Dzikri Firmansyah Hakam
Nur Afida Nuzula
Atik Aprianingsih- School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia
Cooking significantly contributes to global energy demand and carbon dioxide emissions. In Indonesia, the largest consumer of liquefied petroleum gas (LPG), much of this demand, is met through imports. Transitioning to more sustainable energy sources, such as induction stoves and solar cookers, has become a priority. However, the shift to induction stoves poses challenges due to concerns about electricity availability and the cost of new installations. Engaging Indonesia’s young generation is critical to ensuring the success of this transition. This study explores user behavior and adoption of induction stoves in Indonesia from the perspective of the younger generation. It employs a methodological framework combining elements of the value-based adoption model and the unified theory of acceptance and use of technology, focusing on Performance Expectancy, Perceived Alternative Value, and Conversion Cost in relation to Conversion Intention. Surveys were conducted with 192 individuals aged 12–42 years who currently use LPG as a cooking fuel. Data were analyzed using partial least squares structural equation modeling, incorporating reflective, formative, and structural measurement models. The findings revealed that performance expectancy significantly influences conversion intention, and perceived alternative value has a direct impact on conversion intention and mediates the relationship between performance expectancy and conversion intention, while conversion cost does not have a significant effect. These results highlight a strong inclination among younger individuals toward sustainability and their readiness to adopt new technologies despite potential financial challenges. The insights gained from this study can inform policymakers in designing targeted programs that align with the values and preferences of the younger demographic, facilitating a smoother transition to sustainable cooking energy solutions.
1 Introduction
Cooking represents a substantial energy demand globally, contributing significantly to CO2 emissions (Adria and Bethge, 2013). South and Southeast Asia predominantly rely on liquefied petroleum gas (LPG) for cooking, with Indonesia being the largest consumer, showing a persistent increase in demand, 13.72 million tons in the next 7 years (Asian Development Bank, 2020). However, a significant portion of Indonesia’s LPG consumption is met through imports, posing economic challenges exacerbated by geopolitical conflicts (Reuters Staff, 2021; Wicaksana et al., 2022). Amidst these challenges, Indonesia aims to transition toward greener energy sources to reduce reliance on fossil fuels and meet international commitments (Ministry of Energy and Mineral Resources, 2023). This transition involves exploring alternatives such as solar cookers, dimethyl ether (DME) production from coal gasification, and induction stoves. While solar cookers and DME production show potential, induction stoves emerge as a cost-effective and environmentally favorable option compared to LPG stoves (IRENA, 2017). However, the adoption of induction stoves hinges on user acceptance and aligning policies with environmental and economic goals as Indonesian citizen dominated by low middle-income people.
Indonesia’s commitment to reducing carbon emissions aligns with its objectives outlined in the Sustainable Development Goals (SDGs), Paris Agreement, and Nationally Determined Contributions (NDC). Transitioning toward net-zero emissions, particularly in daily activities such as cooking, is imperative to meet these targets. To facilitate this transition, the government has set forth dual objectives: diminishing the budget allocated for LPG imports and fostering the adoption of greener energy sources (Asian Development Bank, 2020). User intention mainly from the young generation as the target of the policy in 2030, the study of shifting toward induction stoves emerges as a pivotal factor in realizing this agenda, analogous to the significance attributed to the geothermal project, as renewable electricity sources. Notably, the government has earmarked substantial financial resources, 550 million USD for augmenting geothermal capacity (Thinkgeoenergy, 2023).
Existing scholarly investigations have underscored the role of performance expectancy as a determinant influencing users’ choice of cooking fuels. This study endeavors to delve into the impact of performance expectancy on perceived alternative value and conversion intention. Furthermore, performance expectancy is anticipated to exert a significant influence on perceived alternative value and conversion intention concerning induction stoves. This study aims to investigate user perspectives on energy fuel choices for cooking, induction stoves, to inform government strategies in reducing LPG subsidies and promoting sustainable energy use.
User acceptance is crucial for evaluating readiness for new technologies, especially through regional surveys. Studies have investigated user preferences and needs for stove technologies in Rural Mexico and Bangladesh (Pine et al., 2011; Ruiz-Mercado et al., 2013; Troncoso et al., 2019). The acceptance relies on the health problem, fuel efficiency, and durability. In Indonesia, the shift from LPG to induction stoves is being considered for its convenience across all age groups in urban areas (Noverita et al., 2020). However, there is a lack of segmentation in research, especially for youth as future generation. This research aims to pioneer the study of user acceptance and technology adoption of induction stoves in Indonesia, focusing on youth (Millennials and Gen Z) as target demographics for upcoming policies.
This research conducts a thorough investigation of induction stove user acceptance and technology uptake among Indonesian adolescents. Section 2 offers a comprehensive materials and methods, while Section 3 discusses the research methodology that employs the UTAUT and VAM theory frameworks. Section 4 analyzes questionnaire data using SMARTPLS, including reflective, formative, and structural measures. Finally, Section 5 summarizes major findings and provides recommendations.
2 Literature review
2.1 Previous user perspective study of stove worldwide
There are prior studies about the stove adoption in every country. Table 1 presents a comprehensive overview of global research on user acceptance and stove adoption, categorized by geographic region, objective variables, target user demographics, and stove type. Studies were conducted in Asia, America, Africa, and Europe. Asia includes Indonesia, Bangladesh, Jordan, and India. America consists of Mexico, Peru, and Mayan regions. Africa includes Ghana, Ethiopia, and Tanzania, while Europe includes Norway. Regarding stove types, research has examined the transition from traditional cookers to LPG stoves (Billah et al., 2020; Troncoso et al., 2019; Martínez-Gómez et al., 2016; Rosenbaum et al., 2015; Jeuland et al., 2015; Dickinson et al., 2019). The result shows that the attitude depends on many factors, including cost, health problem, convenience, policy, and post-service stove. In addition, in some developing countries, there is research on the transition from LPG to induction stoves, focusing on user perspectives (Noverita et al., 2020; Shuhaiber and Mashal, 2019). Urban convenience, trust, enjoyment, and perceived hazard contribute in adopting new technologies or features.
Table 1. Previous relevant research.
2.2 Cooking fuels and young generation in Indonesia
The growth of households has increased energy demand for transportation and cooking. Traditional fuels include firewood, plants, and animal waste, while modern options include LPG, electricity, biogas, and solar power (Rishanty et al., 2022; Suharsono and Lontoh, 2022). However, clean cooking access has reduced traditional fuel usage from 60% in 2010 to less than 18% in 2021, leaving nearly 50 million Indonesians without access (Pangaribowo and Iskandar, 2023). The Asian Development Bank found that 61.85% of households use a 3 kg LPG canister for cooking, while 72.53% rely on gas. Indonesia’s LPG consumption has increased since 2007 due to the kerosene-to-LPG conversion program, requiring 75% of 2020’s demand to be imported (Asian Development Bank, 2020). The government subsidizes this amount, resulting in 6.4 million tons in 2020. LPG has the highest emissions from building, causing 28 MtCO2-eq (Christian and Suryadi, 2021).
Diversification of cooking energy is needed to reduce import dependency. The government aims to convert 8.3 million families to electric stoves by 2022, but this target has not been achieved. The reduction of LPG is a target, but only 0.76% of households use induction stoves, which are unattractive for both wealthier and poorer societies due to cost, infrastructure, and convenience (BPS, 2020; Hakam et al., 2022). Indonesia still uses over 50% of coal for electricity supply (Anggraini, 2022). Induction stoves in Ecuador have lower CO2 emissions than LPG, and switching to induction stoves can save energy up to $5.17 per month (Martínez-Gómez et al., 2016). Induction stoves also offer better cooking time, energy consumption, CO2 emissions, acceptable food, less vitamin A loss, and high food safety compared to LPG in food processing (Martínez-Gómez et al., 2016).
The next target policies for energy transition are younger generation, including Generation Z and millennials (Yamane and Kaneko, 2021). They are crucial in developing motivational, compensation, work environment, and human resource policies (Hakam et al., 2024). By 2030, they will be the predominant working force, driving sustainability efforts and contributing to the achievement of the Sustainable Development Goals (Eurobarometer, Special, 2009; Jürkenbeck et al., 2021). Young people are more concerned about climate change and environmental issues than older citizens, with a higher sensitivity (67% compared to 56%). Millennials are known for their social consciousness and strong support for the SDGs (Cheng, 2019; Klimkiewicz and Oltra, 2017).
3 Research methodology
The present study employs a methodological framework integrating elements of the value-based adoption model (VAM) and the unified theory of acceptance and use of technology (UTAUT) to investigate user perspectives. UTAUT is a research methodology based on psychology and sociology that identifies four key factors influencing technology acceptance: performance expectancy, effort expectancy, social influence, and facilitating condition (Puspitasari et al., 2019). Performance expectancy refers to an individual’s belief that using a system will improve job performance (Lescevica et al., 2013). The VAM model, an alternative to the TAM, incorporates exogenous variables and enjoyment and perceived fee into the cost–benefit perspective, explaining technology usage behavior by focusing on benefits and sacrifices, aiding in understanding initial adoption intention and post-adoption behavior (Kim et al., 2007; Lin et al., 2012; Kim et al., 2017). Behavioral economics and socio-cultural factors play a crucial role in energy transition. Habit persistence, status quo bias, and loss aversion can hinder the adoption of induction stoves, as individuals tend to stick with familiar routines, resist change, and perceive the potential losses of switching—such as costs or learning curves—as outweighing the benefits, even when the new technology offers greater safety and sustainability. The integration of the value-based adoption model (VAM) and the unified theory of acceptance and use of technology (UTAUT) offers a comprehensive framework to examine induction stove adoption. UTAUT captures key external and social influences such as performance expectancy and facilitating conditions, while VAM adds depth by addressing intrinsic motivations such as perceived value and enjoyment. Their combination allows for a more holistic and predictive understanding of user behavior, balancing rational decision-making with emotional and value-based factors—critical for designing effective policies to support energy transitions. Conversion intention (COIN) covers the primary or secondary cooking device and the desire to switch from LPG to induction stove (Noverita et al., 2020). PAV includes functional, social, emotional, and conditional value (Hakam et al., 2020, 2022).
In Bangladesh, citizens prefer traditional cooking stoves over improved ones, but the taste is shifting due to performance after 3 weeks (Rosenbaum et al., 2015). PAV influences consumption decisions for induction kitchen appliances, affecting conversion intention partially on certain segments. Conversion intention in induction stoves, focusing on a person’s tendency to change behavior from initial to new conditions (Noverita et al., 2020). The study found that usage intention is the most significant predictor of use behavior, with sample size and culture significantly influencing the relationship (Baabdullah et al., 2019; Yu et al., 2019). In addition, attitudes toward learning to use an induction electric stove positively influence adoption (Kurniawan, 2023).
This research explores the scope of conversion intention, leveraging UTAUT and VAM theory (Osiolo, 2021; Noverita et al., 2020). Key factors such as perceived alternative value (PAV) significantly influence intention and adoption rates (Shuhaiber and Mashal, 2019). Surveys examined the relationship between performance expectancy (PE), perceived alternative value (PAV), and conversion intention (COIN), with conversion cost (CC) as a mediating factor. Data were collected through questionnaires of 192 young generations (12–42 years old) who used LPG as the cooking fuels in Indonesia, asking about their expectancy in cooking plan using induction stove which is going to be government policy in 2030. The result analyzed using partial least squares structural equation modeling (PLS-SEM) via the SMARTPLS software. The analysis includes reflective measurement model assessment (outer loadings, internal consistency reliability, convergent validity (AVE), and discriminant validity using HTMT), formative measurement model assessment (convergent validity, collinearity, and the significance and relevance of the indicators), and structural measurement model assessment (t-statistic and p-value). The findings were interpreted considering the hypothesized relationships. The hypotheses are shown in Figure 1.
Figure 1. Research framework.
H1: Performance expectancy (PE) has a significant impact on conversion intention (COIN).
H2: Performance expectancy (PE) has a significant impact on perceived alternative value (PAV).
H3: Perceived alternative value (PAV) has a significant impact on conversion intention (COIN).
H4: Perceived alternative value (PAV) mediates the relationship between performance expectancy (PE) and conversion intention (COIN) to convert LPG to induction stove as cooking energy.
H5: Conversion cost (CC) has a significant impact on conversion intention (COIN).
The survey was conducted on LPG stove users, specifically targeting Millennial and Gen Z, who make up 69.3% of the population. The survey was conducted using a Likert Scale (LS) to measure participants’ agreement with statements of interest (1–5). Table 2 represents the question list of survey. The study used questionnaire data and SMART-PLS software for structural equation modeling (SEM), a widely used statistical technique. It performed well with small sample sizes and distributions, attempting to understand the connection between latent constructs reflected by different metrics.
Table 2. Questionnaire list.
The survey was collected by gathering the information from the questionnaire. Table 2 shows a questionnaire list items, related to the PE, PAV, CC, and COIN. PAV consists of functional, social, emotional, and conditional value. CC includes risk, set-up, and learning cost. The data were processed using the software SMART-PLS using structural equation modeling (SEM). PLS-SEM was chosen for its suitability with smaller sample sizes, such as the 192 respondents in this study, and its capacity to handle complex models with multiple constructs. Its predictive focus and flexibility with data distribution make it ideal for exploratory research on conversion intentions (Noverita et al., 2020).
4 Statistical analysis of induction user perception
Data were gathered from 192 Indonesian youth. Gender perspective revealed a balanced population, with women primarily involved in cooking activities. The number of respondents was 65.26% belong to Generation Z, with over half having bachelor’s degrees. Most users reported income levels meeting or exceeding the minimum regional wage ($244.1–367) and engage in cooking activities 2–5 times a week. In addition, 84% of respondents demonstrated familiarity with induction stoves.
Statistical SMART-PLS analysis use to evaluate reflectively measured constructs encompassed several crucial dimensions: (1) assessment of outer loadings, (2) internal consistency reliability, (3) convergent validity (AVE), and (4) discriminant validity (using HTMT). Table 3 indicates that the variables met the satisfactory standard of 0.708, in alignment with the criteria set forth (Sarstedt et al., 2022). Particularly noteworthy are the robust outer loadings observed for items COIN 2 and COIN 4, each registering at 0.906, thereby surpassing the prescribed threshold. This adherence to the outer loading criterion bolsters the validity of the data (Cheah et al., 2023). Moreover, the internal consistency reliability, as assessed through Cronbach’s alpha coefficients, yielded values of 0.899 and 0.921 for the constructs PE and COIN, respectively. These coefficients fall within the recommended range of 0.70–0.95, affirming the reliability of the measurement instruments. The correlation-based reliability measures, namely, ρA and ρC, also corroborate the high reliability of the constructs within this range. These reliability indicators significantly contribute to the determination of AVE, encompassing both positive and negative aspects of the variables. Convergent validity is defined as AVE with the minimum amount of 0.5 which is categorized as valid (Ringle et al., 2012). Notably, all variables surpassed this threshold, with AVE values ranging from 0.712 to 0.76, thereby affirming the convergent validity of the measurement model. Furthermore, HTMT using Fornell-Larcker results in 0.874 which is less than the threshold of 0.9. HTMT indicates the average indicator correlation across the numerator smaller than the average indicator within the denominator (Benitez et al., 2020; Guenther et al., 2023).
Table 3. Reflective measurement analysis.
The inclusion of formative assessment in the research is imperative due to its status as a higher-order construct aimed at ameliorating the pervasive inadequacies in reporting standards delineated within the scholarly literature, while concurrently ensuring the establishment of robust measurement frameworks (Becker et al., 2012; Ringle et al., 2012). Differing from reflective indicators that manifest latent variables, formatively measured indicators yield latent variables. Given the distinct nature of these indicators, there exists no interchangeability concern, thereby obviating the need for reliability testing, internal consistency assessments, or scrutiny of discriminant validity. The formative measurement calculates (1) convergent validity, (2) collinearity, and (3) the significance and relevance of the indicators. Convergent validity serves as a gage of internal consistency, aimed at verifying that the items purported to measure each latent variable indeed do so, without inadvertently capturing another latent variable.
Table 4 represents the validation of overall PAV and CC. The items include the assessment of individual item reliability, Cronbach’s alpha coefficient, composite reliability (CR), and average variance extracted (AVE). The result shows that path coefficient of PAV (PAV → Overall PAV) is 0.682 and the CCI (CCI → overall CCI) is 0.822. The path coefficients linking latent variables are required to meet specific criteria: They should be no less than 0.1, exhibit the appropriate algebraic sign (in this investigation, positive), and achieve statistical significance, typically at a level of at least 0.05. The number indicates VIF in the range of 2.051–2.880 in PAV and 1.472–2.300 in CC. The standard of VIF is valid below 10 and meeting the standard of SMART-PLS application. A collinearity problem may be present if the VIF is five or above (Hair et al., 2021).
Table 4. Redundancy analysis.
Table 5 depicts the collinearity, significance, and relevance testing of PAV and CC. Indicator weight represents relative contribution to construct, while absolute contribution is represented by indicator loading (Shela et al., 2023). The analysis was conducted using bootstrapping for 10,000 times tested in two-tailed at 5% significant test. The contribution to construct of PAV and CC is mostly significant, except CCI 2 (t = 1.463), CCI 3 (t = 1.581), CCI 4 (t = 0.524), and CCI 5 (t = 1.555). The indicators that are insignificant passed the test from the weight to loading; thus, the items are retained to analyze. The result of t-statistic shows significant above 1.960 as the minimum of acceptance, meaning the items should be accepted (Chiwaridzo, 2024; Yudatama et al., 2019). All the number of indicators both in PAV and CC makes a relative and absolute contribution to their construct.
Table 5. Collinearity, significance, and relevance testing of PAV and CC.
Structural measurement for SMART-PLS consists of collinearity testing, significance and relevance testing, and explanatory power testing using R2 and f2. Collinearity testing among indicators constitutes a latent variable using the variance inflation factor (VIF). Elevated levels of multicollinearity can lead to non-significant estimates and unexpected signs of coefficients. Traditionally, VIF values surpassing 5 are indicative of problematic multicollinearity (Benitez et al., 2020). When the VIF value is 5 or above, it indicates a potential issue with collinearity problem (Hair et al., 2021). Table 6 presents data extracted from the questionnaire pertaining to the performance expectancy (PE), perceived alternative value (PAV), and conversion cost paths, revealing VIF values of 2.227, 2.175, and 1.030, respectively. The values meet standard criteria, indicating no collinearity issues along the paths. Subsequent analysis can proceed to assess t-statistics and p-values to determine whether hypotheses can be rejected or accepted.
Table 6. Collinearity testing structural model.
Table 7 shows structural model which estimates the designed path through path coefficient, t-statistic, and p-value. After the bootstrapping ran for 10,000 times at the 5% confident level, the path coefficients show the number in the range of −1 to +1. Stronger relationships are indicated by values closer to +1 or −1, while weaker or negligible relationships are indicated by values closer to 0. The highest path coefficient is the relationship between PE and PAV resulting in 0.737, while the weakest with the number closer to zero (р = 0.050) is CC that moderates PAV to COIN. The number affecting the t-statistic, as mentioned before the standard significance is 1.960 (Chiwaridzo, 2024; Yudatama et al., 2019). Aligned with theory, t-statistic is achieved from the first hypothesis to fourth hypothesis with the range of 5.907–23.886 (p-value = 0.000). It is convinced that the PE and PAV significantly influence young generations to switch from LPG to induction stove. CC moderates PAV insignificantly affecting the COIN with the t-statistic under 1.960 (p-value = 0.160), resulting in the rejection of the hypothesis. It means that the conversion cost does not affect the intention people to switch from the LPG to induction stove.
Table 7. Structural model estimates.
The data validity is assessed through explanatory power testing, including regression and effect size analyses. Table 8 defines the explanatory power testing of PAV and COIN. A high R2 value indicates overly conformity to the data. PAV significantly contributes to the data, accounting for 53.20% of variance without and 53.00% with moderating effects. Conversion intention moderately conforms to the data, with R2 = 68.40. Effect size values (f2) are crucial for comparing path coefficients and establishing consistency in ranking orders. In the specified path model, moderation has a 17.20% effect size. Effect sizes as minor (2–15%), moderate (15–35%), and high (>35%) determine the strength and importance of correlations between latent components and facilitate comparisons across models or studies (Sarstedt et al., 2020).
Table 8. Explanatory power testing.
The inferential analysis, conducted through structural equation modeling (SEM), reveals that performance expectancy and perceived alternative value have statistically significant positive effects on conversion intention, with standardized path coefficients of 0.52 and 0.41, respectively (p < 0.05). These results indicate that users’ expectations of improved safety, efficiency, and overall utility from induction stoves which substantially drive their willingness to convert. Meanwhile, the effect of conversion cost is statistically insignificant (p > 0.05), suggesting that for younger generations, financial or setup barriers are less influential compared to perceived benefits. This highlights a clear behavioral trend where values related to sustainability and performance outweigh cost concerns in technology adoption decisions.
5 Indonesian induction stove perception insight and policy recommendation
This study focuses on a quantitative analysis of the relationship between predictor variables—performance expectancy, perceived alternative value, and conversion cost—and conversion intention, as viewed through the perspectives of Generation Z and millennials. The research is grounded in the unified theory of acceptance and use of technology (UTAUT) and the value-based adoption model (VAM), offering both explanatory insights and predictive outcomes that enhance understanding of user behavior and technology adoption.
The intention to switch from LPG to induction stoves is significantly influenced by users’ performance expectancy (PE). Evidence from the results indicates that the majority of respondents believe induction stoves should be practical for daily cooking. They expect induction stoves to offer safety and convenience comparable to, or exceeding, that of LPG stoves. Similar to previous research confirming the significant contributions of users, teachers perceive the use of mobile Internet in teaching as both useful and valuable (Nikolopoulou et al., 2021). Another study demonstrated that colleagues believe positive user experiences, high satisfaction levels, and enjoyment could enhance their connection with information technologies and likely motivate them to continue using these technologies in the future (Camilleri, 2024). However, public concerns persist regarding the safety and convenience of induction stoves, despite the distribution of 2,000 units in two cities in Indonesia (Nurbaiti, 2022).
The role of PAV is important in significantly affecting the conversion intention, both direct and indirectly. PAV which consists of functional, social, emotional, and conditional value elements influences the young generations to convert their stove from LPG to induction stove. Previous research in Indonesia has demonstrated that time-oriented convenience significantly influences the perceived consumption value of induction stoves (Hilmiyati-Mas’adah et al., 2023). Consequently, perception plays a crucial role in enhancing the intention to convert from LPG-fueled stoves to electric-powered cooking energy. The functional aspect plays a significant role in decision-making, with many people believing that electric stoves cannot deliver the best cooking results due to the minimum energy required. The optimal heat that an electric stove should have is 1,800 watts for the efficiency (Hakam et al., 2022), but most households in Indonesia can only support 900 watts or R1-900 (Directorate General of Electricity, 2022). This factor can be a deliberation of government switching fuel planning based on the energy ladder. Access to electricity must play a wide range of critical direct and indirect roles in achieving the United Nations Millennium Development Goals (UN MDGs); moreover, in developing countries, poverty and human development become critical aspects in the lack of electricity (Shyu, 2014).
Social and emotional values elevate the public’s perception of using this type of stove. From previous research mentioned, improved cooked stove strongly influences consumers’ choice (Gill-Wiehl et al., 2021; Nyrud et al., 2008). Younger generation’s view is using induction stoves as a means of supporting clean, green energy, reflecting their awareness of sustainability (Ogiemwonyi, 2022; Oinonen and Paloniemi, 2023). The argument supported by fact that induction stove, microwaves, and electric stove has lowest level of CO2 emissions (zero emission) (Hilmiyati-Mas’adah et al., 2024; Hakam et al., 2022). Meanwhile, conditional values highlight the importance of subsidies and availability. Since these factors depend on government regulation, policies should support the transition from LPG to induction stoves to make this shift a reality. In a similar case in Ecuador, government pushed to use clean energy (both LPG and induction stove), influenced by availability, convenience, and subsidy (Gould et al., 2018; Valarezo et al., 2023). Indonesia’s roadmap for developing renewable energy, such as geothermal energy, should also be considered regarding availability and subsidies, which are managed by the state-owned enterprise PLN. Mirroring from energy switch kerosene to LPG in 2007, PAV plays a critical factor for the program key success (Hilmiyati-Mas’adah et al., 2024).
Typically, cost is an important factor in decision-making; however, surveys indicate that young generations do not consider switching costs significantly when transitioning to new technologies. Gen Z and Millennials demonstrate quick adaptation to new technology, including electric stoves, showing minimal concern for economic risk costs, moreover when they are satisfied with the tools (Pichler et al., 2021; Quintal et al., 2016). In terms of learning costs, these generations quickly adapt to new technology, facilitating their transition to induction stoves (Pichler et al., 2021). Furthermore, setup costs do not significantly impact their intention to shift from LPG to induction stoves. These generations are willing to incur additional expenses if the technology provides environmental benefits (Ogiemwonyi, 2022; Oinonen and Paloniemi, 2023). The findings are aligned with previous research, which PE and PAV (both direct and indirect) affecting COIN. However, CC is not a significant variable in COIN important factors.
The 2023 policy aims to shift cooking fuels from LPG to alternatives to reduce oil imports, meet domestic demand using natural resources, and achieve net-zero emissions by 2060. Performance expectancy, perceived alternative value, and conversion cost are key factors influencing youth’s conversion intention toward induction stoves. A study of 192 users revealed that 84% were aware of induction stoves. Performance expectancy, which includes aspects such as safety and convenience, significantly affects the youth’s intention to switch from LPG to induction stoves. Perceived alternative value (PAV) positively affects the intention to switch from LPG to induction stoves, indirectly contributing to the purchasing intention of induction stoves from LPG. Conversion cost (CC) does not significantly affect the conversion to induction stoves as many young generations prioritize sustainability and are willing to pay higher costs if it benefits the environment. Induction stoves fulfill safety and convenience needs, offering a morally correct choice in people’s perspectives. Although conversion cost was not found to significantly influence adoption intention, this may be due to the presence or expectation of subsidies that lower financial barriers. Mandatory policies can also create social momentum and a FOMO effect, encouraging broader adoption regardless of cost. These behavioral dynamics can enhance perceived alternative value (PAV), especially when supported by incentives and awareness campaigns. Thus, policy can play a key role in accelerating adoption and shaping long-term behavioral trends. The acceptance of shifting from LPG to induction stoves remains consistent, with the higher t-statistic indicating that the younger generation finds the functional, social, emotional, and conditional value elements of induction stoves to meet their standards.
The transition from LPG stoves to renewable energy sources, such as induction stoves, is a gradual process aimed at reducing import expenses, achieving net-zero emissions by 2060, and enhancing user safety and convenience. Performance expectancy significantly influences conversion intentions, with users needing assurance about safety, fulfilling their needs, and convenience. Induction stoves pose a challenge as many people still worry about safety and electrocution. Perceived alternative value, including social, economic, and conditional factors, significantly impacts conversion intentions. Young people derive pride from using induction stoves due to their lower emissions compared to LPG stove, aligning with environmental friendliness. However, the availability of electricity presents a challenge as not all households can afford sufficient electricity. Conversion cost is a significant factor, but the initial cost of installing induction tools should be considered. Induction stoves’ low carbon emissions and potential savings make them an attractive option for young generations.
In conclusion, this study highlights that performance expectancy and perceived alternative value significantly influence the intention of Gen Z and Millennials in Indonesia to switch from LPG to induction stoves, while conversion cost is less impactful. These findings suggest that young consumers are more driven by functionality, environmental concerns, and perceived benefits than by economic constraints. Based on this, policy efforts should focus on increasing public awareness, improving access to electricity, and offering support through subsidies or incentives to ease the transition. However, the study is limited by its urban sampling and cross-sectional design, which may not fully represent broader population behavior. Future research should consider rural contexts, longitudinal data, and additional influencing factors such as social norms, trust in policy, and perceived risks to enrich the understanding of clean cooking technology.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.
Author contributions
DH: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. NN: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Visualization, Writing – original draft, Writing – review & editing. AA: Supervision, Validation, Visualization, Writing – review & editing. AU: Funding acquisition, Supervision, Validation, Visualization, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. The research was supported by the Bank Indonesia Institute under the Research Grant Bank Indonesia, as stipulated in contract number 26/38/PKS/BINS/2024.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Gen AI was used in the creation of this manuscript.
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References
Adria, O., and Bethge, J. (2013). “Energy-efficient cooking what users can save with stoves and ovens energy-efficient cooking stoves and ovens.” Wuppertal Institute for Climate, environment and energy. Available online at: https://bigee.net/media/filer_public/2014/03/17/appliance__residential_cookingstoves__user_savings__20140220__8.pdf.
Anggraini, Y. (2022). “Indonesia’s ‘LPG to induction stove conversion program’ demands careful review.” Energy Review Newsletter. Available online at: https://www.energyreview.in/post/indonesia-s-lpg-to-induction-stove-conversion-program-demands-careful-review.
Asian Development Bank (2020). Indonesia energy sector assessment, strategy, and road map – update. Available online at: https://www.adb.org/sites/default/files/institutional-document/666741/indonesia-energy-asr-update.pdf.
Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., and Patil, P. (2019). Consumer use of Mobile banking (M-banking) in Saudi Arabia: towards an integrated model. Int. J. Inf. Manag. 44, 38–52. doi: 10.1016/J.IJINFOMGT.2018.09.002
Becker, J. M., Klein, K., and Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long Range Plan. 45, 359–394. doi: 10.1016/J.LRP.2012.10.001
Benitez, J., Henseler, J., Castillo, A., and Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: guidelines for confirmatory and explanatory IS research. Inf. Manag. 57:103168. doi: 10.1016/J.IM.2019.05.003
Billah, S. M., Islam, S., Tasnim, F., Alam, A., El Arifeen, S., and Raynes-Greenow, C. (2020). Self-adopted ‘natural users’ of liquid Petroleum gas for Household Cooking by pregnant women in rural Bangladesh: characteristics of high use and opportunities for intervention. Environ. Res. Lett. 15:095008. doi: 10.1088/1748-9326/ab7b25
BPS (2020). Statistik Kesejahteraan Rakyat (welfare statistics). Available online at: https://www.bps.go.id/site/resultTab.
Camilleri, M. A. (2024). Factors affecting performance expectancy and intentions to use ChatGPT: using SmartPLS to advance an information technology acceptance framework. Technol. Forecast. Soc. Chang. 201:123247. doi: 10.1016/J.TECHFORE.2024.123247
Cheah, J. H., Amaro, S., and Roldán, J. L. (2023). Multigroup analysis of more than two groups in PLS-SEM: a review, illustration, and recommendations. J. Bus. Res. 156:113539. doi: 10.1016/J.JBUSRES.2022.113539
Cheng, M. (2019). “8 characteristics of millennials that support sustainable development goals (SDGs).” Forbes. Available online at: https://www.forbes.com/sites/margueritacheng/2019/06/19/8-characteristics-of-millennials-that-support-sustainable-development-goals-sdgs/?sh=28922f6d29b7.
Chiwaridzo, O. T. (2024). Unleashing Tomorrow’s energy for sustainable development: pioneering green building technologies and green tourism supply chain Management in Zimbabwe’s tourism sector. Energy Sustain. Dev. 78:101382. doi: 10.1016/J.ESD.2024.101382
Dickinson, K. L., Piedrahita, R., Coffey, E. R., Kanyomse, E., Alirigia, R., Molnar, T., et al. (2019). Adoption of improved biomass stoves and stove/fuel stacking in the REACCTING intervention study in northern Ghana. Energy Policy 130, 361–374. doi: 10.1016/J.ENPOL.2018.12.007
Directorate General of Electricity (2022). Statistik Ketenagalistrikan Tahun 2022 [in Bahasa]. Available online at: https://gatrik.esdm.go.id/assets/uploads/download_index/files/72f25-web-publish-statistik-2022.pdf?utm_source=chatgpt.com.
Gill-Wiehl, A., Price, T., and Kammen, D. M. (2021). What’s in a stove? A review of the user preferences in improved stove designs. Energy Res. Soc. Sci. 81:102281. doi: 10.1016/J.ERSS.2021.102281
Gould, C. F., Jagoe, K., Moreno, A. I., Verastegui, A., Pilco, V., García, J., et al. (2018). Prevalent degradation and patterns of use, maintenance, repair, and access to post-Acquisition Services for Biomass Stoves in Peru. Energy Sustain. Dev. 45, 79–87. doi: 10.1016/J.ESD.2018.05.004
Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., and Cartwright, S. (2023). Improving PLS-SEM use for business marketing research. Ind. Mark. Manag. 111, 127–142. doi: 10.1016/J.INDMARMAN.2023.03.010
Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2021). A primer on partial least squares structural equations modeling (PLS-SEM). 2nd Edn. Thousand Oaks, CA: Sage. pp. 200–215.
Hakam, D. F., Triani, M., Wirasangka, I. P., and Aisyah, S. (2020). Economic simulation of Indonesia’s clean energy policy: Shifting from LPG to induction stove. In Proceedings of the 2nd Faculty of Industrial Technology International Congress (FOITIC 2020) (pp. 252–256). Bandung, Indonesia: Institut Teknologi Nasional. Available at: https://eproceeding.itenas.ac.id/index.php/foitic/article/view/88/81
Hakam, D. F., Haryadi, F. N., Indrawan, H., Hanri, M., Hakam, L. A., Kurniawan, O., et al. (2024). Analyzing current trends in career and employer from the perspectives of millennials within the Indonesian energy sector. Energies 17:2570. doi: 10.3390/en17112570
Hakam, D. F., Nugraha, H., Wicaksono, A., Rahadi, R. A., and Kanugrahan, S. P. (2022). Mega conversion from LPG to induction stove to achieve Indonesia’s clean energy transition. Energ. Strat. Rev. 41:100856. doi: 10.1016/J.ESR.2022.100856
Hilmiyati-Mas’adah, H., Sudiro, A., Rohman, F., Yuniarinto, A., Hakam, D. F., and Nugraha, H. (2024). Switching from LPG to Electricity in Indonesia: a study in the Java Bali grid. Cog. Bus. Manag. 11:2298221. doi: 10.1080/23311975.2023.2298221
Hilmiyati-Mas’adah, H., Sudiro, A., Rohman, F., Yuniarinto, A., Hakam, D. F., and Nugraha, H. (2023). Assessing the impact of urban lifestyle and consumption values on conversion intention: a study towards energy sustainability. Sustainability (Switzerland) 15:6549. doi: 10.3390/su15086549
Hing, S., and Gadgil, A. (2023). Sensors show long-term dis-adoption of purchased improved Cookstoves in rural India, while surveys miss it entirely. Dev. Eng. 8:100111. doi: 10.1016/J.DEVENG.2023.100111
IRENA (2017). Renewable energy prospects: Indonesia. Abu Dhabi: International Renewable Energy Agency.
Jagadish, A., and Dwivedi, P. (2018). In the hearth, on the mind: cultural consensus on fuelwood and Cookstoves in the middle Himalayas of India. Energy Res. Soc. Sci. 37, 44–51. doi: 10.1016/J.ERSS.2017.09.017
Jeuland, M. A., Bhojvaid, V., Kar, A., Lewis, J. J., Patange, O., Pattanayak, S. K., et al. (2015). Preferences for improved cook stoves: evidence from rural villages in North India. Energy Econ. 52, 287–298. doi: 10.1016/J.ENECO.2015.11.010
Jürkenbeck, K., Spiller, A., and Schulze, M. (2021). Climate change awareness of the young generation and its impact on their diet. Cleaner Respons. Consum. 3:100041. doi: 10.1016/J.CLRC.2021.100041
Kim, H. W., Chan, H. C., and Gupta, S. (2007). Value-based adoption of Mobile internet: an empirical investigation. Decis. Support. Syst. 43, 111–126. doi: 10.1016/J.DSS.2005.05.009
Kim, Y., Park, Y., and Choi, J. (2017). A study on the adoption of IoT smart home service: using value-based adoption model. Total Qual. Manag. Bus. Excell. 28, 1149–1165. doi: 10.1080/14783363.2017.1310708
Klimkiewicz, K., and Oltra, V. (2017). Does CSR enhance employer attractiveness? The role of millennial job seekers’ attitudes. Corp. Soc. Respons. Environ. Manage. 24, 449–463. doi: 10.1002/csr.1419
Kulindwa, Y. J., Lokina, R., and Ahlgren, E. O. (2018). Driving forces for households’ adoption of improved cooking stoves in rural Tanzania. Energ. Strat. Rev. 20, 102–112. doi: 10.1016/J.ESR.2017.12.005
Kurniawan, Y. (2023). Intention to use induction electric stove according to theory of trying. Int. J. Multidiscip. Res. Anal. 6, 1663–1716. doi: 10.47191/ijmra/v6-i4-41
Lescevica, M., Ginters, E., and Mazza, R. (2013). Unified theory of acceptance and use of technology (UTAUT) for market analysis of FP7 CHOReOS products. Proc. Comput. Sci. 26, 51–68. doi: 10.1016/J.PROCS.2013.12.007
Lin, T. C., Sheng, W., Hsu, J. S. C., and Chou, Y. C. (2012). The integration of value-based adoption and expectation–confirmation models: an example of IPTV continuance intention. Decis. Support. Syst. 54, 63–75. doi: 10.1016/J.DSS.2012.04.004
Martínez-Gómez, J., Ibarra, D., Villacis, S., Cuji, P., and Cruz, P. R. (2016). Analysis of LPG, electric and induction cookers during cooking typical Ecuadorian dishes into the National Efficient Cooking Program. Food Policy 59, 88–102. doi: 10.1016/J.FOODPOL.2015.12.010
Ministry of Energy and Mineral Resources (2023). Pemanfaatan Gas Domestik Capai 68 Persen, Dukung Program Gasifikasi Kelistrikan [in Bahasa]. Available online at: https://migas.esdm.go.id/post/read/pemanfaatan-gas-domestik-capai-68-persen-dukung-program-gasifikasi-kelistrikan.
Nikolopoulou, K., Gialamas, V., and Lavidas, K. (2021). Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use Mobile internet. Comput. Educ. Open 2:100041. doi: 10.1016/J.CAEO.2021.100041
Noverita, R., Jacob, D., and Mussry, S. (2020). “Proposed PT PLN (Persero) marketing capability to realize induction stove as a preferable option for LPG substitution and electrifying lifestyle growth.” In Proceedings of the International Conference on Business and Management Research (ICBMR 2020). Atlantis Press. doi: 10.2991/aebmr.k.201222.006
Nurbaiti, I. (2022). “Pro Kontra Konversi, Ini Kelebihan Dan Kekurangan Kompor Listrik [in Bahasa].” Indonesia Business. Available online at: https://bisnisindonesia.id/article/pro-kontra-konversi-ini-kelebihan-dan-kekurangan-kompor-listrik.
Nyrud, A. Q., Roos, A., and Sande, J. B. (2008). Residential bioenergy heating: a study of consumer perceptions of improved woodstoves. Energy Policy 36, 3169–3176. doi: 10.1016/J.ENPOL.2008.04.019
Ogiemwonyi, O. (2022). Factors influencing generation Y green behaviour on green products in Nigeria: an application of theory of planned behaviour. Environ. Sustain. Indicat. 13:100164. doi: 10.1016/J.INDIC.2021.100164
Oinonen, I., and Paloniemi, R. (2023). Understanding and measuring young People’s sustainability actions. J. Environ. Psychol. 91:102124. doi: 10.1016/J.JENVP.2023.102124
Osiolo, H. H. (2021). Cook stove technology adoption: evidence from Kenya. Energy Sustain. Dev. 63, 133–144. doi: 10.1016/J.ESD.2021.06.004
Owusu-Amankwah, G., Abubakari, S. W., Apraku, E. A., Iddrisu, S., Kar, A., Malagutti, F., et al. (2023). Socioeconomic determinants of household stove use and stove stacking patterns in Ghana. Energy Sustain. Dev. 76:101256. doi: 10.1016/J.ESD.2023.101256
Pangaribowo, E. H., and Iskandar, D. D. (2023). Exploring socio-economic determinants of energy choices for cooking: the case of eastern Indonesian households. Environ. Dev. Sustain. 25, 7135–7148. doi: 10.1007/s10668-022-02362-y
Pichler, S., Kohli, C., and Granitz, N. (2021). DITTO for gen Z: a framework for leveraging the uniqueness of the new generation. Bus. Horiz. 64, 599–610. doi: 10.1016/J.BUSHOR.2021.02.021
Pine, K., Edwards, R., Masera, O., Schilmann, A., Marrón-Mares, A., and Riojas-Rodríguez, H. (2011). Adoption and use of improved biomass stoves in rural Mexico. Energy Sustain. Dev. 15, 176–183. doi: 10.1016/J.ESD.2011.04.001
Puspitasari, N., Firdaus, M. B., Haris, C. A., and Setyadi, H. J. (2019). An application of the UTAUT model for analysis of adoption of integrated license service information system. Proc. Comput. Sci. 161, 57–65. doi: 10.1016/J.PROCS.2019.11.099
Quintal, V., Phau, I., Sims, D., and Cheah, I. (2016). Factors influencing generation Y’s purchase intentions of prototypical versus me-too brands. J. Retail. Consum. Serv. 30, 175–183. doi: 10.1016/J.JRETCONSER.2016.01.019
Reuters Staff (2021). Indonesia LPG imports to fall sharply by 2025 as coal gasification ramps up. Available online at: https://www.reuters.com/article/indonesia-coal-idUSL4N2L715W.
Ringle, C. M., Sarstedt, M., and Straub, D. W. (2012). Editor’s comments: a critical look at the use of PLS-SEM in MIS quarterly. MIS Q. 36, iii–xiv. doi: 10.2307/41410402
Rishanty, A., Sambodo, M. T., Fajar, D., Retno, A., and Wicaksono, P. K. (2022). “Energy transition: Prospect and challenges at ASEAN plus three countries.” Working Paper Bank Sentral Indonesia.
Rosenbaum, J., Derby, E., and Dutta, K. (2015). Understanding consumer preference and willingness to pay for improved Cookstoves in Bangladesh. J. Health Commun. 20, 20–27. doi: 10.1080/10810730.2014.989345
Ruiz-Mercado, I., Canuz, E., Walker, J. L., and Smith, K. R. (2013). Quantitative metrics of stove adoption using stove use monitors (SUMs). Biomass Bioenergy 57, 136–148. doi: 10.1016/J.BIOMBIOE.2013.07.002
Sarstedt, M., Hair Jr, J. H., Nitzl, C., Ringle, C. M., and Howard, M. C. (2020). Beyond a tandem analysis of SEM and PROCESS: use of PLS-SEM for mediation analyses! Int. J. Mark. Res. 62, 288–299. doi: 10.1177/1470785320915686
Sarstedt, M., Hair Jr, J. F., and Ringle, C. M. (2022). ‘PLS-SEM: indeed a silver bullet’ – retrospective observations and recent advances. J. Mark. Theory Pract. 31, 261–275. doi: 10.1080/10696679.2022.2056488
Shela, V., Ramayah, T., Aravindan, K. L., Ahmad, N. H., and Alzahrani, A. I. (2023). Run! This road has no ending! A systematic review of PLS-SEM application in strategic management research among developing nations. Heliyon 9:e22476. doi: 10.1016/J.HELIYON.2023.E22476
Shuhaiber, A., and Mashal, I. (2019). Understanding users’ acceptance of smart homes. Technol. Soc. 58:101110. doi: 10.1016/J.TECHSOC.2019.01.003
Shyu, C. W. (2014). Ensuring access to electricity and minimum basic electricity needs as a goal for the post-MDG development agenda after 2015. Energy Sustain. Dev. 19, 29–38. doi: 10.1016/J.ESD.2013.11.005
Suharsono, A., and Lontoh, L. (2022). “Indonesia’s energy policy briefing.” February 2022 (pp. 1–17). International Institute for Sustainable Development. Available at: https://www.iisd.org/system/files/2022-03/indonesia-energy-policy-briefing-february-2022-en.pdf
Takama, T., Tsephel, S., and Johnson, F. X. (2012). Evaluating the relative strength of product-specific factors in fuel switching and stove choice decisions in Ethiopia. A discrete choice model of household preferences for clean cooking alternatives. Energy Econ. 34, 1763–1773. doi: 10.1016/J.ENECO.2012.07.001
Thinkgeoenergy (2023). Pertamina earmarks $550 million budget for 1 GW geothermal capacity target. Available online at: https://www.thinkgeoenergy.com/pertamina-earmarks-550-million-budget-for-1-gw-geothermal-capacity-target/.
Troncoso, K., Segurado, P., Aguilar, M., and Soares da Silva, A. (2019). Adoption of LPG for cooking in two rural communities of Chiapas, Mexico. Energy Policy 133:110925. doi: 10.1016/J.ENPOL.2019.110925
Valarezo, A., Lissete Dávila, M., Bejarano, L., Nolivos, I., Molina, E., Schlesinger, S. B., et al. (2023). Resilient clean cooking: maintaining household clean cooking in Ecuador during the COVID-19 pandemic. Energy Sustain. Dev. 74, 349–360. doi: 10.1016/J.ESD.2023.03.018
Wicaksana, K. S., Ramadhan, R. F., Sujaka, M. A., and Salahudin, A. (2022). The effect of Russia-Ukraine crisis on Price fluctuations and trade in energy sector in Indonesia. Jurnal Nasional Pengelolaan Energi MigasZoom. 4, 1–12. doi: 10.37525/mz/2022-1/345
Yamane, T., and Kaneko, S. (2021). Is the younger generation a driving force toward achieving the sustainable development goals? Survey experiments. J. Clean. Prod. 292:125932. doi: 10.1016/J.JCLEPRO.2021.125932
Yu, H., Seo, I., and Choi, J. (2019). A study of critical factors affecting adoption of self-customisation service – focused on value-based adoption model. Taylor Francis J. 30, S98–S113. doi: 10.1080/14783363.2019.1665822
Keywords: cooking, energy transition, youth perspective, induction stove, Indonesia
Citation: Hakam DF, Nuzula NA, Aprianingsih A and Utama AA (2025) Youth perspectives on induction stoves: advancing sustainable energy transitions in Indonesian cities. Front. Sustain. Cities. 7:1554457. doi: 10.3389/frsc.2025.1554457
Edited by:
Caterina Brandoni, Ulster University, United KingdomReviewed by:
Zahid Hussain, Liaoning University, ChinaLaura Varela Candamio, University of A Coruña, Spain
Amir Budhathoki, Prince of Songkla University, Thailand
Copyright © 2025 Hakam, Nuzula, Aprianingsih and Utama. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dzikri Firmansyah Hakam, ZHppa3JpLmhha2FtQHNibS1pdGIuYWMuaWQ=