Innovation, Social Networks, and Service Ecosystems

Managing Value in the Digital Economy

Jennifer D. Chandler

• Publisher: Palgrave Macmillan
• Year: 2020
• Print ISBN:
  9783030477967
• eBook ISBN:
  9783030477974
• Topic: Business
• Subtopic: Management
• Index: Business

This book examines the ways in which value is created in the digital economy from a social networks and service ecosystems perspective. Focusing on innovation, this project explores analytics, Big Data, and privacy with respect to service management and value creation. It debunks these technology-centric buzzwords by relating cross-disciplinary research topics from seminal sociology, business, management, marketing, information systems, organizational, and technology theory under the common theme of plasticity, which is the ability of a system to take and retain form. A keen understanding of plasticity is the route to success in the digital economy. This book, aimed at academics, graduate students and practitioners in fields related to innovation, service research, and strategic management, offers a holistic perspective on innovation that is informed by scholarly research from multiple disciplines.

© The Author(s) 2020

J. D. ChandlerInnovation, Social Networks, and Service Ecosystemshttps://doi.org/10.1007/978-3-030-47797-4_1

Begin Abstract

1. Innovation from a Networked, Ecosystems Perspective

Jennifer D. Chandler¹

(1)

California State University, Fullerton, CA, USA

Jennifer D. Chandler

Email: [email protected]

End Abstract

Innovation is the dilemma of the century. While it is complex and difficult to understand, innovation has been shown to be key for creating, harnessing, and managing value in the digital economy. This is because innovation is claimed to be the source or wellspring of unique and novel ideas. It is also supposed to be the key to fruitfully moving the world forward in ways that we can only imagine.

However, innovation has also become a sore spot for society as it has become a constant challenge that has become necessary for survival. Because technology is advancing at a very rapid speed, our world is now in a constant state of disruption. In our new digital economy, innovation often takes the form of technological superpowers that are based on artificial intelligence, machine learning, analytics, and big data. Together, these innovations have changed how we do business and how we conduct ourselves as human beings as we manage value in the digital economy.

Yet, it is still unclear how these will affect our society in the long term, including positive and negative effects on organizations, consumers, and government. Much of twenty-first-century technological innovations have afforded us value that we could not imagine before. We simply did not have the technology that would allow recent life-changing innovations, including, but not limited to, better treatments for illnesses, nanotechnology, energy-efficient transportation, more transparency in our governments, to name a few. Specifically, though, when it comes to organizations and the general realm of administration and business, much of the innovations afforded by these new technological superpowers stem from data and data-driven devices. These data are often the basis for value in the digital economy. The data often originate from interactions on the Internet, sensors from mobile devices, cameras in public spaces, and emails in private conversations, to name a few. The data capture what human beings do on an everyday basis, including mundane transactions at the grocery store, checking out library books, paying bills, and interacting with friends and family on social media. These data are captured by organizations since they often facilitate these interactions. Within organizations, data also capture the functions that organizations execute on an everyday basis, including sales, marketing, logistics, emails, and communications via corporate websites. Data are everywhere and are being used to create value by humans, organizations, governments, and institutions. It is no wonder that these data have given rise to unprecedented innovations such as machine learning and artificial intelligence.

Despite these, as the world has become more connected than ever, we find ourselves troubled with incessant and constant connection. We are cautious at the very least about the data that we see about ourselves. When we receive an advertisement based on an email conversation that we just had ten minutes ago, we become suspicious of the organizations that surround us. In these ways, our trust is being tested. Thus, we still face the same old problem that we did in yesteryear which is about the pursuit of meaning and happiness in our everyday lives, no matter what that means for each of us. However, now we have the additional worry and opportunity of thinking about being surrounding by big data, machine learning, and artificial intelligence. This is both exciting and also somewhat scary to us human beings.

Data are scary because they share our behaviors, values, and norms with others. We ourselves may not be aware of our own behaviors, values, or norms. When data make these salient and visible, it is scary to human beings. This is because humans are innately creatures of routine, repetition, and habit. Although we value the benefits that can come from allowing our data to be available to and used by organizations, we fear the consequences of organizations owning or gaining access to this data. Sometimes, organizations and individuals may not use this data to create value for those whose behaviors and values are reflected in the data. The inherent assumption is that the data can predict future behaviors and values, since humans are creatures of habit. Although it is difficult to escape our nature of finding comfort in repetitive behaviors or habit, we do not like that our behaviors are, for the most part, predictable.

Since human beings are creatures of habit, our preferences for routine and repetition establish habits in our daily lives that are difficult to alter. They are hallmarks of our own personal comforts. Simply put, the routine behaviors give us comfort and help us to find value and meaning in our everyday lives. In the United States and other Westernized countries, people relish the certainty embedded in these routines and habits. For many human beings, their physical and mental well-being depends on the existence of routine. Because of this, it is certainly possible that the organizations that we support are collecting, housing, and harnessing data about us and our most personal daily behaviors. To a large extent, many of us enjoy how these data help our favorite organizations like Google or Apple make our lives easier; this occurs when smart devices automatically turn on lights in our houses or when our smart phones give us turn-by-turn directions as we drive to work. All the while, organizations are collecting data about our everyday lives. Many Americans and citizens of other countries are happy to share their data with companies in order to reap the value of autonomous integrations that help us to lead harmonized, simpler lives. The value, again, stems from the predictability of our behaviors, routines, and processes. Unless we can become more spontaneous and random, organizations and government can use the data to predict, inform, or even control our future behaviors.

However, the price of data and automation based on this data are not without costs. Generally speaking, we think of these technological superpowers as afforded to organizations; however, it is equally important for consumers and governments to understand these superpowers as well. The value of technology is in the data that can be easily collected and eventually harnessed via integrated devices and information systems. However, the irony is that many equate the value of digital innovation with these superpowers and the organizations associated with them. However, innovation and value do not have much to do with digital as much they have to do with problem-solving (Satell 2018). We find value when we solve problems; analogously, we innovate when we solve problems. But, because the “digital economy” is somewhat new at the time of this writing (it is the year 2020 and the Internet came into existence only 30 years ago), innovation has become the buzzword that is now interchangeable with our understanding of the digital economy. Oftentimes, innovation has become synonymous with digital economy, and vice versa. However, as a human society, we still face the same challenges that we have always encountered since the very beginning of time. These are not necessarily digital challenges. The challenges, sadly yet somewhat gratefully, remain as simple, mundane, and analog in nature as they always have been. That is, the challenges that we face as humans are the same as they always have been: the challenges center on creating meaning in our lives. We, as human beings, are driven to innately and continuously survive; once we prove to ourselves that we can survive, we pursue meaning and happiness. These motivations have simply taken different forms over the years. For example, in the year 750, humans in China sought meaning by learning about tea-drinking, while in 1789 humans in France sought meaning by inciting political instability and uprising against their government. At the time of writing, in 2020, the humans in our world still seek meaning, but face challenges of continuing to find meaning in, or in spite of, newly introduced digital modes and formats.

This being said, the somewhat abrupt introduction of the digital economy is not going away anytime soon. As a result, it is important to understand what innovation and value entail. If we are conscious about the analysis and collection of this data, we as human beings can also use this data to improve ourselves and our worlds. If we can find the patterns that are most fundamental to finding meaning and happiness in our personal lives, the data can be harnessed for powerful value creation. Furthermore, other parts and dimensions of society that are also based in routine can benefit from the use of technology to positively influence process-oriented efforts. For example, diseases, energy use, wildlife ecology, and transportation patterns are typically also routine and process oriented. The data generated in these spaces are also reflective of patterns as well. By finding ways to harness data, it is more likely that machine learning and artificial intelligence can take a bigger role in our society, whether that role is good or bad. For all these reasons, it is important to understand innovation and value creation so we can understand how these new technological superpowers can be harnessed to benefit society.

In the big scheme of things, we are just beginning to be transformed by the digital economy. To manage this well, we need to understand how innovation and managing value in the digital economy can allow us to devise and execute new solutions to the same old problems. As stated earlier, the “same old problem” is finding meaning and happiness in our lives. From an organizational perspective, the “same old problem” would be helping our customers to find meaning in happiness in their own lives. How do we find meaning in a world that is moving too fast? How do we find happiness when we are constantly being surveilled? How do we find solace when we are constantly inundated with new stimulus, data, and attempts to build relationships? The constraint in our powerful digital economy is the digital economy itself. As humans, we are being forced to adapt to this digital economy at an alarmingly fast rate, while we deal simultaneously with the high levels of unce...

Table of contents

• Cover
• Front Matter
• 1. Innovation from a Networked, Ecosystems Perspective
• 2. Plasticity: Toward a Better Understanding of Innovation
• 3. The Micro and the Individual Innovator
• 4. Innovation and Diffusion at the Meso Level
• 5. Macro: Innovation as Renovated Connections
• 6. The Importance of Being Human
• Back Matter