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Development Of Measurement Scale For Personalized Recommended Product Acceptance (Prpa-Scale)

Author

Listed:
  • Ampadu Seth

    (Hefei University of Technology, Hefei 230009, Anhui, China)

  • Yuanchun Jiang

    (Hefei University of Technology, Hefei 230009, Anhui, China)

  • Samuel Adu Gyamfi

    (Akenten Appiah-Menka University of skills Training and Entrepreneurial Development (AMMUSTED))

  • Debrah Emmanuel

    (University of Professional Studies, Ghana)

  • Eric Amankwa

    (Presbyterian University College, Ghana)

Abstract

ersonalized recommendation (PR) system has been established to enhance consumers experience by suggesting products for consumers. Researches in PR mostly focus on the PR “system” acceptance but not the “actual product” acceptance. Therefore, this research aims to develop an instrument that measures the psychometric indicators of personalized product recommended acceptance. The sample size for the study were made up of (N=521) consumers from various accessible online marketplace in Ghana (jumia, kikuu, tonaton, jiji, amazon, eBay, aliexpress, alibaba, and other platforms) who represent the end-users of the e-tailers recommendation system. The study was quantitative in nature. In an attempt to evaluate the Personalized Recommended Product Acceptance Scale (PRPA-SCALE), an instrument was developed then submitted to 1 psychologist, 2 Marketing experts and 2 consumer behaviour researchers to test and rate items developed for the study. The EFA and CFA were performed to validate the instrument. The finding indicated significant content validity and further provided evidence of a good model fit for the five factors extracted constructs ((Price consciousness (5 items), Product Review factor (6 items), Brand Influence (5 items), Perceived Quality (6 items) and E-tailers Promotional Factor (8 items)). To the best of our knowledge, the PRPA-scale is the first scale robustly developed to measure personalized product recommendation acceptance. This also set the foundation for future research in the area of consumers’ purchase decision processes towards recommended products.

Suggested Citation

  • Ampadu Seth & Yuanchun Jiang & Samuel Adu Gyamfi & Debrah Emmanuel & Eric Amankwa, 2022. "Development Of Measurement Scale For Personalized Recommended Product Acceptance (Prpa-Scale)," Malaysian E Commerce Journal (MECJ), Zibeline International Publishing, vol. 6(2), pages 76-85, October.
    • Handle: RePEc:zib:zbmecj:v:6:y:2022:i:2:p:76-85
    DOI: 10.26480/mecj.02.2022.76.85
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    References listed on IDEAS

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    1. Hair, Joe F. & Howard, Matt C. & Nitzl, Christian, 2020. "Assessing measurement model quality in PLS-SEM using confirmatory composite analysis," Journal of Business Research, Elsevier, vol. 109(C), pages 101-110.
    2. Baier, Daniel & Stüber, Eva, 2010. "Acceptance of recommendations to buy in online retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 17(3), pages 173-180.
    3. Rezgar Mohammed & Olga Murova, 2019. "The Effect of Price Reduction on Consumer's Buying Behavior in the U.S. Differentiated Yogurt Market," Applied Economics and Finance, Redfame publishing, vol. 6(2), pages 32-42, March.
    4. Book, Laura A. & Tanford, Sarah & Chang, Wen, 2018. "Customer reviews are not always informative: The impact of effortful versus heuristic processing," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 272-280.
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