Table 2. Future research agenda... | Emerald Publishing

Table 2.

Future research agenda framework

Framework	Research agenda
Theories:	How do consumers’ intrinsic needs for autonomy, competence and relatedness influence their purchasing decisions in the metaverse? In what ways do users’ expectations and the perceived value of virtual experiences shape their purchase intentions in the metaverse marketplace? How does the construction of virtual identities and social group affiliations affect purchasing decisions in virtual environments like the metaverse?
Self-Determination Theory (SDT) suggests that consumers are motivated by intrinsic needs for autonomy, competence and relatedness in their purchasing decisions (Ryan and Deci, 2017; Gilal et al., 2019). SDT provides insights into how these needs drive behavior in both physical and virtual marketplaces, informing strategies to enhance consumer engagement, satisfaction and loyalty
Value Expectancy Theory (Wigfield and Eccles, 2000) posits that individuals’ intentions are influenced by their expectations and the value they place on outcomes. In the metaverse, this theory helps understand how users’ expectations and perceived value shape their behavior and satisfaction, enabling businesses to tailor offerings to align with consumer preferences
Social Identity Theory (Tajfel, 1981) suggests that individuals’ self-concept is shaped by their membership in social groups, influencing behaviors and attitudes. In the metaverse, users’ virtual identities affect their interactions and consumption behaviors, offering insights into the role of social identity in shaping consumer behavior
Context:	How can virtual sustainability practices be integrated into metaverse shopping behaviors to promote environmentally conscious consumption? What factors influence users’ attitudes and behaviors toward responsible consumption in virtual environments? How does digital consumption in the virtual economy shape consumers’ purchasing decisions in metaverse shopping? What is the impact of virtual consumption on real-world economic trends?
Virtual sustainability and ethical consumption focus on environmentally sustainable and ethical practices in virtual environments (Scurati et al., 2021). Research explores users’ attitudes and behaviors toward responsible consumption, guiding strategies to promote sustainability in the metaverse
The virtual economy involves activities like virtual currency, asset trading and property ownership (Scarle et al., 2012). Research explores digital consumption, purchasing motivations and its impact on real-world economics, helping businesses monetize virtual experiences in the metaverse
Characteristics:	How do AI-powered assistants and personalized experiences influence purchase decisions in virtual shopping environments, considering users’ levels of digital literacy and their ability to navigate virtual spaces? In what ways do cognitive load and perceived risk (e.g., privacy concerns) mediate the relationship between virtual shopping experiences and consumer purchase decisions in the metaverse? How do users’ virtual identities, experience levels, and psychological traits (such as personality and cognitive style) moderate their responses to virtual shopping environments in the metaverse? What impact do virtual assets (e.g., digital goods, property ownership), word-of-mouth (WOM), and brand equity have on consumer behavior in the metaverse?
Antecedents: AI-powered assistants and personalized experiences influence engagement (Sung et al., 2021). Digital literacy, including navigation and privacy protection, affects users’ interactions and decision-making (Tella et al., 2023)
Mediators: High cognitive load reduces decision-making and engagement (Chang et al., 2017). Perceived risk, such as privacy concerns, impacts trust and willingness to engage (X. Zhang and Yu, 2020). Brand perception shapes purchase intentions and loyalty (Ha, 2004)
Moderators: Experience affects how users interact with virtual environments (Kim et al., 2021), while virtual identity shapes responses to stimuli and social interactions (Buisine and Guegan, 2020). Psychological traits, such as personality and cognition, impact user behavior and susceptibility to persuasion (Oyibo and Vassileva, 2019)
Outcomes: Virtual assets hold economic, social and symbolic value (Watkins et al., 2016). WOM influences perceptions and behaviors (Gupta and Harris, 2010). The virtual economy includes currency exchanges, asset trading and property ownership (Scarle et al., 2012). Brand equity affects user preferences and behaviors (Arya et al., 2024)
Methods:	How can MCDM methods like AHP, TISM and IRP be used to prioritize and evaluate factors that influence consumer behavior in metaverse shopping environments, and what are their implications for strategic decision-making in the metaverse? In what ways can neuroscientific techniques, such as brain imaging and physiological measurements, be applied to understand consumers’ emotional and cognitive responses to virtual shopping experiences in the metaverse? How can ethnographic observations provide deeper insights into users’ behaviors, social dynamics, and cultural practices within virtual shopping environments, and what role do these insights play in shaping virtual commerce strategies? What is the potential of VR prototyping in designing and refining virtual shopping experiences, and how can iterative testing using VR improve user engagement and satisfaction in the metaverse?
MCDM techniques like AHP, TISM and IRP help businesses evaluate and prioritize factors influencing consumer behavior in the metaverse (Saaty, 2004; Sushil, 2012, 2009)
Brain imaging and physiological measurements reveal users’ cognitive and emotional responses to virtual experiences, aiding in the design of engaging environments (Bohil et al., 2011; Huang et al., 2022)
Ethnographic methods provide qualitative insights into users’ behaviors, social interactions and cultural practices in virtual environments (Williams, 2007; Hossain et al., 2024)
VR prototyping allows businesses to test and refine virtual shopping experiences, improving usability and user engagement (Seth et al., 2011)

Framework	Research agenda
Theories:	How do consumers’ intrinsic needs for autonomy, competence and relatedness influence their purchasing decisions in the metaverse? In what ways do users’ expectations and the perceived value of virtual experiences shape their purchase intentions in the metaverse marketplace? How does the construction of virtual identities and social group affiliations affect purchasing decisions in virtual environments like the metaverse?
Self-Determination Theory (SDT) suggests that consumers are motivated by intrinsic needs for autonomy, competence and relatedness in their purchasing decisions (Ryan and Deci, 2017; Gilal et al., 2019). SDT provides insights into how these needs drive behavior in both physical and virtual marketplaces, informing strategies to enhance consumer engagement, satisfaction and loyalty
Value Expectancy Theory (Wigfield and Eccles, 2000) posits that individuals’ intentions are influenced by their expectations and the value they place on outcomes. In the metaverse, this theory helps understand how users’ expectations and perceived value shape their behavior and satisfaction, enabling businesses to tailor offerings to align with consumer preferences
Social Identity Theory (Tajfel, 1981) suggests that individuals’ self-concept is shaped by their membership in social groups, influencing behaviors and attitudes. In the metaverse, users’ virtual identities affect their interactions and consumption behaviors, offering insights into the role of social identity in shaping consumer behavior
Context:	How can virtual sustainability practices be integrated into metaverse shopping behaviors to promote environmentally conscious consumption? What factors influence users’ attitudes and behaviors toward responsible consumption in virtual environments? How does digital consumption in the virtual economy shape consumers’ purchasing decisions in metaverse shopping? What is the impact of virtual consumption on real-world economic trends?
Virtual sustainability and ethical consumption focus on environmentally sustainable and ethical practices in virtual environments (Scurati et al., 2021). Research explores users’ attitudes and behaviors toward responsible consumption, guiding strategies to promote sustainability in the metaverse
The virtual economy involves activities like virtual currency, asset trading and property ownership (Scarle et al., 2012). Research explores digital consumption, purchasing motivations and its impact on real-world economics, helping businesses monetize virtual experiences in the metaverse
Characteristics:	How do AI-powered assistants and personalized experiences influence purchase decisions in virtual shopping environments, considering users’ levels of digital literacy and their ability to navigate virtual spaces? In what ways do cognitive load and perceived risk (e.g., privacy concerns) mediate the relationship between virtual shopping experiences and consumer purchase decisions in the metaverse? How do users’ virtual identities, experience levels, and psychological traits (such as personality and cognitive style) moderate their responses to virtual shopping environments in the metaverse? What impact do virtual assets (e.g., digital goods, property ownership), word-of-mouth (WOM), and brand equity have on consumer behavior in the metaverse?
Antecedents: AI-powered assistants and personalized experiences influence engagement (Sung et al., 2021). Digital literacy, including navigation and privacy protection, affects users’ interactions and decision-making (Tella et al., 2023)
Mediators: High cognitive load reduces decision-making and engagement (Chang et al., 2017). Perceived risk, such as privacy concerns, impacts trust and willingness to engage (X. Zhang and Yu, 2020). Brand perception shapes purchase intentions and loyalty (Ha, 2004)
Moderators: Experience affects how users interact with virtual environments (Kim et al., 2021), while virtual identity shapes responses to stimuli and social interactions (Buisine and Guegan, 2020). Psychological traits, such as personality and cognition, impact user behavior and susceptibility to persuasion (Oyibo and Vassileva, 2019)
Outcomes: Virtual assets hold economic, social and symbolic value (Watkins et al., 2016). WOM influences perceptions and behaviors (Gupta and Harris, 2010). The virtual economy includes currency exchanges, asset trading and property ownership (Scarle et al., 2012). Brand equity affects user preferences and behaviors (Arya et al., 2024)
Methods:	How can MCDM methods like AHP, TISM and IRP be used to prioritize and evaluate factors that influence consumer behavior in metaverse shopping environments, and what are their implications for strategic decision-making in the metaverse? In what ways can neuroscientific techniques, such as brain imaging and physiological measurements, be applied to understand consumers’ emotional and cognitive responses to virtual shopping experiences in the metaverse? How can ethnographic observations provide deeper insights into users’ behaviors, social dynamics, and cultural practices within virtual shopping environments, and what role do these insights play in shaping virtual commerce strategies? What is the potential of VR prototyping in designing and refining virtual shopping experiences, and how can iterative testing using VR improve user engagement and satisfaction in the metaverse?
MCDM techniques like AHP, TISM and IRP help businesses evaluate and prioritize factors influencing consumer behavior in the metaverse (Saaty, 2004; Sushil, 2012, 2009)
Brain imaging and physiological measurements reveal users’ cognitive and emotional responses to virtual experiences, aiding in the design of engaging environments (Bohil et al., 2011; Huang et al., 2022)
Ethnographic methods provide qualitative insights into users’ behaviors, social interactions and cultural practices in virtual environments (Williams, 2007; Hossain et al., 2024)
VR prototyping allows businesses to test and refine virtual shopping experiences, improving usability and user engagement (Seth et al., 2011)