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Article
Publication date: 1 July 2011

Jiang Wei, Xiao Min and You Jiaxing

The purpose of this paper is to empirically analyze the effects of managerial overconfidence on debt maturity structure decisions in terms of liquidity risk and asset…

1320

Abstract

Purpose

The purpose of this paper is to empirically analyze the effects of managerial overconfidence on debt maturity structure decisions in terms of liquidity risk and asset match in Chinese listed companies.

Design/methodology/approach

Combining data from CSMAR with some default data collected by hand, this paper selects age, tenure, education, education background and whether the board chair and CEO positions are consolidated in Chinese listed companies as proxies of managerial overconfidence. Thus, the authors acquired needed and credible empirical data.

Findings

It was found that, the younger the CEO, the shorter the tenure, the lower the education, having economics or management education and being chairman concurrently, CEOs have stronger managerial overconfidence. Thus, corporate debt maturity structure is more weakly correlated with debt ratio and asset structure.

Research limitations/implications

The findings in this study suggest that managerial irrationality, especially overconfidence, does have an effect on the financing decisions of firms.

Originality/value

This is the first paper to analyze the effects of managerial overconfidence on debt maturity structure decisions in terms of liquidity risk and asset match. The findings inspire firm risk management policies from managerial overconfidence.

Details

China Finance Review International, vol. 1 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

Case study
Publication date: 1 January 2011

Lee Zhuang

Business management, entrepreneurship, strategic management and business environment.

Abstract

Subject area

Business management, entrepreneurship, strategic management and business environment.

Study level/applicability

Undergraduate and Masters level business and management programmes.

Case overview

This case features a small labour intensive Chinese company, Bags of Luck (BoL), located in the south-eastern Fujian province. BoL makes ladies fashion handbags, unisex fashion backpacks and trendy lightweight cases for laptop and netbook computers for export to the US market. BoL have done very well over the years as a small private enterprise focusing on low-tech manufacturing and have managed to stay afloat through the most difficult period of the recent world recession. Currently troubled by fast changing market trends, rising material and employment costs, continuing appreciation of the Chinese currency, severe labour shortage, declining production volume and profitability, dated machinery, passive and reactive nature of business model, ineffective management structure and a complete lack of strategic vision, BoL is in deep crisis with its fate now hanging on the balance.

Expected learning outcomes

The case provides encourages students to: research into a range of current business management issues; analyse the impact of environmental changes on the survival and growth of a business organisation; develop their strategic thinking informed by real life and real-time research and assess the impact of exchange rate changes on the Chinese economy and the sustainability of Chinese model of economic growth.

Supplementary materials

Teaching note.

Details

Emerald Emerging Markets Case Studies, vol. 1 no. 1
Type: Case Study
ISSN: 2045-0621

Keywords

Article
Publication date: 29 October 2020

Mu Shengdong, Wang Fengyu, Xiong Zhengxian, Zhuang Xiao and Zhang Lunfeng

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges…

Abstract

Purpose

With the advent of the web computing era, the transmission mode of the Internet of Everything has caused an explosion in data volume, which has brought severe challenges to traditional routing protocols. The limitations of the existing routing protocols under the condition of rapid data growth are elaborated, and the routing problem is remodeled as a Markov decision process. this paper aims to solve the problem of high blocking probability due to the increase in data volume by combining deep reinforcement learning. Finally, the correctness of the proposed algorithm in this paper is verified by simulation.

Design/methodology/approach

The limitations of the existing routing protocols under the condition of rapid data growth are elaborated and the routing problem is remodeled as a Markov decision process. Based on this, a deep reinforcement learning method is used to select the next-hop router for each data transmission task, thereby minimizing the length of the data transmission path while avoiding data congestion.

Findings

Simulation results show that the proposed method can significantly reduce the probability of data congestion and increase network throughput.

Originality/value

This paper proposes an intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era. With the help of deep reinforcement learning, it is possible to dynamically select the transmission jump router according to the current network state, thereby reducing the probability of congestion and improving network throughput.

Details

International Journal of Web Information Systems, vol. 16 no. 5
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 3 February 2021

Beena Kumari, Sangeeta Sahney and Anuradha Madhukar

This paper intends to explore the measure for aligning the goals of researchers toward achieving organizational R&D targets. The paper also explores the significance and…

179

Abstract

Purpose

This paper intends to explore the measure for aligning the goals of researchers toward achieving organizational R&D targets. The paper also explores the significance and ordering of R&D outputs and the factors that influence generation of R&D outputs, from the perspective of researchers working in the Indian public sector organizations.

Design/methodology/approach

Data were collected in five Indian R&D laboratories, and weighted average method Spearman correlation coefficient and rank regression were utilized for the analysis.

Findings

The findings indicated that various groups of researchers prefer to target different R&D outputs and not all the factors are considered as equally significant in influencing the generation of R&D outputs. Further, the R&D organization should include preferred real factors while policy making for achieving collaborative efforts toward fulfilling organizational objectives. The set of selected R&D outputs and influencing factors were also ordered according to the average rankings given by the researchers.

Practical implications

The findings can help R&D managers to identify the expectations of the researchers and include their preferences in R&D Planning. The study could be extended to a larger dataset of researchers working in other government as well as private R&D organizations.

Originality/value

Hardly any studies were found that explored the preferences of researchers with respect to R&D outputs and influencing factors with respect to the Indian public sector R&D laboratories.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 5
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 11 January 2022

Ilesanmi Daniyan, Khumbulani Mpofu and Samuel Nwankwo

The need to examine the integrity of infrastructure in the rail industry in order to improve its reliability and reduce the chances of breakdown due to defects has brought…

Abstract

Purpose

The need to examine the integrity of infrastructure in the rail industry in order to improve its reliability and reduce the chances of breakdown due to defects has brought about development of an inspection and diagnostic robot.

Design/methodology/approach

In this study, an inspection robot was designed for detecting crack, corrosion, missing clips and wear on rail track facilities. The robot is designed to use infrared and ultrasonic sensors for obstacles avoidance and crack detection, two 3D-profilometer for wear detection as well as cameras with high resolution to capture real time images and colour sensors for corrosion detection. The robot is also designed with cameras placed in front of it with colour sensors at each side to assist in the detection of corrosion in the rail track. The image processing capability of the robot will permit the analysis of the type and depth of the crack and corrosion captured in the track. The computer aided design and modeling of the robot was carried out using the Solidworks software version 2018 while the simulation of the proposed system was carried out in the MATLAB 2020b environment.

Findings

The results obtained present three frameworks for wear, corrosion and missing clips as well as crack detection. In addition, the design data for the development of the integrated robotic system is also presented in the work. The confusion matrix resulting from the simulation of the proposed system indicates significant sensitivity and accuracy of the system to the presence and detection of fault respectively. Hence, the work provides a design framework for detecting and analysing the presence of defects on the rail track.

Practical implications

The development and the implementation of the designed robot will bring about a more proactive way to monitor rail track conditions and detect rail track defects so that effort can be geared towards its restoration before it becomes a major problem thus increasing the rail network capacity and availability.

Originality/value

The novelty of this work is based on the fact that the system is designed to work autonomously to avoid obstacles and check for cracks, missing clips, wear and corrosion in the rail tracks with a system of integrated and coordinated components.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

Open Access
Article
Publication date: 17 July 2020

Mukesh Kumar and Palak Rehan

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter…

Abstract

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.

Details

Applied Computing and Informatics, vol. 17 no. 2
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 21 October 2022

Çağatay Özada, Merve Ünal, Eslem Kuzu Şahin, Hakkı Özer, Ali Riza Motorcu and Murat Yazıcı

This study produced epoxy-filled urea-formaldehyde (UF) microcapsules (MCs) and T-403 amine MCs using the in situ technique. The Taguchi method was used to determine the…

Abstract

Purpose

This study produced epoxy-filled urea-formaldehyde (UF) microcapsules (MCs) and T-403 amine MCs using the in situ technique. The Taguchi method was used to determine the effects of the control factors (temperature, stirring speed, core-shell ratio and surfactant concentration) affecting MCs’ core diameter and core content and optimizing their optimum levels with a single criterion. Optimum control factor levels, which simultaneously provide maximum core diameter and core content of MCs, were determined by the PROMETHEE-GAIA multi-criteria optimization method. In addition, the optimized MC yield was analyzed by thermal camera images and compression test.

Design/methodology/approach

Microcracks in materials used for aerospace vehicles and automotive parts cause serious problems, so research on self-healing in materials science becomes critical. The damages caused by micro-cracks need to heal themselves quickly. The study has three aims: (1) production of self-healing MCs, mechanical and chemical characterization of produced MCs, (2) single-criteria and multi-criteria optimization of parameters providing maximum MC core diameter and core content, (3) investigation of self-healing property of produced MCs and evaluation. Firstly, MCs were produced to achieve these goals.

Findings

The optimized micro cures are buried in the epoxy matrix at different concentrations. Thermal camera images after damage indicate the presence of healing. An epoxy-amine MC consisting of a 10% by weight filled aluminum sandwich panel was prepared and subjected to a quasi-static compression test. It was determined that there is a strong bond between the UF shell and the epoxy resin.

Originality/value

The optimization of production factors has been realized to produce the most efficient MCs that heal using less expensive and more accessible methods.

Details

Multidiscipline Modeling in Materials and Structures, vol. 18 no. 6
Type: Research Article
ISSN: 1573-6105

Keywords

Open Access
Article
Publication date: 1 June 2022

Hua Zhai and Zheng Ma

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages…

Abstract

Purpose

Effective rail surface defects detection method is the basic guarantee to manufacture high-quality rail. However, the existed visual inspection methods have disadvantages such as poor ability to locate the rail surface region and high sensitivity to uneven reflection. This study aims to propose a bionic rail surface defect detection method to obtain the high detection accuracy of rail surface defects under uneven reflection environments.

Design/methodology/approach

Through this bionic rail surface defect detection algorithm, the positioning and correction of the rail surface region can be computed from maximum run-length smearing (MRLS) and background difference. A saliency image can be generated to simulate the human visual system through some features including local grayscale, local contrast and edge corner effect. Finally, the meanshift algorithm and adaptive threshold are developed to cluster and segment the saliency image.

Findings

On the constructed rail defect data set, the bionic rail surface defect detection algorithm shows good recognition ability on the surface defects of the rail. Pixel- and defect-level index in the experimental results demonstrate that the detection algorithm is better than three advanced rail defect detection algorithms and five saliency models.

Originality/value

The bionic rail surface defect detection algorithm in the production process is proposed. Particularly, a method based on MRLS is introduced to extract the rail surface region and a multifeature saliency fusion model is presented to identify rail surface defects.

Details

Sensor Review, vol. 42 no. 4
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 24 May 2022

Yi Zhang, Renhuai Liu and Haiquan Chen

This paper aims to answer the following two questions: What are the affecting factors of platform leadership? How do the business ecosystem and unique attributes of…

Abstract

Purpose

This paper aims to answer the following two questions: What are the affecting factors of platform leadership? How do the business ecosystem and unique attributes of platform enterprises affect the formation of platform leadership?

Design/methodology/approach

Based on the niche theory, this study used the grounded theory research methods to explore the strategic behavior of platform enterprises, analyze the characteristics of platform leadership and systematically explore the influencing factors of platform leadership based on four internet platform enterprises and their business ecosystem.

Findings

The result shows that the acquisition of platform leadership is closely related to the platform enterprises’ Niche, where they are located in the business ecosystem. Platform enterprises play the roles of the founder, coordinator, leader and arranger in the ecosystem, and there are four affecting factors of platform leadership: architecture foundation, connection and coordination, innovation leading and integrated expansion. The architecture foundation consists of four factors: platform architecture, installation base, intellectual property and network coverage; the connection and coordination contain five factors: interactive collaboration, multilateral user connection, information matching, neutral arbitration and mutualism; the innovation leading is composed of four factors: research and development investment, common components, complementary innovation, cross-border search and standard-setting; the integrated expansion includes resource orchestration, modular design, data collaboration, supportive enabling and scenario application.

Originality/value

This research constructs a framework of platform leadership with the influencing factors.

Details

Nankai Business Review International, vol. 13 no. 3
Type: Research Article
ISSN: 2040-8749

Keywords

Article
Publication date: 7 July 2020

Wai-Chung Ho and Wing-Wah Law

The purpose of this paper is to examine music teachers' perceptions of teaching cultural and national values (also defined as national cultural values) to explore the…

Abstract

Purpose

The purpose of this paper is to examine music teachers' perceptions of teaching cultural and national values (also defined as national cultural values) to explore the tensions facing school music education in the choice of music types to be delivered in Hong Kong and Taiwan.

Design/methodology/approach

With specific regard to music teachers' perceptions of “values,” “music cultures” and “nationalism,” data were drawn from a survey questionnaire given to 343 music teachers (155 preservice and 188 in-service music teachers) and semistructured interviews with 36 of these respondents.

Findings

The findings of the study showed that though many respondents in Hong Kong and Taiwan felt comfortable teaching traditional Chinese music, they did not want to teach contemporary Mainland Chinese music and other political or patriotic forms in the school music curriculum. The data also demonstrated some shortcomings in introducing a balance of music types into the curriculum, as well as limitations in promoting national education in response to the respective sociopolitical situations in Hong Kong and Taiwan.

Research limitations/implications

This study was subject to limitations regarding the potential generalizability of the findings on school music teachers' perceptions in Hong Kong and Taiwan.

Practical implications

The implications for teachers and student teachers regarding the development of cultural and national values related to the political processes in Hong Kong and Taiwan are complicated, because of not only their relationship with Mainland China and its education based on nationalism but also the extent of teachers' professional training to help create an enabling environment for national and cultural development.

Originality/value

The findings of this study revealed that there are fundamental gaps in the overt and operational curricula in Hong Kong and Taiwan concerning the sociopolitical function of values in school music education in response to their respective sociopolitical situations.

Details

International Journal of Comparative Education and Development, vol. 22 no. 3
Type: Research Article
ISSN: 2396-7404

Keywords

1 – 10 of over 2000