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1 – 10 of 94Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined…
Abstract
Purpose
Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.
Design/methodology/approach
We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.
Findings
Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.
Originality/value
Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.
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This article explores whether six broad categories of activities undertaken by Canadian business scholars’ academics: publications record, citations record, teaching load…
Abstract
Purpose
This article explores whether six broad categories of activities undertaken by Canadian business scholars’ academics: publications record, citations record, teaching load, administrative load, consulting activities, and knowledge spillovers transfer, are complementary, substitute, or independent, as well as the conditions under which complementarities, substitution and independence among these activities are likely to occur.
Design/methodology/approach
A multivariate probit model is estimated to take into account that business scholars have to consider simultaneously whether or not to undertake many different academic activities. Metrics from Google Scholar of scholars from 35 Canadian business schools, augmented by a survey data on factors explaining the productivity and impact performances of these faculty members, are used to explain the heterogeneities between the determinants of these activities.
Findings
Overall, the results reveal that there are complementarities between publications and citations, publications and knowledge spillovers transfer, citations and consulting, and between consulting and knowledge spillovers transfer. The results also suggest that there are substitution effects between publications and teaching, publications and administrative load, citations and teaching load, and teaching load and administrative load. Moreover, results show that public and private funding, business schools’ reputation, scholar’s relational resources, and business school size are among the most influential variables on the scholar’s portfolio of activities.
Originality/value
This study considers simultaneously the scholar’s whole portfolio of activities. Moreover, the determinants considered in this study to explain scholars’ engagement in different activities reconcile two conflicting perspectives: (1) the traditional self-managed approach of academics, and (2) the outcomes-focused approach of university management.
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Wided Bouaine, Karima Alaya and Chokri Slim
The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship…
Abstract
Purpose
The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship between them.
Design/methodology/approach
In order to achieve the objective, a succession of eight ordered probit regressions has been carried out. Moderating variables between the political connection and governance characteristics were introduced. The whole population is taken as a sample, i.e., 27 Tunisian companies that are evaluated by FITSH NORTH AFRICA agencies over a period of 10 years (2009–2018).
Findings
The outcomes are mixed. They show that the political connection does not always influence credit rating; the size and board independence always improves credit rating; the duality between the functions affects credit rating; whereas the majorities’ proportion does not influence credit rating; and a substitution between the political connection and the governance characteristics is validated.
Research limitations/implications
Like any other research, our results are factors of our measures and variable choice and depends heavily on the how these variables were conceived. Also, although our number of observations responds to the statistical result generalization requirements, our sample remains relatively narrow with 27 companies only.
Practical implications
In practice, the research will allow investors to have a better vision upon the future of their investments based on whether to develop their governance system or promote political networking. It will also prompt lenders to look beyond ratings and consider factors such as political connections to make a rational judgment on their future placements.
Social implications
This study leads us to find various solutions: the establishment of credit agencies that take into consideration all the data of all the operators taken as a whole (bank, leasing company, and factoring). It encourages the reorganization of the Tunisian banking sector through mergers for example.
Originality/value
This study is a pioneer in the credit rating field in Tunisia, where the source of debt financing is the most used by all enterprises across all sectors. This study extends the literature of political connection effectiveness, independent directors, board size, in improving corporate performance and credit rating.
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Andrea Bonomi Savignon, Riccardo Zecchinelli, Lorenzo Costumato and Fabiana Scalabrini
This study aims to estimate the value of the impact from digital transformation (DX) focusing on its automation effect, looking at the time and cost savings coming from the…
Abstract
Purpose
This study aims to estimate the value of the impact from digital transformation (DX) focusing on its automation effect, looking at the time and cost savings coming from the substitution effect with an adoption of digital technologies. For example, cloud and artificial intelligence technologies such as ChatGPT have the potential to change ways of working, substituting and replacing several of the tasks that are currently carried out by public administration (PA) employees and labor processes underpinning PA services.
Design/methodology/approach
The paper outlines a new framework to estimate the potential impact of DX on the public sector. The authors apply this framework to estimate the value of the impact of DX on the Italian PA, defining the latter by the collection of the value of its labor (i.e. PA workforce salaries) and by the collection of the value of its outputs (i.e. public services’ costs).
Findings
This study ultimately maps out the magnitude and trends of how likely the PA occupations and services could be substituted in a wider process of DX. To do this, the authors apply their framework to the Italian PA, and they triangulate secondary data collection, from official accounts of the Italian Ministry of Economics and the National Statistical Institute, with methodological antecedents from the UK Office for National Statistics and experts’ insights. Results provide a snapshot on the type and magnitude of PA jobs and services projected to be affected by automation over the next 10 years.
Originality/value
To the best of the authors’ knowledge, this paper provides for the first time an approach to estimate the value of the impact of DX on the public sector in a data-constrained environment – or in the lack of the required primary data. Once applied to the Italian PA, this approach provides a granular map of the automatability of each of the PA occupations and of the PA services. Finally, this paper mentions preliminary insights on potential challenges related to equity in public sector jobs and implications on recruitment processes.
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Miquel Centelles and Núria Ferran-Ferrer
Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific…
Abstract
Purpose
Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.
Design/methodology/approach
This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.
Findings
This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.
Originality/value
The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.
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Gianluca Piero Maria Virgilio, Fausto Saavedra Hoyos and Carol Beatriz Bao Ratzemberg
The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.
Abstract
Purpose
The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.
Design/methodology/approach
The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.
Findings
Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.
Originality/value
The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338
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Sifeng Liu, Ningning Lu, Zhongju Shang and R.M. Kapila Tharanga Rathnayaka
The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series…
Abstract
Purpose
The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.
Design/methodology/approach
The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.
Findings
(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.
Practical implications
The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.
Originality/value
The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.
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Margarethe Born Steinberger-Elias
In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by…
Abstract
In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.
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Abbas Ali Gillani and Khadija M. Bari
The purpose of this study is to estimate the impact of conflict witnessed in Pakistan on the enrolment rates of boys and girls. Pakistan has the world’s second-highest number of…
Abstract
Purpose
The purpose of this study is to estimate the impact of conflict witnessed in Pakistan on the enrolment rates of boys and girls. Pakistan has the world’s second-highest number of out-of-school children, with an estimated 22.8 million children aged 5–16 years not attending school.
Design/methodology/approach
By merging data on violence with the data on enrolment rates, this paper finds that exposure to violence is correlated with a decline in overall district-level enrolment rates in the short run at primary-level schools and middle-level schools.
Findings
However, for boys, violence is also negatively correlated with enrolment rates at middle-level schools in the medium run. One possible mechanism tested in this paper is the potential substitution of boys into the labour market during a period of conflict.
Originality/value
To the best of the authors’ knowledge, this paper adds to the existing literature in several ways. Firstly, the effect of conflict on the labour market by impacting schooling for boys and girls is examined for the first time in Pakistan. Secondly, the district-level data set on enrolment rates used for this study is novel and has not been used before for this type of analysis. Thirdly, while this study strengthens the evidence that the short run effects of conflict are stronger than the long-run effects, it also confirms the negative effects of conflict do not fade away immediately. Fourthly, this study emphasizes that each conflict is unique in terms of its heterogeneous effects across different cohorts, such as gender, as these effects are dependent on the mechanism through which conflict impacts each individual.
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Zhongyi Wang, Xueyao Qiao, Jing Chen, Lina Li, Haoxuan Zhang, Junhua Ding and Haihua Chen
This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the DDiv index, for this purpose.
Abstract
Purpose
This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the DDiv index, for this purpose.
Design/methodology/approach
The DDiv index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.
Findings
The sensitivity analysis demonstrated the DDiv index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the DDiv index reached the highest prediction accuracy of 0.8. Furthermore, the DDiv index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.
Originality/value
This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.
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