TY - GEN

T1 - Responding to the UN Sustainability Goals through network action learning

AU - Dreyer-Gibney, Katrin

AU - Coughlan, Paul

AU - Coghlan, David

AU - Wu, Szu-Hsin

AU - McNabola, Aonghus

AU - Novara, Daniele

AU - Spriet, Jan

AU - Williams, Prysor

A2 - Bello-Dambatta, Aisha

A2 - Dallison, Richard

A2 - Rafique, Annum

A2 - Schestak, Isabel

A2 - Walker, Nathan

PY - 2020/12/6

Y1 - 2020/12/6

N2 - The UN Sustainability Goals challenge society to consider how it is behaving and to respond with new partnerships to sustain our communities, resources and planet. The scale and scope of this challenge is enormous and not amenable to single discipline actions, nor to actions which do not integrate research and practice. In the classic sense of Revans (1998), the challenge is a problem rather than a puzzle: a puzzle is a difficulty for which a correct solution exists, and which is amenable to specialist and expert advice; a problem is a difficulty where no single solution exists. Complex organisational change initiatives fall into the category of a problem, as there is no single solution while there may be many opinions as to what the preferred course of action might be (Coughlan & Coghlan, 2011). Problems are amenable to action learning where different people can advocate alternative courses of action in accordance with their own value systems, past experience and intended outcomes. In this paper, we explore a particular response to the UN Sustainability Goals undertaken through network action learning. The problem setting is that of the creative application of novel technology with the potential to reduce the carbon footprint associated with water distrivution and use. Increasingly, water, where available, is not in the right place at the right time. That is a well-recognised problem with implications for food production and human habitation. However, a less recognised related problem is that the energy burden associated with water production and distribution is substantial. Treating raw and waste water to acceptable standards for consumption is energy intensive. Such activity accounts for 2–3% of the global energy use. Therefore, initiatives to reduce that energy burden have the potential to reduce the carbon footprint and sustain water as a resource. In this paper we explore how network action learning impacts the practice of exploring and exploiting the application of novel technology to reduce 2 the energy burden associated with water production and distribution and how, through learning in action, innovation capabilities are developed. We apply action learning research (ALR) as the overall research methodology. We combine research and project practices, designs and philosophies to enable the timely production of valid, actionable knowledge and innovative solutions and we illustrate how we ensured that our collaborative research approach was rigorous, reflective and relevant (Pasmore et al, 2008; Eden & Ackermann, 2018; Shani & Coghlan, 2019; Lindhult, 2019)

AB - The UN Sustainability Goals challenge society to consider how it is behaving and to respond with new partnerships to sustain our communities, resources and planet. The scale and scope of this challenge is enormous and not amenable to single discipline actions, nor to actions which do not integrate research and practice. In the classic sense of Revans (1998), the challenge is a problem rather than a puzzle: a puzzle is a difficulty for which a correct solution exists, and which is amenable to specialist and expert advice; a problem is a difficulty where no single solution exists. Complex organisational change initiatives fall into the category of a problem, as there is no single solution while there may be many opinions as to what the preferred course of action might be (Coughlan & Coghlan, 2011). Problems are amenable to action learning where different people can advocate alternative courses of action in accordance with their own value systems, past experience and intended outcomes. In this paper, we explore a particular response to the UN Sustainability Goals undertaken through network action learning. The problem setting is that of the creative application of novel technology with the potential to reduce the carbon footprint associated with water distrivution and use. Increasingly, water, where available, is not in the right place at the right time. That is a well-recognised problem with implications for food production and human habitation. However, a less recognised related problem is that the energy burden associated with water production and distribution is substantial. Treating raw and waste water to acceptable standards for consumption is energy intensive. Such activity accounts for 2–3% of the global energy use. Therefore, initiatives to reduce that energy burden have the potential to reduce the carbon footprint and sustain water as a resource. In this paper we explore how network action learning impacts the practice of exploring and exploiting the application of novel technology to reduce 2 the energy burden associated with water production and distribution and how, through learning in action, innovation capabilities are developed. We apply action learning research (ALR) as the overall research methodology. We combine research and project practices, designs and philosophies to enable the timely production of valid, actionable knowledge and innovative solutions and we illustrate how we ensured that our collaborative research approach was rigorous, reflective and relevant (Pasmore et al, 2008; Eden & Ackermann, 2018; Shani & Coghlan, 2019; Lindhult, 2019)

M3 - Conference contribution

BT - European Academy of Management

ER -