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Generic quality management system standard ISO 9001 and the automotive quality management system standard IATF 16949 both require organisations to demonstrate continual improvement in their customer satisfaction and the number of non-conformities identified during quality system audits. However, the long-term trends of these two parameters under ISO 9001 and IATF 16949 standards are not researched so far. It is expected that under continual improvement, organisations will achieve a step-function/stair-case shaped pattern. This study evaluates if this expectation is true when long-term performance of certified organisations is assessed.

A longitudinal exploration of three organisations certified to ISO 9001 standard and three certified to IATF 16949 standard is done. The observations are further substantiated using secondary data for the same ten years period about customer satisfaction of the major automobile manufacturers.

It is observed that none of the two indicators, i.e. the customer satisfaction and number of non-conformities, in any of the six organisations show step-wise/stair-case type improvement. All indicators followed random up and down patterns like ocean waves. It is paradoxical that certified organisations are claiming continual improvement and are remaining certified but there is actually no long-term improvement.

Longitudinal studies for the generic quality management standard ISO 9001 and the quality system standard for automotive sector IATF 16949 are rare. The revelation about ocean wave patterns observed in the long-term trends for customer satisfaction and the number of non-conformities in ISO 9001 and IATF 16949 certified organisations is a startling finding. It is outlandishly different from the conventional perception of a staircase-styled continual improvement pattern expected a priori in certified organisations.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The current research aims to analyze the literature to determine its strengths and weaknesses and extract the required information, which will be used to identify the characteristics of the highly competitive organization (HCO), define it and identify the HCO's critical success factors (CSFs). Finally, the future research agenda will be proposed.

A multiple stages research methodology was used to fulfill the research objectives. The research started with the systematic literature review (SLR). Then, focus group discussions and Pareto analysis were used to fulfill research objectives.

Eleven points were identified in the research to represent the characteristics of the HCO. Then, the HCO was defined based on the elements of these points. Moreover, the vital few CSFs to successfully implement many research scopes were identified. Then, the CSFs of the HCO was generated based on these vital few CSFs.

The main limitation of the current research is the literature sample size. A larger sample selection could enrich the generated lists with many other CSFs.

Many implications points were highlighted in this research which showed the importance of the current research for academic and practical audiences.

The SLR process showed that the reviewed literature lacked a consolidated list of the HCO characteristics and a clear definition of the HCO. Moreover, the reviewed literature lacked a unified list of the HCO CSFs. Therefore, the current research approach is novel and original.