Upload
others
View
5
Download
0
Embed Size (px)
Citation preview
1
Handbook of Knowledge Management for Sustainable Water Systems (KM4SWS)
Introduction and a Theoretical Framework for KM4SWS
Meir Russ-Final Draft-May 30, 2017
According to the World Health Organization (WHO), in 2009, about one fifth of the
world's population lived in countries that did not have enough water for their use. By 2025, 1.8
billion people will experience absolute water scarcity, and by 2030, almost half the world will
live under conditions of high water stress. Yet, only recently has the science of coupled human-
water system been initiated (Partelow, 2016; Sivapalan & Blösch, 2015) and transdisciplinarity
research utilized for societal sustainability problem solving (Polk, 2014). But, the understanding
of needs for data and knowledge transfer bridging organizational boundaries, and technological
aspects that challenge the praxis of policy making and planning are paradoxically increasing or
even worse, lacking (Cash et al., 2003; Hinkel, Bots, & Schlüter, 2014; Polk, 2014; Thomson,
El-Haram, Walton, Hardcastle, & Sutherland, 2007). For example, in a recent Water JPI (2014)
paper presenting eight major water topics for Europe (Horizon 2020), while identifying the gaps
and game changers, knowledge management was listed directly and indirectly in ALL of them.
These real life issues and academic research gaps are the motivators for this handbook.
Managing knowledge more effectively and efficiently might be a solution to many of the critical
water issues humans in the 21st century are, and will be, facing. Knowledge commons (e.g.
Brewer, 2014) and virtual, digital spaces of learning (Niccolini, in this book) provide some
unexpected and surprising rays of hope, of what might happen when knowledge is created and
managed well. The Israeli experience (Jacobsen, 2016; Siegel, 2015) is an illustration of a water
miracle (not phantoms) that can happen in the desert, and by extension, everywhere, where and
when people will set their minds to it.
As the new knowledge-driven economy continues to evolve, knowledge is being
recognized as a key asset and a crucial component of organizational, inter-organizational and
national strategy. The ability to manage knowledge, therefore, is quickly becoming vital for
securing and maintaining survival and success. As a result, organizations at all levels are
investing heavily in Information Systems (IS) and/or Knowledge-Based Systems (KBS)
technologies. Unfortunately, such investments frequently do not meet expected outcomes and/or
returns. For the purpose of this handbook we will recognize Knowledge Management (KM) as a
socio-technical phenomenon in which the basic social constituents such as person, team and
organization require interaction with IS/KBS applications to support a strategy and add value to
the organization (Russ, 2010) while improving the sustainability of a water system. Many
organizations and their executives recognize that the critical source of sustainable competitive
advantage is not only having the most ingenious product design, the most brilliant marketing
strategy, or the most state-of-the-art production technology, but also having the ability to attract,
retain, develop and manage its most valuable human assets (talent) and their knowledge and
2
innovation. Furthermore, such an interaction of talent, processes and systems is what enables
organizations to develop and manage knowledge for success.
Sustainability has been defined as economic development that meets the needs of the
present generation without conceding the ability of future generations to meet their own needs
(e.g., Russ, 2014b.) With growing pressure from customers and regulators toward environmental
and social issues, organizations and governments at all levels are increasingly expected to
shoulder greater responsibility for making sustainable development a reality. Recent droughts
and water shortages worldwide and the advanced scientific understanding and documentation of
the impact of demographic and economic forces on water footprint and embedded water make
the need for sustainable development and management of water systems only more acute. This
requires policy makers, planners and executives to balance economic, business, social and
environmental concerns and outcomes. For that to happen, leaders need to quantify the
relationships of all those aspects across different time horizons and link their organizational
knowledge-base to strategy and outcomes so they can consider the tradeoffs of different
alternatives for their long-term success.
This book is envisioned as a manuscript that will provide a robust scientific foundation
for an inter-disciplinary, multi-perspective theory and practice of knowledge management in the
context of, and for the advancement of, sustainable water systems. The book goes beyond the
current literature by providing a platform for a broad scope of discussion regarding KM4SWS,
and, more importantly, by encouraging an interdisciplinary/transdisciplinary fusion between
diverse disciplines. Specifically, the call for proposals for this book solicited chapter proposals
from a multidisciplinary array of scholars to discuss socio-hydrology sustainable systems within
the present political (legislative), economic and technological context from a number of
disciplines/perspectives, including: Economic Development, Financial, Systems-Networks,
IT/IS Data/Analytics, Behavioral, Social, Water Systems, Governance Systems and Related
Ecosystems. Multi-level and multi-discipline chapters that synthesize diverse bodies of
knowledge were strongly encouraged. When appropriate, plurality of empirical methods from
diverse disciplines that can enhance the building of a holistic theory of KM4SWS were also
encouraged.
While preparing for, and editing this book, a number of alternative theoretical
frameworks were considered (e.g, Elliot, 2011). The multi-level framework that was adopted
(described briefly below) is an amalgamation of a number of models reviewed (some are listed in
the bibliography below) with the addition of models I developed regarding knowledge
management over the last twenty years of teaching and studying the subject.
The first building block (see Figure 1.) is the model of co-evolution of the Human
Systems (political, economic, technological, social; see discussions and indicators in, for
3
example: Partelow, 2016, Vogt, Epstein, Mincey, Fischer, & McCord, 2015; mostly based on
Ostrom, 2009) and the Sustainable (in our case) Natural and Engineered Water Systems (see for
example Sivapalan & Blöschl, 2015). Such co-evolution results, of course, from the impact
human activities have (mediated by technology) on the systems and the responses and outcomes
of the water systems to these activities. The co-evolutionary model (e.g. Sivapalan Blöschl,
2015) was modified and enhanced by adding on the human system side: the complexity of the
different potential units of analysis involved on the human systems side, starting with an
individual, teams, organizations and then going up in complexity to inter-organization, national,
regional and global units and scales. Each unit has its own learning complexity and more
complex units, issues, and boundary management aspects (see excellent discussions of the
importance of this complex management in Cash et al., 2003). On the sustainable water system
side, the different levels of the systems were added (e.g. household, city, river basins, etc.). Each
one of them is connected to the framework by models that are used and/or understood by the
human actors (see the interesting discussion in Sivapalan & Blöschl, 2015, about two models:
stylized and comprehensive). Finally, Knowledge Management (KM) was added at the heart of
the Human Systems’ section and the Co-evolution’s section (the two KMs are of course related
and intertwined).
________________
Figure 1. about here
________________
The second level of the model is the construct of Knowledge Management (see Figure
2.). Here, the model developed by Russ, Fineman, and Jones, (2010) was used, with focus on the
actors, (or talent), the process, or specifically the learning and decision making, and the systems,
or in this case the knowledge based systems. The majority of the chapters in this book touch on
all three factors and illustrate different aspects (e.g. content and process) of KM.
________________
Figure 2. about here
________________
In the third level of the model, each one of the three constructs used as building blocks
for KM (listed above) was broken down into its specific models (see Figure 3.a.-3.e.). For
example, learning, might focus on tacit knowledge using the Kolb active learning model (1976),
or on codified learning using the virtual Ba model illustrated by Niccolini et al. in this book, or
any mix of the two; or others as appropriate for the case; all, (potentially) using up to the three
feedback loops of learning (e.g., Argyris’ double-loop learning, 2002; or the review in Tosey,
4
Visser, & Saunders, 2012 of triple loop learning). The human actors’, talent was modeled using
the HC praxis model (Russ, 2014a) and the Knowledge-Based-Systems (KBS) using the six life
cycle stages of KBS (e.g., Russ, Jones, & Jones, 2008), including the sustainability aspect of the
KBS as well as consideration (Elliot, 2011).
________________
Figure 3. about here
________________
The complexity of the reality of KM in SWS are overwhelming, as they are illustrated in
the chapters in this book. Such complexity is a result of the nature of knowledge management
which could cut across ALL levels of the model, as well as across the unit of analysis in the
water systems. Add to that the complexity of the diverse scientific areas and the diverse styles of
learning and decision making of the different actors, and you can see a complex networked
system at its best.
But the truth of the matter is that one aspect is still missing from this analysis and must be
added to the proposed framework, thus adding the fourth level, time (see Figure 4.). Again and
again, while teaching my KM classes, consulting with clients, researching and reading other
practitioner and academic research, I was perplex by the failures of all the constituencies to
understand the importance of time, on its complexities for strategic decision making, managing
knowledge or human capital, among many others aspects. Time is one of the hidden assumptions
(dimensions) we have and use continually without giving it a second thought.
________________
Figure 4. about here
________________
In practice, the misalignment of time horizons (present and future) and time frames of
events, makes an enormous difference, but is rarely explicitly identified as an issue and/or
studied (see a rare very recent exception in Myllykoski, 2017). In our context of KM4SWS, the
key players that take actions or make decisions, not only might have a diverse set of expertise,
understating and knowledge of the subject at hand, but they also operate in a different time
“space”. Politicians’ time horizons of the relevant future for their decision making is different
from that of the farmer, the hydrologist and the weather scientist. Their understanding of an
event (and it time frame) and the implication the event might have within a complex system,
including the impact of time-lags and complex feedback loops, could be startlingly different and
diverse (from others) within the realm of their intentions, goals and their time horizon. This
5
factor (of time) can explain by itself why knowledge is not used effectively regarding important
aspects of the sustainability of water systems. Corralling all the different actors into a single
space of knowledge and coherent time for the purpose of advancing sustainable water systems
can happen rarely if at all. One case in which all of this might potentially happen is in a major
disaster. Recent history should tell us that even in the vast majority of the cases of disaster this is
not sufficient to create such a coherent space. To illustrate the praxis of such situations, an
updated model of the “garbage can model of decision making” (Cohen, March, & Olsen, 1972) is
proposed here, where time is a multi-dimensional construct having a synchronized (or not) time
horizon, time frame, and event-time, or what I would define as the “quantum model of
organizational time”. This model advances the model of time described by Myllykoski (2017)
(building on Hernes, 2014) in which she described the past and the future as a stream of events,
that get their “true” meaning at the present time, resulting from a stream of events, creating or
enabling a decision to be made, seeing time as agentic (p. 23). Events, or the bits of information
perceived by the observer that are remarked by the actor as events, are seen as collapsing at the
time of the decision. As such, it enables us to freeze an understanding of the past, from the
present perspective and the planning for the future, confirming a present rational for the decision
regarding the future (Tsoukas, 2016). Viewing time as agentic, and seeing the stream of bits of
information coming from the past and going toward the future, collapsing at a time of a decision
into one interpretation, brings Schrödinger’s cat from the quantum realm into individual decision
making, and results in what I would call, the “individual quantum model of decision making”.
Adding the complexity of multiple key actors with different time frames, etc. results in an
“organizational quantum model of decision making” which is illustrated in Figure 4. Finally, one
plausible explanation for the success of role playing (Sivapalan & Blöschl, 2015) and simulation-
based learning (Deegan et al., 2014) in a complex context as described here, is because it allows
for the time horizons of the participating individuals and the time frame of the event they engage
with to become coherent, enabling an improved process of decision making.
The chapters in this book not only illustrate the framework proposed above, and suggest
new venues for improving our water systems; more than that, they illuminate opportunities to
eliminate the risks of a thirsty world.
Acknowledgment
The call for chapters for this book stimulated the authors to synthesize multi-level and multi-
discipline diverse bodies of knowledge by encouraging an interdisciplinary fusion between
diverse disciplines. The authors were invited to contribute chapters to the book based on
proposals approved by the editor. Each complete chapter received external, blind review in
addition to the editor review. The editor thanks Kelly Anklam for her assistance in editing this
introduction and number of chapters. He wishes to thank also Dr. Vallari Chandna for editing
number of chapters, as well as the reviewers for their in depths reviews. Finally the editor want
to thank the Philip J. and Elizabeth Hendrickson Professorship in Business at UW-Green Bay for
partial financial support. As always, all mistakes are his.
6
Bibliography
Argyris, C. (2002). Double-loop learning, teaching, and research. Academy of Management
Learning & Education, 1(2), 206-218.
Baldassarre, G. D., Kooy, M., Kemerink, J. S., & Brandimarte, L. (2013). Towards
understanding the dynamic behaviour of floodplains as human-water systems. Hydrology and
Earth System Sciences, 17(8), 3235-3244.
Baldassarre, G. D., Viglione, A., Carr, G., Kuil, L., Salinas, J. L., & Blöschl, G. (2013). Socio-
hydrology: Conceptualising human-flood interactions. Hydrology and Earth System Sciences,
17(8), 3295-3303.
Blackburn, W. (2007). The sustainability handbook: The complete management guide to
achieving social, economic and environmental responsibility. Environmental Law Institute.
ISBN: 978-1585761029
Bogardi, J. J., & Kundzewicz, Z. W. (Eds.). (2002). Risk, reliability, uncertainty, and robustness
of water resource systems. Cambridge, UK: Cambridge University Press.
Brewer, J. (2014). Harvesting a knowledge commons: Collective action, transparency, and
innovation at the Portland Fish Exchange. International Journal of the Commons, 8(1), 155–178.
Cash, D. W., Clark, W. C., Alcock, F., Dickson, N. M., Eckley, N., Guston, D. H., . . . Mitchell,
R. B. (2003). Knowledge systems for sustainable development. PNAS 100:8086–8091.
Downloaded August 19, 2013 from http://www.pnas.org/content/100/14/8086.full.pdf+htm
Cohen, M. D., March, J. G., & Olsen, J. P. (1972). A garbage can model of organizational
choice. Administrative Science Quarterly, 17(1), 1-25.
Deegan, M., Stave, K., MacDonald, R., Andersen, D., Ku, M., & Rich, E. (2014). Simulation-
based learning environments to teach complexity: The missing link in teaching sustainable public
management. Systems, 2(2), 217-236.
Eccles, R. G., & Serafeim, G. (2013). The performance frontier. Innovating for a sustainable
strategy. Harvard Business Review, May, 50-60.
Elliot, S. (2011). Transdisciplinary perspectives on environmental sustainability: A resource base
and framework for IT-enabled business transformation. MIS Quarterly, 35(1), 197-236.
7
EPA. (2012, October). Resource guide to effective utility management and lean. Available at
http://water.epa.gov/infrastructure/sustain/upload/EUM-and-Lean-Resource-Guide.pdf
EPA. (2014, April). Moving toward sustainability: Sustainable and effective practices for
creating your water utility roadmap. Available at
http://water.epa.gov/infrastructure/sustain/upload/Sustainable-Utilities-Roadmap-12-10-
14_508.pdf
FEWresources.org. (n.d.). Water scarcity. Available at http://www.fewresources.org/water-
scarcity-issues-were-running-out-of-water.html. (Updated 06/15/15; downloaded Oct 5, 2015).
Hernes, T. (2014). A process theory of organization. Oxford, UK: Oxford University Press.
Hernes, T. (2017). Process as the becoming of temporal trajectory. In Langley, A. & Tsoukas,
H. (Eds.), The SAGE handbook of process organization studies (pp. 601-606). London: Sage
Publications.
Hinkel, J., Bots, P. W., & Schlüter, M. (2014). Enhancing the Ostrom social-ecological system
framework through formalization. Ecology and Society, 19(3). Article 51.
Hodgson, A. (2010, September 13). Global water shortages will pose major challenges.
Euromonitor International. Available at http://blog.euromonitor.com/2010/09/special-report-
global-water-shortages-will-pose-major-challenges.html
Hoekstra, A.Y. (2015). The water footprint of industry. In J. J. Klemes, (Ed.), Assessing and
Measuring Environmental Impact and Sustainability (pp. 221-254). Oxford, UK: Butterworth-
Heinemann (Elsevier).
Kasemir, B., Jäger, J., Jaeger, C. C., Gardner, M. T, (2003). Public participation in sustainability
science, a handbook. Cambridge, UK: Cambridge, University Press.
Khatri, K., & Vairavamoorthy, K. (2011). A new approach of risk analysis for complex
infrastructure systems under future uncertainties: A case of urban water systems. In Reston, VA:
ASCE copyright Proceedings of the First International Symposium on Uncertainty Modeling and
Analysis and Management(ICVRAM 2011), and the Fifth International Symposium on
Uncertainty Modeling and Anaylsis(ISUMA); Hyattsville, Maryland, April 11 to 13, 2011, d
20110000. American Society of Civil Engineers.
Khatri, K. B. (2013). Risk and uncertainty analysis for sustainable urban water systems.
UNESCO-IHE, Institute for Water Education.
8
Kolb, D. A. (1976). Management and the learning process. California Management Review,
18(3), 21-31.
Lago, P., Koçak, S. A., Crnkovic, I., & Penzenstadler, B. (2015). Framing sustainability as a
property of software quality. Communications of the ACM, 58(10), 70-78.
Mounce, S. R., Brewster, C., Ashley, R. M., & Hurley, L. (2010). Knowledge management for
more sustainable water systems. Journal of Information Technology in Construction, 15, 140-
148.
Mukheibir, P., Howe, C., & Gallet, D. (2015). Institutional Issues for Integrated ‘One Water’
Management. Water Intelligence Online, 14, 9781780407258. Available at
http://www.waterrf.org/PostingReportLibrary/4487a.pdf
Myllykoski. J. (2017). Strategic change emerging in time. Dissertation. University of Oulu. G91.
Newell, S., Robertson, M., Scarbrough, H., & Swan, J. (2009). Managing knowledge work and
innovation. New York, NY: Palgrave Macmillan.
Newig, J., Pahl‐Wostl, C., & Sigel, K. (2005). The role of public participation in managing
uncertainty in the implementation of the Water Framework Directive. European Environment,
15(6), 333-343.
Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological
systems. Science, 325, 419-422.
Pahl-Wostl, C. (2002). Towards sustainability in the water sector–The importance of human
actors and processes of social learning. Aquatic Sciences, 64(4), 394-411.
Pahl-Wostl, C., Holtz, G., Kastens, B., & Knieper, C. (2010). Analyzing complex water
governance regimes: The management and transition framework. Environmental Science &
Policy, 13(7), 571-581.
Pahl-Wostl, C., Mostert, E., & Tàbara, D. (2008). The growing importance of social learning in
water resources management and sustainability science. Ecology and Society, 13(1), Article 24.
Pahl-Wostl, C., Sendzimir, J., Jeffrey, P., Aerts, J., Berkamp, G., & Cross, K. (2007). Managing
change toward adaptive water management through social learning. Ecology and Society, 12(2),
Article 30.
9
Partelow, S. (2016). Coevolving Ostrom’s social–ecological systems (SES) framework and
sustainability science: Four key co-benefits. Sustainability Science, 11(3), 399-410.
Polk, M. (2014). Achieving the promise of transdisciplinarity: A critical exploration of the
relationship between transdisciplinary research and societal problem solving. Sustainability
Science, 9(4), 439-451.
Raine, S. R., Meyer, W. S., Rassam, D. W., Hutson, J. L., & Cook, F. J. (2007). Soil–water and
solute movement under precision irrigation: Knowledge gaps for managing sustainable root
zones. Irrigation Science, 26(1), 91-100.
Rockström, J., Karlberg, L., Wani, S. P., Barron, J., Hatibu, N., Oweis, T., . . . Qiang, Z. (2010).
Managing water in rainfed agriculture—The need for a paradigm shift. Agricultural Water
Management, 97(4), 543-550.
Russ, M. (Ed.). (2010). Knowledge management strategies for business development. Hershey,
PA: Business Science Reference.
Russ, M. (2014a). What kind of an asset is human capital, how should it be measured, and in
what markets? In M. Russ (Ed.), Management, valuation, and risk for human capital and human
assets: Building the foundation for a multi-disciplinary, multi-level theory (pp. 1-33).. New
York, NY: Palgrave-Macmillan.
Russ, M. (2014b). Homo Sustainabiliticus and the “new gold”. In M. Russ (Ed.). Value creation,
reporting, and signaling for human capital and human assets: Building the foundation for a
multi-disciplinary, multi-level theory (pp. 1-6). New York, NY: Palgrave-Macmillan.
Russ, M., Fineman, R., & Jones, J.K. (2010). Conceptual theory: What do you know? In M.
Russ, (Ed.), Knowledge management strategies for business development (pp. 1-22). Hershey,
PA: Business Science Reference.
Russ, M., Jones, J. G. & Jones, J. K. (2008). Knowledge-based strategies and systems: A
systematic review, in M. Lytras, M. Russ, R. Maier and A. Naeve (Eds.) Knowledge
management strategies: A handbook of applied technologies (pp. 1-62). Hershey, PA: IGI
Publishing.
Russ, M., & Jones, J. K. (2011). Knowledge management’s strategic dilemmas typology. In D.
G. Schwartz & D. Te’eni (Eds.). Encyclopedia of knowledge management (2nd ed,) (pp. 804-
821). Hershey, PA: IGI Reference.
10
Siegel, S. M. (2015). Let there be water: Israel’s solution for a water-starved world. New York,
NY: Macmillan.
Sivapalan, M., & Blösch, G. (2015), Time scale interactions and the coevolution of humans and
water, Water Resources Research, 51, 6988–7022. doi:10.1002/2015WR017896.
Sivapalan, M., Savenije, H. H., & Blöschl, G. (2012). Socio‐hydrology: A new science of people
and water. Hydrological Processes, 26(8), 1270-1276.
Stember, M. (1991). Advancing the social sciences through the interdisciplinary enterprise. The
Social Science Journal, 28(1), 1-14.
Thomson, C., El-Haram, M., Walton, J., Hardcastle, C., & Sutherland, J. (2007). The role of
knowledge management in urban sustainability assessment. Submitted to SUE-MOT
International Conference on Whole Life Urban Sustainability and its Assessment, 27-29 June
2007. Downloaded August 19, 2013 from http://download.sue-mot.org/Conference-
2007/Papers/Thomson.pdf
Tosey, P., Visser, M., & Saunders, M. N. (2012). The origins and conceptualizations of ‘triple-
loop’ learning: A critical review. Management Learning, 43(3), 291-307.
Tsoukas, H. (2016) Don’t simplify, complexify: From disjunctive to conjunctive theorizing
in organization and management studies. Journal of Management Studies. Accepted
article. doi: 10.1111/joms.12219
U. S. Army Corps of Engineers. (2014). Building strong collaborative relationships for a
sustainable water resources future: Understanding integrated water resources management.
Available at http://aquadoc.typepad.com/files/iwrm-report-jan2014.pdf
Vacik, H., & Lexer, M. J. (2001). Application of a spatial decision support system in managing
the protection forests of Vienna for sustained yield of water resources. Forest Ecology and
Management, 143(1), 65-76.
Vogt, J. M., Epstein, G. B., Mincey, S. K., Fischer, B. C., & McCord, P. (2015) Putting the ‘‘E’’
in SES: unpacking the ecology in the Ostrom social–ecological system framework. Ecology and
Society, 20(1), 55. http://dx.doi.org/10.5751/ES-07239-200155
11
Wallington, T. J., Maclean, K., Darbas, T., & Robinson, C. J. (2010). Knowledge – Action
systems for integrated water management: National and international experiences, and
implications for South East Queensland. Urban Water Security Research Alliance Technical
Report No. 29. Available at http://www.urbanwateralliance.org.au/publications/UWSRA-
tr29.pdf
Water JPI. (2014, June 16). Water JPI position paper on the Horizon 2020 Societal Challenge 5
2016-2017 Work Programme: Response to the stakeholder consultation. Available at
http://www.waterjpi.eu/
Winz, I., Brierley, G., & Trowsdale, S. (2009). The use of system dynamics simulation in water
resources management. Water Resources Management, 23(7), 1301-1323.
Ziemba, E. (Ed.). (2016). Towards a sustainable information society: People, business and
public administration perspectives. Cambridge, UK: Cambridge Scholars Publishing.
Zygmunt, J. (2007). Hidden waters. London, UK: Waterwise. Available at
http://waterfootprint.org/media/downloads/Zygmunt_2007_1.pdf
12
Figure 1. The coevolution of human and water systems
13
Figure 2. Knowledge management in sustainable water systems
14
Figure 3. The three elements of knowledge management in sustainable water systems (detailed)
15
Figure 4. The time aspect of the quantum organizational decision making model