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Book part
Publication date: 14 October 2015

Igor Gurkov

The aim of the chapter is to evaluate the concept of corporate parenting styles, identify missing elements in the theoretical constructs, and develop new theoretical constructs.

Abstract

Purpose

The aim of the chapter is to evaluate the concept of corporate parenting styles, identify missing elements in the theoretical constructs, and develop new theoretical constructs.

Methodology/approach

The chapter provides a summary of the existing literature on corporate parenting styles and uncovers the missing elements in the theoretical constructs. New theoretical constructs fill the gaps.

Findings

The chapter presents a new typology of corporate parenting style by combining corporate parents’ processes of adding value to and extracting value from subsidiaries. The five-type typology of corporate styles outlines the different levels of value addition and value extraction and various degrees of reciprocity in both processes. This chapter determines the most important factors that affect the selection of corporate parenting style. It postulates that the multinational corporation should exhibit different parenting styles toward its subsidiaries simultaneously and should be ready to amend its parenting styles to reflect changes in a subsidiary’s strategy and its motives for corporate ownership.

Research limitations/implications

A new agenda for empirical studies oriented toward variability of parenting styles is proposed. Empirical tests of our propositions are needed. I encourage researchers to extend our research by considering the regional (supra-national), industry, and individual levels of analyses.

Originality/value

The chapter provides a more realistic view of corporate parenting styles than that found in the previous literature and outlines promising directions for further theoretical and empirical research.

Book part
Publication date: 13 March 2023

Xiaohang (Flora) Feng, Shunyuan Zhang and Kannan Srinivasan

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured…

Abstract

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

Book part
Publication date: 5 July 2005

Guglielmo Carchedi

This article aims at contributing to the development of a Marxist theory of the production of knowledge, and in particular of natural sciences and techniques (NST), under…

Abstract

This article aims at contributing to the development of a Marxist theory of the production of knowledge, and in particular of natural sciences and techniques (NST), under capitalism. It rejects the double critique that the labor theory of value has become obsolete under modern capitalism and that Marx’s theoretical structure cannot accommodate mental production. The paper starts with two preliminary sections. First, some relevant aspects of dialectics as a tool of social research are submitted. Then, notions such as Information Society or Service Society are debunked. On this basis, the production of individual and of social knowledge is inquired into and the conditions for knowledge production to be production of (surplus) value are analyzed. Next, the question is tackled as to why and how this knowledge (and in particular NST) is functional for the interests of the capitalist class, even though in a contradictory way. Several examples are provided. Particular attention is paid to the computer and to biotechnology and genetic engineering. The most common objections against the thesis of the class determination of knowledge are dealt with. It is argued that class determination of knowledge can explain why the science and techniques developed in one society and by one class can be used in other societies and by other classes. Examples are provided of trans-class and trans-epochal elements of knowledge. Finally, the last section submits that a radically different type of NST can originate only from a radically different type of society, based on radically different production relations.

Details

The Capitalist State and Its Economy: Democracy in Socialism
Type: Book
ISBN: 978-0-76231-176-7

Book part
Publication date: 19 June 2020

Cătălin Popescu and Lazăr Avram

European projects from a wide list of subjects are sharing and promoting good practice in knowledge development but there appears to be opportunities to exploit the findings of…

Abstract

European projects from a wide list of subjects are sharing and promoting good practice in knowledge development but there appears to be opportunities to exploit the findings of these projects more effectively, especially relating to sustainability issues, in the implementation and development of robust curricula within higher education at undergraduate and postgraduate levels.

A detailed description will be given of an example of a partnership between several universities from Sweden, France, Romania, and Lebanon related to a high-profile industry area: oil and gas. This partnership was created within a European Project carried out during the 2015–2018 period. The importance of this project is focused on how energy issues play an important role in the global development of industrial and underdeveloped countries. Energy issues are commonly accompanied with the challenging trade-off of energy production and environmental sustainability. The research project evaluates the creation and delivery of a new curriculum at the Lebanese universities based upon the joint effort and support of the European partners of the Project Consortium.

The overall aim of the project was to promote academic excellence through an academic network and by joint research, education, and exchange of experience, but also knowledge that has led to the high-quality curriculum. It is expected that this will contribute in the sustainable development of the Lebanese higher educational system. The project is in perfect alignment with the EU Commission’s action aiming to deepen the knowledge of extraction technologies and practices of unconventional gas and oil while minimizing potential health and environmental risks. The project succeeded in the delivery and the transfer of specific knowledge, through a more effective curriculum, for future educators and offers students a high-quality educational experience preparing them for the oil and gas industry.

Details

University Partnerships for Sustainable Development
Type: Book
ISBN: 978-1-78973-643-4

Keywords

Book part
Publication date: 10 July 2019

Tianxing Wu, Guilin Qi and Cheng Li

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and…

Abstract

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

Details

The New Silk Road Leads through the Arab Peninsula: Mastering Global Business and Innovation
Type: Book
ISBN: 978-1-78756-680-4

Keywords

Book part
Publication date: 11 June 2021

Hanlie Smuts and Alet Smith

Significant advances in digital technologies impact both organisations and knowledge workers alike. Organisations are now able to effectively analyse significant amounts of data…

Abstract

Significant advances in digital technologies impact both organisations and knowledge workers alike. Organisations are now able to effectively analyse significant amounts of data, while accomplishing actionable insight and data-driven decision-making through knowledge workers that understand and manage greater complexity. For decision-makers to be in a position where sufficient information and data-driven insights enable them to make informed decisions, they need to better understand fundamental constructs that lead to the understanding of deep knowledge and wisdom. In an attempt to guide organisations in such a process of understanding, this research study focuses on the design of an organisational transformation framework for data-driven decision-making (OTxDD) based on the collaboration of human and machine for knowledge work. The OTxDD framework was designed through a design science research approach and consists of 4 major enablers (data analytics, data management, data platform, data-driven organisation ethos) and 12 sub-enablers. The OTxDD framework was evaluated in a real-world scenario, where after, based on the evaluation feedback, the OTxDD framework was improved and an organisational measurement tool developed. By considering such an OTxDD framework and measurement tool, organisations will be able to create a clear transformation path to data-driven decision-making, while applying the insight from both knowledge workers and intelligent machines.

Details

Information Technology in Organisations and Societies: Multidisciplinary Perspectives from AI to Technostress
Type: Book
ISBN: 978-1-83909-812-3

Keywords

Abstract

Details

Knowledge Risk and its Mitigation: Practices and Cases
Type: Book
ISBN: 978-1-78973-919-0

Book part
Publication date: 26 October 2021

Denise Bedford and Thomas W. Sanchez

This chapter explores the role of nodes in knowledge networks. The authors characterize knowledge nodes by the type of actors they represent, including individual human agents…

Abstract

Chapter Summary

This chapter explores the role of nodes in knowledge networks. The authors characterize knowledge nodes by the type of actors they represent, including individual human agents, collective human groups and teams, explicit non-human objects and resources, and non-human agents and machines. The authors define knowledge nodes by their role in the network, including producer, consumer, or broker of knowledge, and in terms of the stock of knowledge they represent and their capacity to absorb knowledge made available in the network.

Details

Knowledge Networks
Type: Book
ISBN: 978-1-83982-949-9

Abstract

Details

Knowledge Assets and Knowledge Audits
Type: Book
ISBN: 978-1-78973-771-4

Content available
Book part
Publication date: 13 March 2023

Abstract

Details

Artificial Intelligence in Marketing
Type: Book
ISBN: 978-1-80262-875-3

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