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Purpose This study aims to propose a model for predicting consumers’ esports videogame engagement on their ensuing consumption behaviors, which remains nebulous to date. Design/methodology/approach After approaching esports consumers in different gaming zones in Pakistan, this paper collected data from 364 videogame-based esports consumers. This paper deployed SmartPLS 3.2.8 software to perform the partial least squares-structural equation modeling-based analyzes. Findings The structural model results show that consumers’ affective and behavioral esports videogame engagement positively affects their consumption behavior, including heightened community engagement, purchase intent, coproduction, word-of-mouth and new player recruitment. However, while consumers’ cognitive esports engagement was found to positively impact community engagement, new player recruitment and coproduction, it failed to predict consumers’ esports-related purchase intent or word-of-mouth behaviors. Practical implications The findings reveal that a strategic focus on consumers’ esports game engagement will enable practitioners to nurture desirable consumer behaviors, including enhanced purchase intent, coproduction, word-of-mouth and new player recruitment behaviors, thus warranting consumer engagement’s strategic value as a key esports gaming metric. Originality/value Empirical research into the role of consumers’ esports videogame engagement on their ensuing consumption behaviors remains scant to date. Based on this gap, this study offers a timely contribution by exploring and validating a model that gauges the effect of consumers’ cognitive, emotional and behavioral esports videogame engagement on their community engagement, purchase intention, coproduction, word-of-mouth and new player recruitment. It, thus, offers important insight into the rapidly advancing field of digital esports games.

Background: Problematic smartphone use (PSU) has been increasing hastily in recent decades, and it has become inseparable during the COVID-19 pandemic, especially among the students who are at risk of problematic smartphone use. Therefore, the present study aimed to investigate the prevalence and associated factors of PSU during the COVID-19 pandemic among the Bangladeshi students. Methods: A total of 601 Bangladeshi students were recruited through an online-based crosssectional survey that was conducted between October 7 and November 2, 2020. The survey collected information related to socio-demographics, behavioral health, internet use behaviors, depression, anxiety, and PSU. Independent samples t-test and one-way ANOVA were performed to present the relationship between the studied variables and PSU. Multiple linear regression analysis was also used for investigating the explanatory power of the predictive models for PSU. Results: Surprisingly, about 86.9% of the students scored to be problematic smartphone users (≥21 out of a total 36 based on the Smartphone Application-Based Addiction Scale). In addition, medical students, engaging in a relationship, performing less physical activity, longer duration of internet use, some sorts of internet use purpose (eg, messaging, watching videos, using social media), depression, and anxiety were significantly associated with higher scores of PSU. After adjusting all the studied variables, the final model explained a 31.3% variance predicting PSU. Conclusion:The present study is one of the first approaches to assess the prevalence of PSU among the Bangladeshi students during the COVID-19 pandemic, whereas the addiction level was superfluous (and this may be due to more online engagement related to the pandemic). Thus, the study recommended strategies or policies related to the students' riskreducing and healthy use of smartphones.

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The aim of the study is to develop a new instrument to measure engagement in videogame play termed as consumer videogame engagement. The study followed the scale development procedure to develop an instrument to measure the construct of consumer videogame engagement. In this study, we collected the data in two different phases comprising study 1 (n=136) and study 2 (n=270). We employed SPSS 22.0 for exploratory factor analysis using study 1 respondents to explore the factors for consumer videogame engagement and reliability analysis. Results of EFA resulted with six-factor solution. We further used SmartPLS 3.0 software on study 2 respondents to further confirm the six-factor solution as reflective measurement model on the first-order level, and three second-order formative constructs on the second-order or higher-order level as formative measurement model. Results of the reflective measurement model and formative measurement model evidenced that consumer videogame engagement has strong psychometric properties and is a valid instrument to measure engagement in videogame play. Results also confirmed that consumer videogame engagement is a multidimensional construct as well as a reflective-formative construct. The study is unique in its investigation as it develops an instrument to measure engagement in videogame play which comprises the cognitive, affective, and behavioral dimensions.