Empirical study on a class of problems for omnichannel retailing in india with special reference to apparel industry

include bibliographic reference and index

PhD: 2023; Management studies

Omnichannel retailing is an integrated experience that melds the advantages of physical stores with information-rich online shopping. To offer a seamless omnichannel shopping experience, retailers need to understand what drives customers towards omnichannel and what dissuades them away from omnichannel. Also, retailers need to build cross channel synergies with effective decision-making regarding order fulfillment. Thus, with this premise, this study addresses a class of problems related to omnichannel with specific research objectives to (a) understand customer-specific drivers and barriers for the adoption of omnichannel (b) rank those drivers and barriers according to their importance (c) classify omnichannel customers according to sociodemographic characteristics and buying behavior, and (d) propose a solution methodology for fulfillment decision problem in omnichannel. To address these objectives, this study is confined to the apparel industry in India and the required primary data is collected from Mumbai and Bangalore as they are among top five Indian cities in terms of omnichannel orders and their price-value. For addressing the first research objective, 10 unique drivers for the adoption of omnichannel retailing in the Indian apparel industry (D-AOCRIAI): Improved Shopping Experience, Reduced Effort, Social Influence, Habit, Hedonic Motivation, Technology Development, Enhanced Promotion, Sporadic Event, Personalization, and Integrated Supply chain and 9 unique barriers (B-AOCRIAI): Inconsistency in Offering, Channel Discord, Lack of Trust, Data Privacy Concern, Lack of Infrastructure and Resources, Psychological Hinderance, Poor Customer Support, Inefficient Order Fulfillment, and Difficulty due to Sporadic Events and their measurement variables are identified. Total Interpretive Structural Modelling (TISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) approaches are used to propose an initial conceptual framework for each of D-AOCRIAI and B-AOCRIAI using data from 12 domain experts and 23 customers. The proposed conceptual framework for each of D-AOCRIAI and B-AOCRIAI is statistically validated and finalized by following descriptive research methods including confirmatory factor analysis and structural equation modeling. The data required for statistically finalizing the proposed framework is collected from 850 customers comprising of 448 adopters and 402 non-adopters of omnichannel by developing an appropriate questionnaire. From the total variance (R2) explained with respect to D-AOCRIAI (R2 = 0.86) and B-AOCRIAI (R2 = 0.71), final version for each of the frameworks is constructed. Further, it is evident that Drivers: Improved Shopping Experience, Reduced Efforts, and Social Influence directly and positively impact omnichannel adoption. Also, Barriers: Lack of Trust, Psychological Hindrance, and Lack of Infrastructure and Resources directly and negatively impact omnichannel adoption. To address the second research objective, the identified unique drivers and barriers are ranked using MCDM methods: Analytical Hierarchy Process (AHP), and Best Worst Method (BWM) respectively using data collected from the group of 36 customers by developing suitable questionnaire for each of these MCDM methods.