Exploring survival rates of companies in the UK video-games industry: An empirical study

The study presented in this paper investigates companies operating in the UK video-game industry with regard to their levels of survivability. Using a unique dataset of companies founded between 2009 and 2014, and combining elements and theories from the fields of Organisational Ecology and Industrial Organisation, the authors develop a set of hierarchical logistic regressions to explore and examine the effects of a range of variables such as industry concentration, market size and density on companies' survival rates. The analysis addresses locational dimension of the video-game industry is considered by introducing an extra regionally-related variable into the models, associated with the number of video-game university programmes locally available. In addition, companies are investigated with regard to their organisational type in order to identify potential effects associated with their intrinsic organisational structures. Findings from the analysis confirm that UK video-game companies operate in an increasingly globalised market, limiting the effects related to any operation conducted at a local level. For instance, a higher supply of specialised graduates within spatial proximity does not contribute significantly to increase the chances of survivability of video-game companies, although different locations seem to provide better conditions and higher life expectancy, mainly due to positive network effects occurring at a local level. Results seem also to suggest that investing in managerial resources increases businesses' survival rates, corroborating evidence about the significant role entrepreneurs have for companies operating within innovative and technologically intensive industries.

From value chains to technological platforms: The effects of crowdfunding in the digital game industry

This study contributes to understanding the effects of crowdfunding on the value creation process in the digital game industry. Specifically, it integrates the value chain logic with the platform logic to examine collaborative value creation enabled by opening up the business models of game developers to the crowd. Through a multiple case design this research shows that the benefit of using crowdfunding goes well beyond fundraising. As an implementation of open innovation, crowdfunding unifies the channels that bring capital, technology and market knowledge from the crowd into the game. This finding leads to the exploration of a new complex system of interactions between game developers and value chain stakeholders, and invokes the analysis of crowdfunding as a form of technological platform to identify and analyze new types of collaboration and competition. This research limits its findings to the effects of reward-based crowdfunding. Other forms of crowdfunding require further investigations. The paper also aims to help practitioners understand how crowdfunding is transforming the game industry.

Combining Gameplay Data With Monte Carlo Tree Search To Emulate Human Play

Monte Carlo Tree Search (MCTS) has become a popular solution for controlling non-player characters. Its use has repeatedly been shown to be capable of creating strong game playing opponents. However, the emergent playstyle of agents using MCTS is not necessarily human-like, believable or enjoyable. AI Factory Spades, currently the top rated Spades game in the Google Play store, uses a variant of MCTS to control non-player characters. In collaboration with the developers, we collected gameplay data from 27,592 games and showed in a previous study that the playstyle of human players significantly differed from that of the non-player characters. This paper presents a method of biasing MCTS using human gameplay data to create Spades playing agents that emulate human play whilst maintaining a strong, competitive performance. The methods of player modelling and biasing MCTS presented in this study are generally applicable to digital games with discrete actions. 

Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner

As part of their design, card games often include information that is hidden from opponents and represents a strategic advantage if discovered. A player that can discover this information will be able to alter their strategy based on the nature of that information, and therefore become a more competent opponent. In this paper, we employ association rule-mining techniques for predicting item multisets, and show them to be effective in predicting the content of Netrunner decks. We then apply different modifications based on heuristic knowledge of the Netrunner game, and show the effectiveness of techniques which consider this knowledge during rule generation and prediction. 

A Conceptual Framework of Business Model Emerging Resilience

In this paper we introduce an environmentally driven conceptual framework of Business Model change. Business models acquired substantial momentum in academic literature during the past decade. Several studies focused on what exactly constitutes a Business Model (role model, recipe, architecture etc.) triggering a theoretical debate about the Business Model’s components and their corresponding dynamics and relationships. In this paper, we argue that for Business Models as cognitive structures, are highly influenced in terms of relevance by the context of application, which consequently enriches its functionality. As a result, the Business Model can be used either as a role model (benchmarking) or a recipe (strategy). For that purpose, we assume that the Business Model is embedded within the economic (task) environment, and consequently affected by it. Through a typology of the environmental impact on the Business Model productivity, we introduce a conceptual framework that aims to capture the salient features of Business Model emergent resilience as reaction to two types impact: productivity constraining and disturbing.

The impact of organizational culture on Concurrent Engineering, Design-for-Safety, and product safety performance

This paper empirically extends the research on the relationships between organizational culture, new product development (NPD) practices, and product safety performance (PSP). Using Schein's conceptualization of culture (i.e., underlying assumptions, espoused values, and artifacts), we build and test a model among five variables: top management commitment to safety (MCS), group level product safety culture (PSC) at NPD, Concurrent Engineering (CE), Design-for-Safety (DFS), and product safety performance. We propose that the underlying assumption of safety first affects the espoused values (group level product safety culture at NPD) and artifacts of organizational culture (Concurrent Engineering and Design-for-Safety); espoused value influences artifacts; and artifacts impact product safety performance. These hypotheses are tested by structural analyses of 255 survey responses collected from 126 firms in the juvenile product sector. While management commitment to safety, product safety culture, and Design-for-Safety are significant product safety predictors, as expected, Concurrent Engineering has no significant direct effect on product safety. We discuss the implications of these findings for the field of product safety.

A Strategic Roadmap for Business Model Change for the Video-games Industry

The global video games industry has experienced and exponential growth in terms of socioeconomic impact during the last 50 years. Surprisingly, little academic interest is directed towards the industry, particularly in the context of BM Change. As a technologically intensive creative industry, developing studios and publishers experience substantial internal and external forces to identify, and sustain, their competitive advantage. To achieve that, managers are called to systematically explore and exploit, alternative BMs that are compatible with the company’s strategy. We build on empirical analysis of the video-games industry to construct a Toolkit that i) will help practitioners and academics to describe the industrial ecosystem of BMs more accurately, and ii) use it a strategic roadmap for managers to navigate through alternatives for entrepreneurial and growth purposes.

The UK Video-game Industry in 2009 – 2014: Companies’ Survival Rates and Population Analysis from an Organisational Ecology Perspective

Since its first development in early 1970, the video-game industry has experienced a considerable growth in terms of economic and societal impact. Video-games are regarded as an integral part of the broader creative industries. Similarly to other entertainment industries, such as film and music, video-games are frequently characterised by project-based production processes and face some market-related risks that affect their level of competitiveness and survival in the market. The study presented in this paper aims to explore and examine the UK video-game industry through the prism of Organisational Ecology and Industrial Organisation. Using hierarchical logistic models, the authors investigate UK-based video-game companies in relation to a range of traditional explanatory variables related to market survival rates. Findings from the analysis suggest that predictions related to companies’ success of failure can be further enhanced with the introduction of variables related to the location and type of organisation the companies, captured with information gathered from their corresponding postcodes and SIC codes respectively. 

Player Preference and Style in a Leading Mobile Card Game

Tuning game difficulty prior to release requires careful consideration. Players can quickly lose interest in a game if it is too hard or too easy. Assessing how players will cope prior to release is often inaccurate. However, modern games can now collect sufficient data to perform large scale analysis postdeployment and update the product based on these insights. AI Factory Spades is currently the top rated Spades game in the Google Play store. In collaboration with the developers, we have collected gameplay data from 27 592 games and statistics regarding wins/losses for 99 866 games using Google Analytics. Using the data collected, this study analyses the difficulty and behaviour of an Information Set Monte Carlo Tree Search player we developed and deployed in the game previously. The methods of data collection and analysis presented in this study are generally applicable. The same workflow could be used to analyse the difficulty and typical player or opponent behaviour in any game. Furthermore, addressing issues of difficulty or non-human-like opponents post-deployment can positively affect player retention.

Predicting Player Disengagement and First Purchase with Event-Frequency Based Data Representation

In the game industry, especially for free to play games, player retention and purchases are important issues. There have been several approaches investigated towards predicting them by players’ behaviours during game sessions. However, most current methods are only available for specific games because the data representations utilised are usually game specific. This work intends to use frequency of game events as data representations to predict both players’ disengagement from game and the decisions of their first purchases. This method is able to provide better generality because events exist in every game and no knowledge of any event but their frequency is needed. In addition, this event frequency based method will also be compared with a recent work by Runge et al. in terms of disengagement prediction.  A pre-print of this paper is available here.

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