INTRODUCTION:

The paradigm of life time employment has become unrealistic. In sectors such as software, finance, marketing where the skills are by and large transferable from one work environment to another, there is an increasing tendency to ‘buy in’ talents and this has led to instability in the labor market. In order to tackle this problem, one needs to fix it at the root by hiring the right candidate. Hiring practices have a massive impact on an organization’s financial performance (Fitz-Enz, 2002). The decision to recruit an employee with the right skills within a limited time period has always been a challenge for the employer.

From literature it has been found that current hiring practices have been haphazard (Fernández-Aráoz, Groysberg and Nohria, 2009).

Studies related to recruitment in general and decision making in recruitment in particular are almost absent in the Indian context. This study proposes to develop and test a conceptual framework of how people arrive at recruitment decisions in organisations using Brunswik’s Lens model.

Over the last 15 years, radical innovations have taken place in the human resource management (HRM) function in India due to phased liberalization of the Indian economy which has created a dynamic, turbulent, and hypercompetitive business environment. Human resource (HR) functions in Indian organizations have responded to this turbulent environment (Som, 2007). To understand this phenomenon, a growing spate of literature has tried to study the emerging role of HRM in the Indian context (Budhwar, 2001; Budhwar and Boyne, 2004; Som, 2008; Venkata Ratnam, 1998 cited in Som, 2010). A study conducted by Som (2008) suggests that among the five HRM practices tested (viz. the role of HRM department, recruitment, retraining and redeployment, performance appraisal and compensation and reward practices) only innovative recruitment and compensation practices emerged as the most important practice for enhancing firm performance among the Indian firms.

This study examines Brunswik’s “Lens model” as an appropriate recruitment approach. The lens model has emerged as an important conceptualization of the processes involved in human judgment and decision making (Cooksey and Freebody, 1985). With lens model as its basic framework, twenty years later Hammond and his colleagues offered a distinctively Brunswikian metatheory of judgment, called Social Judgment Theory (SJT; Hammond, Stewart, Brehmer, and Steinmann, 1975). The lens model has been used for over 50 years and in many different theoretical and applied psychological contexts (Kaufmann and Athanasou, 2009). This model provides a useful basis from which interviewers can make appropriate assessment of job applicants (Gifford, Ng, and Wilkinson, 1985). The objective of this paper is to show the kind of results/insights that the lens model can yield in the context of recruitment decisions by using the competency approach.

LITERATURE REVIEW:

Over the last six decades the major sub-topics studied within the gamut of ‘recruitment’ are the predictors used during the process of recruitment (broadly personality attributes, cognitive predictors, emotional intelligence and person-organisation fit) and various methods (such as interview, assessment centers, situational judgment tests etc.) used to select candidates. However, we argue that ‘decision making’ in recruitment is the most fundamental because recruitment is essentially a decision making process. Whenever recruiters assess an applicant they have to arrive at a decision, irrespective of the predictors used or the methods adopted. Guion (1998) notes that judgments and decisions play increasingly large roles in the employment process, but they have not been given a commensurate role in research. Posthuma, Morgeson and Campion (2002) assert, “Employment interview is primarily a decision-making tool, it is surprising that so few studies have utilized theories of decision making. The studies that have been conducted provide only a modest amount of insight into the interviewer's decision-making process”. Decision making studies in interview have considerably reduced in number over a period of time (from 1976 to 2002 cited in Posthuma, Morgeson and Campion, 2002). It is not irrelevant therefore, to deduce that decision making is a fundamental aspect of recruitment and more research is required in this area.

Common decision errors:

The topic of ‘decision making in personnel selection’ is both exciting and challenging because of the various possibilities of errors that recruiters commit. Complex tasks such as selection decisions, involves uncertainty, complexity, and other ill-structured problems, where people simplify the decision process by relying on heuristics (Payne, 1976; Prahalad and Bettis, 1983 cited in Hitt and Barr, 1989). Management and cognitive psychology literature suggests that an underlying cognitive model governs the way in which people integrate items of information into a single judgment (Hitt and Middlemist, 1979; MacCrimmon and Taylor, 1976; March and Simon, 1958 cited in Hitt and Barr, 1989). However, decision makers have a difficult time weighing and combining information in the appropriate manner such that they are relevant to their decisions (Slovic and Lichtenstein, 1971; Tversky and Kahneman, 1974; Slovic, Fischhoff, and Lichtenstein, 1977). This introduces cognitive bias and can lead to systematic errors (Duhaime and Schwenk, 1985; Tversky andKahneman, 1974). Reliance on cognitive biases, heuristics, and inadequate information may lead to use of job-irrelevant variables in a selection decision (Hitt and Barr, 1989).

Debate between experiential versus rational decision making:

It is important to address this issue in order to lay the ground for analytical decision making styles on which the model of this study is based. The debate between statistical and intuitive judgments has been prominent since Meehl (1954 cited in Lodato, 2008) suggested that statistical predictions are more effective than predictions based on intuition. However, Meehl himself had suggested that in a complex problem when there are too many variables interacting, a person may be unable to comprehend the relationships between all of them at a time, and he might take recourse to holistic judgment (Meehl, 1967 cited in Lodato, 2008). This phenomenon is especially prevalent in organizations, where managers prefer selection on the basis of intuition and subjectivity (Dipboye, 1997; Highhouse, 2002, Ryan and Sackett, 1989; Ryan and Sackett, 1998). However, there are urgings from scholars in more mainstream business periodicals such as the Harvard Business Review to rely more on analytical decision making styles (Bazerman and Chugh, 2006; Davenport, 2006; Pfeffer and Sutton, 2006).

Studies on decision making within an analytical framework:

Since the present study would be based on Brunswik’s Lens model, we delineate aspects that have been highlighted by other studies operating within the analytic framework. Studies which have deployed the lens model are able to find out the extent to which one can gauge the accuracy of the judge’s decision (Roose and Doherty, 1976; Graves and Karren, 1992); the extent of individual difference between judges (Roose and Doherty, 1976; Graves and Karren, 1992); group differences among judges (Roose and Doherty, 1976). More importantly the lens model is able to capture the pattern of the judge’s decision known as ‘policy capturing’ in the lexis of the lens model, where judges assign relative weights to various cues and combine them in particular ways (Zedeck, Tziner and Middlestadt, 1983). Due to the idiographic statistical approach of the lens model, this approach points out that aggregation of data can mask or eliminate valuable individual differences among interviewers (Zedeck , Tziner and Middlestadt, 1983). Bootstrapping has generally been considered superior to the decision maker himself, as it systematically smoothens the variances in the cue-to-judgment relationships (Dougherty, Ebert and Callender, 1986). With the aid of bootstrapping, this model is successful in showing that the equation generated from a judge’s decision has more predictive ability than the judge himself.

THE CONCEPTUAL FRAMEWORK:

As noted from literature, there is no significant study based on competency approach to understand decision making in recruitment within the analytic framework. In order to address this literature gap, the present paper argues for a competency based approach to generate predictors on the basis of which candidates need to be chosen. A competency model describes the combination of knowledge, skills and abilities needed to effectively perform a role in an organization and is used as a human resource tool for selection, training and development, appraisal and succession planning. The competency approach promotes a clear understanding of what the interviewer should be looking for under a number of defined headings in terms of the level of competency required. (Sanghi, 2007).

Methodology:

If a study wants to use a competency framework to generate the cues on the basis of which candidates will be evaluated during the job interview, the following steps may be followed to deploy a study using the Lens model framework:

Step 1: The study needs to generate the competencies required for whichever functional position is of interest for recruitment decisions. These competencies can act as cues in the decision making process.

Step 2: In order to gain cognizance of how the lens model could be useful to understand the ‘decision making’ pattern among the recruiters, we delineate the concepts and the method to be followed:

Figure 1. Lens model on decision making in recruitment

For one candidate (or interviewee) X₁, X₂, X₃, X₄…….X_n are the competencies which are the reflected through behavioral indicators or cues. Three recruiters, say, Y₁,Y₂andY₃ evaluate each candidate based on these cues. Y_s is the judgment of one recruiter to hire or not to hire. Therefore,

Y_s= β₁ X₁ + β₂ X₂ + β₃ X₃+………….+ β_nX_n

And, β_sis the weightage given to each cue according to the importance of that cue in the hiring decision.

In order to compute Y_e,one can collect performance data of employees after they have been recruited, so that one can know the competencies that contribute to better performance. When performance of the candidates will be measured (say after one year) the competencies on which they will be measured would remain same as used during hiring. But, performance ratings would be done by their respective supervisors.

Thus, the framework can compare the competencies that are given importance during recruitment and those that may emerge crucial during performance rating. Depending upon competencies that are proving to be important after the performance scores are obtained, the recruiters can be given feedback (which is the ‘feedback loop’ in Brunswik’s model).

To understand this more clearly in Lens model terms for one judge only:

Source: Goldstein, W.M. (2004). Social Judgment Theory: Applying and Extending Brunswik’s Probabilistic Functionalism. In D.J.Koehler and N.Harvey (Eds) Blackwell Handbook of Judgment and Decision Making. Malden, MA: Blackwell Publishing Ltd. Page 42.

Y_e represents the true state of some natural phenomenon (also referred to as the distal variable). In our case Y_e is the candidate to be recruited. The competencies that the ‘true state’ (in our case the candidate) possesses is not immediately available to the subject (recruiter who is judging) but must be gauged through the subject's utilization of cues in the environment which indicate the true state of the phenomenon. So, for example, if X₁ is the competency of ‘ability to communicate’, cues such as good written and spoken English, presentation skills, interpersonal skill may reflect that the candidate has the competency to communicate. So, these are the cues on the basis of which the recruiter has to infer whether the candidate possesses these competencies or not.

That is why Brunswik argued that this immediately available sensory information (in terms of cues) is virtually always ambiguous (Brunswik, 1952 and 1956 cited in Goldstein, 2004). Thus, the perceiver must use multiple cues and indicators (such as good written and spoken English, presentation skills etc) to infer something (in this case the competency of communication) that goes beyond the cues themselves. The above example illustrates what Hammond puts forth in an abstract way, “the lens model tells the researcher what to look for. What tangible indicators are present and available to the organism in its effort to reach an inference about an intangible object or event of interest? That is, what information that can be "seen" is available to make inferences about the "unseen"? How is the information that can be "seen" used by the organism to make inferences about the "unseen"? (Hammond, 1996; pg 86-87) It is important here to appreciate that only some indicators would be ‘seen’ by some, what indicators one can ‘see’ would be used in some

way (within the lens model paradigm through a linear combination) to make inferences about the “unseen”.

Brunswik called his approach ‘Probabilistic Functionalism’. Thus one of his principles of Probabilistic Functionalism is what he terms ‘Probabilistic Relationships’ where Brunswik theorized that the proximal cues would never be perfectly reliable or valid indicators of a particular distal state of affairs. This led him to conclude that cues are only probabilistically related to distal criteria, a concept he termed ‘ecological validity’ (Brunswik, 1952 cited in Cooksey, 2008). In the above diagram, these cues that have a true correlation with the distal variable, r_e,i , indicate how predictive of the distal variable the cue actually is. One can also find out ‘cue validity’ in the sense that which cues are meaningful indicators of the distal variable.

Another principle of Probabilistic Functionalism is the ‘Principle of Parallel Concepts’ where the principle states that the ecological system and the perceptual/cognitive of the organism can and should be described using the same types of concepts. So the proximal cues X₁, X₂, . . ., X_nis related in to the ‘true state’ by ecological validities (i.e., cue–criterion correlations r_e,i) and the extent to which judges on the other hand can infer about the true state through X₁, X₂, . . ., X_nisby cue utilization coefficients (i.e., cue–judgment correlations r_s,i). So, the recruiter’s judgments Y_s plays the role of central perceptions at the terminal focus. While ecological validity was defined as the correlation between the proximal cue and distal criterion and functional validity was defined, in parallel fashion, as the correlation (r_s,i) between a proximal cue and the organism’s functional response (Brunswik 1952 cited in Cooksey, 2008). So, Y_sis an estimate of the ‘true state’ of the phenomenon that the judge (or recruiter) perceives about the distal variable from the available cues.

Mathematically it would be, as elucidated by Karelaia and Hogarth (2008):

(where decision making is modeled as a linear function of a set of k cues, X_j, where j = 1, 2…k.)

Thus,

the β _s,j’s represent the weights that the person (or judge) gives to the different cues.

Similarly, the environmental criterion, Ye, can be modeled as a function of the same cues, Xj, j= 1, 2 . . . ,k.

β _e,j’s represent the weights that the environment gives to the different cues.

The lens model equation:

Another principle of Probabilistic Functionalism is the ‘Requirement for Successful Functional Response’. An achievement would be considered successful depending on which specific cues the judge relied upon, and how much utilization of those particular cues matched the degree of validity for inferring something about the distal variable. Achievement was defined as the correlation between the values of some distal criterion within the ecology and the person’s judgments of those values based on available cue information (Cooksey, 1996). ‘Achievement’ is the extent to which there is correspondence between judge’s judgment on one side and the actual candidate who is the distal variable.

It is Tucker’s (1964 cited in Goldstein, 2004) modification that is generally known as the lens model equation (LME) which decomposes the achievement coefficient, i.e., the correlation between criterion (environmental distal variable) and judgment (organismic central response), for a given set of proximal cues.

As elucidated by Goldstein (2004):

r_a is the achievement coefficient, i.e., the correlation between the criterion variable Ye and the judgment variable Ys;

R_e is the multiple correlation of the criterion variable with the proximal cues;

R_s is the multiple correlation of the judgments with the proximal cues;

G is the correlation between the linear components of the criterion and judgment variables, i.e., the correlation between the values Y ′_e that are predicted by linear regression of the criterion variable on the proximal cues and the values Y ′_s that are predicted by linear regression of the judgments on the proximal cues.

C is the correlation between the nonlinear components: of the criterion and judgment variables, i.e., the correlation between the residuals Y_e − Y ′_e and the residuals Y_s − Y ′_s.

Residual correlation (C), captures the part of judgmental achievement related to cues that have been omitted from the models, nonlinearities in the cue–criterion relations, and possible configurality. Thus, high values of C may reflect:

(a) accurate nonlinear or configural use of cues presented by the investigator,

(b) accurate linear, nonlinear, or configural use of cues that the investigator did not include in the analysis (i.e., nonmodeled knowledge); or

This product GR_s, termed “performance” by Lindell (1976 cited in Karelaia and Hogarth, 2008) and “linear cognitive ability” by Hogarth and Karelaia (2007 cited in Karelaia and Hogarth, 2008), quantifies the human contribution to achievement (as opposed to the environmental), and captures the extent to which judges both match task requirements and are consistent in the execution of their strategies.

The product GR_e is an estimate of the validity of the model created when a person is replaced by his or her strategy, that is, by bootstrapping (Camerer, 1981; Dawes, 1971; Goldberg, 1970 cited in Karelaia and Hogarth, 2008). Many studies have shown that bootstrapping does better than individual judges in clinical decision making (Karelaia and Hogarth, 2008). The implication is that decision making procedures in many organizations (individual judgment or consensus) could be replaced by models derived from human decision makers.

The higher the correlation between Ye and Ys, called "achievement" by Brunswik the more accurately a judge perceives the relationship between the cue and the distal state. So, if the recruiter perceives that the candidate has the ‘ability to communicate’ as a competency on the basis of the cues such as good written and spoken English, presentation skills, interpersonal skill etc. If the candidate infact has good communication skills, that means that the judge perceived his competency correctly and the judge’s level of ‘achievement’ is high. Although these cues are probabilistic, the judge can learn to utilize these cues more accurately.

The central contribution of the Lens Model to Social Judgment Theory is to compare the task ecology and a judge’s judgement in order to find out how accurate the judge is while making decision (Cooksey, 1996). Therefore, people must infer or construct a percept from a collection of sensory cues that provide only incomplete and fallible information. The perceiver must use multiple cues and indicators to infer something that goes beyond the cues themselves. Thus, Brunswikian research on judgment has taken accuracy, not rationality, as its central concern (Goldstein, 2004).

Another principle of Probabilistic Functionalism is, ‘Idiographic Statistical Approach’. Rather than averaging across organisms to obtain a general index of performance, Brunswik maintained that, for a representative sample of situations within an ecology, each organism’s behavior should “be individually examined and statistically tested before attempting to generalize behavioral trends” (cited in Cooksey, 2008 p 7). To understand each judge’s decision making pattern in terms of cue utilization either linear regression or logistic regression may be computed to understand how much weightage a judge gives to each of the competencies in order to arrive at the hire/no hire decision.

Lens model can also be employed to find out whether judges agree when forming impressions (i.e., consensus) by using estimates of inter-rater reliability.

The Relationship between Social Judgment Theory and Cognitive Continuum Theory:

The debate between analytical versus intuitive judgment has been tackled within the Lens model framework. This theory claims that different modes or forms of cognition can be ordered on a continuum with intuitive and analytical on either pole which is a clear departure from the traditional view of intuition and analysis as dichotomous and competitive models of thought (cited in Cooksey, 2008 p13). Quasi-Rationality is the middle ground in the cognitive-continuum where elements of both intuition and analysis and are encompassed (in differing proportion). Quasi rationality is closely related to Heider’s (1958) view of ‘common sense’ and Simon’s (1986) concept of ‘bounded rationality’ (cited in Cooksey, 2008 p15). Social Judgment theory is particularly well suited for providing insights into the quasi-rational region of the Cognitive Continuum. Hammond has strongly argued that Cognitive Continuum Theory provides the unifying framework that was desperately needed in the domain of judgment and decision making (cited in Cooksey, 2008[1996] p 26). While studying the decision making process in recruitment this study attempts to capture the quasi-rational area in the cognitive continuum which has remained unexplored in studies on recruitment.

CONCLUSION:

Studies related to ‘recruitment’ in general and ‘decision making in recruitment’ in particular are almost absent in the Indian context. Decision making is a fundamental aspect of recruitment and deserves much more research investigation than it has received so far. Role of competency in recruitment is also relatively unexplored. This paper proposes a conceptual framework of how people arrive at recruitment decisions using Brunswik’s Lens model.

This model has been compared with other decision making approaches to understand how this model is probably appropriate for a study on recruitment. This comparison will help us to gauge lens model with other decision making approaches in terms of perspective, advantages and limitations. Hammond (cited in Cooksey, 2008) conducted a very thorough comparison of fourteen major approaches to judgment and decision making. These approaches can be ranked in the order of least psychological (most mathematical) to most psychological (least mathematical) dimension: Decision Theory (Expected Utility); Behavioral decision making (Subjective Expected Utility); the Analytic Hierarchy process, Fuzzy decision theory, Signal detection theory, Heuristics and Biases/ Prospect Theory; Requisite decision models; Lens model and Social Judgment Theory; Information Integration Theory; Image theory; Attribution Theory; Recognition primed decision models; Explanation based decision theory, Conflict/constraints theory. It is beyond the capacity of this paper to claim how lens model as a school of thought it better or worse than the other approaches mentioned.

However, if we notice lens model and social judgment theory lies at the middle of the rung (among the decision making approaches) where it has combinations of both mathematical and psychological components. Though this model is mathematical in representation, but it has elements of subjectivity in it, which makes this model only partially analytical. The strongest proof of this lies in Brunswik’s emphasis throughout on the importance of ‘perception’ in judgment. Harvey, (2001) puts forth that, “Those interested in decision making are influenced by economists’ and statisticians’ research into how decisions ought to be made... In contrast, those interested in judgment have been influenced mainly by research on perception (e.g., Brunswik, 1956). They are concerned primarily with how probabilistic environmental cues to some criterion variable and fallible cognitive processing of those cues result in estimates or predictions for that variable”. Decision making became an interesting domain of reasoning that Brunswik saw as cutting across the dichotomy of perception and thinking (Doherty and Kurz, 1996). It is not that the person does not think or does not need to think while taking a decision, but it is the earlier instance of perception which is followed by thinking which makes ‘decision making’ a complex phenomenon lying at the interface of subjective and objective assessments. Possibly this ability to capture both subjective and objective dimensions in decision making that makes the Lens model a robust method.

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Received on 18.09.2013 Modified on 25.10.2013

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