تجربه کاربر در خرید آنلاین شخصی: یک تحلیل فازی مجموعه ای User experience in personalized online shopping: a fuzzy-set analysis

Introduction With the advancement of digital platforms, online shopping environments are evolving as well, and they are able to offer consumers more options in the purchase process, providing them with better services and products. Indeed, personalization strategies can be used to influence consumers’ behaviour and increase their loyalty both offline (Melewar et al., 2017) and online (Ho and Bodoff, 2014; Pappas et al., 2016), while at the same time they may indicate a company’s commitment to offer value to its customers (Adobe, 2015). By 2020, four billion people are expected to be online, suggesting that addressing customers’ needs will be more important than ever (IDC, 2015) while developing new or improved business strategies and models. Personalization can change consumers’ behaviour, and reduce acquisition costs, while increasing revenues, and marketing efficiency (Ariker et al., 2015). However, marketing practice requires further advancement, as it is not at the same level as current technical capabilities (Adobe, 2015). Cognitive and affective factors (Ho and Bodoff, 2014; Pappas et al., 2017b), trust and privacy (Lee and Rha, 2016) and experience (Pappas et al., 2014b) may affect consumers’ attitudes and evaluations in online shopping. As marketers use interactive technologies to modify consumers’ behaviour (Kaptein and Eckles, 2012), they develop strategies that build on logical arguments, make emotional appeals or request input or feedback from and for them (Pappas et al., 2017b). Recent studies in personalization have identified the critical role of trust towards the online vendor, privacy and emotions (Bleier and Eisenbeiss, 2015; Pappas et al., 2016). When using personalized services or receiving customized recommendations, the personalization–privacy paradox may occur (Baek, 2014; Xu et al., 2011), based on which consumers have to make a choice between personalization benefits and privacy risks. In such cases, recent studies show that trust, emotions and previous purchase experience (Lee and Rha, 2016; Pappas et al., 2017b) are sometimes key factors that can influence consumers’ behavioural intentions. Although trust is a multidimensional construct, here, unless otherwise mentioned, we take the point of view of the consumer, thus “trust” refers to consumers’ trust perceptions towards the online vendor when using personalized online services and refers to continuing trust rather than initial trust (Gefen et al., 2003). Also, emotions are defined as how happy, anxious, sad or angry consumers feel (Ekman, 1992a, 1992b), which are considered among the basic emotions, clearly distinguished from each other, and have been found to be effective in explaining how people perform and behave with computers (Kay and Loverock, 2008). Therefore, as these factors are critical for successful personalized online shopping and they may interact with each other in multiple ways, they may be studied together to better assess their effects on customers’ purchase intentions