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Article

Environmentally and Socially Sustainable Behaviors of Generation Z in Poland Stimulated by Mobile Applications

by
Ewa Jaska
1,
Agnieszka Werenowska
2 and
Agata Balińska
1,*
1
Institute of Economics and Finance, Warsaw University of Life Sciences, 02-787 Warsaw, Poland
2
Management Institute, Warsaw University of Life Sciences, 02-787 Warsaw, Poland
*
Author to whom correspondence should be addressed.
Energies 2022, 15(21), 7904; https://doi.org/10.3390/en15217904
Submission received: 24 September 2022 / Revised: 21 October 2022 / Accepted: 23 October 2022 / Published: 25 October 2022
(This article belongs to the Special Issue Conditions and Changes in Energy Consumption)
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Versions Notes

Abstract

:
The aim of this study was to identify environmentally and socially sustainable behaviors and explore the role of mobile applications in encouraging them among young residents of Poland. The study involved a literature review and a survey carried out on a sample of 772 representatives of Generation Z (through the use of CAWI method). The collected material was subjected to quantitative and qualitative analyses involving factor analysis and statistical tests. The analysis of the obtained dataset shows that there is a significant difference between pro-environmental behaviors assigned to the following areas: (I) purchasing activity enhanced by visual identification, (II) sustainable consumption, (III) behavior stimulated by legal regulations and economic factors. The research revealed a statistically significant difference between the sustainable behaviors of men and women, and a slight difference between the behaviors of people from different places of residence and with different levels of income. It was also shown that respondents using the three analyzed mobile applications: Vinted (an online marketplace and community that allows its users to sell, buy, and swap new or secondhand items, mainly clothing and accessories), Veturilo (an app for users of city bike system) and GdzieWyrzucić (an app helping with waste sorting) rated their pro-environmental activities significantly higher in almost all areas covering socially and environmentally sustainable behaviors.

1. Introduction

Environmentally and socially sustainable behavior is nowadays the topic of public debate and numerous scientific studies. This was inspired, inter alia, by the Sustainable Development Goals announced by the United Nations in 2015 with a vision lasting until 2030. Promoting the principles of sustainable development in Poland is also the underlying aim of the document prepared by the Ministry of the Environment in 2019 entitled: “State Environmental Policy 2030” (Polityka Ekologiczna Państwa-PEP 2030). The goals listed there include ensuring sustainable consumption and production patterns and taking action to combat climate change.
The topic of climate change has recently been explored not only in scientific studies and analyses of various organizations, such as the New Climate Institute, but was also discussed during the Climate Summit in Glasgow (31 November, 12 October 2021) and the G7 Summit (Cornwall, 11–13 June 2021) [1]. Intensive works are being carried out at the European Union level, including regulatory work (e.g., the European Green Deal, a new strategic agenda for the EU 2019–2024) [2], the aim of which is to reduce greenhouse gas emissions in the EU by 2030 by at least 55% compared to the 1990 level [3]. This goal should be reflected in the National Recovery and Resilience Plans prepared by EU member states to mitigate the economic and social impact of the COVID-19 pandemic.
The undertaken pro-environmental actions are assessed by Germanwatch and the NewClimate Institute. One of the tools for tracking the climate protection performance is the Climate Change Performance Index (CCPI) which covers 57 countries, including European Union countries, which together are responsible for approx. 90 percent of global greenhouse gas emissions. The CCPI takes into account greenhouse gas emissions (40%), renewable energy (20%), energy use (20%), and climate policy (20%) of a given country. “As an independent monitoring tool it aims to enhance transparency in international climate politics and enables comparison of climate protection efforts and progress made by individual countries” [4].
In 2021, the highest value of the index was recorded in Sweden (CCPI = 74.42), and the lowest in the United States (CCPI = 19.75), which placed this country on the 61st position. Poland was ranked 48 in the cited ranking (CCPI = 38.94) [5] and, similarly to Hungary, is an example of an EU country where environmental policy should be intensified. Such actions should be accompanied by bottom-up initiatives supported by legal and political solutions. That is why it is so important to build environmental awareness and shape socially and environmentally responsible attitudes by promoting the principles of sustainable development and responsible consumption [6]. This goal should be supported by scientific research aimed at recognizing environmentally and socially sustainable behaviors and the role of mobile applications in encouraging them. The authors of this study addressed this problem by carrying out empirical research on a sample of young residents of Poland.
The rest of the article is organized as follows: Section 2,“Literature review”, discusses the literature on socially and environmentally responsible behavior and hypothesis development. Section 3,“Materials and Methods”, discusses the methods used and the process of the study. Section 4, “Results,” presents the results of the study, which are shown in tables, graph and comments. The discussion of results is separated into (i) “Analysis of socially and environmentally sustainable behavior”, (ii) “Differences in the results of the behavior areas due to the independent variables”, (iii) “Differences in the results of behavior areas and the recognition of individual applications”. Section 5 includes a scientific discussion. Section 6 presents a discussion of the summary of the research results. It includes theoretical implications, practical implications, limitations and future research.

2. Literature Review

2.1. Theoretical Background

2.1.1. Sustainable Behaviors and Consumption

Consumer equilibrium (a state of maximum satisfaction) is a well-known economic concept. It is a key category of consumer utility theory [7] which explains why an individual chooses a given combination of goods and services with a certain level of satisfaction. The utility function enables an identification of the relationship between the combinations of different components of the product and the utility achieved through its consumption. Consumer behavior is characterized by utility maximization, contrary to the behavior of providers of goods and services who maximize profit. Unfortunately, satisfying consumer needs while maximizing utility leads to adverse environmental effects, including climate change. Therefore, it is necessary to take actions aimed at preventing environmental degradation by developing solutions aimed both at the system and individual consumer.
The industry particularly harmful to the environment is the production of clothing. “The fashion industry is the second largest industrial polluter after aviation, accounting for up to 10% of global pollution. [...] Impacts from the fashion industry include over 92 million tonnes of waste produced per year and 79 trillion liters of water consumed” [8]. In the European Union countries, clothing is responsible for 2–10% of the negative impact of consumption on the environment. Less than half of unnecessary clothes are recycled, and only 1% of recycled textiles are used to produce new clothes [9]. Many fashion industry manufacturers in Asian countries violate human rights by taking advantage of slavery and child labor [10]. Therefore, limiting the purchase and increasing the conscious buying of clothes also has an ethical dimension. Other researchers investigating this topic include Thornton [11], Ting and Stagner [12], Islam et al. [13], Niinimäki et al. [8], Sohna et al. [14]. They emphasize the need to mitigate the negative effects of the fashion industry and extend the life cycle of clothes. One way to do this is via mobile applications that enable the sale, purchase or swap of used clothing and accessories. One of these type of applications, Vinted, was included in the current study.
Another important research area is the role of information and digital technologies in ethical consumption. Unfortunately, there is little empirical research into how consumers engage in ethical consumption via applications on a daily basis. Hawkins and Horst [15] conducted a study to identify the extent to which the use of mobile applications mediates people’s experiences of ethical consumption. These applications allow consumers to scan the barcodes of products they intend to purchase and determine if they are in line with their ethical values.

2.1.2. Mobile Applications

Mobile application can be defined as a type of software designed to run on a mobile device, such as phone, tablet or watch. The mobile apps cover almost every aspect of our life. According to statistics provided by Digital 2020 [16], average time spent using mobile devices each day worldwide in January 2020 was 3 h 40 min.
The researchers’ interest in mobile applications is evidenced by the number of scientific publications in which their use in various areas of socio-economic life was explored. Ngubelanga [17], Yadav et al. [18] investigated the use of mobile commerce applications, while Sardjono et al. [19] focused on the increased use of mobile commerce application as a result of the covid-19 pandemic. Other researchers studied the use of mobile applications in logistics, e.g., Dong [20], Sidiropoulos et al. [21] or tourism, Stepaniuk [22]. Moreover, mobile health applications were investigated with the emphasis on their usefulness in remote health monitoring and the willingness of users to pay for the service [23], as well as their role in delivering medical data and information [24]. In order to improve the availability of energy and efficiently manage this resource, a web application was developed to control access and ensure effective and efficient management of energy consumption from anywhere with access to the Internet [25].
The pandemic also inspired research on the effectiveness of mobile applications use in the area of education. This area was extensively explored, inter alia, by Sheng et al. [26] or Eryilmaz [27], who indicated new learning opportunities for students and teachers [28,29]. Jiménez-Parra et al. [30], in turn, attempted to evaluate the effectiveness of using mobile applications in combination with traditional methods of teaching about sustainable development and corporate social responsibility among students. They found that this type of learning encouraged greater engagement in social and environmental problems.
Fernanda Francielle de Oliveira Malaquias and Romes Jorge da Silva Júnior [31] explored the role of mobile applications in a comprehensive approach to social and economic development. Their research shows that downloads of mobile applications developed by the local governments of Brazilian smart cities and covering, inter alia, access to public information and services, health, education, security, tourism, water supply systems, and the environment are correlated with development indicators. The role of eco-apps in encouraging pro-environmental behavior of young people was also explored by Balińska et al. [32].

2.2. Hypothesis Development

The aim of the current research was to identify environmentally and socially sustainable behaviors and explore the role of mobile applications in encouraging them among young residents of Poland. The issue of pro-environmental and pro-social applications in creating socially and environmentally responsible behavior has not been sufficiently studied and described in the literature. The need to conduct research in this field is evidenced by the number of studies focusing on pro-environmental mobile applications, socially responsible behavior and climate change in the last 10 years. The ProQuest research base listed only 548 papers on 24 January 2022 (used filters: scientific journals, last 10 years, environmental impact and the English language).
To address this research gap, the current study examines the following main hypothesis (H): Mobile applications stimulate the socially and environmentally sustainable behaviors of Gen Z consumers.
Individual motivations to take action to protect the environment, including the climate, may be economic or non-economic in nature, e.g., health-related motives [33,34,35]. These motives were also included in the research conducted by the authors of this study. Both economic and health-related motives encourage city residents to look for alternative, ecological forms of transport. Traditional public transport and individual car journeys have a destructive impact on the natural environment and the health of city residents [36,37,38]. Hence, it becomes necessary to promote low-emission solutions, also made available through mobile applications, e.g., city bikes, scooters, etc.
Due to the numerous environmental threats indicated above, it is necessary to popularize socially and environmentally responsible attitudes through the media, as research by Hase et al. [39] showed that the interest of the mass media in the subject of climate change had not changed over the years 2006–2018. This need is confirmed by the research conducted by Reichl et al. [35] and Bonan et al. [40] who highlight the importance of coherent media delivered message on climate change that can stimulate the desired behaviors and attitudes.
With the above in mind, we proposed the following detailed hypothesis:
H1.
The most common environmentally and socially sustainable behaviors are stimulated by economic and legal factors.
H2.
Women rate their socially and environmentally responsible behaviors significantly higher than men.
H3.
Residents of large cities rate their behavior as socially and environmentally sustainable higher than residents of smaller cities and villages.
H4.
People with the highest income rate their purchasing activity, enhanced by visual identification considerably higher than other income groups.
Young generations are increasingly relying on information provided by the new media. Interestingly, the research by Lutzke et al. [41] indicate that both people noticing climate change and those who negate these changes shared and “liked” information about these changes.
The issues of environmental protection and sustainable consumption are increasingly often addressed in scientific papers. According to Calafell et al. [42], traditional consumer education directed at young people is insufficient to meet the challenges posed by the goals of sustainable development. Understanding the habits of young people as consumers and citizens of the future becomes essential for shaping their pro-ecological attitudes. According to the quoted study conducted in Catalonia, young people did not take into account the sustainability criteria when using and buying mobile phones (the replacement rate for mobile phones was very high (1, 2 or 3 years), and the most important purchase criteria were price, technical features and brand).
That is why education in the area of sustainable development should be based on modern teaching methods and tools as well as reliable sources of information, e.g., mobile applications. Therefore, it seems justified to conduct research on mobile applications to enhance their perception as a reliable, up-to-date and useful source of information. Therefore, we also proposed a hypothesis regarding mobile applications:
H5.
Knowing and using pro-environmental mobile applications has a positive impact on socially and environmentally sustainable behavior.
Although the study has drawn upon the research experience of the authors cited in this article, we also intended to make this work part of:
  • the implementation of the Glasgow Climate Pact-the outcome of COP26;
  • the works on responsible consumer behavior, analyzed, inter alia, by Thornton [11], Ting and Stagner [12], Islam et al. [13], Niinimäki et al. [8], Sohna et al. [14];
  • the analysis of behavioral factors undertaken, inter alia, by Thurston [33]; Cohen et al. [34], Reichel et al. [35], Zheng et.al [6];
  • the analysis of innovative (using mobile applications) methods of communication and education in the field of responsible behavior explored, inter alia, by Hase et al. [39], Reichel et al. [35], Lutzke et al. [41], Ngubelanga [17], Yadav et al. [18], Dong [20], Sidiropoulos et al. [21], Stepaniuk [22], Yan et al. [43], Calafell et al. [42] Jiménez-Parra et al. [30], Hawkins and Horst [15].
This paper is part of the current scientific discourse on the implementation of the UN Sustainable Development Goals. There is a need to integrate scientific knowledge with pro-environmental and pro-social activities undertaken by various entities.
The research has gaps both regarding the selection of sustainable behaviors and eco-apps which vary across countries.

3. Materials and Methods

The research process covered the stages presented in Figure 1.
The analysis of the literature, popular science publications, reports, thematic websites and the results of in-depth focus group interview enabled the selection of the following sustainable consumer behaviors: sorting waste, taking public transport instead of driving a car, purchasing products in recycled packaging, purchasing organic food, purchasing “zero waste” products, packing fruit and vegetables in reusable, not single-use bags, saving water, using ecological/biodegradable washing and cleaning products, walking instead of taking public transport for short distances, buying used clothes and those with an ecological certification, buying food with the FAIR TRADE label, getting around by bike and using shared car transport (e.g., Blablacar). The respondents rated their own behaviors in the aforementioned categories on a five-point Likert scale.
In order to reduce the number of variables and identify latent areas of sustainable behavior, the Exploratory Factor Analysis (EFA) was performed using the principal components method with Varimax rotation. Three areas of environmentally and socially sustainable behavior emerged, namely: (I) purchasing activity enhanced by visual identification, (II) sustainable consumption, (III) behavior stimulated by legal regulations and economic factors. To check the significance of differences between the areas of environmentally and socially sustainable behaviors which emerged in the factor analysis the Friedman ANOVA analysis and the Wilcoxon signed-rank test with Bonferroni correction were performed. Table 1 presents the factor loadings. The factor analysis used in the current study was also used in the research by Hogg et al. [44].
The test revealed that buying food with the FAIR TRADE label is strongly related to purchasing enhanced by visual identification; walking instead of taking public transport for short distances is strongly related to sustainable consumption; while waste sorting showed the strongest relationship to behaviors stimulated by legal regulations and economic factors.
The use and recognition of applications that encourage socially and environmentally responsible behavior were also analyzed. The selection of the mobile applications for analysis was carried out in a number of stages. First of all, from the database of available applications, those that corresponded to the socially and environmentally responsible behavior were selected. Then, an in-depth group interview was conducted with a group of students (via the Teams platform), which enabled selecting the applications that were recognized to the greatest extent. This group included: ZeroWasteApp, (an app which helps find favorite places for zero waste lifestyle such as bulk stores, zero waste shops, vegan cafes and restaurants and waste-free activities); ZdroweZakupy (an app which analyzes the ingredients and nutritional values and shows their health impact after scanning the bar code on a food product; ToGoodToGo (an app which connects customers to restaurants and stores that have unsold food surplus), Ingred (an app which checks the product label for ingredients of cosmetics or food that can be harmful to health) GdzieWyrzucić (an app helping with waste sorting), Vinted (an online marketplace and community that allows its users to sell, buy, and swap new or secondhand items, mainly clothing and accessories), Veturilo (an app for users of city bike system), BlaBlaCar (an app for car sharing), HappyCow (an app which helps to find vegetarian and vegan restaurants). These applications were included in the survey. The logos of the analyzed applications were also placed in the questionnaire.
Three reply groups emerged from the analysis of the responses regarding the recognition and use of the applications: Group I: “I don’t know this app”; Group II: “I know this app but don’t use it”; and Group III: “I know and use this app”. The best-known and most frequently used applications as declared by the respondents included Vinted (44.6% of respondents know and use it, 40.7% know it but do not use it, 14.7% do not know or use it) and Veturilo (35% know and use it, 40.3% know it, but do not use it, 24.7% do not use it and do not know it). The least recognizable apps included HappyCow, Ingred and ZeroWasteApp, as, respectively, 95%, 91.2% and 89.5% of the respondents declared that they were not familiar with them. The recognition and use of other applications were indicated by an average of every tenth respondent, and seven out of ten had never heard of them. To address the research objectives and cover the behavior areas which emerged in the factor analysis, the two best known and most frequently used applications (Vinted and Veturilo) were qualified for further analysis together with the application GdzieWyrzucić, which corresponds to the scope of Area III, (9.6% of respondents know and use it, 16.3%, know it but do not use it and 74.1% do not know or use it).
The obtained dataset was analyzed statistically. The values of the analyzed parameters are presented using the mean value, median value and standard deviation. The Mann-Whitney test and the Kruskal-Wallis test were performed to compare the results. The significance level of p < 0.05 was adopted, indicating the existence of statistically significant differences or relationships. The software used to analyze the data was Statistica 9.1 (StatSoft, Poland).
The survey was conducted in April 2022. The sample included people aged 17–25 (N = 772). The survey questionnaire was designed on the Google platform, and the link was made available through various Internet channels.
Most of the respondents were women (62.2%), which is typical of social research survey methods [45]. The place of residence and the level of household income per capita varied. The variables describing the study cohort are presented in Table 2.
Most of the respondents lived in cities with population over 500,000 residents. Over 60% declared the household income per capita exceeding PLN 2000 (EUR 442).

4. Results

4.1. Analysis of Socially and Environmentally Sustainable Behavior

To address the adopted research objectives, the respondents were asked to evaluate their own socially and environmentally sustainable behavior (Table 3).
The respondents assessed their own behavior in the indicated areas quite critically. The highest scores were assigned to: sorting waste, saving water and resignation from covering short distances by public transport in favor of walking. The lowest rating was given to buying food with the FAIR TRADE label and clothes with an environmental certification, which may result from the fact that pricing of this type of products is not competitive. Furthermore, the use of shared car transport was rated low, which seems justified taking into account the epidemic threat.
As indicated in the methodology, an important stage of the research was the selection of activities undertaken in the field of socially and environmentally sustainable behavior. For this purpose, a factor analysis was performed.
It was checked whether there were statistically significant differences between the assessment of activities grouped in the following three areas (Table 4).
Statistically significant differences were found between all analyzed areas (p < 0.001) (Table 4). The result in Area I: “purchasing activity enhanced by visual identification” turned out to be significantly lower than in the Area II: ”sustainable consumption” and significantly lower than the result in Area III: “behaviors stimulated by legal regulations and economic factors” and the result in Area II was significantly lower than in Area III. This result confirms H1: The most common environmentally and socially sustainable behaviors are stimulated by economic and legal factors.
Comparing the individual pairs of grouped behaviors (Wilcoxon signed-rank test), it was shown that each area differs from the others (Figure 2).
Each area is different from the others (Figure 2). The respondents rated their activities the lowest in terms of purchasing activity enhanced by visual identification, significantly better in terms of sustainable consumption, and the highest in terms of behavior stimulated by legal regulations and economic factors.

4.2. Differences in the Results of the Behavior Areas due to the Independent Variables

It was checked whether the self-evaluation of behaviors in the outlined areas are statistically significantly differentiated by the respondents’ gender (Table 5).
In all areas, women rated their actions higher than men (Table 5), which allowed for a positive verification of H2: Women evaluate their socially and environmentally responsible behavior significantly higher than men.
In the next stage of the research the Kruskal-Wallis test was employed, differences were noted in the assessment of individual factors depending on the place of residence (Table 6).
The value of the result in the area of sustainable consumption (II) is significantly lower in the case of people living in rural areas than residents of cities with more than 500,000 inhabitants (Table 6). The value of the result in the area of behavior stimulated by legal regulations and economic factors (III) is significantly higher for people living in rural areas than in cities with more than 500,000 inhabitants and significantly higher in cities with population of 50,000–500,000 residents than in cities over 500,000 residents. This means that H3: Residents of large cities rate their socially and environmentally sustainable behavior higher than residents of smaller cities and villages has only been partially positively verified.
Small differences were found in the results of individual areas between respondents with different levels of income, which was verified by the Kruskal-Wallis test (Table 7).
Only the value of the result in the area of sustainable consumption was significantly higher in the group of respondents with income up to PLN 1000 (EUR 221) than in the group declaring income exceeding PLN 3000 (EUR 663) (Table 7). There were no statistically significant differences in the area of purchasing activity enhanced by visual identification (Area I) depending on the level of respondents’ income, which negatively verified H4: People with the highest income rate their purchasing activity, enhanced by visual identification considerably higher than other income groups.

4.3. Differences in the Results of Behavior Areas and the Recognition of Individual Applications

It was checked whether the results describing behaviors in the selected areas are differentiated by the familiarity with the Vinted, Veturillo and GdzieWyrzucić applications (Table 8).
The research shows that respondents using the GdzieWyrzucić application rated the areas of purchasing activity enhanced by visual identification (Area I), sustainable consumption (Area II), behavior stimulated by legal regulations and economic factors (Area III) significantly higher than respondents who did not know this application or those that knew it but did not use it (in the case of Areas II and III). The respondents who indicated that they knew the application but did not use it also assessed their behavior in Area I and Area II significantly higher than the respondents who did not know the application.
The respondents declaring that they knew and used the Vinted application rated their activities in each of the above-mentioned areas significantly higher than the respondents who indicated that they knew the application but did not use it. The respondents from the third reply group also assessed their activities in the area of sustainable consumption (Area II) significantly higher than the first reply group.
Furthermore, in the case of the Veturilo application, the respondents from the third reply group assessed their behavior significantly higher in Area I and Area II than respondents from the second reply group. They also assessed their behavior in Area II significantly higher than the respondents from the first reply group.
There was no statistically significant difference between the reply groups apart from the value of Area III and the Veturilo application. It can therefore be assumed that the H5: Knowing and using pro-environmental applications have positive influence on socially and environmentally responsible behavior has been almost fully positively verified.

5. Discussion

The conducted research supplements and updates the knowledge in the field of environmentally and socially sustainable behaviors encouraged by mobile applications, which have not been analyzed extensively in the literature.
In the field of natural resources management and social research; many significant factors influencing pro-environmental behavior have been defined so far. For example, Gifford and Nilsson [46] listed 18 personality and social factors influencing these behaviors and Bamberg and Möser [47] listed eight basic socio-psychological variables. This category of determinants was also investigated by Lithuanian researchers who conducted research among consumers involved in sustainable consumption [48]
According to the authors of the current study, an important determinant is the dynamically changing information environment, including media sources of information. Similarly, Ziemba [49] examined the impact of information and communication technologies (ICT) in households on the improvement of sustainable development.
An increasing number of consumers recognize the environmental, social and economic threats and are therefore ready to take action in this area. This has been showed in the research conducted by Milfont and Schultz [50], which demonstrated consumer interest in sustainable consumption and simultaneous commitment to the implementation of appropriate solutions. The pro-environmental and pro-social commitment of consumers starts with changes in purchasing decisions. Simultaneously, social bonds are built [48].
Concari et al. [51] point to the need for an interdisciplinary approach to the research of pro-environmental consumer behavior and list such areas as: engineering, chemistry, ecology, economics, marketing, law, business management, sociology and psychology. In the case of environmental engineering, we deal with a multifaceted description of the phenomenon [52]. In economic sciences, the researchers focus on the purchase phase while the recycling phase, which is becoming increasingly important due to environmental consequences, is largely overlooked [53].
The government initiatives taken so far, including legal regulations, have had a positive impact on consumer behavior in the field of environmental protection. However, the researchers emphasize the need to coordinate the decisions of policymakers and manufacturers to popularize energy-saving devices [54].
The modern consumer is better educated, uses various sources of information and expects manufacturers to offer products that meet their needs. Environmentally oriented consumers expect environmentally friendly production technologies and distribution channels, but also being part of the new economic model of the circular economy [55]. This direction of changes is inextricably linked with the need to popularize consumer law concerning, inter alia, the access to safe products and reliable information as well as living in a clean natural environment [56].
Women more often exhibit ecologically responsible attitudes compared to men, which is confirmed by the results of research conducted by Xiao et al. [57]. Smerichevskyi et al. [58] also emphasize that women are more active consumers of ecological goods and services, thus caring for the health of their families. Moreover, the studies by Antonetti and Maklan [59], Brough et al. [60] show that socially and environmentally responsible activities are more often undertaken by women than men. Swim et al. [61] emphasize that this is due to higher social sensitivity displayed by women compared to men. Similar conclusions were drawn by Houser et al. [62] analyzing the factors influencing the adaptation policy. The research by Kahsay et al. [63] shows that women’s participation in formal decision-making processes is essential for achieving environmental goals.
Greater involvement of inhabitants of large cities than of small towns and villages in socially and environmentally responsible behavior results from many factors. They include better access to pro-environmental solutions such as, for example, a city bike system or food sharing facilities as well as personal experiences of the negative impact of various sectors of the economy on the environment [64]. The behaviors analyzed by the authors of this study also fit into the concept of smart city [65] where mobile applications are an integral component. Eisenack and Roggero [66] go a step further by analyzing various models of city functioning in the area of caring for the urban environment. The analysis also covered Polish cities, including Warsaw.
The authors’ assumption about stimulating pro-environmental and pro-social behavior by legal and economic factors was confirmed by the results of the study by Parzonko et al. [67]. Their analysis showed that pro-environmental behavior was mainly determined by legal regulations and financial benefits, for example, lower maintenance costs. Both the factors encouraging and discouraging pro-environmental behavior were economic in nature.
The expansion of social media inspires new research questions such as whether these information sources influence pro-environmental behavior. Research by Han and Xu [68] shows that traditional media have almost no influence on environmentally responsible behavior, differing from social media, which enhance interpersonal communication considered most effective due to the direct perception of environmental risk. The advantage of a mobile application is continuous access to updated information [69]. Mobile applications connect the interests of various stakeholders and allow them to communicate their abilities and needs, which, as emphasized by Howarth et al. [70] makes the action against climate change more effective.

6. Conclusions

The proposed main hypothesis (H) has been positively verified.
Applications play a very important educational role. They are a user-friendly way of integrating knowledge, they provide up-to-date information and behavior models, relieving the user of the necessity to actively search for them, and thus broaden the knowledge by including areas beyond the scope and level of received education [71]. It was also important that in an increasingly digital world, applications are used daily, in particular by young people. Therefore, our research focused on the representatives of Generation Z. The choice of this age group was made due to their ease of use of new media and digital technologies. Being digital natives, the representatives of Generation Z in Poland do not differ from their peers in other European countries. Consequently, the presented research results can be discussed and compared with research conducted in other countries.
The conducted research findings enabled the formulation of the following conclusions:
  • To date, research shows that among all the factors influencing pro-environmental behavior, four types are most often mentioned: perception of environmental risk, knowledge about the environment, concern for the natural environment and willingness to participate in pro-environmental actions. In the case of the first two factors, it is important to reach individuals with information, and in the case of the Generation Z, the information transfer channels are social media and mobile applications;
  • Actions should be taken to increase the recognition of pro-environmental mobile applications by Generation Z in order to promote environmentally and socially sustainable attitudes;
  • The development of social media in the last 20 years has inspired radical transformations in the information environment and consequently it is important to conduct research exploring how thematic applications impact pro-environmental and socially sustainable behavior;
  • Mobile applications are not only a source of information, but also tools supporting the planning and implementation of behaviors that will have the least destructive impact on the natural and social environment;
  • Legal and economic factors play a significant role in encouraging socially and environmentally responsible behavior.

6.1. Theoretical Implications

The findings of the current study have the following theoretical implications:
  • Methodical: it is necessary to use various research methods in order to recognize sustainable behaviors and the role played by mobile applications in encouraging these behaviors. Further studies could use methods such as: an experiment, a focus group and, in the case of mobile applications, a customer satisfaction index.
  • Scientific: the conducted research prompted the authors to propose a model of socially and environmentally sustainable behavior stimulated by mobile applications (Figure 3).

6.2. Practical Implications

The findings of the current study have the following practical implications:
  • In order to stimulate environmentally and socially sustainable behaviors, it is necessary to disseminate information about mobile applications that can both initiate such behaviors and consolidate them. To perform their function, they must be effectively promoted and widely used. The collected data provide guidelines for actors along the entire chain of production and distribution of consumer products enabling identification of consumer expectations and behavior;
  • The state institutions and the European Union bodies should continue to put effort into creating legal and financial instruments encouraging citizens to behave in a socially and environmentally responsible manner.

6.3. Limitations and Future Research

The limitation restricting research in this area is a very large number of applications dedicated to sustainable behavior. Due to the dynamic technological development, research results in this area may become outdated relatively quickly. Therefore, cyclical studies should be conducted to properly diagnose the role of mobile applications in influencing consumer behavior. Another limitation lies in the selection of the research sample. For the proper diagnosis of the analyzed phenomenon, it would be beneficial to conduct comparative studies in other countries.
Moreover, future studies should take into account the environmentally and socially sustainable behavior of respondents from older age groups. It would also be advisable to investigate the behavior of small town and rural residents. Future research should also include refraining from buying as a manifestation of an environmentally and socially responsible attitude.

Author Contributions

Conceptualization, E.J., A.W. and A.B.; Data curation, E.J., A.W. and A.B.; Formal analysis, E.J., A.W. and A.B.; Funding acquisition, E.J., A.W. and A.B.; Investigation, E.J., A.W. and A.B.; Methodology, E.J., A.W. and A.B.; Project administration, E.J., A.W. and A.B.; Resources, E.J., A.W. and A.B.; Software, E.J., A.W. and A.B.; Supervision, E.J., A.W. and A.B.; Validation, E.J., A.W. and A.B.; Visualization, E.J., A.W. and A.B.; Writing–original draft, E.J., A.W. and A.B.; Writing–review & editing, E.J., A.W. and A.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data is not public. The database is available from the co-author of the study. https://docs.google.com/spreadsheets/d/1kFEWf3z5VJxyMDNwegm3Suur47K6eR_psVchKvsSr4A/edit#gid=1336598459.

Conflicts of Interest

The authors declare no conflict of interest.

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Energies 15 07904 g001 550
Figure 1. Stages of the research process. Source: own study.
Figure 1. Stages of the research process. Source: own study.
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Energies 15 07904 g002 550
Figure 2. Comparison of individual pairs of grouped behaviors (Wilcoxon signed-rank test). Source: own research.
Figure 2. Comparison of individual pairs of grouped behaviors (Wilcoxon signed-rank test). Source: own research.
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Energies 15 07904 g003 550
Figure 3. Model of socially and environmentally sustainable behavior stimulated by mobile applications. Source: own research.
Figure 3. Model of socially and environmentally sustainable behavior stimulated by mobile applications. Source: own research.
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Table
Table 1. Matrix of rotated components.
Table 1. Matrix of rotated components.
Areas
Specification of BehaviorsPurchasing Enhanced by Visual Identification (I)Sustainable Consumption (II)Behaviors Stimulated by Legal Regulations and Economic Factors (III)
Buying food with the FAIR TRADE label0.7560.1050.028
Buying eco-certified clothes0.7540.247−0.026
Buying organic food0.7400.0750.100
Buying “zero waste” products0.6990.2050.208
Buying products in recycled packaging0.6490.1890.236
Using eco-friendly laundry and cleaning products0.5870.1110.345
Resignation from using public transport in favor of walking for short distances0.0260.6660.242
Resignation from using a car in favor of public transport0.0310.6240.003
Getting around by bike0.1690.5640.220
Use of shared car transport (e.g., Blablacar)0.3380.562−0.032
Buying second-hand clothes0.2410.5550.000
Sorting waste0.021−0.0040.727
Saving water0.1770.1680.715
Packing fruit and vegetables in reusable bags instead of single-use bags0.3880.1740.519
VARIANCE (cumulative percentage)23.76138.05949.821
Source: own research.
Table
Table 2. Variables characterizing the respondents.
Table 2. Variables characterizing the respondents.
Variables%
GenderWomen62.2
Men37.8
Place of residenceVillage25.4
City ≤ 50,000 residents15.5
Cities of 50,000 to 500,000 residents15.0
Cities ≥ 500,000 residents41.1
Household income per capita≤PLN 1000 (EUR221)9.1
PLN 1000–2000 (EUR 222–441)25.6
PLN 2000–3000 (EUR 442–662)33.7
≥PLN 3000 (EUR 663)31.6
PLN to EUR exchange rate as of 19 September 2022, Source: own research.
Table
Table 3. Self-evaluation of sustainable behaviors on a 5-point Likert scale.
Table 3. Self-evaluation of sustainable behaviors on a 5-point Likert scale.
VariablenMMeSD
Buying products in recycled packaging7583.033.01.00
Buying organic food7332.783.01.06
Buying “zero waste” products7002.563.01.09
Using eco-friendly laundry and cleaning products6812.412.01.08
Buying clothes with eco-labels (environmental certification)6782.382.01.12
Buying food with FAIR TRADE label6422.322.01.10
Resignation from using public transport in favor of walking for short distances7223.384.01.26
Buying second-hand clothes6682.893.01.42
Getting around by bike7223.143.01.34
Car sharing (e.g., Blablacar)5632.472.01.34
Resignation from using a car in favor of public transport7153.143.01.39
Packing fruit and vegetables in reusable bags instead of single-use bags7493.123.01.42
Saving water7663.554.01.00
Sorting waste7613.724.01.04
M-mean, Me-median, SD-standard deviation, Source: own research.
Table
Table 4. Descriptive statistics of the results of the analyzed behavior areas.
Table 4. Descriptive statistics of the results of the analyzed behavior areas.
Behavior AreasMMeQ1Q3SDFriedman ANOVA
Purchasing activity enhanced by visual identification (Area I)2.442.421.833.00.816Chi2 = 526.234
p < 0001
I < II, I < III, II < III *
Sustainable consumption (Area II)2.782.802.203.40.873
Behaviors stimulated by legal regulations and economic factors (Area III)3.423.333.004.00.854
M-mean, Me-median, Q1-lower quartile, Q3-upper quartile, SD-standard deviation, * Results based on the Wilcoxon signed-rank test with Bonferroni correction, Source: own research.
Table
Table 5. Difference in the results of behavior areas by gender.
Table 5. Difference in the results of behavior areas by gender.
Behavior AreasGenderMMeQ1Q3SDZ, p
Purchasing activity enhanced by visual identification (Area I)Women2.492.502.003.000.79Z = 2.738
p = 0.006
Men2.362.331.672.830.85
Sustainable consumption (Area II)Women2.862.802.203.600.87Z = 3.488
p < 0.001
Men2.652.602.003.200.86
Behaviors stimulated by legal regulations and economic factors (Area III)Women3.473.673.004.000.86Z = 2.182
p = 0.029
Men3.353.332.674.000.85
M-mean, Me-median, Q1-lower quartile, Q3-upper quartile, SD-standard deviation, Z-Mann-Whitney test, p-statistical significance (p-value), Source: own research.
Table
Table 6. Differences in the results of behavior areas by the place of residence.
Table 6. Differences in the results of behavior areas by the place of residence.
Behavior AreasPlace of ResidenceMMeQ1Q3SDH, p
Purchasing activity enhanced by visual identification (Area I) (I) village2.362.331.832.830.78H= 6.295
p = 0.098
(II) city ≤ 50,000 residents2.392.331.833.000.76
(III) city 50,000–500,000 residents2.612.672.003.170.88
(IV) city ≥ 500,000 residents
2.452.501.833.000.83
Sustainable consumption (Area II) (I) village2.652.602.003.200.90H= 11.399
p = 0.010
I < IV
(II) city ≤ 50,000 residents2.692.602.203.200.86
(III) city 50,000–500,000 residents2.923.002.203.600.91
(IV) city ≥ 500,000 residents2.862.802.203.400.84
Behaviors stimulated by legal regulations and economic factors (Area III) (I) village3.523.673.004.000.77H = 13.853
p = 0.003
I > IV
III > IV
(II) city ≤ 50,000 residents3.463.333.004.000.81
(III) city 50,000–500,000 residents3.573.673.004.330.92
(IV) city ≥ 500,000 residents3.293.332.674.000.89
M-mean, Me-median, Q1-lower quartile, Q3-upper quartile, SD- standard deviation, H-Kruskal-Wallis test, p-statistical significance (p-value), Source: own research.
Table
Table 7. Differences between the results of behavior areas by the respondents’ income.
Table 7. Differences between the results of behavior areas by the respondents’ income.
Behavior AreasIncomeMMeQ1Q3SDH, p
Purchasing activity enhanced by visual identification (Area I) (I) ≤PLN 1000 (EUR 221)2.602.501.833.330.95H = 2.683
p = 0.44(3
(II) PLN 1000–2000 (EUR 222–441)2.472.421.833.000.84
(III) PLN 2000–3000 (EUR 442–662)2.432.502.002.830.73
(IV) ≥ PLN 3000 (EUR 663)2.392.331.673.000.83
Sustainable consumption (Area II)(I) ≤PLN 1000 (EUR 221)3.033.002.203.800.98H = 10.913
p = 0.012
I > IV
(II) PLN 1000–2000 (EUR 222–441)2.822.802.203.600.87
(III) PLN 2000–3000 (EUR 442–662)2.802.802.203.400.81
(IV) ≥ PLN 3000 (EUR 663)2.662.602.003.200.90
Behaviors stimulated by legal regulations and economic factors (Area III)(I) ≤PLN 1000 (EUR 221)3.413.332.674.000.90H = 0.976
p = 0.807
(II) PLN 1000–2000 (EUR 222–441)3.483.673.00 0.80
(III) PLN 2000–3000 (EUR 442–662)3.413.333.004.000.83
(IV) ≥PLN 3000 (EUR 663)3.403.332.674.000.90
M-mean, Me-median, Q1-lower quartile, Q3-upper quartile, SD- standard deviation, H-Kruskal-Wallis test, p-statistical significance (p-value), PLN to EUR exchange rate as of 19 September 2022, Source: own research.
Table
Table 8. Differences in results of behavior areas by recognition of individual applications (p value).
Table 8. Differences in results of behavior areas by recognition of individual applications (p value).
Reply Based GroupsHpDifferences Between Groups
I Don’t Know this AppI Know this App but I Don’t Use itI Know This App and I Use it
MMeSDMMeSDMMeSD
GdzieWyrzucić
Area I2.3292.3330.7642.5522.5000.7733.1333.0830.91550.9770.000I < II, I < III, II < III
Area II2.6842.6000.8362.9593.0000.8773.2513.2000.95527.6340.000I < II, I < III
Area III3.3633.3330.8643.4443.5000.7683.8474.0000.79220.7100.000I < III, II < III
Vinted
Area I2.4812.3331.0312.3202.3330.7512.5412.5000.77813.4330.0012II < III
Area II2.7122.6000.9042.6242.6000.8212.9513.0000.88124.0890.000I < III, II < III
Area III3.3683.3330.8643.3313.3330.8543.5233.6670.84210.4620.0053II < III
Veturilo
Area I2.4702.5000.7912.3352.3330.8052.5462.5000.8338.5010.0143II < III
Area II2.562.6000.8592.6842.6000.8383.0493.0000.85936.21780.000I < III, II < III
Area III3.4693.6670.8243.3673.3330.8623.4533.3330.8632.5739250.2761
M-mean, Me-median, Q1-lower quartile, Q3-upper quartile, SD-standard deviation, H-Kruskal-Wallis test, p-statistical significance (p-value), Source: own research.
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Jaska, E.; Werenowska, A.; Balińska, A. Environmentally and Socially Sustainable Behaviors of Generation Z in Poland Stimulated by Mobile Applications. Energies 2022, 15, 7904. https://doi.org/10.3390/en15217904

AMA Style

Jaska E, Werenowska A, Balińska A. Environmentally and Socially Sustainable Behaviors of Generation Z in Poland Stimulated by Mobile Applications. Energies. 2022; 15(21):7904. https://doi.org/10.3390/en15217904

Chicago/Turabian Style

Jaska, Ewa, Agnieszka Werenowska, and Agata Balińska. 2022. "Environmentally and Socially Sustainable Behaviors of Generation Z in Poland Stimulated by Mobile Applications" Energies 15, no. 21: 7904. https://doi.org/10.3390/en15217904

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