Gaming and luxury fashion: exploring factors driving gamers’ luxury virtual in - game fashion

This study investigates the factors driving gamers’ intention to purchase virtual luxury fashion in online games. The study’s conceptual framework is grounded in the social identity and social capital theory. A total of 468 responses were collected using an online survey from Fortnite players and analyzed using covariance-based structural equation modelling (CB-SEM). The results reveal that avatar identification was positively associated with perceived value, social presence, and intention to purchase virtual luxury fashion. Perceived value and social presence were positively associated with intending to purchase virtual luxury fashion. Brand love strengthened the positive association between the perceived value and social presence on the intention to purchase virtual luxury fashion. This study contributes to the marketing and information systems literature by offering the first insights into virtual luxury fashion in online games. The findings would assist game developers and marketers in better understanding gamer behaviour to capitalize on virtual luxury fashion

Obese customers’ fitness goal disclosure on social media: exploring weight-loss image sharing on emotions and healthy lifestyle aspirations

Purpose – Obesity is today’s most neglected, yet blatantly visible, public health problem. This study aims to examine the role of social media and goal-directed behavior in motivating healthy lifestyle intentions for customers experiencing obesity. It investigates the distinct roles of self-conscious emotions (shame and pride) and weight-transformational posts shared by others on social media as moderators of these relationships. Design/methodology/approach – The conceptual model uses the goal-directed behavior theory and social comparison theory, tested using data collected from 804 obese customers in Fiji through an experimental design. Findings – Weight-loss transformation posts by others on social media, elicit distinct emotions for obese customers. Obese customers who felt guilt and shame due to shared weight-loss transformation posts showed a stronger association between goal disclosure and healthy lifestyle intention. In addition, the association between goal disclosure and healthy lifestyle intention is conditionally mediated by goal commitment, specifically for those obese customers that elicited guilt over shame due to shared weight-loss transformation posts by others on social media. Research limitations/implications – Despite the adoption of an experimental design using a fictional stimulus being a commonly used method in marketing studies, external validity issues are likely. Also, this study examines obese customer behavior relating to Facebook. In addition, data collection for this study has been done from a single country perspective. Therefore, caution needs to be exercised when generalizing the findings of this study. Practical implications – The findings assist businesses and marketers in the health and fitness industry to better leverage social media and goal-directed behavior and understand the emotions of obese customers to undertake data-driven precision marketing strategies. Originality/value – The findings provide novel insights into goal disclosure and commitment, electronic word-of-mouth on social media platforms, self-conscious emotions and healthy lifestyle intentions for customers experiencing obesity

Virtual fitness: investigating team commitment and post - pandemic virtual workout perceptions

The COVID-19 pandemic has disrupted the fitness landscape leading to phenomenal growth in virtual workouts. This study investigates factors influencing virtual workout team commitment and post-pandemic workout intentions. A conceptual framework is developed that is grounded in the social identity theory. Online data collection is employed to gather responses from 406 team virtual workout participants. Results reveal that virtual workout team participation positively influences team identification, satisfaction, and compliance with team norms. Additionally, virtual workout team identification, satisfaction, and compliance to team norms were found to be antecedents of commitment to the virtual workout team. Commitment to virtual workout teams is revealed to be positively associated with post-pandemic virtual team workout intention and post-pandemic traditional team workout intention. However, the relationship with post-pandemic traditional team workout intentions was found to be stronger. Valuable theoretical and practical insights emerge, providing a better understanding of virtual workout team commitment and how marketers and practitioners can ensure post-pandemic success by better understanding customer behaviour

Reward - based advertisement in online games: a win for advertisers, developers, and gamers

This study examines factors affecting gamers’ attitude towards reward-based advertisements (RBA) in online games. A conceptual model is developed based on the Ducoffe’s web advertising model and tested using a quantitative design through data collected from 532 online gamers in Fiji. Covariance-based structural equation modelling (CB-SEM) was employed to perform the analysis. Results reveal that informativeness, credibility, entertainment, and incentive positively influence advertisement value. Advertisement value was found to positively influences attitude towards RBA. The moderating factors of perceived competitiveness and gamer envy were found to strengthen the positive association between perceived advertisement value and attitude towards RBA. This study is novel is it is the first exploration of RBA in online gaming. In so doing, this study contributes to both marketing and gaming literature and provides valuable insight for marketers and game developers to influence customers to be more receptive to advertisements in online games

Does psychological distance and religiosity influence fraudulent customer behaviour?

Online businesses incur significant losses because of fraudulent customer behaviour. This study investigates the factors motivating fraudulent customer intention on eBay. A conceptual framework is developed that extends the theory of planned behaviour with religiosity factors, social detection risk, ethical judgement, and moderating factor of perceived psychological distance. A quantitative methodology is adopted that collects data from 450 respondents. Covariance-based structural equation modelling is used to analyse the proposed hypotheses. Results reveal that intrinsic and extrinsic religiously negatively influences attitude towards fraudulent customer behaviour on eBay. Attitude, subjective norms, and perceived behavioural control positively influence fraudulent customer intentions, while ethical judgement negatively impacts it. Psychological distance strengthened the relationship between attitude, perceived behavioural control, and fraudulent customer intentions on eBay. Additionally, the association between ethical judgement and fraud intention was weaker for individuals with higher perceived psychological distance. The study contributes to the literature and provides insights to online businesses and cyber security developers into factors motivating fraudulent customer behaviour and strategies that can be used to combat this growing threat

Exploring customer adoption of autonomous shopping systems

Autonomous technology is on the rise, allowing customers to delegate shopping tasks and decisions to such artificial intelligence-based systems. However, trust and privacy issues are impeding the adoption of such technology. This study examines the factors affecting the adoption of autonomous shopping systems. A conceptual framework is developed by adding trust and moderating variables of privacy concern to the UTAUT model. Using a quantitative research design, data is collected from 454 respondents and analysed using covariance-based structural equation modelling. Results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively impact perceived trust in autonomous shopping systems. Privacy concern as a moderator dampens the positive relationship between performance expectancy and perceived trust. Also, privacy concerns dampen the positive relationship between social influence and perceived trust. This study is one of the first to empirically examine customers’ autonomous shopping system intention by revising the UTAUT with trust and privacy concerns. These findings generate valuable insights into an under-researched area of customer behaviour and artificial intelligence

Drone food delivery: a solution to crowding during the Global COVID-19 Pandemic

The COVID-19 pandemic has altered the retail landscape and introduced new risks for customers. Customers, in turn, are increasingly turning toward technology to reduce pandemic-associated risks. This study investigates the impact of crowding at food retail outlets on customers’ willingness to utilize drone food delivery. Data were collected using an online survey and analyzed using covariance-based structural equation modeling. The results confirm that crowding is positively associated with social withdrawal tendency and mortality threat. Perceived vulnerability and perceived severity act as moderators to strengthen the positive association of crowding with mortality threat and social withdrawal tendency. Social withdrawal tendency and mortality threat, in turn, are positively associated with customers’ attitudes toward drone delivery. A positive attitude toward drone delivery positively impacts customer willingness to utilize drone delivery, while a negative attitude has a negative impact. This study provides novel insights into technology adoption driven by crowding as an environmental factor during a global pandemic. It also offers evidence that technology adoption is driven by threat perceptions. Our findings have important implications for retailers, who can consider drone food delivery as a possible solution to reduce customers’ threat perception

Stockpiling intentions and customer well - being during the COVID-19 pandemic

The COVID-19 pandemic and associated factors influence customers' stockpiling intentions. This study examines the impact of various factors on stockpiling intentions. It develops a model combining threat severity and fear of COVID-19,customer well-being dimensions, and constructs relating to theories of planned behavior and competitive arousal to explain the effect of these on stockpiling intentions. Adopting a quantitative design,we analyzed data from 476 respondents using covariance-based structural equation modeling.The empirical results confirm that threat severity (with the fear of COVID-19 as a mediator) and fear of COVID-19 positively influenced individuals' attitudes toward stckpiling. Additionally, a positive attitude toward stockpiling, subjective norms that support stockpiling,the degree of perceived behavioral control, perceived scarcity, and time pressure positively influence stockpiling intentions. This study's findings thus contribute to a better understanding of customers' stockpiling intentions during a crisis and assist policymakers in developing effective COVID-19 response and recovery strategies

Disposition of youth in predicting sustainable development goals using the Neuro - fuzzy and random forest algorithms

This paper evaluates the inclination of Asian youth regarding the achievement of Sustainable Development Goals (SDGs). As the young population of a country holds the key to its future development, the authors of this study aim to provide evidence of the successful application of machine learning techniques to highlight their opinions about a sustainable future. This study’s timing is critical due to rapid developments in technology which are highlighting gaps between policy and the actual aspirations of citizens. Several studies indicate the superior predictive capabilities of neuro-fuzzy techniques. At the same time, Random Forest is gaining popularity as an advanced prediction and classification tool. This study aims to build on the previous research and compare the predictive accuracy of the adaptive neuro-fuzzy inference system (ANFIS) and Random Forest models for three categories of SGDs. The study also aims to explore possible differences of opinion regarding the importance of these categories among Asian and Serbian youth. The data used in this study were collected from 425 youth respondents in India. The results of data analysis show that ANFIS is better at predicting SDGs than the Random Forest model. The SDG preference among Asian and Serbian youth was found to be highest for the environmental pillar, followed by the social and economic pillars. This paper makes both a theoretical and a practical contribution to deepening understanding of the predictive power of the two models and to devising policies for attaining the SDGs by 2030