!['WHO IS THIS CHILD?' DEMANDED THE
BARONESS
FOOTNOTES:
[10] Room.
[11] Salable daughters.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-59-320.jpg)
![river's brink with its great pools of black slime in which to wallow.
They stopped their mad dashing about and gathered around the
boy, and he, too, turned and led them from the village.
It was a funny sight, this village procession. First came Marushka
in her little peasant's costume, decked with her wreath and garlands
of forget-me-nots, and followed by her snow-white geese. Next,
Banda Bela, playing his violin and escorting his pigs, while last of all
came the motor car of the High-Born Baron, the Baron looking
amused, the Baroness in spasms of laughter.
Oh, Léon, she cried. Could our friends who drive on the Os
Budavara[12] see us now! Such a procession! That child who leads is
the most beautiful little creature and so unconscious, and the boy's
playing is wonderful.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-65-320.jpg)
![Semeyer about her. In the meantime, say not one word to the little
girl for fear she be disappointed if we have made a mistake.
Yes, Your High-Born Graciousness, and Banda Bela led
Marushka away, playing as they went down the hill the little song of
his father.
The hills are so blue,
The sun so warm,
The wind of the moor so soft and so kind!
Oh, the eyes of my mother,
The warmth of her breast,
The breath of her kiss on my cheek, alas!
FOOTNOTE:
[12] Celebrated drive in Buda-Pest.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-72-320.jpg)
![You speak about the Emperor sometimes, said Marushka. And
other times about the King. Who is the King?
The same as the Emperor, replied the Baroness. You see,
Austria and Hungary have been united under one government, and
the King of Hungary is Emperor of Austria. There were many wars
fought before this arrangement was made, and all the different
peoples of the empire agreed to live peaceably together.
How long has Hungary had a king? asked Marushka.
Oh, for years and years, said the Baroness. It was about the
twelfth century when the Aranybulla[13] was made, which gave to
the nobles the right to rebel if the king did not live up to the
constitution. See! There are the barracks and the soldiers drilling.
The country boys who come up to be trained are sometimes so
stupid that they don't know their right foot from the left. So the
sergeant ties a wisp of hay on the right foot and a wisp of straw on
the left. Instead of saying, right-left, to teach them to march, he
says szelma-szalma. Isn't it droll?
What is that building by the river? asked Marushka. The one
with the little turrets and the tower before which the geese are
swinging?
That, my little goose girl, is the Agricultural Building, and should
you go inside you would find specimens of every kind of food raised
in Hungary. But here we are at the hotel where we shall spend the
night. You must have some supper and then hurry to bed, for to-
morrow is the fête day of St. Stephen, and all must be up early to
see the procession.
Marushka was so sleepy the next day that she could only yawn
and rub her eyes when the maid called her at five o'clock to dress
for the fête.
The twentieth of August, the feast of St. Stephen, is the greatest
fête of the year in Hungary.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-78-320.jpg)
![That I cannot tell you now, she said. This afternoon at your
castle I will ask you to tell me!
FOOTNOTE:
[13] Hungarian Magna Charta.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-81-320.jpg)
![instead of the old-fashioned ways of thrashing. Now we are getting
into the country. See how beautifully the road winds along the
Danube! Is it not a wonderful river? There is a famous waltz called
the 'Beautiful Blue Danube' and the river is certainly as blue as the
sky. See that queer little cemetery among the hills. I have often
wondered why some of the gravestones in the village cemeteries
had three feathers and coloured ribbons on them.
If you please, Your Graciousness, said Banda Bela, I can tell
you. That is for the grave of a girl who has died after she was of an
age to be married, yet for whom no one had offered the buying
money. Aszszony Semeyer told me that.
Aszszony Semeyer told me that every peasant kept a wooden
shovel hung upon the wall of his house with which to throw in the
last shovelful of earth upon his loved ones, said Marushka with a
shudder. Ugh! I didn't like that.
Very few people like to think about death, said the Baroness.
See that thicket of prickly pears beside the road? Once when I was
a little girl and very, very naughty, I ran away from my nurse and to
hide from her I jumped over the wall and landed in just such a
thicket as that. I think the pears must be naughty, too, for they liked
that little girl and would not let her go. The thorns pricked her legs
and tore her frock and scratched her hands when she tried to get
her skirts loose, until she cried with pain and called 'Kerem jojoro
ide'[14] to her nurse.
I did not think the Gracious Baroness was ever naughty, said
Marushka.
The Gracious Baroness was quite like other little girls, my dear,
she said, smiling. Ah, I have a little twinge of toothache! she
exclaimed.
That is too bad. Marushka was all sympathy. Aszszony Semeyer
says that if you will always cut your finger nails on Friday you will
never have toothache.](https://image.slidesharecdn.com/1133276-250522032829-601bd697/85/Sociotechnical-Networks-Science-And-Engineering-Design-Fei-Hu-84-320.jpg)
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- 8. Socio-Technical Networks Science and Engineering Design Edited by Fei Hu Ali Mostashari Jiang Xie
- 9. CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2011 by Taylor and Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-1-4398-0981-5 (Ebook-PDF) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmit- ted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright. com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com
- 10. © 2011 by Taylor & Francis Group, LLC To Fang Yang and Gloria Yang Hu …… To Ali’s family …… To Linda’s family
- 12. vii © 2011 by Taylor & Francis Group, LLC Contents Preface.............................................................................................................ix About the Authors...........................................................................................xi Contributors List. ......................................................................................... xiii 1 Sociotechnical Systems: A Conceptual Introduction..............................1 ALI MOSTASHARI 2 Systems-Level Modeling of Sociotechnical Systems..............................13 ALI MOSTASHARI 3 Dynamic Models and Analysis for Information Propagation in Online Social Networks........................................................................39 XIAOHONG GUAN, YADONG ZHOU, QINGHUA ZHENG, QINDONG SUN, AND JUNZHOU ZHAO 4 Analyzing Sociotechnical Networks: A Spectrum Perspective..............71 XINTAO WU, XIAOWEI YING, AND LETING WU 5 Sociotechnical Network Models: A Review.........................................105 TODD AYCOCK, JUSTIN HEADLEY, JUSTIN FLOYD, AND FEI HU 6 Understanding Interactions among BitTorrent Peers. .........................127 HAIYANG WANG, LI MA, CAMERON DALE, AND JIANGCHUAN LIU 7 Sociotechnical Environments and Assistive Technology Abandonment......................................................................................167 STEFAN PARRY CARMIEN 8 A Sociotechnical Collaborative Negotiation Approach to Support Group Decisions for Engineering Design...........................................181 STEPHEN C-Y. LU, NAN JING, AND JIAN CAI 9 Risk Analysis in Sociotechnical System..............................................229 JONATHAN SCOTT CORLEY AND FEI HU
- 13. viii ◾ Contents © 2011 by Taylor & Francis Group, LLC 10 Privacy Support in Cloud-Computing-Based Sociotechnical Networks.............................................................................................249 YAO WU, FEI HU, AND QI HAO 11 Trust Models in Cloud-Computing-Based Sociotechnical Networks.............................................................................................271 YAO WU, FEI HU, AND QI HAO 12 Networking Protocols in Sociotechnical Networks. ............................297 DONG ZHANG AND FEI HU 13 Design Tools of Sociotechnical Networks...........................................313 LING XU AND FEI HU 14 Sociotechnical Networks for Healthcare Applications........................325 JOSHUA DAVENPORT, GABRIEL HILLARD, AND FEI HU 15 Collaborative Software Development Based on Socialtechnical Networks............................................................................................ 343 RYAN ANDREW TAYLOR AND FEI HU 16 Virtual Communities Based on Sociotechnical Systems.....................369 KELI KOHOUE, SADITH OSSENI, AND FEI HU Index............................................................................................................383
- 14. ix © 2011 by Taylor & Francis Group, LLC Preface Needless to say, one of the hottest research fields across computer networking and social sciences is sociotechnical networks (STNs). In general when we discuss socio- technical networks in this book, we are referring to systems such as the Internet, power grids, and transportation networks enabled by data communication networks and telecommunication networks. Thus, the focus is on the technological network and understanding the complexities of designing, managing, and operating such networks using social/organization networks. This sets the focus apart from work process design or ergonomics, and concentrates on the design and architecture of large-scale technological networks that are influenced by and in turn impact a social network of people and organizations with different goals and values. Here, we define a sociotechnical system as a dynamic entity comprised of inter- dependent and interacting social/institutional and physical/technological parts, characterized by inputs, processes/actions, and outputs/products. Sociotechnical systems are usually composed of a group of related component and subsystems, for which the degree and nature of the relationships is not always clearly understood. They have large, long-lived impacts that span over a wide geographical area. Many have integrated subsystems coupled through feedback loops and are affected by social, political, and economic issues. Examples of systems that fall within this category are transportation networks, telecommunication systems, energy systems, the World Wide Web, water alloca- tion systems, financial networks, etc. Such systems have wide-ranging impacts, and are characterized by different types and levels of complexity, uncertainty, and risk, as well as a large number of stakeholders. This book will mainly cover the following aspects in STNs: 1. Fundamentals of Sociotechnical Networks: In this part, we will introduce the basic concept of STN including its definition, historical background, and significance. 2. STN Models: Social Network Analysis (SNA) is a mathematical method for “connecting the dots.” SNA allows us to map and measure complex, and sometimes covert, human groups and organizations.
- 15. x ◾ Preface © 2011 by Taylor & Francis Group, LLC 3. Privacy and Security: We will cover the following topics: risk models, trust models, and privacy preserving protocols. Those topics will assist in defin- ing the parameters and processes for reducing risk, managing security, and maintaining continuity of operations for critical infrastructure systems in vulnerable social network regions. 4. STN applications: We will explain the STN applications in some popular fields, such as healthcare, virtual community, and others. This book can serve as a good technical reference for college students, researchers, and social scientists. To the best of our knowledge, up to this point this is the first book that covers the comprehensive knowledge on STNs.
- 16. xi © 2011 by Taylor & Francis Group, LLC About the Authors Dr. Fei Hu is currently an associate professor in the Department of Electrical and Computer Engineering at the University of Alabama (main campus), Tuscaloosa, Alabama. His research interests are sensor networks, wireless networks, network security, and their applications in biomedicine. His research has been supported by the U.S. National Science Foundation, Cisco, Sprint, and other sources. He obtained his Ph.D. degrees at Tongji University (Shanghai) in the field of sig- nal processing (in 1999), and at Clarkson University (New York) in the field of electrical and computer engineering (in 2002). He obtained his M.S. and B.S. degrees in telecommunication engineering from Shanghai Tiedao University in 1996 and 1993, respectively. He has published over 100 journal/conference papers and book (chapters). Dr. Ali Mostashari is currently the director of the Center for Complex Adaptive Sociotechnological Systems (COMPASS), and an associate professor (Research) at the School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, New Jersey. He obtained his Ph.D. in engineering systems/technology, and man- agement and policy from the Massachusetts Institute of Technology in 2005. He was a Young Global Leader Nominee 2008. He was also listed as Asia 21 Young Leader by the Asia Society (2007). His research focus is complex sociotechnical network design. Dr. Jiang (Linda) Xie received her B.E. degree from Tsinghua University, Beijing, China, in 1997, M.Phil. degree from Hong Kong University of Science and Technology in 1999, and M.S. and Ph.D. degrees from the Georgia Institute of Technology in 2002 and 2004, respectively, all in electrical engineering. She is currently an assistant professor with the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. She was a graduate research assistant in the Broadband and Wireless Networking Laboratory (BWN- LAB) at the Georgia Institute of Technology from August 1999 to April 2004. She is also a member of the IEEE Communications Society, IEEE Women in Engineering, the Association of Computing Machinery (ACM), and Eta Kappa Nu (ECE Honor Society).
- 18. xiii © 2011 by Taylor & Francis Group, LLC Contributors List Todd Aycock ECE Department University of Alabama Tuscaloosa, Alabama Jian Cai Peking University Beijing, China Stefan Parry Carmien Department of NeuroEngineering Fatronik-Tecnalia Foundation San Sebastian, Spain Jonathan Scott Corley ECE Department University of Alabama Tuscaloosa, Alabama Cameron Dale School of Computing Science Simon Fraser University Burnaby, British Colombia, Canada Joshua Davenport ECE Department University of Alabama Tuscaloosa, Alabama Justin Floyd ECE Department University of Alabama Tuscaloosa, Alabama Xiaohong Guan System Engineering Institute Xi’an Jiaotong University Xi’an, China Qi Hao ECE Department University of Alabama Tuscaloosa, Alabama Justin Headley ECE Department University of Alabama Tuscaloosa, Alabama Gabriel Hillard ECE Department University of Alabama Tuscaloosa, Alabama Fei Hu ECE Department University of Alabama Tuscaloosa, Alabama
- 19. xiv ◾ Contributors List © 2011 by Taylor & Francis Group, LLC Nan Jing University of Southern California Los Angeles, California Keli Kohoue ECE Department University of Alabama Tuscaloosa, Alabama Jiangchuan Liu School of Computing Science Simon Fraser University Burnaby, British Colombia, Canada Stephen C-Y. Lu University of Southern California Los Angeles, California Li Ma School of Computing Science Simon Fraser University Burnaby, British Colombia, Canada Ali Mostashari School of Systems and Enterprises Stevens Institute of Technology Hoboken, New Jersey Sadith Osseni ECE Department University of Alabama Tuscaloosa, Alabama Qindong Sun System Engineering Institute Xi’an Jiaotong University Xi’an, China Ryan Andrew Taylor ECE Department University of Alabama Tuscaloosa, Alabama Haiyang Wang School of Computing Science Simon Fraser University Burnaby, British Colombia Canada Leting Wu Department of Software and Information Systems College of Computing and Informatics University of North Carolina at Charlotte Charlotte, North Carolina Xintao Wu Department of Software and Information Systems College of Computing and Informatics University of North Carolina at Charlotte Charlotte, North Carolina Yao Wu ECE Department University of Alabama Tuscaloosa, Alabama Ling Xu ECE Department University of Alabama Tuscaloosa, Alabama Xiaowei Ying Department of Software and Information Systems College of Computing and Informatics University of North Carolina at Charlotte Charlotte, North Carolina Dong Zhang ECE Department University of Alabama Tuscaloosa, Alabama
- 20. Contributors List ◾ xv © 2011 by Taylor & Francis Group, LLC Junzhou Zhao System Engineering Institute Xi’an Jiaotong University Xi’an, China Qinghua Zheng System Engineering Institute Xi’an Jiaotong University Xi’an, China Yadong Zhou System Engineering Institute Xi’an Jiaotong University Xi’an, China
- 22. 1 © 2011 by Taylor & Francis Group, LLC Chapter 1 Sociotechnical Systems: A Conceptual Introduction Ali Mostashari Contents 1.1 Introduction..................................................................................................2 1.2 Tightly Coupled Social and Technological Hierarchies.................................2 1.3 Characteristics of Sociotechnical Systems. .....................................................3 1.3.1 Complexity........................................................................................3 1.3.2 Scale..................................................................................................5 1.3.3 Integration and Coupling..................................................................5 1.3.4 Interactions with the External Environment......................................5 1.3.5 Uncertainty and Risk in Sociotechnical Systems...............................5 1.4 Dimensions of Sociotechnical Systems..........................................................7 1.5 Sociotechnical Networks...............................................................................8 1.5.1 Security.............................................................................................8 1.5.2 Resilience...........................................................................................9 1.5.3 Reliability..........................................................................................9 1.5.4 Distributed versus Centralized Control.............................................9 1.6 Sociotechnical Networks and Cognition.....................................................10 1.7 Analyzing Sociotechnical Networks: CLIOS Analysis and the STIN Heuristics. .........................................................................................10 References............................................................................................................11
- 23. 2 ◾ Ali Mostashari © 2011 by Taylor & Francis Group, LLC 1.1 Introduction The term sociotechnical systems is generally used for systems where human beings and organizations interact with technology. However, within the literature, there are many different interpretations of what aspect of the interactions between the social and technological parts constitute a sociotechnical study. In this chapter we will explore the definitions of sociotechnical networks within the context of this book and identify the various perspectives through which they will be analyzed in subsequent chapters. In general, when we discuss sociotechnical networks in this book, we are referring to systems such as the Internet, power grids and transportation networks enabled by data communication networks, and telecommunication networks. Thus, the focus is on the technological net- work and understanding the complexities of designing, managing, and operat- ing such networks using social/organization networks. This sets the focus apart from work process design or ergonomics, and concentrates on the design and architecture of large-scale technological networks that are influenced and that in turn impact a social network of people and organizations with different goals and values. Here we define a sociotechnical system as a dynamic entity comprised of inter- dependent and interacting social/institutional and physical/technological parts, characterized by inputs, processes/actions, and outputs/products. Sociotechnical systems are usually composed of a group of related component and subsystems, for which the degree and nature of the relationships are not always clearly understood. They have large, long-lived impacts that span over a wide geographical area. Many have integrated subsystems coupled through feedback loops and are affected by social, political, and economic issues (Mostashari and Sussman, 2009). Examples of systems that fall within this category are transportation networks, telecommunication systems, energy systems, the World Wide Web, water alloca- tion systems, financial networks, etc. Such systems have wide-ranging impacts, and are characterized by different types and levels of complexity, uncertainty, risk, as well as large number of stakeholders (Mostashari, 2005). 1.2 Tightly Coupled Social and Technological Hierarchies A sociotechnological system/network normally consists of at least two (and some- times three) interacting and tightly coupled networks of components. One layer includes the physical/technological components of the system, and the other layer the social/institutional components, which are usually connected through an infor- mation network (Figure 1.1). Within each of these layers the components relate to each other in a hierarchy (Figures 1.2).
- 24. Sociotechnical Systems: A Conceptual Introduction ◾ 3 © 2011 by Taylor Francis Group, LLC 1.3 Characteristics of Sociotechnical Systems In order to study and analyze a sociotechnical system, a deep understanding of each of these aspects is necessary. In the following paragraphs, we will look at these more closely (Mostashri, 2009). 1.3.1 Complexity There are many definitions of complex systems, but in this context we consider a system as complex when “it is composed of a group of interrelated units (component and subsystems, to be defined), for which the degree and nature of the relationships is imperfectly known, with varying directionality, magnitude and time-scales of Parts Components/Nodes Subsystems Systems System of Systems Human Technologies Megasystem Human Society Countries/Regions Cities/Communities/Extended Enterprises Individuals Terms/Divisions Organizations/Institutions Figure 1.2 Hierarchies within the social/institutional and physical/technological layers. (Earll M. Murman and Thomas J. Allen, “Engineering systems: An Aircraft perspective.” Engineering systems symposium, MIT, 2003.). Social/Institutional Technological/Physic Information Network Figure 1.1 Sociotechnical system layers.
- 25. 4 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC interactions. Its overall emergent behavior is difficult to predict, even when subsys- tem behavior is readily predictable.” (Sussman, 2003) Sussman also defines three types of complexity in systems: behavioral (also called emergence), internal (also called structural), and evaluative (Sussman, 2003). Behavioral complexity arises when the emergent behavior of a system is difficult to predict and may be difficult to understand even after the fact. For instance, the easiest solution to traffic congestion seems to be to build new highways. New highways, however, cause additional traffic by attracting “latent transportation demand” due to the increased attractiveness of private autos, thus leading to more congestion in the long run. Internal or structural complexity is a measure of the interconnectedness in the structure of a complex system, where small changes made to a part of the system can result in major changes in the system output and even result in systemwide failure. A good example of this type of complexity is the side effect of chemother- apy, which, in addition to destroying cancerous cells, also suppresses the immune system of the body, resulting in death by infection in cancer patients. Evaluative complexity is caused by the existence of stakeholders in a complex system and is an indication of the different normative beliefs that influence views on the system. Thus, even in the absence of the two former types of complexity, and even if one were able to model the outputs and the performance of the system, it would still be difficult to reach an agreement on what “good” system performance signifies. This type of complexity is one of the primary motivators for engaging stakeholders in systems modeling and policy design and is an essential aspect of such systems. There are many different criteria to value particular outcomes in a sociotechnical system. Which criteria are used to evaluate outcomes, and how they are measured, have to be determined by the consensus or overwhelming majority agreement of the stakeholders. Otherwise, the valuation can be considered that of the experts and decision makers alone. Some of the social and economic valuation approaches for outcomes include (Mostashari, 2009) Utilitarian: This criterion is one of neoclassic economics. Essentially, the goal here is to maximize the sum of individual cardinal utilities. (W(x) = U1(x) + U2(x) + ... + Un(x)). Of course, this can only function if U1 is cardinal (and if the U’s are interpersonally comparable). Pareto optimality: The goal here is to reach an equilibrium that cannot be replaced by another one that would increase the welfare of some people with- out harming others. Pareto efficiency: This occurs when one person is made better off and no one is made worse off. Compensation principle: A better-off person can compensate the worse-off per- son to the extent that both of them are better off. Social welfare function: Here the state evaluates the outcome based on overall social welfare, taking into account distributional issues.
- 26. Sociotechnical Systems: A Conceptual Introduction ◾ 5 © 2011 by Taylor Francis Group, LLC Nested complexity exhibited by sociotechnical systems, refers to the fact that a tech- nologically complex system is often embedded or nested within in a complex insti- tutional structure. This added dimension of complexity is what makes the design and management of a sociotechnical system a great challenge. 1.3.2 Scale Sociotechnical systems are often large-scale systems characterized by a large num- ber of components, often stretching over a large geographical area or virtual nodes, and across physical, jurisdictional, disciplinary, and social boundaries. Often, their impacts are considered long-lived and significant, and affect a wide range of stake- holders (Mostashari and Sussman, 2009). 1.3.3 Integration and Coupling Subsystems within a sociotechnical system are connected to one another through feedback loops, often reacting with delays. The existence of multiple interacting feedbacks makes it harder to understand the effect of one part of the system. In such a system, an institutional decision may impact technologi- cal development, also impacting social, environmental, and economic aspects of the system. 1.3.4 Interactions with the External Environment Systems may be characterized as either closed or open. A closed system is one that is self balancing and independent from its environment. Open systems interact with their environment in order to maintain their existence. Most sociotechnical systems are affected by the environment they operate in and, in this sense, can be considered open systems. 1.3.5 Uncertainty and Risk in Sociotechnical Systems One of the main products of complexity in a system is uncertainty in its initial state, its short- and long-term behavior, and its outputs over time. Webster’s Dictionary defines uncertainty as “the state of being uncertain.” It further defines uncertain as “not established beyond doubt; still undecided or unknown.” Uncertainty refers to a lack of factual knowledge or understanding of a subject matter and, in this case, to the inability to fully characterize the structure and behavior of a system now or in the future. In analyzing complex systems, uncertainty can apply to the current state of a system and its components, as well as uncertainties on its future state and outcomes of changes to the system. Essentially, there are two categories of uncertainty: Reducible, and irreducible. Reducible uncertainty can be reduced over time with extended observation, better tools, better measurement, etc., until
- 27. 6 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC it reaches a level when it can no longer be reduced. Irreducible uncertainties are inherent uncertainties due to the natural complexity of the subject matter. We can distinguish the following types of uncertainty (Walker, 2003): Causal Uncertainty: When scientists draw causal links between different parts of the system, or between a specific input and an output, there is an uncertainty in the causal link. For instance, the relationship between air pollution concentration and respiratory problems is associated with causal uncertainty, given that the same air pollution concentrations can result in different levels of respiratory problems. This occurs because other, sometimes unknown, factors can influence the causal link. There is also the important difference between correlation and causation, in that an existing correlation does not necessarily indicate causation. Another source of causal uncertainty is the existence of feedback loops in a system. Causal uncertainty is strongly dependent on the “mental map” of the person drawing the linkages. Measurement Uncertainty: When measuring physical or social phenomena, there are two types of measurement uncertainty that can arise. The first is the reliability of the measurement, and the second is its validity. Reliability refers to the repeatability of the process of measurement, or its “precision,” whereas validity refers to the consistency of the measurement with other sources of data obtained in a different ways or its “accuracy.” The acceptable imprecision and inaccuracy in the case of different subject matters can be very different. For instance, the acceptable inaccuracy for a weather forecast is different from the inaccuracy of measurements for the leakage rate of a nuclear waste containment casket, given the different levels of risk involved. Therefore, defining the acceptable uncertainty in measurements is a rather subjective decision. Sampling Uncertainty: It is practically impossible to measure all parts of a given system. Measurements are usually made for a limited sample and generalized over the entire system. Such generalization beyond the sample gives rise to sampling uncertainty. Making an inference from sample data to a conclusion about the entire system creates the possibility that error will be introduced because the sample does not adequately represent that system. Future Uncertainty: The future can unfold in unpredictable ways, and future developments can impact the external environment of a system or its internal struc- ture in ways that cannot be anticipated. This type of uncertainty is probably one of the most challenging, given that there is little control over the future. However, it is possible to anticipate a wide range of future developments and simulate the effect of particular decisions or developments in a system across these potential futures. In sociotechnical systems, the effects of new technologies often cannot be adequately determined a priori. Collingridge (1980) indicates that, historically, as technologies have developed and matured, negative effects have often become evident that could not have been anticipated initially (automobile emissions or nuclear power accidents and waste disposal). Despite this ignorance, a decision has to be made today.
- 28. Sociotechnical Systems: A Conceptual Introduction ◾ 7 © 2011 by Taylor Francis Group, LLC Experts use models to predict values of some variables based on values of other variables. A model is based on assumptions about the initial state of a system (data), its structure, the processes that govern it, and its output. Any of these assumptions has inherent uncertainties that can affect the results that the model produces. The parameters and initial conditions of a model can often be more important than the relationships that govern the model in terms of the impact on the output. The “Limits to Growth” Models of the 1970s show how long-range models are not capable of characterizing long-term interactions between the economy, society, and the environment in a sociotechnical system. Additionally, individual and institu- tional choices can make socioeconomic models inherently unpredictable (Land and Schneider 1987). In real life, uncertainties cannot be reduced indefinitely, and the reduction of uncertainty is associated with costs. Therefore, an acceptable level of uncertainty for decision making has to be determined subjectively. The subjective nature of such a determination is one of the main rationales for stakeholder participation in decision making. Risk is the combination of the concepts probability (the likelihood of an out- come) and severity (the impact of an outcome). In fact, acceptable levels of uncer- tainty in the analysis of a system depend on acceptable levels of risk associated with that system. The concept of acceptable risk is essentially a subjective, value-based decision. While there are methodologies, such as probabilistic risk assessment, that try to provide an objective assessment of risk, it is the perception of the risk- bearing individuals, organizations, or communities that determine how much risk is acceptable. While many experts focus on providing the public with probabilities of possible outcomes for a system, Sjöberg (1994) indicates that the public is more concerned with the severity than with the probability. Allan Mazur (1981) empha- sizes the role of the media in affecting risk perceptions for people. He argues that the more people see or hear about the risks of a technology, for example, the more concerned they will become. This effect could occur both for negative coverage as well as positive coverage. 1.4 Dimensions of Sociotechnical Systems A sociotechnical system is defined through four main aspects: Its (manmade) structure and artifacts (technology, architecture, protocols, components, links, boundaries, internal complexity), its dynamics and behavior (emergence, nonlinear interactions, feedback loops), and its actors/agents (conscious entities that affect or are affected by the system’s intended or unintended effects on its environment). Finally, the environment it operates in also defines a sociotechnical system. Here, environment refers to the social, cultural, political, economic, and legal context within which the system is operating (Mostashari, 2009).
- 29. 8 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC A proposed taxonomy of sociotechnical systems studies can therefore consist of the following: ◾ ◾ Structural Studies: Research on architecture, technological artifacts, protocols and standards, networks, hierarchies, optimization and structural “ilities,” etc. ◾ ◾ Behavioral Studies: Research on nonlinearity, dynamic or behavioral com- plexity, dynamic “ilities,” material/energy/information flows, dynamic pro- gramming, emergence, etc. ◾ ◾ Agent/Actor System Studies: Research on decision making under uncertainty, agent-based modeling, enterprise architecture, human–technology interac- tions, labor–management relations, organizational theory, lean enterprise, etc. ◾ ◾ Policy Studies: Research on the interactions of the sociotechnical system with its environment, including institutional context and political economy, stake- holder involvement, labor relations, and social goals of sociotechnical sys- tems, as well as ecosystem and sustainability research. 1.5 Sociotechnical Networks One major type of sociotechnical system is sociotechnical networks. These are nor- mally networked physical/technological systems used and managed by a network of people, organizations, and enterprises. The Internet is a good example of such a system, as is the power grid. Sociotechnical networks are important because they can span across nations and impact millions of individuals. They are often critical in the effective functioning of societies and economies. Because of their networked nature, sociotechnical networks face major challenges with regard to security, resil- ience, reliability, multiobjective multilayer optimization, and tensions between local and global control and optimization. Additionally, there are organizational/ institutional challenges in regulation, standards, management, and governance of these networks. We will look at each of these issues briefly in subsequent sections. 1.5.1 Security The networked nature of sociotechnical systems makes them vulnerable to major security breaches that can endanger the operations of the network and compromise critical information and data. Due to the large number of access points in larger sociotechnical networks, developing a “secure” network is a highly challenging notion. The security aspect of sociotechnical networks has been primarily explored at the data network level. Many sociotechncial data network layers are heteroge- neous in nature and can include a TCP/IP backbone, sensor networks, WiMax, wireless local area networks, and cellular networks, all of which are vulnerable to security breaches. There have been extensive studies on network security for different sociotechnical systems, including risk and vulnerability assessment for
- 30. Sociotechnical Systems: A Conceptual Introduction ◾ 9 © 2011 by Taylor Francis Group, LLC sociotechnical power grids (Byres and Lowe, 2005), and security technology and practice assessments (Byres and Franz, 2006). In this book we will devote a key chapter to sociotechnical network security. 1.5.2 Resilience Resilience is defined as the ability of a system to maintain or recover its service delivery in the face of major external disruptions. Given the criticality of socio- techncial networks such as the power grid, the Internet, transportation networks, telecommunication networks, etc., in the proper functioning of society, the resil- ience of such systems in the face of various kinds of external shocks is critical. The resilience of sociotechnical networks is a function of their vulnerability as well as adaptive capacity (Omer et al., 2009). The less the vulnerability, the lower the pos- sibility that sociotechnical network performance will be compromised. The more the adaptive capacity of the system, the faster will the system jump back to its initial performance levels after being affected by a shock. Sociotechnical network resilience can increase when diversity, redundancy, modularity, and cognition/ autonomy are designed into the system. 1.5.3 Reliability Network reliability refers to the reliability of the overall network to provide commu- nication in the event of failure of a component or a set of components in the network (Wiley Encyclopedia of Electrical and Electronics Engineering, 1999). For sociotechnical networks, the reliability expands to all three layers, namely, the physical/technological network layer, the data communication layer, and the social/institutional layer. The main challenge is to define the holistic reliability of the sociotechnical network, given that the reliability of each network layer cannot be easily combined with that of the other layers. This is due to the differences in the fault modes and the asynchronous nature of failures within the components within each layer (physical, data, social). 1.5.4 Distributed versus Centralized Control In sociotechnical networks the physical or virtual connections are controlled either through a single network controller or through several controllers. The former is called centralized control, and the latter is known as decentralized control. In a sociotechnical network, distributed control systems are more common, as different parts of the system will have different types of control actions and would be distrib- uted over jurisdictional and geographical boundaries. Issues of local versus global optimization for larger-scale sociotechnical networks are fundamental systems-level decisions that need to depend on the organization and structure of the social net- work layer and on the economic optimization of locally managed networks as well as other system attributes and properties such as reliability, resilience, and security.
- 31. 10 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC 1.6 Sociotechnical Networks and Cognition The ability of a sociotechnical network to autonomously sense changes in its envi- ronment and respond to those changes relatively autonomously based on its prior experiences demonstrates its level of cognition. The higher the autonomy, the higher the cognitive ability of the network. One can define a Cognitioncentric System as having the following capabilities (Mitola, 2006): 1. Sensing individual internal and external changes 2. Perceiving the overall picture that these changes represent 3. Associating the new situation with past experienced situations and acting accordingly if similar 4. Planning various alternatives in response to the change within a given response timeline 5. Choosing course of action that seems best suited to the situation 6. Taking action by adjusting resources and outcomes to meet new needs and requirements 7. Monitoring and learning from the impact of capabilities 1–6 From the definition it follows that every system could exhibit these capabilities in different degrees. Each of these capabilities is used in a systems process that directly corresponds to it. The chain of the seven resulting processes constitutes the full cognitive process cycle for the system for any given set of changes. Chapter 10 will look at cognitioncentric sociotechnical systems in more detail. 1.7 Analyzing Sociotechnical Networks: CLIOS Analysis and the STIN Heuristics There are two main analysis methodologies for sociotechnical networks. The CLIOS (Complex, Large-scale, integrated, open systems) process (Mostashari and Sussman, 2009, Sussman, 2003) and the sociotechnical interaction network (STIN) concept (Kling et al., 2003). We will discuss the CLIOS process in detail in the sociotechnical systems modeling chapter. STIN is based on earlier work by Kling and Scacchi (1982) and identifies the following broad analysis activities for sociotechnical networks (Kling et al., 2003): 1. Stakeholder/Actor Analysis 2. Network Relationship Analysis 3. Network Trajectory Analysis In the first, the relevant population of system interactors is identified, the core inter- actor groups are mapped, and incentives within the network are characterized. In the second, excluded actors and undesired interactions are identified, and existing
- 32. Sociotechnical Systems: A Conceptual Introduction ◾ 11 © 2011 by Taylor Francis Group, LLC communication forums and resource flows are mapped. In the third, the architec- tural choice points are identified and mapped to the sociotechnical characteristics of the system (Kling, 2003). This approach is similar to the CLIOS process described in later chapters, although the CLIOS process identifies relevant models and meth- ods within a step-by-step analysis framework. In the following chapters of this book we will look at many of these issues in more detail. References Byres, E. and Franz, M. Uncovering Cyber Flaws, http://www.isa.org/InTechTemplate. cfm?Section=Article_Index1tContentID=50583, January 1, 2006, accessed October 2009. Byres, E. and Lowe, J. Insidious threat to control systems, InTech, vol. 52, no.1, 2005, p. 28. David Collingridge (1980), “The social control of Technology”, New York: St. Martin’s Press; London: Pinter. Encyclopedia of Electrical and Electronics Engineering 1999, ISBN: 978-0-471-13946-1. Hardcover. 17616 pages. Wiley: March 1999. Kling, R., McKim, G., and King, A. 2003. A bit more to IT: scholarly communication forums as socio-technical interaction networks. Journal of the American Society for Information Science and Technology, 54(1), 46–67. Kling, R. and Scacchi, W. 1982. The web of computing: computer technology as social orga- nization. Advances in Computers, Vol. 21, 3–87. Land, K.C. and Schneider, S.H. 1987. Forecasting in the Social and Natural Sciences: An Overview and Statement of Isomorphisms. In K.C. Land and S. H. Schneider, eds., Forecasting in the Social and Natural Sciences. Boston: D. Reidel. Mazur, A. 1981. Media Coverage and Public Opinion on Scientific Controversies. 31 J. COMM., 106 (1981). Mitola, J. 2006. Cognitive Radio Architecture: The Engineering Foundations of Radio XML. Wiley: Hoboken, NJ. Mostashari, A. and Sussman, J. 2009. A framework for analysis, design and operation of complex large-scale sociotechnological systems. International Journal for Decision Support Systems and Technologies, 1(2), 52–68, April–June. Omer, M., Nilchiani, R., and Mostashari, A. 2009. Assessing the Resiliency of the Global Internet Fiber-Optics Network, Proceedings of the International Symposium of Systems Engineering (INCOSE), July 2009, Singapore. Sjöberg, L. and. Drottz-Sjöberg, B.M. 1994. Risk Perception of Nuclear Waste: Experts and the Public Center for Risk Research, Stockholm School of Economics, Rhizikon: Risk Research Report 16. Sussman, J. 2003. Collected Views on Complexity in Systems. Massachusetts Institute of Technology, Engineering Systems Division Working Paper Series ESD-WP-2003-01.06- ESD Internal Symposium. Vincent Hogan and Ian Walker, (2003) “Education choice under uncertainty: Implications for public policy,” Labour Economics, Vol 14, 2007, Issue 6, Pages 894–912. Wall, M.B. 1996. A Genetic Algorithm for Resource-Constrained Scheduling, Doctoral Dissertation for Mechanical Engineering at the Massachusetts Institute of Technology, 1996.
- 34. 13 © 2011 by Taylor Francis Group, LLC Chapter 2 Systems-Level Modeling of Sociotechnical Systems Ali Mostashari Contents 2.1 Introduction................................................................................................14 2.2 Systems Analysis.........................................................................................14 2.2.1 Systems Engineering........................................................................14 2.2.1.1 Trade-Off Analysis............................................................15 2.2.1.2 Optimization.....................................................................15 2.2.1.3 Game Theory.....................................................................17 2.2.1.4 Agent-Based Modeling......................................................17 2.2.1.5 Benefit–Cost Analysis and Discounted Cash Flow............18 2.2.1.6 Utility Theory....................................................................18 2.2.1.7 Real-Options Analysis.......................................................18 2.2.2 System Dynamics............................................................................19 2.2.3 The CLIOS Process. .........................................................................20 2.2.3.1 Physical Domain and Institutional Sphere.........................20 2.2.3.2 The CLIOS Process as a Conceptual Methodology. ...........21 2.2.3.3 Relationship to Other Quantitative and Qualitative Systems Methodologies and Tools.....................................21 2.2.3.4 Overview of the CLIOS Process........................................22 2.2.3.5 Iterative Nature of CLIOS.................................................23 2.3 Conclusion..................................................................................................36 References............................................................................................................36
- 35. 14 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC 2.1 Introduction In addition to network models of sociotechnical networks, there are many other ways to model sociotechnical systems, taking into account the interactions between social and technological components. When analyzing a sociotechnical system, it is necessary to look at the entire system in a holistic fashion. One of the major milestones favoring this type of systemic approach in the analysis of complex sys- tems is systems theory. It was first proposed as an alternative to reductionism in the 1940s by the biologist Ludwig von Bertalanffy, who published his General Systems Theory (Bertalanffy, 1968). He emphasized that real systems were open and that they exhibited behavioral complexity or emergence. Rather than analyzing the individual behaviors of system components in isolation, systems theory focuses on the relationship among these components as a whole and within the context of the system boundaries. According to Bertalanffy, a system can be defined by the system-environment boundary, inputs, outputs, processes, state, hierarchy, goal directedness, and its information content (Bertalanffy, 1968). 2.2 Systems Analysis While systems theory provides the fundamental concepts for understanding a complex sociotechnical system, it does not provide a common methodology for how to analyze such a system. In the 1960s and 1970s, systems analysis evolved as an approach to analyzing complex systems. The American Cybernetics Society defines systems analysis as “an approach that applies systems principles to aid a decision-maker with problems of identifying, reconstructing, optimizing, and managing a system, while taking into account multiple objectives, constraints and resources. Systems analysis usually has some combination of the following: iden- tification and re-identification of objectives, constraints, and alternative courses of action; examination of the probable consequences of the options in terms of costs, benefits, and risks; presentation of the results in a comparative framework so that the decision maker can make an informed choice from among the options.”* Many systems analysis tools and processes have been proposed for analyzing different aspects of complex systems. Here we will look at Systems Engineering, Systems Dynamics, and the CLIOS Process as important ways to analyze CLIOS. In the following sections, we will take a look at each of these approaches. 2.2.1 Systems Engineering Systems engineering is a discipline that develops and exploits structured, efficient approaches to analysis and design to solve complex engineering problems. Jenkins * Web Dictionary of Cybernetics and Systems, American Cybernetics Society, http://pespmc1.vub. ac.be/ASC/indexASC.html.
- 36. Systems-Level Modeling of Sociotechnical Systems ◾ 15 © 2011 by Taylor Francis Group, LLC (1971) defines the following stages for a systems engineering approach to solv- ing complex systems: Systems Analysis, System Design, and Implementation and Operation. For each of these stages, a different number of systems engineering tools and methods exist that can help analyze different aspects of the system. The methods include such elements as trade-off analysis, optimization (operations research), sen- sitivity analysis, utility theory, benefit–cost analysis, real-options analysis, game theory, and diverse simulation methods such as genetic algorithms or agent-based modeling.* At any stage of a systems engineering analysis of a complex system, a combination of these tools and methods can be used. In the following paragraphs, we will consider each of these tools and methods and comment on their strengths and weaknesses. 2.2.1.1 Trade-Off Analysis When dealing with a complex system, there are multiple values that we would like to maximize. Often, these goals and objectives can be in direct conflict with one another, and maximizing one can adversely affect the other. Trade-off analysis allows us to find those outcomes in the systems that have combinations of values that are acceptable to us, and which maximize the overall value of the system as a way to deal with evaluative complexity. Multiattribute trade-off analysis can be used for cases where there are multiple objectives in a given system. The draw- back with trade-off analysis is that many benefits are not continuous in nature. For instance, in the case of a sociotechnical power grid, there is a trade-off between local and global optimization: either the grid parameters are optimized for a local area or for the global grid as a whole. Trade-off is thus not a continuous curve and cannot be well represented using trade-off analysis. 2.2.1.2 Optimization Optimization is the maximization or minimization of an output function from a system in the presence of various kinds of constraints. It is a way to allocate system resources such that a specific system goal is obtained in the most efficient way. Optimization uses mathematical programming (MP) techniques and simulation to achieve its goals. The most widely used MP method is linear programming, which was made into an instant success when George B. Dantzig developed the simplex method for solving linear-programming problems in 1947. Other widely used MP methods are integer and mixed-integer programming, dynamic programming, and different types of stochastic modeling. The choice of methodology depends mainly on the size of the problem and the degree of uncertainty. Table 2.1 shows what * The Institute for Systems Research, What is Systems Engineering, http://www.isr.umd.edu/ ISR/about/definese.html#what.
- 37. 16 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC methods are used for certain and uncertain conditions in the strategy evaluation and generation stages of systems analysis. Another type of optimization method is Genetic Algorithm (GA). A genetic algorithm is an optimization algorithm based on Darwinian evolutionary mecha- nisms and uses a combination of random mutation and crossover and selection procedures to breed better models or solutions from an originally random starting population or sample (Wall, 1996). Optimization methods are tools that are suitable for analyzing large-scale net- works and allocation processes, but may not fit all purposes. Often when social considerations exist, the goal is not optimization but satisfaction of all stakeholder groups involved. Also, when optimization occurs, there is no room for flexibility in the system, making the system vulnerable to changes that happen in its environment over time. Table 2.1 A Systems Engineering Approach for Dealing with Complex Sociotechnical Systems Stages Methods • System Analysis 1. Recognition and formulation of the problem 2. Organization of the project 3. Definition of the system 4. Definition of the wider system 5. Definition of the objectives of the wider system 6. Definition of the objectives of the system 7. Definition of the overall economic criterion 8. Information and data collection • System Design 1. Forecasting 2. Model building and simulation 3. Optimization 4. Control • Implementation 1. Documentation and sanction approval 2. Construction • Operation 1. Initial operation 2. Retrospective appraisal of the project Source: Jenkins, 1971.
- 38. Systems-Level Modeling of Sociotechnical Systems ◾ 17 © 2011 by Taylor Francis Group, LLC 2.2.1.3 Game Theory Game theory is a branch of mathematics first developed by John von Neumann and Oskar Morgenstern in the 1940s, and advanced by John Nash in the 1950s. It uses models to predict interactions between decision-making agents in a given set of conditions. Game theory has been applied to a variety of fields such as economics, market analysis, and military strategy. It can be used in a complex system where multiple agents (conscious decision-making entities) interact noncooperatively to maximize their own benefit. The underlying assumption for game theory is that agents know and understand the benefits they can derive from a course of action, and that they are rational. 2.2.1.4 Agent-Based Modeling Agent-based modeling is a bottom-up system modeling approach for predicting and understanding the behavior of nonlinear, multiagent systems. An agent is a conscious decision-making element of the system that tries to maximize its local benefit. The interaction of agents in a system is a key feature of agent-based systems. It assumes that agents communicate with each other and learn from each other. The proponents of this approach argue that human behavior in swarms (or soci- ety) within a CLIOS can only be predicted if individual behavior is considered a Table 2.2 Mathematical Programming and Simulation Modeling Methods for Sociotechnical Systems Solution Evaluation Solution Generation Certainty − − Deterministic Simulation − − Linear Programming − − Econometric Models − − Network Models − − System of ODEs − − Integer and mixed-integer programming − − Input–Output Models − − Nonlinear programming − − Control Theory Uncertainty − − Monte Carlo Simulation − − Decision Theory − − Econometric Models − − Dynamic Programming − − Stochastic Processes − − Inventory Theory − − Queuing Theory − − Stochastic Programming − − Reliability Theory − − Stochastic Control Theory Source: Applied Mathematical Programming. Bradley, Hax, and Magnanti. Addison- Wesley, 1977.
- 39. 18 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC function of information exchange among individuals who are trying to maximize their profits (Cetin and Baydar, 2004). The main drawback of agent-based model- ing approaches is that the initial assumptions about an individual’s behavior can predetermine the aggregate systems behavior, making the outcome very sensitive to the initial assumptions of the system. 2.2.1.5 Benefit–Cost Analysis and Discounted Cash Flow Benefit–cost analysis (also called cost–benefit analysis) is a methodology developed by the U.S. Army Corps of Engineers before World War II that allows decision mak- ers choose projects that produce the greatest net benefit for every dollar spent. This method has been used to analyze the feasibility of complex large-scale projects by the public and private sectors. It uses the net present value (NPV) as a basis for decision making, and is used extensively to this day. The underlying assumption of this type of analysis is that benefits and costs can be converted easily to monetary benefits and can be compared across heterogeneous projects. This can be a particularly bad assumption when dealing with social systems, where benefits are less tangible in monetary terms and evaluated differently by different stakeholders. Also, the choice of the discount rate and distributional effects are hard to capture with this methodology. 2.2.1.6 Utility Theory Utility is an economic concept that realizes that the benefits of a specific good or service are not uniform across the population. It is a measure of the satisfaction obtained from gaining goods or services by different individuals. It can comple- ment benefit–cost analysis by including the decision-maker’s preferences as a mea- sure of comparison of large-scale projects. One of the problems with utility theory is that people’s preferences can change very fast, and often there are conflicting utilities among the different decision makers and stakeholders, making it difficult to use a single utility for a course of action or a system outcome. 2.2.1.7 Real-Options Analysis Real-options analysis is the application of financial option pricing to real assets. Instead of the now-or-never investment options that are used in a traditional NPV (Net Present Value) analysis, real-options analysis provides an opportunity but not an obligation for the decision maker to make use of opportunities that arise under uncertain conditions. Similar to stock options, the decision maker spends an initial investment that provides them with an opportunity to act under certain conditions to improve the value of the system they manage (Amram and Kulatlaika, 1998). A drawback of the real options analysis is that it depends on a known volatility pro- file for any given system, something that is a far stretch for most complex systems where historical data is not necessarily predictive of future behavior.
- 40. Systems-Level Modeling of Sociotechnical Systems ◾ 19 © 2011 by Taylor Francis Group, LLC 2.2.2 System Dynamics System dynamics is a tool for modeling complex systems with feedback that was developed by Jay Forrester at the Massachusetts Institute of Technology in the 1960s. He developed the initial ideas by applying the concepts from feedback control theory to the study of industrial systems (Forrester, 1961). One of the best- known and most controversial applications of the 1960s was Urban Dynamics (Forrester, 1969). It tried to explain the patterns of rapid population growth and subsequent decline that had been observed in American cities such as New York, Detroit, St. Louis, Chicago, Boston, and Newark. Forrester’s simulation model portrayed the city as a system of interacting industries, housing, and people, and was one of the first systems models for a sociotechnical system. Another widely known application of system dynamics was the “Limits to Growth” study (Meadows et al., 1972), which looked at the prospects for human population growth and industrial production in the global system over the next century. Using computer simulations, resource production and food supply changes in a system with growing population and consumption rates were modeled. The model predicted that societies could not grow indefinitely and that such growth would bring the downfall of the social structure and result in catastrophic short- ages of food for the world population. Given that the results of the model were highly dependent on initial assumptions as well as the designed structure, most of the predictions were not confirmed by observation in the years since, and many in the academic community have used this as evidence to discredit the value of system dynamics in modeling large-scale sociotechnical systems. Therefore, system dynamics has in recent years shifted mostly toward solving specific prob- lems rather than modeling entire large-scale systems. While system dynamics has made substantial progress in the past four decades, those academics not in the field still consider its merits limited, mainly because of the early large-scale experiments by Forrester and Meadows. System dynamics uses causal loop diagrams to represent relationships and causal links between different components in a system. In addition to qualitative representations, system dynamics also uses control theory for quantification. It uses stocks and flows along with feedback loops and delays, which can explain how the different elements of a complex system are linked together. Its qualitative representation, combined with its quantitative output, make it a suitable tool for modeling sociotechnical systems. In terms of quantitative capa- bilities, system dynamics has the ability of performing extensive multivariable sen- sitivity analysis. This means that, if we are not certain of the inputs into the model, we can provide a range for each, and the system dynamics model will calculate all the possible combinations and provide a range of values as the output. One of the major strengths of system dynamics is in simulating effects that are delayed in time. This helps us model how an event or series of events five years ago might have contributed to the status of things today, or how current policies
- 41. 20 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC might start to pay off in a couple of years and not immediately. System dynamics emphasizes quantification of a systems model as the only way to gain insights from its behavior. The CLIOS process, which uses a similar concept for representing complex systems, emphasizes both qualitative and quantitative insights. We will look at the CLIOS process in more detail in the upcoming section. 2.2.3 The CLIOS Process The CLIOS process (Mostashari and Sussman, 2009) is an approach to fostering understanding of complex sociotechnical systems by using diagrams to highlight the interconnections of the subsystems in a complex system and their potential feed- back structures. The motivation for the causal loop representation is to convey the structural relationships and direction of influence between the components within a system. In this manner, the diagram is an organizing mechanism for exploring the system’s underlying structure and behavior and then identifying options and strategies for improving the system’s performance. 2.2.3.1 Physical Domain and Institutional Sphere A CLIOS system can be thought of as consisting of a physical domain—with inter- connected physical subsystems—nested in an institutional sphere (i.e., nested com- plexity). This is illustrated in Figure 2.1. Therefore, when we speak of a CLIOS system, we refer both to the physical and the institutional aspects of the system in which we are interested. The choice of system boundary (for both the physical domain and the institutional sphere) within the CLIOS process depends on the problem we are trying to address and the extent of our leverage over the system. Physical Domain Subsystem 1 Subsystem 2 Subsystem 3 CLIOS System Boundary Component Institutional Sphere Figure 2.1 A CLIOS system consists of a physical domain (made up of subsys- tems), nested within an institutional sphere.
- 42. Systems-Level Modeling of Sociotechnical Systems ◾ 21 © 2011 by Taylor Francis Group, LLC However, the choice of systems boundary for the physical domain will affect our choice of boundary for the institutional sphere, and vice versa. Recently, there have been important attempts at looking at complex CLIOS- type systems from a holistic, enterprise perspective (Swartz and DeRosa, 2006). There has been a recognition on behalf of systems engineering practitioners that standard processes need to be adapted based on insights from complexity science, and various principles for incorporating complexity as a consideration within such processes have been proposed (Sheard and Mostashari, 2009). One of the most important developments in this area was the definition of a research agenda for Complex Engineered, Organizational and Natural Systems by over 50 thought lead- ers in complexity (Rouse, 2007). In particular, with regard to particular CLIOS Systems, there have been important studies looking at the analysis and design of urban and regional transportation systems (Sussman, Sgoruidis and ward, 2004), air combat systems (Kometer, 2005), maritime surveillance systems (Martin, 2004), lean manufacturing systems, aerospace systems design (McConnell, 2007), regional energy systems design (Mostashari, 2005), nuclear waste transportation and storage systems (Sussman, 2000), municipal electric utilities (Osorio Urzua, 2007), public–private partnerships in infrastructure development (Ward, 2005), and environmental systems (Mostashari and Sussman, 2005) among others. 2.2.3.2 The CLIOS Process as a Conceptual Methodology As an alternative systems design process for CLIOS Systems, this chapter proposes the CLIOS process, a highly iterative and modular 12-step conceptual process for concurrent analysis, design, and management of coupled complex technological and institutional systems in the face of uncertainty. An overview of the CLIOS process is presented, followed by papers exploring detailed applications in complex large-scale engineering systems. As an engineering systems design, analysis, and management process, the CLIOS process does not rely on a particular analysis methodology or modeling tool. Rather similar to ANSI/EIA 632, it is a conceptual process that can serve as an organizing framework for the design, analysis, and management process of CLIOS systems. 2.2.3.3 Relationship to Other Quantitative and Qualitative Systems Methodologies and Tools As indicated, the CLIOS process is a conceptual framework and does not limit the user to a particular methodology. As such, it allows for a variety of computational (quantitative) or qualitative tools to be utilized for analyzing the physical domain and the institutional sphere. Table 2.4 represents the variety of quantitative and qualitative methodologies and tools that can be applied in the different steps of the CLIOS process. This is not an exhaustive list but provides a starting point for the user depending on the type of CLIOS system at hand.
- 43. 22 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC 2.2.3.4 Overview of the CLIOS Process The CLIOS process is composed of twelve steps divided into three stages (see Figure 2.2). The three stages are Representation; Design, Evaluation, and Selection; and Implementation and Adaptation (Table 2.3). In stage one—Representation— the CLIOS system representation is created and considered in terms of both its Representation Design, Evaluation and Selection Implementation and Adaptation A B C D E 1. Describe CLIOS System: Checklists Preliminary Goal Identification 2. Identify Subsystems in Physical Domain Groups on Institutional Sphere 3. Populate the Physical Domain Institutional Sphere 4A. Describe Components 4B. Describe Links 5. Transition from Descriptive to Prescriptive Treatment of System 6. Refine CLIOS System Goals Identify Performance Measures 7. Identify Design Strategic Alternatives for System Improvements 8. Identify Important Areas of Uncertainty 9. Evaluate Strategic Alternatives Select “Bundles” 10. Physical Domain/ Subsystems 11. Institutional Sphere 12. Evaluate, Monitor Adapt Strategic Alternatives for CLIOS System Design and Implement Plan for: G F Figure 2.2 The twelve steps of the CLIOS process with suggested iteration points. (From Mostashari A. and Sussman J. 2009. A framework for analysis, design and operation of complex large-scale sociotechnological systems. International Journal for Decision Support Systems and Technologies, 1(2), 52–68, April–June 2009.)
- 44. Systems-Level Modeling of Sociotechnical Systems ◾ 23 © 2011 by Taylor Francis Group, LLC structure and behavior. In this stage, we also establish preliminary goals for the system—that is, in what ways do we want to improve its performance? In stage two—Design, Evaluation, and Selection—strategic alternatives for performance improvements to the physical domain and institutional sphere are designed, evaluated, and, finally, some are selected. In stage three—Implementation and Adaptation—implementation plans for the physical domain and the institutional sphere are designed and refined. The strategies are then adapted to new needs and observations. An overview of the three stages is shown in Figure 2.2. The twelve steps are coded by the shading of the boxes to indicate whether they are part of the representation; design, evaluation, and selection; or implementation stage. 2.2.3.5 Iterative Nature of CLIOS While the CLIOS process is constructed as a set of ordered steps, it constitutes an iterative process, and not a rigid, once-through process. Indeed, as shown in Figure 2.2, there are several important points where iteration can occur. In the fol- lowing sections, we will outline each of the steps in more detail. Table 2.3 Summary of Three Stages of CLIOS Stage Key ideas Outputs 1. Representation • Understanding and visualizing system structure and behavior • Establishing preliminary system objectives System description, issue identification, goal identification, and structural representation 2. Design, Evaluation, and Selection • Refining system objectives while cognizant of complexity and uncertainty • Developing bundles of strategic design alternatives Identification of performance measures, identification and design of strategic alternatives, evaluation of bundles of strategic alternatives, and selection of the best performing bundles 3. Implementation and Adaptation • Implementing bundles of strategic alternatives • Following-through— changing and monitoring the performance of the CLIOS System Implementation strategy for strategic alternatives in the physical domain and the institutional sphere, actual implementation of alternatives, and postimplementation evaluation
- 45. 24 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC Table 2.4 Selected Quantitative and Qualitative Methodologies for the CLIOS Process CLIOS Process Step Methodology Quantitative or Qualitative Description CLIOS Step 1: Describe CLIOS system Data collection and stakeholder surveys and interviews Qualitative Interactive and written interviews with people with knowledge, expertise, and critical interest in the system, and data collection from existing published info on system Delphi process Qualitative Structured process for stakeholder knowledge collection and distillation with controlled opinion feedback (Adler and Ziglio, 1996) Requirements Elicitation and Analysis Qualitative Process that identifies and extracts the necessary attributes, capabilities, characteristics, or quality of systems from stakeholders (Young, 2001) Mutually Exclusive, Collectively Exhaustive (MECE) analysis Qualitative Information grouping process dividing information into subgroups that are collectively comprehensive and that do not overlap (Rasiel, 1999) CLIOS Steps 2, 3, 4, and 5: Identify subsystems, populate them, and identify components and links within each Causal Loop Diagramming (Systems Mapping) Qualitative Systems diagramming process visualizing how interrelated variables within a system affect one another (Sterman, 2000) Stakeholder-Assisted Modeling and Policy Design (SAM-PD) process Qualitative Collaborative stakeholder process using insights from systems thinking, conflict assessment, and linguistics to extract stakeholder knowledge for systems representation (Mostashari, 2005)
- 46. Systems-Level Modeling of Sociotechnical Systems ◾ 25 © 2011 by Taylor Francis Group, LLC CLIOS Steps 6, 7, and 8: Refine system objectives, identify system design and improvement strategies, and identify uncertainties Delphi process Qualitative Described earlier SAM-PD process Qualitative Described earlier Scenario Analysis Qualitative Process of analyzing possible futures for a system (Schwartz, 1996) Risk Management Qualitative/ quantitative Process for analyzing threats to a system and identifying ways to mitigate them CLIOS Step 9: Evaluate strategic alternatives (Systems Modeling) Systems Dynamics Modeling Quantitative Control-theory-based stock and flow modeling methodology addressing feedback loops and time delays that affect the behavior of the entire system (Sterman, 2000) Social Network Analysis Quantitative Analysis methodology for modeling the interactions and connections on the institutional sphere and among social actors interacting with the physical domain (Mullins, 1973) Agent-Based Modeling Quantitative Computational model for simulating the actions and interactions of actors (individuals or organizations) in a network (Holland, 1995) (Continued)
- 47. 26 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC Table 2.4 (Continued) Selected Quantitative and Qualitative Methodologies for the Clios Process CLIOS Process Step Methodology Quantitative or Qualitative Description Flow Network Analysis methodologies Quantitative A mathematical methodology for analyzing flows within a network consisting of nodes (edges) and links (arcs). Applicable to most CLIOS systems that can be modeled as networked systems (Ahuja et al., 1993) Statistical and Economic Analysis methodologies Quantitative Methods for analyzing relationships between different variables based on existing data sets; Useful for systems in which ample long-term data exist Operations Research (OR) methods Quantitative An interdisciplinary field that uses mathematical modeling and statistics to arrive at optimal or near-optimal solutions based on constraints and objective functions CLIOS Steps 10, 11, and 12: Implement, monitor, and improve system Project Management Qualitative Structured process for implementing a product, service, or system with quality assurance in a limited time Adaptive Management Qualitative A structured, iterative process of optimal decision making in the face of uncertainty, accruing information needed to improve future systems management (Holling, 1978) Source: Mostashari, A. and Sussman, J. 2009. A framework for analysis, design and operation of complex large-scale sociotechno- logical systems. International Journal for Decision Support Systems and Technologies, 1(2), 52–68, April–June 2009.
- 48. Systems-Level Modeling of Sociotechnical Systems ◾ 27 © 2011 by Taylor Francis Group, LLC 2.2.3.5.1 CLIOS Stage 1: Representation The representation stage aids in the understanding of the complete CLIOS system by examining the structures and behaviors of the physical subsystems and institu- tional sphere and the interactions between them. The CLIOS process usually uses a combination of diagrams and text to capture the critical aspects of the CLIOS system and present them in an easy-to-comprehend format. When the CLIOS pro- cess is carried out jointly by a group of analysts, decision makers, and stakeholders, the representation stage is used to create a common understanding of the system among these actors (Mostashari and Sussman, 2005). 2.2.3.5.1.1 CLIOS Step 1: Describe CLIOS System: Checklists and Preliminary Goal Identification — In defining the system that pertains to the problem, we first create several checklists to serve as a high-level examination of the CLIOS system. The lists should address the question “What is it about the system that makes it interesting, and what major systems issues/goals are we interested in?” (Puccia and Levins, 1985). The first of the checklists is the characteristics checklist that may relate to (a) the temporal and geographic scale of the system, (b) the core technologies and systems, (c) the natural physical conditions that affect or are affected by the system, (d) the key economic and market factors, (e) important social or political factors or controversies related to the system, and (f) the historical development and context of the CLIOS system. The second checklist, essentially a SWOT Strengths, Weaknesses, Opportunites, and Threats analysis, captures opportuni- ties, issues, and challenges—those aspects of the CLIOS System for which we may seek constructive improvements through strategic alternatives in Stage 2. Finally, in the third checklist, we identify preliminary system goals and require- ments that often relate to the opportunities, issues, and challenges found in the second checklist. To compile the lists, one can draw upon a wide range of sources: academic articles and books, popular press, reports published by the government, business, nongovernmental organizations (NGOs), discussions/interviews with stakeholders, or personal expertise or experience with the system, etc. 2.2.3.5.1.2 CLIOS Step 2: Identify Subsystems in the Physical Domain and Actor Groups on the Institutional Sphere — To outline the general struc- ture of the CLIOS system, we determine (a) which major subsystems make up the physical domain of the CLIOS System, (b) who the main actor groups are on the institutional sphere, and (c) how they relate to one another on a macro level (Mostashari and Sussman, 2009). For the Physical Domain: Here we parse the physical domain (or system) into subsystems, map out the structure of those subsystems (which can be envisioned as layers), and finally identify the key linkages between the subsystems. This is a difficult process but worthwhile in that many of the insights into the structure and
- 49. 28 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC behavior of the CLIOS system will come through while thinking about how it can be subdivided into the different layers. For the Institutional Sphere: We then identify the major actor groups on the institutional sphere. The general categories may include government agencies, pri- vate sector firms, citizen groups, as well as independent expert/advisory entities and so forth. This can be derived from the checklists in terms of who manages the system, who is affected by it, who attempts to influence, it, and, in general, who worries about it. 2.2.3.5.1.3 CLIOS Step 3: Populate the Physical Domain and the Institutional Sphere — Populating the Physical Domain: In this step we employ the type of basic subsystem diagram common in systems sciences, “defined as having components and relations that may be represented (at least in principle) as a network-type diagram with nodes representing components and lines repre- senting the relationships” (Flood and Carson, 1993). Initial CLIOS subsystem diagrams are created by detailing each subsystem and identifying the major com- ponents in each and the links indicating the influence of the components on each other. Sometimes a component can be common to more than one subsystem (Mostashari and Sussman, 2009). Figure 2.3 shows the populated subsystems and the concept of the common driver linking them. This type of representation is similar to causal loop diagrams (CLDs) used in System Dynamics, and system dynamics software provides a good platform for developing computer-aided CLIOS systems representations. One technique that can be used for increasing the resolution of the system representation without creat- ing overcrowded diagrams is expanding. Expanding focuses on critical components and magnifies their functions into separate diagrams for more detailed study. This is shown in Figure 2.4. Populating the Institutional Sphere: Parallel to populating the subsystems of the physical domain with components, we populate the institutional sphere with Subsystem 1 Component Link Subsystem 2 Subsystem 3 Subsystem 4 Common Driver Common Driver Figure 2.3 Populating the subsystem diagrams.
- 50. Systems-Level Modeling of Sociotechnical Systems ◾ 29 © 2011 by Taylor Francis Group, LLC Physical Domain Institutional Sphere Economic Activity Land Use Environment Transportation Institutional Sphere Map VM T CLIOS Sub-systems (Layering) CLIOS Congestion Charging GDP Vehicle Emissions Resident and Workplace Location Emission Regulations Highway Infrastructure Funding Allocation Highway Operations Expanding Partial CLIOS Diagram for the Transportation Subsystem Highway Network Intermodal Connections M a p p i n g S p h e r e t o P l a n e State DOT EPA Federal DOT Figure 2.4 Illustration of Step 3 for a sociotechnical transportation network example. (From Mostashari, A. and Sussman, J. 2009. A framework for analysis, design and operation of complex large-scale sociotechnological systems. International Journal for Decision Support Systems and Technologies, 1(2), 52–68, April–June 2009.)
- 51. 30 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC individual actors within each of the major actor groups and show the links between them. Figure 2.4 illustrates the tasks described in Step 3 for a transportation system example. It shows the various subsystems selected, the institutional sphere mapped onto a plane for convenience, with the subsystems and sphere populated with com- ponents and actors, respectively (Mostashari and Sussman, 2009). 2.2.3.5.1.4 CLIOS Step 4A: Describe Components in the Physical Domain and Actors on the Institutional Sphere — Components of the physical domain: Up to this point, the components have been considered as generic. In this step we more carefully characterize the nature of the individual components. Within the physical domain, we consider three basic types of components. Regular components (or from now on, simply “components” and indicated by circles) are usually the most common in the subsystem diagrams within the physical domain. Policy Levers (indicated by rectangles) are components within the physical domain that are most directly controlled or influenced by decisions taken by the actors—often institu- tions and organizations—on the institutional sphere. Common Drivers (indicated by diamonds) are components that are shared across multiple and possibly all sub- systems of the physical domain (Mostashari and Sussman, 2009). In Figure 2.5 we show three shapes used for different CLIOS system compo- nents. External factors are indicated by shading, rather than by shape, and can still be either a component or a common driver. Actors on the institutional sphere: In parallel to describing the components in the physical domain, we also describe the actors on the institutional sphere. In describing the actors, we can identify important characteristics, such as their power or mandate over different parts of the physical subsystems, their interests in the subsystems, their expertise and resources, and their positions with regard to differ- ent potential strategic alternatives. Much of this information can be derived from the actor’s formal mandate, as well as interviews and other information sources that shed light on the described characteristics. 2.2.3.5.1.5 CLIOS Step 4B: Describe Links — As the components are char- acterized and divided into different types, we also, in parallel, need to characterize the nature of the several kinds of links. Link notation needs to be consistent; if they represent different things, one should use different diagrammatic components (Flood and Carson, 1993). In the diagrams used in the CLIOS system representa- tion, these links will be largely qualitative. Generally, the links should indicate Component Common External Policy Figure 2.5 CLIOS system diagram component shapes.
- 52. Systems-Level Modeling of Sociotechnical Systems ◾ 31 © 2011 by Taylor Francis Group, LLC directionality of influence and feedback loops, as well as the magnitude of influ- ence (big/important or small/marginal impacts on the adjoining components) (Mostashari and Sussman, 2009). In thinking about the linkages, a key aspect of the CLIOS system representa- tion is to develop a framework for thinking about and describing the links in the system. We identify here three classes of links: ◾ ◾ Class 1: Links between components in a subsystem ◾ ◾ Class 2: Links between components in a subsystem and actors on the institu- tional sphere (also called “projections”) ◾ ◾ Class 3: Links between actors on the institutional sphere There are different approaches appropriate to each class of links. Generally, the links within the physical domain (Class 1) can be analyzed using engineering- and microeconomics-based methods, and will often be quantifiable. Regarding the links from the institutional sphere to the physical subsystems (Class 2 or projec- tions), quantitative analysis is less useful since human agency and organizational and stakeholders’ interests come into play as they attempt to induce changes in the physical domain. Finally, there are the interactions that take place within the insti- tutional sphere itself (Class 3). Understanding this class of links requires methods drawing upon theories of organizations, institutions, politics, and policy. According to Karl Popper (1972), “obviously what we want is to understand how such non- physical things as purposes, deliberations, plans, decisions, theories, intentions and values, can play a part in bringing about physical changes in the physical world” (cited in Almond and Genco (1977), emphasis in original). 2.2.3.5.1.6 CLIOS Step 5: Transition from Descriptive to Prescriptive Treatment of System — Once the general structure of the CLIOS system has been established, and the behavior of individual components, actors, and links has been relatively well characterized, we can use this information to gain a better understanding of the overall system behavior and, where possible, counterintuitive or emergent system behavior by asking the following types of leading questions (Mostashari and Sussman, 2009). First, with respect to the physical layers (Class 1 links), are there strong interac- tions within or between subsystems? Are there chains of links with fast-moving, high-influence interactions? Are some of the paths of links strongly nonlinear and/ or irreversible in their impact? Finally, can strong positive or negative feedback loops be identified? Second, looking at the links between the institutional sphere and the physical subsystems (Class 2 links or projections), can we identify components within the physical domains that are influenced by many different organizations in the insti- tutional sphere? If so, are the organizations pushing the system in the same direc- tion, or is there competition among organizations in the direction of influence?
- 53. 32 ◾ Ali Mostashari © 2011 by Taylor Francis Group, LLC Alternatively, do some organizations on the institutional sphere have an influence on many components within the physical domain? Finally, within the institutional sphere itself (Class 3 links), are the relationships between organizations characterized by conflict or cooperation? Are there any high- influence interactions, or particularly strong organizations, that have direct impacts on many other organizations within the institutional sphere? What is the hierarchi- cal structure of the institutional sphere, and are there strong command and control relations among the organizations, and/or are they more loosely coupled? What is the nature of interaction between several organizations that all influence the same subsystems within the physical domain? 2.2.3.5.2 CLIOS Stage 2: Design, Evaluation, and Selection Having considered the CLIOS system from the standpoint of its structure and behav- ior during the Representation stage, the next stage focuses on the design, evaluation, and selection of strategic alternatives for the system. This culminates in the develop- ment of a robust bundle of strategic alternatives. Among these strategic alternatives may be organizational and institutional changes that may be necessary to meet the CLIOS system goals (defined in Step 1, and to be reconsidered in Step 6). 2.2.3.5.2.1 CLIOS Step 6: Refine CLIOS System Goals and Identify Performance Measures — Entering the second stage of the CLIOS process, it is necessary to refine the preliminary goals developed in Step 1 to reflect the knowledge and insight gained at this point in the process. The concrete vision of the desired future state of the system, as prescribed by the refined goals, can then be used to identify performance measures that mark the progress from the current to the desired future state. 2.2.3.5.2.2 CLIOS Step 7: Identify and Design Strategic Alternatives for CLIOS System Improvement — The establishment of refined goals and perfor- mance measures naturally leads to questions about how CLIOS system performance can be improved through strategic alternatives. This is a creative step in the CLIOS process where imagination in developing strategic alternatives is to be valued, and out-of-the-box thinking and brainstorming is often a key to success. Performance improvements through strategic alternatives can take three forms. Thinking about nested complexity, we can characterize strategic alternatives as ◾ ◾ Physical changes involving direct modification of components in the physical domain ◾ ◾ Policy-driven changes involving the policy lever projections from the institu- tional sphere on the physical domain ◾ ◾ Actor-based—architectural changes of the institutional sphere either within actors or between actors
- 54. Systems-Level Modeling of Sociotechnical Systems ◾ 33 © 2011 by Taylor Francis Group, LLC In many cases, in order to achieve changes in the physical domain, policy-driven strategic alternatives need to be considered. These strategic alternatives may rely on incentives or disincentives such as taxes, subsidies, voluntary agreements, and restrictions on certain behaviors. Implicit in these types of alternatives is usually an assumption about how a policy change, initiated by actors on the institutional sphere, will cascade through the physical domain, and what changes in the perfor- mance measure will occur. Following this process can also reveal where strategic alternatives of this kind are counterproductive, diminishing the performance in other parts of the system. 2.2.3.5.2.3 CLIOS Step 8: Flag Important Areas of Uncertainty — A parallel activity to the identification of strategic alternatives for CLIOS system performance improvements is uncertainty analysis. In addition to internal and external risks that can be identified in a risk-management framework, there are additional uncertainties that deal with our lack of understanding of the system due to its emergent behaviors. In identifying key uncertainties, one can rely on the insights gained in Stage 1 and Step 6, in which we looked for chains of strong interactions, areas of conflict between stakeholders, or emergent behavior resulting from feedback loops. A promising qualitative methodology for identify- ing key uncertainties and understanding their impact on the CLIOS system is Scenario Planning as developed by Royal Dutch/Shell in the years leading up to the oil shocks of the 1970s (Schwartz, 1996). Quantitative approaches such as probabilistic risk assessment and event tree analysis are of value as well in this step of the CLIOS process. Another way of approaching uncertainty is exempli- fied by real options used to value flexibility and flexible strategic alternatives. McConnell (2007) describes ways that life-cycle flexibility can be integrated into the CLIOS Process. 2.2.3.5.2.4 CLIOS Step 9: Evaluate Strategic Alternatives and “Bundles” — In this step, the individual strategic alternatives that were generated in Step 7 are evaluated using the models developed in Step 6 or additional models if need be. Also, we can return here to the insights gained in Stage 1. Usually, each alternative is exam- ined with regard to how it impacts the CLIOS system, especially for the performance areas that it was designed for. The use of trade-off analysis is an alternative approach that allows comparison of strategic alternatives across difference performance mea- sures. A large number of alternatives can be compared in this manner, and there is no need to reduce performance measures to a single measure. Given system complexity, it would be unusual if a single strategic alternative could be deployed and meet CLIOS system goals. However, by combining strate- gic alternatives into bundles or packages, the analyst may accomplish two objec- tives. First, one can mitigate and/or compensate for negative impacts. Given the interconnectedness of the CLIOS system, improvements along one dimension of performance may degrade performance in other areas of the system.
- 55. Exploring the Variety of Random Documents with Different Content
- 56. supposed to know about that. The lover and his friend, who is called the staro sta, on a Saturday night go to the door of the lady's cottage and say: Good friends, we have lost our way. In the king's behalf we seek a star. At this the girl hastily leaves the room and the staro sta exclaims: Behold! There is the star for which we seek. May we go and seek her? We have flowers with us to deck her, flowers fair as those which Adam bound upon the brow of Eve in the Garden. I will call her back, says the bride's father, and the girl returns to smilingly accept the staro sta's flowers, and his offer of marriage for his friend. The flowers are distributed, speeches are made, and everybody drinks the health of the betrothed pair in slivovitza, binding their hands together with a handkerchief. The night before the wedding there is a cake dance, when the czardas is danced, the wedding cake is displayed, and everybody cries, laughs, and puts a bit of money into a plate to help toward the wedding expenses, for the wedding feast must last two days, and it costs a great deal of money. Irma's feast was very fine, for her father was village magistrate and could afford to make her marriage quite a social event. Even the High-Born Baron and Baroness from the great house came, and Marushka was delighted to see them, for she had heard the little peasant girls tell how kind the Baron was, and how beautiful his wife. The High-Born Baron danced the czardas with the bride and the High-Born Baroness trod the measures with the bridegroom, and Marushka could hardly keep her eyes off the Baroness. Her eyes were soft and brown, her teeth white as little pearls, her complexion a soft olive with rose-hued cheeks, her hair blue-black, soft and fine, waving about her face and piled high with roses at each side above her ears. Her dress was of brocaded silk, the bodice trimmed with
- 57. pearls, the large sleeves filmy with laces almost as fine as those she might have worn to court. Hungarian women love fine clothes and dress beautifully and the High-Born Baroness wished to pay honor to Sömögyi Vazul, for he had served the Baron's house and his father's before him. The Baron wore his handsomest uniform, top boots, embroidered coat and magnificent cloak, trimmed in gold braid and buttons, and it was a proud moment in Irma's life when he put his hand upon her elbow and led her out to dance the quaint dance of the Hungarians, with its slow movement gradually growing faster and faster until it ends in a regular whirl. Banda Bela played his best and the czardas of Irma's wedding was long talked of in the village as the most beautiful which had ever been danced. Then the High-Born Baron spoke to his wife and she smiled and nodded her head and asked Banda Bela if he could play the accompaniment to any of the folk-songs. Yes, Your Graciousness, he answered, to any one of them. Then I will sing for you, said the Baroness, and a rustle of expectancy went round the 'szvoba, for it was well known in the village that the High-Born Graciousness was a famous singer and had often been asked to sing to the King. She sang the little folk- song which every Hungarian knows. How late the summer stars arise! My love for thee was late in rising too. But what of that, or aught, to me? Why is thy glance so icy cold? My heart burns hot with love for thee! Her voice was tender and sad like that of all the Magyar women, and Marushka thought she had never heard anything so beautiful as the song to which Banda Bela's notes added a perfect accompaniment.
- 58. Then the wedding cakes were passed about, and the little girl had her full share. Banda Bela rejoiced in the present of a silver piece from the Baron. Who is this child? demanded the Baroness, attracted by Marushka's fair hair amidst the dark-haired little Magyars and Slövaks. A little one adopted by Aszszony Semeyer, replied the magistrate, as is also the Gypsy boy who played for you. She does not look like a Gypsy child, said the Baroness, knitting her brows a little. She reminds me of some one I have seen— as Marushka smiled up at her and made her a quaint little peasant's courtesy with more than peasant's grace.
- 59. 'WHO IS THIS CHILD?' DEMANDED THE BARONESS FOOTNOTES: [10] Room. [11] Salable daughters.
- 61. CHAPTER VII THE UNEXPECTED Aszszony Semeyer's brother-in-law had a large vineyard and, when it came time for the vintage, the good woman drove the children over to her brother's farm. The grapes grew in long lines up and down the hillside where the sun was strongest. White carts, drawn by white oxen, were driven by white-frocked peasants. All were decked with grape leaves, all had eaten golden grapes until they could eat no more, for the great bunches of rich, yellow grapes are free to all at vintage time. From these golden grapes is made the amber-hued Riesling, and the children enjoyed very much helping to tread the grapes, for the wine is made in the old-fashioned way, the grapes being cast into huge vats and trod upon with the feet till the juice is entirely pressed out. The peasants dance gaily up and down upon the grapes, tossing their arms above their heads and making great pleasure of their work. After the long, happy, sunny day the white cart of Aszszony Semeyer joined the line of carts which wound along from the vineyard, filled with gay toilers. At her brother's farm they stayed all night, for the vintage dance upon the grass under the golden glow of the harvest moon was too fair a sight to miss. They stayed, too, for the nut-gathering. Hungarian hazel nuts are celebrated the world over, and the nutting was as much a fête as had been the vintage. This was the last frolic of the year, and the children went back to Harom Szölöhoz to work hard all winter. Banda Bela still helped the swine-herd, but Marushka was no longer a goose girl. Aszszony Semeyer had grown very fond of the little girl and spent long hours teaching her to sew and embroider. Many salt
- 62. tears little Marushka shed over her Himmelbelt, or marriage bed- cover. Every girl in Hungary is supposed to have a fine linen bedspread embroidered ready to take to her home when she is married. It takes many months to make one of them, and Marushka's was to be a very elaborate one. The linen was coarse, but spun from their own flax by Aszszony Semeyer herself. In design Marushka's Himmelbelt was wonderful. The edge was to be heavily embroidered in colours, and in one corner was Marushka's name, a space being left for the day of the wedding. In the centre was a wedding hymn which was embroidered in gay letters, and began: Blessed by the Saints and God above I'll be If I do wed the man who loveth me; Then may my home be full of peace and rest, And I with goodly sons and daughters blest! Marushka worked over it for hours and grew to fairly hate the thought of marrying. I shall never, never marry, she sobbed. I shall never finish this horrid old Himmelbelt and I suppose I can't be married without it. Banda Bela sympathized with her and often played for her while she worked. Through the long winter the children learned to read and write, for all children are compelled to go to school in Hungary, and the Gypsies are the only ones who escape the school room. Marushka learned very fast. Her mind worked far more quickly than did Banda Bela's, though he was so much older. There was nothing which Marushka did not want to know all about; earth, air, sky, water, sun, wind, people,—all were interesting to her. The wind, Banda Bela, whence comes it? she would ask. It is the breath of God, the boy would answer. And the sun?
- 63. It is God's kindness. But the storms, with the flashing lightning and the terrible thunder? It is the wrath of Isten, the flash of his eye, the sound of his voice. But I like to know what makes the things, said Marushka. It is not enough to say that everything is God. I know He is back of everything. Aszszony Semeyer told me that, but I want to know the how of what He does. I think we cannot always do just what we like, said Banda Bela calmly. I have found that out many times, so it is best not to fret about things but to live each day by itself. At this philosophy Marushka pouted. One afternoon in the summer the children asked for permission to go to the woods, and Aszszony Semeyer answered them: Yes, my pigeons, go; the sky is fair and you have both been good children of late,—go, but return early. They had a happy afternoon playing together upon the hills which were so blue with forget-me-nots that one could hardly see where the hilltops met the sky. Marushka made a wreath of them and Banda Bela crowned her, twining long festoons of the flowers around her neck and waist, until she looked like a little flower fairy. They wandered homeward as the sun was setting, past the great house on the hill, and Maruskha said: I wonder if the High-Born Baron and his gracious lady will soon be coming home? In the village they say that they always come at this time of the year. Do you remember how beautiful the High-Born Baroness looked at Irma's wedding? She was beautiful and kind, and sang like a nightingale, said Banda Bela. Come, Marushka, we must hurry, or Aszszony Semeyer
- 64. will scold us for being late! As they neared the village they heard a noise and a strange scene met their gaze! A yoke of white oxen blocked the way; several black and brown cattle had slipped their halters and were running aimlessly about tossing their horns; seventeen hairy pigs ran hither and thither, squealing loudly, and all the geese in town seemed to be turned loose, flapping their wings and squawking at the top of their voices. Children were dashing around, shouting and screaming, in their efforts to catch the different animals, while the grown people, scarcely less disturbed, tried in vain to silence the din. They are frightened by the machine of the High-Born Baron, Marushka, said Banda Bela. See, there it is at the end of the street. I have seen these queer cars in Buda-Pest, but none has ever been in this little village before, so it is no wonder that everyone is afraid. There, the men have the cattle quiet, but the geese and the pigs are as bad as ever. Let us run and lead them out, Banda Bela, cried Marushka. You can make the pigs follow you and I can quiet the geese. It is too bad to have the homecoming of their High-Born Graciousnesses spoiled by these stupids! Marushka dashed into the throng of geese calling to them in soft little tones. They recognized her at once and stopped their fluttering as she called them by the names she had given them when she was goose girl and they all flocked about her. Then she sang a queer little crooning song, and they followed her down the street as she walked toward the goose green, not knowing how else to get them out of the way. Banda Bela meantime was having an amusing time with his friends the pigs. They were all squealing so loudly that they could scarcely hear his voice, so he bethought himself of his music and began to play. It was but a few moments before the piggies heard and stopped to listen. Banda Bela had played much when he was watching the pigs on the moor, and his violin told them of the fair green meadow where they found such good things to eat, and of the
- 65. river's brink with its great pools of black slime in which to wallow. They stopped their mad dashing about and gathered around the boy, and he, too, turned and led them from the village. It was a funny sight, this village procession. First came Marushka in her little peasant's costume, decked with her wreath and garlands of forget-me-nots, and followed by her snow-white geese. Next, Banda Bela, playing his violin and escorting his pigs, while last of all came the motor car of the High-Born Baron, the Baron looking amused, the Baroness in spasms of laughter. Oh, Léon, she cried. Could our friends who drive on the Os Budavara[12] see us now! Such a procession! That child who leads is the most beautiful little creature and so unconscious, and the boy's playing is wonderful.
- 66. FIRST CAME MARUSHKA They must be the Gypsy children Aszszony Semeyer adopted. We saw them when we were here last year, replied her husband. What a story this would make for the club! We must give these children a florin for their timely aid. But the children, unconscious of this pleasant prospect, led their respective friends back into the village by another way, so that it was not until the next day that the High-Born ones had a chance to see them, and this time in an even more exciting adventure than that of
- 67. the village procession. It was the motor car again which caused the trouble. Marushka and Banda Bela had been sent on an errand to a farm not far from the village and were walking homeward in the twilight. Down the road came a peasant's cart just as from the opposite direction came the honk-honk of the Baron's motor. Such a sight had never appeared to the horses before in all their lives. They reared up on their hind legs, pawing the air wildly as the driver tried to turn them aside to let the motor pass. A woman and a baby sat in the cart, and, as the horses became unmanageable and overturned the cart into the ditch, the woman was thrown out and the baby rolled from her arms right in front of the motor. The mechanician had tried to stop his car, but there was something wrong with the brake and he could not stop all at once. Marushka saw the baby. If there was one thing she loved more than another it was a baby. She saw its danger and in a second she dashed across the road, snatched up the little one and ran up the other side of the road just as the motor passed over the spot where the baby had fallen. Marushka, cried Banda Bela as he ran around the motor. Are you hurt? Brave child! cried the Baron, who sprang from his car and hurried to the group of frightened peasants. Are you injured? Not at all, Most Noble Baron, said Marushka, not forgetting to make her courtesy, though it was not easy with the baby in her arms. The child's mother had by this time picked herself out of the ditch and rushed over to where Maruskha stood, the baby still in her arms and cooing delightedly as he looked into the child's sweet face, his tiny hand clutching the silver medal which always hung about Marushka's neck. The mother snatched the baby to her breast and, seating herself by the roadside, she felt all over its little body to see if it was hurt.
- 68. You have this brave little girl to thank that your baby was not killed, said the Baron. The woman turned to Marushka. I thank you for— she began, stopped abruptly, and then stared at the little girl with an expression of amazement. Child, who are you? she demanded. Marushka, said the little girl simply. The woman put her hand to her head. It is her image, she muttered. Her very self! The Baroness had alighted from the motor and came up in time to hear the woman's words. Whose image? she demanded sharply. The woman changed colour and put her baby down on the grass. The little girl looks like a child I saw in America, she stammered, her face flushing. Was she an American child? demanded the Baroness. Oh, yes, Your Graciousness, said the woman hastily. Of course, she was an American child. Now I know that you are speaking falsely, said the Baroness. This little one looks like no American child who was ever born. Léon, turning to her husband, is this one of your peasants? Then she added in a tone too low to be heard by anyone but her husband, I know that she can tell something about this little girl. Question her. The Baron turned to the woman and said: This little girl saved your baby's life. Should you not do her some kindness?
- 69. What could I do for her, Your High-Born Graciousness? the woman asked. That I leave to your good heart. The Baron had not dwelt upon his estates and managed his peasants for years without knowing peasant character. Threats would not move this woman, that he saw in a moment. She is a Gypsy child, the woman said sullenly. Banda Bela spoke suddenly, for he had come close and heard what was said. That she is not! She is Magyar. Deserted by the roadside, she was cared for by Gypsy folk. Does she look like a Gypsy? Would a Gypsy child wear a Christian medal upon her breast? The boy's tone was sharp. Marushka heard nothing. She was playing with the baby. The woman looked from Marushka to the baby, then at the Baron, hesitating. Let me see your pretty medal, child, she said at length, and Marushka untied the string and put the medal in the woman's hand. I used to think it was my mother, but now I know it is Our Lady, said Marushka gently. The woman looked at it for a moment, then gave it back to the little girl and stood for a moment thinking. High-Born Baron, she said at last, I will speak. Those it might harm are dead. The little girl who saved my baby I will gladly serve, but I will speak alone to the ears of the Baron and his gracious lady. Very well, said the Baron as he led the woman aside. Škultéty Yda is my name, Your Graciousness, she said. I was foster-sister to a high-born lady in the Province in which lies Buda- Pest. I loved my mistress and after her marriage I went with her to the home of her husband, a country place on the Danube. There I met Hödza Ludevit, who wished to marry me and take me to America, for which he had long saved the money. He hated all
- 70. nobles and most of all the High-Born Count, because the Count had once struck him with his riding whip. Then the Countess' little daughter came and I loved her so dearly that I said that I would never part from her. Ludevit waited for me two years, then he grew angry and said, 'To America I will go with or without you.' Then he stole the little baby and sent me word that he would return her only on condition that I go at once to America with him. To save the little golden-haired baby I followed him beyond the sea to America. He swore to me that he had returned little Marushka to her parents. The Count traced us to America thinking we might have taken the child with us, and then I learned that the baby had never been sent home. My wicked husband had left it by the roadside and what had become of it no one knew. It turned my heart toward my husband into stone. Now he is dead and I have brought my own baby home, but my family are all dead and I have no place to go. These people were kind to me on the ship, so I came to them, hoping to find work to care for my baby, since all my money was spent in the coming home. This little girl who saved my baby I know to be the daughter of my dear mistress. She stopped. How do you know it? demanded the Baroness. Your High-Born Graciousness, she is her image. There is the same corn-coloured hair, the same blue eyes, the same flushed cheek, the same proud mouth, the same sweet voice. What was the name of your lady? interrupted the baroness, who had been looking fixedly at Marushka, knitting her brows. The child has always reminded me of someone; who it is I cannot think. The foster sister whom I loved was the Countess Maria Andrássy. I see it, cried the Baroness. The child is her image, Léon. I have her picture at the castle. You will see at once the resemblance. I have not seen Maria since we left school. Her husband we see often at Court. I had heard that Maria had lost her child and that
- 71. since she had never left her country home. I supposed the child was dead. This little Marushka must be Maria Andrássy. We must have proofs, said the Baron. Behold the medal upon the child's neck, said Yda. It is one her mother placed there. I myself scratched with a needle the child's initials 'M. A.' the same as her mother's. The letters are still there; and if that is not enough there is on the child's neck the same red mark as when she was born. It is up under her hair and her mother would know it at once. The only way is for her mother to see her and she will know. This Gypsy boy may be able to supply some missing links. We shall ask him, said the Baron. When Banda Bela was called he told simply all that he knew about Marushka and all that old Jarnik had told him. There is no harm coming to her, is there? he asked anxiously, and the Baroness said kindly: No, my boy, no harm at all, and perhaps much good, for we think that we have found her people. Banda Bela's face clouded. That would make you sad? she asked. Yes and no, Your Graciousness, he answered. It would take my heart away to lose Marushka for whom I have cared these years as my sister, but I know so well the sadness of having no mother. If she can find her mother, I shall rejoice. Something good shall be found for you, too, my lad. The Baroness smiled at him, but he replied simply: I thank Your High-Born Graciousness. I shall still have my music. The Baroness flashed a quick glance at him. I understand you, boy; nothing can take that away from one who loves it. Now take the little one home, and to-morrow we shall come to see Aszszony
- 72. Semeyer about her. In the meantime, say not one word to the little girl for fear she be disappointed if we have made a mistake. Yes, Your High-Born Graciousness, and Banda Bela led Marushka away, playing as they went down the hill the little song of his father. The hills are so blue, The sun so warm, The wind of the moor so soft and so kind! Oh, the eyes of my mother, The warmth of her breast, The breath of her kiss on my cheek, alas! FOOTNOTE: [12] Celebrated drive in Buda-Pest.
- 73. CHAPTER VIII MARUSHKA MAKES A JOURNEY Marushka was so excited that she scarce knew how to contain herself. The Baroness had come to see Aszszony Semeyer and had talked long with her. Then she had called Marushka and the little girl saw that Aszszony Semeyer had been crying. Marushka, the Baroness said. Will you come with me and make a journey? I want to take you in the motor to Buda-Pest. The High-Born Baroness is very good, said Marushka, her eyes shining. I should like to go very much, but not if Aszszony Semeyer does not wish it. Good child, said Aszszony Semeyer, I do wish it. Then why do you cry? There are many things to make old people cry, said the peasant woman. I am certainly not crying because the High-Born Graciousness wishes to honour you with so pleasant a journey—(that is the truth, for it is the fear that she will not come back that forces the tears from my eyes, she added to herself). Aszszony Semeyer will have Banda Bela, said the Baroness. Marushka opened her eyes very wide. Oh, no, Your Graciousness, because Banda Bela must go wherever I go. If he stays at home, then I must stay, too. Such a child! exclaimed Aszszony Semeyer. She has always been like this about Banda Bela. The two will not be separated.
- 74. In that case we shall have to take Banda Bela also, said the Baroness, and Marushka clapped her hands with glee. That will be nice, she exclaimed. I shall love to see the city and all the beautiful palaces, and I shall bring you a present, Aszszony Semeyer, but I will not go unless you wish me to. I do wish it, dear child, but do not forget your old aunt, for so she had taught the children to call her. So it was decided that they should start the next week when the Baron's business would have been attended to. Part of Marushka's journey was to be taken in the motor, and, as she had never ridden in one before, she was very much excited as they set out on a bright day in August. She wanted to sit beside Banda Bela with the driver, but the Baroness said, No, it would not be proper for a little girl. So she had to be satisfied with sitting between the Baron and Baroness on the back seat. Up hill and down dale they rode. The road at times was so poor that the wheels wedged in the ruts and all had to get out while the driver pushed from behind. They ate their luncheon at a ruined castle which had once been a beautiful country place. It belonged to a friend of the Baron but had been deserted for many years. Beyond it lay a corn-coloured plain and blue hills, and on top of one of the hills gleamed the white walls of a monastery. Near here are some famous marble quarries, said the Baroness. They are finer even than the ones at Carrara in Italy, which are celebrated all over the world. There is so much marble around here that it is cheaper than wood. See there! even the walls of that pig- pen are of marble. Yonder is a peasant's hut with a marble railing around the garden. Even the roads are mended with it, and the quarries in the hillsides have hardly been touched yet. Some day
- 75. someone will be made very rich if they will open up this industry, and it will keep many of our people from going to America. Why do they go to America? asked Marushka. And where is America? It cannot be so nice as Magyarland. Well, little one, it is as nice to Americans, but when our Hungarian people go there they always come back. Sometimes the Slövaks remain, but never the Magyars. They go there and work and save. Then they send for their families, and they too work and save, and at last they all come home. There is a story told of the last war in Hungary. Two Magyar peasants had gone to America and worked in the far west. One day in a lonely cabin on the plains they found an old newspaper and read that there was war in Hungary. They put together all their money, saved and scrimped, ate little and worked hard, until they got enough to go home. They reached Hungary before the fighting was over and begged to be sent at once to the front, to have a chance to serve their country before the war was over. But how do people know about America? asked Marushka. There are agents of the steamship companies who go from village to village trying to get the people to emigrate, said the Baroness. They tell them that in America one finds gold rolling about in the streets and that there everyone is free and equal. Our people believe it and go there. Many of those who go are bad and discontented or lazy here at home. When they get to America and find that gold does not roll in the streets and that they must work for it if they want it, they are more discontented than ever, and the people of America think that Hungarians are lazy and good for nothing. When they come home they talk in the villages of the grand things they did in America and make the people here discontented and unhappy. Why don't the people ask them, if America was so nice, why did they not stay there? asked Marushka, and the Baroness smiled.
- 76. Those of us who have estates to take care of wish they would, she said. The returned emigrant is one of the problems of Hungary. Why are there so many beggars? asked Marushka. I never saw one in Harom Szölöhoz. That is a prosperous village with a kind over-lord, said the Baroness. But there are so many beggars in Hungary that they have formed themselves into a kind of union. In some towns there is a beggar chief who is as much a king in his way as is His Majesty the Emperor. The chief has the right to say just where each beggar may beg and on what days they may beg in certain places. The beggars never go to each other's begging places, and if anyone does, the other beggars tell the police about him and he is driven out of town. In some provinces the very old and sick people are sent to live with the richest householders. Of course no one would ever refuse to have them, for alms asked in the name of Christ can never be refused, and as our gracious Emperor has said, 'Sorrow and suffering have their privileges as well as rank.' He must be a very good Emperor, said Marushka. It seems to me that you are a very wonderful lady and that you know everything. It is interesting to know all about these things. When I grow up I am going to know all about Magyarland. The journey in the train was even more exciting for the children than that in the motor, and they enjoyed very much hearing about the various places through which they passed. When they reached Buda-Pest, Marushka was dumbfounded, for she had never imagined anything so beautiful. The train rolled into the huge station, with its immense steel shed and glass roof, upon which the sun beat like moulten fire. The children followed the Baroness through the gate and into the carriage, which rattled away so quickly that it swayed from side to side, for in Hungary people are proud of their fine horses and always drive as fast as they can.
- 77. 'ACROSS THE RIVER YOU SEE BUDA,' SAID THE BARONESS Marushka caught glimpses of broad, well-paved streets and large, handsome buildings, as the Baroness pointed out the opera house, theatres, churches, museums, and the superb houses of parliament built upon the banks of the Danube. Across the river you see Buda, said the Baroness. In old times Buda was very old-fashioned, but in the last twenty years the royal palace has been built and many other costly buildings, and soon it will be as handsome as Pest. The improvements within the last ten years are wonderful. The streets are clean and neat, no ugly signs are permitted upon the houses, no refuse on the streets, and the citizens vie with each other in trying to make that side of the river as beautiful as this. The Emperor takes great interest in the enterprise.
- 78. You speak about the Emperor sometimes, said Marushka. And other times about the King. Who is the King? The same as the Emperor, replied the Baroness. You see, Austria and Hungary have been united under one government, and the King of Hungary is Emperor of Austria. There were many wars fought before this arrangement was made, and all the different peoples of the empire agreed to live peaceably together. How long has Hungary had a king? asked Marushka. Oh, for years and years, said the Baroness. It was about the twelfth century when the Aranybulla[13] was made, which gave to the nobles the right to rebel if the king did not live up to the constitution. See! There are the barracks and the soldiers drilling. The country boys who come up to be trained are sometimes so stupid that they don't know their right foot from the left. So the sergeant ties a wisp of hay on the right foot and a wisp of straw on the left. Instead of saying, right-left, to teach them to march, he says szelma-szalma. Isn't it droll? What is that building by the river? asked Marushka. The one with the little turrets and the tower before which the geese are swinging? That, my little goose girl, is the Agricultural Building, and should you go inside you would find specimens of every kind of food raised in Hungary. But here we are at the hotel where we shall spend the night. You must have some supper and then hurry to bed, for to- morrow is the fête day of St. Stephen, and all must be up early to see the procession. Marushka was so sleepy the next day that she could only yawn and rub her eyes when the maid called her at five o'clock to dress for the fête. The twentieth of August, the feast of St. Stephen, is the greatest fête of the year in Hungary.
- 79. Marushka and Banda Bela were very much excited over it, for they had often heard of the fête but had never supposed they would have the good fortune to see it. Come, children, the Baroness said as they hastily ate their breakfast. We must hurry away. Hear the bells and the cannon! Every church in the city is ringing its chimes. We must be in the Palace Square by seven or we will miss some of the sights. I think the High-Born Baron and his Gracious Lady are the finest sights we shall see, whispered Banda Bela to Marushka, and the Baroness caught the words and smiled at him. There was a subtle sympathy between these two, the high and the lowly, the Magyar noblewoman and the Gypsy boy, a sympathy born, perhaps, of the love of music which swayed them both. Marushka felt wonderfully fine as their carriage rolled into the Palace Square, where the procession in honour of St. Stephen was forming. It was a gorgeous sight, for all were dressed in their gayest attire, and officers, soldiers, prelates, and guard of honour from the palace made a continual line of conflicting hues. While the procession was passing Marushka almost held her breath, then, as the golden radiance of colour flashing in the sunlight streamed past, she clapped her hands in glee, and cried: Oh, your Gracious High-Bornness! Isn't it splendid! How glad I am that St. Stephen is the Magyar saint and that I am a Magyar! The child's eyes were shining, her cheeks flushed, her hair a golden coronet in the sunshine, and she looked like a beautiful little princess. At the sound of her voice an officer in uniform, who was passing, turned and looked into the child's face, then glanced from her to the Baroness, who waved her hand in greeting. He doffed his cap and then came to the carriage.
- 80. Good morning, Count. It is long since I have seen you in Buda- Pest. Are you not marching to-day? the Baroness said. No, Madame. The officer had a kind face, but it seemed very sad to Marushka. She thought she had seen him before, but did not remember where until Banda Bela whispered that it was the officer who had given them money for Marushka's top boots at the fair. I was on duty at the palace this morning, but am returning home at once. My wife is not very well, he said. It is long since I have seen her. Will she receive me if I drive out to your home? the Baroness asked. She will be glad to see you, he said, though she sees but few since her ill health. I shall drive out to-day with these little folk, to whom I am showing the sights, said the Baroness. The count's eyes fell upon Banda Bela, and he gave a quick smile. Why, this is the little genius who played the violin so wonderfully well down at the village fair, he said; and Banda Bela smiled, well pleased at being remembered. The little girl is yours? he asked. The Baroness hesitated. No, she said. She is not mine. She is the child of a friend of mine. Marushka wondered what good Aszszony Semeyer would say to hear herself spoken of as a friend of the Baroness, and, amused, she looked up at the Count with a beaming smile. He started a little and then stared at her fixedly, just as the Baroness with a hasty adieu bade the coachman drive on. Madame, he asked quickly, as the horses started. Who is the friend whose child this is? The Baroness looked back at him over her shoulder.
- 81. That I cannot tell you now, she said. This afternoon at your castle I will ask you to tell me! FOOTNOTE: [13] Hungarian Magna Charta.
- 82. CHAPTER IX OH, THE EYES OF MY MOTHER! Oh, High-Born Graciousness, what is that beautiful street we are driving into? asked Marushka, as they drove out in the afternoon, and the coachman turned the horses into a magnificent avenue. This is Andrássy-ut, the famous boulevard, which leads to the park, replied the Baroness. We are driving toward Os Budavará, the Park of Buda-Pest, and it is one of the most beautiful sights in the world. As she spoke they entered the park, and the children gazed in wonder at its beauty. Swans floated on the miniature lakes; in the feathery green woods bloomed exquisite Persian lilacs, children played on the green grass beneath the willows or ran to and fro over the rustic bridges. On the Corso the fashionables drove up and down in the smartest of costumes, their turnouts as well appointed as any in Paris or London. The men were many of them in uniform, the women, some of them with slanting dark eyes almost like Japanese, were graceful and elegant. The skating fêtes held in the park in winter are the most beautiful things you can imagine, said the Baroness. The whole country is white with snow. Frost is in the air, the blood tingles with the cold. Ice kiosks are erected everywhere, and coloured lights are hung up until the whole place seems like fairyland, and the skaters, dressed from top to toe in furs, look like fairy people skimming over the ice. It must be beautiful, said Marushka.
- 83. But what is that man playing? The taragato, the old-fashioned Magyar clarinet, was the answer, and the old instrument seemed to tell tales of warlike days, its deep tones rolling out like the wind of the forest. A boy near by played an impudent little tilinka (flageolet), and Banda Bela said: That never sounded like real music to me; only the violin sings. It is like the wind in the trees, the rustle of the grass on the moor, the dash of the waves on the shore, the voice of the mother to her child. Banda Bela, you are poet as well as musician, said the Baroness. You shall never go back to Harom Szölöhoz to live. You shall stay with me. I will sing to your music, and you shall study music till you are the greatest violin player in all Hungary. When a Gypsy child comes into the world they say his mother lays him on the ground and at one side places a purse and at the other a violin, said Banda Bela. To one side or other the baby will turn his head. If he turns to the purse he will be a thief, if he turns to the violin he will earn his living by music. My mother said she would give me no chance to choose ill, but an old woman near by laid forth both the purse and the violin and I turned my head to the violin and reached for it with my baby hand. When they placed the bow in my hand I grasped it so tight they could scarce take it from me. Banda Bela, said Marushka, and her tone was pettish. You like your violin better than you do me! The boy laughed. My violin has earned you many a supper, Little One; do not dislike it! Oh, Your Graciousness, what are those strange things? cried Marushka. They are not automobiles, are they? No, my child, they are the new steam thrashing machines which the government has just bought, and is teaching the peasants to use
- 84. instead of the old-fashioned ways of thrashing. Now we are getting into the country. See how beautifully the road winds along the Danube! Is it not a wonderful river? There is a famous waltz called the 'Beautiful Blue Danube' and the river is certainly as blue as the sky. See that queer little cemetery among the hills. I have often wondered why some of the gravestones in the village cemeteries had three feathers and coloured ribbons on them. If you please, Your Graciousness, said Banda Bela, I can tell you. That is for the grave of a girl who has died after she was of an age to be married, yet for whom no one had offered the buying money. Aszszony Semeyer told me that. Aszszony Semeyer told me that every peasant kept a wooden shovel hung upon the wall of his house with which to throw in the last shovelful of earth upon his loved ones, said Marushka with a shudder. Ugh! I didn't like that. Very few people like to think about death, said the Baroness. See that thicket of prickly pears beside the road? Once when I was a little girl and very, very naughty, I ran away from my nurse and to hide from her I jumped over the wall and landed in just such a thicket as that. I think the pears must be naughty, too, for they liked that little girl and would not let her go. The thorns pricked her legs and tore her frock and scratched her hands when she tried to get her skirts loose, until she cried with pain and called 'Kerem jojoro ide'[14] to her nurse. I did not think the Gracious Baroness was ever naughty, said Marushka. The Gracious Baroness was quite like other little girls, my dear, she said, smiling. Ah, I have a little twinge of toothache! she exclaimed. That is too bad. Marushka was all sympathy. Aszszony Semeyer says that if you will always cut your finger nails on Friday you will never have toothache.
- 85. Is that so? Then I shall certainly try it, said the Baroness soberly. Do you see the gleam of white houses between the trees? Those are the beautiful villas and castles of the Svabhegy, the hill overlooking the Danube, and here live many of my very good friends. I am going to visit one of them for a little while and you must be good, quiet children and sit in the carriage while I go in to make my call. Then, perhaps, I will take you in for a few moments to see the house, for it is a very beautiful one. See! here we are at the gate, as the carriage turned into a beautifully ornamented gateway, above which was carved the legend: If you love God and your Country, enter; with malice in your heart, go your way. The driveway wound through beautiful grounds, and through the trees were seen glimpses of the Danube. The house itself was white and stood at the crest of the hill overlooking the river. This place belongs to the Count Ándrassy, said the Baroness. He has also another place in the Aföld and is very wealthy. When my grandfather went to visit his grandfather in the old days, they once took the wheels from his carriage and tied them to the tops of the tallest poplar trees on the estate to prevent his leaving. Another time they greased the shafts with wolf fat, so that the horses would not allow themselves to be harnessed up, for they are so afraid of the wolf smell. Still another time they hid his trunks in the attic so that it was three months before my grandfather finally got away. That was old-fashioned hospitality. Here we are at the door. Sit quietly here and I will return, and the Baroness sprang down. There was a swish of her silken skirts and the front door closed behind her. The children chattered gaily to each other of all they had seen and heard since they had left Harom Szölöhoz, and Marushka said: It seems so long since we have left the village, Banda Bela; somehow it seems as if we would never go back.
- 86. I think you never will. Banda Bela spoke a little sadly. Were you happy there, Little One? Oh, yes, she said brightly. I was happy with you and Aszszony Semeyer. Only, when I saw other children with their mothers, there was the ache right here— she laid her hand on her heart. I know, said Banda Bela. I have that always. Only when I play my violin do I forget. But I cannot play the violin, nor can I do anything, only embroider that horrible Himmelbelt, and Marushka pouted, while Banda Bela laughed at her. Think how proud you will be some day to show that Himmelbelt to your husband, he said, but just then the Baroness and the Count came out of the house together. What do you think? the Baroness asked the Count. I think you are right, but Maria shall decide, he answered. We will say nothing to her and her heart will speak. Come in, children, said the Baroness, who looked strangely excited. Her eyes shone and her cheeks were flushed, while the Count's face was pale as death and he looked strangely at Marushka. Banda Bela, said the Baroness, the Countess is not very well. She loves music as you and I do, and I want you to come in and play for her. She is very sad. Once she lost her dear little daughter, and you may play some gentle little songs for her. It may give her pleasure. It is a beautiful thing, Banda Bela, to give pleasure to those who are sad. The Baroness chattered on as they entered the house. Marushka looked up at the Count's face. Sad as it was she felt drawn toward him. She saw him watching her closely and smiled up at him with the pretty, frank smile which always lighted up her face so charmingly.
- 87. High-Born Count, she said shyly, I have to thank you for the first present I ever received in all my life. What was that, Little One? he asked. The top boots which Banda Bela bought for me at the fair at Harom Szölöhoz. They were bought with the florin you gave to Banda Bela for his playing. They were so nice! She dimpled prettily. I am glad they gave you pleasure. Come, we will go in and hear Banda Bela play, said the Count, holding out his hand. Marushka slipped her hand into his and he led her into the house, entering by the large hall, on the walls of which hung deer horns and wolf heads, while a huge stuffed wolf stood at one end, holding a lamp in his paws. The Count was a great sportsman and had shot many of these animals himself in the forests of the Transylvania. Banda Bela tuned his violin and then began to play. It seemed to Marushka as if she had never before heard him play so beautifully. Many things he played, all soft and dreamy, with a gentle, haunting sadness through them, until at last he struck into a peculiar melody, a sort of double harmony of joy and sorrow, which he had never played before. What is that, Banda Bela? demanded the Baroness. Who wrote it, what are the words? If you please, Your Graciousness—the boy flushed, it is but a Gypsy song of sorrow. The words are but in my own heart. Strange boy, she thought, but at that moment the door opened and a lady hastily entered the room. She was tall and very beautiful, with great masses of corn-coloured hair and deep blue eyes, but her face had a look of terrible sadness. Arpád! she exclaimed. What is this music? It makes me weep for my lost one and I am nearly blind with weeping now. Her eyes, seeking her husband's, fell upon Marushka, who during the music had been leaning against the Count, his arm around her. The
- 88. Countess' eyes travelled up and down the little figure, then sought her husband's face with a sort of eager, frightened questioning. Arpád! she cried. Arpád! Who is this child? Maria, my dearest! I have brought her here that you may tell me who she is, he said, trying to speak calmly. She drew the little girl toward her and Marushka went willingly and stood looking into the sweet face of the Countess. Such a likeness, whispered the Baroness. They are as like as two sisters. Then, all in a moment, the Countess gathered Marushka into her arms and covered the child's face with kisses. You are mine, she cried, tears streaming down her face. Mine! Arpád! I know it is our little daughter come back to us after all these years. My heart tells me it is she! Marushka looked frightened for a moment, then she clung around her mother's neck, and the Baroness quietly drew Banda Bela from the room. From the hall the sound of the Gypsy boy's violin came as he played, with all his soul in his touch, the song of his father:
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