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Cited by 54Technology Adoption and User BehaviourConsumer Behavior and Marketing InfluenceE-commerce and Technology Innovations

The Role of Platform Quality on Consumer Purchase Intention in the Context of Cross-Border E-Commerce: The Evidence from Africa

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Han, Lintong, Ma, Yuehuan, Addo, Prince Clement, Liao, Miyan, Fang, Jiaming·2023·Behavioral Sciences
DOI 10.3390/bs13050385PMC PMC10215088
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Abstract

Africa, as one of the rapidly growing markets, presents a significant opportunity for cross-border e-commerce companies to penetrate their consumer market, which is in dire need of development. This study utilizes the Information System Success model to investigate the impact of cross-border e-commerce platform quality on consumers’ purchase intentions. Additionally, the study identifies the role of perceived value and trust in the purchase process. Moreover, the moderating effect of consumer acculturation on the relationship between cross-border platform quality and perceived value is examined. A total of 446 valid responses were obtained through a questionnaire survey and analyzed using structural equations. The findings reveal that platform information quality, system quality, and service quality significantly enhance consumers’ perceived value, thereby positively influencing their purchase intention. Furthermore, the results highlight the joint effect of perceived value and trust on purchase intention, and trust plays a mediating role in this relationship. The moderating effect of acculturation is also confirmed, indicating that it negatively moderates the impact of system and information quality on perceived value, while positively moderating the impact of service quality on perceived value. These findings complement and extend existing cross-border e-commerce research and provide valuable insights into the buying behavior of African consumers.

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  1. Cheng, 2019, Designing a talents training model for cross-border e-commerce: A mixed approach of problem-based learning with social media, Electron. Commer. Res., 19, 801, 10.1007/s10660-019-09341-y · DOI
  2. Pencea, 2017, A look into the complexities of the one belt, one road strategy, Glob. Econ. Obs., 5, 142
  3. Hoque, M., and Bashaw, R.E. (2020). Cross-Border E-Commerce Marketing and Management, IGI Global. · DOI
  4. Hazarika, 2021, Review of cross-border E-commerce and directions for future research, J. Glob. Inf. Manag., 30, 1, 10.4018/JGIM.20220301.oa1 · DOI
  5. Signé, L. (2023). Africa’s Fourth Industrial Revolution, Cambridge University Press. · DOI
  6. Manteaw, 2012, Education for sustainable development in Africa: The search for pedagogical logic, Int. J. Educ. Dev., 32, 376, 10.1016/j.ijedudev.2011.08.005 · DOI
  7. Dirgantari, 2020, Level of use and satisfaction of e-commerce customers in COVID-19 pandemic period: An information system success model (ISSM) approach, Indones. J. Sci. Technol., 5, 261, 10.17509/ijost.v5i2.24617 · DOI
  8. Kumar, 2021, E-retail factors for customer activation and retention: An empirical study from Indian e-commerce customers, J. Retail. Consum. Serv., 59, 1, 10.1016/j.jretconser.2020.102399 · DOI
  9. DeLone, 2003, The DeLone and McLean model of information systems success: A ten-year update, J. Manag. Inf. Syst., 19, 9, 10.1080/07421222.2003.11045748 · DOI · Paper page
  10. DeLone, 2004, Measuring e-commerce success: Applying the DeLone & McLean information systems success model, Int. J. Electron. Commer., 9, 31, 10.1080/10864415.2004.11044317 · DOI
  11. Das, 2020, Impact of acculturation to western culture (AWC) on western fashion luxury consumption among Gen-Y consumers in the Asia-Pacific region, J. Retail. Consum. Serv., 56, 1, 10.1016/j.jretconser.2020.102179 · DOI
  12. Cheetham, 2021, Consumer multiculturation in multicultural marketplaces: Mexican immigrants’ responses to the global consumer culture construction of Tex-Mex as Mexican food, J. Bus. Res., 134, 70, 10.1016/j.jbusres.2021.05.012 · DOI
  13. Shen, 2018, Domestic tourism of Chinese in Canada: Distinct differences, J. Destin. Mark. Manag., 8, 125
  14. Kizgin, 2018, The impact of social media on consumers’ acculturation and purchase intentions, Inf. Syst. Front., 20, 503, 10.1007/s10796-017-9817-4 · DOI
  15. Lacka, E., Chan, H.K., and Yip, N. (2014). E-Commerce Platform Acceptance: Suppliers, Retailers, and Consumers, Springer. · DOI
  16. Levy, 2021, Engagement of ethnic-minority consumers with electronic word of mouth (eWOM) on social media: The pivotal role of intercultural factors, J. Theor. Appl. Electron. Commer. Res., 16, 2608, 10.3390/jtaer16070144 · DOI
  17. Zhu, 2019, Exploring purchase intention in cross-border E-commerce: A three stage model, J. Retail. Consum. Serv., 51, 320, 10.1016/j.jretconser.2019.07.004 · DOI
  18. Cui, 2019, Understanding information system success model and valence framework in sellers’ acceptance of cross-border e-commerce: A sequential multi-method approach, Electron. Commer. Res., 19, 885, 10.1007/s10660-019-09331-0 · DOI
  19. Deng, 2016, Early-mover advantages at cross-border business-to-business e-commerce portals, J. Bus. Res., 69, 6002, 10.1016/j.jbusres.2016.05.015 · DOI
  20. Ai, 2016, Revelation of cross-border logistics performance for the manufacturing industry development, Int. J. Mob. Commun., 14, 593, 10.1504/IJMC.2016.079302 · DOI
  21. Gao, 2021, Intelligent Prediction Algorithm of Cross-Border E-Commerce Logistics Cost Based on Cloud Computing, Sci. Program., 2021, 1
  22. Zhang, 2021, An optimization model for logistics distribution network of cross-border e-commerce based on personalized recommendation algorithm, Secur. Commun. Netw., 2021, 1
  23. Liu, C., Wu, J., and Lakshika Jayetileke, H. (2022). Overseas Warehouse Deployment for Cross-Border E-Commerce in the Context of the Belt and Road Initiative. Sustainability, 14. · DOI
  24. Shi, 2022, Design of the cost allocation rule for joint replenishment to an overseas warehouse with a piecewise linear holding cost rate, Oper. Res., 22, 4905
  25. Chen, 2021, Optimization model of cross-border E-commerce payment security by blockchain finance, Wirel. Commun. Mob. Comput., 2021, 9192219, 10.1155/2021/9192219 · DOI
  26. Fang, 2021, Cross-border E-commerce supply chain risk evaluation with FUZZY-ISM model, Secur. Commun. Netw., 2021, 5155524, 10.1155/2021/5155524 · DOI
  27. Huang, 2022, Influence of Cultural Differences on the Establishment of Consumer Trust in a Socialized Cross-Border E-Commerce, Mob. Inf. Syst., 2022, 9952335
  28. Huang, 2019, Cross-border e-commerce: Consumers’ intention to shop on foreign websites, Internet Res., 29, 1256, 10.1108/INTR-11-2017-0428 · DOI
  29. Xiao, L., Guo, F., Yu, F., and Liu, S. (2019). The effects of online shopping context cues on consumers’ purchase intention for cross-border E-Commerce sustainability. Sustainability, 11. · DOI
  30. Chen, 2017, Mechanism of government policies in cross-border e-commerce on firm performance and implications on m-commerce, Int. J. Mob. Commun., 15, 69, 10.1504/IJMC.2017.080578 · DOI
  31. Qiu, 2022, The Impact of Government Behavior on the Development of Cross-Border E-Commerce B2B Export Trading Enterprises Based on Evolutionary Game in the Context of “Dual-Cycle” Policy, J. Theor. Appl. Electron. Commer. Res., 17, 1741, 10.3390/jtaer17040088 · DOI
  32. Ma, 2018, Rise of Cross-border E-commerce Exports in China, China World Econ., 26, 63, 10.1111/cwe.12243 · DOI
  33. Martens, 2014, The drivers and impediments for cross-border e-commerce in the EU, Inf. Econ. Policy, 28, 83, 10.1016/j.infoecopol.2014.05.002 · DOI
  34. 2022, Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model, World Econ., 45, 251, 10.1111/twec.13140 · DOI
  35. DeLone, 1992, Information systems success: The quest for the dependent variable, Inf. Syst. Res., 3, 60, 10.1287/isre.3.1.60 · DOI · Paper page
  36. Aparicio, 2019, Gamification: A key determinant of massive open online course (MOOC) success, Inf. Manag., 56, 39, 10.1016/j.im.2018.06.003 · DOI
  37. Baabdullah, 2019, Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model, Int. J. Inf. Manag., 44, 38, 10.1016/j.ijinfomgt.2018.09.002 · DOI
  38. Chatterjee, 2018, Success of IoT in smart cities of India: An empirical analysis, Gov. Inf. Q., 35, 349, 10.1016/j.giq.2018.05.002 · DOI
  39. Isaac, 2019, Online learning usage within Yemeni higher education: The role of compatibility and task-technology fit as mediating variables in the IS success model, Comput. Educ., 136, 113, 10.1016/j.compedu.2019.02.012 · DOI
  40. Sharma, 2019, Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation, Int. J. Inf. Manag., 44, 65, 10.1016/j.ijinfomgt.2018.09.013 · DOI
  41. Xu, 2018, Factors influencing users’ satisfaction and loyalty to digital libraries in Chinese universities, Comput. Hum. Behav., 83, 64, 10.1016/j.chb.2018.01.029 · DOI
  42. Joy, 2020, Evaluating E-learning systems success: An empirical study, Comput. Hum. Behav., 102, 67, 10.1016/j.chb.2019.08.004 · DOI · Paper page
  43. Sarkar, 2020, A meta-analysis of antecedents and consequences of trust in mobile commerce, Int. J. Inf. Manag., 50, 286, 10.1016/j.ijinfomgt.2019.08.008 · DOI · Paper page
  44. Santa, 2019, The role of trust in e-Government effectiveness, operational effectiveness and user satisfaction: Lessons from Saudi Arabia in e-G2B, Gov. Inf. Q., 36, 39, 10.1016/j.giq.2018.10.007 · DOI
  45. Wang, 2008, Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success, Inf. Syst. J., 18, 529, 10.1111/j.1365-2575.2007.00268.x · DOI
  46. Redfield, 1936, Memorandum for the study of acculturation, Am. Anthropol., 38, 149, 10.1525/aa.1936.38.1.02a00330 · DOI
  47. Veroff, 1995, Psychology of acculturation, The Culture and Psychology Reader, Volume 3, 457
  48. Cleveland, 2007, Acculturaton to the global consumer culture: Scale development and research paradigm, J. Bus. Res., 60, 249, 10.1016/j.jbusres.2006.11.006 · DOI
  49. Riddle, 2011, Diaspora entrepreneurs as institutional change agents: The case of Thamel. com, Int. Bus. Rev., 20, 670, 10.1016/j.ibusrev.2011.02.013 · DOI
  50. Wang, 1996, Beyond accuracy: What data quality means to data consumers, J. Manag. Inf. Syst., 12, 5, 10.1080/07421222.1996.11518099 · DOI · Paper page
  51. Kim, 2013, A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention, Decis. Support Syst., 56, 361, 10.1016/j.dss.2013.07.002 · DOI
  52. Sproles, 1978, Informational inputs as influences on efficient consumer decision-making, J. Consum. Aff., 12, 88, 10.1111/j.1745-6606.1978.tb00635.x · DOI
  53. Tam, 2004, Customer satisfaction, service quality and perceived value: An integrative model, J. Mark. Manag., 20, 897, 10.1362/0267257041838719 · DOI
  54. Lin, 2021, Factors influencing consumers’ continuous purchase intention on fresh food e-commerce platforms: An organic foods-centric empirical investigation, Electron. Commer. Res. Appl., 50, 1, 10.1016/j.elerap.2021.101103 · DOI
  55. Saha, 2012, Evaluation of government e-tax websites: An information quality and system quality approach, Transform. Gov. People Process Policy, 6, 300
  56. Gorla, 2010, Organizational impact of system quality, information quality, and service quality, J. Strateg. Inf. Syst., 19, 207, 10.1016/j.jsis.2010.05.001 · DOI
  57. Park, 2003, Identifying key factors affecting consumer purchase behavior in an online shopping context, Int. J. Retail. Distrib. Manag., 31, 16, 10.1108/09590550310457818 · DOI · Paper page
  58. Suh, 2014, A Study on Consumers’ regulatory focus as a determinant of perceived value of online shopping mall VMD, Manag. Inf. Syst. Rev., 33, 213
  59. Zhou, 2013, An empirical examination of continuance intention of mobile payment services, Decis. Support Syst., 54, 1085, 10.1016/j.dss.2012.10.034 · DOI
  60. Zeithaml, V.A., Bitner, M.J., and Gremler, D.D. (2006). Services Marketing: Integrating Customer Focus across the Firm, McGraw-Hill/Irwin.
  61. Lai, 2014, The role of service quality, perceived value, and relationship quality in enhancing customer loyalty in the travel agency sector, J. Travel Tour. Mark., 31, 417, 10.1080/10548408.2014.883346 · DOI
  62. Lo, 2014, Effect of consumption emotion on hotel and resort spa experience, J. Travel Tour. Mark., 31, 958, 10.1080/10548408.2014.895692 · DOI
  63. Fang, 2019, Polluted online reviews: The effect of air pollution on reviewer behavior, Int. J. Electron. Commer., 23, 557, 10.1080/10864415.2019.1655206 · DOI
  64. Andreu, 2004, Emotions in segmentation: An empirical study, Ann. Tour. Res., 31, 682, 10.1016/j.annals.2003.12.018 · DOI
  65. Lin, 2012, Effects of authenticity perception, hedonics, and perceived value on ceramic souvenir-repurchasing intention, J. Travel Tour. Mark., 29, 779, 10.1080/10548408.2012.730941 · DOI
  66. Yang, 2011, Festival tourists’ emotion, perceived value, and behavioral intentions: A test of the moderating effect of festivalscape, J. Conv. Event Tour., 12, 25, 10.1080/15470148.2010.551292 · DOI
  67. Babin, 1994, Work and/or fun: Measuring hedonic and utilitarian shopping value, J. Consum. Res., 20, 644, 10.1086/209376 · DOI · Paper page
  68. Ogden, 2004, Exploring the impact of culture and acculturation on consumer purchase decisions: Toward a microcultural perspective, Acad. Mark. Sci. Rev., 3, 1
  69. Fang, 2013, The equivalence of Internet versus paper-based surveys in IT/IS adoption research in collectivistic cultures: The impact of satisficing, Behav. Inf. Technol., 32, 480, 10.1080/0144929X.2012.751621 · DOI
  70. Chen, 2021, Antecedents and consequence of the consumer’s psychic distance in cross-border e-commerce, Int. Trade Politics Dev., 5, 156, 10.1108/ITPD-08-2021-0008 · DOI
  71. Czarnecka, 2019, Do consumers acculturated to global consumer culture buy more impulsively? The moderating role of attitudes towards and beliefs about advertising, J. Glob. Mark., 32, 219, 10.1080/08911762.2019.1600094 · DOI
  72. Lv, 2018, How do sellers use live chat to influence consumer purchase decision in China?, Electron. Commer. Res. Appl., 28, 102, 10.1016/j.elerap.2018.01.003 · DOI
  73. Chai, 2014, How consumer acculturation influences interpersonal trust, J. Mark. Manag., 30, 60, 10.1080/0267257X.2013.803140 · DOI
  74. Miocevic, 2020, Acculturation of expatriate consumers: Conditional effects of mental attachments to home country, J. Glob. Mark., 33, 193, 10.1080/08911762.2019.1710642 · DOI
  75. Uslu, 2013, Word of mouth, brand loyalty, acculturation and the Turkish ethnic minority group in Germany, Procedia-Soc. Behav. Sci., 99, 455, 10.1016/j.sbspro.2013.10.514 · DOI
  76. Davis, 2017, Service quality and acculturation: Advancing immigrant healthcare utilization, J. Serv. Mark., 31, 362, 10.1108/JSM-03-2016-0118 · DOI
  77. Steenkamp, 2006, How country characteristics affect the perceived value of web sites, J. Mark., 70, 136, 10.1509/jmkg.70.3.136 · DOI · Paper page
  78. Zhuang, 2010, The impact of perceived value on behavior intention: An empirical study, J. Glob. Bus. Manag., 6, 1
  79. Mathwick, 2001, Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment, J. Retail., 77, 39, 10.1016/S0022-4359(00)00045-2 · DOI
  80. Overby, 2006, The effects of utilitarian and hedonic online shopping value on consumer preference and intentions, J. Bus. Res., 59, 1160, 10.1016/j.jbusres.2006.03.008 · DOI
  81. Dodds, 1991, Effects of price, brand, and store information on buyers’ product evaluations, J. Mark. Res., 28, 307
  82. Chen, 2008, Investigating structural relationships between service quality, perceived value, satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan, Transp. Res. Part A Policy Pract., 42, 709, 10.1016/j.tra.2008.01.007 · DOI
  83. Jin, 2015, The effect of experience quality on perceived value, satisfaction, image and behavioral intention of water park patrons: New versus repeat visitors, Int. J. Tour. Res., 17, 82, 10.1002/jtr.1968 · DOI · Paper page
  84. Lee, 2007, The roles of quality and intermediary constructs in determining festival attendees’ behavioral intention, J. Travel Res., 45, 402, 10.1177/0047287507299566 · DOI
  85. Rossi, 2008, Word-of-mouth communications in marketing: A meta-analytic review of the antecedents and moderators, J. Acad. Mark. Sci., 36, 578, 10.1007/s11747-008-0121-1 · DOI
  86. Han, 2021, Performing arts and sustainable consumption: Influences of consumer perceived value on ballet performance audience loyalty, J. Psychol. Afr., 31, 32, 10.1080/14330237.2020.1871240 · DOI
  87. Rizwan, 2013, Impact of green marketing on purchase intention: An empirical study from Pakistan, Asian J. Empir. Res., 3, 87
  88. Ladhari, 2015, eWOM effects on hotel booking intentions, attitudes, trust, and website perceptions, Int. J. Hosp. Manag., 46, 36, 10.1016/j.ijhm.2015.01.010 · DOI
  89. Ho, 2014, Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust–A theoretical analysis, Comput. Hum. Behav., 31, 182, 10.1016/j.chb.2013.10.013 · DOI
  90. Yang, 2020, Influence of informational factors on purchase intention in social recommender systems, Online Inf. Rev., 44, 417, 10.1108/OIR-12-2016-0360 · DOI
  91. Agarwal, 2015, Food security, productivity, and gender inequality, Oxf. Handb. Food Politics Soc., 861, 273
  92. Baten, 2021, Educational gender inequality in Sub-Saharan Africa: A long-term perspective, Popul. Dev. Rev., 47, 813, 10.1111/padr.12430 · DOI
  93. 2007, Acculturation attitudes: A comparison of measurement methods 1, J. Appl. Soc. Psychol., 37, 1462, 10.1111/j.1559-1816.2007.00222.x · DOI
  94. Kizgin, 2019, The impact of social networking sites on socialization and political engagement: Role of acculturation, Technol. Forecast. Soc. Chang., 145, 503, 10.1016/j.techfore.2018.09.010 · DOI
  95. Gefen, 2000, E-commerce: The role of familiarity and trust, Omega, 28, 725, 10.1016/S0305-0483(00)00021-9 · DOI · Paper page
  96. Dijkstra, 2015, Consistent partial least squares path modeling, MIS Q., 39, 297, 10.25300/MISQ/2015/39.2.02 · DOI · Paper page

Authors
Han, L., Ma, Y., Addo, P. C., Liao, M., & Fang, J.
Affiliations
  • University of Electronic Science and Technology of China (CN)
  • University of Skills Training and Entrepreneurial Development (GH)
Corresponding author
Fang, Jiaming
ORCID
Venue
Behavioral Sciences
Publisher
MDPI AG
Published
2023-05-06
Volume
13
Issue
5
Pages
385
ISSN
2076-328X (ISSN-L)
DOI
10.3390/bs13050385
PMC
PMC10215088
OpenAlex
W4378348491
Cited by
54
References
7
Citations by year
2026: 14 · 2025: 20 · 2024: 16 · 2023: 4
FWCI
13.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Behavioral Sciences (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Centre for West African Studies of University of Electronic Science and Technology of China (CWAS2022060601)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
  • Social Sciences › Business, Management and Accounting › Business and International Management › E-commerce and Technology Innovations
Keywords
cross-border e-commerce, platform quality, purchase intention, perceived value, consumer trust, consumer acculturation, information quality, system quality, service quality, African consumers, DeLone and McLean model

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