Search results

This study aims to investigate how small talk interaction affects knowledge sharing, examining the mediating role of interpersonal trust (affect- and cognition-based trust) and the moderating role of perceived similarity among the mechanisms of small talk and knowledge sharing.

This research conducts complementary studies and collects multi-culture and multi-wave data to test research hypotheses and adopts structural equation modeling to validate the whole conceptual model.

The research findings first reveal two trust mechanisms linking small talk and knowledge sharing. Meanwhile, the perceived similarity between employees, specifically, strengthens the affective pathway of trust rather than the cognitive pathway of trust.

This study combines Interaction Ritual Theory and constructs a dual-facilitating pathway approach that aims to reveal the impact of small talk on knowledge sharing, describing how and when small talk could generate a positive effect on knowledge sharing. This research provides intriguing and dynamic insights into understanding knowledge sharing processes.

This paper applied grey wave forecasting in a decomposition–ensemble forecasting method for modelling the complex and non-linear features in time series data. This application aims to test the advantages of grey wave forecasting method in predicting time series with periodic fluctuations.

The decomposition–ensemble method combines empirical mode decomposition (EMD), component reconstruction technology and grey wave forecasting. More specifically, EMD is used to decompose time series data into different intrinsic mode function (IMF) components in the first step. Permutation entropy and the average of each IMF are checked for component reconstruction. Then the grey wave forecasting model or ARMA is used to predict each IMF according to the characters of each IMF.

In the empirical analysis, the China container freight index (CCFI) is applied in checking prediction performance. Using two different time periods, the results show that the proposed method performs better than random walk and ARMA in multi-step-ahead prediction.

The decomposition–ensemble method based on EMD and grey wave forecasting model expands the application area of the grey system theory and graphic forecasting method. Grey wave forecasting performs better for data set with periodic fluctuations. Forecasting CCFI assists practitioners in the shipping industry in decision-making.

Although there has been much research on government support for export in China and other emerging economies, considerably less attention has been given to government subsidy-related importing activity in China. This study aims to propose that the government subsidies as the source of financial resources produce a significant increase of imports, as the firms are more likely to engage actively in importing technology-related products which are conducive for China’s future innovation. However, state ownership in firms negatively moderates this relationship and holds back technology imports. Improved formal regulatory institutions do not help to improve but rather weaken this relationship.

To investigate how government policy affects imports of strategic resources in China, all of the listed firms on Chinese stock markets (from 2008 to 2014) have been selected, the firms that are engaged in exporting and importing activities. The data from the China Stock Market & Accounting Research database have been selected and merged with those of the General Administration Customs in China. A panel analysis has been done with several robustiness tests.

First, the study indicates that government subsidies are a driving force for the development of importing activities. Second, it finds conflicts of interests between government subsidies and state ownership of a firm, as increased ownership will weaken and even negate the positive effect of a government policy, thus negatively affecting the national competitiveness in the long run. Third, it is important to take into account the issue on different levels of institutional development, even allowing for the fact that a nationwide government policy is applied to the firms located in all corners of the country.

The authors suggested a regional difference in regulatory development but did not find the proposed direction. In their future study, the authors will validate and generalize this intriguing substitutional effect. They expect the results will help the government to ensure that it can fulfill a policy (e.g. regulation) down to every gross-roots organization so the development of regulatory infrastructure will help the firm to obtain and accumulate strategic resources through increased imports of them. Another direction of their future study will explore how government policy will prompt the firms to increase their spending so that they can possess plenty of “stamina” for their future development.

Different levels of institutional development exist in China even allowing for the fact that a nationwide government policy should be applied to all firms within the territory. This certainly has impacts on technology imports and thus creates difficulties for firms located in the western parts of China about which the government is particularly concerned. The government needs to ensure that its policies (laws and regulations) can be fulfilled down to every gross-roots organization so that the development of regulatory infrastructure can be inclusive and pervasive, given its influence on technology importation and indigenization.

Both of the theoretical and empirical work centered on policy initiatives and particularly government subsidies in emerging economies that significantly influence imports of strategic resources, a means with which the firm is better able to maintain and develop its competitive advantages, particularly in an economy with institutional void. Relatedly, the results on a causal relationship help envision a transcending trajectory of China’s economy, suggesting that businesspeople should capitalize on the policy advantage so that they are better able to sustain their long-term development. The results also present implications for policymakers to encourage and support strategic move toward such import endeavors.

The aim of this study is to examine the relationships between taking charge, bootlegging innovation and innovative job performance, and to explore the moderating roles of felt responsibility for constructive change (FRCC) and creative self-efficacy (CSE).

Data for this research was collected from 503 employees working in a chain company. Through a longitudinal study design, a three-wave survey with 397 valid data provided support for the proposed theoretical model.

The results maintain a positive association between taking charge, bootlegging innovation and innovative job performance, indicating the mediating effect of bootlegging innovation. Additionally, both the FRCC and CSE facilitate the indirect effect of taking charge on innovative job performance through bootlegging innovation. Furthermore, the integrated moderated mediation model analysis suggested that FRCC is more vital in improving employees' innovative job performance.

This research aims to break the black box between taking charge and innovative job performance, which has been relatively unexplored. Drawing from self-determination theory (SDT) and the proactive motivation model, the authors verify the bridge-building role of bootlegging innovation and the dual-facilitating effects of FRCC and CSE while employees conduct taking charge. This study’s results provide new insight for managers to foster, encourage and support employees' proactive behavior.

Regarding the important roles of accuracy and robustness of tightly-coupled micro inertial measurement unit (MIMU)/global navigation satellite system (GNSS) for unmanned aerial vehicle (UAV). This study aims to explore the efficient method to improve the real-time performance of the sensors.

A covariance shaping adaptive Kalman filtering method is developed. For optimal performance of multiple gyros and accelerometers, a distribution coefficient of precision is defined and the data fusion least square method is applied with fault detection and identification using the singular value decomposition. A dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed.

Hardware-in-the-loop numerical simulation was adopted, the results indicate that the gain of the covariance shaping adaptive filter is self-tuning by changing covariance weighting factor, which is calculated by minimizing the cost function of Frobenius norm. With the improved method, the positioning accuracy with tightly-coupled MIMU/GNSS of the adaptive Kalman filter is increased obviously.

The method of covariance shaping adaptive Kalman filtering is efficient to improve the accuracy and robustness of tightly-coupled MIMU/GNSS for UAV in complex and dynamic environments and has great value for engineering applications.

A covariance shaping adaptive Kalman filtering method is presented and a novel dual channel parallel filter scheme with a covariance shaping adaptive filter is proposed, to improve the real-time performance in complex and dynamic environments.

In recent years, private brands for e-commerce platforms have experienced rapid growth. However, whether these platforms developing private brands should share their demand information with others and how such information sharing affects the sales format selection of national brand manufacturers have puzzled firm managers in practice. This paper aims to investigate the information-sharing strategy for the e-commerce platform and its influence on the sales format selection in the presence of the private brand.

The authors use a game-theoretical model to examine the interaction between the information-sharing strategy and sales format selection in a supply chain consisting of a manufacturer and a platform that operates a private brand.

The equilibrium results show that when the commission rate is low, the manufacturer favors agency selling, and the platform shares demand information with the manufacturer; when the commission rate is high, the manufacturer prefers reselling, and the platform does not share the information. This preference is affected by information forecasting accuracy; as the information forecasting accuracy increases, the manufacturer prefers to adopt agency selling, and the platform tends to share the information. Interestingly, under agency selling, sharing information with the manufacturer can increase the platform’s profit from selling the private brand and achieve a win-win situation for them. Furthermore, we show that the manufacturer can inspire the platform to share the information with himself by adopting agency selling, whereas the platform sharing the information improves the probability that the manufacturer adopts agency selling. Moreover, the manufacturer may have a first-mover advantage. In particular, the manufacturer moving first increases the likelihood that the manufacturer chooses agency selling and the platform shares the information.

This paper contributes to sales format literature by exploring the effect of information sharing strategy on sales format selection in the presence of the private brand and can help manufacturers and platforms to make suitable decisions regarding information sharing and sales format selection.

This paper aims to clarify the CO₂ emissions of global construction industries under the consideration of different patterns of international trade and thus to draw a comprehensive picture for understanding the international paths of CO₂ transfer to global construction industries.

This research inventories the CO₂ emissions induced by the final demand of 15 economies for construction products and explores the CO₂ intensities of these economies based on a multi-regional input–output model. This paper further decomposes CO₂ emissions into four components based on different patterns of international trade to estimate the roles of four patterns of international trade in shaping the environmental pressures from global construction industries.

The results indicate that the CO₂ intensities of the construction industries in Russia, India and China were higher than those in other economies, and the CO₂ intensities of global construction industries experienced a decline over the years 2000–2014. The decomposition analysis demonstrates that domestic and foreign CO₂ emissions accounted for 42.67 and 54.23%, respectively, of the CO₂ emissions of the construction industries in the 15 economies during the period 2000–2007. Although the major part of the CO₂ emissions of the construction industries come from domestic production systems, the final demand for construction products in the 15 economies caused substantial emissions in other economies. Further decomposition by upstream industrial production source indicates that 58.65% of domestic emissions and 66.53% of foreign emissions can be traced back to the electricity industry.

Although the major patterns of CO₂ emissions of the construction industry have been identified in this paper, the difficulty of understanding the relationship between upstream production industries or countries and the construction industry deserves more attention in the future research.

Previous research on inventorying CO₂ emissions has generally been limited to evaluating the impact of industrial consumption activities on national or global emission accounting, tending to ignore the effects of different international trade patterns on the change in industrial CO₂ emissions. This research is the first attempt to account for and decompose the CO₂ emissions of global construction industries under consideration of the effects of different patterns of international trade on environmental pressures. The decomposition and upstream industrial distributions of different patterns of CO₂ emission provide a comprehensive picture for better understanding of the emission pattern and source of the CO₂ emissions of global construction industries. The research outcomes reveal how the final demand of a country for construction products induces CO₂ emissions in both domestic and foreign systems, thus providing basic information and references for policy adjustment and strategy design in relation to mitigation of climate change and sustainable development.

This paper aims to better understand the linkage between CO₂ emitters and industrial consumers. The border-crossing frequency is applied to calculate the average number of steps that a country takes in relation to the CO₂ emissions of its construction industry. The maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

This paper maps the CO₂ transfer that accompanies global production chains using the frequency of border crossing in the production processes of construction products. As the basic analysis framework, a multi-regional input–output model is adopted to analyse the average border-crossing frequency of CO₂ transfer. Additionally, indicators including the maximum border-crossing frequency and declining speed of CO₂ transfer are employed. Also, the maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

The results indicate that 85.49% of the CO₂ in construction products needs to be processed in at least one country, reflecting that direct trade is the major pattern of transfer of CO₂ from primary producers in global construction industries. The maximum border-crossing frequency is 4.88 for 15 economies, meaning that construction products cross the international borders up to 4.88 times before they are absorbed by the final users. The scale of the average border-crossing frequency ranged from 1.16 to 1.87 over 2000–2014, indicating that the original construction products crossed the international borders at least 1.16 times to satisfy the final demand of the consuming countries.

The data from the economic MRIO tables in the WIOD are only available until 2014, which is a limitation for conducting this research in recent years.

The fragmentation of production is not only reshaping global trade patterns, but also leading to the separation of CO₂ emitters and final consumers in production chains. A growing number of studies have focussed on the impact of production fragmentation on accounting for regional and national CO₂ emissions, but little research has been done at the scale of a specific industry. The major contribution of this paper lies in mapping the CO₂ emissions that accompany the production chains of construction products from the perspectives of both magnitude and length. Additionally, this paper is the first to propose using maximum border-crossing frequency and declining speed to analyse the characteristics of global production chains induced by the final demand of major economies for construction products.

In order to accurately forecast nonlinear and complex characteristics of solar power generation in China, a novel discrete grey model with time-delayed power term (abbreviated as TDDGM(1,1,tα) is proposed in this paper.

Firstly, the time response function is deduced by using mathematical induction, which overcomes the defects of the traditional grey model. Then, the genetic algorithm is employed to determine the optimal nonlinear parameter to improve the flexibility and adaptability of the model. Finally, two real cases of installed solar capacity forecasting are given to verify the proposed model, showing its remarkable superiority over seven existing grey models.

Given the reliability and superiority of the model, the model TDDGM(1,1,tα) is applied to forecast the development trend of China's solar power generation in the coming years. The results show that the proposed model has higher prediction accuracy than the comparison models.

This paper provides a scientific and efficient method for forecasting solar power generation in China with nonlinear and complex characteristics. The forecast results can provide data support for government departments to formulate solar industry development policies.

The main contribution of this paper is to propose a novel discrete grey model with time-delayed power term, which can handle nonlinear and complex time series more effectively. In addition, the genetic algorithm is employed to search for optimal parameters, which improves the prediction accuracy of the model.

Due to product value uncertainty, consumers do not know the product matching rate before they get the product, which is the probability of product fitness. Taking the consumers’ anticipated regret into account, this paper aims to develop a theoretical model to explore how the anticipated regret affects pricing and advertising decisions and profits of retailers in the online to offline (O2O) supply chain.

This paper considers an O2O supply chain consisting of an e-retailer and a brick-and-mortar retailer; both retailers cooperate to provide buying online and pick up in-store (BOPS) for consumers.

It shows three major findings. Retailers should decide whether to introduce BOPS channel according to the matching rate of the product when the BOPS channel is not very convenient for consumers. When the BOPS channel does not exist in the market, the profits of two retailers increase with the online regret of consumers, while the BOPS channel exists in the market and the matching rate of the product is low, the higher offline regret can enable both retailers to increase the profits; furthermore, when the matching rate is high, the higher degree of online regret can bring more profit to the O2O supply chain. Therefore, both retailers can take measures together to induce consumers’ regrets according to the different matching rates, which makes both retailers obtain more profits. Counterintuitively, consumer surplus will not always increase due to consideration of anticipated regret.

The model has some limitations that are worth further discussing. First, in practice, the O2O supply chain includes many forms except the BOPS channel, for example, order online and pick-up in-store (ROPS) channel; future research can discuss and consider the impact of consumers’ anticipated regret on ROPS. Second, the authors consider that O2O is a supply chain composed of two retailers. In reality, there is also a situation where an oligopoly retailer opens two channels to realize O2O supply chain, in the case the inventory decision-making of the product is worth studying. Finally, to highlight the impact of the anticipated regret on consumers’ decision-making, the return of the product is not considered. Future research can take the return of the product into account to assess the robustness of the results.

The contributions are in two main aspects. First, this paper considers an O2O supply chain with consumer value uncertainty, where there are duopoly retailers in the market and most of the existing literature focus on oligopoly retailer operates both online and offline channels; meanwhile, consumers’ value perceptions of the product is deterministic. Second, this paper explores how the consumer anticipated channel regret affects the pricing and advertising decisions of O2O supply chain, and the authors take behavioral theory into account when studying omnichannel operations, while most studies on anticipated regret consider traditional two-stage price reduction management, product innovation, etc.