Better measurement practices are critical to better understanding of sales management issues

Better measurement practices are critical to better understanding of sales management issues Author:- gilbert a. Churchill, jr.

Presented by:- Akanksha (h14127)Hrm - c (2014-16)introductionKnowledge and understanding of measurement tools must increase for advancement of sales and marketingConceptual foundation of measurement as to how they apply to sales researchReviews the notions of validity and reliabilitySuggestions on how sales researchers should proceed with new or borrowed measuresNature and importance of measurementccccccResearcher uses theories to explain phenomenonThese theories and models consist of constructs, linkages between them and data that connects the constructs to the empirical worldSingle lines represent conceptual or constitutive definitions in which a given construct is defined with respect to other constructs in the setThis relationship can be precisely or imprecisely definedDouble lines represent operational definitions that specify how a construct is measured

Nature and importance of measurementSpecifies activities that a researcher must undertake to assign value to the constructsConceptual definitions logically precede the operational definitionsAssess the strength, direction and form of relationships between observable variablesMeasurement is difficult through psychological constructsMeasurement - Rules for assigning numbers to objects to represent quantities of attributesRigour with which the rules have been defined & skill with which they are implemented determine if the construct has been captured by the measureClassification and assessment of errorsObserved measurement (XO) = True Score (XT) + Systematic Error (XS) + Random Error (XR)Systematic error is a constant errorRandom error is not constant & due to transient aspectsDifferences between random and systematic error is essential to assess the validity of measuresValidity of a measuring instrument: The extent to which differences in scores on it reflect the true differences among individuals on the characteristic we seek to measure, rather than on constant & random errorsResearchers responsibility to ensure that the measure accurately captures the characteristic of interestThe relationship between measured score & true score is never established unequivocally but always inferredValidity measuresPREDICTIVE VALIDITY: Focuses on the usefulness of the measuring instrument as a predictor of some characteristic or behaviourCriterion related validity which is relatively easy to assess

CONTENT VALIDITY:Focuses on the adequacy with which the domain of the characteristic is captured by the measureFace validity which is assessed by examining the measure with an eye towards ascertaining the domain being sampled

CONSTRUCT VALIDITY: Most directly concerned with what the instrument is actually measuringThe salespersons motivations, attitudes, behaviours etc. are constructs that are measured through a set of observablesMost difficult type of validity to establishNeed to ensure the domain has been adequately sampled and there is internal consistencyConvergent validity - High correlation with constructs designed to measure same thingsDiscriminant validity - Not correlate too highly with constructs designed to measure different thingsNomological validity - Behave as expected w.r.t. other constructs to which it is theoretically related to

Reliability measuresRELIABILITY: The similarity of results provided by independent but comparable measures of the same object, trait or constructValid measures are usually reliable and the more reliable a measure is, lesser are the random errors involvedIt is a necessary but not a sufficient condition for validity of a measureMore easily measured than validity

STABILITY:Measure the same objects at two different points of time and correlate the obtained scoresScores should correlate perfectly, else random disturbances were operating in either one or both of the test situationsThis process is known as test-retest reliability assessment

EQUIVALENCE:Focuses on internal consistency or homogeneity of the set of items forming the scaleEarliest measure was split-half reliability of scale but the necessarily arbitrary division of items into equivalent halves has an inherent weaknessA better way is to look at all the items simultaneously using coefficient alpha as in the domain sampling modelCoefficient alpha provides a summary measure of the internal homogeneity that exists among a set of items and its square root equals the estimated correlation of the test scores with the true scoresNEW MEASURE

Burden on researcher to prove the reliability and validity of the measureThe steps to be followed for the same are:-1) Defining the construct & specifying its domain2) Generating items to sample the domain3) Collecting data & calculating the required indexes

BORROWED MEASURES

Researcher needs to assess the reliability & validity evidence gathered in support of the measureScales developed in other situations might not display the same desirable properties in the new contextNeed to check these properties by calculating the appropriate coefficients

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