Bridging the gap between customer experience management and mobile shopping

Abstract

Purpose -The purpose of this research is to study three clues (employee reputation, site design, and security) of the Customer Experience Management framework that can prompt mobile shopper satisfaction and repurchase intention. The moderator role of perceived distance of the retailer is explored.Design/methodology/approach -The Partial Least Squares approach was employed to analyze information gathered from 1053 mobile shoppers in a geographically extensive and emerging market (Mexico).Findings -The Customer Experience Management framework is helpful in explaining m-shopper satisfaction and intention to repurchase via mobile phone. Our findings show that reputation (particularly for consumers who perceive that retailers are near), site design (principally for consumers who perceive that retailers are far away), and security enhance mobile-shopper satisfaction. Satisfactory experiences increase repurchase intention, regardless of perceived distance of alternative retailers.Originality/value -This study contributes to understanding which factors mobile vendors (m-vendors) could manage in different ways to engender satisfaction and intention to repurchase via mobile, from the unexplored Customer Experience Management perspective and in a scarcely studied emerging market. Also, a key facet of this study is related to the moderating influence of perceived distance on the relationship between employee reputation, site design, and security, on one hand, and m-shopper satisfaction on the other.

Mobil Alışveriş Düzleminde Consistent PLS-SEM ve CB-SEM Yöntemlerinin Karşılaştırılması

“…The search process had a result of 14 articles in Science Direct (Elsevier), 3 articles in Web of Science Core Collection, 21 articles in Emerald Insight, and 12 articles in Proquest ABI/INFORM Collection (in a total of 50 articles). The articles reviewed in the literature, by and large, are on mobile shopping (Jimenez et al 2019;Tan & Ooic, 2018;Dakduk et al 2020;Verkijika, 2018;Groß, 2016;Faqih;Mahapatra, 2017;Nel & Boshoff, 2019Chen, 2018;Ghazali et al 2018;Rezaei & Valaei, 2017;Thakur, 2018;Celik & Kocaman, 2017;Shukla et al 2018;Liu et al, 2019;San-Martín et al 2019); mobile application use and its adoption (Molinilloa et al 2019;Ameen et al 2020;Schmitz et al 2016;Tseng, 2020;Sung, 2020;Tan et al 2017;Gong et al 2018;Gupta et al 2018;Hong et al 2017;Kuo et al 2019;Nakuze et al 2019); mobile advertising (Tan et al 2018;Bakare et al 2017;Goh et al 2020); mobile banking (Tran & Corner, 2016;Owusu Kwateng et al 2019;Thaker et al 2019;Singh & Srivastava, 2020); mobile payment (Gupta & Arora, 2019;Hariguna et al 2020); mobile coupons (Souiden et al 2019;Liu et al 2015); mobile services ( Rezaei et al 2016, Smith, 2020…”

“…CB-SEM separates the variance of each variable into two components. First is the common variance that is calculated from the variance combined with other items in a construct, and second is unique variance that includes both specific and error variance (Bollen, 1989;Rigdon, 1998).…”