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Article
Publication date: 30 July 2019

Zhizhou Wu, Yiming Zhang, Guishan Tan and Jia Hu

Traffic density is one of the most important parameters to consider in the traffic operation field. Owing to limited data sources, traditional methods cannot extract…

Abstract

Purpose

Traffic density is one of the most important parameters to consider in the traffic operation field. Owing to limited data sources, traditional methods cannot extract traffic density directly. In the vehicular ad hoc network (VANET) environment, the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) interaction technologies create better conditions for collecting the whole time-space and refined traffic data, which provides a new approach to solving this problem.

Design/methodology/approach

On that basis, a real-time traffic density extraction method has been proposed, including lane density, segment density and network density. Meanwhile, using SUMO and OMNet++ as traffic simulator and network simulator, respectively, the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.

Findings

Based on the simulation platform, a simulated intersection in Shanghai was developed to investigate the adaptability of the model.

Originality/value

Most research studies use separate simulation methods, importing trace data obtained by using from the simulation software to the communication simulation software. In this paper, the tight coupling simulation method is applied. Using real-time data and history data, the research focuses on the establishment and validation of the traffic density extraction model.

Details

Journal of Intelligent and Connected Vehicles, vol. 2 no. 1
Type: Research Article
ISSN: 2399-9802

Keywords

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Article
Publication date: 5 June 2017

Yuanzhu Zhan, Kim Hua Tan, Guojun Ji, Leanne Chung and Minglang Tseng

The purpose of this paper is to suggest how firms could use big data to facilitate product innovation processes, by shortening the time to market, improving customers 

Abstract

Purpose

The purpose of this paper is to suggest how firms could use big data to facilitate product innovation processes, by shortening the time to market, improving customers’ product adoption and reducing costs.

Design/methodology/approach

The research is based on a two-step approach. First, this research identifies four potential key success factors for organisations to integrate big data in accelerating their product innovation processes. The proposed factors are further examined and developed by conducting interviews with different organisation experts and academic researchers. Then a framework is developed based on the interview outputs. The framework sets out the key success factors involved in leveraging big data to reduce lead times and costs in product innovation processes.

Findings

The three determined key success factors are: accelerated innovation process; customer connection; and an ecosystem of innovation. The authors believe that the developed framework based on big data represents a paradigm shift. It can help firms to make new product development dramatically faster and less costly.

Research limitations/implications

The proposed accelerated innovation processes demand a shift in traditional organisational culture and practices. It is, though, meaningful only for products and services with short life cycles. Moreover, the framework has not yet been widely tested.

Practical implications

This paper points to the vital role of big data in helping firms to accelerate product innovation processes. First of all, it allows organisations to launch new products to market as quickly as possible. Second, it helps organisations to determine the weaknesses of the product earlier in the development cycle. Third, it allows functionalities to be added to a product that customers are willing to pay a premium for, while eliminating features they do not want. Last, but not least, it identifies and then prioritises customer needs for specific markets.

Originality/value

The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation process based on big data is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.

Details

Business Process Management Journal, vol. 23 no. 3
Type: Research Article
ISSN: 1463-7154

Keywords

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Article
Publication date: 19 April 2013

Tsung‐Hsien Kuo

The purpose of this paper is to look at the relationships among factors which result in improved knowledge sharing, through the empirical validation of a theoretical model…

Abstract

Purpose

The purpose of this paper is to look at the relationships among factors which result in improved knowledge sharing, through the empirical validation of a theoretical model consisting of three dimensions: expected benefit in relation to knowledge sharing, trust at workplace, and employee knowledge‐sharing behavior.

Design/methodology/approach

This study targets three technological companies with a total of employees exceeding 1,500 (n=563), utilizing a survey questionnaire as the data collection instrument to test the relationship among the three dimensions. The structural equation modeling approach is used to test the proposed model.

Findings

The results show that trust at workplace has a mediating effect on organizational knowledge‐sharing behavior. It is also discovered that there is significant correlation between expected personal benefit through sharing knowledge and the development of trust at workplace.

Originality/value

This study contributes empirical data to the predominantly theoretical literature by offering a deeper understanding of the mediating effect of trust on employee's expected benefit for the purpose of knowledge exchange behavior within teams and among teams.

Details

Industrial Management & Data Systems, vol. 113 no. 4
Type: Research Article
ISSN: 0263-5577

Keywords

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Article
Publication date: 13 April 2015

MingLang Tseng, Ming Lim and Wai Peng Wong

Assessing a measure of sustainable supply chain management (SSCM) performance is currently a key challenge. The literature on SSCM is very limited and performance measures…

Abstract

Purpose

Assessing a measure of sustainable supply chain management (SSCM) performance is currently a key challenge. The literature on SSCM is very limited and performance measures need to have a systematic framework. The recently developed balanced scorecard (BSC) is a measurement system that requires a balanced set of financial and non-financial measures. The purpose of this paper is to evaluate the SSCM performance based on four aspects i.e. sustainability, internal operations, learning and growth, and stakeholder.

Design/methodology/approach

This paper developed a BSC hierarchical network for SSCM in a close-loop hierarchical structure. A generalized quantitative evaluation model based on the Fuzzy Delphi Method (FDM) and Analytical Network Process (ANP) were then used to consider both the interdependence among measures and the fuzziness of subjective measures in SSCM.

Findings

The results of this study indicate that the top-ranking aspect to consider is that of stakeholders, and the top five criteria are green design, corporate sustainability, strategic planning for environmental management, supplier cost-saving initiatives and market share.

Originality/value

The main contributions of this study are twofold. First, this paper provides valuable support for supply chain stakeholders regarding the nature of network hierarchical relations with qualitative and quantitative scales. Second, this paper improves practical performance and enhances management effectiveness for SSCM.

Details

Industrial Management & Data Systems, vol. 115 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

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Article
Publication date: 21 September 2015

Yu-Wei Chang, Ping-Yu Hsu, Wen-Lung Shiau and Ronghua Yi

The purpose of this paper is to investigate how customer power of environmental factors affects customer support (CS) engineers’ personal motivations in a…

Abstract

Purpose

The purpose of this paper is to investigate how customer power of environmental factors affects customer support (CS) engineers’ personal motivations in a knowledge-sharing context. The authors examine extrinsic (i.e. organizational rewards, reputation, and reciprocity) and intrinsic motivations (i.e. knowledge self-efficacy) affecting knowledge-sharing intentions based on the social exchange theory (SET) and self-efficacy theory. Furthermore, the authors introduce the concept of the social power theory to investigate the moderating effect of customer power on the relationships between personal motivations and knowledge-sharing intentions.

Design/methodology/approach

This study collects 349 questionnaires of CS engineers from 16 countries, including the USA, China, Japan, South Korea, and Taiwan. After the data collection, the research model and hypotheses are tested using partial least squares.

Findings

The empirical results show that reputation, reciprocity, and knowledge self-efficacy are significantly and positively related to knowledge-sharing intentions. Also, the results show that customer power can significantly moderate the relationships between personal motivations and knowledge-sharing intentions.

Research limitations/implications

The findings help multinational corporations employ the perception of customer power to motivate CS engineers to share knowledge. Especially, the results can help organizations increase customer added value through effective knowledge sharing.

Originality/value

The research model integrates personal motivations derived from the SET and self-efficacy theory and customer power of environmental factors. Additionally, this study is the first to investigate the moderating effect of customer power on employees’ personal motivations and behavioral intentions.

Details

Aslib Journal of Information Management, vol. 67 no. 5
Type: Research Article
ISSN: 2050-3806

Keywords

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Article
Publication date: 16 August 2019

Chih-Ming Chen, Jung-Ying Wang and Yu-Chieh Lin

Developing attention-aware systems and interfaces based on eye tracking technology could revolutionize mainstream human–computer interaction to make the interaction…

Abstract

Purpose

Developing attention-aware systems and interfaces based on eye tracking technology could revolutionize mainstream human–computer interaction to make the interaction between human beings and computers more intuitive, effective and immersive than can be achieved traditionally using a computer mouse. This paper aims to propose an eye-controlled interactive reading system (ECIRS) that uses human eyes instead of the traditional mouse to control digital text to support screen-based digital reading.

Design/methodology/approach

This study uses a quasi-experimental design to examine the effects of an experimental group and a control group of learners who, respectively, used the ECIRS and a mouse-controlled interactive reading system (MCIRS) to conduct their reading of two types of English-language text online – pure text and Q&A-type articles on reading comprehension, cognitive load, technology acceptance, and reading behavioural characteristics. Additionally, the effects of learners with field-independent (FI) and field-dependence (FD) cognitive styles who, respectively, used the ECIRS and MCIRS to conduct their reading of two types of English-language text online – pure text and Q&A-type articles on reading comprehension are also examined.

Findings

Analytical results reveal that the reading comprehension of learners in the experimental group significantly exceeded those in the control group for the Q&A article, but the difference was insignificant for the pure text article. Moreover, the ECIRS improved the reading comprehension of field-independent learners more than it did that of field-dependent learners. Moreover, neither the cognitive loads of the two groups nor their acceptance of the technology differed significantly, whereas the reading time of the experimental group significantly exceeded that of the control group. Interestingly, for all articles, the control group of learners read mostly from top to bottom without repetition, whereas most of the learners in the experimental group read most paragraphs more than once. Clearly, the proposed ECIRS supports deeper digital reading than does the MCIRS.

Originality/value

This study proposes an emerging ECIRS that can automatically provide supplementary information to a reader and control a reading text based on a reader’s eye movement to replace the widely used mouse-controlled reading system on a computer screen to effectively support digital reading for English language learning. The implications of this study are that the highly interactive reading patterns of digital text with ECIRS support increase motivation and willingness to learn while giving learners a more intuitive and natural reading experience as well as reading an article online with ECIRS support guides learners’ attention in deeper digital reading than does the MCIRS because of simultaneously integrating perceptual and cognitive processes of selection, awareness and control based on human eye movement.

Details

The Electronic Library , vol. 37 no. 4
Type: Research Article
ISSN: 0264-0473

Keywords

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