Vicente E. Montano, Joanna Lynn L. Mercado


This study delves into the complex and evolving landscape of e-commerce in the Philippines, focusing on the relationship between E-Commerce Sales as the endogenous variable and a set of influential exogenous variables, including Digital Marketing Spending, GDP Growth, Internet Penetration, and Mobile Phone Ownership. This research employs a flexible spline modeling approach, uncovers non-linear associations, and offers significant implications for academic understanding and practical applications. The findings underscore the growing impact of Digital Marketing Spending on E-Commerce Sales, revealing the paramount role of online advertising and promotional strategies in the digital marketplace. Moreover, the study explains the intricate interplay between GDP Growth, Internet Penetration, Mobile Phone Ownership, and E-Commerce Sales, highlighting the non-linear nature of these relationships. As the Philippines continues its economic expansion and technological integration, these associations exhibit insightful implications for policymakers, businesses, and e-commerce stakeholders.


Article visualizations:

Hit counter


e-commerce sales, spline modeling, the Philippines

Full Text:



Akomaning, B. (2019). Oil Price Volatility: GARCH, SVR-GARCH, and EVT Approach (Doctoral dissertation, North-West University (South Africa)).

Ammad, M., & Ramli, A. (2019, July). Cubic B-Spline curve interpolation with arbitrary derivatives on its data points. In 2019 23rd International Conference in Information Visualization–Part II (pp. 156–159). IEEE.

Attié, E., & Meyer-Waarden, L. (2022). The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy calculus theories. Technological Forecasting and Social Change, 176, 121485.

Awa, H. O., Ojiabo, O. U., & Emecheta, B. C. (2015). Integrating TAM, TPB, and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science & Technology Policy Management, 6(1), 76-94.

Balinbin, A. (26 August 2021). PHL e-commerce seen to hit $15 billion by 2025. Business World. https://www.bworldonline.com/corporate/2021/08/26/391702/phl-e-commerce-seen-to-hit-15-billion-by-2025/.

Barry, M., & Jan, M. T. (2018). Factors influencing the use of m-commerce: An extended technology acceptance model perspective. International Journal of Economics, Management and Accounting, 26(1), 157-183.

Bednarczyk, J. L., & Brzozowska-Rup, K. (2019). Non-Decreasing Economic Growth Rate of Inflation (NDEGRI) in light of empirical studies. Econometrics, 23(1), 9-18.

Berry, S. M., Carroll, R. J., & Ruppert, D. (2002). Bayesian smoothing and regression splines for measurement error problems. Journal of the American Statistical Association, 97(457), 160-169.

Bessaoud, F., Daures, J. P., & Molinari, N. (2005). Free knot splines for logistic models and threshold selection. Computer methods and programs in biomedicine, 77(1), 1-9.

Borup, D., Coulombe, P. G., Rapach, D., Schütte, E. C. M., & Schwenk-Nebbe, S. (2022). The anatomy of out-of-sample forecasting accuracy.

Buhalis, D., & Deimezi, O. (2003). Information Technology Penetration and E‐commerce Developments in Greece, With a Focus on Small to Medium‐sized Enterprises. Electronic Markets, 13(4), 309-324.

Chu, B., & Qureshi, S. (2022). Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast US GDP Growth. Computational Economics, 1-43.

Chen, B., Wang, L., Rasool, H., & Wang, J. (2022). Research on the impact of marketing strategy on consumers’ impulsive purchase behavior in livestreaming e-commerce. Frontiers in Psychology, 13, 905531.

Clarete, R. L. (2019). E-commerce in the Philippines. Developing the Digital Economy in ASEAN, 200.

CR Team (30 October 2023). E-Commerce in Philippines: Outlook & Retail Trends in 2023. OOSGA. https://oosga.com/e-commerce/phl/

Dash, A., Bhattacharya, D., Dhakre, D. S., & Kishan, M. (2022). On Selection of Best Model from Spline Regression and ARIMA Models for Forecasting Rabi Food Grain Production of Odisha. Environment and Ecology, 40(3B), 1428-1437.

Dhaher, Y. Y., Delp, S. L., & Rymer, W. Z. (2000). The use of basis functions in modelling joint articular surfaces: application to the knee joint. Journal of Biomechanics, 33(7), 901-907.

Digital Ad Spending, Philippines. eMarketer. https://www.insiderintelligence.com/forecasts/5a1de3ff84a1ba0780e313ac/5a1de0df84a1ba0780e313a2/

Dynan, K., & Sheiner, L. (2018). GDP as a measure of economic well-being (Vol. 43, p. 53). Hutchins Center Working Paper.

E-commerce market size in the Philippines in 2019 and 2021, with a forecast for 2022 and 2025 (October 2023). Statista. https://www.statista.com/statistics/1125455/e-commerce-market-size-philippines/

eCommerce: market data & analysis (September 2023). Statista. https://www.statista.com/study/42335/ecommerce-report/

eCommerce. (25 July 2022). Philippines - Country Commercial Guide. Official Website of the International Trade Administration. https://www.trade.gov/country-commercial-guides/philippines-ecommerce

E-commerce in the Philippines - statistics & facts (6 July 2023). Statista. https://www.statista.com/topics/6539/e-commerce-in-the-philippines/.

Francom, D., & Sansó, B. (2020). Bass: An r package for fitting and performing sensitivity analysis of Bayesian adaptive spline surfaces. Journal of Statistical Software, 94(LA-UR-20-23587).

Gao, J., Siddik, A. B., Khawar Abbas, S., Hamayun, M., Masukujjaman, M., & Alam, S. S. (2023). Impact of E-commerce and digital marketing adoption on the financial and sustainability performance of MSMEs during the COVID-19 pandemic: An empirical study. Sustainability, 15(2), 1594.

GDP growth (annual %) - Philippines. World Bank. https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?locations=PH

Global e-commerce jumps to $26.7 trillion, fuelled by COVID-19. (3 May 2021). UN News Global perspective Human stories. https://news.un.org/en/story/2021/05/1091182.

Harrell, Jr, F. E., & Harrell, F. E. (2015). General aspects of fitting regression models. Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis, 13-44.

Highlights of the Philippines Economic Update June 2023: Securing a Clean Energy Future. (14 June 2023). The World Bank. https://www.worldbank.org/en/country/philippines/publication/highlights-of-the-philippines-economic-update-june-2023-securing-a-clean-energy-future

Ho, S. C., Kauffman, R. J., & Liang, T. P. (2007). A growth theory perspective on B2C e-commerce growth in Europe: An exploratory study. Electronic Commerce Research and Applications, 6(3), 237-259.

Hong, W., & Zhu, K. (2006). Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level. Information & management, 43(2), 204-221.

Individuals using the Internet (% of population) – Philippines. World Bank. https://data.worldbank.org/indicator/IT.NET.USER.ZS?locations=PH

Jeong, H., Yi, Y., & Kim, D. (2022). An innovative e-commerce platform incorporating metaverse to live commerce. International Journal of Innovative Computing, Information and Control, 18(1), 221-229.

Jílková, P., & Králová, P. (2021). Digital consumer behaviour and ecommerce trends during the COVID-19 crisis. International Advances in Economic Research, 27(1), 83-85.

Mallick, M., Mohanta, A., & Kumar, A. (2020). Multivariate adaptive regression spline approach to the assessment of surface mean pressure coefficient on surfaces of C-shaped building. Scientia Iranica, 27(6), 2967-2984.

Marco, K. (9 May 2023). PH eCommerce: Data, Statistics, Strategies for 2023 and Beyond - RUSH. https://www.rush.ph/blog/ph-ecommerce-data-statistics-strategies-2023-and-beyond.

Marsh, L. C., & Cormier, D. R. (2001). Spline regression models (No. 137). Sage.

Mobile cellular subscriptions (per 100 people) – Philippines. World Bank. https://data.worldbank.org/indicator/IT.CEL.SETS.P2?locations=PH

Molinari, N., Durand, J. F., & Sabatier, R. (2004). Bounded optimal knots for regression splines. Computational statistics & data analysis, 45(2), 159-178.

Nabot, A., Garaj, V., & Balachandran, W. (2018). Consumer attitudes toward online shopping: An exploratory study from Jordan. In Mobile Commerce: Concepts, Methodologies, Tools, and Applications (pp. 1110-1123). IGI Global.

Omay, R. E. (2013). The relationship between environment and income: regression spline approach. International Journal of Energy Economics and Policy, 3(4), 52-61.

Panda, R., & Dash, M. (2006). Fractional generalized splines and signal processing. Signal Processing, 86(9), 2340-2350.

Pantelimon, F. V., Georgescu, T. M., & Posedaru, B. Ş. (2020). The impact of mobile e-commerce on GDP: A comparative analysis between Romania and Germany and how covid-19 influences the e-commerce activity worldwide. Informatica Economica, 24(2), 27-41.

Perperoglou, A., Sauerbrei, W., Abrahamowicz, M., & Schmid, M. (2019). A review of spline function procedures in R. BMC medical research methodology, 19(1), 1-16.

Pham Thi Van, H. (2021). Multivariate Adaptive Regression Splines (MARS) for non-linear time series dependence: An application in biostatistics (Master's thesis, Universitat Politècnica de Catalunya).

Rabbath, C. A., & Corriveau, D. (2019). A comparison of piecewise cubic Hermite interpolating polynomials, cubic splines and piecewise linear functions for the approximation of projectile aerodynamics. Defence Technology, 15(5), 741-757.

Racine, J. S. (2014). A primer on regression splines. URL: http://cranrprojectorg/web/packages/crs/vignettes/splineprimerpdf.

Royston, P., & Sauerbrei, W. (2007). Multivariable modeling with cubic regression splines: a principled approach. The Stata Journal, 7(1), 45-70.

Sandhu, P. (2012). Mobile commerce: beyond E-commerce. IJCST, 3(1), 59-63.

Schia, N. N. (2018). The cyber frontier and digital pitfalls in the Global South. Third World Quarterly, 39(5), 821-837.

Shaghaghi, S., Bonakdari, H., Gholami, A., Kisi, O., Binns, A., & Gharabaghi, B. (2019). Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods. International Journal of River Basin Management, 17(3), 333-352.

Soava, G., Mehedintu, A., & Sterpu, M. (2022). Analysis and Forecast of the Use of E-Commerce in Enterprises of the European Union States. Sustainability, 14(14), 8943.

Staněk, F. (2021). Optimal Out-of-sample Forecast Evaluation Under Stationarity. CERGE-EI Working Paper Series, (712).

Statistics report on e-commerce in the Philippines. Statista. https://www.statista.com/study/74971/e-commerce-in-the-philippines/

Tarhini, A., Alalwan, A. A., Shammout, A. B., & Al-Badi, A. (2019). An analysis of the factors affecting mobile commerce adoption in developing countries: Towards an integrated model. Review of International Business and Strategy, 29(3), 157-179.

Tayao-Juego. (3 April 2020). Lazada, Shopee, ZALORA top list of most visited online stores in PH. Philippine Daily Inquirer. https://business.inquirer.net/293997/lazada-shopee-zalora-top-list-of-most-visited-online-stores-in-ph

Tirta, I. M., Anggraeni, D., & Pandutama, M. (2017, June). Online Statistical Modeling (Regression Analysis) for Independent Responses. In Journal of Physics: Conference Series (Vol. 855, No. 1, p. 012054). IOP Publishing.

Wahba, G., & Wang, Y. (2014). Spline function. JA Matthews, Encyclopedia of Environmental Change, SAGE Publications, Thousand Oaks, California, 91320.

Wongsai, N., Wongsai, S., & Huete, A. R. (2017). Annual seasonality extraction using the cubic spline function and decadal trend in temporal daytime MODIS LST data. Remote Sensing, 9(12), 1254.

Yang, G., Zhang, B., & Zhang, M. (2023). Estimation of knots in linear spline models. Journal of the American Statistical Association, 118(541), 639–650.

Zhao, B., Takasu, A., Yahyapour, R., & Fu, X. (2019, November). Loyal consumers or one-time deal hunters: Repeat buyer prediction for e-commerce. In 2019 International Conference on Data Mining Workshops (ICDMW) (pp. 1080-1087). IEEE.

DOI: http://dx.doi.org/10.46827/ejmms.v8i3.1603


  • There are currently no refbacks.

Copyright (c) 2023 Vicente E. Montano, Joanna Lynn L. Mercado

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

The research works published in this journal are free to be accessed. They can be shared (copied and redistributed in any medium or format) and\or adapted (remixed, transformed, and built upon the material for any purpose, commercially and\or not commercially) under the following terms: attribution (appropriate credit must be given indicating original authors, research work name and publication name mentioning if changes were made) and without adding additional restrictions (without restricting others from doing anything the actual license permits). Authors retain the full copyright of their published research works and cannot revoke these freedoms as long as the license terms are followed.

Copyright © 2017-2023. European Journal of Management and Marketing Studies (ISSN 2501 - 9988) is a registered trademark of Open Access Publishing GroupAll rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library. All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All the research works published on this journal are meeting the Open Access Publishing requirements and standards formulated by Budapest Open Access Initiative (2002), the Bethesda Statement on Open Access Publishing (2003) and  Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003) and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License. Copyrights of the published research works are retained by authors.