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Journal of Property InvestmenFinance, Vol. 17 No. 4, 19

pp. 333-352. # MCB UniverPress, 1463-5

ACADEMIC PAPERS

Behavioral research intoheuristics and bias as an

academic pursuitLessons from other disciplines and

implications for real estateWilliam Hardin III

Department of Finance and Economics, Mississippi State University,Mississippi, USA

Keywords Heuristics, Real estate, Operational research, Influence

Abstract Behavioral research is an accepted research paradigm in business disciplines outsideof finance including management, marketing and accounting. This paper looks at thesedisciplines and proposes goals for increasing acceptance of this form of research in realestate. Primary goals include investigation of actual heuristic use, concentration onexpert decision makers, either as a group or in comparison to novices, incorporation ofadditional theory advocating functional heuristics, incorporation of real estate specific theory andidentifying both theoretically and empirically when, why and how heuristic use may bias thedecision process.

IntroductionFinance and real estate researchers have been late in the acceptance, or at leastpartial acceptance, of behavioral theory as a paradigm for the study of decisionmaking. This is in contrast with other areas of business specializationincluding marketing, accounting and management which have a tradition ofusing cognitive behavioral theory to both describe the decision process andprescribe possible methods for improving the decision making environment.This paper presents a broad overview of the general theoretical concepts andprior empirical research concerning decision making and heuristic[1] use in real

estate and other business disciplines and advocates the development of atheoretical foundation for decision making within a real estate framework. Thefirst section addresses the theory of human information processing and buildsa foundation for real estate as an area for research. The second section reviewsmajor non-real estate theoretical concepts and heuristics. Empiricalinvestigations are presented in section three while the final section reviews realestate studies and outlines possible areas suitable for real estate-specific theorydevelopment and empirical investigation.

The research register for this journal is available at

http://www2.mcb.co.uk/mcbrr/jpif.asp

The current issue and full text archive of this journal is available at

http://www.emerald-library.com

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Human information processing, intelligence, expertise and realestateThe theoretical foundation used in most studies of the decision making isderived from Simon (1957, 1978) and Newell and Simon (1972). Simon (1957)postulates that decisions are made within a subset of all potential solutions.Limitations in the use and review of all potential solutions is a rationalbehavior as other factors, including search cost and data evaluation, impact aspecific individual's utility. Newell and Simon (1972) and Simon (1978) expandand refine Simon's initial work by emphasizing individuals' cognitivelimitations and by developing a theory of human information processing thatintegrates limitations in short-term memory with the decision making process.Further theory developed by Evans (1989), Baron (1985) and Shanteau (1992)emphasizes that the use of schemas[2] or heuristics is fundamentally a rationalresponse to expanding levels of information.

Newell and Simon's (1972) and Simon's (1978) extensive foundation ofhuman information-processing theory can be presented in simplified terms. Anindividual interprets a task (decision to be made) and tries to formulate it into aknown, structured problem space[3]. The selection of a problem space, orschema, is an interactive process composed of information processing, taskenvironment comprehension, and problem space definition. Interaction isfacilitated by information-processing heuristics at the task environment[4]interpretation stage and the problem space generation stage of the decisionprocess. The use of heuristics reduces the number of alternatives available forproblem resolution. Simon's fundamental argument is:

problem solving behavior is produced by a small set of elementary information processes,

organized into strategies or programs (Simon, 1978, p. 279).

When properly applied, information-processing heuristics reduce search timeby providing for proper task definition and problem space generation. Theability to quickly access and effectively process data is the essence of domain-specific expertise. In fact, Newell and Simon (1981) define intelligence based onan individual's capacity to use simplifying heuristics. There is no limit to theamount of information that is available for search, or in the number of potentialsearch patterns, but in order to function in an ill-structured environmenthumans must be able to determine what data are relevant and whatrelationships are plausible. The decision maker must interpret the task

environment and generate a problem space that allows for the solution of thetask.

Building on the Newell and Simon framework, Evans (1989) postulates thatexperience and training will allow for better task recognition and greaterdevelopment of problem spaces. Heuristics are preconscious allowing for therapid acquisition and implementation of data search procedures when facedwith familiar tasks. When faced with a familiar task, the decision maker uses apreconscious, pre-developed schema that determines the task and theproduction rules available to resolve the problem. The schema is domain

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specific and includes related ` declarative and procedural knowledge.'' Anexpert has domain-specific knowledge and a procedure, or procedures, forincorporating that knowledge into the decision making process. Baron (1985)argues that the selection of one schema may result in the selection of one set ofrelevant information while the use of another schema may result in a differentset of relevant information. Each schema contains knowledge from a particulardomain that serves as a guide to relevant data selection.

In summary, human information processing theory indicates that humansobtain domain-specific schema that lead to optimal decisions within theframework of their domains of expertise. Bias may occur because of themisapplication of schema that control processing heuristics or underdevelopeddomain knowledge. Therefore, the development of additional theory on whenschema misapplication may occur is necessary and is partially provided byShanteau (1992) with the prerequisite to the misapplication of schema, ofcourse, being sufficient domain expertise for schema development.

Shanteau's Theory of Expert Competence includes five specific factorsaffecting an expert's competence to address sources of potential bias found inempirical research on decision making presented by both behavioral andcognitive researchers. The model's first factor is domain knowledge includingtextbook knowledge plus experience gained by working in a real worldproblem solving environment. The second factor is psychological traits andincludes self-confidence, responsibility, and an ability to adapt, as traitsrequired of an expert. The third factor is cognitive skill and involves theexpert's ability to determine relevant data cues from complex and stressfulexternal environments. The fourth factor is called decision strategies; it

includes simplification strategies for data acquisition and the use ofpreconscious decision procedures or heuristics. These initial four factorsrequire the decision maker to have sufficient knowledge and experience todevelop data acquisition heuristics that work.

The fifth and final factor affecting expertise is task characteristic. Shanteaupostulates that in more dynamic situations actual task interpretation andpresentation are difficult. For experts to show good performance, the task mustbe repetitive, objective, decomposable, allow for substantial feedback, haveagreed upon stimuli, and have predictable problem parameters. Even ifagreement is reached on the actual task to be solved, the characteristics of thetask environment will impact problem resolution. Bias in decision making may

occur through an inaccurate perception of the task or the incorporation ofpoorly developed schema. When humans are asked to solve tasks that areinherently difficult to master due to poor feedback, uncertainty with regard tothe variability of inputs and outputs, uncertain stimuli, and unpredictableproblem parameters, heuristic use is likely to lead to sub-optimal decisions.

In the context of real estate research, Shanteau's theory provides twoimportant insights. The first is a requirement for domain-specific expertise.In investigating human information processing in a real estate context,special attention is required when specifying expertise because without

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expertise at some level, the existence and effect of heuristic use can only beinferred as a general decision making condition. Heuristic bias would occurbecause domain knowledge is insufficient and general information-processing heuristics are inadequate to address the task. Consequently, anover-reliance on the use of nave or novice study participants may render realestate based research simply replications of studies showing that bias isgreatest in general cases with limited domain-specific expertise. Second, theactual task definition is critical. Because effective heuristic developmentrequires a task to be repetitive, objective and decomposable with substantialfeedback, researchers must control the research environment to adequatelytest for heuristic use and potential bias. Real estate decision making takesplace in an ill-structured environment with uncertain stimuli, limitedfeedback and numerous overlapping domains of expertise a dynamicresearch environment requiring substantial due diligence by researchers.Task definition and the researcher's definition of optimal may lead to theappearance of heuristic bias when, in fact, none exists. For example, anattempt by appraisers to cognitively confirm a sales price may be afunctional[5] heuristic even if it does not meet the criteria of normativeappraisal models. Real estate decision making provides an opportunity tosubstantially expand empirical research provided this research conformswith a general theory of functional heuristics where sub-optimization mayoccur due to limitations in task definition, actual expertise or environment.

Heuristics and biasThe focus of much of the general information-processing literature has been on

situations where the use of heuristics may bias the decision process. The threeheuristics identified in the early 1970s by Tversky and Kahneman therepresentative heuristic, the availability heuristic, and the anchoring andadjustment heuristic along with the positivity heuristic defined by Evans(1989) have been the center of much research. The observance and definition ofadditional heuristics has also occurred, but these four heuristics remain themost studied and most acknowledged within the literature. They are identifiedbelow because an understanding of these heuristics is essential for evaluatingtheir applicability in a real estate context.

Tversky and Kahneman (1971, 1972) observed and defined therepresentative heuristic. They found that humans interpret a sample to be more

representative of the parent population than it actually is. Subjectiveassessment of probability may be at odds with actual probability. Theirdefinition of the representative heuristic allows that bias occurs as the inabilityto properly assess the probability of an event over different sample sizes andpopulations affects decisions. In a thesis on judgment, Tversky and Kahneman(1974) provide an example of the representative heuristic and how it mightcause bias. A description of an individual was developed. The researchers thenasked respondents to determine to which profession the individual belonged.The description of the individual is below:

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Steve is very shy and withdrawn, invariably helpful, but with little interest in people or theworld of reality. A meek and tidy soul, he has a need for order and structure, and a passion fordetail.

The authors then listed a number of professions and asked the respondents to

determine the profession to which Steve belonged. Librarian was the mostcommon response. Such a response, however, was at odds with the base-ratefrequency[6] of librarians when contrasted with the general population andother professions. People can be insensitive to sample size, prior probability ofoutcomes, and misconceptions of chance.

The availability heuristic (Tversky and Kahneman, 1973) states thatindividuals assess probabilities based on their familiarity with a certain task,idea, or environment. Humans attempt to frame a decision based on priorsituations confronted and successfully negotiated. Bias occurs because once atask or situation has been perceived in a certain way such a perception isdifficult to change. Furthermore, bias occurs because of data retrievability,

salience, and illusory correlation. The availability heuristic restricts theformation of more effective heuristics unless feedback demonstrates that biashas been created.

The anchoring and adjustment heuristic is the last major heuristic definedby Tversky and Kahneman (1974). This heuristic simply means thatindividuals start at one place in a decision matrix and adjust from that initialpoint. Individuals try to get ``close'' and then make adjusts from an initial pointby obtaining and using additional information. Bias occurs when the initialanchor is incorrect, insufficient adjustment is made, or there is an overlyoptimistic estimation of conjunctive probability. Much of the literature on thedecision making process concerns the anchoring and adjustment heuristic as it

is the most easily operationalized.Evans (1989) uses the work of Tversky and Kahneman and others as a

foundation for his synthesis of heuristics and bias and definition of a positivitybias. Evans' arguments are based on an extension of the concept of aconfirmation heuristic meaning that humans seek data that is fundamentallyconsistent with existing beliefs, theories and cognition. Bias occurs when datathat should be deemed relevant is not because of a preconscious search forpositive feedback. Evans, however, argues that the concept of confirmationbias is not correct and that confirmation bias is a function of ` cognitive failure''in the human information-processing system developed by Simon. Specifically,Evans proposes a positivity bias and states:

Positivity bias is assumed to arise from the preconscious heuristic processes which determinethe locus of the subjects' attention (Evans, 1989, p. 43).

Humans are looking for ways of confirming their individual interpretations ofthe world via their perception of the task environment and determination of theproblem space.

The four foundation heuristics have provided a framework for behavioralresearch within a real estate framework, but only as an extension of the generaluse of heuristics. The heuristics represent a call for descriptive research that

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will allow for the actual confirmation of the existence of systematic dataacquisition. There is a need to describe the decision process without accessing acorrect solution. If expertise requires systematic data search then a first step inthe research should include confirmation of some level of expertise by showingthat experts actually use systematic data retrieval. At a second level, theexistence of sub-optimal results then can be addressed. The goal of this secondlevel would be the determination of what tasks and environments createheuristic bias. The definition or replication of bias caused by heuristic use innon-domain-specific areas of interest is no longer enough unless theorydevelopment is included or direct real world application is possible.

Empirical researchResearch on the business decision making process has included actual versusnormative decision making, the potential of information-processing heuristicsto cause bias, and differences in data processing between novices and experts.A brief review of normative lending and real estate models and an analysis ofheuristics, bias, novices, and experts from other business disciplines arepresented. The research presented is by all means not all inclusive, but doesprovide exposure to the diversity of areas of interest and the sophistication ofthe actual research design process.

The breadth of the subjects that have been investigated empirically showsthat theory, practice and real world applications must all be addressed.Normative and descriptive modeling have been investigated. Theory has beenempirically tested requiring theory refinement and experimental designchanges. Specific heuristics have been researched, as have data acquisition

strategies. The noted research is helpful in design evaluation for real estateresearch and allows real estate researchers a feel for the acceptance level ofheuristic study in other fields; the goal being theory testing with someapplicability to practical business decision making.

Normative decision modelsBeaulieu (1994) studied the normative Five Cs of Credit Model[7] and lenders'actual use of this model in making a loan decision. The investigation wasspecifically concerned with the use of character and accounting data ascomponents of the loan decision. Participants included students in acommercial lending training school who were given a general loan scenario[8]

and then given 26 facts about the company providing information for characteranalysis and credit analysis. After being presented these facts, the respondentseither approved or declined the loan, and were asked to measure theirconfidence in the decision made and the probability of loan repayment. Thefacts where manipulated to evidence positive, neutral, or negative characterand positive, neutral, or negative accounting performance (a 3X3 design).

Results indicated that experienced lenders weighted the negative accountingmore heavily than lending novices. When confronted by a scenario withnegative accounting performance, none of the experienced lenders approved

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the loan even with positive character attributes. Novices facing the samesituation approved the loan 31 percent of the time. The experienced lendersmore heavily weighted the accounting data and were less concerned withcharacter in all the scenarios presented. Unfortunately, since actual companyfinancial data were not presented to the respondents, there was no ranking ofdata that could be used to determine relevant data cues by lender group. Thestudy, however, provides evidence that the normative Five Cs of Credit Modeltaught in business schools and in bank training programs is not alwaysapplied.

In an investigation of the decision making processes used by appraiserswhen compared to the normative model prescribed by theory and promulgatedby the Appraisal Institute and government regulation in the United States, Diaz(1990a) found substantial differences. Diaz used a single factor (familiarity high, low) design to determine if geographic familiarity impacts the dataacquisition strategy of expert appraisers. Diaz found that experiencedappraisers dealing with both familiar and unfamiliar demographic areasdeviated from prescribed appraisal practices. He was also able to show that thepattern of cue utilization is similar in both appraisal situations. This indicatesthat appraisers use production rules that deviate from the prescribed model,but are functional in the actual determination of an appraised value.

Beaulieu and Diaz provide evidence that lenders and appraisers, two majorparticipants in the real estate industry, deviate from prescribed decisionmodels. This is further support for Kanaan's (1993) commentary on the need toredefine normative models and to determine what actually occurs whenindividuals make decisions. What is evident from these studies is that the

human decision process is often simplified as data are determined to be eitherrelevant or irrelevant within the context, or schema, of the decisionenvironment. The ability to describe the decision process sufficiently will beessential for the comparison of normative models and actual decision makingprocesses especially if one accepts that heuristic use is functional. Within thereal estate research arena, the decision making process remains under-investigated.

Consumer behavior researchThere is a large volume of research in the consumer behavior literature onheuristics, bias, preconscious information processing, and schema

development. A primary reference for this literature is the Handbook ofConsumer Behavior (Bettman et al., 1991) as well as the Journal of Consumer

Research. In a general context, most studies support the theoretical foundationfound in the psychology literature. Within the context of this paper, consumerchoice and data acquisition strategies have been shown to be subject toheuristic bias. A sample of relevant, well-designed empirical research ispresented below.

Folkes (1988) studied the availability heuristic in a consumer setting usingfour separate experiments. In Study 1, instances of product success and failure

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(the product used in the case was a rust-stain removal product) were presentedto 46 undergraduate students in combination with more or less distinctivenames. Three conditions were studied failing products with non-distinctivenames, failing products with distinctive names, and half-failing and half-succeeding products with brand names. In estimating failure rates, thedistinctively named products were judged to have a greater probability offailure. In Study 2, Folkes observed the amount of time respondents wereattentive to the products in the aforementioned scenario and found that therespondents paid more attention to the ineffective outcomes with distinctivebrand names. In Study 3, Folkes investigated students' estimation of the failurerate of an escalator in a major campus building. Due to building design, it waspossible to segment the sample into students that used a combination ofescalators and stairs or an elevator and students that only used an escalator(students could access the building's sixth floor using a combination of

escalators and stairs or an elevator while the first four floors were served by anescalator system). Students were asked to estimate the percentage of time theescalator was broken. The students that were dependent on the escalatorsystem estimated that the escalator was broken 54 percent of the time while theother student group estimated a failure rate of 31 percent. The distinctivenature of walking up a broken escalator was thought to have increased thesaliency of the escalator failure. In the first part of Study 4, 97 studentscompleted a questionnaire to test whether instances of failure were more easilyrecalled than instances of success. Recall of successful instances was correlatedwith frequency of use while recall of instances of failure was based on thedistinctive source of the failure. In the second part of Study 4, the respondents

indicated the likelihood of instances of success or failure. Likelihood estimateswere not correlated with the recall of successful instances, but were correlatedwith the recall of instances of failure.

In all instances studied, Folkes found that there was bias in judgment causedby the availability heuristic: individuals overestimated failure rates afterexposure to distinctive situations. Increased saliency, caused bydistinctiveness, is likely to influence the perception of relevant data in adecision situation. The decision maker may create a schema to addressdistinctive features of the task while relevant data are not accessed, leading to abiased result.

Sujan (1985) tested how prior knowledge affects the evaluation process. Thepiecemeal (attribute by attribute) approach to information processing wascompared to categorical information processing where an item is grouped byclass in a schema-driven process. Using a complex verbal protocol design withcameras as the basic stimuli, Sujan found that both experts and novicesattempted to use a categorical strategy, but that experts were better atunderstanding and evaluating deviations from the prescribed category.Experts are able to evaluate deviations and better assess categorical variations.Sujan finds the experiment's results:

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consistent with a general schema perspective that suggests that schema-consistentinformation can be chunked into large perceptual units and processed more easily (Sujan,1985, p. 45).

Brucks (1985) completed a study of the effects of product knowledge oninformation search. Using sewing machines as a product class, Brucksanalyzed the way that novices and experts search for data. An interactiveprocess was created that permitted the study participants to ask for data andhave the data presented via a computer allowing Brucks to trace data cueselection. Brucks' primary finding was that when humans are faced withcomplex decisions:

objective knowledge was associated with seeking less information about inappropriatealternatives and with using a pattern of search that exhibits a greater degree of variance inthe number of questions asked about the considered alternatives (indicating greater searchefficiency) (Brucks, 1985, p. 12).

This finding supports the postulate that simplification heuristics are indicativeof expertise. Expertise will make individuals more effective at data acquisition,but such efficiency will only be evident when situations warrant. In lesscomplicated decisions, there is limited need for simplification heuristics so theywill not be evident. Also, domain-specific knowledge is a prerequisite.

In a study of preconscious data acquisition and recognition, Janiszewski(1988) found that attitude formation occurs preconsciously. Janiszewski usedevaluation of a print ad to study if the evaluation of an ad could change withouta change in ad recognition. Using contralateral conduction and thephysiological premise that the left and right hemispheres of the brain process

differing forms of information, Janiszewski was able to show that evaluationcan take place without recognition. This lends support to Simon and Newell's(1972), Simon's (1978) and Evans' (1989) hypotheses that informationprocessing has a preconscious component. Information is processedpreconsciously before humans are conscious of the presence of information. Inreal estate, do purchasers or investors develop preconscious schema based onvisual stimulation?

Consumer behavior research, as evidenced by the review of only a few of themajor studies available from the literature, provides support for theinformation-processing capabilities proposed in the psychology literature.

Consumers are influenced by heuristics that can bias, use schema to simplifythe information search process, simplify data search within domain-specificknowledge, and process information on a preconscious basis. Expertise ismanifested by systematic data search and data retrieval. So, within the realm ofreal estate, can one design studies of stigma, the influence of ``view'' or ``curbappeal,'' or any other market driven effect? Can one test for the influence of race,nationality or gender using a cognitive approach? Can one simply showsystematic data acquisition strategies? Do real estate experts recognizeanomalies in value or price?

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Accounting researchLike consumer researchers, accounting academics have embraced cognitive,human behavioral research. Several of the numerous noteworthy empiricalstudies from this literature are summarized below as is Smith and Kida's (1991)review of heuristic research in accounting. Heuristic bias is a common researchtopic as judgment is generally required within the accounting field. The bestaccountants are able to look past the numbers, the data, and generateinformation.

In a study of the anchoring and adjustment heuristic and the potential forbias in an accounting setting, Kinney and Uecker (1982) found that theanchoring and adjustment heuristic can cause bias in at least two situations:compliance sampling and completing financial analysis. In two tests of seniorauditors from the then Big Eight accounting firms, the authors found thatfinancial presentation influenced the level of variability expected in a firm'sperformance and that compliance sampling was influenced by the method ofsampling error estimation. Auditors may be susceptible to historical datatrends when interpreting current unaudited results. The key is at what level ofvariability in present versus past performance should additional investigationbe required when assessing a specific income or balance sheet account. In thesampling case, results showed that senior auditors did not properly assess therepresentativeness of a sample versus the population of interest. In bothinstances, pre-audit company presented data influenced auditors.

In an investigation of the data acquisition heuristics used by equity analysts,Biggs (1984) traced the information acquisition strategies and decision makingcapabilities of expert financial analysts. Using verbal protocol, Biggs studied

11 experienced equity analysts and found that the analysts used two basicdecision strategies historical and predictive to determine which of fivepaper companies was the most likely to be the top performer over the next five-year period. The convergence of data acquisition strategy and decisionmethodology shows that training and expertise development can cause groupsof experts to frame a decision similarly while also allowing for the fact thatexperts can and do frame the same task differently.

Ashton and Ashton (1990), in an important empirical investigation ofconfirmation bias, propose that confirmation bias can only be measured withinthe context of the decision being made. The authors argue that many priorstudies have misrepresented the function of an auditor. Because ``the purpose of

auditing is to enhance credibility'' (Ashton and Ashton, 1990, p. 3), training andexperience lead to search heuristics that focus on negative data: the auditorseeks to find negative data, as that is part of the audit function. In a series oftests, auditors were studied in an auditing task environment and auditors andexecutives were studied in a non-auditing task environment. In the auditingtask environment (two experiments), the auditors were more responsive tonegative rather than positive financial data. In the non-auditing environment,the auditors responded in a similar manner, but the executives did not exhibitnegative responsiveness. Ashton and Ashton propose that experience and

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training impact how auditors track and assess data. Cognitive heuristics andincentives lead to a search for negative data as ``negative evidence may beconsidered good news for auditors'' (Ashton and Ashton, 1990, p. 16).

Smith and Kida (1991) provide an extensive review of heuristic research inthe accounting profession. The authors believe that because auditors, as amatter of practice, are paid to make judgments, the accounting profession is anexcellent industry within which to study judgment and decision making. Theynote that although much research in auditing has used experiencedprofessionals, ``auditors appear susceptible to the same biases found in theheuristics literature'' (Smith and Kida, 1991, p. 473). Empirical studies supportthe basic research developed by psychologists that shows the prevalence ofheuristic usage. The authors also believe that training and experience canmitigate heuristic bias, but that the complexity of real world experiences makesthe elimination of bias problematic. Finally, Smith and Kida (1991, p. 473) note

evidence:suggesting that specialized heuristics may be used for tasks within an expert's domain,whereas basic heuristics may be used in situations in which the individual lacks theinformation or expertise to indicate a strategy better suited to a particular task.

Empirical research in the accounting discipline is supportive of the use ofheuristics while recognizing the need to know how and when heuristics causebias. The research also provides a foundation for judgment research within areal estate context with goals of identifying systematic data acquisition andunderstanding when and why heuristic use might bias a decision. Can wedifferentiate situations in real estate where expertise has little effect? Does a

lack of information in a certain situation make experts more like novices?

Real estate researchNorthcraft and Neale (1987) provide one of the first studies of heuristics andbias in a real estate setting. The anchoring and adjustment heuristic wasstudied in a home valuation context. A total of 48 undergraduate studentsparticipated in the study as novices and 21 real estate agents participated asexperts in residential valuation. All participants provided estimates of marketvalue, listing price, a price they would actually pay, and a minimum sellingprice for a specific house after reviewing information on the house and after

being exposed to one of four levels of listing price. In all instances, both expertsand novices anchored on the listing price. Even when the anchor price was lesscredible, anchoring was evident. The use of sales agents, however, as expertsunfortunately reduces the strength of the results as sales agents are familiarwith pricing techniques, but not necessarily residential valuation techniques.Also, if in the actual market for residential property sales agents are generallygood at estimating value, then the sales agents' anchoring is not evidence ofheuristic bias, but is instead a learned functional heuristic. The research showsa need for additional research into possible heuristic use and bias in real estate.

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In an extension of prior work on normative decision techniques in appraisal,Diaz (1990b) found that the information-processing techniques used to selectsales comparables differed by level of appraiser expertise. Expert residentialappraisers considered fewer comparable sales than novices did. The

comparable selection process used by the expert appraisers indicates a schema-driven process that is cognitively efficient, but may lead to bias. Such apractice, however, may be learned, as residential appraisal has become veryprice competitive, volume oriented, and less geared to actual valuedetermination. The residential appraiser may define his task as the justificationof a sales price as opposed to an estimate of market value. This would confirmtheory indicating that heuristics are functional.

In a second study by Diaz (1997), experts and novices in an ill-structuredappraisal environment did not anchor to the valuation estimate of ananonymous expert (Member of the Appraisal Institute (MAI)). Diaz also foundthat the dispersion in value estimates for expert appraisers was not impactedby the anchor, but was reduced for novices. Although heuristic theory mightpropose an anchoring effect if the anonymous expert was deemed relevant, thefact that the MAI was anonymous may have mitigated the respondents' use ofthe anchor. If a specific appraiser acknowledged by the field and known bythose in the field to be an expert in appraisal was suggested as the expert,anchoring would have been more likely because the expert's appraisalvaluation would have been considered more relevant. In a subsequent study,Diaz and Hansz (1997) found that appraisers valuing property in areas withinwhich they have limited knowledge anchor to an anonymous appraiser's prioropinion. This may indicate a generally functional heuristic when experts are

faced with insufficient domain-specific knowledge. Without actual domain-(market) specific knowledge, anchoring to a report generated by a fellow MAI,may be a rational response.

Levy (1997) found that nave experiment participants evidenced a recencyeffect (possible anchoring) caused by the order in which value estimates weregenerated. The estimate of a specific property's selling price was affected bythe prior property on which selling price was estimated. The research confirmsgeneral heuristic use when faced with an unfamiliar task. Concurrently, it begsthe question, ``Does the sequencing of house showings by sales agents affectwhich house a purchaser may decide to buy?''

Gallimore (1994) studied three information-processing heuristics including

the anchoring and adjustment heuristic, the recency heuristic, the use of lessrelevant information or feedback due to the timing of exposure, and the dilutionheuristic, the ability of less relevant data or noise to reduce the use of relevantdata, using a survey methodology to obtain 276 responses (from a mailing of498). In the test of the anchoring and adjustment heuristic, the respondentswere segmented into two groups by the incorporation of two versions of thefollowing question in the questionnaire:

Which of the following statements would you agree with?Circle letter A or B at the end of the statement with which you agree.

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Freehold prices typically vary by5 percent or more on either side of average price AFreehold prices typically vary by less than5 percenton either side of average price B (Gallimore, 1994, p. 102)

One of the questionnaire versions used the 5 percent level from above and oneversion used a 20 percent level. A later question embedded in the questionnaireasked for the respondents to state the amount of variability that is typicallyfound in an appraisal. The respondents with the 20 percent question provided astatistically significant higher estimate of variation than those respondentswith the 5 percent question.

To test the recency heuristic, respondents were given a 50 percentconfidence interval of the market value of a property on a per square foot basis.Respondents were segmented into two groups by presenting two sequences ofcomparable data that the respondents could use to adjust their initialconfidence intervals. The comparables presented were in one of the two

following sequences: two confirming comparables followed by twodisconfirming comparables or two disconfirming comparables followed by twoconfirming comparables. The group receiving the confirming comparables lastwere more confident in their value estimate than the group receiving thedisconfirming comparables last.

To investigate the dilution heuristic, two groups of respondents were givendata on the rental rate of a retail property either simultaneously or on asequential basis and asked to state their level of confidence in the given rentalrate. No presentation effect was shown as the two groups were equallyconfident in the estimated rental rate.

Gallimore was able to show that heuristic bias might exist in the valuation of

real estate assets, but the method of analysis (questionnaire format) might notbe realistic enough to make the respondents expend sufficient cognitive effortto mitigate the evidenced bias. The fact remains, however, that the general useof heuristics and their potential biasing effect were present even with moreexperienced respondents. This confirms prior decision research on consumers,accountants, and real estate appraisers.

The anchoring and adjustment heuristic has also been investigatedin the context of real estate negotiation with mixed results. Black and Diaz(1996) showed in a controlled experiment using graduate students andreal estate professionals that asking sales price can serve as an anchor. This ispreliminary confirmation of another area where heuristic bias might be

likely. A weakness in the study was the fact that no controls for expertise werenoted and students in real estate are taught that having a well-defined andaccurate asking price is a requirement for selling a property. Black (1997) did afollow-up study to determine if a better presentation of salient facts mightmitigate anchoring. In cases where the negotiations were concluded, anchoringmay have been evident. An alternative explanation to the experiment's results,however, is possible as six (6) of fifteen (15) negotiating groups with a ``high''asking price were unable to reach a negotiated price even when instructedto do so.

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Hardin (1997) in a descriptive study of experienced real estate andcommercial lenders found that experts do have identifiable data searchpatterns and that these patterns differ by domain of expertise. In this study,two groups of experienced lenders evidenced different data relevancy andacquisition strategies. The differing data acquisition strategies led to differentcue utilization and different lending decisions. Hardin could have tested theanchoring and adjustment heuristic, but instead allowed that each group wouldhave functional but different heuristic use based on training, feedback anddomain-specific expertise. What is unique about the study is that substantialinsight was provided without the need to test for heuristic bias. Any inferredbias would have been due to different task definitions. In short, if the researcherpostulated one correct data acquisition strategy for both groups, then biaswould have been manifested. In a dynamic environment like that found in realestate, actual domains of expertise may be narrow and definition of experienceor expertise critical.

In a study of appraisers in the United States and the United Kingdom,Gallimore and Wolverton (1997) found that task definition may differ bycountry due to data availability and requirements on the disclosure of pendingsales price. Choice of comparable sales differed by country, although in theUnited Kingdom sales price knowledge also served as an anchor. This researchwas descriptive and provides support for domain-specific, but culturallysensitive, effective heuristics.

Diaz and Wolverton (1998) found that appraisers might anchor to their ownprevious estimates of value. In a longitudinal study requiring the re-appraisalof real property, it was concluded that the appraisers were less likely to make

adjustments in value. The authors contend that this may be a reason for thesmoothing effect found in many real estate indices.The information-processing paradigm has been introduced to the real estate

literature and to real estate academics. Bias caused by heuristic use has beenidentified with novices, experts and in certain instances where studyparticipants have limited data or some form of task unfamiliarity. Progress hasbeen made in expanding descriptive research and in expanding research toexperts within the field of real estate. A general acknowledgement of thepotential biasing effect of heuristic use can be made with regard to real estatedecision making, but the when, why and how have not been adequatelyaddressed. Advancing from this foundation should be the next task.

ImplicationsIntegration of theoretical and empirical researchThere is a substantial theoretical foundation on the development and use ofinformation-processing heuristics. Simon (1957, 1978) and Newell and Simon(1972) have developed a theory of human information processing thatacknowledges human weaknesses in data acquisition and interpretation whileallowing for an overall framework that permits the development of successfuldata simplification heuristics. Evans (1989) expands this theoretical foundation

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to include the use of schema as well as a potential positivity bias in the humaninformation-processing system. Hogarth (1981) emphasizes that heuristics aregenerally functional and that feedback and training are important in thegeneration of heuristics. While acknowledging the potential biasing effect ofheuristics, Hogarth concludes that experience and feedback should mitigatemuch bias. In essence, if the heuristics are always biasing, why do theycontinued to be developed and used? Baron (1985) is in agreement with thetheoretical work of Newell and Simon, and Simon, but concludes that theinherent human proclivity for biasing heuristics can be offset via experience,training and education. Human information processors can, and do, rise aboveminimal cognitive responses when making a judgment or choice, but only withfeedback indicating that past data selection and heuristics usage have beenbiased. The question that begs to be asked is ``Is it enough for real estateresearchers to show that heuristics affect decisions in real estate, especiallywith nave or novice decision makers?''

The position taken in this paper is that it is not enough to only show thatnovices, or experts given little data, may be subject to heuristic bias. Additionalstudies at the real estate specialization level might use novices to showpotential heuristic bias with subsequent studies comparing experiencedpractitioners with novices. Reasons for heuristics bias would be developed. Acritical question to be asked is whether lack of data or lack of actual heuristicdevelopment might be the cause for observed sub-optimization in real estatedecision making. Do experts and novices exhibit the same behavior when littlerelevant data are presented and different behavior when given a choicebetween relevant and irrelevant data?

Concurrently, real estate researchers must move forward with substantivetheory development and research in addition to research at the novice level.The development of real estate-specific decision making theory and subsequentempirical testing has to be addressed. A final area of interest would be theinteraction between real estate experts and the actual decision making process.Since for most individuals and even corporate and investment entities, majorreal estate related decisions are infrequent, the role of the real estate expert is acrucial area for study. This area has substantial implications for the use ofexperts in any situation. What role do experts play and are there limits to theireffectiveness? Is the expert the decision maker or just in a position to influencethe decision maker?

Real estate research in decision making should incorporate Shanteau's (1992)Theory of Expert Competence. The use of information-processing heuristicswill be productive when coupled with domain-specific knowledge andsufficiently developed cognitive skills that allow for effective data retrieval andinterpretation. However, even with the development of preconscious andconscious information-processing skills, the manifestation of real estateexpertise may be limited because of the actual characteristics of the task that isbeing solved. This is not to say that expertise does not exist, but to suggest thatits quantification may be limited by its specialization. Heuristic bias found by

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researchers may only be indicative of poorly specified expertise or a lack of itsapplication during the research process. Some domains cannot or do notprovide for adequate, timely, and relevant feedback while many taskenvironments have such variability in input data that the development of thecognitive skills necessary to manifest expertise is limited, but not non-existent.Consequently, the ability to develop both procedural and declarativeknowledge should be investigated with the goal being the determination of theextent of both types of knowledge. Can we show that real estate practitionersdevelop procedural knowledge and problem resolution related heuristic use?The outcomes from employing such knowledge may differ, but its applicationmay be similar across tasks. For example, Hardin (1997) shows that differinggroups of real estate lending professional develop procedural heuristics that arejob or task dependent. These procedural heuristics, however, lead to differinglending outcomes, but are not indicative of heuristic bias. Research questionsshould focus on the actual manifestation of expertise and when and whyheuristic bias might occur with the base case, once again, being functionalheuristics. A belief that heuristic development is cognitively beneficial shouldbe a theoretical foundation.

Finally, as previously noted, in the context of real estate research, there is alack of cogent theory with most studies attempting to say that people facing areal estate decision are subject to bias primarily due to the fact that real estateis composed of ill-structured decision making tasks. However, since functionalexpertise can be, and is, developed in real estate specializations, a genericargument for heuristic bias due to the ill-structured environment of real estateis not sufficient. Real estate research may be captive to Hogarth's (1981)

critique that heuristic research is enamored by definition while losing sight ofthe fact that heuristics must be useful or they would not be developed.Investigations of declarative and procedural knowledge, as specified above,and theory development will allow for a better foundation than allusions to anill-structured environment and task. Real estate-specific theory of when, whyand how heuristics affect real estate related decisions is needed. This is a majortask and is of paramount importance.

Diaz (1993) may provide a foundation for this theory with his defense of realestate as a separate academic discipline. If we look at the real estate industry asan overlay of all business disciplines with real property as the focus, a theory ofdecision making may be formulated. Real estate decision making is composed

of novices, numerous experts and overlapping domains of expertise. Theinteraction of real estate decision makers and the use of expertise can beincorporated into theoretical development. For example, the very existence ofexpertise may limit macro-level decision making as task complexity limitsgeneral ``real estate'' expertise. For example, a real estate attorney is challengedon a daily basis with changes in code and enforcement and must expend mucheffort to retain domain-specific expertise. Consequently, the attorney may notbe an expert except in one area of specialization, real estate law. When facedwith a real estate decision his domain-specific knowledge and heuristics are

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likely to dominate. A global theoretical framework is needed to address thistype of interaction. This will allow for consideration of when, why and howheuristics affect decision making.

As a first step in theory development, the definition of real estate as adiscipline can be integrated into Shanteau's Theory of Expert Competence toformulate when real estate-specific heuristic might exist. It is possible that suchtheory would dictate that heuristic bias exists at the novice level due toinsufficient domain knowledge. This has been shown to be the case in otherdisciplines, but theory has been generally lacking unless one uses the generalheuristics and bias literature. At the expert level, one should see more heuristicuse but less heuristic bias. Why is this the case? Heuristics only exist andbecome preconscious when one gets positive feedback. If this is not the case,then additional theory of the task environment may be necessary. A theory ofreal estate decision making should postulate when and why heuristic bias

occurs with novices and experts and when real estate decision makers interactwith one another.

Finally, real estate research must incorporate practice and theory. This canbe done with descriptive studies to determine the existence of information-processing heuristics. It can also be done through the use of domain-specificexperts in the experimental design stage of research. If one wants to determineif experts use, and or, are biased by heuristics, one will have to move to realworld, empirical research. This is difficult as it is time consuming andextremely unappreciated, but is necessary to advance knowledge. Researchdesign becomes paramount.

Additional goals and objectivesIn addition to the mentioned need for theory, which is a formidablerequirement, real estate researchers are faced with several choices.

The first and foremost is whether they simply want to replicate the existenceof heuristics in a new discipline. The goal in this case would be to show that invarious real estate decisions, people are subject to bias through the use ofgeneral heuristics. This may be a laudable goal, but must be tempered by thelack of discipline specific theory and few real estate outlets for publication. Theresearch would be more ``mainstream'' decision making with real estate as theavenue for investigation.

A second choice is available and has been employed to some extent byseveral real estate researchers including Diaz, Gallimore, Wolverton, andHardin. This choice is to concentrate research on procedural knowledge, thetesting of data relevancy by experts and comparisons between novice andexperts. Specific goals would include the documentation of heuristic use, thedocumentation of when bias occurs and the development of theory on why thisbias might occur. There is substantial difficulty in selecting this route.Questions of the definition of an expert persist. The lack of large numbers of

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experts within domains of expertise is apparent. Experimental design is criticaland differs substantially from most forms of analysis used in real estate andfinance.

The study of experts is critical for acceptance of heuristic use and potentialbias in the general real estate literature. If experts are affected by heuristic biasas opposed to just novice participants in a controlled experiment there wouldbe a broader acceptance of decision making research. At a theory testing level,real estate research could provide the means to advance past the psychologicalresearch by empirically testing a possible mitigating effect when expertise isdeveloped and by testing if, in fact, heuristic bias exists within domains ofexpertise as opposed to potentially misidentifying expertise and bias. Realestate and business researchers in general have a better opportunity to movetheory forward because their fields of interest are applied. This allows foraccess to experts and better experimental design.

Finally, theoretical and empirical research should be expanded from thevaluation area which remains an important base of study, to include otherareas of real estate decision making. Commercial real estate lending is an areaof interest as the complexity of large commercial transactions requiresjudgment and decision making skills. Differences between lender types andlender institutions is a viable research option. Lender versus equityunderwriting can also serve as a basis for investigation. With regard toresidential real estate, there are numerous avenues of study. The interactionbetween realtors and clients, the difference between novice and expert homepurchasers, presentation effects, etc. are all open to investigation. In addition,

the effect of heuristics on the negotiation process is a viable research venue.Since real estate is generally purchased through a negotiated process, this ispotentially a rich area for investigation. There are substantial other areas forresearch with experimental design and data acquisition being the majorobstacles to productive research. If one considers that behaviorists in consumerresearch can convincingly argue that ad placement affects retention, thenoptions for research in real estate seem almost limitless.

The goals are simple. Develop theory much as consumer behaviorists havedone, test theory on novices and experts and show how heuristics might affectreal estate decision making. This will be of substantial interest both within thereal estate field and within the decision making literature. Research should test

Evans' and others' hypothesis that heuristics are functional with a frameworkprovided by Shanteau adapted to the real estate decision making environment.External validity must become important in addition to the testing of theoriesof heuristic use. This will tie theory to practice and relevance.

Notes

1. A heuristic is a cognitive short-cut that allows for a reduction in the amount of informationprocessed. It, in essence, is a cognitive data reduction process. Cognitive processsimplification can be based on data, as well as declarative and procedural knowledge.

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2. Schema are domain-specific cognitive processes for interpreting declarative and proceduralknowledge. See Evans (1989) for additional discussion of schema.

3. Problem space is how the decision maker cognitively perceives the problem to be solved.

4. The task environment is the actual problem to be solved.

5. Functional heuristics are those that are effective in completing the decision task. Forheuristics to develop positive feedback is required. Much in the literature portrays aheuristic bias where sub-optimal decisions are being made. It can be argued that this biasmight be a function of researchers' misidentification of the actual task. The taskenvironment as manifested to the decision maker is being solved.

6. The base-rate frequency is the rate at which an event actually occurs within a populationof interest.

7. These are generally defined as Character, Capacity, Capital, Conditions and Collateral.

8. A $750,000 five-year amortizing term loan secured by equipment to a company with salesof $20 million.

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