Understanding podcast users: Consumption motives and behaviors

Abstract

Through a large-scale national survey, this study provided the first comprehensive examination of podcast users in the United States from the perspectives of motivation and usage. It deepened our understanding of this new on-demand audio platform in the context of consumption drivers, behaviors, and competing media options. The results showed that entertainment, information, and audio platform superiority were the most important motivators for podcast consumption. In addition, motives were found to affect listening behaviors, including listening settings, width, depth, and routine of listening, and usage of competing audio media, such as regular radio, online radio, and streaming music. The findings revealed that podcasting is a distinct medium with unique characteristics rather than a mobile, on-demand extension of existing audio platforms like radio. Podcast consumption, especially on today’s complex media platforms, is multidimensional and should be measured from multiple aspects and examined in various settings.

Keywords

Consumption settings listening behaviors motives podcasting radio streaming music uses and gratifications

In 2005, “podcasting” was chosen as “the word of the year” by the New Oxford American Dictionary (BBC News, 2005). It was anticipated that this new audio service would challenge the traditional radio industry (Morris and Patterson, 2015). However, podcasting did not burgeon as expected. Experts attributed the stagnant growth to everything from its confusing name to the competition from the then online video newcomers, such as YouTube (Bottomley, 2015). The growth of podcasting picked up steam again when National Public Radio’s (NPR) podcast program, Serial, began to garner listeners in 2014. By 2019, 51% of Americans older than 12 had listened to a podcast and 32% did so in the last month (Edison Research and Triton Digital, 2019).

As an evolving on-demand audio platform, the definition of “podcast” has changed over time and been used in various contexts: digital audio files distributed via Really Simple Syndication (RSS), downloadable radio available on the Internet, downloadable audio programs that have aired through broadcast radio, a program, an episode, and so on (Bottomley, 2015). It appears that downloadability and audio are even no longer the absolute, defining characteristics as podcasters and consumers are using YouTube as an important distribution platform and have started to talk about “video podcasts” (Colligan, 2018). Researchers have addressed podcasting in various contexts, such as education (Şendağ et al., 2018), health (Turner-McGrievy et al., 2013), journalism (Park, 2017), and media criticism (Von Krogh and Svensson, 2017). Some have examined specifically the media format itself, discussing its evolution, production, relationship with radio, and impact on the radio industry (Berry, 2016; McHugh, 2016; Morris and Patterson, 2015; Sellas and Solà, 2019).

Podcasting has been discussed in relation to many other audio media. For example, it was regarded to be “closely intertwined” with broadcast radio, sharing techniques and content (Berry, 2016: 17), and similar to digital music in terms of personalization and self-curation (Nyre, 2015). What makes podcasting a distinct form of audio media is the unique set of “practices and cultural meanings that are entirely entwined with the technologies for its distribution, organization, and consumption” (Morris and Patterson, 2015: 221–222). How it is consumed differently from other audio media by the media audience is particularly important because the distinction between two audio media actually lies in the minds and behaviors of the audience (Black, 2001). A limited number of studies have investigated the nature of the podcast audience, exploring factors predicting non-users’ adoption intention (Li and Zeng, 2011; Mou and Lin, 2015) and users’ listening motives (Boling and Hull, 2018; Chung and Kim, 2015; McClung and Johnson, 2010; Perks and Turner, 2019; Swanson, 2012). Nevertheless, since the exponential growth of podcasting with an influx of content and access platforms, including the widespread mobile apps, our understanding of the podcast consumer is very limited, especially regarding their listening drivers and patterns (Bottomley, 2015; Markman, 2015).

A review of the literature on podcast users reveals several research gaps. First, the studies often sampled a specific group of users, such as college students (e.g. Chung and Kim, 2015; Swanson, 2012) and fans of certain podcast programs (e.g. Boling and Hull, 2018; Pavelko and Myrick, 2020), failing to draw a comprehensive picture incorporating diverse user segments. Second, although some of the studies addressed the relationship between motives and overall podcast usage, they did not link specific motives to different usage aspects or consumption settings, which are a key differentiator of podcasting as an on-demand audio platform. It is plausible that podcast users driven by different motives would consume podcasts in different ways and/or at different levels. The current study aims to fill the research gaps by developing a more generalizable motive typology based on a wide range of podcast users and by investigating the interplay between podcast consumption motives and behaviors. The study also explores the relationship between podcasting and its competing audio media based on podcast consumers’ motives and usage. Note that podcasting, in the context of this study, is defined largely as an audio platform, though delivery channels like YouTube have been used for both audio and video podcast consumptions.

Literature review

Podcast consumption motives

The uses and gratifications paradigm (U&G; Katz et al., 1973) proposes that individuals are active media consumers who select media content intentionally to gratify their needs. The approach has been widely used in studying media consumption patterns, especially when new media technologies emerge (Perse and Dunn, 1998). Motivation and gratification are two key constructs in the U&G approach. Generally, motivation refers to what consumers seek and expect, while gratification refers to what consumers actually obtain (Hearn, 1989; Shade et al., 2015). To explore the motivations for podcast consumption, the authors of the current study reviewed the existing literature of podcast consumption motivations as well as gratifications. Research on the topics is limited. The few pioneer studies are reviewed below.

An earlier study addressing motivations for podcast consumption was conducted by McClung and Johnson (2010) with fans of top podcast programs. The study identified five motives, including entertainment, library building, time-shifting (i.e. convenient and on-demand access), advertising (i.e. consuming advertising and supporting advertisers), and social aspect (i.e. interaction with friends and other audience). Later, with a focus on college students, Swanson (2012) studied the penetration of podcasting in that population and their preferred genres, devices, and consumption settings. The study also identified that college students listened to podcasts for information, entertainment, and social sharing. Another study of college students found six major motive categories of podcast consumption, namely, voyeurism/social interaction/companionship, entertainment/relaxation/arousal, education/information, pastime/escape, habit, and convenience (Chung and Kim, 2015).

Recently, intrigued by the popularity of the true crime genre, Boling and Hull (2018) examined the true crime podcast audience and reported the extent to which they were motivated to consume by 11 motives. Among the 11 motives, entertainment, convenience, and boredom were the most salient, while news and information, escape, and social interaction were the least. Another study concerning the true crime genre was conducted by Pavelko and Myrick (2020), which identified five motives pertaining to listeners with mental illness. Entertainment and true crime interests were the most common motives; some listeners reported social support and connection-related motives as well.

A more comprehensive picture of podcast listening motivations was provided by Perks and colleagues (Perks et al., 2019; Perks and Turner, 2019). In a qualitative study (Perks and Turner, 2019), they uncovered several new gratifications and indicated possible motivations. The first gratification noted podcasting’s role as a good replacement for radio, music, and television given its mobility, engagement, and the fresh, non-repetitive content available on it. As a result, a possible motive for podcast consumption is the perceived advantages of podcasting over competing media such as its superiority in terms of convenience and content. The other gratifications, which could also be motivations, included customizable experiences, multitasking companionship, para-social interactions with podcast personalities and other listeners, and social interactions with friends and families (Perks and Turner, 2019). They later developed a scale based on the qualitative findings and identified four motive factors (i.e. controlling edutainment, storytelling transportation, social engagement, and multitasking; Perks et al., 2019).

Overall, most of the motives identified in previous studies only applied to a subset of podcast users, focused on a specific genre, or approached qualitatively. Since the main goal of the current study is to contribute to our fundamental understanding of the podcasting medium, the current study attempts to develop a more generalizable motivation typology based on a comprehensive list of motive items derived from existing academic and industry literature, using a cross-sectional, large-scale national survey of podcast users in the United States. Accordingly, the first research question is posited below.

RQ1. What are the motives for podcast consumption in the United States?

Podcast motives and behaviors

A key proposition of the U&G approach is that media consumption motives will affect the attitudinal and behavioral results of media consumption (Ruggiero, 2000). Motives are powerful predictors in communication research. They could address the behavioral changes that “cannot be explained by external forces alone” (Winter, 1973: 21), and oftentimes perform better than demographics in predicting audiences’ media consumption attitudes and behaviors (e.g. Omar et al., 2018; Sun et al., 2008). To explain podcast users’ consumption patterns, the current study approaches the investigation from the motivation aspect. Specifically, this study examines the relationships between podcast consumption motives and two particular aspects of consumption behaviors, namely, consumption setting and usage.

Consumption setting

Podcasting has long been presented as something for people on the go (O’Brien, 2017). However, a recent industry report found that podcast users have changed how they consume podcasts as podcasts’ availability and access technology improved over time (Edison Research and Triton Digital, 2019). Home has become the most common place to listen to podcasts, while many other locations, such as in a car, at a gym, at work, and on public transportation were also ranked high. About 70% of podcast users also reported that sometimes they did not multitask when listening to podcasts—no driving, no gym, just focusing on listening to the podcast content (Edison Research and Triton Digital, 2019). It seems that podcasting has matured to become a media platform that is no longer a simple, fill-in-the-gap secondary audio medium; it is now an appealing audio platform that is accessed in different settings for various reasons. In other words, with its on-demand, time-shifting, and mobile characteristics (Berry, 2016; Markman, 2015), podcasting’s time has arrived as a major audio medium for today’s demanding media consumers. Consequently, there is a need to understand how different consumer segments might utilize this emerging media platform.

One way to learn about how consumers realize their media consumption motives behaviorally is to see the situation of the usage. Researchers have argued that the concept of media use situation should contain not only a physical dimension, but also a social dimension and a technological dimension (Zhang and Zhang, 2012). Given that the physical location of listening has always been an important aspect in studying audio media audience (Nielsen, 2019), and the history of podcast use in an out-of-home environment, the current article focuses on the physical dimension of podcast consumption situation. To avoid confusion, this article uses “setting” to refer to this specific dimension of consumption situation.

The relationship between media consumption settings and motives has been discussed in the literature of information systems (Karnowski and Jandura, 2014; Leung and Wei, 2000; Zhang and Zhang, 2012). For example, consumers who use mobile web at home are largely driven by the motive of entertainment, while those who use the medium at work or with friends are more motivated by information seeking (Karnowski and Jandura, 2014). The motive of mobility could lead to more usage of mobile phones on transportation (Leung and Wei, 2000). Therefore, it is possible that the extent to which podcast users listen to podcasts in different settings is influenced by their listening motives. The research question is posited next.

RQ2. How do podcast consumption motives differ by podcast consumption settings?

Usage

There has been extensive research on the relationship between media consumption motives and usage. It is believed that media consumers’ motivations would eventually affect their consumption behaviors such as usage (Chung and Kim, 2015). Regarding podcasting, previous studies showed inconsistent results. For example, Chung and Kim (2015) found that voyeurism/social interaction/companionship and entertainment/relaxation/arousal were two positive predictors of podcast usage, while McClung and Johnson (2010) reported social motive to be the only significant predictor. A possible reason is that the researchers defined and operationalized podcast usage differently. Usage has long been an important topic in media research, but researchers differ in its measurement. Existing measures of media usage (e.g. Anderson et al., 1986; Chan-Olmsted et al., 2013; Chung and Kim, 2015; Clavio, 2008; Davenport et al., 2014; McClung and Johnson, 2010) range from broad measurement (e.g. overall use frequency, time spent on a medium, number of programs consumed/downloaded, subscription behaviors) to specific measurement (e.g. different usage levels or behaviors associated with a medium). The variation in measurement reveals that usage is in fact a multifaceted concept and different usage dimensions are likely to yield different implications.

There is a long tradition of assessing consumer behavior from multiple dimensions in consumer research. In a study of consumer product adoption, Gatignon and Robertson (1985) proposed that both the width (e.g. reach and variety) and the depth (e.g. usage amount and monetary commitment) of adoption should be assessed. In a study of mobile app usage, Hwang et al. (2014) measured usage from not only the width aspect (i.e. reach), but also the depth aspect (i.e. time intensity and frequency intensity). In line with these studies, the present study argues that podcast usage, with its on-demand and multiple access point/technology/location characteristics, is a multidimensional concept to be assessed from multiple aspects. We propose that the multiplicity should be captured in three ways: width, depth, and routine. The width of podcast usage can be evaluated by consumption quantity such as the number of podcasts one listens to in a typical period. By comparison, the depth of podcast usage can be assessed by the length of time per typical podcast usage such as the number of minutes users usually spend on listening when they tune in. Since podcast usage is largely tied to subscription, another usage dimension can be measured by the routine or commitment aspect of podcast consumption. For example, the number of podcast programs a user subscribes to. The usage research question below would be investigated from such multiple angles.

RQ3. How do podcast consumption motives affect podcast usage?

Podcast motives and usage of competing audio media

Research on media substitutability and complementarity has clearly stated that consumers’ motives of using one medium could affect their usage of other media (Cha and Chan-Olmsted, 2012; Ferguson and Perse, 2000; Lee and Lee, 2015). Technologies that are functionally similar and could satisfy the same underlying needs are considered to be in the same technology cluster (Rogers, 1995). Within a technology cluster, the adoption and usage of one technology can affect that of other technologies (Rogers, 1995). Either a displacement effect or a complement effect may occur, depending on the characteristics of the media and the motives of the consumers (Lee and Lee, 2015). For instance, as the amount of entertainment programming continues to increase on TV, consumers seeking entertainment from print media may switch to TV and their usage of print media may decrease as a result (Kaplan, 1978). However, consumers seeking information from print media may allocate time to TV without cutting time for print media because the two fulfill different needs.

As mentioned earlier, the relationship between podcasting and other audio media—especially regular broadcast radio, online radio, and streaming music—is a focal point in the podcasting literature (Berry, 2016; Markman, 2015; Menduni, 2007; Nyre, 2015; Webster, 2018). It has long been wondered whether podcasting is “the future of radio” and “the missing link connecting radio and the Net that Internet radio stations were not able to establish” (Menduni, 2007: 9). Compared with regular and online radio, which are basically linear and standardized, podcasting is on-demand, time-shifted, personalized, and diverse in content and style (Berry, 2016; Markman, 2015; Nyre, 2015). Compared with streaming music, podcasting is more engaging, but less of companion value, as it requires a lot of attention (Berry, 2016; Nyre, 2015). Studying how podcast users driven by different motives use the competing audio media at different levels can help advance our understanding of the relationships among the media and how they might compete with or complement one another going forward in the audio media market. Therefore, the following research question is proposed:

RQ4. What is the relationship between podcast consumption motives and alternative audio media usage?

Method

Data collection

This study utilized a national online survey to collect data. The survey method is deemed useful to study the perceptions and behaviors of a population, as it allows researchers to gather various information from large samples (Jones et al., 2013). Before the main test, a pretest with 100 participants was carried out on MTurk to test the readability of the questionnaire and the reliability of the scales. The questionnaire was revised accordingly. Then, in the main test, 2000 regular podcast users who had listened to podcasts in the last 6 months were recruited from the Qualtrics (2014) panel, which is probability-based and statistically representative of US consumers. Specifically, the panelists were selected based on two screening criteria: (1) they considered themselves a regular podcast user (either monthly or weekly) and (2) they have listened to podcasts in the last 6 months. The gender and age quotas of the sample were designed to resemble the demographics of podcast users in the United States based on data from Edison Research and Triton Digital (2018). Ultimately, the sample participants had a mean age of 40.3 years old (SD = 14.4). Of the participants, 51.9% were male, 47.9% were female, and the rest self-identified as “other genders”; 4.4% had an annual household income below US$39,999, while 31.4% indicated above US$70,000. Regarding level of education, 19.5% of the participants finished high school, 28% had some college, 13.2% earned an associate degree, and 37.0% earned a bachelor’s degree or higher. In the survey, the participants answered questions about their subscription of podcast programs, podcast consumption frequency and time, usage of other media, podcast listening motives, and podcast listening settings. The specific measures are presented next.

Measures

Consumption motives

A total of 30 items were adapted from a number of previous studies and industry reports (Chan, 2014; Haridakis and Hanson, 2009; Khan, 2017; Nabi et al., 2006; Papacharissi and Mendelson, 2007; Rubin, 1983; Ruggiero, 2000; Sundar and Limperos, 2013). The items covered not only well-established motives, such as pastime, companion, entertainment, voyeurism, and so on, but also newly emerged, more exploratory motives, such as personal identification, communal identification, and podcast’s superior performance in terms of content and convenience. Each of the motives was measured on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree).

Consumption setting

The participants were instructed to indicate on 5-point scales how often they listened to podcasts (1 = not at all, 5 = a great deal) in six locations: at home, at work, when riding public transportation, in a car/truck, during exercise, and when walking around. The locations were derived from both academic and industry reports on where podcasts were typically consumed. Based on the work of Karnowski and Jandura (2014), consumptions in the latter four locations were averaged to indicate consumption on the go. As such, the six locations were transformed into three setting categories: at home, at work, and on the go.

Usage of podcasts

The usage variable was measured from three aspects: number of podcasts listened per week (i.e. the width of listening), number of minutes spent per time (i.e. the depth of listening), and number of subscribed podcast programs (i.e. the routine of listening). For the first indicator, number of podcasts listened per week, the participants first indicated whether they listened to podcasts weekly or monthly, then answered how many podcasts they listened to in a typical week/month. For monthly users, their usage was later transformed into weekly usage by being divided by four. Regarding number of minutes spent per time, the participants were instructed to write down a specific number. Answers including a time range (e.g. 30–45 minutes) were recoded using the middle point of the range (e.g. 37.5 minutes in the case of 30–45 minutes). As for the last indicator, number of subscribed podcast programs, the participants were instructed to choose the corresponding number.

Usage of competing audio media

Three audio media that have been discussed in the literature in relation to podcasts—regular radio, online radio, and streaming music—were presented and the participants indicated their typical usage of each of the media on 5-point scales (1 = not at all, 5 = a great deal).

Data analyses

To answer RQ1, an exploratory factor analysis was performed using a principal-component extraction with promax rotation. Number of factors was determined by the eigenvalues and a visual assessment of the scree plot. Two items were dropped due to severe cross-factor loading and unsatisfying loading size (i.e. “it is convenient” and “it is easier to use compared with other media”). The remaining items were analyzed again using the same method to identify the ultimate structure of the items.

To answer RQ2–RQ4, a series of hierarchical multiple regression analyses were performed. Demographic variables (i.e. age and gender) were entered in the first step as control variables and motives were entered in the second step. Listening at work, number of subscribed programs, number of podcasts listened per week, and minutes spent on listening each time were log transformed (i.e. lg10) to cope with the strong, positive skewness identified in the data. A reflect and square root transformation was applied to listening at home to convert the moderately, negatively skewed data to normality. As such, the current study was able to identify the contribution of the variables of interests while ruling out the effects of demographic variables.

Results

RQ1 addresses the motives of podcast consumption. The analysis revealed seven factors (see Table 1), accounting for 69.60% of the total variance. The factors were entertainment (three items, Cronbach’s α = .82, M = 4.35, SD = 0.68), information (two items, Cronbach’s α = .69, M = 4.16, SD = 0.80), audio platform superiority (six items, Cronbach’s α = .87, M = 4.03, SD = 0.72), escapism/pastime (five items, α = .87, M = 3.49, SD = 0.98), personal/communal identification (five items, α = .85, M = 3.43, SD = 0.91), social interactions (three items, Cronbach’s α = .83, M = 3.28, SD = 1.09), and companion/connection (four items, Cronbach’s α = .85, M = 3.03, SD = 1.11). Entertainment, information, and audio platform superiority were the most prominent motives, and companion/connection was the least. Specifically, the entertainment motive entailed one’s desire to enjoy, relax, and be entertained through the podcast experience. The information motive included podcast users’ needs to learn new things and the world around them. Audio platform superiority was about the desire to use an audio platform that is perceived to be superior to other audio alternatives, including on-demand convenience (time and place) and content (variety and uniqueness). The escapism/pastime motive addressed a podcast user’s need to escape from the presence and to pass the time. Personal/communal identification was mostly about the need to fulfill or reinforce personal and communal identity/value (e.g. the listeners/audience community of the same podcast). While social interaction was about the desire to use podcasting as a vehicle to socialize with personal friends and family, companion/connection focused on one’s general need for companion and to be connected with others by learning about them (e.g. voyeurism to learn about others).

Table 1.

Factor analysis results for podcast consumption motives.

	Motives
	SUP	ESC	IDT	CON	ENT	SOI	INF
Podcasts allow me to listen to audio anytime better than other audio media	.860	.244	.409	.237	.463	.321	.111
Podcasts allow me to listen to audio anywhere better than other audio media	.844	.255	.396	.209	.444	.324	.101
Podcasts are more convenient than other audio media	.791	.209	.386	.233	.390	.293	.213
Podcasts offer more content variety than other audio media	.750	.209	.326	.308	.532	.267	.356
Podcasts offer more unique content than other audio media	.724	.186	.347	.339	.511	.257	.375
Podcasts are more on-demand than other audio media	.700	.180	.266	.206	.334	.197	.266
To fill in empty moments	.258	.852	.270	.377	.327	.205	.028
When I have nothing better to do	.149	.808	.205	.328	.221	.166	−.041
To pass the time	.236	.806	.159	.339	.359	.167	.126
To escape the hustle and bustle of daily activities	.341	.775	.477	.518	.461	.384	−.177
To get away from other things	.325	.767	.485	.536	.431	.370	−.202
It makes me feel unique	.366	.343	.830	.480	.322	.461	−.025
It improves my understanding about what kind of person I am	.390	.272	.808	.474	.292	.392	.098
It reaffirms my personal values	.398	.180	.797	.319	.289	.353	.154
I feel like I belong to a community	.388	.272	.755	.383	.488	.520	.017
I identify with the listeners of my podcasts	.419	.212	.647	.256	.575	.445	.095
So I can get a peek into other people’s lives	.258	.415	.429	.882	.304	.339	−.017
So I get to see a side of people that I wouldn’t normally get to see	.284	.361	.414	.869	.318	.379	.052
Because it keeps me company	.348	.569	.606	.756	.352	.300	−.318
Because it makes me feel less lonely	.261	.526	.622	.720	.267	.285	−.340
It’s enjoyable	.496	.254	.326	.236	.872	.265	.311
It’s entertaining	.443	.345	.270	.295	.870	.283	.227
It’s relaxing	.451	.440	.438	.370	.792	.333	.014
So I can share the experience with friends/family	.329	.222	.473	.340	.343	.897	.143
So I can talk with others about the podcast	.335	.227	.457	.349	.351	.879	.154
Because it’s something to do with friends/family	.278	.334	.447	.365	.271	.800	−.100
To learn new things	.419	.090	.294	.121	.361	.220	.736
To see what’s out there	.399	.330	.309	.291	.420	.340	.662

SUP: audio platform superiority; ESC: escapism/pastime; IDT: personal/communal identification; ENT: entertainment; CON: companion/connection; SOI: social interaction; INF: information.

RQ2 addresses the impact of consumption motives on consumption settings (see Table 2). First, at home podcast consumption was examined. The model was statistically significant, R2 = .091, F(10, 1987) = 19.864, p < .001. When age and gender were controlled, motives alone were significant predictors, ΔR2 = .085, ΔF(7, 1987) = 26.400, p < .001. Three individual motives were significant in predicting consuming podcasts at home, namely, entertainment (B = .060, β = .1, p < .001), personal/communal identification (B = .071, β = .159, p < .001), and companion/connection (B = .026, β = .071, p = .013). In addition, escapism/pastime (B = −.022, β = −.054, p = .052) was marginally significant. Second, workplace podcast consumption was examined. The model was statistically significant, R2 = .151, F(10, 1987) = 35.289, p < .001. The addition of the motive block into the model led to a significant increase in R2, ΔR2 = .043, ΔF(7, 1987) = 14.292, p < .001. Audio platform superiority (B = .057, β = .160, p < .001) and escapism/pastime (B = .019, β = .070, p = .008) were positive predictors, while information was a negative predictor (B = −.018, β = −.054, p = .030). Finally, on-the-go podcast consumption was investigated. The model was statistically significant, R2 = .256, F(10, 1987) = 68.471, p < .001. With demographics controlled, motives significantly contributed to the prediction of consuming on the go, ΔR2 = .152, ΔF(7, 1987) = 58.034, p < .001. Regarding individual motives, all the motives were significant except entertainment (p = .987). Audio platform superiority was the strongest predictor (B = .282, β = .183, p < .001), followed by social interaction (B = .156, β = .152, p < .001) and personal/communal identification (B = .121, β = .099, p < .001). Information was the only negative predictor (B = −.068, β = −.049, p = .037). In summary, the results showed that podcast users had distinct and similar motivations in the three settings. Personal/communal identification and companion/connection were positively related to consumption at home and on the go. Audio platform superiority and escapism/pastime were positive predictors of consumption at work and on the go, while information was a negative factor for both out-of-home settings. Social interaction was only related to consumption on the go. Although escapism/pastime was only marginally significant in the home setting, it revealed that motives being positive in some settings (i.e. on the go and work) could be negative in another setting (i.e. at home). In comparing home versus out-of-home audio usage settings in an industry tradition (Nielsen, 2019), the biggest difference between the two would be the entertainment motive for home consumption and the platform superiority motive, the escapism/pastime motive, and the negative need for information for the out-of-home setting (i.e. workplace and on-the-go use).

Table 2.

Regressions of consumption settings on motives.

	At home			At work			On the Go
	B	SE	β	B	SE	β	B	SE	β
Block 1. Demographics
Gender (other)^a	.136	.175	.017	−.166	.108	−.032	−1.115**	.435	−.050
Gender (female)^a	.048**	.018	.058	−.083***	.011	−.161	−.034	.043	−.015
Age	.003***	.001	.096	−.005***	.000	−.260	−.020***	.002	−.260
Block 2. Motives
Audio platform superiority	.017	.016	.029	.057***	.010	.160	.282***	.039	.183
Social interaction	.003	.010	.009	.007	.006	.029	.156***	.024	.152
Entertainment	.060***	.017	.100	−.009	.010	−.023	.001	.042	.000
Information	.025	.013	.048	−.018*	.008	−.054	−.068*	.033	−.049
Personal/communal identification	.071***	.014	.159	.010	.008	.035	.121***	.033	.099
Companion/connection	.026*	.011	.071	.006	.006	.028	.065*	.026	.065
Escapism/pastime	.022	.011	−.054	.019**	.007	.070	.075**	.028	.066

SE: standard error.

“Male” is used as the reference level of gender

p < .05; **p < .01; ***p < .001.

RQ3 discusses the effects of podcast motives on podcast usage, as reflected by number of podcasts listened per week, minutes spent on listening each time, and number of subscribed programs (see Table 3). Regarding usage width (i.e. number of podcasts listened per week), the model was significant, R2 = .103, F(10, 1987) = 22.864, p < .001. The addition of the motives resulted in a significant increase in R2, ΔR2 = .081, ΔF(7, 1987) = 25.724, p < .001. Audio platform superiority (B = .129, β = .203, p < .001) and entertainment (B = .051, β = .076, p = .007) were significant individual predictors. Regarding usage depth (i.e. minutes per time), the overall model was again significant, R2 = .082, F(10, 1987) = 17.634, p < .001. The block of motives significantly increased R2, ΔR2 = .052, ΔF(7, 1987) = 16.176, p < .001. While audio platform superiority (B = .072, β = .152, p < .001) and entertainment (B = .062, β = .122, p < .001) remained significant, social interaction also became significant—though negatively—this time, B = –.029, β = –.092, p = .001. Finally, as for usage routine/commitment (i.e. number of subscribed programs), the model was significant, R2 = .124, F(10, 1987) = 28.200, p < .001. The addition of the motive block led to a significant increase in R2, ΔR2 = .069, ΔF(7, 1987) = 22.242, p < .001. Audio platform superiority (B = .101, β = .215, p < .001) and information (B = .024, β = .057, p = .024) were positive predictors of this usage indicator. Overall, audio platform superiority was the best predictor of podcast usage behaviors. While the need for entertainment encouraged the listening behavior, the need for information drove more routine, committed podcast usage behavior.

Table 3.

Regressions of podcast usage dimensions on motives.

	Podcasts per week			Minutes per time			Programs subscribed
	B	SE	β	B	SE	β	B	SE	β
Block 1. Demographics
Gender (other)^a	−.064	.196	−.007	.080	.147	.012	−.011	.143	−.002
Gender (female)^a	−.078***	.020	−.085	−.041**	.015	−.060	.019	.014	.029
Age	−.003***	.001	−.089	−.003***	.001	−.144	−.005***	.001	−.214
Block 2. Motives
Audio platform superiority	.129***	.018	.203	.072***	.013	.152	.101***	.013	.215
Social interaction	−.003	.011	−.008	−.029**	.008	−.092	−.011	.008	−.035
Entertainment	.051**	.019	.076	.062***	.014	.122	.016	.014	.032
Information	.007	.015	.013	.009	.011	.021	.024*	.011	.057
Personal/communal identification	−.001	.015	−.001	−.013	.011	−.036	−.019	.011	−.050
Companion/connection	.015	.012	.037	.008	.009	.026	.015	.009	.049
Escapism/pastime	.016	.013	.034	.003	.010	.008	.010	.009	.028

SE: standard error.

“Male” is used as the reference level of gender

p < .05; **p < .01; ***p < .001.

RQ4 addresses the relationship between consumers’ podcast consumption motives and usage of three competing audio media—regular radio, online radio, and streaming music (see Table 4). Regarding regular radio, the full model was statistically significant, R2 = .043, F(10, 1987) = 8.983, p < .001. The block of motives contributed to an increase in R2, ΔR2 = .038, ΔF(7, 1987) = 11.381, p < .001. Social interaction (B = .176, β = .153, p < .001) was found to be a significant predictor, while companion/connection (B = .063, β = .056, p = .058) was marginally significant. The model predicting online radio usage was significant as well, R2 = .089, F(10, 1987) = 19.440, p < .001. The addition of motives significantly increased R2, ΔR2 = .068, ΔF(7, 1987) = 21.269, p < .001. Three individual motives were significant, namely, audio platform superiority (B = .112, β = .061, p = .032), social interaction (B = .149, β = .122, p < .001), and personal/communal identification (B = .182, β = .124, p < .001). Finally, the model for streaming music was also significant, R2 = .193, F(10, 1987) = 47.655, p < .001. With age and gender controlled, motives alone resulted in a significant increase in R2, ΔR2 = .056, ΔF(7, 1987) = 19.774, p < .001. Social interaction (B = .130, β = .105, p < .001), information (B = .149, β = .088, p < .001), and personal/communal identification (B = .087, β = .058, p = .040) were significant predictors. In summary, podcast users who were driven by the social interaction motive were more likely to use the other audio media, analog or digital, more frequently. Podcast users who sought personal/communal identification were also more likely to use other digital audio media (see Table 5 for correlations among consumption settings, podcast usage, and usage of competing audio media).

Table 4.

Regressions of usage of competing audio media on motives.

	Regular radio			Online radio			Streaming music
	B	SE	β	B	SE	β	B	SE	β
Block 1. Demographics
Gender (other)^a	−1.467***	.552	−.059	.223	.575	.008	−.674	.549	−.025
Gender (female)^a	−.083	.055	−.033	−.016	.057	−.006	−.019	.055	−.007
Age	.001	.002	.007	−.010***	.002	−.111	−.032***	.002	−.339
Block 2. Motives
Audio platform superiority	.024	.050	.014	.112*	.052	.061	.030	.050	.016
Social interaction	.176***	.031	.153	.149***	.032	.122	.130***	.031	.105
Entertainment	−.026	.053	−.014	−.062	.055	−.031	.070	.053	.035
Information	.022	.042	.014	.036	.043	.022	.149***	.041	.088
Personal/communal identification	.026	.043	.019	.182***	.044	.124	.087*	.042	.058
Companion/connection	.063	.033	.056	.010	.035	.008	.019	.033	.015
Escapism/pastime	−.014	.036	−.011	.039	.037	.029	.016	.036	.011

SE: standard error.

“Male” is used as the reference level of gender

p < .05; **p < .01; ***p < .001.

Table 5.

Correlations among consumption settings, podcast usage, and usage of competing audio media.

	At work	At home	On the go	Podcasts per week	Minutes per time	Programs subscribed	Regular radio	Online radio	Streaming music
At work	1.00	–	–	–	–	–	–	–	–
At home	.11***	1.00	–	–	–	–	–	–	–
On the go	.42***	−.09***	1.00	–	–	–	–	–	–
Podcasts per week	.26***	−.13***	.30***	1.00	–	–	–	–	–
Minutes per time	.14***	−.07**	.10***	.16***	1.00	–	–	–	–
Programs subscribed	.24***	−.08***	.32***	.54***	.18***	1.00	–	–	–
Regular radio	.11***	−.04	.22***	.03	−.08***	−.07***	1.00	–	–
Online radio	.23***	−.14***	.35***	.14***	.03	.12***	.23***	1.00	–
Streaming music	.20***	−.13***	.35***	.10***	.04	.20***	.10***	.40***	1.00

**p < .01; ***p < .001.

Discussion

This study provides the first comprehensive examination of podcast users in the United States from the perspectives of motivation and usage. It also explores the interaction between podcast motives and consumption of other audio media. The goal is to better understand this new on-demand audio platform in the context of consumption drivers, behaviors, and competing media options.

Podcasting is, at its core, about content and a unique way of delivering that content on demand, as entertainment, information, and audio platform superiority were found to be the three most important motivators. However, the results also showed that podcast consumption is dynamic—users listen to podcasts in different settings for different reasons. Rubin (1983, 1984) proposed two orientations of media consumption—instrumental and ritualized. Instrumental consumption is more intentional, selective, and active in comparison with ritualized consumption. Therefore, instrumental consumption is often associated with motives like information seeking, while ritualized consumption is likely to be related to pastime and habit (Rubin and Perse, 1987). This study found that consuming podcasts at home was negatively associated with the motive of escapism/pastime but positively associated with information seeking (though both marginally), while consuming out of home (i.e. at work and on the go) was positively associated with escapism/pastime but negatively associated with information seeking. It seems that podcast consumption at home is more active and instrumental, while out-of-home podcast use is more ritualized. This consumption pattern is drastically different from that of radio, which is used passively as “aural wallpaper” at home to accompany domestic routine tasks (Berry, 2016: 12). Given that home is indicated by podcast users as the most common place to consume podcasts (Edison Research and Triton Digital, 2019), it is evident that this audio platform has developed quite differently from the traditional radio medium, which is often consumed out of home (Nielsen, 2019).

In addition, although information and entertainment were found to be two primary drivers of podcast consumption in general, out-of-home podcast consumption seems to be less about these two needs, but more about the platform’s advantages in content, control, and mobility, and its utility to escape, to connect and socialize, and to affirm self-identity. In comparison, when at home, podcasting’s superiority over other audio media may be less evident because consumers have easy access to different media options for various needs. In this case, podcasting might serve as a platform for active, individualized content that delivers more cognitive value. It is necessary for content producers and marketers to keep these in mind, as they would have important implications on consumer targeting, content development, and sponsorships as the audio platform grows.

The finding that the motive of personal/communal identification was positively associated with podcast consumption in several settings manifests the importance of this motive. Perks and Turner (2019) pointed out that podcast users could develop a strong relationship with their favorite programs/personalities. This relationship could have several cognitive and affective consequences, such as greater engagement, enjoyment, identification, and loyalty. Pavelko and Myrick (2020) also found that podcast users’ para-social relationship and identification with hosts predicted how much users perceived themselves as benefiting from the programs socially and mentally. The current study supports these arguments and finds that the need for identification has behavioral consequences as well. It is an important motive that drives podcast users to consume more podcasts at home and on the go. Aware of podcasts’ great potential in building relationships, an increasing number of celebrities and social media influencers are joining the podcasting space to connect with their fans and to find a new audience (Moore and Moore, 2019). The bond between listeners and their programs/personalities on this platform has significant marketing communication implications as brand sponsors attempt to breakthrough clutters in today’s attention economy.

From the perspective of podcast usage, while the impact of audio platform superiority motive was consistent across the three usage measures, the differences between the frequency/time (i.e. number of podcasts per week and minutes per time) and routine/commitment (i.e. number of programs subscribed) factors are interesting. It seems that affective, entertainment-related motives play a more significant role in the actual usage level (i.e. amount consumed), while cognitive, information-related motives lead to more continuous engagement with the podcast content/host (i.e. subscription). Future research should explore subscription-related measures as indicators of content/host engagement, because content/host engagement has significant implications in sponsorship and audience development. Moreover, although demographic variables are beyond the interests of this study and, therefore, treated as control variables, they showed a great impact on podcast consumption patterns and usage levels. This probably explains why previous studies on podcasting, which focused on different demographics, have inconsistent results. The impact of demographics indicates that audience segmentation based on demographics could be useful and could help with podcast content and market development.

The investigation of podcast motives in the context of competing audio media also reveals new insights and implications. First, users who perceived podcasting as superior to other audio media tended to be heavy users of online radio, indicating that podcasting shares many of its audience with online radio, and might be attracting audience from the latter platform. This finding is not surprising, since iHeartRadio is also the top-ranked podcast publisher (Podtrac, 2020). It seems that the two digital audio platforms, podcasting and online radio, both offer a more active listening experience in comparison with traditional radio. Next, the positive association between the information motive for podcast listening and the usage of music streaming services signals a complementary relation between the two seemingly competing audio formats in the information sphere. Since information is a primary motivation for podcast listening but hardly one for music streaming, it seems that dedicated music listeners turn to podcasts, whose audio format better matches their media habits, to fulfill information needs. Realizing this trend, streaming music giants Spotify and Pandora have been investing heavily in the podcasting area to appeal to the audio audience (Slefo, 2019). Finally, podcast consumption appears to be more a “personal” media experience for self-reflection and connection with podcast hosts/communities than for social sharing purposes. The social interaction motive does not differentiate or elevate podcasting from other audio platforms, as it was not significantly associated with lower usage of the competing audio media. Similarly, podcasting’s digital counterparts in online radio and streaming music do not seem to offer better means of affirming personal identity.

The findings from this study support the notion that media usage, especially on today’s complex media platforms, is multidimensional and should be measured from multiple aspects and examined in various settings. For example, both the regression and correlation results suggest that the home setting for podcast consumption is very different from the workplace and on-the-go settings. Consumption at home was not only negatively correlated with consumption on the go, but also all the usage indicators of podcasting and other audio media. This reveals that users who prefer to listen to podcasts at home are unlikely to be traditional podcast users who bring podcasts with them everywhere; they even may not be typical audio media consumers as they consume all types of audio media less, either offline or online radio, podcasting or streaming music. These findings suggest that podcasting is no longer merely a mobile, on-demand extension of radio; it has evolved into a more sophisticated, unique medium with diverse user segments, offering an alternative, distinct audio platform of messaging for communication/marketing campaigns. This shift is likely to be enhanced by the popularity of other platforms not specifically designed for audio (e.g. YouTube) as new channels for podcast listening (Alexander, 2019), and the increasing penetration of new devices, such as smart speakers in households, since more and more podcasts are consumed via smart speakers (Edison Research and Triton Digital, 2018). The rise of celebrity and influencer podcasters may also have contributed to the change, because they are bringing new listeners to podcasting from their existing, huge fan bases (Moore and Moore, 2019).

In summary, this study sheds light on how scholars might “frame podcasting as a subject of scrutiny” (Berry, 2016: 8) and what practitioners could do to improve content strategy, audience targeting, market development, and sponsor collaboration. We argue that it is no longer appropriate to consider podcasting as a digital, mobile, and on-demand extension of radio, since it is consumed differently by the audience and is gradually diverging from radio in terms of audience base (e.g. the gain of non-radio listeners), platforms (e.g. the popularity of non-radio platforms), and producers (e.g. the burgeoning of non-expert, individual creators). Podcasting is not only a new medium, but also a new way of communication. On one hand, it holds a unique position in the media landscape and has the potential to connect radio, streaming music, and the outer non-audio world. On the other hand, it creates an intimate, focused atmosphere for listeners to engage and build a relationship with the content and hosts, as well as to affirm personal and social identities. Furthermore, we argue that the podcast audience is not a monolith; it is imperative for researchers to delve more deeply into podcasting and gain a more thorough understanding of the listeners. This study serves as an initial attempt and finds that the podcast audience is internally diversified, with the more active home listeners seeking for information and entertainment, and the more ritualized out of home listeners who value mobility and control. While listeners driven by affective, entertainment motives consume more intensively, those driven by cognitive, informational motives exhibit higher levels of long-term engagement and commitment.

A few limitations of this study need to be addressed. First, podcast consumption is complex and affected by many factors. Although motives are important and significant predictors, they cannot fully explain the variance in behaviors. A full range of other factors, such as those related to individual differences, social influence, program genres, technology availability, and environment, would all presumably have a huge impact on consumption patterns. Given this, it is not surprising that the models in this study have relatively low R² values. Future studies could incorporate more factors if the purpose is to improve predictability. Nevertheless, this study demonstrates that overall, there is a small but reliable relationship between motives and various podcast consumption behaviors, regardless of all other factors. This small difference is meaningful and of practical significance. It tells how podcasts fit in people’s daily lives and offers insights to content creators and service providers. The second limitation is that this study relied on self-reported data of media consumption. Future studies could employ consumption data generated by podcast applications for more accurate measurement. Third, this study mainly focused on consumption behaviors; perceptions and attitudes were not investigated. How podcast users perceive and feel about the media format could be a fruitful area to explore. Fourth, this study only examined users’ interactions with the podcasting medium; studying how users interact with podcast personalities and other users could further help with our understanding of this audience from the para-social conceptual tradition. Finally, this study only investigated podcasting in comparison with regular radio, online radio, and streaming music, it would be interesting to also consider other audio media formats, such as audiobooks, and maybe non-audio formats as well, such as online videos.

In closing, it is interesting that several recent industry studies found podcasting to be “pandemic proof” (Stitcher, 2020; Westwood One, 2020). During the first 8 weeks of the coronavirus disease 2019 (COVID-19) pandemic (i.e. March and April), total podcast listening hours on the podcast platform Stitcher did drop a little bit (i.e. 14%), mainly due to the decrease of listening during weekday commuting hours. However, since the second half of April, podcast listening started to show a return to the pre-pandemic level (Stitcher, 2020). In July, more than 90% of weekly podcast listeners indicated that they listened to podcasts for about the same amount of time or even more time since the pandemic (Westwood One, 2020). Certain genres, such as news and topical shows and kids and family content, became more popular during the pandemic, indicating that listeners are incorporating podcasting into many aspects of their lives (Stitcher, 2020). It would be fascinating for future researchers to study podcast listening patterns in a year or so to examine the effects of quarantine and remote work on listening motives and behaviors.

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Sylvia Chan-Olmsted

Rang Wang

Author biographies

Sylvia Chan-Olmsted is a professor in the College of Journalism and Communications at University of Florida. She received her doctorate from Michigan State University. Her research expertise includes digital/mobile media consumption, branding, and strategic competition in emerging media/communications industries. She has conducted consumer research and consulted for Google, Nielsen, National Association of Broadcasters, the Cable Center, and the Center for International Business Education and Research.

Rang Wang is a doctoral candidate in the College of Journalism and Communications at University of Florida. She received her master’s degree from University of Florida. Her research interests focus on how brands engage with consumers through technology, branded content, and social media influencers. She has conducted both academic and industrial research.

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