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The purpose of this paper is to study the effect of second generation involvement on corporate innovation in Chinese family firms.

Based on the manually collected sample of listed Chinese family firms from 2003 to 2014, the study empirically examines the impact of second generation involvement on corporate innovation. The authors apply a difference-in-differences research design and a Heckman two-stage least squares regression to relieve the endogeneity concerns.

The research finds a positive relationship between second generation involvement and corporate innovation. This effect is more pronounced among the firms appointing second generation family members with overseas training experience and firms with weak external monitoring. Further analysis shows that the curtailment of related party transactions and the improvement of accounting information quality are important channels.

The findings provide several practical implications for Chinese family firms to survive the succession process and maintain competitive advantages across generations.

First, this study is helpful to understand the strategies adopted by family firms to maintain their long-term competitiveness and pursue continuing growth across generations. Second, the findings are also consistent with the transfer cost hypothesis of Fan et al. (2012) and Bennedsen et al. (2015). Finally, the findings imply that second generation involvement has a substitutive effect for external monitoring mechanisms.

The use of consumer credit by Chinese citizens has risen rapidly in the Internet era. The purpose of this paper is to predict a mechanism for credit consumption through Internet usage, with social comparison and materialism as mediators. Four types of Internet usage (social use, entertainment use, informational use, and online shopping) were identified to investigate whether different types of Internet usage influence credit consumption differently and whether the influencing mechanisms vary.

A structured online survey involving 558 valid responses from Chinese college students was completed, with structural equation modeling being applied to analyze the collected data.

Among the four types of Internet activities, online shopping was found to be the most significant predictor of credit consumption; results show that it influences credit consumption through two indirect pathways: materialism and a combination of social comparison and materialism. Social use was found to only affect credit consumption through materialism. In contrast, the influences of both informational use and entertainment use on credit consumption were insignificant.

By testing the concurrent mediating effects of social comparison and materialism, this study broadens our understanding of how Internet usage and credit consumption are connected. While most studies empirically test overall Internet usage and focus on direct relationships, we identify four types of Internet activities and demonstrate the mechanisms by which different types of Internet usage influence credit consumption, and how consumption varies based on Internet activity.

This study integrates the spiral of silence (SoS) theory and theory of planned behavior (TPB) by examining Facebook users' opinion expression avoidance, the reactions to dissenting views without revealing one's true opinion, in the context of political discussions. The present integrative approach provides a more comprehensive framework that expands our understanding of online opinion expression and withdrawal.

A cross-sectional online survey was employed, which rendered 348 valid responses from US college students (61.5% female; average age 19.11) recruited from a northeastern university.

The results categorized two sets of opinion avoidance strategies from six Facebook features. The intention to adopt “proactive avoidance strategies” (filtering out unwanted information) is positively related to descriptive norms and perceived self-efficacy, but negatively related to fear of isolation and perceived control of the urge to debate. Regarding the intention to employ “reactive avoidance strategies” (less obtrusive articulations), fear of isolation and attitudes toward opinion expression avoidance are positive determinants, whereas perceived control of the urge to debate again exerts a negative influence.

This study examines the growing variety of features that users adopt to avoid expressing their true opinion in reacting to dissenting views, updating our understanding of opinion circumvention in social media environment. As one of the few theoretically driven empirical investigations of SoS theory and TPB, the findings not only elucidate the significance of perceived behavioral control as the common ground in association with user adoption intention but also identify distinct qualities of the two sets of strategies that affect the likelihood of adoption. That is, proactive avoidance is more susceptible to normative influences, while reactive avoidance reflects user attitude and belief. This theoretical integration also helps identify diverse levels of intentions to strategically avoid opinion expression influenced by fear of isolation.

The purpose of this paper is to relate participative decision-making (PDM) to organizational learning, and examine the impact of PDM on organizational performance.

The paper integrates the resource-based theory with organizational learning theory to develop a framework, and distinguishes PDM in which decisions are jointly made by employees and managers from employee decision-making (EDM) in which decisions are completely in the hands of employees. The paper incorporates an augmented Cobb–Douglass production function into a structural equation model to estimate the performance impact of PDM and EDM.

The paper tests the framework against firm-level data form China, and finds that PDM provides an opportunity for collective learning, and has a positive relationship with productivity-based profit gains; the positive relationship is stronger in firms whose management has greater accumulated knowledge and experience; EDM fails to provide an opportunity for collective learning, and has a negative relationship with productivity-based profit gains.

Prior research focused on the role of PDM in enhancing the motivation and performance of individual employees, considered the degree of employee involvement as a continuum with the highest being decision-making “completely in the hands of employees,” and concluded that the more involved are employees in decision-making the better. This paper relates PDM to organizational performance, and challenges this conventional view from an organizational learning perspective.

In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts.

The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019.

In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects.

Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.

The purpose of this study is to examine the impact of MoS₂ on the microstructure and characteristics of micro-arc oxidized (MAO) ceramic coatings created on ZK60 magnesium alloy through the addition of varying concentrations of MoS₂ particles to the electrolyte, aiming to enhance the corrosion resistance of magnesium alloy.

The surface morphology, roughness and phase composition of the coatings were analyzed using scanning electron microscopy, a hand-held roughness tester and an X-ray diffractometer, respectively, and the corrosion resistance of the MAO coatings prepared by the addition of different contents of MoS₂ particles was tested and analyzed using an electrochemical workstation.

The results demonstrate that MoS₂/MgO composite coatings have been successfully prepared on the surface of magnesium alloys through micro-arc oxidation. Furthermore, the corrosion resistance of the ZK60 magnesium alloy prepared with the addition of 1.0 g/L MoS₂ was the best compared to the other samples.

MoS₂ particles were able to penetrate the coatings successfully during the micro-arc oxidation process, acting as a barrier in the micropores to prevent the corrosion medium from touching the surface, thus improving the corrosion resistance of the sample. The electrochemical workstation was used to study the corrosion resistance of the MoS₂/MAO coating on the ZK60 magnesium alloy.

Appropriate disposal of end-of-life (EOL) electric vehicle battery (EVB) requires new method of supply chain management (SCM) toward sustainability. Sustainable supply chain finance (SSCF) is an innovative managerial practice dedicated to release cash flow pressure and improve operational efficiency in supply chain, which has drawn increasing attentions from academia and industry. There has been few researches on the integration of EOL EVB management and SSCF yet. The paper aims to fulfill this research gap and lead to the conjunction of environmental management with economic and social concerns.

The paper conducts a systematic literature review to discuss the probable SSCF adoption on potential market of EOL EVB disposal.

The results indicate unsustainable factors and potentials to be explored in current market of EOL EVB disposal. As a solution of sustainable SCM, SSCF can ease the tension between the urgent need of EOL EVB disposal and financing problems in the supply chain, strengthening competitive advantages of EV industry.

The significance of this paper lies in offering an interdisciplinary view by drawing upon key perspectives from the emerging sustainable technology of EVB disposal and its underlying battery second use (B2U) market considering SSCF.

The paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.

In total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.

Some models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.

Providing climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

Cloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.

Cloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.

The fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.

The findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.

Using a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

Tactile sensation is an important sensory function for robots in contact with the external environment. To better acquire tactile information about objects, this paper aims to propose a three-layer structure of the interdigital flexible tactile sensor.

The sensor consists of a bottom electrode layer, a middle pressure-sensitive layer and a top indenter layer. First, the pressure sensitive material, structure design, fabrication process and circuit design of the sensor are introduced. Then, the calibration and performance test of the designed sensor is carried out. Four functions are used to fit and calibrate the relationship between the output voltage of the sensor and the contact force. Finally, the contact force sensing test of different weight objects and the flexible test of the sensor are carried out.

The performance test results show that the sensitivity of the sensor is 0.93 V/N when it is loaded with 0–3 N and 0.23 V/N when it is loaded with 3–5 N. It shows good repeatability, and the cross-interference between the sensing units is generally low. The contact force sensing test results of different weight objects show that the proposed sensor performs well in contact force. Each part of the sensor is a flexible material, allowing the sensor to achieve bending deformation, so that the sensor can better perceive the contact signs of the grasped object.

The sensor can paste the surface of the paper robot’s gripper to measure the contact force of the grasping object and estimate the contour of the object.

In this paper, a three-layer interdigital flexible tactile sensor is proposed, and the structural parameters of the interdigital electrode are designed to improve the sensitivity and response speed of the sensor. The indenter with three shapes of the prism, square cylinder and hemisphere is preliminarily designed and the prism indenter with better conduction force is selected through finite element analysis, which can concentrate the external force in the sensing area to improve the sensitivity. The sensor designed in this paper can realize the measurement of contact force, which provides a certain reference for the field of robot tactile.