A Mathematical Model of Factors Driving Product Success in an Indonesian Market using Design of Experiment

Previous studies have not agreed on factors that affect the success of different kinds of products. These studies have used independent variables with a different number of success factors to examine several products, and some of these variables have been redundant. No standardized factor predicts the success of various products; thus, no generalizable result has provided a reference for further studies or use recommendations for practices. Therefore, this study produced a model that not only examined specific products and scope but also used a number of standardized success factors by building a mathematical model of the success factors that affect the success of various products. The study utilized 304 products from the Indonesian market as well as design of experiment to build the mathematical model. The results suggested that six standardized success factors affected the success of various products: (1) price, (2) product performance, (3) brands, (4) aesthetic design, (5) services and (6) marketing. Services and marketing (i.e., appropriately timed marketing) were positively correlated and proportional to the increase of market share. Therefore, focusing on the services and marketing factors that will drive the success of a product is important for many companies. The factors that positively drive success can be determined by characteristic sales in the Indonesian market.

Design of experiment; Indonesian market; Mathematical models; Success factors

Predicting the potential factors that drive product success is important for companies. Besides being very costly, product development activities are also critical to the company to know which potential factors will drive success. Its means that product development activities must be based on the potential factors that will drive success. In addition, companies must minimize potential investment failures in product development. Therefore, this study investigated potential factors that drive success in the Indonesian market.

        Previous research has identified success factors in the market. For example, Montoya-Weiss and Calantone (1994), Cooper (1979a), Cooper et al. (2014) and Henard and Szymanski (2001) examined key factors that affect product success. These factors include product quality (Cantner et al., 2012), branding and marketing (Gao et al., 2006), product services (Jiang and Liu, 2012), price promotion (Lee and Zhou, 2012), product performance and marketing (Ernst, 2002). 

    Several literature reviews and a meta-analysis also investigated the factors of product success (Griffin and Page, 1993; Ernst, 2002; Kleinknecht and Panne, 2012; Setyaningrum et al., 2016) then the product success factor become research trend. Previous research identified success factors in business incubators (Gozali et al, 2020) and multi factors productivity that a priori insights in capital project (Woodhead and Berawi, 2020).

According to previous research, models that examined the factors of product success had some weaknesses. They used independent variables with a different number of success factors for several products, and some variables were redundant. This was because no standardized factor effecting a product’s success exists (Cooper, 1979b; Henard and Szymanski, 2001; Wijaya, 2011; Handaru, 2012; Mutjaba, 2013; Cooper et al., 2014; Nugroho, 2014; Armunifah, 2014; Susilowati, 2016; Lenggono, 2016).

The studies by Wijaya (2011), Handaru (2012), Mutjaba (2013),vNugroho (2014), Armunifah (2014), Susilowati (2016) and Lenggono (2016) used various factors for different kinds of products. The most common factors used to predict product success are shown in Figure 1. The number of factors used to predict product success varied for different products. Electronic products used 12 success factors,14 smartphone products used 5–14 success factors (Wijaya, 2011; Armunifah, 2014), automotive products used 12–14 success factors (Wijaya, 2011; Lenggono, 2016), wood products used 11 success factors (Mutjaba, 2013; Nugroho, 2014; Susilowati, 2016), and service products used 7–12 success factors (Nugroho, 2014) and product success analysis (Suharyanti et al., 2017). No agreement was found on the factors determining success for various products. Additionally, some factors were redundant and could be grouped together.

Figure 1 The utilization percentage of success factors based on 12 studies

1.1. Aims and Benefits of the Research

To fill the gap in previous research, this study aimed to determine the success factors of various products. Additionally, it aimed to develop a mathematical model of the relationship between market share and success factors for various products. The research established the standardized factors that affect product success. The results of the study can be used to determine product development strategies by optimizing potential success factors; investigating these factors is important for companies.

This study has important implications for the research community on product development and success. The results showed that six standardized factors affect the success of various products: (1) price, (2) product performance, (3) brands, (4) aesthetic design, (5) services and (6) marketing (launching time). This study also produced some other interesting conclusions related to automotive products in the Indonesian market. For example, the relationship between market share and success factors in high-automotive, medium-automotive, and low-automotive models showed that increasing services will increase market share. The results concerning some success factors (i.e., product performance, brand, aesthetic design and marketing) varied, as these variables showed a variety of automotive compositions. The variables of price and marketing influenced the market share significantly in the high-automotive and low-automotive models. The aesthetic design significantly influenced the market share in the medium-automotive model. In the non-automotive (low-automotive) model, price, product performance, aesthetic design and services were positively correlated and proportional to market share. In the era of internet and big data storage, this study’s model can be used to predict the factors that drive success. The mathematical models in this study can be conducted by building a database of the model. Then, the results can predict the level of success of a particular product. Therefore, further research is needed to profile the characteristics of all factors completely. 

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article. This article was financially supported by the Ministry of Research, Technology and Higher Education of the Republic of Indonesia (project number 025/E3/2017).

Armunifah, I., 2014. Contribution of Launching Product Strategy toward Success Products. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Box, G.E., Hunter, J.S., Hunter, W.G., 2005. Statistics for Experimenters: Design, Innovation and Discovery. 2^nd Edition. USA: John Wiley & Sons, Inc

Cantner, U., Krüger, J., Söllner, R., 2012. Product Quality, Product Price, and Share Dynamics in German Compact Car Market. Industrial and Corporate Change, Volume 21(5), pp. 1085–1115

Cooper, R.G., Egdet, S.J., Kleinschimidt, E.J., 2014. Portofolio Management: Fundamental for New Product Success. Work Paper, State-Gate International and Product Development Institute, Inc. USA

Cooper, R.G., 1979a. Project New Produce in New Product Success. European Journal of Marketing, Volume 14(56), pp. 277–292

Cooper, R.G., 1979b. The Dimension of Industrial New Product Success and Failure. Journal of Marketing, Volume 43(3), pp. 93–103

Chuang, M., Chen, C., 2008. Integrating the Kano Models into a Robust Design Approach to Enhance Customer Satisfaction with Product Design. International Journal of Production Economics, Volume 114(2), pp. 667–681

Ernst, H., 2002. Success Factor of New Product Development: A Review of the Empirical Literature. International Journal of Management Reviews, Volume 4(1), pp. 1–40

Gao, G., Pan, Y., Tse, D., Yim, C., 2006. Market Share Performance of Foreign and Domestic Brands in China. Journal of International Marketing, Volume 14(2), pp. 32–51

Geng, Z., Grivoyannis, E., Zhang, S., He, Y., 2016. The Effects of the Interest Rates on Bank Risk in China: A Panel Data Regression Approach. International Journal of Engineering Business Management, Volume 8(1), pp. 1–7

Gozali, L., Masrom, M., Zagloel, T.Y.M., Haron, H.B., Garza-Reyes, J.A., Tjahjono, B.,  Irawan, A.P., Daywin, F.J., Syamas, A.F., Susanto, S., Aliwarga, H.K.K., Marie, I.A., 2020. Performance Factors for Successful Business Incubators in Indonesian Public Universities. International JournaI of Technology, Volume 11(1), pp. 156–166

Griffin, A., Page, A.L., 1993. An Interim Report on Measuring Product Development Success and Failure. Journal of Product Innovation Management, Volume 10(4), pp. 291–308

Hair, J.F., Black, B.C., Babin, B.J., and Anderson, R.E, 2010. Multivariate Data Analysis: A Global Persective (7^th ed.), Person, pp.133-147

Handaru, G.D., 2012. Prediction of Product Success based on Kano Methods in Bamboo Product. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Henard, D., Szymanski, D.M., 2001. Why Some New Products are More Successful than Others. Journal of Marketing Research, Volume 38(3), pp. 362–375

Jiang, Y., Liu, Y., 2012. Optimization of Online Promotion: A Profit-maximizing Model Integrating Price Discount and Product Recommendation. International Journal of Information Technology and Decision Making, Volume 11(5), pp. 961–982

Khentout , A., Kezzar, M, Khochemane, L.,  2019. Taguchi Optimization and Experimental Investigation of the Penetration Rate of Compact Polycrystalline Diamond Drilling Bits in Calcareous Rocks. International JournaI of Technology, Volume 10(2), pp. 225–235

Kleinknecht, A., Panne, G.V.D., 2012. Predicting New Product Sales: The Post Launch Performance of 215 Innovators. International Journal of Innovation Management, Volume 16(2), pp. 1–14

Kuruzovich, J., Han, S., Koukova, N., Ravichandran, T., 2013. Testing the Steve Jobs Hypothesis in B2B Context: Will a Portfolio of Hierarchically Related Technology Products Improve Customer Outcomes? Journal of Service Research, Volume 16(3), pp. 372–385

Lee, R.P., Zhou, K.Z., 2012. Is Product Imitation Good for Firm Performance? An Examination of Product Imitation Types and Contingency Factors. Journal of International Marketing, Volume 20(3), pp. 1–16

Lenggono, Y.B., 2016. Prediction Models of Automotive Product Success with Kano Approach. Master’s Thesis, Graduate Program, Department of Engineering, Dian Nuswantoro University, Semarang, Indonesia

Mitra, A., Patankar, J.G., 1997. Market Share and Warranty Cost for Renewable Warranty Programs. International Journal of Production Economics, Volume 50(2-3), pp. 155–168

Moon, J., Chadee, D., Tikoo, S., 2008. Culture, Product Type, and Price Influences on Customer Purchase Intention to Buy Personalized Product Online. Journal of Business Research, Volume 61(1), pp. 31–39

Montgomery, D.C., 2001. Design and Analysis of Experiments. 5^th Edition. USA: John Wiley & Sons, Inc

Montoya-Weiss, M.M., Calantone, R., 1994. Determinants of New Product Performance: A Review and Meta-analysis. Journal of Product Innovation Management, Volume 11(5), pp. 397–417

Mutjaba, A., 2013. Improvement of Success Prediction Models based on Kano Methods in Woods Product. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Nugroho, S.S., 2014. Relationship of Product Success and Success Factors in Services Product. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Postel, V., 2001. Can Good Looks Guarantee a Product Success? The New York Times. New York

Setyaningrum, R., Wijaya, A.R., Subagyo, 2016. Meta-analysis of Cultural Correlation and Product Success. Advanced Science Letters, Volume 22(12), pp. 4155–4158

Suharyanti, Y., Subagyo. B., Masruroh, N.A., Bastian, I., 2017. A Multiple Triangulation Analysis on the Role of Product Development Activities on Product Success. International Journal of Engineering Business Management, Volume 9(1), pp. 1–15

Susilowati, I.N., 2016. Effect of Distribution Channel to Success Products. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Torres, A., Tribo, J.A., 2011. Customer Satisfaction and Brand Equity. Journal of Business Research, Volume 64(10), pp. 1089–1096

Wijaya, W., 2011. Improvement of Product Success Prediction Models. Master’s Thesis, Graduate Program, Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, Indonesia

Wind, J., Rangaswamy A., 2001. Customerization: The Next Revolution in Mass Customization. Journal of Interactive Marketing, Volume 15(1), pp. 13–32

Woodhead, R., Berawi, M.A., 2020. Value Creation and the Pursuit of Multi Factor Productivity Improvement.  International JournaI of Technology, Volume 11(1), pp. 111–122