Hyunwoo Park

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.

Understanding variations in pediatric asthma care processes in the emergency department using visual analytics

Health care delivery processes consist of complex activity sequences spanning organizational, spatial, and temporal boundaries. Care is human-directed so these processes can have wide variations in cost, quality, and outcome making systemic care process analysis, conformance testing, and improvement challenging. We designed and developed an interactive visual analytic process exploration and discovery tool and used it to explore clinical data from 5784 pediatric asthma emergency department patients.

Visual Analytics for Early-Phase Complex Engineered System Design Support

This article reports on our ongoing experiences in developing visual analytics tools for real-world CESs. Our work focuses on the early design phase during which a large design space is explored, poor alternatives are pruned, and valuable alternatives are considered further. Visual analytics tools can provide interactive discovery, exploration, and understanding of real-world complex engineered systems (CES). The proposed tool, which focuses on the early design phase, can help users perform routine CES design analysis tasks and offer stakeholder-specific visual representations of complex design models.

Visualization of Innovation in Global Supply Chain Networks

This methodological note identifies and describes a data-driven visualization approach to study innovations in supply chain networks (ISCN). We demonstrate its value and applicability with illustrative examples to pertinent structure-related ISCN research questions in the global electronics industry. Our visualization approach can be used to reveal and understand important clusters, patterns, trends, and outliers of ISCN not necessarily identified with traditional methods. The broader aim of this note is to demonstrate the complementary value of emerging visual analytic approaches in managerial decision-making contexts and describe how actionable insights can be achieved.

A visual analytics approach to understanding care process variation and conformance

With greater pressures of providing high-quality care at lower cost due to a changing financial and policy environment, the ability to understand variations in care delivery and associated outcomes and act upon this understanding is of critical importance. Building on prior work in visualizing healthcare event sequences and in collaboration with our clinical partner, we describe our process in developing a multiple, coordinated visualization system that helps identify and analyze care processes and their conformance to existing care guidelines. We demonstrate our system using data of 5,784 pediatric emergency department visits over a 13-month period for which asthma was the primary diagnosis.

Bicentric diagrams

In an era where data on social, economic, and physical networks are proliferating at a rapid pace, the ability to understand the underlying complex structural connections, discover prominent entities, and identify clusters is becoming increasingly important. It is also well-established that interactive visualizations can amplify human cognition and augment decision making. Motivated by a practical need articulated by corporate decision makers and limitations of existing visual representations, this research presents our journey in designing and implementing bicentric diagrams, a novel graph-based set visualization technique. A bicentric diagram enables simultaneous identification of sets, set relationships, and set member reach in integrated egonetworks of two focal entities. Our technique builds on the well-established sociological theory of tie strength to visually group and position nodes. We illustrate the broad applicability of bicentric diagrams with examples from four diverse sample domains: university collaboration, technology co-occurrence, health app purchases, and interfirm alliance networks. We assess the value of our technique using an expert-based evaluation approach. The paper concludes with implications and a discussion of opportunities for implementation in real-world decision support settings. Interactive visualizations amplify human cognition and augment decision making.Bicentric diagrams enable identification of sets, relationships, and reach.Bicentric diagrams enable visual exploration of strong and weak ties.Study provides illustrative examples from commerce, news, research, and strategy.Value-driven expert evaluation reveals utility and usefulness of bicentric diagrams.

Computational Analysis and Visualization of Global Supply Network Risks

Management of supply network risks is a critical competency for todays global enterprises. Current practices and tools, however, have limited capabilities and do not allow for systemic exploration of alternate risk strategies. We develop a computational model of risk diffusion in global supply networks that is grounded in techniques from complex systems, network analysis, and epidemiological risk modeling. We draw on a unique, curated dataset of firms, their supply networks, and financial risk in the global electronics industry. Specifically, we assess and visualize the impact of network structure on risk diffusion and supply network health, and determine the impact of visibility on reduction and potential mitigation of cascading risks. Our approach enables decision makers to identify risks and determine potential paths of their diffusion. In doing so, we advance our understanding of the design and development of computational risk management tools in a global supply network context.

ecoxight: Discovery, Exploration, and Analysis of Business Ecosystems Using Interactive Visualization

The term ecosystem is used pervasively in industry, government, and academia to describe the complex, dynamic, hyperconnected nature of many social, economic, and technical systems that exist today. Ecosystems are characterized by a large, dynamic, and heterogeneous set of geospatially distributed entities that are interconnected through various types of relationships. This study describes the design and development of ecoxight, a Web-based visualization platform that provides multiple coordinated views of multipartite, multiattribute, dynamic, and geospatial ecosystem data with novel and rich interaction capabilities to augment decision makers ecosystem intelligence. The design of ecoxight was informed by an extensive multiphase field study of executives. The ecoxight platform not only provides capabilities to interactively explore and make sense of ecosystems but also provides rich visual construction capabilities to help decision makers align their mental model. We demonstrate the usability, utility, and value of our system using multiple evaluation studies with practitioners using socially curated data on the emerging application programming interface ecosystem. We report on our findings and conclude with research implications. Collectively, our study contributes to design science research at the intersection of information systems and strategy and the rapidly emerging field of visual enterprise analytics.

Bicentric Diagrams: Design of a Graph-Based Relational Set Visualization Technique

Visualizations can help amplify human cognition. In an era where networks are becoming increasingly complex, the desirability of tools to compare and contrast sets, relationships, and reach is significant. Motivated by a practical need articulated by corporate decision makers, this research presents our journey in designing and implementing bicentric diagrams, a novel graph-based set visualization technique. A bicentric diagram enables simultaneous identification of sets, set relationships, and set member reach in integrated egonetworks of two focal entities. Our technique builds on the well-established theory of tie strength to visually group and position nodes. We illustrate the applicability of bicentric diagrams with an example from technology co-occurrence in press releases. We assess the value of our technique using an expert-based value-driven evaluation approach.

Challenges and Opportunities for Enterprise Transformation Research

This article summarizes the activity of the First International Workshop on Enterprise Transformation, hosted by the Tennenbaum Institute at the Georgia Institute of Technology in March 2013. The workshop brought together researchers (faculty and students) from a wide range of disciplines (e.g., engineering, management, computing, and social science) and institutions to (1) discuss and define the scholarly challenges and opportunities for enterprise transformation research and (2) facilitate the development of an emerging interdisciplinary academic community. The results of the workshop highlight the particular complexities of conducting enterprise transformation research in an academic context and identify both near- and long-term opportunities for impactful future research.