Share:


Investigation of digital retail companies financial performance using multiple criteria decision analysis

Abstract

Digital retail (online retail or e-commerce) sector is continuously expanding its stake in the global economy each year. According to the statistics, online retail share of the total global retail sales takes approximately 11.9% in 2018 and is expected to reach 17.5% at the end of 2021. The same pattern of rapid growth was noticed more than 18 years ago when a burst of dot-com bubble crashed many of the internet-based online shopping companies. “Growth over profits” mentality and overestimated perception of the magnitude of online sales resulted in a superficial understanding of the business’ financial performance. Because of that, it is highly necessary to analyze and adequately evaluate the financial performance of digital retail companies. Thus, the purpose of this article is to investigate the top 4 digital retail companies’ financial performance by applying multiple criteria decision analysis (MCDA) TOPSIS and SAW methods to demonstrate that sales turnover is not the only and the prime measure to evaluate the successful company’s financial performance.


Article in English.


Skaitmeninės mažmeninės prekybos įmonių finansinės veiklos tyrimas taikant daugiakriterius sprendimų analizės metodus


Santrauka


Skaitmeninės mažmeninės prekybos (mažmeninė prekyba internetu arba elektroninė prekyba) vaidmuo pasaulio ekonomikoje kasmet didėja. Statistikos duomenimis, skaitmeninės mažmeninės prekybos dalis pasaulio mažmeninės prekybos sektoriuje 2018 m. siekė apie 11,9 %, o 2021 m. pabaigoje tikimasi, kad ji pasieks 17,5 %. Toks spartus augimas buvo pastebėtas ir daugiau nei prieš 18 metų, kai „dot-com“ burbulo sprogimas sužlugdė daugelį elektroninės prekybos įmonių. „Augimo per pelną“ mentalitetas ir pervertinta internetinės prekybos apimtis privedė prie paviršutiniško verslo finansinių rezultatų suvokimo. Būtent dėl šios priežasties yra itin svarbu tinkamai analizuoti bei įvertinti skaitmeninės mažmeninės prekybos įmonių finansinius rezultatus. Taigi šio straipsnio tikslas – ištirti 4 didžiausių skaitmeninės mažmeninės prekybos bendrovių finansinius rezultatus, taikant daugiakriterius sprendimų analizės (DSMA) TOPSIS ir SAW metodus, tam, kad būtų galima įrodyti, jog pardavimų apyvarta nėra vienintelis ir svarbiausias matas siekiant įvertinti sėkmingą įmonės finansinę veiklą.


Reikšminiai žodžiai: finansiniai rezultatai, skaitmeninė mažmeninė prekyba, skaitmeninė transformacija, mažmeninė prekyba internetu, elektroninė prekyba, DSMA, TOPSIS metodas, SAW metodas.

Keyword : financial performance, digital retail, digital transformation, online retail, e-commerce, MCDA, TOPSIS method, SAW method

How to Cite
Urbonavičiūtė, K., & Maknickienė, N. (2019). Investigation of digital retail companies financial performance using multiple criteria decision analysis. Mokslas – Lietuvos Ateitis / Science – Future of Lithuania, 11. https://doi.org/10.3846/mla.2019.9737
Published in Issue
Jun 14, 2019
Abstract Views
2718
PDF Downloads
1089
Creative Commons License

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

References

Alibaba Group Holding Ltd. (2019). BABA company financials. Retrieved from https://www.nasdaq.com/symbol/baba/financials?query=income-statement

Amazon, Inc. (2019). AMZN company financials. Retrieved from https://www.nasdaq.com/symbol/amzn/financials?query=incomestatement

Anggraeni, E. Y., Huda, M., Maseleno, A., Safar, J., & Jasmi, K. A. (2018). Poverty level grouping using SAW method. International Journal of Engineering & Technology, 7(2.27), 218-224. https://doi.org/10.14419/ijet.v7i2.27.11948

Chen, S., & Leteney, F. (2000). Get real! Managing the next stage of internet retail. European Management Journal, 18(5), 519-528. https://doi.org/10.1016/S0263-2373(00)00041-4

Chen, T. Y., & Tsao, C. Y. (2008). The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets and Systems, 159(11), 1410-1428. https://doi.org/10.1016/j.fss.2007.11.004

Corporate Finance Institute. (2019). Profitability ratios. Retrieved from https://corporatefinanceinstitute.com/resources/knowledge/finance/profitability-ratios/

eBay, Inc. (2019). EBAY company financials. Retrieved from https://www.nasdaq.com/symbol/ebay/financials?query=income-statement

Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. (2013). Embracing digital technology: a new strategic imperative. MITSloan Management Review, 1-12. https://doi.org/10.1057/palgrave.ejis.3000650

Hitchner, J. R. (2011). Financial valuation: applications and models (103 p.). Hoboken, N.J: Wiley. https://doi.org/10.1002/9781119205517

Ishfaq, R., Defee, C. C., Gibson, B. J., & Raja, U. (2016). Realignment of the physical distribution process in omni-channel fulfillment. International Journal of Physical Distribution and Logistics Management, 46(6-7), 543-561. https://doi.org/10.1108/IJPDLM-02-2015-0032

Ishizaka, A., & Nemery, P. (2013). Goal, aspiration or reference-level approach. Multi-Criteria Decision Analysis: Methods and Software. Retrieved from http://ebookcentral.proquest.com

Jackson, T. (2009). Prosperity without growth. Economics for a finite planet (Vol. 39). London, New York: Earthscan. https://doi.org/10.4324/9781849774338

JD.com, Inc. (2019). JD company financials. Retrieved from https://www.nasdaq.com/symbol/jd/financials?query=income-statement

Matt, C., Hess, T., & Benlian, A. (2015). Digital transformation strategies. Business and Information Systems Engineering, 57(5), 339-343. https://doi.org/10.1007/s12599-015-0401-5

Meffert, J., & Swaminathan, A. (2018). Leadership and the urgency for digital transformation. Leader to Leader, 2018(88), 44-49. https://doi.org/10.1002/ltl.20357

Mithas, S., Tafti, A., & Mitchell, W. (2013). How a firm’s competitive environment and digital strategic posture influence digital business strategy. MIS Quarterly, 37(2), 511-536. https://doi.org/10.25300/MISQ/2013/37.2.09

Podvezko, V. (2011). The comparative analysis of MCDA methods SAW and COPRAS. Engineering Economics, 22(2), 134-146. https://doi.org/10.5755/j01.ee.22.2.310

Rapp, A., Baker, T. L., Bachrach, D. G., Ogilvie, J., & Beitelspacher, L. S. (2015). Perceived customer showrooming behavior and the effect on retail salesperson self-efficacy and performance. Journal of Retailing, 91(2), 358-369. https://doi.org/10.1016/j.jretai.2014.12.007

Rigby, D. (2011). The future of shopping. Harward Business Review, 65-76.

Statista. (2018a). E-commerce share of total global retail sales from 2015 to 2021. Retrieved from https://www.statista.com/statistics/534123/e-commerce-share-of-retail-sales-worldwide/

Statista. (2018b). Retail e-commerce sales worldwide from 2014 to 2021. Retrieved from https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/

Sustainanalytics. (2018). ESG risk ratings. Retrieved from https://www.sustainalytics.com/esg-ratings/

The World Bank. (2019). GDP per capita (current US$). Retrieved from https://data.worldbank.org/indicator/NY.GDP.PCAP.CD

Wang, Y. M., & Elhag, T. M. S. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems with Applications, 31(2), 309-319. https://doi.org/10.1016/j.eswa.2005.09.040

World Trade Organization. (2018). Goods and services – what is being traded? World Trade Statistical Review 2018, 40-65. https://doi.org/10.30875/7021dec9-en

Yahoo Finance. (2018). Environment, Social and Governance (ESG) ratings. Retrieved from https://finance.yahoo.com/quote/AMZN/sustainability?p=AMZN&.tsrc=fin-srch

Zhu, J., Goraya, M. A. S., & Cai, Y. (2018). Retailer–consumer sustainable business environment: how consumers’ perceived benefits are translated by the addition of new retail channels. Sustainability 2018, 10(9), 2959. https://doi.org/10.3390/su10092959