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Sociologists have long thought of the integration of people in communities – social integration – and hierarchical social systems – systemic integration – as contradictory goals. What strategies allow organizations to reconcile social and systemic integration? We examine this question through 40 in-depth, longitudinal interviews with leaders of nonprofit organizations that engage in the dual pursuit of social and systemic integration. Two processes reveal how the internal structure of organizations often mirrors the ways in which organizations are embedded in their local environments. When organizations engage in loose demographic coupling, relegating those who “match” the community to the work of social integration, they produce internal inequalities and justify them by claiming community building as sacred work. When engaging in community anchoring, organizations challenge internal and external inequalities simultaneously, but this process comes with costs. Our findings contribute to a constructivist understanding of community, the mechanisms by which organizations produce inequalities, and a place-based conception of organizations as embedded in community.

The impact of artificial intelligence (AI) and extended reality (XR, including virtual reality [VR], augmented reality [AR], and mixed reality [MR]) on marketing in Industry 5.0 and Society 5.0 is explored with systematic literature review in this chapter. AIXR is becoming a necessary aspect of marketing, driven by efficiency, productivity, and innovation. Despite AI's capabilities, the human touch in marketing is preferred due to superior adaptive, creative, and innovative abilities. The use of fully automated marketing systems is limited to specific tasks. This research will benefit both practitioners and academics focusing on AIXR in marketing and is limited by the number of included literature.

Stockbrokers’ frauds in India frequently occur, causing investors significant financial loss. This study aims to unfold the various dubious practices adopted by stock brokers in the recent past to defraud investors and the necessary corrective regulations passed by the market regulator to prevent and detect fraud.

The authors conduct exploratory research using a collective model of literature review, case studies and regulatory changes.

The authors find tightening the system’s loopholes and strengthening the regulatory system using technology helps in the early detection and prevention of fraud. Media activism and investors’ awareness play a role in reducing incidences of fraud.

This study unfolds the practices followed by stock brokers to defraud investors, indicative of regulatory gaps and enforcement lapses. Regulators are evolving a robust system to curb these practices and make them on par with international standards. But, it has a long way to go.

Robust fraud detection and prevention mechanism is desirable to restore investors’ confidence in the stock market. Regulators should focus on investors’ protection and education and whistleblowers’ protection. Compared to the market regulators worldwide, the Securities and Exchange Board of India has less power to identify, detect and punish fraudulent brokers and needs to be empowered.

Besides the regulatory changes, strict enforcement and investor campaigns are required to increase public awareness and restore trust in the stock market to combat the recurrence of fraud.

This paper can be helpful to regulators, investors and financial intermediaries like stock brokers and aid in strengthening the reliability of capital markets and restoring investors’ confidence.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

The purpose of this study is to investigate the behaviour of M40 grade of self-compacting concrete (SCC) with high volume of ground granulated blast furnace slag (GGBS) (50%) and recycled concrete aggregate (RCA) content up to 100% to assess the mechanical properties of SCC. As per guidelines of IS: 383 – 2016, the RCA can be replaced up to 20% of natural coarse aggregate up to M25 grade of concrete. This study assesses the mechanical properties of SCC beyond 20% of RCA content. Based on the experimental investigations, the compressive strength of mixes decreases as the content of RCA increases. It is found that concrete mixes with 20% RCA and shows the maximum compressive strength at 56 days.

The fresh properties as per EFNARC and IS: 10262–2019 guidelines, ultrasonic pulse velocity testing, mechanical properties and microstructure analysis have been conducted to evaluate the performance of SCC with RCA for practical applications.

From the experimental investigations, it is found that up to 50% of recycled coarse aggregate can be used for structural applications.

The environmental pollution and dumping of waste on green land can be reduced by effective utilization of recycled coarse aggregate and GGBS in the production of SCC.

The purpose of this paper is to clarify the relationship between the use of different polymer matrices for the preparation of composite materials, namely, polyethylene terephthalate-glycol (PET-G) and polyamide (PA), using Composite Fiber Co-Extrusion technology with the application of two types of carbon fibers, short and continuous. The aim of the study is also to extend the knowledge of the production of composite materials with a defined structure from the point of view of their influence on the microstructure and their physical-mechanical properties.

As part of the experiment, four types of samples were prepared, namely, two types of samples with PA polymer matrix and two types with PET-G polymer matrix. All types contained short carbon fibers and always one set from each polymer matrix in addition to continuous carbon fibers. All types were prepared using the same 3D printing parameters to avoid any further influence. The samples were then tested for microstructure using microCT, mechanical properties using a tensile test and dilatation characteristics from the point of view of aerospace applications. Finally, the raw materials themselves were tested.

The paper provides insight into the influence of polymer matrix types on the physico-mechanical properties of 3D printed composites. The analysis confirmed that the physico-mechanical results varied with respect to the interface between the polymer matrix and the carbon fiber. The implications of the conclusions can be extended to the development of products in the aerospace and automotive sectors.

This study provides information for composite applications in the aerospace industry, focusing on evaluating dilatation characteristics within very low temperatures (−60 °C) when using carbon fibers (continuous carbon fibers, short carbon fibers and a combination of both) in two types of thermoplastic matrices. This perspective on materials characterisation for aerospace applications is a very important and unpublished approach within the 3D printing of composites. These characteristics are important parameters in the design of prototypes and functional samples with regard to the resulting behaviour in real conditions.

This paper aims to explore how graphene can improve the mechanical and anti-corrosion properties of TiO₂-SiO₂ sol-gel coating. This sol-gel coating has been prepared on aluminum alloy substrate using graphene as both nano-filler and corrosion inhibitor.

To examine the effect of graphene on mechanical properties of sol-gel coating, the abrasion resistance, adhesion strength and scratch resistance of coating have been evaluated. To reveal the effect of graphene on the anti-corrosion property of coating for aluminum alloy, the electrochemical impedance spectroscopy (EIS) has been conducted in 3.5 Wt.% NaCl medium.

Scanning electron microscopy images indicate that graphene nanoplatelets (GNPs) have been homogeneously dispersed into the sol-gel coating matrices (at the contents from 0.1 to 0.5 Wt.%). Mechanical tests of coatings indicate that the graphene content of 0.5 Wt.% provides highest values of adhesion strength (1.48 MPa), scratch resistance (850 N) and abrasion strength (812 L./mil.) for the sol-gel coating. The EIS data show that the higher content of GNPs improve both R₁ (coating) and R₂ (coating/Al interface) resistances. In addition to enhancing the coating barrier performance (graphene acts as nanofiller/nano-reinforcer for coating matrix), other mechanism can be at work to account for the role of the graphene inhibitor in improving the anticorrosive performance at the coating/Al interface.

Application of graphene-based sol-gel coating for protection of aluminum and its alloy is very promising.