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The purpose of this study is to identify the critical success factors (CSFs) of corporate social responsibility (CSR) in the post-COVID-19 period and to identify the cause–effect relationships amongst those CSFs.

The success factors impacting CSR activities are identified based on inputs from 14 experts in the CSR domain. Thereafter, authors use a statistical approach to identify CSFs with inputs from useable respondents. Finally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to understand the causal relationship between different CSFs.

Using the DEMATEL method, the authors developed an analytical model showing cause–effect aspects of the CSFs and identified seven factors which firms need to emphasize more to execute better CSR activities in the post-COVID-19 period.

The authors asked 14 experts for their inputs, but more experts could have made identifying success factors more comprehensive. In this study, the DEMATEL method found seven CSFs that improve CSR activities in the post-COVID-19 period. Another identification process could have enriched the study. The findings of this study cannot be generalized since this study is based on the inputs of employees from India only.

This proposed analytical model is effective in determining the complex interactions among all impacting CSFs. Firms' CSR managers and policy makers can use the proposed model, especially in the post-COVID-19 period.

The proposed model provides a precise and most accurate analysis for CSFs impacting CSR activities in the post-COVID-19 period. It also provides a unique opportunity for the competent authorities at firms to understand the interaction of different impacting CSFs and takes necessary actions. No other exhaustive analytical model is available in this context.

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

Approximately, 800m tons of e-waste is generated per year in India. Reverse supply chain (RSC) is the probable strategy to cope up with the issue. Setting up a RSC process is not popular in the Indian sector. There are several factors that basically control the profitability of such kind of business. Hence, the purpose of this paper is to develop a causal model among the identified issues and sub-issues for setting up a RSC in an Indian semiconductor manufacturing industry and then evaluate the critical issues based on the causal relations.

Decision-making trial and evaluation laboratory (DEMATEL) method along fuzzy set theory is used to develop the causal framework among the identified strategical and tactical issues. According to the causal relations from DEMATEL, analytical network process is then used to identify the weights of the sub-issues.

The cause–effect interactions among the main issues show that legislations and regulations, market-related issues and organizational issue are the most significant strategic issues. Uncertainty in the acquisition time is the most significant tactical issue because it has a crucial impact on the quality and quantity of the used products. Based on the obtained causal relations of the main issues, it is identified that the reduction of waste, creation of new opportunity, market competition, cost reduction, change in technology and location, capacity and number of recovery facility are the major sub-issues in RSC implementation.

This study is conducted on the basis of the experts’ opinion from a semiconductor manufacturing industry, situated in the southern part of India. Therefore, this proves its practical implications.

The paper provides the detail illustration of the issues in the RSC process, and the prioritization of the issues based on the cause–effect relationships also provides some meaningful managerial insights.

Notes that quality improvement and management practices involve using tools, which are formulated from industrial practices and quality engineering theory. Points out that the seven old Japanese tools are claimed to be able to solve up to 95 per cent of quality‐related problems and that the seven new Japanese tools are claimed to have started a new era for quality. However, comments that these tools have not been discussed systematically in the context of software sector. Proposes a software process improvement framework, which incorporates the SEI capability maturity model as a self‐assessment tool, and maps these 14 tools to the framework in order to help establish the total quality management culture in software quality practices.

Sustainable waste management (SWM) leads to human safety by eliminating dangerous substances, increasing cost efficiency and reducing environmental impacts. Integrating social, economic and environmental factors is the standard for successfully implementing SWM. However, prior studies have not incorporated the triple bottom line with technological performance and occupational safety in establishing SWM. To drive sustainability in waste management, this study aims to provide a set of SWM attributes and identify a causality model based on the interrelationships among the attributes.

This study used the Delphi method to list the relevant attributes and the decision-making trial and evaluation laboratory (DEMATEL) involving 18 experts from the medical and health-care industry to present the interrelationships indicating the group of cause–effect attributes of SWM.

The study selected 5 aspects and 20 criteria as the relevant attributes of SWM. The cause group consists of environmental impacts and occupational safety, with positive values of 27.031 and 24.499, respectively. The effect group includes technological performance, economic performance and social performance. In particular, the challenges and practices of technological performance are linked to environmental impacts and occupational safety.

The top four criteria for industrial improvement are green practices, government policy and rules, the awareness of workers and waste separation and collection. These results present deeper insights into theoretical and managerial implications.

This study contributes to addressing the challenges and practices of SWM in technological performance leading to environmental impacts and occupational safety. Studies on the technological performance aspect in the causality relationships between environmental impacts and occupational safety are lacking. This study describes SWM using qualitative information and quantitative data.

Some manufacturing and service organizations have made efforts to work on continuous improvement in the form of Kaizen, lean thinking, Six Sigma, etc. The elimination of problems and waste (MUDA for the Japanese) plays a fundamental role in the reduction of operational costs and quality rejections of finished products both internally in the organization and in the supply chain. Some of these efforts use quality control tools to remedy it. Kaoru Ishikawa proposes seven basic quality tools. In this group of quality tools is the cause-and-effect diagram (CED), also known as “The Fishbone” and “Ishikawa diagram”. Exploring this questioning can shed light on the first indications to ratify the arguments of Ishikawa and Deming, that the main problems of companies are found in their processes and perhaps, in a deep way, in some of these cornerstone root causes that have to do with the way organizations are managed. The purpose of this study is to investigate cornerstone root causes through the application of CEDs in 40 Mexican companies that began an effort to improve some of their organizational processes.

An exploratory qualitative study was conducted. As a research strategy, the case study method was applied. Using theoretical sampling, the Ishikawa diagrams of 40 companies were analyzed, and 24 semi-structured interviews in depth were conducted.

The results of this research confirm the main research question: Are there cornerstone root causes that give way to one or several problems or effects of problems in organizations regardless of their sector? In other words, there were at least seven typical patterns that show the first signs of cornerstones root causes in organizations.

The method itself is a limitation; 40 case studies are not enough to generalize the results. In addition, the research was conducted only in a single Latin American country; in some cities of Mexico. However, 60 per cent of these companies are multinationals.

This paper is fundamental to delve into the cornerstones causes that give rise to the problems of organizations of the twenty-first century. The authors understand that these are the first indications, and that they cannot be considered a conclusion of these causes. However, this first theoretical sampling presents a first light on the subject.

The study contributes to the limited existing literature on total quality management and Kaizen in quality control tools and subsequently disseminates this information to provide impetus, guidance and support toward improving the problems of the organizations of twenty-first century.

Six sigma is a structured methodology that uses mathematical and statistical tools to increase productivity and business efficiency. In order to apply it, it is necessary to have a very broad knowledge in the fields of mathematics, management, and sector to which the process or the product under consideration (mechanical, electronic, chemical, etc.) refers. It is based on guidelines with a rigid and formalized approach to deal with misunderstandings and minimize subjectivity as much as possible.

This chapter will provide the basic information regarding the birth of the methodology and the composition of the work team; moreover, the procedure define, measure, analyze, improve, and control (DMAIC) will be presented and some tools will be described in order to obtain the improvements desired for the product or the process.