The effect of the COVID-19 pandemic on Malaysian residential customers’ energy-saving appliance purchasing behaviour
Bibliographic record
Abstract
Purpose The COVID-19 pandemic has caused a dramatic impact on energy supply and demand. It is vital to understand households’ behaviour with regard to energy, particularly during the pandemic, to deploy future sustainable energy systems. This study aims to investigate the nexus of Malaysian households’ energy consumption behaviour in relation to various electrical appliances, their energy-saving appliance purchasing behaviour and their current possession of energy-saving appliances during the pandemic, especially during the lockdown period, from the perspective of the energy cultures framework. Design/methodology/approach The partial least squares structural equation modelling technique was used to test hypothesised relationships based on the 1,485 pieces of household data collected using an online and physical survey during the lockdown period in Malaysia. Findings The energy-saving behaviour cultivated due to the impact of the COVID-19 pandemic led to residential customers’ intentions to purchase energy-saving appliances which subsequently led to their current possession of energy-saving appliances. Indeed, energy-saving behaviours in the kitchen, entertainment, office, home lighting and cooling appliances have more than 77.4% influence on their purchasing behaviour. The consumer’s purchase behaviour for energy-saving appliances has a significant, partially mediating influence on the energy-saving behaviour of various electrical appliances and the consumers’ current possession of energy-saving appliances. Research limitations/implications This study could be enhanced by improving the sample using a higher-income group and involving other parts of Malaysia such as the southern region. The findings do extend the energy cultures framework by demonstrating the mediating role of households’ energy-saving appliance purchasing behaviour on the relationship between their energy consumption behaviour in relation to various electrical appliances and their current possession of energy-saving appliances. Practical implications The results of this study will help develop future action plans for transitioning to energy-saving appliance practices. Originality/value This paper examines the effects of the COVID-19 pandemic on future energy efficiency practices in developing countries from the perspective of the energy cultures framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".