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This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

“NTL suffered huge losses in its foreign exchange hedging activities as its highly complex leveraged structured products backfired badly in the wake of the Global Financial Crisis of 2007 and 2008. The CFO and the Treasury head have both been sacked, and Joshi, the new CFO, has embraced aggressive litigation as NTL's survival strategy to cope with the losses that threaten its solvency. In the meantime, NTL also faces tax investigations and whistleblower allegations of fraud, and it finds that the record-keeping of its derivative transactions was hopelessly incomplete and patchy. A complete reconstruction of the entire derivative transaction history is the only way to rebuild trust, and that task falls on Reddy, a seasoned derivatives expert brought in by the Board specifically for this purpose.

In this dire situation, Seth, the founder Chairman of NTL decides that NTL needs to put all this behind it and focus on rebuilding the business. The challenge for Seth, Joshi and Reddy is to go about doing this in an environment that offers very few rays of hope.”

This paper aims to review, discuss and synthesize the literature focusing on the Indian initial public offering (IPO) market. Understanding the Indian IPO market can help answer broader corporate finance questions. The growing number of IPOs in the Indian context, coupled with the increasing importance of the Indian economy in the global market, makes this review an essential topic.

The systematic literature review methodology was adopted to review 111 papers published between 2002 and 2021. The authors used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach during the review process. Additionally, the authors use a bibliometric review methodology to examine the pattern and trend of research in this area of interest. Furthermore, the authors conduct a critical review and synthesis of the top 20 papers based on citations. The authors also use a co-citation network and manual content analysis method to identify key research themes.

This review helps in identifying major themes of research in this area of interest. The authors find that majority of the research has focused on IPO performance whereas post-IPO performance needs critical attention as well. The authors develop a comprehensive framework and future research agenda based on their discussion.

Meta-analysis of the literature can be conducted to gain better insights into the findings of prior studies.

This review paper develops a comprehensive overview on Indian IPO market which can be of interest not only to Indian scholarship. India as an economy is increasingly gaining attention at the global level. Hence, the future research objectives as illustrated in the study can be of interest for the global scholarship also.

To the best of the authors’ knowledge, this is the first comprehensive review paper that examines, synthesizes and outlines the future research agenda on Indian IPO studies. This review can be useful for researchers, business policymakers, finance professionals and anyone else interested in the Indian IPO market.

The concept of developing clothing sizes has taken importance in recent years due to increasing expectations of consumers for branded clothing and its value in terms of fit and durability. The kids’ ready-to-wear brands are expected to pose the least fit issues, thereby covering a wider population of a particular size. This necessitates the standardization of measurements. The lack of standardized approaches has caused fit issues like mismatching of sizes and alterations, in a heterogenous consumer market, like India. The performance of branded apparel depends on the quality of the measurements considered in developing sizes and the approach for standardization. There is a lacuna in the measurements used by the kids’ apparel domestic brands. This study aims to propose an anthropometric approach for deriving quality measurements that can be used effectively in developing kids’ sizes to fit a wider population of kids, thereby reducing the need for alterations.

The measurement data was gathered through the quantitative method. An anthropometric survey was conducted by measuring school kids. A total of 544 kids (girls and boys) of age group 6–8 years were measured to obtain prime anthropometric measurements required for ready-to-wear apparel production. WHO manual and ISO 8559, 1998 meant for anthropometry survey for garment industry was referred for accurate measuring following the landmarks for measuring.

The findings revealed differences in the anthropometric measurements based on gender and age. The anthropometric measurements showed variations within the same body mass index (BMI) range. S, M and L sizes were identified within an age group. The apparel manufacturers and designers need to focus on the discrepancies occurring in the body measurements of an age group to address and control fit issues in kids ready to wear apparel.

The anthropometric approach can be significantly used to control undesired fit and comfort issues in kids’ ready-to-wear apparel.

This study helped to understand the importance of scientific measuring practices to arrive at standardized measurements to develop sizes in ready-to-wear apparel manufacturing.

Drawing on expectancy violation theory, this study aims to assess the impact of corporate environmental irresponsibility (CEI) on workplace deviant behaviors (WDB) of Generation Z and Millennials through the mediation of moral outrage.

The data were collected from 328 nonmanagerial employees working in the refinery, petroleum and power distribution companies who have been convicted for committing environmental irresponsibility by a court of law. Multigroup analysis (MGA) was used to estimate the hypothesized relationships.

Results revealed that CEI affects WDBs positively. Moreover, the MGA results demonstrated that the deviant behavior of Generation Z in response to environmental irresponsibility is higher than of the Millennials.

Theoretically, the findings implicate that harming the environment will cost organizational performance through deviant behaviors.

This study provides a new lens for the executive management that eliminating social irresponsibility is more important than incurring sustainability initiatives, especially from the new generation’s perspective.

The originality of this study is that it confirmed the impact of CEI on employees’ deviant behaviors; and extended the scope of expectancy violation theory to the field of human resources.

In this study, an attempt has been made to collect the research that has been done on the construction and design of the H₂O₂ sensor. So far, many efforts have been made to quickly and sensitively determine H₂O₂ concentration based on different analytical principles. In this study, the importance of H₂O₂, its applications in various industries, especially the food industry, and the importance of measuring it with different techniques, especially portable sensors and on-site analysis, have been investigated and studied.

Hydrogen peroxide (H₂O₂) is a very simple molecule in nature, but due to its strong oxidizing and reducing properties, it has been widely used in the pharmaceutical, medical, environmental, mining, textile, paper, food production and chemical industries. Sensitive, rapid and continuous detection of H₂O₂ is of great importance in many systems for product quality control, health care, medical diagnostics, food safety and environmental protection.

Various methods have been developed and applied for the analysis of H₂O₂, such as fluorescence, colorimetry and electrochemistry, among them, the electrochemical technique due to its advantages in simple instrumentation, easy miniaturization, sensitivity and selectivity.

Monitoring the H₂O₂ concentration level is of practical importance for academic and industrial purposes. Edible oils are prone to oxidation during processing and storage, which may adversely affect oil quality and human health. Determination of peroxide value (PV) of edible oils is essential because PV is one of the most common quality parameters for monitoring lipid oxidation and oil quality control. The development of cheap, simple, fast, sensitive and selective H₂O₂ sensors is essential.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.