Discovering the Radio and Music Preferences of Generation Z: An Empirical Greek Case from and through the Internet

Abstract

Generation Z’s members are considered to have a strong preference for streaming and on-demand media only. This article is dedicated to Generation Z and comes to investigate the triptych of attitudes, opinions, and behaviors regarding radio and music preferences of its members in Greece through an Internet survey. The research data were collected through a web-based questionnaire, while for the analysis, descriptive and inductive statistics were applied from and through Internet applications and services. The research results and findings confirm previous empirical studies and research regarding the radio, the genealogical characteristics, habits, and ethos of Generation Z as well as that Generation Z can also be characterized as a sound generation. Finally, these research results and findings are considered encouraging and could be leveraged primarily by the radio media ecosystem with the aim of reorganizing or decentralizing the radio for its future form.

1. Introduction

The media landscape is undergoing rapid growth and profound changes due to the convergence of media and Information and Communications Technologies (ICTs) over the past two decades (Dimoulas et al. 2018, 2015; Magnaye and Tarusan 2023; Podara 2021; Tomyuk and Avdeeva 2022). A characteristic typical paradigm of convergence is considered to be the case of radio that nowadays exists in a new era (Asy’ari 2018; Magnaye and Tarusan 2023; Puspitasari et al. 2020). This era is being heralded by media academics and radio professionals as radio era 2.0 (Puspitasari et al. 2020).

Unquestionably, radio through the years has meta-evolved, on the one hand, from analog and/or conventional to digital (Blair [1999] 2002; Flew [2002] 2014; Sellas 2013), and on the other hand, regarding global dissemination from satellite to today’s Internet radio (or otherwise web-radio) (Bonet et al. 2011; Matsiola 2008; Nicolaou et al. 2021b; Vryzas et al. 2020); however, this meta-evolution during the first years has not received the necessary attention from the media studies academic community and media landscape, and especially from the radio media ecosystem. More precisely, the occurrence of Internet radio has brought to the fore the crucial issue of maintaining the essential existence of radio stations, and by extension, the future of radio (see Tacchi 2000).

In summary, nowadays, radio is now considered a worldwide innovative medium, which is constantly meta-evolving without ever losing its identity in whatever form it takes, becoming one of the audience’s first choices (Karypidou 2006; Magnaye and Tarusan 2023; Nicolaou et al. 2021a, 2021b; Nu”azzidane and Sa’idah 2023; Okeke et al. 2020; Puspitasari et al. 2020; Setiawan et al. 2020). Additionally, due to this convergence, it is now possible to consume all kinds of audio content (i.e., from fantasy to informational) in even more genres and sound formats with a specific identity such as podcasts (Terol-Bolinches et al. 2022), which allows radio to reorganize or decentralize as well as to reach new target groups, such as Generation Z (i.e., people born from 1995 to 2012) (cf. Nicolaou and Matsiola 2023b).

Generation Z (GenZ) is one of the youngest generational cohorts with adult members who are characterized as digital natives due to being born within the Internet and social media era as well as to their early exposure to electronic gadgets (Nicolaou and Matsiola 2023b; Podara and Kalliri 2023; Podara 2021; Smaliukiene et al. 2020). Given the era in which they were born and their established habits of relying on technology and using only the Internet to consume audiovisual content via streaming and on-demand media, this generational cohort was prematurely baptized by academics as a visual generation or even a technology generation (Epafras et al. 2021; Nicolaou and Matsiola 2023b; Nicolaou 2023; Tarigan 2024; Treviño Benavides et al. 2023); however, recent empirical studies and research have shown that this generational cohort can also be characterized as a sound generation (Döring et al. 2022; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021a, 2021b).

GenZ’s study has gained a lot of worldwide academic attention in recent years (Nicolaou and Matsiola 2023b; Podara and Kalliri 2023), which has played a key role in its delineation; however, despite the rich literature of recent years regarding GenZ in general, there is a dearth of literature dedicated to the specific characterization of the generational cohort as a sound generation, thereby creating the relative gap in the literature. To be more precise, GenZ, and by extension its members, have been researched individually and through multiple different approaches, such as in relation to various music fields and/or podcasts or even radio (Cicchetti 2022; Galán-Arribas et al. 2022; Golden 2019; Saragih 2016; Xu 2022), but not under the spectrum of characterization that GenZ could be considered a sound generation.

Based on the aforementioned gap, the research purpose (RP) of this article is therefore to shed further light on the reported characterization of GenZ as a sound generation, opening a new chapter in the literature regarding the de novo delineation of this generational cohort. More concretely, is in our goal to investigate the triptych of attitudes, opinions, and behaviors of the members of GenZ in Greece, with respect to their radio and music preferences (i.e., sound preferences), thereby filling the existing gap in the literature and contributing to the current debate about the future of radio, and by extension the pantheon of radio studies which have been further revived during the COVID-19 pandemic due to the popularity of podcasts in the educational environment (Nicolaou et al. 2021a, p. 159).

In closing, it should be mentioned that this article is an integral part of a larger, ongoing original, innovative, multidisciplinary, and cross-cultural research project that incorporates media, audiovisual content, and education (henceforth, MACE). Notably, it investigates the employment of ICTs in Higher Education and Adult Education in Greece and Cyprus in the light of media studies and broadcast journalism, which started in 2016. Finally, the rest of the article is organized into three (3) additional sections: (a) Section 2 presents in-depth the framework of the applied research methodological approach; (b) Section 3 presents, justifies, and explains through discussion the research results and findings; and (c) Section 4 provides a sort of summary and conclusions.

2. Materials and Methods

This article presents the triptych of attitudes, opinions, and behaviors among GenZ’s adult members (i.e., 18 to 28 years old at the time the investigation was conducted) in relation to their radio and music preferences based on gender (i.e., male, female, and other). To complete this undertaking, two (2) research hypotheses were used, which emerged based on a review of relevant recent and global literature in relation to GenZ’s members and the new forms and services that arose through the convergence of media and ICTs such as eBooks, digital audiobooks, podcasts, and Internet radio, showing that gender does not appear to generally affect their respective use (see, for example, Döring et al. 2022; Galán-Arribas et al. 2022; Puspitasari et al. 2020; Srirahayu et al. 2022). More specifically, these two (2) research hypotheses will simultaneously contribute to the de novo delineation of the GenZ and the current debate about the future of radio:

H1. 

It is expected that there will be no significant statistical difference in attitudes, opinions, and behaviors among the genders of the research sample, since they belong to the same generational cohort; and finally

H2. 

It is expected that there will be a significant statistical difference in attitudes, opinions, and behaviors of the research sample among radio, podcasts, and music.

The article’s research implemented a web-based research methodology though questionnaire (hereinafter the Internet survey) as measuring instrument that followed our previous empirical studies and research in relation to GenZ (Matsiola et al. 2019; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021b). The design of the web-based questionnaire was also based on previous questionnaires, and to our knowledge, it is the first academic questionnaire-based study in exploring the radio and music preferences of GenZ in Greece, both during the research planning and the writing of this article. Also, it should be mentioned that this Internet survey, and by extension its research sample, constitutes one of the two sub-surveys (see Nicolaou et al. 2024) of a research project that aims to delineate the sound preferences of adult members of GenZ in Greece with a total of 239 participants (Nicolaou 2024).

The specific Internet survey was carried out in fall semester of the academic year 2023–2024 with undergraduate and postgraduate students of GenZ from Greece who are studying media studies at the School of Journalism and Mass Communications (SJMC) of the Aristotle University of Thessaloniki (AUTh). More concretely, it was implemented during November to December 2023 in two (2) phases (Section 2.3) after performing the preliminary study in June 2023 (Section 2.1), the relevant ethical approval and clearance from the Research Ethics Committee (REC) of the AUTh (192641/2023) in July 2023, and a pilot study in October 2023 (Section 2.2). At this point, and in order for the potential readers and researchers to better understand the inquiry stages of this research through the chronological implementation, the research timeline was created in the form of a chart, presented as Figure 1. Regarding the analysis of the research data, it was decided to apply the qualitative research methodology.

In summary, the rest of the section is organized into three (3) subsections and details the process of designing, validating, and implementing the web-based questionnaire used as well as the process of collecting and analyzing the research data. More precisely, (a) the first subsection presents the web-based questionnaire that is used as measuring instrument in this Internet survey (Section 2.1); (b) in the next subsection, the pilot study is presented in detail (Section 2.2); and finally, (c) the last subsection presents the collection, processing, and analysis of research data, including the name and version of the software used (Section 2.3).

2.1. Web-Based Questionnaire: The Measuring Instrument

The framework of the web-based questionnaire was based on previous research results and findings of our empirical studies and research with participants from Higher Education and Adult Education studying in the field of media studies (Matsiola et al. 2019; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021b). Likewise, the design of the web-based questionnaire was based on four (4) relevant tried and tested questionnaires which were re-tailored to create one based on three (3) pylons: radio, podcasts, and music. Specifically, the web-based questionnaire relied on (a) the research questionnaire of Podara and her collaborators regarding GenZ’s viewing habits (Podara et al. 2019, 2022); (b) Roussou’s research questionnaire regarding television (TV from here on) and the cultural identity of Greek-Cypriot youth (Roussou 2001, 1996); (c) the research questionnaire of Juslin and Laukka (2004) regarding expression, perception, and induction of emotion in the context of ordinary listeners’ interactions with music in everyday life; and finally, (d) the music USE (i.e., MUSE) questionnaire of Chin and Rickard (2012) regarding engagement in music which is based on the brief Music Experience Questionnaire of Werner and his collaborators (Werner et al. 2006) and the Emotion Regulation Questionnaire of Gross and John (2003).

After the initial drafting of the questionnaire in printed form, it had to pass the relevant testing (Papanastasiou and Papanastasiou 2005, p. 204). In this case, eight adults (18 years old and older), four volunteers from Greece and four volunteers from Cyprus, who had again participated in previous pilot studies of the research project MACE (see Nicolaou 2021, 2023), were conscripted to participate in the study’s primary validation via the form of an online focus group as a preliminary test (i.e., a kind of pre-test) (see Carpenter 2018, pp. 33–34) in June 2023—preliminary study. At this point, it should be mentioned that this conscription was necessary due to the fact that the research project MACE implements the methodological development (or the multi-methodological approach) (see Nicolaou et al. 2021a, p. 166). In addition, it should also be mentioned that the specific sample size of the preliminary study involved is considered acceptable in the context of a pre-test (i.e., 5 to 100 participants) (Carpenter 2018, pp. 33–34), while it is characterized as a convenience sample (see Kontogiannatou 2018, p. 104). Subsequently, the collected information from online focus group was studied, analyzed, and implemented in the questionnaire. Overall, there was no ambiguity in the phrasing of questions, and the questionnaire was ready to be converted into a digital version, so that it could then be submitted to the competent REC of the AUTh for the relevant ethical approval and clearance.

The final web-based questionnaire was developed based on the relevant guidelines in the literature (Papanastasiou and Papanastasiou 2005; Papanis 2011; Williams 2003) and consisted of 26 final questions (i.e., 23 closed-ended single-choice with Likert scale or multiple-choice questions and 3 open-ended qualitative questions) through forced-choice: (a) 3 demographic questions; (b) 7 questions related to radio; (c) 4 questions related to sound platforms and podcasts; and (d) 12 questions related to music. Finally, the web-based questionnaire was intended to be answered by both Greek and Greek-Cypriot prospective participants of GenZ studying at SJMC, and it was developed through the online hosting platform EUSurvey which is proposed by the European Commission for reasons of compliance and safeguarding of personal data based on the General Data Protection Regulation (GDPR) (EUR-Lex 2016).

2.2. Pilot Study

Before conducting the final Internet survey, a pilot study was conducted to ascertain the effectiveness of the web-based questionnaire and identify or correct any errors so that necessary corrective interventions could be made in time (see Siardos 2005, p. 197). Similarly, the study needed to achieve a kind of double cross-cultural adaptation (see also Nicolaou and Matsiola 2023a), due to the fact that the original research project MACE, as mentioned above, is carried out simultaneously in two (2) countries (i.e., Greece and Cyprus). To summarize, the pilot study was conducted as a method of checking the validity of the final Internet survey (see Papanastasiou and Papanastasiou 2005), while it was decided that its evaluation would be in three (3) successive phases in October 2023 with a total sample of 31 people, which is considered an indicated acceptable fidelity for a pilot study based on the literature (i.e., 26 to 34 participants ensure 75–100% reliability, respectively) (Lewis et al. 2021), while meeting the requirements proposed by the Central Limit Theorem (CLT) for the research sample’s total number for a survey (i.e., ≤30 participants) (Chang et al. 2006; Memon et al. 2020):

• The first phase served as a pre-test, where the selected participating sample answered the web-based questionnaire in printed form in the presence of the main researcher/principal investigator, in order for the participants to provide any feedback or comments. Notably, a total of 18 GenZ’s students with different origins (i.e., Cyprus, Greece, Russia, and Bulgaria) were randomly selected from KES College in Cyprus. The specific students attended the fall semester of the academic year 2023–2024 in the Greek course in “Principles of Public Relations” of the Office Administration and Secretarial Studies program of the School of Business and Administration Studies or the Greek course in “Principles of Marketing” of the Medical Representatives Management program of the School of Health Studies or the Greek courses in “Public Relations Campaigns” and “Crisis Management and Public Relations” of the Journalism with Public Relations program of the School of Journalism and Media Studies. Additionally, the particular participant sample is characterized as a convenience sample (see Kontogiannatou 2018, p. 104), while its size is considered acceptable in the context of a pre-test (i.e., 5 to 100 participants) (Carpenter 2018, pp. 33–34);
• The second phase served as expert feedback and was in the form of an online focus group. Specifically, nine adults from Greece with backgrounds in humanities, mass media, and audiovisual industry, who had again participated in previous pilot studies of the research project MACE, were conscripted to participate (Nicolaou et al. 2022). Obviously, the specific sample is also characterized as a convenience sample (see Kontogiannatou 2018, p. 104). This specific phase, due to the methodological approach applied, could also be considered a pre-test (Carpenter 2018, pp. 33–34) or a kind of pre-pilot test, because the participants also answered the web-based questionnaire at the end of online focus group, giving comments and observations; and finally
• The third and final phase served as a pilot test, involving four Greek graduate postgraduate students of the SJMC and members of GenZ. Participants are also designated as a convenience sample (see Kontogiannatou 2018, p. 104), and their task was to participate in a rehearsal of the Internet survey in real field conditions, in order to estimate the time required to complete the web-based questionnaire.

In conclusion, the diverse interculturality and cross-cultural aspect of the pilot study, as well as the different backgrounds of the participants involved in this, obviously ensure the face and content validity (Papanastasiou and Papanastasiou 2005, pp. 159–61), and the reliability of the web-based questionnaire (Nicolaou and Matsiola 2023a; Papanastasiou and Papanastasiou 2005; Thabane et al. 2010). Additionally, the web-based questionnaire showed no ambiguities in the wording of the questions by all participants who took part in the pilot study. Moreover, some of the participants during the first and second phases indicated that having examples in some questions was considered necessary and helpful. Finally, the size of the web-based questionnaire did not cause fatigue or irritation, and it could be completed in less than five minutes.

2.3. Research Data Collection, Processing, and Analysis

Implicit objective of the Internet survey was to collect at least 100 digital questionnaires, which would be enough to cover the needs of a study (Comrey and Lee [1992] 2016). The research data collection was carried out in two (2) phases through the aforementioned online hosting platform EUSurvey, adopting the rules of skip logic through 13 section breaks with 32 forced choices via the associated uniform resource locator (URL) address. More precisely, the associated URL address of the hosting platform (a) was sent to all registered and active undergraduate and postgraduate students of the SJMC to be completed at their own convenience via the official mailing list from the central services of the Institution by SJMC’s secretariat at the beginning of November 2023 (first phase), and (b) announced through a post on the official closed Facebook group of the SJMC at the end of November 2023 as an online expression of interest in participating in an Internet survey (second phase). At this point, it should be said that initially the research data collection would only be implemented through the first phase; however, after a week, since sending the web-based questionnaire via electronic mail (or e-mailing or e-mail or email or mail) (email from here on) the required research sample number had not been collected, it was decided to implement the second phase.

The associated URL address from the online hosting platform EUSurvey included, in addition to the questions, a preface about the research context, stating and explaining the aims and procedure, and emphasizing anonymity, while thanking the participants at the end. Also, the main researcher/principal investigator periodically checked the aforementioned online hosting platform regarding the number of volunteers who had answered the web-based questionnaire, and as soon as the required number of participations was collected (i.e., at least 100), he locked access for the associated URL address in early December 2023.

The acquired research data were coded based on the new and modern research methodological approaches as well as from and through Internet applications and services. Notably, they were entered into the specialized online platform ‘Survs.com’ as well as into the IBM Statistical Package for Social Sciences (SPSS) (version 29), which were the software chosen for the descriptive and statistical analysis. Furthermore, some of the selected research data were also analyzed through SPSS by one-way analysis of variance (i.e., one-way ANOVA) based on gender, while some others were analyzed with Pearson’s r correlation. Additionally, for the purposes of this article, only 19 of the 26 final questions included in the questionnaire were studied, analyzed, and presented in this article. To be more precise, they were grouped in the following four (4) sections to assist us in our analysis:

• The first section consists of three (3) demographic questions (i.e., gender—male, female, and other; age groups: 18–21 years old, 22–25 years old, and 26–28 years old; and place of residence—13 administrative peripheries of Greece);
• The second section consists of six (6) questions regarding radio: (a) whether they listen to the radio with a closed-ended single-choice (i.e., ‘YES’ or ‘NO’); (b) the daily listening hours with a closed-ended single-choice (i.e., less than 1 h daily, 1–2 h daily, 2–3 h daily, 3–4 h daily, and more than 4 h daily); (c) the times of listening during day (i.e., morning, midday, afternoon, night, and after midnight) with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’); (d) what radio shows and programs they usually listen to through 10 multiple-choices that were formally validated after the end of the preliminary study (i.e., news shows, entertainment shows, talk shows, political shows, educational shows, cultural shows, religious shows, theater shows, another radio shows, and music radio stations); (e) whether they listen to the radio to pass the time without being interested with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’); and (f) whether they listen to the radio to keep them company when they are at home with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’);
• The third section consists of three (3) questions about podcasts: (a) whether they listen to podcasts with a closed-ended single-choice (i.e., ‘YES’ or ‘NO’); (b) the daily listening hours with a closed-ended single-choice (i.e., less than 1 h daily, 1–2 h daily, 2–3 h daily, 3–4 h daily, and more than 4 h daily); and (c) what podcast genres they usually listen to through 18 multiple-choices that were formally validated after the end of the preliminary study (i.e., true crimes, self-improvement, comedies, health and fitness, sports, movies, TV series, TV shows, news, technology, financial news/analysis, politics, educational shows, culture, science, religious, music, and another kind); and finally
• The fourth section consists of seven (7) questions related to music: (a) whether they listen to music with a closed-ended single-choice (i.e., ‘YES’ or ‘NO’); (b) the daily listening hours with a closed-ended single-choice (i.e., less than 1 h daily, 1–2 h daily, 2–3 h daily, 3–4 h daily, and more than 4 h daily); (c) the times of listening during day (i.e., morning, midday, afternoon, night, and after midnight) with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’); (d) ways of being informed on how to discover new songs and music or what they are listening to through 19 multiple-choices that were formally validated after the end of the preliminary study, which were also grouped and adjusted through 7 and 6 multiple choices, respectively, for presentation needs and better understanding (i.e., friends, family, printed media, radio, TV, and Internet—social media and new media); (e) what are the factors that influence their music preferences through 13 multiple-choices that were formally validated after the end of the preliminary study, which were grouped and adjusted through 6 multiple choices for presentation needs and better understanding (i.e., friends, family, printed media, radio, TV, and Internet); (f) whether they listen to music to pass the time without being interested with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’); and (g) whether they listen to music to keep them company when they are at home with a five-point Likert scale (i.e., ‘NEVER’, ‘SOMETIMES’, ‘OFTEN’, ‘VERY OFTEN’, and ‘ALWAYS’).

In closing, all research results and findings are presented in the next section (Section 4), following the relevant literature which is based on the guidelines from the American Psychological Association (APA) (Papanastasiou and Papanastasiou 2005, pp. 324–33; Siardos 2005, pp. 251–57). More concretely, they are presented after relevant analysis through SPSS and ‘Survs.com’ as (a) tables—either overall, or individually, also in single tables, in double entry tables with frequencies and/or relative frequencies (i.e., percentages), average values (or mean values; MEAN), and standard deviations (SD) based in part on the most recent APA style guide (American Psychological Association 2020) (at the time of writing this article); or even in (b) graph or diagram form (i.e., as figures) through various types of charts, as is also stated in the relevant literature in order to be more manageable and easily visually understandable as well as to distinguish the created sections, or the type or the categorization and/or the grouping of the selected questions from the questionnaire by potential readers and researchers based on the analysis that has been carried out (see Coffey and Atkinson 1996; Fink 1995; Flick [1995] 2009). Summing up, it should also be noted that descriptive and inductive statistics were applied for this analysis from and through Internet applications and services, while (a) Microsoft Excel 365^® (version 2403), (b) Microsoft PowerPoint 365^® (version 2403), (c) Microsoft Paint (version 22H2), and (d) the specialized online platform Piktochart were used to visualize the research data in interactive color infographics based on the recommended color palettes that are suggested by them for better understanding (cf. Kalliri and Veglis 2022; Karypidou and Veglis 2022; Karypidou et al. 2019).

3. Research Results and Findings through Discussion

In this section, the research results and findings are provided through discussion. Notably, to better present the research data, this section has been organized into three (3) subsections: (a) Section 3.1 presents the description statistic of the research sample’s characteristics; (b) Section 3.2 presents the radio and music preferences of GenZ’s participants; (c) Section 3.3 presents the statistical criteria from the one-way ANOVA and the correlations regarding the frequency of daily listening hours for radio, podcasts, and music; and finally, (d) Section 3.4 presents the general profile of the GenZ’s participants who took part in the Internet survey resulting from additional correlations in relation to radio and music, as a conclusion.

3.1. Research Sample Characteristics and Descriptive Statistics

The final research sample of this Internet survey consisted of 125 active undergraduate and postgraduate students of GenZ (i.e., 18 to 28 years old at the time the Internet survey was conducted) from SJMC, which is considered sufficient to cover the needs of a study (i.e., ≥100 participants) (Comrey and Lee [1992] 2016). Likewise, it is also suitable for conducting a behavioral study (i.e., 30 to 500 participants) (Roscoe 1975) such as this one, while covering the requirements proposed by the Central Limit Theorem (CLT) for the research sample’s total number for a survey (i.e., ≤30 participants) (Chang et al. 2006; Memon et al. 2020). Additionally, it represents ~0.14 of the students studying at AUTh as well as ~24% of all active undergraduate and postgraduate students studying at SJMC, a percentage which, based on the literature, is sufficient to implement a valid study (i.e., ≥10%) (Comrey and Lee [1992] 2016).

Undoubtedly, the selection of this particular research sample is not considered random at all. In continuation of the research results and findings of our previous empirical studies and research (Matsiola et al. 2019; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021b), which also provided the inspiration for this Internet survey, their participants were also GenZ’s students or learners studying media studies in Higher Education and/or Adult Education in Greece. Additionally, students and learners in the field of media studies, based on the literature, indicate that they can more readily adopt new technological innovations and approaches than other academic programs and professions (Matsiola et al. 2019; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021b; Paschalidis and Milioni 2010; Podara 2021; Podara and Kalliri 2023; Podara et al. 2019, 2022); therefore, this choice was inevitable, while it was considered the ideal research sample to investigate the triptych of attitudes, opinions, and behaviors in relation to their radio and music preferences from and through the Internet.

At this point, it should be mentioned that until the posting of the relevant URL address in the official closed Facebook group of the SJMC for voluntary participation in the Internet survey, the web-based questionnaire was answered by only 68 of the 125 participants (with a percentage of 54.4%) (Figure 2 and

Table 1. Research participant details per phase based on age groups.

Age Groups	First Phase	Second Phase	Subtotal
18–21 years old	33–48.5%	43–75.4%	76–60.8%
22–25 years old	26–38.2%	9–15.8%	35–28%
26–28 years old	9–13.3%	5–8.8%	14–11.2%
18–25 years old	59–86.7%	52–91.2%	111–88.8%
22–28 years old	35–51.5%	14–24.6%	49–39.2%
Subtotal	68–54.4%—100%	57–45.6%—100%	125–100%

) who were included as the final research sample. Specifically, from the statistical analysis it was discovered that during the first phase, by sending the web-based questionnaire via email, the age of the GenZ’s participants ranged in age groups 22–28 years old (i.e., 35 out of 68 participants with a percentage of 51.5%) (Figure 2 and Table 1), while during the second phase with the expression of interest via the official closed Facebook group of the SJMC, the age of the GenZ’s participants was by far from age group 18–21 years old (i.e., 43 out of 57 participants with a percentage of 75.4%) (Figure 2 and Table 1). This research finding is very interesting because it corroborated the relevant literature which supports that GenZ’s members as a communication channel seem to use social media more than other members of older generational cohorts (Carr and Bard 2023; Fietkiewicz et al. 2016), such as members of Generation Y (or otherwise Millennium Generation) (i.e., people born from 1980 to 1994) (cf. Nicolaou 2023) who tend to use email (Williams and Page 2011; Williams et al. 2010). Notably, the GenZ’s members find it perfectly normal to receive important information via Facebook Messenger or ask their university professor about their queries via Viber (Podara 2021, p. 90). Furthermore, it should be mentioned that the linguistic way of writing both the email and the Facebook post may also have played a key and decisive role in attracting GenZ’s members to participate in the Internet survey based on their age group. More concretely, the email was written based on the model business documents (cf. Taylor 2004), while the Facebook post was written based on the GenZ’s norma of verbal and non-verbal communication style (e.g., emojis) (cf. Nicolaou 2023; Nicolaou and Matsiola 2023b) as well as the modern suggested social media techniques (cf. Nicolaou 2023) (Figure 3). Admittedly, if this has played a role in their participation in the Internet survey, then it opens a new chapter for how emails or even other business documents are written from here on out. Likewise, maybe it’s time to change the way we communicate in writing today or education may be failing to fulfill its important role, something that should definitely be explored further.

Regarding the origin of the participants, the whole of the research sample that answered the web-based questionnaire originates only from Greece, and specifically from the thirteen (13) administrative peripheries of Greece (Figure 4), making the specific Internet survey an empirical Greek case study. More precisely, the largest percentage comes from Central Macedonia (i.e., 71 out of 125 participants with a percentage of 56.8%) (Figure 4), which is partly justified given that both the SJMC and the AUTh are based in this administrative periphery. Additionally, the aftermath of the Greek crisis in 2009 to 2018, and by extension the Cypriot crisis in 2012 to 2013, as well as the consequences of a series of local or even world events (e.g., the refugee/migrant crisis, the COVID-19 pandemic, the new forms of climate change, the energy crisis, the ongoing threat of a new world war, etc.) (Nicolaou 2023, p. 9), have forced the majority of GenZ’s students to choose universities or colleges or even Vocational Training Institutes that are close to their homes or hometown, because they did not have or do not have the financial support to leave their city or region or even country (Podara et al. 2019, 2022), something which seems to be the case in Cyprus due to the fact that no potential Greek-Cypriot students from GenZ answered the web-based questionnaire. Likewise, it also leads us to the safe conclusion that Greek students from GenZ may be more willing to answer web-based questionnaires than Greek-Cypriot students from GenZ, something that should be studied further.

The statistical distribution of the variable of gender of research participants was (a) 79 females with a percentage of 63.2%; (b) 40 males with a percentage of 32%; and (c) 6 others with a percentage of 4.8% (Figure 5 and

Table 2. Demographics of research participants by age group and gender.

Gender	18–21 Years Old			22–25 Years Old			26–28 Years Old			Subtotal
	N	%		N	%		N	%		N	%
Female	53	69.7	42.4	18	51.4	14.5	8	57.1	6.3	79	63.2
Male	20	26.3	16	14	40	11.2	6	42.9	4.8	40	32
Other	3	4	2.4	3	8.6	2.4	-	-	-	6	4.8
Subtotal	76	100	60.8	35	100	28.1	14	100	11.1	125	100

). Undeniably, this research finding is considered to be reproducible due to the fact that it seems to be a common phenomenon that females generally outperform as a research sample in empirical studies, especially in various empirical studies and research conducted in Greece (cf. Matsiola et al. 2019; Manolika et al. 2022; Nicolaou et al. 2021a; Podara 2021).

Finally, let us mention that the statistical distribution of the variable of GenZ’s age groups of research participants was (a) 76 participants 18–21 years with a percentage of 60.8% (specifically, 53 females with a percentage of 69.7%—42.4%, 20 males with a percentage of 26.3%—16%, and 3 others with a percentage of 4%—2.4%); (b) 35 participants 22–25 years with a percentage of 28.1% (specifically, 18 females with a percentage of 22.8%—51.4%, 14 males with a percentage of 35%—40%, and 3 others with a percentage of 30%—8.6%); and (c) 14 participants 26–28 years with a percentage of 11.1% (specifically, 8 females with a percentage of 57.1%—6.3% and 6 males with a percentage of 42.9%—4.8%) (Figure 2, and Table 1 and Table 2).

3.2. Radio and Music Preferences—RP

According to the visualization percentages in Figure 6 and the research sample’s mean values based on daily listening hours in the triptych of radio, podcasts, and music in

Table 3. Detailed and grouped responses of the research sample regarding the frequency of daily listening hours for radio, podcasts, and music.

	Sample Listening	Sample Not Listening	N	Less than 1 h Daily	1–2 h Daily	2–3 h Daily	3–4 h Daily	More than 4 h Daily	N	MEAN	SD
RADIO	112–89.6%	13–10.4%	125	72–64.3%	25–22.3%	10–8.9%	2–1.8%	3–2.7%	112	1.56	0.928
PODCASTS	97–77.6%	28–22.4%		66–68%	24–24.7%	6–6.2%	1–1%	-	97	1.40	0.656
MUSIC	125–100%	-		10–8%	20–16%	21–16.8%	20–16%	54–43.2%	125	3.70	1.374

and

Table 4. Detailed and grouped responses of the research sample regarding the frequency of daily listening hours for radio, podcasts, and music based on gender.

	Gender	Sample Listening	Sample Not Listening	N	Less than 1 h Daily	1–2 h Daily	2–3 h Daily	3–4 h Daily	More than 4 h Daily	N	MEAN	SD
RADIO	Female	73–92.4%	6–7.6%	125	49–67.1%	18–24.7%	6–8.2%	-	-	112	1.41	0.642
	Male	35–87.5%	5–12.5%		22–62.9%	4–11.4%	4–11.4%	2–5.7%	3–8.6%		1.86	1.332
	Other	4–66.7%	2–33.3%		1–25%	3–75%	-	-	-		1.75	0.500
PODCASTS	Female	65–82.3%	14–17.7%	125	49–75.4%	11–16.9%	4–6.2%	1–1.5%	-	97	1.34	0.668
	Male	27–67.5%	13–32.5%		15–55.6%	10–37%	2–7.4%	-	-		1.52	0.643
	Other	5–83.3%	1–16.7%		2–40%	3–60%	-	-	-		1.60	0.548
MUSIC	Female	79–100%	-	125	5–6.3%	10–12.7%	18–22.8%	16–20.3%	30–38%	125	3.71	1.273
	Male	40–100%	-		5–12.5%	10–25%	-	4–10%	21–52.5%		3.65	1.610
	Other	6–100%	-		-	-	3–50%	-	3–50%		4.00	1.095

obtained from the statistical analysis, the research results and findings are interesting. Likewise, they help to reject the H1 and to confirm the H2. More specifically, it is observed that the higher mean value is derived for music (i.e., all participants surveyed with a percentage of 100%) (MEAN: 3.70 and SD: 1.374) (Table 3) and in particular from the female participants (i.e., 79 participants with a rate of 63.2%) (MEAN: 3.71 and SD: 1.273) (Table 4), followed by radio (i.e., 112 out of 125 participants with a percentage of 89.6%) (MEAN: 1.56 and SD: 0.928) (Table 3) with the male participants (i.e., 35 out of 125 participants with a percentage of 87.5%) (MEAN: 1.86 and SD: 1.332) (Table 4), and podcasts (i.e., 97 out of 125 participants with a percentage of 77.6%) (MEAN: 1.40 and SD: 0.656) (Table 3) with the other participants (i.e., 5 out of 125 participants with a percentage of 83.3%) (MEAN: 1.60 and SD: 0.548) (Table 4). Undeniably, the remarkable research finding here is not the greatest preference from the participants to music, but the fact that the participants listen to the radio, thereby debunking the prevailing view that almost all people rarely listen to the radio anymore (cf. Nu”azzidane and Sa’idah 2023; Puspitasari et al. 2020), and especially the GenZ’s members who appear to consume only visual content (cf. Puspitasari et al. 2020; Smaliukiene et al. 2020); after all, there are many empirical studies and research that have examined the effects of music in various fields (e.g., emotion in music, music use in sport and exercise, connections between music, business, and management, etc.) (Chin and Rickard 2012; Hallett and Lamont 2016; Juslin and Laukka 2004; Pizzolitto 2023). Now as to the research results and findings for the podcasts, they confirm the research results and findings of research by Galán-Arribas and his colleagues that investigated the impact of podcasts on GenZ’s members (Galán-Arribas et al. 2022).

Also of notable interest are the research results and findings deriving from the radio shows and programs (Figure 7) and podcast genres (Figure 8) that the survey’s participants listen to. Similarly, the time of the day they listen to the radio (Figure 9 and Figure 10,

Table 5. Detailed and grouped responses in terms of the time of listening to the radio.

	NEVER	SOMETIMES	OFTEN	VERY OFTEN	ALWAYS	N	MEAN	SD
Early in the Morning (06:00–10:00)	58–51.8%	26–23.2%	17–15.2%	5–4.5%	6–6.4%	112	1.88	1.153
Morning (10:00–14:00)	19–17%	46–41.1%	33–29.5%	11–9.8%	3–2.7%	112	2.40	0.972
Midday (14:00–16:00)	30–26.8%	48–42.9%	26–23.2%	8–7.1%	-	112	2.11	0.884
Afternoon (16:00–21:00)	19–17%	41–36.6%	36–32.1%	13–11.6%	3–2.7%	112	2.46	0.995
Night (21:00–00:00)	32–28.6%	38–33.9%	23–20.5%	16–14.3%	3–2.7%	112	2.29	1.110
After Midnight (00:00–06:00)	56–50%	40–35.7%	7–6.3%	7–6.3%	2–1.8%	112	1.74	0.956

and

Table 6. Grouped responses with MEAN and SD in terms of the time of listening to the radio based on gender.

		Early in the Morning (06:00–10:00)	Morning (10:00–14:00)	Midday (14:00–16:00)	Afternoon (16:00–21:00)	Night (21:00–00:00)	After Midnight (00:00–06:00)
Female	N	73	73	73	73	73	73
	Mean	1.85	2.44	2.14	2.59	2.23	1.60
	SD	1.175	0.943	0.918	0.925	1.034	0.795
Male	N	35	35	35	35	35	35
	Mean	1.86	2.29	2.06	2.09	2.26	1.86
	SD	1.141	1.073	0.873	1.011	1.221	1.115
Other	N	4	4	4	4	4	4
	Mean	2.75	2.75	2.00	3.50	3.50	3.25
	SD	0.500	0.500	0.000	1.000	1.000	0.957
Subtotal	N	112	112	112	112	112	112
	Mean	1.88	2.40	2.11	2.46	2.29	1.74
	SD	1.153	0.972	0.884	0.995	1.110	0.956

) and music (Figure 11 and Figure 12,

Table 7. Detailed and grouped responses in terms of the time of listening to music.

	NEVER	SOMETIMES	OFTEN	VERY OFTEN	ALWAYS	N	MEAN	SD
Early in the Morning (06:00–10:00)	41–32.8%	26–20.8%	23–18.4%	16–12.8%	19–15.2%	125	1.21	0.408
Morning (10:00–14:00)	3–2.4%	31–24.8%	35–28%	34–27.2%	22–17.6%	125	1.25	0.434
Midday (14:00–16:00)	9–7.2%	15–12%	35–28%	43–34.4%	23–18.4%	125	1.12	0.326
Afternoon (16:00–21:00)	4–3.2%	10–8%	26–20.8%	54–43.2%	31–24.8%	125	1.08	0.272
Night (21:00–00:00)	2–1.6%	16–12.8%	25–20%	46–36.8%	36–28.8%	125	1.13	0.335
After Midnight (00:00–06:00)	17–13.6%	28–22.4%	19–15.2%	36–28.8%	25–20%	125	1.22	0.419

and

Table 8. Grouped responses with MEAN and SD in terms of the time of listening to music based on gender.

		Early in the Morning (06:00–10:00)	Morning (10:00–14:00)	Midday (14:00–16:00)	Afternoon (16:00–21:00)	Night (21:00–00:00)	After Midnight (00:00–06:00)
Female	N	79	79	79	79	79	79
	MEAN	1.25	1.29	1.10	1.08	1.14	1.23
	SD	0.438	0.457	0.304	0.267	0.348	0.422
Male	N	40	40	40	40	40	40
	MEAN	1.15	1.20	1.18	1.10	1.13	1.18
	SD	0.362	0.405	0.385	0.304	0.335	0.385
Other	N	6	6	6	6	6	6
	MEAN	1.00	1.00	1.00	1.00	1.00	1.50
	SD	0.000	0.000	0.000	0.000	0.000	0.548
Subtotal	N	112	112	112	112	112	112
	MEAN	1.88	2.40	2.11	2.46	2.29	1.74
	SD	1.153	0.972	0.884	0.995	1.110	0.956

), something which should be taken very seriously by senior management in the radio media ecosystem, and by extension in the media landscape in order to utilize the present research results and findings to reorganize radio or even to develop a more effective strategy communication (Asy’ari 2018; Barrios-Rubio 2021; Nu”azzidane and Sa’idah 2023; Pandusaputri et al. 2024; Pilitsidou et al. 2019). At this point, it should be mentioned that the day was categorized into six (6) dayparts after and since the implementation of the preliminary study, namely (a) early in the morning between 06:00 to 10:00; (b) morning between 10:00 to 02:00; (c) midday between 02:00 to 16:00; (d) afternoon between 16:00 to 21:00; (e) night between 21:00 to 00:00; and (f) after midnight between 00:00 to 06:00.

Based on the above statistical analyses, we see that most research participants sometimes listen to the radio mainly at midday (i.e., 48 out of 112 participants with a percentage of 42.9%) (MEAN: 2.11 and SD: 0.884) (Figure 9 and Figure 10, Table 5 and Table 6) and radio stations that only play music (i.e., 90 out of 112 participants with a percentage of 80.4%) (Figure 7) and especially the GenZ’s females (i.e., 62 out of 112 participants with a percentage of 84.9%) (Figure 13); thereby also confirming the research results and findings of a corresponding research by Puspitasari and her colleagues which state that GenZ’s members like to listen to radio without many commercial advertisements because what they really like is to listen to only the songs that are being broadcasted (Puspitasari et al. 2020, pp. 64–65). In addition, they very often listen to music mainly at afternoon (i.e., 54 out of 125 participants with a percentage of 43.2%) (MEAN: 1.08 and SD: 0.272) (Figure 11 and Figure 12, Table 7 and Table 8), night (i.e., 46 out of 125 participants with a percentage of 36.8%) (MEAN: 1.13 and SD: 0.335) (Figure 11 and Figure 12, Table 7 and Table 8), and midday (i.e., 43 out of 125 participants with a percentage of 34.4%) (MEAN: 1.12 and SD: 0.326) (Figure 11 and Figure 12, Table 7 and Table 8). Furthermore, they listen to podcasts with an emphasis on specific themes, such as, for example, true crime (i.e., 33 out of 97 participants with a percentage of 34%) (Figure 8), comedies (i.e., 29 out of 97 participants with a percentage of 29.9%) (Figure 8), and self-improvement (i.e., 26 out of 97 participants with a percentage of 26.8%) (Figure 8), something that is really interesting if we consider the genealogical characteristics, habits, and ethos of this generational cohort (Nicolaou and Matsiola 2023b; Podara 2021; Podara and Kalliri 2023; Podara et al. 2019, 2022), while further examination of the underlying motivations to listen to podcasts is warranted. Summing up, therefore, all these research results and findings also help to reject the H1 and to confirm the H2, while at the same time providing the impetus for further investigation. Finally, more detailed research results and findings can be found in Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12 and Figure 13 and Table 5, Table 6, Table 7 and Table 8.

In closing, it is worth mentioning that the largest amount of the survey’s participants sometimes listen to the radio without interest and enthusiasm (i.e., 45 out of 112 participants with a percentage of 40.2%) (MEAN: 2.41 and SD: 0.935) (

Table 9. Detailed and grouped responses of the sample regarding the radio and music habits.

	NEVER	SOMETIMES	OFTEN	VERY OFTEN	ALWAYS	N	MEAN	SD
I listen to the radio to pass the time without being interested.	18–16.1%	45–40.2%	36–32.1%	11–9.8%	2–1.8%	112	2.41	0.935
I listen to music to pass the time without being interested.	9–7.2%	23–18.4%	42–33.6%	30–24%	21–16.8%	125	3.25	1.155
I listen to the radio to keep me company when I’m at home.	33–29.5%	36–32.1%	17–15.2%	16–14.3%	10–8.9%	112	2.41	1.291
I listen to music to keep me company when I’m at home.	3–2.4%	13–10.4%	27–21.6%	39–31.2%	43–34.4%	125	3.85	1.086

), while in relation to music often (i.e., 42 out of 125 participants with a percentage of 33.6%) (MEAN: 3.25 and SD: 1.155) (Table 9). Likewise, when they are at home, most of the participants sometimes have the radio to keep them company at home (i.e., 36 out of 112 participants with a percentage of 32.1%) (MEAN: 2.41 and SD: 1.291) (Table 9) like other peers (Robert-Agell et al. 2022), while in relation to music, most of them they always listen to music when they are at home (i.e., 43 out of 125 participants with a percentage of 34.4%) (MEAN: 3.85 and SD: 1.086) (Table 9), thus confirming the relevant literature that states that most people of all ages tend to listen to music when they are at home and/or doing other activities at the same time (Boal-Palheiros and Hargreaves 2001; Gazi et al. 2014; Juslin and Laukka 2004). Additionally, their musical preferences are mainly influenced by their friendly environment (i.e., 85 out of 125 participants with a percentage of 68%) (Figure 14 and

Table 10. Grouped responses with frequencies and percentages as to the influences of music preferences based on gender.

Gender	Friends	Family	Social Media Friends	Advertisements	Background Music	Personal Choice	N
Female	52–65.8%	32–40.5%	22–27.8%	37–46.8%	37–46.8%	47–59.5%	79
Male	27–67.5%	11–27.5%	16–40%	10–25%	14–35%	18–45%	40
Other	6–100%	-	6–100%	4–66.7%	3–50%	-	6
Subtotal	85–68%	43–34.4%	44–35.2%	51–40.8%	54–43.2%	65–52%	125

), thus confirming the literature that GenZ’s members share content with their friends on social media, as well as that they detect the content (e.g., news, music, video, etc.) through sharing made by their friends-followers (i.e., social media friends) on social media (Galán-Arribas et al. 2022; Podara 2021). Similarly, the ways of being informed about new songs and music or what they listen to are mainly influenced by their friendly environment again (i.e., 77 out of 125 participants with a percentage of 61.6%) (Figure 15 and Figure 16, and

Table 11. Grouped responses with frequencies and percentages on how they find out about new songs and music or what they listen to, based on gender.

Gender	Friends	Family	Printed Media	Radio	TV	Internet	N
Female	49–62%	22–27.8%	2–2.5%	21–26.6%	19–24.1%	77–97.5%	79
Male	22–55%	3–7.5%	6–15%	9–22.5%	9–22.5%	40–100%	40
Other	6–100%	3–50%	-	-	1–16.7%	6–100%	6
Subtotal	77–61.6%	28–22.4%	8–6.4%	30–24%	29–23.2%	123–98.4%	125

) and the Internet (i.e., 123 out of 125 participants with a percentage of 98.4%) (Figure 15 and Figure 16, and Table 11), and more specifically from social media (i.e., 117 out of 125 participants with a percentage of 93.6%) (Figure 15 and Figure 16), but also from the foreign series they watch from international subscription-based online audiovisual platforms (e.g., Netflix, Disney+, Amazon Prime Video, Max, Apple TV+, etc.) (i.e., 46 out of 125 participants with a percentage of 36.8%) (or otherwise new media) (Figure 15 and Figure 16), something which should be taken very seriously by senior management in the radio media ecosystem, and by extension in the media landscape as well as audiovisual industry for the application or implementation or even exploitation of sensory marketing, especially audio marketing (Čvirik and Naďová Krošláková 2022), since these research results and findings also presented in other global empirical studies and research (see also Galán-Arribas et al. 2022; Gazi et al. 2014). Moreover, a remarkable research result and finding is also the fact that the GenZ’s participants of this study seem to be rather affected by advertisements (i.e., 51 out of 125 participants with a percentage of 40.8%) (Figure 14 and Table 10) or even their background music (i.e., 54 out of 125 participants with a percentage of 43.2%) (Figure 14 and Table 10), something that should be studied further since research has shown that radio audiences tend to be influenced by radio advertising (Flaherty et al. 2004) or even by radio messages to raise awareness with burning issues (e.g., blood donation, smoking, driving under the influence of alcohol, malaria, etc.) (cf. Talabi and Oko-Epelle 2024), which are also considered a type of advertising (see also Karypidou 2006, pp. 60–61). Conclusively, more details are provided in Figure 14, Figure 15 and Figure 16 and Table 9, Table 10 and Table 11, which should definitely be further explored in the future.

3.3. Statistical Criteria: One-Way ANOVA and Correlations

The research results and findings obtained from the one-way ANOVA highlighted that there is a significant statistical difference in attitudes, opinions, and behaviors among the GenZ’s gender of the research sample in relation to the daily hours spent listening to radio (F [2.901] = 2.917, p < 0.05) (

Table 12. The one-way ANOVA regarding the frequency of daily listening hours for radio, podcasts, and music based on gender.

	Gender	Ν		MEAN	SD	F	df
RADIO	Female	73	112	1.41	0.642	2.917	2.109
	Male	35		1.86	1.332
	Other	4		1.75	0.500
PODCASTS	Female	65	97	1.34	0.668	0.958	2.940
	Male	27		1.52	0.643
	Other	5		1.60	0.548
MUSIC	Female	79	125	3.71	1.273	0.168	2.122
	Male	40		3.65	1.610
	Other	6		4.00	1.095

), podcasts (F [2.940] = 0.958, p < 0.05) (Table 12), and music (F [2.122] = 0.168, p < 0.05) (Table 12), thus again rejecting H1 and confirming H2. More concretely, the comparisons showed that (a) GenZ’s females statistically listen to the radio more hours daily than GenZ’s males (1.41 ± 0.642 and 1.86 ± 1.332, respectively, p < 0.05) (Table 4 and Table 12), while there were no differences between GenZ’s females and GenZ’s others, as well as GenZ’s males with GenZ’s others; (b) GenZ’s others statistically listen to podcasts more hours daily than GenZ’s females (1.60 ± 0.548 and 1.34 ± 0.668, respectively, p < 0.05) (Table 4 and Table 12), while there were no differences between GenZ’s females and GenZ’s males, as well as GenZ’s males with GenZ’s others; and finally, (c) GenZ’s others statistically listen to music more hours daily than GenZ’s males (4.00 ± 1.095 and 3.65 ± 1.610, respectively, p < 0.05) (Table 4 and Table 12), while there were no differences between GenZ’s females and GenZ’s males, as well as GenZ’s females with GenZ’s others.

In conclusion, from the performed correlation analysis, the research results showed that there is a statistically significant positive correlation between daily radio listening and daily podcast listening by GenZ’s members (r = 0.384, p < 0.01) (

Table 13. Pearson’s r correlation test for daily listening in relation to radio, podcasts, and music.

Correlations
			Q1	Q2	Q3
Q1	RADIO	Pearson Correlation	1	0.384 **	0.287 **
		Sig. (2-tailed)		0.000	0.002
		N	112	88	112
Q2	PODCASTS	Pearson Correlation	0.384 **	1	0.198
		Sig. (2-tailed)	0.000		0.052
		N	88	97	97
Q3	MUSIC	Pearson Correlation	0.287 **	0.198	1
		Sig. (2-tailed)	0.002	0.052
		N	112	97	125

** Correlation is significant at the 0.01 level (2-tailed).

), which is surprising but can be justified considering that both radio and podcasts have various themes (Figure 7 and Figure 8, respectively). Likewise, there is a low, yet positive correlation between daily music listening and daily radio listening (r = 0.287, p < 0.01) (Table 13), something that is also justified in relation to the grouped answers of the research participants in terms of the type of radio shows and programs that GenZ’s members listen to the most (Figure 7 and Figure 13), as well as the grouped answers of the research sample with percentages regarding the frequency of daily listening hours for radio and music respectively (Figure 6, Table 3 and Table 4). In general, these research results and findings again help to confirm the H2, while they are characterized as particularly interesting and should be investigated further. Finally, more details about the correlations in relation to the triptych of radio, podcasts, and music are provided in Table 13.

3.4. General Profile of the Participants

This subsection presents the research results and findings obtained from the additional correlations analysis in order to better outline the general profile of this study’s GenZ’s participants who took part in this Internet survey in relation to music and radio. Specifically, correlations among the frequency of daily listening hours and the time of listening to the radio and music, respectively, were implemented. According to the derived research results, there have been: (a) 17 significant correlations in relation to radio with 112 out of 125 participants (with a percentage of 89.6%) who reported listening to the radio (

Table 14. Pearson’s r correlation test for daily and time of listening to the radio.

Correlations
		Ν		Q1	Q2	Q3	Q4	Q5	Q6	Q7
Q1	RADIO	112	Pearson Correlation	1	0.331 **	0.356 **	0.211 *	0.300 **	0.210 *	0.359 **
			Sig. (2-tailed)		0.000	0.000	0.025	0.001	0.026	0.000
Q2	Early in the Morning (06:00–10:00)	112	Pearson Correlation	0.331 **	1	0.404 **	0.065	0.150	0.139	0.218 *
			Sig. (2-tailed)	0.000		0.000	0.493	0.116	0.145	0.021
Q3	Morning (10:00–14:00)	112	Pearson Correlation	0.356 **	0.404 **	1	0.411 **	0.262 **	0.176	0.336 **
			Sig. (2-tailed)	0.000	0.000		0.000	0.005	0.063	0.000
Q4	Midday (14:00–16:00)	112	Pearson Correlation	0.211 *	0.065	0.411 **	1	0.465 **	0.391 **	0.364 **
			Sig. (2-tailed)	0.025	0.493	0.000		0.000	0.000	0.000
Q5	Afternoon (16:00–21:00)	112	Pearson Correlation	0.300 **	0.150	0.262 **	0.465 **	1	0.458 **	0.317 **
			Sig. (2-tailed)	0.001	0.116	0.005	0.000		0.000	0.001
Q6	Night (21:00–00:00)	112	Pearson Correlation	0.210 *	0.139	0.176	0.391 **	0.458 **	1	0.588 **
			Sig. (2-tailed)	0.026	0.145	0.063	0.000	0.000		0.000
Q7	After Midnight (00:00–06:00)	112	Pearson Correlation	0.359 **	0.218 *	0.336 **	0.364 **	0.317 **	0.588 **	1
			Sig. (2-tailed)	0.000	0.021	0.000	0.000	0.001	0.000

** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed).

); and (b) 6 significant correlations in relation to music with 125 participants (with a percentage of 100%) who reported listening to music (

Table 15. Pearson’s r correlation test for daily and time of listening to music.

Correlations
		Ν		Q1	Q2	Q3	Q4	Q5	Q6	Q7
Q1	MUSIC	125	Pearson Correlation	1	−0.004	−0.187 *	−0.082	−0.324 **	−0.285 **	−0.318 **
			Sig. (2-tailed)		0.961	0.037	0.363	0.000	0.001	0.000
Q2	Early in the Morning (06:00–10:00)	125	Pearson Correlation	−0.004	1	0.116	−0.129	−0.078	−0.137	0.103
			Sig. (2-tailed)	0.961		0.196	0.153	0.384	0.127	0.254
Q3	Morning (10:00–14:00)	125	Pearson Correlation	−0.187 *	0.116	1	0.130	−0.169	0.057	0.091
			Sig. (2-tailed)	0.037	0.196		0.149	0.059	0.526	0.311
Q4	Midday (14:00–16:00)	125	Pearson Correlation	−0.082	−0.129	0.130	1	0.073	0.153	0.097
			Sig. (2-tailed)	0.363	0.153	0.149		0.421	0.088	0.283
Q5	Afternoon (16:00–21:00)	125	Pearson Correlation	−0.324 **	−0.078	−0.169	0.073	1	0.417 **	0.195 *
			Sig. (2-tailed)	0.000	0.384	0.059	0.421		0.000	0.029
Q6	Night (21:00–00:00)	125	Pearson Correlation	−0.285 **	−0.137	0.057	0.153	0.417 **	1	−0.034
			Sig. (2-tailed)	0.001	0.127	0.526	0.088	0.000		0.710
Q7	After Midnight (00:00–06:00)	125	Pearson Correlation	−0.318 **	0.103	0.091	0.097	0.195 *	−0.034	1
			Sig. (2-tailed)	0.000	0.254	0.311	0.283	0.029	0.710

** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed).

).

Following the radio correlations, they showed that there is a strong correlation in the time of listening to the radio between (a) night and after midnight (r = 0.588, p < 0.01) (Table 14); (b) midday and afternoon (r = 0.465, p < 0.01) (Table 14); (c) afternoon and night (r = 0.458, p < 0.01) (Table 14); (d) morning and midday (r = 0.411, p < 0.01) (Table 14); (e) early in the morning and morning (r = 0.404, p < 0.01) (Table 14); (f) midday and night (r = 0.391, p < 0.01) (Table 14); (g) midday and after midnight (r = 0.364, p < 0.01) (Table 14); (h) morning and after midnight (r = 0.336, p < 0.01) (Table 14); and (i) afternoon and after midnight (r = 0.317, p < 0.01) (Table 14). Similarly, correlations are strong between daily music listening and the time of listening to music in the (a) after midnight (r = 0.359, p < 0.01) (Table 14); (b) morning (r = 0.356, p < 0.01) (Table 14); (c) early in the morning (r = 0.331, p < 0.01) (Table 14); and (d) afternoon (r = 0.300, p < 0.01) (Table 14). Additionally, they showed that there is a statistically significant positive correlation in the time of listening to the radio between morning and afternoon (r = 0.256, p < 0.01) (Table 14). Moreover, there is a low, yet positive correlation in the time of listening to the radio between morning and afternoon (r = 0.262, p < 0.01) (Table 14) and early in the morning and after midnight (r = 0.218, p < 0.05) (Table 14). Likewise, there is a positive correlation between daily music listening and the time of listening to music in the midday (r = 0.211, p < 0.05) (Table 10) and night (r = 0.211, p < 0.05) (Table 14).

Regarding the music correlations, they showed that there is a strong correlation in the time of listening to music between afternoon and night (r = 0.417, p < 0.01) (Table 15). In addition, they showed that there is a statistically significant positive correlation between daily music listening and the time of listening to music in the (a) afternoon (r = −0.324, p < 0.01) (Table 11); (b) night (r = −0.285, p < 0.01) (Table 15); and (c) after midnight (r = −0.318, p < 0.01) (Table 15). Furthermore, there is a low, yet positive correlation between daily music listening and the time of listening to music in the morning (r = −0.187, p < 0.05) (Table 15), as well as also in the time of listening to music between afternoon and after midnight (r = 0.195, p < 0.05) (Table 15).

In summary, based on the above research results and findings from the performed correlation analysis, we see that the survey’s participants tend to listen to music mainly in the night (Table 15), while they listen to the radio mainly after midnight (Table 14). If we take into account that most radio stations in Greece after midnight play almost only music without or with very few commercial advertisements and of course without a music producer or announcer, apparently radio is an ideal choice for these GenZ’s participants who stated that they listen to music for more than four hours daily (i.e., 54 out of 125 participants with a percentage of 43.2%) (MEAN: 3.70 and SD: 1.374) (Figure 6 and Table 3), something which should also be taken very seriously by senior management in the radio media ecosystem, and by extension in the media landscape with the aim of reorganizing or decentralizing the radio for its future form.

4. Conclusions

The presented work purposed to shed further light on the reported characterization of GenZ as a sound generation. The research results and findings obtained contribute to this RP, while at the same time confirm and agree with research results and findings of previous empirical studies and research regarding the aforementioned characterization (Döring et al. 2022; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021a, 2021b). Obviously, these research results and findings also contribute to the de novo delineation of this generational cohort, thus opening a new chapter in the literature regarding the genealogical characteristics, habits, and ethos of GenZ’s members.

The Internet survey also showed as a final conclusion that H2 is confirmed, further strengthening the literature in this particular field which the article deals with, and especially in radio studies. Similarly, it affirms that H1 is rejected, thus confirming previous and recent research results and findings of a series of different empirical studies and research in various and multiple fields with burning issues such as skill development (cf. Stareček et al. 2020), health issues (cf. Deckman et al. 2020; Kamenidou et al. 2020), and political matters (cf. Mueller and Mullenbach 2018), that show that there is indeed a difference among the genders of GenZ’s members; demonstrating that further research is needed in this regard.

The most important research finding is, however, that this generational cohort’s members listen to the radio, confirming previous studies and research that argue that the radio still continues to be one part of our everyday fabric of life without losing its identity, thus making it one of the first choices of the audience (Karypidou 2006; Magnaye and Tarusan 2023; Nicolaou et al. 2021a, 2021b; Nu”azzidane and Sa’idah 2023; Okeke et al. 2020; Puspitasari et al. 2020; Setiawan et al. 2020). Furthermore, this research finding also points to the need for the further study of radio in a broader context where the results will significantly contribute to its path-making and future, and by extension the pantheon of radio studies. Similarly, it is also necessary to investigate how and why these members listen to the radio.

In summary, the presented article as well as its research methodological approach obviously contains limitations, like all empirical studies and research (cf. Papanastasiou and Papanastasiou 2005; Siardos 2005). Although this Internet survey covers the needs of a study based on the final research sample of participation (cf. Comrey and Lee [1992] 2016), it cannot, however, allow their generalization to the population. Nevertheless, it laid the groundwork for delineating the case of Greece based on GenZ, filling an important gap in the literature. In addition, the research results and findings are aligned with the research results and findings of the second sub-survey which has been mentioned in Section 2 (i.e., Nicolaou et al. 2024), thus further contributing to the development of a comprehensive delineation of the genealogical characteristics, habits, and ethos of Greek GenZ’s members regarding their sound preferences (see Nicolaou 2024).

In conclusion, it could be stated that this article also presents research results and findings with criterion-related validity since they could be utilized for the essential quality of the journalistic profession or even Higher Education and Adult Education in the field of media studies. After all, one of the main concerns of media studies is also teaching–learning the skills of critical study of media and media technologies such as radio (cf. Matsiola et al. 2019; Nicolaou et al. 2021a; Shutaleva et al. 2020), which involves dealing with the technological, cultural, and historical particularities of particular media used in a particular time and place (Shutaleva et al. 2020); these goals are considered a special challenge for an educator if we consider the genealogical characteristics, habits, and ethos of the GenZ (Matsiola et al. 2019; Nicolaou and Matsiola 2023b; Nicolaou et al. 2021a, 2021b). Additionally, senior management in the radio media ecosystem, and by extension the media landscape, should consider these research results and findings seriously, with a view to reorganizing or decentralizing radio for its future form. More specifically, they should take into account the trends, views, and habits of GenZ’s members that emerge from this research analysis, and especially their particular preferences in terms of the kind of audio content (i.e., from fantasy to informational) and/or radio shows and programs they listen to (Section 3.2). Likewise, management should take into account the times of day that they tend to listen to the radio based on correlation research results and findings (Section 3.4), so that they can meaningfully tailor their program schedules and/or content to current trends. Finally, what we need to keep in mind is that GenZ’s members seem predisposed to make radio one of, if not, the first choice of media for a long time to come.