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1 – 10 of 98Korbkul Jantarakolica and Tatre Jantarakolica
The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of…
Abstract
The rapid change of technology has significantly affected the financial markets in Thailand. In order to enhance the market efficiency and liquidity, the Stock Exchange of Thailand (SET) has granted Thai stock brokers permission to develop and offer their customers algorithm and automatic stock trading. However, algorithm trading on SET was not widely adopted. This chapter intends to design and empirically estimate a model in explaining Thai investors’ acceptance of algorithm trading. The theoretical framework is based on the theory of reasoned action and technology acceptance model (TAM). A sample of 400 investors who have used online stock trading and 300 investors who have used algorithm stock trading were observed and analyzed using structural equations model (SEM) and generalized linear regression model (GLM) with a Logit specification. The results confirm that attitudes, subjective norm, perceived risks, and trust toward algorithm stock trading are factors determining investors’ behavior and acceptance of using algorithm stock trading. Investor’s perception and trust on algorithm stock trading as a trading strategy is a major factor in determining their perceived behavior and control, which affect their decision on whether to invest using algorithm trading. Accordingly, it can be concluded that Thai investors is willing to accept algorithm trading as a new financial technology, but still has concern about the reliability and profitable of this new stock trading strategy. Therefore, algorithm trading can be promoted by building investors’ trust on algorithm trading as a reliable and profitable trading strategy.
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This study aims to examine the effects of audit quality on earnings management and cost of equity capital (COE) considering the impact of two owner types: government ownership and…
Abstract
Purpose
This study aims to examine the effects of audit quality on earnings management and cost of equity capital (COE) considering the impact of two owner types: government ownership and foreign ownership.
Design/methodology/approach
The study uses a panel data set of 236 Vietnamese firms covering the period 2007 to 2017. Because the two main dependent variables of the COE capital and the absolute value of discretionary accruals receive fractional values between zero and one, the paper uses the generalised linear model (GLM) with a logit link and the binomial family in regression analyses. The paper uses numerous audit quality measures, including hiring Big 4 auditors or the industry-leading Big 4 auditor, changing from non-Big 4 auditors to Big 4 auditors or the industry-leading Big 4 auditor, and the length of Big 4 auditor tenure. Big 4 companies include KPMG, Deloitte, EY and PwC, whereas the non-big 4 are the other audit companies.
Findings
The study finds a negative relationship between audit quality and both the COE capital and income-increasing discretionary accruals. The effects of audit quality on discretionary accruals and the COE capital depend on the ownership levels of two important shareholders: the government and foreign investors. Foreign ownership is negatively associated with discretionary accruals; however, the effect is more pronounced in the sub-sample of state-owned enterprises (SOEs), the firms where the government owns 50% or more equity, than in the sub-sample of Non-SOEs.
Originality/value
To the best of the knowledge, no prior similar study exists that used the GLM with a logit link and the binomial family regression. Global investors may be interested in understanding how unique institutional settings and capital markets of each country impact the financial reporting quality and cost of capital. Further, policymakers of developing markets may have incentives to improve the quality of financial reporting and reduce the cost of capital which should result in attracting more foreign investments.
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Mao-Feng Kao, Lynn Hodgkinson and Aziz Jaafar
Using a data set of Taiwanese listed firms from 2002 to 2015, this paper aims to examine the determinants to voluntarily appoint independent directors.
Abstract
Purpose
Using a data set of Taiwanese listed firms from 2002 to 2015, this paper aims to examine the determinants to voluntarily appoint independent directors.
Design/methodology/approach
This study uses panel estimation to exploit both the cross-section and time-series nature of the data. Further, this paper uses Tobit regression, generalized linear model (GLM) in the additional analysis and the two-stage least squares to mitigate for a possible endogeneity issue.
Findings
The main findings show that Taiwanese firms with large board sizes tend to voluntarily appoint independent directors and firms that already have independent supervisors more willingly to accept additional independent directors onto the board. Furthermore, ownership concentration and institutional ownership are positively associated with the voluntary appointment of independent directors. On the contrary, firms controlled by family members are generally reluctant to voluntarily appoint independent directors.
Research limitations/implications
The findings are important for managers, shareholders, creditors and policymakers. In particular, when considering the determinants of the voluntary appointment of independent directors, the results indicate that independent supervisors, outside shareholders and institutional investors are significant factors in influencing effective internal and external corporate governance mechanisms. This research work focuses on the voluntary appointment of independent directors. It would be interesting to compare the effectiveness of voluntary appointments with a mandatory appointment within Taiwan and with other jurisdictions.
Originality/value
This study incrementally contributes to the corporate governance literature in several ways. First, this study extends the earlier research by using a more comprehensive data set of non-financial Taiwanese firms and using alternative methodologies to investigate the determinants of voluntary appointment of independent directors. Second, prior studies tend to neglect the possible issue of using a censored and fractional dependent variable, the proportion of independent directors, which might yield biased and inconsistent parameter estimates when using ordinary least squares regression estimation. Finally, this study addresses the relevant econometric issues by using the Tobit, GLM and the two-stage least squares for a possible endogeneity concern.
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Sudip Adhikari and Aditya R. Khanal
The purpose of this paper is to present theoretical synopsis of risk balancing hypothesis (RBH) and estimate empirical models examining debt, savings and debt-to-equity use…
Abstract
Purpose
The purpose of this paper is to present theoretical synopsis of risk balancing hypothesis (RBH) and estimate empirical models examining debt, savings and debt-to-equity use decisions of small US farms.
Design/methodology/approach
The authors use primary survey data from Tennessee and generalized linear models (GLMs).
Findings
The study’s findings suggest that the perceived higher business risk (BR) significantly increases the extent of debt use, savings use and debt-to-equity of small farmers. Moreover, results indicate that factors such as age and education of the operator, family involvement, incomes, land acreage, adoption of alternative on-farm enterprises and farmers' continuation plan significantly influence the financing decisions of small farm operations.
Originality/value
The authors investigated an essential empirical question examining the risk balancing behavior of small US farm operations. While risk balancing has been a theme of several studies, none of the previous studies have specifically looked at the behavior in the context of small US farms. The theoretical synopsis and empirical findings contribute to the literature of risk balancing, debt use and savings use decisions and the policy discussions on farm financial and support strategies.
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Jyoti Rai and Jean Kimmel
Do women exhibit greater financial risk aversion than men? We answer this question using attitudinal and behavioral specifications of risk aversion drawn from the 2010 Survey of…
Abstract
Do women exhibit greater financial risk aversion than men? We answer this question using attitudinal and behavioral specifications of risk aversion drawn from the 2010 Survey of Consumer Finances (SCF). To approximate attitudinal specification of risk aversion, we use individuals’ self-reported financial risk tolerance. We use individuals’ relative risk aversion, that is, the effect of wealth on the proportion of assets categorized as risky as behavioral specification of risk aversion. We find that while women display greater attitudinal risk aversion, gender difference in behavioral risk aversion depends upon individuals’ marital status and role in household finances. Single women exhibit greater behavioral risk aversion compared to single men. However, this gender difference does not exist when we compare behavioral risk aversion of married women and men in charge of household finances.
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David S. DeGeest and Ernest H. O’Boyle
To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.
Abstract
Purpose
To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.
Methodology
The article provides a narrative review of different practices used to assess change over time. It also shows how different research questions require different methodologies for assessing changes over time. Finally, it presents worked examples for modeling these changes.
Findings
Our review suggests that there is a lack of research in social entrepreneurship that takes into account the many different considerations for addressing how time influences outcomes.
Originality/value
This chapter introduces an analytic technique to social entrepreneurship that effectively models changes in predictors and outcomes even when data are non-normal or nested across time or levels of analysis.
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Youngkeun Choi and Jae Won Choi
Job involvement can be linked with important work outcomes. One way for organizations to increase job involvement is to use machine learning technology to predict employees’ job…
Abstract
Purpose
Job involvement can be linked with important work outcomes. One way for organizations to increase job involvement is to use machine learning technology to predict employees’ job involvement, so that their leaders of human resource (HR) management can take proactive measures or plan succession for preservation. This paper aims to develop a reliable job involvement prediction model using machine learning technique.
Design/methodology/approach
This study used the data set, which is available at International Business Machines (IBM) Watson Analytics in IBM community and applied a generalized linear model (GLM) including linear regression and binomial classification. This study essentially had two primary approaches. First, this paper intends to understand the role of variables in job involvement prediction modeling better. Second, the study seeks to evaluate the predictive performance of GLM including linear regression and binomial classification.
Findings
In these results, first, employees’ job involvement with a lot of individual factors can be predicted. Second, for each model, this model showed the outstanding predictive performance.
Practical implications
The pre-access and modeling methodology used in this paper can be viewed as a roadmap for the reader to follow the steps taken in this study and to apply procedures to identify the causes of many other HR management problems.
Originality/value
This paper is the first one to attempt to come up with the best-performing model for predicting job involvement based on a limited set of features including employees’ demographics using machine learning technique.
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