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This paper aims at providing a comparative analysis of the existing protocols that address the security issues in the Future Internet (FI) and also to introduce a Collaborative Mutual Identity Establishment (CMIE) scheme which adopts the elliptical curve cryptography (ECC), to address the issues, such as content integrity, mutual authentication, forward secrecy, auditability and resistance to attacks such as denial-of-service (DoS) and replay attack.

This paper provides a comparative analysis of the existing protocols that address the security issues in the FI and also provides a CMIE scheme, by adopting the ECC and digital signature verification mechanism, to address the issues, such as content integrity, mutual authentication, forward secrecy, auditability and resistance to attacks such as DoS and replay attack. The proposed scheme enables the establishment of secured interactions between devices and entities of the FI. Further, the algorithm is evaluated against Automated Validation of Internet Security Protocols and Application (AVISPA) tool to verify the security solutions that the CMIE scheme has claimed to address to have been effectively achieved in reality.

The algorithm is evaluated against AVISPA tool to verify the security solutions that the CMIE scheme has claimed to address and proved to have been effectively achieved in reality. The proposed scheme enables the establishment of secured interactions between devices and entities of the FI.

Considering the Internet of Things (IoT) scenario, another important aspect that is the device-to-location (D2L) aspect has not been considered in this protocol. Major focus of the protocol is centered around the device-to-device (D2D) and device-to-server (D2S) scenarios. Also, IoT basically works upon a confluence of hundreds for protocols that support the achievement of various factors in the IoT, for example Data Distribution Service, Message Queue Telemetry Transport, Extensible Messaging and Presence Protocol, Constrained Application Protocol (CoAP) and so on. Interoperability of the proposed CMIE algorithm with the existing protocols has to be considered to establish a complete model that fits the FI. Further, each request for mutual authentication requires a querying of the database and a computation at each of the participating entities side for verification which could take considerable amount of time. However, for applications that require firm authentication for maintaining and ensuring secure interactions between entities prior to access control and initiation of actual transfer of sensitive information, the negligible difference in computation time can be ignored for the greater benefit that comes with stronger security. Other factors such as quality of service (QoS) (i.e. flexibility of data delivery, resource usage and timing), key management and distribution also need to be considered. However, the user still has the responsibility to choose the required protocol that suits one’s application and serves the purpose.

The originality of the work lies in adopting the ECC and digital signature verification mechanism to develop a new scheme that ensures mutual authentication between participating entities in the FI based upon certain user information such as identities. ECC provides efficiency in terms of key size generated and security against main-in-middle attack. The proposed scheme provides secured interactions between devices/entities in the FI.

Data, either in primary or secondary form, represent the core strength of quantitative research. However, there is significant difference between collected data and the final researchable data. The data collection is driven by objectives of the research. The data also could be in various formats at different sources. The collected data in its original form may contain systematic and random errors. Such errors need to be cleaned from the data which is termed as data cleaning process.

The present chapter discusses about the different methodologies and steps that may be helpful for fine tuning the data into researchable format. The discussions are instantiated with the applications of methodologies on a set of financial data of companies listed in Bombay Stock Exchange. Various steps involved in transformation of collected data to researchable data are presented. A schematic model including data collection, data cleaning, working with variables, outlier treatment, testing the assumption of statistical test, normality, and heteroscedasticity is presented for the benefit of research scholars. Beyond this generic model, this paper focuses exclusively on financial data of listed companies in the Bombay Stock Exchange. The challenges involved in various sources, data gathering and other pre-analysis stages are also considered. This is also applicable for research based on secondary data sources in other fields as well.

This paper aims to study the productivity growth in the Indian apparel industry in aggregate over the period 1995–2015 and compare the performance of the Indian apparel industry during the decade of the Agreement on Textiles and Clothing (ATC) and the decade post its expiry.

The aggregate productivity performance has been studied using the technique of growth accounting and the translog index. A comparison of industry performance has also been made by analysing data. The data has been collated from Annual Survey of Industries reports, CMIE Economic Outlook and CMIE Industry Outlook databases.

The apparel industry has seen significant growth in terms of all industry variables and exports. However, the growth in exports is much lower than the growth in other industry variables related to output and input. While there is productivity improvement in aggregate over the study period, the quantum is low. Total factor productivity growth is positive and higher for the period post the ATC.

To the best of the author’s knowledge, there has been no such recent study comparing performance and productivity in Indian apparel manufacturing during and after the expiry of the ATC.

The case was developed from secondary sources and interviews with a security analyst. The secondary sources include company annual reports, news reports, analyst reports, industry reports, company websites, stock exchange websites and databases such as Bloomberg and CMIE Prowess.

Increasing competition in product and capital markets has put tremendous pressure on managers to become more cost competitive. To address their firms' uncompetitive cost structures, managers may have to consider dramatic restructuring of their businesses. During 2014–2017, Tata Steel Ltd (TSL) UK considered a series of divestitures and a merger plan to nurse the company back to health. The case considers the economics of the restructuring plan. The case is designed to help students analyze a corporate downsizing program undertaken by a large Indian company in the UK and to highlight the dynamic role of the CFO and governance issues in family firms. It introduces students to issues surrounding a typical restructuring and provides students a platform to practice the estimation of value creation in a restructuring exercise. While some cases on corporate restructuring in the context of developed economies are available, there are very few cases written in an emerging market context. This case bridges that gap. TSL presents a unique opportunity to study corporate restructuring necessitated by a failed cross-border acquisition. It illustrates the potential for value loss in large, cross-border acquisitions. It shows how managerial hubris can prompt family firm owners to overbid in acquisitions and create legacy hot spots. In addition, the case can be used to discuss the causes of governance failures such as weak institutional monitoring and poor legal enforcement in emerging markets that could potentially harm minority shareholders.

The case was developed from secondary sources and interviews with a security analyst. The secondary sources include company annual reports, news reports, analyst reports, industry reports, company websites, stock exchange websites and databases such as Bloomberg and CMIE Prowess.

The purpose of this paper is to analyze the status of gross and net working capital and their association with sales of Andhra Pradesh Paper Mills Ltd, with reference to the Indian paper industry over a decade, from 1999 to 2008.

The research is mainly based on secondary financial data obtained from the Centre for Monitoring Indian Economy (CMIE). It focused on the size, character, and annual growth rates of gross and net working capital of the company. In addition, it analyzed the growth trends of gross and net working capital of the company in relation to sales. With the help of the Karl Pearson's correlation model, the inter‐relationship between sales and working capital has been identified. Then the strength and significance of such a relationship has been tested with the use of other statistical tools such as coefficient of determination and Student's t‐test.

The major findings of the research showed that while there was an increase in sales positively, strongly, and significantly associated with an increase in gross working capital for both the company and the industry, its association with net working capital was negative, poorly related, weak, and insignificant for the company under study.

There is a dearth of studies in the world literature that discuss the relationship that exists between sales and working capital in India's paper industry, in general and Andhra Pradesh Paper Mills Ltd in particular, and therefore this research is expected to add significant value to exploring the said linkage.

The purpose of this study is to introduce working capital efficiency multiplier (WCEM) as a direct profitability measure of working capital management. The existing accounting measures in the literature establish an indirect approach to study the relationship between working capital efficiency and profitability of the firms.

Using the help of a set of companies from CMIE Prowess database, the study introduces WCEM as a direct profitability measure of working capital efficiency.

In this study, a new direct measure of working capital efficiency is introduced which is multiplicative in nature. WCEM is a product of three components, namely, WACC, ratio of the sum of trade receivables and inventories to trade payables and ratio of net working capital (NWC) to net sales.

The importance of direct measure like WCEM could be enormous in performance evaluation of a firm. It can be used as an indicator for choosing a suitable investment opportunity by an investor. This is due to the fact that the firm that is highly efficient in managing working capital is less exposed to liquidity risk. At the same time, the firm is less dependent on external financing. Therefore, such firms eventually create more value for their shareholders. Another indication that WCEM provides is to gauge the bargaining power of the firm and its competitive position in the market. Lower WCEM indicates higher bargaining power of a firm across the value chain, and its superior position relative to its competitors.

Most of the studies on WCM are of the empirical type and there is a complete dearth on theoretical framework. Researchers hereafter can consider WCEM as one of the financial performance variables in place of the existing measures such as return on asset (ROA), return on invested capital (ROIC), return on equity (ROE), gross operating income (GOI) and net operating income (NOI) and thereby can contribute new empirical insights through their research outcomes.

There is a rich literature which states that India did not suffer much from the impacts of the US financial crisis, but there is a school of thought which believes that the idea of India being insulated or decoupled from the contagion on account of limited integration into the world economy has been proved to be wrong. What is interesting is the focus has always been on the services sector and not on the manufacturing sector in India. In this background, this chapter tries to understand whether manufacturing sectors' productivity growth was one of the reasons that the crisis worsened in India or was it because of the crisis that India's manufacturing sector went into a deep recession. To look into the causality issue, the author estimates the productivity loss index (PLI) for the Indian industries during the period between July 2007 and July 2010 by estimating the fall in growth percentages in consecutive months for a total of 9,000 manufacturing, mining, and electricity industries. The data at monthly level have been retrieved from the Centre for Monitoring Indian Economy (CMIE) Prowess database. Based on the causality results, the chapter shows that it was because of the subprime crisis that India's manufacturing sector went into a deep recession. Using a probit model, the chapter also estimates the probability of the US subprime crisis being responsible for the productivity loss in India's manufacturing sector during the above-mentioned period.

This chapter measures total factor productivity growth (TFPG) using Malmquist productivity index (MPI) and the growth of MPI of Indian Textile Industry employing nonparametric data envelopment analysis (DEA), during 1995–2016, exploring company (firm) level Center for Monitoring of Indian Economy (CMIE) Prowess data; examines whether TFPG has improved after the withdrawal of multifiber trade agreement (MFA) since 2005; decomposes TFPG into technical change (TC), technical efficiency change (TEC), and scale efficiency change (SEC); and explains the factors behind the movement of TFPG, considering the effect of R&D (RD), exports (EX), marketing expenditures (MKTs) advertisement expenditures (ADVs), imports (IMP), using second-stage panel regression. Empirical evidence supports fluctuating pattern of TFPG during 1995–2016, with a marginal declining tendency. TFPG has increased in 1999–2000, 2000–01, 2009–10, and 2012–13. After dismantling MFA, MPI level has significantly declined, with an increase in its growth rate, but the increase is not statistically significant. The effect of EX, RD, ADV are nonlinear, U-shaped, and IMP and MKT are inverted U-shaped, implying that the sign effect of any variable depends on its size. There are joint interaction effects of (a) RD and EX; RD and MKT which are positive, (b) ADV and MKT as represented by the ratio (ADV/MKT), having nonlinear inverted U-shaped relation. The joint interaction effect supports that the impact of one variable depends on the magnitude of other. The marginal effect of EX, IMP, and ADV are positive; increase in these variables promotes TFPG. The greater role of ADV over MKT is evident. The marginal effect of RD is negative; the average level of RD is too low to generate positive effects, and, thus, there is an urgency of increasing RD. The promising part of the decomposition analysis is that highest contribution to growth rate of TFPG is the growth rate of TEC followed by growth rate of TC, and thus by increasing TEC and TC, higher growth rate of TFPG is achieved and may be beneficial in the long run and may lead to absorption of economic shocks for an economy facing recession in its output growth. Some policy suggestions are made for boosting up TFPG.

This study investigates the supply chain efficiency of selected companies in the Indian food processing sector. Additionally, it explores the relationship between supply chain efficiency and firm performance.

To determine the supply chain efficiency, the study uses supply chain efficiency measures, such as supply chain length, inefficiency ratio and working capital productivity. Secondary data were collected from the Center for Monitoring Indian Economy (CMIE) Prowess database for the years 2011–2017. Various return measures, such as Return on Net Worth (RONW), Return on Total Assets (ROTA) and Return on Capital Employed (ROCE), were used to measure firm performance. Collected data were analyzed to investigate the relationship between supply chain efficiency and firm performance.

Findings of the study reveal the prevalence of inefficient supply chains in the context of the selected companies. There is a significant negative correlation between supply chain efficiency and firm performance. RONW has a significant negative correlation with the length of supply chain as well as supply chain inefficiency.

This study expands the limited existing research perspective; the study helps to understand the supply chain efficiency and firm performance.

This is an original piece of work and provides valuable insight into the relationship between supply chain efficiency and firm performance.

The purpose of this paper is to understand the impact of components of marketing expenditures, i.e. advertising and distribution expenditures on intangible value of firm (measured in terms of Tobin's Q). The relationship is studied in the context of branding approaches (corporate and house of brands) that various firms follow.

The data are collected from databases of Centre for Monitoring Indian Economy (CMIE) and from the web site of National Stock Exchange. Time series regression is performed using SPSS software to test the model.

Advertising expenditure has a positive impact on the intangible value of the firm and this relationship is stronger for firms following corporate branding than for firms that follow house of brands strategy. Distribution expenditure has negative impact on the intangible value of the firm and this relationship is stronger for firms following corporate branding than for firms that follow house of brands strategy.

Since most of the data retrieved for the analysis were of B2B (business to business) firms, the findings may not be generalized for all firms.

Advertising expenditure has a diminishing marginal utility in creating intangible value. It would be useful for firms to understand where they are on this continuum and whether their advertising expenditure is giving adequate returns or may be better spent elsewhere.

In the literature, researchers have expressed mixed viewpoints regarding the impact of total marketing spend on intangible value. The marketing expenditures are found to have both positive and negative impact on intangible value, with respect to various contexts. However, the impact of major components of marketing expenditures is not addressed. This gap is addressed in this research paper.