# Analyzing the Enablers of Customer Engagement in Healthcare Using TISM and Fuzzy MICMAC
## 3 Materials and Methods  
Structural modelling identifies certain factors and their interactions [48]. One such modelling approach is Interpretive structural modelling (ISM), primarily propounded by [49]. It detects factors and then models them in a structure depicting a relationship. ISM converts a complex relationship to a well-defined and unambiguous model. The digraph in ISM is represented at two-level, nodes and links. Nodes can be interpreted by delineating the different factors showing them. The pairwise comparison describes the interpretation of links by contextual relationship and relationship direction. Such an interpretation is unable to explain the contextual relationship between the links. Thus, understanding does not help in making a robust decision. To augment decision-making, the relationship in the digraph must be effectively interpreted [50]. Using the interpretive matrix in the ISM approach extends the total interpretive structural modeling technique (TISM). It is the latest and upgraded form of the ISMtechnique [51]. With expert opinion, the TISM approach helps answer the question of how different factors are related and why they are intended to be related. Thus, TISM helps answer what, why, and how in relationship building [50]. The TISM approach has been widely used in previous studies. Researchers identified and modelled the interactions amid the factors contributing toward readiness to change in the healthcare sector using TISM [52]. Enablers of efficiency and sustainability of the healthcare sector were modelled using the TISM approach [53]. In another study, authors applied the TISM methodology to identify and establish interactions among the factors of additive manufacturing in healthcare [54]. Also, the authors used the TISM approach to identify and model the barriers to health 4.0 in India [55]. As per the study conducted [33], Fuzzy TISM and DEMATEL were used to model the factors influencing lean manufacturing in the healthcare sector. The TISM approach was used to model the factors of sustainable resilience in healthcare organizations during the COVID-19 scenario [56]. Therefore, our study is an addition to the existing studies of literature employing TISM and MICMAC in the healthcare sector. The present study uses TISM and Fuzzy MICMAC to model the enablers of customer engagement for branded content in healthcare. Initially, 13 enablers were identified using a literature review. The Delphi technique was employed to finalize the enablers of customer engagement and develop a reachability matrix. A total of seven experts from the academic (4) and healthcare sectors (3) were consulted. Seven being an adequate size, as suggested by [57], the sample size of 5-15 can be used for getting good results from a panel of experts. A questionnaire highlighting the importance of 13 enablers on a 5-point Likert scale was sent to all seven experts. The enablers with a mean score greater than three were further considered for the study. Therefore, eight enablers were finalized by an expert panel for further research. In the second round, the expert panel were given a questionnaire to make a pairwise comparison among the enablers in the form of Yes and No. Yes, is used if enabler 'I' influence '? ', and No if 'I' do not influence '?'. Entry for a particular interaction given by four or more experts was taken. The steps followed in the TISM approach for analyzing enablers of consumer engagement towards branded content are discussed below:  
**Step I: Identification and definition of enablers impacting customer engagement**  
The initial step in the TISM approach is identifying and delineating the enablers from the systematic review of relevant literature. An extant literature review and an expert survey were conducted to identify various enablers of customer engagement for branded content in the healthcare sector. Initially, 13 enablers were identified. These enablers were reconsidered after the discourse with the experts. Finally, eight enablers were considered for further study.