In this section, I list a theoretical grounded review of the most important limitations of the reviewed literature. The gaps that the research aims to fulfil and which are to be considered in the analysis and design framework proposed later in this thesis. The following section gives a detailed description of the issues that are poorly considered: 1) Consideration of social aspects when developing the enterprise models, 2) The dynamicity and evolution of the environment, ’dynamics analysis’, 3) Reasoning about design choices, 4) External risk consideration
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through the analysis, 5) Language issues, 6) Complexity and the abstraction level of the enterprise model.2.5.1 Consideration of Social Aspects
People differ in their understanding, acceptance, agreement and commitment (Hoppenbrouwers, 2005). It is impossible for a human being to be aware of everything in the environment. Human thinking is always influenced by their knowledge acquired, experiences, observation and mood (Sterman, 2000). Many studies in psychology, cognitive science and computer science have tried to draw a mental model describing how the human mind works (thinking, action, feeling and sensing). Belief is changeable, therefore human goals and behaviour are dynamic (Khan and Lespérance, 2010; Ceresia, 2009).
On the other hand, many studies have talked about design theories and how design should be more collaborative to increase the collective intelligence. Possible solutions can be found in the collaborative design framework, allowing stakeholders to negotiate and perform collaborative brainstorming and knowledge sharing which will help to reduce the risk of project failure (Fischer and Hermann, 2011).
However, intentional knowledge is often indirectly suggested, not easily available, not systematically managed, and frequently misplaced (Yu et al., 2006). Yu’s (2009) argument declares that goal-oriented RE frameworks (such as the KAOS and NFR frameworks) employ ontology, which is intentional but not completely social. Semantic-based intentional modelling (Yu, 2009) represents the behavioural and intentional aspects of the stakeholders’ goals but is still inadequate in presenting social aspects, as social modelling should contain intensive work on cognitive, reasoning, expectation and emergent behaviour mitigation aspects. We can say that ‘belief’ can only be understood in the current EM tools as either 1) Claims and expectations, or 2) Facts.
As we have seen in the literature review, the approaches of socio-technical systems with intensive social focus better analyse and consider the social aspects, whereas the EM and EAFs represent social aspects in a controlled or engineering manner, which is again limited in its description. Having techniques from both disciplines will make the representation of social aspects more mature. I see social aspects as being distinguished within two groups: 1) social aspects relevant to the design process (e.g. collaboration, thinking and reasoning); 2) social aspects and influencers of enterprise design and operation (e.g. trust, skills, leadership).
2.5.2 Dynamics and Evolving with the Environment
Uncertainty and evolution are two main characteristics of any domain or environment. However, change and evolution are not particularly considered in the current methodologies;
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therefore, how can we treat the dynamic nature of the business environment? It is very difficult to find an answer to this question. Change will always occur, whether it is intended or not; whether we know about it or not; and whether we can do something about it or not (Tran and Massacci, 2011). In Jarke et al.’s (2009; 2011) studies, the authors considered the importance of the inter-relationship between requirements and contexts. They also point out the issue of evolving IS design along with ecologies following the requirement to bring through new artefacts from the system environment with the acceptance of this evolution as a fact that occurs in all systems at different rates. Yu (2009) admits the limitation of the current methods in handling evolution and change as well as moving from ‘as is’ to ‘to be’ or handling what ‘might be’. In addition, there is a limitation in the proposed evolution alignment developed by Samavi et al. (2009) for two reasons: 1) The limitation of the strategic dependency model in describing the operational level of the business; 2) The alignment is not mature enough in terms of technical applicability, choosing among alternatives and automating stakeholders' network creation. The analysis of the twelve EAFs shows that none of these frameworks consider dynamic modelling (Table 7), especially in term of dynamic simulation or re-configurability.2.5.3 Reasoning
We focus on two kinds of problem: knowledge problems which we need to know, and design problems which we need to do. Reasoning about strategic and operational activities is essential, especially around issues related to the intentional structure. An interactive method with a high degree of human judgement may be best suited to the early stages of requirements engineering, owing to its participatory and informal nature (Yu, 2009). Reasoning about the way in which the risks and opportunities should be handled is crucial to understanding how several solutions affect a wide spectrum of organisational and risk-related issues. Lamsweerde (2009) proposed a method for reasoning about alternative requirements to be considered based on qualitative and quantitative assessment; the author built requirements models based on goal-oriented modelling and evaluated the goals based on the nature of their impact. Tran and Massacci (2011) proposed a reasoning method for the evolutionary model based on prioritising and classifying requirements using a rule-based approach. Nevertheless, the analysis of the twelve EAFs shows that none of these frameworks considers reasoning modelling (Table 7) as part of the framework or part of the analysis techniques used to execute the framework.
2.5.4 Risk Associated with the External Environment
Risk is always associated with change, and most of the enterprise frameworks focus on the internal environment of the enterprise. It is possible that the consideration of risk should be extended to cover wider possible influencers, which might be internal or external. Risk has
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different levels, and consideration of risk should have several levels of maturity, based on the consideration of multiple levels of influencers, dependences and causal loops. Sometimes it is not easy to identify the risk within a single causal loop, thus the enterprise should define what level of maturity it needs to achieve. A good risk analysis should understand the impact of direct and indirect influencers; the analysis should also provide insight into the level of the impact, alternative scenarios and potential solutions and the speed of the impact’s spread on other components, in order to decide the required response time in the case of event-based scenarios. The risk analyst needs to understand the impact on/of ecology, business, technology, and social systems (Jarke et al., 2009). Governance and control should be central and distributed at the same time: central in terms of planning, and design, and distributed in terms of power, privileges and collaborative thinking, for handling emergent events. The literature analysis shows that the previous studied approaches have a lack of consideration of at least one of these external influencers.2.5.5 Language
Domain terms, concepts and vocabulary are all still issues which must be considered by researchers. Liu et al. (2011) argued that business-IT alignment is difficult because of miscommunication resulting from ‘language’ differences between the business and IT domains. In Yu (2009), the adoption of a project lexicon or ontology (Breitman and Leite, 2003) is worth considering, to facilitate knowledge sharing and a common understanding among stakeholders. It has also been suggested that lightweight natural language processing may also be helpful (Sawyer et al., 2005). Guarino (2009) confirmed the importance of language in knowledge representation, and outlined a method to represent ontological semantics. Chen (1994) pointed to the issue of the existence of a gap between collaborators in terms of the vocabulary used; it will be based on their fields or environment. It is a challenge for the designers of collaborative systems to overcome this issue. In other research (Lautenbacher et al., 2007), language understanding has been shown to not only affect people’s understanding, but to influence machine understanding: a semantic annotation method is the only way to overcome such problems; the author proposed a linguistic modelling method using terms and ontology for requirements engineering. In addition, Hoppenbrouwers (2005) recommended using controlled natural language to overcome ambiguity and misunderstanding in developing business and information systems. The literature analysis in this chapter shows that none of the previous studied approaches has adopted a language facilitating technique.
2.5.6 Complexity and Level of Abstraction
The socio-technical systems are complex by their nature, STS design methodologies and enterprise modelling architectures exhibit considerable variation in the level of detail they