To date, our conceptual framework is the first application of the affordance-actualisation theory by Strong et al. (2014) in order to explain the socio-technical interaction between an actor and a Green IS. We have identified four publications from the Green IS domain that draw upon affordance theory for different purposes: (1) Seidel and Recker (2012) theorise how functional affordances of IS facilitate the creation of green business processes; (2) Seidel et al. (2013) identify four functional affordances of IS providing green transformative power to organisations; (3) Reuter et al. (2014) identify five functional affordances of IS that assist organisations in reducing energy consumption;
and (4) Recker (2016b) uses the concept of functional affordances to detail the building blocks of his Green IS design theory in form and function.
Strong et al.’s (2014) generic affordance-actualisation theory provides the necessary framework to explain how IS and actors interact with each other. Insights from Recker’s (2016b) Green IS design theory furnish the components of an abstract-level, idealistic Green IS, which we use to specify the constructs IS artifact (hitherto: IT artifact) and
Green IS affordance (hitherto: affordance). While the specified Green IS affordances (cf.,
chapter 3.2.1.3) assist us in the development of reasonable scenarios depicting how Green IS can environmentally support individuals and organisations, the detailed definition of the IS artifact, using the six generic data-driven material properties (cf., chapter 3.2.1.1), demonstrates how any IS artifact can eventually be perceived as environmentally supportive based on the user’s intentions.
The four principles of affordance theory, introduced in chapter 2.3, are reflecting the main implications of our affordance-based theory for Green IS research. The first and second principle (cf., first principle: Affordances are functional/ relational; second principle: Affordances are opportunities for action) suggest that scholars – when conceptualising Green IS – should cater for two types: Intentionally implemented Green IS versus Green IS that unintentionally emerged and became environmentally supportive. Available research oftentimes understand Green IS as systems that are the product of a purposeful design and implementation process (cf., Watson et al. (2008) or Chen et al. (2009), or Seidel et al. (2013)). However, when understanding the socio-technical IS as an affordance-driven concept emerging from the relational interaction between IS artifact and actor, we must also account for Green IS affordances that may unexpectedly emerge from IS without any initial environmental intention. This tweaked conceptualisation can be helpful when analysing the emergence, adoption, and appropriation of Green IS initiatives in organisations.
Furthermore, our affordance-based Green IS framework expands existing analytical and explanatory capabilities when analysing Green IS implementations. An underlying advantage of the affordance-actualisation theory is its wide applicability across industries and business models, which is the case for the Green IS domain as well. We identify two main features that increase the explanatory power of our framework: Firstly, the deliberate distinction between affordance perception and affordance realisation (cf., second principle: Affordances are opportunities for action) provides the researcher with a more granular analysis instrument, allowing for a separate investigation of both sub- processes. This extension becomes particularly interesting when conducting a variance analysis between Green IS affordances from different scopes of operation (i.e., belief
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formation, action formation, or outcome assessment). Questions concerning differing
perception-realisation-journeys between affordances from different scopes of operations can be investigated. Secondly, the feedback relationships (cf., fourth principle: Affordances are learnable) offer an analytical instrument to explain short and long-term organisational developments induced by the Green IS. Furthermore, our current analytical instrument can be extended and enriched by a stronger focus on the collective realisation of affordances (cf., Strong et al. (2014)). This will further increase the framework’s explanatory power as interdependencies between individual affordance realisations can be investigated in more detail.
Additionally, our affordance-based framework includes characteristics of process and
systems theory (cf., Webster and Watson (2002)), as it combines the scientific
understanding of probabilistic and sequential relationships between events (i.e.,
Realisation Immediate concrete result) with emerging and reciprocal relationships
between system-comprising parts (i.e., IS artifact + User Green IS affordance;
Immediate concrete result User). This hybridised theoretical approach extends the
researcher’s toolset for three reasons: Firstly, balancing the theory’s focus between technology (i.e., IS artifact) and actor (i.e., user) endows researchers with a separate and transparent understanding of both while their interweaving (i.e., emerging interrelationship) is acknowledged simultaneously (cf., first principle: Affordances are functional/ relational). Secondly, the sequential process approach allows us to break down the socio-technical construct into its atomic instantiations. Meaning, every single interaction between an actor and the IS artifact (i.e., affordance perception and – if actualised – realisation) can be evaluated in terms of its impact (cf., fourth principle: Affordances are learnable). Thirdly, reciprocal feedback relationships (cf., chapter 3.2.2) – characteristic for the system approach (cf., Garud and Kumaraswamy (2005) or Clark et al. (2007)) – enable us to evaluate and explain different impact intensities at different points in time (cf., third principle: Affordance realisation is actor and goal dependent; fourth principle: Affordances are learnable).
The extensions are particularly important for multilevel research that pursues the objective to explain organisational impact over time: Oftentimes, “researchers […] assume that the effect of independent variables on dependent variables is instantaneous, [which] may not be the case; especially in collectives, the relationship between predictor and outcome variables may take time (e.g., days, months or years) to emerge” (Burton- Jones and Gallivan 2007, p. 671). Our conceptual framework supports this opinion and provides good reasons why we should not assume that instantaneous effect.