PLAYING MOBILE GAMES: CONSUMER PERCEPTIONS

AN EMPIRICAL STUDY

Krassie Petrova.and Haixia Qu

Auckland Unoversoty of Technology, School of Computing and Mathematical Sciences

Keywords: Mobile gaming, mobile commerce, mobile business, survey, adoption, New Zealand.

Abstract: The paper presents the design and the results of a project studying the adoption of mobile gaming (playing

mobile games) in the New Zealand youth market. An adoption model extending TAM (Technology

Adoption Model) was used, with intention to use as the dependent variable. Data were gathered from a

sample group consisting of undergraduate university students. It was found that adopters of mobile gaming

were likely to be male as well as female, and also that the group surveyed exhibited a behaviour towards

relatively high spending on mobile entertainment (in proportion to income). Perceived expressiveness was

found to be the most significant influential factor affecting intention to use, while perceived enjoyment was

found to be motivated by perceived ease of use. Recommendations regarding developing and offering

mobile games are also included.

1 INTRODUCTION

It has been suggested in the literature that mobile

gaming is a mobile service which will become a

significant revenues stream builder for mobile

business (Anckar & D’Incau 2002; Kleijnen, de

Ruyter & Wetzels 2003; Shchiglik et al. 2004).

Supporting this market research forecasts predict that

worldwide mobile gaming revenues will “increase

six-fold within the next four to five years (Armitt

2005). According to Paavilainen (2003, p. 94) the

expected adopters of mobile gaming are young

people who already use regularly mobile devices.

Based on the potential of this market segment, the

compound annual growth rate of mobile gaming

revenue worldwide is predicted to fall anywhere

between 31% and 50% in 2008 (Wisniewski &

Morton 2005). In New Zealand, where the cellular

market is expected to increase from NZ$1.4 billion

in 2003 to NZ$2.0 billion in 2008 and the number of

subscribers to grow from 2.8 to 3.5 million

respectively (Buckley 2004), it may be expected that

the mobile gaming market will also show growth.

Mobile gaming falls into the broader category of

interactive mobile entertainment (Moore & Rutter

2004). A number of potential drivers of the adoption

process of mobile entertainment services have been

identified in prior research (Baldi & Thaung 2002;

Pedersen, Methlie & Thorbljornsen 2002; Barnes &

Huff 2003; Pagani & Schipani 2003; Moore & Rutter

2004; Carlsson et al. 2005; Pedersen 2005). A point

had been made in several studies that the socio-

cultural and economic contexts have been a

significant factor in the development of mobile

gaming markets in countries such as Japan and Korea

where customers had been predisposed to adopt and

use both small and mobile electronic accessories as a

result of the leading edge electronic industry cultures

(Barnes & Huff 2003; Dhaliwal 2003; Wisniewski &

Morton 2005).

The study presented here aims to contribute to the

understanding the preferences and perceptions of the

young people in New Zealand about mobile gaming,

and whether there are any specific factors or

motivators related to the its adoption.

The paper is organized as follows: The next

section defines mobile gaming. Section three

introduces the initial research model. Section four

presents a summary of the survey results and

discusses some of the most important findings. In the

last section the study limitations are identified and

directions for further research are suggested.

209

Petrova K. and Qu H. (2007).

PLAYING MOBILE GAMES: CONSUMER PERCEPTIONS AN EMPIRICAL STUDY.

In Proceedings of the Second International Conference on e-Business, pages 209-214

DOI: 10.5220/0002115202090214

 SciTePress

2 MOBILE GAMING

Mobile gaming is an example of a mobile commerce

(mCommerce) application which is provided through

a paid for service. Typically the mobile network

operator to whose network the player subscribes

collects the revenue; the revenue stream may be also

shared with other business entities involved – such as

mobile network infrastructure providers, mobile

content developers and publishers, portal

aggregators, and retailers (Petrova & Qu 2006).

There is a variety of mobile game types

depending on the level of complexity and on the

device platform used - from Short Message Service

(SMS)-based games to real-time games involving

multiple players which are played on sophisticated

smart phones. Some more advanced games might

require a persistent network connection and a

dedicated game server, and might have location

sensitive features (Moore & Rutter 2004; Maintland

et al, 2005).

Three currently prevalent mobile gaming

deployment scenarios are currently prevalent. Their

industry positioning is shown in Figure 1, adapted

from Wong and Hiew (2005).

Figure 1: Mobile gaming positioning. Adapted from Wong

and Hiew (2005).

In Segment 1, gamers play real-time 2D or 3D

games on a 3G mobile phone and interact with

groups of gamers via network carriers. Revenue is

collected by the mobile services provider (for

downloading a game) and by network carriers (for

transferring data). The segment covers multiplayer

games, including also WAP (Wireless Application

Protocol)- and SMS- based games.

In Segment 2 gamers play without connecting to

a carrier network – rather they create a private ad hoc

Bluetooth network or play individually. They pay

once only – for downloading the game.

In Segment 3 (which lies entirely outside both the

wireless environment and mCommerce), games still

are played on mobile devices, but these need not be

connected to a network as the games are embedded

in the devices at the time of manufacturing (Ollila et

al. 2003). Subsequently there is no usage cost and no

direct financial benefit to other business entities

except to manufacturers and device vendors.

3 RESEARCH MODEL

Mobile gaming may involve both monetary and non-

monetary transactions across the mCommerce value

chain model (Barnes 2003). A number of value chain

actors (network operators, game designers and

distributors, mobile service providers) are involved

in providing a mobile gaming service; studying

consumer (user) readiness to accept such a service

may help identify potential market segments and

provide useful insights into factors motivating

consumers’ acceptance. Information systems and

technology acceptance models (e.g. Davies 1989;

Venkatesh 2003) have been adapted and used in a

number of studies of mobile business services

adoption (Aarnio et al., 2002; Hung, Ku & Chang

2003; Pagani & Schipani 2003; Nysveen, Pedersen &

Thornbjornsen 2005; Yang 2005; Wu & Wang

2005), in empirical studies on mobile gaming

adoption (Kleijnen, de Ruyter & Wetzels 2003;

Yoon, Ha, & Choi 2005) and in studies on online

gaming (Hsu & Lu 2004).

The constructs of the Technology Acceptance

Model (TAM) and of its extensions found in the

reviewed literature on mobile services and

specifically on mobile gaming were identified and

used to build a research model and to formulate the

hypotheses of the study. The research model of the

study is shown in Figure 2. “Intention to use’ (IU) is

a dependent variable; ‘actual use’ (a dependent

variable in TAM), was dropped from the model

based on results which confirm the positive

relationship between intention to use and actual use

(Bhattacherjee 2000; Wu & Wang 2005). A similar

approach was followed in other related research

(Pagani & Schipani 2003; Nysveen, Pedersen &

Thornbjornsen 2005).

3.1 Perceived Usefulness and Perceived

Ease of Use

Mobile gaming is an activity well suited to ‘filling

gaps’ in time when travelling or waiting (Anchar &

D’Incau 2002); therefore it may be perceived as a

useful value added service. Mobile device or context

limitations (small screen, playing a game in a public

place) may also be of significance.

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210

H1: Perceived usefulness (PU) has a positive

effect on IU.

H2: Perceived ease of use (PEOU) has a positive

effect on IU.

Figure 2: Proposed research model.

3.2 Perceived Enjoyment

As mobile gaming is a leisure-oriented service it may

be expected that the enjoyment and fun-seeking

aspects will be important. A positive relationship

between ‘computer playfulness’ and ‘perceived ease

of use’ was found in Venkatesh (2000). While a

challenging game evoke positive feelings, a game

which is technically difficult to play may be

perceived as not enjoyable (Moore & Rutter 2004).

H3: Perceived enjoyment (PE) has a positive

effect on IU.

H3a: PEOU has a positive effect on PE.

3.3 Attitude

Attitude was dropped in the extended TAM proposed

by Venkatesh and Davies (2000). As prior research

of mobile services adoption indicates that

consumers’ attitude may influence intention to use

(Hung, Ku & Chang 2003; Nysveen, Pedersen &

Thorbjornsen 2005; Yoon, Ha & Choi, 2005), the

construct was included.

H4: Attitude (AT) has a positive effect on IU.

H4a: AT has a positive mediating effect between

PU and IU.

H4b: AT has a positive mediating effect between

PEOU and IU.

3.4 Perceived Critical Mass

This construct refers to the notion that consumers

may use a service because other people around them

are using it (i.e. people would follow others’

behaviour). A positive relationship between critical

mass and intention to use was reported in a wireless

services context (Kleijnen, de Ruyter & Wetzels

2003) and in online gaming (Hsu & Lu 2004)..

H5: Perceived critical mass (PCM) has a positive

effect on IU.

3.5 Subjective Norm

This construct refers to the notion that an

individual’s perceptions depend on a reference

group’s opinion as playing a mobile game may give

a sense of commonness, leading to being ‘approved’

by the members of the reference group (Kleijnen, de

Ruyter & Wetzels 2003). Similar constructs have

been used in (Hsu & Lu 2003; Nysveen, Pedersen &

Thornbjornsen 2005).

H6: Subjective norm (SN) has a positive effect

on IU.

3.6 Behavioural Control

Behavioural control includes external factors related

to the quality of the service and the revenue model of

the supplier. Adoption of mCommerce may be

constrained by perceived security and privacy risks,

and by service cost (Kleijnen, de Ruyter & Wetzels

2004; Wu & Wang 2005).

H7: Behavioural control (BC) factors (security

and cost) have a negative effect on IU.

3.7 Perceived Expressiveness

A mobile phone and the related services contribute to

the owner’s identity, status and public image (Baldi

& Thaung 2003; Barnes & Huff 2003; Funk, 2004,

p.27). The effect of ‘perceived expressiveness’ is

stronger in the mobile gaming context compared to

other mobile services (Nysveen, Pedersen &

Thornbjornsen 2005).

H8: Perceived expressiveness (EX) has a positive

effect on IU.

4 SURVEY AND RESULTS

A form of purposive sampling known as ‘judgment

sampling’ (Sekaran, 2003, p. 277) was used and a

PLAYING MOBILE GAMES: CONSUMER PERCEPTIONS

211

sample of university students was selected. It

included both New Zealand and international

students. The survey instrument was based on items

used in the reviewed literature. The anonymous

questionnaire contained between 3 and 6 questions

per construct, with answers to be provided on a

Likert scale from 1 (strongly disagree) to 5 (strongly

agree). The questionnaire was structured into three

parts, with all respondents answering the general

questions in the first part. Part 2 (29 questions) and

part 3 (15 questions) were aimed at respondents who

were actual users (‘mobile gamers’) or were ‘non-

mobile gamers’, respectively.

The sample consisted of 96 respondents, with

44.8% males, 54.2% females, and one not specified.

The majority (96.9%) were young adults between 15

and 35 years of age. They fitted well with the mobile

generation group (Aarnio et al. 2002; Paavilainen,

2003, p. 93; Shchiglik et al. 2004; Pedersen 2005;

Wong & Hiew 2005).

The sample data showed that mobile phone

penetration had reached a saturation point: Only one

respondent did not have a mobile phone. Most

respondents (80.1%) owned a less than two years old

device. A very small number of respondents (less

than 10%) had a 3G cell phone. A significant number

of the respondents (72.9%) owned a model with a

colour display but only 75.2% of them were mobile

gamers. However owing a relatively high-end mobile

device as a pre-condition to engaging in mobile

gaming was met by the sample: 57.3% of the

respondents had WAP-enabled devices and 45.7%

had Java-enabled devices. Significantly, respondents

ranked mobile entertainment as one of the top mobile

services available –second after SMS.

A relatively low ‘mobile phone expenditure’

group dominates the sample (with average monthly

expenditure less than NZ$60). This is consistent with

the high proportion of prepaid customers in New

Zealand reported by Buckley (2004) and may

indicate that in New Zealand, those who spend more

are likely to be using the technology for business

rather than for personal use.

In-phone games dominated the actual users

segment (51.09%), followed by downloadable games

(27.17%) . This result aligns with reported results

(Schiglick et al. 2004; Wisniewski & Morton 2005).

The mobile gamer sub-sample consisted of both

female and male consumers (55.7% and 44.3%

respectively). The possibility of an association

between ‘gender’ and ‘playing’ in the sample was

tested and rejected (Pearson’s Chi-Square .103 with a

significance level of .749), meaning that both males

and females were likely to be mobile gaming

adopters.

A small number of respondents (5.7%, males

only) preferred strategy games and the same number

(females only) preferred card games. Action and

sports games were preferred by females and males

(12.9% and 21.4%) with more females than males

expressing the preference (the respective ratios were

2:1 and 3:2).

Consistent with the proposed research model

further analysis was performed on the mobile game

sub-sample only (70 respondents). The construct

validity of the instrument was evaluated by

computing convergent and discriminate validity

performing a principal component analysis with a

Varimax rotation. Seven factors (PE, PU, PEOU, SN,

BC, EX, IU) met the criteria used in the study (Hair

et al., 1998, p. 90, p.111). As a result un the revised

model two constructs (PCM and AT) were dropped.

Using SPSS12.0 a correlation bivariate procedure

was run including the factors retained in the revised

model. Using Pearson’s correlation (‘r’) as a measure

of strength it was found that IU had a significantly

strong relationship with SN (r=.264, sig. =.030),

PEOU (r=.339, sig.=.005), PE (r = .366, sig.=.002),

PU (r =.398, sig.=.001), and EX (r=.428, sig.=.000).

Figure 3: Survey results.

The correlation between PE and PEOU was

strong with r=.826 and sig.=.000.

The hypotheses were tested using regression

analysis in SPSS 12.0 and considered supported

when path coefficients (Beta) were significant at the

.05 and .01 levels of the p-value (Figure 3).

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Hypotheses H1, H2, H3, H3a, H6 and H8 were

supported while H7 was not. Hypotheses H4, H4a

H4b and H5 could not be tested.

5 DISCUSSION & CONCLUSION

The results indicated hat the target groups for mobile

gaming adoption among the ‘mobile generation’

include a high percentage of owners of relatively

advanced mobile phone devices, both female and

male, with different mobile game type preferences.

Current usage was found to be predominantly of

embedded games - not a significant revenue

generator.

As also suggested in Repo et al. (2006) mobile

service providers may take advantage of the high

level of ownership of devices with advanced

functions by offering and actively promoting services

to meet the preferences of ‘Segment 2’ consumers -

such as new and updated downloadable games which

are relatively cheap but are still revenue builders

(though not as profitable as interactive games). The

rate of adoption of mobile gaming services may

increase if consumers were made more

knowledgeable and aware about them, to capture low

‘mobile budget’ consumers willing to spend on

mobile entertainment. Mobile game developers and

distributors may explore the gender differences in the

youth market and develop games and game

distribution strategies differentiating between the

preferences of two gender segments.

‘Perceived expressiveness’ was found to be most

significant factor influencing adopter’s behaviour

and should be included as a construct in further

studies. ‘Perceived ease of use’ is a significant

motivator directly and indirectly through ‘perceived

enjoyment’. The relationship between these two

constructs needs to be studied in more depth. Cost

and security were not found to be significant factors

influencing adoption which may be context

dependent.

The study has a number of limitations: it was not

longitudinal and socio-economic factors were not

explored. Considering separately mobile gamers and

non-mobile gamers reduced the size of the sample

and imposed constraints on the subsequent factor

analysis; the initial research model had to be revised.

d testing of four of the initial eleven hypotheses

could not be tested.

ACKNOWLEDGEMENTS

The paper is based in part on an unpublished

Master’s dissertation (Qu, 2006). The authors would

like to thank the reviewers for the helpful critique.

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