Hsu-Che Wu and Yu-Ting Wu
An increasing number of investors have begun using financial data to develop optimal investment portfolios; therefore, the public financial data shared in the capital market plays…
Abstract
Purpose
An increasing number of investors have begun using financial data to develop optimal investment portfolios; therefore, the public financial data shared in the capital market plays a critical role in credit ratings. These data enable investors to understand the credit levels of debtors from a bank perspective; this facilitates predicting the debtor default rate to efficiently evaluate investment risks. The paper aims to discuss these issues.
Design/methodology/approach
A credit rating model can be developed to reduce the risk of adverse selection and moral hazard caused by information asymmetry in the loan market. In this study, a random forest (RF) was used to evaluate financial variables and construct credit rating prediction models. Data-mining techniques, including an RF, decision tree, neural networks, and support vector machine, were used to search for suitable credit rating forecasting methods. The distance to default from the KMV model was then incorporated into the credit rating model as a research variable to increase predictive power of various data-mining techniques. In addition, four-level and nine-level classification were set to investigate the accuracy rates of various models.
Findings
The experimental results indicated that applying the RF in the variable feature selection process and developing a forecasting model was the most effective method of predicting credit ratings; the four-level and nine-level feature-selection settings achieved 95.5 and 87.8 percent accuracy rates, respectively, indicating that RF demonstrated outstanding feature selection and forecasting capacity.
Research limitations/implications
The experimental cases were based on financial data from public companies in North America.
Practical implications
Practical implication of this study indicates the most effective financial variables were dividends common/ordinary, cash dividends, volatility assumption, and risk-free rate assumption.
Originality/value
The RF model can be used to perform feature selection and efficiently filter numerous financial variables to obtain crediting rating information instantly.
Details
Keywords
Yu-Ting Cheng and Chih-Ching Yang
Constructing a fuzzy control chart with interval-valued fuzzy data is an important topic in the fields of medical, sociological, economics, service and management. In particular…
Abstract
Purpose
Constructing a fuzzy control chart with interval-valued fuzzy data is an important topic in the fields of medical, sociological, economics, service and management. In particular, when the data illustrates uncertainty, inconsistency and is incomplete which is often the. case of real data. Traditionally, we use variable control chart to detect the process shift with real value. However, when the real data is composed of interval-valued fuzzy, it is not feasible to use such an approach of traditional statistical process control (SPC) to monitor the fuzzy control chart. The purpose of this paper is to propose the designed standardized fuzzy control chart for interval-valued fuzzy data set.
Design/methodology/approach
The general statistical principles used on the standardized control chart are applied to fuzzy control chart for interval-valued fuzzy data.
Findings
When the real data is composed of interval-valued fuzzy, it is not feasible to use such an approach of traditional SPC to monitor the fuzzy control chart. This study proposes the designed standardized fuzzy control chart for interval-valued fuzzy data set of vegetable price from January 2009 to September 2010 in Taiwan obtained from Council of Agriculture, Executive Yuan. Empirical studies are used to illustrate the application for designing standardized fuzzy control chart. More related practical phenomena can be explained by this appropriate definition of fuzzy control chart.
Originality/value
This paper uses a simpler approach to construct the standardized interval-valued chart for fuzzy data based on traditional standardized control chart which is easy and straightforward. Moreover, the control limit of the designed standardized fuzzy control chart is an interval with (LCL, UCL), which consists of the conventional range of classical standardized control chart.
Details
Keywords
Chong Liu, Wanli Xie, Tongfei Lao, Yu-ting Yao and Jun Zhang
Gross domestic product (GDP) is an important indicator to measure a country's economic development. If the future development trend of a country's GDP can be accurately predicted…
Abstract
Purpose
Gross domestic product (GDP) is an important indicator to measure a country's economic development. If the future development trend of a country's GDP can be accurately predicted, it will have a positive effect on the formulation and implementation of the country's future economic development policies. In order to explore the future development trend of China's GDP, the purpose of this paper is to establish a new grey forecasting model with time power term to forecast GDP.
Design/methodology/approach
Firstly, the shortcomings of the traditional grey prediction model with time power term are found out through analysis, and then the generalized grey prediction model with time power term is established (abbreviated as PTGM (1,1, α) model). Secondly, the PTGM (1,1, α) model is improved by linear interpolation method, and the optimized PTGM (1,1, α) model is established (abbreviated as OPTGM (1,1, α) model), and the parameters of the OPTGM (1,1, α) model are solved by the quantum genetic algorithm. Thirdly, the advantage of the OPTGM (1,1, α) model over the traditional grey models is illustrated by two real cases. Finally the OPTGM (1,1, α) model is used to predict China's GDP from 2020 to 2029.
Findings
The OPTGM (1,1, α) model is more suitable for predicting China's GDP than other grey prediction models.
Originality/value
A new grey prediction model with time power term is proposed.
Details
Keywords
Wei‐Wen Wu, Lawrence W. Lan and Yu‐Ting Lee
The aim of this paper is to propose a novel evaluation framework to explore the “root causes” that hinder the acceptance of using internal cloud services in a university.
Abstract
Purpose
The aim of this paper is to propose a novel evaluation framework to explore the “root causes” that hinder the acceptance of using internal cloud services in a university.
Design/methodology/approach
The proposed evaluation framework incorporates the duo‐theme DEMATEL (decision making trial and evaluation laboratory) with TAM (technology acceptance model). The operational procedures were proposed and tested on a university during the post‐implementation phase after introducing the internal cloud services.
Findings
According to the results, clear understanding and operational ease under the theme perceived ease of use (PEOU) are more imperative; whereas improved usefulness and productivity under the theme perceived usefulness (PU) are more urgent to foster the usage of internal clouds in the case university.
Research limitations/implications
Based on the findings, some intervention activities were suggested to enhance the level of users' acceptance of internal cloud solutions in the case university. However, the results should not be generalized to apply to other educational establishments.
Practical implications
To reduce the resistance from using internal clouds, some necessary intervention activities such as developing attractive training programs, creating interesting workshops, and rewriting user friendly manual or handbook are recommended.
Originality/value
The novel two‐theme DEMATEL has greatly contributed to the conventional one‐theme DEMATEL theory. The proposed two‐theme DEMATEL procedures were the first attempt to evaluate the acceptance of using internal clouds in university. The results have provided manifest root‐causes under two distinct themes, which help derive effectual intervention activities to foster the acceptance of usage of internal clouds in a university.
Details
Keywords
Jack Shih-Chieh Hsu, Chao-Min Chiu, Yu-Ting Chang-Chien and Kingzoo Tang
Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been…
Abstract
Purpose
Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.
Design/methodology/approach
The authors designed and conducted a survey to collect data from social networking platform users.
Findings
Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.
Originality/value
This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.
Details
Keywords
Yu-Ting L.V., Yong Li, De-Xing Yang, Zhenhua Bai, Jinlong Li and Rui Wang
Continuous annealing (CA) units usually lack a physical shapemeter; consequently, real-time display and closed-loop control of the strip shape are impossible to achieve.
Abstract
Purpose
Continuous annealing (CA) units usually lack a physical shapemeter; consequently, real-time display and closed-loop control of the strip shape are impossible to achieve.
Design/methodology/approach
A shape model for the CA process is established in this study. Specifically, a virtual shapemeter and closed-loop control system based on the advanced parameter acquisition system and information transmission of CA units are developed in C++ programming language. This system realises real-time dynamic shape display, closed-loop control and shape prediction by collecting raw data of steel coils and parameters during CA.
Findings
Field test results show that the shape predicted by the virtual shapemeter coincides with the measured shape by over 90 per cent, which fully meets the precision requirement of industrial applications.
Originality/value
Moreover, shape quality is effectively improved without increasing hardware investments.
Details
Keywords
Yu-Hsiang Hsiao and Yu-Ting Hsiao
This study was to develop a methodology of online review analytics for hotel quality management at macro and micro levels. The macro level was for understanding the service…
Abstract
Purpose
This study was to develop a methodology of online review analytics for hotel quality management at macro and micro levels. The macro level was for understanding the service properties critical to quality and future development. The micro level was for personalized quality diagnosis for individual hotels.
Design/methodology/approach
Textual reviews of superior hotels were studied using latent semantic analysis and Kano model to understand what service properties customers concern and expect. Taguchi's quality engineering was applied to establish a quality reference base using superior hotels for evaluating other hotels in the same semantic space. A decision tree algorithm was then used to identify the properties critical to quality discrimination, and the decision rules were used to diagnose individual hotels.
Findings
The service properties concerned by customers for superior hotels were identified. The market positioning and value of each property to customers were clarified. For individual hotels, the deficiencies of service properties were diagnosed. With reference to market positioning, deficient properties of priority in improvement and the strategies for enhancing competitiveness were suggested.
Originality/value
The proposed methodology demonstrated the potential value that review analysis can achieve a new and deeper understanding of customer voices and transform it into more specific business operation requirements. The research and application gap that most previous studies only stayed at the macro-level analytics was filled. Moreover, this study effectively applied the diagnostic techniques derived from quality engineering to online review analytics.
Details
Keywords
For decades, consumer identification and motivation, either alone or jointly, have been essential constructs for behavioral researchers. The resultant output is significant in…
Abstract
Purpose
For decades, consumer identification and motivation, either alone or jointly, have been essential constructs for behavioral researchers. The resultant output is significant in terms of both quality and quantity. However, at a deeper level, a lack of conceptual clarity in the relationship between these constructs has led to theoretical and practical irregularities, which this study aims to address.
Design/methodology/approach
An online questionnaire was distributed to sport consumers aged over 18 participating in an online panel, prompted 293 completed responses. Structural equations modeling was used to examine the data.
Findings
Findings show that identification mediates the effects of intrinsic and extrinsic motivation on sport supporters’ loyalty and explain 90% of the variance in that construct. In addition, identification mediates the adverse effects of extrinsic motivation on loyalty and strengthens loyalty when levels of satisfaction decline.
Originality/value
This study extends previous work by providing a theoretical perspective that clarifies the relationship between motivation and consumer identification; deepens theory by empirically observing the relationship at different levels of consumer satisfaction; and presents a parsimonious, valid and reliable method that managers can leverage to strengthen sport supporters’ loyalty.
Details
Keywords
Edward Shih-Tse Wang, Hung-Chou Lin and Yu-Ting Liao
The paper focuses on social capital as the characteristic of social groups that promote coordination; moreover, social identity plays a key role in the construction of group…
Abstract
Purpose
The paper focuses on social capital as the characteristic of social groups that promote coordination; moreover, social identity plays a key role in the construction of group relationships. However, few research studies have looked at how the social capital of social networking sites (SNSs) is related to the social identity of its members. Drawing on social capital and social identity theory, this study investigated the effects of SNS social capital (shared language, social trust and network density) on social identity and continuous participation. The mediating role of social identity was also investigated.
Design/methodology/approach
In total, 444 SNS members volunteered to participate in this study. Structural equation modeling was applied to analyze a conceptual model.
Findings
The results revealed that SNS social trust and network density directly and significantly affected the social identity and continuous participation behavior of members. SNSs using a shared language positively affected social identity, but this was not directly associated with continuous participation behavior.
Originality/value
Because the network externalities of SNSs exert critical effects on user benefits, attracting continuous user participation remains one of the critical challenges for SNS administrators. Both the theoretical and practical implications of this study can aid SNS administrators in developing effective continuous participation strategies.
Peer review
The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2021-0369
Details
Keywords
Wei‐Wen Wu, Lawrence W. Lan and Yu‐Ting Lee
The purpose of this paper is to propose a benchmarking framework to evaluate the efficiency and effectiveness of the hotel industry, in a multi‐period context, with consideration…
Abstract
Purpose
The purpose of this paper is to propose a benchmarking framework to evaluate the efficiency and effectiveness of the hotel industry, in a multi‐period context, with consideration of perishable traits and carry‐over activities. The sustained high performers in the case study are identified and their business strategies are discussed.
Design/methodology/approach
The dynamic DEA (data envelopment analysis) approach is used to identify the multi‐period sustained high performers. The super‐efficiency DEA approach is employed to conduct a thorough ranking under an input‐output‐consumption structure. The supplementary analysis is further implemented to help elucidate the benchmarking results.
Findings
In total, nine out of 80 international tourist hotels in Taiwan during 2006‐2010 are identified as the sustained high performers. These hotels have diverged business strategies in terms of employees (intensive versus economical labor forces), products (room versus F&B (food and beverage) services), prices (extremely expensive versus very inexpensive room rates), guests (business versus tourism guests), and others (e.g. location advantages).
Originality/value
This study contributes to benchmarking literature and to hotel industry in several aspects. Compared with conventional single‐period benchmarking in efficiency aspect only, the proposed multi‐period benchmarking framework under input‐production‐consumption structure can take into account the carry‐over activities, account for perishable traits, provide more robust results, and add more useful information to facilitate the hotel managers to ameliorate the efficiency and effectiveness. The proposed framework should be readily applied to other service industries (e.g. transport).