100% tevredenheidsgarantie Direct beschikbaar na je betaling Lees online óf als PDF Geen vaste maandelijkse kosten
logo-home
Total Summary MMSR: lectures, chapters of Hair and article (grade: 8) €16,06
In winkelwagen

Samenvatting

Total Summary MMSR: lectures, chapters of Hair and article (grade: 8)

 0 keer verkocht

This document contains all the Hair chapters needed for the exam, very detailed written down and highlighted what is important. Article of Henseler, Hubona & Ray (2016) is summarized as well. All the lectures are added along the chapters to make it complete. Each chapter shows all the steps that ...

[Meer zien]

Voorbeeld 5 van de 96  pagina's

  • Nee
  • Hoofdstuk 1,2,3,5,6,8,9,10 en 13
  • 29 januari 2025
  • 96
  • 2024/2025
  • Samenvatting
book image

Titel boek:

Auteur(s):

  • Uitgave:
  • ISBN:
  • Druk:
Alle documenten voor dit vak (3)
avatar-seller
vyneegilissen
Samenvatting Hoorcolleges MMSR

Contents
Samenvatting Hoorcolleges MMSR.........................................................................................................1
Lecture 1: Strategy & marketing research lecture...............................................................................1
Lecture information........................................................................................................................2
Literature: Hair, chapters 1, 9 (first part only to section "A simple example of”)............................5
Chapter 1: overview of multivariate methods................................................................................5
Chapter 9: structural equation modeling: an introduction...........................................................12
Lecture 2: Technique consultation: Explorative Factor Analysis........................................................13
Literature: Hair, chapters 2 and 3.................................................................................................15
Chapter 3: Exploratory Factor Analysis.........................................................................................15
Chapter 2: Examining your data....................................................................................................23
Lecture 4: Application lecture...........................................................................................................29
Chapter 10: SEM: Confirmatory Factor Analysis...........................................................................32
Lecture 5: Technique consultation (MANCOVA/ ANCOVA)...............................................................38
Brightspace questions...................................................................................................................38
Chapter 6: MANOVA: extending ANOVA.......................................................................................40
Chapter 5: Multiple Regression.....................................................................................................53
Chapter 8 Logistic regression........................................................................................................63
Discovering Statistics Field Multiple regression analysis...............................................................67
Example of the Logistic Regression...............................................................................................72
Chapter 9: SEM.............................................................................................................................76
Chapter 13: PLS-SEM....................................................................................................................78
PLS-SEM............................................................................................................................................78
Lecture 11: Technique consultation (PLS).........................................................................................86
Article Henseler (2016) “Using PLS path modeling in new technology research: updated
guidelines”....................................................................................................................................90
Lecture 13: end lecture/exam...........................................................................................................92



Lecture 1: Strategy & marketing research lecture
Modeling in Quantitative Research in Marketing and Strategy: Related Constructs

Nominal = Data are categorized into distinct, non-overlapping groups or categories that do not have
a specific order.

1

, For example: gender.
MODE

Ordinal = Data are categorized, but the categories are ordered or ranked in a meaningful way.
However, the differences between the ranks are not measurable or meaningful.
For example, economical status (high, medium, low) OR customer satisfaction (very satisfied,
not satisfied)
MEDIAN and MODE

Interval = Data are measured on a scale with equal intervals between values, but there is no true
zero point (i.e., zero does not mean "none" of the quantity being measured).
For example, temperature, 0 does not mean anything. 20 degrees is not 2x hotter than 10
degrees.
MEDIAN, MODE, MEAN

Ratio = Data are measured on a scale with equal intervals and a true zero point (zero means "none"
of the quantity being measured). This allows for meaningful ratios between values.
For example, height, weight
MEDIAN, MODE, MEAN

Median = middle number
Mode = most frequently
Mean = average


Lecture information
Understanding the nature of constructs
The relationship between them
How to make constructs operational

A theory is a proposed description, explanation or model of the manner of interaction of a set of
phenomena capable of predicting future occurrences or observations of the same kind and capable
of being tested through experiment or otherwise falsified through empirical observation.

A theory in marketing are often not that theoretical. They are the better when they are more
prohibited.
They do not explain something. They consists of constructs (concepts, phenomena, variables). They
are empirically testable or falsifiable.
We need them because the result of a certain situation can be different based on which theory you
use.

A hypothesis
- Usually consists of 2 parts: a condition and a consequence
- Each of the parts contain a construct: independent variables (condition) and the dependent
variables (consequence)

A construct is a conceptual term used to describe a phenomenon of theoretical interest. An indirectly
observable construct is called ‘latent’ for example IQ. A construct MUST be defined in terms of:

2

, - Object: customer loyalty
- Attribute: do people talk positively/ do they come back?
- Rater entity: who is it that rates the construct?
The relationship between constructs
- Direct causal relationship
o A linear effect. A is called exogenous (independent) variable, B is endogenous
(dependent) variable. (the higher A the higher B).

- Mediated causal relationship
o A influences B indirectly. There is an mediator. There can be
full mediation but also partial. Mediation is called partial if the
effect between A and B remains significant after inclusion of
the mediator. Z is called a mediator (variable) and thus
endogenous just like B.

- Spurious relationships
o A third variable influences A and B but sometimes we don’t
have it in our model. For example: both driven by temperature
(drowning and ice cream), but in data there is a correlation
between the 2.

- Bidirectional causal relationship
o A leads to B and B leads to A. does not have to be at the same time. Very difficult to
measure. You need longitudinal setup ad measure over time
to see better how they relate.

- Unanalyzed relationship
o There is a correlation between A and B, we might not see
it, detect it or are not interested but it.

- Moderated causal relationships
o The strength and or direction of the effect of A and B
depends on the level M. M is the moderator (variable). The
more you know (A) the better your result (B) but the class
attention can influence the result eventually as well (M).
they test out boundary conditions.

Example: theory of reasoned action
Action is influenced by the intention which is influenced by the norms and attitudes.

The Two-Language concept
Theoretical variables and observable variables.

Linking theory and observation
Plane of theory: Greek letters
Plane of observation: Roman letters
Correspondence letters: Greek letters


3

,Measurement model and structural model.
structural model uses Greek letters and
theoretical side.
Relationships between constructs is the
structural model.
First the measurement model and then the
structural model.


Measurement model =
The measurement model is observed variables into one construct.




Measurement model looks at the variables that create a phenomenon and thus a construct. While
the structural model looks at the relationship between the constructs (the relationship between the
phenomenon).

Structural model = Relationships between constructs is the structural model.




Multi-item measurement
Increases reliability and validity of measures. It allows measurement assessment:
- Measurement error
- Reliability
- validity

2 forms of measurement models:
- formative (emerging)
o direction of causality is from measure to construct
o no reason to expect indicators to be correlated
o based on multiple regression


4

, o typical for success factor research
o different aspects taking into account that don’t correlate
- reflective (latent)
o validity and reliability is part of this
o direction of causality is from construct to measure
o indicators expected to be correlated
o dropping an indicator from the measurement model does not alter
the meaning of the construct
o the construct determines the measure
o takes measurement error into account at the
item level
o similar to factor analysis

For example: drunkenness
Reflective: walking straight, high level of alcohol in blood (based on multi-collinearity, you want
correlation).
Formative: consumption of beer, consumption of wine, consumption of hard liquor. (you don’t want
correlations and thus no multi-collinearity).
Other variables play a role as well: gender, body mass, training.




Literature: Hair, chapters 1, 9 (first part only to section "A simple example of”)
Chapter 1: overview of multivariate methods
Multivariate analysis methods will increasingly influence not only the analytical aspects of research
but also the design and approach to data collection for decision making and problem solving. Analysis
of multiple variables in a single relationship or set of relationships.


Three converging trends:
1. Big data: Volume, Variety, Velocity, Veracity, Variability and Value.

5

Dit zijn jouw voordelen als je samenvattingen koopt bij Stuvia:

Bewezen kwaliteit door reviews

Bewezen kwaliteit door reviews

Studenten hebben al meer dan 850.000 samenvattingen beoordeeld. Zo weet jij zeker dat je de beste keuze maakt!

In een paar klikken geregeld

In een paar klikken geregeld

Geen gedoe — betaal gewoon eenmalig met iDeal, creditcard of je Stuvia-tegoed en je bent klaar. Geen abonnement nodig.

Direct to-the-point

Direct to-the-point

Studenten maken samenvattingen voor studenten. Dat betekent: actuele inhoud waar jij écht wat aan hebt. Geen overbodige details!

Veelgestelde vragen

Wat krijg ik als ik dit document koop?

Je krijgt een PDF, die direct beschikbaar is na je aankoop. Het gekochte document is altijd, overal en oneindig toegankelijk via je profiel.

Tevredenheidsgarantie: hoe werkt dat?

Onze tevredenheidsgarantie zorgt ervoor dat je altijd een studiedocument vindt dat goed bij je past. Je vult een formulier in en onze klantenservice regelt de rest.

Van wie koop ik deze samenvatting?

Stuvia is een marktplaats, je koop dit document dus niet van ons, maar van verkoper vyneegilissen. Stuvia faciliteert de betaling aan de verkoper.

Zit ik meteen vast aan een abonnement?

Nee, je koopt alleen deze samenvatting voor €16,06. Je zit daarna nergens aan vast.

Is Stuvia te vertrouwen?

4,6 sterren op Google & Trustpilot (+1000 reviews)

Afgelopen 30 dagen zijn er 65907 samenvattingen verkocht

Opgericht in 2010, al 15 jaar dé plek om samenvattingen te kopen

Begin nu gratis
€16,06
  • (0)
In winkelwagen
Toegevoegd