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Article
Publication date: 6 September 2019

Ani Dong, Zusheng Zhang and Jiaming Chen

Magnetic sensors have recently been proposed for parking occupancy detection. However, there has adjacent interference problem, i.e. the magnetic signal is easy to be…

Abstract

Purpose

Magnetic sensors have recently been proposed for parking occupancy detection. However, there has adjacent interference problem, i.e. the magnetic signal is easy to be interfered by the vehicles which are parking on adjacent spaces. The purpose of this paper is to propose a sensing algorithm to eliminate the adjacent interference.

Design/methodology/approach

The magnetic signals are converted to the pattern representation sequences, and the similarity is calculated using the pattern distance. The detection algorithm includes two levels: local decision and data fusion. In the local decision level, the sampled signals can be divided into three classes: vacant, occupied and uncertain. Then a collaborative decision is used to fusion the signals which belong to the uncertain class for the second level.

Findings

An experiment system included 60 sensor nodes that were deployed on bay parking spaces. Experiment results show that the proposed algorithm has better detection accuracy than existing algorithms.

Originality/value

This paper proposes a data fusion algorithm to eliminate adjacent interference. To balance the energy consumption and detection accuracy, the algorithm includes two levels: local decision and data fusion. In most of cases, the local decision can obtain the accurate detection result. Only the signals that cannot be correctly detected at the local level need data fusion operation.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 4
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 19 June 2019

Yihao Lai, Wei-Shih Chung and Jiaming Chen

This paper aims to apply the heterogeneous autoregressive model of realized volatility (HAR-RV) model to minimum-variance hedge ratio estimation and compares the hedging…

Abstract

Purpose

This paper aims to apply the heterogeneous autoregressive model of realized volatility (HAR-RV) model to minimum-variance hedge ratio estimation and compares the hedging performance of presenting a model with that of a conventional rolling ordinary-least-square (OLS) hedging model. Moreover, this paper empirically analyzes the relationship between hedging performance and the heterogeneity of investors with different trading frequency in forming the expectation for the spot volatility, futures volatility and the covariance in the market.

Design/methodology/approach

Use HAR-RV to form expectations of participants of spots and futures market for the next period volatility based on two parts. One is the current observable realized volatility at the same time scale. The other is the expectation for the next longer time scale horizon volatility. Compare hedging performance with rolling OLS model and HAR-RV model. Present a three-times-scale-length (daily, weekly and monthly) HAR-RV model for the spot and futures returns and volatility to analyze the relationship between the hedging performance and the heterogeneity among participants in each market.

Findings

The empirical results show that HAR-RV model outperforms the rolling OLS in terms of variance reduction and expected utility in the out-of-sample period. The results also indicate that the greater variance reduction occurs when investors with different trading frequency have a less heterogeneous expectation for spot volatility and more heterogeneous expectation for futures volatility and the covariance. In addition, the expected utility increases along with lower heterogeneity in spot volatility and higher in futures volatility and the covariance. Hedging performance improves along with decreasing heterogeneity of investors in spot volatility and increasing heterogeneity in futures volatility and the covariance.

Originality/value

This paper considers the heterogeneity of participants in spot and futures market, the authors apply HAR-RV model to MVHR estimation and compare the hedging performance of presenting a model with that of conventional rolling OLS hedging model, providing more evidence in hedging literature. This paper analyzes in depth the relationship between hedging performance and the heterogeneity in the market.

Details

Studies in Economics and Finance, vol. 36 no. 3
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 18 March 2020

Jiaming Zhang and Xiangrong Deng

This study aims to empirically analyze how interest rate liberalization affects bank liquidity creation, and investigate whether the relationship between them is linear.

Abstract

Purpose

This study aims to empirically analyze how interest rate liberalization affects bank liquidity creation, and investigate whether the relationship between them is linear.

Design/methodology/approach

Based on panel data on 145 banks in China over the period 1997–2015, this paper regresses the econometric model by conducting feasible generalized least square estimation.

Findings

The regression results show that, first, interest rate liberalization has a nonlinear impact on bank liquidity creation, and the relationship between them is inverted U-shaped. In other words, as interest rate liberalization progresses, bank liquidity creation increases first, and then decreases. Second, through the mediation effect tests, this study found that interest rate liberalization affects bank liquidity creation through bank risk-taking. That is, interest rate liberalization leads to changes in bank risk-taking, thus resulting in changes in bank liquidity creation.

Research limitations/implications

The effect of interest rate liberalization on bank liquidity creation is nonlinear, so promoting interest rate liberalization faces a trade-off because excessive bank liquidity creation may lead to asset price bubbles, while insufficient bank liquidity creation may inhibit economic growth.

Practical implications

Interest rate liberalization has a significant impact on bank liquidity creation; therefore, bank liquidity creation should be added to the objective function of the regulator that determines interest rate liberalization reform in China.

Social implications

Interest rate liberalization has a direct impact on bank risk-taking, so the consequences of interest rate liberalization should be included in the framework of macro-prudential supervision.

Originality/value

Interest rate liberalization is one of the most important financial reforms in China, yet its potential impact on firm-level bank liquidity is little explored. This paper attempts to fill the gap.

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Article
Publication date: 19 June 2017

Jiaming Liu, Chong Wu and Tianyi Su

The purpose of this paper is to discuss the role of reference effect on newsvendor’s decision behavior in a market with strategic customers and work out the newsvendor’s…

Abstract

Purpose

The purpose of this paper is to discuss the role of reference effect on newsvendor’s decision behavior in a market with strategic customers and work out the newsvendor’s optimal pricing policy and ordering quantity.

Design/methodology/approach

This study utilizes the prospect theory and strategic customer framework to analyze the decision-making behavior on the newsvendor’s optimal pricing policy and ordering quantity. The paper further presents an extension of newsvendor model and provides the model’s properties. The paper finally analyzes the results with various parameters on the model and reports on the insights generated by the model.

Findings

The paper indicates that the ordering quantity is not altered with the changing proportion of strategic customers and myopic customers, but the ordering quantity and the pricing strategy are influenced in terms of newsvendor’s reference effect, loss aversion, product cost, and salvage price.

Practical implications

The research findings have important implications for decision makers. Previous researches have studied the incomplete rationality newsvendor’s decision-making behavior mainly by analyzing the vendor’s risk preferences or loss aversion, but the effect of reference point also plays an important role in analyzing the decision-maker’s behavior. The paper provides the optimal pricing policy and ordering quantity with the reference effect considering the strategic customers behavior. This model is also a valid complementarity to behavioral operations management research area.

Originality/value

The paper examines the role of reference effect in newsvendor problem with the strategic customers and analyzes the impact of parameters such as loss aversion on the newsvendor’s decision behavior.

Details

Management Decision, vol. 55 no. 5
Type: Research Article
ISSN: 0025-1747

Keywords

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Article
Publication date: 7 July 2020

Jiaming Liu, Liuan Wang, Linan Zhang, Zeming Zhang and Sicheng Zhang

The primary objective of this study was to recognize critical indicators in predicting blood glucose (BG) through data-driven methods and to compare the prediction…

Abstract

Purpose

The primary objective of this study was to recognize critical indicators in predicting blood glucose (BG) through data-driven methods and to compare the prediction performance of four tree-based ensemble models, i.e. bagging with tree regressors (bagging-decision tree [Bagging-DT]), AdaBoost with tree regressors (Adaboost-DT), random forest (RF) and gradient boosting decision tree (GBDT).

Design/methodology/approach

This study proposed a majority voting feature selection method by combining lasso regression with the Akaike information criterion (AIC) (LR-AIC), lasso regression with the Bayesian information criterion (BIC) (LR-BIC) and RF to select indicators with excellent predictive performance from initial 38 indicators in 5,642 samples. The selected features were deployed to build the tree-based ensemble models. The 10-fold cross-validation (CV) method was used to evaluate the performance of each ensemble model.

Findings

The results of feature selection indicated that age, corpuscular hemoglobin concentration (CHC), red blood cell volume distribution width (RBCVDW), red blood cell volume and leucocyte count are five most important clinical/physical indicators in BG prediction. Furthermore, this study also found that the GBDT ensemble model combined with the proposed majority voting feature selection method is better than other three models with respect to prediction performance and stability.

Practical implications

This study proposed a novel BG prediction framework for better predictive analytics in health care.

Social implications

This study incorporated medical background and machine learning technology to reduce diabetes morbidity and formulate precise medical schemes.

Originality/value

The majority voting feature selection method combined with the GBDT ensemble model provides an effective decision-making tool for predicting BG and detecting diabetes risk in advance.

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Article
Publication date: 28 October 2014

Chao Wen, Victor R. Prybutok, Charles Blankson and Jiaming Fang

The purpose of this paper is to develop and test an empirically grounded comprehensive framework of e-quality that is the composite of the relationship between…

Abstract

Purpose

The purpose of this paper is to develop and test an empirically grounded comprehensive framework of e-quality that is the composite of the relationship between e-satisfaction and e-loyalty. This study’s objectives were: first, to develop a comprehensive measurement scale of perceived quality from an operations perspective, based on the classic Engel-Kollat-Blackwell (EKB) decision-making process; second, to develop a framework that integrates dimensions of quality and measures perceptions of e-quality during the customer’s decision-making process; and third, to examine the predictive capability of quality attributes in relation to service operations that rely on customer satisfaction and customer loyalty.

Design/methodology/approach

Following review of the related literature, focus group protocols were developed and interviews conducted. Based on the focus group input, surveys were developed and administered. Survey data from 717 online customers allowed testing the research hypotheses, and structural equation modeling allowed validation of the research framework.

Findings

The study determined that “e-channel quality”, “e-service quality” (including “web site quality” and “transaction quality”), and “product quality” positively influence customer e-satisfaction within an online operation. These constructs, in turn, influence customer e-loyalty in the e-commerce domain. The findings contribute valuable theoretical and managerial implications that can improve e-service operations.

Originality/value

The paper fills a relevant gap in the e-commerce and services operations literature by empirically developing and validating a new and robust quality measurement scale based on the EKB consumer decision-making process. The study also makes an important research contribution by providing empirical evidence that quality is pivotal in gaining customer loyalty and a competitive e-commerce edge.

Details

International Journal of Operations & Production Management, vol. 34 no. 12
Type: Research Article
ISSN: 0144-3577

Keywords

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Article
Publication date: 24 May 2018

Jiaming Han, Zhong Yang, Guoxiong Hu, Ting Fang and Hao Xu

This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.

Abstract

Purpose

This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.

Design/methodology/approach

The proposed method includes two main stages: drivable region estimation and vanishing point detection. In drivable region estimation stage, the road image is segmented into a set of patches; then the drivable region is estimated by the patch-wise manifold ranking. In vanishing point detection stage, the LSD method is used to extract the straight lines; then a series of principles are proposed to remove the noise lines. Finally, the vanishing point is detected by a novel voting strategy.

Findings

The proposed method is validated on various unstructured road images collected from the real world. It is more robust and more efficient than the state-of-the-art method and the other three recent methods. Experimental results demonstrate that the detected vanishing point is practical for vision-sensor-based navigation in complex unstructured road scenes.

Originality/value

This paper proposes a patch-wise manifold ranking method to estimate the drivable region that contains most of the informative clues for vanishing point detection. Based on the removal of the noise lines through a series of principles, a novel voting strategy is proposed to detect the vanishing point.

Details

Sensor Review, vol. 39 no. 1
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 15 August 2008

Coen Heijes

The purpose of this paper is to define and test a supplier selection model for Chinese and foreign banks in China.

Abstract

Purpose

The purpose of this paper is to define and test a supplier selection model for Chinese and foreign banks in China.

Design/methodology/approach

In total, 12 reasons affecting customers' choice in selecting Chinese or foreign banks are developed and their respective importance are tested through 2,000 questionnaires which were distributed over the city‐zones of Hangzhou.

Findings

Supplier performance in terms of responsiveness is of particular importance in preferring foreign banks, which are seen to have an advantage in terms of professionalism, innovation and client‐orientation. For Chinese banks only one selection reason belongs to an inherent advantage, a large and convenient network, with the other reasons deriving from government's protection and historical conditions. Surprisingly, cultural aspects such as “guanxi” or personal relationship are only of minor importance.

Research limitations/implications

Differentiates customers only by way of age and salary and focuses on the eastern urban population. Another shortcoming is the lack of extended qualitative research.

Practical implications

With the transition of the market for financial services in China customers will have increasing options to choose between Chinese and foreign banks. This paper offers valuable information regarding customer selection processes in China.

Originality/value

With most cross‐comparative research based on standard cultural dimensions, this study focuses on specific behaviour of Chinese customers in selecting services with Chinese or foreign banks, finding cross‐national differences to be less important than the characteristics of the specific market or product. This work also adds to the ongoing research agenda concerning Chinese customers' behaviour and Chinese banking.

Details

Chinese Management Studies, vol. 2 no. 3
Type: Research Article
ISSN: 1750-614X

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Article
Publication date: 10 August 2020

Jörg Finsterwalder and Volker G. Kuppelwieser

This article explores the impact of crises, such as the coronavirus pandemic, on service industries, service customers, and the service research community. It…

Abstract

Purpose

This article explores the impact of crises, such as the coronavirus pandemic, on service industries, service customers, and the service research community. It contextualizes pandemics in the realm of disasters and crises, and how they influence actors' well-being across the different levels of the service ecosystem. The paper introduces a resources–challenges equilibrium (RCE) framework across system levels to facilitate service ecosystem well-being and outlines a research agenda for service scholars.

Design/methodology/approach

Literature on disasters, crises, service and well-being is synthesized to embed the COVID-19 pandemic in these bodies of work. The material is then distilled to introduce the novel RCE framework for service ecosystems, and points of departure for researchers are developed.

Findings

A service ecosystems view of well-being co-creation entails a dynamic interplay of actors' challenges faced and resource pools available at the different system levels.

Research limitations/implications

Service scholars are called to action to conduct timely and relevant research on pandemics and other crises, that affect service industry, service customers, and society at large. This conceptual paper focuses on service industries and service research and therefore excludes other industries and research domains.

Practical implications

Managers of service businesses as well as heads of governmental agencies and policy makers require an understanding of the interdependence of the different system levels and the challenges faced versus the resources available to each individual actor as well as to communities and organizations.

Social implications

Disasters can change the social as well as the service-related fabric of society and industry. New behaviors have to be learned and new processes put in place for society to maintain well-being and for service industry's survival.

Originality/value

This paper fuses the coronavirus pandemic with service and well-being research, introduces a resources-challenges equilibrium framework for service ecosystem well-being and outlines a research agenda.

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Article
Publication date: 21 June 2021

Abdulqadir Rahomee Ahmed Aljanabi

This conceptual paper aims to provide a further understanding of the impact of economic policy uncertainty (EPU), news framing and information overload on panic buying…

Abstract

Purpose

This conceptual paper aims to provide a further understanding of the impact of economic policy uncertainty (EPU), news framing and information overload on panic buying behavior during the COVID-19 pandemic.

Design/methodology/approach

Drawing on earlier research and news releases about the COVID-19 outbreak, this paper advances testable propositions based on the protection motivation theory and information processing theory.

Findings

This paper infers that the major shift in consumer decision-making towards panic buying is a result of high EPU. International reports have contributed to deepening this uncertainty, and the consequences of this EPU are expected to affect the economic recovery through 2022. Furthermore, the adoption of particular frames of the pandemic has played a key role in the dissemination of misinformation and fake news during the public health crisis and affected purchasing decisions. The study also infers that the perceived threat among consumers is driven by information overload as a source of mistrust towards economic and health information sources.

Originality/value

This paper addresses two theoretical gaps associated with consumer buying behaviour. First, it highlights the impact of EPU, as a macroeconomic indicator, on consumer buying behaviour. Second, this paper is an attempt to integrate theories from different disciplines to foster an adequate understanding of buying behavior during the COVID-19 outbreak period.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

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