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This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

The purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality, service quality, air quality, etc.

In this paper, a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus, obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.

The proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results, it is observed that the proposed model performs better than the existing models.

The management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.

The proposed method is an improved version of the adaptive time-variant FTS model. Further, a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.

The study examines the emancipatory potential of entrepreneurship for women in STEM who have experienced a mid-career break. As studies on this subject are rather scarce, it also makes an important contribution to the literature by providing key insights into the entrepreneurial journeys of women in STEM who have experienced a career break and have started their own enterprises. The findings could be used by governments to intervene in the identified areas of difficulty and to facilitate the entrepreneurial endeavours of women in order to bring this community back into the workforce.

The study maps the entrepreneurial journeys of 23 women with a STEM background who turned into entrepreneurs after experiencing a career break. Qualitative data was collected through personal interviews with women entrepreneurs and was then analysed to interpret the results.

While the study confirms the emancipatory potential of entrepreneurship among well-educated middle-class women with a STEM background who face constraints related to career advancement and work–life balance, it also provides insights on various aspects related to their entrepreneurial development. This includes aspects such as their motivation to start a business, major barriers they face in developing their businesses and the strategies they use to handle those barriers. Suggestions for policy development are also proposed.

In addition to studying the entrepreneurial aspect of a rather underexamined segment of women in STEM who have experienced a career break, the study also examines the scope of the emancipatory potential of entrepreneurship for this segment of women. To the best of our understanding, no such study on STEM women has been carried out in developing nations in spite of the fact that this segment of women forms an important techno-economic resource which remains largely underutilised in developing economies.

The issuance of sweat equity shares has recently created controversies. The limitations backing the conservatism of sweat equity shares issuance can be ascribed to confabulating recipient recognition process, uneasy tax treatment and procedural inconsistencies. This paper aims to study the theoretical and legal underpinnings, rightful recipients and the procedure for issuing sweat equity shares.

The authors choose the jurisdictions of India, the USA and Japan to study the problems plaguing issuance of sweat equity shares. The USA's prototypical reference and burgeoning technical soundness coupled with the sound venture capitalism of India and Japan has inspired the choice. The regulatory regime subsisting in the above jurisdictions governing sweat equity is studied comprehensively and comparatively. The structuring of sweat equity transactions and the tax treatment of sweat equity shares in the USA, India and Japan are discussed.

It is found that due to the absence of set standards and precedents the method for identifying the right recipients has trembled abysmally.

The paper focuses on the issues surrounding the practice of employees contributing to an organization being remunerated through shares.

The purpose of this paper is to present an approach to successful supplier selection process (SSP) by understanding the dynamics between SSP enablers (SSPEs), using interpretive structure modelling (ISM) methodology and find out driving and the dependence power of enablers, using fuzzy MICMAC (Matriced’ Impacts Croisés Appliquée á un Classement) analysis.

The group of experts from industries and the academics were consulted and ISM is used to develop the contextual relationship among various SSPEs for each dimension of supplier selection. The results of the ISM are used as an input to the fuzzy MICMAC analysis to identify the driving and the dependence power of SSPEs.

The research presents a hierarchy-based model and mutual relationships among SSPEs. The research shows that there is a group of SSPEs having a high driving power and low dependence, which requires maximum attention and is of strategic importance, while another group consists of those SSPEs that have high dependence and low driving power, which requires the resultant actions.

The weightage obtained for the ISM model development and fuzzy MICMAC are obtained through the judgment of academician and few industry experts. It is the only subjective judgment and any biasing by the person who is judging the SSPEs might influence the final result. A questionnaire survey can be conducted to catch the insight on these SSPEs from more organizations.

This category provides a useful tool for top management to differentiate between independent and dependent SSPEs and their mutual relationships which would help them to focus on those key SSPEs that are most significant for effective supplier selection.

Arrangement of SSPEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of supplier selection.