Meta-analytic review of online purchase intention: conceptualising the study variables

References

• Adnan, H. (2014). An analysis of the factors affecting online purchasing behavior of Pakistani consumers. International Journal of Marketing Studies, 6(5), 1–28. https://doi.org/10.5539/ijms.v6n5p133
   Google Scholar
• Agarwal, J., & Wu, T. (2018). ECommerce in emerging economies: A multitheoretical and multilevel framework and global firm strategies. In J. Agarwal, & T. Wu (Eds.), Emerging issues in global marketing: A shifting paradigm (pp. 231–253). Springer International Publishing. https://doi.org/10.1007/9783319741291_9
   Google Scholar
• Ahn, T., Ryu, S., & Han, I. (2007). The Impact of Web Quality and Playfulness on user acceptance of online retailing. Information & Management, 44(3), 263–275. https://doi.org/10.1016/j.im.2006.12.008
   Web of Science ®Google Scholar
• Akhlaq, A., & Ahmed, E. (2015). Digital commerce in emerging economies: Factors associated with online shopping intentions in Pakistan. International Journal of Emerging Markets, 10(4), 634–647. https://doi.org/10.1108/IJoEM-01-2014-0051
   Web of Science ®Google Scholar
• Akram, U., Junaid, M., Zafar, A. U., Li, Z., & Fan, M. (2021). Online purchase intention in Chinese social commerce platforms: Being Emotional or Rational? Journal of Retailing and Consumer Services, 63, 102669. https://doi.org/10.1016/j.jretconser.2021.102669
   Web of Science ®Google Scholar
• Al-Jundi, S. A., Shuhaiber, A., & Augustine, R. (2019). Effect of consumer innovativeness on new product purchase intentions through learning process and perceived value. Cogent Business & Management, 6(1), 1–21. https://doi.org/10.1080/23311975.2019.1698849
   Web of Science ®Google Scholar
• Allard, T., Babin, B. J., & Chebat, J.-C. (2009). When income matters: Customers evaluation of shopping malls’ hedonic and utilitarian orientations. Journal of Retailing and Consumer Services, 16(1), 40–49. https://doi.org/10.1016/j.jretconser.2008.08.004
   Google Scholar
• Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29(2), 130–141. https://doi.org/10.1016/j.technovation.2008.07.004
   Web of Science ®Google Scholar
• Alvarez-Risco, A., Quipuzco-Chicata, L., & Escudero-Cipriani, C. (2021). Determinants of online repurchase intention in COVID-19 times: Evidence from an emerging economy. Lecturas de Economía, 96(96), 101–143. https://doi.org/10.17533/udea.le.n96a342638
   Google Scholar
• Amos, C., Holmes, G. R., & Keneson, W. C. (2014). A meta-analysis of consumer impulse buying. Journal of Retailing and Consumer Services, 21(2), 86–97. https://doi.org/10.1016/j.jretconser.2013.11.004
   Google Scholar
• Ashraf, N., Faisal, M. N., Jabbar, S., & Habib, M. A. (2019). The role of website design artifacts on consumer attitude and behavioral intentions in online shopping. Technical Journal, 24(02), 50–60.
   Google Scholar
• Ashraf, A. R., Thongpapanl, N. ()., & S., Auh. (2014). The application of the technology acceptance model under different cultural contexts: The case of online shopping adoption. Journal of International Marketing, 22(3), 68–93. https://doi.org/10.1509/jim.14.0065
   Web of Science ®Google Scholar
• Awad, N. F., & Ragowsky, A. (2008). Establishing trust in electronic commerce through online word of mouth: An examination across genders. Journal of Management Information Systems, 24(4), 101–121. https://www.jstor.org/stable/40398913 https://doi.org/10.2753/MIS0742-1222240404
   Web of Science ®Google Scholar
• Azizi, S., & Javidani, M. (2010). Measuring e-shopping intention: An Iranian perspective. African Journal of Business Management, 4(13), 2668–2675.
   Google Scholar
• Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377–386. https://doi.org/10.1162/qss_a_00019
   Google Scholar
• Badrinarayanan, V., Becerra, E. P., & Madhavaram, S. (2014). Influence of congruity in store-attribute dimensions and self-image on purchase intentions in online stores of multichannel retailers. Journal of Retailing and Consumer Services, 21(6), 1013–1020. https://doi.org/10.1016/j.jretconser.2014.01.002
   Google Scholar
• Bala, M., & Verma, D. (2018). A critical review of digital marketing. International Journal of Management, IT & Engineering, 8(10), 321–339.
   Google Scholar
• Bartels, J., & Reinders, M. J. (2011). Consumer innovativeness and its correlates: A propositional inventory for future research. Journal of Business Research, 64(6), 601–609. https://doi.org/10.1016/j.jbusres.2010.05.002
   Web of Science ®Google Scholar
• Bauman, A., & Bachmann, R. (2017). Online consumer trust: Trends in research. Journal of Technology Management & Innovation, 12(2), 68–79. https://doi.org/10.4067/S0718-27242017000200008
   Google Scholar
• Baytar, F., Chung, T., & Shin, E. (2020). Evaluating garments in augmented reality when shopping online. Journal of Fashion Marketing and Management: An International Journal, 24(4), 667–683. https://doi.org/10.1108/JFMM-05-2018-0077
   Google Scholar
• Begg, C. B., & Mazumdar, M. (1994). Operating Characteristics of a rank correlation test for publication bias. Biometrics, 50(4), 1088. https://doi.org/10.2307/2533446
   PubMed Web of Science ®Google Scholar
• Bezes, C. (2013). Effect of channel congruence on a retailer’s image. International Journal of Retail & Distribution Management, 41(4), 254–273. https://doi.org/10.1108/09590551311330537
   Google Scholar
• Bhukya, R., & Singh, S. (2015). The effect of perceived risk dimensions on purchase intention. American Journal of Business, 30(4), 218–230. https://doi.org/10.1108/AJB-10-2014-0055
   Web of Science ®Google Scholar
• Bianchi, C., & Andrews, L. (2012). Risk, trust, and consumer online purchasing behaviour: A Chilean perspective. International Marketing Review, 29(3), 253–275. https://doi.org/10.1108/02651331211229750
   Web of Science ®Google Scholar
• Blut, M., Wang, C., & Schoefer, K. (2016). Factors influencing the acceptance of self-service technologies. Journal of Service Research, 19(4), 396–416. https://doi.org/10.1177/1094670516662352
   Web of Science ®Google Scholar
• Cai, Z., Fan, X., & Du, J. (2017). Gender and attitudes toward technology use: A meta-analysis. Computers & Education, 105, 1–13. https://doi.org/10.1016/j.compedu.2016.11.003
   Web of Science ®Google Scholar
• Carpenter, J. M., & Fairhurst, A. (2005). Consumer shopping value, satisfaction, and loyalty for retail apparel brands. Journal of Fashion Marketing and Management: An International Journal, 9(3), 256–269. https://doi.org/10.1108/13612020510610408
   Google Scholar
• Celik, H. E., & Yilmaz, V. (2011). Extending the technology acceptance model for adoption of e-shopping by consumers in Turkey. Journal of Electronic Commerce Research, 12(2), 152–164.
   Web of Science ®Google Scholar
• Çera, G., Phan, Q. P. T., Androniceanu, A., & Çera, E. (2020). Financial capability and technology implications for online shopping. E + M Ekonomie a Management, 23(2), 156–172. https://doi.org/10.15240/tul/001/2020-2-011
   Web of Science ®Google Scholar
• Chan, Y. Y. Y., & Ngai, E. W. T. (2011). Conceptualising electronic word of mouth activity: An input-process-output perspective. Marketing Intelligence & Planning, 29(5), 488–516. https://doi.org/10.1108/02634501111153692
   Google Scholar
• Chandon, P., Wansink, B., & Laurent, G. (2000). A benefit congruency framework of sales promotion effectiveness. Journal of Marketing, 64(4), 65–81. https://doi.org/10.1509/jmkg.64.4.65.18071
   Web of Science ®Google Scholar
• Chang, Y. W., & Chen, J. (2021). What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness. Journal of Retailing and Consumer Services, 58, 102325. https://doi.org/10.1016/j.jretconser.2020.102325
   Web of Science ®Google Scholar
• Cheung, C. M. K., Chan, G. W. W., & Limayem, M. (2005). A critical review of online consumer behavior: Empirical research. Journal of Electronic Commerce in Organizations, 3(4), 1–19. https://www.igi-global.com/article/critical-review-online-consumer-behavior/3463 https://doi.org/10.4018/jeco.2005100101
   Google Scholar
• Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345–354. https://doi.org/10.1509/jmkr.43.3.345
   Web of Science ®Google Scholar
• Chiu, Y., Lin, C., & Tang, L. (2005). Gender differs: Assessing a model of online purchase intentions in e-tail service. International Journal of Service Industry Management, 16(5), 416–435. https://doi.org/10.1108/09564230510625741
   Google Scholar
• Chiu, C. M., Wang, E. T. G., Fang, Y. H., & Huang, H. Y. (2014). Understanding customers’ repeat purchase intentions in B2C e-commerce: The roles of utilitarian value, hedonic value and perceived risk. Information Systems Journal, 24(1), 85–114. https://doi.org/10.1111/j.1365-2575.2012.00407.x
   Web of Science ®Google Scholar
• Chopdar, P. K., Paul, J., Korfiatis, N., & Lytras, M. D. (2022). Examining the role of consumer impulsiveness in multiple app usage behaviour among mobile shoppers. Journal of Business Research, 140, 657–669. https://doi.org/10.1016/j.jbusres.2021.11.031
   Web of Science ®Google Scholar
• Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55(1), 591–621. https://doi.org/10.1146/annurev.psych.55.090902.142015
   PubMed Web of Science ®Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
   Google Scholar
• Dai, B., Forsythe, S., & Kwon, W. S. (2014). The impact of online shopping experience on risk perceptions and online purchase intentions: Does product category matter. Journal of Electronic Commerce Research, 15(1), 13–24.
   Web of Science ®Google Scholar
• Das, M., Habib, M., Saha, V., & Jebarajakirthy, C. (2021). Bandwagon vs. snob luxuries: Targeting consumers based on uniqueness dominance. Journal of Retailing and Consumer Services, 61, 102582. https://doi.org/10.1016/j.jretconser.2021.102582
   Web of Science ®Google Scholar
• Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: three experiments. International Journal of Human-Computer Studies, 45(1), 19–45. https://doi.org/10.1006/ijhc.1996.0040
   Web of Science ®Google Scholar
• Deng, W., Su, T., Zhang, Y., & Tan, C. (2021). Factors affecting consumers’ online choice intention: A study based on Bayesian network. Frontiers in Psychology, 12, 731–850. https://doi.org/10.3389/fpsyg.2021.731850
   Web of Science ®Google Scholar
• DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled Clinical Trials, 7(3), 177–188. https://doi.org/10.1016/0197-2456(86)90046-2
   PubMedGoogle Scholar
• Dewi, C. K., Mohaidin, Z., & Murshid, M. A. (2019). Determinants of online purchase intention: A PLS-SEM approach: Evidence from Indonesia. Journal of Asia Business Studies, 14(3), 281–306. https://doi.org/10.1108/JABS-03-2019-0086
   Web of Science ®Google Scholar
• Dharmesti, M., Dharmesti, T. R. S., Kuhne, S., & Thaichon, P. (2019). Understanding online shopping behaviours and purchase intentions amongst millennials. Young Consumers, 22(1), 152–167. https://doi.org/10.1108/yc-12-2018-0922
   Web of Science ®Google Scholar
• Dwidienawati, D., Tjahjana, D., Abdinagoro, S. B., Gandasari, D., & Munawaroh. (2020). Customer review or influencer endorsement: Which one influences purchase intention more? Heliyon, 6(11), e05543. https://doi.org/10.1016/j.heliyon.2020.e05543
   PubMed Web of Science ®Google Scholar
• Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical Research ed.), 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629
   PubMed Web of Science ®Google Scholar
• Ely, R. J. (1994). The effects of organizational demographics and social identity on relationships among professional women. Administrative Science Quarterly, 39(2), 203–238. https://doi.org/10.2307/2393234
   Web of Science ®Google Scholar
• Erkan, I., & Evans, C. (2016). Social media or shopping websites? The influence of eWOM on consumers’ online purchase intentions. Journal of Marketing Communications, 24(6), 617–632. https://doi.org/10.1080/13527266.2016.1184706
   Google Scholar
• Espejel, J., Fandos, C., & Flavián, C. (2007). The role of intrinsic and extrinsic quality attributes on consumer behaviour for traditional food products. Managing Service Quality: An International Journal, 17(6), 681–701. https://doi.org/10.1108/09604520710835000
   Google Scholar
• Fandos, C., & Flavián, C. (2006). Intrinsic and extrinsic quality attributes, loyalty and buying intention: An analysis for a PDO product. British Food Journal, 108(8), 646–662. https://doi.org/10.1108/00070700610682337
   Web of Science ®Google Scholar
• Fatima, J. K., Ghandforoush, P., Khan, M., & Masico, R. D. (2017). Role of innovativeness and self-efficacy in tourism m-learning. Tourism Review, 72(3), 344–355. https://doi.org/10.1108/TR-02-2017-0019
   Web of Science ®Google Scholar
• Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/s1071-5819(03)00111-3
   Web of Science ®Google Scholar
• Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic in judgments of risks and benefits. Journal of Behavioral Decision Making, 13(1), 1–17. https://doi.org/10.1002/1099-0771(200001/03)13:1%3C1::aid-bdm333%3E3.0.co;2-s
   Web of Science ®Google Scholar
• Fogel, J., & Schneider, M. (2010). Understanding designer clothing purchases over the Internet. Journal of Fashion Marketing and Management: An International Journal, 14(3), 367–396. https://doi.org/10.1108/13612021011061843
   Google Scholar
• Fortes, N., & Rita, P. (2016). Privacy concerns and online purchasing behaviour: Towards an integrated model. European Research on Management and Business Economics, 22(3), 167–176. https://doi.org/10.1016/j.iedeen.2016.04.002
   Web of Science ®Google Scholar
• Fowler, K., & Bridges, E. (2010). Consumer innovativeness: Impact on expectations, perceptions, and choice among retail formats. Journal of Retailing and Consumer Services, 17(6), 492–500. https://doi.org/10.1016/j.jretconser.2010.08.004
   Google Scholar
• Ganguly, B., Dash, S. B., Cyr, D., & Head, M. (2010). The effects of website design on purchase intention in online shopping: The mediating role of trust and the moderating role of culture. International Journal of Electronic Business, 8(4/5), 302–330. https://doi.org/10.1504/IJEB.2010.035289
   Google Scholar
• Gawor, T., & Hoberg, K. (2019). Customers’ valuation of time and convenience in e-fulfilment. International Journal of Physical Distribution & Logistics Management, 49(1), 75–98. https://doi.org/10.1108/IJPDLM-09-2017-0275
   Web of Science ®Google Scholar
• Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389. https://doi.org/10.2307/249720
   Web of Science ®Google Scholar
• Ghosal, I. (2015). A demographic study of buying spontaneity on e-shoppers: Preference Kolkata (West Bengal). Journal of Technology Management for Growing Economies, 6(2), 65–75. https://doi.org/10.15415/jtmge.2015.62008
   Google Scholar
• Guadagno, R. E., Muscanell, N. L., Rice, L. M., & Roberts, N. (2013). Social influence online: The impact of social validation and likability on compliance. Psychology of Popular Media Culture, 2(1), 51–60. https://doi.org/10.1037/a0030592
   Google Scholar
• Han, M. C., & Kim, Y. (2016). Why consumers hesitate to shop online: Perceived risk and product involvement on Taobao.com. Journal of Promotion Management, 23(1), 24–44. https://doi.org/10.1080/10496491.2016.1251530
   Google Scholar
• Har Lee, C., Cyril Eze, U., & Oly Ndubisi, N. (2011). Analyzing key determinants of online repurchase intentions. Asia Pacific Journal of Marketing and Logistics, 23(2), 200–221. https://doi.org/10.1108/13555851111120498
   Google Scholar
• Hassanein, K., & Head, M. (2007). Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. International Journal of Human-Computer Studies, 65(8), 689–708. https://doi.org/10.1016/j.ijhcs.2006.11.018
   Web of Science ®Google Scholar
• Hepola, J., Leppäniemi, M., & Karjaluoto, H. (2020). Is it all about consumer engagement? Explaining continuance intention for utilitarian and hedonic service consumption. Journal of Retailing and Consumer Services, 57, 102232. https://doi.org/10.1016/j.jretconser.2020.102232
   Web of Science ®Google Scholar
• Hernández, B., Jiménez, J., & José Martín, M. (2011). Age, gender and income: Do they really moderate online shopping behaviour? Online Information Review, 35(1), 113–133. https://doi.org/10.1108/14684521111113614
   Web of Science ®Google Scholar
• Hsu, S. H., & Bayarsaikhan, B.-E. (2012). Factors influencing on online shopping attitude and intention of Mongolian consumers. The Journal of International Management Studies, 7(2), 167–176.
   Google Scholar
• Hsu, C., Chuan-Chuan Lin, J., & Chiang, H. (2013). The effects of blogger recommendations on customers’ online shopping intentions. Internet Research, 23(1), 69–88. https://doi.org/10.1108/10662241311295782
   Web of Science ®Google Scholar
• Hsu, C. L., & Lu, H. P. (2004). Why do people play online games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853–868. https://doi.org/10.1016/j.im.2003.08.014
   Web of Science ®Google Scholar
• Hyun, H., Thavisay, T., & Lee, S. H. (2022). Enhancing the role of flow experience in social media usage and its impact on shopping. Journal of Retailing and Consumer Services, 65, 102492. https://doi.org/10.1016/j.jretconser.2021.102492
   Web of Science ®Google Scholar
• Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage within government institutions in Yemen: An extended technology acceptance model (TAM) with Internet self-efficacy and performance impact. Science International, 29(4), 737–747.
   Google Scholar
• Jaradat, M. I. R. M., Moustafa, A. A., & Mashaqba, A. M. A. (2018). Exploring perceived risk, perceived trust, perceived quality and the innovative characteristics in the adoption of smart government services in Jordan. International Journal of Mobile Communications, 16(4), 399. https://doi.org/10.1504/IJMC.2018.092669
   Web of Science ®Google Scholar
• Jiang, Z., & Benbasat, I. (2004). Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 21(3), 111–147. https://doi.org/10.1080/07421222.2004.11045817
   Web of Science ®Google Scholar
• Jordan, G., Leskovar, R., & Marič, M. (2018). Impact of fear of identity theft and perceived risk on online purchase intention. Organizacija, 51(2), 146–155. https://doi.org/10.2478/orga-2018-0007
   Web of Science ®Google Scholar
• Kahan, D. M. (1997). Social influence, social meaning, and deterrence. Virginia Law Review, 83(2), 349. https://doi.org/10.2307/1073780
   Web of Science ®Google Scholar
• Katta, R. M. R., & Patro, C. S. (2017). Influence of web attributes on consumer purchase intentions. International Journal of Sociotechnology and Knowledge Development, 9(2), 1–16. https://doi.org/10.4018/IJSKD.2017040101
   Google Scholar
• Kaur, A., & Thakur, P. (2019). Determinants of Tier 2 Indian consumer’s online shopping attitude: an SEM approach. Asia Pacific Journal of Marketing and Logistics, 33(6), 1309–1338. https://doi.org/10.1108/apjml-11-2018-0494
   Google Scholar
• Kautish, P., Paul, J., & Sharma, R. (2021). The effect of assortment and fulfilment on shopping assistance and efficiency: An e-tail servicescape perspective. Journal of Retailing and Consumer Services, 59, 102393. https://doi.org/10.1016/j.jretconser.2020.102393
   Web of Science ®Google Scholar
• Kayworth, T., & Whitten, D. (2010). Effective information security requires a balance of social and technology factors. MIS Quarterly Executive, 9(3), 163–178.
   Web of Science ®Google Scholar
• Keeling, K., Keeling, D., & McGoldrick, P. (2013). Retail relationships in a digital age. Journal of Business Research, 66(7), 847–855. https://doi.org/10.1016/j.jbusres.2011.06.010
   Web of Science ®Google Scholar
• Keeney, R. L. (1999). The value of internet commerce to the customer. Management Science, 45(4), 533–542. https://www.jstor.org/stable/2634822 https://doi.org/10.1287/mnsc.45.4.533
   Web of Science ®Google Scholar
• Keisidou, E., Sarigiannidis, L., & Maditinos, D. (2011). Consumer characteristics and their effect on accepting online shopping in the context of different product types. International Journal of Business Science & Applied Management (IJBSAM), 6(2), 31–51. https://www.econstor.eu/handle/10419/190625
   Google Scholar
• Kelman, H. C. (1961). Processes of opinion change. Public Opinion Quarterly, 25(1), 57–78. https://doi.org/10.1086/266996
   Web of Science ®Google Scholar
• Khare, A., & Rakesh, S. (2011). Antecedents of online shopping behavior in India: An examination. Journal of Internet Commerce, 10(4), 227–244. https://doi.org/10.1080/15332861.2011.622691
   Google Scholar
• Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125–150. https://doi.org/10.1007/s10660-012-9089-5
   Web of Science ®Google Scholar
• Kim, S., & Park, H. (2013). Effects of various characteristics of social commerce (s-commerce) on consumers’ trust and trust performance. International Journal of Information Management, 33(2), 318–332. https://doi.org/10.1016/j.ijinfomgt.2012.11.006
   Web of Science ®Google Scholar
• Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
   Web of Science ®Google Scholar
• Kraemer, H. C., & Andrews, G. (1982). A nonparametric technique for meta-analysis effect size calculation. Psychological Bulletin, 91(2), 404–412. https://doi.org/10.1037/0033-2909.91.2.404
   Web of Science ®Google Scholar
• Kumar, A., & Kashyap, A. K. (2018). Leveraging the utilitarian perspective of online shopping to motivate online shoppers. International Journal of Retail & Distribution Management, 46(3), 247–263. https://doi.org/10.1108/IJRDM-08-2017-0161
   Web of Science ®Google Scholar
• Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use. Computers in Human Behavior, 26(2), 254–263. https://doi.org/10.1016/j.chb.2009.04.011
   Web of Science ®Google Scholar
• Laroche, M., Yang, Z., McDougall, G. H. G., & Bergeron, J. (2005). Internet versus bricks-and-mortar retailers: An investigation into intangibility and its consequences. Journal of Retailing, 81(4), 251–267. https://doi.org/10.1016/j.jretai.2004.11.002
   Web of Science ®Google Scholar
• Law, M., Kwok, R. C., & Ng, M. (2016). An extended online purchase intention model for middle-aged online users. Electronic Commerce Research and Applications, 20, 132–146. https://doi.org/10.1016/j.elerap.2016.10.005
   Web of Science ®Google Scholar
• Lee, G., & Lin, H. (2005). Customer perceptions of e-service quality in online shopping. International Journal of Retail & Distribution Management, 33(2), 161–176. https://doi.org/10.1108/09590550510581485
   Google Scholar
• Leeraphong, A., & Mardjo, A. (2013). Trust and risk in purchase intention through online social network: A Focus Group Study of Facebook in Thailand. Journal of Economics, Business and Management, 1(4), 314–318. https://doi.org/10.7763/JOEBM.2013.V1.68
   Google Scholar
• Lee, C. H., & Wu, J. J. (2017). Consumer online flow experience: The relationship between utilitarian and hedonic value, satisfaction and unplanned purchase. Industrial Management & Data Systems, 117(10), 2452–2467. https://doi.org/10.1108/IMDS-11-2016-0500
   Web of Science ®Google Scholar
• Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252–260. https://doi.org/10.1016/j.ijinfomgt.2010.07.006
   Web of Science ®Google Scholar
• Lissitsa, S., & Kol, O. (2016). Generation X vs. generation Y – A decade of online shopping. Journal of Retailing and Consumer Services, 31(31), 304–312. https://doi.org/10.1016/j.jretconser.2016.04.015
   Google Scholar
• Lu, J., Yu, C., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. https://doi.org/10.1108/10662240310478222
   Web of Science ®Google Scholar
• Luk, S. T. K., & Yip, L. S. (2008). The moderator effect of monetary sales promotion on the relationship between brand trust and purchase behaviour. Journal of Brand Management, 15(6), 452–464. https://doi.org/10.1057/bm.2008.12
   Google Scholar
• Magnusson, P., Peterson, R., & A. Westjohn, S. (2014). The influence of national cultural values on the use of rewards alignment to improve sales collaboration. International Marketing Review, 31(1), 30–50. https://doi.org/10.1108/IMR-09-2012-0151
   Web of Science ®Google Scholar
• Manis, K. T., & Choi, D. (2019). The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. Journal of Business Research, 100, 503–513. https://doi.org/10.1016/j.jbusres.2018.10.021
   Web of Science ®Google Scholar
• Martín, S. S., & Camarero, C. (2009). How perceived risk affects online buying. Online Information Review, 33(4), 629–654. https://doi.org/10.1108/14684520910985657
   Web of Science ®Google Scholar
• Massey, M., O’Cass, A., & Otahal, P. (2018). A meta-analytic study of the factors driving the purchase of organic food. Appetite, 125, 418–427. https://doi.org/10.1016/j.appet.2018.02.029
   PubMed Web of Science ®Google Scholar
• Mavlanova, T., Benbunan-Fich, R., & Lang, G. (2016). The role of external and internal signals in E-commerce. Decision Support Systems, 87, 59–68. https://doi.org/10.1016/j.dss.2016.04.009
   Web of Science ®Google Scholar
• McCloskey, D. W. (2006). The importance of ease of use, usefulness, and trust to online consumers. Journal of Organizational and End User Computing, 18(3), 47–65. https://doi.org/10.4018/joeuc.2006070103
   Google Scholar
• Meskaran, F., Ismail, Z., & Shanmugam, B. (2013). Online purchase intention: Effects of trust and security perception. Australian Journal of Basic and Applied Sciences, 7(6), 307–315.
   Google Scholar
• Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4(4), 229. https://doi.org/10.1086/208701
   Web of Science ®Google Scholar
• Mishra, M. (2017). For Indian online shoppers, have saying and doing parted ways? Psychology & Marketing, 35(1), 5–19. https://doi.org/10.1002/mar.21067
   Web of Science ®Google Scholar
• Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer Affairs, 35(1), 27–44. https://doi.org/10.1111/j.1745-6606.2001.tb00101.x
   Web of Science ®Google Scholar
• Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Physical Therapy, 339(jul21 1), b2535–b2535. https://doi.org/10.1136/bmj.b2535
   Google Scholar
• Moslehpour, M., Pham, V., Wong, W.-K., & Bilgiçli, İ. (2018). E-purchase intention of taiwanese consumers: Sustainable mediation of perceived usefulness and perceived ease of use. Sustainability, 10(1), 234. https://doi.org/10.3390/su10010234
   Web of Science ®Google Scholar
• Mukherjee, A., & Nath, P. (2007). Role of electronic trust in online retailing. European Journal of Marketing, 41(9/10), 1173–1202. https://doi.org/10.1108/03090560710773390
   Web of Science ®Google Scholar
• Mummalaneni, V., & Meng, J. (.). (2009). An exploratory study of young Chinese customers’ online shopping behaviours and service quality perceptions. Young Consumers, 10(2), 157–169. https://doi.org/10.1108/17473610910964732
   Google Scholar
• Nath, R., & Murthy, N. R. V. (2004). A study of the relationship between internet diffusion and culture. Journal of International Information Management, 13(2), 123–132. https://scholarworks.lib.csusb.edu/jiim/vol13/iss2/5/
   Google Scholar
• Nawi, N. C., Mamun, A. A., Hamsani, N. H. B., & Muhayiddin, M. N. B. (2019). Effect of consumer demographics and risk factors on online purchase behaviour in Malaysia. Societies, 9(1), 10. https://doi.org/10.3390/soc9010010
   Web of Science ®Google Scholar
• Noh, M., Runyan, R., & Mosier, J. (2014). Young consumers’ innovativeness and hedonic/utilitarian cool attitudes. International Journal of Retail & Distribution Management, 42(4), 267–280. https://doi.org/10.1108/IJRDM-07-2012-0065
   Google Scholar
• Obal, M., & Kunz, W. (2013). Trust development in e-services: A cohort analysis of Millennials and Baby Boomers. Journal of Service Management, 24(1), 45–63. https://doi.org/10.1108/09564231311304189
   Web of Science ®Google Scholar
• O’Cass, A., & Carlson, J. (2012). An e-retailing assessment of perceived website-service innovativeness: Implications for website quality evaluations, trust, loyalty and word of mouth. Australasian Marketing Journal (AMJ), 20(1), 28–36. https://doi.org/10.1016/j.ausmj.2011.10.012
   Google Scholar
• Pahari, S., Ghosal, I., Prasad, B., & Dildar, S. M. (2023). Which determinants impact consumer purchase behavior toward online purchasing of organic food products? Prabandhan: Indian Journal of Management, 16(1), 25–41. https://doi.org/10.17010/pijom/2023/v16i1/172667
   Google Scholar
• Pan, Z., Lu, Y., Wang, B., & Chau, P. Y. K. (2017). Who do you think you are? Common and differential effects of social self-identity on social media usage. Journal of Management Information Systems, 34(1), 71–101. https://doi.org/10.1080/07421222.2017.1296747
   Web of Science ®Google Scholar
• Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320. https://doi.org/10.1177/109467050024001
   Google Scholar
• Parasuraman, A., & Colby, C. L. (2014). An updated and streamlined technology readiness index. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730
   Web of Science ®Google Scholar
• Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105. https://doi.org/10.2307/25148783
   Web of Science ®Google Scholar
• Peinkofer, S. T., Esper, T. L., & Howlett, E. (2016). Hurry! sale ends soon: The impact of limited inventory availability disclosure on consumer responses to online stockouts. Journal of Business Logistics, 37(3), 231–246. https://doi.org/10.1111/jbl.12136
   Web of Science ®Google Scholar
• Peña-García, N., Gil-Saura, I., Rodríguez-Orejuela, A., & Siqueira-Junior, J. R. (2020). Purchase intention and purchase behaviour online: A cross-cultural approach. Heliyon, 6(6), e04284. https://doi.org/10.1016/j.heliyon.2020.e04284
   PubMed Web of Science ®Google Scholar
• Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. The Journal of Applied Psychology, 90(1), 175–181. https://doi.org/10.1037/0021-9010.90.1.175
   PubMed Web of Science ®Google Scholar
• Pranckute, R. (2021). Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications, 9(1), 12. https://doi.org/10.3390/publications9010012
   Web of Science ®Google Scholar
• Prashar, S., Sai Vijay, T., & Parsad, C. (2017). Effects of online shopping values and website cues on purchase behaviour: A study using S–O–R framework. Vikalpa: The Journal for Decision Makers, 42(1), 1–18. https://doi.org/10.1177/0256090916686681
   Google Scholar
• Raijas, A., & Tuunainen, V. K. (2001). Critical factors in electronic grocery shopping. The International Review of Retail, Distribution and Consumer Research, 11(3), 255–265. https://doi.org/10.1080/713770596
   Google Scholar
• Rana, S., Bag, S., Ghosal, I., & Prasad, B. (2023). How do influencers moderate purchase motives? An application of S-O-R model to assess the effects of reviewers’ rating on online purchase. Journal of Promotion Management, 29(8), 1168–1197. https://doi.org/10.1080/10496491.2023.2216292
   Google Scholar
• Rana, N. P., Dwivedi, Y. K., & Williams, M. D. (2013). A meta-analysis of existing research on citizen adoption of e-government. Information Systems Frontiers, 17(3), 547–563. https://doi.org/10.1007/s10796-013-9431-z
   Web of Science ®Google Scholar
• Ranaweera, C., Bansal, H., & McDougall, G. (2008). Web site satisfaction and purchase intentions. Managing Service Quality: An International Journal, 18(4), 329–348. https://doi.org/10.1108/09604520810885590
   Google Scholar
• Ranganathan, C., & Grandón, E. E. (2002). An exploratory examination of factors affecting online sales. Journal of Computer Information Systems, 42(3), 87–93. https://doi.org/10.1080/08874417.2002.11647507
   Web of Science ®Google Scholar
• Rašković, M., Ding, Z., Škare, V., Ozretić Došen, Đ., & Žabkar, V. (2016). Comparing consumer innovativeness and ethnocentrism of young adult consumers. Journal of Business Research, 69(9), 3682–3686. https://doi.org/10.1016/j.jbusres.2016.03.029
   Web of Science ®Google Scholar
• Ray, S., Kim, S. S., & Morris, J. G. (2014). The central role of engagement in online communities. Information Systems Research, 25(3), 528–546. https://doi.org/10.1287/isre.2014.0525
   Web of Science ®Google Scholar
• Reinartz, W., Wiegand, N., & Imschloss, M. (2019). The impact of digital transformation on the retailing value chain. International Journal of Research in Marketing, 36(3), 350–366. https://doi.org/10.1016/j.ijresmar.2018.12.002
   Web of Science ®Google Scholar
• Rita, P., Oliveira, T., & Farisa, A. (2019). The impact of e-service quality and customer satisfaction on customer behaviour in online shopping. Heliyon, 5(10), e02690. https://doi.org/10.1016/j.heliyon.2019.e02690
   PubMed Web of Science ®Google Scholar
• Rosenthal, R. (1979). Psychological bulletin. Psycnet.apa.org, 86(3), 638–641. https://doi.org/10.1037/0033-2909.86.3.638
   Google Scholar
• Ruiz Mafé, C., & Sanz Blas, S. (2006). Explaining internet dependency. Internet Research, 16(4), 380–397. https://doi.org/10.1108/10662240610690016
   Web of Science ®Google Scholar
• Salem, S. F., & Alanadoly, A. B. (2022). What drives Malaysian online fashion shopping? The mediating role of perceived value. Journal of Global Fashion Marketing, 13(1), 75–89. https://doi.org/10.1080/20932685.2021.1978308
   Web of Science ®Google Scholar
• San-Martín, S., Jiménez, N., & Liébana-Cabanillas, F. (2020). Tourism value VS barriers to booking trips online. Journal of Retailing and Consumer Services, 53, 101957. https://doi.org/10.1016/j.jretconser.2019.101957
   Web of Science ®Google Scholar
• Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216. https://doi.org/10.1016/j.elerap.2009.07.005
   Web of Science ®Google Scholar
• See-To, E. W. K., & Ho, K. K. W. (2014). Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust – A theoretical analysis. Computers in Human Behavior, 31(1), 182–189. https://doi.org/10.1016/j.chb.2013.10.013
   Web of Science ®Google Scholar
• Shaouf, A., & Altaqqi, O. (2018). The impact of gender differences on adoption of information technology and related responses: A review. International Journal of Management and Applied Research, 5(1), 22–41. http://www.ijmar.org/v5n1/18-003.html https://doi.org/10.18646/2056.51.18-003
   Google Scholar
• Shin, D. H. (2009). Towards an understanding of the consumer acceptance of mobile wallets. Computers in Human Behavior, 25(6), 1343–1354. https://doi.org/10.1016/j.chb.2009.06.001
   Web of Science ®Google Scholar
• Silva, S. C., Rocha, T. V., De Cicco, R., Galhanone, R. F., & Manzini Ferreira Mattos, L. T. (2020). Need for touch and haptic imagery: An investigation in online fashion shopping. Journal of Retailing and Consumer Services, 59, 102378. https://doi.org/10.1016/j.jretconser.2020.102378
   Web of Science ®Google Scholar
• Snoj, B., Pisnik Korda, A., & Mumel, D. (2004). The relationships among perceived quality, perceived risk and perceived product value. Journal of Product & Brand Management, 13(3), 156–167. https://doi.org/10.1108/10610420410538050
   Google Scholar
• Soares, J. C., Limongi, R., De Sousa Júnior, J. H., Santos, W. S., Raasch, M., & Hoeckesfeld, L. (2023). Assessing the effects of COVID-19-related risk on online shopping behaviour. Journal of Marketing Analytics, 11(1), 82–94. https://doi.org/10.1057/s41270-022-00156-9
   Google Scholar
• Sobieraj, S., & Krämer, N. C. (2020). Similarities and differences between genders in the usage of computers with different levels of technological complexity. Computers in Human Behavior, 104, 106145. https://doi.org/10.1016/j.chb.2019.09.021
   Web of Science ®Google Scholar
• Sorce, P., Perotti, V., & Widrick, S. (2005). Attitude and age differences in online buying. International Journal of Retail & Distribution Management, 33(2), 122–132. https://doi.org/10.1108/09590550510581458
   Google Scholar
• Sukno, R., & Pascual del Riquelme, I. (2019). E-Commerce C2C en Chile: Incorporación de La Reputación y de la Confianza en El TAM. Journal of Technology Management & Innovation, 14(3), 72–81. https://doi.org/10.4067/S0718-27242019000300072
   Google Scholar
• Tan, Q., & Sousa, C. M. P. (2015). Leveraging marketing capabilities into competitive advantage and export performance. International Marketing Review, 32(1), 78–102. https://doi.org/10.1108/IMR-12-2013-0279
   Web of Science ®Google Scholar
• Teas, R. K., & Agarwal, S. (2000). The effects of extrinsic product cues on consumers’ perceptions of quality, sacrifice, and value. Journal of the Academy of Marketing Science, 28(2), 278–290. https://doi.org/10.1177/0092070300282008
   Web of Science ®Google Scholar
• Teo, T. S. H. (2002). Attitudes toward online shopping and the Internet. Behaviour & Information Technology, 21(4), 259–271. https://doi.org/10.1080/0144929021000018342
   Web of Science ®Google Scholar
• Teo, T., & Liu, J. (2007). Consumer trust in e-commerce in the United States, Singapore and China. Omega, 35(1), 22–38. https://doi.org/10.1016/j.omega.2005.02.001
   Web of Science ®Google Scholar
• Thakur, R., & Srivastava, M. (2015). A study on the impact of consumer risk perception and innovativeness on online shopping in India. International Journal of Retail & Distribution Management, 43(2), 148–166. https://doi.org/10.1108/IJRDM-06-2013-0128
   Web of Science ®Google Scholar
• Tormala, Z. L., & Rucker, D. D. (2017). Attitude certainty: Antecedents, consequences, and new directions. Consumer Psychology Review, 1(1), 72–89. https://doi.org/10.1002/arcp.1004
   Google Scholar
• Truong, D., & Truong, M. D. (2022). How do customers change their purchasing behaviours during the COVID-19 pandemic? Journal of Retailing and Consumer Services, 67, 102963. https://doi.org/10.1016/j.jretconser.2022.102963
   Web of Science ®Google Scholar
• Tsai, Y. C. T., & Yeh, J. C. (2010). Perceived risk of information security and privacy in online shopping: A study of environmentally sustainable products. African Journal of Business Management, 4(18), 4057–4066.
   Google Scholar
• Turban, E., King, D., Lee, J. K., Liang, T.-P., & Turban, D. C. (2015). Electronic commerce: A managerial and social networks perspective (8th ed.). Springer International Publishing.
   Google Scholar
• Tyrväinen, O., Karjaluoto, H., & Saarijärvi, H. (2020). Personalization and hedonic motivation in creating customer experiences and loyalty in omnichannel retail. Journal of Retailing and Consumer Services, 57, 102233. https://doi.org/10.1016/j.jretconser.2020.102233
   Web of Science ®Google Scholar
• Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: contributions from technology and trust perspectives. European Journal of Information Systems, 12(1), 41–48. https://doi.org/10.1057/palgrave.ejis.3000445
   Web of Science ®Google Scholar
• Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, Social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139. https://doi.org/10.2307/3250981
   Web of Science ®Google Scholar
• Ventre, I., & Kolbe, D. (2020). The impact of perceived usefulness of online reviews, trust and perceived risk on online purchase intention in emerging markets: A Mexican perspective. Journal of International Consumer Marketing, 32(4), 287–299. https://doi.org/10.1080/08961530.2020.1712293
   Web of Science ®Google Scholar
• Verhagen, T., & van Dolen, W. (2009). Online purchase intentions: A multi-channel store image perspective. Information & Management, 46(2), 77–82. https://doi.org/10.1016/j.im.2008.12.001
   Web of Science ®Google Scholar
• Wang, S., Beatty, S. E., & Mothersbaugh, D. L. (2009). Congruity’s role in website attitude formation. Journal of Business Research, 62(6), 609–615. https://doi.org/10.1016/j.jbusres.2008.05.020
   Web of Science ®Google Scholar
• Wang, Y., & Herrando, C. (2019). Does privacy assurance on social commerce sites matter to millennials? International Journal of Information Management, 44, 164–177. https://doi.org/10.1016/j.ijinfomgt.2018.10.016
   Web of Science ®Google Scholar
• Wang, M. C. H., Wang, E. S. T., Cheng, J. M. S., & Chen, A. F. L. (2009). Information quality, online community and trust: a study of antecedents to shoppers’ website loyalty. International Journal of Electronic Marketing and Retailing, 2(3), 203. https://doi.org/10.1504/IJEMR.2009.021806
   Google Scholar
• Wang, Q., Yang, X., & Xi, W. (2018). Effects of group arguments on rumour belief and transmission in online communities: An information cascade and group polarization perspective. Information & Management, 55(4), 441–449. https://doi.org/10.1016/j.im.2017.10.004
   Web of Science ®Google Scholar
• Wani, T., & Wajid, S. (2016). Determinants of online purchase intentions: A study of Indian Buyers. Amity Journal of Management Research AJMR Amity Journal of Management Research, 1(1), 94–109.
   Google Scholar
• Wells, J. D., Valacich, J. S., & Hess, T. J. (2011). What signal are you sending? How website quality influences perceptions of product quality and purchase intentions. MIS Quarterly, 35(2), 373. https://doi.org/10.2307/23044048
   Web of Science ®Google Scholar
• Wen, I. (2012). An empirical study of an online travel purchase intention model. Journal of Travel & Tourism Marketing, 29(1), 18–39. https://doi.org/10.1080/10548408.2012.638558
   Web of Science ®Google Scholar
• Wolf, F. M. (1986). Meta-analysis: Quantitative applications in the social sciences. SAGE Publications, Inc. methods.sagepub.com https://doi.org/10.4135/9781412984980
   Google Scholar
• Wolfinbarger, M., & Gilly, M. C. (2003). eTailQ: Dimensionalizing, measuring and predicting etail quality. Journal of Retailing, 79(3), 183–198. https://doi.org/10.1016/s0022-4359(03)00034-4
   Web of Science ®Google Scholar
• Wood, C., Conner, M., Miles, E., Sandberg, T., Taylor, N., Godin, G., & Sheeran, P. (2015). The impact of asking intention or self-prediction questions on subsequent behavior. Personality and Social Psychology Review, 20(3), 245–268. https://doi.org/10.1177/1088868315592334
   PubMed Web of Science ®Google Scholar
• Wu, S. (2003). The relationship between consumer characteristics and attitude toward online shopping. Marketing Intelligence & Planning, 21(1), 37–44. https://doi.org/10.1108/02634500310458135
   Google Scholar
• Wu, J. J., Hwang, J.-N., Sharkhuu, O., & Tsogt-Ochir, B. (2018). Shopping online and offline? Complementary service quality and image congruence. Asia Pacific Management Review, 23(1), 30–36. https://doi.org/10.1016/j.apmrv.2017.01.004
   Web of Science ®Google Scholar
• Yu, S., Hudders, L., & Cauberghe, V. (2018). Are fashion consumers like schooling fish? The effectiveness of popularity cues in fashion e-commerce. Journal of Business Research, 85, 105–116. https://doi.org/10.1016/j.jbusres.2017.12.035
   Web of Science ®Google Scholar
• Yuen, K. F., Wang, X., Wong, Y. D., & Zhou, Q. (2018). The effect of sustainable shipping practices on shippers’ loyalty: The mediating role of perceived value, trust and transaction cost. Transportation Research Part E: Logistics and Transportation Review, 116, 123–135. https://doi.org/10.1016/j.tre.2018.06.002
   Web of Science ®Google Scholar
• Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302
   Web of Science ®Google Scholar
• Zhang, Y. (2005). Age, gender, and Internet attitudes among employees in the business world. Computers in Human Behavior, 21(1), 1–10. https://doi.org/10.1016/j.chb.2004.02.006
   Web of Science ®Google Scholar
• Zhang, F., Sun, S., Liu, C., & Chang, V. (2020). Consumer innovativeness, product innovation and smart toys. Electronic Commerce Research and Applications, 41, 100974. https://doi.org/10.1016/j.elerap.2020.100974
   Web of Science ®Google Scholar
• Zhao, X., Deng, S., & Zhou, Y. (2017). The impact of reference effects on online purchase intention of agricultural products. Internet Research, 27(2), 233–255. https://doi.org/10.1108/IntR-03-2016-0082
   Web of Science ®Google Scholar
• Zhao, H., Wang, X., & Jiang, L. (2021). To purchase or to remove? Online shopping cart warning pop-up messages can polarize liking and purchase intention. Journal of Business Research, 132(2021), 813–836. https://doi.org/10.1016/j.jbusres.2020.10.067
   Google Scholar