1 Introduction

There are many reasons why electric bike sharing systems are becoming increasingly popular as a viable alternative to conventional forms of transportation in urban areas [1, 2]. To begin, electric bike sharing systems are a versatile and easy commuting option, particularly for navigating busy city streets and avoiding congestion [3]. Second, electric bikes help reduce air pollution in cities because they do not produce any emissions [4, 5]. Third, electric bike sharing systems encourage fitness and a healthy way of life by allowing people to make biking to and from work part of their daily routine [6].

Cities that are experiencing traffic congestion, air pollution, and a lack of inexpensive and sustainable transportation options would benefit greatly from electric bike sharing systems [7, 8]. Electric bike sharing systems have the potential to alter urban mobility and improve the quality of life for city dwellers by providing a more efficient and sustainable way of transportation [9]. It is crucial to understand the elements that contribute to a city's willingness to accept this innovative transportation solution, as adoption of electric bike sharing systems differs across cities and regions.

Electric bikes and scooters, as well as bike-sharing systems, are often used to facilitate first/last-mile connectivity to bus, tram, and metro stops. These systems cater primarily to unprotected road users, such as pedestrians and cyclists. Ensuring the safety of these users is critical. Recent studies have highlighted the factors influencing the severity of bicyclist injuries in crashes involving motor vehicles [10,11,12] and the risk factors associated with pedestrian deaths in such accidents [13, 14]. Therefore, it is essential to consider road traffic safety for these vulnerable groups when designing and implementing bike-sharing systems.

This study aims to determine whether Hungarian cities are prepared to adopt electric bike sharing systems by examining specific factors that contribute to the readiness of cities to adopt this mode of transportation. In this study, we analyze the impact of infrastructure, demographics, transportation options, and regulation on the spread of electric bike sharing programs throughout large Hungarian cities, as cycling has been gaining popularity in Hungary in recent years, with an increasing number of people using bicycles for commuting, recreation, and sport [15]. This study provides policymakers, city planners, and transportation providers in Hungary and beyond with useful insights by analyzing the factors that determine the readiness of cities to embrace electric bike sharing programs. The findings of this research have the potential to inform the creation of policies and tactics that can promote sustainable and efficient urban transportation networks, such as the widespread implementation of electric bike sharing systems.

This manuscript is organized into several sections. Following this introduction, the Literature Review outlines existing research relevant to electric bike sharing systems. The Methodology section details the approach for evaluating city readiness, followed by the Results and Discussion, which presents and interprets the findings. Finally, the manuscript concludes with a summary of key outcomes and suggestions for future research in the Conclusions section.

2 Literature review

In recent years, plenty of research has been put into examining the positive aspects of electric bike sharing systems [16, 17]. Chen et al. [18] and Zhang et al. [19] discovered that electric bike sharing systems can dramatically reduce CO2 emissions and air pollution in urban areas, in addition to promoting physical activity and reducing traffic congestion. In the same direction, the results of a study that was carried out in Velenje, Slovenia and presented by Bruzzone et al. [20] revealed that electric bike sharing systems can increase the accessibility and cost of transportation for groups that have low incomes. Other studies [21, 22] have emphasized the potential economic benefits of electric bike sharing programs, including increased tourism and employment generation.

A considerable amount of research has also been put into determining whether or not communities are prepared to embrace cycling as a mode of transportation. According to the findings of a study [23] that was carried out in the Portugal, the existence of cycling infrastructure, which includes things like designated bike lanes and facilities for parking bicycles, is an important element in the promotion of cycling as a means of transportation. Other studies [24,25,26] have shown the importance of demographic parameters like age, income, and education in determining the willingness of communities to adopt cycling as a mode of transportation.

One area that has been the focus of research is the degree to which urban areas are prepared to implement shared mobility solutions, such as bike sharing systems. According to the findings of Polydoropoulou et al. [27] that was carried out in three European metropolitan cities, one of the most important factors that will determine the success of shared mobility services is the regulatory environment. This includes the availability of permits and licensing criteria.

Additionally, the readiness of cities to adopt electric mobility has been a developing topic of research in recent years. According to the findings of Metaid et al. [28] and Pardo-Bosch [29], two of the most important elements in increasing the adoption of electric mobility services are the availability of charging infrastructure and the regulatory environment. According to the findings of another study that was carried out in Spain [30] discovered that the availability of electric mobility choices, such as electric bike sharing programs, can boost the adoption of electric vehicles and reduce emissions in urban areas.

Accordingly, to address the indicators in light of the literature, we summarize and present in the following elaboration on the significance of each indicator that has been included, supported by relevant literature references. Bike lane density and public bike parking facilities are crucial for the safety and convenience of cyclists. Studies have shown that cities with more bike lanes tend to have higher cycling rates, indicating that well-developed cycling infrastructure encourages more people to choose cycling as a mode of transport [31, 32]. Safety indicators, such as accident rates involving cyclists, are essential because high accident rates can deter potential cyclists, underscoring the importance of designing safe infrastructure to promote cycling [33, 34]. Demographic indicators like population density and age distribution are also significant. Higher population density often correlates with increased bike-sharing usage due to shorter travel distances, and younger populations are generally more inclined to use bike-sharing systems [35, 36]. Legislation indicators, including supportive cycling laws and government initiatives for cycling, play a vital role in enhancing the adoption of bike-sharing systems. Effective policies and supportive legislation create an environment conducive to cycling, further encouraging its uptake [37, 38]. Transportation system indicators, such as public transport connectivity, are critical for facilitating first-mile and last-mile connectivity, making bike-sharing a more viable option for urban commuters. Integration with public transport networks enhances the practicality and convenience of bike-sharing systems, thereby increasing their usage [39, 40].

This research aims to contribute to the existing literature by examining the readiness of cities in Hungary to adopt electric bike sharing systems, which per the researchers’ knowledge is the first one in this field to be conducted. By examining the specific factors that contribute to the readiness of cities in Hungary, this research can provide valuable insights for policymakers, city planners, and transportation providers in Hungary and beyond, and inform the development of policies and strategies that can promote sustainable and efficient urban transportation systems.

3 Methodology

This section describes the step-by-step approach used to collect and analyze data in order to achieve the research objectives. These steps are listed as follows:

Selection of Cities: Among all cities in Hungary, we have chosen the eight large cities in population (more than 100,000 inhabitants). These cities are distributed geographically all over Hungary and have potential for future growth as well, which provides a representative sample of cities in Hungary. The population of these cities form 28% of the total population of Hungary. The cities and their related population and area are presented in Table 1. In addition, the geographic distribution is shown in Fig. 1.

Table 1 Population and area of large Hungarian cities
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Fig. 1
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Geographical distribution of large Hungarian cities

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Next, compiling a comprehensive list of factors along with their respective definitions is important for evaluating the readiness of a city to adopt an electric bike-sharing system. These factors are determined based on the literature review, researchers' expertise, and data availability. Alongside, for each factor, we identified the indicators that are used to measure the factor. These indicators are specific, measurable, and relevant to the factor. This research identified 25 indicators. This selection is comprehensive and covers a wide range of factors. This adds to the strength and validity of the research. Table 2 elaborates the factors, their definitions, and the related indicators.

Table 2 Definition of factors and indicators used in the research
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The collection of data for the selected indicators for each of the eight selected cities in Hungary was obtained from various sources such as government reports, academic papers, and online databases. Table 3 elaborates the sources of each indicator:

Table 3 Sources of collected indicators
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To compare the eight cities using the identified indicators, we utilized normalization method. This involved dividing the lowest score by the highest score for each indicator, ensuring that all scores fell between 0 and 1. The average of the 25 normalized indicators was then calculated, providing a final score out of 1 for each city. This method follows a systematic and transparent way of scoring the cities based on a set of indicators. The use of two methods of normalization—one for positively related indicators and another for negatively related indicators—ensures that the scores are comparable and represent the readiness of the cities for each factor. Equation 1 describes the normalization method:

$$Normalized\ Score \ for \ City\ i \ on\ Indicator\ j = \left\{ {\begin{array}{*{20}c} {\frac{{\left( {Score\ for \ City \ i \ on \ Indicator\ j} \right)}}{{\left( {Maximum \ Score \ for \ Indicator \ j} \right)}}, Positive \ relation} \\ {\frac{{\left( {Minimum \ Score \ for \ Indicator j} \right)}}{{\left( {Score \ for \ City \ i \ on \ Indicator j} \right)}}, Negative \ relation} \\ \end{array} } \right.$$
(1)

The final score for each city is then calculated as the average of the normalized scores across all indicators. Equation 2 describes the cities final score:

$$Final \ Score \ for \ City \ i = \frac{{\left( {Sum\ of \ Normalized \ Scores \ for \ City \ i \ across \ all \ Indicators} \right)}}{{\left( {Number \ of \ Indicators} \right)}}$$
(2)

Following this, we added the process of ranking and weighting various indicators to assess city readiness for deploying an electric bike sharing system involved multiple steps with input from 15 experts in the field.

  1. 1.

    Expert ranking: initially, the experts were tasked with ranking 10 main criteria based on their importance in influencing city readiness. Each expert provided a ranking for each criterion on a scale of 100, where a higher score indicated greater importance. This allowed for the collection of diverse expert opinions on the significance of each criterion.

  2. 2.

    Weight calculation: after gathering all the expert rankings, average weights for each criterion were calculated. This was done by summing up the scores provided by all experts for each criterion.

  3. 3.

    Application of weights: the next step involved applying these calculated weights to the indicators listed in Table 5 of the study. Each indicator's score was multiplied by its corresponding weight. This multiplication adjusted the scores to reflect the weighted importance of each indicator, ensuring that more significant factors had a greater influence on the overall assessment.

These weighted indicators were integrated into the overall analysis. This integration allowed for a nuanced evaluation of city readiness, taking into account the proportional importance of each criterion as determined through expert consensus. The result was a comprehensive assessment where each factor's impact on readiness was aligned with its relative importance. This methodical approach ensured that the evaluation of city readiness for deploying electric bike sharing systems was both balanced and reflective of expert insights, providing a robust framework for decision-making.

In the end, we rank the cities based on their total score to determine their readiness to adopt electric bike sharing and analyze the results to identify each city's strengths and weaknesses in this regard. This is required to draw conclusions and make recommendations based on the analysis.

4 Results and discussion

In this section, the collected data are presented as indicators. Next, they are normalized, and then cities are ranked. Table 4 presents the 25 indicators used in this study to assess the readiness of the eight Hungarian cities to adopt an electric bike-sharing system. It is noticed that the cities vary among all the indicators.

Table 4 Assessment of the indicators for the 8 cities
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Following that, the normalized values are shown in Table 5. The green colors represent the score of one, while the red colors represent the score of zero. The normalization process was used to standardize the values of the indicators, with 1 indicating the highest value and 0 indicating the lowest value. The normalized values were then used to calculate the overall scores for each city, as described in the following section. Noting that there are positive and negative factors; factors of 4 (unpaved roads), 10 (passengers’ cars per 1000 inhabitants), 18 (rainy and snowy days), 19–22 (Safety indicators), and 23 (living cost index).

Table 5 Normalized values for the indicators used in assessment of the eight cities
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To address the issue of additivity and equivalence, we employed an expert judgment approach to assign weights to the indicators. Fifteen experts in the field of urban transportation and sustainable development were consulted to rank the importance of each indicator. The final readiness scores were calculated by multiplying each indicator by its assigned weight and summing the results for each city. This approach ensures that the most critical factors have a greater influence on the overall readiness score, providing a more accurate representation of each city's preparedness for implementing a shared electric bike system. Participation in the survey was voluntary. They ranked the criteria levels C1 through C10 as presented in Table 6. The criterion values reveal that C1 (Existing infrastructure), with a score of 0.820, holds the highest position in the ranking, while C7 (Climate) has the lowest criterion value of 0.463. Following this, we have multiplied the scores of each indicator with the normalized values from Table 5 to get the weighted values for the indicators used in assessment of the eight cities as shown in Table 7.

Table 6 Ranking the main criteria
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Table 7 Weighted values for the indicators used in assessment of the eight cities
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In summary, the final scores and ranking of the cities are presented in Table 8. The rankings reflect the overall readiness of each city to adopt an electric bike-sharing system, with higher scores indicating greater readiness. The results show that Budapest is the readiest city to deploy electric bike sharing system in Hungary with a score of 0.903, while Nyíregyháza and Kecskemét are the least with a score of 0.422, and 0.419 respectively. Gyor in the second place, followed by Szeged. The fourth, fifth, and sixth ranked cities are Miskolc, Pecs, and Debrecen, respectively.

Table 8 Final Scores and rank for the cities
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The analysis revealed the readiness level of the eight Hungarian cities for electric bike sharing. The findings provide a comprehensive understanding of the current situation and can inform policy decisions and interventions to improve the sustainable transport options in these cities. The following section present a detailed analysis of each city's readiness level and identify the strengths and weaknesses of their active mobility infrastructure and policies.

4.1 Budapest

Budapest has shown a strong readiness to adopt electric bike sharing systems, with a high score in most of the indicators. As it has already well established bike sharing system, its score highlights the readiness of deploying the electric bike sharing system. However, there is still room for improvement in areas such as safety concerns in road accidents, and buses fleet.

4.2 Debrecen

Even the city is the second populated in Hungary, but its rank is sixth among the large Hungarian cities. Debrecen has a relatively low score in most of the indicators, indicating a low readiness to adopt electric bike sharing systems. The city faces challenges in areas such as the availability of cycling infrastructure and culture, public transportation, and regulations. However, there are opportunities for improvement through targeted policies and investment.

4.3 Szeged

The third populated city in Hungary has a moderate to high level of readiness to adopt electric bike sharing systems, with a relatively balanced score across the indicators. While the city has an excellent demographic profile that contributes to interesting potential of deploying the electric bike sharing system, there is still a need for more investment in public transportation, infrastructure, and cycling-related facilities and public awareness campaigns.

4.4 Miskolc

Miskolc has demonstrated a moderate readiness to adopt electric bike sharing systems, with a relatively balanced score across the indicators. The city has a good profile to future implementation of the electric bike sharing system in demographics, safety, and some infrastructure indicators. On the other hand, there is still a need for more investment in cycling-related facilities, public transportation network, and public awareness campaigns.

4.5 Pecs

The City of Pecs has a moderate level of readiness to adopt electric bike sharing systems, with a relatively lower scores across the indicators. While the city has good buses network, bike sharing program, good weather, and preferable living cost, it needs to make significant progress in cycling network, trams network, safety, and bike stations.

4.6 Gyor

Unexpectedly, Gyor has shown a high level of readiness to adopt electric bike sharing systems, with a strong score in several indicators; even it is the sixth populated city. Indicators such as roads infrastructure, shared mobility programs, demographics, and regulations make the city in advanced rank for future implementation of electric bike sharing system. However, the city should invest in trams network, and road hotspots.

4.7 Nyíregyháza and Kecskemét

Both cities have a relatively low score in most of the indicators, indicating a low readiness to adopt electric bike sharing systems. The cities face challenges in areas such as public transportation network, cycling culture, and regulations. Positively, both cities have strong points in sidewalks development, young age, weather, and living cost, which make these cities have also potential for shared electric mobility.

5 Conclusions

This study investigated whether or not the large eight Hungarian cities are prepared to implement environmentally friendly modes of transportation such as electric bike sharing system. It is found that certain cities such as Budapest and Gyor are better prepared for sustainable transportation than others by assessing 25 factors relating to infrastructure, safety, demographics, legislation, and transportation systems. The expert-driven weighting approach not only refined our assessment but also highlighted critical areas for urban planning and policy intervention. According to the findings of our research, the degree to which individual cities are prepared to implement environmentally friendly modes of transportation varies greatly; likewise, every city has both positive and negative aspects. In general, the establishment of infrastructure for cycling and should be given top priority in Hungarian cities. Additionally, connectivity to public transportation systems needs to be improved. The cities should implement safety action plans in their roads network. The culture of cycling and scootering, as well as, electric vehicles should be demonstrated.

Our findings offer important new perspectives to researchers and policymakers interested in environmentally responsible transportation, as well as to urban planners and urban designers. Having said that, this study does have a few limitations that ought to be addressed in subsequent research. First, the findings of this study may not be generalizable to other countries or regions. The specific context of Hungarian cities, such as infrastructure, policy environment, and cultural factors, may limit the applicability of the results to other settings. Second, the methodology used to calculate the scores and indicators may involve some level of subjectivity as we assigned similar weights for all indicators. Finally, the analysis of the readiness of cities for electric bike sharing was done based on data collected until 2021. Thus, the results may have changed over time, and the readiness of cities may vary. This study, despite its limits, makes a contribution to the knowledge of the readiness of sustainable mobility in Hungarian cities and provides a platform for additional research in this field. According to the findings, one of the most important things that can be done to promote sustainable mobility in metropolitan areas is to take an all-encompassing strategy that takes into account a variety of elements, such as policies, infrastructure, and usage. We have high hopes that our research will be able to lend support to ongoing efforts to make cities in Hungary and abroad more livable, sustainable, and resilient.