Search results

1 – 10 of over 16000
To view the access options for this content please click here
Article
Publication date: 6 March 2020

Pavitra Dhamija and Surajit Bag

“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational…

Downloads
2627

Abstract

Purpose

“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its social and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have the people reached with respect to artificial intelligence research. The present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals and citation statistics.

Design/methodology/approach

As rightly remarked by past researchers that reviewing is learning from experience, research team has reviewed (by applying systematic literature review through bibliometric analysis) the concept of artificial intelligence in this article. A sum of 1,854 articles extracted from Scopus database for the year 2018–2019 (31st of May) with selected keywords (artificial intelligence, genetic algorithms, agent-based systems, expert systems, big data analytics and operations management) along with certain filters (subject–business, management and accounting; language-English; document–article, article in press, review articles and source-journals).

Findings

Results obtained from cluster analysis focus on predominant themes for present as well as future researchers in the area of artificial intelligence. Emerged clusters include Cluster 1: Artificial Intelligence and Optimization; Cluster 2: Industrial Engineering/Research and Automation; Cluster 3: Operational Performance and Machine Learning; Cluster 4: Sustainable Supply Chains and Sustainable Development; Cluster 5: Technology Adoption and Green Supply Chain Management and Cluster 6: Internet of Things and Reverse Logistics.

Originality/value

The result of review of selected studies is in itself a unique contribution and a food for thought for operations managers and policy makers.

Details

The TQM Journal, vol. 32 no. 4
Type: Research Article
ISSN: 1754-2731

Keywords

To view the access options for this content please click here
Article
Publication date: 1 January 1986

Emerson Hilker

We have long been obsessed with the dream of creating intelligent machines. This vision can be traced back to Greek civilization, and the notion that mortals somehow can…

Downloads
1227

Abstract

We have long been obsessed with the dream of creating intelligent machines. This vision can be traced back to Greek civilization, and the notion that mortals somehow can create machines that think has persisted throughout history. Until this decade these illusions have borne no substance. The birth of the computer in the 1940s did cause a resurgence of the cybernaut idea, but the computer's role was primarily one of number‐crunching and realists soon came to respect the enormous difficulties in crafting machines that could accomplish even the simplest of human tasks.

Details

Collection Building, vol. 7 no. 3
Type: Research Article
ISSN: 0160-4953

Abstract

Details

HR without People?
Type: Book
ISBN: 978-1-80117-037-6

To view the access options for this content please click here
Article
Publication date: 10 December 2020

Faten F. Kharbat, Abdallah Alshawabkeh and M. Lynn Woolsey

Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues…

Abstract

Purpose

Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues also mean increased absence and additional lags in academic achievement and development of adaptive and social skills. The incorporation of artificial intelligence in the education of a child with ID/DD could ameliorate the educational, adaptive and social skill gaps that occur as a direct result of persistent health problems.

Design/methodology/approach

The literature regarding the use of artificial intelligence in education for students with ID/DD was collected systematically from international online databases based on specific inclusion and exclusion criteria. The collected articles were analyzed deductively, looking for the different gaps in the domain. Based on the literature, an artificial intelligence–based architecture is proposed and sketched.

Findings

The findings show that there are many gaps in supporting students with ID/DD through the utilization of artificial intelligence. Given that the majority of students with ID/DD often have serious and chronic and comorbid health conditions, the potential use of health information in artificial intelligence is even more critical. Therefore, there is a clear need to develop a system that facilitates communication and access to health information for students with ID/DD, one that provides information to caregivers and education providers, limits errors, and, therefore, improves these individuals' education and quality of life.

Practical implications

This review highlights the gap in the current literature regarding using artificial intelligence in supporting the education of students with ID/DD. There is an urgent need for an intelligent system in collaboration with the updated health information to improve the quality of services submitted for people with intellectual disabilities and as a result improving their quality of life.

Originality/value

This study contributes to the literature by highlighting the gaps in incorporating artificial intelligence and its service to individuals with ID/DD. The research additionally proposes a solution based on the confounding variables of students’ health and individual characteristics. This solution will provide an automated information flow as a functional diagnostic and intervention tool for teachers, caregivers and parents. It could potentially improve the educational and practical outcomes for individuals with ID/DD and, ultimately, their quality of life.

To view the access options for this content please click here
Article
Publication date: 17 June 2019

Jeannette Paschen, Jan Kietzmann and Tim Christian Kietzmann

The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B…

Downloads
7525

Abstract

Purpose

The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research.

Design/methodology/approach

The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge.

Findings

The paper explains AI from an input–processes–output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge.

Practical implications

Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions.

Originality/value

The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.

Details

Journal of Business & Industrial Marketing, vol. 34 no. 7
Type: Research Article
ISSN: 0885-8624

Keywords

To view the access options for this content please click here
Book part
Publication date: 7 October 2020

Ali B. Mahmoud, Shehnaz Tehseen and Leonora Fuxman

This chapter attempts to provide answers to the following questions:

  • What is artificial intelligence (AI)? Moreover, what is AI-based retail innovation?
  • How does AI work?

Abstract

Learning Outcomes

This chapter attempts to provide answers to the following questions:

  • What is artificial intelligence (AI)? Moreover, what is AI-based retail innovation?

  • How does AI work?

  • What are the applications of AI in retail services innovation?

  • What are the ethical aspects, considerations and issues regarding the employment of AI in retail?

What is artificial intelligence (AI)? Moreover, what is AI-based retail innovation?

How does AI work?

What are the applications of AI in retail services innovation?

What are the ethical aspects, considerations and issues regarding the employment of AI in retail?

To view the access options for this content please click here
Book part
Publication date: 15 July 2020

William D. Casebeer

Discussions of ethics and Artificial Intelligence (AI) usually revolve around the ethical implications of the use of AI in multiple domains, ranging from whether machine…

Abstract

Discussions of ethics and Artificial Intelligence (AI) usually revolve around the ethical implications of the use of AI in multiple domains, ranging from whether machine learning trained algorithms may encode discriminatory standards for face recognition, to discussions of the implications of using AI as a substitute for human intelligence in warfare. In this chapter, I will focus on one particular strand of ethics and AI that is often neglected: whether we can use the methods of AI to build or train a system which can reason about moral issues and act on them. Here, I discuss (1) what an “artificial conscience” consists of and what it would do, (2) why we collectively should build one soon given the increasing use of AI in multiple areas, (3) how we might build one in both architecture and content, and (4) concerns about building an artificial conscience and my rejoinders. Given the increasing importance of artificially intelligent semi- or fully autonomous systems and platforms for contemporary warfare, I conclude that building an artificial conscience is not only possible but also morally required if our autonomous teammates are to collaborate fully with human soldiers on the battlefield.

Details

Artificial Intelligence and Global Security
Type: Book
ISBN: 978-1-78973-812-4

Keywords

To view the access options for this content please click here
Article
Publication date: 12 May 2020

Serge-Lopez Wamba-Taguimdje, Samuel Fosso Wamba, Jean Robert Kala Kamdjoug and Chris Emmanuel Tchatchouang Wanko

The main purpose of our study is to analyze the influence of Artificial Intelligence (AI) on firm performance, notably by building on the business value of AI-based…

Downloads
5620

Abstract

Purpose

The main purpose of our study is to analyze the influence of Artificial Intelligence (AI) on firm performance, notably by building on the business value of AI-based transformation projects. This study was conducted using a four-step sequential approach: (1) analysis of AI and AI concepts/technologies; (2) in-depth exploration of case studies from a great number of industrial sectors; (3) data collection from the databases (websites) of AI-based solution providers; and (4) a review of AI literature to identify their impact on the performance of organizations while highlighting the business value of AI-enabled projects transformation within organizations.

Design/methodology/approach

This study has called on the theory of IT capabilities to seize the influence of AI business value on firm performance (at the organizational and process levels). The research process (responding to the research question, making discussions, interpretations and comparisons, and formulating recommendations) was based on a review of 500 case studies from IBM, AWS, Cloudera, Nvidia, Conversica, Universal Robots websites, etc. Studying the influence of AI on the performance of organizations, and more specifically, of the business value of such organizations’ AI-enabled transformation projects, required us to make an archival data analysis following the three steps, namely the conceptual phase, the refinement and development phase, and the assessment phase.

Findings

AI covers a wide range of technologies, including machine translation, chatbots and self-learning algorithms, all of which can allow individuals to better understand their environment and act accordingly. Organizations have been adopting AI technological innovations with a view to adapting to or disrupting their ecosystem while developing and optimizing their strategic and competitive advantages. AI fully expresses its potential through its ability to optimize existing processes and improve automation, information and transformation effects, but also to detect, predict and interact with humans. Thus, the results of our study have highlighted such AI benefits in organizations, and more specifically, its ability to improve on performance at both the organizational (financial, marketing and administrative) and process levels. By building on these AI attributes, organizations can, therefore, enhance the business value of their transformed projects. The same results also showed that organizations achieve performance through AI capabilities only when they use their features/technologies to reconfigure their processes.

Research limitations/implications

AI obviously influences the way businesses are done today. Therefore, practitioners and researchers need to consider AI as a valuable support or even a pilot for a new business model. For the purpose of our study, we adopted a research framework geared toward a more inclusive and comprehensive approach so as to better account for the intangible benefits of AI within organizations. In terms of interest, this study nurtures a scientific interest, which aims at proposing a model for analyzing the influence of AI on the performance of organizations, and at the same time, filling the associated gap in the literature. As for the managerial interest, our study aims to provide managers with elements to be reconfigured or added in order to take advantage of the full benefits of AI, and therefore improve organizations’ performance, the profitability of their investments in AI transformation projects, and some competitive advantage. This study also allows managers to consider AI not as a single technology but as a set/combination of several different configurations of IT in the various company’s business areas because multiple key elements must be brought together to ensure the success of AI: data, talent mix, domain knowledge, key decisions, external partnerships and scalable infrastructure.

Originality/value

This article analyses case studies on the reuse of secondary data from AI deployment reports in organizations. The transformation of projects based on the use of AI focuses mainly on business process innovations and indirectly on those occurring at the organizational level. Thus, 500 case studies are being examined to provide significant and tangible evidence about the business value of AI-based projects and the impact of AI on firm performance. More specifically, this article, through these case studies, exposes the influence of AI at both the organizational and process performance levels, while considering it not as a single technology but as a set/combination of the several different configurations of IT in various industries.

Details

Business Process Management Journal, vol. 26 no. 7
Type: Research Article
ISSN: 1463-7154

Keywords

To view the access options for this content please click here
Article
Publication date: 20 May 2019

Anastassia Lauterbach

This paper aims to inform policymakers about key artificial intelligence (AI) technologies, risks and trends in national AI strategies. It suggests a framework of social…

Downloads
2531

Abstract

Purpose

This paper aims to inform policymakers about key artificial intelligence (AI) technologies, risks and trends in national AI strategies. It suggests a framework of social governance to ensure emergence of safe and beneficial AI.

Design/methodology/approach

The paper is based on approximately 100 interviews with researchers, executives of traditional companies and startups and policymakers in seven countries. The interviews were carried out in January-August 2017.

Findings

Policymakers still need to develop an informed, scientifically grounded and forward-looking view on what societies and businesses might expect from AI. There is lack of transparency on what key AI risks are and what might be regulatory approaches to handle them. There is no collaborative framework in place involving all important actors to decide on AI technology design principles and governance. Today's technology decisions will have long-term consequences on lives of billions of people and competitiveness of millions of businesses.

Research limitations/implications

The research did not include a lot of insights from the emerging markets.

Practical implications

Policymakers will understand the scope of most important AI concepts, risks and national strategies.

Social implications

AI is progressing at a very fast rate, changing industries, businesses and approaches how companies learn, generate business insights, design products and communicate with their employees and customers. It has a big societal impact, as – if not designed with care – it can scale human bias, increase cybersecurity risk and lead to negative shifts in employment. Like no other invention, it can tighten control by the few over the many, spread false information and propaganda and therewith shape the perception of people, communities and enterprises.

Originality/value

This paper is a compendium on the most important concepts of AI, bringing clarity into discussions around AI risks and the ways to mitigate them. The breadth of topics is valuable to policymakers, students, practitioners, general executives and board directors alike.

Details

Digital Policy, Regulation and Governance, vol. 21 no. 3
Type: Research Article
ISSN: 2398-5038

Keywords

To view the access options for this content please click here
Book part
Publication date: 16 April 2020

Devanathan Sudharshan

Abstract

Details

Marketing in Customer Technology Environments
Type: Book
ISBN: 978-1-83909-601-3

1 – 10 of over 16000