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With the rapid development of paid online social question and answer (Q&A) communities, monetary social functions have been introduced and have potential benefits for both platforms and users. However, these functions' impact on knowledge contribution remains uncertain. This study proposes a conceptual model based on the stimulus–organism–response framework, according to which monetary and non-monetary social functions can help nurture short-term and long-term relationships among community users, and thereafter improves social identity and knowledge-sharing intentions.

This study selects Zhihu, a famous online social Q&A community in China, and conducts an online survey to collect data from its frequent users. A sample of 286 valid questionnaires was collected to test our research model by using a structural equation modeling method. In addition, a bootstrapping approach is used to test the mediation effect.

Results indicate that monetary social functions help nurture short-term and long-term relationships among community users. However, non-monetary social functions only affect short-term relationships directly. Short-term and long-term relationships both have a positive relationship with social identity and thereafter improve users' knowledge-sharing intentions.

This study focuses on users' knowledge-sharing intentions in Q&A communities from the perspective of social. Specifically, we separated social functions in Q&A platforms into monetary and non-monetary ones and explored their impact on the development of short-term and long-term relationships. Results demonstrate the importance of monetary social functions and explain how monetary and non-monetary social functions affect users' knowledge-sharing intentions in different approaches.

As social network sites (SNS) have increasingly become one of the most important channels for communication, the related privacy issues gain more and more attention in both industry and academic research fields. This study aims to connect the antecedents of information privacy disclosure on SNS.

Based on exchange theory, this study tries to investigate the decision-making process for information privacy disclosure on SNS. Factors from both user’s and website’s perspectives are taken into account in the proposed model.

The results suggest that an individual’s perceived benefits will increase their willingness to disclose information privacy on SNS, but perceived risks decrease this kind of willingness. The authors also find social network size, personal innovativeness and incentive provision positively affect people’s perceived benefits.

Moreover, privacy invasion experience enhances perceived personal risks, but website reputation helps to reduce perceived risks.

To improve the efficiency and economy of electro-mechanical product's recycle process, this paper aims to propose a disassembly sequence planning (DSP) method to reduce additional efforts of removing extra parts in selectable disassembly.

The methodology has three parts, which includes a disassembly hybrid graphic model to describe the product disassembly information, an object inverse-directed method to optimize the disassembly design and a model reconstruction method to achieve a better DSP.

According to the disassembly cost criteria and the parameters of disassembly tools, the disassembly efficiency increases and the disassembly cost decreases due to the use of partial destructive mode compared with non-destructive mode. The proposed partial destructive DSP is more efficient and economical.

Partial destructive disassembly mode cannot be used for the flammable or explosive component in the procedure of the DSP optimization algorithm.

DSP of an electric corkscrew is analyzed to investigate the accuracy and efficiency of the proposed method.

This paper proposes a partial destructive disassembly based DSP method for product disassembly, which provides a new approach for the disposal of end-of-life products.

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 purpose of this paper is to find alternative strategies to change negative output gaps in China.

A path Philips curves approach is proposed to investigate output gaps, which develops hybrid Philips curves with the control variables of money, house prices and interest rates.

An alternative strategy to stop the decline in output gaps rate is to perform interest rate, house price, and money growth rate about 3, 1 and 15 percent, respectively. The results also indicate that only one of monetary increase, changes in interest rates, and house price adjustments are difficult to change the negative output gap.

Alternative strategies cannot only change the negative output gap, but also succeed in pushing the inflation rate down to 3 percent.

This study provides a new path Philips curves to simulate how the macroscopic control variables influence output and inflation. It provides a useful insight for stopping the decline in output gaps.

The purpose of this study is to investigate the influence of varying concentrations of nano-SiO₂ particle doping on the structure and properties of the micro-arc oxidation (MAO) coating of 7075 aluminum alloy. This research aims to provide novel insights and methodologies for the surface treatment and protection of 7075 aluminum alloy.

The surface morphology of the MAO coating was characterized using scanning electron microscope. Energy spectrometer was used to characterize the elemental content and distribution on the surface and cross section of the MAO coating. The phase composition of the MAO coating was characterized using X-ray diffractometer. The corrosion resistance of the MAO coating was characterized using an electrochemical workstation.

The results showed that when the addition of nano-SiO₂ particles is 3 g/L, the corrosion resistance is optimal.

This study investigated the influence of different concentrations of nano-SiO₂ particles on the structure and properties of the MAO coating of 7075 aluminum alloy.

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.

Building on a TripAdvisor data for five Mediterranean destinations, namely, Greece, Croatia, Italy, France and Spain, this study analyses the constituents of restaurants' online reputation and their interrelation with destination competitiveness, in particular two Travel and Tourism Competitiveness Index (TTCI) pillars, namely, Prioritisation of Travel and Tourism and Price Competitiveness.

The analysis has revealed that restaurants' online reputation is positively influenced by two factors, namely, Core elements, i.e. cooking, service and price-quality ratio, and Price. Furthermore, the restaurants' online reputation does not influence destination competitiveness (TTCI) directly, but indirectly throughout its main constituents, i.e. service and price. Price is the only variable with significant influence on overall TTCI. Within the sample of these destinations, Balkan countries, i.e. Greece and Croatia, perform very well in terms of their restaurants' online reputation. On the other hand, considering the overall TTCI rating, their competitive positions are substantially lower than those of Italy, France and Spain.

The study provides new insights into the relationship between gastronomic offer and destination competitiveness, and valuable practical implications for destination and hospitality management. Moreover, this study addresses various gaps in existing research on this topic. Specifically, it validates the reputation elements presented online using TripAdvisor data and analyses the impact of electronic Word of Mouth (eWOM) not only as the outcome variable of other constructs, as is the case in the literature, but also as a central construct of the analysis. In doing so, it extends current research on this topic and fills the gap regarding the inclusion of the supply-side stakeholder perspective, which has long been recognised as necessary in any attempts to measure competitiveness.

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.