Search results

Drawing upon social exchange theory, this study justified the indirect effects of responsible leadership and knowledge sharing on job performance through the mediation of work engagement and helping initiatives. Job tenure was examined as a moderator.

The hypotheses of this study were empirically tested with structural equation modeling (SEM) and moderated regression analyses. This study conducted a field survey on 512 knowledge workers who employed a high portion of or highly specialized tacit knowledge to do their job.

This research presented that both work engagement and helping initiatives mediated the indirect effects of responsible leadership and knowledge sharing on job performance. The empirical results revealed that job tenure moderated the relationships between responsible leadership and work engagement, and between responsible leadership and helping initiatives. However, job tenure did not moderate the relationships between knowledge sharing and work engagement, and between knowledge sharing and helping initiatives.

This research is one of the few to verify the key role of responsible leadership from the theoretical aspect of social exchange, complementing the leadership literature based on stakeholder theory. This research is a pioneer by taking into account the simultaneous influences of responsible leadership and knowledge sharing on job performance in a single model setting.

Predicting the inactivity and the repeat transaction frequency of a firm's customer base is critical for customer relationship management. The literature offers two main approaches to such predictions: stochastic modeling efforts represented by Pareto/NBD and machine learning represented by neural network analysis. As these two approaches have been developed and applied in parallel, this study systematically compares the two approaches in their prediction accuracy and defines the relatively appropriate implementation scenarios of each model.

By designing a rolling exploration scheme with moving calibration/holdout combinations of customer data, this research explores the two approaches' relative performance by first utilizing three real world datasets and then a wide range of simulated datasets.

The empirical result indicates that neither approach is dominant and identifies patterns of relative applicability between the two. Such patterns are consistent across the empirical and the simulated datasets.

This study contributes to the literature by bridging two previously parallel analytical approaches applicable to customer base predictions. No prior research has rendered a comprehensive comparison on the two approaches' relative performance in customer base predictions as this study has done. The patterns identified in the two approaches' relative prediction performance provide practitioners with a clear-cut menu upon selecting approaches for customer base predictions. The findings further urge marketing scientists to reevaluate prior modeling efforts during the past half century by assessing what can be replaced by black boxes such as NNA and what cannot.

Although the literature has somewhat discussed social capital and knowledge sharing, the mediating and moderating mechanisms that influence team workers to move from connecting with one another to building social capital and consequently engaging in knowledge sharing still remain largely understudied. For that reason, this study aims to develop a holistic research framework that links social capital to knowledge sharing with positive affective tone as a mediator and hypercompetition as a moderator.

Drawing upon the social capital theory and the affective events theory (AET), this study proposes a research framework to assess how social capital factors influence knowledge sharing with the mediation of positive affective tone and the moderation of hypercompetition in high-tech teams. This study obtains survey data based on 330 questionnaires of working professionals from 66 high-tech teams in Taiwan, in which each team comprises four members and their team leader.

The empirical results of this study show that social interaction, shared vision and trust are positively related to knowledge sharing via the mediation of positive affective tone. Moreover, hypercompetition has positive moderating effects on the relationships between social interaction and positive affective tone as well as between trust and positive affective tone.

This study expands the previous literature to study through what mediating mechanism the effects of different social capital factors on knowledge sharing can be effectively realized and whether there exists any critical moderator that influences these effects.

This research aims to investigate how entrepreneurial orientation influences a firm’s differentiation–cost advantage ambidexterity (DCAA) and performance indirectly through dynamic capabilities, while also investigating the impact of the interactive effect of the level and consistency of entrepreneurial orientation on dynamic capabilities. The goal of this study is to better understand the importance of consistently following an entrepreneurial orientation, as well as the linkage of such a consistently implemented strategy upon gaining both a cost and differentiation positioning enhancement.

Two empirical studies are conducted to test the proposed hypotheses – one longitudinal with multiple forms of data (i.e. text data, survey data and archival data) from 100 Taiwanese electronics firms and the other using primary data from a survey of senior managers.

Entrepreneurial orientation improves dynamic capabilities, which in turn promote superior DCAA and enhanced firm performance. In addition, as captured through a unique measure of consistency allowed through computer-aided text analysis, the results indicate that the effect of entrepreneurial orientation on dynamic capabilities is amplified when a firm consistently adopts entrepreneurial decisions and actions.

The specific context was a sample of electronics firms in Taiwan. This limits the generalization of findings, as would be possible with assessing the hypotheses in other industries.

This research clearly demonstrates the significance of consistency in pursuing a strategic orientation. The consistent support and deployment of resources facilitates an organization’s achieving positive outcomes associated with an entrepreneurial orientation.

While entrepreneurial orientation contributes to firm performance, extant knowledge on the internal process through which entrepreneurial orientation affects performance is relatively limited. The findings not only highlight the full mediating role of dynamic capabilities and DCAA, but also shed light on the importance of consistency in entrepreneurial orientation over time.

Automatic defect detection is a fundamental and vital topic in the research field of industrial intelligence. In this work, the authors develop a more flexible deep learning method for the industrial defect detection.

The authors propose a unified framework for detecting defects in industrial products or planar surfaces based on an end-to-end learning strategy. A lightweight deep learning architecture for blade defect detection is specifically demonstrated. In addition, a blade defect data set is collected with the dual-arm image collection system.

Numerous experiments are conducted on the collected data set, and experimental results demonstrate that the proposed system can achieve satisfactory performance over other methods. Furthermore, the data equalization operation helps for a better defect detection result.

An end-to-end learning framework is established for defect detection. Although the adopted fully convolutional network has been extensively used for semantic segmentation in images, to the best knowledge of the authors, it has not been used for industrial defect detection. To remedy the difficulties of blade defect detection which has been analyzed above, the authors develop a new network architecture which integrates the residue learning to perform the efficient defect detection. A dual-arm data collection platform is constructed and extensive experimental validation are conducted.

Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.

Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.

The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.

This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.

The purpose of this paper is to examine the ethical investment willingness decision-making process to understand how investors evaluate corporate social responsibility (CSR) actions.

Data were collected through a survey of 298 individual investors and analyzed using structural equation modeling.

Results reveal that perfectionist decision-making style is positively related to perceived moral intensity, substitutability of financial returns, and ethical investment willingness. In addition, perceived moral intensity and substitutability of financial returns are positively related to ethical investment willingness. Finally, perceived moral intensity is positively related to substitutability of financial returns, and a two-factor causal mediation model is supported.

The limitation of this study was that the pre-tests and sampling methods required all participants to have investing experience; however, procurement of trading information for each investor was impossible; thus, actual investment behaviors were undetermined. This study shed light on the mediating roles of perceived moral intensity and the substitutability of financial returns. Future studies can further investigate the factors influencing perceived moral intensity and the substitutability of financial returns.

Future ethical investment education can focus on cultivate the ability to distinguish ethical investments and change ethical investment willingness into actual investment behavior.

Understanding the relationship between these variables can help understand why ethical investment willingness varies among investors and how the traditional financial theory investment decision model should be revised as, internationally, more people have begun to observe CSR and sustainable development.

This research note aims to present a summary of research concerning economic‐lot scheduling problem (ELSP).

The paper's approach is to review over 100 selected studies published in the last 15 years (1997‐2012), which are then grouped under different research themes.

Five research themes are identified and insights for future studies are reported at the end of this paper.

The motivation of preparing this research note is to summarize key research studies in this field since 1997, when the ELSP problems have been verified as NP‐hard.

ELSP is an important scheduling problem that has been studied since the 1950s. Because of its complexity in delivering a feasible analytical closed form solution, many studies in the last two decades employed heuristic algorithms in order to come up with good and acceptable solutions. As a consequence, the solution approaches are quite diversified. The major contribution of this paper is to provide researchers who are interested in this area with a quick reference guide on the reviewed studies.

In recent years, many new and interesting business models for Internet-based selling have emerged with the advent of electronic commerce, one of which is the Internet-based group-buying. Since group-buying can be quickly built and removed, and the consumers can pay a lower price for the product through it, the group-buying can be a new online promotion form. In this chapter we build up a two-period pricing model for a supply chain when a supply chain member utilizes group-buying program to promote its products. In detail, we consider a supply chain consisting of a supplier and a retailer, where the supplier or retailer may launch a group-buying program to promote the products via a group-buying web site in the promotion period (i.e., the first period), as well as the supplier may sell its products through the retailer traditionally in both periods. Utilizing game theory, we derive the equilibrium decisions of the two supply chain members in three different scenarios, that is, (i) there is no group-buying program, (ii) the supplier launches a group-buying program, and (iii) the retailer launches a group-buying program. Analysis of the equilibrium decisions illustrates the following results: (i) both, the supplier and the retailer, will set low prices in the promotion period and high prices in the regular period; (ii) this trend will be enhanced when a group-buying program occurs, especially when such program is launched by the supplier; (iii) while the retailer can always benefit from a group-buying program, the supplier’s profit may be reduced under certain conditions; and (iv) in spite of the fact that the supplier’s profit may be damaged by the group-buying program, when the two supply chain members decide to launch a group-buying program, the unique equilibrium is that the supplier will launch such a program.

This paper aims to analyze the rates of returns on education in China and in the process raises issues relevant to the management of China’s system of education. In the ongoing great transformation period of China, the rising rates of returns on education may have been indicators reflecting China’s social progressiveness. However, very little research efforts have been devoted to the study of the impacts of such factors as geographical regions and genders, etc. The authors hope to fill these gaps in the literature.

The China Health and Nutrition Survey (CHNS) database is used for this study (University of North Carolina). The longitudinal nature of the data sets covering 1989, 1991, 1993, 1997, 2000, 2004, 2006, 2009 and 2011 provides a good basis for comparative analyses. The theory is grounded upon the Mincer equations through which econometric estimates are then made.

Disparities in returns on education are found between genders and across geographical regions. The regression results show that the women’s returns on education are consistently higher than those of men. However, the scales of such gender differences differ between the rural and urban areas: smaller for rural area and larger, more significantly so for urban. Additionally, we have found that the rates of returns on education in China have risen significantly over these years, and these increases have been largely due to the effects of institutional reforms. The urban-rural gap in their degrees of market orientation has contributed to the differences in their rates of returns on education. The analyses also suggest that foreign direct investment inflows, international trade and the increasing competitiveness from private enterprises render human capital more valuable to urban businesses. In case of the rural areas, a lack of incentive system tends to have contributed to the lower rates of returns on education.

The authors have presented evidence on the trends in the rates of returns on education during China’s critical transition period. Analyses of the possible reasons behind the differential rates of returns are provided. These findings are helpful for the government to shape their policies towards education. For instance, the government should give more emphasis to vocational schooling due to their significantly higher rates of returns.