The acceptance of nuclear energy as an alternative source of energy among Generation Z in the Philippines: An extended theory of planned behavior approach

Belmonte, Zachariah John A.; Prasetyo, Yogi Tri; Benito, Omar Paolo; Liao, Jui-Hao; Susanto, Krisna Chandra; Young, Michael Nayat; Persada, Satria Fadil; Nadlifatin, Reny

doi:10.1016/j.net.2023.04.047

Cited by 9 publications

(3 citation statements)

References 87 publications

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“…Generation Z comprises individuals born from 1996 to 2010, whose current ages span from 13 to 27 years old as of 2023 [1]. This emerging generation was poised to inherit a robust economy characterized by historically low levels of unemployment.…”

Section: Introductionmentioning

confidence: 99%

“…As many employees of various ages enter the workforce, the old generations (millennials, Generation X, and boomers) are anticipated to be replaced by the younger generation. It has been reported that Generation Z makes up 40% of the population in the Philippines [1]. It will soon reach the highest percentage of the workforce, replacing retired individuals.…”

Section: Introductionmentioning

confidence: 99%

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Exploring Employee Retention among Generation Z Engineers in the Philippines Using Machine Learning Techniques

Bautista,

Cahigas

2024

Sustainability

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Generation Z represents a significant portion of the current workforce and is poised to become dominant in the engineering field. As the new generation arises, employee retention becomes a crucial topic in the Philippines. Hence, this study explored the factors influencing employee retention among Generation Z engineers in the Philippines using machine learning feature selection (filter method’s permutation, wrapper method’s backward elimination, and embedded method’s Least Absolute Shrinkage and Selection Operator) and classifiers (support vector and random forest). A total of 412 participants were gathered through a purposive sampling technique. The results showed that six out of seven investigated features were found to be significant factors impacting Generation Z engineers’ intention to remain in a company. These six features were supervisor support, company attachment, job satisfaction, contribution, emotional support, and shared value, organized in descending order of feature importance. These were further explained by fifteen significant subfeatures representing each feature. Only one feature, servant leadership, was deemed insignificant. These findings were extracted from the optimal combination of machine learning algorithms. Particularly, feature selection’s backward elimination brought 85.66% accuracy, and the random forest classifier further enhanced the accuracy value to 90.10%. In addition, the model’s precision, recall, and F1-score values were 89.50%, 90.10%, and 88.90%, respectively. This research also provided practical insights for the company executives, organizational leaders, and human resources department seeking to enhance employee retention strategies. These implications were based on the significant features influencing Generation Z engineers’ retention, ultimately contributing to the long-term success and competitiveness of organizations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring Employee Retention among Generation Z Engineers in the Philippines Using Machine Learning Techniques

Bautista,

Cahigas

2024

Sustainability

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“…Recently, with the lack of renewable energy sources, nuclear energy has become one of the world's vital sources of electrical power. [1][2][3][4] The waste from these nuclear processes contains a high level of liquid, which contains many radioactive ions. 5,6 The eld of nuclear research, in addition to nuclear power plants, non-peaceful uses of nuclear energy as lethal weapons, and nuclear accidents, besides mining, is the most dangerous source of radioactive elements.…”

Section: Introductionmentioning

confidence: 99%

Recent progress in high-performance environmental impacts of the removal of radionuclides from wastewater based on metal–organic frameworks: a review

Sheta,

Hamouda,

Ali

et al. 2023

RSC Adv.

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Factors influencing the intention to use e-wallet among generation Z and millennials in the Philippines: An extended technology acceptance model (TAM) approach

Belmonte,

Prasetyo,

Cahigas

et al. 2024

Acta Psychologica

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The acceptance of nuclear energy as an alternative source of energy among Generation Z in the Philippines: An extended theory of planned behavior approach

Cited by 9 publications

References 87 publications

Exploring Employee Retention among Generation Z Engineers in the Philippines Using Machine Learning Techniques

Exploring Employee Retention among Generation Z Engineers in the Philippines Using Machine Learning Techniques

Recent progress in high-performance environmental impacts of the removal of radionuclides from wastewater based on metal–organic frameworks: a review

Factors influencing the intention to use e-wallet among generation Z and millennials in the Philippines: An extended technology acceptance model (TAM) approach

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