A Guide to Planning and Managing Open Innovative Ecosystems

João Leitão, Vanessa Ratten, Jean Barroca, João Leitão, Vanessa Ratten, Jean Barroca

• Publisher: Emerald Publishing Limited
• Year: 2020
• Print ISBN:
  9781789734102
• eBook ISBN:
  9781789734119
• Topic: Economics
• Subtopic: Business Development
• Index: Economics

Digital technology in the form of big data and data analytics is transforming the global economy. This book is the first to take an open innovation perspective to the study and practice of ecosystems, providing a novel way of understanding the impact data has on the way entrepreneurial firms develop. Governments are emphasising the use of open innovation ecosystems due to increased levels of digitalization in the global economy. This enables information and knowledge to be disseminated in a way that enables entrepreneurial projects to develop. 

Written primarily for practitioners and academic researchers, A Guide to Planning and Managing Open Innovative Ecosystems focuses on the unique nature of open innovation by utilising a government and data perspective. This helps to understand the dynamic manner in which digital technology in the form of big data is changing society. The role of the government in influencing an open innovation culture in society is discussed through the use of different cultural examples, enabling a holistic perspective about how government and data are influencing entrepreneurial endeavours.

Chapter 1

Planning and Managing Open Innovative Ecosystems, Data and Government

Vanessa Ratten and Abu Zafar Shahriar

Abstract

The rise of the digital economy has led to a focus on how to manage big data and business intelligence for entrepreneurial purposes. The aim of this chapter is to discuss how to plan for open innovative ecosystems that harness the potential of new data analytics techniques in order to progress society. This means concentrating on the increasingly complex world of data analytics in order to derive information about potential entrepreneurial opportunities. The role of knowledge management in influencing an open innovation ecosystem predicated on big data and computing acumen is stated. This helps to understand how the future of the global economy relies on an open data policy that encourages the sharing and dissemination of information. Implications for managers are also suggested that emphasize the role of innovation ecosystems, data and government.

Keywords: Data; ecosystem; entrepreneurship; entrepreneurial ecosystem; government; innovation; open innovation; planning

1. Introduction

The concepts of ecosystems, data and government have evolved over the years based on societal trends (Bliemel, Flores, De Klerk, & Miles, 2019). This is influencing how people view the concepts and how they are understood in society. Culture plays a role in this as people will consider data differently depending on their experiences. This has meant some countries where there are more open discussions and a democratic society tend to view data differently compared to more autocratic societies. This has also changed with increased computing platforms being available that enable the open and free sharing of information. This is evident in websites like Wikipedia being edited on a daily basis based on new information becoming available. This has increased internationalization as more individuals can communicate and work together on projects. Most of the research on big data has been conducted in the analytics field due to its emphasis on statistics (Olszak, 2016). There is also a lot of research being conducted in the information systems area due to the need to introduce new data analysis methods. However, less research has focused on innovation, data and government from an innovation perspective, which is the reason for this chapter.

There has been a shift in entrepreneurship research from the individual entrepreneur to an ecosystem perspective that acknowledges the cultural and social embeddedness of entrepreneurship (Ferreira, Ratten, & Dana, 2017). This means being aware of how entrepreneurship occurs at multiple levels in society from the individual, firm to societal. An intersectionality approach to entrepreneurship is useful to understand the effects of different identities and contexts. Entrepreneurs self-identify with being a risk taker and innovator, but they can also have other roles in society (Dy & Agwunbi, 2019). This comes from their socio-demographic features such as gender, geographic location and income level. Context also impacts entrepreneurial behavior with some contexts more conducive to entrepreneurship (Shepherd, 2019). Although the concept of entrepreneurship dates back a long time, it is only recently with the internet and technology revolution has an entrepreneurial ecosystem emphasis swept the industry. In order to support entrepreneurship, different levels of analysis are needed that focus on the role of data and government in society. The core attribute of an ecosystem is in the complex interactions that are hard to define due to their intangible nature (Puhakka, 2010). In addition, there is a time effect evident in ecosystems due to the need for connections based on time factors. The government is a crucial ecosystem member that determines the fate of many involved in a functioning entrepreneurial environment (Ferreira, Fernandes, & Ratten, 2017). This is due to the role institutions play in managing business activities and introducing new regulatory systems. One of the key drivers of a good ecosystem is a government structure that is sympathetic to entrepreneurship (Lichtenstein, 2011). This means the role of government needs to be considered as one of the most important factors influencing the entrepreneurial climate.

Entrepreneurship is not an isolated event but occurs based on environmental conditions (Ferreira, Fayolle, Ratten, & Raposo, 2018). This means it is important to understand the role ecosystems play in fostering a good environment for entrepreneurship. Thereby enabling a focus on how interconnected individuals, businesses and government entities intersect to create business ventures. To do this can be a hard task due to the continued and varied interactions occurring in an ecosystem. This means the entrepreneurial processes need to be understood as systemic interactions (Miller & Bound, 2011). In an entrepreneurial ecosystem, there is a wide range of related activities taking place that often occur in a synchronous manner. A sustainable ecosystem develops in a way that facilitates mutual interactions based on common goals (Parente, El Tarabishy, Botti, Vesci, & Feola, 2020). This means there are different activities occurring at the same time that produce a collective outcome.

Ecosystems involve a large number of entities that depend on each other for their survival. This results in both strong and weak ties among the entities that facilitate mutual goals. Moore (1996, p. 26) defined a business ecosystem as “an economic community supported by a foundation of increasing organisations and individuals in the organisms of the business world.” This definition highlights how the effectiveness of an ecosystem will depend on how the entities interact in order to facilitate future gain. Thus, an entrepreneurial ecosystem is a form of ecosystem that focuses on entrepreneurial endeavors. This means stakeholders involved in entrepreneurial projects such as entrepreneurs, research institutions and start-ups work together in a collaborative manner. Certain cities and regions like Silicon Valley in San Francisco have become famous due to their entrepreneurial ecosystem. This has made other places want to replicate their environment in order to obtain the same kind of economic success. In an entrepreneurial ecosystem, there needs to be a variety of entities in existence such as government institutions and trade groups in order to foster entrepreneurship (Pitelis, 2012). This is required as the interconnection of human and social capital enables entrepreneurial ideas to emerge. Governments have tried to create entrepreneurial environments due to the benefits they bring to a region in terms of jobs and growth. This has resulted in science and technology parks created to enable a number of entities to work together in a region (Ratten, 2016). This also enables support systems in terms of venture capital, financing and other support services to be offered. Thereby ensuring that the entities in the region have access to required services they need.

To build an understanding of how to plan and manage ecosystems, this chapter examines the current research on ecosystems. This ensures a full understanding of how ecosystems work and operate based on the input of data and government. Through the discussion provided in this chapter, it is possible to identify the distinct elements and dynamics of entrepreneurial ecosystems. In addition, this chapter provides an agenda for future research based on open innovative ecosystems, thereby suggesting a major contribution to the literature on ecosystems. This is by discussing the importance of ecosystems in society and being able to stress the role digitalization plays in the economy. This means integrating the current literature with new research strands about big data and data analytics. This is important as it focuses on how the digital economy is influencing entrepreneurship. Moreover, the literature on digital business with ecosystems is discussed in order to derive theoretical and practical insights. This can help build phenomenon-driven research on ecosystems, data and government.

In the remainder of this chapter, the role of ecosystems, data and government in society is discussed. This includes focusing on the importance of these topics for both scholars and practitioners. This will help to highlight the relevant issues for analyzing and solving societal problems related to big data and entrepreneurial ecosystems. The last section of this chapter identifies opportunities for future research on ecosystems, data and government that can also provide advice for managers and educators.

2. Knowledge Economy

The knowledge economy has transformed organizations into being repositories of intangible resources (Nonaka & Takeuchi, 1995). In the past, land and material capital was emphasized, but this has changed with more interest in knowledge and intelligence. Thus, the way firms compete is based on the information and wisdom they have that can differentiate them in the marketplace. Gupta, Iyer, and Aronson (2000, p. 17) state that knowledge management is “a process that helps organizations find, select, organize, disseminate and transfer important information and expertise.” This means it is important to manage knowledge as a source of information. Most knowledge is derived from gut feelings and intuition about events (Polanyi, 1958). This makes it important to act on hunches in order to progress in society. Some individuals do this by focusing on insights they have that bring meaning to certain occurrences. Often it is hard to put knowledge into words in order to explain it to others, which makes knowledge a crucial asset individuals have that can determine their success (Polanyi, 1966).

There can be some skepticism around the value of knowledge due to uncertainty about whether it will alter market conditions. Knowledge can be distinguished in terms of information or know-how (Becerra-Fernandez & Subherwal, 2001). Information refers to what something means and can be accrued from experience. Some forms of information are embedded in events or procedures. This means it is important to understand the context from which the information was obtained. Know-how refers to how to do something and is embodied inexperience (Suseno & Ratten, 2007). This means in order for knowledge to be valued, it needs to be shared in a way that gives meaning to those involved. To do this can be a hard task as knowledge involves information that needs to be acted upon in order to provide a benefit to society. Those who value knowledge tend to understand its impact and recognize it as an asset. This means intelligent people can harness the potential of knowledge by acting on it for their own gain. This involves having the ability to continually learn and innovate based on the accumulated knowledge.

Business intelligence is associated with knowledge management and data analytics. This is due to it being an umbrella term to describe a set of concepts that relate to the use of information. In order to improve decision-making processes, businesses are investing in ways to utilize information. This enables the use of fact-based support systems that are characterized by the collection and then analysis of information. In order to evaluate information, there needs to be a set of business functions to transform data into information. This enables advanced analytical tools to be used in order to support the strategic decision-making initiatives in an organization. The use of data analytics is needed in order to systematically organize data so that intelligent decisions can be made. Business intelligence provides a way for firms to leverage information in order to make informed decisions. In order to realize the potential of data, it needs to be analyzed using appropriate tools and technologies. This helps firms to improve their decision-making systems based on the data provided (Watson & Wixom, 2007). To do this requires the gathering of data that can be stored for later usages. Firms can use business intelligence in order to provide analytical processing and predictive analysis. This enables the reporting of data that can lead to performance benefits.

Information technology services have become a large share of overall investments in the economy. There has been an exponential increase in the amount of data being circulated in society due to the adoption of mobile computing devices. Networked devices such as smartphones have also contributed to this growth due to the way they are connected to the internet. In addition, user-generated content streaming from social media has further fueled this growth. Big data analytics is becoming more important as a way to realize the value in structured and unstructured data. In order to solve societal problems, big data are being hailed as a new innovation that has huge potential. Big data are a significant source of business intelligence due to the way they can capture opinions. This means big data can make a difference to human life and enable businesses to deliver better value.

A decision support system is defined as “a computer-based information system that supports business or organizational decision-making activities that typically result in ranking, sorting or choosing from among alternatives” (Mariani, Baggio, Fuchs, & Hoepken, 2018, p. 4). Cloud-based services are being used to provide business intelligence on demand. This enables data to be accessed on demand and enables a faster way to analyze data. Cloud-based architecture also enables more flexibility in accessing data from any geographic location. Due to advances in computing power and machine intelligence, the use of big data is becoming more popular. Business intelligence can be defined as “a set of conceptus and methods based on fact-based support systems for improving decision making” (Trieu, 2017, p. 111). It is important to utilize business intelligence in order to gather information about government processes regarding entrepreneurship. This can enable a more open innovation ecosystem to develop that utilizes the government and other key stakeholders in the business environment.

More firms are basing their decisions on big data due to the voluminous amounts of data it contains. Despite the importance of big data, there exist digital inequalities in society that might affect their usage. This is due to there being a digital divide in terms of who has the capacity and opportunity to work with big data. In order to manage data, there should be some form of project management in place. A project is defined as “a temporary endeavour undertaken to create a unique product, service or result” (Sanchez, 2015, p. 319). Thus, projects can integrate complex data in a way that benefits both business and government.

Those firms with the financial resources to buy data analytics tools will have a distinct advantage. Computational intelligence can be used to analyze big data as it enables a focus on understanding ideas through computing processes. Fulcher (2...

Table of contents

• Cover
• Title
• Chapter 1. Planning and Managing Open Innovative Ecosystems, Data and Government
• Chapter 2. Understanding Bio Health Technologies Entrepreneurial Ecosystems: An Intellectual Capital Approach
• Chapter 3. Transformative University in Quadruple Helix Sustainability Governance
• Chapter 4. Entrepreneurship and University Brands: The Sense of Belonging in Higher Education
• Chapter 5. Business Concept in a Health-related Donation Context
• Chapter 6. Empowerment and Performance in SMEs: Examining the Effect of Employees’ Ethical Values and Emotional Intelligence
• Chapter 7. Technology Ecosystems in Sport: A Bibliometric Analysis
• Chapter 8. International Sports Organizations and Internationalization of Sports Firms
• Chapter 9. Traditional Cultural Industry in Jepara: An Open Innovative Ecosystem Approach
• Chapter 10. An Education Ecosystem View to Managing Ethics and Entrepreneurial Intention
• Chapter 11. State-owned Companies and Innovative Ecosystem: A Case of 3-kg LPG
• Index