创业导向有助于激发员工创新行为吗——创新意愿的中介作用

创新创业浪潮下,组织创业导向与员工创新问题已成为学术界探讨的前沿论题,是提升组织创新能力的关键环节.基于以往文献回顾,从社会认知视角,探讨组织创业导向对员工创新行为的作用机理,并分析个体创新意愿在作用过程中的调节效应.通过问卷调查获取湖南省9家企业264份有效问卷,采用SPSS21.0和 AMOS17.0对数据进行处理,验证假设.结果显示:创业导向与员工创新行为存在显著正向影响,与员工创新意愿具有正向关系;员工创新意愿与创新行为显著正相关;员工创新意愿在创业导向与创新行为关系间发挥中介作用.     

Synthesizing enterprise data through digital dashboards to strategically align performance: Why do operational managers use dashboards?

Based on a cross-sectional field study, Reinking et al. (2019) propose a complex theoretical model for understanding the characteristics of dashboards that promote use and lead to individual and organizational performance gains. This study tests the theoretical model using survey data collected from 323 middle and upper level managers with experience using corporate dashboards. The data were analyzed using components based structural equation modeling, and the results provide strong support for the external validity of the Reinking et al. (2019) theoretical model. The results show that two primary constructs, strategy alignment and interactive management control, are important factors impacting the extent of dashboard use, perceived managerial performance, and perceived organizational performance. Prior research has expressed concerns over the tendency of managers to lose sight of strategic objectives (i.e., strategy surrogation) and focus solely on performance measures. However, our results indicate that operational managers perceive that dashboards focused on specifically tailored KPIs lead to both improved managerial and organizational performance. This study contributes to management control and strategy research in two important ways. While prior research has examined strategy in the executive level context through evaluations, changes, or initiative implementations, this study investigates strategy alignment at the operational levels of the organization. Second, the results suggest that intentional strategy surrogation may have beneficial effects at the lower operational levels in an organization.     

A New Zealand failure prediction model: Development and international implications

In this study we develop a failure prediction model for New Zealand listed companies and theorise on the usefulness and international implications of the results. In developing the model, we obtained data from 60 failing and 60 matched non failing New Zealand listed companies, providing an unusually rich database for model development. Binary logistic regression (logit) was applied on 21 potentially significant variables. The predictive strength was tested using holdout tests, with support from applications to more recent company data. Multicollinearity was minimised through a theoretically informed selection of variables, the Pearson correlation and stepwise regression. The resulting model is significant to 91.7% overall, which tested well for prediction and non-multicollinearity, and reveals a unique combination of variables. We conclude by considering the research implications of small-market model development, and the benefits of local, contextually-based models as evidenced by the results of this study.     

The Contribution of Internal Audit as a Determinant of External Audit Fees and Factors Influencing This Contribution

Despite extensive research on the determinants of external audit fees, there is little empirical evidence on the effect of internal audit contribution on the external audit fee. Using a cross-sectional regression model based on prior audit fee research, this study provides evidence that internal audit contribution is a significant determinant of the external audit fee. Further, a second model that provides evidence on the determinants of internal audit contribution is developed and tested. This second model indicates that internal audit contribution is influenced by internal audit quality and, conditional on the level of inherent risk, the availability of internal audit and the extent of coordination between internal and external auditors. These results are based on a unique data-set comprised of publicly available data matched with survey responses from internal and external auditors affiliated with 70 non-financial services Fortune 1000 firms. The sample includes all of the former "Big 6" international accounting firms and clients from twenty-nine different industries.     

Determinants of International Insurers' Participation in Foreign Non-Life Markets

Mirroring the trend in the broader marketplace, the global insurance industry is steadily moving toward increased liberalization and deregulation. This study seeks to develop the first empirical model that examines the importance of foreign market characteristics as they relate to the participation of international insurers in the non‐life business of those countries. The analysis reveals that market structure is an important factor in determining whether international insurers participate in a given foreign market. In addition, for markets that are not competitive, removing trade barriers would significantly improve the desirability of those countries as host markets. The results also suggest that countries with higher gross domestic product tend to attract more involvement from international insurers. While this research focuses on the markets of industrialized countries, the findings will provide significant implications for those emerging markets that have not yet collected relevant data on a number of the variables included in this study.     

我国股指期货与现货市场信息传递与波动溢出关系研究

股指期货与现货市场关系是监管者关注的重点问题。本文采用我国股指期货上市以来1分钟级高频数据,应用向量误差修正模型、方差分解、多元T-GARCH等,考察期现两市信息传递、波动溢出效应的影响。实证结果表明,尽管股指期货和股票市场之间短期内存在相互引导关系,但股票市场价格变动更多来自于自身影响,起主导作用,而且两市长期均衡收敛也是以股票市场占主导地位;两市存在显著的双向波动溢出,期货市场的波动溢出效应强于股票市场的波动溢出效应;两市场存在明显的非对称效应,期货市场对坏消息更为敏感,而现货市场对好消息更为敏感。     

Empirical Evidence on the Value of Group‐Level Financial Information in Insurer Solvency Surveillance

The existing empirical research on insurer insolvency relies almost exclusively upon individual insurance company financial data, even though the insurance industry is dominated by group‐affiliated firms. This is the first study to evaluate the benefit of using group‐level data to predict insurer insolvencies for group‐affiliated insurers. The study uses financial ratios from the NAIC FAST scoring system, measured at both the company level and group level, as potential predictor variables. The results indicate that group‐level financial information substantially improves the predictive power of an insolvency prediction model relative to a model that uses only the analogous company‐level variables. In fact, the group‐level variables are found to often be substantially more powerful than company‐level variables in predicting individual insurer insolvencies. These results suggest that future insolvency analysis should, whenever feasible, include group‐level information to obtain higher predictive accuracy.     

Influencia de los sistemas de información en los resultados organizacionales

Over the last years, information systems (IS) have constituted the main focus of research in the business organization literature. This has created the need to identify their entrepreneurial value. The paper presents a theory-based model that was developed to assess the degree of IS success in SMEs. The aim of the proposed model is to determine the influence of IS on organizational performance. To achieve this aim, the Partial Least Square statistical technique is used to analyze data from 133 questionnaires administered to businesses across the state of Tamaulipas, Mexico. The results show that those enterprises that are more concerned with the improvement of the systems’ quality, information quality and the informatics service enhance the organizational outcomes. The present study contributes to the body of literature on the assessment of IS success in the context of an emerging country. In particular, the study provides a thorough assessment of the IS effectiveness and their impact on organizational performance.     

房价波动、银行信贷与经济增长

运用联立方程模型、面板分析技术及省际面板数据研究发现,我国房价波动、银行信贷与经济增长之间具有紧密的联系.分区域的实证研究结果显示:各地区房价的上涨与金融支持有关,过度的金融支持使东中部地区的房价偏离了经济基本面;中西部地区房价的上涨对银行信贷的扩张有显著影响,而经济增长是各地区促进银行信贷扩张的共同因素.此外,房价的上涨与银行信贷的扩张共同促进了我国各区域经济的繁荣.     

住房价格、住房投资、消费与货币政策——基于金融加速器效应的DSGE模型研究

以BGG模型为基础建立包含金融加速器机制的DSGE模型,采用数值模拟方法研究中国货币政策冲击对住房价格与住房投资及消费的影响,结果表明金融加速器机制明显放大了货币政策冲击对三者的影响;与不带金融加速器模型相比,使用带有金融加速器效应模型分析时,中国货币政策冲击对房价、投资和消费的影响程度更大,并且更符合现实数据特征。模拟结果还显示货币政策对消费的影响与已有文献的结论存在差异,即货币政策冲击对消费短期影响较大,且影响持续时间也较长。     

Do economic statistics contain information to predict stock indexes futures prices and returns? Evidence from Asian equity futures markets

This research examines the impact of local and international market factors on the pricing of stock indexes futures in East Asian countries. The purpose of this paper is to present a study of the significant factors that determine the major stock indexes futures’ prices of Hong Kong, Malaysia, Singapore, South Korea and Taiwan. This study first investigates the relationships between Hang Seng Index Futures, KLCI Futures, SiMSCI Futures, KOSPI Futures, Taiwan Exchange Index Futures and local interest rates, dividend yields, local exchange rates, overnight S&P500 index and a newly constructed index, Asian Tigers Malaysia Index (ATMI). 11 years historical data of stock indexes futures and the economic statistics are studied; 10 years in-sample data are used for testing and developing the pricing models, and 1 year out-of-sample data is used for the purpose of verifying the predicted values of the stock indexes futures. Using simple linear regressions, local interest rates, dividend yields, exchange rates, overnight S&P500 and ATMI are found to have significant impact on these futures contracts. In this research, the next period close is predicted using simple linear regression and non-linear artificial neural network (ANN). An examination of the prediction results using nonlinear autoregressive ANN with exogenous inputs (NARX) shows significant abnormal returns above the passive threshold buy and hold market returns and also above the profits of simple linear regression (SLR). The empirical evidence of this research suggests that economic statistics contain information which can be extracted using a hybrid SLR and NARX trading model to predict futures prices with some degree of confidence for a year forward. This justifies further research and development of pricing models using fundamentally significant economic determinants to predict futures prices.

     

THE USE OF PROTOCOL ANALYSIS IN ACCOUNTING

The primary objective of accounting is to provide information that helps decision makers make better decisions. Yet knowledge about how accountants and other professionals make decisions is limited. This article examines verbal protocol analysis, a methodology that uses detailed process information to model decision making behavior. There are many protocol analysis techniques, with different ways to collect data and different ways to analyze it. The selection of a particular technique depends on the specific research objectives. The article concludes with an illustration of a detailed protocol analysis study and a discussion of its results.     

The use of open source internet to analysis and predict stock market trading volume

The objective of this paper is to evaluate the impact of information demand and supply on stock market trading volume. Few studies have demonstrated the role of Google search data in analyzing trading volume activity. In this study, we employ a proxy for information demand which is derived from weekly internet search volume. The latest is from Google Trends database, for 25 of the largest stocks traded on CAC40 index, between April 2007 and March 2014. We use news headlines as a proxy for information supply. We use Garch model to analyze and predict trading volume.The empirical results present new evidences. First, information supply has an impact on trading volume but information demand's impact is much more important. Secondly, by applying MCA to results found, it could be concluded that the impact of public information on transaction volume is conditioned by two elements: the firm and market news disclosure and the second element relates to the characteristics of the market participants, more precisely their news interpretations and their risk aversion. Thirdly, we used Chow structural break test to verify the stability of our model. We found that for securities with structural changes, information demand is the responsible variable of the change in our model. Finally, we found that information variables have a predictive power on transaction volume.This paper contributes to existing literature by incorporating open source internet-based data into the analysis and prediction of transaction volume. Using internet information about the stock market, which has appeared recently as an interesting research for financial empiricists, computer scientists and practitioners, will have a very important utility because quantifying demand and supply of information becomes possible.     

Liquidity,Skewness and Stock Returns: Evidence from Chinese Stock Market

In this paper, a capital asset pricing model (CAPM) incorporating liquidity and skewness factors is proposed and tested by using the Chinese stock market data. The empirical results indicate that, under various market conditions, the liquidity-adjusted three-moment CAPM provides a better fit to the realized returns of various stock portfolios. Overall, this research reveals that illiquidity cost, liquidity risk and as well as skewness have important impacts on asset pricing in the Chinese stock market.     

Is China’s Manufacturing Industry Efficient? Evidence from an Energy-Rebound Effect Perspective

Majority of the increase in global energy consumption is from China; hence, studying energy issues, especially in China’s manufacturing industry (CMI), is worthwhile and of much interest in the academic field. Based on the translog cost function, we develop a research framework to study the rebound effect of CMI. Considering the effect of asymmetric energy price, we augment the energy-cost function with asymmetric influence constraint of energy price. Again, we add time series data of CMI’s capital, labor, energy, and mid-input to the model to calculate the direct rebound effect of CMI. We find that the rebound effect of CMI is 44.2%, and CMI still has large energy-conservation potentials. Based on the results of this study, some policy recommendations are provided.     

SME internationalisation: Do the types of innovation matter?

Existing evidence suggest that innovative Small and Medium-sized Enterprises (or SMEs) are more likely to internationalise (i.e. have a greater propensity to export) than non-innovative SMEs. However, it is not yet clear whether and to what extent different types of innovation (i.e. product, service, and process) affect SME internationalisation. To address this issue, this study uses a research model that integrates the resource and institutional perspectives and empirically test it using data from the United Kingdom (UK) Longitudinal Small Business Survey. Our results confirm that SME internationalisation is more likely to occur in firms undertaking product innovation than process and/or service innovation, and a specific configuration of resource and institutional drivers influence SME internationalisation depending on the innovation type. These results lead to major policy and managerial implications in relation to promoting SME internationalisation through different types of innovation, given the UK withdrawal from the European Union.     

对中国上市公司债务期限影响因素的实证研究——基于面板数据的因子分析和回归分析

国内外诸多学者已经开始从代理成本、税盾作用、信息不对称等角度来研究影响债务融资期限的各种因素。但综合各种因素来考察企业融资期限结构影响的研究却相对较弱。以中国546家A股的上市公司最近9年相关数据为样本,从企业规模、财务杠杆、债务税率、清算比率和资产期限等因素对企业融资期限结构的影响做因子分析和回归分析后,指出代理成本等理论对中国上市公司债务期限解释是有限的。     

The Impact of Spatial Interpolation Techniques on Spatial Basis Risk for Weather Insurance: An Application to Forage Crops

Weather index insurance for crops is at the developmental stage, however, this type of insurance is particularly susceptible to the problem of spatial basis risk. Spatial basis risk occurs when the weather observed at weather stations does not match the weather experienced on the farmer’s property, causing improper indemnities to be paid to the farmer. However, spatial basis risk may be reduced through the use of averaging and spatial interpolation techniques, such as inverse distance weighting and kriging. These techniques make it possible to incorporate multiple weather stations in the estimation process rather than using only the single closest station, potentially resulting in more accurate estimations and thereby reducing spatial basis risk. Therefore, the objective of this study is to examine the extent to which the choice of spatial interpolation techniques can influence the amount of spatial basis risk in a weather-based insurance model. Using forage crops from the province of Ontario, Canada, as an example, a weather insurance index is developed based on cooling degree days. The weather index represents the heat stress that the crops receive over the growing season. This insurance index is used to determine to what extent spatial basis risk can be reduced by the insurer’s choice of spatial interpolation technique. Seven different interpolation methods are applied to temperature data from Ontario, and theoretical indemnities are calculated for forage producers across the province. By analyzing the correlation between the estimated indemnities and reported forage yields, the amount of spatial basis risk in each model is quantified. The results of this study highlight the importance of choosing an appropriate method based on the characteristics of the target region (and data). Operationally this is important because insurers typically apply the same interpolation methods across an entire region. While one finding of this research may suggest that governments and/or insurance companies may wish to invest in additional weather stations to improve the accuracy of the interpolation method and index, this may not be feasible in practice. Given this, future research may consider utilizing satellite-based remote sensing weather estimates to augment the weather station data and reduce basis risk.     

民间借贷融资的影响因素和发展探究

近年来,民间借贷融资越来越活跃,也容易在借贷过程中引发一些社会问题。本文通过对民间融资盛行的福建进行调研,研究民间借贷融资的影响要素,从而寻找出解决民间借贷融资问题的解决方案。模型显示,年龄与收入来源和民间借贷的需求呈反向关系,家庭人口和流动资产与之呈正向关系。根据模型的结果,提出了对民间借贷融资的发展建议。