Architecting Smart Cities: An Integrated Analytics Platform for Aligning Market-Based Sustainability

March 11, 2013

Methods, Research, Tech Insight, Theory

Smart City

With 70% of the earth’s population expected to be living in urban settings by 2050, architecting sustainable cities via efficient resource supply chains is a major human imperative.  Whereas the technical infrastructures for advanced ‘smart city’ initiatives have been rapidly developing, an understanding of the associated political and economic dynamics raised by these emerging tools is less well understood.  However, the methods and tools for complex systems engineering have developed in terms of their ability to incorporate human systems dynamics into formal engineering models.  Meanwhile, understandings of organizational and economic behavior have developed an appreciation of uncertainty, economic game playing, multi-agent dynamics, and bounded-rationality in complex systems decision making.

This research proposes applying Model-Based Systems Engineering (MBSE), a methodology typically used for software and engineered systems development, and SysML, a systems modeling standard, to design and test advanced regulatory and incentive models for public-private collaborations.  A practical reference case is used to analyze as-is and proposed to-be incentive structures intended to optimize aggregate sustainability goals.  The benefit of the proposed approach is that SysML models can be formally tested for aggregate systemic efficiency via computer-based simulation and optimization.  Thus hypothetical regulatory and market models can be tested in vitro to derive insight and revise assumptions.

Uniting formal methods for design and testing with research models of organizational and behavioral economic dynamics, it becomes possible to consider the composition of an incentive design ‘toolkit’ for multi-stakeholder satisficing. In particular, the Knowledge-Based View theory of the firm allows for a structured analysis of management control system incentives, information exchanges, and assessment schemes (Grant, 1997).  Being able to design and test combinations of such models in complex environments via simulation allows regulators and stakeholders to engage in the mutual design of complex resource supply chains with the goal of satisficing multi-stakeholder sustainability.

The research proposal focuses on multi-stakeholder economic incentive architectures in sustainable supply chains. Sustainability and structured modeling as state-of-the-art topics in Operations Management research are central foundations (Sodhi & Tang, 2010). The research of Paul Kleindorfer focusing on sustainability in extended supply chains is a central reference (Kleindorfer, Singhal, & Wassenhove, 2005). The Natural Capitalism perspective that multi-stakeholder sustainability is an inherent value driver in business is embraced (Lovins, Lovins, & Hawken, 2007). Extended supply chains, viewed as economic systems with multiple, conflicting stakeholders, are modeled as complex ‘systems of systems’.  Complexity science thus serves as an overarching methodological foundation for the structural-functional analysis of modeled multi-organizational systems.

For full paper:








Core Concept:  Multi-agent value satisficing is a central factor in driving sustainable supply chains

Master Proposal:  Supply chains which efficiently satisfice multi-agent value drivers are more sustainable

1.1.     Idea One:  Extended Supply Chains are Result of Technical Advancement

Idea:  Technical and procedural advancements have led to the ability to manage extended supply chain complexity

Proposal:  Extended supply chain complexity is an emergent phenomenon which is evidencing unanticipated social and economic effects

1.2.     Idea Two:  Extended supply chains inherently invoke multiple stakeholders

Idea:  Extended supply chains involve multiple stakeholders with diverse goals

Proposal:  Value in extended supply chains is subject to multi-stakeholder economic satisficing

1.3.      Idea Three:  Sustainability is a value driver

Idea:  Sustainability is a central value driver in extended supply chains

Proposal:  Optimally sustainable supply chains evidence higher long-term economic value

1.4.     Idea Four:  Sustainability invokes multi-stakeholder definitions of value which need to be satisficed

Idea:  Sustainability in extended supply chains involves efficient satisfaction of multiple-stakeholder interests

Proposal:  Sustainability is a phenomenon which can be modeled in terms of an argument concerning different perspectives on value within a particular domain

1.5.     Idea Five:  Stakeholders in markets compete to optimize their own incentives

Idea:  Stakeholders are agents with unique sets of incentives which they seek to optimize in multi-agent markets

Proposal:  Stakeholder games can be modeled as multi-agent incentive optimization games



Core Concept:  Structured systems modeling and simulation can be used to assess systems efficiency

Master Proposal:  Performance in structured extended supply chain models can be evaluated via computer-based simulation of structured multi-agent models

2.1.     Idea Six:  Social Phenomenon is Systemic by Nature

Idea:  Systems analysis is appropriate to the study of complex behavioral dynamics

Proposal:  Organizational phenomenon can be meaningfully modeled in terms of systems dynamics

2.2.     Idea Seven:  Management Control Systems Provide a Context for Understanding Behavior in Organizations

Idea:  Management control systems provide an understanding of behavior in reaction to market incentives within organizational structures

Proposal:  Management Control Systems can be used to model behavior according to incentives in organizational contexts

2.3.     Idea Eight:  Complex Supply Chains as Multi-Agent Games

Idea:  Complex supply chains can be simulated as intra-organizational multi-agent games

Proposal:  Multi-agent simulation is a suitable method for gaining insight into complex supply chains

2.4.     Idea Nine:  Supply Chain Incentive Architectures Lead to Differing Social Welfare Value End-States

Idea:  Efficiency in complex system models can be pursued via structured systems engineering modeling and computer simulation

Proposal:  Different sustainable supply chain incentive architectures will result in more or less efficient social welfare value outcomes

2.5.     Idea Ten:  Model-Based Systems Engineering Combined with SysML for Modeling Multi-Agent Organizational Dynamics

Idea:  Model-Based Systems Engineering (MBSE) combined with SysML can be used to model multi-agent behavioral interactions in business systems

Proposal:  Different sustainable supply chain incentive architectures will result in more or less ‘social welfare enhancing’ outcomes


Core Concept:  Market-based mechanisms serve to align multi-stakeholder interests to sustainability goals

Master Proposal:  Market incentives and constraints can be carefully architected to promote systemic collaboration to optimize social value targets

3.1.     Idea Eleven:  Optimal Sustainability is a Negotiated Social Value Construct

Idea:  Purely technical attempts to optimize sustainability in extended supply chains will lead to inefficiencies and instability due to agency and behavioral bias factors

Proposal:  Sustainability optimality involves foremost the negotiation of a multi-stakeholder definition of ‘value’

3.2.     Idea Twelve:  Market-Mechanisms as Complexity Orchestrators

Idea:  Market-based mechanisms can be used to address behavioral factors in complex multi-organizational supply chains

Proposal:  Market incentive and constraint instruments and processes can be used to optimize multi-stakeholder value in complex supply chains

3.3.     Idea Thirteen:  Aligning Market-Mechanisms with Stakeholder Value

Idea:  Market-based mechanisms can be aligned to key performance indicators in order to orient systemic goals

Proposal:  Market-mechanisms can be aligned to multi-stakeholder value targets via metrics

3.4.     Idea Fourteen:  Aligned Metrics with Market Incentives

Idea:  Systematization of KPI-aligned market-based mechanisms will lead to trading and collaborative market behavior focused on systemic efficiency

Proposal:  Simulation can be used to test the feasibility of market incentives as aligned to shared stakeholder metrics

3.5.     Idea Fifteen:  Multi-Agent Simulation as a Multi-Organizational Management Control Systems Assessment Methodology

Idea:  Structural interactions, behavioral incentives, information sharing, and trading behavior can be simulated and assessed via multi-agent models

Proposal:  Multi-agent simulation is suitable for the assessment of multi-organizational Management Control System fitness



The guiding intention of this research proposal is to address the Operations Management gap between operational efficiency in managed technical infrastructure and poor related understandings of organizational architecture factors and effects (with particular attention to open markets and multi-stakeholder incentive engineering).  Beyond providing companies with guidance in defining and addressing sustainability specifically, the general intent is to provide a methodology for architecting better and more efficient systems from the standpoint that organizational architectures ground and guide technical architectures.

The assertion is that human guidance and context is a contextual ‘wrapper’ around operational efficiency, such that powerful operational infrastructure without a socio-economic context and design is essentially wasteful and/or flawed.  Thus the addressed gap intends to arrive at a better understanding of human-computer interfaces between complex technical infrastructure and complex multi-organizational systems (from both a structural and relational standpoint). It is hoped that by charting best practices related to complex resource infrastructure orchestration this research can provide a map to areas where software and technology interfaces (i.e. ‘smart agent’ driven technology and systems) can collaborate to ensure human resources are orchestrated at peek sustainability and efficiency levels.

At a more general level, the hope is that this research platform proposal will raise awareness of an emerging trend:  rapidly advancing supply chain automation technology leading to increased organizational complexity, and thus uncertainty and potential risk.  By mapping organizational ‘boundaries’ in terms of their interface with complex supply chains, this research can serve to orient managers to where organizations need to evolve to adapt to growing complexity.  Given the growing state of ‘information overload’ facing most managers, this research should also serve to orient the attention of management to key concerns related to complex technical systems architectures, with special relevance to the ‘organizational orchestration’ capacity of multi-agent aware Management Control Systems (market-based incentives being the most powerful).

For full paper:

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About SARK7

Scott Allen Mongeau (SARK7) is an INFORMS Certified Analytics Professional (CAP) and a Data Scientist in the Cybersecurity business unit at SAS Institute. Scott has over 20 years of experience in project-focused analytics functions in a range of industries, including IT, biotech, pharma, materials, insurance, law enforcement, financial services, and start-ups. Scott is a part-time PhD (ABD) researcher at Nyenrode Business University. He holds a Global Executive MBA (OneMBA) and Masters in Financial Management from Erasmus Rotterdam School of Management (RSM). He has a Certificate in Finance from University of California at Berkeley Extension, a MA in Communication from the University of Texas at Austin, and a Graduate Degree (GD) in Applied Information Systems Management from the Royal Melbourne Institute of Technology (RMIT). He holds a BPhil from Miami University of Ohio. Having lived and worked in a number of countries, Scott is a dual American (native) and Dutch citizen. He may be contacted at: All posts are copyright © 2015 SARK7 All external materials utilized imply no ownership rights and are presented purely for educational purposes.

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