A Model of Antecedents and Consequences of Intuition in Strategic Decision-making: Evidence from...

Long Range Planning 46 (2013) 149e176 http://www.elsevier.com/locate/lrp

A Model of Antecedents andConsequences of Intuition inStrategic Decision-making:Evidence from Egypt

Said Elbanna, John Child and Mumin Dayan

While management theorists have recently paid more attention to the use of intuition instrategic decision-making, there is still little empirical research on the subject. Examinationof potentially relevant contextual variables and outcomes is particularly lacking. This articleadvances our understanding by proposing and examining a model of antecedents andconsequences of intuition in strategic decision-making using partial least squares (PLS). Inaddition to intuition, the model consists of four antecedent variables (decision motive,decision uncertainty, company performance, and company size), two moderating variables(environmental uncertainty and hostility), one decision outcome (decision disturbance),and one control variable (rationality). A study of Egyptian manufacturing firms indicatesthat decision uncertainty and company size are related to the use of intuition; that intui-tion significantly influences decision disturbance; and that environmental hostility mod-erates the relationship between decision intuition and disturbance. The implications ofthese findings for strategic decision-making theory, for practice, and for further research,are discussed.� 2012 Elsevier Ltd. All rights reserved.

IntroductionThis paper proposes and examines a model of the contextual antecedents and consequences of in-tuition in strategic decision-making. It also incorporates rationality into the model. Executives whomake strategic decisions on the basis of intuition often have a hard time explaining the reasons fortheir particular decision choices (Covin et al., 2001). However, the presumption in favour of ratio-nality in decision-making has recently come to be questioned. For example, Miller and Ireland

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(2005) claim that many managers embrace intuition as an effective approach to strategic decision-making. Making decisions on the basis of intuition is increasingly viewed as a viable approach intoday’s business environment, because few strategic decisions have the advantage of complete, ac-curate and timely information. Similarly, Nutt (2002) suggests that a judgmental approach to mak-ing strategic choices is successful under certain circumstances, such as time pressure.

It is difficult to describe intuition but easier to recognize it (Sadler-Smith and Shefy, 2004). Re-cently, the conceptualization of intuition has received growing attention both among psychologistsand management theorists. Frantz (2000) sees intuition as a mental process but not a consciousanalytical-logical, step-by-step, and reasoned way of thinking. Eisenhardt and Zbaracki (1992) statethat intuition refers to incremental adaptations based on deep and intimate knowledge of the sit-uation faced by decision-makers. Intuition is a synthetic psychological function in that it appre-hends the totality of a given situation. It is often associated with having a hunch or a strongfeeling of knowing what is going to occur (Vaughan, 1979), without being able to express the ra-tionale behind this (Nutt, 1998). Parikh et al. (1994) observes that intuition could be a form of in-telligence which decision-makers can use when they cannot access rational processes.

Dane and Pratt (2007, p. 40) define intuition as “affectively-charged judgments that arise throughrapid, non-conscious, and holistic associations.” Mitchell et al. (2005, p. 667) define intuitionamong opportunity-seeking entrepreneurs as “the dynamic process by which entrepreneurial alert-ness cognitions interact with domain competence.to bring to consciousness an opportunity tocreate new value.” Miller and Ireland (2005) distinguish two forms of intuition in strategicdecision-making: holistic hunch, involving a synthesis of diverse experiences, novel combinationsof information, and a strong feeling of being right; and automated expertise, based on a combinationof situation-specific experiences, past learning, and a sense of familiarity. Khatri and Ng (2000) sug-gest that intuition is subconscious, complex and quick; but not coming from emotion and not nec-essarily a biased process. Drawing upon these various conceptualizations, we regard intuition as “amental process based on a ‘gut feeling’ as opposed to explicit, systematic analysis, which yields anintuitive insight or judgment that is used as a basis for decision making.”1

We argue that theoretical progress on the role of intuition in decision-making is difficult withoutadequate empirical examination. While management theory has recently paid more attention to in-tuition, there is limited research on the antecedents and consequences of intuition in strategicdecision-making (Ritchie et al., 2007).

Despite recent interest in intuition in management research, empirical work has lagged behind(Akinci and Sadler-Smith, 2012; Elbanna, 2006; Hensman and Sadler-Smith, 2011). Rather than ex-amining intuition empirically, scholars have instead advanced arguments concerning its conceptual-ization, role, antecedents and outcomes (e.g., Dane and Pratt, 2007; Sinclair and Ashkanasy, 2005).

Theoretical progress on the antecedents and consequences of intuition in decision-making is difficultwithout adequate empirical examination.

Other authors have suggested that top executives use intuition in strategic decision-making (e.g.,Sadler-Smith and Shefy, 2004) and strategy workshops (e.g., Hodgkinson et al., 2006), but withoutinvestigating whether contextual variables influence its use or the impact of intuition on decision orstrategy outcomes.

In one of the very few robust applied studies which have addressed the role of intuition in stra-tegic decision-making, Khatri and Ng (2000) examined the impact of intuitive synthesis on orga-nizational performance. Sadler-Smith (2004) replicated and extended their study by investigatingthe impact of both rationality and intuition on the performance of SMEs. Ritchie et al. (2007) testedthe relationship between chief executives’ intuitive decision style, and financial measures of non-profit organization performance. This present paper extends previous work by investigating poten-tial contextual antecedents of intuition in strategic decision-making as well as the impact of

1 The authors thank one of the two anonymous reviewers for bringing their attention to this definition.

150 A Model of Antecedents and Consequences of Intuition in Strategic Decision-making

intuition on decision outcomes. Its focus complements previous work and enhances our under-standing of the use of intuition in strategic decision-making. In so doing, we followed Sadler-Smith (2004) in building upon Khatri and Ng’s work by including rationality as a control variablein our research model.

We argue in this paper that the use of intuition in strategic decision-making cannot be fully un-derstood unless the context and consequences of the decision-making are taken into account. Theterm “context” in the present study encompasses three categories of variables: decision-specificcharacteristics; characteristics of the firm itself that may be antecedents of intuition; and featuresof the external environment that could be moderators of the relationship between intuition anddecision consequences. This is not to deny the potential relevance of other factors for relianceon intuition, such as decision-maker personality, but rather to maintain that context deservesmore attention than it has hitherto received. Any examination of strategic decision intuitionthat fails to consider these contextual factors and their possible impact is likely to provide an in-complete and potentially inaccurate picture. This is because factors such as decision motive andcompany performance can be expected to influence the use of intuition in several ways. For in-stance, they affect the imperative that strategic decision makers may face to “get the decisionright,” through applying a careful and rational analysis rather than relying on intuition. On theother hand, a lack of clarity concerning relevant environmental conditions or the likely outcomesof a decision could limit the perceived relevance of rationality and instead favour a reliance onintuition.

Previous studies by Dean and Sharfman (1993), Elbanna and Child (2007a), and Papadakis et al.(1998) have adopted integrative models that take some account of the context. However, they havefocused on rationality, and, with the exception of a few theoretical studies (e.g., Dane and Pratt,2007), the same has not been done for intuition. Similarly, few studies have examined the impactof intuition on decision outcomes. To the best of our knowledge, no study has examined the effectsof intuition on decision disturbance. According to Rodrigues and Hickson (1995), decision distur-bance refers to the degree to which unforeseen negative problems or outcomes arose. Using deci-sion disturbance as an outcome variable in this study will enable us to extend the range of decisionoutcomes taken into account.

The role of intuition in strategic decision-making cannot be fully understood unless its antecedentsand consequences are taken into account.

Unusually, we report research conducted in a non-Anglo-Saxon setting, namely Egypt. The lo-cation in Egypt of the research reported here may give rise to some results that are specific tothat national context, owing to cultural and institutional characteristics. In this way, the studymay serve to raise awareness of nationally relevant factors, as the literature has revealed that differ-ent cultural assumptions regarding the environment result in different approaches to formulatingstrategy (Schneider, 1989; Savvas et al., 2001). Savvas et al. (2001), for instance, found a significantdifference in cognitive style between UK graduate students and Egyptian MBA students; more spe-cifically, the UK participants were more intuitive (lower CSI scores) than the Egyptian participants.On the other hand, comparative cross-cultural investigation by Hofstede (1991) suggests that Egyp-tian managers are likely to be relatively respectful of leadership and hierarchical distance, fatalistic,and inclined to act according to the particular relationship involved rather than in accord with gen-eral rules or standards. Such a respectful behaviour would be associated with an unwillingness ofsubordinates to take unfamiliar risks, and a tendency towards uncertainty avoidance (Hofstede,1991) on strategically important issues. Moreover, from their review of relevant studies, Hicksonand Pugh (2001) characterize Egyptian managers as sensitive to personal relationships (especiallywith superiors), and cautious. Other authors confirm that there is respect for seniority in Egypt(e.g., Elbanna and Child, 2007a; Parnell and Hatem, 1999). Overall, these features might be ex-pected to increase a reliance on top managers’ intuition in the strategic decision-making processand a reduction in their application of rational techniques.

Long Range Planning, vol 46 2013 151

Having introduced the key issues and challenges concerning the study of intuition in strategicdecision-making, we now proceed by developing a model of contextual influences and outcomesof the use of intuition in strategic decision-making, hypothesizing the effects of contextual variablesidentified by two theoretical perspectives and the impact of intuition on decision disturbance.

Theoretical modelA theoretical model integrating the literature on the antecedents of intuition and its outcomes instrategic decision-making was developed and tested (see Figure 1). This model combines factorsassociated with two perspectives on decision intuition; namely, decision-specific features andfirm characteristics. It also incorporates an outcome variable e decision disturbance. The modelalso postulates a moderating impact of two factors associated with the environmental perspective,and it controls for the possible influence of rationality.

Given the wide range of contextual variables that may influence the intuition of decision-makingprocess, it is necessary to be selective. We applied two criteria to the selection of contextual vari-ables: their relation to major theoretical perspectives, and the continuity they would providewith previous research on strategic decision-making. We decided to examine four contextual vari-ables, grouped by their identifying theoretical perspectives, which have been the subject of substan-tial discussion and/or empirical attention. The fact that these variables have been of interest tomany researchers enhances the possibility of comparing the findings of our study with those of pre-vious investigations.

The first type of antecedents consists of two decision characteristics, that is, decision uncertaintyand decision motive, which have been the subject of considerable interest in previous research(Dayan and Elbanna, 2011). Moreover, Papadakis et al. (1998) find that these two characteristicsinfluence the strategic decision-making process more than environmental, organizational and man-agerial factors. Elbanna and Child (2007a, 2007b) partially support this finding.

The firm-specific variables examined in the present study are company performance and com-pany size. For the reasons given below, we expected that these two firm-level characteristics wouldbe highly likely to impact on the use of intuition. Other firm-specific variables of a more intrinsi-cally organizational nature, such as degree of structure, development of internal systems, and del-egation to specialists, were excluded not just for reasons of economy but because they were thoughtto be much closer ontologically to the focal variable, manifesting the extent to which formal analysiswas preferred to a reliance on intuition.

Intuition is expected to have an impact on decision outcomes. In this study, we assume that in-tuition may increase the likelihood of decision disturbance e the existence of major negative

Intuition

Rationality

Decision-specific antecedents

Decision uncertainty

Decision motive

Firm-based antecedents

Company performance

Company size

Decisiondisturbance

Environmental-based moderators

Environmentaluncertainty

Environmentalhostility

Figure 1. Theoretical model


unexpected outcomes. Moreover, we expect environmental characteristics to have a moderating im-pact on the relation between decision intuition and disturbance. The literature indicates that the im-pact of intuition on organizational performance differs across various environmental conditions,suggesting that such conditions should be investigated as moderating variables (e.g., Dane andPratt, 2007). Khatri and Ng (2000), for instance, found that environmental uncertainty moderatesthe relationship between intuition and organizational performance. Similarly, Dayan and Elbanna(2011) reported that environmental turbulence moderates the impact of intuition on product success.

The primary environmental characteristics of complexity, dynamism and hostility (Miller et al.,2006) were assumed to translate for strategic decision makers into perceptions of environmentaluncertainty and hostility. Perceptions of environmental uncertainty and hostility have appeared fre-quently in empirical studies of strategic decision-making or been suggested as subjects for futureresearch, as Baum and Wally (2003) note. Uncertainty can arise from either or both complexityand dynamism (variability) in a firm’s environment (Sia et al., 2004). For reasons of parsimony,as well as that of maintaining continuity with previous work on strategic decision-making, we choseto focus on environmental hostility and environmental uncertainty as the consequence perceived bysenior executives of external complexity and dynamism.

Finally, we should not examine intuition in strategic decision-making without controlling for ra-tionality. Previous research supports the view that managers who tend to use rational processes willalso use a kind of “heuristic” based on their intuition (Eisenhardt, 1989). In fact, reliance on intu-ition can be a reasonable course to follow when the environment is unstable and a prompt “satis-ficing” decision is essential. Moreover, the use of intuition can complement the gaps in rationalanalysis arising from uncertainty and lack of relevant information in making the decision. Giventhe possible interaction between these two variables, we controlled for the effect of rationalitywhen examining the antecedents and consequences of intuition.

Hypotheses

Decision-based factors

Decision uncertaintyUncertainty refers to a lack of clear information relevant to making a decision, ambiguity in ana-lysing decision options, and difficulty in predicting decision outcomes (Sonenshein, 2007). Uncer-tainty here refers to a specific decision, as opposed to environmental uncertainty in general.Decision-making, especially of the non-routine kind, is liable to be conducted under uncertainty.Some theorists maintain that uncertainty creates an ambiguity that cannot be resolved by rationalprocesses (e.g., Hayashi, 2001). Dane and Pratt (2007) argue that for ill-defined issues, an intuitiveapproach may be the appropriate approach. Daft and Lengel (1986) suggest that the use of intuitionis necessary when the matter is not analysable. Others also argue that uncertainty will increase thereliance on intuition (e.g., Burke and Miller, 1999; Sonenshein, 2007). Similarly, in the literature ongroup behaviour, the point is made that when decision uncertainty is high, team members relymore on their intuitive judgments to make decisions (e.g., Wegner, 1986).These contributionssuggest:

H1: There will be a positive relationship between decision uncertainty and the use of intuition.

Decision motiveA strategic decision may be triggered by the perception that there is either a crisis or an opportu-nity. Papadakis et al. (1999) show that decision-makers react in a quite different manner when theyare facing a crisis, as opposed to a situation of opportunity. This has important implications formanagers because it deeply affects the subsequent processes of decision-making. Previous researchsupports this notion (e.g., Jackson and Dutton, 1988). Sayegh et al. (2004) argue that the use of tacitknowledge and intuition may be the only feasible approach under crisis conditions since decision-


makers will not have sufficient time to apply the protocols of rational decision-making. By contrast,Dutton (1986) claims that the process of resolving a strategic issue becomes easier when the stra-tegic issue represents an opportunity; hence decision-makers may rely more on intuition. However,Mintzberg et al. (1976) conclude that the strategic decision-making process is less intuitive whenthe decision is interpreted as a crisis as opposed to an opportunity. Fredrickson (1985) arguesthat managers initially characterize decision motives as having positive or negative effects, andthey expect decisions which are interpreted as opportunities to lead to significant positive resultsfor firms. These decisions do not provide critically needed solutions; on the contrary, simply re-sponding to these stimuli promises previously unanticipated benefits. Therefore, managers wouldtend to exploit opportunities using an intuitive approach. Tindale and Sheffey (2002), for example,argue that groups are willing to rely on their intuitive skills, if they perceive that the decision theyare about to make may result in seizing an opportunity.

In short, although there are contradictory arguments concerning the relationship between deci-sion motive and intuition, and the evidence is limited, the empirical results reported by Mintzberget al. (1976) and arguments of both Fredrickson (1985), and Tindale and Sheffey (2002) lead to thefollowing hypothesis:

H2: The strategic decision-making process will rely more on intuition when it is motivated byopportunity.

Firm-based factors

Company performanceWe define performance as the level of a firm’s attainment on both financial (e.g., return on assetsand growth rate of sales) and non-financial indicators (e.g., quality of product and efficiency of op-erations) compared to companies that are similar in size and industry (see Appendix 2 for the fulllist of performance indicators). Cyert and March (1963) argued that slack, a product of good or-ganization performance, decreases the intensity with which organizations will search for informa-tion in pursuit of rationality. Other authors also take this view (e.g., Bourgeois, 1981). For example,Fredrickson (1985) argued that managers in successful firms sometimes make a series of what ap-pear to be intuitive decisions. Moreover, high performance may motivate decision-makers to bemore confident in their intuition, and hence reduce their desire to search for and analyse informa-tion. Whereas in low-performing firms a wrong decision may seriously harm the firm and threat thepositions of decision-makers. In such circumstances, decision makers may be reluctant to rely uponunexplained and risky intuition, and be willing to use rational supports for decision-making, suchas hiring consultants, collecting relevant data, and conducting detailed analyses. Cyert and March(1963) similarly argue that poor performance puts pressure on decision-makers to make precise de-cisions. This gives rise to:

H3: There will be a positive relationship between company performance and the use of intuition.

Company sizeCompany size has frequently been identified as a factor that can influence strategic decision processes(e.g., Child, 1997). Small firms tend to be less formalized which may encourage a greater use of intu-ition. Snyman and Drew (2003), for example, argue that in small firms managers may pursue a singlestrategic decision-making process, whereas in larger firms, managers will need two or more strategicdecision processes to formulate and implement strategy. Hart and Banbury (1994) argue that in smallfirms, strategy-making relies on the idiosyncratic capabilities of a single (or a few) individual(s), whilethe larger firm must typically develop more formalized approaches to planning. Larger organizationalsize is a highly consistent predictor of arrangements supporting the application of rationality todecision-making, such as the formalization of procedures and employment of specialists (Child andMansfield, 1972). We therefore suggest that smaller firms will employ more intuitive processes, for


two reasons. First, small firms may well not be able to afford the costs of pursuing a rational process.Second, small firms may not have specialized subunits or staff who encourage and facilitate the adop-tion of rational decision-making procedures (cf. Fredrickson and Iaquinto, 1989). Hence:

H4: There will be a negative relationship between company size and the use of intuition.

ConsequencesAlthough some authors have argued that intuition has an important role in strategic decision-making, there has been limited empirical research on its consequences. For example, Eisenhardt(1989), Judge and Miller (1991), and Wally and Baum (1994) investigate the impact of intuitionon the pace of strategic decision-making, but they do not directly investigate the relationship be-tween intuition and decision outcomes. In one of the few applied studies that have addressedthe role of intuition on organizational outcomes, Khatri and Ng (2000) found that the use of in-tuition in the strategic decision-making process is negatively related to organizational performancein a stable environment. Similarly, Elbanna and Child (2007b) hypothesized that the use of intui-tion in strategic decision-making will be negatively related to strategic decision effectiveness. Sauter(1999) mentions that managers using intuition may become impatient with routine or details, andthey may reach conclusions very quickly, ignore relevant facts, or follow an inspiration when it isclearly bad. Hence, intuition may increase the chance of producing unforeseen problems. In otherwords, using intuition in decision-making increases the possibility of decision disturbance.

In view of the above, we posit the following hypothesis:

H5: The use of intuition in strategic decision-making will increase the likelihood of decisiondisturbance.

Moderating environmental influences

Environmental uncertaintyIt is likely to be more difficult to rely on formal analysis and in-depth study when having to deal withunpredictable or high-velocity environments that are characterized by an absence of precedents, in-formation scarcity and rapid change (Covin et al., 2001). For this reason, one may expect environ-mental uncertainty and limited information to increase managers’ reliance on intuition when makingstrategic decisions. Dane and Pratt (2007: 46), for example, argue that under conditions of environ-mental uncertainty, “decision-making scenarios may move from the intellective end of the task con-tinuum toward the judgment end.” Similarly, McCarthy et al. (1987) claim that a principal problemwith the application of formal models in high-tech environments is the difficulty facing decision-makers in acquiring the relevant, timely and valid data required for the effective use of these models.In the absence of such data, it is argued that intuition provides an alternative basis for strategicdecision-making. Rajagopalan et al. (1997) point out that the performance effects of the decision pro-cess are likely to be different across different types of environmental uncertainty. Eisenhardt (1989)supported this conclusion. Goll and Rasheed (1997) found that environmental munificence (as anopposite of hostility) moderates the relationship between decision-making process and performance.Khatri and Ng (2000) report that environmental stability moderates intuition and company perfor-mance link. We therefore argue that decision-makers who rely on intuition, in an uncertain environ-ment, are more likely to forgo systematic analysis, and that this increases the probability ofunfavourable and unforeseen outcomes. In conclusion, the use of intuition in strategic decision-making is expected to be greater in an uncertain environment than in a certain environment, andhence we anticipate that the impact of intuition on decision disturbance will be greater in the formertype of environment than in the latter one. Therefore, we offer the following hypothesis:

H6: The higher the level of environmental uncertainty, the greater the impact of intuition ondecision disturbance.


Environmental hostilityA hostile environment is one in which the changes in the external environment of the firm are per-ceived as unfavourable to the mission or outputs of the firm (Edelstein, 1992). This environmentcan be characterized, for example, by tough competition in the market, low margins, oppressive gov-ernmental regulations, and limited growth opportunities (Zahra et al., 1997). Although there is onlylimited empirical research examining the impact of environmental hostility (or its opposite, environ-mental munificence) on the relationship between decision process and outcomes, this clearly points toits importance (Elbanna and Child, 2007a; Rajagopalan et al., 1997; Wan and Hoskisson, 2003). Golland Rasheed (1997), for instance, reported that environmental munificencemoderates the relationshipbetween decision-making process and company performance. McArthur and Nystrom (1991) foundenvironmental munificence to be a significant predictor of the strategy-performance relationship. Sim-ilar results are reported by Covin and Slevin (1989), who found that in hostile environments an organicstructure and entrepreneurial strategic posture are positively related to firm performance. In a hostileenvironment, firms need to make a greater analytical effort to understand the threats they face(Khandwalla, 1973). Similarly, Miller and Friesen (1983) report that organizations respond to in-creased environmental hostility through decision-making characterized by greater analysis and re-duced innovation. Hence, we anticipate that intuition is more likely to lead to unexpected negativeoutcomes in hostile environments than in munificent environments. In formal terms:

H7: The higher the level of environmental hostility, the greater the impact of intuition on decisiondisturbance.

MethodologyThis study takes the strategic decision as its unit of analysis. This choice is due to the fact that,within the same organization, the decision process can differ from one type of decision to another(Hickson et al., 1986). The strategic decisions to be investigated were selected according to four cri-teria. These are: 1) the decision had to be defined by both the respondent and the researcher asa strategic one; 2) the decision was made during the last two years to minimize memory error;3) the respondent was closely involved in making the chosen decision; and 4) the decision outcomeswere clear at the time when the data were collected. The decision areas in the sample vary widely,with no area accounting for more than 30% of the sample: investment in capital equipment, prod-uct introduction or discontinuation, geographical expansion, diversification, restructuring, down-sizing. Given the likely effects of context, we conducted an exploratory investigation prior tohypothesis testing. This is a distinctive feature of this study, which significantly contributed toits quality (see Appendix 1).

SampleGiven the difficulty of conducting a research survey on the basis of a random sample, e.g., the ab-sence of accessible sampling frames (Zahra, 2011), a convenience sample was suggested and is con-sistent with previous research conducted in Arab countries (e.g., Elbanna, 2012). The targetpopulation was limited to Egyptian private manufacturing companies operating in greater Cairoand employing more than 100 people. These three aspects of our population helped us to controlpartially for unspecified industry effects, to control for unknown effects of regional variation, and toreduce the variability in the population and hence minimize the need to enlarge the sample size.

We collected data from people who were closely involved in making strategic decisions. Respon-dents were directors (35%), CEOs (31%), general managers or managing directors (20%), andchairmen or presidents (14%). The firms represent a variety of industries, with no sector account-ing for more than 23% of the sample. Employment in 77% of the companies ranged between 100and 600 persons, while 23% of the companies had between 600 and 2,500 employees. We comparedthe distribution of company sizes in our sample with that used for a prior exploratory study (seeAppendix 1), applying a two-sample t-test. There was no significant difference between the twosamples in terms of company size (p ¼ 0.56). This may suggest that our sample is representative


of the population. Regarding the non-response bias of “sporadic” items, sample means were used toreplace missing values with the mean for the variable concerned.

Four hundred questionnaires were dropped off in person, and 206 completed schedules were col-lected. Out of these 206 questionnaires, thirty-seven were excluded for different reasons, such asincompleteness; non-relevant respondents or questionnaires inadvertently collected from state-owned enterprises. The remaining 169 usable questionnaires (a final response rate of 42%) wereincluded in the analysis. Eight respondents completed the revised questionnaire a second time,for purposes of judging test-retest reliability. The difficulty of gaining permission to conduct a mul-tiple-informant survey led to the reliance on single respondents.

Harman’s one-factor test (Podsakoff et al., 2003) shows that a substantial amount of commonmethod variance (CMV) does not appear to be present. More specifically, an unrotated factor anal-ysis resulted in factor solution, which accounted for 71% of the total variance; and Factor 1 ac-counted for 22% of the variance. Because a single factor did not emerge and Factor 1 did notexplain most of the variance, common method bias is unlikely to be a concern in our data. In ad-dition, we can strengthen our argument that CMV is not a major concern in this study, since we arealso predicting a moderating effect. Survey respondents would less likely be able to guess the natureof the moderation or interaction effect, and therefore, would be unlikely to provide responses thatcan be seen as contributing to CMV (Dayan and Di Benedetto, 2010). We also used eleven instancesof multiple respondents within the same company to test for inter-respondent reliability. Our dataenjoy a modest level of inter-respondent reliability. The ANOVA-based intra-class correlation andPearson correlation analyses show that ten out of the eleven cases with two informants demon-strated significant correlations at the 1 percent level or better.

OperationalizationThe questionnaire was developed through the following processes. First, based on the review of rel-evant literature, the first author developed a draft questionnaire in English to measure the variablesin our hypotheses (see Appendices 1 and 2 for more details). Second, the draft questionnaire wasreviewed by three academics. Third, the final English version of the questionnaire was translatedinto Arabic by the first author. Fourth, five academics who were bilingual in Arabic and Englishchecked the translation. Finally, a modified Arabic version was administered to seven Egyptian ex-ecutives leading to some amendments. The resulting Arabic questionnaire could be described as be-ing as close in meaning to the original English version as possible. Moreover, the same layout,paper, order of questions and number of pages were used in both versions.

Since each variable was measured reflectively with seven-point Likert-scales, the results derivedfrom Stage 1 were carefully examined and subjected to tests of internal reliability and validity. Inthe light of the first stage results, a number of amendments were made to the questions asked. Sev-eral items were changed, deleted or reordered, in some cases to avoid undue sensitivity among re-spondents. For example, two items referring to politics at the country level were removed from thescale of environmental uncertainty because respondents had been reluctant to answer these twoitems (see Appendix 1 for more details).

Data analysisWe used Smart PLS 2.0 M3 software (Ringle et al., 2005) to test the proposed model by conductingpartial least squares (PLS) analysis, which is a structural equation modelling (SEM) technique (e.g.,Lew and Sinkovics, forthcoming). PLS was preferred as the methodological choice because of thefollowing reasons: First, as a component-based approach, it places minimal requirements on samplesize and residual distributions to achieve sufficient statistical power (Hair et al., 2012; Reinartzet al., 2009; Lohmoller, 1989). Second, it allows us to model latent variables and simultaneouslyassess both measurement and structural models (Chin, 1998; Barclay et al., 1995). Third, it is con-sidered one of the most suitable techniques for the development of new theory. Fourth, it can beused to evaluate the effect of common method bias (Liang et al., 2007; Podsakoff et al., 2003).


We followed the guidelines of Hair et al. (2011 and 2012) on how to apply and report the PLS-SEM method. In order to identify the minimum sample size, as suggested by Chin (1998), the num-ber of paths leading to the endogenous construct with the most paths was multiplied by 10. Theperformance variables (both of financial and non-financial performance variables), have four pathsleading into each of these performance variables, suggesting that a minimum sample size of 40would be sufficient. Moreover, as indicated by Reinartz et al. (2009, p. 340) “the minimum samplesize necessary to achieve a given level of statistical power in PLS is always less than or equal to thesize required for ML-based CBSEM, and in many cases, ML-based CBSEM needs twice as muchinformation as PLS to avoid Type II error.” Indeed, one of the main reasons of choosing PLS isthat statistical power of PLS is higher than ML-based CBSEM (Reinartz et al., 2009; Chin et al.,2003). Since our aim is to identify potentially significant relationships that may exist, ratherthan confirming the significant relationships that have been proved by past research, achieving suf-ficient statistical power is essential for this study. Therefore, given our sample size of 169 partici-pants, we are confident that our use of PLS to test the hypotheses was appropriate.

Measurement model resultsThe psychometric properties of the scales and the explanatory and predictive power of the struc-tural model were assessed by conducting PLS analysis. However, variables related to environmentalcharacteristics were not included because they were used as moderators in this study. Instead, weperformed factor analysis to test convergent and discriminant validity of the environmental vari-ables. As expected, factor analysis produced five distinct factors, four of environmental uncertaintyand one of environmental hostility. Since the four sub-scales of environmental uncertainty did notseparately add to the prediction of decision intuition as compared to their aggregation, we used anaggregate of all twenty-one environmental uncertainty items in the analysis.

In the PLS analysis, item loadings, discriminant validity, and reliabilities were first examined inorder to assess the psychometric properties of the scales. Construct items were dropped when therewere very small and insignificant item loadings, as suggested by Chu et al. (2004). Item loadings andreliabilities above 0.70 were considered acceptable (Fornell and Larcker, 1981). Table 1 shows PLSitem loadings and cross-loadings. In PLS analysis, the loadings of items are interpreted as loadingsin a principal component factor analysis (Chin et al., 2003). As Table 2 shows, the items have load-ings above 0.70. Descriptive statistics for the model constructs, composite reliability scores, and in-terconstruct correlations are shown in Table 2. All constructs have acceptable internal consistency,with all reliability scores being above 0.70. Specifically, the composite reliability scores range from0.80 for decision motive to 0.92 for rationality. Thus, the composite measurement items have ad-equate item reliability.

In PLS analysis, there are two criteria used to assess discriminant validity. First, items should loadmore strongly on their corresponding construct than on other constructs; and second, the squareroot of each reflective construct’s AVE should be greater than the level of correlations involving theconstruct (Chin, 1998). As shown in Table 2, all items load more highly on their correspondingconstruct than on other constructs (i.e., loadings are higher than cross-loadings). Additionally,as shown in Table 2, all constructs share more variance with their items (AVE) than with other con-structs. Moreover, all the correlations were well below the cutoff value of 0.80 (Hair et al., 1995);and skewness values, ranged from �1.38 to 0.25, are well below the levels suggested for transfor-mation of variables (Ghiselli et al., 1981). Therefore, we conclude that our model has adequate val-idity and reliability to continue with analysis of the explanatory and predictive power of thestructural model.

Structural model resultsWe assessed our proposed model by running the structural model in Smart PLS to test our hypoth-eses. Path coefficients of a PLS model are interpreted same as standardized beta weights in a regres-sion analysis. A PLS model’s quality is assessed by two indicators: the variance explained (R2) in theendogenous variables and the regression coefficients’ significance (Chin, 1998; Saade, 2007). Table 3


Table 1. PLS factor loadings

Item Decision

motive

Decision

uncertainty

Financial

performance

Non-financial

performance

Intuition Rationality

Item 1 0.853 �0.316 0.257 0.451 �0.175 0.478

Item 2 0.773 �0.191 0.382 0.336 �0.144 0.397

Item 1 �0.206 0.858 �0.161 �0.190 0.205 �0.261

Item 2 �0.252 0.878 �0.163 �0.190 0.220 �0.287

Item 3 �0.325 0.724 �0.199 �0.297 0.208 �0.360

Item 1 0.406 �0.171 0.812 0.404 �0.169 0.335

Item 2 0.330 �0.181 0.828 0.396 �0.126 0.338

Item 3 0.192 �0.133 0.817 0.353 �0.150 0.287

Item 4 0.325 �0.213 0.836 0.400 �0.155 0.348

Item 1 �0.169 0.191 �0.142 �0.220 0.877 �0.268

Item 2 �0.188 0.266 �0.187 �0.275 0.937 �0.366

Item 1 0.273 �0.192 0.409 0.762 �0.201 0.350

Item 2 0.423 �0.228 0.356 0.807 �0.167 0.388

Item 3 0.460 �0.253 0.464 0.902 �0.248 0.514

Item 4 0.439 �0.229 0.332 0.820 �0.269 0.461

Item 1 0.498 �0.357 0.381 0.468 �0.338 0.917

Item 2 0.439 �0.300 0.324 0.479 �0.343 0.917

Item 3 0.506 �0.324 0.352 0.455 �0.257 0.817

Note: Figures in boldface represent the loadings of individual items on their corresponding factors.

shows the PLS path modelling results (overall and under different environmental conditions); thedifferences in two comparisons’ path coefficient estimates (High uncertainty vs. Low uncertainty;and High hostility vs. Low hostility). It also provides the results of multigroup comparisons basedon Keil et al.’s (2000) parametric test, the permutation test (Chin, 2003; Chin and Dibbern, 2010),and Henseler’s (2007) approach.

Results of model testing indicated that our model results in acceptable R2 statistics because theyare greater than the recommended 10% (Falk and Miller, 1992): R2 ¼ 0.17 for intuition andR2 ¼ 0.27 for decision disturbance. Hypothesis 1 predicted that there would be a positive relation-ship between decision uncertainty and the use of intuition. As the results in Table 3 indicate, de-cision uncertainty had a weak positive relationship with the use of intuition (path ¼ 0.13, t ¼ 1.70,p < 0.10), which provides some support for Hypothesis 1. Decision motive was not significantlyrelated to the use of intuition (path ¼ 0.03, t ¼ 0.39, p > 0.10). Thus, Hypothesis 2 was notsupported.

Hypothesis 3 posited that performance would be positively related to the use of intuition. Theresults indicate that neither financial performance nor non-financial performance are related tothe use of intuition (path for financial performance ¼ 0.09, t ¼ 0.12, p > 0.10; path for non-financial performance ¼ �0.10, t ¼ 1.77, p > 0.10). Thus, Hypothesis 3 was not supported.

Hypothesis 4 predicted that there would be a negative relationship between company size and theuse of intuition. The results indicate that company size had a negative relationship with the use ofintuition (path ¼ �0.16, t ¼ 2.39, p < 0.05), which provides support for Hypothesis 4.

Hypothesis 5 predicted that the use of intuition would be positively related to decision distur-bance. The results indicate that there is a positive relationship between the use of intuition and de-cision disturbance (path ¼ 0.20, t ¼ 3.23, p < 0.01). Thus, Hypothesis 5 was supported.

Finally, the results revealed that our control variable, rationality, had a negative relationship withboth intuition and decision disturbance (path for rationality on the use of intuition ¼ �0.25,t ¼ 2.52, p < 0.05; path for rationality on decision disturbance ¼ �0.41, t ¼ 4.85, p < 0.01).


Table 2. Reliability and inter-construct correlations

Variables Composite

Reliability

Mean S.D. 1 2 3 4 5 6 7 8 9 10

1. Intuition 0.90 4.04 1.96 0.90

2. Decision uncertainty 0.86 2.32 1.43 0.25** 0.86

3. Decision motive 0.80 5.65 1.36 �0.19* �0.31** 0.81

4. Financial performance 0.89 4.84 1.15 �0.18* �0.22** 0.40** 0.82

5. Non-financial performance 0.89 5.69 1.08 �0.27** �0.28** 0.48** 0.46** 0.82

6. Company size (log) N/A 2.45 0.42 �0.22** �0.11 0.05 0.21** 0.17* 1

7. Rationality 0.92 5.81 1.17 �0.35** �0.37** 0.53** 0.40** 0.52** 0.17* 0.88

8. Decision disturbance N/A 2.40 1.46 0.35** 0.36** �0.37** �0.26** �0.50** �0.05 �0.50** 1

9. Environmental uncertainty 0.92 4.13 1.21 0.11 0.12 �0.07 �0.12 0.02 0.15þ �0.13þ 0.03 N/A

10. Hostility 0.86 3.59 1.63 0.26** 0.15þ �0.21** �0.33** �0.25** �0.09 �0.31** 0.32** 0.43** N/A

Notes: N ¼ 169. Boldface values are the square root of the average variance extracted. It shows the variance shared between a construct and its measures. Boldface diagonal elements shouldbe larger than off-diagonal elements in order to satisfy discriminant validity requirements. N/A ¼ not applicable, þp < 0.10, *p < 0.05, **p < 0.01.

160

AModel

ofAnteced

ents

andConseq

uences

ofIntuitio

nin

Stra

tegic

Decisio

n-m

aking

Table 3. PLS path modeling results: overall & under environmental conditions

Sample size Overall Uncertainty jDj Multigroup comparison test results Hostility jDj Multigroup comparison test results

High Low Parametric Permutation Henseler High Low Parametric Permutation Henseler

169 93 76 91 78

Path

coefficients

Decision uncertainty /

Intuition

0.132þ 0.142þ 0.128þ 0.014 1.940þ 1.612 0.034 0.153) 0.139þ 0.014 1.970þ 1.323 0.067

Decision motive /

Intuition

0.03 0.071 0.064 0.007 0.383 0.733 0.045 0.081 0.076 0.005 0.121 0.076 0.011

Financial

Performance / Intuition

0.093 0.098 0.086 0.012 1.735 1.357 0.012 0.097 0.088 0.009 0.229 0.102 0.032

Non-financial

Performance / Intuition

0.10 0.112 0.104 0.008 0.256 0.187 0.128 0.092 0.084 0.008 0.321 0.287 0.087

Company size /

Intuition

0.16* 0.193* 0.189* 0.004 0.145 0.067 0.031 0.188* 0.181* 0.007 0.288 0.112 0.045

Rationality / Intuition 0.25** 0.332** 0.253** 0.079 3.562** 2.692** 0.125 0.372** 0.264** 0.108 3.970*** 2.794** 0.782

Rationality / Decision

disturbance

0.41** 0.571** 0.39** 0.181 4.176** 2.829** 0.133 0.494** 0.448** 0.046 2.763* 2.014* 0.592

Intuition / Decision

disturbance

0.20** 0.180* 0.178* 0.002 0.089 0.082 0.029 0.210** 0.186* 0.024 2.460* 1.945þ 0.089

Adjusted R2 Intuition 0.17 0.19 0.16 0.18 0.16

Decision disturbance 0.27 0.28 0.25 0.27 0.24

Notes: jDj ¼ Absolute difference of high environmental condition’s data and low environmental condition’s data results; **Significant at .01, *Significant at .05, þSignificant at .10; Results forHenseler (2007) eligible for a one-sided test.

Long

Range

Planning,

vol46

2013161

In sum, the results on the aggregate data revealed that with a path coefficient of �0.25, rationalityis the strongest predictor of intuition, whereas company size has a moderate coefficient (path co-efficient of �0.16) and decision uncertainty has the weakest coefficient (path coefficient of 0.13).The essential link between rationality and decision disturbance has the highest coefficient(�0.41) for the PLS path model estimation on the aggregate data level.

Moderating role of environmental uncertainty and hostilityWe used the subsample method (Sarstedt et al., 2011; Rigdon et al., 2011; Henseler and Fassott,2010), performing a quantile split to create separate groups for the lower and higher third of thedataset, to test for the moderating effect of environmental uncertainty and hostility. We estimatedthe path coefficients through PLS path modelling for each subsample. The differences between thepath coefficients indicate whether environmental uncertainty and hostility act as moderatingvariables.

In general, the results (see Table 3) indicate that according to the parametric test and the permu-tation test, environmental uncertainty does not significantly moderate the impact of the use of in-tuition on decision disturbance (jDj ¼ 0.002, t ¼ 0.089 and 0.082 for the parametric test and thepermutation test, respectfully, p > 0.10 for both), but environmental hostility does (jDj ¼ 0.024,t ¼ 2.460 and 1.945 for the parametric test and the permutation test, respectfully, p < 0.10 forboth). Thus, Hypothesis 7 was supported, but Hypothesis 6 was not.

More specifically, in the structural model, the R2 values of latent variables in the different envi-ronmental conditions model estimation show the same rank order compared with the results forthe R2 values on the aggregate data level. The bootstrapping results show that the same paths (De-cision uncertainty / Intuition, Company size / Intuition, Rationality / Intuition,Rationality / Decision disturbance, and Intuition / Decision disturbance) that are significantin the overall model estimation are also significant in each environmental conditions model estima-tion. In comparison with the aggregate level results, the path coefficients in environmental condi-tions model estimations show differences (in absolute values) in the range of 0.005 to 0.161.However, structural model path coefficients mainly demonstrate the same order of relative relevance.

The environmental conditions model estimations, on the other hand, show stronger differencesthat range (in absolute values) between 0.002 and 0.181. The results of PLS-MGA approach(Henseler et al., 2011; Sarstedt et al., 2011) show that the parametric test and the permutationtest, in most cases, yield significant and higher t-values than the Henseler’s approach. More specif-ically, the analysis indicates that the same paths that are significant in both the overall model esti-mation and the different environmental conditions model estimation are also significantly differentacross different environmental conditions according to the parametric test and the permutationtest, with one exception (i.e., the relationship between Decision uncertainty and Intuition). For in-stance, under the high uncertainty condition, the negative relationship between rationality and de-cision disturbance is significantly stronger than under the low-uncertainty condition(jDj ¼ �0.181, p � 0.01). The similar significant differences also exist under high and low hostilityconditions, such as between rationality and intuition (jDj ¼ �0.108, p � 0.01). In sum, the resultsshow that the group specific data is more representative to meet our analytical goals than overallsample data.

Discussion

Theoretical implicationsThe present investigation attempts to examine a more comprehensive model of the antecedents andconsequences of intuition in strategic decision-making than those previously formulated. As antic-ipated, our results show that decision uncertainty and company size are significant predictors of theuse of intuition, that intuition significantly influences decision disturbance, and that environmentalhostility moderates the linkage between decision intuition and disturbance.


Consistent with earlier research (Sadler-Smith, 2004, r ¼ �0.27, p < 0.01; Scott and Bruce, 1994,r ¼ �0.17, p < 0.05), the relationship between intuition and rationality was significantly negativebut relatively low (r ¼ �0.25, p < 0.01). However, this does not mean that intuition and rationalityare necessarily the two opposite extremes of a single dimension, for Hodgkinson and Sadler-Smith(2003), and Leybourne and Sadler-Smith (2006) found a non-significant correlation between intu-ition and rationality. Using a version of the Rational-Experiential Inventory (REI) that measuresrational and experiential/intuitive thinking styles, Pacini and Epstein (1999) report that the twostyles were independent and exhibited discriminant validity. Similarly, Epstein (2011) claims thatthere are individual differences with people relying more on their intuitive processing and otherson their rational processing in response to a change in incentive level.

Surprisingly, decision motive and performance do not predict intuition, and environmental un-certainty does not moderate the relationship between intuition and decision disturbance. We nowconsider the interpretation of these findings.

It is worth noting that none of the previous studies examined the impact of decision motive onthe use of intuition empirically. Therefore, it was not possible to compare this result to related re-search. A possible explanation for our result is that the impact of decision motive on decision in-tuition will vary according to decision-makers’ characteristics. Leybourne and Sadler-Smith (2006),for example, report that more experienced managers may be more intuitive than less experiencedones. Similarly, Sayegh et al. (2004) argue that experience is critical in the use of intuition in thestrategic decision-making process.

Interestingly, neither financial nor non-financial performance significantly predicts the use of in-tuition. Related research in different settings, such as the USA and Greece, reveals that different as-pects of performance are differentially related to the use of intuition (e.g., Khatri and Ng, 2000) andto other aspects of strategic decision-making (e.g., Papadakis, 1998). In view of this and the fact thatperformance is a complex and multidimensional phenomenon, we suggest that divergent aspects ofperformance may differently influence the use of intuition in strategic decision-making. Althoughfinancial and non-financial performance inversely influence decision disturbance in our study, thisimpact was insignificant. As suggested in our revised theoretical model (Figure 2), future researchcould examine the impact of other aspects of performance, not considered in the current study,such as the effect on the use of intuition of long and short-term performance, subjective and ob-jective performance, past performance, and balanced scorecard perspectives.

It is also worth noting that the causal relationship between intuition and performance could bebi-directional. While some researchers have examined the impact of intuition on organizationalperformance (e.g., Khatri and Ng, 2000; Sadler-Smith, 2004), we regarded performance as an an-tecedent of intuition. An important consideration, which should be taken into account when as-suming causal direction, is the unit of analysis of the study. If the unit of analysis is the overalldecision-making of an organisation, the direction of causal relationship between intuition andperformance can be examined both ways. If the study examines isolated strategic decisions, asdoes the current study, the overall performance of an organisation may have only a weak relation-ship to any individual decision. This is because the same firm makes diverse strategic decisions(Hickson et al., 1986), and because different decisions in the same firm can produce diverse pat-terns of success (Nutt, 2002). Rajagopalan et al. (1997) suggest that overall organizational perfor-mance measures cannot be linked to the actions of a manager, let alone a specific decision. In thatcase, the examination of both past and current performance as an explanatory factor of decisionprocess makes greater logical sense. It avoids the problem of causal ambiguity, which would attendthe choice of organisational performance as an outcome of a single decision. This is essential in thelight of the many exogenous effects on organisational performance (Pearce et al., 1987). Moreover,in order to clarify the nature of what is likely to be a two-way recursive relationship, we suggestthat future investigations should adopt a longitudinal research design, using both laboratory andfield settings.

There is a positive statistical relationship between relying on intuition and decision disturbance.


Decision-based antecedents

- Decision uncertainty- Decision motive, experience as a moderator

- Decision type- Decision structure

Firm-based antecedents

- Organization size- Different aspects of performance

- Short and long term- Subjective and objective- Current and previous performance- Balanced scorecard perspectives

- Organization age- Organizational culture- Slack

Demographic and personal-based

antecedents

- Age; education; tenure; experience- Affect/emotion; self confidence; propensity to risk; cognitive styles; mood states

Possible moderators

- Environmental hostility- Environmental turbulence- Environmental instability- Previous experience

Methodological Improvements

A new scale of intuition in decision-making; the use of multiple respondents; carefully select the unit of analysis; longitudinal research design; clarification of the causal relationship between in tuition and performance; take account of the national context of the study

Multi indicators of success

- Decision quality- Decision effectiveness- Decision disturbance- Decision speed

Intuition

- Dual-process theory- CEST theory - The associative/rule-based theory- C-system-X-system distinction

- Types of intuition- Intuition outcomes- Purposes behind the use of intuition

Possible control variables

- Peer consensus- Environmental favorability- Quality of decision implementation- Belief/self-confidence in intuition- Other modes of processing information- Country or region

Figure 2. Revised theoretical model and platform for future research

As expected, the use of intuition increases the possibility of decision disturbance, while environ-mental hostility significantly moderates the relationship between intuition and decision distur-bance. However, there was no support for a moderating impact of environmental uncertainty onthe intuition-decision disturbance linkage. This result is consistent with Elbanna and Child(2007b), who reported that environmental uncertainty did not moderate the relationship betweenintuition and decision effectiveness. Similar results were reported regarding other dimensions of thedecision process such as rationality and political behaviour (e.g., Dean and Sharfman, 1996;Elbanna and Child, 2007b). However, the above findings contradict those of other studies whichfound environmental uncertainty to moderate the relationship between decision processes and or-ganizational performance (e.g., Goll and Rasheed, 1997). It should be noted that all of the abovestudies, apart from Dean and Sharfman (1996) and Elbanna and Child (2007b), examine organiza-tional performance, which is normally not explicitly assessed in terms of decision outcomes. Thissuggests that variations between the constructs of organizational outcomes used in previous re-search may be a possible source of the inconsistencies in the results obtained.

The absence of a moderating effect from environmental uncertainty could also be due to anotherfactor, specific to the national context of the study. There is reason to suspect that the degree offamiliarity with an environmental condition such as uncertainty may affect the extent to whichit moderates the relationship between intuition and decision disturbance. Getting used to livingwith environmental uncertainty appears to lead Egyptian managers to discount it when makingstrategic decisions. This is suggested by evidence from our interviews which revealed that Egyptianexecutives have become accustomed to working under conditions of environmental uncertainty.They appear to take these conditions for granted in decision-making within the Egyptian setting.

Egyptian managers tend to discount environmental uncertainty when making strategic decisions.

This lends support to the argument that the way in which managers perceive environment in na-tional settings may differentially influence strategy formulation (Schneider, 1989; Savvas et al.,2001), and also affect the moderating impact of environmental uncertainty on the decision


process-outcomes linkage (Elbanna and Child, 2007b). While, as previously noted, studies haveidentified fatalism and uncertainty avoidance as characteristics of Egyptian culture, it may wellbe that such characteristics are reinforced by genuine instability in the national business and polit-ical system. The relevance for modelling the strategic decision process of such national differenceswarrants further comparative investigation.

“The Middle East area including Egypt . is a completely unstable area. If we base our policies onit, we will never ever develop,” an executive said.

Commencing January 25, 2011, Egypt underwent a revolution against the dictatorship of HosniMubarak. The revolution secured widespread popular support, especially among the younger gen-eration, which demanded “Dignity, Freedom and Social Justice”. It is expected to influence man-agerial practices including the use of intuition in strategic decision-making. One of the interviewedmanagers, for example, described the chairperson as being “self-opinionated, insisting on his pointof view regardless of the other managers’ opinions or feedback.” “Our Chairman is a dictator. He isa good listener . but he does not react to what he listens to . we know this fact well and accord-ingly act!” another manager in the same company said. This confirms the high power distance andhigh respect for seniority in the Egyptian culture as noted by other researchers (e.g., Elbanna andChild, 2007a; Hickson and Pugh, 2001; Hofstede, 1991; Parnell and Hatem, 1999). This is consid-ered a major drawback of the decision making process in Egypt which tends to leave little room foreffective participation and innovation. However, as a consequence of the January 25 revolution,these assumptions may require revision. This opens a promising avenue for future research.“The flame of freedom and dignity is spreading and the culture of fear has been broken and thereis no going back,” said Mohamed ElBaradei, the ex-Director General of the International AtomicEnergy Agency, commenting on the impact of the Arab Spring on Arabs in his speech in the Cin-ema for Peace Gala e Berlin 2012.

As a consequence of the January 25, 2011 revolution, current assumptions concerning managementpractices in Egypt may require revision.

Practical implicationsSince decision-makers can be trained to make better intuitive decisions (Hogarth, 2001), this studyhas some practical implications. First, such training can help decision-makers understand intuitionand value it as a legitimate mental function that is particularly useful for some situations. Manyexecutives try to keep secret the fact that they rely upon intuition (Agor, 1989); while others, actinglike attorneys, search for confirmatory evidence and provide a post hoc rationalization for decisionsreached intuitively (Reynolds, 2006). This reflects the absence of executives’ self-confidence in in-tuition as an effective approach to decision-making, which may be due to the perception that it isunscientific (Sadler-Smith and Shefy, 2004) and a result of limited empirical research on the sub-ject. This study helps to fill this gap through empirically pointing to the variables that may lead tothe use of intuition in the strategic decision-making process and its impact on decision disturbance.Moreover, the study calls attention to another important consideration which executives should beaware of when examining the impact of intuition on decision outcomes. This is that the use of in-tuition in decision-making can differentially influence diverse types of decision outcomes. Realizingthis will help executives to better understand the practical value of intuition and its shortcomings.

Second, given that there is a growing interest among practitioners in ways of developing and un-derstanding intuition, this line of inquiry may help them to a clearer view of where and when theycan trust their intuition. Third, since research suggests that executives do make significant use ofintuition, the process of intuition and its antecedents and outcomes should form part of the man-agement education curriculum. This study and related research may encourage its inclusion.

Intuition should form part of the management education curriculum.


LimitationsThis study is subject to a number of limitations. First, while our data enjoy a modest level of inter-respondent reliability, and many related studies have collected data from a single respondent, itwould have been preferable to have had multiple respondents in order to minimize the risk of sys-tematic response bias.

Second, our sample was drawn only from Egyptian private manufacturing firms. Therefore, cau-tion should be expressed in generalizing these findings.

A third limitation is that the conceptual and operational scope of this study does not do justice tothe full breadth of the contextual variables potentially affecting intuition. To some extent, our re-sults might therefore be idiosyncratic to our model and another model including an equally wellthought-out set of explanatory variables might yield different results.

Fourth, although environmental uncertainty and environmental hostility are related to observedheterogeneity, there is also unobserved heterogeneity that cannot be attributed to pre-determinedvariable(s). As noted by Sarstedt et al. (2011), unobserved heterogeneity would lead to misinterpre-tation of PLS path-modelling results if it is not considered in the analysis. Thus, future researchshould investigate this essential issue by using mixture PLS such as FIMIX-PLS (Money et al.,forthcoming).

Fifth, decision success is multifaceted in nature. This means that a decision may be successfulfrom one aspect; for instance, it achieves its stated objective. However, unforeseen consequencesof the decision, such as on employee morale, may represent a failure. Hence, a limitation of thisstudy and most of previous research is that they apply a single indicator of success e in ourcase decision disturbance. Therefore, as suggested in Figure 2, future research needs to considerthe multi-dimensional nature of decision success by examining the relationship between intuitionand different types of decision outcomes in order to have a better understanding of this compli-cated relationship. A good way to do so is to ask the people who make the decision to observeits effects and comprehend its context to judge, retrospectively and on several indicators, howthe decision turned out. Similarly, Nutt (2002) suggests that the documentation of decision successrequires multiple measures to capture the different dimensions of decision success.

Research needs to consider the multi-dimensional nature of decision success.

Finally, we should also acknowledge the limitations of the survey study, such as inability to trackchanges over time or capture causal relationships and errors associated with reporting past behav-iour. As discussed above, we attempted to minimise these limitations.

Directions for future researchSeveral lines of future research are suggested by this study. First, an important development wouldbe to incorporate other predictors of intuition into the theoretical framework for intuition. As sug-gested in Figure 2, these could include some of the following variables: affect or emotions, experi-ence, organizational culture (e.g., Sonenshein, 2007), decision complexity (e.g., Hensman andSadler-Smith, 2011), decision type (Papadakis et al., 1998), confidence (e.g., Leybourne andSadler-Smith, 2006), thinking styles, mood states, decision structure (Sadler-Smith and Sparrow,2007), and implicit and explicit learning (e.g., Dane and Pratt, 2007). Other variables may be ex-amined as moderators such as environmental turbulence (e.g., Dayan and Elbanna, 2011) and en-vironmental instability (e.g., Fredrickson and Iaquinto, 1989; Khatri and Ng, 2000).

Second, researchers need also to control for the effect on the intuition-outcomes link of severalvariables at different levels. At the personal level, these would include level of agreement with thedecisions and self-confidence in intuition; at the decision level: quality of decision implementation;at the organizational level: organization size; at the industry level: type of industry; at the environ-mental level: environmental favourability and country or region. It is worth noting that accordingto the research design proposed in Figure 2, antecedents of intuition might be used as moderators,such as performance (e.g., Elbanna and Child, 2007b), or controls such as size (e.g., Khatri and Ng,


2000), and vice versa. Moreover, some researchers examine the moderating impact of environmen-tal variables on both the intuition-outcome link and the relations between antecedents and intui-tion (e.g., Dayan and Elbanna, 2011).

Third, a more precise understanding of the causal relationships between antecedents and decisionintuition requires the adoption of a longitudinal research design (e.g., Dean and Sharfman, 1996;Pettigrew, 1990). For example, a longitudinal design may help to reduce the limitations of our crosssectional/survey study such as reliance on the responses of managers who articulate a post hoc jus-tification in order to rationalize their intuitions.

Fourth, intuition remains an understudied mental process with respect to its role in the strategicdecision-making process. Further empirical research, together with continued theoretical develop-ment, will help us to construct well-developed alternative theoretical perspectives on the subject.

Fifth, when researchers have found a negative relationship between rationality and organizationaloutcomes, there has been a tendency to suppose that intuition is an alternative that is better suitedto the prevailing environmental circumstances. However, it does not follow that the use of intuitionand rationality are simply alternatives. Both approaches could be used as “dual processes” whereby,for example, rationality is employed up to its limits in terms of the availability of relevant informa-tion and intuition takes over beyond those limits. For example, Woiceshyn (2009) examines howdecision makers manage complex situations by combining rational analysis with intuition. Itmay therefore be more appropriate to conceive of intuitive and rational-comprehensive processesof decision-making as two complementary systems of understanding used to inform strategic de-cision making. Environmental circumstances are likely to have relevance for the weight each processhas in arriving at a decision, but it would be an over-simplification to conclude that decision-makers opt for the one approach rather than the other.

Hence, as shown in Figure 2, further research should investigate intuition as a dual process in thecontext of strategic decision making. As argued by Hodgkinson et al. (2008), dual process formu-lations such as CEST (Epstein, 1994), the associative/rule-based theory (Sloman, 1996), and C-sys-tem-X-system distinction (Lieberman et al., 2004) provide a promising framework forunderstanding the dynamics of intuitive and rational processing.

Sixth, drawing from Langley’s (1989) framework of decision rationality and recent reviews onintuition (Akinci and Sadler-Smith, 2012; Sinclair, 2011), future research can extend this workin order to enhance our knowledge on intuition types (Gl€ockner and Witteman, 2010; Pretz,2011), purposes (e.g., Klein, 2002; Mueller et al., 2007) and outcomes (Akinci and Sadler-Smith,2012; Dane and Pratt, 2009) (see Figure 2).

Seventh, as previously mentioned, the use of Khatri and Ng’s (2000) scale of intuition in thisstudy was found to be justified, and it was significantly correlated with the well-establishedScott-Bruce measure of intuitive decision-making style. However, some authors have recently ar-gued that Kathri and Ng’s scale should be refined to include more facets, and to improve its psy-chometric properties (e.g., Sadler-Smith, 2010: 164-165). As depicted in Figure 2, this is anotherpromising avenue for further research to capture the essence of intuitive processing, as containedin many relevant theoretical and empirical studies, in order to capture intuition beyond using per-sonal judgment and gut feeling.

ConclusionThis paper offers five main contributions to knowledge: 1) it contributes to understanding the useof intuition in decision making in the context of organizations by developing a model of the con-textual influences on and consequences of intuition, and controls for the effect of rationality; 2) itreports research conducted in a non-Anglo-Saxon setting; 3) it examines the impact of intuition ona hitherto unresearched decision outcome variable, decision disturbance; 4) on a practical note, itpoints to the variables that may lead to the use of intuition in the strategic decision-making processand its impact on decision disturbance; and 5) it concludes with a new theoretical model of intu-ition in strategic decision-making which can be considered as a highly plausible foundation for


further research on intuition. In formulating the new model, we also highlight some methodolog-ical concerns which should be considered by further research. The new model can help decision-makers to better understand intuition and value it as a legitimate mental function that is particu-larly useful for strategic decision-making in some situations.

AcknowledgementsThe first author gratefully acknowledges the research grant from the UAEU (Research Project #FSRGP/2009/BUSA/002) that supported the preparation of this paper. The authors wish to thankthe guest editors and two reviewers for their insightful comments. The authors are also grateful toDavid Wilson, Kilani Ghoudi, and C. Anthony Di Benedetto for their comments on earlier drafts ofthis paper.

Appendix 1. The exploratory studyData collection in the first stage exploratory study covered both private and state-owned firms.One-hundred and twenty-eight questionnaires were collected from a wide range of industries, rep-resenting chemicals, food, cement, cars, metals, furniture, paper, railroads, poultry products, elec-trical and electronic goods, and textiles. Two responses per company were collected from elevencases to check inter-rater reliability. Examples of decisions examined are downsizing, launchinga new product, new investment, geographical expansion and restructuring.

Along with the survey questionnaire, the first author conducted thirty-six semi-structured inter-views, with executives who closely participated in making strategic decisions, in both private andpublic sectors. These were divided into twenty-one interviews in private business sector companiesand fifteen interviews in public business sector companies. All interviewees were male. We followedseveral rules for the interviews, e.g., detailed interview notes and impressions were completedwithin one day of the interview. The interviewer started the interview by explaining the natureof the present study, and the benefits the interviewee would get from this research. The followingare examples of questions which were included in our interview guide: 1) “How and when did thisdecision start and finish?”; 2) “Please provide me with a detailed description of this decision, theprocess followed in making it, the main sequence of events from its inception to its completion,and the interactions between decision-makers.”

The exploratory stage was used to 1) clarify concepts; 2) operationalize measures; 3) determinethe practical problems of carrying out the research; 4) finalize our theoretical model; and 5) enrichthe discussion of our results. For example, the interviews revealed that top management teams instate-owned manufacturing companies in many cases were not allowed to take strategic decisionswithout getting approval from their holding companies. Indeed, their top managers were takingsome strategic decisions merely in response to governmental policies. The decision to initiate anearly retirement policy, for instance, which was one of the most frequently arising decisions inthe first stage sample, was merely the implementation of the government’s policies related to itsprivatization programme. Given these limitations, state-owned firms were excluded from the sec-ond stage of the investigation.

The first exploratory stage, also, helped us to exclude some variables from our model, rewordsome questions, refine questionnaire design and enrich our interpretation of the findings. For ex-ample, because of the considerations of sensitivity of Egyptian executives to items related to pol-itics, two items were removed from the scale of environmental uncertainty (i.e., the ability of theparty in power to maintain control of the country and the threat of armed conflict in the MiddleEast). These two items led to respondent resistance to cooperate with the researcher. Similarly, thisstudy does not incorporate the demographic and personal characteristics of the decision-makersthemselves because, by contrast to countries like the U.S.A, such data are not publicly availablein Egypt and exploratory direct questioning indicated that Egyptian respondents are reluctant toprovide them.


Appendix 2. Operationalization of the study variables2

Intuition: Khatri and Ng’s (2000) measure of intuition was used in this study for the followingreasons: 1) their measure appears to capture the main indicators of intuition, namely knowing(judgement) and sensing (gut feeling), which have been addressed by previous studies; 2) differ-ent methods have been employed to test the validity and reliability of this measure; 3) Khatri andNg applied their measure to strategic decision-making, which was also the aim of the presentstudy; and 4) using this measure, Khatri and Ng report that intuition is a characteristic that man-agers often exhibit in their strategic decision-making, and that it captures meaningful variationsin the strategic decision-making process. Based on results of confirmatory factor analysis, theirquestion on experience was eliminated from the scale. The interviews indicated that some respon-dents saw the question as a test of whether they have enough experience. For example, the com-mercial director of a textile and clothing company replied: “The long experience of our topmanagement team is enough to make any decision ... this experience permits any member ofthe team to manage one of the biggest consultation centres.” Coefficient alpha for the revisedscale was 0.90. Finally, in a new sample of fifty-two respondents, we examined the relationshipbetween the intuition scale with an established measure of intuitive decision-making style intro-duced by Scott and Bruce (1995) and successfully adopted by other researchers, e.g., Sadler-Smith(2004). Our intuition scale and the Scott-Bruce measure were significantly correlated (r ¼ 0.51,p < 0.01).

Outcomes: It is significant that the largest body of empirical research on organizational outcomesdeals with organizational performance, which is generally not explicitly portrayed as a decision out-come. Drawing on Rodrigues and Hickson (1995), we used a perceptual measure of decision out-comes, namely decision disturbance (the existence of major negative unexpected outcomes of thedecision). This measure can be applied to all types of strategic decisions in different organisations,which is an important consideration since the present study includes different decisions from var-ious kinds of organisations working in different manufacturing sectors.

Context: Three items developed by Khandwalla (1977) and successfully used by many re-searchers (e.g., Papadakis et al., 1998) were used to measure environmental hostility. Investiga-tion of the measure of environmental uncertainty (Miller, 1993) during Stage 1 suggestedseveral changes to overcome operational problems, such as the ambiguity of some items, ques-tionnaire length, and the sensitivity of managers to political issues as discussed in Appendix 1.Factor analysis was used to inform the reduction of items to a more manageable number(Gerbing and Anderson, 1988). The original thirty-five environmental items were reduced totwenty-one, still retaining four of the original six components. After conducting Stage 2, thetwenty-one items of environmental uncertainty and the three items of environmental hostilitywere factor analysed, and five factors were derived: four factors for environmental uncertaintyand one factor for environmental hostility. The five factors are consistent with the hypothesizedstructure of constructs.

Depending on Hart and Banbury’s conclusions (1994), ten items of financial, market and non-financial performance were postulated. Respondents were asked to assess their companies’ perfor-mance on each of these items in relation to major competitors (e.g., Khatri and Ng, 2000). Com-parisons were scored on a 7-point Likert scale for each item ranging from one (very poor) to seven(excellent). Based on results of factor analysis, two items were eliminated from the scale, namely,new product development and diversification into new business. In line with many previous stud-ies, company size is assessed by the number of full-time employees. This statistic is more willinglymade available by companies than others, such as sales turnover and is less prone to erroneous orfalse reporting.

To measure decision motive, two questions were asked based on our conception of opportunityand crisis, which is described by Mintzberg et al. (1976, p. 251) as follows: decisions may be cat-egorized by the stimuli that evoked them along a continuum. At one extreme are opportunity

2 Further information on the operationalization of the variables can be obtained from the first author.


decisions, those initiated on a purely voluntary basis, to improve an already secure situation. Atthe other extreme are crisis decisions, where organizations respond to intense pressures. Here a se-vere situation demands immediate action. Five items derived from previous research (Beach andMitchell, 1978; Dean and Sharfman, 1993; Papadakis et al., 1998) and successfully used by otherscholars (e.g., Dayan and Elbanna, 2011) were used to measure decision uncertainty. Based onresults of confirmatory factor analysis, two of the five original items were eliminated fromthe scale.

We measured our control variable e rationality e using three items derived from Dean andSharfman (1996) which reflect well our definition of rationality, “the extent to which the decisionprocess involves the collection of information relevant to the decision and the reliance upon anal-ysis of this information in making the choice” (Dean and Sharfman, 1993: 1071).

Given that the perceptual measures employed may not truly reflect the phenomenon of inter-est, we attempted to reduce this limitation in several ways: 1) scale anchors were reversed in sev-eral places; 2) multiple sources of data were used; and 3) assurances were given of completeanonymity and confidentiality. The Pearson correlation coefficients between the answers of eightrespondents, who completed the identical questionnaire on two different occasions, three monthsapart, range between 0.83 and 0.99. This result suggests a high degree of stability (inter-temporalreliability) of the measures used in this study. Finally, factor analysis of the variables making upeach construct confirmed the unidimensionality of each construct.

Measurement items

Decision motive

Item 1 To what extent did you have adequate freedom in addressing this decision?

Item 2 What was the motivation for the company in making this decision e crisis or opportunity?

Decision uncertainty

Item 1 How confident were the decision-makers that they were making the right choice?

Item 2 To what extent were the goals of this decision clear for the participants?

Item 3 It was not at all clear what kind of information we should collect so as to make this decision.

Financial and market performance

Item 1 Return on assets

Item 2 Operating profits

Item 3 Market share

Item 4 Growth rate of sales or revenues

Non-financial performance

Item 1 Quality of product

Item 2 Employee satisfaction

Item 3 Efficiency of operations

Item 4 Social responsibilities

Company size

Item 1 Number of full time employees

Intuition

Item 1 To what extent did participants in making this decision rely basically on personal judgment?

Item 2 On many occasions, decision-makers do not have enough information, and must make decisions

based on a ‘gut-feeling’. To what extent did participants in making this decision depend on a ‘gut

feeling’ to make it?

Rationality

Item 1 To what extent did the decision-makers gather relevant information for making this decision?

Item 2 How extensively and thoroughly did the decision-makers analyse relevant information for making

this decision?

Item 3 How successful were the decision-makers at focusing their attention on crucial information

during making this decision?


Decision disturbance

Item 1 To what extent were there any major negative unexpected outcomes of this decision?

Environmental uncertainty

21 items Clients’ preferences, demand, changes in product components, changes in product quality, new

product, changes in the production process, inflation rate, exchange rate with the dollar, interest

rate, results of economic restructuring, changes in competitors’ prices, markets and strategies,

entry of new companies into the market, tax policies, monetary policy, public service provision,

control of prices, legal regulations, national laws, tariffs on imported goods

Environmental hostility

Item 1 Threat to survival

Item 2 Stressfulness

Item 3 Dominance over the company

Note: All items are measured using a seven-point scale.

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BiographiesSaid Elbanna received his BCom (Hons) and MBA from Cairo University, Egypt, and his PhD from the university

of Birmingham, the UK. He is an Associate Professor, the founding director of the UAEU Centre for Strategic

Management at the United Arab Emirates University, and a Strategic Advisor at Alain Municipality in the UAE. His

main research interests are strategic decision-making, strategic planning, internationalization of SMEs, and new

product development. He has published in academic journals such as Strategic Management Journal, Journal of

Product Innovation Management, Journal of Management Studies, and International Journal of Management Reviews.

His awards include the JMS Best Paper Award for 2007. E-mail: [email protected]

John Child received his PhD and ScD from the University of Cambridge, UK. He is Emeritus Professor of Com-

merce at the University of Birmingham, UK. His research interests include the internationalization of SMEs,

and new organizational forms. He has published twenty-one books and over 150 articles. His book co-authored

with Suzana Rodrigues, Corporate Co-evolution, published by Wiley won the 2009 Terry Book Award of the

Academy of Management. His latest books are The Evolution of Organizations and The Dynamics of Co-evolution,

both published by Edward Elgar. E-mail: [email protected]

Mumin Dayan is an Associate Professor at UAEU, Al Ain, UAE. He received his M.B.A in Marketing from the Ben-

nett S. Le Bow College of Business at Drexel University, and his Ph.D. in Marketing from the Fox School of

Business at Temple University, Philadelphia, PA. His current research areas are new product/technology devel-

opment, cognitive/social psychology in innovation and small business management, and decision-making in teams.

His work has been published in a variety of leading journals, including Journal of Product Innovation Management,

R&D Management, Information & Management and Journal of Business and Industrial Marketing.

E-mail: [email protected]


mailto:[email protected]



A Model of Antecedents and Consequences of Intuition in Strategic Decision-making: Evidence from...

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