Introduction and a theoretical framework for Knowledge Management for Sustainable Water Systems

Meir Russ

University of Wisconsin–Green Bay, Green Bay, Wisconsin, USA

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 that humans in the 21st century are, and will be, facing. Knowledge commons (e.g. Brewer, 2014) and virtual, digital spaces of learning (Niccolini et al., 2018) 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 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 that 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 interdisciplinary, 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 Knowledge Management for Sustainable Water Systems 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 20 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 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 The coevolution of human and water systems and Knowledge Management.

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 Knowledge Management in Sustainable Water Systems.

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–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. (See Chapter 11), 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, 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 The three elements of Knowledge Management in Sustainable Water Systems (detailed).

The complexity of...