Frameworks for studying complex systems

among policy makers as a tool that aides the systematic organisation, analysis and prescription of capabilities (Gibson, McKean and Ostrom, 2000; Sawyer, 2005; Aligica and Boettke, 2009).

Described by (Ostrom, 2011) as a multi-tier conceptual map, it centres around action situations, the subsequent patterns of interactions, and resultant outcomes. Within these action situations, defining actors make a series of action decisions based on available information, and the underlying rules that order their relationships. They are affected by the decisions of other actors and feel the impact of collective actions. Over time, this process constitutes adaptive strategies, whereby individuals change their behaviour as they learn from the results of past actions. For example, in competitive environments, individuals who can maximise key variables associated with success (such fitness or profit) in that environment will survive. By systematically following the decision-making path from problem identification, to designing a solution, planning the intervention, execution and evaluation, this framework has frequently been used to contextualise policy processes. Rudd (2004), Benson et al., (2013), and Nigussie et al., (2018) are examples of studies that have conceptualised the management of common resources using the IAD framework.

Through multiple collaborations, the IAD was further modified to produce a more dynamic framework useful for analysing the sustainability of Social-Ecological Systems (SES) (Basurto and Ostrom, 2009; Ostrom, 2009; Ostrom, 2011). Here, the framework situates all resources used by humans in a complex social ecological system. It introduces more internal variables and incorporates it with multiple layers of subsystems (resource systems, resource units, users and governance structures) in a way that allows for the interaction of these levels to produce outcomes at the SES level. This version takes into account ecosystem dynamics by analysing the relationships between multiple spatial and temporal levels of the systems.

2.6.3 Ecological transitions (Bennett’s adaptive dynamics)

Bennett (1976) offers a framework that studies how social factors influence human-environment interactions in the anthropological field (and within the specific context of cultural ecology). This approach has proved popular because it diverges from the traditional views that analyse adaptations based on causal determinism, and instead considers a structure of interconnected feedback loops – a more systems based approach. In a structured process, Bennett asserts the uniqueness of human ecologies and discusses what makes them distinct; the process of identification, and allocation of value to natural resources (not just based on biological needs but also culturally determined wants). These are cognitive steps that show that the human-environment relationship is an interactive, dynamic process that is imperfect (there are no absolute

standards for culturally allocated value). It contextualises and incorporates the goal oriented, purposive behaviours to satisfy wants with the consequent impact of adaptation on individuals, societies and the environment itself (thereby fusing micro-macro levels – favourable for multi-agent simulations). As such, it follows that the Bennett framework can lend itself to the technical modelling of complex decision-making processes. This has been notably and practically demonstrated in the agricultural domain by Bharwani (2004). For modelling purposes, Bharwani’s work offers some practical insights into the possibilities of adopting such conceptual frameworks to guide emerging computational and modelling techniques.

2.6.4 Other models of strategic choice

Similar to the formalised frameworks of complex systems, there are also many models of strategic choice in business and organisational management fields. One approach (presented by Wilson and Gilligan, 1997) places decision-making processes as one element of a broader problem solving framework. As illustrated in Figure 2.5, this broader view consists of

i. Strategic analysis: centred around understanding the strategic position of the organisation – clearly defining the boundaries and activities of the organisation, and thus the opportunities to, and limits of change.

ii. Strategic choice: focused on generating, evaluating and selection options.

iii. Strategic implementation: involving translating decisions into actions. This takes into consideration the feasibility and acceptability of strategic choices/decisions.

Figure 2.7 A summary model of the elements of strategic management Source: Johnson and Scholes (1988) and Wilson and Gilligan (1997)

However, this view of strategy is distinct from the traditional idea of strategy as a long-term plan.

Wilson and Gilligan (1997) explain that this process is one of continous adjustment in relation to competitors’ actions and changed cirmumstances. This approach emphasises organisational openness to revision and modification while working towards a preferred state. It contrasts with the tendency of organisations to focus on efficiency (essentially introsepctive) rather than effectiveness (an interaction between organisations and the environment). Interestingly, such organisational choice processes (governed by the context) share a great deal of similarity with Bennett’s definition of adaptive strategy – the final selection is determined by intent and assesment of the environment (among other things). Macmillan and Tampoe (2001) highlight additional components that factor into the choice process (services/products, markets, resourcces/capabilities and options to progress). Figure 2.6 highlights possible future strategic choices of organisations.

Figure 2.8 Ansoff’s matrix Source: Macmillan and Tampoe (2001)

The top-left cell of the matrix is the current status of the organisation (it is in one of four possible states). Movement within this matrix represent organisational choices about products and markets.

An organisation might chose to continue with present strategies (do nothing), leave the market (withdraw), attempt to hold existing market shares (consolidate), or increase market share (market penentration). Organisations can also leave its cell and transition to develop new products, address new market needs or enter new markets with new products. In this space, strategic choice has logical as well as political dimenions. Available options have to align with the organisation’s strategic intent, as well as be feasible. In order to meet the latter criteria, organisations might have to invest in building skills and experience – thus capability options are important considerations. Similar to the analytical frameworks mentioned in the sub-sections above, this approach incormporates a combination of bottom-up and top-down approaches. From

the top, the genereal goals in terms of organisational direction is linked to the more detailed low-level strategic options at the bottom. A last important aspect guiding the selection of a strategic option is its relative attractiveness or at least acceptability to the parties concerned (Bharwani, 2004).

In summary, the concepts around decision making processes in this organisational manangement field illustrate social and cultural processes. Organisations consider their contexts, the alignment/feasibility/acceptability of strategic options. Perceptions of risk and vulnerability also influence the acceptability of chosen options and organisations often employ risk reduction measures to varying degrees.

Because there are so many moving parts and concepts to grasp when practically modelling a complex adaptive system, it is useful to have a structure to guide thinking, simulating, and analysing the system. As such, a key consideration in selecting an appropriate framework to study this system is a structure that allows for a smooth transition between modelling the system and analysing it.

The questions explored in this thesis weave through the theories studied, the frameworks utilised, and the model developed. In practice, this means that the methodology is informed by pre-emptively taking into consideration the data analysis portion of this research – there is a whole section dedicated to the process of formalising this data.¹⁵ Consequently, Bennett’s Adaptive Dynamics framework was selected early on for two main reasons. First, it has a clear structure which accounts for individual strategies, as well as the effects of those strategies on the community or society as a whole i.e. how micro-level decisions shape the overall macro-level system dynamics.

By providing sets of categories of these behaviours and effects, this framework also facilitates the process of modelling a system with all the principles of complexity in a way that is tractable for the modeller. Second, while this research is exploring fairly new terrain in the development field, there are opportunities to learn from other domains that employ similar approaches and techniques. In this sense, it is pragmatic to refer to existing templates and not ‘rebuild the wheel’.

The adaptive dynamics framework developed by Bennett has been demonstrated as a useful guide by Bharwani (2004). Accordingly, it serves as a useful template for this research – the application

15 This will be done using adaptive strategies from the analytical framework in Chapter 6.