Intellectual Capital Risk Management for Knowledge-Based Organizations

2016 ◽  
pp. 257-282
Author(s):  
Jolanta Jurczak
Keyword(s):  
Risk Management ◽  
Intellectual Capital ◽  
Knowledge Based

scholarly journals ENTERPRISE RISK MANAGEMENT DAN INTELLECTUAL CAPITAL DISCLOSURE : PERSPEKTIF INVESTOR

2018 ◽  
Vol 8 (2) ◽  
pp. 187 ◽  
Author(s):  
Yolanda Yolanda ◽  
Ihyaul Ulum ◽  
Setu Setyawan
Keyword(s):  
Risk Management ◽  
Intellectual Capital ◽  
Firm Value ◽  
Sampling Technique ◽  
Enterprise Risk Management ◽  
Partial Least Square ◽  
Least Square ◽  
Corporate Value ◽  
Coding System ◽  
Enterprise Risk

This paper aims to examine the effect of corporate value on investor reactions with enterprise risk management (ERM) and intellectual capital disclosure (ICD) as a mediation variable on Indonesian companies listed in the Jakarta Islamic Index in 2016. The sample of this study consists of 25 companies with purposive sampling technique. Five ways numerical coding system and Partial Least Square (PLS) are used as a tool to perform data analysis. The results show that firm value has a significant influence on investor reaction. Unlike the ERM capable of mediating the relationship between corporate value and investor reactions, ICD is unable to mediate.

scholarly journals Transition to the Knowledge-Based Economy within the Modernization Paradigm for the States in the Core and Semi-Periphery of the Global Economic System

2021 ◽  
Vol 3 (49) ◽  
pp. 117-123
Author(s):  
O. A. Dovgal ◽  
◽  
G. V. Dovhal ◽  
H. V. Serdiuk ◽  
◽  
...  
Keyword(s):  
Economic System ◽  
Intellectual Capital ◽  
Main Function ◽  
Economic Resource ◽  
The Core ◽  
Knowledge Based ◽  
Catching Up ◽  
Knowledge Based Economy ◽  
Innovative Model ◽  
Intellectual Production

Abstract: The article generalizes the features of modern transition from industrial to post-industrial (or knowledge-based) economy within the modernization paradigm for the states in the core and semi-periphery of the global economic system. It is proved that among the historical diversity of national modernization phenomena one can single out two alternative models: an innovative model and a catching-up one. It is substantiated that the innovative model is most typical for the countries forming the core of the world economic system, while the catching-up model is more typical for countries in the periphery of global development. It is revealed that modern intellectual production covers, first of all, economic sectors producing information and knowledge. At the same time, intellectual capital also functions in productive industries, influencing their indicators as well. That is why knowledge workers, who form the intellectual strata of society, are considered to be subjects of intangible intellectual production, the latter making up the core of knowledge economy. Their main function is to produce intellectual products (socially valuable knowledge), in contrast to groups, whose social function is to embody these values and knowledge. It should also be noted that concrete historical forms of knowledge objectivisation, ways of their reproduction and, accordingly, historical types of intellectual layers can differ considerably. It is concluded that knowledge-based economy is considered as a sphere of economic activity, which nowadays is characterized by intensive use of intellectual capital as the main economic resource, in the fields of material production as well.

Intellectual capital and firm performance in emerging economies: the case of India

2016 ◽  
Vol 26 (3) ◽  
pp. 410-430 ◽  
Author(s):  
Santi Gopal Maji ◽  
Mitra Goswami
Keyword(s):  
Firm Performance ◽  
Intellectual Capital ◽  
Value Added ◽  
Relative Importance ◽  
Content Type ◽  
Knowledge Based ◽  
Traditional Sector ◽  
Steel Sector ◽  
Capital Efficiency ◽  
The Impact

Purpose The purpose of this paper is to examine the impact of intellectual capital (IC) on Indian traditional sector and compare the relative importance of IC on corporate performance of Indian knowledge-based sector (engineering sector) and traditional sector (steel sector). Design/methodology/approach Secondary data on 100 listed Indian firms, comprising of 44 firms from the engineering sector and 56 from the steel sector, are collected from “Capitaline Plus” Corporate database for a period of 14 years from 1999-2000 to 2012-2013. IC and its components are computed using Pulic’s value-added intellectual coefficient model and firm performance is measured by return on asset. Fixed effect regression model is used to investigate the hypothetical relationship between IC and firm performance. Further, quantile regression is used to check the robustness of the results. Findings The results indicate that IC efficiency and physical capital efficiency are positively and significantly associated with the firm performance for both the sectors. Regarding the components of IC, the coefficient of human capital efficiency is positive and significant, but the present effort fails to disentangle any significant influence of structural capital efficiency on firm performance. However, the results indicate that the influence of IC efficiency on firm performance is significantly greater in case of knowledge-based sector than that of traditional sector. Practical implications The findings of the study are useful for the decision makers, as the results indicate that the IC plays crucial role in value creation not only for knowledge-based firms but also for the firms belonging to the traditional manufacturing sector. Originality/value In the Indian context, this is the first study to examine the relative importance of IC in a knowledge-based sector and a traditional sector using appropriate methodology.

scholarly journals Measurement of Intellectual Capital as Exemplified by Methods of Groups Based on the Roa Indicator and on Market Capitalization

e-Finanse ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. 58-71
Author(s):  
Karolina Palimąka ◽  
Mateusz Mierzejewskl
Keyword(s):  
Intellectual Capital ◽  
Food Industry ◽  
Intangible Assets ◽  
Financial Statements ◽  
Point Of View ◽  
Market Capitalization ◽  
Knowledge Based ◽  
Theoretical Approaches ◽  
Knowledge Based Economy ◽  
Business Analysis

Abstract The concept of a knowledge-based economy is a relatively new topic, but it does not mean that the previous economies did not use knowledge. For many years, knowledge formed the basis of any economy, it was a factor that set the pace of each of them, but just nit is making a significant impact on the entrepreneurial environment, and more. Inherent KBE is the concept of intellectual capital. The article raises both theoretical approaches towards the concept of intellectual capital, and points to the importance (from the point of view of managing this intangible value in the company) -of measuring intellectual capital. The process of good management of the value of intangible assets must be supported by knowledge about, e. g.,its size, value, etc. The authors focus on presenting methods of measuring intellectual capital from two groups of methods by the classification made by K. E. Sveiby, who is considered one of the fathers of the IC concept. The goal of the article is to compare methods from these two groups in terms of their flaws and advantages as regards preparing business analysis. This is done through presentation of the topic, including the concept and methods of intellectual capital measurement, which was based on the review of the literature.Furthermore, based on financial statements of companies from the WIG- oil&gas index and WIG- food industry indexwaysof interpreting the final results are presented.

Incorporating the risk of knowledge loss in supply chain risk management

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdelkader Daghfous ◽  
Abroon Qazi ◽  
M. Sajid Khan
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Risk Mitigation ◽  
Relevant Literature ◽  
Future Research ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Knowledge Loss ◽  
Content Type ◽  
Knowledge Based

PurposeThe literature on supply chain risk management (SCRM) has investigated a multitude of supply chain risks. This paper aims to make a case for the importance of managing the risk of knowledge loss in the supply chain management (SCM) function and incorporating knowledge loss as a critical risk within the SCRM process.Design/methodology/approachThis paper adopts a knowledge-based view of the SCRM process and attempts to bring to light insights based on a synthesis of the relevant literature. The authors conducted a systematic literature review of peer-reviewed articles published between 1998 and 2019. Further, a case study was conducted to illustrate the significance of the risk of knowledge loss in the SCM function in terms of how it operates and why it has such a significant impact on performance.FindingsKnowledge loss is a relatively neglected type of supply chain risk that can be added to the existing typologies. This paper argues that knowledge loss in the SCM function has the propensity to significantly impact the performance of the focal firm, exacerbate other types of supply chain risk and impede risk mitigation efforts. We put forth several strategies that supply chain managers can adopt to mitigate the risk of knowledge loss in their function.Research limitations/implicationsThis paper generates an exploratory opening that could pave the way for a systematic theory of knowledge loss as a supply chain risk and future empirical research. The study culminates in a number of important insights and initiatives for supply chain managers to recognize and manage the risk of knowledge loss.Originality/valueThis paper argues for the importance of incorporating the risk of knowledge loss in SCRM research and practice. It also provides an examination of some promising angles for future research in SCRM from a knowledge-based perspective.

Applying Artificial Intelligence to Financial Investing

2018 ◽  
pp. 1-14
Author(s):  
Hayden Wimmer ◽  
Roy Rada
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Language Processing ◽  
Credit Scoring ◽  
Bankruptcy Prediction ◽  
Asset Valuation ◽  
Artificial Intelligence Techniques ◽  
Academic Literature ◽  
Market Inefficiencies ◽  
Knowledge Based

Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. While there are many subfields to artificial intelligence this work seeks to identify the most commonly applied AI techniques to financial investing as appears in academic literature. AI techniques, such as knowledge-based, machine learning, and natural language processing, are integrated into systems that simultaneously address data identification, asset valuation, and risk management. Future trends will continue to integrate hybrid artificial intelligence techniques into financial investing, portfolio optimization, and risk management. The remainder of this article summarizes key contributions of applying AI to financial investing as appears in the academic literature.

Intellectual Capital

2010 ◽  
pp. 237-252 ◽  
Author(s):  
Maria do Rosário Cabrita ◽  
Virgílio Cruz Machado ◽  
António Grilo
Keyword(s):  
Competitive Advantage ◽  
Intellectual Capital ◽  
Sustainable Competitive Advantage ◽  
Central Question ◽  
Organisational Performance ◽  
Holistic Model ◽  
Knowledge Based ◽  
Study Support ◽  
Key Driver ◽  
Strategic Perspective

With the rise of the “new economy”, knowledge became a most valuable resource. Accepting knowledge as a resource suggests that knowledge can be acquired, transferred, combined and used, and it may be a potential source of sustainable competitive advantage. In this context, knowing how an organization creates value, based on its potential of knowledge, became a central question in management research. Under a strategic perspective, knowledge that creates value is defined as intellectual capital, the application of which will give organisations sustainable competitive advantage. Therefore, identifying, measuring and managing intellectual capital is crucial for corporate innovation and competitiveness. The purpose of our study is to examine the interrelationships and the effects of interaction between intellectual capital components and organisational performance, and defines how knowledge creates value. The study is developed in the context of Portuguese banks, an industry where differentiation of products and services almost exclusively hinges on the continuous rejuvenation of the underlying knowledge base. Empirical findings from this study support the propositions that intellectual capital is a key driver of organisational performance and that a knowledge-based perspective holds a more holistic model of organisations’ value creation.

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