scholarly journals A Micro Perspective of Research Dynamics Through “Citations of Citations” Topic Analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaoli Chen ◽  
Tao Han
Keyword(s):  
Artificial Intelligence ◽  
Topic Modeling ◽  
Design Methodology ◽  
Topic Model ◽  
Research Impact ◽  
Research Trends ◽  
Topic Analysis ◽  
Forward Chaining ◽  
Practical Implications ◽  
Highly Cited

AbstractPurposeResearch dynamics have long been a research interest. It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject. A micro perspective of research dynamics, however, concerning a single researcher or a highly cited paper in terms of their citations and “citations of citations” (forward chaining) remains unexplored.Design/methodology/approachIn this paper, we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance, and topic innovation in each generation of forward chaining.FindingsFor highly cited work, scientific influence exists in indirect citations. Topic modeling can reveal how long this influence exists in forward chaining, as well as its influence.Research limitationsThis paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations. Paraphrasing or semantically similar concept may be neglected in this research.Practical implicationsThis paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining. This can serve as an inspiration on how to adequately evaluate research influence.OriginalityThe main contributions of this paper are the following three aspects. First, besides research dynamics of topic inheritance and topic innovation, we model topic disappearance by using a cross-collection topic model. Second, we explore the length and character of the research impact through “citations of citations” content analysis. Finally, we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton's publications and the topic dynamics of forward chaining.

Autonomous vehicles: a review of the ethical, social and economic implications of the AI revolution

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shweta Banerjee
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Design Methodology ◽  
Technological Advancement ◽  
Economic Implications ◽  
Content Type ◽  
The Public ◽  
Autonomous Cars ◽  
The Subject ◽  
Practical Implications

PurposeThere are ethical, legal, social and economic arguments surrounding the subject of autonomous vehicles. This paper aims to discuss some of the arguments to communicate one of the current issues in the rising field of artificial intelligence.Design/methodology/approachMaking use of widely available literature that the author has read and summarised showcasing her viewpoints, the author shows that technology is progressing every day. Artificial intelligence and machine learning are at the forefront of technological advancement today. The manufacture and innovation of new machines have revolutionised our lives and resulted in a world where we are becoming increasingly dependent on artificial intelligence.FindingsTechnology might appear to be getting out of hand, but it can be effectively used to transform lives and convenience.Research limitations/implicationsFrom robotics to autonomous vehicles, countless technologies have and will continue to make the lives of individuals much easier. But, with these advancements also comes something called “future shock”.Practical implicationsFuture shock is the state of being unable to keep up with rapid social or technological change. As a result, the topic of artificial intelligence, and thus autonomous cars, is highly debated.Social implicationsThe study will be of interest to researchers, academics and the public in general. It will encourage further thinking.Originality/valueThis is an original piece of writing informed by reading several current pieces. The study has not been submitted elsewhere.

How to optimize marketing strategy development

2020 ◽  
Vol 36 (8) ◽  
pp. 17-19
Keyword(s):  
Artificial Intelligence ◽  
Marketing Strategy ◽  
Design Methodology ◽  
Reading Time ◽  
Marketing Strategies ◽  
Strategy Development ◽  
Content Type ◽  
Human Creativity ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Artificial Intelligence (AI) is enabling companies to perform many functional tasks more efficiently. Some organizations are starting to further utilize its capabilities by combining the rationality of AI with human creativity in order to optimize development of marketing strategies. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

scholarly journals Managing the tension between opposing effects of explainability of artificial intelligence: a contingency theory perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Babak Abedin
Keyword(s):  
Artificial Intelligence ◽  
System Performance ◽  
Fuzzy Systems ◽  
Data Analytics ◽  
Design Methodology ◽  
Contingency Theory ◽  
Content Type ◽  
The Social ◽  
Opposing Effects ◽  
Practical Implications

PurposeResearch into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.Design/methodology/approachThe author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.FindingsThe author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).Research limitations/implicationsAs in other systematic literature review studies, the results are limited by the content of the selected papers.Practical implicationsThe findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.Originality/valueThis study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

scholarly journals Robotopias: mapping utopian perspectives on new industrial technology

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rhiannon Firth ◽  
Andrew Robinson
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
New Technologies ◽  
Social Role ◽  
Content Type ◽  
Human Essence ◽  
The Relationship ◽  
Labour Power ◽  
Practical Implications

PurposeThis paper maps utopian theories of technological change. The focus is on debates surrounding emerging industrial technologies which contribute to making the relationship between humans and machines more symbiotic and entangled, such as robotics, automation and artificial intelligence. The aim is to provide a map to navigate complex debates on the potential for technology to be used for emancipatory purposes and to plot the grounds for tactical engagements.Design/methodology/approachThe paper proposes a two-way axis to map theories into to a six-category typology. Axis one contains the parameters humanist–assemblage. Humanists draw on the idea of a human essence of creative labour-power, and treat machines as alienated and exploitative form of this essence. Assemblage theorists draw on posthumanism and poststructuralism, maintaining that humans always exist within assemblages which also contain non-human forces. Axis two contains the parameters utopian/optimist; tactical/processual; and dystopian/pessimist, depending on the construed potential for using new technologies for empowering ends.FindingsThe growing social role of robots portends unknown, and maybe radical, changes, but there is no single human perspective from which this shift is conceived. Approaches cluster in six distinct sets, each with different paradigmatic assumptions.Practical implicationsMapping the categories is useful pedagogically, and makes other political interventions possible, for example interventions between groups and social movements whose practice-based ontologies differ vastly.Originality/valueBringing different approaches into contact and mapping differences in ways which make them more comparable, can help to identify the points of disagreement and the empirical or axiomatic grounds for these. It might facilitate the future identification of criteria to choose among the approaches.

The impacts of artificial intelligence (AI) on jobs: an industry perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Placide Poba-Nzaou ◽  
Malatsi Galani ◽  
Sylvestre Uwizeyemungu ◽  
Arnela Ceric
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Employability Skills ◽  
Rapid Review ◽  
Professional Literature ◽  
Content Type ◽  
Job Tasks ◽  
Hr Function ◽  
Near Future ◽  
Practical Implications

Purpose This paper aims to explore the impacts of artificial intelligence (AI) on jobs. Design/methodology/approach The authors followed rapid review guidelines. The authors collected industry and government reports published prior and up to August 2017 in Google and Google Scholar using combination of key words: “job automation” or “work automation” with technology keywords: “artificial intelligence,” “machine learning,” etc. In total, 11 were included in this research. Findings The use of AI technologies will impact jobs in the near future as some job tasks are automated. AI is likely to substitute both, routine and nonroutine tasks. It is expected that humans and robots would work together in ways never imaginable. Changes in employability skills are expected. Because of the magnitude of these impacts on jobs, consulted reports call for concerted solutions that go beyond organizations’ and industry’s boundaries to include other relevant stakeholders. Moreover, organizations will have to rethink their human resource (HR) function to realign its expertise to the reality of AI. Practical implications In this context, the HR function will have to understand the dynamics that generate the impacts of these technologies in a workplace, to anticipate changes and actively contribute to creating an organizational environment that will facilitate the collaboration between human workers and complex digital agents, while ensuring compliance with labor and employment laws and supporting strategic organizational objectives. Originality/value This paper contributes to the debate on ongoing concerns by providing a synthesis of relevant professional literature.

scholarly journals Do prestigious Spanish scholarly book publishers have more teaching impact?

2018 ◽  
Vol 70 (6) ◽  
pp. 673-690 ◽  
Author(s):  
Amalia Mas-Bleda ◽  
Mike Thelwall
Keyword(s):  
Design Methodology ◽  
Research Impact ◽  
Educational Impact ◽  
Scholarly Book ◽  
Educational Value ◽  
Content Type ◽  
Social Sciences And Humanities ◽  
Book Publishers ◽  
Practical Implications ◽  
High Educational

PurposeThe purpose of this paper is to assess the educational value of prestigious and productive Spanish scholarly publishers based on mentions of their books in online scholarly syllabi.Design/methodology/approachSyllabus mentions of 15,117 books from 27 publishers were searched for, manually checked and compared with Microsoft Academic (MA) citations.FindingsMost books published by Ariel, Síntesis, Tecnos and Cátedra have been mentioned in at least one online syllabus, indicating that their books have consistently high educational value. In contrast, few books published by the most productive publishers were mentioned in online syllabi. Prestigious publishers have both the highest educational impact based on syllabus mentions and the highest research impact based on MA citations.Research limitations/implicationsThe results might be different for other publishers. The online syllabus mentions found may be a small fraction of the syllabus mentions of the sampled books.Practical implicationsAuthors of Spanish-language social sciences and humanities books should consider general prestige when selecting a publisher if they want educational uptake for their work.Originality/valueThis is the first study assessing book publishers based on syllabus mentions.

Artificial intelligence-based training learning from application

2019 ◽  
Vol 33 (2) ◽  
pp. 20-23 ◽  
Author(s):  
Ashwani Kumar Upadhyay ◽  
Komal Khandelwal
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Theoretical Foundation ◽  
Relevant Information ◽  
Relevant Research ◽  
Research Papers ◽  
Content Type ◽  
Training Systems ◽  
Effectiveness Of Training ◽  
Practical Implications

Purpose This paper aims to discuss the rationale, theoretical foundation, application, and future of artificial intelligence (AI)-based training. Design/methodology/approach A review of relevant research papers, articles and case studies is done to highlight developments in research and practice. Findings AI-based training systems are smart, intelligent and expert in handling queries. These systems can curate content, grade, evaluate, and provide feedback to trainee, thus making learning adaptive and contextual. Practical implications Application of AI is vital in the field of training, as it helps personalization and customization of training programs to increase the effectiveness of training. Originality/value Executives and researchers can save time by reading relevant information on the linkage, and its contribution to AI is discussed and summarized in an easy to read format.

Citation classics published in knowledge management journals. Part III: author survey

2017 ◽  
Vol 21 (2) ◽  
pp. 330-354 ◽  
Author(s):  
Alexander Serenko ◽  
John Dumay
Keyword(s):  
Knowledge Management ◽  
Design Methodology ◽  
Personal Characteristics ◽  
Research Approach ◽  
Content Type ◽  
Citation Classic ◽  
Citation Practices ◽  
Citation Classics ◽  
Practical Implications ◽  
Highly Cited

Purpose This paper is the third part of a series of works investigating the top 100 knowledge management (KM) citation classic articles. The purpose of this paper is to understand why KM citation classics are well-cited. Design/methodology/approach The results of a survey of 58 KM citation classic authors were reported as descriptive statistics and subjected to content analysis. Findings An archetype of a KM citation classic author was constructed including demographics, personal characteristics, motivation and work preferences. There is a need for developing novel ideas in KM research. Timeliness of a publication is directly linked to its future impact. Editors should involve citation classics authors as reviewers, and KM researchers should improve their citation practices. Serendipity played a very important role in early KM research, especially from the perspective of discovering new and interesting phenomena. Research limitations/implications Whereas the importance of serendipity is not questioned, future KM researchers should rely more on a formal, meticulous and well-planned research approach rather than on the hope of making a discovery by accident or luck. KM citation classics authors relied on serendipity to form the foundation of the discipline, but extending their work requires formal and structured inquiries. Practical implications Many authors conducted research to solve a problem to serve the needs of both practice and academia, rather than being overly theoretical. Originality/value Because KM researchers can no longer rely on past bibliometric theories, this paper helps understand why specific articles are highly cited and recommends how to conduct and develop future KM research that has impact.

Artificial intelligence and policy: quo vadis?

2019 ◽  
Vol 21 (3) ◽  
pp. 238-263 ◽  
Author(s):  
Anastassia Lauterbach
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Fast Rate ◽  
Content Type ◽  
Social Governance ◽  
Board Directors ◽  
Quo Vadis ◽  
The Many ◽  
Practical Implications

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.

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