IDEAS home Printed from https://ideas.repec.org/a/ibn/ijmsjn/v10y2018i2p60-75.html
   My bibliography  Save this article

Exploring Factors Affecting Consumers¡¯ Adoption of Shopping via Mobile Applications in Turkey

Author

Listed:
  • Oguz YILDIZ
  • Hakan KITAPCI

Abstract

The aim of this study is to identify the factors behind consumers¡¯ adoption of shopping via mobile applications and to develop a new model that explains this situation. The related literature was examined for this purpose. Delphi technique was preferred to determine factors in the study. Data was collected through questionnaires. Exploratory Factor Analysis (EFA) was conducted with SPSS. A research model based on an integration of various theoretical fields was developed. As a result of EFA, ten new dimensions emerged in the study. And then, in order to statistically analyze the measurement and structural models, this study used Smart PLS for Structural Equation Modeling (SEM) technique. After path analysis with Smart PLS, a new conceptual model was developed to explain adoption of shopping via mobile applications by consumers in Turkey. Structures such as Personalization, Word of Mouth Communication and Perceived Mobility used in the model developed within the scope of this research, but rarely used in this field of studies, were verified to be determinants of shopping behavior via mobile applications in Turkey. The model developed within the study is both valid and reliable in terms of its structure and all relations established within the scope of the model are significant.

Suggested Citation

  • Oguz YILDIZ & Hakan KITAPCI, 2018. "Exploring Factors Affecting Consumers¡¯ Adoption of Shopping via Mobile Applications in Turkey," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 10(2), pages 60-75, June.
  • Handle: RePEc:ibn:ijmsjn:v:10:y:2018:i:2:p:60-75
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ijms/article/view/74066/41553
    Download Restriction: no

    File URL: http://www.ccsenet.org/journal/index.php/ijms/article/view/74066
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Kiseol, 2012. "Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 19(5), pages 484-491.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Shimp, Terence A & Kavas, Alican, 1984. "The Theory of Reasoned Action Applied to Coupon Usage," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(3), pages 795-809, December.
    4. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Oecd, 2013. "Electronic and Mobile Commerce," OECD Digital Economy Papers 228, OECD Publishing.
    7. Kim, Byoungsoo, 2012. "The diffusion of mobile data services and applications: Exploring the role of habit and its antecedents," Telecommunications Policy, Elsevier, vol. 36(1), pages 69-81.
    8. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
    9. Se-Joon Hong & James Y. L. Thong & Jae-Yun Moon & Kar-Yan Tam, 2008. "Understanding the behavior of mobile data services consumers," Information Systems Frontiers, Springer, vol. 10(4), pages 431-445, September.
    10. Agrebi, Sinda & Jallais, Joël, 2015. "Explain the intention to use smartphones for mobile shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 16-23.
    11. Margherita Pagani, 2004. "Determinants of adoption of third generation mobile multimedia services," Post-Print hal-02313098, HAL.
    12. Rujipun Assarut & Somkiat Eiamkanchanalai, 2015. "Consumption Values, Personal Characteristics and Behavioral Intentions in Mobile Shopping Adoption," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 27(1), pages 21-41.
    13. Ström, Roger & Vendel, Martin & Bredican, John, 2014. "Mobile marketing: A literature review on its value for consumers and retailers," Journal of Retailing and Consumer Services, Elsevier, vol. 21(6), pages 1001-1012.
    14. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Shih-Wei Chen & Ku-Yuan Lee & Chi-Ming Hsieh, 2021. "Determinants of Consumers’ Trust in Biotech Brands and Purchase Intentions towards the Cord Blood Products," IJERPH, MDPI, vol. 18(21), pages 1-17, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jeeyeon Jeong & Yaeri Kim & Taewoo Roh, 2021. "Do Consumers Care About Aesthetics and Compatibility? The Intention to Use Wearable Devices in Health Care," SAGE Open, , vol. 11(3), pages 21582440211, August.
    2. Anastasiou Kartas & Sigi Goode, 2012. "Use, perceived deterrence and the role of software piracy in video game console adoption," Information Systems Frontiers, Springer, vol. 14(2), pages 261-277, April.
    3. Luis Edwin Chimborazo & Marta Frasquet & Alejandro Mollá, 2021. "Explaining Mobile Commerce Usage Intention Based on Technology Acceptance Models in a Developing Market Context," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 33(1), pages 25-40.
    4. Luceri, Beatrice & (Tammo) Bijmolt, T.H.A. & Bellini, Silvia & Aiolfi, Simone, 2022. "What drives consumers to shop on mobile devices? Insights from a Meta-Analysis," Journal of Retailing, Elsevier, vol. 98(1), pages 178-196.
    5. Daniel Belanche & Marta Flavián & Alfredo Pérez-Rueda, 2020. "Mobile Apps Use and WOM in the Food Delivery Sector: The Role of Planned Behavior, Perceived Security and Customer Lifestyle Compatibility," Sustainability, MDPI, vol. 12(10), pages 1-21, May.
    6. Yu-Jin Choi & Jin-Woo Park, 2020. "Investigating Factors Influencing the Behavioral Intention of Online Duty-Free Shop Users," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    7. Fahad Asmi & Rongting Zhou & Liu Lu, 2017. "E-government Adoption in Developing Countries: Need of Customer-centric Approach: A Case of Pakistan," International Business Research, Canadian Center of Science and Education, vol. 10(1), pages 42-58, January.
    8. Nedra, Bahri-Ammari & Hadhri, Walid & Mezrani, Mariem, 2019. "Determinants of customers' intentions to use hedonic networks: The case of Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 21-32.
    9. Martins, José & Costa, Catarina & Oliveira, Tiago & Gonçalves, Ramiro & Branco, Frederico, 2019. "How smartphone advertising influences consumers' purchase intention," Journal of Business Research, Elsevier, vol. 94(C), pages 378-387.
    10. Bilgihan, Anil & Barreda, Albert & Okumus, Fevzi & Nusair, Khaldoon, 2016. "Consumer perception of knowledge-sharing in travel-related Online Social Networks," Tourism Management, Elsevier, vol. 52(C), pages 287-296.
    11. Chen, Shih-Chih & Hung, Chung-Wen, 2016. "Elucidating the factors influencing the acceptance of green products: An extension of theory of planned behavior," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 155-163.
    12. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    13. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    14. Oghuma, Apollos Patricks & Chang, Younghoon & Libaque-Saenz, Christian Fernando & Park, Myeong-Cheol & Rho, Jae Jeung, 2015. "Benefit-confirmation model for post-adoption behavior of mobile instant messaging applications: A comparative analysis of KakaoTalk and Joyn in Korea," Telecommunications Policy, Elsevier, vol. 39(8), pages 658-677.
    15. McLean, Graeme & Osei-Frimpong, Kofi & Al-Nabhani, Khalid & Marriott, Hannah, 2020. "Examining consumer attitudes towards retailers' m-commerce mobile applications – An initial adoption vs. continuous use perspective," Journal of Business Research, Elsevier, vol. 106(C), pages 139-157.
    16. Hossain, Akram & Quaresma, Rui & Rahman, Habibur, 2019. "Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: An empirical study," International Journal of Information Management, Elsevier, vol. 44(C), pages 76-87.
    17. Deborah Compeau & Barbara Marcolin & Helen Kelley & Chris Higgins, 2012. "Research Commentary ---Generalizability of Information Systems Research Using Student Subjects---A Reflection on Our Practices and Recommendations for Future Research," Information Systems Research, INFORMS, vol. 23(4), pages 1093-1109, December.
    18. Marta Perdigoto & Winnie Picoto, 2012. "Analysing Intention And Action In Mobile Banking Services," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 133-152.
    19. Kasilingam, Dharun Lingam, 2020. "Understanding the attitude and intention to use smartphone chatbots for shopping," Technology in Society, Elsevier, vol. 62(C).
    20. Chen Wei, 2021. "The influence of Consumers’ Purchase intention on Smart Wearable Device: A study of Consumers in East China," International Journal of Science and Business, IJSAB International, vol. 5(8), pages 46-72.

    More about this item

    Keywords

    consumer adoption; exploratory factor analysis; mobile applications; mobile shopping; structural equation modeling; smart PLS;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ijmsjn:v:10:y:2018:i:2:p:60-75. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.