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21.Ability, Motivation and Opportunity theory: a
formula for employee performance?
Ashlea Kellner, Kenneth Cafferkey and Keith Townsend
INTRODUCTION In the human resource management (HRM) discipline, the Ability, Motivation and Opportunity (AMO) theory has been adopted extensively to potentially explain the complex relationship between how people are managed and subsequent performance outcomes. A commonly accepted view is that some combination of an individual’s ability (A), motivation (M) and their opportunities (O) can give us a measure of an individual’s performance (P) (expressed as AMO = P). Although it is unclear through the expression of this formula, HRM researchers have in recent decades applied the AMO framework in a way that suggests it is the associated HRM practices that in fact influence an individual’s ability, motivation and opportunity, which therefore leads to performance-related outcomes. Employee ability, for instance, could possibly be improved via training , motivation potentially develops through performance-based pay , and opportunity to participate could be influenced by self-directed team membership. Unfortunately, the application of such HRM practices is somewhat vague and a prescriptive course of action to realize the potential of AMO remains elusive. However, taken broadly as a HRM system, the total effect of practices is to increase outcomes such as individual productivity, team performance or firm profitability. Similarly, the AMO model can also be used to understand behavioural processes between people management initiatives and potential performance improvements (Purcell et al., 2003). There is a lot to like about this model and, hence, intuitive acceptance is commonplace in the discipline (Boselie et al.,
2005). AMO theory allows various practices to be grouped together into three different dimensions of performance antecedents and suggests the interaction of these elements can help predict a large number of performance outcomes. There are, though, some fundamental issues associated with the model which we explore in detail in this chapter. First, AMO theory when traced back to its roots appeared to be concerned with individual characteristics as independent variables, however, the HRM field uses organizationally determined HR practices and policies as independent variables. This means there are at least two different incarnations of the AMO model, although this differentiation is often unclear in the literature. Second, while AMO is a commonly adopted framework to explain performance, very few researchers actually empirically test the model. Further to this point, there is significant inconsistency in the definition and selection of dependent and independent variables, compounded by lack of consideration of context in determining how variables should be selected.
In this chapter, we develop an argument to suggest AMO theory is poorly defined and tested, and that intuitive appeal is not because it is a robust theoretical model, but that it can be adapted to suit almost any HRM study. Consequently, theoretical development of the AMO model has been stagnant, and without deeper consideration of the variable relationships and interactions, development of AMO will continue to be piecemeal and overly simplistic. We first consider the development of the model in a historical context and the antecedents to its evolution. Next, we discuss in greater detail the key application issues associated with AMO theory, namely, relating to variable definition, thereby restricting comparison of extant research. Subsequently, we explore the related issue of confounding dimensions, whereby there is inconsistency as to which category (AMO or P) variables are assigned. We offer some explanations for these critical issues, and outline an agenda for future development, supported by our own preliminary model of AMO for HRM research. This model begins to
performance. These contextual factors are potentially vast in number, but can be described as ‘states of nature’ and ‘actions of others’, and are combined to create the dimension of opportunity (p. 563).
In their seminal work, Blumberg and Pringle (1982) use the terminology ‘capacity’ (tantamount to ability) and ‘willingness’ (tantamount to motivation). Hence, they promote a model that is analogous with AMO, but termed OCW (Opportunity, Capacity, Willingness). Their formula is interactive in nature, P = f (O × C × W) where all three elements must be present in some degree for work performance to occur (demonstrated in Figure 21.1). There is, however, no explicit statement about what performance is or how it should be measured aside from ‘performance is determined by opportunity, willingness, and capacity and, in turn, is a partial determinant of each’ (p. 565). In essence, this means aspects of performance are not only driven by AMO elements, but good performance will influence the employee’s job satisfaction and consequently, as an example, increase willingness (motivation) even further.
Figure 21.1Blumberg and Pringle’s (1982) early interactive OCW model
Blumberg and Pringle argue an individual’s performance will influence other variables, hence AMO should not be considered a static model. For example, when an employee goes through a performance evaluation process (commonly considered as a motivator variable) a strong evaluation may provide new opportunities for the employee. Equally, a strong positive evaluation may provide higher levels of motivation for the employee to continue working hard and further improve their performance. Negative performance evaluations may similarly decrease motivation and limit future opportunities. Therefore, it is reasonable to suggest that all variables interact with performance and are interdependent with each other and thus could be described as self-reinforcing.
literature. In effect, individualism (personal characteristics) drove AMO developments to circa 2000, and then the individual became somewhat lost as the majority of AMO research transitioned to a systems approach driven by HR policies as espoused by Appelbaum et al. (2000). Another important variation to note here is that the change from an individual to a systems-based approach highlights a pro-management unitarist view of performance, whereas Applebaum et al. (2000) address broader outcomes such as equality, inclusion and justice.
In short, we illustrate the approach of the HRM discipline in applying the AMO framework in Figure 21.2.
Figure 21.2Standard contemporary adoption of AMO model in HRM research
The model in Figure 21.2 can be compared with Figure 21.1 as an illustration of the evolution of AMO in the HRM discipline. There has been confusion between the psychology model and the HRM model of AMO; a confusion between an individual’s AMO and AMO- enhancing practices. Lacking is an explicit discussion that it is the ability-enhancing practices that are presumed to enhance an individual’s ability, which in turn enhances performance outcomes. Hence, we have not shown these relationships in this model. In the following section, we discuss the application of the model in the extant literature, which has seen resultant issues relating to demonstrating causation between AMO-enhancing practices and performance, and poor justification for inclusion and exclusion of HRM practices.
A great disparity exists in the variables considered within the empirical AMO literature. As we will show, this disparity means we have an ever-increasing volume of empirical studies pointing to the relationship between AMO variables and performance, but very limited capacity to compare these studies. Consequentially, as a field we will find it difficult to progress theory in a meaningful way when we continue to move in incremental developments with minor changes to variables used. In the following we report our findings of a comprehensive review of the empirical articles that use AMO theory in a meaningful way. We outline issues with the core variables, both individually and when taken together as a model where confounding and confusion inevitably arise.
UNPACKING ABILITY, MOTIVATION AND OPPORTUNITY Training appears to be the most commonly adopted ‘ability-enhancing’ HR practice used in empirical work adopting the AMO framework. Selective hiring and recruitment closely follow. What is concerning is the notion research is being published that considers recruiting as a variable at all, as any organization which does not select or recruit staff will obviously have no level of performance. Selective hiring provides a more nuanced description of more sophistication than simply selection and recruiting and therefore becomes more useful as a concept to measure.
When we consider the effect that motivation or motivation-enhancing practices have on performance the picture is similarly bleak. Of the different variables used, those that were present in multiple studies included only compensation, performance-based pay, work-life balance, performance appraisals and performance evaluations. Again, suggesting compensation improves performance is somewhat underwhelming and should be considered standard – paying people will increase the likelihood that they will work – this is hardly the cutting edge of social sciences. What is more interesting is whether performance-based pay will increase performance and none of the AMO-focused studies show that to be the case.
When we look at the use of opportunity variables, the cohesion is no clearer. Variables that appear more than twice in our review of the literature include: teamwork, social networks, autonomy, communication, employee surveys, information sharing, involvement in decision-making and participation. Bos-Nehles et al. (2013) found role overload to be negatively associated with performance of frontline managers, and Innocenti et al. (2011) found the presence of employee surveys was negatively associated with the performance measure of employee attitude towards the organization. This, however, might be logically
made (flexible) working arrangements. Similarly, and although excluded from this study as it is not a journal article, we have also seen conference papers where the use of work-life balance policies has been used as a dependent variable (Lee et al., 2015). Involvement in decision-making has been used as a motivation (Trullen et al., 2016) and as an opportunity (Boselie, 2010; Harney and Jordan, 2008; Lee et al., 2019; O’Donohue and Torugsa, 2016; Ogbonnaya and Valizade, 2018; Raidén et al., 2006; Sarikwal and Gupta, 2013; Tian et al., 2016).
Performance appraisal has been operationalized in all three dimensions of the model, as an ability-enhancing practice (Sarikwal and Gupta, 2013), motivation enhancing (Fabi et al., 2015; Lee et al., 2019; Ma et al., 2017; Obeidat et al, 2016; Ogbonnaya and Valizade, 2018; Tian et al., 2016; Vermeeren, 2015) and as an opportunity-enhancing policy (Raidén et al., 2006). Closely related variables – job evaluation (Innocenti et al., 2011) and formal job analysis (Obeidat et al., 2016) – have also been listed as ability enhancing, with performance evaluation as a motivator on three occasions (Andreeva and Sergeeva, 2016; Bello-Pintado, 2015; Prieto Pastor, 2010). Communication skills has been presented as an ability variable (Lee et al., 2019), while Lertxundi and Landeta (2011) and Tregaskis et al. (2013) suggest communication is a motivator variable, and yet it is seen as an opportunity-enhancing practice in the research of Birgit Raidén et al. (2006), Ogbonnaya and Valizade (2018) and Fabi et al. (2015). This inconsistency in classification of variables is not necessarily due to researcher error, however, and we propose three potential explanations below.
POSSIBLE EXPLANATIONS FOR AMO THEORY LIMITATIONS The examples discussed above demonstrate a level of conceptual confusion within the AMO literature and we argue this confusion points to one of three possible explanations that are not
mutually exclusive – in fact, all three may be operating within the literature. The first explanation is that the model is a meaningless chameleon that allows any data set to fit because the ability, motivation and opportunity dimensions are so vague it allows any interpretation researchers deem appropriate (or convenient). The second possible explanation is that, as Kellner et al. (2016) suggest, context is a central explanatory variable. For example, involvement in decision-making is certainly a motivating approach for employees in certain circumstances and also provides opportunities in others – what becomes important here is the performance variable that is being measured. Involvement may be a motivator when measuring, for example, job satisfaction, but it then becomes an opportunity-enhancing practice when we are measuring safety as it allows employee contributions to problematic and unsafe practices and processes within the organization. Theoretical development is hence reliant upon the specifics of context and study design because if this explanation is salient, the variables are changeable depending on the context and performance measures.
A third potential explanation is that there is confusion within the literature over what we consider within the AMO model, pointing towards a fundamental flaw within our current collective understanding of AMO. As previously mentioned, many studies draw together a series of HR policies that are then combined into aggregated ‘enhancing’ policies. By taking this approach we can see there is strong evidence that each of the AMO dimensions contribute to performance, but we do not know from the AMO literature whether, for example, performance management systems contribute positively to performance and, if so, under what circumstances. There are other studies though which embrace a more traditional view of AMO variables – drawn from the Blumberg and Pringle era of AMO – and use variables like ‘willingness to act’ as a motivator or ‘personal traits’ as an ability measure. Hence, we clearly have three different types of studies within this domain of measuring AMO as it relates to performance and HRM: (1) studies of individual characteristics; (2) studies of
systems level we can measure various enhancing practices for the abilities and motivations variables, however opportunities present a slightly more complicated challenge. Individuals do not ‘own’ opportunities, nor are they inherent in the HR system. As Blumberg and Pringle (1982) stated almost four decades ago, opportunities make up ‘environmental variables not under the control of the individual …’ (p. 563). These opportunity variables can overlap the individual and systems level of the model. Equally, we draw on past literature in our model to demonstrate all dimensions can (and will) interact with each other, and with performance, resulting in an effect on the AMO variables at an individual and HRM systems level. The utility of this model is that the imbalance towards HR practices is addressed and the individual is restored to parallel prominence alongside the HR system dimensions. In doing so, we dispel the myth that HR practices are the sole antecedents of performance irrespective of the individual involved. The individual is not viewed a latent robotic conformist to HRM intentions. As researchers we must acknowledge that performance could equally be driven by variables outside the remit of the HR department, that is, individual traits.
Figure 21.3A dynamic model of AMO for HRM research
An individual’s performance will have a direct influence on the individual’s abilities, motivation and opportunities just as much as these variables affect performance (Jiang et al., 2012). This is not to say we have a situation of reverse causality to disentangle. What we mean here is that an employee’s performance is not the only outcome in this model, but changes in the AMO variables occur as a result of an individual’s performance. As noted by Jiang et al. (2012), there are significant differences in the predictive capacity of AMO variables. If, for example, an employee is performing well in their role, there would be many circumstances where the employee’s motivation is increased with this success. Equally, the interaction between motivation and opportunities are clear here as it is not unreasonable to
This chapter provides a number of different avenues for future research that can lead to a cumulative body of knowledge. First, AMO research should distinguish between individual characteristics and HR practices that are aimed to enhance the individuals’ AMO. Second, there is a significant deficiency in addressing the interactions between variables in contemporary AMO research. Research of this vein would undoubtedly prove useful in providing a weight to the predictive capacity of each variable. Finally, in its present form of a simplistic input–output model, AMO provides little by means of value. It would be beneficial to conceptualize and test AMO as a continuous process such as suggested in our model, whereby AMO influences performance and performance subsequently reinforces AMO in turn.
In conclusion, we have unearthed several deficiencies in the AMO model in terms of its conceptualization, application, measurement and internal workings. In its current form the model, while having obvious intuitive appeal, has severe practical limitations that are thwarting both theoretical and empirical advancement. This chapter has demonstrated that while AMO is commonly used, it is used without a common basis or purpose. There is an understandable, albeit scattergun approach to determining the dependent variable (performance) and substantial confusion over what constitutes the abilities, motivations and opportunities variables.
Within the broadly interpreted HRM field, we have (at least) two types of AMO considered – one where individual characteristics are measured and a second where HR practices are measured. Both approaches provide some small steps to improving our understanding of what leads to better performance, but independently, both approaches have limited value. We agree with previous researchers who have suggested there is a lot to like about the AMO model, hence why acceptance in the HRM discipline is almost universal. However, the problem remains that there are two AMO models operating autonomously. We
hope this chapter begins a conversation among HRM scholars that will develop AMO theory and enhance the theoretical and practical utility of the AMO model.
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