The model of products competition in mobile devices market Yana - PowerPoint PPT Presentation

The model of products competition in mobile devices market Yana Salikhova, PhD Assoc. Prof. of Marketing Department in St. Petersburg State University of Economics Victoria Grigoreva, PhD Assoc. Prof. of Management Department in St. Petersburg National Research University Higher School of Economics Ivan Svetunkov, PhD Assoc. Prof. of Centre for Marketing Analytics and Forecasting in Lancaster University, UK

Work is performed with financial support of the Russian Fund for Fundamental Researches, grant № 16-02-00172 «The development of multi-level competition theory, its methods and techniques» .

Outline Relevance Theoretical background Research method Findings and discussion 3

The relevance of the topic • The complexity of market structure Customer intermediary and sellers mobile device producers platform ecosystem developers

The relevance of the topic Traits of The role of the network carriers US mobile device market Carriers not only operate the network, (Kenney, but also sell handsets and provide Pon 2011) content carriers are making decisions about how data is consumed on their networks and what services can be used

The relevance of the topic • The anti-trust lawsuits Microsoft bundling its browser to its operating system (Winkler, 2014) Google Google service as main on the device ((Edelman, 2015). investigating Google’s tactics in mobile (Kendall and Barr, Google 2015)

Theoretical background • examines whether it is the concentration in the market that causes the firms to mutually collude Structural to enhance market power, or there are some other factors responsible for it (Rezitis, 2010) • observes that when the size of the firm increases, its share in market Non-structu also increases and provides an ral opportunity for that firm to earn higher profits (Claessens and Laeven, 2004).

Research method Sample Data Data selection collection analysis • Top 6 US • Euromonitor • segment tablet and Internationa approach smartphone l database, • Model of vendors • IDC shares dynamics

Segment approach to market concentration • heterogeneity of commodity markets , a set of separate parts (segments) reflecting the demand characteristics of different types of consumers; • product differentiation and methods of its marketing; • the intensity of competition on one segment may differ from the intensity of competition in another segment and the entire market

Evaluation of market structure • the degree of market concentration (CR, HHI, Holl-Taydman, an index of entropy and Jeanie's coefficient and etc.) • the degree of market share distribution by segment - Ratio of shares distribution

Market concentration US tablet and smartphone vendors, Market share, First Quarter 2017 Brand Tablet Smartphone Market share Apple 24,7 43,6 24,1 Samsung 15,1 28,5 17,5 Motorola (Lenovo) 7 5 4,1 Huawei 6 0 0,4 HTC 0 3,2 1,6 LG 0 9,6 9,4 CR4=55,1 K=0,09 Sources: comScore Mobilens, IDC Quarterly Personal Computing Device Tracker, 2017, Euromonitor International database, 2017

Market types in the concentration degree Market share Market concentration distribution by Low Moderately Highly segment concentrated concentrated concentrated Uniform Oligopoly Inhomogeneous Segment distribution oligopoly monopoly Oligopoly with Inhomogeneous Monopoly with Nonuniform with features oligopoly with segment distribution of segment features of competition monopoly segment monopoly

Research development Modelling dynamics of ecosystems of products in mobile devices market

The Idea 1. Model the dynamics of shares of companies in the market of mobile devices; 2. Take possible connections of different types of products (e.g. iPhone and iPad); 3. Get estimates of overall shares of companies in the mobile devices market; 4. Forecast the shares dynamics for several years ahead.

What to do 1. Calculate shares of sales of each product type in each category. 2. Transform the data by dividing by number of categories, so all of that adds up to one. 3. Form vectors of shares in mobile devices market. 4. Choose the model. 5. Model estimation and validation. 6. Error measure. 7. Analyse the model. 8. Produce forecasts.

1. Calculate shares of sales of each product type in each category. let’s assume that we have the following shares in 2016: Apple Samsung Lenovo LG Overall Smartphones 42% 23% 15% 20% 100% Tablets 37% 30% 27% 6% 100% Overall 79% 53% 42% 26% 200% 2. Transform the data by dividing by number of categories, so all of that adds up to one. Apple Samsung Lenovo LG Overall Smartphones 21% 12% 8% 10% 50% Tablets 19% 15% 14% 3% 50% Overall 40% 27% 22% 13% 100%

3. Form vectors of shares in mobile devices market. Name of product Shares, 2016 Smartphones, Apple 21% Smartphones, Samsung 12% Smartphones, Lenovo 8% Smartphones, LG 10% Tablets, Apple 19% Tablets, Samsung 15% Tablets, Lenovo 14% Tablets, LG 3% These values will be encoded as Yt , where t is the time index.

4. Choose the model . where A1 is the square matrix of parameters, which has size of n×n (in our example n=8 ) and Et is the vector of errors of the model, assumed to be distributed normally. This way matrix A1 will contain parameters that characterise the relation between different shares today and the same shares last year. For example, if there is a connection between “Smartphones, Apple” in 2016 and “Tablets, Apple” in 2015, this will be captured by the corresponding parameter in A1 .

5.Each of the elements of Y t should be positive; We propose a simple modification that addresses this issue: where A ∘ B is the Hadamar product (element wise multiplication of vectors) and Et is assumed to have multivariate log-normal distribution. In this model A1Yt − 1 is a vector, each element of which is multiplied by each element of the vector Et . Now Y t is always positive.

6. The sum of elements of Y t should be equal to one . For example, the previous model can be modified the following way: where 1n' is the vector of ones, which means that in the denominator we sum up all the values produced by the model . The number of these past shares is denoted as p : An alternative approach of reconciliation is to use modified VAR model, where only firs t n − 1 shares are taken into account and the last is formed as “one minus sum of firs t n − 1 shares”.

Last steps 7. Model estimation and validation. 8. Analyse the model. 9. Produce forecasts.

Thank you for the attention!

The model of products competition in mobile devices market Yana Salikhova, PhD Assoc. Prof. of Marketing Department in St. Petersburg State University of Economics Victoria Grigoreva, PhD Assoc. Prof. of Management Department in St. Petersburg National Research University Higher School of Economics Ivan Svetunkov, PhD Assoc. Prof. of Centre for Marketing Analytics and Forecasting in Lancaster University, UK