IDEAS home Printed from https://ideas.repec.org/r/eee/tefoso/v129y2018icp117-130.html
   My bibliography  Save this item

Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Francisco Liébana-Cabanillas & Nidhi Singh & Zoran Kalinic & Elena Carvajal-Trujillo, 2021. "Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: a multi-analytical approach," Information Technology and Management, Springer, vol. 22(2), pages 133-161, June.
  2. Ramírez-Correa, Patricio & Grandón, Elizabeth E. & Rondán-Cataluña, F. Javier, 2020. "Users segmentation based on the Technological Readiness Adoption Index in emerging countries: The case of Chile," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
  3. Dash, Ganesh & Sharma, Kiran & Yadav, Neha, 2023. "The diffusion of mobile payments: Profiling the adopters and non-adopters, Roger's way," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
  4. Faruk Ahmeti & Burim Prenaj, 2022. "Determinants Affecting Consumer Acceptance and Adoption of Internet Banking in Developing Countries: The case study of Kosovo," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 60-79.
  5. Soriano, José Luis & Mejía-Trejo, Juan, 2022. "Modelado de Ecuaciones Estructurales en el campo de las Ciencias de la Administración [Structural Equations Modeling in the Management Sciences]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 242-263, June.
  6. Brem, Alexander & Viardot, Eric & Nylund, Petra A., 2021. "Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  7. Bölen, Mehmet Cem, 2020. "Exploring the determinants of users’ continuance intention in smartwatches," Technology in Society, Elsevier, vol. 60(C).
  8. Armah, Abdul Karim & Li, Jinfa, 2023. "Generational cohorts’ social media acceptance as a delivery tool in sub-Sahara Africa motorcycle industry: The role of cohort technical know-how in technology acceptance," Technology in Society, Elsevier, vol. 75(C).
  9. Shahidi, Niousha & Tossan, Vesselina & Bourliataux-Lajoinie, Stéphane & Cacho-Elizondo, Silvia, 2022. "Behavioural intention to use a contact tracing application: The case of StopCovid in France," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
  10. Oussama Tounekti & Antonio Ruiz-Martínez & Antonio F. Skarmeta Gomez, 2022. "Research in Electronic and Mobile Payment Systems: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
  11. Simona Sternad Zabukovšek & Zoran Kalinic & Samo Bobek & Polona Tominc, 2019. "SEM–ANN based research of factors’ impact on extended use of ERP systems," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 703-735, September.
  12. Tang, Jia-Wei & Tsai, Pei-Hsuan, 2024. "Exploring critical determinants influencing businesses’ continuous usage of mobile payment in post-pandemic era: Based on the UTAUT2 perspective," Technology in Society, Elsevier, vol. 77(C).
  13. Al-Okaily, Manaf & Lutfi, Abdalwali & Alsaad, Abdallah & Taamneh, Abdallah & Alsyouf, Adi, 2020. "The Determinants of Digital Payment Systems’ Acceptance under Cultural Orientation Differences: The Case of Uncertainty Avoidance," Technology in Society, Elsevier, vol. 63(C).
  14. Noor Irliana Mohd Rahim & Noorminshah A. Iahad & Ahmad Fadhil Yusof & Mohammed A. Al-Sharafi, 2022. "AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
  15. Türker, Cansu & Altay, Burak Can & Okumuş, Abdullah, 2022. "Understanding user acceptance of QR code mobile payment systems in Turkey: An extended TAM," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  16. Alcántara-Pilar, Juan Miguel & Rodriguez-López, María Eugenia & Kalinić, Zoran & Liébana-Cabanillas, Francisco, 2024. "From likes to loyalty: Exploring the impact of influencer credibility on purchase intentions in TikTok," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
  17. Larbi-Siaw, Otu & Xuhua, Hu & Owusu, Ebenezer & Owusu-Agyeman, Abigail & Fulgence, Brou Ettien & Frimpong, Samuel Akwasi, 2022. "Eco-innovation, sustainable business performance and market turbulence moderation in emerging economies," Technology in Society, Elsevier, vol. 68(C).
  18. Lew, Susan & Tan, Garry Wei-Han & Loh, Xiu-Ming & Hew, Jun-Jie & Ooi, Keng-Boon, 2020. "The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model," Technology in Society, Elsevier, vol. 63(C).
  19. Leong, Lai-Ying & Hew, Teck-Soon & Ooi, Keng-Boon & Chong, Alain Yee-Loong, 2020. "Predicting the antecedents of trust in social commerce – A hybrid structural equation modeling with neural network approach," Journal of Business Research, Elsevier, vol. 110(C), pages 24-40.
  20. Singh, Nidhi & Sinha, Neena, 2020. "How perceived trust mediates merchant's intention to use a mobile wallet technology," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
  21. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
  22. Tu, Gengyang & Faure, Corinne & Schleich, Joachim & Guetlein, Marie-Charlotte, 2021. "The heat is off! The role of technology attributes and individual attitudes in the diffusion of Smart thermostats – findings from a multi-country survey," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  23. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
  24. Tewari, Alok & Mathur, Smriti & Srivastava, Smriti & Gangwar, Divya, 2022. "Examining the role of receptivity to green communication, altruism and openness to change on young consumers’ intention to purchase green apparel: A multi-analytical approach," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
  25. Ahmad Ghandour & Hussein Al-Srehan & Alhanof Almutairi, 2023. "Analysis of Demand and Supply for Mobile Payments in the UAE during COVID-19," JRFM, MDPI, vol. 16(2), pages 1-11, January.
  26. Rishi Manrai & Kriti Priya Gupta, 2023. "Investor’s perceptions on artificial intelligence (AI) technology adoption in investment services in India," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 1-14, March.
  27. Naeem Hayat & Abdullah Al Mamun & Noorul Azwin Md Nasir & Ganeshsree Selvachandran & Noorshella Binti Che Nawi & Quek Shio Gai, 2020. "Predicting Sustainable Farm Performance—Using Hybrid Structural Equation Modelling with an Artificial Neural Network Approach," Land, MDPI, vol. 9(9), pages 1-37, August.
  28. Komlan Gbongli & Yongan Xu & Komi Mawugbe Amedjonekou, 2019. "Extended Technology Acceptance Model to Predict Mobile-Based Money Acceptance and Sustainability: A Multi-Analytical Structural Equation Modeling and Neural Network Approach," Sustainability, MDPI, vol. 11(13), pages 1-33, July.
  29. Roy, Sanjit K. & Singh, Gaganpreet & Sadeque, Saalem & Gruner, Richard L., 2024. "Customer experience quality with social robots: Does trust matter?," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  30. Kamble, Sachin S. & Gunasekaran, Angappa & Kumar, Vikas & Belhadi, Amine & Foropon, Cyril, 2021. "A machine learning based approach for predicting blockchain adoption in supply Chain," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  31. Hiran, Kamal Kant & Dadhich, Manish, 2024. "Predicting the core determinants of cloud-edge computing adoption (CECA) for sustainable development in the higher education institutions of Africa: A high order SEM-ANN analytical approach," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
  32. Simona Sternad Zabukovšek & Samo Bobek & Uroš Zabukovšek & Zoran Kalinić & Polona Tominc, 2022. "Enhancing PLS-SEM-Enabled Research with ANN and IPMA: Research Study of Enterprise Resource Planning (ERP) Systems’ Acceptance Based on the Technology Acceptance Model (TAM)," Mathematics, MDPI, vol. 10(9), pages 1-28, April.
  33. Yu Hao & Shuang Liu & Zhu Liduzi Jiesisibieke & Yi-Jie Xu, 2019. "What Determines University Students’ Online Consumer Credit? Evidence From China," SAGE Open, , vol. 9(1), pages 21582440198, March.
  34. Naeem, Muhammad & Ozuem, Wilson, 2021. "The role of social media in internet banking transition during COVID-19 pandemic: Using multiple methods and sources in qualitative research," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
  35. Yuyang Zhao & Fernando Bacao, 2021. "How Does the Pandemic Facilitate Mobile Payment? An Investigation on Users’ Perspective under the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(3), pages 1-22, January.
  36. Irma Agárdi & Mónika Anetta Alt, 2024. "Do digital natives use mobile payment differently than digital immigrants? A comparative study between generation X and Z," Electronic Commerce Research, Springer, vol. 24(3), pages 1463-1490, September.
  37. Liébana-Cabanillas, Francisco & Japutra, Arnold & Molinillo, Sebastián & Singh, Nidhi & Sinha, Neena, 2020. "Assessment of mobile technology use in the emerging market: Analyzing intention to use m-payment services in India," Telecommunications Policy, Elsevier, vol. 44(9).
  38. María de los Ángeles Pérez-Sánchez & Zhuowei Tian & Almudena Barrientos-Báez & José Gómez-Galán & Hanliang Li, 2021. "Blockchain Technology for Winning Consumer Loyalty: Social Norm Analysis Using Structural Equation Modeling," Mathematics, MDPI, vol. 9(5), pages 1-18, March.
  39. Darehshiri, Mahsa & Ghaemi Asl, Mahdi & Babatunde Adekoya, Oluwasegun & Shahzad, Umer, 2022. "Cross-spectral coherence and dynamic connectedness among contactless digital payments and digital communities, enterprise collaboration, and virtual reality firms," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
  40. Shaw, Norman & Eschenbrenner, Brenda & Brand, Benedikt M., 2022. "Towards a Mobile App Diffusion of Innovations model: A multinational study of mobile wallet adoption," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
  41. Jang, Sunghoon & Hong, Doosun & Lee, Chungwon, 2024. "Exploring the behavioral adoption of automated parcel locker systems under COVID-19," Transport Policy, Elsevier, vol. 151(C), pages 1-11.
  42. Yosaka Eka Putranta & Rusli Alamsyah & Lisan Tan & Dewi Tamara, 2020. "The Determinant Factors of Mobile Payment Adoption," Eurasian Journal of Social Sciences, Eurasian Publications, vol. 8(3), pages 134-147.
  43. Dastane, Omkar & Goi, Chai Lee & Rabbanee, Fazlul, 2020. "A synthesis of constructs for modelling consumers’ perception of value from mobile-commerce (M-VAL)," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
  44. Kajol, K. & Singh, Ranjit & Paul, Justin, 2022. "Adoption of digital financial transactions: A review of literature and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  45. Higueras-Castillo, Elena & Kalinic, Zoran & Marinkovic, Veljko & Liébana-Cabanillas, Francisco J., 2020. "A mixed analysis of perceptions of electric and hybrid vehicles," Energy Policy, Elsevier, vol. 136(C).
  46. Ahmad Aburayya, 2024. "Analysing the Influence of Augmented Reality on Organization Performance via Supply and Logistics Value Chain Functions: A Hybrid ANN-PLS Model Assessment in the Gulf Cooperation Council Region," Logistics, MDPI, vol. 8(4), pages 1-20, November.
  47. Ng, Felicity Zi-Xuan & Yap, Hui-Yee & Tan, Garry Wei-Han & Lo, Pei-San & Ooi, Keng-Boon, 2022. "Fashion shopping on the go: A Dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
  48. Yoonyoung Hwang & Sangwook Park & Nina Shin, 2021. "Sustainable Development of a Mobile Payment Security Environment Using Fintech Solutions," Sustainability, MDPI, vol. 13(15), pages 1-15, July.
  49. Balakrishnan, Vimala & Shuib, Nor Liyana Mohd, 2021. "Drivers and inhibitors for digital payment adoption using the Cashless Society Readiness-Adoption model in Malaysia," Technology in Society, Elsevier, vol. 65(C).
  50. Ameen, Nisreen & Shah, Mahmood Hussain & Sims, Julian & Choudrie, Jyoti & Willis, Robert, 2020. "Are there peas in a pod when considering mobile phone and mobile applications use: A quantitative study," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
  51. Suhail, Faisal & Adel, Mouhand & Al-Emran, Mostafa & AlQudah, Adi Ahmad, 2024. "Are students ready for robots in higher education? Examining the adoption of robots by integrating UTAUT2 and TTF using a hybrid SEM-ANN approach," Technology in Society, Elsevier, vol. 77(C).
  52. Kalinic, Zoran & Marinkovic, Veljko & Molinillo, Sebastián & Liébana-Cabanillas, Francisco, 2019. "A multi-analytical approach to peer-to-peer mobile payment acceptance prediction," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 143-153.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.