Management in the Age of Digital Business Complexity
  1. 296 pages
  2. English
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eBook - ePub

About this book

Management in the Age of Digital Business Complexity focuses on how the digital age is changing management and vastly speeding up complexity dynamics.

The recent coevolution of technologies has dramatically changed in just a few years how people and firms learn, communicate, and behave. Consequently, the process of how firms coevolve and the speed at which they coevolve has been dramatically changed in the digital age, and managerial methods are lagging way behind. Combining his own expertise with that of a number of specialist and international co-authors, McKelvey conveys how companies that fall behind digitally can quickly be driven out of business.

The book has been created for academics seeking to upgrade management thinking into the modern digital age and vastly improve the change capabilities of firms facing digital-oriented competition.

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Information

Publisher
Routledge
Year
2021
eBook ISBN
9781000393828

1 Managing the consequences of digital networks and accelerated complexity dynamics in digital business ecosystems

Bill McKelvey

Introduction

The first management-oriented Special Issue focusing on digital business (DB) was published in 2013 by the MIS Quarterly, titled Digital Business Strategy: Toward a Next Generation of Insights (all the articles are cited later). It’s about how a firm’s competitive environment and digital strategic posture influence DB strategy. Several additional information systems (IS)-oriented articles had also appeared before the Special Issue (Varian 1996; Katsikas et al. 2005; Damiani et al. 2007; Salam et al. 2008; Al-Debei and Avison 2010; Tsatsou et al. 2010; and Melville 2012). In addition, there are now many other articles and books writing more broadly about DB ecosystems, of which a few recent ones are: Choi 2017; Durand et al. 2017; Kshetri 2017; Ponce-Jara et al. 2017; Remane et al. 2017; Schallmo et al. 2017; Seo 2017; Thomson et al. 2017; Wokurka et al. 2017; Yager and Espada 2017; Qiu et al. 2018; Schallmo and Williams 2018; Weill and Woerner 2018. Earlier published articles and books are listed later.
The complexity dynamics stemming from agent interactions often result in the formation of rare and extreme outcomes—often called Stochastic Frontiers by strategy theorists—such as dominant firms in industries (Scheinkman and Woodford 1994; Stanley et al. 1996; Lee et al. 1998; Stanley et al. 2000; Axtell 2001; Moss 2002; Jones 2005; Andriani and McKelvey 2007, 2009, 2011; Aoyama et al. 2009; Park et al. 2010; Glaser 2013; Chew 2015), entrepreneurial firms (Crawford et al. 2015; Crawford and McKelvey 2018; Salmador Sanchez and McKelvey 2018) and other kinds of network effects (cited previously), some of which show up as skew distributions on social media sites such as Facebook or Twitter (comments, photos, or stories “going viral” on the Internet) (Bedhead 2013).
The Internet is now a dominant feature of all developed economies and is a growing feature in developing economies (Seigneur 2005; Malecki and Moriset 2008; Briscoe 2010; Li et al. 2012; El Sawy and Pereira 2013; Verdouw et al. 2013; Mullineux and Murinde 2014; Coeckelbergh 2015; Kim and Mauborgne 2015; Manyika et al. 2015; Mullineux 2015; Kshetri 2017; Majeed 2017; Ponce-Jara et al. 2017). Networks form much more quickly in Internet-connected DB ecosystems (deCosta 2013; Kellmereit and Obodovski 2013; McEwen and Cassimally 2013; McQuivey 2013; Schmidt and Cohen 2014; Da Xu et al. 2014; Al-Fuqaha et al. 2015; Greengard 2015; Manyika et al. 2015; Miller 2015; Keerthana and Ashika Parveen 2017; Yager and Espada 2017; Hassan et al. 2018; Qiu et al. 2018). Many, if not most, networks tend to be skew-distributed (see the aforementioned studies). The Internet now allows firms to learn much more about their customers via “crowdsourcing” and firms can also get information from their customers about what customers like or don’t like about their products via crowdsourcing (Day et al. 2003; Mulhern 2009; Faed 2010; Strader 2010; McKormack 2011; Chaffey and Ellis-Chadwick 2012; Escoffier and McKelvey 2014, 2015, 2018; Holliman and Rowley 2014; Kim and Mauborgne 2015). Using the Internet also allows customers to learn details about a similar product produced by competing firms. Companies can also use the Internet to quickly learn about their competitors’ new products. The foregoing Internet-based, quickly gained knowledge then speeds up the coevolution of DB ecosystems. The coevolution of dinosaurs took some 180 million years. The coevolution of Apple’s iPhone and iPod, Samsung’s Galaxy phone, and Google’s Android have dramatically changed how people and firms learn, communicate, and behave in just thirteen years (the iPhone went to market in June of 2007). Consequently, the coevolutionary process of how firms coevolve and the speed at which they coevolve has been dramatically changed in the Digital Age.
Many if not most managers and their firms have not kept up with the increased speed of coevolution in their now-digital ecosystems. The MBA programs that train students on how to be effective managers struggle to develop programs in response to the changed managerial world of the Digital Age. They still have to recognize that, because of the speeding up of information flows and increasingly pervasive digital access to information about customers and competing firms, the managerial skills they teach have to be realigned with the coevolutionary dynamics of the Digital Age.
A recent story in The Economist (2018), which is titled “Automation and productivity: producing ideas,” makes no mention of digital information flows or Internet connections. And yet firms can learn about markets, customer preferences and complaints, and what their competitors are in the process of planning and creating by hacking (i.e. finding ways to get access to information in digital devices) into their internal digital-information flows about new products, new ideas, information about customer preferences, marketing and production techniques, etc. While, for sure, a new idea comes from an employee’s brain, in the Digital Age, digital information flows are what bring knowledge and existing ideas together such that new creative ideas emerge. DB firms, thus, have rapidly occurring opportunities for more creativity and change than firms that are stuck in traditional ways of doing business. Given all the information available on Google, remembering information is, pretty much, irrelevant!
The mention of “digital business” in the Academy of Management Review is only in two articles: Ancona et al. (2001) and Albert et al. (2015). The Strategic Management Journal has published two articles: one by Rosenbloom (2000) and a second by Durand et al. (2017). Organization Science has now published 32 articles mentioning “digital business.” But I don’t yet know how much “depth” is given to the topic in each article. Organization Studies has published only two articles. Worse, the European Management Review has published only one: Dum (2007). Several articles in the Harvard Business Review relate more or less vaguely to “digital business.” Circa July 2018, Amazon shows that 396 DB books have appeared since the first one in 1995 (Tapscott 1995: The Digital Economy [second “anniversary edition” published in 2015.]) Given the nearly 400 books available on Amazon and the 1000+ articles (in different disciplines) available via Google Scholar, it is clear that the Digital Age and DB are part of 21st century reality. But in 2015 I found only three digital MBA Programs via Google (all in Europe); as of July 2018, Google now shows that more than ten top-ranked digital-business MBA Programs exist in the US. It is both surprising and disturbing, however, that so little attention to this new reality that managers now face is offered by so few of the top-ranked American management-oriented journals or business schools.
The development of coevolution (Kauffman 1993) in the DB age consists of four elements: first, I focus on IS because it is information that is now being transferred digitally among people and firms connected to the Internet. Second, I then focus on complexity dynamics that lead to new-order creation because they are vastly speeded up in the digital world. Third, I offer information about how the effect of digital complexity speeds up the coevolution of digital-businesses in DB ecosystems. Finally, I focus on implications for effective management in the Digital Age.

Digital-age effects on information systems

Needless to say, digital effects obviously speed up information flows because modern information flowing between computers, smartphones, iPads, and iPods, etc. is the result of the digital connections, which allow information to flow at the speed of electricity and/or light vs. the speed of horses, postal service trucks, trains, or planes. Any business-related aspect that has some relation to what is transferred by digital-speed information flows is going to change very quickly: almost instantly if people are not involved; a bit or quite a bit slower if people are involved. Obviously, firms that have changed their equipment so as to deal with digital speeds, and have also managed to get their employees to more quickly change so as to respond to digital-speed information flows, have better survival chances.

Realities of the Digital Age

There are now many articles and books describing DB ecosystems, and how they are different from prior business ecosystems. Some of these are: Tapscott 1995, 2015; Ancona et al. 2001; Coupey 2001, 2016; Day et al. 2003; Dourmas et al. 2005; Seigneur 2005; Brousseau and Pénard 2007; Corallo et al. 2007; Muntaner-Perich and de la Rosa Esteva 2007; Nachira et al. 2007a,b; Pappas et al. 2007; Razavi et al. 2007; Tan et al. 2009; Stanley and Briscoe 2010; Tan and Macaulay 2011; Herdon et al. 2012; Li et al. 2012; Passerini and El Tarabishy 2012; El Sawy and Pereira 2013; Attour and Della Peruta 2014; Cojocaru et al. 2014; Jensen et al. 2014; Morabito 2014; Rong and Shi 2014; Turcoane 2014; Liu and Rong 2015; Tafti et al. 2015; Rogers 2016; Choi 2017: Durand et al. 2017; Kshetri 2017; Ponce-Jara et al. 2017; Remane et al. 2017; Schallmo et al. 2017; Seo 2017; Thomson et al. 2017; Wokurka et al. 2017; Yager and Espada 2017; Qiu et al. 2018; Schallmo and Williams 2018; Weill and Woerner 2018.

The “Internet of Things” and other digital-world realities

The “Internet of Things” (deCosta 2013; Kellmereit and Obodovski 2013; McEwen and Cassimally 2013; McQuivey 2013; Schmidt and Cohen 2014; Greengard 2015; Miller 2015; Sawicki 2016; Keerthana and Ashika Parveen 2017; Yaqoob et al. 2017) consists of computers or embedded miniature computers in smartphones or other everyday objects that can connect with the Internet wirelessly. For example, because of lack of banks but their growing number of Internet and smartphone connections, more and more people in Africa use their smartphones rather than real money to buy things (Smith 2014; Brazzell 2017; Monks 2017).
Thus: imagine you live in a small village in rural Kenya. Your daughter attends university in Nairobi and needs financial support to buy textbooks and pay her rent. How do you send her money if you, like many Kenyans, don’t have an electronic bank account or Internet access?
In the US, the answer would be simple. In fact, you would have an abundance of options: PayPal, Venmo, online banking, checks, money orders, or good old-fashioned cash. Many people around the world, however, don’t have access to the financial services some of us Americans take for granted. Two billion ‘unbanked’ adults, mostly in developing countries, face barriers ...

Table of contents

  1. Cover
  2. Half-Title
  3. Series
  4. Title
  5. Copyright
  6. Dedication
  7. Contents
  8. List of contributors
  9. 1 Managing the consequences of digital networks and accelerated complexity dynamics in digital business ecosystems
  10. 2 Rescuing economics and management from Darwin’s evolution via death-and-replacement by the Baldwin Effect: learning during a lifetime
  11. 3 Why Lamarck dominates Darwin in explaining organizational change and evolution
  12. 4 “Simple rules” for improving digital corporate IQ: Basic lessons from complexity science
  13. 5 Digital dynamic capabilities
  14. 6 Understanding value conflict between business and society: a new perspective from neuro and complexity sciences
  15. 7 A digital perspective about how complexity science pushes firms into the stochastic frontier
  16. 8 Using Crowd wisdom via crowdsourcing: Proof of concept of an efficient digital strategy in the age of digital business complexity
  17. Index

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