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<p>Foreword ix</p> <p>Introduction xiii</p> <p><b>Chapter 1. Characteristics and Main Types of Measurement </b><b>1</b></p> <p>1.1. Introduction 1</p> <p>1.2. The basis of the measure 2</p> <p>1.2.1. Definition of the measure and connected concepts 2</p> <p>1.2.2. The basic scales 5</p> <p>1.3. Attitude scales 9</p> <p>1.3.1. The main formats of multiple scales for measuring attitudes 12</p> <p>1.3.2. The choice of an attitude scale 21</p> <p>1.4. Conclusion 25</p> <p>1.5. Knowledge tests 25</p> <p><b>Chapter 2. Standardizing or Constructing a Measurement Scale </b><b>27</b></p> <p>2.1. Introduction 27</p> <p>2.2. Existing or new scale: a range of choices 28</p> <p>2.2.1. Standardizing or constructing a scale: benefits and limits 29</p> <p>2.2.2. A continuum of possible choices 31</p> <p>2.3. Reflection points to facilitate the choice of a scale’s mode of use 34</p> <p>2.3.1. The basis for the decision 35</p> <p>2.3.2. The search for equivalence 37</p> <p>2.4. Conclusion 44</p> <p>2.5. Knowledge tests 44</p> <p><b>Chapter 3. Conception of a Measurement Scale </b><b>47</b></p> <p>3.1. Introduction 47</p> <p>3.2. Conception according to the nature of indicator-construct relationships 48</p> <p>3.2.1. The types of construct specification 48</p> <p>3.2.2. The production protocols of a scale according to its nature 53</p> <p>3.3. Conception of a single-item or multi-item measurement scale 62</p> <p>3.3.1. The C-OAR-SE procedure: controversial contributions 62</p> <p>3.3.2. The choice of a scale apprehension: large or small? 65</p> <p>3.4. Conclusion 67</p> <p>3.5. Knowledge tests 68</p> <p><b>Chapter 4. Construction of a Measurement Scale </b><b>69</b></p> <p>4.1. Introduction 69</p> <p>4.2. The foundations for producing a multi-item measurement scale 70</p> <p>4.2.1. Churchill’s paradigm 70</p> <p>4.2.2. Extensions and improvements to the scale development process 72</p> <p>4.3. Updating the process of constructing a measurement scale 85</p> <p>4.3.1. The process of developing a scale: updated sequence 86</p> <p>4.3.2. The main axes for developing a scale 89</p> <p>4.4. Conclusion 95</p> <p>4.5. Knowledge tests 95</p> <p><b>Chapter 5. Design of a Measurement Scale </b><b>97</b></p> <p>5.1. Introduction 97</p> <p>5.2. The quantitative attributes of a measurement scale 98</p> <p>5.2.1. Optimal number of items 98</p> <p>5.2.2. Number of response modalities 101</p> <p>5.3. The verbal components of a measurement scale 109</p> <p>5.3.1. The formulation of the items 109</p> <p>5.3.2. Label of the response modalities 118</p> <p>5.4. The arrangement of the design components of a scale 120</p> <p>5.4.1. Marking the scale attributes: some results 121</p> <p>5.4.2. Points of reference 127</p> <p>5.5. Conclusion 129</p> <p>5.6. Knowledge tests 130</p> <p><b>Chapter 6. Quantitative Purification of a Reflective Scale </b><b>131</b></p> <p>6.1. Introduction 131</p> <p>6.2. Examination of the dimensionality of a measurement scale 132</p> <p>6.2.1. The contributions of exploratory factor analysis to the scale development process 133</p> <p>6.2.2. The implementation of exploratory factor analysis 135</p> <p>6.2.3. Practices for better use of exploratory factor analysis 139</p> <p>6.3. The true value model 144</p> <p>6.4. Reliability 147</p> <p>6.4.1. Conventional tests of the reliability of a measurement scale 147</p> <p>6.4.2. Some recommendations for reliability testing 151</p> <p>6.5. Conclusion 153</p> <p>6.6. Knowledge tests 154</p> <p><b>Chapter 7. Validity of a Measurement Scale </b><b>155</b></p> <p>7.1. Introduction 155</p> <p>7.2. The main forms of the validity of a measurement scale 156</p> <p>7.2.1. Content validity 156</p> <p>7.2.2. Construct validity 163</p> <p>7.2.3. Nomological validity 163</p> <p>7.3. Protocols for checking the construct validity 168</p> <p>7.3.1. The multitrait-multimethod matrix (MTMM) 169</p> <p>7.3.2. Confirmatory factor analysis 173</p> <p>7.4. Practical guides for assessing the validity of a measurement scale 179</p> <p>7.4.1. Focus on confirmatory factor analysis (CFA) 179</p> <p>7.4.2. Focus on the multitrait-multimethod matrix (MTMM) 181</p> <p>7.4.3. Synergy in perspective 183</p> <p>7.5. Conclusion 186</p> <p>7.6. Knowledge test 187</p> <p>Conclusion 189</p> <p>Glossary 191</p> <p>References 201</p> <p>Index 219</p>

Azza Frikha has a PhD in Management Sciences from the University of Rennes 1 and is a University Professor of Marketing at the Tunis Business School (ESCT).

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