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A laser‐based system has been developed to automatically measure complete inner profiles of various structures. The system uses a pointed laser source passing through a rotating optical device to obtain a series of distance measurements. To enhance the portability of the system, a hand‐held computer is selected to control the laser source and the rotating optical device. In addition to system control, the software associated with the handheld computer has also been developed to use the series distance measurements to construct a complete profile of the measured structure as well as to estimate the crosssectional area of the profile. The system can provide critical information for the construction industry and a variety of other commercial applications. The evaluation and analysis of measurement indicated that on accuracy within 4 per cent, for typical window designs and floor patterns, could be achieved. Recommendations for improvement of the system have also been included.

The field of Human Resource Management (HRM) has long recognized the importance of interpersonal influence for employee and organizational effectiveness. HRM research and practice have focused primarily on individuals’ characteristics and behaviors as a means to understand “who” is influential in organizations, with substantially less attention paid to social networks. To reinvigorate a focus on network structures to explain interpersonal influence, the authors present a comprehensive account of how network structures enable and constrain influence within organizations. The authors begin by describing how power and status, two key determinants of individual influence in organizations, operate through different mechanisms, and delineate a range of network positions that yield power, reflect status, and/or capture realized influence. Then, the authors extend initial structural views of influence beyond the positions of individuals to consider how network structures within and between groups – capturing group social capital and/or shared leadership – enable and constrain groups’ ability to influence group members, other groups, and the broader organizational system. The authors also discuss how HRM may leverage these insights to facilitate interpersonal influence in ways that support individual, group, and organizational effectiveness.

Organisational change is increasingly important and interesting to study. Change may affect employees’ attitudes and impact on their well-being. In this regard, it is important to examine how organisations enhance employees’ well-being when the competitive environment requires organisational changes whose implementation could cause well-being to deteriorate. Research suggests that human resource management practices (HRMPs) may have a positive impact on well-being. However, there is little research that analyses how the internal and external contexts of changing organisations may influence the outcome of HRMPs as regards well-being, which is of interest as it pertains to the application of suitable HRMPs in every setting. Thus, to address this research gap, the purpose of this paper is to analyse how employees’ perceptions of HRMPs and support from supervisors enhance well-being, taking into account the national cultural context of organisations.

Linear regression models tested the proposed hypotheses on a sample of 10,866 employees from 18 European countries who participated in the Fifth European Working Conditions Survey. Of the total sample, 5,646 respondents were involved in substantial restructuring and organisational change.

Results confirm the importance of national “uncertainty avoidance” values in the choice of the proper HRMPs to enhance employees’ well-being.

The literature highlights that HRMPs and supervisor support have a positive impact on well-being, and it also warns that national culture may condition the outcomes of human resource (HR) interventions. Based on this, the current study analyses how such HR interventions enhance well-being, taking into account national cultural context of organisations in both stable contexts and those involving change.

The paper aims to estimate abnormal audit fees more precisely than the traditional audit fee model by applying an artificial intelligence (AI) method.

The AI technique employed in this paper is the deep neural network (DNN) model, which has been successfully applied to a wide variety of decision-making tasks. The authors examine the ability of the classic ordinary least squares (OLS) and the DNN models to describe the effects of abnormal audit fees on accounting quality based on recent research that demonstrates a systematic link between accruals-based earnings management and abnormal audit fees. Thus, the authors seek to imply that their new method provides a more precise estimate of abnormal audit fees.

The findings indicate that abnormal audit fees projected using the DNN model are substantially more accurate than those estimated using the classic OLS model in terms of their association with earnings management. Specifically, when abnormal audit fees predicted using the DNN rather than the OLS are incorporated in the accruals-based earnings management model, the adjusted R²s are larger. Additionally, the DNN-estimated coefficient of abnormal audit fees is more favorably associated to earnings management than the classic OLS-estimated coefficient. Additionally, the authors demonstrate that the DNN outperforms OLS in terms of explanatory power in a negative discretionary accruals subsample and a Big 4 auditor subsample. Finally, abnormal audit fees projected using the DNN method provide a better explanation for audit hours than those estimated using the OLS model.

This is the first approach that utilized a machine learning technology to estimate abnormal audit fees. Because more precise measurement yields more credible research results, the findings of this study imply a significant advancement in calculating unusually higher audit fees.

The purpose of this study is to examine the relationship between explanatory language, audit fees and audit hours to demonstrate that auditors use explanatory language in audit reports to explain perceived audit risk.

The authors construct the sentiment value, a novel audit risk proxy derived from audit reports, using big data analysis. The relationship between sentiment value and explanatory language is then investigated. The authors present the validity of their new metric by examining the relationship between sentiment value and accounting quality, taking audit fees and hours into account.

The authors first find that reporting explanatory language is positively related to audit fees. More importantly, the authors provide an evidence that explanatory language in audit reports is indicative of increased audit risk as it is negatively correlated with sentiment value. As a positive (negative) sentimental value means that the audit risk is low (high), the results indicate that auditors describe explanatory language in a negative manner to convey the inherent audit risk and receive higher audit fees from the risky clients. Furthermore, the relationship is strengthened when the explanatory language is more severe, such as reporting the multiple numbers of explanatory language or going-concern opinion. Finally, the sentiment value is correlated with accounting quality, as measured by the absolute value of discretionary accruals.

Contrary to previous research, the authors’ findings suggest that auditors disclose audit risks of client firms by including explanatory language in audit reports. In addition, the authors demonstrate that their new metric effectively identifies the audit risk outlined qualitatively in audit report. To the best of the authors’ knowledge, this is the first study that establishes a connection between sentiment analysis and audit-related textual data.

Prior literature on online customer reviews (OCRs) suggests that individuals are socially influenced by information shared by others. Given that the online environment brings together users from different cultures, understanding how users differ in their processing and generation of OCRs across cultures is imperative. Specifically, this paper explores how cross-cultural differences influence OCR generation when there are inconsistencies between recent and overall review ratings.

The authors employ an empirical study and an experimental approach to test the predictions. For the empirical study (Study 1), the authors collected and analyzed actual review data from an online hotel review platform, Booking.com. This was followed by an experimental study (Study 2) in which the authors manipulated the thinking style represented by each cultural orientation to further explain how and why cross-cultural differences exist.

The results show that compared with the review ratings of users from collectivist cultures, those of users from individualistic cultures are more likely to follow recent review ratings. Based on the experimental study, the authors further find that such cross-cultural differences in OCR generation are driven by differences in thinking style.

This research extends the literature by demonstrating the cross-cultural differences in individuals' herding tendencies in OCR generation. The authors also add to the literature by showing in which direction OCR herding occurs when there is a discrepancy between overall and recent review ratings. From a managerial perspective, the findings provide guidelines for online platforms serving the global market on predicting customers' OCR generation and constructing appropriate response strategies.

The purpose of this paper is to shed light on the relationship between the adoption of Social Accountability 8000 (SA8000) – which is considered the most important ethical certification standard – and firm performance, building on agency and contingency theories.

The authors analyse secondary longitudinal balance sheet data of listed firms employing a rigorous event-study approach and compare SA8000-certified companies to different control groups based on three matching criteria, i.e., industry, size, and pre-certification performance. The authors then study the moderating effects of the cultural features, the country’s development level, and the labour intensity on the causal relationship through multiple regression methods.

The authors find that SA8000 certification positively affects labour productivity and sales performance but has no effect on profitability. Furthermore, the study supports that the relationship between SA8000 and profitability is moderated by two cultural features of the home country of the firms (i.e. power distance and uncertainty avoidance).

This is the first study, which empirically tests the effects of the ethical certification SA8000 on firm performance using a cross-country sample. In addition, the authors contribute to the wider debate on the effects of corporate social responsibility practices on firm performance.

Development of new cultivars requires extensive genetic knowledge, trained personnel, and significant financial resources, so it is crucial for breeders to focus on the attributes most preferred by the key supply chain stakeholders such as consumers and producers. The purpose of this paper is to identify which attributes generate the highest total revenue or social surplus, information that breeders can take into account as they allocate resources to focus on attributes in their breeding programs.

This study used mail-in and online surveys to collect consumer and producer choice experiment data, and then employed mixed logit models to analyze and simulate individual producer and consumer willingness to pay (WTP) for the apple attributes.

Based on the simulation results, this study derived the supply and demand curves and the market equilibrium prices and quantities for each apple attribute. Based on the WTP analysis for both consumer and producer, this paper found the highest equilibrium price and welfare for apples come from crispness, followed by flavor.

The authors propose a framework to estimate the equilibrium prices and quantities of a product based on the results of choice experiments. The framework can be easily adapted to understand any countries’ producer and consumer preferences for certain products.

Many companies worldwide are currently involved in open innovation processes (OIPs), through which they aim to collect innovative insights and ideas from the crowd. The phenomenon has grown – and is destined to continue to grow – massively. As a result, there is strong interest from scholars and practitioners in rebuilding the relevant processes and developing a set of best practices. What seems to be missing from this developing topic of research is a focus on its antecedents and consequences. Since the phenomenon is so new, a focus on its consequences seems untimely. A focus on its antecedents, on the other hand, seems both promising and intriguing.

The fact that more and more companies are involved in OIPs suggests that they have already developed an organizational open innovation (OI) culture. If an OI culture already exists, how widespread is it and to what extent is it shared among those involved in knowledge ecosystems? With this question in mind, it seems worthwhile to investigate whether OI is supported culturally at both social and individual levels.

Finally, this chapter summarizes the state of the art of OI culture at social, organizational and individual levels and considers how an OI culture developed at company level may serve to drive its development at the social and individual levels.

The purpose of this paper is to investigate surroundings for transfer film formation and removal, the effect of the transfer film formation on friction coefficients, the effect of four different abrasive components, ZrO₂, ZrSiO₄, Al₂O₃ and Fe₃O₄, on transfer film formation and the effect of lubricating component MoS₂ on transfer film formation and friction coefficients.

Two different MoS₂ contents of 5.5 and 8.5 per cent were added to friction materials with no MoS₂ content, which have four different abrasive components, ZrO₂, ZrSiO₄, Al₂O₃, Fe₃O₄. Friction tests composed of three different stages were conducted for those materials, and the friction surfaces of the counterpart disks were examined by scanning electron microscopy (SEM) to access the formation of transfer film at each stage.

For the transfer film formation, high temperature was a prerequisite, but the magnitude of deceleration rate was not important. The effect of the transfer film formation was to reduce the friction coefficients for most friction materials. Friction coefficients of materials which contain lubricating component MoS₂ were higher than those which contain no MoS₂ for most friction materials. The effect of the lubricating component MoS₂ was to suppress the formation of transfer film, thus resulting in increase in friction coefficients.

The transfer film was rather thin, with thickness of 1-2 µm for most friction materials. That hindered the examination of mechanical properties of the transfer film, such as hardness.

This research explained the surroundings for transfer film formation, and its effect on friction coefficients. The research suggests to suppress the formation of transfer film to make friction materials with high friction coefficient, and the lubricating component MoS₂ can be used for the purpose.

Development of high-friction-brake materials conventionally depends on the use of strong abrasive components, which may induce attacking of counterpart disks. The enhancement of friction coefficients with addition of MoS₂ content is expected to open a new prospect in development of high-performance friction materials, which can be applicable to brake pads for racing cars.

The study is in pursuit of the transfer film formation in successive friction stages, which revealed the conditions for transfer film generation and removal. Specimen preparation for SEM observation of cross section of friction surface was painstaking to not damage the developed friction surface. The study revealed the effect of different abrasive components on transfer film formation and the effect of lubrication contents of MoS₂ on transfer film formation and friction coefficients.