Martha G. Russell

Understanding Business Ecosystem Dynamics: A Data-Driven Approach

Business ecosystems consist of a heterogeneous and continuously evolving set of entities that are interconnected through a complex, global network of relationships. However, there is no well-established methodology to study the dynamics of this network. Traditional approaches have primarily utilized a single source of data of relatively established firms; however, these approaches ignore the vast number of relevant activities that often occur at the individual and entrepreneurial levels. We argue that a data-driven visualization approach, using both institutionally and socially curated datasets, can provide important complementary, triangulated explanatory insights into the dynamics of interorganizational networks in general and business ecosystems in particular. We develop novel visualization layouts to help decision makers systemically identify and compare ecosystems. Using traditionally disconnected data sources on deals and alliance relationships (DARs), executive and funding relationships (EFRs), and public opinion and discourse (POD), we empirically illustrate our data-driven method of data triangulation and visualization techniques through three cases in the mobile industry Google’s acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.

A Call for Creativity in New Metrics for Liquid Media

ABSTRACT This paper presents a call for creativity, within adaptive structures, to develop new metrics for new media. It first reviews recent innovations in audience metrics for online media, including some evolving metrics for the Web 2.0 media ecosystem. It then describes the disciplinary roots of academic research on which the current understanding of audience engagement and persuasion are based. It further describes current software and hardware developments that are driving a new era of liquid media. A framework for conceptualizing layers of media delivery and audience engagement that will be enabled by these new technologies is described. Recommendations are made for collaboration between academics and practitioners in order to rapidly pursue an understanding of advertising effectiveness in this new environment and to develop metrics that can be harnessed to monetize audience engagement, rationalize media expenditures, and create reporting structures for sharing insights.

Insights for orchestrating innovation ecosystems: the case of EIT ICT Labs and data-driven network visualisations

This paper explores opportunities for supporting the orchestration of innovation ecosystems, hence contributing to a fundamental capability in the networked world. We present analysis, evaluation and interpretation toward the objective of decision support and insights for transforming innovation ecosystems with a case study of EIT ICT Labs, a major initiative intended to turn Europe into a global leader in ICT innovation. Towards this, we use a data-driven, relationship-based and network centric approach to operationalise the ‘innovation ecosystems transformation framework’. Our results indicate that with coordinated and continuously improved use of visual and quantitative social network analysis, special characteristics, significant actors and connections in the innovation ecosystem can be revealed to develop new insights. We conclude that the IETF transformation framework can be used to develop shared vision and to support the orchestration of innovation ecosystem transformations.

Visual decision support for business ecosystem analysis

Comparative evaluation of the effectiveness of three ecosystem visualization methods.Extend cognitive fit theory to examine impact of ecosystem complexity and task type.Ecosystem complexity significantly influences decision performance.Contribute to our understanding of visual business ecosystem intelligence tools. This study comparatively evaluates the effectiveness of three visualization methods (list, matrix, network) and the influence of data complexity, task type, and user characteristics on decision performance in the context of business ecosystem analysis. We pursue this objective using an exploratory study with 14 prototypical users (e.g. executives, analysts, investors, and policy makers). The results show that in low complexity contexts, decision performance between visual representations differ but not substantially. In high complexity contexts, however, decision performance suffers significantly if visual representations are not appropriately matched to task types. Our study makes several theoretical and practical contributions. Theoretically, we extend cognitive fit theory by investigating the impact of business ecosystem task type and complexity. Managerially, our study contributes to the relatively underexplored, but emerging area of the design of business ecosystem intelligence tools and presentation of business ecosystem data for the purpose of decision making. We conclude with future research opportunities.

Ostinato: The Exploration-Automation Cycle of User-Centric, Process-Automated Data-Driven Visual Network Analytics

Network analysis is a valuable method for investigating and mapping the social structure driving phenomena and sharing the findings with others. The interactive visual analytics approach transforms data into views that allow the visual exploration of the structures and processes of networks represented by data, therefore increasing the transparency of editorial processes on social media as well as networked structures in innovation ecosystems and other phenomena. Although existing tools have opened many new exploratory opportunities, new tools in development promise investigators even greater freedom to interact with the data, refine and analyze the data, and explore alternative explanations for networked processes. This chapter presents the Ostinato Model—an iterative, user-centric, process-automated model for data-driven visual network analytics. The Ostinato Model simultaneously supports the automation of the process and enables interactive and transparent exploration. The model has two phases, Data Collection and Refinement and Network Creation and Analysis. The Data Collection and Refinement phase is further divided into Entity Index Creation, Web/API Crawling, Scraping, and Data Aggregation. The Network Construction and Analysis phase is composed of Filtering in Entities, Node and Edge Creation, Metrics Calculation, Node and Edge Filtering, Entity Index Refinement, Layout Processing and Visual Properties Configuration. A cycle of exploration and automation characterizes the model and is embedded in each phase.

Alumni network analysis

Alumni connections are important resources that contribute to university evaluation. Even though alumni connections represent networks, they have been mostly evaluated as tabular data (e.g. by providing average salary, employment rate, etc.). This ironically disregards all qualities of a network, from which an alumni network gets its name. It is desirable to evaluate an alumni network as a network, because networks have the potential to provide very insightful information. Evaluation of alumni networks as a network has not been feasible in the past due to data fragmentation (neither universities nor companies willing to share meaningfully significant data in its entirety). Recently the feasibility of such analysis has changed, due to new trends towards democratization of information, accelerated by the Web 2.0 user-generated content phenomenon and crowd-sourcing mentality. Utilizing web-crawlers, we actively harvested data and assembled a dataset on alumni in leadership positions in technology-based industries. Moreover, we included a high proportion of startup companies, which allowed us to evaluate alumni networks with respect to entrepreneurial as well as technology involvement. We show that by analyzing alumni connections as networks, it is possible to uncover new patterns, as well as provide a new way of examining the old.

Narrowcast Pricebook-Driven Persuasion: Engagement at Point of Influence, Purchase and Consumption in Distributed Retail Environments

The integration of information systems with advertising over wireless and broadband communications opens opportunities for sophisticated services to be delivered to small and medium sized organizations which often do not have the telecommunications, data management or integrated operations infrastructure and staff that are often maintained by many large organizations. This study of the effectiveness in retail locations of a narrowcast price book-driven video messaging system documents the impact of the marketing messages in influencing consumer attention, perception and behavior. Results point to increased category and brand purchases, as well as improved perceptions of store benevolence and staff effectiveness. Product marketers, brand managers, retailers, engineers, and academicians can draw actionable insights for the use of price book-driven video messaging system by understanding the dynamics of engagement in persuasive technologies. The participation of information scientists is needed in order to develop valid and actionable analytics that serve both the information sciences and retail communities.

Benevolence and Effectiveness: Persuasive Technology's Spillover Effects in Retail Settings

Results point to perceived store benevolence and staff effectiveness as important spillover effects in the use of persuasive technologies in the retail setting. The comparison of customer exit interviews, conducted at control stores and at test stores, before and after the introduction of video displays playing advertising and promotion messages, documented that customers noticed the displays, recalled the content and were influenced toward the desired effect. Additionally, significant attitudinal differences related to customer perception of staff and stores were also noted. Product marketers, brand managers, retailers, and academicians can draw actionable insights for the use of persuasive technologies by understanding the impact of persuasive technologies on relational exchanges.

Visualizing the Geography of Platform Boundary Resources: The Case of the Global API Ecosystem

Platform boundary resources play an increasingly transformative role in the global digital ecosystem. In this study, we focus on one type of platform boundary resource, namely application programming interfaces (APIs). Guided by two competing assumptions—1) that geographic boundaries are blurred and potentially less important in a digitally connected world, and 2) that geographic proximity matters for co-innovation—we investigate the global footprint of APIs. Using a datadriven visual network analysis approach to examine more than 15,000 APIs and mashups, we first map the global locations of where APIs are being created. We then examine how API mashups connect these locations globally and regionally. Our results show that while APIs are globally distributed, they are mainly concentrated in major entrepreneurial regions. We also find that there is a skewed distribution, with the U.S. and Silicon Valley in particular leading the way. We conclude with both theoretical and managerial implications.

Innovation Ecosystems vs. Innovation Systems in Terms of Collaboration and Co-creation of Value

In this paper, we explore the relevance of the term “innovation ecosystem” to describe dynamic collaborative networks of people and organizations formed around projects with an innovation objective. We present a survey of literature reviews on ecosystems studies to clarify typical features and interpretations of innovation ecosystems, and we highlight differences in terms of collaboration and value co-creation. We explore ecosystem thinking and illustrate patterns of innovation ecosystems by describing the structure of regional clusters, global value chains and platforms. We offer policy insights on the role of governments in stimulating innovation ecosystems and innovationconducive environments.