Users’ Perspectives of Bidirectional Charging in Public Environments

Abstract

Technological advances such as Vehicle-to-Grid (V2G) have the potential to support renewable energy integration and grid stability, but large-scale deployment depends on users’ willingness to participate, particularly in public charging environments. While prior research has examined V2G from technical feasibility and system-level perspectives, everyday public settings remain unexplored. This study investigates electric vehicle (EV) users’ willingness to engage in V2G services in public spaces, with a focus on incentives, expectations, and how participation aligns with existing routines and parking conditions. A mixed-method approach was applied, combining a survey of 544 car users with two waves of user-centered interviews. The survey data were analyzed using factor analysis and linear regression models, while the interview data were thematically analyzed. The results show that users’ evaluations of V2G are shaped by sustainability expectations, perceived efficiency, and uncertainties, and preferences for public V2G participation are strongly influenced by convenience, clarity of the offer, and perceived control. Home charging practices emerged as a key reference point shaping expectations of public V2G services. Across both methods, simple and transparent incentives, such as reduced charging or parking costs, were consistently preferred over more complex reward models, including point-based systems or dynamic energy trading. Concerns related to control over trips, battery degradation, trust in service providers, and added complexity remain important barriers to participation. The findings highlight the need for user-centered and socio-technical design of public V2G services that align with users’ everyday routines, parking conditions, and expectations to support broader adoption beyond the home context.

1. Introduction

Technological advances in the energy and transportation sectors are critical for achieving sustainable development, with renewable energy and electric vehicles (EVs) playing central roles. Among these advances, Vehicle-to-Grid (V2G) technology has emerged as a promising solution by enabling bidirectional energy exchange between EVs and the power grid. Through this interaction, EVs can function as mobile energy storage units, contributing to grid stability and load balancing. When integrated with renewable energy sources, V2G can enhance system reliability and increase the overall environmental value of electrified transport. Importantly, V2G supports a transition toward a more decentralized energy system in which individual users move from being passive consumers to active participants in energy production, storage, and distribution [1,2,3].

User adoption of V2G is essential for the delivery of many—if not all—potential V2G services. Key user-related factors include willingness to participate, plug-in probability, plug-in duration, and the share of battery capacity made available for V2G. These behaviors are influenced by users’ knowledge, motivation, and exposure to both financial and non-financial incentives. Together, such behavioral and psychological factors shape both the pace and extent of V2G market development [4]. Consequently, research that examines user behavior, user needs, and interactions with other actors within the V2G ecosystem is of central importance.

Existing research has made considerable progress in understanding V2G from technical and system-level perspectives, and a growing body of research has begun to address user acceptance, motivations, and barriers. However, this work has largely concentrated on home-based charging contexts or controlled experimental trials [5].

Home charging remains the most common and preferred charging context for EV users, and much of what is known about user attitudes toward V2G reflects this setting. Studies examining willingness to participate, incentive preferences, and perceived barriers have predominantly drawn on home V2G scenarios, where users exercise high levels of control over charging conditions and routines [5,6,7].

Public environments, by contrast, introduce distinct decision-making conditions. Parking arrangements, charging convenience, trust in multiple service providers, and reduced user control all shape how EV users evaluate and respond to V2G participation in these contexts. Previous studies of V2G in public environments have predominantly focused on theoretical potential based on driving and parking patterns [5]; what remains largely unexplored is how everyday EV users perceive, evaluate, and decide whether to engage in V2G services in public spaces—and how their home charging practices, parking behaviors, incentive preferences, and concerns about control and trust shape those decisions. Insights derived from home charging contexts cannot be directly transferred to public V2G participation, leaving a significant gap in the literature.

This study addresses this gap by using a mixed-method design combining a survey of 544 car users with two waves of qualitative interviews. We investigate EV users’ willingness to participate in V2G services in public spaces, with particular attention to incentive preferences, everyday routines, and the conditions under which users are willing to cede control of their vehicle’s battery. Specifically, this study addresses the following research questions:

RQ 1. What aspects of economic incentives attract the most EV users to participate in V2G in public spaces?

RQ 2. What future expectations do EV users have for bidirectional charging, based on their preferences, needs, and routines?

In the following sections, a literature overview is presented with relevant studies to understand users’ willingness to participate in V2G services in public environments. Although the target behavior concerns public settings, understanding decision-making in these contexts requires insight into users’ reference points. Home charging remains the most common and preferred charging context [5], and therefore, the home environment is expected to serve as an anchoring baseline when users evaluate participation in V2G services in public spaces.

We identified four key aspects as particularly relevant in the literature for understanding users’ behaviors and needs related to V2G services in public environments: (1) household-level energy consumption behavior, (2) parking behavior, (3) perceived barriers, and (4) incentives [5,6,7,8]. These four key aspects form the structure of the following subsection.

Literature Overview

• Energy consumption at the household level

One of the key challenges within the V2G ecosystem is the monetization of V2G services for users. This challenge is partly driven by uncertainties across multiple actors, including variability in users’ charging behaviors. In addition, users’ charging patterns are closely linked to household electricity consumption, making household energy practices a critical contextual factor.

An EV typically represents a substantial share of a household’s electricity demand, meaning that electricity contracts play an important role in determining potential revenues from V2G services. The type of electricity contract held by a user may also indicate an interest in flexibility and energy efficiency at the household level, which in turn may reflect a higher degree of behavioral readiness for V2G participation.

By 2022, all Nordic countries had achieved near-universal deployment of smart meters [9,10]. Smart meters constitute a technical prerequisite for adopting Time-of-Use (ToU) electricity contracts, which are commonly based on hourly electricity consumption and corresponding spot prices.

A Swedish study involving 2679 households found that 75.6% of respondents who reported actively managing their electricity consumption began doing so in 2022, with 54.4% starting during the autumn of that year. Even households that had held ToU contracts for more than two years reported that increased price volatility between day and night, as well as across days in 2022, heightened their awareness and interest in managing electricity use [11].

The most frequently cited motivations for managing electricity consumption were reducing electricity trading costs under ToU contracts and lowering grid-related costs linked to power- or time-based tariffs. Cost savings, along with technological interest, were also identified as primary motivations among households that had adopted ToU contracts earlier [11].

Households that did not actively manage their electricity use were asked to rank factors that might encourage them to do so. Respondents living in detached houses most frequently ranked greater potential savings as the most influential factor, followed by lower costs for acquiring control systems and improved information regarding achievable savings. These factors highlight the central role of financial incentives and uncertainty about economic benefits [11].

2.

Parking behavior

Another critical determinant of V2G potential is vehicle parked time and associated plug-in behavior. EVs can only provide V2G services when parked and connected to a charger. Although vehicles are parked for most of the day, transforming parked time into plug-in time requires both access to charging infrastructure and user willingness to connect the vehicle. While parked time is largely determined by driving patterns, plug-in behavior can be influenced through incentives and behavioral interventions.

A Dutch study found that EV users expressed a preference for V2G at locations where they already tend to charge, such as home or the workplace. However, no clear preference emerged between these two locations, and neither was identified as a decisive factor for V2G acceptability [6].

3.

Perceived barriers

Range anxiety has been identified as one of the main barriers to V2G adoption, as concerns about driving range may reduce users’ willingness to share battery capacity through V2G services [12,13].

A UK study measuring drivers’ physiological responses under different charging conditions showed that anxiety levels decrease with greater experience and familiarity with EVs. However, the study also identified a direct correlation between heart rate and anxiety, revealing increased stress associated with infrastructure bottlenecks such as limited charger availability and payment system complexity [14,15]. Additional UK research confirms that range anxiety decreases with longer BEV experience and is further reduced among participants in V2G trials over time [16].

Beyond range anxiety, other behavioral factors significantly influence V2G adoption, including charging preferences, desired state of charge, time constraints, minimum plug-in durations, driving needs, and contract conditions [17,18,19,20]. Psychological factors—such as the need for control, perceptions of guilt-free mobility, hedonic motivations, gender roles, perceived transparency of contract terms, and willingness to pay—can also limit V2G uptake if system design does not adequately reflect users’ needs and boundaries [21]. Additional barriers include double taxation, negative experiences with public charging infrastructure [14,15], limited trust in V2G stakeholders, and concerns regarding battery degradation [8].

4.

Incentives

Using a self-report online survey conducted among 929 Norwegian car users in November 2021, a study examined how perceptions and beliefs about the V2G system influence EV users and non-EV users (combustion engine car owners as potential future EV users) to utilize V2G technology. The main findings from the authors were that positive perceptions and beliefs about V2G technology significantly motivate users to adopt it, while concerns about the reliability and cost of V2G systems are major barriers to adoption. Younger users and those with higher environmental awareness are more likely to support V2G technology [22].

While several businesses have been emerging in the European and Nordic markets aiming at monetizing V2G services, some studies have identified other drivers for V2G participation, such as the idea of having a smart and resilient home. A Swedish study conducted an online questionnaire to gather data from Swedish EV drivers. Respondents were asked about their preferences and concerns related to Vehicle-to-Everything (V2X) applications. The study found that Swedish EV drivers are more interested in Vehicle-to-Home (V2H) applications compared to V2G. V2H allows EVs to supply power to homes, which is seen as more beneficial by the respondents [23].

In a study of how household values and attitudes towards automated electric vehicle (EV) charging systems influence the adoption and use of such technology, the authors identified that households prioritize environmental sustainability and express a strong preference for technologies that contribute to a cleaner planet. They also found that automated EV charging is seen as beneficial for reducing the environmental footprint and simplifying the charging process for their participants [24].

While non-monetary incentives, such as having a smart, sustainable, and resilient household, may be an important driver for potential users of V2G services, the literature has also looked at the potential economic incentives and revenues for users that could increase the willingness to participate in V2G services.

A Norwegian study found that Norwegians require a financial compensation (FC) of $144 and a minimum state of charge (SoC) of 71% to use V2G services. The analysis revealed a reciprocal and negative relationship between FC and minimum SoC, both influenced by external factors. In a multi-equation equilibrium context, the marginal effects indicate that a one-unit increase in minimum SoC leads to a $5 reduction in the expected FC, all else being equal. Conversely, a $1 increase in FC results in a 0.05 decrease in the required minimum SoC, all else being equal [25].

The economic relationship between minimum SoC and FC is significantly affected by factors such as age, perceived usefulness of the V2G system, experience with EVs, and higher levels of trust in the V2G system. Specifically, individuals with high trust in V2G require less FC for a given amount of minimum SoC. Additionally, younger individuals (aged 18–22) tend to demand higher FC when the minimum SoC is reduced [25].

Based on these four key aspects from the literature, this study was designed to provide information for designing incentives that are most attractive to users and how expectations, needs, and routines shape future acceptance of bidirectional charging in public contexts.

2. Methods

This study applied a mixed-method research design combining a quantitative survey with qualitative interviews. The mixed-method approach was chosen to capture both the breadth of user attitudes toward V2G services and the depth of users’ underlying motivations, expectations, and concerns. The two methods were applied sequentially, with the survey providing a general overview of user perspectives and the interviews offering contextualized insights into the survey findings. Survey data were analyzed using exploratory factor analysis to identify latent constructs related to users’ perceptions of V2G, followed by linear regression analysis to examine the relationship between these constructs and users’ stated willingness to participate in public V2G services. Standard diagnostic tests were conducted to ensure that the assumptions underlying the regression models were satisfied.

Qualitative interview data were analyzed using thematic analysis. Interview transcripts were coded iteratively, with themes emerging both from the data and from concepts identified in the literature. This approach enabled triangulation between quantitative and qualitative findings and strengthened the interpretation of results.

2.1. Survey

The objective of the survey was to assess the overall evaluation of attitudes and expectations towards V2G with a larger sample size. The items were based on other studies that also incorporated behavioral questions in their research questions [13,14] and went through expert validation with a diverse set of stakeholders (such as representatives of Original Equipment Manufacturer (OEMs), parking operators, and electricity providers).

The survey was sent out via intranet by one of the partners of the project and it was composed of 25 items, taking approximately 5–7 min to fill in. The questions comprised the following aspects: socio-demographic, household profile, travel behavior patterns, access to charging infrastructure, energy consumption behavior, attitudes towards V2G, and willingness to use a vehicle that has V2G functionality. The latent variables were measured by a 7-point Likert scale, where 1 means “totally disagree” and 7 means “totally agree”.

The final sample comprised 544 valid answers. The majority of respondents were men (N = 452; 83.1%), among the age groups of 36–45 years old (N = 160; 29.4%) and 46–55 years old (N = 202; 37.1%), with children in the household (N = 339; 62.3%).

2.2. Interviews

The interviews were divided into two waves: the first wave aimed at understanding the daily needs and routines around the EV and potential for V2G in the household context; the second wave aimed at understanding what offers of V2G in the context of public spaces would attract EV users and why. The interview data were recorded using Microsoft Teams, and the recordings were uploaded to the Reduct qualitative analysis platform and transcribed.

2.2.1. Interviews—Wave 1

In the first wave of interviews, the participants were invited for an interview of approximately one and a half hours. They described their daily routines and uses of EV and answered questions related to the potential future use of a vehicle with V2G functionality (see the protocol in Appendix B). The interview data was coded by three researchers independently and cross-checked for a consistent analysis. Five tag groups were used for coding—individual values, household characteristics, daily/occasional routine, system level, and expectations on V2G.

The predefined tags were related to answering the research questions. The individual values category contained aspects such as positive and negative attitudes, fears and uncertainties, pain points, and potential positive outcomes related to V2G. The household characteristics category included demographic tags such as age, occupation, family, car brand and type of ownership, and what type of energy contract was used in the household. The daily/occasional routine category contained behavioral tags connected to the daily life of the participants, how they charged their vehicles, how much, where, and how they drive, and what role the vehicle has in their daily life and for occasional trips. The expectations on V2G included tags on incentives, battery health, the need for minimum state of charge, and to what level of detail the participants require to control the charge/discharge algorithm and the related information flow. After the coding process was done, the material was clustered according to themes using the canvas function in the Reduct software (https://reduct.video/). The clusters were further reviewed by three researchers.

Eight EV drivers were interviewed; the age span was 35–65, two interviewees were women, and all except one participant lived in a detached house and had a parking space. In Appendix A,

Table A1. Profile of participants in wave 1 of interviews.

	J Male	D Male	A Female	JN Male	K Male	M Female	P Male	L Male
Car ownership	Owner	Owner	Owner	Owner	Leased	Leased	Leased	Leased
Household	2 adults, 3 children	2 adults	2 adults, 2 children	1 adult	1 adult	2 adults	3 adults	3 adults
Housing type	House	House	House	House	Apartment	House	House	House
Energy contracts	ToU (Hourly based)	ToU (Hourly based)	ToU (Hourly based)	ToU (Hourly based)	NA	Fixed	ToU (Hourly based)	ToU (Monthly based)
House’s energy system	Pellets	Heat pump, radiator and fireplace	Solar panels	Floor heating with an exhaust air heat pump	NA	NA	Solar panels	Heat pump
Commuting driving distances	Short	Long	Long	Long	Long	Long	Long	Long
Charging location	Home mostly	Home only	Home mostly	Home mostly	Public	Home mostly	Home—sunny days	Home mostly
Minimum SoC	30%	60%	60%	40%	NA	NA	NA	NA
Other modes of transport	Active commuting	None	Active commuting	None	None	None	Active commuting	None
Battery degradation	Not much concerned	Concerned	NA	Not much concerned	Concerned	Concerned if private owner	Concerned	Not much concerned

presents a summary of characteristics of the participants in terms of car ownership, household profiles, housing characteristics (type, electricity contracts, and energy systems), charging patterns and locations, use of alternative modes of transport, concerns about battery degradation, and overall self-evaluations of how much weather affects their travelling habits. The identified themes from the first wave interviews shaped the interview structure and incentive offers of the second wave interviews.

2.2.2. Interviews—Wave 2

In the second wave of interviews, seven participants with EVs were invited to a 30-min online interview. The participants were particularly selected according to gender, EV experience, interest in new technology, family and household configuration, and mobility pattern. Before the online interviews, the participants were pre-interviewed in their homes to build a detailed profile background about their routines, charging preferences, and attitudes to technology. Then, in the following online interview, they were exposed to five different offers of parking, provided that they would make their vehicles available for V2G services while parked at two different locations: Location L and Location T (for a description of participants’ profiles from wave 2, see Appendix A,

Table A2. Profile of participants in wave 2 interviews.

	SK Female	PL Female	NÅ Female	CU Male	NH Male	MW Male	CE Female	MH Male
N Cars	3 (2 BEVs)	1 BEV	2 BEVs	2 (1 BEV)	2 (1 BEV)	2 (1 BEV)	Leased	2 BEVs
Household	2 adults with teens	2 adults	2 adults with teens	2 adults with children	2 adults with teens/children	2 adults with children	2 adults with children	2 adults with teens/children
Housing type	House	Apartment	House	House	House	House	House	House
Energy contracts	ToU (Hourly + power tariff)	ToU (Monthly)	ToU (Hourly + power tariff)	ToU (Hourly + power tariff)	ToU (Monthly)	ToU (Hourly)	ToU (Monthly)	ToU (Monthly + power tariff)
Charging set up	Wallbox	Wallbox	Wallbox	Wallbox	Wallbox	Wallbox + solar +battery	Wallbox	Wallbox + solar
Commuting (km)	40	10	20	15	20	15	70	60
Charging location	Home mostly	Home mostly	Home only	Home only	Home only	Home only	Home and Workplace	Home only

). Location L is a business area in Gothenburg, Sweden, where parking is provided by different fees and contracts with parking operators; Location T is an enclosed private area where parking is free for employees. The participants of wave 2 were employees of the organization partner of the research project.

The participants were asked to rank the offers based on their preferences and explain why they chose that particular order (see the protocol in Appendix B). The offers presented to the participants were based on the premise that, provided that the EV would be available for V2G services during a certain period and under a certain agreement, a benefit would be exchanged for this availability, and the benefits were classified into 5 offers (for visual representation of the offers, see Appendix A, Figure A1). The offers were:

A—Cheaper charging: This offer provides discounts for charging.

B—Point system: This offer includes a system of credits and points that the EV user could collect and exchange for other products and services.

C—VIP parking: This offer provides a parking spot with a better location (in terms of proximity to the final destination, better availability, and size/comfort).

D—Cheaper parking: This offer provides a discount for parking (not applicable at Location T; the participants from this location were asked to base their answer on locations where they typically pay for parking).

E—Selling electricity/capacity: This offer gives the possibility for the EV user to sell electricity/capacity to the grid and therefore receive direct monetary incentives.

In summary, the methodological structure was designed to address the research questions using diverse instruments: an online survey, interviews focused on users’ daily routines in the first wave, and visual prompts to evaluate incentive model preferences in the second wave. The survey aimed to capture an overall evaluation of users’ expectations, fears, uncertainties, and perceived efficiency. While the survey reached a larger sample and focused on cognitive evaluations and user attitudes, the same themes were explored in the first wave of interviews with a more detailed perspective on participants’ daily routines, household dynamics, and the reasoning behind their preferences, attitudes, and expectations. These two approaches were intended to gather information relevant to RQ2. To address RQ1, the second wave of interviews focused on offers with different incentives for participating in V2G services while parked in public spaces.

3. Results

This section is divided into the results from the survey and the results from the interviews.

3.1. Results from the Survey

The results of the survey study are divided into two subsections. First, a factor analysis was performed to identify the underlying factors that build the evaluation of V2G by the EV users. Three factors were identified: Sustainability, Efficiency, and Uncertainties. This result is presented under the Factor Analysis Subsection. Following this, these three factors were used as outcome variables in multiple linear regressions in which the socio-demographic variables were used as predictors. The objective of this analysis was to identify societal groups that could be associated with the different factors of evaluation of V2G. For example, with these regressions, one may identify associations between different types of household profiles and the extent to which they value the sustainability of V2G, or for example, identify if there are certain groups that have higher levels of uncertainties towards V2G. These results are presented in the Linear Regression Models Subsection.

3.1.1. Factor Analysis

Three components were extracted in a Principal Component Analysis (PCA) with Oblimin rotation; RMSR = 0.03; TLI = 0.93; RMSEA = 0.076, with 90% CI [0.058, 0.094]. The three components accounted for 61% of the total variance. The scale of expected outcomes was then defined into factors of “Sustainability”, “Efficiency”, and “Uncertainties” as underlying factors of cognitive evaluation of V2G technology. All three dimensions presented satisfactory levels of reliability. The items, components’ loadings after rotation, and reliability tests (Cronbach’s alpha, α) are shown in Appendix A,

Table A3. Obliquely (oblimin) rotated principal components loadings of ratings of Sustainability, Efficiency, and Uncertainties evaluations of Vehicle-to-Grid (V2G).

	Sustainability (std. α = 0.77)	Efficiency (std. α = 0.85)	Uncertainties (std. α = 0.85)
“I believe that the use of renewable energy will increase”	0.58	0.22	−0.09
“I believe that parked cars will be better used if connected to V2G”	0.96	0.25	−0.11
“I believe that the energy prices on the market will decrease”	0.24	0.80	−0.16
“I believe that the risk of power outages will decrease”	0.25	0.81	−0.15
“I believe that the need for energy production will decrease”	0.11	0.71	−0.01
“I would fear that I would not have sufficient range to complete my transport needs”	−0.05	−0.15	0.71
“I would be afraid that battery life would be shorter than without bidirectional charging”	−0.04	−0.07	0.60
“I would expect an increase of charging failures on public spaces”	−0.16	−0.09	0.62
“I fear that V2G will add complexity to planning the charging of my vehicle”	−0.05	−0.06	0.84
“I will lose some control of charging my electric vehicle”	−0.07	−0.01	0.83
Cumulative Variance explained	0.27	0.20	0.14

Loadings with std. α values over the threshold 0.3 are highlighted in bold text.

.

3.1.2. Linear Regression Models

To determine the effect of socio-demographic variables on the three dimensions of expected outcomes from V2G, meaning the three dimensions extracted from the PCA, “Sustainability”, “Efficiency”, and “Uncertainties”, three multiple linear regressions were modelled, with the dimensions as dependent variables and the socio-demographic variables as independent variables. The prediction of each dimension was based on car type (Internal Combustion Engine (ICE), Plug-in Hybrid Electric Vehicle (PHEV), Battery Electric Vehicle (BEV)), gender, age, electricity plan (variable rate hourly, variable rate monthly, or fixed rate), and housing (house, rented apartment, or owned apartment) (see

Table 1. Multiple linear regression analyses with the variables Sustainability, Efficiency, and Uncertainties as outcomes and socio-demographic variables as predictor variables.

	Sustainability			Efficiency			Uncertainties
	ß (SE)	t	p	ß (SE)	t	p	ß (SE)	t	p
Car type ICE	−0.45 (0.24)	−1.86	0.063	0.56 (0.23)	2.46	0.014	−0.27 (0.23)	−1.15	0.248
Car type PHEV	−0.28 (0.23)	−1.17	0.241	0.42 (0.22)	1.86	0.062	−0.17 (0.23)	−0.72	0.468
Gender (woman)	−0.33 (0.14)	−2.25	0.024	0.31 (0.13)	2.23	0.026	−0.25 (0.14)	−1.78	0.075
Age (26–35 years)	−0.13 (0.56)	−0.23	0.817	−0.12 (0.53)	−0.23	0.813	−0.44 (0.55)	−0.80	0.420
Age (36–45 years)	−0.33 (0.56)	−0.59	0.554	0.13 (0.53)	0.24	0.803	−0.58 (0.55)	−1.06	0.289
Age (46–55 years)	−0.33 (0.56)	−0.59	0.552	0.37 (0.53)	0.69	0.487	−0.50 (0.55)	−0.91	0.359
Age (56–65 years)	−0.53 (0.56)	−0.93	0.348	0.39 (0.54)	0.72	0.468	−0.65 (0.56)	−1.16	0.244
Age (66+ years)	0.35 (1.09)	0.32	0.745	−0.78 (1.04)	−0.75	0.450	−1.23 (1.07)	−1.14	0.253
El_plan Others	−0.25 (0.29)	−0.86	0.389	−0.13 (0.27)	−0.49	0.617	−0.08 (0.28)	−0.30	0.764
EL_plan Variable rate (hourly)	0.35 (0.13)	2.62	0.008	−0.21 (0.12)	−1.67	0.094	0.13 (0.13)	0.99	0.322
EL_plan Variable rate (monthly)	−0.11 (0.13)	−0.84	0.400	−0.03 (0.12)	−0.28	0.776	−0.19 (0.13)	−1.49	0.136
Housing_Rented apartment	−0.05 (0.17)	−0.28	0.776	0.25 (0.16)	1.53	0.125	−0.14 (0.17)	−0.81	0.418
Housing_Owned apartment	−0.34 (0.16)	−2.08	0.037	0.38 (0.15)	2.45	0.014	−0.00 (0.16)	−0.02	0.977
Housing_Other	1.06 (0.98)	1.08	0.279	−0.75 (0.93)	−0.81	0.417	0.06 (0.96)	0.06	0.948
Model	R2 adju = 0.08, F(14, 369) = 3.5, p < 0.001			R2 adju = 0.07, F(14, 369) = 3.07, p < 0.001			R2 adju = 0.01, F(14, 369) = 1.48, p = 0.112

).

For the regression model for Sustainability, the coefficients for gender, housing, and electricity contracts presented values under the significance level. Women (ß = −0.33, p = 0.024) and people living in apartments that they own (ß = −0.34, p = 0.037) had a negative association with the sustainability aspects of V2G, while users who have hourly based electricity contracts had a positive association (ß = 0.35, p = 0.008).

For the regression model for Efficiency, the coefficients for gender, housing, and car type presented values under the significance level. Women (ß = 0.31, p = 0.026), people living in apartments that they own (ß = 0.38, p = 0.014), and drivers of ICE cars (ß = 0.56, p = 0.014) had positive associations with aspects related to the efficiency of V2G.

For the regression model for Uncertainties, any of the tested socio-demographic variables presented values under the significance level.

3.2. Results from the Interviews

3.2.1. First Wave Interviews

In the first wave of interviews, the following themes were identified as critical for the acceptance of V2G technology in the everyday life of the interviewees: Convenient and resilient home, minimum range for emergencies, fear of battery degradation, trust in system providers, economic and social incentives, user preferences, and need for control. Following this, each theme is described, and quotes are provided to exemplify the themes.

• Convenient and resilient home

Most of the participants stated that home charging is their main way of charging. There are strong routines related to the commute journey and charging the car when coming home from work, and it is important that the charging can be performed in a convenient way. Apparently, connecting the vehicle for short periods of charging, e.g., at a supermarket, does not seem to be needed or of interest for many of the participants, unless the vehicle’s SOC is very low. Home resilience, i.e., the idea of using the car as a source of backup electricity in case of power outages, is also mentioned as an interesting and valuable feature, although very few have actually tried it in practice.

“We have a charging box at home. So, we always charge at home. I’ve charged away from home once in a year, so I have the habit of plugging in and charging every time we come home.”

Participant M.

“No, it’s the same thing there. In that parking lot, there are charging stations, but since they are from an external provider, I feel it’s too complicated for me to connect the car, charge it so that I maybe have a driving range of two miles. And then I go home again. It’s way too complicated. So, I just park.”

Participant K.

• Minimum range for emergencies

The minimum range left in the vehicle is an important concern for all participants. However, the number of kilometers varies greatly depending on the daily life of the vehicle owner and the family’s routines. For example, one participant mentions sick relatives in combination with living in the countryside as a concern with an impact on the minimum range needed for potential emergencies. For others, a lower SOC level is acceptable but can vary with weekly routines.

“If I’m driving only in the city, but still, I will want to charge it when it’s like close to 60–50 km [Remaining range]. That’s when I feel like I need to charge. But my husband usually let it go to like 30 km. He said, “yeah, but we don’t need to charge it”. “Yes, we do.”

Participant A.

“That it never discharges more than 50% [Battery level]. But I could allow it to discharge down to 20%, provided that by the time I need to leave, it is back to at least 50%.”

Participant JN.

• Fears of battery degradation

There is an apparent fear of economic loss related to the hypothetical question of possible battery degradation when increasing the number of charging cycles due to V2G services. The participants seem aware of the value of a non-degraded battery to maintain the vehicles’ value on the second-hand market. Different types of economic compensation for battery degradation were discussed. Battery insurance from the V2G service provider was also suggested to reduce the fear of battery degradation by relieving the battery ownership responsibility. Another aspect mentioned is the possibility of selling the battery in the second-life market.

“So, if I had owned the car, I would definitely have been more worried about the wear and tear on the battery. Eh, because then I would have invested in the car in a different way.”

Participant M.

“I need to be sure somehow that doesn’t affect too much, doesn’t degrade too much.”

Participant D.

• Trust in the system/providers

There are many actors in the V2G ecosystem, such as electricity-, grid-, parking-, car leasing companies, etcetera. Some participants mention the need to have trust in the service providers and stakeholders setting out the rules and prerequisites for V2G services. The vehicle owner’s engagement is crucial for enabling V2G capabilities, and participants state a fear of being exploited, i.e., someone else making a profit on their engagement and effort, rather than contributing to society and sustainable energy production.

“It’s less likely that they’re going to be working [Public charging]. So you run into ones where the screen doesn’t work or the payment system doesn’t work and you have to download a new app and it’s kind of frustrating thing.”

Participant J.

“Yeah, because I mean, that from, I think that is one if you look at the society as a whole and then, the aspect of bidirectional becomes more relevant to me if it’s clear how it’s being used and if it’s being used as a benefit to society, then I would be more likely to use it rather than if I just, ok, it’s some electrical company who has some sort of gain, then I would be less interested for my liking”

Participant K.

• Economic and social incentives

Most participants express economic incentives as a key driver to become involved in V2G services. Incentives of interest can be purely economic, as in getting paid for the energy fed back to the grid or the power used for frequency balancing. Other economic rewards can also be cut in parking costs. There is also an interest in convenience rewards, such as a parking spot closer to the office building. Social incentives are also mentioned as important drivers, e.g., helping the grid from a societal or environmental perspective.

“One would like to see perhaps the needs of the grid if one can somehow predict it. When will the next need arise? Uh, in time, so one might be able to adapt oneself. Okay. Yes, but then one might be able to park here and help out, right?”

Participant P.

“And then it is the case that when I have looked at charging in places other than at home, I have never seen dynamic prices there, but it is the same price regardless of when I would charge. And since those prices are significantly higher than what I charge at home, it is not interesting because it [home charging] take me back and forth. It is more of an emergency solution.”

Participant JN.

• User preferences and need for control of V2G services

Everyone expressed some basic needs for a charging status at a glance and controls to be able to set up their preferences for the type of charging and minimum charge level. Some expressed a need for more detailed information on the energy flow, historically, now, and as forecast. This was mentioned to be needed to be able to build trust in the service or provide fun facts about the usage.

“I want to see the numbers and the values and build trust for the numbers and the estimations. And when I get an idea of how much error there is in the estimations”

Participant D.

“I always sort of connect [Charging cable] and then normally it will be used either as a vehicle to grid or charging or whatever. Yeah. As long as it doesn’t go below my threshold [minimum battery level]. But I always want the possibility to say, ah, today I want something else.”

Participant L.

3.2.2. Second Wave Interviews

In the second wave of interviews, it was identified that convenience and clarity of the business offer for participating in V2G services in public spaces were the main drivers of choices.

“Yes, I’m probably too comfortable there. I had counted it out first. Time is too big a factor rather than this [selling energy V2G offer] to think about. Because then I need to know what my price is right now. It’s not worth the effort.”

Participant SK.

The choices were also influenced by their current parking conditions; the participants from Location T (free parking at workplace) rated the offer with cheaper charging as their favorite, while the ones who are currently paying for parking at Location L had the cheaper parking offer as their top-rated offer.

“This one [Cheap charging] is absolutely interesting… Then the other can charge at home, so you don’t have to worry about whose turn it is to charge.”

Participant SK.

“Yes, I like that idea [Cheap Parking]. Because you could apply it not only at work, but I can still see it in front of me when you go to a football game in Ullevi or something else.”

Participant NA.

Table 2. Ranking of Vehicle-to-Grid (V2G) offers in public spaces by participants from two different locations.

	Location L				Location T
Offer	NH	CU	NA	Total	PL	MH	CE	SK	Total
A—Cheaper charging	3	1	3	7	5	3	4	5	17
B—Point system	1	3	1	5	1	4	2	2	9
C—VIP parking	4	2	2	8	3	1	5	4	13
D—Cheaper parking	5	4	5	14	2	2	3	3	10
E—Selling electricity/capacity	2	5	4	11	4	5	1	1	11

Location L (paid parking at workplace); Location T (free parking at workplace).

shows the ranking of each offer by each participant. The rows present the ranking number (from 1—least preferred to 5—most preferred) for each participant (named with fictional letters by columns). Each offer has a total score indicating the degree of preference; the higher the score, the more preferred by the participants. The participants are grouped by the locations where they park their cars at their workplace.

The participants favored models that were easy to understand and use. Cheaper charging and parking fee discounts were consistently ranked high due to their direct and predictable benefits. The VIP parking was also quite favored by the participants parking at Location T, as arriving late to work at this location often meant a need for a lot of extra time to search for an available parking slot, which was often only available far away from the office location. The VIP parking offer was also expected to provide a more spacious slot for one of the participants.

“Spontaneously, I think it’s interesting. Time is a factor that is not to be underestimated. So this one close by [VIP parking] is easy. Then I’m also a bit picky when it comes to too tight parking spaces, for example. I usually park at the far end where no one else parks just so I don’t have to mess with it.”

Participant SK.

The selling of electricity/capacity offer was polarizing; some found it attractive for financial gain; others saw it as too complex or disruptive.

“This one is the most attractive to me [Selling electricity]. I would go for this one in that case. … Then I can discharge out 50%. In that case, I would have calculated it a bit and tried to charge at home overnight in that case and then discharged during the day.”

Participant MH.

“This one is [Selling energy] …, now you know me. This is where my laziness comes in. This was too many parameters for me to try to keep track of for me to think that this feels, yes”.

Participant CE.

The offer with a point system to collect credits was the least favored due to concerns about complexity and unclear value and ranked the lowest for both parking groups of participants.

“But there [Point system], the business case is a little fuzzier. What is it? It’s not real money?”

Participant PL.

4. Discussion

This study set out to examine electric vehicle (EV) users’ willingness to participate in V2G services in public charging environments, with particular attention to incentives, perceived benefits, and behavioral constraints. By focusing on public settings and anchoring user decision-making in everyday routines, the findings directly address the research gap identified in the introduction and extend the existing V2G literature that has largely emphasized technical feasibility and home-based contexts.

The results demonstrate that users’ evaluations of public V2G services are strongly shaped by convenience, clarity, and perceived control. These findings align with earlier studies showing that user acceptance of V2G depends not only on financial compensation but also on how well services fit into existing charging and parking practices [1,2,3,4]. Similar to findings previously reported [4,18,23], users in this study expressed a preference for V2G participation at home, where charging already occurs as part of daily routines, rather than locations requiring additional effort or behavioral change, in this case, the workplace.

As discussed in the introduction, home charging remains the dominant reference point for EV users, and expectations formed in this setting appear to influence how public V2G offers are evaluated. The practices of home charging, the perception of charging availability, and satisfaction with charging infrastructure are different between drivers living in detached houses and apartment buildings [26].

The linear regression models showed that both women and apartment owners exhibited a negative association with the sustainability aspects of V2G, despite demonstrating positive associations with its efficiency aspects. Because this study did not employ a controlled experimental design, it is not possible to determine whether these associations reflect true underlying characteristics of the sample or the influence of unmeasured confounding variables. Within the interpretive limits of the present design, one plausible explanation aligns with the existing literature, indicating that environmental and climate concerns play a stronger role in women’s transport choices than in men’s, often guiding them toward public transport and other non-automobile modes that collectively reduce environmental impact [27]. From this perspective, car use— even when the vehicle is electric—may be perceived as less sustainable compared to alternatives such as public transport, walking, or cycling. Another consideration requiring further investigation concerns the documented gender gap in digital inclusion and its potential effect on women’s sensitivity to issues such as data privacy and technological uncertainty regarding adopting V2G [28].

For apartment owners, a potential explanation of this effect is that residents of multi-dwelling buildings often live closer to daily amenities, workplaces, and educational institutions. Such proximity is associated with travel patterns characterized by greater use of walking and cycling, reduced reliance on driving, and lower vehicle-kilometers traveled (VKT). When these individuals evaluate V2G or EV use, they may compare it not against conventional car driving but against their own low-carbon baseline of active and public transport modes, leading to a perception of V2G as less sustainable within their context [29]. However, further research is needed to assess whether this reasoning holds across different residential contexts and populations.

The linear regressions also indicated that drivers of ICE cars showed positive associations with V2G’s efficiency aspects, while individuals with ToU electricity contracts had positive associations with V2G’s sustainability aspects. This supports earlier research suggesting that household energy practices and electricity contract types shape users’ openness to flexibility services more broadly [7,8]. Users familiar with time-based electricity pricing and active energy management were more likely to view V2G as understandable and potentially beneficial, reinforcing the role of prior experience and learning effects identified in demand flexibility research [7,8].

Consistent with previous V2G studies, economic incentives were found to be important but not sufficient on their own to motivate participation in V2G services in public spaces [2,3,10]. Users showed a clear preference for simple and transparent incentives, such as reduced charging or parking costs, over more complex remuneration schemes. This finding echoes earlier work highlighting that complexity and uncertainty can undermine perceived fairness and reduce willingness to engage in flexibility services [11,12,13].

Beyond monetary compensation, trust emerged as a critical factor influencing acceptance. Concerns related to battery degradation, loss of control, and unclear responsibilities among service providers mirror barriers identified in earlier V2G trials and pilot studies [14,15,16]. These results reinforce the argument that V2G services at public spaces must be designed not only as technical solutions but also as socio-technical systems in which transparency, contractual clarity, and user autonomy are central design principles.

In this study, concerns related to battery degradation, loss of control, and charging failures were captured within the latent variable Uncertainties. However, the survey results did not reveal any associations between socio-demographic predictors and this dimension. It therefore remains unclear whether different groups perceive these uncertainties differently. One possible explanation is that the scale’s items assessing Uncertainties combined aspects at the individual level, such as loss of control, with aspects outside the individual’s locus of control, such as charging failures in public spaces. Further refinement and development of these scales may yield clearer results and potentially improve model fit.

Overall, the findings contribute to the broader discussion on the decentralization of energy systems by empirically demonstrating how individual users become active actors in flexibility provision. As outlined in the introduction, V2G represents a shift from centralized control toward user-centered energy systems. However, the results suggest that this shift is contingent on aligning system design with users’ everyday constraints and expectations. Without such alignment, the decentralizing potential of V2G risks remains theoretical rather than realized in practice.

From a policy and market design perspective, the results suggest that participation in V2G services at public spaces should prioritize locations with more predictable parking durations, clear user benefits, and low participation barriers. These insights complement system-level modeling studies by providing behavioral evidence that can inform more realistic assumptions about user participation rates and available flexibility.

Limitations

Several limitations should be acknowledged when interpreting the results. First, the study is based on self-reported data, which may be subject to social desirability bias and hypothetical bias, particularly regarding stated willingness to participate in future V2G services. While the mixed-method approach helped contextualize survey responses, actual behavior in real-world V2G deployments may differ.

Second, this study focuses on users within the Swedish regulatory context characterized by relatively high EV adoption, widespread smart metering, and increasing exposure to time-based electricity pricing. As a result, the findings may not be directly transferable to countries or markets with different tariff structures, charging infrastructure availability, or levels of user familiarity with energy flexibility.

A third important limitation concerns the composition of the sample. Recruitment was conducted within a single organization, which resulted in a relatively homogeneous group of respondents and interview participants. This narrow sampling frame restricts the diversity of perspectives represented in the data and limits the extent to which the findings can be generalized to the broader population of EV users. The gender imbalance in the survey—where 83% of respondents were male—further constrains the representativeness of the sample and may have influenced the patterns observed in attitudes, expectations, and perceived barriers.

In addition, public charging environments were assessed primarily through users’ perceptions rather than through direct observation of actual charging or plug-in behavior. While perceptions are central to understanding decision-making, they may not fully reflect real-world practices, especially in contexts where V2G participation is still emerging and unfamiliar to most users. The qualitative component of this study also relied on a small number of interview participants, which limits the depth and variability of experiences that could be captured. Together, these factors reduce the generalizability of the qualitative results and may have constrained the ability to detect meaningful differences across user groups.

Future research that integrates stated preference data with real charging and discharging data from public V2G pilots would provide a stronger foundation for understanding user behavior. As more pilot projects allow actual V2G participation, users will be better positioned to assess how V2G affects their everyday routines with an EV. Currently, most research is based on hypothetical scenarios, reducing ecological validity. As more empirical studies emerge on V2G participation in public settings, the knowledge base will expand, but for now, it remains limited. Despite these limitations, this study provides robust insights into user perspectives on public V2G participation and highlights key design considerations for scaling V2G services beyond the home environment.