Factors Influencing Consumer Impulsive Buying Behavior regarding Mobile Game Purchase Intention ^†

Abstract

We explored impulsive buying behavior regarding mobile games and the factors influencing it. Data were collected from 389 participants. The results presented differences between different types of impulse buying. The findings contribute to the future study of consumer behavior and provide implications for commercial providers.

1. Introduction

According to the report from the Groupe Speciale Mobile Association (GSMA), the number of smartphone users reached 4.3 billion in 2022, comprising 54% of the total population [1]. Since the majority of consumers use smartphones, applications (APPs) are launched, and more categories are created. With smartphones, we can browse the internet, send emails, or download apps anywhere [2]. Also, we can play mobile games and watch videos. Therefore, playing video games is one a usual leisure activity.

Mobile games refer to games played on mobile handheld devices such as smartphones and personal digital assistants (PDAs) with wireless communication capabilities [3]. Newzoo announced that the number of global mobile gamers increased to 3.3 billion in 2023, and the market size reached USD 9.26 billion [4]. The majority of game players are from the Asia–Pacific region, approximately 53% of the global market. According to statistics from Sensor Tower, Taiwan ranked fifth in the global mobile game consumer market in 2022 [5]. This shows the importance of Taiwan’s mobile game market in the global industry.

Research related to mobile games has been conducted on how mobile games can help college students relieve stress, release negative emotions, exchange ideas, meet social needs, improve academic achievements, etc., and help their physical and mental development through games. These are the positive impacts [6,7,8]. Chu indicated that college students are a high-risk group for mobile game addiction [9]. When mobile players spend more time playing, their degree of involvement will increase [10,11]. Also, mobile game use affects impulse buying [12]. Impulsive buying is a perceptual, strong, and urgent behavior that occurs when consumers suddenly feel emotionally excited and have a continued desire to buy [13]. On the other hand, previous studies have shown that when mobile players are highly involved, emotions are easily aroused [12,14]. Indeed, when mobile game players have more positive emotions while they play games, they usually engage in impulsive buying [15,16]. Emotion is a term related to the human body, a personal psychological state related to thoughts, feelings, and behaviors [17,18]. Therefore, involvement, emotion, and impulse buying behaviors are related to each other. The majority of college students play mobile games and are easily addicted. We explored impulsive buying behavior in mobile games, the degree of involvement, and positive emotions.

2. Methodology

The students from a university in Taiwan were selected as participants. To investigate the characteristics of the students, a stratified random sampling method was applied. In 2019, 11,317 students were enrolled at this university. Under the confidence level of 95% and the maximum error d = 0.05, the following equation was used to estimate the minimum sample size.

$$n={\displaystyle \frac{N}{N({\frac{2d}{Z_{\alpha /2}})}^2+1}}$$

(1)

The minimum sample size was determined to be 372. Thus, 400 questionnaires were collected from students at the university, and 389 valid responses were collected (97.3%).

3. Results and Discussions

3.1. Descriptive Statistics

Since the stratified random sampling method was adopted, the chi-square test (goodness-of-fit test) was conducted to examine whether the sampling structure was fit for the normal distribution. All variables were fit to the population parameters. Among the respondents, there were 100 freshmen (25.7%), 73 sophomores (18.7%), 127 juniors (32.7%), and 89 senior students (22.8%). In total, 146 of the respondents were male (37.6%) and 243 were female (62.4%), 136 students majored in management (35.0%), 54 students majored in science and engineering (13.8%), 61 students majored in design (15.6%), 82 students majored in humanities and social sciences (21.2%), and 56 students majored in informatics (14.3%). Regarding monthly disposable income, 25.83% students had an income of NTD 3001–6000, 24.04% earned NTD 6001–9000, 17.90% earned less than NTD 3000, 11.76% earned NTD 9001–12,000, 11.25% earned more than NTD 15,001, and 9.21% earned NTD 12,001–15,000. A total of 99.74% of the participants played mobile games, and 41.43% spent money on mobile games. To understand the behavior of the participants regarding mobile games, the questionnaire was divided into two parts: positive emotions and impulse buying. We used a Likert 5-point scale [19]. To reduce the dimensions of the questionnaire, factor analysis was used [20].

3.2. Factor Analysis

The KMO value of the degree of involvement was 0.569, and two main factors were extracted. Factor 1 was named “Time and Energy” [10,11]; Factor 2 was named “Interest” based on the definition of “involvement is the consumer’s perceived value of the product or purchase decision” [21] (

Table 1. Results of involvement.

Items	F1	F2	Factor Name
I spend a lot of time playing mobile games every week	0.781	0.136	Time and Energy
I spend a lot of time playing mobile games every time	0.644	0.071
Most of my leisure and entertainment are related to technology products, such as playing TV consoles, online games, etc.	0.607	0.052
I spend a lot of money on mobile games every month	0.263	0.770	Interest
I am fond of mobile games	0.303	0.709
KMO value	0.569

).

Table 2. Positive emotion.

Items	F1	F2	Factor Name
Spending in games makes me proud	0.826	0.084	Positive behavior
Spending in games makes me pleasantly surprised	0.789	0.136
Spending in games makes me calm	0.737	−0.009
Spending in games makes me glad	0.699	0.193
Playing this game puts me in a good mood	0.160	0.854	Positive feelings
I think this is a fun game	0.131	0.810
I feel very happy now	0.056	0.741
I think the story of this game is very interesting	0.059	0.713
KMO value	0.784

shows that the KMO value of positive emotion was 0.784. Two main factors were extracted, named “Positive Behavior” and “Positive Feelings”.

Table 3. Results of impulse buying.

Items	F1	F2	F3	Factor Name
I enjoy buying products on impulse	0.893	0.043	0.184	Glad type
I get a rush of pleasure when I buy something impulsively	0.925	0.119	0.109
When I buy on impulse, I find myself joyful, happy, and fanaticism	0.914	0.110	0.141
Sometimes I regret making impulsive buying	0.030	0.732	0.134	Conflict type
Sometimes I feel self-accusation for impulsively buying things	0.078	0.833	0.095
I experience some emotional conflict when making impulse buying	0.129	0.811	0.089
I experience mixed feelings of pleasure and guilt trip from impulse buying	0.254	0.782	0.031
I tend to spend the money I make as quickly as possible	0.187	0.053	0.835	Uncontrollable type
I buy things even if I can’t afford them	0.179	0.042	0.805
I often buy things I don’t need and by the time I know it, I have a little money left	0.030	0.211	0.756
KMO value	0.780

shows that the KMO value of impulse buying was 0.780. After rotating the axis, the component matrix extracts three factors. Factor 1 was named “Glad type”; Factor 2 was named “conflict type.” Since consumers who bought mobile games impulsively usually lacked thoughtfulness and made reckless buying decisions, Factor 3 was named “Uncontrollable”.

Pearson correlation coefficient analysis is used to explore the degree of linear correlation between factors [22].

Table 4. Correlation coefficients matrix of factors.

	Time and Energy	Interest	Positive Behavior	Positive Feelings	Glad Type	Conflict Type	Uncontrollable Type
Time and Energy	1
Interest	0.000	1
Positive behavior	0.320 *	−0.002	1
Positive feelings	0.172 *	0.149 *	0.000	1
Glad type	0.122 *	0.202 *	0.181 *	0.422 *	1
Conflict type	0.121 *	−0.090	0.089	−0.066	0.000	1
Uncontrollable type	0.023	0.233 *	−0.176 *	0.230 *	0.000	0.000	1

Note: * p < 0.05.

shows a highest positive correlation coefficient of 0.422 between positive feelings and the glad type, with a significant p-value of 0.05. The lowest positive correlation coefficient was between time and energy and the conflict type (0.121). A negative correlation was observed for positive behaviors and the uncontrollable type (−0.176). Most items were related to each other positively.

It was found that Taiwanese college students spent more time and energy playing mobile games. In addition to having higher positive consumption behaviors and feelings, they also had feelings such as high pleasure, regret, and self-blame when impulsive buying happened. When consumers spent more money on mobile games, they had higher positive feelings, emotions for impulse buying, and irrational consumption behaviors.

4. Conclusions

The degree of involvement, positive emotions, and impulse buying behavior of Taiwanese college student players regarding mobile games were closely related. The popularity of mobile games has advantages and disadvantages for college students. Although people improve their physical and mental development through mobile games, they have negative problems due to addiction, which affects impulsive buying and emotions. The players’ involvement in mobile games affected emotions and impulsive buying behavior, thus confirming the correlation between the three for Taiwanese college students’ use of mobile games.