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Article
Publication date: 6 December 2019

Alon Sela, Orit Milo, Eugene Kagan and Irad Ben-Gal

The purpose of this paper is to propose a novel method to enhance the spread of messages in social networks by “Spreading Groups.” These sub-structures of highly connected…

603

Abstract

Purpose

The purpose of this paper is to propose a novel method to enhance the spread of messages in social networks by “Spreading Groups.” These sub-structures of highly connected accounts intentionally echo messages between the members of the subgroup at the early stages of a spread. This echoing further boosts the spread to regions substantially larger than the initial region. These spreading accounts can be actual humans or social bots.

Design/methodology/approach

The paper reveals an interesting anomaly in information cascades in Twitter and proposes the spreading group model that explains this anomaly. The model was tested using an agent-based simulation, real Twitter data and questionnaires.

Findings

The messages of few anonymous Twitter accounts spread on average more than well-known global financial media groups, such as The Wall Street Journal or Bloomberg. The spreading groups (also sometimes called BotNets) model provides an effective mechanism that can explain these findings.

Research limitations/implications

Spreading groups are only one possible mechanism that can explain the effectiveness of spread of tweets from lesser known accounts. The implication of this work is in showing how spreading groups can be used as a mechanism to spread messages in social networks. The construction of spreading groups is rather technical and does not require using opinion leaders. Similar to the case of “Fake News,” we expect the topic of spreading groups and their aim to manipulate information to receive growing attention in public discussion.

Practical implications

While harnessing opinion leaders to spread messages is costly, constructing spreading groups is more technical and replicable. Spreading groups are an efficient method to amplify the spread of message in social networks.

Social implications

With the blossoming of fake news, one might tend to assess the reliability of news by the number of users involved in its spread. This heuristic might be easily fooled by spreading groups. Furthermore, spreading groups consisting of a blend of human and computerized bots might be hard to detect. They can be used to manipulate financial markets or political campaigns.

Originality/value

The paper demonstrates an anomaly in Twitter that was not studied before. It proposes a novel approach to spreading messages in social networks. The methods presented in the paper are valuable for anyone interested in spreading messages or an agenda such as political actors or other agenda enthusiasts. While social bots have been widely studied, their synchronization to increase the spread is novel.

Details

Online Information Review, vol. 44 no. 1
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 2 November 2010

Irad Ben‐Gal, Michael Wangenheim and Avraham Shtub

The purpose of this paper is to develop a model for physician staffing requirements that could be generally applied to any hospital department, taking into account factors such as…

1021

Abstract

Purpose

The purpose of this paper is to develop a model for physician staffing requirements that could be generally applied to any hospital department, taking into account factors such as occupancy level, professional absences, allowances, physician work duties and patient service levels.

Design/methodology/approach

The ability to generalize the model was tested via its implementation in five hospital departments considered to represent a cross‐section of all hospital requirements: internal medicine, surgery, orthopedics children's (pediatrics), and gynecology. The work is based on a combination of a survey, work sampling and direct time study, conducted by professional observers with a high degree of frequency and over a relatively long period of time.

Findings

The model is based on the concept of “required work capacity” of physicians. The model makes it possible to account for such factors as yearly capacity, level of desired service, increments for work conditions, roster duties and necessary absences.

Practical implications

The findings indicate that the departments studied required a significant increase in their physician staffing. In these departments the present manpower situation stands at 80–90 percent of the necessary staffing based on the average annual occupancy. The new staffing requirements model can be implemented in various departments.

Originality/value

This paper is an original effort to develop a model for physician staffing requirements at hospitals based on a survey, work‐study and direct time study. This contributes to past research that focused on the development of staffing requirements models, e.g. for nurse or family physicians. The paper presents an original model for physician staffing requirements at hospitals.

Details

International Journal of Productivity and Performance Management, vol. 59 no. 8
Type: Research Article
ISSN: 1741-0401

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Article
Publication date: 5 May 2023

Nicole Böhmer and Heike Schinnenburg

Human resource management (HRM) processes are increasingly artificial intelligence (AI)-driven, and HRM supports the general digital transformation of companies' viable…

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Abstract

Purpose

Human resource management (HRM) processes are increasingly artificial intelligence (AI)-driven, and HRM supports the general digital transformation of companies' viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces and workers’ organizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work.

Design/methodology/approach

A systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities.

Findings

The analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting and HR analytics in particular.

Research limitations/implications

The four ambiguities' context-specific potential for capability building in firms is indicated, and research avenues are developed.

Originality/value

This paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization's competitive advantage.

Details

Employee Relations: The International Journal, vol. 45 no. 5
Type: Research Article
ISSN: 0142-5455

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