You plant a virtual tree, we'll plant a real tree: Understanding users' adoption of the Ant Forest mobile gaming application from a behavioral reasoning theory perspective
Graphical abstract
Introduction
Among the corporate social responsibility (CSR) activities, addressing environmental pollution (e.g., reducing carbon footprints) is considered particularly important (Gupta, 2020; Li et al., 2020). Many companies use CSR as a crucial tool to present themselves as more socially responsible actors to attract consumers, society, and government in general (Bahta et al., 2020; Waheed et al., 2020). On the other hand, consumers may feel particularly good when using a product or service provided by a socially responsible company.
Going green, which can be described as “the adoption of environmental management practices, intended as practices aimed at minimizing the detrimental impact on the environment in terms of both resource depletion and pollution” (Tzschentke et al., 2008, p. 126), has become a global phenomenon (Li and Liu, 2020). Environmental pollution can be generated from many sources, such as using plastic (Hameed et al., 2020) or vehicles (Gupta, 2020). According to Jambeck et al. (2015), an average individual produces 52 kg of plastic waste yearly, and vehicles are also perceived as the primary contributor to environmental problems through petrol or diesel exhaust (Gupta, 2020).
Like some other countries, China is facing air pollution-related problems (Zhang et al., 2020). China is one of the biggest energy consumers in the world (Gong et al., 2020). It is the most significant emerging economy with a growth rate of up to 9.5% (Gong et al., 2020), and this rapid growth is at the cost of ecological damage from the use of heavy machinery and resources (Du et al., 2019). Different policies to address environmental issues are being introduced by the Chinese government, intended to encourage both organizations and individuals to contribute to avoiding ecological pollution (Zhang et al., 2020).
In light of the above, a new Ant Forest mobile gaming application was launched in China by Ant Financial Service Group in cooperation with Alipay. Alipay is the world's most popular and the largest third-party payment platform in China (Wang and Yao, 2020; Zhang et al., 2020). Since its launch in August 2016, Ant Forest has already prevented 20,000 tons of carbon emissions by providing convenient green transportation services to over 30 million people (Ant Financial, 2020). Inspired by this phenomenon, over 200,000 people use public bicycles every day in China, tantamount to planting 20,000 trees. In addition, Ant Forest created a 354,000-ton decrease in carbon emissions nationwide via electronic payments and documents (Ant Financial, 2020). Overall, as of the end of 2019, Alipay Ant Forest had reduced carbon emissions by 7.9 million tons by attracting over 500 million users and planting 122 million trees in China (see Fig. 1 for more detail; Business Wire, 2020). These contributions resulted in Ant Forest receiving the United Nations' “Champion of the Earth Award” in 2019 (Wang and Yao, 2020).
To participate in public benefit activities such as walks, online payment, travel by public transport, and other activities (e.g., bike shares), Ant Forest users need to create a carbon account. The user counts low-carbon activities and converts them into virtual green energy to plant a virtual tree in the personal Ant Forest account. When a user has enough energy in his/her carbon account to grow a virtual tree, Alipay plants a real tree in China. This motivates Ant Forest users to continue green activities, a new kind of green behavior activity that offers users a new way to protect the environment and reduce pollution.
Although Ant Forest has already met with great success, the sustainable growth of the Ant Forest will mainly depend on continued usage decisions (Zhang et al., 2020). Thus, understanding Ant Forest users' attitudes toward and intentions to continue using Ant Forest is vital to draw out insights regarding users' adoption of this novel green behavior. Therefore, the main objective of this study is to investigate the key factors that may play significant roles in shaping users’ attitudes toward Ant Forest and their intention to continue using it.
In recent years, there have been numerous studies focusing on the green phenomenon, eco-friendly products, or low-carbon behavior activities, such as actual green purchase behavior (Ali et al., 2020; Zarei and Maleki, 2018), green creativity (Li et al., 2020), green luxury or eco-luxury (Athwal et al., 2019), green skincare products (Hsu et al., 2017), green purchase intention (Sreen et al., 2018), or intention to buy green products (Yadav and Pathak, 2016), and green advertising (Matthes and Wonneberger, 2014) from the perspective of the theory of planned behavior (TPB; Ajzen, 1991), behavioral reasoning theory (BRT; Claudy and Peterson, 2014), or self-determination theory. Although these studies help us understand the background of greening, we use the BRT to develop a research framework to contribute to the current unexplored green phenomenon. Also, we show how environmental knowledge as moderation to the current BRT augments its effectiveness in the environmental setting.
The remainder of the paper presents the theoretical background and hypotheses development. Then the methodology and results are reported. The last parts of the paper are devoted to the conclusion and implications. A description of the limitations of the study and directions for further research are provided.
Section snippets
Behavioral reasoning theory
Growing interest in the BRT is evident in the literature (Diddi et al., 2019; Dhir et al., 2021; Pillai and Sivathanu, 2018; Tandon et al., 2020). Social scientists across different domains have widely applied the traditional theories in the consumer behavior literature, such as the TPB (Ajzen, 1991) and the TAM (Davis, 1989), to understand individual behavior. Although these are well-established theories in information technology and social psychology, they are often criticized for neglecting
Research model and hypotheses
Fig. 3 presents the research model of the current study adapted from Claudy and Peterson (2014). We used BRT as a theoretical foundation to develop our research model on understanding users' adoption of the Ant Forest mobile gaming app. BRT is a well-known theory for explaining customers’ behavioral intentions in the behavior literature. In this study, value is measured using “openness to change” following the literature (see Claudy et al., 2015; Gupta and Arora, 2017a). Recent studies
Data collection and procedure
Using a combined convenience/snowball sampling technique, we collected 293 valid responses to a questionnaire from individuals in China. The questionnaire was created using the Wenjuanxing platform (https://www.wjx.cn), which is commonly used in China (Wang et al., 2020). First, the link to the questionnaire was shared with potential respondents through QQ and WeChat. QQ is one of the largest instant messaging software in China (Zhang et al., 2020). Second, we asked respondents to share the
Data analysis
We used SmartPLS 3 (Ringle et al., 2015) and SPSS (version 25) for data analysis using a previously described PLS-SEM approach (Hair et al., 2019). Further, a two-step approach of measurement and structural models was applied to test our proposed model (Chin, 2010; Hair et al., 2010).
Conclusions
The current study used BRT to understand users’ attitudes toward Ant Forest and their intentions to continue using Ant Forest, with the moderating role of environmental knowledge. We employed SEM with SmartPLS 3 to analyze data collected from actual Ant Forest users. The findings suggest the following significant outcomes.
First, the user values have a significant influence on RF, RA, and users' attitudes toward Ant Forest. Another significant finding is that both RF and RA were observed to have
Limitations and future research directions
Although this work has provided some interesting findings and contributions to the green behavior literature, it has several limitations. However, addressing these limitations can serve as fruitful avenues for future studies. First, the sample size in this study was relatively small. Future research should reinvestigate to understand whether increasing the sample size affects the findings. Second, our proposed model was based on a limited number of variables to explain Ant Forest adoption in
CRediT authorship contribution statement
Muhammad Ashfaq: Contribution, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draftWriting - original draft, Writing – review & editing. Qingyu Zhang: Contribution, Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draftWriting - original draft, Writing
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
This research was funded by Guangdong 13th-Five-Year-Plan Philosophical and Social Science Fund (#GD20CGL28); Natural Science Foundation of Guangdong – Guangdong Basic and Applied Basic Research Foundation (#2021A1515011894); National Natural Science Foundation of China (#71572115); Major Program of Social Science Foundation of Guangdong (#2016WZDXM005); Natural Science Foundation of SZU (#836).
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