The Moderating Roles of Gender and Age in Tablet Computer Adoption

Abstract

This study aims to examine the relationship between perceived usefulness, ease of use, and enjoyment and attitude toward tablet computers, and between social influence and use intentions for such devices, as moderated by gender and age. Results from a partial least squares analysis using a sample of 482 consumers in South Korea showed that perceived usefulness and enjoyment have a positive effect on attitude toward tablets, while social influence and attitude toward tablet computers have a positive influence on intention to use tablets. Furthermore, gender and age moderated the relationship between perceived ease of use and attitude toward tablets.

Introduction

In the past few years, the tablet PC (tablet) has become a core computing device because of its mobility, computing power, and convenience.¹ Past research on the tablet has mainly focused on its adoption and effectiveness in a variety of fields, including the industrial and education markets.² However, despite the rapid sales growth and market expansion of this device, marked by the launch of the iPad in 2010, little research has been performed regarding consumers' behavioral intentions and related variables. Thus, it is worthwhile examining the significant factors influencing the adoption and diffusion of tablets, especially those of new models that have been released since the launch of the iPad (e.g., Kindle, Galaxy Tab), from a marketing perspective. Because of the limited research, the benefits and qualities consumers seek in tablets are still unclear. Since demographic segmentation of consumer markets is one of the common segmentation strategies for tapping into a potential market, many studies^3–5 have examined the effect of demographic factors such as age and gender on new technology adoption. These studies, however, showed different results. For example, men and women perceive and use information technology in different ways. Specifically, while men tend to use the tablet as office equipment for corporate communication, women use it for information and entertainment due to its visual and tactile appeal.⁶ Owing to the limitations of the current body of research, it is necessary to examine how the various technology benefits and marketing activities regarding a new technology such as tablets influence different genders and age groups.

This study explored the different factors that affect a consumer's intention to use a tablet adopting the Technology Acceptance Model (TAM). Since one of the benefits of using tablets is content consumption, we considered perceived enjoyment as an additional factor in the TAM. We also demonstrated the impact of attitude toward using tablets and the influence of perceived peer norms on consumers' use intentions based on the theory of reasoned action (TRA).⁷ In particular, we examined the moderating role of gender and age in the relationship between technology acceptance factors and attitude, as well as that between social influence and use intentions, by adopting two sociological constructs: (a) gender schema theory⁸ and (b) socio-emotional selectively theory (SST).^9,10 The results provide implications for management strategies for new technology devices based on gender and age and for the IT and telecommunication service industries.

Theoretical Background

Technology acceptance factors

In the past few decades, the TAM has become a well-established model for explaining consumers' usage of new technologies. According to the TAM, perceived usefulness and perceived ease of use determine an individual's attitude toward using a new system.^11,12 A considerable number of studies have tested the TAM within various contexts such as e-mails,¹³ e-shopping,¹⁴ mobile commerce,¹⁵ and Lotus Notes.¹⁶ In addition, some studies have explored additional factors other than the TAM's original two variables. Vijayasarathy¹⁷ demonstrated that the variables in the TAM may not sufficiently capture situations involving users' voluntary choices. When people voluntarily engage in a certain behavior, intrinsic motivations—such as pleasure and satisfaction derived from the behavior—may function as extrinsic motivation.¹⁸ Davis et al.¹⁹ also extended the original TAM by considering perceived enjoyment as an additional variable in technology usage. Teo²⁰ showed that perceived enjoyment has an influence on the usage of the Internet. Because the tablet features mobile multimedia services including mobile Internet, perceived enjoyment is expected to influence attitude toward tablets. Therefore, we hypothesize the following:

H1a: Perceived usefulness increases a consumer's attitude toward tablet PCs.

H1b: Perceived ease of use increases a consumer's attitude toward tablet PCs.

H1c: Perceived enjoyment increases a consumer's attitude toward tablet PCs.

Attitude and social influence

According to TRA, two factors influence an individual's behavioral intention to use a system: the individual's attitude and his perception of social pressure (subjective norm). In the context of the model's belief–attitude–intention causal relationship, an individual's attitude is influenced by one's behavioral beliefs about the expected outcomes of using a new system, which, in turn, impacts one's behavior intentions. Meanwhile, social influences derived from subjective norms refer to a person's perception that others expect an individual to use the system.²¹ People's intention to comply with a social actor, who has the ability to reward or punish in mandatory settings, drives the use of a new system. On the other hand, social influence is also driven by people's identification with or internalization of other's opinions on using the system.²² In addition, men and women are subject to different social norms, and they also differ in their susceptibility to social influence because they often form social relationships in different ways.²³ Luarn and Lin²⁴ found that social norms impact the intention to use new mobile services, which comes from the influence of reference groups.¹⁸ Thus, in this study, we hypothesize that social norms regarding the use of tablets will have a significant effect on behavior intentions:

H1d: Attitude increases behavior intention for tablet PCs.

H1e: Social influence increases behavior intention for tablet PCs.

Moderating effects of gender

Gender differences in technology acceptance have been found to be a fundamental sociocultural factor that influences people's perception or attitude.³ Ong and Lai²⁵ showed that men rate perceived ease of use more highly than women in using an e-learning system due to high computer self-efficacy, whereas Venkatesh and Morris²⁶ found that women place greater emphasis on perceived ease of use than men. In addition, perceived enjoyment is considered to be a stronger determinant in technology acceptance for female users than for male users because women are more intrinsically motivated than men in technology adoption.²⁷

In the gender schema theory,⁸ social influences are more significant for females than males because they tend to pay more attention to norms. For example, because female patterns are likely to be network oriented, they tend to be more influenced by peer groups.²⁸ Although several studies^29,30 have shown that gender difference is diminishing in technology acceptance such as in Internet technology applications and mobile commerce, the moderating effect of gender still exists in the use of new systems.³¹ Consequently, we propose that:

H2a: The relationship between perceived usefulness and attitude is moderated by gender.

H2b: The relationship between perceived ease of use and attitude is moderated by gender.

H2c: The relationship between perceived enjoyment and attitude is moderated by gender.

H2d: The relationship between social influence and behavior intention is moderated by gender.

Moderating effects of age

There has been little research on the TAM with respect to age differences.³² The SST is one of the most influential theories of life-span development in recent aging research.¹⁰ According to the SST, positive emotional experiences become more salient to people as they become older because they realize that their life-span is not infinite. Driven by the interest to derive the most pleasure from their remaining time, people, as they age, become increasingly motivated to maximize their experiences of positive emotions and to minimize their experiences of negative emotions.¹⁰ In the context of new technology adoption, older adults demand pleasure, novelty, and high self-efficacy when using a new system while avoiding inconvenience and low self-efficacy. Thus, older people tend to perceive more usability issues in new technologies, even when the level of computer or Internet experience is controlled for.³³ Meanwhile, perceived usefulness of a new technology is also likely to influence technology acceptance to a greater extent for younger people.^32,34 Younger users also rate perceived enjoyment more highly than older users because they engage in more activities involving tablets, and their perceived enjoyment is significantly related to those activities.³⁵ In this study, we also expect age to moderate the relationship between social influence and the use of new technologies because younger people socialize more and are more susceptible to the influence of reference groups.³⁶ Therefore, we hypothesize the following:

H3a: The relationship between perceived usefulness and attitude is moderated by age.

H3b: The relationship between perceived ease of use and attitude is moderated by age.

H3c: The relationship between perceived enjoyment and attitude is moderated by age.

H3d: The relationship between social influence and behavior intention is moderated by age.

FIG. 1.

Research model.

Method

Measures

Our survey scales were constructed based on established measurements of constructs from prior research, which were adapted for the context of our proposed model. The variables of the study were measured with multiple 5-point Likert-type items from a published scale and adapted for this context (see Table 1). Four items for measuring perceived usefulness (PU) and three items for measuring perceived ease of use (PEU) were adapted from Davis et al.¹² and Kim et al.³⁷ Perceived enjoyment (PE) was measured using four items adapted from Ha and Stoel¹⁴ and Kim et al.³⁷ To assess social influence (SI), three items based on Kulviwat et al.³⁸ were used. Meanwhile, the behavior intention (BI) was based on Davis et al,¹² and Kulviwat et al.³⁸

Table 1.

Constructs and Their Measurements

Construct	Measurement items	λ	α	CR	AVE
Perceived usefulness^a	Using a tablet computer enables me to accomplish my work/learning/life tasks more quickly.	0.92	0.94	0.96	0.84
	Using a tablet computer would improve my work/learning/life performance.	0.91
	Using a tablet computer would enhance my work/learning/life effectiveness.	0.92
	Using a tablet computer would increase my work/learning/life productivity.	0.92
Perceived ease of use^a	Tablet computers are easy to use.	0.86	0.86	0.91	0.78
	Learning to operate a tablet computer is easy.	0.88
	Overall, I believe tablet computers are easy to use.	0.90
Perceived enjoyment^*	I take pleasure in using tablet computers.	0.94	0.95	0.97	0.91
	The process of using tablet computers is enjoyable.	0.96
	I have fun using tablet computers.	0.96
Social influence^a	People important to me think I should use a tablet computer.	0.88	0.84	0.90	0.76
	People like me are expected to use tablet computers.	0.84
	People I look up to expect me to use a tablet computer.	0.90
Attitude	Overall, how would you describe your experience in using tablet computers? For me, using the tablet computer is:
	Negative/positive (1=“negative”; 5=“positive”)	0.95	0.93	0.96	0.88
	Unfavorable/favorable (1=“unfavorable”; 5=“favorable”)	0.93
	Unpleasant/pleasant (1=“unpleasant”; 5=“pleasant”)	0.93
Behavioral intention	Assuming you have access to such a tablet computer in the future, what is the probability that you would use it?
	Unlikely/likely (1=“unlikely”; 5=“likely”)	0.93	0.92	0.95	0.86
	Improbable/probable (1=“improbable”; 5=“probable”)	0.94
	Impossible/possible (1=“impossible”; 5=“possible”)	0.92

Note. ^aLikert-type items anchored by 1=“strongly disagree” to 5=“strongly agree.” ^*p<0.01.

CR, composite reliability; AVE, average variance extracted.

Sample

Data for this study were collected using an online survey administered to an online consumer panel. The respondents were identified from a randomly chosen database from a marketing research company, which has an online consumer panel of more than 800,000 people in South Korea. An e-mail was randomly sent to 2,000 people between the ages of 20 and 55 years, and those who with knowledge of tablet PCs were eligible to participate in the survey. The positions of blocks of thematically related questions were randomly rotated to avoid order effects. In total, 482 questionnaires were collected in August 2011. A preliminary analysis revealed that 50.1% of the subjects were male, with an average age of 37.3 years (SD=5.17). A majority of the participants (nearly 59%) were university educated, 20.4% were college educated, and 20.6% had a high school education.

Results

We use latent constructs with multiple measurement items to explain the drivers of attitude toward and behavior intention for tablets. As noted by Hair et al.,³⁹ when estimating such models, researchers need to take into account simultaneously both the measurement and structural components used in marketing⁴⁰ and the information system^41,42 to estimate the factor loadings of the measurement model and path coefficients of the structural model. Compared to the traditional covariance-based structural equation modeling (SEM), partial least squares (PLS) tend to have higher statistical power under equal conditions.⁴³ Therefore, we performed the data analysis in this study using PLS rather than other SEM methods.

Test of measurement model

The reliability test, which examines the internal consistency within a construct, was performed using Cronbach's alpha and composite reliability (CR). As shown in Table 1, all constructs show a value above the threshold (0.7 for both Cronbach's α and CR, adopted by Bagozzi and Yi⁴⁴). To test convergent validity, CR, factor loading, and average variance extracted (AVE) were examined. Table 1 presents the individual items' factor loading, weight, CR, and AVE. All loadings for constructs exceed 0.7 and are significant at the bootstrap t statistics (α=0.01) while satisfying the CR and AVE criteria.⁴⁵

Discriminant validity was tested by comparing the AVE of each construct with the shared variance between the constructs (see Table 2). For each construct, the AVE's squared root exceeds its shared variance with other constructs. Table 2 reveals that all the constructs in this study fulfill discriminant validity.

Table 2.

Construct Means, Standard Deviations, and Correlations

	Perceived usefulness	Perceived ease of use	Perceived enjoyment	Social influence	Attitude	Behavioral intentions
Perceived usefulness	0.84
Perceived ease of use	0.61	0.78
Perceived enjoyment	0.79	0.65	0.91
Social influence	0.73	0.56	0.69	0.76
Attitude	0.84	0.55	0.72	0.78	0.88
Behavioral intentions	0.73	0.52	0.66	0.75	0.76	0.86
Mean	3.32	3.23	3.37	3.03	3.11	2.83
SD	0.86	0.81	0.89	0.92	0.91	0.86

Note. Bold italic figures indicate AVEs.

Test of structural model

All the parameter estimates are shown in Table 3. Overall, the hypothesized structural model explains the variance very well. First, support for H1a and H1c were provided by the significant positive relationship found between PU and attitude (β=0.70, p<0.01) and between PE and attitude (β=0.17, p<0.01). Second, H1b was not supported, as indicated by the insignificant effect of PEU on attitude (β=0.01, p>0.05). Third, H1d and H1e were supported, as shown by the positive association between SI and attitude (β=0.49, p<0.01) and between attitude and BI (β=0.44, p<0.01).

Table 3.

Results for Main Effects

	Path	β	R²
H1a	Perceived usefulness→Attitude toward tablet computers	0.70^**	0.71
H1b	Perceived ease of use→Attitude toward tablet computers	0.01^**
H1c	Perceived enjoyment→Attitude toward tablet computers	0.17^**
H1d	Social influence→Behavioral intention	0.49^**	0.64
H1e	Attitude toward tablet computers→Behavioral intention	0.44^**

Note. ^**p<0.01.

Table 4 presents the results for the second set of hypotheses, which examines the moderating effects of gender on the relationship between PU (H2a), PEU (H2b), and PE (H2c), and attitude toward tablets, and that between SI and BI (H2d). In H2a, we found that PU had a positive effect on attitude for both males (β=0.72, p<0.01) and females (β=0.66, p<0.01). In addition, the difference between the structural loading linking PU to attitude in males and females was smaller than the critical threshold (t=0.54, p>0.05). Therefore, H2a was rejected. In H2b and H2c, we found that PEU had a positive effect on females (β=−0.05, p>0.05; β=0.11, p<0.1), while PE had a greater positive effect on males (β=0.21, p<0.01; β=0.11, p>0.05). Since the critical ratio for the difference was smaller than the critical threshold of 1.96, H2b and H2c were rejected. In H2d, we found that SI affects behavior intention in both males (β=0.49, p<0.01) and females (β=0.34, p<0.01). In addition, the effect of SI was stronger in males than in females (critical ratio for difference=1.69, p<0.1), thereby contradicting H2d.

Table 4.

Results for Moderating Effects

Path	Male (n=242)	Female (n=240)	t Test	Younger (n=241)	Older (n=241)	t Test
PU→ATT	0.72^**	0.66^**	0.54	0.76^**	0.60^**	1.99^**
PEU→ATT	−0.05	0.11^*	1.99^*	−0.06	0.10^**	2.78^**
PE→ATT	0.21^**	0.11	0.93	0.16^*	0.21^**	0.56
SI→BI	0.49^**	0.34^**	1.69^*	0.34^**	0.49^**	1.32

Note. ^*p<0.05; ^**p<0.01.

PU, perceived usefulness; PEU, perceived ease of use; PE, perceived enjoyment; SI, social influence; ATT, attitude toward tablet computer; BI, behavioral intention.

Table 4 presents the results for the third set of hypotheses, which examines the moderating effects of age on the relationship between perceived usefulness (H3a), PEU (H3b), and PE (H3c), and attitude toward tablets, and that between SI and BI (H3d). In H3a, we found that PU had a positive effect on attitude in both young consumers (β=0.76, p<0.01) and old consumers (β=0.60, p<0.01). In addition, the difference between the structural loading linking PU to attitude in both groups was larger than the critical threshold (t=1.99, p<0.05). Therefore, H3a is supported. In H3b, we found that PEU had a positive effect on attitude in old consumers (β=0.10, p<0.01) but an insignificant effect in young consumers (β=−0.06, p>0.05). The difference between the structural loading linking PU to attitude in young consumers and old consumers was greater than the critical threshold (t=2.78, p<0.05). Therefore, we concluded that H3b was supported. In H3c, we found that PEU had a positive effect on attitude in young consumers (β=0.16, p<0.01) and old consumers (β=0.21, p<0.01). The difference between the structural loading linking PE to attitude in young consumers and older consumers was smaller than the critical threshold (t=0.56, p>0.05). Therefore, H3c is rejected. Finally, in H3d, we found that SI has a positive effect on BI in young consumers (β=0.34, p<0.01) and old consumers (β=0.49, p<0.01). Since the critical ratio for the difference was smaller than the critical threshold of 1.96 (t=1.32, p>0.05), H3d is rejected.

Conclusion

Implications for research and practice

This study contributed to the conceptual and empirical research on tablet adoption by examining the moderating roles of gender and age. Our findings have several important implications for both researchers and practitioners.

First, the relationship between PEU and attitude is moderated by gender and age. Specifically, this study shows that PEU significantly influences attitude toward tablets in females and older consumers. As previous studies^26,33 have suggested, this may be because these segments generally require more effort to learn new technologies than males and younger consumers do. Thus, product managers and marketers should promote user-friendly interfaces and convenience for these consumers.

Second, in contrast to the gender schema theory,⁸ this study found that the effect of SI was stronger in males than in females. Generally, women are considered to be more influenced by reference groups than men are. However, our results suggest the opposite—that men are more affected by social influence than women are in tablet adoption. This finding may stem from product characteristics of the tablet, which is still at the introduction stage of the product life cycle. Men tend to adopt new devices earlier than women do.⁴⁶ Moreover, they use the tablet for a wider range of activities including office work and more for social media than women,⁶ and thus men tend to value collective attachment to peer groups more than women do.²⁴ Thus, our findings indicate that male consumers pay more attention to the social norms and have a strong desire for social approval when it comes to tablet adoption. Finally, this study found that the effect of PU was stronger in younger consumers than in older consumers, while that of PE was stronger in older consumers than in younger consumers. The findings provide strong empirical support for the SST, which suggest that younger people are strongly motivated to pursue useful information. That is, they desire to expand their horizons and knowledge for cognitive tasks in using a tablet, since they perceive time as being open-ended.⁹ On the contrary, older adults are usually motivated to pursue entertainment by deriving the emotional satisfaction from their constrained time. Thus, the findings suggest that since current tablets have contents and features targeted more at younger consumers, marketers need to pay additional attention to older users by considering their psychological and physical traits when developing various contents and features for them.

Limitations and future research

Although our study has crucial implications for the moderating effects of gender and age on new product adoption, we acknowledge that it has limitations, which can be addressed in future research. First, our sample consists of consumers in South Korea only. Therefore, future studies could overcome generalization issues by including more samples from different regions. Second, this study used a survey-based research design. Thus, future research should employ experimental designs to obtain more internally valid tests of the associations in the model. For example, experimental studies could control the contents people consume or alternative devices they use, since the specific content or the compatibility with other technology may affect the perception and usage of tablets. Third, this study is based on data obtained at a specific moment in time. Because longitudinal studies could fill the gap between intentions and actual usage, future work should analyze how the TAM components and other socio-demographic variables affect actual purchase and usage over time.

Footnotes

Acknowledgment

This research was supported by Pukyong National University Research Fund in 2012 (PK-2012-32).

Author Disclosure Statement

No competing financial interests exist.

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