Ostinato Process Model for Visual Network Analytics: Experiments in Innovation Ecosystems

More often than ever before, innovation activities are crossing organizational boundaries and taking place in the spaces between formal, organizational structures. This new context for innovation activities is increasingly referred to as an innovation ecosystem. Open innovation, co-creation, user-driven innovation, API and platform economies, and business ecosystems are key drivers of the transformation. Innovation ecosystems are open, dynamic systems that cross geographical as well as organizational boundaries and include financial, technological, and political dimensions. Talented humans have a crucial driving role in ecosystemic innovation activities. Innovation ecosystems set a new framework for analyzing, investigating, and therefore measuring innovation.Measuring and visualizing innovation is difficult, particularly within innovation ecosystems where activities take very complex forms and even identifying all relevant actors and stakeholders is challenging. At the same time, ecosystem-level analyses of innovation ecosystem structures are imperative for three groups: innovation ecosystem scholars, policy and decision makers, and innovation ecosystem actors. Moreover, new sources of digital data on innovation activities have become available, introducing new opportunities to investigate innovation ecosystems at the ecosystem level.In this dissertation, we seek to develop new means to utilize digital data in analyzing innovation ecosystems at the ecosystem level. We take an action design research approach to develop the means to investigate the structural properties of innovation ecosystems at the ecosystem level by using visual network analytics. We start from the realization that interconnectedness is a key property of innovation ecosystems. Addressing innovation ecosystems as networks, that is, as collections of pairs of interconnected innovation ecosystem actors, allows scholars and practitioners to gain insight into innovation ecosystem structures and the structural roles of individual ecosystem actors. To determine how innovation ecosystems should be modeled and analyzed as networks, we investigate several innovation ecosystems representing regional, metropolitan, national, and international contexts as well as investigating the context of programmatic activities that support innovation and growth. Our main objective in the dissertation is to develop a process model for data-driven visual network analytics of innovation ecosystems.Visual network analytics is a valuable method for investigating and mapping the innovation ecosystem structure. In the proposed approach, transactional microdata on innovation ecosystem actors and their interconnections is collected from various digital sources. Innovation ecosystem actors are represented as network nodes that are connected through transactions, including investments and acquisitions and advisory, founder, and contributor affiliations. Network metrics are used to quantify actors’ structural positions. Interactive visual analytics tools are used to support the visual exploration of the innovation ecosystem under investigation by using both top-down and bottom-up strategies.This work makes several contributions to the art and science of data-driven visual network analytics of innovation ecosystems. Most importantly, the dissertation proposes 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. The cycle of exploration and automation characterizes the model and is embedded in each phase.In addition to the ostinato model, we contribute a set of design guidelines for modeling and visualizing innovation ecosystems as networks. Finally, we contribute to the empirical body of knowledge on innovation ecosystems through a series of investigations of innovation ecosystems of different levels of abstraction and complexity. Innovation ecosystem scholars, policy makers, orchestrators, and other stakeholders in the innovation ecosystem under investigation in this dissertation have subscribed to the approach presented herein. The design guidelines, together with the ostinato model, allow innovation ecosystem investigators and actors an opportunity to significantly advance in utilizing visual network analytics in managing and orchestrating innovation ecosystems. Further research and development of supporting processes and tools are needed to take full advantage of the presented approach in analyzing, investigating, facilitating, and orchestrating interorganizational innovation activities

Using games to disrupt the conference Twittersphere

Social media tools are changing practices in many industries, including academia, and the Twitter platform is widely recognised as the ‘tool of choice’ for microblogging. Academic conferences often use social media to provide conference ‘backchannels’. This article describes a conference game using toys as alter egos, driven through Twitter. We found that the soft toy game format was participated in by a majority of the attendees, with early posts in advance of the conference a good signal of engagement. We look at what the organisers learnt from the game and how such games, including Twitter elements, could support wider networks beyond the conference itself

Tourists’ Personal Development Through Participatory Consumer-Generated Content

The paper seeks to investigate key factors influencing the personal development of tourists. This study examines the relationship between participatory consumer-generated content and tourists’ capabilities, emotions, and skills, as well as the moderating effect of previous tourists’ experiences. To evaluate the research model, 301 valid responses were examined using the PLS-SEM technique. The empirical findings showed that participatory consumer-generated content positively relates to tourists’ capabilities, emotions, and skills. Moreover, previous tourists’ experiences moderate the relationships of participatory consumer-generated content with tourists’ capabilities and skills; however, previous tourists’ experiences have no moderation effect on tourists’ emotions. Thus, our paper's findings offer valuable contributions to theory and practice. Practitioners and authorities should stimulate users to share their tourism experiences and take the initiative to share easily traceable and searchable data. Moreover, businesses should implement activities that encourage tourists to share their experiences as soon as possible and make travel and tourism websites and social media platforms readily available

Tourists’ Personal Development Through Participatory Consumer-Generated Content

The paper seeks to investigate key factors influencing the personal development of tourists. This study examines the relationship between participatory consumer-generated content and tourists’ capabilities, emotions, and skills, as well as the moderating effect of previous tourists’ experiences. To evaluate the research model, 301 valid responses were examined using the PLS-SEM technique. The empirical findings showed that participatory consumer-generated content positively relates to tourists’ capabilities, emotions, and skills. Moreover, previous tourists’ experiences moderate the relationships of participatory consumer-generated content with tourists’ capabilities and skills; however, previous tourists’ experiences have no moderation effect on tourists’ emotions. Thus, our paper\u27s findings offer valuable contributions to theory and practice. Practitioners and authorities should stimulate users to share their tourism experiences and take the initiative to share easily traceable and searchable data. Moreover, businesses should implement activities that encourage tourists to share their experiences as soon as possible and make travel and tourism websites and social media platforms readily available

Detecting Tie Strength from Social Media Data in a Conference Setting

The concept of tie strength was introduced by Granovetter as “a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services which characterize the tie”. Since the publication of this seminal study, several studies have been conducted incorporating the concept of tie strength in numerous fields. The growing rise of social media in recent years has shaped a new way of establishing and maintaining ties between people. As a result, studies have been conducted that, based on social media data, are focused on the evaluation of tie strength between users. Social media has also positioned itself as a key tool in the development of events such as conferences, as it is consolidated as the communication platform through which to disseminate information and knowledge and networking. Therefore, in the present study, it is sought to evaluate tie strength using publicly available Twitter data in the context of a conference. Specifically, the aim is to analyse the potential of implicit networks (particularly, mentions networks) generated in social media sites (particularly, Twitter) when evaluating tie strength and social ties, with special emphasis on weak ties and latent ties. Ultimately, the aim is to obtain conclusions that result in the demonstration of the utility and the advantages of implementing this analysis in the recommendation systems in conferences. To address the main statement problem, this study starts with a review of the existing literature related to the topic. Subsequently, as regards the empirical part of the study, a case study approach is conducted. Specifically, a longitudinal single-case analysis is analysed, since the mentions networks generated from the publicly available Twitter data of the conference HICSS along nine editions (from 2010 to 2018) are studied. Different measures of social network analysis have been used to obtain results and conclusions. Based on the analysis, different potentially useful measures for the evaluation of mentions networks and social ties are identified. These measures have served to analyse the social structures formed in a conference setting (highlighting star structures that reflect the information disseminating role of certain nodes), to identify the most relevant and influential participants (which generally correspond to important roles of the conference, as organizers or speakers), or to observe tendencies and groupings in communities according to common interests, among others

Evaluating tie strength from Twitter data in conference setting: Case CMAD

The concept of tie strength as well as the different kind of ties- strong and weak ties was introduced by Granovetter in his seminal paper titled “Strength of Weak Ties”. Over the decades, this concept has been used in a variety of fields to study a lot of different phenomena. In the recent years, the rise of social media and social networking services has given rise to new ways of maintaining and establishing ties. This has resulted in studies that have used personal social media data to predict the tie strength of these online relationships. Social media is also being used in events like conferences for networking purposes. In this study we evaluate the tie strength and identify different kind of ties using publically available Twitter data in the context setting of a conference. In order to address the formulated research problem, this study began by reviewing the relevant literature related to tie strength, social media and conference setting. From the literature review it was observed that: communication frequency was the most commonly used proxy for tie strength evaluation; social media was used for networking in conferences; and current methods of tie strength evaluation from social media use personal social media data which may not be accessible in case of conferences. The empirical study used the single-case based case of CMAD which is community managers’ online discussions in social media in connection to yearly-organized Community Manager Appreciation Day event in Finland. Two different data sources (survey data and Twitter data) were used to carry out the analysis. Different social network analysis methods were used to analyze the case. Based on the analysis, it was possible to identify potentially useful dimensions (e.g. amount of time, reciprocal services and structural factors) and measures (e.g. weighted degree, shortest path length) for evaluating tie strength in the context of events. These measures were useful in identifying to a useful extent the strong ties and the potential weak ties in the context of this study

Identification & Role of Implicit Social Ties from Social Data

The concept of social ties was introduced by Granovetter through the seminal paper titled" Strength of weak ties". Across the past five decades, this topic has attracted much attention from both academics and practitioners. In the past two decades, the rapid increase in digitization and new modes of communication have led to collecting and analyzing data about people. One of the most popular sources for such large and granular data about people is social media platforms. The rise in the popularity of social media in the past 15 years has resulted in many research studies that have used social media data to understand a lot of different phenomena. Some of this research has focused on using social data, including social media data, on identifying different kinds of social ties online and the role these social ties play in various contexts. Over the past decade, many different approaches and models have been built to identify social ties using social media data. These methods have been built using private data and explicit social relationship data of users’ social media platforms. However, in the past few years, it has become nearly impossible to access this kind of social media data due to the changes in the business models of the social media platforms and the introduction of new privacy laws like GDPR. This thesis aims to identify the social ties from publicly available social data and study the role of the identified social ties in different contexts like business conferences and business phenomena. In order to achieve this research objective, three separate studies were conducted. The first two studies were single-case case studies, while the third was an experiment where two different sets of hypotheses were tested using empirical data. All three studies used publicly available social media data related to a specific context. The first study used a large dataset related to a game developer community on Facebook. The second study used social media data related to a business event from Twitter and Facebook. The third study used a large dataset associated with social media data about crowdfunding projects from Twitter. This study adds to the existing literature related to identifying social ties from social media data in multiple manners. The thesis illustrates a novel approach based on reciprocal interaction for filtering relevant social ties from large publicly available social media data. The thesis also contributes to the understanding of the role multiple social media platforms play in an event. Thus, showing the impact this can have on identifying social ties from publicly available social media data in case of an event. The dissertation adds to the existing literature about the role social ties have towards crowdfunding success. The thesis shows that implicit social ties, in general, positively impact crowdfunding project success. In addition, the thesis has practical implications for designers of conference recommendation systems. The dissertation also has implications for the crowdfunding project owners and the crowdfunding project campaign designers

Unleashing the power of supply chain learning: an empirical investigation

Purpose Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances. Design/methodology/approach This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences. Findings SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL. Practical implications Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes. Originality/value This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL

Public Innovation and Digital Transformation

Public innovation and digitalization are reshaping organizations and society in various ways and within multiple fields, as innovations are essential in transforming our world and addressing global sustainability and development challenges. This book addresses the fascinating relationship of these two contemporary topics and explores the role of digital transformation in promoting public innovation. This edited collection includes examples of innovations that emerge suddenly, practices for processing innovations, and the requirements for transformation from innovation to the "new normal". Acknowledging that public innovation refers to the development and realization of new and creative ideas that challenge conventional wisdom and disrupt the established practices within a specific context, expert contributions from international scholars explore and illustrate the various activities that are happening in the world of multiple digitalization opportunities. The content covers public administration, technical and business management, human, social, and future sciences, paying attention to the interaction between public and private sectors to utilize digitalization in order to facilitate public innovation. This timely book will be of interest to researchers, academics and students in the fields of technology and innovation management, as well as knowledge management, public service management and administration.fi=vertaisarvioitu|en=peerReviewed