The Concept Of Decision Making

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02 Nov 2017

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2.1 Introduction

This chapter introduces the key literature areas for the research. Decision-making is considered to be the parent discipline of the research. The concept of decision-making, more specifically strategic decision-making from an organisational perspective is discussed. This is followed by a critique of literature on strategic decision-making. The literature review is based on an amalgamation of the comprehensive reviews of the works on strategic decision-making by scholars such as Harrison and Phillips (1991), Eisenhardt and Zbaracki (1992), Meindel et al (1996), Papadakis and Barwise (1998) and more recently Nutt and Wilson (2010). The literature and arguments for the descriptive model of strategic decision-making is presented, and the choice of the ‘Bounded Rationality Model’ is discussed in depth. The different level of decision-making including a brief look at the literature on the concept of group decision-making is also discussed as the research explores the decision-making process of a group of African leaders in the context of the succession to the Kyoto Protocol under the United Nations Framework Convention on Climate Change.

The research problem, critique of the literature on strategic decision-making and the emergent research issues culminates in the identification of the research gap leading to the questions the study intends to address.

The decision-making processes within the UN system as it relates to the Framework Convention on Climate Change are discussed in depth in the subsequent chapter. More specifically, strategic decision-making as it relates to Climate Change Policy decisions in the context of the United Nations in its primary role as an international organisation for addressing a wide range of global issues, such as climate change is then examined. The various research areas are brought together to further highlight the gaps in the literature.

Whilst this review is extensive, the justification is given based on the breadth of the bodies of literature and the complexity of the nature of the research.

The structure of the literature review is illustrated in Figure 1 below.

Figure 1 Structure of the Literature

2.2 The Concept of Decision-making

The study of decision-making is not new. Decision-making has traversed a number of levels of analysis, from individual human cognition to the cultural characteristics of nation states, and as an area of research has a significant historical trajectory with many distinguished contributions (Nutt, 2011).

The term strategic decision-making is frequently used to signify important or key decisions made at the helm of organisations in all types. In the context of this research, the UN is the organisation in question. The UN as an organisation includes a collection of social, economic and political activities involving a plurality of human effort (Wilson, 2007) and is discussed in more depth in relation to the research phenomenon in the subsequent chapter.

World leaders are required to make decisions amongst alternatives choices. The decisions that are required to be made are often uncertain choices, furthermore, these choices are required to benefit both the organisation to which they relate and key influential stakeholders (Nutt et al, 2010). As a result, according to Nutt et al (2010)

…’this has prompted researchers to study decision processes to find ways in which decisions can be improved’ (Nutt et al, 2010:3).

Additionally,

…strategic decisions are seen as large, expensive, and precedent setting producing ambiguity about how they find a solution and uncertainty in the solutions outcomes’’ (Nutt et al, 2010:4).

Moreover, researchers contend that strategic decisions have the following general characteristics: -

‘Elusive problems that are difficult to define precisely;

Require an understanding of the problem to find a viable solution;

Rarely have one best solution, but often a series of possible solutions;

Solution benefits are difficult to access as to their effectiveness, in part because they lack a clear and final end point against which effectiveness can be judged;

High levels of ambiguity and uncertainty are associated with the solutions;

Realising hoped for benefits has considerable risks; and

Strategic decisions have competing interests that prompt key players to use political pressure to ensure that a choice aligns with their preferences’ (Nutt et al, 2010:4).

Researchers contend that strategic decision-making is frequently treated as an instantaneous choice between two or more known alternatives (Nutt, 2011). However, this approach is unable to capture the richness and complexity of the processes that are involved in making these decisions (Nutt and Wilson, 2010). Intrinsically, decision-making studies often undertake observations, interviews and surveys to find out about the processes or procedures that are used in practice (Nutt and Wilson, 2010; Nutt et al, 1984; Dean and Sharfman, 1996). Nonetheless, researchers have argued that whilst decision-making research has offered capacious investigations, structuring techniques, prescriptions and analytical tools, few scholars have integrated this body of knowledge into sound theory. Furthermore, the literature suggests that research has yet to develop a coherent description of the process of decision- making; and the need for research that informs practice to enhance the decision-making process of managers to enable decisions and their outcomes to be successful (Nutt, 2011).

The research contributes to this field of literature by exploring the decision-making processes of African leaders in relation to the succession of the Kyoto Protocol within the Framework Convention on Climate Change with the United Nations organisation.

Since the 1950’s theories surrounding the art of decision-making has been an active area of research in several fields such as management, economics, statistics, psychology, and engineering. For example, decision theory is an area of discrete mathematics that models human decision-making. As a result decision theory has become a useful tool to many professionals, such as, in the social science and management arenas. Furthermore, because decisions are made at all levels of an organisation it is not surprising that it has continued to attract the attention of leaders, management academics, social science researchers and consultants, (Huczynski and Buchanan, 2007).

Two common tenets of Decision Theory are ‘normative’ or ‘prescriptive’ and ‘positive’ or ‘descriptive’. ‘Normative Decision Theory’ is concerned with identifying the best decision to make, in other words what decisions ‘should’ we make, whilst ‘Descriptive Decision Theory’ describes ‘how’ decisions are made, that is, what people actually do, and as such, allows for further tests of the kind of decision-making that occurs in practice.

This research addresses how a group of African leaders make decisions on Climate Change adopting the ‘descriptive’ approach to decision-makingbased on the Bounded Rationality Model. The model is used to examine the decision-making processes of African leaders in an international setting, i.e. within the United Nations organisational system, more specifically, the Framework Convention on Climate Change. Research to date has revealed that due to the poor decision-making of African nations in relation to climate change, this has had an immense detrimental impact on these nations (Onyema, 2010).

According to Mallard (2012) the term ‘Rationality’ refers to the ability of individuals to make optimal decisions based on information available to them. The information may be currently available, in the past or future. ‘Global Rationality’, is also known as ‘Objective Rationality’ on the other hand relates to an individual’s ability to identity and absorb all the relevant information present to address the challenge faced, processing it to ensure that the given objective function is maximised (Mallard, 2012). The concept of ‘Bounded Rationality’ stems from the Theory of Rationality, as a contrary argument to the theory (Mallard, 2012).

The concept of Bounded Rationality is accredited to Herbert Simon (1957). A crucial premise of the theory argued by Simon (1957) is that

…’ the capacity of the human mind for formulating and solving complex problems is very small compared to the size of the problems whose solutions is required for objectively rational behaviour in the real world – or even for a reasonable approximation to such objective rationality’ (Simon, 1957:197).

According to Simon (1957) the notion of decision-making is contrasted with the more classical notion of decision-making used in economics. Economics uses a model of behaviour where behaviour is explained by individuals maximising their utility based on fixed preferences that are only influenced by price and income (Gsottbauer and van den Bergh, 2012). In essence, economist assumes that decision makers are rational in all circumstances (Ibrahim, 2009). However, behavioural economics offers an alternative elucidation based on recognising ‘Bounded Rationality’ and limited self-interest. Simon (1957) contends that while individuals gather, analyse and retrieve information from memory, their ability to make meaningful inferences is limited due to a number of inherent factors. These factors include the complexity of the external environment, the limited mental capabilities of individuals in comparison with the demands of the environment, and resource constraints in terms of time and budgets. As such, decisions are made under conditions of extreme uncertainty and these decisions are made only in an ‘intendedly’ rational manner.

According to Mallard (2012) the incorporation of ‘Bounded Rationality’ into the field of economic analysis has produced

‘…a more realistic and powerful behavioural assumption into economic theory’ (Mallard, 2012: 674).

However, Mallard (2012) also suggests the need to explore how ‘Bounded Rationality’ can be used in different contexts and how it can be used in the literature to model group or intra- organisation decision-making as this presents a gap in the literature. Other researchers such as Nutt, 2011; Nutt and Wilson, 2010; Brown et al (2009) and Basov (2005) support this view.

A good understanding of decision-making is essential to explain how decisions are made and the processes involved in decision-making (Mallard, 2012). The degree of rationality in decision-making has been widely recognised as one of the key dimensions of strategic decision-making and has been the subject of copious theoretical and empirical investigations within the literature (Dean and Sharfman, 1993; Eisenhardt and Zbaracki, 1992; Elbana, 2006; Wilson, 2003; Nutt and Wilson, 2010; Nutt, 2011).

However, to date researchers have revealed that there have been radical changes to how strategic decision-making has been researched (Nutt, 2011). For instance, according to Nutt (2011) in the 1950’s and 60’s a planning approach to decision-making was accentuated based on portfolio matrices. Yet, in the 1970’s decision-making focused on payoffs to organisations based on alternative strategic options being adopted. These options included diversification, acquisition, joint ventures and internationalisation decisions. The following decade, more specifically the 1980’s involved the move from the content of strategic decisions to the processes involved in making decision-making. In this era, researchers attempted to explore the stages of a strategic decision and make inferences about the processes as to why and how they occur (Hickson, 1986).

Notwithstanding, from the 1990s to date, interest has been growing amongst researchers in unfolding the characteristic of decision-making processes and more recently on the relationship between decision-making and decision outcomes (Nutt et al, 2010). For example, in terms of outcomes, the curiosity now is in exploring whether the decision succeeded or failed (Nutt, 1999, 2002; Hickson et al 2003). This recent trend is also validated by Jarzabkowski and Wilson (2006) who assert that:

‘…much of the traditional strategic decision-making theory has been criticised because it is not actionable in practice’ (Jarzabkowski and Wilson, 2006:46).

Another important aspect of strategic decision-making in the literature is the ‘situation’ of the decision (Jarzabkowski, 2005). This forms an important part of the understanding of decision-making. The term ‘situation’ or ‘situated’ identifies the relational nature of the actors with the ‘situations’ being the ‘context’ in which they operate. In other words, the action by a leader or manager must be seen and understood in the context of the situation in which the action occurs (Nutt, 2010). Researchers have argued that context influences choices, the benefits realised and the processes applied in decision-making (Nutt, 1998, Bell et al, 1998).

These arguments are applicable in the current research, as it explores the decision-making processes of African leaders using the model of ‘Bounded Rationality’ in the contextual situation of the United Nations Climate Change Conference negotiations in relation to the succession of the Kyoto Protocol in Copenhagen, Denmark in 2009. The exploration of the decision-making processes enabled a better understanding of how decisions were made in relation to the outcome, i.e. the Copenhagen Accord.

Additionally, researchers in strategic decision-making have long argued and re-iterated that the current focus of strategic decision-making research should centre on the following themes aspects of which are applicable in this study:

Increasing the focus of outcomes in order to increase managerial relevance;

Explaining the influence of the broader context on strategic decision-making processes and outcomes; for example the organisation, the specifics of the decision, planning systems, national culture, and corporate governance;

Integrated research to bridge the gap between strategy process and strategy content;

The inclusion of CEOs and top management teams in strategic decision-making research;

In-depth research on strategic decision-making as it relates to learning, implementation and Information Systems (Papadakis et al, 2010).

Furthermore, national culture is another key area that researchers have argued for in research in strategic decision-making. For instance, according to Nutt (2011) the majority of research on strategic decision-making comes from the USA. Yet, in an era of increased globalisation, it is important managerially as well as scientifically to investigate how closely the various concepts, theories and results apply to strategic decision-making in other nations (Nutt, 2011).

Whilst numerous articles were reviewed in the relevant fields relating to the research, more specifically, the extensive relevant studies identified and comprehensively reviewed by the researcher on strategic decision-making is shown in Table 1 below. The articles were drawn from the years 1998 to 2012 and reflect the various studies appearing in the strategic decision-making literature; however, only one study on strategic decision-making is based in Africa. This study investigates 169 strategic decisions of Egyptian manufacturing firms employing more than 100 employees. The research was undertaken using a cross-sectional field study using both qualitative and quantitative methods. The study concludes that rationality is shaped by decisions relating to environmental and firm characteristics (Elbanna and Child, 2007).

According to researchers strategic decisions are intentionally made and implemented resulting in strategic action of one form or another (Ericson, 2010). Conversely, when engaged in complex and contentious situations, leaders tend to address conflicting decisions through an array of political tactics, i.e. alliances, the use of experts, limiting the availability of information, etc. to build allies and/ or a strong power base in order to peruse their particular decision of interest (Eisenhardt and Bourgeois, 1998; Pettigrew, 1992). In these situations, the leader controlling the information has the power to exert influence on the decision making-process (Ericson, 2010). Similarly, ‘Bounded Rationality’ can involve behavioural inconsistencies when leaders are faced with choices under risk and uncertainty, intertemporal choice and other unpredictable actions in decision-making.

In addition, some researchers argue that an individual can be rational when faced with the influences of power and/or politics in decision-making, however in a group of individuals made of these same individuals this is not usually the case (Pfeffer, 1992). Pfeffer (1992) argues that in these situations, emphasis is on resolving conflict and using tactics such as coalitions, information control and influence to arrive at a decision (Pettigrew, 1973).

Limited research has been undertaken in observing ‘Bounded Rationality’ and ‘Environmental Policy’ research (Gsottbauer and van den Bergh, 2012). Research that has been undertaken has been from an environmental perspective, rather than from a social science or management standpoint.

Today, the most important area of environmental policy making is climate change, more specifically the reduction of greenhouse gases, mitigation and adaptation (Gsottbaur and van den Bergh, 2012). According to Gssottbaur and van den Bergh (2012) most proposals for climate change policy rests on the assumption of rational behaviour in strategic decision-making.

Table 1 Literature review of various studies in the Strategic Decision-making literature from 1998 – 2012

No

Author(s)

Date(s)

Sample

Design / Sources of Information

Analyses

Linkage(s)

Main Findings

Brenes et. al (2008)

2008

81 firms operating in Latin America.

Survey research, Cross-sectional.

Descriptive Statistics

4, 3, 6.

Strategic formulation process, CEO leadership, systematic execution, and strategy control and follow-up influence the successful implementation of business strategy.

Elbanna and Younies (2008)

2008

As that of Elbanna and Child (2007a).

As that of Elbanna and Child (2007a).

PCA

12.

Decision makers can be simultaneously rational, political, and / or intuitive.

Miller (2008)

2008

79 US firms from various industries.

Survey research, cross-sectional, multiple respondents’ performance is measured with archival data.

Multiple Regression

5B, 2B.

In non-turbulent environments comprehensiveness and performance exhibit an inverted U-shaped relationship while in turbulent environments there is appositive relationship that is concave downward based on diminishing effects.

Nutt (2008)

2008

202 strategic decisions in US and Canadian firms.

Field study, longitudinal, multi-method, multiple respondents.

ANOVA,

MANOVA

5A, 7A.

Controlling for context and content (based on the type of decision), discovery processes lead to more successful strategic decisions than idea imposition, redevelopment, and emergent opportunity processes.

Nooraie (2008)

2008

44 firms operating in Malaysia.

Survey research, cross-sectional.

Hierarchical Regression

5A, 1A.

Rationality mediates the relationship between decision magnitude of impact and decision satisfaction. There is a positive relationship between decision magnitude of impact and decision rationality.

Walter et. al (2008)

2008

106 strategic alliances from high-technology US firms.

Survey research, cross-sectional.

CFA for scales and Multiple Regression

5A, 2A, 7A.

The relationship between alliance performance and processes (rationality, openness, recursiveness) is moderated by micro political context.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

Elbanna and Child (2007a)

2007a.

169 strategic decisions from Egyptian manufacturing firms, employing more than 100 employees.

Field study, cross-sectional, utilises

both qualitative and quantitative approaches.

Hierarchical Regression and PCA

1A.

Rationality is shaped by decision, environmental and firm characteristics.

Elbanna and Child (2007b).

2007b.

As that of Elbanna and Child (2007a).

Field study, cross-sectional, utilises

both qualitative and quantitative approaches

Hierarchical Regression and correlations

5A, 2A, 7A.

Rationality and political behaviour influence strategic decision effectiveness more than intuition. This relationship is shaped by decision, environmental and firm characteristics variables.

Martinsons and Davison (2007)

2007.

133 Americans, 82 Japanese and 88 Chinese top managers.

Multi-method (questionnaires and interviews), cross-sectional.

Pairwise t-tests.

1B.

Executives from the three countries have distinct decision-making styles.

Mueller et al. (2007)

2007.

42 undiversified US manufacturing firms.

Survey research, cross-sectional, multiple respondents.

Hierarchical

Regression

5B, 2B, 7B.

The elements of rationality are related to firm performance (ROA). Environmental dynamism moderates this relationship.

Nutt (2007)

2007.

As that of Nutt (2000a).

Field study, longitudinal, multi-method, multiple respondents.

ANOVA

5A.

Performance Gapping and Premising influence the search approach that managers use to uncover alternatives.

Olson, Boo, and Parayitam (2007)

2007.

252 Chinese managers.

Survey research, multiple TMT responses.

Hierarchical Regression

2A, 5A.

Cognitive diversity has a positive relationship with decision commitment and quality. This relationship is moderated by affect-based and cognition-based trust.

Olson, Parayitam and Yongijian (2007)

2007.

85 Top Management Teams from US hospitals.

Survey research.

CFA and SEM

2A, 5A.

Cognitive diversity has a positive relationship with task conflict. Task conflict mediates the relationship between cognitive diversity and decision outcomes.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

Papadakis (2006)

2006.

107 Strategic Decisions from 59 manufacturing firms operating in Greece.

Field study, cross-sectional, multiple sources.

Hierarchical Regression.

1A.

Broader context is more influential than the characteristics of the CEO. CEO’s demographic characteristics appear to influence some process characteristics, while personality characteristics exert no influence.

Carr (2005)

2005.

28 UK, 35 German, 14 US and 13 Japanese vehicle component firms.

Interviews, longitudinal.

Content Analysis.

1B.

Institutional and cultural factors have a profound effect on the style of decision-making.

Forbes (2005)

2005.

98 Internet start-up firms from the ‘Silicon Alley’ Community.

Field study, cross-sectional.

T-tests and OLS regression.

2A, 5A.

Firms managed by older and experienced managers make faster strategic decisions.

Goll and Rasheed (2005)

2005.

159 manufacturing firms operating in the USA.

Rational decision making was measured based on a survey, while all the other variables are archival, multiple TMT responses.

Multiple Regression

1B, 2B, 5B, 7B.

Top Management Team demographic characteristics (age, tenure) influence the degree of rational decision making. Environmental munificence moderates the relationship between rational decision making and firm performance.

Hough and Ogilvie (2005)

2005.

749 Executives.

Simulation

SEM

5A, 7A.

Cognitive style influences decision outcomes.

Nutt (2005)

2005.

As that of Nutt (2000a).

As that of Nutt (2000a)

ANOVA,

MANOVA

5A.

A rational, goal-oriented search is more apt to produce more successful outcomes.

AtuaheneGima and Li (2004)

2004

373 Chinese firms involved in technological ventures.

Survey research, cross-sectional, multiple TMT responses.

CFA and Hierarchical Regression

5A, 2A, 7A.

The relationship between strategic decision comprehensiveness and new product performance was negatively moderated by technology uncertainty but positively moderated by demand uncertainty.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

AtuaheneGima and Murray (2004)

2004.

149 US manufacturing firms.

Survey research

CFA and Hierarchical Regression

1A, 5A, 2A, 7A.

Marketing strategy comprehensiveness is influenced by organisational and environmental factors. The relationship between marketing strategy comprehensiveness and product performance is positively moderated by implementation speed and technology uncertainty and negatively by market uncertainty.

Collier et al. (2004)

2004.

6394 managers attending an executive course in a UK university.

Survey research, cross-sectional.

Correlations

4,6.

There is a positive relationship between involvement in strategy-making and rationality and a negative one between involvement and politics.

Miller et al. (2004)

2004.

As that of Hickson et al. (2003)

As that of Hickson et al. (2003).

PCA and Correlations

2A, 4, 6.

Managerial experience and organisational context (structure, culture) influence the successful implementation of strategic decisions.

Sadler – Smith (2004)

2004.

141 firms operating in the UK.

Survey research, cross-sectional, performance is measured with archival data.

Correlations, Hierarchical Regression

5B, 2B, 7B.

Intuition is positively related to firm performance. Environmental instability does not moderate this relationship.

Walters and Bhuian (2004)

2004.

89 acute-care hospitals operating in the USA.

Survey research, cross-sectional, objective and subjective measures of performance.

SEM

10,11,2B,

5B, 7B.

Environmental dynamism positively moderates the relationship between comprehensiveness and performance and hybrid strategy and performance.

Baum and Wally (200

2003.

318 CEOs of US firms.

Survey research, cross-sectional, multiple respondents, subjective measures of performance

SEM

2A, 9,2B.

Strategic decision speed is influenced by a multiplicity of organisational and environmental factors and moderates the relationship between dynamism, munificence centralization, formalization, and firm performance.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

Hickson et al. (2003).

2003.

55 UK firms.

Case study design, longitudinal.

PCA and Multiple Regression

2A, 4, 6.

Planned and prioritized options influence the success of strategic decisions.

Hough and White (2003).

2003.

400 decisions.

Simulation.

ANOVA, correlations and logistics regression

5A, 2A, 7A.

Environmental dynamism moderates the relationship between rational decision making and decision quality.

Papadakis and Barwise (2002).

2002.

As that of Papadakis et. al (1998).

As that of Papadakis et al. (1998).

Hierarchical Regression

1A

TMT and CEO influence the strategic decision-making processes, but the former has more influence.

Covin et.al (2001).

2001.

96 manufacturing firms in South-western Pennsylvania.

Field study, cross-sectional,

multiple sources, performance is measured with archival data.

Multiple Regression

5B, 2B, 7B.

The relationship between decision-making style and organisational performance is moderated by environmental and technological sophistication.

Brouthers et. al (2000).

2000.

42 Dutch financial institutions.

Field study, cross-sectional,

survey research.

Multiple Regression

1B.

Strategic aggressiveness is shaped by environmental and management factors.

Khatri and Ng (2000).

2000.

221 US companies drawn from three sectors (computers, banks and utilities).

Survey research, cross-sectional and subjective measure of performance.

ANOVA and Regression Analyses

5B, 2B, 7B.

A positive relationship exists between intuition and firm performance in an unstable environment and a negative in a stable one.

Nutt (2000a).

2000a.

376 Strategic decisions in US and Canadian firms.

Field study, longitudinal, multi-method, multiple respondents.

ANOVA, Duncan Test

1A.

Public, private and third sector organizations follow different tactics to uncover alternatives.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

Nutt (2000b).

2000b.

As that of Nutt (1998b).

As that of Nutt (1998b).

Multiple Regression and Duncan Test

5A, 2A.

Decision makers use nine tactics (e.g. bargaining, judgment, analysis) to uncover alternatives.

Gottschalk (1999).

1999.

190 Norwegian firms.

Survey research, cross-sectional.

Multiple Regression

4.

There is a positive relationship between planning and implementation.

Papadakis et. al (1999).

1999.

A Greek chemical firm.

Qualitative longitudinal.

Content Analysis

1A.

The categorization of an issue (i.e. crisis, opportunity) influences the processes followed.

Simons et al. (1999).

1999.

57 Top Management Teams from 57 electronic components manufacturing US firms.

Survey research, multiple TMT responses.

Hierarchical Regression

5B.

Comprehensiveness mediates the interactive effects of diversity and debate on firm performance.

Brouthers et. al (1998).

1998.

90 Dutch Firms.

Survey research, Cross-sectional.

Descriptive Statistics

1B.

Executives of small firms tend to rely more on intuition.

Chou and Dyson (1998)

1998.

80 Strategic Investment Decisions from Taiwanese firms.

Survey research, cross-sectional.

PCA and Correlations

2A, 1A.

IT intensity in the investment project in negatively related to the effectiveness of SDs and to several process characteristics (duration, interaction, involvement).

Goll and Sambharya

(1998)

1998.

92 large US manufacturing firms.

Survey research, cross-sectional, performance is measured with archival data.

Multiple Regression

5B, 8.

Diversification strategy acts as a mediator in the relationship between rational decision making and firm performance.

Kim and Mauborgne (1998)

1998.

Interviews with 48 senior executives from 8 firms (Round 1).

Qualitative design.

Content Analysis

4, 5A.

A sense of procedural justice among the team enhances the right execution of strategic decisions.

No

Author(s)

Dates

Sample

Design/ Sources of Information

Analyses

Linkage(s)

Main Findings

Miller et al. (1998)

1998.

Study1: 38 CEOs of USA firms operating in various industries.

Study 2: 108 CEOs from hospitals in Texas.

Study 3: TMT responses for 71 companies in various industries in the USA.

Survey research, cross-sectional.

Multiple Regression

1B, 5B.

Comprehensiveness and extensiveness of strategic planning are negatively related to Top Management Team cognitive diversity. Firm performance is positively related to both comprehensiveness and strategic planning. Also, an indirect relationship exists between executive diversity and firm performance.

Nutt (1998a)

1998a.

376 Strategic decisions in US and Canadian firms.

Field study, longitudinal, multi-method, multiple respondents.

Duncan Test, Chi-square

6.

4 distinct implementation approaches (i.e. intervention, participation, persuasion, and edict). The first two seem to lead to more successful decisions that the last two.

Nutt (1998b)

1998b.

317 Strategic decisions in US and Canadian firms.

Field Study, longitudinal, multi-method, multiple respondents.

ANOVA, Duncan Test

5A.

Political tactics although rarely used are quite effective. Judgmental tactics (intuitive) have the poorest success record. Analytical tactics are most widely used and successful in most of the cases.

Papadakis et. al (1998)

1998.

70 Strategic decisions form 38 manufacturing firms operating in Greece.

Field study, cross-sectional, multiple sources.

Multiple Regression and PCA

1A.

Decision processes are shaped by multiple factors, though decision-specific characteristics have the most important influence.

Papadakis et. al (1998)

1998.

As that of Papadakis et. al (1998).

As that of Papadakis et. al (1998), both objective and subjective measures of performance.

Correlations

1A.

Long-term performance is related more to ‘structural’ characteristics of SD processes (rationality, financial reporting) while short-term performance is related to more ‘behavioral’ characteristics of SDs.

Source: Nutt and Wilson (2010).

Figure 2 Linkages between the literature research areas in Table 1 in relation to strategic decision making

Source: Nutt and Wilson (2010)

The explanation of the various linkages in relation to the various studies identified in Table 1 is given below:

Linkage 1A: Context influences on the process of making strategic decisions (decision level).

Linkage 1B: Context influences on the process of making strategic decisions (organisational level).

Linkage 2A: Context influences on the success of strategic decisions (decision level).

Linkage 2B: Context influences on organisational performance (organisational level).

Linkage 3: Context influences on implementation.

Linkage 4: The relationship between formulation and implementation.

Linkage 5A: Process influences on the success of strategic decisions (decision level).

Linkage 5B: Process influences on organisational performance (organisational level).

Linkage 6: Implementation influences on outcomes (organisational and decision level).

Linkage 7A: Moderating effects of context variables on the relationship between process and decision success.

Linkage 7B: Moderating effects of context variables on the relationship between process and organisational performance.

Linkage 8: The relationship between process and content.

Linkage 9: The relationship between decision process outcomes and organisational performance.

Linkage 10: Content influences on organisational performance.

Linkage 11: Moderating effects of context variables on the relationship between content and outcomes (organisational and decision level)

Linkage 12: The relationship between the characteristics of the strategy process.

2.3 What does decision-making really mean?

As discussed in Section 2.2, decision-making has a long history surrounding a diverse number of perspectives, philosophical positions and prescriptions. Over the years there have been various debates about the possibilities and practices of effective strategic decision-making, the significance of strategic decision-making for other aspects of organisational functioning, the links with power in organisational settings and whether the concept has any real efficacy (Miller et al, 2006). To this extent, the term decision-making is first defined before the terminology strategic decision-making. Decision-making has been defined in numerous ways, the most common definition of the term

...‘is to make a judgement of what an individual should do in a certain situation after deliberating on some alternative course of action’ (Ofstad, 1961:5).

Likewise, Stoner et al (1994) defines decision-making as the

‘…process by which a course of action is selected as the solution to a specific problem’ (Stoner et al, 1994:132).

Adair (1999) defines decision-making as deciding what action to take usually involving a choice between different alternatives, while Mele (2010) contends that decision-making is a process in which a problem is defined and the decision maker structures one or more objectives to solve the problem. Other researchers consider decision-making and problem solving as activities that are in synergy with one another, an argument that is not held by all researchers. For instance, Lang et al (1978) argues that whilst some researchers view problem solving as a broad process that includes decision-making, others accept that problem solving is an element of decision-making.

The researcher maintains that decision-making may be part of the decision-making problem solving process up to the stage of implementation. This is because no decision needs to be made but there are significant steps in assessing whether the decision and outcome of the decision is effective.

There is no doubt that decision-making is an important topic especially in today’s current turbulent environment. According to Adair (1994) the ‘actual moment’ of a decision cannot be studied, therefore the process of decision-making is what needs to be understood. Adair (1994) further postulates that the outcome of a decision in terms of its success or failure is dependent on both the decision itself and the effective implementation of the decision.

Other researchers such as Kania (2008), argue that good decision-making needs data collection, analysis, action planning, implementation and evaluation concluding that a good decision will not adhere to just one approach but consider several methods. This view is also held by Hoy and Tarter (2010) stating:

‘…there is no best way to make decisions, in fact, a large part of the art of successful decision-making rests with the notion of matching the correct model of decision-making with the appropriate situation’ (Hoy and Tarter, 2010:351)

For the purpose of the research, a decision is defined as ‘a moment in an on-going process of evaluating alternatives for meeting an objective, in this case, the succession of the Kyoto Protocol, at which expectations about a particular course of action impel the decision maker to select that course of action most likely to result in stating the objective’ (Harrison, 1999). Decision-making on the other hand, is defined as ‘the process of making choices from amongst several options or alternatives (Huczynski and Buchanan, 2007).

Strategic decision making are those that are made at the helm of the organisation and have a wide impact both internally and externally (Xxx)

2.3.1 Arguments for the Descriptive Models of Decision-making

Decision-making is a multifactor, multi-dimensional process that often requires the processing of information. As research has evolved, the distinction between descriptive and normative theories has become unclear (Dillion, 2007). Earlier researchers, Luce and von Winterfeldt (1994) postulate that the gap between ‘descriptive’ decision-making – what we are observed to do and ‘normative’ decision-making - what we should do, is extensive and has widened in recent years.

Normative theories have been refined so that they better ‘describe’ decision-making, e.g. Prospect Theory (Kahneman and Tversky 1979), Subjective Expected Utility (Von Neuman and Morgenstein, (1947). Similarly, descriptive theories have sought to introduce normative axioms; examples include the Advantage Model (Shafir, Osherson, and Smith, 1993). However, it is important that the distinction between the descriptive and normative models remains clear (Dillon, 2007). From a practitioners perspective the distinction acts as a useful reference point when attempting to improve managerial decision-making (Dillion, 2007). More recently, a third classifier has been introduced which better describes models such as the Advantage Model and the Prospect Theory, known as the ‘PrescriptiveModel’.

The ‘Prescriptive Model’ is one which can and should be used by a real decision maker and is tuned to both the specific situation, and needs of the decision maker. According to Dillon (2007) prescriptive models are based on both strong theoretical foundations of normative theory in combination with the observation of descriptive theory. The differences between the models of decision-making are highlighted in Figure 3 below.

Figure 3 Basic Models of Decision Making

1

Source: Dillon (2007); Descriptive Decision-making: Comparing Theory with Practice, Department for Management Systems, University of Waikato, New Zealand

Simon (1977) proposed a three phase trichotomy of decision processes namely, ‘Intelligence’, ‘Design’ and ‘Choice’ as illustrated in Figure 4 below.

Figure 4Simon's Model of Decision Making

Source: Simon, H. A (1977); ‘The New Science of Management Decision’, Prentice Hall, New Jersey, Revised Edition

Intelligence involves identifying the need for a decision. Once the need for a decision has been identified, the design phase commences which involves investigating and developing the problem domain and alternatives. According to Simon (1977) the final stage in the decision-making process is choice, which describes the activity of selecting the most appropriate course of action from the alternatives previously generated.

Huber (1980) distinguishes decision-making from ‘choice making’ and ‘problem solving’. Huber (1980) argues that ‘choice making’ refers to the narrow set of activities involved in choosing one option set from another set of alternatives. Choice making is one part of decision-making, while ‘problem solving’ refers to the broad set of activities involved in finding and implementing a course of action to correct an unsatisfactory situation (Huber, 1980). Decision-making incorporates both these components and a decision process can therefore be defined as:

‘…a set of action and dynamic factors that begins with the identification of a stimulus for actions and ends with a specific commitment to action’ (Mintzberg et al, 1976:251).

Plunkett and Hale (1982) stress that decision-making is not an art but a process, the most important part of the process is the identification of worthwhile actions to undertake (Nutt, 1983). As such, Nutt (1983, 2011) therefore defines a decision process as:

‘… a made up stream of action taking steps that begins with claims by stakeholders drawn from signals that seem important and end with a decision being adopted’ (Nutt, 1983:14)

Due to the complex nature of decision-making, various studies have attempted to explain the decision-making process. Examples include Simon (1977 cited by Knapp and Zupancic, 2007) stating that:

‘…decision-making comprises of four principal phases which are; finding the occasion for making a decision; finding possible courses of action; choosing among those courses of action and evaluating past choices’ Simon (1977 cited by Knapp and Zupancic, 2007:527).

The section below attempts to simplify the numerous processes involved in decision-making. No single analyses manage to incorporate all possible variables of decision-making. An alternative method researchers have taken to examine decision-making is to deconstruct the process into separate stages as illustrated in Figure 5 below.

2.3.2 The Decision-making Process

‘Decision-making is a process of making a choice from a number of alternatives to achieve a desired result’ (Eisenfuhr, 2011:2). Notably, leaders make a variety of decisions each day. These decisions can affect a limited number of individuals within an organisation or a wide range of people across continents. These decisions can be present from a few seconds to a few days or in the future, from a few weeks to many years. Furthermore, in the context of organisations such as the UN, a group of members consisting of representative countries, referred to as member states makes organisational decisions which impact the world, rather than individuals. On such basis, decision-making can be described as a social process whose outcomes are usually dispersed amongst an array of organisational members (Chen, Lawson, Gordon and McIntosh 1996: Gioffre, Lawson and Gordon 1992; Offermand and Gowing 1991; Sniezek and Henry 1990).

As previously stated, Figure 5 below illustrates the stages of decision-making which includes both process and outcome. Lawson and Shen (1998) argue that organisational decision-making usually arises within turbulent, cacophonous or high velocity environments in which change is ever present. The numerous challenges faced by leaders worldwide due to the impacts of climate change are a point in time. World leaders and governments have to make decisions to adjust and invest in policies, programmes, projects and other initiatives that reduce CO2 emissions to reduce the impact of climate change. The decision-making process within the UN is discussed in more depth in the subsequent chapter.

Figure 5 The Decision-making Processes

Source: Compiled by the Author from the works of Stoner, Yetton, Craic and Johnston (1994)

Decision-making usually commences with the identification of an opportunity also known as ‘anticipatory decision-making’ or a problem i.e. ‘reactive decision-making’. The challenges posed by climate change are reactive despite an aspect of anticipatory decision-making in terms of making decisions to lessen the impact of climate change. To date, some of the impacts of climate change are being mitigated by implementing various ‘green initiatives’ i.e. tree planting and other environmental friendly programmes, such as the Clean Development Mechanism (CDM) – a carbon trading scheme between rich and poor nations.

Generally, the more closely the decision-making group is to the real time data (Lawson and Shen, 1998) the more likely they are to identify opportunities (such as technology transfer, new markets, organisational processes) rather than focus on problems defined by historical or forecasted data sets. Thereafter the decision-making group needs to determine if the focal situation is an important opportunity or problem that requires attention and action.

Using the decision-making diagram above, Stages 3 and 4 can be completed quickly or slowly depending on the decision maker’s level of tolerance for risk. In considering different alternatives climate change decision makers are now focusing on implementation issues, so there is a clear linkage between the process and outcome components (UN, 2010).

In stages 5 and 6 there is a shift to what may be called the right-to the-left thinking in that the goal or anticipated outcome of the decision is now clearly stated and attention is given to plans of action that outline what specifically needs to be undertaken. This right-to-left thinking increases the anticipation of the barriers and the development of strategies to deal with them. Once a decision is implemented, it is important to monitor the outcome measures such as improved quality, reduced environmental impact, reduced costs, shorter delivery timescales, environmental programme performance, etc. (Nutt and Wilson, 2010). The outcome measures need to be determined and undertaken carefully including an appropriate feedback loop. However, Lawson and Shen (1998) argue that without systematic feedback it is impossible to determine the overall effectiveness of the decision-making process.

Furthermore, leaders often have to vary their approach to decision-making depending on the particular ‘situation’ in question (Stoner et al, 1994). Simon (1997) assumes that decisions can be classified as either programmed or non-programmed.

Lawson and Shen (1998) ascertain that programmed decisions usually involve highly repetitive and routine problems in which the procedures for decision-making are well established, applied frequently, easily triggered and requires immediate action. Similarly, Simon (1977) suggests that in programmed decision-making the focus is on the implementation of the decision with the first steps highly standardised as represented in operating manuals and standard operating procedures.

Nutt (2010) also suggested that programmed decisions are made in routine, well-structured situations using predetermined decision rules. The decision may be based on habit, statistical techniques or established policies and procedures that stem from prior experience or technical knowledge about what works in the particular situation.

In contrast, non-programmed decisions are used when predetermined decision rules are impractical, as in novel or ill-structured situations (Bass 1983).  Most significant managerial decisions are non-programmed and involve significant uncertainty (Bartol et al 1998; Lawson and Shen 1998; Robbins, Bergman, Stagg and Coulter 2000; Stoner et al. 1994).  Decisions made under these conditions involve risk (Bartol et al 1998; Lawson and Shen 1998; Robbins, Bergman, Stagg and Coulter 2000; Stoner et al. 1994) and the possibility of a chosen action leading to losses rather than the intended results.

Bromiley and Rau (2010) suggested that uncertainty stems from a variety of sources. For example, elements in the environment that are difficult to predict or control can affect the success of a decision and cost and time constraints can limit information collection. Bartol et al (1998) also point out that social and political organisational factors such as poor inter unit communication makes relevant information gathering difficult in such situations. Moreover, rapid situational changes render information quickly obsolete.

Furthermore, according to researchers, the proportion of non-programmed decisions that leader makes increases at each hierarchical level (Bartol et al 1998). Since these decisions require effective decision-making skills and creativity, they provide the biggest challenge to leaders. Larrick (1993) points out that preferences for risk or certainty arises not only from the perceived value of outcomes and their probability but more importantly the outcomes will enhance or erode one's self-esteem and efficacy as a decision maker.

In general, most leaders believe that they reason clearly, exercise sound judgement and make decisions rationally and logically. However, many researchers have identified a number of systemic errors and fallacies that leaders tend to commit when thinking and making decisions (Nutt, 2010).

For example, leaders are influenced by whether a choice is framed in terms of gains or losses. Similarly leaders often take risk because they do not necessarily assume that they will have to suffer the consequences of a ‘risky’ decision (Bromiley and Rau, 2010). Thus a leader’s choice is often unduly tilted in the direction of what they want or what they want to believe. Moreover, as previously stated, when making decisions leaders tend to over estimate how many other people agree with their attitudes and beliefs. According to Larrick (1993) a judgemental bias known as ‘false-consequence bias’ can modulate decision-making; as such, decision-makers need to appreciate both the rational, objective forces, the cognitive and affective forces that can shape a decision.

2.3.2 Models of Decision-making

The interdisciplinary aspects of decision-making are best illustrated within the framework of models. These models illustrate how much emphasis applicable disciplines receive in the strategic decision-making literature.  Moreover, models can represent a particular segment of the real world when placed under varying conditions (Nutt, 2010).    

Rice and Bishoprick (1971) defined models as follows:

'Models can be mathematical, social or philosophical. They can involve physical phenomena, emotional phenomena or in fact anything capable of theoretical analysis. Because they are used in theoretical analysis they have been many different models developed to explain the same or similar phenomena.  Each theoretical discipline, in examining an occurrence must develop its own model to explain it'. Rice and Bishoprick (1971:47)

Researchers have argued that there are four types of decision-making models (Kania 2008, Browne, 1993; Harrison, 1987). These models are the

Rationality Model or Rational Choice Model

Bureaucratic / Organisational Model

Political Model

Process models.  

A summary of these models are given in Table 2 below.

Table 2 Interdisciplinary Models of Decision-making

Model

Decision-making

criterion

Key aspects

Associated assumptions

Rational Model

(Classical)

Descriptive

Maximised outcome

Objectives: specific states of nature; subjective probabilities; quantified utilities; exhaustive alternatives; computational decision making strategy, short term horizon; highest structured process.

Fixed objectives unlimited information, no cognitive limitations, no time and cost constraints, quantifiable and controlled variables, closed systems; quantitatively limited outcomes.

Organisational

(Neoclassical)

Normative

Satisfying outcome

Objectives: General states of nature limited subjective probabilities; partially quantified utilities; non-exhaustive alternatives; sensitive environment; judgemental decision-making strategy: short-term horizon; moderately structured process.

Attainable objectives: Limited information; cognitive limitations; time and cost constraints; partially quantifiable and intransitive alternatives; open system; qualitatively and moderately quantitatively limited.

Political

(Adaptive)

Prescriptive

Acceptable outcome

Objectives: General states of nature; no probabilities; unquantifiable utilities; non-exhaustive alternatives; dominant environment; compromise or bargaining decision-making strategy; restricted numbers of outcome; short term horizon; incremental steps; loosely structured process.

Limited objective: Unlimited information; no cognitive limitations; no time and cost constraints; non-quantifiable and generally transitive alternative; open system; environmentally-limited.

Outcomes; no ‘right’ decision.

Process

(Managerial)

Normative

Objective oriented outcome

Objectives: general states of nature; generally subjective probabilities, objective-oriented utilities; exhaustive alternatives; sensitive to environment constraints; judgemental decision-making strategy with selective use of computation and compromise; long term horizon; limited number of outcomes; highly structured process.

Highly dynamic objective:

Limited information; time and cost constraints generally non-quantifiable and intransitive alternatives; open system; sequential decision-making functions; objective-oriented outcomes.

Source: Adapted form Harrison E. F. (1993); ‘Interdisciplinary Models of Decision-making’, Management Decision

Section 2.2 discussed the main tenants of strategic decision-making theory – i.e. ‘Descriptive’, ‘Prescriptive’ and ‘Normative’ which is also depicted in Table 2. The researcher’s choice and arguments for the descriptive model of decision-making is based on the fact that descriptive models describe the process of what leaders and managers actually do in decision-making (Dillon, 2007). The section below gives an overview of the various descriptive models of decision-making, concluding with the justification for the ‘Bounded Rationality Model’ as none of the other models were considered suitable for the phenomenon under investigation.

2.3.3 Descriptive Models of Decision-Making

Descriptive decision-making models vary by the extent to which they make trade-offs among attributes (Payne et al, 1993). According to Schoemaker (1980) a model is deemed Non-Compensatory if ‘surpluses’ on subsequent dimensions cannot compensate for deficiencies uncovered at an early stage of the evaluation process; since the alternative will have already been eliminated. In other words, models which eliminate alternatives through sequential comparison or assessment of their attributes are classified as being Non-Compensatory. Once these attributes have been disregarded based upon the single attribute evaluation, they cannot be assessed on any other attribute regardless of their performance on these subsequent attributes. Other researchers have argued on the contrary that being ‘Compensatory’ implies that a decision maker will ‘trade-off’ between a high value on one dimension of an alternative and a low value on another dimension (Payne, 1976).

The oldest descriptive theory is the ‘Satisfying Model’ which is closely linked to the idea of ‘Bounded Rationality’ (Simon, 1960). The theory posits that decision makers choose an alternative that exceeds some criterion or standard. This argument is centred on the fact that decision makers do not and cannot maximise in most situations. In other words, the ‘Satisfying Model’ entails choosing the first alternative that satisfies minimal standards of acceptability without exploring all possible alternatives (Nielsen, 2011). According to Simon (1997:141)

…. ‘Decision-making whether individual or organisational is concerned with the discovery and selection of satisfactory alternatives; only in exceptional circumstances is it concerned with the discovery and selection of optimal alternatives’’.

In the case of the current research, the Fiftieth ‘Conference of the Parties’ (COP15) of the UNFCCC aimed to establish a decisive legally binding agreement by the end of 2012 to succeed the Kyoto Protocol. The establishment of a legally binding agreement to reduce CO2 emissions to stabilize greenhouse gases to reduce the impacts of climate change is taken as the optimal outcome of the decision-making process. The concept of ‘Bounded Rationality’ is therefore considered more appropriate and is discussed in more depth in Section 2.4 below.

The ‘Garbage Can Model’ is another ‘Descriptive Model’ in response to organised anarchies also known as decision situations, characterised by three general properties: ‘Problematic Preferences’, ‘Unclear Technology’ and ‘Fluid Participation’ (Cohen et al, 1972). The theory postulates that within an organised anarchy, it is difficult to assign preferences to a specific decision problem due to the fact that the organisation consists of a loose, ill-defined group of ideas rather than a set of clear preferences. This model is fundamentally distinct from other descriptive theories, on the basis that when most decision situations occur, conventional practice is to determine the most appropriate action. Therefore, to understand processes within an organisation, one can view a choice opportunity as a ‘Garbage Can’ into which various kinds of problems and solutions are deposited by participants as they are generated (Cohen, et al, 1972). This model was deemed unsuitable for the current research in that this model does not take contextual factors into account. Rajagopalan et al (1993) maintains that despite the differences amongst the various models which have attempted to explain strategic decision-making, general propositions can be drawn about the likely influencing factors such as the internal organisation, context and environmental factors. Furthermore, mixing problems, solutions and decision participants results in interaction patterns leading to decisions which do not follow a logical process (Lunenburg, 2010).

A modern theory of the descriptive model of decision-making is the ‘Image Theory’ developed by Beach and Mitchell (1990). ‘Image Theory’ is based on the ‘Lexicographic Model’ discussed below, and the ‘Strategy Selection Model’ (Tversky, 1972). This model is a refinement and synthesis of existing ideas applied to real world decisions. The model attempts to describe two types of decision-making namely, ‘Progress Decisions’ and ‘Adoption Decisions’. Progress decisions relate to whether past decisions are being carried out whilst adoption decisions replace incorrect or unachievable decisions made previously (Tversky, 1972). Due to the changing nature and complexity of climate change and the decision-making processes within the UN organisation, this model was not considered appropriate for the current research. More specifically, whilst progress decisions are applicable within the UN system, once a decision has been adopted, these decisions are not usually ratified due to the global impact these decisions have on nations.

The ‘Conjunctive’ also known as the ‘Disjunctive Model’ is a combination of models and works by combining information. The model as proposed by a number of researchers (Coombs and Kao, 1955; Dawes, 1974; Einhorn, 1970) and aims to select a solution or a group of potential solutions from a list of alternatives. All alternatives which exceed some threshold or aspiration level become part of this group. Alternatives which do not exceed the level are eliminated. The model attempts to search for an adequate solution or solutions rather than the optimal solution.

Inconsistent CO2 emission reduction targets amongst member, mainly the developed nations and other signatory parties to the UNFCCC excluded the ‘Conjunctive Model’. In essence, this is based on the premise that currently there exists no common threshold in terms of CO2 reduction targets amongst member states to discuss available alternatives in terms of the succession to the Kyoto Protocol. The Convention text is neither linked with quantitative emission reduction targets nor with certain threshold values as the limit of the atmospheric GHG concentrations (UNFCCC 2006:21).

In the Lexicographic Model the decision maker should know the attributes which make up the alternatives and must be able to rank them in order of importance (Tversky, 1969). Each pair of alternatives is compared in terms of attributes beginning with the most important, until dominance over one solution over the other occurs. Tversky (1974) goes a step further and presents a probabilistic model of choice – the ‘Elimination By Aspects (EBA) Model’ which is related to the earlier ‘Lexicographic Model’ in that they both follow intra-dimensional evaluation strategies (Payne et al, 1993). Each alternative is viewed as a set of aspects which are sequentially evaluated.

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