Mobile-assisted showrooming behavior and the (r)evolution of retail: The moderating effect of gender on the adoption of mobile augmented reality

Afthanorhan, 2015, Permutation test, non-parametric, and confidence set approaches to multigroup analysis for comparing 2 groups using partial least square structural equation modeling (pls-sem), Int. J. Math. Stat. Stud., 194–201 Aguirre-Urreta, 2018, Statistical inference with PLSc bootstrap confidence intervals, MIS Q., 42, 1001, 10.25300/MISQ/2018/13587 Ajzen, 1991, The theory of planned behavior, Organ. Behav. Hum. Decis. Process., 50, 179, 10.1016/0749-5978(91)90020-T Alesanco-Llorente, 2021, Augmented reality as a key to open the physical store to the mobile-assisted showroomer: present or future of retail? Revista de Marketing y Publicidad, CEF, 4, 31 Ameen, 2020, Employees’ behavioural intention to smartphone security: a gender-based, cross-national study, Comput. Hum. Behav., 104, 10.1016/j.chb.2019.106184 Attuquayefio, 2014, Using the UTAUT model to analyze students’ ICT adoption, Int. J. Educ. Dev. Using Inf. Commun. Technol., 10, 75 Baker, 2007, The effects of gender and age on new technology implementation in a developing country, Inf. Technol. People, 20, 352, 10.1108/09593840710839798 Beck, 2018, I virtually try it… I want it! Virtual fitting room: a tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions, J. Retail. Consum. Serv., 40, 279, 10.1016/j.jretconser.2016.08.006 Berman, 2019, Flatlined: combatting the death of retail stores, Bus. Horiz., 62, 75, 10.1016/j.bushor.2018.08.006 Blaise, 2018, Mobile commerce competitive advantage: a quantitative study of variables that predict m-commerce purchase intentions, J. Internet Commer., 17, 96, 10.1080/15332861.2018.1433911 Bonetti, 2018, Augmented reality and virtual reality in physical and online retailing: a review, synthesis and research agenda, 119 Brakus, 2009, Brand experience: what is it? How is it measured? Does it affect loyalty?, J. Mark., 73, 52, 10.1509/jmkg.73.3.052 Brengman, 2019, Can’t touch this: the impact of augmented reality versus touch and non-touch interfaces on perceived ownership, Virtual Reality, 23, 269, 10.1007/s10055-018-0335-6 Caboni, 2019, Augmented reality in retailing: a review of features, applications and value, Int. J. Retail Distrib. Manag., 47, 1125, 10.1108/IJRDM-12-2018-0263 Carmines, 1979 Chang, 2014, The influence of web aesthetics on customers’ PAD, Comput. Hum. Behav., 36, 168, 10.1016/j.chb.2014.03.050 Cho, 2019, Consumer attitudes, intention to use technology, purchase intention of Korean 20's women on the acceptance of Fashion Augmented Reality (FAR) with the application of the UTAUT model, J. Korean Soc. Cloth. Text., 43, 125, 10.5850/JKSCT.2019.43.1.125 2021 Conner, 2017, Cultural antecedents to the normative. Affective. And cognitive effects of domestic versus foreign purchase behavior, J. Bus. Econ. Manag., 18, 100, 10.3846/16111699.2016.1220975 CORDIS Dacko, 2017, Enabling smart retail settings via mobile augmented reality shopping apps, Technol. Forecast. Soc. Chang., 124, 243, 10.1016/j.techfore.2016.09.032 Davis, 1989, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Q., 13, 319, 10.2307/249008 Dijkstra, 2015, Consistent partial least squares path modelling, MIS Q., 39, 297, 10.25300/MISQ/2015/39.2.02 Dijkstra, 2015, Consistent and asymptotically normal PLS estimators for linear structural equations, Comput. Stat. Data Anal., 81, 10, 10.1016/j.csda.2014.07.008 Ding, 2018, Emotional effect of cinematic VR compared with traditional 2D film, Telematics Inform., 35, 1572, 10.1016/j.tele.2018.04.003 Do, 2020, Effects of mobile augmented reality apps on impulse buying behavior: an investigation in the tourism field, Heliyon, 6, 10.1016/j.heliyon.2020.e04667 Edgington, 2007 Fiestas, 2021, Mobile-assisted showroomers: understanding their purchase journey and personalities, J. Retail. Consum. Serv., 58, 10.1016/j.jretconser.2020.102280 Fishbein, 1975 Flavián, 2019, The impact of virtual. Augmented and mixed reality technologies on the customer experience, J. Bus. Res., 100, 547, 10.1016/j.jbusres.2018.10.050 Flavián, 2020, Combining channels to make smart purchases: the role of webrooming and showrooming, J. Retail. Consum. Serv., 52, 10.1016/j.jretconser.2019.101923 Fornell, 1981, Structural equation models with unobservable variables and measurement error: algebra and statistics, J. Mark. Res., 18, 382, 10.1177/002224378101800313 Frasquet, 2021, Competitive (versus loyal) showrooming: an application of the push-pull-mooring framework, J. Retail. Consum. Serv., 62, 10.1016/j.jretconser.2021.102639 García-Milon, 2020, Towards the smart tourism destination: key factors in information source use on the tourist shopping journey, Tour. Manag. Perspect., 36 García-Milon, 2021, Assessing the moderating effect of COVID-19 on intention to use smartphones on the tourist shopping journey, Tour. Manag., 87, 10.1016/j.tourman.2021.104361 Gefen, 2011, An update and extension to SEM guidelines for administrative and social science research, MIS Quarterly, 35, iii, 10.2307/23044042 Giovanis, 2019, Adoption of mobile self-service retail banking technologies, Int. J. Retail Distrib. Manag., 47, 894, 10.1108/IJRDM-05-2018-0089 Hair, 2011, PLS-SEM: indeed a silver bullet, J. Mark. Theory Pract., 19, 139, 10.2753/MTP1069-6679190202 Hair, 2014, Partial least squares structural equation modeling (PLS-SEM), Eur. Bus. Rev., 26, 106, 10.1108/EBR-10-2013-0128 Henseler, 2009, The use of partial least squares path modeling in international marketing, 22, 277 Henseler, 2016, Using PLS path modeling in new technology research: updated guidelines, Ind. Manag. Data Syst., 10.1108/IMDS-09-2015-0382 Hew, 2015, What catalyses mobile apps usage intention: an empirical analysis, Ind. Manag. Data Syst., 115, 1269, 10.1108/IMDS-01-2015-0028 Holdack, 2020, The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables, J. Retail. Consum. Serv., 102259 Huang, 2001, The theory of emotions in marketing, J. Bus. Psychol., 16, 239, 10.1023/A:1011109200392 Instituto Nacional de Estadística, 2021 2019 Kim, 2008, Adoption of virtual try-on technology for online apparel shopping, J. Interact. Mark., 22, 45, 10.1002/dir.20113 Kim, 2017, Consumer adoption of smart in-store technology: assessing the predictive value of attitude versus beliefs in the technology acceptance model, Int. J. Fash. Des. Technol. Educ., 10, 26, 10.1080/17543266.2016.1177737 Koo, 2010, The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention, Comput. Hum. Behav., 26, 377, 10.1016/j.chb.2009.11.009 Kourouthanassis, 2015, Tourists responses to mobile augmented reality travel guides: the role of emotions on adoption behavior, Pervasive Mob. Comput., 18, 71, 10.1016/j.pmcj.2014.08.009 Lee, 2018, Consumer experiences. The key to survive in an omni-channel environment: use of virtual technology, J. Text. Appar. Technol. Manag., 10 Lim, 2021, Are men from Mars. Women from Venus? Examining gender differences towards continuous use intention of branded apps, J. Retail. Consum. Serv., 60, 10.1016/j.jretconser.2020.102422 Loureiro, 2015, The role of website quality on PAD, attitude and intentions to visit and recommend island destination, Int. J. Tour. Res., 17, 545, 10.1002/jtr.2022 Miniero, 2014, Being green: from attitude to actual consumption, Int. J. Consum. Stud., 38, 521, 10.1111/ijcs.12128 Mosquera, 2018, Key factors for in-store smartphone use in an omnichannel experience: millennials vs. nonmillennials, Complexity, 2018, 10.1155/2018/1057356 Natarajan, 2017, Understanding the intention to use mobile shopping applications and its influence on price sensitivity, J. Retail. Consum. Serv., 37, 8, 10.1016/j.jretconser.2017.02.010 Nizar, 2019, Examining the use behaviour of augmented reality technology through MARLCardio: adapting the UTAUT model, Asian J. Univ. Educ., 15, 198, 10.24191/ajue.v15i3.7799 Nunnally, 1994, Validity, Psychom. Theory, 3, 99 Ogunjimi, 2021, Smart mirror fashion technology for the retail chain transformation, Technol. Forecast. Soc. Chang., 173, 10.1016/j.techfore.2021.121118 Or, 2011, Factors affecting home care patients' acceptance of a web-based interactive self-management technology, J. Am. Med. Inform. Assoc., 18, 51, 10.1136/jamia.2010.007336 Pantano, 2016, The effect of mobile retailing on consumers' purchasing experiences: a dynamic perspective, Comput. Hum. Behav., 61, 548, 10.1016/j.chb.2016.03.071 Paulo, 2018, Understanding mobile augmented reality adoption in a consumer context, J. Hosp. Tour. Technol., 9, 142 Pelegrín-Borondo, 2016, Assessing the moderating effect of the end user in consumer behavior: the acceptance of technological implants to increase innate human capacities, Front. Psychol., 7, 132, 10.3389/fpsyg.2016.00132 Pelegrín-Borondo, 2017, Assessing the acceptance of technological implants (the cyborg): evidences and challenges, Comput. Hum. Behav., 70, 104, 10.1016/j.chb.2016.12.063 Podsakoff, 2003, Common method biases in behavioral research: a critical review of the literature and recommended remedies, J. Appl. Psychol., 88, 879, 10.1037/0021-9010.88.5.879 Poushneh, 2018, Augmented reality in retail: a trade-off between user's control of access to personal information and augmentation quality, J. Retail. Consum. Serv., 41, 169, 10.1016/j.jretconser.2017.12.010 Pwc, 2019 Qin, 2021, A virtual market in your pocket: how does mobile augmented reality (MAR) influence consumer decision making?, J. Retail. Consum. Serv., 58, 10.1016/j.jretconser.2020.102337 Reinares-Lara, 2018, Do you want to be a cyborg? The moderating effect of ethics on neural implant acceptance, Comput. Hum. Behav., 85, 43, 10.1016/j.chb.2018.03.032 Rese, 2017, How augmented reality apps are accepted by consumers: a comparative analysis using scales and opinions, Technol. Forecast. Soc. Chang., 124, 306, 10.1016/j.techfore.2016.10.010 Rodrigues, 2019, Mobile five senses augmented reality system: technology acceptance study, IEEE Access, 7, 163022, 10.1109/ACCESS.2019.2953003 Roldán, 2012, Variance-based structural equation modeling: guidelines for using partial least squares in information systems research, 193-221 Russell, 1979, Affective space is bipolar, J. Pers. Soc. Psychol., 37, 345, 10.1037/0022-3514.37.3.345 Saprikis, 2021, Determinants of the intention to adopt Mobile augmented reality apps in shopping malls among university students, J. Theor. Appl. Electron. Commer. Res., 16, 491, 10.3390/jtaer16030030 Sarstedt, 2016, Estimation issues with PLS and CBSEM: where the bias lies, J. Bus. Res., 69, 3398, 10.1016/j.jbusres.2016.06.007 Schneider, 2020, Searching offline and buying online–an analysis of showrooming forms and segments, J. Retail. Consum. Serv., 52, 10.1016/j.jretconser.2019.101919 Shang, 2017, Mobile augmented reality applications for heritage preservation in UNESCO world heritage sites through adopting the UTAUT model, 10.1063/1.4980928 Shao, 2019, Antecedents of trust and continuance intention in mobile payment platforms: the moderating effect of gender, Electron. Commer. Res. Appl., 33, 10.1016/j.elerap.2018.100823 Sit, 2018, Showrooming and retail opportunities: a qualitative investigation via a consumer-experience lens, J. Retail. Consum. Serv., 40, 163, 10.1016/j.jretconser.2017.10.004 Subero-Navarro, 2022, Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia, J. Retail. Consum. Serv., 64, 10.1016/j.jretconser.2021.102813 Taylor, 1995, Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions, Int. J. Res. Mark., 12, 137, 10.1016/0167-8116(94)00019-K Taylor, 1995, Understanding information technology usage: a test of competing models, Inf. Syst. Res., 6, 144, 10.1287/isre.6.2.144 Tehseen, 2017, Testing and controlling for common method variance: a review of available methods, J. Manag. Sci., 4, 142 Venkatesh, 2008, Technology acceptance model 3 and a research agenda on interventions, Decis. Sci., 39, 273, 10.1111/j.1540-5915.2008.00192.x Venkatesh, 2000, A theoretical extension of the technology acceptance model: four longitudinal field studies, Manage, Sci, 46, 86 Venkatesh, 2000, Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior, MIS Q., 24, 115, 10.2307/3250981 Venkatesh, 2012, Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Q., 36, 157, 10.2307/41410412 Venkatesh, 2003, User acceptance of information technology: toward a unified view, MIS Q., 27, 425, 10.2307/30036540 Verkijika, 2020, Assessing the role of simplicity in the continuous use of mobile apps, J. Organ. End User Comput., 32, 26, 10.4018/JOEUC.2020100102 Viejo Fernández, 2020, Is showrooming really so terrible? Start understanding showroomers, J. Retail. Consum. Serv., 54, 10.1016/j.jretconser.2020.102048 Von Briel, 2018, The future of omnichannel retail: a four-stage Delphi study, Technol. Forecast. Soc. Chang., 132, 217, 10.1016/j.techfore.2018.02.004 Wang, 2009, Investigating the determinants and age and gender differences in the acceptance of mobile learning, Br. J. Educ. Technol., 40, 92, 10.1111/j.1467-8535.2007.00809.x Wang, 2010, User acceptance of mobile internet based on the unified theory of acceptance and use of technology: investigating the determinants and gender differences, Soc. Behav. Personal. Int. J., 38, 415, 10.2224/sbp.2010.38.3.415 Watson, 2018, The impact of experiential augmented reality applications on fashion purchase intention, Int. J. Retail Distrib. Manag., 48, 433, 10.1108/IJRDM-06-2017-0117 Willems, 2017, The path-to-purchase is paved with digital opportunities: an inventory of shopper-oriented retail technologies, Technol. Forecast. Soc. Chang., 124, 228, 10.1016/j.techfore.2016.10.066 Yuan, 2016, An investigation of users’ continuance intention towards mobile banking in China, Inf. Dev., 32, 20, 10.1177/0266666914522140