CHAPTER 4: RESEARCH DESIGN AND METHODOLOGY
4.7 Method of Data Analysis
4.7.4 PLS: The Outer Model
The outer model describes the relationships between the observable variables, which are called manifest variables (MV) or indicators, and the unobservable latent variables (LV) or constructs. The nature of the relationship between a construct and its indicators can be modeled in three ways: the reflective (Mode A or principal factor model), the formative (Mode B or composite latent model), and the MIMIC (Mode C). All three models as well as the relationships between the LV and the MVs are presented in Figure 4.2 and 4.3 below (Chin 1998a; Diamantopoulos, Riefler et al. 2008; Franke, Preacher et al. 2008; Westlund, Kallstrom et al. 2008). In this study, the formative measurement model was selected for all constructs. In the reflective model, the MVs are reflections of the LVs (LV→ MV); the indicators are known as effect indicators and the LV as latent
construct. The reflective model is the most common type used in SEM and particularly in the business field. In the formative model, the MVs cause variance in the LV (LV← MV); the indicators are known as formative indicators and the LV
as the emergent construct (Diamantopoulos and Winklhofer 2001; Coltman, Devinney et al. 2008; Westlund, Kallstrom et al. 2008; Cenfetelli and Bassellier 2009). The MIMIC (multiple indicators-multiple causes) model is a mixture of the reflective and the formative models (Franke, Preacher et al. 2008; Vinzi, Chin et al. 2010).
Figure 4.2: Reflective and Formative measurement models
Source: (Diamantopoulos, Riefler et al. 2008)
Figure 4.3: MIMIC model
Source: (Franke, Preacher et al. 2008)
parameter estimation and lead to incorrect conclusions on tested relationships (Jarvis, Mackenzie et al. 2003; Diamantopoulos, Riefler et al. 2008). According to Diamantopoulos and Winklhofer (2001, p.274), there is “an almost automatic
acceptance of reflective indicators in the minds of researchers”. They believe that in many cases, constructs are operationalized with reflective indicators instead of the more appropriate formative indicators. Jarvis, Mackenzie et al. (2003) through their research on the marketing literature confirmed the above. They found that 29% of top-level marketing articles have adopted the wrong model and from those 95% had incorrectly used the reflective instead of the formative model.
The selection of the model should also be based on theoretical considerations, the objectives of the study, and empirical issues (Fornell and Bookstein 1982; Diamantopoulos and Winklhofer 2001). In order to determine which one is the appropriate measurement model for this study, we have used the four primary decision rules - the direction of causality, the interchangeability of the indicators, the intercorrelation among the indicators and relationship of the indicators with the construct - suggested by Jarvis, Mackenzie et al. (2003). The first rule is the direction of causality between the MV and the LV, which is also the basic theoretical consideration between reflective and formative models. In the reflective model the causality is from the constructs to the indicators while in the formative model it is from the indicators to the constructs. This is illustrated in Figure 4.2 (Panel 1) where the unidimensional construct (η) is represented by
formative model (Panel 2), the flow of arrows is from the indicators
X
i to theconstruct η and
i is a coefficient capturing the effect of indicatorX
i on thelatent variable η and ζ represents all other possible causes that are not represented in the indicators (Diamantopoulos and Winklhofer 2001; Jarvis, Mackenzie et al. 2003; Coltman, Devinney et al. 2008; Westlund, Kallstrom et al. 2008; Cenfetelli and Bassellier 2009).
The second rule is the interchangeability of the indicators; the characteristics of the indicators that are used to measure the construct are different in the reflective and formative models. In the reflective model, the indicators are manifested by the construct and changes in the construct lead to changes in the indicators. So, the indicators should be internally consistent and conceptually interchangeable. Adding or removing an indicator may affect reliability but does not change the nature of the construct. In the formative model, the indicators define the construct and a change in the indicators lead to changes in the construct without necessarily affecting the other indicators. So, the construct is sensitive to the number and type of indicators used (Jarvis, Mackenzie et al. 2003; Coltman, Devinney et al. 2008; Franke, Preacher et al. 2008).
The third rule is the covariation among the indicators; expected in reflective but not necessary in formative models. For example, in our case a drop in the level of satisfaction with the depth of the products offered is not expected to bring any changes in the level of satisfaction with car parking or
the store does not imply that there is any change in the level of satisfaction with the music inside the store.
The final rule is the relationship of the indicators with the construct. In the reflective model the indicators should not be different, they should have the same antecedents and consequences. In the formative model, the indicators do not need to have a similar relationship thus it is important to find a balance between the level of aggregation of the formative indicators and the level of diversity and richness that the indicators describe the construct (Diamantopoulos and Winklhofer 2001; Jarvis, Mackenzie et al. 2003). Using these rules, the formative measurement model was selected for this study and thus the appropriate type of analysis was followed.
Our model examines the relationship between the endogenous variable of SB purchases and the three exogenous variables of customer satisfaction, trust in SB, and word-of-mouth. However, the constructs of customer satisfaction and trust in SB are conceptualized and operationalized as multidimensional entities (Law, Chi-Sum et al. 1998). As is illustrated in Figure 4.4, there are a number of formative indicators (the observed variables) that are used to measure the three dimensions (first-order) and then we relate these dimensions to the (second-
order) latent construct (Diamantopoulos, Riefler et al. 2008). The construct 4 is a multidimensional aggregate construct, that is if we combine all dimensions, 1,
2
, and
3
, we produce the construct. These three dimensions are not directly observable, instead they are constructs themselves and they are measured using
indicators to be directly related to the model, this will result in a larger model and in a loss in parsimony. Furthermore, we might not obtain the same level of accuracy in our analysis of relationships since our measurement – with the deconstruction – will be at higher level (Petter, Straub et al. 2007).
Figure 4.4: Formative First-Order, Formative Second-Order
Source: (Diamantopoulos, Riefler et al. 2008)
Our definition of customer satisfaction emphasizes the evaluative process by which the response is determined rather than the construct itself. Therefore, in our model, we conceptualized the satisfaction with the service environment, the service delivery and the service product as three interrelated constructs (first- order constructs), which report different aspects of the customer satisfaction construct. Therefore, these first-order constructs can be grouped together to provide us with customer satisfaction (the second-order construct). In addition, we conceptualized the trust in food SB and the trust in non-food SB as two interrelated constructs that can provide us with an overall level of trust in SB. The overall measurement model as well as the formative indicators used to
measure the first-order constructs is illustrated in Table 4.14. In SmartPLS, the selected software application for this study, second-order constructs are measured using the repeated indicator approach. That is, we have reassigned all indicators given to the first order constructs to the second order.
Table 4.14: Emergent Measurement Model
Formative Indicators First – Order
Construct
Second – Order Construct The cleanliness of the space
Service Environment
Customer Satisfaction The signs on the aisles of the store
The music inside the store
Available employees for help/service
Service Delivery Frequency of expired products
The prices are visible on the shelves
The prices are the same on the shelves and at the cashier
Frequency of out of stocks The size of the store
Service Product The distance from the house/work
The parking
Level of satisfaction with the width Level of satisfaction with the depth Luncheon Meat/Cheese Trust in Food SB Trust in SB Soft drinks Dairy products Wine Beer
Other food products Juices
Detergents Trust in
Non-Food SB Shampoo & Bath foams
Paper products
As we see in Table 4.14, thirteen formative indicators were used for the construct of customer satisfaction, ten formative indicators for the construct of trust in the SB and one for W-O-M. So, the above mentioned constructs are dependent variables and the formative indicators are the explanatory variables that may cause variance in their respective constructs (Diamantopoulos and Winklhofer 2001). The formative indicators are Likert scale items measuring each of the three constructs and were selected in such a way as to adequately describe the constructs.