Abstract
Purpose
Information verification is an important factor in commercial valuation practice. Valuers use their professional autonomy to decide on the level of verification required, thereby creating an opportunity for client-related judgement bias in valuation. The purpose of this paper is to assess the manifestation of client attachment risks in information verification.
Design/methodology/approach
A case-based questionnaire was used to retrieve data from 290 commercial valuation professionals in the Netherlands, providing a 15 per cent response rate of the Dutch commercial valuation population. Descriptive and inferential statistics have been used to test research hypotheses involving relations between information verification and professional features that may indicate client attachment such as an executive job level and brokerage experience.
Findings
The results reveal that valuers acting at partner level within their organisation obtain lower scores on information verification compared to lower-ranked valuers. Also, brokerage experience correlates negatively to information verification of valuation professionals. Both findings have statistical significance.
Research limitations/implications
The results reflect valuers’ reasoning behaviour rather than actual behaviour. Replication of findings through experimental design will contribute to research validity.
Practical implications
Maintaining close client contact in a competitive environment is important for business continuity yet may foster client attachment. The associated downside risks in valuation practice call for higher awareness of (subconscious) client influence and the development of attitudinal scepticism in valuer training programmes.
Originality/value
This paper is one of the few that explore possible sources of valuer judgement bias by relating client-friendly valuer features to a key area of valuation i.e. information verification.
Keywords
Citation
Klamer, P., Gruis, V. and Bakker, C. (2019), "How client attachment affects information verification in commercial valuation practice", Journal of Property Investment & Finance, Vol. 37 No. 6, pp. 541-554. https://doi.org/10.1108/JPIF-04-2019-0059
Publisher
:Emerald Publishing Limited
Copyright © 2019, Pim Klamer, Vincent Gruis and Cok Bakker
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Professional standards require real estate valuers to produce accurate valuations sustaining public confidence in their work. The importance of information verification skills in this is recognised by relevant professional institutions, which require valuers to undertake reasonable steps to judge the extent to which the information provided is likely to be reliable (RICS, 2017; TEGoVA, 2016). However, the accuracy of valuation reports is debated due to perceived influence of clients impacting valuer’s autonomy (Levy and Schuck, 2005). Valuers are often hired, paid and fired by clients to provide value estimates on their properties, indicating issues of client attachment, independence and associated judgement bias (Baum et al., 2000; Newell et al., 2010).
Acting in competitive market places, valuers often work under time pressure to deliver their reports. When it comes to information verification, a valuer needs to find a balance in effort, somewhere on a continuum between the extremes of paranoia (i.e. overdone effort which will boost quality yet extend the process) and naiveté (i.e. limited effort implying lowering reporting quality yet assuring timely completion) (Nelson, 2009). Valuers use their professional autonomy to make such judgemental decisions, providing scope for judgement bias related to client influence and the use of heuristics. As such, the context of valuation practice does not materially differ from other professional service industries as tax, audit and consulting (Tepalagul and Lin, 2015). However, the topic of judgement bias has been explored only marginally in real estate valuation, contrary to for instance the field of auditing where it has received wide research attention (Trotman et al., 2011; Klamer et al., 2017).
Bias in judgement may expose itself in various ways, ranging from deliberate bias (i.e. fraud) to sub-conscious levels of bias. Regardless the manner, the manifestation of bias is by definition idiosyncratic and may relate to one’s knowledge base, experience or personality. Psychological research on the impact of self-serving bias proposes that unconscious judgement bias is far more pervasive than conscious bias (Moore et al., 2006). Furthermore, it is argued that professionals are often unconsciously less sceptical of clients with whom they have developed close working relationships (Bazerman et al., 1997).
However, studies on valuer characteristics in relation to client-related bias seem limited. Levy and Schuck (1999) find that age and experience could impact valuation outcomes, as younger valuers tend to be more methodological in their approach, whereas older and more experienced valuers tend to make greater use of “gut feeling” in their judgement. In addition, valuers that are involved in commercial work (i.e. brokerage activities) tend to be vulnerable to judgement bias (Northcraft and Neale, 1987; Amidu and Aluko, 2007). Aluko (2007) finds that heads of combined valuation and agency departments, while experienced, are likely to demonstrate judgement bias as well. Given the close interaction between professional and client in valuation practice, we consider the limited attention on valuer characteristics in relation to client-related judgement bias a drawback in behavioural valuation research.
This paper aims to shed more light on the manifestation of client-related bias in valuation practice. More specifically, it concerns the relationship between a valuer’s choice of information verification and professional work experience and job position. We performed this study in the Netherlands using case-based questionnaires. Dutch commercial valuers operate in a transparent market place featured by strong market competition (JLL, 2018). In 2015, the Dutch valuation industry witnessed the instigation of stricter valuation guidelines with the launch of a new certification institute “NRVT”. Advanced regulations are in part based on “best practice” recommendations adopted from the audit industry (NRVT, 2017; PTA, 2013). The combination of a competitive market setting and increased guidelines provide challenging circumstances to Dutch valuers with regard to information verification effort, time pressure and client retention.
The remainder of this paper is structured as follows. The next section comprises a literature review on client attachment in professional service industries in order to deduce our research hypotheses. Subsequently, we present our research methodology. The final section outlines key findings and discusses practical implications.
2. Review of the literature
Successful performance in professional service firms require professionals to act independently, i.e. be free from relationships that a reasonable person would expect to increase the risk of losing judgement-making impartiality (Johnstone et al., 2001). However, successful performance often also requires close interaction with clients (Achu, 2013). This may be referred to as the “client contact paradox”, referring to an effective client mode while balancing between public and private interests. Johnstone et al. (2001) point to the dual impact of incentives with regard to judgemental quality in such industries. Direct incentives (i.e. monetary benefits such as fee income, employment, financial reliance on clients) and indirect incentives (interpersonal relationships with various stakeholders including client relationships) are meant to stimulate and reward high service quality, yet can punish malpractice performance (Shaub and Lawrence, 2002; Johnstone et al., 2001). Given that clients have discretionary power to terminate service provision, the concept of service failure can easily be stretched to include the extent to which clients’ needs are not being fulfilled or interests are not being served. For example, a real estate valuer showing inflexibility to reconsider his valuation figure for a loan requirement may trigger client switching behaviour (Levy and Lee, 2009).
In this regard, reference is made to an upcoming commercialism in professional service industries. In auditing firms the traditional professional-technical orientated view on auditing, which underlies the provision of public sustainable audit opinions, has been overcome by a commercial logic associated with revenue growth and future business perspectives (Spence and Carter, 2014; Liu and Simunic, 2005). Valuation and auditing professionals both perform public interest tasks in a commercial environment, and often work together in preparation of financial reporting standards.
In response to client attachment-sourced audit failures, a call for “professional scepticism” towards evidential input was introduced in 1988 in auditing standards, which has since been regarded as a key component of professional due care (Nelson, 2009). The element of professionalism in information verification characterises the propensity of an individual to defer concluding until the evidence provides sufficient support while disregarding client opinions or client interests (Hurtt, 2010). It therefore requires both attitude and effort, including a questioning mind and a critical assessment of relevant evidence (Shaub and Lawrence, 2002).
Valuation and auditing professionals face comparable client-related issues challenges, as both perform public interest tasks in a commercial environment. As valuers more often assist in the preparation of international financial reporting standards, the International Valuation Standards Council identified the need for more effective cooperation between both professions (IVSC, 2012). The “client attachment” concern was also raised in Dutch valuation practice by local regulators (Klaver, 2017). The Dutch valuation industry is organised relatively fragmented, with about 2,000 commercial real estate valuers presently working in approximately 1,400 organisations (NRVT, 2018). Consequently, relatively many valuers will hold a senior or partner position within their respective firms. Furthermore, Dutch real estate professionals are allowed to combine valuation and brokering activities in professional practice (albeit not simultaneously and subject to meeting the relevant certification routes for each track). From the perspective of clients, professionals who offer multiple services to a single client or perform their work on executive levels may be (perceived to be) incentivised to support client interests on account of a profound client relationship or economic incentives. This leads us to two features of attachment risks: job level and brokerage experience.
Job level
Higher ranked professionals usually may have more professional experience but also more personal involvement in judgement behaviour than lower-ranked professionals, as it is likely that they have served their clients longer (Bonner, 2008). Valuers with equity ownership within their firm combine several professional roles including the role of principal (co-owner sharing in organisational profits and responsible for revenue growth) and agent of the firm (protecting the firm’s reputation and managing output quality). These – potentially conflicting – roles need to be aligned in the partner’s incentive package through firm compensation arrangements. Coram and Robinson (2017) indicate that audit partners whose compensation is closely tied to business revenue and client retention are more likely to be influenced by client evidential preferences.
Basically, professionals with solid industry expertise should be able to counter the client’s preferences on evidential input with persuasive arguments. However, Shaub and Lawrence (1996) state that the effect of experience could be confounded by lower stages of ethical reasoning once higher positions in the firm have been reached (Ponemon and Gabhart, 1990). Knechel et al. (2013) add that partners have a high degree of autonomy to exercise professional judgement in the course of an engagement, based on relevant experience achieved. Judgement quality may be affected if compensation incentives undermine the partner’s scepticism and objectivity towards commercial client interests.
Based on the above, we postulate that valuation professionals that reached partner level benefit from substantial professional experience, maintain longstanding client relationships and enjoy high autonomy in judgement and decision making. Yet, higher ranking implies more incentive-based compensation packages, potentially fuelling a more client-oriented attitude in comparison to lower-ranked valuers. Hence, for the first research hypothesis, we expect valuers who hold a partner position within their organisation to obtain lower scores on information verification than less senior valuers.
Brokerage experience
The supply of multiple services within a business practice, such as combining audit and financial consulting or valuation and brokering services, can be viewed as either leading to efficiencies or impairing objectivity (Frankel et al., 2002). The first view is that the professional’s knowledge of the client company is enhanced, and that such knowledge spill-over effects increase efficiency effects. The latter view is that economic dependence is increased and the relationship becomes too close, adversely impacting independence.
The commercial role of brokering activities, i.e. best serving the client’s private interests in real estate transactions, strongly contradicts the public nature of valuation activities. Real estate brokers benefit from a client-friendly attitude, while valuers are expected to provide accurate and independent valuations upon which real estate financiers and investors – and ultimately the entire financial system – can rely. A professional offering both services to clients may face professional dilemmas upon role switching. The more services are provided to a single client, the greater the dependence will be on the client and hence the greater the desire will be not to lose that client’s (future) services (Herath and Pradier, 2018; Beattie and Fearnley, 2002). Cross-selling hence provides a trigger for client attachment (Shaub and Lawrence, 1996; Nelson, 2009). As such, brokerage experience may enforce a commercial, client-friendly attitude that (sub-)consciously impacts valuation objectivity.
Based on the above, we propose that the provision of valuation in combination with brokerage services creates client attachment through both economic incentives and interwoven client relationships. As a result, valuers with (substantial) brokerage experience may perform less critical information verification. For the second research hypothesis, we therefore expect brokerage experience to show negative correlation with information verification.
3. Research methodology
Questionnaire structure
In order to test our hypotheses, we have set up a case-based questionnaire that is distributed by means of an online survey tool. Besides its reach within the population, a questionnaire survey will enable us to distinguish variance in levels of information verification across respondents and statistically explore links with client attachment indicators (Verschuren and Doorewaard, 2015). Furthermore, the advantage of response anonymity should reduce potential social desirability bias effects (e.g. stimulate “correct” answering behaviour rather than truthful answering) (De Lange et al., 2016). Our questionnaire consists of three parts:
respondent profile features to confirm sample homogeneity and provide relevant valuer characteristics for hypothesis testing;
three business cases offering three recurring answering modes to choose from; and
six Likert-based statements (scale 1–5) reflecting self-perceptive views on information verification.
The three cases involve practical work situations in different stages of valuation practice (i.e. input/process/output stage) and are based on prior research on valuer’s perception of task complexity (Klamer et al., 2018). The respondent is required to select one (out of three) recurring answer modes in each case. An example case is included in Appendix 1. To acknowledge potential client attachment issues in information verification, we refer to Johnstone et al.’s (2001) typology of independency risk. Their typology is used to exhibit varying information verification strategies in case answer modes as follows:
substantial information verification (SIV), reflecting a questioning mind towards client-related information as evidential input in value assessment;
limited information verification (LIV), reflecting a client-friendly mind towards client-related information as evidential input in value assessment; and
refusal of information verification (RIV), i.e. reflecting a (risk-)averse mind towards client-related information as evidential input in value assessment.
Substantial information reflects a neutral stance as valuers are expected to soundly investigate all input information, including information derived from clients or related to client interests. However, sound investigation requires verification which may entail risking project deadlines and time budgets (Shaub, 1996). Contrary, valuers that opt for limited verification have a tendency to easily trust their clients because they assume others are generally trustworthy (Fatmawati et al., 2018). Such an attitude may stimulate acceptance of biased information rather than (critical) examination (Toba, 2011; Einhorn and Hogarth, 1981). Rejection of subjective client-related information relates to valuers who do not easily trust people and endorse a presumptive doubt perspective (Fatmawati et al., 2018). Such an attitude may imply high quality standards and loose economic bonds with clients due to concerns over litigation and reputation risk, yet it may overlook potential relevant information to substantiate reporting (Nelson, 2009; Shaub, 1996).
In order to enhance construct validity, all three cases reflect realistic work-related situations of different parts of valuation practice that have been discussed with three senior commercial valuation professionals to ensure realistic yet neutral answer modes. Furthermore, to offset potential response bias in case answering we also included six statements on features of information verification, which function as control variables (CVs) on case answers (i.e. high scores on information verification in the cases would imply high scores on one’s attitude towards information verification). The attitudinal statements are based on Hurtt’s (2010) literature review on characteristics of professional information verification across different fields (e.g. psychology, philosophy and consumer behaviour).
Data sample
At the time of research, NRVT holds approximately 7,000 registrations of qualified valuation professionals in the Netherlands. This includes approximately 2,000 commercial property valuer registrations (i.e. excluding residential and agricultural valuation services). The commercial subset of 2,000 professionals is our population (NRVT, 2018).
In order to achieve satisfactory response on our case-based questionnaire, we have made use of two surveys. One survey was sent out to commercial valuation professionals enlisted with the Academie voor Vastgoed, a nationwide institute for permanent real estate education. The other survey was distributed to commercial valuers registered at Dutch valuation certification institute NRVT who had not enroled at the Academie voor Vastgoed. We performed sample distribution analysis on both subsets which revealed no material differences on professional features of respondents. This enables us to combine both subsets into one sample of 290 respondents, resulting in an overall 14.5 per cent response rate.
The relatively low response rate can partially be explained by non-response feedback, which included incorrect sampling (i.e. respondent was not yet or no longer registered as a full commercial valuer) and timing issues. In addition, the fact that the business cases may require some mental effort may explain the relatively low response rate as well: a total of 241 respondents aborted the questionnaire when reaching part two involving the business cases. We tested for non-response bias by examining the difference in profile features between finished (290) and unfinished (241) questionnaires. Depending on the measurement scale of variables such as age, education and organisational size, we applied t-tests, Mann–Whitney U tests and χ2 tests to specify differences in respondent profiles between the two groups. No significant differences (p<0.05) in profile features emerged as is illustrated in Table AI.
Data analysis
In order to test our hypotheses we made use of SPSS Statistics software version 24. Information verification is measured ordinally, as is explained in the next section. Job level, the first independent variable, is ranked ordinally (e.g. ranging employee/manager/(co-)owner). We applied a non-parametric Kruskal–Wallis H test to analyse mean variance differences for job level data (Baarda et al., 2014). Kruskal–Wallis is considered the non-parametric alternative to the one-way ANOVA test and an extension to the Mann–Whitney U-test to allow for a comparison of more than two independent groups (De Vocht, 2012). Brokerage experience is the other independent variable, which is measured as a discrete variable shown in number of years. Standard correlation testing procedures for variables measured at least at ordinal level have been conducted using Spearman’s ρ and Kendall’s τ rank coefficients.
4. Results and discussion
Descriptive statistics
We provide some descriptive sample data in Table I. The total sample reflects a relatively senior group of professionals as evidenced by education, age, firm position and working experience, which is working predominantly in small- and medium-sized professional service firms. The average sample age of 51.0 years resembles the average population age of NRVT registered valuers of 50.6 years.
Individual respondent’s case results on information verification are shown in Table II. With professional standards emphasising sound investigation during valuation practice (RICS, 2017; TEGoVA, 2016), the high scores on “substantial” verification are not surprising.
Given our hypotheses, we concentrate our analysis on substantial verification scores and relate relatively low scores on this preferred mode of professional performance to client attachment features. We therefore ranked the number of SIV scores across three cases, as is shown in Table III. The mode of 2 is selected by 122 respondents (42 per cent), while 64 valuation professionals (22 per cent) score low on SIV. Individual scores on SIV across three cases (SIVtotal) will be our dependent variable for hypothesis testing, ranking from 0 to 3 for the number of SIV choices in three cases.
Hypotheses testing
Below we provide testing results for information verification in relation to our research hypotheses on job level and professional experience. Our first research hypothesis states that:
SIVtotal is lower for valuers acting at (co-)owner level within their organisation than for other job levels (i.e. acting at manager or employee level).
Therefore, we assume a null hypothesis of equal distribution of SIV scores across categories of job level. Alternatively, co-owner valuers score lower on SIV than other types of valuers:
SIVtotal scores of (co-)owners do not differ from SIVtotal scores of lower-ranked job levels.
SIVtotal scores of (co-)owners are lower than SIVtotal scores of lower-ranked job levels.
Results are provided in Table IV. Managers score higher on SIV than employees on average, reflecting their experience and responsibility for quality management within the organisation. However, we find that valuers acting at (co-)owner level score an SIV of 2.0, which is lower than both other groups of valuers. Interestingly, average valuation experience of (co-)owners and valuers acting at management level corresponds quite well (19.9 years vs 18.8 years).
In order to examine statistical significance of these differences, we used a Kruskal–Wallis test to obtain SIVtotal mean ranks of job level groups and applied post hoc tests on pair-wise mean rank differences. Using conventional probability errors of 1 and 5 per cent, we find a significant difference (p=0.038) on SIVtotal scores between (co-)owners and managers. Conversely, valuation experience does not significantly differ between managing valuers and (co-)owning valuers (p=0.402). We reject the null hypothesis of equal distribution of SIVtotal scores across job levels, as valuers acting at a (co-)owner job level score lower on information verification in comparison to other valuers and significantly lower vis-à-vis manager valuers (Table V).
Our second research hypothesis states that:
Brokerage experience correlates negatively with SIVtotal scores.
Our null hypothesis assumes no relationship between variables, while the alternative hypothesis follows the hypothesised theoretical direction of negative correlation:
Results are shown in Table VI. Correlation tests on SIVtotal scores have been applied using both Spearman’s ρ and Kendall’s τ coefficients. We find that brokerage experience shows (small) negative yet significant correlation coefficients (p<0.01), indicating that information verification reduces (slightly) with increasing brokerage experience. We therefore reject H20, and accept the alternative hypothesis that brokerage experience correlates negatively with information verification[1].
Interestingly, we performed similar correlation tests on valuation experience and we found comparable negative correlation effects as is illustrated in Table VII (p<0.05). Apparently, when it comes to information verification, the more experienced the valuer becomes, regardless of the type of experience, the less methodologically he or she operates. Although performance usually increases with effort (Che et al., 2018), more experienced valuers tend to trust their gut feeling over methodological scrutiny (Levy and Schuck, 1999). Bonner (2008) adds that experience creates personal involvement in a task, which can have negative effects on judgement quality (i.e. overconfidence bias).
In order to examine case data consistency, we compared respondents’ scores on SIVtotal with self-perceptive CVs. CVs 1 to 6 in Table VIII refer to six characteristics on professional scepticism in information verification. Respondents have been asked to select one option (ranging from 1 – “never” to 5 – “always”).
Average sample scores range from 2.52 on CV 5 (suspension of judgement) to 4.52 on CV 1 (questioning mind). One could argue that these outcomes reflect somewhat conflicting scores on professional features of information verification, as apparently respondents highly recognise a questioning mind attitude, yet at the same time have early indications of valuation outcomes. Interestingly, all types of valuer score relatively low on interpersonal understanding (CV 3), indicating signs of client trusting bias (Table IX).
Given equivalent professional valuation experience levels between managers and (co-)owners, we focus on pair-wise differences between those groups. Significant differences in mean ranks are shown in Table X. We find that differences in three characteristics of professional information verification are significant, albeit in opposite directions when compared to case results (i.e. on all three features valuers at partner level score relatively higher than valuers at management level).
Apparently, (co-)owning valuers do possess the relevant professional traits on information verification, but may not always act in accordance as is evidenced by their relatively low scores in the presented business cases. This outcome implies that the responsibilities that come with the partner position (i.e. balancing commercial, organisational and personal interests) may subdue professional scepticism in information verification effort, due to lack of time or otherwise. Engaging circumstances may prevent such senior valuers to convert sceptical thought into sceptical verification action (Shaub and Lawrence, 2002). Arguably, reinforcement of sceptical action would require enhancing professional development programs in our view, to stimulate bias awareness and improve judgement and decision-making skills when operating within a commercial task environment.
5. Conclusion
This paper involves a study on effects of client attachment upon a valuer’s judgement behaviour, focussing in particular on the relationship between valuers’ experience and job position and their approach to information verification. From our literature review, we expect that a commercial attitude of valuers, as proxied by brokerage experience and partner job level, may negatively affect information verification. Both brokerage experience and firm ownership may stimulate inclination to and identification with clients’ interests. To test these assumptions, we performed a case-based questionnaire in the Netherlands. Our research generates the following conclusions. Brokerage experience tends to correlate negatively with information verification, implying that valuers with high levels of brokerage experience score relatively low on information verification. Also, valuers acting at (co-)owner level within their organisations score lower on information verification in comparison to valuers operating on a lower organisational level with similar levels of valuation experience. Effects of both brokering experience and job level differences appeared significant. We cross-checked case results with self-perceptive Likert scores on professional characteristics of information verification and found that, contrary to case results, (co-)owner valuers score significantly higher on certain relevant traits than valuers operating at management level. This indicates that sceptical thinking with regard to information verification is seemingly well developed at executive levels, yet may be oppressed by environmental influences in relation to commercial interests.
In terms of research implications, we note that our questionnaire reflects reasoning behaviour, not actual performance. While case validity is carefully examined, the results would benefit from experimental research on the subject reflecting real-life valuation settings. Moreover, future research may consider the impact of professional experience in general i.e. does one’s verification effort reduce as experience increases and why?
In light of practical implications, we note that a substantial part of (Dutch) valuers hold ownership positions in SME companies that combine valuation and brokerage services. Close working relationships in professional services industries may trigger client attachment, which seems counterproductive to sound investigation in commercial valuation practice. With client attachment arguably emerging predominantly at sub-conscious levels, the effect of advanced regulation in order to enforce impartial judgement is debatable. Like in auditing, valuation professionals may need to enhance professional scepticism and improve judgement and decision-making skills in order to subdue judgement bias and find a proper balance between professional due care and client management in a commercial task environment.
Descriptive statistics
| Descriptive statistics | Total | |||
|---|---|---|---|---|
| Education | Pre-BSc 59 (20.3%) | BSc 139 (47.9%) | Post-BSc 92 (31.7%) | 290 |
| RICS/REV qualific. | No 236 (81.4%) | Yes 54 (18.6%) | 290 | |
| Age | 51.0 years (11.3) | 247 | ||
| Valuation exper. | 18.3 years (10.0) | 290 | ||
| Brokerage exper. | 16.0 years (11.6) | 290 | ||
| Job level | Employee 67 (23.1%) | Manager 25 (8.6%) | (Co-)owner 198 (68.3%) | 290 |
| Valuation team | <4p. 247 (85.2%) | 4–10p. 31 (10.7%) | >10p. 12 (4.1%) | 290 |
| Company size | <6p. 186 (64.1%) | 6–20p. 52 (17.9%) | >20p. 52 (17.9%) | 290 |
Notes: BSc, Bachelor of Science education. Average and standard deviation provided for age and experience variables. In total, 43 age cells were left blank. Percentage differences due to rounding
Individual case responses
| Individual case responses | Case 1 (%) | Case 2 (%) | Case 3 (%) |
|---|---|---|---|
| Limited information verification | 15.2 | 8.3 | 5.5 |
| Refusal of information verification | 14.5 | 33.1 | 14.1 |
| Substantial verification information | 70.3 | 58.6 | 80.3 |
| 100.0 | 100.0 | 100.0 |
Note: Percentage differences due to rounding
SIV scores
| No. of SIV scores in 3 cases | Frequency | SIVtotal score | Label |
|---|---|---|---|
| 0 out of 3 | 13 | 0 | No SIV |
| 1 out of 3 | 51 | 1 | Low SIV |
| 2 out of 3 | 122 | 2 | Medium SIV |
| 3 out of 3 | 104 | 3 | High SIV |
| Total | 290 |
Job level scores
| Job level scores | N | Valuation experience (years) | SIVtotal group average | SIVtotal group mean rank |
|---|---|---|---|---|
| Employee | 67 | 13.5 | 2.13 | 147.84 |
| Manager | 25 | 18.8 | 2.40 | 176.06 |
| (Co-)owner | 198 | 19.9 | 2.04 | 140.85 |
| 290 |
Mean rank differences
| p-values (2-tailed) for pair-wise mean rank differences | |||
|---|---|---|---|
| Employee | Manager | (Co-)owner | |
| Employee | – | ||
| Manager | 0.100 | – | |
| (Co-)owner | 0.517 | 0.038* | – |
Notes: *,**Significant at 0.05 and 0.01 confidence levels, respectively
Correlation coefficients brokerage experience
| Correlation coefficients | Brokerage experience | |
|---|---|---|
| SIVtotal | Spearman’s ρ | −0.154 |
| p-value | 0.009** | |
| SIVtotal | Kendall’s τ | −0.122 |
| p-value | 0.009** | |
Notes: *,**Significant at 0.05 and 0.01 confidence levels, respectively
Correlation coefficients valuation experience
| Correlation coefficients | Valuation experience | |
|---|---|---|
| SIVtotal | Spearman’s ρ | −0.122 |
| p-value | 0.038* | |
| SIVtotal | Kendall’s τ-b | −0.098 |
| p-value | 0.036* | |
Notes: *,**Significant at 0.05 and 0.01 confidence levels, respectively
Control variables information verification
| Control variables on information verification | |
|---|---|
| 1 | I investigate the correctness of received valuation information (questioning mind) |
| 2 | I want to know how comparable transactions have been realised (search for knowledge) |
| 3 | I assume that real estate owners are not reliable in their information provision (interpersonal understanding) |
| 4 | I try to hold off concerned clients during the course of a valuation assignment (autonomy) |
| 5 | I withhold my value judgement until there is appropriate level of evidence (suspension of judgement) |
| 6 | I engage in a dialogue with a client to clarify my valuation estimate (self-confidence) |
Note: Professional characteristic in brackets
Control variables by job level
| Control variables results by job level | |||||||
|---|---|---|---|---|---|---|---|
| CV 1 | CV 2 | CV 3 | CV 4 | CV 5 | CV 6 | ||
| Job level | n | Mean Likert scores | |||||
| Employee | 67 | 4.46 (0.73) | 3.93 (0.66) | 2.79 (0.71) | 3.60 (0.91) | 2.63 (0.76) | 3.67 (0.82) |
| Manager | 25 | 4.48 (0.87) | 3.96 (0.89) | 2.56 (0.87) | 3.28 (1.10) | 2.20 (0.65) | 3.72 (0.79) |
| (Co-)owner | 198 | 4.54 (0.62) | 3.81 (0.71) | 2.86 (0.73) | 3.79 (0.93) | 2.53 (0.67) | 3.55 (0.86) |
| Sample average | 290 | 4.52 | 3.85 | 2.82 | 3.70 | 2.52 | 3.59 |
Note: Standard deviations in brackets
Mean rank differences
| p-values (2-tailed) for mean rank differences | ||||||
|---|---|---|---|---|---|---|
| CV 1 | CV 2 | CV 3 | CV 4 | CV 5 | CV 6 | |
| Mean rank manager | 112.18 | 122.92 | 87.20 | 88.60 | 90.00 | 122.46 |
| Mean rank (co-)owner | 111.98 | 110.62 | 115.13 | 114.95 | 114.78 | 110.68 |
| p-value | 0.986 | 0.327 | 0.025* | 0.042* | 0.044* | 0.360 |
Notes: *,**Significant at 0.05 and 0.01 confidence levels, respectively
Non-response bias
| Non-response bias | p-value |
|---|---|
| Ordinal scale variables (Mann–Whitney U test) | |
| Education | 0.613 |
| Job level | 0.377 |
| Valuation team | 0.422 |
| Company size | 0.865 |
| Ratio scale variables (Student’s t-test) | |
| Agee | 0.845 |
| Valuation experiencee | 0.147 |
| Brokerage experienceu | 0.581 |
| Nominal scale variables (χ2 test) | |
| Professional qualification | 0.137 |
Notes: eassuming equality of variance; uassuming unequality of variance. *,**Significant at 0.05 and 0.01 confidence levels, respectively
Note
Rejection of both H10 and H20 should be regarded in view of weak positive correlation between job level and brokerage experience (r=0.253).
Appendix 1. Example of questionnaire case
You have gained a valuation instruction that requires the open market value assessment of a newly built office building. The building is one of the first to be erected in an urban business development area. The client is the office developer who requests the submission of a draft valuation report before finalisation. During the draft-reporting meeting your client seems to regard your views on rental growth perspective in the area as being conservative. He sets out his own professional views on the area’s attraction to new users and provides you a recent market report from his own letting agent. The developer is an active market participant in the local area and has been a client of your organisation for years. What will you do?:
You free up time to contact one or two other local letting agents with regard to anticipated rental growth potential in the development area.
You adjust your draft report based on the market report delivered by your client and make reference to this adjustment in the final report.
You stick to your previous rental growth projections and finalise the valuation report without adjustments.
Appendix 2
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Corresponding author
About the authors
Pim Klamer is Senior Lecturer at HU University of Applied Sciences, the Netherlands and PhD Student at University of Utrecht, the Netherlands. He gained an MSc at VU University Amsterdam in 2000 and has 10 years of international working experience in real estate investment management.
Vincent Gruis is Professor of Housing Management and Head of the Department of Management in the Built Environment at Delft University of Technology, the Netherlands. His research includes organisational strategies in housing management.
Cok Bakker is Professor of World View Education at the Faculty of Humanities of Utrecht University, the Netherlands. His research focuses on the relationship between education and professionalism, including education policy, school ethos and the professional and moral development of teachers and other professionals.