The global body for professional accountants
Trust and confidence in SMEs’ use of advisers.
Prof. Robin Jarvis (Brunel University; ACCA)Emmanouil Schizas (ACCA)
The global body for professional accountants
THE AGENDA IN BRIEF
• Accountants are the most likely advisers of SMEs in many countries
• Deregulation reduces compliance work• (Cross) selling value-added services
requires combination of demonstrated competence and trust
• Accountants and clients disagree re: importance of rapport v. competence
• Many SMEs don’t take advice at all
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CALLS FOR VALIDATION
• Trust & competence must be securely inferred from behaviour
• Must be distinct• Must be compartmentalised• Must interact• Framework must apply to other
business support, esp. Government-funded
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Distinguishing between Trust, Confidence and Familiarity (Luhmann 2000)
Dimension Trust Confidence Familiarity
Focus of disappointment (Barber 1983)
Fiduciary duty Effectiveness Natural / moral order
Dimension of 'trust' (1)(Mouzas et al, 2007)
Individual trust Business trust N/A
Dimension of 'trust' (2)(Tyler & Stanley, 2007)
Affective trust Calculative trust N/A
Nature of contingency Risk Danger Danger
Assumed characteristic Benevolence / affinity Competence Continuity
Attribution of outcomes Internal External Nonpersonal
Perception of alternatives High Low None
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• 1,777 SMEs• 6 countries • Nov 2010
THE FORBES INSIGHTS (2010) DATASET
• Taxation• Financing• Financial
Management• Legal and
regulatory• Marketing• Operations• Technology
• Friends and family• Trade & Prof. Assoc• Business association• Professional colleagues• Accountants• Attorneys• Banks etc• Online resources• Others
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KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .664
Bartlett's Test of Sphericity
Approx. Chi-Square 17324.081
Df 2926
Sig. .000
• Factor Analysis• Promax rotation
(oblique)• Input: 7x11
dummies• Output: 6 factors
explaining much of the variation in use of advice by SMEs
Proxies for the need for confidence and trust
‘Crossover’Experts
InternetFamily & Friends‘Reading Up’
Business Associations
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TESTING THE ‘CROSSOVER’ FACTOR
• Two tests against Luhmann (2000)
• Greater ‘need for trust’ creates more internal attributions for failure
• Greater ‘need for trust’ leads to a wider use of ‘alternative’ advisers
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USING THE FACTORS
• Correlation of adviser use with need for trust/confidence = implied trust/confidence
• Comparisons suggest optimal engagement strategies for government and private sector advisers
• Market segmentation explains why competence comes first
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Transaction
Casual/no relationship
Partnership
Conversation
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Comparing confidence in accountants and government in the UK
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Comparing trust in accountants and government in the UK
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OTHER FINDINGS (I)
• The use of value added advice may be driven more by clients rather than by advisers
• The combination of confidence and trust does further drive demand for value added advice
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OTHER FINDINGS (II)
• Experts rarely enjoy as much trust as assumed – mostly confidence
• Accountants benefit from perception of broad competence
• But this is not universal• Accountants outperform government
but there may be a case for an independent broker for financial mgmt
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CONTACTManos [email protected]
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EstimateStd. Error Wald df Sig.
95% Confidence Interval
Lower Bound Upper Bound
Got all of the finance applied for 1.232 .299 16.990 1 .000 .646 1.819 Got most of the finance applied for .849 .275 9.551 1 .002 .311 1.388 Got some of the finance applied for .514 .274 3.518 1 .061 -.023 1.052 Got none of the finance applied for 0a . . 0 . . . Community cross-over .233 .241 .935 1 .334 -.239 .705 Expert -.011 .279 .002 1 .968 -.557 .535 Internet -.066 .071 .846 1 .358 -.206 .074 Friends and Family .018 .082 .051 1 .822 -.142 .179 Reading up -.058 .075 .590 1 .442 -.206 .090 Business Association -.196 .073 7.243 1 .007 -.339 -.053 Got all finance * Community -.896 .302 8.816 1 .003 -1.488 -.305 Got most finance * Community -.597 .273 4.793 1 .029 -1.132 -.063 Got some finance * Community -.596 .280 4.520 1 .033 -1.146 -.047 Got no finance * Community 0a . . 0 . . . Got all finance * Expert .153 .316 .233 1 .630 -.467 .773 Got most finance * Expert .146 .303 .232 1 .630 -.447 .739 Got some finance * Expert .150 .303 .246 1 .620 -.443 .743 Got no finance * Expert 0a . . 0 . . . Note: The regression analysis also controlled for employment, turnover, legal status, type of customer (B2B v. B2C), Turnover growth (past and expected) and country. Note also that the dependent variable was coded as (1 = total agreement … 5 = total disagreement).
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Est.Std.
Error Wald df Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Community cross-over 1.097 .080 190.002 1 .000 .941 1.252
Expert .047 .064 .546 1 .460 -.078 .173 Internet .752 .061 153.554 1 .000 .633 .871
Friends and Family .546 .068 64.034 1 .000 .412 .679
Reading up .455 .063 52.023 1 .000 .331 .578
Business Association .736 .063 135.503 1 .000 .612 .860
Less than $2m turnover -.518 .325 2.536 1 .111 -1.156 .120 $2m to $4.9m turnover -.266 .326 .667 1 .414 -.905 .373 $5m to $9.9m turnover -.573 .334 2.946 1 .086 -1.227 .081 $10m to $24.9m turnover -.380 .348 1.189 1 .276 -1.063 .303
Over $25m turnover 0a . . 0 . . . No employees -.683 .375 3.317 1 .069 -1.418 .052 1 to 9 employees -.662 .221 8.989 1 .003 -1.094 -.229 10 to 49 employees -.323 .179 3.241 1 .072 -.674 .029 50 to 99 employees .041 .206 .040 1 .841 -.362 .444 100 to 249 employees 0a . . 0 . . .
Note: The regression analysis also controlled for employment, legal status, type of customer (B2B v. B2C), Turnover growth (past and expected) and country; only significant effects are highlighted on this table.