Effects of Gamified Mobile Apps on Purchase Intentions and Word-of-Mouth Engagement: Implications for Sustainability Behavior

Abstract

In today’s competitive environment, stimulating and maintaining customer engagement through gamified apps seems essential for gaining a sustainable competitive advantage. Consequently, gamification in marketing apps has garnered increased attention from companies interested in exploring how gaming processes and experiences can be utilized to create more engaging digital platforms. The objective of this study is to examine how consumer experiences and satisfaction with mobile gaming apps influence their purchase intentions and propensity to participate in word-of-mouth (WOM) communication. A total of 351 study participants who have used gamified mobile apps completed an online survey. The study results indicate that user experience with the gamified mobile apps has a positive influence on consumers’ perceived value and satisfaction. Furthermore, perceived value and satisfaction mediate the relationships between gamified mobile app experience and marketing outcomes, specifically purchase intentions and WOM communication. The implications for sustainable behavior are also discussed.

1. Introduction

According to eMarketer, consumers spend approximately four hours and 15 min per day on mobile apps [1], with a growth rate of 2.5% year over year. Although this trend might have been influenced by the recent COVID-19 pandemic, experts predict that elevated levels of consumer time spent on mobile gaming apps will persist in the future. Kartajaya, Setiawan, & Kotler (2021) [2] conceptualized Marketing 5.0 as the utilization of applications that emulate human behavior to create, explain, present, and enhance value throughout the customer journey. This approach involves leveraging technologies such as artificial intelligence, virtual reality, and the Internet of Things to deliver tailored offers to customers. By using technology for the benefit of customers, companies can positively influence brand loyalty by strengthening customers’ perception of value. The digital experiences offered by companies will have profound effects on customer decisions, particularly among Generation Y and Z, who are adept at using technology and represent a significant portion of consumer markets especially for the sustainable products. By incorporating gamification elements into digital experiences, brands can gain a significant competitive advantage. As a result, gamification and games have received increased attention from companies interested in exploring how game-like processes and experiences can be used to create more engaging digital platforms. Typically, marketers use online games to influence consumers’ brand engagement, attitudes, promotion, and behavior. Unlike traditional loyalty and reward programs offered to customers, marketers’ interest in gamified apps (online or mobile) has been increasing because gamified applications are known to improve customer brand engagement [3]).

Gamification can be defined as “…the incorporation of game-like mechanics into non-gaming contexts to increase user engagement” [4,5,6]. Gamified applications are assumed to encourage users to visit the app more frequently, hence, forming habits or promoting behavior change. For example, T-Mobile Tuesdays offers a variety of incentives for users to visit their app on a regular basis, such as every Tuesday. Moreover, by providing various incentives, such as badges, points, visual tokens or symbols, leaderboards, or cash prizes that can be earned and redeemed through engagement, gamified apps encourage users to share their experiences through word-of-mouth communication on various online social media platforms. We argue that this trend will continue in the future and consumers will be more engaged with gamified marketing apps as they spend more time on mobile devices. As a result, marketers have incentives to offer gamified apps to influence consumer behavior and improve user experience. However, it’s crucial that these decisions be guided by empirical evidence that supports expected behavioral outcomes. Self-determination theory (SDT) suggests that consumers’ intrinsic and extrinsic motives affect their desire to engage in specific behaviors [7,8]. While intrinsic and extrinsic rewards are crucial in influencing consumer behavior, it’s important to consider their interactions with other marketing concepts, such as customer satisfaction, instead of viewing them in isolation.

Therefore, the objective of this study is to explore how user experience and participation in gamified mobile apps impact their purchase intentions and propensity to engage in word-of-mouth communication. Specifically, we consider a stimulus-organism-response (SOR) conceptual model where user experiences are formed based on perceived hedonic and utilitarian value of the gamified apps, as well as its game design elements. We hypothesize that these experiences positively influence customers’ purchase intentions and the likelihood of engaging in word-of-mouth communication. However, we argue that customer satisfaction with the gamified mobile apps plays an important role in mediating the relationship between app experience and marketing outcomes. Hence, we attempt to expand on previous work by examining how satisfaction mediates the relationship between app experience and behavior.

We anticipate that our study to contribute to the understanding of the relationship between gamified apps and desired marketing outcomes in two ways. First, we provide additional empirical evidence on the role of gamified apps in marketing outcomes by building on previous literature. Second, by including satisfaction as a potential mediator, we hope to improve the understanding of how consumers actually respond to app experiences. We argue that satisfaction plays a crucial role in determining the impact of app experiences on purchase intentions and word-of-mouth engagement. By investigating the mediating effect of satisfaction, we aim to provide a more nuanced understanding of this relationship.

2. Literature Review

While the benefits of use of gaming in marketing applications were discussed in early literature [9], academic research on gamification in marketing has been relatively limited [10], with most attention coming from practitioners. Games have always played an important role in human life, from childhood to adulthood. They are known to be effective in capturing attention, motivating, encouraging engagement [11], and facilitating learning. Stories have become an integral part of the games through a creative narrative design, they are embedded to evoke intense human emotions such as fun, challenge, sacrifice, defeat, win, and recognition. As a result, game-like applications have become popular in various areas, including education, training, social sciences, business, marketing, management, and IT to achieve desired learning or behavioral outcomes [12,13].

Gamification attempts to transfer the positive behavioral and emotional effects of game-playing into non-gaming contexts. This phenomenon involves designers incorporating various game mechanisms into non-game contexts to promote behavioral changes [14]. Using a similar objective, marketers use gamification to improve customer motivation, engagement, learning, brand connection, loyalty, and participation in positive word-of-mouth. Various motivational psychology and learning theories may be used to explain the goals attempted to be achieved through gamification. Among them, the Social Determination Theory (SDT) is perhaps the most widely used theory supporting the adoption of gamification, as it posits that people need to feel autonomy, competence, and relatedness to achieve self-determination, well-being, and growth [15]. An important element of gamification is the creation of an “enjoyment effect” while people perform certain tasks through exploration, prioritization, and feedback mechanisms [16]. Increased motivation and enjoyment facilitate satisfaction and learning. Consequently, gamification of marketing elements has become attractive to marketers trying to benefit from the potential effects of gamification in achieving their specific marketing goals. Offering incentives to users while encouraging them to earn rewards throughout their entire journey can stimulate increased interest in a product or service. If the consumers interact longer with a product or service through the app, the higher its lifetime value to the business. Applying gamification to the product will likely have a positive effect on users’ psychology, making them more motivated and engaged.

Marketing management involves fundamental tasks such as attracting, retaining, and growing a customer base by creating, communicating, and delivering value to a target market [17]. Scholars suggest that gamification of marketing activities offers significant opportunities to achieve marketing objectives [18]. By using engaging design and creating joyful customer experiences, gamification encourages users to participate in desired behaviors sought by the marketer [19]. The term gamification refers to the use of game-like interfaces that users enjoy interacting with [20]. Although there is no clear consensus, games are generally associated with fun, internal control, internal motivation, and internal reality [21]. Huizinga [22] (2006) defines a game as a free activity that is consciously set outside of ordinary life, not serious, but at the same time intense and stimulating all senses of the participants. Huotari & Hamari [23] (2017) describe gamification as “a process of enhancing a service with affordances for gameful experiences in order to support users’ overall value creation” (p. 25). Therefore, the interactive aspects of digital commerce and services marketing offer an excellent opportunity for marketers to incorporate gamification into their marketing tactics.

Due to its perceived and expected benefits, gamification has garnered the attention and interest of marketers. Some argue that gamification is merely a different form of available sales promotion tools enabled by online technologies and/or mobile devices. However, we believe that gamification differs from traditional sales promotion tools by primarily focusing on customers’ gameful experiences and engagement to generate perceived intrinsic and extrinsic value. This is accomplished through the use of creatively narrated stories that elicit human emotions. In other words, the emphasis is on customer engagement and experience, and the benefits of this engagement can be observed in the form of achieving desired marketing outcomes [23].

3. Theoretical Framework and Hypotheses

Gamification is based on the theoretical foundations that games engage participants on an emotional level and motivate them by keeping them interested in using apps [24,25]. Accordingly, designers use different systems, processes, and principles to motivate, engage, and influence users [26,27]. In addition, marketers can gather valuable usage data either directly from users who volunteer to supply the requested data or indirectly through tracking usage data with user consent. Hence, these apps can be tailored based on user interests, which may further increase users’ interest and engagement. Literature provides evidence that gamification has attracted interest in the marketing field for a variety of purposes [14,23]. Ning and Xi [28] (2017) focused on the application of game design elements in marketing to enhance customer service value and create value. Gamification has become a popular tool among marketers and has caught additional attention. The main goals of gamification applications include increased engagement, loyalty, brand awareness, motivation, ownership over purpose and/or tasks. Social media marketers have also used gamification as a means of increasing consumers’ motivation to engage in prosocial behavior through value exchange. There are many game design elements in the literature, including points earned, leaderboards, achievements, levels, story, clear goals, feedback, rewards, progression, and difficulty. Gamification is known to be an effective method of increasing customer participation [2] because it is closely connected with human desires such as reaching high goals or having their achievements recognized in the form of rewards or self-actualization. It encourages customers to continuously engage with the company and create a stronger emotional connection. Gamification also offers benefits by forming a strong sense of responsibility. Rewards are offered when a customer completes steps or actions, such as loyalty in the form of repeat buy or participating in WOM through inviting their friends to participate. Customers go through the promotion structure (e.g., digital or status badges, which improves their status or standing, and they are offered more notable rewards. This also allows marketers to focus on their most valuable customers. In addition, gamification is compatible with highly converging technologies in the digital economy. It is a smart way to collect additional customer information (mostly volunteered by the users), which allows the marketers to personalize their offerings or communications. Big data analytics collected and stored from customers also help companies better understand their customers’ behavior patterns, which is useful for companies to perform marketing automation (i.e., personalized selling, cross-selling, and up-selling).

We argue that a stimulus-organism-response (SOR) theory may be a useful framework to explore the factors affecting customers’ response when they engage with gamified mobile apps [29]. SOR theory hypothesizes that individuals react to environments (experiences) in two ways: through approach behaviors or positive actions such as a desire to explore or affiliate or avert behaviors such as no desire to act [30]. Different scholars have examined both emotional and cognitive responses within the SOR theory in the past, but more recently, Jacoby (2002) [31] used a more integrative SOR framework that incorporated all previous engagement experiences (i.e., affective, and cognitive). In addition, the SOR model is considered an important paradigm for exploring how humans respond to stimuli. SOR model has been used to identify factors influencing consumers’ innovative green product adoption behavior [32], to measure the success of sharing economy platforms in tourism [33], and a framework for understanding how gamification influences customers’ intentions to book eco-friendly hotels [34]. In the context of our study, we predict that the higher the customers’ positive interaction experiences with the gamified mobile apps, the higher the perceived value (hedonic and utilitarian values) and behavioral intentions. For instance, Harwood and Garry (2015) [35] studied the processes for online brand engagement in gamification platforms and found that gamification elements served as stimuli that resulted in emotions and ultimately led to brand engagement. We adopt a simpler version of the Hsu and Chen (2018) [36] model, where we focus on satisfaction as the critical mediating factor for the relationship between gamified app benefits and the desired marketing outcomes. In addition, we test the conceptualized model in a different cultural environment, which provides additional support and generalizability for the relationships tested in the model. Figure 1 displays the conceptual model used in this study.

3.1. Gamified Design and Perceived Value

As previously mentioned, the use of game-like thinking and gaming principles to influence real-world behaviors has become increasingly popular, particularly with the widespread adoption of mobile technology. Businesses are encouraged to employ gamification to increase customers’ engagement with their brand and boost sales [37], while advertisers use it to enhance the effectiveness of their advertising messages. Game thinking has been found to increase ad attitude, memory, persuasion, choice behavior, and persuasion knowledge activation [38].

As a result, gamification has been applied to various functional areas in business, including management and marketing, supported by the empirical evidence of its effectiveness in improving user engagement [39,40]. For example, Bitrian, Buil, and Catalan (2021) [41] reported that gamification increases user engagement by fulfilling users’ needs for competence, autonomy, and relatedness, which, in turn, contributes to higher intentions to use the app and positive word-of-mouth (WOM) recommendations. Moreover, Rodrigues, Oliveira, and Rodrigues (2019) [42] suggested that gamified websites are more likely to attract the attention of younger consumers and increase their desire to re-visit the website.

Palmer et al., (2012) [43] proposed four key gamification elements—progress path, feedback and reward, social connection, and user experience—using principles from game mechanics, behavioral economics, and user experience design thinking. However, gamification may not be enough to motivate consumers unless it creates perceived value. Hence, gamified mobile apps must generate perceived value (i.e., utilitarian, or hedonic), to effectively encourage consumer participation and engagement. The literature provides evidence that gamification is effective in creating various perceived values, such as emotional, enjoyment, excitement, economic (reward), and playfulness [44]. While consumer behavior literature provides a variety of different perceived values, previous studies have generally grouped consumer needs into two broad categories: hedonic and utilitarian [45,46]. According to Hirschman and Holbrook (1982) [47], hedonic needs are related to consumption experiences and linked to the desire for pleasure, fun, and excitement. Utilitarian needs, on the other hand, are associated with functional and rational benefits that can be cognitively evaluated [48]. Therefore, perceived utilitarian value is related to the utilitarian aspect of consumer behavior, while perceived hedonic value is related to the hedonic aspects of consumption behavior [49]. Accordingly, we hypothesize that gamified mobile apps will positively influence consumers’ perceived utilitarian and hedonic values.

Hypothesis 1:

The experience of gamified mobile apps will positively influence consumers’ perceived utilitarian value.

Hypothesis 2:

The experience of gamified mobile apps will positively influence consumers’ perceived hedonic value.

3.2. Perceived Value (Utilitarian and Hedonic)

In principle, consumers seek value, whether utilitarian or hedonic, when they engage in the marketing exchange process. However, empirical studies indicate that rather than an objective assessment, customers’ perceptions of gains and losses from the transaction are the primary considerations in their minds [50,51]. Kaur et al. [52] (2023) concluded that various benefits, such as fun, enjoyment, and connection with others, that are created by gamified apps, lead to a greater sense of satisfaction. In this study, we hypothesize that consumers’ evaluation of the perceived benefits obtained from using gamified mobile apps contributes to their satisfaction, as supported by the self-determination theory [8]. Gamified contexts offer opportunities for consumers to meet their psychological needs for competence, autonomy, and relatedness, and as they evaluate how those needs are met, it contributes to their satisfaction. The literature has examined the relationship between perceived value and satisfaction [49] and has reported an association between perceived values (utilitarian and hedonic) and satisfaction [53].

Hypothesis 3:

Consumers’ perceived utilitarian value with the experience of gamified mobile apps will positively influence their satisfaction.

Hypothesis 4:

Consumers’ perceived hedonic value with the experience of gamified mobile apps will positively influence their satisfaction.

3.3. Satisfaction and Marketing Outcomes

Customer satisfaction is a critical objective to achieve in all marketing activities and has been the focus of researchers and practitioners for several decades [54]. Therefore, customer satisfaction is an essential element for success in competitive markets, both online and offline [55]. Scholars and practitioners assume that when customers are satisfied, business performance improves, and satisfaction is considered to have a strong connection with crucial marketing outcomes such as word-of-mouth (WOM) communication and purchase intentions.

As a theoretical construct, there is no clear agreement in the literature on what customer satisfaction entails, but it is often assumed to include both cognitive and affective components of customers’ evaluations of their experiences. Kokthi et al., [56] (2022) conducted a study to examine the effect of consumers’ brand trust on brand value judgments. The results obtained indicate that brand names have a positive impact on brand value judgments, suggesting that they can strengthen brand trust. Brand trust, in turn, influences customer preferences, perceived quality, and ultimately customer satisfaction. Researchers frequently consider satisfaction as a cumulative measure, achieved when the consumer’s expectations are met or exceeded [57,58]. Customer loyalty literature often uses satisfaction as a mediator variable in the path towards consumer commitment [59,60,61]. For instance, Hsu, Chang, & Chen [62] (2012) used customer satisfaction as an intervening variable between website quality and purchase intentions. Mediating variables are known to explain the relationship between antecedent variables and results. In this study, we also incorporate satisfaction into our conceptual model as a mediator of the relationship between perceived benefits and desirable marketing outcomes (WOM and purchase intentions).

Hypothesis 5:

Satisfaction with the gamified mobile app experience acts as a mediator between consumers’ perceived benefits and marketing outcomes (WOM and purchase intentions).

4. Study Methodology

4.1. Measures

To measure the constructs used in the conceptual model, we adopted various scales from the literature [36,63,64,65]. We measured user experience using a four-item scale adapted from Nowakowski [63] (2020), utilitarian value using a five-item scale adapted from Eppmann et al., [65] (2018), hedonic value, word-of-mouth, and satisfaction using four-item scales adapted from Hsu and Chen [36] (2018), and purchase intentions using a three-item scale adapted from Overby and Lee [64] (2006). All scale items were measured using a Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree).

4.2. Questionnaires and Data Collection

The questionnaire consisted of various scale items designed to measure the study constructs, as well as a few demographic questions for classification purposes. Additionally, a qualifying question was included to determine eligibility for participation. Specifically, participants were initially asked whether they had previous experience with gamified mobile apps. Those who answered it negatively were asked to terminate the questionnaire. To ensure that the questionnaire was clear and easy to answer, a small pilot test was conducted with 20 participants. The results indicated that participants did not encounter any significant challenges in responding to the questions. During this stage, participants were also asked to list the top four gamified mobile apps they had interacted with before. Based on these results, the following four popular gamified apps were selected to be used in the study: McDonald’s Wheel of Fortune, Turkcell Spin the Wheel, Starbucks Collect Stars, and Yemek Sepeti Be a mayor. All four gamified mobile apps are available for both IOS and Android systems. Participants were instructed to consider these gamified apps when responding to the survey questions (see

Table 1. Gamified Mobil Apps used in the study.

McDonald’s Wheel of Fortune	Starbucks Star Collection
Turkcell Spin the Wheel	Yemek Sepeti Be a mayor

).

Due to pandemic restrictions that were still in place during the summer of 2021, this study utilized an online data collection method. Graduate students who were enrolled in marketing classes helped to obtain study participants’ email addresses and identify potential additional subjects who would be willing to participate. The study questionnaire was then converted into a Google Form, and a link to the form was sent to approximately 500 targeted individuals via email. Participants were asked to complete the survey within a one-week period. After eliminating incomplete responses and unqualified subjects, a total of 351 completed surveys were included in the data analyses.

5. Analysis and Results

5.1. Sample Profile

Various descriptive and inferential statistical analyses were conducted to analyze the data. A descriptive analysis of the sample’s demographic characteristics showed that just over 60% of the participants were female, while half of the subjects were under the age of 25. Additionally, most of the participants were highly educated, with two-thirds of them holding a bachelor’s degree or higher. Familiarity with the four mobile apps used in the study was relatively even across the sample, and around 60% of participants reported earning less than $8000 per year. Although this income level might be considered very low when compared to that of the advanced economies, at the time of the data collection, the GDP per capita in Tukey was reported to be approximately $8500 (

Table 2. Sample Profile (n = 351).

Characteristics	Frequency	%
Gender
Male	130	37
Female	221	63
Age
Less than 20	9	3
21–25	181	51
26–30	80	23
Over 30	73	21
Occupation
Student	161	46
Civil servant	70	20
Other	119	34
Education
High school	43	12
Associate degree	25	7
Bachelor’s degree	222	63
Grad school	61	17
Gamification apps used
McDonald’s Wheel of Fortune	74	25
Turkcell Spin the Wheel	51	17
Starbucks Collect Stars	83	28
Yemeksepeti Be a Mayor	86	29
Annual Net Income (US$) *
Less than $5000	78	23
$5000-$8000	130	37
$8000-$10,000	64	18
Above $10,000	76	22

* US$1 = 8TL exchange rate was used.

).

5.2. Construct Reliability and Validity

We began by assessing the reliability of all constructs in the measurement model (see

Table 3. Construct scale items and reliabilities.

Scale Items *	Mean	Alpha
Perceived Utilitarian Value		0.78
Using this gamified platform is useful.	4.15
This gamified platform offers good economic value.	3.92
Perceived Hedonic Value		0.95
It was fun to use this gamified platform.	3.89
I enjoyed using this gamified platform very much.	4.00
I liked using this gamified platform.	3.83
My experience with this gamified platform was very enjoyable.	3.79
Gamified Design		0.85
The presentation of the graphic content of this gamified platform is attractive.	4.12
The textual and graphic content in this gamified platform is intelligible.	4.24
I felt comfortable using this platform.	4.24
My interaction with the interface is clear and understandable.	4.17
Satisfaction		0.93
This gamified platform meets my expectations.	3.83
I am satisfied with my decision to use this gamified platform.	4.03
I would recommend this gamified platform to others.	4.03
I am satisfied with this gamified platform.	4.09
Word-Of-Mouth		0.94
I have recommended this gamified platform to lots of people.	3.67
I “talk up” this gamified platform to my friends.	3.80
I try to spread the good word about this gamified platform.	3.54
I give positive word of mouth about this gamified platform.	3.56
Purchase Intentions		0.89
In the future, this gamified platform is one of the first platforms I intend to look when I need it.	3.47
I intend to continue to visit this gamified platform in the future.	3.89
I intend to continue using this gamified platform in the future.	3.94

* A five-point Likert scale was used where 1 = strongly disagree and 5 = strongly agree.

). According to Table 3, the reliability scores for all constructs were equal to or higher than the suggested levels in the literature (0.70).

To evaluate validity, we calculated various descriptive statistics for all constructs, such as means, standard deviations, and average variance extracted (AVE). Additionally, we analyzed construct intercorrelations to assess discriminant validity (

Table 4. Validity Analysis (CR = Composite Reliability, AVE = Average Variance Extracted, MSV = Maximum Shared Variance, MaxR(H) = Maximum H Reliability, WOM = Word-of-Mouth).

	CR	AVE	MSV	MaxR (H)	Utility	Hedonic	Design	WOM	Purchase Intention	Satisfaction
Utility	0.773	0.631	0.553	0.776	0.794
Hedonic	0.943	0.804	0.724	0.944	0.660	0.897
Design	0.812	0.520	0.513	0.815	0.635	0.716	0.721
WOM	0.926	0.759	0.740	0.932	0.682	0.757	0.538	0.871
Purchase Intentions	0.892	0.735	0.702	0.925	0.676	0.759	0.626	0.766	0.857
Satisfaction	0.923	0.750	0.740	0.925	0.744	0.851	0.652	0.860	0.838	0.866
Validity Analysis—Confidence Intervals
	CR	AVE	Lower 95% CR		Upper 95% CR		Lower 95% AVE		Upper 95% AVE
Utility	0.773	0.631	0.653		0.867		0.485		0.766
Hedonic	0.943	0.804	0.918		0.963		0.738		0.866
Design	0.812	0.520	0.716		0.877		0.388		0.640
WOM	0.926	0.759	0.892		0.952		0.676		0.832
Purchase Intentions	0.892	0.735	0.848		0.925		0.655		0.806
Satisfaction	0.923	0.750	0.888		0.948		0.666		0.820
HTMT Analysis
	Utility	Hedonic	Design		WOM		Purchase		Satisfaction
Utility
Hedonic	0.567
Design	0.506	0.636
WOM	0.584	0.708	0.469
Purchase Intentions	0.572	0.712	0.539		0.715
Satisfaction	0.625	0.796	0.566		0.788		0.766

Thresholds are 0.850 for strict and 0.900 for liberal discriminant validity.

). The AVEs for the constructs ranged from 0.52 to 0.80, which meets the suggested minimum levels in the literature [66]. The construct intercorrelations (also shown in Table 4) were less than the corresponding square root of the AVEs [67]. All intercorrelations were significant at the p < 0.001 level.

We assert that Table 4 presents sufficient evidence of discriminant validity for the model, as indicated by AVEs and squared inter-construct correlations (SIC) that meet or exceed the suggested levels in the literature. Additionally, we applied the recommended Heterotrait-Monotrait (HTMT) inference ratio method to evaluate discriminant validity. This method provides bias-corrected ratios of the constructs’ discriminant validity. We used the AMOS plugin [68] to calculate HTMT values, along with other discriminant validity measures. According to Henseler, Ringle, and Sarstedt [69] (2015), HTMT values below 0.90 (liberally) or below 0.80 (strictly) are acceptable indicators of discriminant validity. Table 4 shows that all HTMT values below the suggested levels (0.80), indicating no significant issues with the constructs’ discriminant validity exist in this study. These results provide evidence for satisfactory convergent validity has been achieved. Additionally, the scales used in this study have undergone testing in previous studies reported in the literature. Considering the measurement model as a whole, we can assume that the results provide acceptable levels of validity for testing the hypothesized structure.

5.3. Common Method Bias

Common method bias (CMB) may be considered an important concern for survey-based studies as it can lead to results that are due to the method used. Although different methods have been suggested in the literature to check the existence of CMB, we decided to use Harman’s Single Factor test [70] due to its simplicity. Although scholars continue to debate the appropriateness of Harman’s single factor test for detecting CMB, Fuller et al. [71] (2016) argued that if CMB bias is strong enough to influence the results, Harman’s single factor method would be sensitive enough to detect it. To check the presence of CMB using Harman’s single factor test, we forced all indicator variables in the model to load onto a single factor and then compared the model fit statistics of the single factor model with that of the hypothesized structural model. The results showed that the model fit indices (CMIN = 416.133, PCMIN/DF = 2.229, CFI = 0.956, PGFI = 0.689, RMSEA = 0.067) for the original model were substantially better than those of the single factor model (CMIN = 1240.819, PCMIN/DF = 6.597, CFI = 0.804, PGFI = 0.553, RMSEA = 0.138), leading us to conclude that CMB was not a major concern in this research.

5.4. Confirmatory Factor Analysis

To verify the underlying factor structure in the model, we conducted a confirmatory factor analysis (CFA) using AMOS. We evaluated the model’s goodness-of-fit using several model fit indices, including CMIN, CFI, GFI, and RMSEA. We followed a two-step approach by first examining the measurement model and then the structural equation model. We confirmed the loadings of individual statements on each construct. The marketing outcomes construct was operationalized as a second-order factor with two first-order factors (word-of-mouth engagement and purchase intentions). The CFA results indicated good model fit indices for this construct (CMIN = 27.28, p < 0.01; CMIN/df = 2.09; GFI = 0.975; CFI = 0.992; RMSEA = 0.06). Additionally, the CFA results showed acceptable model fit indices for all other constructs (see

Table 5. CFA results.

Constructs	Goodness of Fit
	CMIN	p-Value	PCMIN/df	GFI	CFI	RMSEA
Gamified design	0.962	0.62	0.481	0.998	0.999	0.00
Utilitarian value	0.0	-	-	1.00	1.00	0.00
Hedonic value	0.182	0.67	0.182	1.00	1.00	0.00
Satisfaction	14.385	0.001	7.19	0.977	0.986	0.14
Marketing outcomes	27.28	0.01	2.09	0.975	0.992	0.06

). Thus, the results demonstrated that all factor loadings in the model were significant and provided sufficient information to support the relationships between the items and latent factors used in the study.

5.5. Hypothesis Testing

We then used a structural equation model to estimate the relationship among the six constructs (gamified design, utilitarian value, hedonic value, satisfaction, and desired marketing outcomes (WOM and purchase intentions). Structural equation model results are shown in Figure 2, which displays standardized coefficients for the linkages and the r-square values for the model.

Figure 2 shows that marketing outcomes were measured as second-order latent construct composed of two first-order latent constructs (WOM and purchase intentions). The goodness of fit indices for the structural model meets and/or exceeds the cutoff values recommended in the literature (CMIN = 416.133; CMIN/df = 2.29; CFI = 0.956; GFI = 0.880; RMSEA = 0.067; RMR = 0.065). The r-square value was 0.77 for word-of-mouth engagement and 0.74 for the purchase intentions, indicating the portion of the variation in the marketing outcomes that was explained by the constructs included in the model. Model r-square reported in this study is considered acceptable according to the parameters suggested by Cohen (1992) [72].

H1 and H2 proposed that gamified design would have a significant positive effect on perceived utilitarian and hedonic values, respectively. The estimated standardized path coefficient displayed in Figure 2 shows that the relationship between gamified design and both values was significant (β = 0.68, t = 9.187, p < 0.000; β = 0.75, t = 11.152, p < 0.000). Therefore, H1 and H2 are supported.

H3 proposed that perceived utilitarian value would have a significant positive effect on consumer satisfaction. The estimated standardized path coefficient for the relationship is positive and significant (β = 0.33, t = 6.555, p < 0.000), providing support for H3.

Similarly, H4 proposed that perceived hedonic value would have a significant positive effect on satisfaction. The standardized path coefficient for the relationship between the two constructs is positive and significant (β = 0.67, t = 13.294, p < 0.000). Therefore, we obtained support for H4 as well.

Finally, H5 proposed that satisfaction with the gamified mobile app experience acts as a mediator between consumers’ perceived benefits and marketing outcomes (WOM and purchase intentions). To test this mediation hypothesis, we followed a procedure suggested by Baron and Kenny [73] (1986). This procedure suggests that full mediation occurs if the previously significant effect between the independent and dependent variables becomes insignificant when the mediating variable is introduced into the model. Partial mediation occurs if the relationship continues to stay significant, but the size of the effect declines when the mediation variable is introduced. Both paths from perceived utilitarian and hedonic values to marketing outcomes were positive and significant. We then included satisfaction in the model. Standardized path coefficient from satisfaction to marketing outcomes was positive and significant (β = 0.98, t = 16.901, p < 0.001). However, once we included the satisfaction in model, direct links from utilitarian (β = 0.03, t = 0.559, p < 0.58) and hedonic values (β = 0.14, t = 1.641, p < 0.09) to the marketing outcomes become insignificant, indicating that satisfaction fully mediates the relationship between those constructs, hence providing support for H5.

6. Discussion

Although the literature provides evidence that gamified apps contribute to customer engagement and increase purchase intentions, there are gaps in the literature regarding the key aspects of how that relationship works. Using SOR and self-determination theories as the theoretical basis, we examined the relationship between gamified mobile apps and desired marketing outcomes. We conceptualized that experience with gamified mobile apps leads to higher levels of perceived value, which, in turn, contributes to consumer satisfaction with the app, leading to a positive impact on desired marketing outcomes.

Accordingly, all five hypotheses tested are supported by the data. An important focus of the conceptual model we used was the mediating role of satisfaction. Although the literature provides evidence that different scholars use satisfaction as a mediating variable, especially in relationships with loyalty, such studies are limited in the context of our study. Consumers’ perceived value evaluations affected by the use of gamified mobile apps should contribute to satisfaction with the apps; otherwise, the full impact on desired marketing outcomes is not realized. We extend the conceptualization used by Hsu & Chen [53] (2018) by mostly focusing on their value (utilitarian and hedonic) evaluations and satisfaction to see the impact of gamified mobile apps on marketing outcomes in a culturally different context. As mentioned earlier, this study utilized previously established constructs and theories as the conceptual basis for examining the conceptualized relationships.

The findings of this study contribute to a better understanding of the relationship between the role of using gamified apps on desired marketing outcomes. To this end, this study provides additional empirical evidence by building on previous literature. Additionally, using satisfaction as a potential mediator of the relationship sheds additional light on our understanding of how consumers respond to app experiences. We argue that satisfaction plays a crucial role in determining the impact of app experiences on purchase intentions and word-of-mouth engagement. By investigating the mediating effect of satisfaction, this study provides a more nuanced explanation of the relationship.

7. Implications for Sustainability Behavior

Sustainability is a complex concept that focuses on the well-being of consumers, society, and the environment [74]. Previous research on sustainability has emphasized that despite consumers’ understanding of the importance and positive feelings towards participating in sustainability efforts, actual participation in sustainable consumption has been relatively slow [75]. According to Douglas & Brauer (2021) [76], “…gamification has been used for sustainability education, energy reduction, transportation, air quality, waste management, and water conservation…and gamification appears to be a promising avenue for preventing climate change.” Moreover, Kazhamiakin et al., (2023) [77] suggest the use of gamification to incentivize sustainable urban mobility. Therefore, sustainability businesses are encouraged to use gamification [gamified mobile apps in the context of this study] to improve their sustainability efforts and achieve desired consumer behavior changes [78]. Scholars suggest that encouraging participation in such behaviors is more successful through incentives or offering value, rather than appealing to abstract ideals [79].

We can infer from the results reported in this study that sustainable businesses can benefit from the use of gamified apps to improve the effectiveness of their marketing efforts by enhancing the value and satisfaction of sustainable consumption behavior through the gamified apps. Although the results obtained in this study did not directly involve sustainability business apps, we extrapolate that the change in consumer behavior inspired by gamified mobile apps will have a similar positive impact on customers’ perceived utilitarian and hedonic values, satisfaction, and behavioral intentions, therefore, contributing to the desired marketing outcomes such as word-of-mouth and purchase intentions for sustainable businesses.

Sustainable businesses can offer novel incentives, both economic and emotional, social connections [80], and other reward structures to users and encourage them to earn continuous rewards by staying engaged with sustainable consumption behavior. Additionally, through word-of-mouth, users will organically contribute to the marketing efforts and communication campaigns of such businesses, leading to higher levels of awareness and participation. The use of gamified apps is likely to affect the positive psychology of users and motivate them to engage further. Therefore, we expect gamified mobile apps to have a positive influence on consumers’ sustainability behavior (consumption or participation) and word-of-mouth.

Our results showed that gamified mobile apps had a positive impact on perceived value and satisfaction, which in turn led to a positive impact on marketing outcomes. However, we emphasize the mediating role of satisfaction. In other words, the positive effects of gamified apps on marketing outcomes may not be fully realized if the users are not satisfied with the app design and the values it presents. For instance, Tu, Hsieh, & Feng [44] (2019) argued that gamified apps may be valuable in motivating consumers to continue exercising because fitness apps make workouts more fun but making it fun may not be able to sustain their efforts. Therefore, when satisfaction is achieved, gamified apps then positively influence consumers’ purchase intentions and word-of-mouth engagement. We theorize that these results can be easily extended to sustainable businesses’ efforts to encourage sustainability behaviors. However, further scholarly investigation is warranted to test the proposed model in this study by using gamified mobile apps designed specifically for sustainable businesses.

8. Limitations and Future Research

There are a few limitations to this study that could influence the generalizability of the findings to different populations or contexts and need to be addressed. First, the data for the study was collected from a single country while COVID-19 restrictions were still in place. It is important to note that during that time, consumers were more engaged with digital media and used them more frequently due to pandemic restrictions that confined them to their homes. Therefore, relationships identified in this study need to be validated in different times where most restrictions are lifted. Second, sample representativeness and sample size of the study should be carefully considered before extending the results of this study to broader populations. Third, our study simply asked participants to think about their experiences with the four gamified apps considered in the questionnaire and to answer the scale items accordingly. This could make it difficult to attribute the change in consumer behavior to gamified mobile apps. Future studies should use different experimental study designs to control and minimize the effects of other factors that might be valuable to verify some of the relationships identified in this study. For example, new studies should be designed to collect data before and after using a controlled gamified mobile app to isolate the effects of other confounding factors. Finally, our study used self-reported effects on desired marketing outcomes (WOM and purchase intentions). The use of more objective measures of the outcome in the model would have provided valuable insights.