Summary
Smart Business Networks
,Table of Contents
Lecture 1a: Introduction to smart business networking ......................................................................... 1
Lecture 1b: New ways of networking ...................................................................................................... 6
Lecture 2: Analyzing inter-organizational business networks ................................................................. 7
Lecture 3: Guest lecture by Leo Remijn on IoT and LoRa ...................................................................... 10
Lecture 4: IoT-based business model innovation .................................................................................. 11
Lecture 5a: Business model innovation in business networks .............................................................. 12
Lecture 5b: Business network strategies............................................................................................... 15
Lecture 6a: Strategic alignment at the business network level ............................................................ 20
Lecture 6b: Networkability, smartness, and performance of networks ............................................... 22
Lecture 7: Smart business networks and blockchain technologies ....................................................... 24
Article 1: (Van Heck & Vervest, 2007) ................................................................................................... 28
Article 2: (Smits, 2002) .......................................................................................................................... 32
Article 3: (Österle, Alt & Fleisch, 2001) – Chapter 1.............................................................................. 34
Article 4: (Österle, Alt & Fleisch, 2001) – Chapter 2.............................................................................. 35
Article 5: (Österle, Alt & Fleisch, 2001) – Chapter 3.............................................................................. 37
Article 6: (Provan et al., 2007) ............................................................................................................... 40
Article 7: (Smits & Janssen, 2008) ......................................................................................................... 42
Article 8: (Barringer & Harrison, 2000).................................................................................................. 43
Article 9: (Alt & Zimmerman, 2014) ...................................................................................................... 44
Article 10: (Boston Consulting Group, 2009)......................................................................................... 46
Article 11: (Smits et al, 2009) ................................................................................................................ 48
Article 12: (Torabkani, 2007) ................................................................................................................. 50
Article 13: (Straub, 2004) ...................................................................................................................... 51
Article 14: (Smits & Weigand, 2018) ..................................................................................................... 53
Article 15: (Smits & Hulstijn, 2020) ....................................................................................................... 55
NOTES .................................................................................................................................................... 57
,Lecture 1a: Introduction to smart business networking
What is business networking (Österle et al., 2001): business networking in the new economy can be
seen as the coordination of processes within and across companies. More precisely, we define business
networking as the management of IT-enabled relationships between internal and external business
partners.
Smart business networking (Van Heck & Vervest, 2007): firms in a business network using ICT to
outperform other firms and networks.
IT: a variety of (new) technologies:
• Watson (IBM): technology platform that uses natural language processing and machine
learning to reveal insights from large amounts of unstructured data.
• Hadoop (open source): tools enabling to store, process and gain insight from big data
• Blockchain: sequential transaction database found in cryptocurrencies derived from bitcoin. A
distributed database, that maintains a continuously-growing list of data records that each refer
to previous items on this list and is thus hardened against tampering and revision.
• Internet of Things (IoT): “a system of interrelated computing devices, mechanical and digital
machines provided with unique identifiers (UIDs) and the ability to transfer data over network
without requiring human-to-human or human-to-computer interaction” (Wikipedia..).
• Simulation techniques: to provide insight (scenario-analyses) in the effects of policy choices
(System Dynamics, Insightmaker, iThink).
• Group decision and negotiation: using simulation techniques, data visualization, gaming and
gamification to support decisions and policy making.
Technology trends (Gartner, 2016):
• The Device Mesh: expanding set of endpoints people use to access applications and
information or interact with people, social communities, governments and businesses. The
device mesh includes mobile devices, wearable, consumer and home electronic devices,
automotive devices and environmental devices — such as sensors in the Internet of Things
(IoT).
• Ambient User Experience: the device mesh creates the foundation for a new continuous and
ambient user experience. Immersive environments delivering augmented and virtual reality
hold significant potential but are only one aspect of the experience. The ambient user
experience preserves continuity across boundaries of device mesh, time and space. The
experience seamlessly flows across a shifting set of devices and interaction channels blending
physical, virtual and electronic environment as the user moves from one place to another.
• Information of Everything: everything in the digital mesh produces, uses and transmits
information. This information goes beyond textual, audio and video information to include
sensory and contextual information. Information of everything addresses this influx with
strategies and technologies to link data from all these different data sources. Information has
always existed everywhere but has often been isolated, incomplete, unavailable or
unintelligible. Advances in semantic tools such as graph databases as well as other emerging
data classification and information analysis techniques will bring meaning to the often chaotic
deluge of information.
1
, • Advanced Machine Learning: deep neural nets (DNNs) move beyond classic computing and
information management to create systems that can autonomously learn to perceive the
world, on their own. The explosion of data sources and complexity of information makes
manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and
make it possible to address key challenges related to the information of everything trend.
DNNs (an advanced form of machine learning particularly applicable to large, complex
datasets) are what make smart machines appear "intelligent.“
• Autonomous Agents and Things: machine learning gives rise to a spectrum of smart machine
implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs)
and smart advisors — that act in an autonomous (or at least semiautonomous) manner. VPAs
such as Google Now, Microsoft's Cortana and Apple's Siri are becoming smarter and are
precursors to autonomous agents. The emerging notion of assistance feeds into the ambient
user experience in which an autonomous agent becomes the main user interface.
• Adaptive Security Architecture: the complexities of digital business and the algorithmic
economy combined with an emerging "hacker industry" significantly increase the threat
surface for an organization. Relying on perimeter defense and rule-based security is
inadequate, especially as organizations exploit more cloud-based services and open APIs for
customers and partners to integrate with their systems. IT leaders must focus on detecting and
responding to threats, as well as more traditional blocking and other measures to prevent
attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfil
the adaptive security architecture.
• Advanced System Architecture: the digital mesh and smart machines require intense
computing architecture demands to make them viable for organizations. Providing this
required boost are highpowered and ultra-efficient neuromorphic architectures. Fueled by
field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic
architectures, this architecture enables fast processing at speeds of greater than a teraflop
with high-energy efficiency
• Mesh App and Service Architecture: monolithic, linear application designs (e.g., the three-tier
architecture) are giving way to a more loosely coupled integrative approach: the apps and
services architecture. Enabled by software-defined application services, this new approach
enables web-scale performance, flexibility and agility. Micro-service architecture is an
emerging pattern for building distributed applications that support agile delivery and scalable
deployment, both on-premises and in the cloud. Application teams must create new modern
architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible
and dynamic user experiences that span the digital mesh.
• Internet of Things Platforms: IoT platforms complement the mesh app and service
architecture. The management, security, integration and other technologies and standards of
the IoT platform are the base set of capabilities for building, managing and securing elements
in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural
and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital
mesh and ambient user experience and the emerging and dynamic world of IoT platforms is
what makes them possible.
IT = ‘SMACIT’: IT has developed into a worldwide mesh of resources, providing ever changing
opportunities for innovations, smart business services & smart business networking. Also referred to
as ‘the digital ecosystem’.
• Social media.
• Mobile technology.
• Advanced analytics.
• Cloud technology.
• Internet of Things.
2
Smart Business Networks
,Table of Contents
Lecture 1a: Introduction to smart business networking ......................................................................... 1
Lecture 1b: New ways of networking ...................................................................................................... 6
Lecture 2: Analyzing inter-organizational business networks ................................................................. 7
Lecture 3: Guest lecture by Leo Remijn on IoT and LoRa ...................................................................... 10
Lecture 4: IoT-based business model innovation .................................................................................. 11
Lecture 5a: Business model innovation in business networks .............................................................. 12
Lecture 5b: Business network strategies............................................................................................... 15
Lecture 6a: Strategic alignment at the business network level ............................................................ 20
Lecture 6b: Networkability, smartness, and performance of networks ............................................... 22
Lecture 7: Smart business networks and blockchain technologies ....................................................... 24
Article 1: (Van Heck & Vervest, 2007) ................................................................................................... 28
Article 2: (Smits, 2002) .......................................................................................................................... 32
Article 3: (Österle, Alt & Fleisch, 2001) – Chapter 1.............................................................................. 34
Article 4: (Österle, Alt & Fleisch, 2001) – Chapter 2.............................................................................. 35
Article 5: (Österle, Alt & Fleisch, 2001) – Chapter 3.............................................................................. 37
Article 6: (Provan et al., 2007) ............................................................................................................... 40
Article 7: (Smits & Janssen, 2008) ......................................................................................................... 42
Article 8: (Barringer & Harrison, 2000).................................................................................................. 43
Article 9: (Alt & Zimmerman, 2014) ...................................................................................................... 44
Article 10: (Boston Consulting Group, 2009)......................................................................................... 46
Article 11: (Smits et al, 2009) ................................................................................................................ 48
Article 12: (Torabkani, 2007) ................................................................................................................. 50
Article 13: (Straub, 2004) ...................................................................................................................... 51
Article 14: (Smits & Weigand, 2018) ..................................................................................................... 53
Article 15: (Smits & Hulstijn, 2020) ....................................................................................................... 55
NOTES .................................................................................................................................................... 57
,Lecture 1a: Introduction to smart business networking
What is business networking (Österle et al., 2001): business networking in the new economy can be
seen as the coordination of processes within and across companies. More precisely, we define business
networking as the management of IT-enabled relationships between internal and external business
partners.
Smart business networking (Van Heck & Vervest, 2007): firms in a business network using ICT to
outperform other firms and networks.
IT: a variety of (new) technologies:
• Watson (IBM): technology platform that uses natural language processing and machine
learning to reveal insights from large amounts of unstructured data.
• Hadoop (open source): tools enabling to store, process and gain insight from big data
• Blockchain: sequential transaction database found in cryptocurrencies derived from bitcoin. A
distributed database, that maintains a continuously-growing list of data records that each refer
to previous items on this list and is thus hardened against tampering and revision.
• Internet of Things (IoT): “a system of interrelated computing devices, mechanical and digital
machines provided with unique identifiers (UIDs) and the ability to transfer data over network
without requiring human-to-human or human-to-computer interaction” (Wikipedia..).
• Simulation techniques: to provide insight (scenario-analyses) in the effects of policy choices
(System Dynamics, Insightmaker, iThink).
• Group decision and negotiation: using simulation techniques, data visualization, gaming and
gamification to support decisions and policy making.
Technology trends (Gartner, 2016):
• The Device Mesh: expanding set of endpoints people use to access applications and
information or interact with people, social communities, governments and businesses. The
device mesh includes mobile devices, wearable, consumer and home electronic devices,
automotive devices and environmental devices — such as sensors in the Internet of Things
(IoT).
• Ambient User Experience: the device mesh creates the foundation for a new continuous and
ambient user experience. Immersive environments delivering augmented and virtual reality
hold significant potential but are only one aspect of the experience. The ambient user
experience preserves continuity across boundaries of device mesh, time and space. The
experience seamlessly flows across a shifting set of devices and interaction channels blending
physical, virtual and electronic environment as the user moves from one place to another.
• Information of Everything: everything in the digital mesh produces, uses and transmits
information. This information goes beyond textual, audio and video information to include
sensory and contextual information. Information of everything addresses this influx with
strategies and technologies to link data from all these different data sources. Information has
always existed everywhere but has often been isolated, incomplete, unavailable or
unintelligible. Advances in semantic tools such as graph databases as well as other emerging
data classification and information analysis techniques will bring meaning to the often chaotic
deluge of information.
1
, • Advanced Machine Learning: deep neural nets (DNNs) move beyond classic computing and
information management to create systems that can autonomously learn to perceive the
world, on their own. The explosion of data sources and complexity of information makes
manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and
make it possible to address key challenges related to the information of everything trend.
DNNs (an advanced form of machine learning particularly applicable to large, complex
datasets) are what make smart machines appear "intelligent.“
• Autonomous Agents and Things: machine learning gives rise to a spectrum of smart machine
implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs)
and smart advisors — that act in an autonomous (or at least semiautonomous) manner. VPAs
such as Google Now, Microsoft's Cortana and Apple's Siri are becoming smarter and are
precursors to autonomous agents. The emerging notion of assistance feeds into the ambient
user experience in which an autonomous agent becomes the main user interface.
• Adaptive Security Architecture: the complexities of digital business and the algorithmic
economy combined with an emerging "hacker industry" significantly increase the threat
surface for an organization. Relying on perimeter defense and rule-based security is
inadequate, especially as organizations exploit more cloud-based services and open APIs for
customers and partners to integrate with their systems. IT leaders must focus on detecting and
responding to threats, as well as more traditional blocking and other measures to prevent
attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfil
the adaptive security architecture.
• Advanced System Architecture: the digital mesh and smart machines require intense
computing architecture demands to make them viable for organizations. Providing this
required boost are highpowered and ultra-efficient neuromorphic architectures. Fueled by
field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic
architectures, this architecture enables fast processing at speeds of greater than a teraflop
with high-energy efficiency
• Mesh App and Service Architecture: monolithic, linear application designs (e.g., the three-tier
architecture) are giving way to a more loosely coupled integrative approach: the apps and
services architecture. Enabled by software-defined application services, this new approach
enables web-scale performance, flexibility and agility. Micro-service architecture is an
emerging pattern for building distributed applications that support agile delivery and scalable
deployment, both on-premises and in the cloud. Application teams must create new modern
architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible
and dynamic user experiences that span the digital mesh.
• Internet of Things Platforms: IoT platforms complement the mesh app and service
architecture. The management, security, integration and other technologies and standards of
the IoT platform are the base set of capabilities for building, managing and securing elements
in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural
and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital
mesh and ambient user experience and the emerging and dynamic world of IoT platforms is
what makes them possible.
IT = ‘SMACIT’: IT has developed into a worldwide mesh of resources, providing ever changing
opportunities for innovations, smart business services & smart business networking. Also referred to
as ‘the digital ecosystem’.
• Social media.
• Mobile technology.
• Advanced analytics.
• Cloud technology.
• Internet of Things.
2
