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Article

Citizen Participation for Sustainability and Resilience: A Generational Cohort Perspective on Community Brand Identity Perceptions and Development Priorities in a Rural Community

by
Ivan Paunovic
*,
Cathleen Müller
and
Klaus Deimel
CENTIM—Centre for Entrepreneurship, Innovation and SMEs, Bonn-Rhine-Sieg University of Applied Sciences (Campus Rheinbach), 53359 Rheinbach, Germany
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(9), 7307; https://doi.org/10.3390/su15097307
Submission received: 28 February 2023 / Revised: 4 April 2023 / Accepted: 25 April 2023 / Published: 27 April 2023
(This article belongs to the Special Issue Green Development: Rural Communities, Resilience and Sustainability)
Versions Notes

Abstract

:
Citizen participation is deemed to be crucial for sustainability and resilience planning. However, generational equity has been missing from recent academic discussions regarding sustainability and resilience. Therefore, the purpose of this paper is to reintroduce the topic of the existence or absence of an intergenerational consensus on the example of a rural community and its perceived brand image attributes and development priorities. The research is based on primary data collected through an online survey, with a sample size of N = 808 respondents in Neunkirchen-Seelscheid, Germany. The data were analyzed using the Kruskal–Wallis test for the presence and/or absence of consensus among the five generations regarding brand image attributes and development priorities. The findings point to divergence between what the median values indicate as the most relevant brand image attributes and development priorities among the citizens and the areas where the Kruskal–Wallis test shows that an intergenerational consensus either does or does not exist. The results imply the need for new concepts and applied approaches to citizen participation for sustainability and resilience, where intergenerational dialogue and equity-building take center stage. In addition to the importance of the theory of citizen participation for sustainability and resilience, our results provide ample evidence for how sustainability and resilience planning documents could potentially benefit from deploying the concept of intergenerational equity. The present research provides sustainability and political science with new conceptual and methodological approaches for taking intergenerational equity into account in regional planning processes in rural and other areas.

1. Introduction

Engaging citizens in the development of local policies can provide a valuable contribution to the process of local development, especially with regard to identifying and evaluating alternatives, which is an important building block for sustainable development [1]. New forms of citizen engagement are based on the principles of deliberative democracy and take place through participatory governance processes because of the practical need for the meaningful inclusion of overlooked and underrepresented citizens [2]. These approaches are used to promote social sustainability and wellbeing within communities [3,4]. Moreover, certain stakeholder engagement strategies are said to perpetuate the problem of youth marginalization by not taking into account all generations of citizens equally, thereby colliding with international environmental law, which recognizes intergenerational equity as one of its two core principles [5,6]. The intergenerational balance (also termed intergenerational equity and solidarity) has not been mentioned in the latest Agenda for Sustainable Development [7], although it is an important issue that lies at the core of sustainable development from a legal and political point of view, while also including future generations—not just the current ones [8]. The authors see this as one of the major shortcomings of the current Agenda for Sustainable Development, thereby creating a gap in the sustainable development policy at the global level. Most of the literature on citizen engagement for sustainable development is qualitative in nature, while quantitative approaches have not been deployed, thereby creating a gap in the literature on quantitative approaches that needs to be addressed. The analysis presented in this study closes this gap, as it presents a detailed quantitative elaboration on cross-generational preferences that can serve as a basis for multistage citizen participation and mutual learning processes for sustainable development. This approach considers the voices from all relevant age groups, which are potentially very important for overcoming potential biases towards certain age groups or the exclusion of other age groups.
There is a gap in the literature regarding effective means of citizen engagement and public involvement as a pathway towards democratic innovation and creativity for sustainable development [1]. For example, place branding and destination development initiatives have been demonstrated to spur social innovation through the creation of stakeholder networks [9]. It is important to note at this point that one of the identified weaknesses of citizen surveys as a tool for citizen involvement in decision-making processes is their lack of deliberation and opportunity for dialogue [10]. The present approach fills this gap by providing academics and policymakers with a citizen survey analysis method that maps the intergenerational interests through a quantitative analysis and provides a clear pathway from the citizens’ input on issues involving a consensus, as well as those for which no clear consensus could be identified. This should represent a first stage in the process of democratic innovation for sustainable development within a rural community. This research does not directly include future generations (for sustainable development) but, rather, focuses on finding a balance between younger and older generations in a forward-looking manner, while enhancing understanding with regard to intergenerational equity and solidarity. The primary research goal is to provide a generational cohort perspective/analysis of community image perceptions and development priorities in a rural community. This has relevance for citizen participation and for public participation as cornerstones of sustainability and resilience. To achieve this, the following research questions were created:
  • RQ 1: What are the rural communities’ perceived brand image attributes with a consensus among the five generational cohorts (Z, Y, X, BB, and S)?
  • RQ 2: What are the rural communities’ perceived brand image attributes without a consensus among the five generational cohorts (Z, Y, X, BB, and S)?
  • RQ 3: What are the rural communities’ development priorities with a consensus among the five generational cohorts (Z, Y, X, BB, and S)?
  • RQ 4: What are the rural communities’ development priorities without a consensus among the five generational cohorts (Z, Y, X, BB, and S)?

2. Literature Review

2.1. Sustainability, Resilience, and Rural Areas

Sustainability, in general, refers to a transdisciplinary approach to resolving economic, environmental, and social problems while retaining the long-term, future generational perspective [11,12]. Resilience is a similar term that focuses on the interaction between adverse effects perceived as a crisis, a response to a crisis, or feedback loops from these experiences [13]. Sustainability, in the regional context of rural communities, includes bottom-up initiatives of stakeholders with sufficient knowledge and skills to be active agents of change, and who have the same objectives and values [14].
The literature on rural communities recommends discussing the degree of rurality, rather than rurality as an absolute term. One can grasp this through the absence of certain factors, rather than by the presence of factors that make up rural areas in scientific, administrative, and statistical terms [15,16].

2.2. Community Brand Image and Place Branding

Places are brands and have brand images in the same way as products, services, or famous individuals [17]. In general marketing research, the brand image differs from the brand identity, because the brand image is on the receiver’s side (customers), while brand identity finds itself on the sender’s side, e.g., when a small group of managers decides what values a product or a place should represent [17,18]. In territorial and regional research, brand image is the sum of individual attitudes towards certain objects, as a socially shared symbol that can be measured in the attitudes of the stakeholders [19]. Community brand image development is often used as a basis for creating logos and communication strategies, as well as the wider economic development of a region [20]. The process of branding and brand-building in rural communities can spur the creation of networks for social innovation, thereby activating the latent potential for SI in rural communities [9].

2.3. Citizen Engagement for Sustainable Development in Rural Areas: Methodological Approaches and Theoretical Perspectives

There is a gap in the previous research on citizen engagement in (sustainable) rural community development with regard to the application of quantitative research methods, as well as generational cohort theory. Previous studies on citizen engagement in rural areas mostly focus methodologically on case studies, qualitative data collection, and analyses [21,22], while there are also single quantitative-oriented studies. For example, Grabe and Dutt [23] presented a structural equation model of the influence of civic participation on civic engagement and community leadership, mediated by gender ideology, agency, and political efficacy. Regarding the object of the research, the previous research in this field has mostly focused on studying the process of improving the decision-making process through citizen participation [24], improving the ownership, human development, and empowerment of communities through citizen participation [25], as well as using citizen participation to build capacity for the eradication of poverty [26]. An important perspective of the previous research on citizen participation for sustainable development is the transmission of immaterial heritage from generation to generation, pointing to built-in tools for intergenerational knowledge management in rural communities [27]. Previous research in rural areas has dealt with improving the decision-making process through citizen participation, predominantly in a qualitative way. The present research, in contrast, deals with improving the citizen participation process by providing a quantitative-based tool and a theoretical rooting in the generational cohort theory.

2.4. Research on Generational Cohorts for Sustainability in a Rural Context

To understand future generations of sustainability in the rural setting, and to take the long-term perspective, it is important to first understand the relations between the current generations or generational cohorts. However, much of the generational cohort research in recent years has dealt with explaining the generational cohort differences across the rural and urban areas [28,29,30,31], as well as understanding workforce preferences in an organizational context in both urban and rural settings [32,33,34,35]. A relatively small proportion of research has dealt with generational cohorts in the rural context [36,37,38,39]. An even smaller proportion of research has dealt with intergenerational research from the perspective of sustainability and resilience in rural areas, with concrete sustainability perspectives despite austerity measures in Southern European countries as an aftermath of the financial crisis [40]. The present research seeks to close this research gap by providing an applied approach to mapping out the differences between generational cohorts in terms of rural community development priorities. This new and under-researched field of generational cohorts in a rural setting should provide valuable information for rural development researchers and practitioners.

2.5. Generational Cohorts: Definitions, Perspectives, and Challenges

Generation reasoning in general and the generational cohort approach are used extensively in empirical research and have proven their usability for documenting societal and market changes in detail [41,42]. Understanding general cohorts is also of crucial importance for facilitating generational dialogues and resolving intergenerational conflicts [43,44,45], as well as for building intergenerational solidarity within a rural community [46]. Because people of different ages can apply different experiences and resources to different situations, they can adapt to new conditions in different ways [41]. Previous research has identified three ways in which generations, as a concept, are used in everyday social practice for their own and other generations: (1) to portray generations, (2) to deploy generations argumentatively, and (3) delimiting generations (acknowledging intra-generational differences, as well as exercising empathy towards other generations in an act of “generational intelligence”) [47,48].
Generational cohort research provides links between age and the historical circumstances in which certain generations grew up, and it provides an improvement from older generation-based models where reproductive life-cycles and family cycles were falsely thought to be a significant factor for generational effects [41]. The modern generational cohort concept is a model of social change that relies both on intergenerational consensus and on intergenerational conflict—in contrast to the early days of the concept, which dealt primarily with intergenerational conflicts [44,49]. The modern concept of “social generation” has a long tradition of being used as a synonym for “social cohort”, both in social research and in social practice, albeit some sociologists claim that the term “generation” implies kinship connections, while the term “cohort” implies no such connections [50]. In this paper, the term “generation” is used as a synonym for cohort as well as for age group, and it implies no kinship within generations. A social generation or an age group consists of cohort members who have similar attitudes, worldviews, and beliefs that are grounded in a shared context and experiences that are shaped over time [48]. The anticipated dramatic demographic shift in European societies was identified in the earlier literature but mainly focused on the political tension between the young and the elderly, without a differentiated approach for multiple generations present within the society and their social and political profiles [51]. Similar zero-sum political trade-off approaches between elders and children have been applied in the U.S. regarding the distribution of public resources [52].
There is no consensus in the literature on how to precisely define generational groups, because the thresholds do not have clear cutoff values. This ambiguity is especially true for younger generations, such as Generations Y and Z [53]. Part of these differences is also due to demographic differences in different parts of the world, meaning that there is no uniform way to divide generations. While these differences make it harder in certain situations to compare studies from different contexts internationally, this is generally due to the different demographic distributions of generational cohorts. As presented in Table 1 below, McIntosh-Elkins et al. (2007) [54] defined “the Silent Generation” or “Schwarzkopf Generation” as those born before 1946, while those born between 1947 and 1962 were called the “Baby boom” generation. Following that, members of Generation X were born between 1963 and 1977, while members of Generation Y—also called the “Millennials”—were born between 1978 and 1986. However, newer sources cite the time period for Millennials (Gen Y) as between 1981 and 1996. The research approach in the present research, to a large extent, follows the definition of Generations S, BB, and X as defined by McIntosh-Elkins et al. (2007) [54], and the definition of Generations Y and Z as defined by Dimock (2019) [53].
Generation Z and its inherent characteristics as an upcoming generation have previously been researched with regard to the future of the workforce and its members’ characteristics as a workforce [57,58,59]; regarding the challenges related to managing and leading them [60]; their relation to contemporary learning environments in both general and rural student populations [61,62,63]; as the first digital generation [64]; their leisure behaviors [65]; their wine consumption behaviors [42]; and their behaviors towards a sustainable and circular economy, as well as their preferences concerning eco-products [56]. No previous research, apart from that by Vromen [66], has been identified that deals with the political and communal public discourse aspects of Generation Z’s civic engagement. This is a striking gap in the literature, since the majority of the characteristics that are understood to be relevant for the generation’s makeup are related to major global political events [64,67,68].
Generations X and Y are often researched together as they are, to a certain degree, similar “younger” generations [65,69,70]. Akin to the research on Generation Z, the research on Generation Y (or the Millennials) predominantly deals with resolving human resource issues in diversity management, focusing on specific characteristics of that generation [71,72,73,74]. Another important stream of research deals with Generation Y’s consumer behaviors [69,75,76,77] and, more specifically, with their attitude–behavior gap for sustainable consumption [78].
The research on Generation X, similar to that on Generations Y and Z, primarily focuses on the generation’s workforce characteristics [79,80,81]. However, there are also some contemporary cross-cutting issues that have been studied concerning this generation, e.g., issues pertaining to the new economy, knowledge workers [82], and women in technology [83]. Other research fields in which Generation X has been included as a focal generation include the intersection between social classes, upward/downward mobility, and job orientation [84], as well as online shopping behaviors, for which Generation X has been compared to Generation Y [85].
The focus of research on the Baby Boom Generation is somewhat different from that on the younger generations. It focuses primarily on the lack of past opportunities in science for Baby Boomer women [86], the generally lower college completion rates [87], and the changes made that were needed in the university system for lifelong learning opportunities [88]. Other important research fields include tracking the evolution of defining the BB Generation, in terms of educational urgency, problems in all age-graded institutions [89], and the conditions under which Baby Boomer grandparents provide childcare to their grandchildren [90].
The research on the Silent Generation is scarce and covers fewer research fields. It deals primarily with the grandparenting practices of Generation S [91], health risks for Generation S women, multigenerational family attainment [92], travel preferences [93], and intimate partner violence among its members [94]. There has also been an interesting study on how homogeneous private life experiences impact the formation of the generational consciousness in Generation S, apart from political and economic events [95].

3. Methodology

The present study is exploratory because the researched phenomena have not been precisely defined in the previous literature, and it is also quantitative because it uses statistical hypothesis testing to uncover the relations between the research constructs. The overall goal of the research was to compare rural community image perceptions and priority fields of action among the different demographic groups of citizens in Neunkirchen-Seelscheid, Germany. In order to compare the age groups and test whether there were statistically significant differences among the groups, the citizens’ ages were divided into five groups (Generation Z, 16–20; Generation Y or “Millennials”, 21–40; Generation X or “Xers”, 41–60; Generation BB or “Baby Boomers”, 61–70; and Generation S or “The Silent Generation”, above 70). A Kruskal–Wallis test was conducted using IBM SPSS software. Thi9s test is a non-parametric test that is suitable for comparing groups of categorical data (in this case, age groups). It compares the mean ranks of group member values instead of the values themselves. The analysis of the data focuses on statistical hypothesis testing using the Kruskal–Wallis test. However, multiple comparisons are not presented, as they were too extensive to present in this article. Therefore, a descriptive statistical table with the means of each age group and for each researched variable is presented, along with a short analysis of the differences between the means for the variables where statistically significant differences were detected through the Kruskal–Wallis test.
The research was based on primary data collected from December 2017 until January 2018 through a German-language survey, with a sample size of N = 808 respondents. The respondents were elicited by an invitation letter posted on the municipality’s website, as well as at the local banks and the town hall. The respondents were informed about the research process, the usage of the data, the responsible scientists to contact for further questions beforehand, and in a letter signed by the town’s mayoress. The survey could be filled out either on an online platform, by downloading and sending it via email, or by going to a local bank or the town hall, where the questionnaires could be filled out and handed over. This ensured a rather wide reach in terms of respondents with and without IT knowledge and access. Further explanation of the terms could be elicited only by the respondents themselves, while the initial explanation concerning the goals of the survey was provided in the letter from the mayor.
To qualify as participants in the survey, the respondents needed to be citizens of the rural community of Neunkirchen-Seelscheid with voting rights, meaning that they had to be older than 16 years. The analysis of the primary data focused on the perceived community brand images, the areas that required the most attention in the community development, and the differences regarding these two aspects among the different age groups. The survey instrument used a 5-point Likert scale (from 1 to 5). Regarding the community brand image, the study deployed a semantic differential scale of adjectives to access the strength of associations in a symmetrical continuum. This technique is generally used in marketing research [96], and especially in brand image research [97]. This technique is considered to be a quantitative technique, similar to all research based on participants’ evaluation of brand characteristics presented in words or in sentences (see, for example, Roy and Banerjee [98]).
The development of the survey instrument for both the development priorities and the community brand image was carried out by engaging with the public servants in the community workshops, as well as by reading community documentation. Regarding the community brand image, there is an ongoing debate as to whether the community is unsuccessful due to its low tax incomes, which are a result of the community’s inability to set up industrial zones in the water protection areas around the water dam, leading to an attribute of “successful–unsuccessful”. Furthermore, the vision for the development of the community is to raise the quality of living, stop emigration, attract immigration, and obtain the attribute of “uncomfortable–comfortable”. Apart from these ongoing considerations, the brand image pairs were selected from previous studies conducted in the rural mountain tourist destinations [99], as well as in cities [19]. Regarding the community development priorities, they were already previously defined as strategic goals and guidelines in the internal documents of the community of Neunkirchen-Seelscheid.

4. Results

4.1. The Community of Neunkirchen-Seelscheid and the Demographic Makeup of the Sample

The community of Neunkirchen-Seelscheid is an interesting rural community to study, although by some criteria it is not considered to be rural, but rather a metro community, due to its proximity to the large cities of Cologne and Bonn. However, the community shares similar development problems with rural communities, despite its proximity to the large urban centers, because of its inability to develop its own economic zones, due to the water reservoir and nature protection restrictions. This makes the community less suitable for industrial or logistical zones, but better suited for developing the service sector, in terms of education, tourism, creativity, research, and similar economic activities. The current economy is dominated by agricultural and forest economies, as well as a considerable amount of SMEs and long-distance commuters who work in the big cities. The community’s overall population is around 20,000 inhabitants, and this number is shaped by immigration—primarily from refugees from war-torn countries—as well as by emigration to the big cities.
The number of respondents (N = 808) was considered convenient and did not need a special control for the accuracy of the data provided. The demographic makeup of the sample was rather balanced, with 46.6% female and 53.4% male. The distribution of the age groups and educational qualifications loosely followed the data from the official statistics.

4.2. Results Regarding Age Groups

The descriptive statistics, presented in Table 2 below, demonstrate that Generation X (1958–1977) was the largest age cohort in the present research, accounting for 40.96% of respondents, followed by Generation BB (1948–1957) with 19.70%, Generation Y (1978–1997) with 19.22%, and Generation S with 16.06%. Generation Z (1998–2002) was, expectedly, the smallest cohort, accounting for only 4.05%. The whole of Generation Z was not relevant, as the research dealt only with citizens, meaning those of legal voting age for communal elections (16 years) and older, as it is not uncommon in some German states to have a legal voting age of 16 years for communal elections.

4.3. Results Regarding Community Brand Image

In response to RQ 1 and RQ 2, the 15 hypotheses were operationalized for each of the brand image attribute pairs. The results of the Kruskal–Wallis test for the 15 hypotheses regarding the perceptions of the five age groups on the brand image of the rural community are presented in Table 3 below. For hypotheses H1.2, H1.3, H1.4, H1.9, H1.10, and H1.15, the null hypothesis was accepted, leading to the conclusion that there were no statistically significant differences between the age groups regarding community image. This points to the fact that for the community image pairs sleepy–lively, provincial–urban, old-fashioned–modern, pessimistic–optimistic, safe–dangerous, and attractive–unattractive, there was a consensus among all age groups regarding community image. The community image was seen as being largely lively, provincial, somewhat old-fashioned, optimistic, very safe, and somewhat unattractive. For hypotheses H1.1, H1.5, H1.6, H1.7, H1.8, H1.11, H1.12, H1.13, and H1.14, a statistically significant difference between the age groups was confirmed. This means that for the community image pairs sleepy–lively, aspiring–stagnating, family friendly–not family friendly, open–closed, having doubts–confident, neat–neglected, uncomfortable–comfortable, friendly–unfriendly, and successful–unsuccessful, there was no consensus among the different age groups in the rural community.
In the Table 4 below, the mean values for all generational cohorts regarding each variable are presented, with a special focus on community image aspects, for which statistically significant differences between the groups were determined. An asterisk (*) next to the number denotes a statistically significant difference between the age groups. Regarding the aspiring–stagnating pairs, there was a greater perception among those of Generation X that the community image is somewhat more stagnating than was observed in the other generational groups. In relation to the family friendly–not family friendly pair, Generation X perceived the community as not family friendly to a greater extent than the other age groups, while those from Generation Z perceived it as more family friendly. Generation Xers also perceived the community as more closed than the other age groups, while members of Generation S saw it as more open than others. Regarding the having doubts–confident pair, those from Generation S perceived the community as having doubts more than the other groups, while members of Generation Z perceived the community as more confident than the other groups. Baby Boomers found the community to be more neglected than the other age groups, while those from Generation Z found it neater; they also found the community to be more comfortable than those from the other age groups, while members of Generation S found the community to be less uncomfortable. Moreover, Generation Z found the community to be more unfriendly, while members of Generation S found the community to be more friendly. Generation Xers, more so than the other age groups, saw the community as unsuccessful, while members of Generation S saw it as more successful.

4.4. Results Regarding the Development Priorities in the Community

In response to RQ 3 and RQ 4, the 15 hypotheses were operationalized for each of the community development priorities. The results of the Kruskal–Wallis test for the 15 hypotheses regarding the community development priorities are presented in Table 5. For the results of hypotheses H2.1, H2.2, H2.6, H2.8, H2.10, and H2.11, the null hypothesis was accepted, leading to the conclusion that there were no statistically significant differences between the age groups in terms of community development priorities. These are the aspects where a consensus among different age groups within the community existed regarding community development priorities. Among the high-priority areas, there was a consensus regarding the importance of the broadband internet infrastructure and better public transportation. Regarding the low-priority areas, there was a consensus that reducing bureaucracy, more retailers, online forms for citizens, and better gastronomy have a rather low priority for community development. For hypotheses H2.3, H2.4, H2.5, H2.7, H2.9, H2.12, H2.13, H2.14, and H2.15, the alternative hypothesis was confirmed, meaning that a statistically significant difference between the age groups was confirmed. This means that for the community development priorities of reducing transit traffic, rehabilitation of community finances, supporting the economy, medical services, more parking spaces, more educational facilities, more voluntary engagement opportunities, a prettier city center, and more cultural offerings, there was no consensus among the age groups, but certain differences existed.
To inspect the mean value differences among the age groups, a descriptive statistical Table 6 is presented below. An asterisk (*) next to the number denotes a statistically significant difference between the age groups. Members of Generation S saw the reduction in transit traffic as a higher priority than the other age groups, while Generation Z saw it as a lower priority than the other age groups. Generation S also saw the rehabilitation of the community’s finances as a higher priority than the other age groups, while those of Generations Z and Y saw it as a less important development priority. Similarly, members of Generation S saw supporting the economy as a higher priority than the other age groups, while those of Generation Z perceived it as a less important development priority. Members of Generations BB and S were more inclined towards medical services in the community, while those of Generation Z saw this as a less relevant priority. For those of Generation S, more parking spaces were a higher priority than for the other age groups, while for Millennials this was less relevant. For members of Generation Z, more educational facilities were a less relevant priority than they were for the other age groups, while for Generation S they were more relevant, which was a rather unexpected result and demands a more detailed elaboration. Similarly, voluntary engagement opportunities were more relevant for members of Generations S and BB than for the other age groups, while for Generation Z they were a less relevant priority. A prettier city center was more relevant for Generations BB and S than for the other age groups, while for members of Generation Z it was an issue of less relevance. In a similar way, cultural offerings were seen as a higher priority by Generation BB and Generation S, but they were seen as less relevant by Generation Z.

5. Discussion, Future Research Directions, and Limitations

In response to RQ 1, the presented results on community image and development priorities among the different generational age groups lay a foundation for a destination branding concept through ”provincial“, “very safe“, ”inert”, “old-fashioned”, and “attractive” image aspects. These are the fields where a consensus exists between all generational groups regarding community brand image perceptions. In response to RQ 2, the community brand image attributes “friendly” (1st), “family friendly” (3rd), and “neat” (6th) rank very high, but they are not supported by all age groups. Therefore, they should not be regarded as representative of the whole community.
In response to RQ 3, the highest community development priorities for which a consensus among all generations exists are broadband internet, better public transportation, reducing bureaucracy in the community, more retailers, and better gastronomy. Here, an interpretation can be more complex. In response to RQ 4, although medical services (3rd), supporting the economy (4th), and rehabilitation of the community’s finances (5th) rank fairly high, there are also statistically significant differences between certain age cohorts regarding these priorities. Therefore, they cannot be regarded as overall priorities for the community.
The present study contributes to the recent theoretical discussions in several important ways. For example, varying expectations of different generations are often a reason for intergenerational conflicts [100]. However, applying the generational cohort theory, as conceptualized by Stoker [101], to research citizen priorities for democratic participation is a relatively young and unexplored research field [102], which is a research gap that this study seeks to close. The present study’s contributions are also relevant for the literature in political science dealing with the participation of citizens as individuals [2,103], where previously little or no consideration was made of the intergenerational aspects of citizen participation. Another contribution to the field of political science is the literature that deals with the intergenerational aspects of sustainable development, but exclusively with present vs. future generations [1,6,104]. It appears that because generational cohort theory comes from sociology [41], the previously mentioned literature that is rooted in political science makes virtually no use of it. Therefore, the results of the present study contribute to both the sociological literature and the political science literature regarding the application of generational cohort theory to citizen engagement in public discussion, policy creation for sustainable development, and resilience, in a quantitative way. In terms of the methodological contributions to social and political science for sustainable development and resilience, the present research provides a precise statistical analysis tool for providing insight into the areas for which there is a consensus and those that exhibit statistically significant differences between generational cohorts in a rural community. In this sense, the present study builds on the methodology of a few quantitative studies in the field of citizen engagement for rural community development, and specifically on generational cohort research. While Grabe and Dutt [23] deployed structural equation modelling of the influence of civic participation on civic engagement and community leadership, the present study focuses on intergenerational cohort similarities and differences, and we deployed a Kruskal–Wallis test to identify the statistically significant differences between generational cohorts, as well as descriptive statistics in the form of median values for understanding the similarities and statistically insignificant differences between the generational cohorts in the rural community. Another relevant study, in terms of quantitative approaches in the field of generational cohort research, is that of Stark and Poppler [33], where the authors used the Kruskal–Wallis test to analyze data of the General Social Survey in order to analyze the impacts of generational cohorts on job preferences and workplace behavior. The present research deployed the same statistical procedure and confirmed its suitability for survey-based generational cohort research. However, the present study deployed generational cohort theory to map out the generational similarities and differences with regard to the rural community’s perceived image and development priorities.
This research is also relevant for understanding the political process, where political parties and candidates mobilize the voters by appealing to their self-interest, which then leads to political conflicts [51,52]. The results provided here offer a more differentiated approach to multiple generations in a rural community in Europe, thereby going beyond the relations between “the young” and “the old” citizens. Moreover, the results offer a more complex approach to this problem by presenting intergenerational aspects of social and political change in a rural community, due to the differing priorities of the different age groups. Future studies could expand on the presented intergenerational approach to citizen engagement by also including children over the age of eight through the previously identified concept of intergenerational democracy [105].
Generation Z perceives the community as somewhat more lively and family friendly than the other age groups, as well as more confident, neat, comfortable, and unfriendly. The members of Generation Z perceive the reduction in transit traffic, the rehabilitation of the community’s finances, and supporting the economy as less important priorities. Furthermore, they also perceive medical services, education facilities, voluntary engagement opportunities, a prettier city center, and cultural offerings as less relevant than they are to the older age groups. These are the first results that point to Generation Z’s perception of the rural community and its development priorities. Their previously identified tendency for digital technology [57], their lack of environmental activism, and their preference for public goods rather than green products [56] appear to correspond well with our present results for a lack of interest in physical and open meeting spaces, as well as their lack of interest in voluntary engagement and educational offerings, as they spend their free time in a different way.
Generation Y turned out to be the most mainstream age group regarding community image, as Millennials have the perception that the community is somewhat sleepy as opposed to lively. For them, parking spaces are less of a priority, as is the rehabilitation of the community’s finances. These findings confirm those of previous studies on Generation Y that focused only on how Millennials can translate their environmental attitudes into consumer practice [78], while other broader societal, environmental, and economic issues appear to elude the priorities of this generation.
Generation X perceives the community as more stagnating than aspiring compared to the other age groups, as well as more closed than open. Generation X turned out to be the most mainstream age group in terms of development priorities, as they had no significant differences with the other age groups. Stagnating and closed perceptions of a rural community appear to confirm the results of earlier studies on young Generation Xers, where fear and distress about the stagnating economy and not living up to parents’ levels of success stood as a central theme for Generation X from all social milieus [84].
Generation BB perceives the community to be neglected and less neat than the other age groups, as well as unsuccessful. They perceive medical services, voluntary engagement, a prettier city center, and cultural offerings to be higher priorities. The results regarding the community image confirm the previous findings on Generation BB, who generally suffered from low college competition rates [87], and due to the sheer size of the generation, it is understood that they put the graded educational institutions in an emergency state [89].
Generation S sees the community as more open than the other age groups, but also as having more doubts, being less confident and less comfortable, but friendly, successful, and less stagnating. They see the reduction in transit traffic, the rehabilitation of the community’s finances, and supporting the economy as higher priorities. Furthermore, medical services, educational services, voluntary engagement opportunities, a prettier city center, and cultural offerings are perceived to be more relevant priorities. This generation appears to be the most unique generation, being very engaged in certain rural development matters. This confirms the previous findings that Generation S is very likely to hold and share alternative versions of reality and of past historic events that are contrary to the mainstream version [95].
One of the major possible limitations of this study is the inability of the generational cohort theory and research to explain individual behaviors, but only in the case of generational cohort behaviors in relation to other generational cohorts. Generational cohort research is often considered to be context-specific. Therefore, it is not useful when dealing with individuals [106]. This means that any conclusions from our study should be used with caution in other studies, and they should not be used to interpret the individual behaviors of citizens. Furthermore, although critics of the generational approach put forward the hypothesis that many of the identified differences are due to the life-cycle stages of a certain generation, empirical research holds that it is wiser to assume that socialization under different social, political, technological, and economic environments makes a certain generation occupy only one unique position in human history [106,107]. For example, critics claim that a person of a certain age is certainly to be expected to have certain affinities irrespective of the external circumstances, while the generational cohort proponents propose that external factors shape each generation, thereby making them prone to certain behaviors.
A methodological limitation of this study is that the data were collected with predefined groups already selected, so it was not possible to adjust and try out different age-spans of generational cohorts, as they vary across the literature (see, for example, the classifications of [54,55,56], which are listed in Table 1). Different age group spans could also possibly change the results somewhat, but not the presence or absence of statistically significant differences between all of the groups.

6. Conclusions

One of the major problems with imagining future generations for sustainable development is that we are, to a large extent, unable to predict the social forces that will shape the future generations and their priorities. For example, while we might think that ecosystem degradation and climate change through economic activities will shape younger generations’ lives [108], they could be faced with much more basic problems such as war-induced, economic, environmental, and social problems—which, in turn, will shape these generations differently than previously thought. Therefore, resilience in relation to future generations appears to be the crucial skill for sustainability in society. The results of the present study are relevant for supporting the intergenerational dialogue in citizen participation processes for sustainability and resilience. Only by understanding the views of all relevant demographic groups can we design communication and policy measures for the sustainable development of a resilient rural community.
The results of the present study contribute to the research into public involvement and citizen participation for sustainability in rural communities. This study demonstrates the use of a quantitative survey instrument, as well as generational cohort theory, as a first step in the development of public involvement strategies with greater public deliberation potential, greater commitment, and costs at later stages. Citizen surveys are a low-involvement, low-deliberation, but also time-efficient tool for facilitating public involvement, and they can include under-represented groups in other forms of more active public deliberation [10,109].
The results also contribute to generational cohort research by providing direct insight Into the five different generational cohorts (Gen Z, Gen Y, Gen X, Gen BB, and Gen S) and how they perceive the rural communities and the development priorities. The results also confirm that the perceptions are largely subjective and in line with the general character of each generation that has previously been identified in the literature.
The results of this study illustrate the complex and perplexed nature of citizen participation for rural development in terms of perceived rural community image and development priorities among the five age cohorts. In conclusion, the Kruskal–Wallis test is a well-suited tool for analyzing surveys for citizen engagement processes.
Overall, there 9 out of 15 community image pairs and 9 out of 15 community development priorities exhibited certain statistically significant differences between the five age cohorts. The design of the local policies in different areas—such as territorial marketing, infrastructure, and support for businesses—is needed in order to take these results into account and forge the right types of partnerships with the right demographic groups in well-designed participation and communication strategies.

Author Contributions

Conceptualization, I.P. and C.M.; methodology, I.P.; software, I.P.; validation, K.D. and C.M.; formal analysis, I.P.; investigation, K.D. and C.M.; resources, K.D.; data curation, I.P.; writing—original draft preparation, I.P.; writing—review and editing, C.M.; visualization, I.P.; supervision, K.D.; project administration, K.D.; funding acquisition, K.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was co-funded by the German Federal Ministry for Science and Research (BMBF), the Common Science Conference (GWK), and Bonn-Rhein-Sieg University of Applied Sciences through a project “Campus to World”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The dataset in .sav (IBM SPSS) format can be accessed online under: https://doi.org/10.5281/zenodo.7683922.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Overview of the five generational cohorts and their cutoff values in the previous literature and in the present research.
Table 1. Overview of the five generational cohorts and their cutoff values in the previous literature and in the present research.
Generation[55][56][54][53]The Classification Used in the Present Research
Gen Z 1995–2010 1997–1998–
Gen Y1980–19991980–19941978–19861981–19861977–1997
Gen X1961–19791965–19791963–19771965–19801958–1977
Gen BB (Baby Boomers)1946–19601945–19641946–19621946–19641948–1957
Gen S (The Silent Generation, Schwarzkopf) –1945–1945–1947
Table
Table 2. The distribution of the respondents according to their age cohort and share in the overall sample size.
Table 2. The distribution of the respondents according to their age cohort and share in the overall sample size.
Year of BirthAge in 2018The Generational Group’s Name in the LiteratureSample Size (N = 791)Percentage
1998–200216–20Generation Zn = 324.05%
1978–199721–40Generation Y—“Millennials”n = 15219.22%
1958–197741–60Generation X—“Xers“n = 32440.96%
1948–195761–70Generation BB—“Baby Boomers”n = 15619.70%
–1947>71Generation S—“The Silent Generation”n = 12716.06%
Table
Table 3. Kruskal–Wallis test results of the independent samples between the five age cohorts regarding community brand image.
Table 3. Kruskal–Wallis test results of the independent samples between the five age cohorts regarding community brand image.
Hyp. DesignationNull HypothesisSignificance *Decision
H1.1The distribution of “sleepy–lively” is the same across the categories of “Age group”.0.010Reject the null hypothesis.
H1.2The distribution of “inert–dynamic” is the same across the categories of “Age group”.0.168Retain the null hypothesis.
H1.3The distribution of “provincial–urban” is the same across the categories of “Age group”.0.617Retain the null hypothesis.
H1.4The distribution of “old-fashioned–modern” is the same across the categories of “Age group”.0.744Retain the null hypothesis.
H1.5The distribution of “aspiring–stagnating” is the same across the categories of “Age group”.0.04Reject the null hypothesis.
H1.6The distribution of “family friendly–not family friendly” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H1.7The distribution of “open–closed” is the same across the categories of “Age group”.0.001Reject the null hypothesis.
H1.8The distribution of “having doubts–confident” is the same across the categories of “Age group”.0.004Reject the null hypothesis.
H1.9The distribution of “pessimistic–optimistic” is the same across the categories of “Age group”.0.120Retain the null hypothesis.
H1.10The distribution of “safe–dangerous” is the same across the categories of “Age group”.0.144Retain the null hypothesis.
H1.11The distribution of “neat–neglected” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H1.12The distribution of “uncomfortable–comfortable” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H1.13The distribution of “friendly–unfriendly” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H1.14The distribution of “successful–unsuccessful” is the same across the categories of “Age group”.0.006Reject the null hypothesis.
H1.15The distribution of “attractive–unattractive” is the same across the categories of “Age group”.0.096Retain the null hypothesis.
* The asymptotic significance is displayed with the significance level for the hypothesis testing, set at a 0.05 level.
Table
Table 4. Mean values of the five generational cohorts regarding the community brand image.
Table 4. Mean values of the five generational cohorts regarding the community brand image.
Community Image Pairs (1—High, 5—Low)MeanGen. ZGen. YGen. XGen. BBGen. S
1 *Sleepy (1)—lively (5)2.692.972.612.612.882.72
2Inert (1)—dynamic (5)2.33 (5th)2.662.452.272.352.22
3Provincial (1)—urban (5)2.19 (2nd) 2.412.282.172.202.09
4Old-fashioned (1)—modern (5)2.58 (7th)2.692.632.622.622.32
5 *Aspiring (1)—stagnating (5)3.073.222.913.272.972.83
6 *Family friendly (1)—not family friendly (5)2.31 (4th)1.752.382.452.312.02
7 *Open (1)—closed (5)2.642.472.702.802.572.27
8 *Having doubts (1)—confident (5)2.683.032.862.762.632.25
9Pessimistic (1)—optimistic (5)2.863.002.992.942.852.51
10Safe (1)—dangerous (5)2.22 (3rd)1.942.242.262.312.06
11 *Neat (1)—neglected (5)2.55 (6th)2.092.382.552.732.65
12 *Uncomfortable (1)—comfortable (5)3.253.783.633.313.042.76
13 *Friendly (1)—unfriendly (5)2.09 (1st)2.252.182.292.041.47
14 *Successful (1)—unsuccessful (5)3.002.942.993.162.962.65
15Attractive (1)—unattractive (5)2.62 (8th)2.692.462.712.662.54
An asterisk (*) next to the number denotes a statistically significant difference between the age groups.
Table
Table 5. Kruskal–Wallis test results of the independent samples between the five age groups regarding priority fields of action in the community.
Table 5. Kruskal–Wallis test results of the independent samples between the five age groups regarding priority fields of action in the community.
Hyp. No.Null HypothesisSignificance *Decision
H2.1The distribution of “reducing bureaucracy in the community” is the same across the categories of “Age group”.0.071Retain the null hypothesis.
H2.2The distribution of “missing online forms for citizens” is the same across the categories of “Age group”.0.803Retain the null hypothesis.
H2.3The distribution of “reducing transit traffic” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.4The distribution of “rehabilitation of community finances” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.5The distribution of “supporting the economy” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.6The distribution of “broadband internet” is the same across the categories of “Age group”.0.265Retain the null hypothesis.
H2.7The distribution of “medical services” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.8The distribution of “better public transportation” is the same across the categories of “Age group”.0.391Retain the null hypothesis.
H2.9The distribution of “more parking spaces” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.10The distribution of “more retailers” is the same across the categories of “Age group”.0.175Retain the null hypothesis.
H2.11The distribution of “better gastronomy” is the same across the categories of “Age group”.0.147Retain the null hypothesis.
H2.12The distribution of “more educational facilities” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.13The distribution of “more voluntary engagement opportunities” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.14The distribution of “prettier city center” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
H2.15The distribution of “cultural offerings” is the same across the categories of “Age group”.<0.001Reject the null hypothesis.
* The asymptotic significance is displayed with the significance level for the hypothesis testing, set at a 0.05 level.
Table
Table 6. Mean values of the five generational cohorts regarding community development priorities.
Table 6. Mean values of the five generational cohorts regarding community development priorities.
Community Development Priorities (1—High, 5—Low)MeanGen. ZGen. YGen. XGen. BBGen. S
1Reducing bureaucracy in the community2.232.342.402.272.132.00
2Online forms for citizens2.342.442.342.392.372.15
3 *Reducing transit traffic2.183.002.422.241.971.80
4 *Rehabilitation of the community’s finances1.65 (4th)1.971.971.651.531.35
5 *Supporting the economy1.82 (5th)2.252.131.881.611.46
6Broadband internet1.46 (1st)1.381.591.471.371.41
7 *Medical services1.62 (3rd)1.941.721.751.371.39
8Better public transportation1.57 (2nd)1.471.741.601.481.42
9 *More parking spaces2.592.662.802.722.432.17
10More retailers2.282.812.322.262.262.15
11Better gastronomy2.362.842.412.352.252.33
12 *More educational facilities2.373.222.262.482.342.07
13 *More voluntary engagement opportunities2.413.132.442.522.192.17
14 *Prettier city center2.102.752.262.181.821.87
15 *Cultural offerings2.132.912.322.131.921.98
An asterisk (*) next to the number denotes a statistically significant difference between the age groups.
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Paunovic, I.; Müller, C.; Deimel, K. Citizen Participation for Sustainability and Resilience: A Generational Cohort Perspective on Community Brand Identity Perceptions and Development Priorities in a Rural Community. Sustainability 2023, 15, 7307. https://doi.org/10.3390/su15097307

AMA Style

Paunovic I, Müller C, Deimel K. Citizen Participation for Sustainability and Resilience: A Generational Cohort Perspective on Community Brand Identity Perceptions and Development Priorities in a Rural Community. Sustainability. 2023; 15(9):7307. https://doi.org/10.3390/su15097307

Chicago/Turabian Style

Paunovic, Ivan, Cathleen Müller, and Klaus Deimel. 2023. "Citizen Participation for Sustainability and Resilience: A Generational Cohort Perspective on Community Brand Identity Perceptions and Development Priorities in a Rural Community" Sustainability 15, no. 9: 7307. https://doi.org/10.3390/su15097307

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