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Article

What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits

by
Jaemin Song
1,
Sunghan Ryu
2 and
Dongyeon Kim
3,*
1
Department of Business Administration, Sungkonghoe University, Seoul 08359, Republic of Korea
2
USC-SJTU Institute of Cultural and Creative Industry, Shanghai Jiao Tong University, Shanghai 200240, China
3
Department of Business Administration, The Catholic University of Korea, Bucheon 14662, Republic of Korea
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1107-1125; https://doi.org/10.3390/jtaer18020056
Submission received: 23 February 2023 / Revised: 28 April 2023 / Accepted: 8 June 2023 / Published: 12 June 2023
(This article belongs to the Section Digital Marketing and the Connected Consumer)
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Abstract

:
Mobile streaming is increasingly viewed as a major advancement in the wireless industry, as it enables users to consume content without any time or space restrictions. Mobile TV serves as an excellent example of streaming, providing services for watching TV content on mobile devices. While previous studies have explored video-on-demand (VOD) purchasing factors in mobile TV, it is rare to find research examining differences based on users’ mobile TV usage types, such as subscribers and free users. Consequently, we investigated VOD purchase factors for 310 subscribers and 311 free mobile TV users. In other words, using 621 survey responses, we analyze the influence of personality traits, intrinsic and extrinsic motivations, and mobile-related factors on users’ VOD purchase intentions and behavior. Our findings indicate that mobile TV utilization, hedonic needs, and subjective norms are positively related to VOD purchases, and that neuroticism, extraversion, openness, and conscientiousness positively impact mobile TV utilization. We also examine the relationships between the constructs within two sub-groups to highlight the differing perceptions and behavioral patterns of these groups regarding mobile TV utilization and VOD purchases. Theoretical and practical implications are discussed as well.

1. Introduction

The recent wave of digitization has revolutionized media consumption, with the rise of over-the-top (OTT) services offering direct streaming to users, facilitated by the widespread availability of smartphones and advanced networks [1]. Mobile video services are now considered the next major development in the wireless industry [2], as OTT enables users to consume content without time or space constraints. Mobile TV exemplifies this trend, providing services for viewing TV content on mobile devices through various transmission methods, such as mobile phone networks and the internet [3]. Mobile TV services offer both free content and pay-per-view (PPV) services for paid video-on-demand (VOD), which is one of the primary revenue streams for mobile TV service providers.
Mobile TV service adoption is a popular research topic [1], but in-depth studies analyzing mobile-specific settings and PPV services remain scarce. Our aim is to bridge this gap by examining the dynamics of VOD purchase behavior using four motivations. Hirschberg [4] suggests that individual motivation is a crucial construct for explaining behavioral differences, yet little is known about the varying motivations for watching mobile TV versus traditional TV. Our study seeks to comprehensively analyze the mobile TV service environment to better understand the phenomenon of VOD purchases. We focus on motivational factors influencing VOD purchases, particularly in the mobile environment. Moreover, our study investigates the relationship between personality and mobile TV watching behavior. Conway and Rubin [5] contend that individual psychological predictors can impact television-watching motivation, but limited research has explored the connection between mobile TV users’ personalities and VOD purchases in the mobile environment. Thus, we adopt the widely accepted Big Five personality framework to examine how an individual’s personality affects mobile TV usage behavior.
The goal of this study is to discover and identify the factors influencing VOD purchases among mobile TV users, including both subscribers and free users. Specifically, the study aims to comprehend the decision-making process of mobile TV users when considering the purchase of paid VOD content, such as movies and TV shows. Furthermore, this study intends to examine the behavioral differences in VOD purchase dynamics between subscribers and free users. To investigate the relationship between these key factors, the research model is based on a variety of elements, including the Big Five personality traits, intrinsic and extrinsic motivations, public transit usage duration, and mobile-related factors such as mobile utilization and mobile TV utilization.

2. Theoretical Background

2.1. Mobile TV Service

Mobile TV services involve the integration of television content with mobile devices such as smartphones, tablets, and laptops. These services enable access to video content on mobile devices without the need for wired cable subscriptions, transforming the way people consume traditional TV content [6]. A growing number of individuals, particularly younger audiences, receive most of their television content through streaming services, signifying a shift from traditional distribution methods to new digital technology-based approaches [7]. However, despite the significant changes that OTT and mobile services have brought to the media and broadcasting industries, the literature on mobile TV remains relatively limited [8].
To date, common research themes related to mobile TV can be summarized as follows. One literature stream is related to service adoption. Kim et al. [9] indicate that consumer intentions toward new service subscriptions are critical factors for success in the mobile TV business. Kim et al. [8] note the competitive dynamics between OTT and traditional cable TV platforms through a niche analysis. The findings explain how the adoption of new services is competitively superior to existing services. Other researchers adopt perceived value, social cognitive, and motivation theories to explain users’ service adoption and willingness to pay for mobile applications [10]. Although these studies have successfully investigated the dynamics of mobile TV adoption, an in-depth study analyzing mobile-specific settings and PPTV services is still lacking.

2.2. Intrinsic and Extrinsic Motivations

Individual motivation is a crucial construct employed to describe individual differences, shedding light on variations in behavior and intensity [4]. It has been studied in diverse research areas and is considered one of the key predictors of individual behavior. Numerous studies and theories of motivation have focused on goals or outcomes and the means leading to these desired outcomes [11]. For example, expectancy theory [12] outlines the process by which an individual selects one behavior option over another, as well as the rationale behind this decision in relation to their goals. According to this theory, the relationship between rewards and personal goals can determine an individual’s tendency to engage in a target behavior. This means that the degree to which expected benefits from a behavior satisfy a user’s goals or needs can determine their willingness to perform the behavior. Furthermore, Vroom [12] defines motivation as a process that governs choice among alternative forms of voluntary activities and is controlled by the individual. In other words, individuals make choices based on their estimates of how well the expected results of a given behavior will lead to the desired outcomes.
Similarly, attribution theory describes how individuals explain the causes of their behaviors and events [13]. In other words, attribution is an individual’s belief about how the causes of success or failure affect their emotions and motivations. Individuals formulate explanatory attributions to understand the events they experience and seek reasons for their failures. Seeking positive feedback from failures can motivate individuals to demonstrate improved performance. Furthermore, theories of motivation can be divided into two perspectives from an attribution perspective: intrapersonal or interpersonal. The intrapersonal perspective includes self-directed thoughts and emotions, while the interpersonal perspective includes beliefs about others’ responsibility and the effects of emotions on others [14].
Uysal and Jurowski [15] classify motivations into two categories: push and pull motivations. Push motivation is related to people who drive themselves towards their goals or to achieve something. Most push factors are intrinsic motivators, such as the desire for escape, rest, relaxation, prestige, and health [15]. However, pushing motivation can also lead to discouragement when obstacles arise on the path to achievement. Dann [16] refers to motivational influences on an individual as a push factor. On the other hand, pull motivation is a much stronger type of motivation and is generally viewed from the supply-side dimension. For example, the force of attractions in a destination is considered to exert a pull response on the individual [17]. Pull factors emerge from the attractiveness of a destination as perceived by those inclined to travel. They include natural attractions, cultural resources, recreational activities, special events or festivals, and other entertainment opportunities [15].
One of the main topics in previous research has been whether individual behavior can be seen as intrinsically or extrinsically motivated [18]. Intrinsic motivation is defined as performing an activity for its inherent pleasure and satisfaction [19]. Intrinsically motivated individuals tend to carry out tasks voluntarily, without material rewards or external constraints. On the other hand, extrinsically motivated behaviors are performed as a means to an end, not for their own sake [18]. Therefore, extrinsic motivation differs from intrinsic motivation because extrinsically motivated individuals do not perform tasks out of interest but because of their instrumental value.
In media research, Papacharissi and Rubin [20] identify five individual motivations for viewers to use new media: news and chat, personal assistance, search for information, comfort, and entertainment. Oh and Syn [21] also state that viewers use social TV to gain perceived benefits of self-interest and utility through easy communication via the internet. Liao et al. [22] apply expectancy theory to determine the factors affecting the use of modern media. Additionally, researchers have investigated individual motivations for adopting online TV services [23], how mobile TV services can substitute traditional TV [24], and consumers’ motivational factors for using online video platforms using the technology acceptance model [25]. However, little is known about the motivations of individual viewers to watch mobile TV and how they differ from the traditional motivations for TV viewing.

2.3. Big-Five Personality Dimensions

Personality has been conceptualized from various theoretical perspectives [26]. To understand and simplify personality in various domains, personality psychology needs a scientific taxonomy. After decades of research, personality academia is approaching consensus on the general classification of the Big Five personality dimensions [27]. Although personality psychologists largely agree that five superordinate constructs can describe the domain of personality, researchers have used different labels for these five factors. Consequently, Devaraj et al. [28] describe five representative general labels: (a) conscientiousness, referring to the degree of organization, persistence, and motivation in goal-directed behavior; (b) extraversion, characterized by sociability, gregariousness, and ambition; (c) neuroticism, or emotional instability, marked by insecurity, anxiousness, and hostility; (d) openness to experience, relating to flexibility of thought and tolerance of new ideas; and (e) agreeableness, represented by a compassionate interpersonal orientation. The Big Five personality model has significant implications for personnel psychology. Barrick and Mount [29] illustrate that personality consists of five relatively independent dimensions, providing a meaningful taxonomy for studying individual differences.
Extraversion is a personality trait that indicates the degree of sociability, gregariousness, assertiveness, talkativeness, and activity [29]. People with high levels of extraversion highly value close and warm interpersonal relationships [30]. This personality trait is associated with beliefs about specific behaviors. Agreeableness represents a compassionate interpersonal orientation and is characterized by kindness, consideration, likability, helpfulness, and cooperativeness [28]. This personality trait is associated with interpersonal interaction and teamwork, particularly helping and cooperating with others [31]. Agreeable personalities are more likely to be accommodating and cooperative when asked to consider new technology [28]. Neuroticism, on the other hand, indicates the degree of anxiety, depression, anger, embarrassment, emotionality, worry, and insecurity [29]. It is related to negative emotions and adverse reactions to work-related situations [32]. People with high neuroticism are expected to respond negatively to and evaluate a stimulus. Openness (to experience) indicates the degree of being imaginative, cultured, curious, original, broad-minded, intelligent, and artistically sensitive [29]. Individuals with high levels of openness actively seek new and varied experiences and value changes [33]. Conscientiousness refers to the drive to accomplish something and contains the necessary characteristics for such a pursuit: being organized, systematic, efficient, practical, and steady [34]. Conscientious personalities are intrinsically motivated to achieve, perform at a high level, and take action to improve their job performance. This personality trait is self-controlled and reflected in the need for achievement, order, and persistence [35].
Previous research in media studies suggests that individual psychological factors play a significant role in motivating people to watch television [5]. Rosengren [36] argues that individual personality traits impact media selection, usage, and outcomes. To account for this, personality traits need to be considered in media research. Finn and Gorr [37] investigate six personality traits, including shyness, loneliness, self-esteem, and social support, finding that self-esteem and social support are positively related to mood management motives such as relaxation, entertainment, arousal, and information but negatively related to the social compensation motive, which includes companionship, pass time, habit, and escape. Conversely, shyness and loneliness are positively correlated with the social compensation motive. Table 1 summarizes the Big Five personality dimensions examined in this study [28].

3. Hypotheses Development

3.1. Intrinsic Motivation and Purchase

Intrinsic motivation refers to behaviors driven by personal benefits [18]. A customer engages in behavior because they derive pleasure and satisfaction from it. Hedonic need, an intrinsic motivation factor, is crucial because mobile TV users pay to watch VODs for excitement or fun. Thong et al. [38] find that perceived enjoyment, a type of intrinsic motivation, positively impacts the intention to use IT services continuously. Similarly, several studies find that a feeling of excitement or fun significantly and positively affects IT service users’ attitudes and usage intentions [39,40]. Furthermore, Van der Heijden [39] states that a positive experience is a key driver of hedonic service usage, such as mobile service and mobile gaming. Therefore, in the context of mobile TV, it is hypothesized that hedonic needs influence VOD purchases.
Additionally, the advantage of mobility allows mobile TV users to purchase and watch a VOD anytime, anywhere. This spatiotemporal convenience can be an intrinsic motivation factor. Kim et al. [41] find that the temporal and spatial dimensions of mobility positively impact the intention to use mobile payments via perceived usefulness. The spatiotemporal convenience that people can easily experience through mobile services positively affects attitudes and acceptance of mobile services in various contexts, such as mobile financial services and mobile advertising [42]. Thus, we suggest that spatiotemporal convenience influences VOD purchases on mobile TVs.
H1: 
As an intrinsic motivation, hedonic need positively influences users’ VOD purchases on mobile TVs.
H2: 
As an intrinsic motivation, spatiotemporal convenience positively influences users’ VOD purchases on mobile TVs.

3.2. Extrinsic Motivation and Purchase

Extrinsic motivation refers to activities performed to achieve a separate outcome [43]. In the context of mobile TV, two extrinsic motivations, such as price fairness and subjective norms, can influence VOD purchasing behavior. First, as an extrinsic motivation, mobile TV users’ expectations of price fairness can play a crucial role in VOD purchases. Price fairness refers to a consumer’s evaluation of whether a seller’s price is reasonable, acceptable, or justifiable [44], and it has been studied as a psychological determinant of customers’ reactions to prices [45]. Previous research has shown that price fairness can affect customer satisfaction, loyalty, and the intention to use IT services [46,47]. Thus, users’ perception of price fairness influences their decision to purchase VODs on mobile TVs.
Second, subjective norms refer to perceived social pressure to perform a target behavior [48]. In other words, subjective norms explain how significantly others’ opinions can influence users’ purchasing decisions. Social motivation caused by a third party who is regarded as an important person is also considered extrinsic motivation [49]. Previous research has established the importance of subjective norms and their impact on customers’ perceptions and behaviors in various contexts [50,51]. Therefore, it is expected that subjective norms can also affect mobile TV users’ VOD purchases as an extrinsic motivation. In summary, we propose the following hypotheses:
H3: 
As an extrinsic motivation, price fairness positively influences users’ VOD purchases on mobile TVs.
H4: 
As an extrinsic motivation, subjective norms positively influence users’ VOD purchases on mobile TVs.

3.3. Mobile TV Utilization and Purchase

Mobile TV utilization refers to the usage patterns of mobile TV users on a service platform [52]. As Saga and Zmud [53] suggest, the most desirable outcome for a new product or service is for it to become routinized among potential customers, requiring repetitive usage. In other words, users need to become familiar with the new or innovative service before adopting it as routine behavior. Lee et al. [54] find that mobile TV adoption is influenced by media usage levels, as younger generations who are more familiar with IT tend to adopt new IT services more easily. Therefore, we propose that users with higher levels of mobile TV utilization will make more VOD purchases on the mobile TV service platform.
H5: 
Mobile TV utilization positively influences users’ VOD purchases.

3.4. Big Five Personality Model and Mobile TV Utilization

Mass communication theorists have long studied the role of personality factors in media use [55]. Rosengren [36] contends that an individual’s personality has a pervasive impact on various stages of media selection, use, and consequences. Similarly, Weaver [56] asserts that customer behavior should be influenced by predominant personality characteristics. Correa et al. [57] find that users’ personality traits can be crucial factors driving media use. Ross et al. [58] explore the relationship between the Big Five personality traits and Facebook use, while Meng and Leung [59] examine the relationship between the Big Five model and TikTok engagement. In light of the Big Five personality model, we aim to investigate how different personality factors affect mobile TV utilization, the primary variable in our study of VOD purchases.

3.4.1. Neuroticism

In our research context, we suggest that neuroticism is related to users’ TV viewership behavior patterns. Weaver [60] finds that individuals high in the neuroticism trait positively relate to leisure activity, companionship, and relaxation in their TV viewing motives. Moreover, individuals with the neurotic personality type are expected to have a strong positive relationship with watching television, as emotionally unstable people find comfort in popular TV programs [61]. Therefore, we assume that neuroticism positively impacts users’ mobile TV utilization.
H6: 
The neuroticism trait positively influences users’ mobile TV utilization.

3.4.2. Extraversion

Researchers argue that extraverted personalities score low on TV watching, radio listening, and reading for pleasure [62]. However, in the mobile context, studies demonstrate that extraversion is an important predictor of a higher level of mobile phone use. This means that people with extraverted personalities have many friends and social networks [58], which can affect their mobile phone use as they tend to be more sociable with acquaintances and susceptible to peer influence [63]. Similarly, extraverted users are less likely to want to be bored during idle or travel time. Consequently, we propose that extraversion positively affects users’ mobile TV utilization.
H7: 
The extraversion trait positively influences users’ mobile TV utilization.

3.4.3. Openness

The personality trait of openness is known to be a critical determinant of media preferences and cultural participation [61]. Openness has been found to have a positive effect on popular TV viewing [64]. Furthermore, individuals with the openness personality trait are also known to have higher levels of creativity [65]. They tend to be more willing to try new and different things and actively seek out new and varied experiences [33]. Since mobile TV is a relatively new experience with technological advances unlike traditional TV, we propose that openness positively impacts users’ mobile TV utilization.
H8: 
The openness trait positively influences users’ mobile TV utilization.

3.4.4. Agreeableness

Devaraj et al. [28] find that individuals with agreeable personalities are more likely to be accommodating and cooperative when considering new technologies. Similarly, Pentina et al. [66] find that people with agreeable personalities are more likely to adopt information-sensitive mobile applications. This suggests that agreeable individuals may also be more likely to adopt and use new technologies, such as mobile TV, due to their fast adaptation characteristics. Therefore, we hypothesize that agreeableness positively influences users’ mobile TV utilization.
H9: 
The agreeableness trait positively influences users’ mobile TV utilization.

3.4.5. Conscientiousness

Previous research shows that individuals with a conscientious personality are less likely to engage in social media use [67]. Conscientious users are more likely to consider the impact of their actions on others and spend their time on other activities [58]. They may not spend much time using social media or mobile services for entertainment purposes because they prioritize other responsibilities and prefer offline activities [68]. Therefore, we propose that individuals with conscientious personalities may be less likely to watch mobile TV during their spare time. Thus, we hypothesize that conscientiousness negatively influences users’ mobile TV utilization.
H10: 
The conscientiousness trait negatively influences users’ mobile TV utilization.

3.5. Mobile Usage Patterns and Mobile TV Utilization

Smart devices offer a wide range of possibilities through powerful and efficient processors, optimized operating systems, broadband internet access, and various mobile applications [69]. This means that mobile devices facilitate lightweight computing that is accessible on the go and wirelessly connected. Furthermore, most individuals carry mobile devices every day, making it essential to determine their mobile usage pattern. With the emergence of mobile application culture, mobile usage may be the key to understanding the diversity of individual use. Therefore, many studies have investigated mobile device usage patterns in relation to users’ daily lives because mobile devices are an essential part of daily life [70].
Likewise, it is meaningful to examine the relationship between mobile utilization and mobile TV utilization. For example, Huang et al. [71] attempt to predict mobile application usage patterns using overall mobile device usage patterns such as the last used application, location, and user profile. Kim et al. [72] also find that mobile application attention (e.g., number of logins) is an important factor that can predict whether mobile transactions occur. As a result, we propose that mobile utilization positively affects users’ mobile TV utilization.
H11: 
Mobile utilization positively influences users’ mobile TV utilization.
Mobile media is deeply related to travel and transportation, which indicates that mobile usage is directed towards homes, workplaces, and transportation-related places. Kokkinou et al. [73] find that people’s vacation quality is improved when using mobile devices. They also note that active use of mobile devices can make people less weary when waiting at attractions or restaurants. In this sense, daily transit usage (e.g., the duration of public transit use) can positively influence mobile TV usage because people use mobile devices to actively relieve their boredom.
H12: 
Duration of public transit use positively influences users’ mobile TV utilization.

3.6. Research Model

In summary, we aim to investigate how the Big Five personality traits affect mobile TV utilization and how the four motivational factors, namely hedonic need, spatiotemporal convenience, price fairness, and subjective norm, influence VOD purchases. Moreover, we include three mobile-related constructs in our research model: mobile utilization, mobile TV utilization, and duration of public transit use. Figure 1 represents our research model.
Additionally, we aim to examine the differences in this relationship between free users and subscribers to mobile TV. Free users are mobile TV users without paid subscriptions, while subscribers are users who pay for a subscription. We propose various mobile TV usage drivers to identify users’ specific behaviors and factors that motivate them to purchase VOD content. Thus, we emphasize the importance of adopting a psychological perspective that considers users’ personalities and motivations for understanding mobile TV usage drivers.

4. Empirical Analysis

We collect data through surveys and utilize the partial least squares (PLS) technique to examine our research model and hypotheses. PLS is a suitable approach for exploratory and prediction-oriented research, as it does not require a multivariate normal distribution [74], making it appropriate for our study, which aims to explore differences in personalities and motivational factors in the mobile TV context. Furthermore, adopting a survey methodology allows for high external validity, as we expect to gain a more generalized understanding of our research model.

4.1. Measurement Development

The survey questionnaire consists of demographic profile questions and constructed items. Many constructs in this study are adapted from previous research, such as intrinsic motivation (i.e., hedonic need, spatiotemporal convenience), extrinsic motivation (i.e., price fairness, subjective norms), individual characteristics (i.e., neuroticism, extraversion, openness, agreeableness, conscientiousness), and VOD purchase [26,28,75,76,77,78,79,80]. These constructs are modified to fit the mobile TV context, and all items are measured using a 7-point Likert scale.
We introduce three new constructs: mobile utilization, mobile TV utilization, and duration of public transit use. First, mobile utilization represents the extent of a customer’s mobile device usage, measured by the number of mobile devices and mobile applications used. Second, mobile TV utilization denotes the degree of a customer’s mobile TV usage, measured by the degree of mobile TV usage per day. Third, the duration of public transit use refers to the degree of time spent on public transportation per day. Items in these three constructs are measured using a 5-point Likert scale.
Please refer to Appendix A for the constructs and questionnaire items.

4.2. Sample

We conducted a one-month survey through a survey panel service company, targeting individuals aged 20 to 60 who have used a mobile TV application on their mobile devices in South Korea. Mobile TV users utilize at least one application among the four major mobile TV services in South Korea: KT, SKB, LGU+, and TVING. Among the users, subscribers pay a monthly fee for mobile TV, while free users access only free content.
We receive responses from a total of 621 users: 310 subscribers and 311 free users. The sample comprises 313 males and 308 females, with 2 in their teens, 102 in their twenties, 176 in their thirties, 250 in their forties, and 91 in their fifties. Regarding the duration of mobile TV service use, 124 people have used it for 1 to 3 months, 93 people for 4 to 6 months, 66 people for 7 to 12 months, and 207 people for more than one year. Table 2 provides information on the participants’ demographic characteristics.

4.3. Measurement Model

The internal reliability of our measures is assessed using Cronbach’s alpha. The alpha values for our measures ranged from 0.753 to 0.958, indicating satisfactory levels of internal consistency. To validate the measurement model, we conduct tests for both convergent and discriminant validity. Convergent validity is assessed by calculating the composite reliability (CR), average variance extracted (AVE), and item loading. For convergent validity, CR values should be greater than 0.7, while AVE values should be greater than 0.5 [74]. All item loadings should exceed 0.6 [81], and t-values should be greater than 1.96 [82]. Our results, as shown in Table 3, indicate that all CR values, AVE values, and loadings of our research model exceed the recommended threshold values.
For discriminant validity, the square root of all AVEs should be greater than the inter-correlations between constructs [74]. Table 4 reveals that all square roots of AVE are greater than the inter-correlations. In addition, we assess the possibility of multicollinearity. The variance inflation factor values range from 1.042 to 2.843, indicating that multicollinearity is not a significant issue for the proposed model.

4.4. Structural Model

Our study employs structural equation modeling with the PLS technique, and the bootstrap resampling method is utilized with a total of 500 resamples to establish the significance of the research hypotheses. Our findings support most of the hypotheses, with the exception of H2, H3, and H9. Our results indicate that hedonic needs significantly influence VOD purchases, thus supporting H1. However, as spatiotemporal convenience and price fairness do not have a significant impact on VOD purchases, H2 and H3 are not supported. In addition, subjective norms have a significant influence on VOD purchases, which supports H4. Our study also finds that mobile TV utilization significantly impacts VOD purchases, supporting H5. Furthermore, our findings indicate that neuroticism, extraversion, and openness significantly influence mobile TV utilization, thus supporting H6, H7, and H8. However, agreeableness does not significantly impact mobile TV utilization, and H9 is not supported. Our study also finds that conscientiousness significantly influences mobile TV utilization, supporting H10. In addition, our results suggest that mobile utilization and the duration of public transit use significantly impact mobile TV utilization, therefore supporting H11 and H12. The results of the hypothesis test for our research model are displayed in Figure 2.

4.5. Additional Analysis

We conduct a more in-depth analysis by distinguishing between subscribers and free users in the pooled data. Out of the total 621 respondents, 310 pay for subscriptions, and 311 are free users. Analyzing these groups separately yields significant and interesting differences, as shown in Table 5. The variable with the most significant difference between the two groups is VOD purchases, with subscribers making more purchases than free users. This indicates that providing PPV services can be an effective way to retain subscribers. The next variable with a significant difference between the two groups is mobile TV utilization, with subscribers using and watching mobile TV more than free users. Increasing the quality and volume of content can lead to an increase in VOD purchases as mobile TV usage increases. Hedonic need is another variable that shows a significant difference between the two groups, with subscribers finding more pleasure than free users. Understanding the personalities and tastes of free users can help provide content that increases their interest.
Figure 3 and Figure 4 present the results for the subscriber and free user groups, respectively. In comparison to the pooled group, the subscriber group has three differences: hedonic need (H1), neuroticism (H6), and conscientiousness (H10) do not significantly influence the independent variable, purchase. For the free user group, subjective norms (H4) do not have an impact on purchase, and conscientiousness (H10) does not affect mobile TV utilization. Importantly, there are three distinct differences between the subscriber and free user groups. First, hedonic needs only have a positive impact on VOD purchases in the free user group. Second, subjective norms significantly and positively influence VOD purchases only in the subscriber group. Third, neuroticism has a significant positive effect on mobile TV utilization only in the free user group.

5. Discussions and Conclusions

The purpose of this study is to deepen our understanding of individual motivations, personalities, and mobile-related factors in the context of VOD purchases. To accomplish this, we adopt the Big Five personality model, mobile utilization, and duration of public transit use as antecedents to mobile TV utilization. We also examine the significance of motivational factors as determinants of VOD purchases.
Our findings indicate that hedonic needs and subjective norms significantly influence VOD purchases, aligning with previous research examining the effects of hedonic needs and subjective norms on online music purchases [83]. However, spatiotemporal convenience and price fairness do not have a significant impact on purchases. Nowadays, mobile TV services are rarely limited by time or space and are offered at low prices. In other words, these factors make customers more familiar with the service and lead them to view it as less special. Söderlund [84] also finds that familiarity with a service can negatively affect customer behavior in a service environment with poor performance. The agreeableness personality trait does not significantly impact mobile TV utilization. Agreeable users may focus more on social network services or social media when using smart devices due to their orientation towards others [68]. Regarding mobile-related factors, our study reveals that mobile utilization and duration of public transit use significantly influence mobile TV utilization. Furthermore, mobile TV utilization has the most considerable explanatory power in explaining VOD purchases among the determinant constructs. Many previous studies related to information systems confirm the significant relationship between shopping system utilization and purchase [85], so our results are consistent with these findings.
The study findings reveal that the two groups display distinct behavioral patterns in mobile TV utilization and VOD purchases. For free users, hedonic need serves as a motivational factor in purchasing VODs. Users with lower levels of hedonic needs are more sensitive to VOD purchases than subscribers with higher levels of hedonic needs when the hedonic need level increases equally. This suggests that when hedonic needs are lower, a small amount of hedonic stimulation results in a more significant response to a purchase. In contrast, for subscribers, subjective norms are the sole determining factor for VOD purchases among the motivations. Subscribers may actively engage with friends for diverse activities, and these interactions can stimulate them when their acquaintances watch VODs on mobile TV. Similarly, previous research indicates a negative relationship between TV viewing and socialization [86]. We also conclude that word-of-mouth strongly influences subscribers because they have already paid for the subscription and have a deeper connection to the service. Additionally, neuroticism leads to purchases only in the free user group. We hypothesize that users with neurotic personality traits may lack sufficient purchasing power since they do not pay for the subscription, even though they enjoy watching mobile TV. As a result, due to their tendency towards depression and anxiety, these users become more absorbed in watching mobile TV by themselves because they do not have enough money or energy to participate in other activities. In other words, users with low purchasing power and neurotic personalities tend to prefer watching mobile TV to engaging in outdoor activities [86].
This study has several significant theoretical implications. First, it combines motivation factors in the VOD purchase context and the Big Five personality model as antecedents to mobile TV utilization. This fills a gap in the literature, as previous research has not clarified how individual personalities and motivations determine mobile TV utilization and VOD purchase, respectively. Second, this study incorporates mobile-related constructs such as mobile TV utilization, mobile utilization, and the duration of public transit use in the VOD purchase context. This provides a more comprehensive understanding of the behavioral dynamics in a mobile context. Third, the subgroup analysis with the subscriber and free user groups reveals the different relationships between the constructs in the model, with hedonic needs, subjective norms, and neuroticism affecting VOD purchases differently in the two groups. This study confirms that the variables influencing VOD purchases and mobile TV utilization vary based on users’ subscription status. Overall, this study makes an essential contribution to the literature on mobile TV and VOD consumption.
This study has several practical implications. First, it suggests that mobile TV service providers should focus on mobile TV users’ personalities. Since conscientiousness negatively affects mobile TV utilization, service providers may consider increasing relatively productive channels, such as educational or informative channels. Second, according to the results, service providers need to consider how to increase free users’ access to mobile TV and encourage them to stay longer in the watching environment. As mobile TV utilization directly affects purchases, with the strongest explanatory power among the determinants, practitioners may need to find ways to enhance users’ mobile TV utilization. For instance, practitioners can consider loyalty programs for heavy users, offering discounts or points on paid content (e.g., paid VODs and channels). Third, this study reminds practitioners to adopt different strategies based on user status. Hedonic needs are directly associated with purchases only for free users, while subjective norms affect purchases only for subscribers. Thus, practitioners need to consider effective and differentiated strategies for users’ subscription status. For example, practitioners may provide diverse comedy and entertainment content to satisfy free users’ needs. Additionally, practitioners can implement strategies to provide one-plus-one VOD coupons for mobile TV subscribers to share their VOD with their acquaintances.
Our study has several limitations that present opportunities for future research. First, this study adopts a cross-sectional survey methodology, and the data are collected at a single point in time. As a result, it cannot investigate the dynamic nature of purchases over time on mobile TV service platforms. Future research can employ a longitudinal study to address this limitation. Second, since all the samples in this study were collected only in South Korea, there is a possibility of sampling bias and difficulty generalizing the findings to other cultural environments. Therefore, future studies should replicate our findings in different cultural settings. Third, this study does not collect transaction data for VOD purchases. Since users’ self-reported measures only capture the purchase, the findings of this study may be vulnerable to precisely estimating purchase behavior. Future research should include transaction data on mobile TV users’ VOD purchases.

Author Contributions

All three authors contributed to the completion of the research. J.S. contributed to the concept and design of the research and data analysis. S.R. contributed to managerial implications and discussion. D.K. modified the draft and contributed to the interpretation of the analysis result. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. RS-2022-00166755).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This work was supported by the Sungkonghoe University Research Grant of 2022.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Measurement items of research constructs.
Table A1. Measurement items of research constructs.
ConstructMeasurement ItemsReference
Hedonic needIt is fun to do.
I find participating in this service appealing.
I think that participating is quite enjoyable.
I think it is pleasurable.		[75]
Spatiotemporal
convenience		I can use this service any time I want.
I can use this service anywhere I want.
Using the service reduces the time required.
Using the service is convenient because my mobile device is usually with me.		[76]
Subjective normInnovative people around me think that I should subscribe to or purchase the service.
My colleagues think that I should subscribe to or purchase the service.
My close friends think that I should subscribe to or purchase the service.		[77]
Price fairnessThe price of the service is fair.
The price of the service is appropriate relative to its performance.
The price of the service meets my expectations.
The price of the service is clearly understandable.		[78,79]
PurchaseHow much do you pay for VOD content in a month?
How often do you purchase VOD content?
When was the most recent purchase of VOD content?		[80]
NeuroticismI see myself as someone who…
  • gets nervous easily.
  • is depressed or blue.
  • worries a lot.
  • is unstable.
[26,28]
ExtraversionI see myself as someone who…
  • is talkative.
  • is outgoing and sociable.
  • is full of energy.
  • is enthusiastic.
[26,28]
OpennessI see myself as someone who…
  • is inventive.
  • likes to reflect and play with ideas.
  • has an active imagination.
  • is insightful.
[26,28]
AgreeablenessI see myself as someone who…
  • is considerate and kind to others.
  • is helpful and unselfish with others.
  • has a forgiving nature.
  • is cooperative.
[26,28]
ConscientiousnessI see myself as someone who…
  • does a thorough job.
  • does things efficiently.
  • is a reliable worker.
  • is an organized worker.
[26,28]
Mobile utilizationHow many mobile apps do you have on your mobile device?
How many mobile apps do you have that you access at least once a day?
How long do you use them in a day?		Developed by authors
Mobile TV utilizationHow often do you have access to mobile TV?
How long do you watch TV in a day?		Developed by authors
Duration of public transit useHow long do you use public transportation in a day?Developed by authors

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Jtaer 18 00056 g001 550
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. Results of the research model (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
Figure 2. Results of the research model (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
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Jtaer 18 00056 g003 550
Figure 3. Results of the research model for subscribers (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
Figure 3. Results of the research model for subscribers (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
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Figure 4. Results of the research model for free users (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
Figure 4. Results of the research model for free users (* p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01).
Jtaer 18 00056 g004
Table
Table 1. Big Five Personality.
Table 1. Big Five Personality.
Big FivePersonality
ExtraversionSociable, gregarious, assertive, and active
AgreeablenessBeing kind, considerate, likable, helpful, and cooperative
NeuroticismAnxious, depressed, angry, embarrassed, emotional, and worried
OpennessBeing imaginative, cultured, curious, original, and broad-minded
ConscientiousnessBeing organized, systematic, efficient, practical, and steady
Table
Table 2. Demographic information.
Table 2. Demographic information.
ProfileOptionCount%
GenderMale31350.4
Female30849.6
Age10 s20.3
20 s10216.4
30 s17628.3
40 s25040.3
50 s9114.7
Period of mobile TV service use (in months) <113121.1
1~312420.0
4~69315.0
7~126610.6
>1220733.3
Total 621100
Table
Table 3. Reliability and convergent validity.
Table 3. Reliability and convergent validity.
ConstructMean (S.D.)AlphaCRAVEItemsLoadingst-Value
Hedonic
need		4.481
(1.366)		0.9580.9700.889HedN10.937127.689
HedN20.934133.137
HedN30.950188.260
HedN40.950188.872
Price
fairness		3.820
(1.329)		0.9570.9690.886PriF10.940155.423
PriF20.942157.829
PriF30.941168.635
PriF40.942183.836
Spatiotemporal
convenience		4.938
(1.338)		0.9390.9560.846STC10.932121.302
STC20.927116.651
STC30.89076.620
STC40.929107.115
Subjective
norms		3.993
(1.327)		0.9230.9460.815SubN10.931124.058
SubN20.944222.172
SubN30.947224.951
SubN40.77727.366
Agreeableness4.942
(1.004)		0.8800.9180.736Agree10.86245.559
Agree20.89869.212
Agree30.80226.520
Agree40.86845.613
Conscientiousness5.031
(1.020)		0.9100.9370.788Cons10.86841.287
Cons20.90059.513
Cons30.89149.731
Cons40.89155.302
Extraversion4.146
(1.171)		0.8790.9170.735Extra10.77631.159
Extra20.89785.405
Extra30.89166.809
Extra40.86154.035
Neuroticism3.818
(1.254)		0.9070.9350.782Neuro10.91670.632
Neuro20.92190.191
Neuro30.79828.374
Neuro40.89773.536
Openness4.493
(1.152)		0.8990.9370.832Open10.934126.280
Open20.931114.742
Open30.87055.337
Mobile
utilization		3.227
(0.912)		0.7530.8480.652MobA10.71617.533
MobA20.83334.241
MobA30.86639.687
Mobile TV
utilization		2.572
(1.042)		0.8080.9120.839MobTV10.923116.545
MobTV20.909102.880
VOD
purchase		2.260
(1.125)		0.9110.9440.849VODP10.89393.767
VODP20.943175.593
VODP30.927138.345
Table
Table 4. Correlation.
Table 4. Correlation.
AgreeConsExtraHedNMobAMobTVNeuroOpenPriFSTCSubNVODP
Agree0.858
Cons0.6210.887
Extra0.5050.4590.857
HedN0.4950.4660.4950.943
MobA0.2690.2480.1970.3470.808
MobTV0.2110.1530.3460.4500.3330.916
Neuro0.017-0.0600.1260.1110.0810.2030.884
Open0.5490.6460.6150.4660.2060.3090.0260.912
PriF0.3440.3000.5160.5730.1270.4270.3190.4340.941
STC0.5010.4590.3710.7480.3850.3980.0650.3820.4300.920
SubN0.3600.3230.5120.5860.1790.4990.3030.4590.7480.4900.903
VODP0.2400.2680.3790.4910.3080.6070.1990.3670.4850.4040.5360.921
Note: Diagonal numbers indicate the square root of AVE.
Table
Table 5. Differences between subscribers and free users.
Table 5. Differences between subscribers and free users.
Type of UsersNMeanS.D.Differencet-ValueSignificance
Transit useSubscribers3102.6001.2310.417 ***4.105<0.001
Free users3112.1801.298
HedNSubscribers3104.9531.0890.942 ***9.152<0.001
Free users3114.0111.451
STCSubscribers3105.3441.0580.811 ***7.927<0.001
Free users3114.5331.461
SubNSubscribers3104.4741.1820.961 ***9.679<0.001
Free users3113.5131.291
PriFSubscribers3104.1891.2400.737 ***7.184<0.001
Free users3113.4521.315
OpenSubscribers3104.7171.0880.447 ***4.928<0.001
Free users3114.2701.172
ConsSubscribers3105.1490.9550.236 ***2.8990.004
Free users3114.9131.070
ExtraSubscribers3104.4611.0900.629 ***6.944<0.001
Free users3113.8321.167
AgreeSubscribers3105.1050.9280.325 ***4.087<0.001
Free users3114.7801.051
NeuroSubscribers3103.9251.3250.214 **2.1360.033
Free users3113.7111.170
MobASubscribers3103.3750.8150.296 ***4.094<0.001
Free users3113.0790.979
MobTVSubscribers3103.0650.9190.984 ***13.350<0.001
Free users3112.0800.918
VODPSubscribers3102.8300.9911.138 ***14.606<0.001
Free users3111.6920.949
Note: * p ≤ 0.1, ** p ≤ 0.05, *** p ≤ 0.01.
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Song, J.; Ryu, S.; Kim, D. What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits. J. Theor. Appl. Electron. Commer. Res. 2023, 18, 1107-1125. https://doi.org/10.3390/jtaer18020056

AMA Style

Song J, Ryu S, Kim D. What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits. Journal of Theoretical and Applied Electronic Commerce Research. 2023; 18(2):1107-1125. https://doi.org/10.3390/jtaer18020056

Chicago/Turabian Style

Song, Jaemin, Sunghan Ryu, and Dongyeon Kim. 2023. "What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits" Journal of Theoretical and Applied Electronic Commerce Research 18, no. 2: 1107-1125. https://doi.org/10.3390/jtaer18020056

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