A TISM and MICMAC Analysis of Factors During the COVID-19 Pandemic in the Indian Apparel Supply Chain

Abstract

The objective of this study is to explore the challenges faced by the Indian apparel supply chain in the wake of COVID-19 to identify the factors that are being affected and build a multilevel hierarchy model to prioritize the factors and understand their inter-relationships. An intensive literature review was conducted and many experts from apparel supply chain were consulted. The study was conducted by the help of a survey sent to these experts from different echelons in the apparel industry. The data was then analysed using Total Interpretive Structural Modelling (TISM). The “Difficulty in export order fulfilment” factor is found to be the most sensitive factor which means that it is present in the TISM model hierarchy in a place that it is affected by most of the factors and in-turn impacts factors like operational cost, change in marketing strategy, change in consumer buying pattern, which impact Profitability and Cut-off in employment. “Cut-off in employment” is found to be most impacted by all other factors in TISM model.

COVID-19 turbulence and positive shifts in online purchasing by consumers: modeling the enablers using ISM-MICMAC analysis

“…According to Warfield (1982Warfield ( , 1974, the reachability set and the antecedent set for each factor have been attained from the final reachability matrix (see Table 6). When the elements of reachability and intersection set match with each other, that level reaches the topmost position in the ISM hierarchy model (Kumar et al, 2021;Chauhan et al, 2020;Nath et al, 2014). We repeat the matching process by eliminating the set of factors, which are matched until the lowest level in the hierarchy model, is identified.…”

Inhibitors of Industry 4.0 and Circular Economy in Manufacturing Industry Supply Chains

“…The figure below shows the step-wise approach followed in this study to finally evolve the structural model and validation. Moreover, MICMAC analysis is also used to cluster the identified inhibitors based on individual inhibitors' driving and dependency power (Kumar et al, 2022). However, to mitigate the limitation of the ISM, as it does not measure the degree of relationship, thoughtfully Fuzzy AHP is applied.…”

Effect of organic food production and consumption on the affective and cognitive well-being of farmers: analysis using prism of NVivo, etic and emic approach

“…As per the empirical research done in the past, it is well acknowledged that organic farming is a proficiency-based intensive structure rather than input-intensive, but in practice, the implications are reversed. Moreover, marginal farmers are significantly neglected while executing the policies such as extension policies and programs, while smallholders must receive relevant research schemes and funding that target their needs to reverse their condition (HLPE, 2013 ; Kumar et al, 2021 ). By way of breeding, for instance, funding for agroecological research can cause a modest increase in organic production (Murphy et al, 2007 ) or may enhance the knowledge crop rotation and intercropping, and it may raise the overall yield (Kumar et al, 2013 ; Ponisio et al, 2015 ).…”

“…According to Pike (1967), the phonemic and phonetic descriptions of language sounds are where the emic/etic distinction in linguistics first appears. Originally, phonetic accounts were defined as researcher-relevant distinctions about how these sounds are audibly made by native speakers, but phonemic accounts were defined as memberrelevant guidelines about the sound contrasts of language that native speakers maintain in their minds (Markee, 2013;Kumar et al, 2021). Comparisons between cultures or environments are possible because to it (see fig (Watson-Gegeo, 1988), applying NVivo software (Tomar & Sharma, 2021).…”