Determinants of Consumer Intention to Use Online Gambling Services

Abstract

Online gambling has skyrocketed in recent years. As such, knowing the determinants of consumer usage behavior is crucial in understanding online gambling services. This study has as main objective the construction of an explanatory model of the online gambling services usage behavior, based on the incorporation of perceived risk in the conceptual framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The empirical validation of the model was performed by conducting an online survey to a convenience sample of 212 Portuguese online players. Data were processed using the PLS-SEM methodology. The results evidence that performance expectancy, social influence, facilitating conditions, hedonic motivations, price value, habits, as well as perceived risk influence the intention to use online gambling services.

Mapping unified theory of acceptance and use of technology (UTAUT) 2: a taxonomical study using bibliometric visualisation

“…Risk management issues have had an overlap with the privacy-related issues and securityrelated issues, hence the construct studied under the risk management category has few elements related to privacy and security. Therefore, risk management issues have been studied with different constructs and concepts such as risk (Brohi et al, 2018), perceived risk (Lian, 2015;Pascual-Miguel et al, 2015;Slade et al, 2015;Fortes et al, 2016;Tandon et al, 2016;Alalwan et al, 2018;Kazancoglu and Aydin, 2018;Farah et al, 2018;Rita et al, 2018;Verkijika, 2018;Ahmed and Kranthi, 2019;Christino et al, 2019;Chopdar and Sivakumar, 2019), perceived privacy risk (Gao et al, 2015;Shaw and Sergueeva, 2019;Wiegard et al, 2019), privacy risk (Aldossari and Sidorova, 2018;Chopdar et al, 2018;Tandon et al, 2018), security risk (Tandon et al, 2016;Aldossari and Sidorova, 2018;Chopdar et al, 2018;Tandon et al, 2018), financial risk (Tandon et al, 2016(Tandon et al, , 2018, time risk (Tandon et al, 2016(Tandon et al, , 2018, social risk (Tandon et al, 2016(Tandon et al, , 2018 P4. Risk will significantly impact the behavioral intention compared to other UTAUT2 constructs.…”

“…While the majority of the studies were conducted in a service context. The selected studies undertaken in this research reveal studies conducted in the context of consumer behavior addressed issues of "online purchasing behavior of consumers who purchase digital and non-digital goods" (Pascual-Miguel et al, 2015), "different drivers of online airline ticket purchasing behavior" (Escobar-Rodrı ´guez and Carvajal-Trujillo, 2013), "effects of lead-usership on the acceptance of media innovations" (Mu ¨tterlein et al, 2019), "nonmonetary benefits of mobile commerce" (Shaw and Sergueeva, 2019), "motives that lead consumers to become prosumers" (Halassi et al, 2019), "factors affecting technology adoption and the role of personality on individual usage behavior" (Chipeva et al, 2018), "understanding the needs and preferences of different segments of customers, specifically women" (Ameen and Willis, 2019), "information and communication technologies intention behavior and actual use among older adults" (Macedo, 2017), "critical variables that can attract consumers to open and read the advertisement on the short message service" (Shareef et al, 2017), "impact of moderators and trust on consumer's intention to use a mobile phone for purchases" (Trojanowski and Kułak, 2017), "identification and characterization of the three social commerce shopper segments" (Nadeem et al, 2017), "how e-shopping vehicles are interrelated in regard to consumer reliance upon them for their e-purchasing" (Blake et al, 2017), "understanding Jordanian consumers' online purchase intentions" (Singh et al, 2017), "examine the social commerce intentions of customers" (Sheikh et al, 2017), "analyze perceived risk and drivers of online shopping influencing behavioral intention in India" (Tandon et al, 2016), "online gambling services usage behavior" (Fortes et al, 2016), "factors that influence omnichannel consumers' behavior through their acceptance of and intention to use new technologies during the shopping process" (Juaneda-Ayensa et al, 2016) and "explore and predict the intentions to use and use behaviors of Phablets" (Huang and Kao, 2015). Majority of the studies in the consumer behavior context have either tested online purchase behavior or tested the usage of any services or products.…”