A Multigeneration Diffusion Model for IT-Intensive Game Consoles

The video game industry has attracted more and more attention not only from technology giants such as Microsoft but also from software developers and private investors. Information technology dictates how game console producers compete in the marketplace. Intensive IT competition in each console generation has shifted the market balance. Competitors jockey to position themselves as the first-mover within a generation or to wait and enter the market with cheaper and more advanced technologies. To capture the characteristics of IT-intensive products, we propose a multigeneration diffusion model that captures both cannibalization and competition effects. We apply the model to analyze game console diffusion with real shipment data for three game consoles from two companies: Sony and Microsoft. We analyze two scenarios: one with only Sony¡¯s products, and one with both companies¡¯ products. We find that the cannibalization between Sony¡¯s products is minimal, and Microsoft maintains a strong competitive edge that has challenged Sony¡¯s market position. The results also explain how Sony has maintained its position as the market leader over the last two generations. This research sheds light on the nature of an IT-intensive game console competition between companies and generations

The Launch Timing of New and Dominant Multigeneration Technologies

In this paper we introduce a model that is suitable to study the diffusion of new and dominant multi-generation technologies. Examples are computer operat- ing systems, mobile phone standards, video game consoles. Our model incorporates three new features that are not included in related models. First, we add the ability of a firm to transfer users of its old technologies to the new generations, what we call firms’ alpha. Second, we add competitive relations between market technolo- gies. Third, the launch strategies diagnosed by our model cover, as special cases, the now or never strategies and hence it is suitable to study intermediate launch strategies. We find that the appropriate timing of a new technology depends heavily on both the firms’ alphas and on the competitive positioning of their products. In addition, we argue that the strategic interaction of firms may lead to very different sales outcomes depending on the competitive positioning of their products. In the VGC case we find that the Nintendo Wii was launched at an appropriate moment while the Sony PS3 perhaps should have never been launched

Examining Trends of Technology Diffusion Theories in Information Systems

Since the publication of Roger’s fifth edition of Diffusion of Innovations in 2003, there is a need to investigate the recent Innovation Diffusion Theory (IDT) for Information Systems (IS) research for the purpose of finding trends. Much research has been conducted and needs to be synthesized to map a direction for future research. The methodology used in this study is meta-analysis of recent IDT IS research (2003-2011) published in the top eight IS Journals and the International Conference on Information Systems (ICIS). The study’s initial meta-analysis findings suggest that more variables are tested by many studies to increase richness and attempts are made for more objective measures of the Rate of Adoption variable to improve clarity. The paper’s contribution is the direction of Effective Information Systems which can be measured by diffusion into social systems, internationally and collaboratively

Digital supply chain management in the videogames industry: a systematic literature review

As industries mature, they rely more heavily on supply chain management (SCM) to ensure effective operations leading to greater levels of organisational performance. SCM has been widely covered in many industrial areas and, in line with other burgeoning sectors such as Tourism, an industry focus provides the opportunity to look in-depth at the context-based factors that affect SCM. Developments in digital distribution and rapid technological innovations have resulted in an increased focus on Digital Supply Chains (DSCs), which bring about significant changes to how consumers, customers, suppliers, and manufacturers interact, affecting supply chain design and processes. Through a systematic review of the Videogames Industry Supply Chain Management literature, which serves as a pertinent contextual example of a DSC, we look at how supply chains are affected by structural, market and technological change, such as increased platformisation, disintermediation and the proliferation of digital distribution. We distil these findings into a new research agenda, which identifies themes in line with extant DSC research, provides a series of relevant practice recommendations and identifies opportunities for future research

Social Media Networks: The Social Influence of Sentiment Content in Online Conversations on Dynamic Patterns of Adoption and Diffusion

The current study is focusing on diffusion and adoption of new digital artifacts. The goal is to explore the social role of user-generated content (UGC) during the diffusion process of digital artifacts in the context of online social networks. The study spans a wide range of analytics methods and tools such as predictive modeling, latent sentiment analysis, data retrieval, and other tools of time-series analysis & visualization. Data collection is conducted on 260 new digital products and more than 105 thousand social network nodes. Results of the study provide a deeper insight into the influence of textual UGC sentiment on new product diffusion and how such a web system (i.e.: online social networks) can help to enable a process of value co-creation. The overall finding shows that Volume of Post and UGC Sentiment have a dynamic impact on Diffusion (Adoption Rate) of digital products. But, the relationships among them depend on certain situations. Specifically, UGC Sentiment has a dynamic impact on Adoption Rate in the early stage of the diffusion process. That is UGC Sentiment and Adoption Rate have a reciprocal relationship during the early stage. However, this relationship was faded out in the later stage. Volume of Post has a positive impact on Adoption Rate throughout the process. Both UGC Sentiment and Volume of Post are also more likely to influence on a single-generation and successful product than a multiple-generation product. Surprisingly, Depth of Post and Ratings did not play a significant role in the diffusion process. The study sheds light on the crowding power and the long-tail effect in online social networks. Findings also offer valuable implications for organizations to set up their strategic vision in terms of targeted marketing, customer relationship management, and information dissemination

The development and evolution of dominant logic in an innovation project

Master'sMASTER OF SCIENC

Crecimiento de firmas de ingreso tardío a mercados de software estandarizado: un enfoque desde la modelación de la difusión competitiva multigeneracional, con efectos de red.

Según el orden de entrada al mercado, las firmas se clasifican como Pioneras, Seguidoras Tempranas y Entrantes Tardías (en adelante, estas últimas se denominarán ET) (Ansoff and Stewart, 1967). En la industria de software, existe abundante evidencia de que tanto el tiempo de entrada de una innovación disruptiva en el mercado (Keller and Hüsig, 2009), como las ventajas comparativas de la región en la que emerge (Arora and Gambardella, 2005)y la trayectoria tomada por el paradigma tecnológico en el cual están inscritos sus productos, tienden a un crecimiento dependiente de la trayectoria (D'Costa, 2002). Podría interpretarse entonces, que la adopción de los productos de las firmas de software es sensible a factores aleatorios e idiosincráticos presentes al inicio de la difusión, los cuales tienen impactos en los resultados finales. Estas condiciones pueden ubicar a la Pionera en una posición ventajosa frente a sus seguidores. Sin embargo, la incertidumbre tecnológica y de mercado puede hacer que una Pionera quede en condición de desventaja frente a las ET (Lieberman and Montgomery, 1998). Adicionalmente, la Pionera enfrenta el riesgo de seguir una trayectoria tecnológicamente inferior ante la llegada de una ET capaz de introducir en el mercado nuevas generaciones de producto compatibles con el estándar, como en el caso Microsoft Corp. y Google Inc. descrito por Keller and Hüsig (2009). El fenómeno del crecimiento de firmas ET es un desafío que ha venido ganado atención por más de una década, tanto en la literatura de pronóstico tecnológico (Rousseva, 2008),como en economía (Arora and Gambardella, 2005)y política (Schware, 1992; Soete, 1985; Steinmueller, 2001).Sin embargo, si las firmas ET pueden sostener o no sus tasas de crecimiento, sigue siendo una cuestión que se ha abordado empíricamente. Dadas las características del crecimiento de firmas en mercados de software, dos instrumentos teóricos parecen promisorios para el modelamiento del fenómeno. Por un lado la teoría de la difusión de la innovación, enfocada en la explicación y el pronóstico del proceso de adopción de productos por una población de usuarios potenciales de la firma. Por otro, la teoría de los efectos de red, que considera una dinámica en la que los adoptadores potenciales se benefician por comprar el producto de la firma que cuente con mayor base instalada -externalidades de red directas- y con compatibilidad con múltiples productos–externalidades de red indirectas-. Se dispone de abundante literatura para el modelado de la difusión de la innovación (Bass F. , 1969; Bass and Bass, 2001; Maier, 1998; Meade and Islam, 2006; Chanda and Bardhan, 2008)y el modelado de los efectos de red (Oren, Smith, and Wilson, 1982; Katz and Shapiro, 1985; Economides, 1996; Farrell and Saloner, 1986; Church and Gandal, 1996). Von Westarp (2003)y Kemper (2010)hacen contribuciones al modelado de mercados de software; sin embargo, no consideran la difusión competitiva multi-generacional y con efectos de red, presente en el crecimiento a largo plazo de firmas de software. Esta investigación se enmarcada y valida en seis postulados que pueden explicar el crecimiento de ET a mercados de software estandarizado, a saber: i) el indicador de crecimiento de las firmas es la venta anual (Peres, R., Muller, E., and Mahajan, V., 2010); ii) el potencial de mercado es dinámico en función de los efectos de red (β) considerados por Liu et al. (2011); iv) una firma de software sale del mercado cuando no difunde nuevos productos después de dos años de la introducción del producto anterior (Giarratana, 2004); v) en la fabricación de software estandarizado, los principales costos para el desarrollo del producto ocurren en la fase de I and D (OECD, 2009); la inversión en I and D es un indicador de capacidad de innovación. La entrada necesaria para acumular capacidad en I and D es el porcentaje anual de ventas destinado a inversión en I and D y la salida se mide en número de nuevas generaciones de producto que se difunden en el mercado (Li, Shang, and Slaughter, 2010; OECD, 2009). En esta investigación doctoral se explica el fenómeno de crecimiento de firmas ET inmersas en un ambiente de competencia contra un Pionera, mediante la simulación de un modelo y se evalúa la sensibilidad del comportamiento de las ventas, a la inversión en I+D y al tiempo de entrada de sucesivas generaciones del producto. Las múltiples simulaciones del modelo muestran que invertir en I+D, aumentar la base instalada mediante los beneficios de las externalidades de red en la demanda, e introducir en el mercado múltiples generaciones de productos más rápidamente que la Pionera, son estrategias promisorias para que las ET sobrevivan en el mercado./ Abstract. According to their order of market entry, firms are classified as Pioneers, Early Followers and Late Starters(hereinafter, the latter will be referred to as LS) (Ansoff and Stewart, 1967).In the software industry, there is abundant evidence that both the time of entry of a disruptive innovation in the market(Keller and Hüsig, 2009), as the region’s comparative advantages where it emerges(Arora and Gambardella, 2005)and the trajectory taken by the technological paradigm in which their products are inscribed, tend to a trajectory dependent growth (D'Costa, 2002). It could be interpreted then that the adoption of the products of the software firms is sensitive to random and idiosyncratic factors present at the beginning of the diffusion which have impacts on the final results. These conditions can place the Pioneer firms at an advantage against its followers. However, the technological and market uncertainty can place a Pioneer firm in a position of disadvantage compare to the LS firm (Lieberman and Montgomery, 1998). Additionally, the Pioneer firm faces the risk of following a trajectory technologically inferior to the arrival of a LS firm capable of introducing into the market new generations of products compatible with the standard, as in the case of Microsoft Corp. and Google Inc. described by Keller and Hüsig (2009). The phenomenon of LS firms growth is a challenge that has increasingly gained attention for more than a decade, both in technological forecasting literature(Rousseva, 2008),economics(Arora and Gambardella, 2005)and politics(Schware, 1992; Soete, 1985; Steinmueller, 2001).However, whether the LS firms can sustain their growth rates, remains an issue which has been addressed empirically. Given the growth characteristics of firms within the software markets, two theoretical tools seem promising for the modeling of the phenomenon. On the one hand the theory of innovation diffusion, focused on explaining and predicting the product adoption process by a population of potential users of the firm. On the other hand, the theory of network effects, which considers a dynamic in which potential adopters benefit by purchasing the product of the firm that has the largest installed base –direct network externalities- and with compatibility with multiple products–indirect network externalities-. There is abundant literature for modeling the diffusion of innovation (Bass F. , 1969; Bass and Bass, 2001; Maier, 1998; Meade and Islam, 2006; Chanda and Bardhan, 2008)and modeling of network effects (Oren, Smith, and Wilson, 1982; Katz and Shapiro, 1985; Economides, 1996; Farrell and Saloner, 1986; Church and Gandal, 1996). Von Westarp (2003)and Kemper (2010)make contributions to the modeling of software markets; however, they do not consider the multi-generational competitive diffusion and network effects, present in long-term growth of software firms. This research is framed and validated in six principles that can explain the growth of LS firms to standardized software markets, namely: i) the indicator of firm growth is the annual sale (Peres, R., Muller, E., and Mahajan, V., 2010); ii) the potential market is dynamic in terms of network effects(β)considered by Liu et al. (2011); iv) a software firm drops out from the market when it does not disseminate new products after two years of the introduction of the last product (Giarratana, 2004); v) in the manufacture of standardized software, the main costs for the development of a product occur in the I and D phase (OECD, 2009); investment in I and D is an indicator of innovation capacity. The input required to build capacity in I and D is the annual percentage of sales allocated to investment in I and D and the output is measured in the number of new product generations that are spread out in the market (Li, Shang, and Slaughter, 2010; OECD, 2009). This doctoral research explains the growth phenomenon of LS firms immersed in a competitive environment against a Pioneer firm, by simulating a model and evaluating the sensitivity of sales performance, investment in I+D and the time of entrance of successive product generations. The multiple model simulations show that investing in I+D, increasing the installed base through the benefits of network externalities in demand, and bringing to market multiple generations of products faster than the Pioneer firm, are promising strategies for the LS firms survival in the market.Doctorad

Detection and Measurement of Sales Cannibalization in Information Technology Markets

Characteristic features of Information Technology (IT), such as its intrinsic modularity and distinctive cost structure, incentivize IT vendors to implement growth strategies based on launching variants of a basic offering. These variants are by design substitutable to some degree and may contend for the same customers instead of winning new ones from competitors or from an expansion of the market. They may thus generate intra-organizational sales diversion – i.e., sales cannibalization. The occurrence of cannibalization between two offerings must be verified (the detection problem) and quantified (the measurement problem), before the offering with cannibalistic potential is introduced into the market (ex-ante estimation) and/or afterwards (ex-post estimation). In IT markets, both detection and measurement of cannibalization are challenging. The dynamics of technological innovation featured in these markets may namely alter, hide, or confound cannibalization effects. To address these research problems, we elaborated novel methodologies for the detection and measurement of cannibalization in IT markets and applied them to four exemplary case studies. We employed both quantitative and qualitative methodologies, thus implementing a mixed-method multi- case research design. The first case study focuses on product cannibalization in the context of continuous product innovation. We investigated demand interrelationships among Apple handheld devices by means of econometric models with exogenous structural breaks (i.e., whose date of occurrence is given a priori). In particular, we estimated how sales of the iPod line of portable music players were affected by new-product launches within the iPod line itself and by the introduction of iPhone smartphones and iPad tablets. We could find evidence of expansion in total line revenues, driven by iPod line extensions, and inter- categorical cannibalization, due to iPhones and iPads Mini. The second empirical application tackles platform cannibalization, when a platform provider becomes complementor of an innovative third party platform thus competing with its own proprietary one. We ascertained whether the diffusion of GPS-enabled smartphones and navigation apps affected sales of portable navigation devices. Using a unit-root test with endogenous breaks (i.e., whose date of occurrence is estimated), we identified a negative shift in the sales of the two leaders in the navigation market and dated it at the third quarter of 2008, when the iOS and Android mobile ecosystems were introduced. Later launches of their own navigation apps did not significantly affect these manufacturers’ sales further. The third case study addresses channel cannibalization. We explored the channel adoption decision of organizational buyers of business software applications, in light of the rising popularity of online sales channels in consumer markets. We constructed a qualitative channel adoption model which takes into account the relevant drivers and barriers of channel adoption, their interdependences, and the buying process phases. Our findings suggest that, in the enterprise software market, online channels will not cannibalize offline ones unless some typical characteristics of enterprise software applications change. The fourth case study deals with business model cannibalization – the organizational decision to cannibalize an existent business model for a more innovative one. We examined the transition of two enterprise software vendors from on-premise to on-demand software delivery. Relying on a mixed- method research approach, built on the quantitative and qualitative methodologies from the previous case studies, we identified the transition milestones and assessed their impact on financial performances. The cannibalization between on-premise and on-demand is also the scenario for an illustrative simulation study of the cannibalization