the influence of perceived reputation enhancement on

The Influence of Perceived Reputation Enhancement on Wearable Action Camera Usage

Kristijan Markovic1, Anicet Kebou Temdemnou1, and Claus-Peter H. Ernst1 1 Frankfurt University of Applied Sciences,

{kmarkovic | akeboutemdemnou | cernst}@fb3.fra-uas.de

Abstract One factor driving the recent success of wearable action cameras seems to be people’s Perceived Reputation Enhancement. More specifically, people might be using these devices to enhance their reputation by sharing their recorded video clips. In this study, we empirically evaluate the influence of Perceived Reputation Enhancement on wearable action camera usage. After collecting 124 completed online questionnaires about one specific wearable action camera, GoPro HERO4 Black, and applying a structural equation modeling approach, our findings indicate that wearable action cameras are at least partly hedonic technologies whose usage is influenced by Perceived Enjoyment. Furthermore, Perceived Reputation Enhancement had a significant direct positive influence on the Behavioral Intention to Use wearable action cameras, as well as an indirect positive influence on Behavioral Intention to Use through Perceived Enjoyment. These findings suggest that wearable action camera manufacturers need to emphasize the hedonic benefits of their devices as well as promote their capacity for enhancing their users’ reputation.

1 Introduction Wearable action cameras have gained momentum in the marketplace over the past years. The market was forecasted to grow at a compound annual growth rate of 22.2 percent between 2014 and 2019 (Research and Markets 2015). However, the factors driving the success of these action cameras are largely unknown.

Wearable action cameras are typically used by people in order to record point-of-view shots of their sports activities (Jennings 2015). Since individuals have a need to maintain and enhance their reputation (e.g., Emler 1984; Emler and Reicher 1995), they might use the recorded clips of their performances in order to accomplish this. We thus postulate that Perceived Reputation Enhancement positively influences people’s wearable action camera usage.

After collecting 124 completed online questionnaires about one specific wearable action camera, GoPro HERO4 Black, and applying a structural equation modeling approach, our findings indicate that wearable action cameras are at least partly hedonic technologies whose usage is influenced by Perceived Enjoyment. Furthermore, Perceived Reputation Enhancement had a significant direct

Volker Nissen, Dirk Stelzer, Steffen Straßburger und Daniel Fischer (Hrsg.):

Multikonferenz Wirtschaftsinformatik (MKWI) 2016 Technische Universität Ilmenau 09. - 11. März 2016

Ilmenau 2016 ISBN 978-3-86360-132-4 (Druckausgabe, Gesamtwerk)

1582 Kristijan Markovic, Anicet Kebou Temdemnou, Claus-Peter H. Ernst

positive influence on Behavioral Intention to Use as well as an indirect positive influence on Behavioral Intention to Use through Perceived Enjoyment. These findings suggest that wearable action camera manufacturers need to emphasize the hedonic benefits of their devices as well as promote their capacity for enhancing users’ reputation.

In the next section, we will present background information on wearable action cameras, introduce Perceived Enjoyment as an influence factor of hedonic technologies, and also present the theoretical foundations of Perceived Reputation Enhancement. Following this, we will present our research model and research design. We will then reveal and discuss our results before summarizing our findings, presenting their theoretical as well as practical implications, and providing an outlook on further research.

2 Theoretical Background

2.1 Wearable Action Cameras

Wearable action cameras are small-sized cameras that are typically attached to helmets, surfboards, etc., by people in order to record point-of-view shots of their sports activities (Jennings 2015). Although multiple studies have studied different aspects of wearable devices (e.g., Ariyatum et al. 2005; Bodine and Gemperle 2003; Dvorak 2008; Starner 2001), only a few studies have focused specifically on wearable action cameras.

For example, two studies have studied the capacity of wearable action cameras to improve student motivation as well as student understanding of material failure mechanisms in material science classes (McCaslin et al. 2014; McCaslin and Young 2015). Another study evaluated hand tracking and gesture recognition in action cameras’ point-of-view shots (Morerio et al. 2013). However, to the best of our knowledge, no study has yet evaluated the drivers of wearable action camera usage.

2.2 The Role of Perceived Enjoyment on Wearable Action Camera Usage

Sports activities provide people with hedonic benefits such as enjoyment, fun, excitement, etc. (e.g., Côté and Hay 2002; MacPhail et al. 2003; Nielsen et al. 2014; Thedin Jakobsson 2014; Vlachopoulos et al. 2000). As a result, wearable action cameras are regularly used in hedonic contexts, making them at least a partly hedonic technology.

In general, hedonic technologies “aim to provide self-fulfilling value to the user, ... [which] is a function of the degree to which the user experiences fun when using the system“ (Van der Heijden 2004, 696). Various studies in a variety of contexts have consistently confirmed that Perceived Enjoyment — “the extent to which the activity of using a specific system is perceived to be enjoyable in its own right, aside from any performance consequences resulting from system use” (Venkatesh 2000, 351) — is a central antecedent of hedonic technology usage (e.g., Van der Heijden 2004). By applying these findings to our context, a person can be expected to use wearable action cameras if he/she believes that they fulfill his/her expectations with regards to their hedonic benefits such as enjoyment and excitement (e.g., Van der Heijden 2004).

2.3 Perceived Reputation Enhancement

In general, people have a need to maintain and enhance their reputation (e.g., Emler 1984; Emler and Reicher 1995) — that is, other people’s judgment of their talents and character, which is circulated to some degree within the social community (Emler 2013). Since reputation depends on

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an individual’s attributes and actions that are visible to others, people choose a specific self-image that they want to reflect and adjust their behavior accordingly (e.g., Emler 1984; Emler and Reicher 1995; cf. Carroll et al. 2001).

For example, someone who would like to appear wealthy might wear a Rolex; someone who would like to build a reputation of being generous might give money to homeless people; and someone who would like to look athletic might dress accordingly. Generally speaking, if someone believes that a certain behavior can enhance his/her intended reputation, he/she will do so. Or, in other words, Perceived Reputation Enhancement, which we describe as the extent to which a person believes that a certain behavior has positive consequences on his/her reputation, positively influences the behavior in question.

3 Research Model In the following section, we will present our research model in Figure 1 and then outline our corresponding hypotheses.

Figure 1: Research Model

As described earlier, wearable action camera usage likely happens in fun and exciting contexts. Therefore, wearable action cameras can be seen as at least partly hedonic technologies that can provide positive feelings and experiences to their users (cf. Van der Heijden 2004). Perceived Enjoyment has been shown to be an important antecedent of hedonic technology usage (e.g., Ernst et al. 2013; Van der Heijden 2004). We hypothesize that:

There is a positive influence of Perceived Enjoyment on the Behavioral Intention to Use1 wearable action cameras (H1).

People have a need to maintain and enhance their reputation (e.g., Emler 1984; Emler and Reicher 1995). As a result, they perform behaviors that they believe will enhance their reputation. Wearable action cameras are used by people to record shots of their sports activities (Jennings 2015). These clips can be posted to the Internet or, at the very least, shown to friends and peers. These videos of personal performances enable that person to enhance different kinds of reputations: a reputation

1 In line with multiple technology acceptance studies (cf. Yousafzai et al. 2007), we did not include Actual System Use into our research model — indeed, we included only Behavioral Intention to Use. Behavioral Intention to Use is a commonly accepted mediator between people’s beliefs and their actual behavior. It “capture[s] the motivational factors that influence a [person’s] behavior; they are indications of how hard people are willing to try, of how much of an effort they are planning to exert, in order to perform the behavior” (Ajzen 1991, 181).


being brave, bold, athletic, etc. Consequently, Perceived Reputation Enhancement can be expected to exert a positive influence on wearable action camera usage. We hypothesize that:

There is a positive influence of Perceived Reputation Enhancement on the Behavioral Intention to Use wearable action cameras (H2).

Furthermore, being accepted and respected by peers is positively linked to hedonic well-being, represented by the presence of positive hedonic feelings such as enjoyment, happiness, and pleasure (e.g., Baumeister and Leary 1995). Perceived Enjoyment reflects the hedonic motivations of technology use, such as fun, enjoyment and other positive experiences and feelings (Brief and Aldag 1977; Van der Heijden 2004; Venkatesh et al. 2012). Consequently, we believe that Perceived Reputation Enhancement has a positive influence on Perceived Enjoyment in the context of wearable action camera usage. We hypothesize that:

There is a positive influence of Perceived Reputation Enhancement on the Perceived Enjoyment of wearable action cameras (H3).

4 Research Design

4.1 Data Collection

To empirically evaluate our research model, we collected 124 completed German-language online questionnaires about one specific wearable action camera, the GoPro HERO4 Black, between May 24 and June 8, 2015, by posting the link to the questionnaire in multiple Facebook groups and message boards focusing on action cameras as well as on the Facebook pages of two of the authors. At the beginning of the questionnaire, we gave a short description of the GoPro HERO4 Black including official images and an explanation of its general functionalities. The action camera promises users to capture 4K video at up to 30 frames per second. Furthermore, it has built-in Wi-Fi and Bluetooth that enables users to share videos/photos directly via email, Facebook, etc., and it can also connect to the accompanying smartphone and tablet app (GoPro 2015).

65 of our respondents were male (52.42 percent) and 59 were female (47.58 percent). The average age was 27.04 years (standard deviation: 9.02). 1 respondent was unemployed (0.8 percent), 7 were apprentices (5.6 percent), 9 were pupils (7.3 percent), 47 were currently employed (37.90 percent), 54 were students (43.55 percent), and 6 selected “other” as a description of themselves (4.84 percent).

4.2 Measurement

We adapted existing reflective scales to our context in order to measure Behavioral Intention to Use and Perceived Enjoyment. For Perceived Reputation Enhancement, we developed three of our own reflective items and consulted several researchers from our department throughout the development process. Table 1 presents the resulting reflective items with their corresponding sources. All items were measured using a seven-point Likert-type scale ranging from “strongly agree” to “strongly disagree”.


Construct Items (Labels) Source/Adapted from

Behavioral Intention to Use

I intend to use a GoPro2 in the next 6 months (BI1) Hu et al. (2011) Venkatesh, et al. (2003)

In the future, I am very likely to use a GoPro (BI2)

I predict that I will use a GoPro in the next 6 months (BI3)

Perceived Enjoyment

Using a GoPro is pleasant (PE1)

Davis et al. (1992) Using a GoPro is fun (PE2)

Using a GoPro is enjoyable (PE3)

Perceived Reputation Enhancement

By using a GoPro I can enhance my reputation (PRE1)

created by ourselves

Using a GoPro has a positive influence on my reputation (PRE2)

Using a GoPro helps me enhance my reputation (PRE3)

Table 1: Items of our Measurement Model

5 Results Since our data was not distributed joint multivariate normal (cf. Hair et al. 2011), we used the Partial-Least-Squares approach via SmartPLS 3.2.0 (Ringle et al. 2015). With 124 datasets, we met the suggested minimum sample size threshold of “ten times the largest number of structural paths directed at a particular latent construct in the structural model” (Hair et al. 2011, 144). To test for significance, we used the integrated Bootstrap routine with 5,000 samples (Hair et al. 2011).

In the following section, we will evaluate our measurement model. Indeed, we will examine the indicator reliability, the construct reliability, and the discriminant validity of our reflective constructs. Finally, we will present the results of our structural model.

5.1 Measurement Model

Tables 2 and 3 present the correlations between constructs along with the Average Variance Extracted (AVE) and Composite Reliability (CR), and our reflective items’ factor loadings, respectively: All items loaded high (.810 or more) and significant (p<.001) on their parent factor and, hence, met the suggested threshold of indicator reliability of .70 (Hair et al. 2011); AVE and CR were higher than .81 and .92, respectively, meeting the suggested construct reliability thresholds of .50/.70 (Hair et al. 2009). The loadings from our reflective indicators were highest for each parent factor and the square root of the AVE of each construct was larger than the absolute value of the construct’s correlations with its counterparts, thus indicating discriminant validity (Fornell and Larcker 1981; Hair et al. 2011).

2 We did not use the full name of the GoPro HERO4 Black or an abbreviation, but instead chose simply to refer to the camera as GoPro in both our introductory text and items.


BI PE PRE

Behavioral Intention to Use (BI) .909 (.968)

Perceived Enjoyment (PE) .413 .811 (.928)

Perceived Reputation Enhancement (PRE) .349 .429 .838 (.939)

Table 2: Correlations between Constructs [AVE (CR) on the Diagonal]

BI PE PRE

BI1 .954 (74.742) .352 .347

BI2 .963 (106.866) .398 .319

BI3 .942 (47.906) .427 .333

PE1 .178 .826 (14.621) .301

PE2 .428 .931 (51.672) .377

PE3 .438 .940 (83.730) .451

PRE1 .243 .320 .810 (16.405)

PRE2 .369 .446 .964 (103.234)

PRE3 .331 .398 .964 (95.177)

Table 3: Reflective Items Loadings (T-Values)

5.2 Structure Model

Figure 2 presents the path coefficients of the previously hypothesized relationships as well as the R2s of both endogenous variables (* = p<.05; *** = p<.001; ns = non-significant).

Figure 2: Findings

Perceived Enjoyment was found to have a significant positive influence on Behavioral Intention to Use (β=.323, p<.001), confirming hypothesis 1. Also, Perceived Reputation Enhancement was found to have a positive influence on both Behavioral Intention to Use (β=.211, p<.05) and Perceived Enjoyment (β=.429, p<.001), confirming hypotheses 2 and 3, respectively.

Our research model included two predecessors of Behavioral Intention to Use (Perceived Enjoyment and Perceived Reputation Enhancement), and one predecessor of Perceived Enjoyment (Perceived Reputation Enhancement). By taking this into account, the explanatory power of our structural model is good, since it explains 20.7 percent of the variances of Behavioral Intention to Use as well as 18.4 percent of the variances of Perceived Enjoyment.


6 Conclusion In this article, we evaluated the potential influence of Perceived Reputation Enhancement on wearable action camera usage. After collecting 124 completed online questionnaires about one specific wearable action camera, GoPro HERO4 Black, and applying a structural equation modeling approach, our findings indicate that wearable action cameras are at least partly hedonic technologies whose usage is influenced by Perceived Enjoyment. Furthermore, Perceived Reputation Enhancement had a significant direct positive influence on the Behavioral Intention to Use the wearable action camera as well as an indirect positive influence on the Behavioral Intention to Use it through Perceived Enjoyment.

Our findings have important practical implications. Indeed, they suggest that wearable action camera manufacturers need to emphasize the hedonic benefits of their devices as well as to promote their capacity for enhancing their users’ reputation. For example, manufacturers could ask well-known and respected athletes from different disciplines to represent their brand by using their wearable action cameras during their sports activities, in order to convince potential customers that using these devices is directly linked to acquiring a respectable reputation.

Our study has some limitations. First, our empirical findings are based on only one specific wearable action camera: GoPro HERO4 Black. Hence, the results found for this particular wearable action camera might be very different in studies that use other action cameras. Moreover, since we only surveyed German-speaking people, our results might not hold true for non-German speakers. In addition, our sample individuals were relatively young (mean: 27.04 years; standard deviation: 9.02). Hence, differences might be found for other age groups. Finally, our survey was only conducted online and, hence, excluded people that do not use the Internet (which could also explain the lack of older people in our sample).

As a next step, we plan to expand our research and address its limitations. More specifically, we want to rollout our survey to a greater number of countries around the world and with a variety of wearable action cameras in order to evaluate for potential differences between countries and devices. Also, we plan to identify and empirically evaluate additional influence factors of wearable action camera usage. For example, Perceived Health Risk could potentially be an important influence factor of wearable action camera usage. Indeed, a number of media reports have described potential injuries linked to the usage of wearable action cameras (e.g., Hu 2014). As a result, users might believe that the usage of wearable action cameras is associated with increased health risks. Hence, we want to take a closer look at the impact of perceived health risks on wearable action camera usage.

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