Year 3 Update | New Economic Models and Opportunities for digital Games

The New Economic Models and Opportunities for digital Games (NEMOG) project is now in its third year. Recently, many of the founding objectives of the project have been realised, making this a truly exciting time. Funded by ESRC and EPSRC, NEMOG is an interdisciplinary consortium of five universities (University of York, Cass Business School, Durham University and Northumbria University) with a dozen industry partners from around the UK. Our aim is to unlock the social, scientific, and economic benefits stemming from active video gameplay. To this end, our research in the third year has coalesced around eight main areas:

The 2016 NEMOG Symposium taking place on the 12^th of September, 2016 at the University of York, is our yearly public update on the project. In preparation for the event, and for those unable to join us on the day, we herein include a summary of outputs from this year.

Overarching Framework:

In the Year 2 update, we planned to develop a holistic business model framework to include the effect of data analytics to enable data-driven business models and the value ecosystem of the entire game industry, to synthesise all the insights we have gained across the NEMOG project. In Year 3, we found that the data captured or generated via ICT technologies, plays a critical role in decision making, operation management, and strategic management. To improve our understanding of the data-driven impact on a business model , we developed a holistic framework that captures the salient features of this relationship, based on evidence from Google Play Store. One academic paper is written and is ready to be submitted to a leading journal.

Mobile Game Industry Survey:

We captured another value from the dataset from the overarching framework study. We scraped the information of all Android app developers in the Google Play Store, filtered out all the game app developers who are officially registered in the UK as companies, and then combined with UK government’s Company House dataset. This exercise gave us great insight on UK’s mobile game industry transformation, and we found that the corresponding business model transformation does not take place in a vacuum. Seeing that as an opportunity, we mined data about game apps developed in the UK to study the relationship between the industry sector and labour and entrepreneurial mobility.

Business Model Transformation:

We want to understand what is the impact of business model transformation and knew scientific knowledge generations on an industrial and broader economic level. We performed an industrial historical analysis, and developed a framework that classifies the sector’s business models. Currently a journal paper is under review for publication at the Research Policy Journal. We also assessed the UK’s video games industry’s survivability and the impact of regional and national factors via three predictive statistical models. The research outputs were presented in Regional Studies Association Conference in Piacenza 2015, and is being considered for publication in the Technological Forecasting and Social Change Journal.

Business Model Resilience:

We assessed the resilience of the digital-games industry business model archetypes. Performing an in-depth historical analysis, we identified the evolutionary trajectory of the environmental driven business model change. This piece of work, combined with the business model classification framework, provides a solid time-space framework if the digital-games evolutionary trajectory, contributing towards a more in-depth understanding of the sector. A conference paper of this work has been presented at the 2016 European Group of Organisational Studies Colloquium.

Business Model Toolkit

Based on original research, we developed a toolkit aiming to provide practical guidance to practitioners, professionals, and entrepreneurs to make informed, and timely strategic decisions. Combined with the strategic roadmap function, the company is provided with a complete spectrum of alternative risk minimising action strategies. More importantly, the toolkit report can be of great benefit to potential investors that are interested in a technological intensive and vibrant sector such as the digital games industry. In addition, we are organising two events that will take place in London and Newcastle between the 19th and 29th of August. The Toolkit was presented at the 2016 R&D Management Conference.

Video Game Value Chain:

We investigated the key changes of the game industry via macro analysis at the value chain and business model level. These changes have been looked through in two different business environments: at the value chain level which is studied in crowdfunding and at the business model level which is studied within the serious games industry. One paper is developed and is being considered for publication in the Journal of Business Research.

Simulating Business Models via Game Playing:

We analysed the underlying grouping of the decks created by players of popular deck building games: Android: Netrunner and Magic: The Gatheringto allow us to identify play styles and synergies that can be used to inform game design and game play. We discovered different deck building strategies in the two games which we hypothesise is caused by the different business models. We found the different methods of card circulation in the two games are likely to affect the distribution of decks built due to card availability. We plan to focus on developing a technique amenable to analysing a broad range of games and their data to allow us to compare business models and strategies within games and their associated meta-games.

Analytics of Game Play Data:

We employed association rule mining techniques for predicting item multisets, and showed them to be effective in predicting the content of Netrunner decks. We then applied different modifications based on heuristic knowledge of the Android: Netrunner game, and showed the effectiveness of techniques which consider this knowledge during rule generation and prediction. The work is currently being extended to predict the content of opponent’s decks in Magic: The Gathering.