Outlier dan Penentuan Faktor-Faktor yang Mempengaruhi Produksi Gula dan Tetes Tebu dengan Metode Likelihood Displacement Statistic-Lagrange. Jurnal Teknik Industri, 12(2), 95–100. http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/18065

Manosuthi, N., Lee, J.-S., & Han, H. (2021). An innovative application of composite-based structural equation modeling in hospitality research with empirical example. Cornell Hospitality Quarterly, 62(1), 139–156. https://doi.org/https://doi.org/10.1177/1938965520951751

Pervaiz, B., Li, N., & Manzoor, M. Q. (2019). Agricultural land use and food security in pakistan: A structural equation modeling approach. Journal of Animal and Plant Sciences, 29(5), 1402–1412. https://thejaps.org.pk/docs/v-29-05/22.pdf

Riptanti, E. W., Masyhuri, I., & Suryantini, A. (2022). The sustainability model of dryland farming in food-insecure regions: structural equation modeling (SEM) approach. International Journal of Sustainable Development and Planning, 17(7), 2033–2043. https://doi.org/https://doi.org/10.18280/ijsdp.170704

Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology and Marketing, 39(5), 1035–1064. https://doi.org/10.1002/mar.21640

Setiawan, E., Pratiwi, A., Herawati, N., Nisa, K., & Faisol, A. (2021). A Structural Equation Modeling of Factors Affecting Student Motivation in Thesis Preparation. Journal of Physics: Conference Series, 1751(1), 012030. https://doi.org/10.1088/1742-6596/1751/1/012030

Shi, D., Maydeu-Olivares, A., & Rosseel, Y. (2020). Assessing fit in ordinal factor analysis models: SRMR vs. RMSEA. Structural Equation Modeling: A Multidisciplinary Journal, 27(1), 1–15. https://doi.org/https://doi.org/10.1080/10705511.2019.1611434

Shrestha, N. (2021). Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4–11. https://doi.org/10.12691/ajams-9-1-2

Usman, M., Ali, A., Bashir, M. K., Mushtaq, K., Ghafoor, A., Amjad, F., Hashim, M., & Baig, S. A. (2023). Pathway analysis of food security by employing climate change, water, and agriculture nexus in Pakistan: partial least square structural equation modeling. Environmental Science and Pollution Research, 30(38), 88577–88597. https://doi.org/10.1007/s11356-023-28547-0




DOI: https://doi.org/10.31764/jtam.v8i2.20378

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Wardhani Utami Dewi, Khoirin Nisa, Mustofa Usman

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

_______________________________________________

JTAM already indexing:

                     


_______________________________________________

 

Creative Commons License

JTAM (Jurnal Teori dan Aplikasi Matematika) 
is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

______________________________________________

_______________________________________________

_______________________________________________ 

JTAM (Jurnal Teori dan Aplikasi Matematika) Editorial Office: