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In the present knowledge economy, intellectual capital (IC) is regarded as one of the significant determinants of efficiency, profitability, and ultimately value of a firm. This chapter empirically investigates the ramifications of the IC on the level of efficiency of the firm. In addition, exploration of the changing dynamics in the relationship between IC and firm level efficiency in the face of global economic crisis is of special interest of this chapter. In attaining the objectives of the study, a comprehensive database of 299 manufacturing firms (chosen randomly from a stratification of six BSE manufacturing industry subsectors) were utilized during the period from 1999–2000 to 2013–2014. Firm level efficiency scores and implications of IC (as measured by employing Pulic's Value Added Intellectual Capital Model) on the level of efficiency of the firms were examined simultaneously using Stochastic Frontier Analysis. Empirical results revealed that IC significantly determines the efficiency of the manufacturing firms during the period of study. However, the impact of financial crisis was not robust in changing the synergy between efficiency and IC. Size, age, and leverage were also found to be significant determinants of efficiency during the period of study.

Intellectual capital is the set of all intangible assets, that is, invisible, non-monetary assets held by a library, which can be identified as separate assets. Intellectual capital has become the buzzword of a knowledge-based economy and is the ultimate source of competitive advantage. In this work, we review the literature to analyse the effect of intellectual capital utilisation in the overall library management, to identify and classify intellectual capital and to provide some guidelines for researchers and practitioners. A literature review for the intellectual capital in libraries is conducted, and a qualitative analysis is undertaken, which interrelates library management to intellectual capital is taking place. The review leads to identification and classification of intellectual capital as well as to a number of quite innovative and interesting issues for the interrelation of intellectual capital to the management of libraries. The issues studied include intellectual capital economic valuation methods, the effect of the locality (spatial factor) to intellectual capital utilisation and the analysis of co-opetition (cooperation and competition) for intellectual capital utilisation. This is one of only a few studies about the management of intellectual capital in libraries and information services (LIS)—an innovative and challenging area of research in library management.

This study aims to verify the influence of stakeholders on Disruptive Innovation Disclosure (DID) by using company size as a control variable. DID is measured using the DID index. The authors use panel data regression with the period 2011–2020. Observations were made on 198 companies throughout the year in companies around the world. This study proves that shareholders, customers, suppliers, and company size are dimensions that affect DID. This situation shows that these dimensions have the power to control DID. The average company in the world has provided information about disruptive innovation. The scope of this research is limited to countries that have a visualization network of disruptive innovation collaboration in as many as 15 countries. The value of this study is to portray DID in countries that have disruptive innovation collaborative visualization networks.

Much like “Yeti,” the Abominable Snowman whose footprints are everywhere but itself nowhere to be seen, unfounded assertions of human capital as valuable contributors to strategic success continue to proliferate. Many of these treatments are nonbinding, nonmeasureable, idiosyncratic, tautological, and therefore nearly impossible to use for any comparative market valuation. In this chapter, we selectively review the interdisciplinary literature on exemplars of human-derived capital. We systematically examine specific epistemological strengths, weaknesses, and gaps in recognized theories, measures, and practices. In particular, a multidisciplinary, multilevel, connectionist point of view is suggested. We present the case for an evidence-based classification system of human-derived capital at the micro-, meso-, and macro-levels. Our framework goes beyond static stock models by emphasizing dynamic human-derived capital flows, as well as their within-level and cross-level linkages, all within the context of a modern society that increasingly is networked, fluent with technology, and prodigious with social media.

This chapter fills a significant gap in the intelligence literature and the knowledge sciences literature by aligning definitions and characterizations of knowledge capital as an essential intelligence source. The chapter also explains how knowledge capital might be leveraged in each of the four capabilities. The chapter presents a well-researched characterization of knowledge capital drawing from international scholars and practitioners’ work. The value of human capital, structural capital, and relational capital in intelligence work is explored.