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Book part
Publication date: 7 October 2015

Azizah Ahmad

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive…

Abstract

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Details

Sustaining Competitive Advantage Via Business Intelligence, Knowledge Management, and System Dynamics
Type: Book
ISBN: 978-1-78441-764-2

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The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
Type: Book
ISBN: 978-1-78754-853-4

Book part
Publication date: 18 January 2022

Brian McBreen, John Silson and Denise Bedford

This chapter reviews traditional intelligence work, primarily how intelligence was perceived and conducted in the industrial economy. The review includes economic sectors with…

Abstract

Chapter Summary

This chapter reviews traditional intelligence work, primarily how intelligence was perceived and conducted in the industrial economy. The review includes economic sectors with dedicated intelligence functions such as military, law enforcement, and national security. The review also includes secondary intelligence work in all other economic sectors. Looking across all these examples, the authors present a traditional life cycle model of intelligence work and highlight this traditional view of intelligence’s tactical and reactive approach. The chapter details the historical evolution and common intelligence elements in military, business, law enforcement, judicial forensics, national security, market, financial, medical, digital, and computer forensics.

Details

Organizational Intelligence and Knowledge Analytics
Type: Book
ISBN: 978-1-80262-177-8

Book part
Publication date: 25 November 2019

Aleksei Malakhov

This chapter presents an overarching overview of how the rather recent technological phenomena, like data mining, machine learning, and artificial intelligence, are applied in the…

Abstract

This chapter presents an overarching overview of how the rather recent technological phenomena, like data mining, machine learning, and artificial intelligence, are applied in the field of education. The author provides examples of how technological developments associated with the so-called Fourth Industrial Revolution are applied in education and considers the benefits and challenges they may bring regarding the economic system, as education (at least in the higher education sector) tends to be monetized and commercialized. The framework for education is perceived in the context of the economic intelligence of states, which is instrumental in ensuring their economic security. It is further expanded to the global scale, as Digital Education is crossing national borders and is being implemented in broader national processes.

Details

The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
Type: Book
ISBN: 978-1-78754-853-4

Keywords

Abstract

Details

Intelligence and State Surveillance in Modern Societies
Type: Book
ISBN: 978-1-78769-171-1

Book part
Publication date: 14 December 2017

G. Scott Erickson and Helen N. Rothberg

This chapter examines firm strengths and weaknesses from the standpoint of intangible assets. These are compared within and across industry sectors in order to better understand…

Abstract

This chapter examines firm strengths and weaknesses from the standpoint of intangible assets. These are compared within and across industry sectors in order to better understand who might be a potential collaborator (or competitor) in different contexts. Establishing the conceptual basis of a range of intangibles, including data, explicit knowledge, tacit knowledge, and intelligence, the chapter moves to metrics for assessing industry averages and individual firm capabilities. Finally, several sectors in healthcare are examined, specifically identifying what kinds of collaborators would best fit with a technology-driven start-up like Theranos.

Details

Global Opportunities for Entrepreneurial Growth: Coopetition and Knowledge Dynamics within and across Firms
Type: Book
ISBN: 978-1-78714-502-3

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Abstract

Details

Intelligence and State Surveillance in Modern Societies
Type: Book
ISBN: 978-1-78769-171-1

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

Book part
Publication date: 10 May 2023

Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Naresh Kumar and Sandeep Lal

It is difficult to argue against the fact that research has focussed on artificial intelligence (AI) and robotisation over the past few decades. Additionally, during the past…

Abstract

It is difficult to argue against the fact that research has focussed on artificial intelligence (AI) and robotisation over the past few decades. Additionally, during the past several years, it has taken off and is now extensively used in numerous businesses across various industries. Most of the time, AI has been associated with some industrial sector process automation. Still, recently, the authors have noticed more positive technology uses, especially in the financial services industry. Due to several factors, the financial sector needs to adopt AI and recognise its potential. The industry has historically been concerned about unpredictability, legislation, stronger cybersecurity, technological limitations and disruption of established lucrative operations.

Never before has there been more discussion about AI due to the advantages it provides to businesses that are providing financial services. That may explain why this change is referred to as the fourth industrial revolution. Both positively and negatively, it is quite disruptive. The effectiveness, accuracy and cost-effectiveness of solutions greatly increase. However, immense power also entails great responsibility.

Precautions and security are more crucial than ever for businesses since the financial sector is changing significantly and quickly. The various benefits and drawbacks of this technology are yet unknown to humans. Although AI was first shown to us in the 1950s, it has recently gained new prominence as processing power, and the available quantity of data has increased dramatically.

Details

Contemporary Studies of Risks in Emerging Technology, Part A
Type: Book
ISBN: 978-1-80455-563-7

Keywords

Book part
Publication date: 25 November 2019

Vasudha Chaudhari, Victoria Murphy and Allison Littlejohn

Almost every detail of our lives – where we go, what we do, and with whom – is captured as digital data. Technological advancements in cloud computing, artificial intelligence…

Abstract

Almost every detail of our lives – where we go, what we do, and with whom – is captured as digital data. Technological advancements in cloud computing, artificial intelligence, and data analytics offer the education sector new ways not only to improve policy and processes but also to personalize learning and teaching practice. However, these changes raise fundamental questions around who owns the data, how it might be used, and the consequences of use. The application of Big Data in education can be directed toward a wide range of stakeholders, such as educators, students, policy-makers, institutions, or researchers. It may also have different objectives, such as monitoring, student support, prediction, assessment, feedback, and personalization. This chapter presents the nuances and recent research trends spurred by technological advancements that have influenced the education sector and highlights the need to look beyond the technical boundaries using a socio-semiotic lens. With the explosion of available information and digital technologies pervading cultural, social, political as well as economic spaces, being a lifelong learner is pivotal for success. However, technology on its own is not sufficient to drive this change. For technology to be successful, it should complement individual learning cultures and education systems. This chapter is broadly divided into two main sections. In the first section, we contemplate a vision for the future, which is deemed possible based on ongoing digital and computing advancements. The second section elaborates the technological, pedagogical, cultural, and political requirements to attain that vision.

Details

The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
Type: Book
ISBN: 978-1-78754-853-4

Keywords

1 – 10 of over 8000