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21 – 30 of over 11000
Article
Publication date: 25 October 2018

Xie Kefan, Yu Song, Sishi Liu and Jia Liu

The purpose of this paper is to analyze the crowd stampede risk mechanism from the perspective of systems thinking.

Abstract

Purpose

The purpose of this paper is to analyze the crowd stampede risk mechanism from the perspective of systems thinking.

Design/methodology/approach

Causal loop diagram is drawn to outline the non-linear interactions among complex factors across the whole system and dissect the contributory factors of crowd stampede accident. To systematically construct the theoretical framework and find fundamental solutions, co-word analysis with Citespace is used to get the critical data. An agent-based simulation using Pathfinder is conducted to develop a spatial model for the Shanghai Stampede Accident that happened in 2014.

Findings

The causal loop diagram is formed to not only illustrate the symptomatic solutions with a quick fix but also dissect the fundamental solutions through an underlying systemic analysis. The simulation shows that crowd stampede experiences an interactive process of accumulation, trigger, delay, break and diffusion of risk factors within the crowd system. A linkage effect among the multidimensional characters of individuals and the system accelerates the stampede risk deterioration. There exists delay of the result of effect from the deep-level measure.

Practical implications

A top-down approach is offered to policymakers for crowd stampede risk protocol design and synergic emergency control that may reduce the risk of the stampede.

Originality/value

In this study, SDFT paradigm is proposed as the critical solution for the crowd stampede accident. In addition, a chain effect of energy and a linkage effect within the crowd system is illustrated for in-depth understanding of crowd stampede risk.

Details

Kybernetes, vol. 48 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 1 March 2021

Yiqiang Feng, Leiju Qiu and Baowen Sun

The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and…

1185

Abstract

Purpose

The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network.

Design/methodology/approach

The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions.

Findings

The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages.

Research limitations/implications

The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study.

Originality/value

Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value.

Details

International Journal of Crowd Science, vol. 5 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Article
Publication date: 20 November 2017

Thushari Silva and Jian Ma

Expert profiling plays an important role in expert finding for collaborative innovation in research social networking platforms. Dynamic changes in scientific knowledge have posed…

1054

Abstract

Purpose

Expert profiling plays an important role in expert finding for collaborative innovation in research social networking platforms. Dynamic changes in scientific knowledge have posed significant challenges on expert profiling. Current approaches mostly rely on knowledge of other experts, contents of static web pages or their behavior and thus overlook the insight of big social data generated through crowdsourcing in research social networks and scientific data sources. In light of this deficiency, this research proposes a big data-based approach that harnesses collective intelligence of crowd in (research) social networking platforms and scientific databases for expert profiling.

Design/methodology/approach

A big data analytics approach which uses crowdsourcing is designed and developed for expert profiling. The proposed approach interconnects big data sources covering publication data, project data and data from social networks (i.e. posts, updates and endorsements collected through the crowdsourcing). Large volume of structured data representing scientific knowledge is available in Web of Science, Scopus, CNKI and ACM digital library; they are considered as publication data in this research context. Project data are located at the databases hosted by funding agencies. The authors follow the Map-Reduce strategy to extract real-time data from all these sources. Two main steps, features mining and profile consolidation (the details of which are outlined in the manuscript), are followed to generate comprehensive user profiles. The major tasks included in features mining are processing of big data sources to extract representational features of profiles, entity-profile generation and social-profile generation through crowd-opinion mining. At the profile consolidation, two profiles, namely, entity-profile and social-profile, are conflated.

Findings

(1) The integration of crowdsourcing techniques with big research data analytics has improved high graded relevance of the constructed profiles. (2) A system to construct experts’ profiles based on proposed methods has been incorporated into an operational system called ScholarMate (www.scholarmate.com).

Research limitations

One shortcoming is currently we have conducted experiments using sampling strategy. In the future we will perform controlled experiments of large scale and field tests to validate and comprehensively evaluate our design artifacts.

Practical implications

The business implication of this research work is that the developed methods and the system can be applied to streamline human capital management in organizations.

Originality/value

The proposed approach interconnects opinions of crowds on one’s expertise with corresponding expertise demonstrated in scientific knowledge bases to construct comprehensive profiles. This is a novel approach which alleviates problems associated with existing methods. The authors’ team has developed an expert profiling system operational in ScholarMate research social network (www.scholarmate.com), which is a professional research social network that connects people to research with the aim of “innovating smarter” and was launched in 2007.

Details

Information Discovery and Delivery, vol. 45 no. 4
Type: Research Article
ISSN: 2398-6247

Keywords

Article
Publication date: 12 March 2018

Merve Ozen and Ananth Krishnamurthy

Relief item distribution to victims is a key activity during disaster response. Currently many humanitarian organizations follow simple guidelines based on experience to assess…

1158

Abstract

Purpose

Relief item distribution to victims is a key activity during disaster response. Currently many humanitarian organizations follow simple guidelines based on experience to assess need and distribute relief supplies. However, the interviews with practitioners suggest a problem in efficiency in relief distribution efforts. The purpose of this paper is to develop a model and solution methodology that can estimate relief center (RC) performance, measured by waiting time for victims and throughput, for any RC design and analyze the impact of key design decisions on these performance measures.

Design/methodology/approach

Interviews with practitioners and current practice guidelines are used to understand relief distribution and a queuing network model is used to represent the relief distribution. Finally, the model is applied to data from the 2015 Nepal earthquake.

Findings

The findings identify that dissipating congestion created by crowds, varying item assignment decisions to points of distribution, limiting the physical RC capacity to control congestion and using triage queue to balance distribution times, are effective strategies that can improve RC performance.

Research limitations/implications

This research bases the RC designs on Federal Emergency Management Agency guidelines and assumes a certain area and volunteer availability.

Originality/value

This paper contributes to humanitarian logistics by discussing useful insights that can impact how relief agencies set up and operate RCs. It also contributes to the queuing literature by deriving analytic solutions for the steady state probabilities of finite capacity, state dependent queues with blocking.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 8 no. 1
Type: Research Article
ISSN: 2042-6747

Keywords

Article
Publication date: 1 March 2001

K.G.B. Bakewell

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18;…

14378

Abstract

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Details

Property Management, vol. 19 no. 3
Type: Research Article
ISSN: 0263-7472

Article
Publication date: 1 May 2001

K.G.B. Bakewell

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18;…

14155

Abstract

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Details

Journal of Property Investment & Finance, vol. 19 no. 5
Type: Research Article
ISSN: 1463-578X

Open Access
Article
Publication date: 21 June 2019

Pengze Li, Ran Zhang, Lei Liu, Lizhen Cui, Qingzhong Li and Guangpeng Zhou

Science of the Crowd is a new paradigm. The research on the relationship between provision and requirement arising from the behavior of the crowd under the interconnected…

Abstract

Purpose

Science of the Crowd is a new paradigm. The research on the relationship between provision and requirement arising from the behavior of the crowd under the interconnected environment is a promising topic. This paper aims at studying a new type of interconnected architecture.

Design/methodology/approach

This study is a pioneer work on the establishment of a new type of interconnected architecture – rim chain. The rim chain aims at supporting prompt matching between provision and requirements.

Findings

The analytical results suggest that requirements can be fulfilled in accordance with six degrees of separation. In other words, the matching between the requirements and provision takes place with six hops in the rim chain framework.

Originality/value

Knowledge graph is used to implement the rim chain.

Details

International Journal of Crowd Science, vol. 3 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Article
Publication date: 4 July 2016

Bin Hao and Yanan Feng

This paper aims to offer a novel set of insights to understand the role of network ties in pursuit of radical innovation. In this sense, the purpose of the study is to analyze how…

1405

Abstract

Purpose

This paper aims to offer a novel set of insights to understand the role of network ties in pursuit of radical innovation. In this sense, the purpose of the study is to analyze how the heterogeneity in the content of network ties affects radical innovation performance.

Design/methodology/approach

Based on a comprehensive review of existing literature, this paper conceptualizes how different types of network ties affect radical innovation performance by deriving five research propositions.

Findings

Both buyer-supplier ties and peer collaboration ties are positively related to radical innovation performance, whilst the peer collaboration ties may be further affected by partner similarity. Compared to other two types of network ties, equity ties act as more of moderating roles on spurring radical innovation. Crowding out between network ties prevents firms from knowledge searching within an extensive network scope, reducing the opportunities of mixing and matching different kinds of knowledge needed for radical innovation.

Research limitations/implications

The study suggests a natural way of launching marketing strategy by selectively integrating different sources of knowledge (market, supplier or technology) needed for commercializing radical technologies, highlighting the importance of partner selection for radical innovation among different types of firms surrounding the current market. For managers, it is necessary to identify and select network ties helpful for long-term business and strategic interests.

Originality/value

This paper makes two main contributions. First, it addresses the question of how networks influence radical innovation by identifying three types of network ties and their effects – individual and in combination – on extension of the depth and breadth of knowledge and development of disruptive ideas. Second, it develops the existing literature by demonstrating the crowding-out effect of network ties.

Details

Journal of Business & Industrial Marketing, vol. 31 no. 6
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 3 November 2020

K. Satya Sujith and G. Sasikala

Object detection models have gained considerable popularity as they aid in lot of applications, like monitoring, video surveillance, etc. Object detection through the video…

Abstract

Purpose

Object detection models have gained considerable popularity as they aid in lot of applications, like monitoring, video surveillance, etc. Object detection through the video tracking faces lot of challenges, as most of the videos obtained as the real time stream are affected due to the environmental factors.

Design/methodology/approach

This research develops a system for crowd tracking and crowd behaviour recognition using hybrid tracking model. The input for the proposed crowd tracking system is high density crowd videos containing hundreds of people. The first step is to detect human through visual recognition algorithms. Here, a priori knowledge of location point is given as input to visual recognition algorithm. The visual recognition algorithm identifies the human through the constraints defined within Minimum Bounding Rectangle (MBR). Then, the spatial tracking model based tracks the path of the human object movement in the video frame, and the tracking is carried out by extraction of color histogram and texture features. Also, the temporal tracking model is applied based on NARX neural network model, which is effectively utilized to detect the location of moving objects. Once the path of the person is tracked, the behaviour of every human object is identified using the Optimal Support Vector Machine which is newly developed by combing SVM and optimization algorithm, namely MBSO. The proposed MBSO algorithm is developed through the integration of the existing techniques, like BSA and MBO.

Findings

The dataset for the object tracking is utilized from Tracking in high crowd density dataset. The proposed OSVM classifier has attained improved performance with the values of 0.95 for accuracy.

Originality/value

This paper presents a hybrid high density video tracking model, and the behaviour recognition model. The proposed hybrid tracking model tracks the path of the object in the video through the temporal tracking and spatial tracking. The features train the proposed OSVM classifier based on the weights selected by the proposed MBSO algorithm. The proposed MBSO algorithm can be regarded as the modified version of the BSO algorithm.

Open Access
Article
Publication date: 29 October 2019

Zhishuo Liu, Tian Fang, Yao Dongxin and Nianci Kou

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This…

Abstract

Purpose

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

Design/methodology/approach

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

Findings

The simulation results show that this model is superior with high accuracy and anti-aggression.

Originality/value

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.

Details

International Journal of Crowd Science, vol. 3 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

21 – 30 of over 11000