Conceptual Model Building, Model Representation,Conceptual Model Building, Model Representation,Construct Operationalisation Review (CORE) and Construct Operationalisation Review (CORE) and

Construct ValidityConstruct Validity

Professor Luiz MoutinhoProfessor Luiz MoutinhoUniversity of Glasgow, ScotlandUniversity of Glasgow, Scotland

SCIENTIFIC MODELLING is the process of generating abstract, conceptual, graphical or mathematical models.

•A scientific model can provide a way to read elements easily which have been broken down to a simple form.

•Modelling is an essential and inseparable part of all scientific activity.

RESEARCH MODELS

used to describe the overall framework used to look at reality, based on a philosophical stance

•E.g. empiricism, positivism, postmodernism, post-structuralism•Models identity basic concepts and describe what reality is like, and the conditions by which we can study it•Ideas identified in models are called concepts.

RESEARCH MODELSMeanings and Communication

•Concepts are used to impose some sort of coherent meaning on the world•It is through them that we can make sense of reality, and perceive order and coherence•Used to communicate our experience of the environment around us•Our perception of our surroundings is therefore highly dependent on the scale of our knowledge and our familiarity with a wide range of concepts.

RESEARCH MODELS

Concepts and Statements

The use of concepts on their own is limited in research

We expect that research should provide: A system of classification Offer explanations, Make predictions, and Acquire a sense of understanding

Concepts are only useful in providing a system of classification (typology) the remaining expectations are met by research statements.

Definitions

•Model A model is a set of variables and their inter-relations designed to

represent some real system or process, but that not fully represent that same reality

•A theoretical framework is How one theorizes or makes logical sense of the relationships

among factors that have been identified as important to the problem being investigated, which integrate one’s logical beliefs with published research

•Theory comes from ancient Greek theôria meaning contemplation, speculation. Thea – “a view” + horan – “to see”, literally “looking at a show”

•It is from the theoretical framework, then, testable hypotheses can be developed to examine whether the theory formulated is valid or not

RESEARCH MODELS

Caveats

Sometimes the word ‘model’ is used incorrectly – it is used in a much more constrained sense to indicate a set of (hopefully) related concepts

Similar use occurs with ‘framework’ – have to distinguish between the disciplinary usage of the term and the term as it exists in the philosophy of science

Also known as research philosophy, research paradigm,….

THEORIES, METHODS, DOMAINSSingle versus Multi-method Research

•In general the best advice would be to select a single paradigm (qualitative or quantitative) for your research work (after Creswell 2003)•Based on pragmatic choices: time, skills, and overall size of the project•The reason for this is that qualitative and quantitative research are based on differences in:

• Nature of reality – ontology• Relationship to that being research – epistemology• Roles of values – axiology• Use of language/words – rhetorical• Overall process of research - methodological

THEORIES, METHODS, DOMAINS

Methods and Techniques

•Methods (a.k.a techniques) are used to reveal the existence of, identify the ‘value’, significance or extent of, or represent semantic relationships between one of more concepts identified in a model from which statements can be made.

•Sometimes a distinction is made between methods and technique – one definition has technique as the way or manner in which a method is applied or deployed

Reductionism – problems as a whole are better understood if they are reduced into the simplest possible elements.

Entropy is designed to encapsulate the whole of the research measurement process as a system.

Parsimony is the avoidance of unnecessary complexity

Three purposes for modelling in management – measurement, decision support, and explanation or theory building

The purpose of the model is to provide a prediction system which can be manipulated to study the real world situation for the purpose of aiding the decision maker.

Model Benefits

Small models can offer insight

Models can identify phenomena

Operational models can provide long-term benefits

A model is a set of variables and their inter-relationships designed to represent some real system or process.

A theoretical model is a set of assumptions that describes a subject environment. Its purpose is to explain the subjects’ phenomena.

Model Representation

… it models only a very small fragment of a world.

Models in general are representations of systems and their entities in an abstract, easy to understand way, i.e., the model does not contain all the possible details of the actual system, but presents a limited parallelism.

SCIENTIFIC VISUALISATION

(Post) is the transformation, selection, or representation of data from simulations or experiments, with an implication explicit geometric structure, to allow the exploration, analysis, and understanding of the data.

(Pre) Systems visualisation provides a researcher the ability to quickly understand the complexity of a theoretical system. The need of knowledge representation through ontologies.

What is a Model?

A model is a stylized representation of reality that is easier to deal with and explore for a specific purpose than reality itself.

We use the following types of models:

Verbal

Box and Arrow

Mathematical

Graphical

An Example of a Verbal Model

Sales of a new product often start slowly at “innovators” in the population adopt the product. The innovators influence “imitators”, leading to accelerated sales growth. As more people in the population purchase the product, sales continue to increase but sales growth slows down.

Boxes and Arrow Model

Fixed Population Size

Imitators

Timing of Purchases by Imitators

Pattern of Sales Growth of New Product

Innovators

Timing of Purchases by Innovators

InnovatorsInfluenceImitators

Mathematical Model

))(( ttt xNbxadt

dx

Where:

xt = Total number of people who have adopted product by time tN = Population sizea,b = Constants to be determined. The actual path of the curve will depend on these constants

Graphical Model

FixedPopulation Size

Time

Cumulative Salesof a

Product

The model builder’s task is to identify those factors that have a significant effect on the dependent construct and to try to express those effects as “influence functions”, which are then incorporated in the model.

The process of model building is a problem-solving analysis that enables attention to be focused on the relevant factors.

The Modelling Process

Dimensions

Constructs

Sub-constructs

Variables

Items

Measures

Scales

Surveys

Case Study Research

Action Research

Grounded Theory

Mode 2 Research

Ethnographic Research

Positivism

Realism

Interpretativsm

Constructivism

Ontology

Ontology

Reality

RealityPhilosophicPerspectives

Method & Strategies of

Research

Modelling

Natu

reK

no

wled

ge

Research D I C O S U V A M (i) Mnemonic

Modelling

DIMENSIONS(DOMAINS)

CONSTRUCTS

SUB-CONSTRUCTS

VARIABLES

MEASURES

ITEMS

Construct/Construal - is a term/concept that is somehow involved in the

management problem that will be researched

Parameters - define the “state of the system”

Constants - are characteristics of the system that do not change

•The model may be considered to represent relationships among constants, parameters and variables of the business system and its environment. The constants are characteristics of the system which do not change over the period of interest.

•Parameters may be controllable or non controllable in the real world, but once given, they generally remain constant over a time period. Parameters describe the “state” of the system.

•Variables may also be either controllable or non controllable and represent characteristics of the system which change continuously or are subject to change at any time.

MotivationsSocial Groups

Event Attraction& Excitement

Cultural/ Historical Attraction

Socialization & Entertainment

Family Togetherness

Site Novelty

Group Togetherness

G1G2G3

M1M2M3

M4M5M6

M8M9

M10

M11M12M13

M14M15M16

M5M6M7

Theoretical Construct

Operational Construct

Empirical Concept (Variable)

Proposition

Correspondence Rules

HypothesesOperationalDefinitions

Soil of Observation (Experience)

Theoretical framework. Adapted from Bagozzi (1980)

Effects of Group Membership and Motivation on Attendance

Model High-Level Abstraction

•Epistemological (meaning)

•Ontological (nature of being)

•Etymological (roots)

•Nomological validity (theories)

•Semiotics(signs and symbols)

•Epidemics (map out the scope)Causal Network of Concepts

•Identification

of concepts and relationships

of direction of impact

of intensity

of direct/indirect effects

•The notion of the concept “stretching” relates to a construct that is defined at a high level of abstraction and has both a large bandwidth (i.e., broad coverage) and a wide connotation (i.e., lumping of too many classes of things with little attribute precision).

(Osigweh 1989)

Construct Operationalisation Review

(CORE)

CORE•NOMOLOGICAL VALIDITY

•THEORETICAL UNDERPINNINGS

•DISSECTION OF CONSTRUCT VALIDITY

•DEFINITIONS, DIVIDES AND DILEMMAS

•MEASUREMENT SCALING

+•CONTEXT OF RESEARCH

•MANAGERIAL IMPLICATIONS

Review of measurement scales used in previous studies

Loyalty -Repurchase probability (Andreassen and Lindestad, 1998)

-Word of mouth

-Prefer the particular bank to other financial institutions (Nguyen and LeBlanc, 1998; Ruyter, Wetzels and Bloemer, 1998)

-INTEND TO USE THE BANK IN THE YEARS TO COME (Ruyter and Bloemer, 1999; Ruyter, Wetzels and Bloemer, 1998; Pedersen and Nysveen 2001)

-Consider the bank the first choice for following purchases (Ruyter and Bloemer, 1999; Wetzels and Bloemer, 1998; Yu and Dean, 2001)

-Propensity to switch (Parasuraman et al., 1994 – cited in Rosen and Surprenant, 1998; Zeithaml et al., 1996; Mittal and Lassar, 1998; Moutinho and Brownlie, 1989)

-Cognitive loyalty

- provide positive word-of-mouth to potential buyers (Andreassen and Lindestad, 1998; Yu and Dean 2001)

-intend to recommend the financial institution to others (Nguyen and LeBlanc, 1998; Yu and Dean, 2001; Pedersen and Nysveen, 2001)

-Say positive things about the bank to other people (Ruyter, Wetzels and Bloemer, 1998; Yu and Dean, 2001)

-Encourage friends and relatives to do business with the bank (Ruyter, Wetzels and Bloemer, 1998; Yu and Dean, 2001)

Review of measurement scales used in previous studies

Service attributes

Inertia

-Location (Moutinho and Brownlie, 1989; Leonard and Spencer, 2991)

-New and improved services (Moutinho and Brownlie, 1989)

-Helpfulness of staff (Moutinho and Brownlie, 1989)

-Banking fees (Moutinho and Brownlie, 1989)

-Queueing (Moutinho and Brownlie, 1989)

-Courteous personnel (Leonard and Spencer, 1991)

-Modern facilities (Leonard and Spencer, 1991)

-Loans money easily (Leonard and Spencer, 1991)

-No established scale in the existing body of literature

Definition of variables and measurement used in the study

Construct Type of variables

Definition of variables Key relevant research

Measurement

Control Dependent Mechanism of control: the method by which control is exercised

Schann (1988) Measuring the appointment of high-level managers made by whom

Extent of control: the degree of control over a JV is exercised by parents

Killing (1983)Wu (1994)Cheng (1996)

Measuring the score and classifying into 4 type of control

Focus of control: the control is exercised in which area of joint venture’s operation

Killing (1983)

Ownership Independentdependent

The share of equity held by the Taiwanese and foreigner parents

Measured as a percentage

Bargaining Power

IndependentDependent

The power that can be used to affect the outcome of the negotiation process

Fagre & Wells (1982)Yan & Gray (1994)

Using 5-points scale to measure 10 items

Contribution IndependentDependent

The resources contributed by the Taiwanese and foreigner parents

Grant (1991)Barney (1991)Chatterjee & Wernerfelt (1991)

Using 5-points scale to measure 14 items

Motivation Independent The motives of companies cooperate with other firms to establish a joint venture

UNEC (1988) and relevant literatures

Using 5-points scale to measure 26 items

Development of Conceptual Framework

Identify constructs/ concepts

Specify and define constructs/concepts

Decide on a model

Operationalise constructs/concepts

(operational definitions) Identify and explore

relationship between constructs/concepts

Operationalisation of the Constructs

•A model ties together various constructs and their relationships

•A model connects constructs in ordered relationships

•A relationship is a meaningful link believe to exist between two constructs

•The researcher translates the construct into an operational definition, which describes how a researcher measures the construct. That is, an operational definition implies a specific question format that will be used in a survey. To capture the essence of each research construct. Specific measurement scaling and statistical analyses.

Operationalisation of the Constructs

•Decide on a model – once you take a set of constructs and order their relationships with some understandable logic, you create a model

•The amount of effort the researcher spends in gaining an understanding for a research problem, pays off in model specification

What is an operational definition?

•A construct is an abstract concept (the building blocks of a theory and represent the points around which business research is conducted.

•The actual measure of the construct is the construct operationalisation

•Operationalisation refers to the operations by which a concept is measured (example: IQ is a measure for intelligence)

•Operationalising or operationally defining a concept to render it measurable, is done by looking at the behavioural dimensions, facets or properties denoted by the concept

•These are then translated into observable and measurable elements so as to develop an index of measurement of the concept

It is important to be accurate in order to have valid measures.

What an operational definition is not

•Does not describe the correlates of the concepts

•Does not delineate the reasons, antecedents or consequences of the concept

An example: Operationalising the concept of “learning”

Delineate the dimensions and elements of the concept learning

Learning

ApplicationRetentionUnderstanding

Integrate with other relevant

material

Solve problems applying concepts

understood and recalled

Recall material after some

lapse of time

Give appropriate examples

Answer questions correctly

Modelling + Measurement (M2)

•SUBSTANTIATE

•DEFINE

•MEASURE

(SDM)

Cross-Examination of Model Constructs

•Comparability - (CL) – construct, operational measures and interrelationships between

constructs

•Relativity - time frame and amount

•Referencing - attribute by attribute equivalence or valence

•Variability - contextual and group

•Equilibrium - a balanced perspective of the interplay between equivalent research constructs

•Multidimensionality - an assessment of the degree/level and amount of dimensions related to each construct

•Measurability - Construct Measurement Robustness

Construct Validity

The vertical correspondence between a construct which is at an unobservable, conceptual level and a purported measure of it which is at an operational level.

Validity

•Refers to the issue of whether an indicator that is devised to gauge a concept really measures the concept

Face validity: if the measure apparently reflects the content of the concept in question

Concurrent validity Predictive validity Construct validity Convergent validity

The measurement process

•Validity Ensured the ability of a scale to measure the intended concept Types of validity

• Content validity

• Ensures that the measure includes an adequate and representative set of items that tap the concept

• Criterion-related validity

• Is established when the measure differentiates individuals on a criterion it is expected to predict

• Concurrent validity

• Predictive validity

The measurement process

•Validity Types of validity

• Construct validity

• Testifies to how well the results obtained from the use of the measure fit the theories around which the test is designed

• Convergent validity: correlation between two different instruments measuring the same concept

• Discriminant validity: when empirical evidence about correlation between two variables support the initial prediction, based on theory, that the variables are unrelated

• Techniques

• Correlation analysis

• Factor analysis

• Multitrait analysis

For the explanatory-predictive validity of concepts, it is useful to distinguish two evaluative discussions, namely the accuracy and the range of the explanation-prediction. The dimension of accuracy refers to the extent of agreement between the predicted and the observed value for each dependent variable. The range refers to the number of dependent variables that can be explained–predicted with the help of the independent variables. The accuracy is indicated by the criterion-related validity.

Validity of Measurements

•Content validity – the extent to which the measure appears to measure the characteristic it is supposed to measure

•Criterion/pragmatic/empirical validity – the extent to which a measure can be used to predict individual’s score on some other characteristic (the criterion)

•Construct validity – the extent to which the measure behaves in a theoretically sound manner

Different types of equivalence

•Operationalisation equivalence – “best capture the latent construct” (Malhotra and McCort 2001, p. 237)

•Construct equivalents (Singh 1995, Ulijn, et al. 2000,

Weinfurt and Mohgaddam 2001), construct which will …Serve the same function and will be expressed similarly (functional and conceptual equivalence),

Be interpreted similarly (instrumental equivalent), andThe construct equivalency (measurement equivalence) across cultures

Validity Assessment Approaches

Approach Description Procedure

1. Content Validity

The extent to which a measure appears to measure the characteristic it is supposed to measure.

Subjective assessment of the appropriateness of the measure for the task at hand.

1.1 Face Validity The extent to which a measure seems to capture the characteristic of interest.

Agreement between expert and/or non-expert judges as to the suitability of the measure.

1.2 Sampling Validity

The extent to which a “content population” of situations/behaviours relating to the characteristic of interest (i.e. the characteristic’s conceptual domain) is adequately represented by the measure concerned.

As above

2.Criterion Validity*

The extent to which a measure can be used to predict an individual’s score on some other characteristic (the criterion).

Examination of the relationship between the measure and a criterion.

2.1 Concurrent Validity

The extent to which a measure is related to another measure (the criterion) when both are measured at the same point in time.

Comparison of the scores obtained on the measure concerned and those obtained on the criterion.

2.2 Predictive Validity

The extent to which current scores on a given measure can predict future scores of another measure (the criterion).

As above

*Also know as pragmatic or empirical validity

Validity Assessment Approaches

Approach Description Procedure

3. Construct Validity

The extent to which a measure behaves in a theoretically-sound manner.

Investigation of the relationships between the measure concerned and measures of other concepts/characteristics within a theoretical framework.

3.1 Convergent Validity

The extent to which a measure is positively related to other measures of the same concept obtained by independent methods.

Examination of the relationships between measures of the same concept generated by different methods.

3.2 Discriminant Validity

The extent to which a measure is not related to measures of different concepts with which no theoretical relationships are expected

Examination of the relationships between measures of different concepts that are theoretically unrelated.

3.3 Nomological Validity

The extent to which a measure is related to measures of other concepts in a manner consistent with theoretical expectations.

Examination of the relationships between measures of different concepts that are theoretically unrelated

Types of Concept Validity

1. Observational validity The degree to which a concept is reducible to observations

2. Content validity The degree to which an operationalisation represents the concept about which generalisations are to be made.

3. Criterion-related validity

3a. Predictive validity

3b. Concurrent validity

The degree to which the concept under consideration enables one to predict the value of some other concept that constitutes the criterion.

A subtype of criterion-related validity in which the criterion measured is separated in time from the predictor concept.

A subtype criterion-related validity in which the criterion and the predictor concepts are measured at the same time.

4. Construct validity

4a. Convergent validity

4b. Discriminant validity

4c. Nomological validity

The extent to which an operationalisation measures the concept which it purports to measure.

The degree to which two attempts to measure the same concept through maximally different methods are convergent. It is generally represented by the correlation between the two attempts.

The extent to which a concept differs from other concepts.

The extent to which predictions based on the concept which an instrument purports to measure are confirmed.

5. Systemic validity The degree to which a concept enables the integration of previously unconnected concepts and/or the generation of a new conceptual system.

6. Semantic validity The degree to which a concept has a uniform semantic usage.

7. Control validity The degree to which a concept is manipulable and capable of influencing other variables of influence.

As criteria for the descriptive validity of concepts, the following can be proposed: reliability, convergent validity, nomological validity, content validity and discriminant validity. All of these criteria, with the exception of discriminant validity, focus on the relationship between a concept and its real referent.

Discriminant validity

•Discriminant validity describes the degree to which the operationalisation is not similar to (diverges from) other operationalisations that it theoretically should not be similar to.

•The concept of discriminant validity refers to the extent to which an operationalisation of a construct measures just the intended construct itself and not other constructs.

Discriminant validity

•Campbell and Fiske (1959) introduced the concept of discriminant validity within their discussion on evaluating test validity. A successful evaluation of discriminant validity shows that a test of a concept is not highly correlated with other tests designed to measure theoretically different concepts.

•In showing that two scales do not correlate, it is necessary to correct for attenuation in the correlation due to measurement error. It is possible to calculate the extent to which the two scales overlap by using the following formula where is correlation between and is the reliability of , and is the reliability of :

rxy x,y rxx ryy

y

yyxx

xy

rr

r

,

x

Discriminant validity

•Although there is no standard value for discriminant validity, a result less than .85 tells us that discriminant validity likely exists between the two scales. A result greater than .85, however, tells us that the two constructs overlap greatly and they are likely measuring the same thing. Therefore, we cannot claim discriminant validity between them.

Discriminant validity – an example

•Consider a researcher developing a new scale designed to measure Narcissism. They may want to show discriminant validity with a scale measuring Self-esteem. |Narcissism and Self-esteem are theoretically different concepts, and therefore it is important that they researcher show that the new scale measures Narcissism and not simply Self-esteem.

•First, we can calculate the Average Inter-Item Correlations within and between the two scales:

-Narcissism – Narcissism: 0.47

-Narcissism – Self-esteem: 0.30

-Self-esteem – Self-esteem: 0.52

Discriminant validity – an example

•We then use the correction for attenuation formula:

•Since 0.607 is less than 0.85, we can conclude that discriminant validity exists between the scale measuring narcissism and the scale measuring self-esteem. The two scales measure theoretically different constructs.

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