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The present study has been carried out to assess the effect of constructs of service convenience on customer satisfaction of the Indian online shoppers.

The primary data was collected through a structured questionnaire. Convenience sampling has been used to choose a sample (n = 260) of e-shoppers in India. Factor analyses (both EFA and CFA) have been done to validate different factors and its items. A conceptual model has been proposed to measure the effect of different factors of service convenience on customer satisfaction. Moreover, the perceived difference with respect to study variables has been measured. The path analysis through AMOS 22.0 has been done to test the hypotheses under study.

It can be concluded that the effect of access convenience, search convenience, and order convenience have significant effects on customer satisfaction. However, evaluation convenience and logistics and reverse logistics convenience have an insignificant effect on customer satisfaction. The present study has a unique contribution in the field of service convenience to e-retailing customers. Moreover, the present study indicates that gender does not moderate the effect of convenience on customer satisfaction.

This is one of the few papers that focuses solely on the effect of gender on service convenience and customer satisfaction. The findings will generate value with their originality and significant managerial implications for marketers, as well as future research directions for the researchers.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.