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Presents a macro analysis of the dynamics of temporally linked crisis events and the non‐linear effects resulting from the linkage. The nature of crisis is explored as a singular conceptual construct, and four forms of linkage between crises are assessed. Specific emphasis is placed on how such linkages amplify the total damage upon society and lengthen the duration of the cumulative recovery effort. Based on the assessment, new points of strategic planning focus are identified to drive continued empirical research and to support the development of future operational plans in crisis response.

This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this paper: designing an unsupervised method for extracting online Chinese features and opinion pairs, distinguishing different intensities of polarity in opinion words and examining the changes in polarity in the time series.

In this paper, a review analysis system is proposed to automatically capture feature opinions experienced by other tourists presented in the review documents. In the system, a feature-level SA is designed to determine the polarity of these features. Moreover, an unsupervised method using a part-of-speech pattern clarification query and multi-lexicons SA to summarize all Chinese reviews is adopted.

The authors expect this method to help travellers search for what they want and make decisions more efficiently. The experimental results show the F-measure of the proposed method to be 0.628. It thus outperforms the methods used in previous studies.

The study is useful for travellers who want to quickly retrieve and summarize helpful information from the pool of messy hotel reviews. Meanwhile, the system will assist hotel managers to comprehensively understand service qualities with which guests are satisfied or dissatisfied.

We investigate herding behavior and explore how risk aversion interacts with herding in a sample of selected sustainability indices. Furthermore, we evaluate volatility co-movements and dynamic and time-varying correlations of two notable indicators: the cross-sectional absolute deviation of returns (CSAD) and the risk aversion index (RAI). Moreover, we explore a spillover mechanism (in the short and long run) of risk aversion to sustainable investing.

Our study uses daily prices from 01/06/2012 to 15/07/2022 obtained from S&P Dow Jones Indices. We use autoregressive - Glosten, Jagannathan, and Runkle generalized autoregressive conditional heteroscedastic (AR(1)-GJR GARCH) methodologies to measure the impact of cross-sectional absolute deviation of returns (CSAD) and risk aversion (RAI) indicators on the conditional variance of selected sustainability indices. Furthermore, we employ dynamic conditional correlation with generalized autoregressive conditional heteroscedasticity, generalized autoregressive conditional heteroscedasticity generalized autoregressive conditional heteroscedasticity mixed data sampling and dynamic conditional correlation with mixed data sampling models to examine any dynamic correlation, spillover volatility effects and the predictability stance of the CSAD and the RAI factors on sustainable investing.

Our empirical outcomes capture no-herding behavior but display herding on the risk aversion indicator. The cross-sectional dispersion of returns positively affects the conditional variance of all selected sustainable markets, besides emerging markets, while the risk aversion factor negatively influences the conditional variance for Europe and the USA. We have identified long-term contagion effects relating to the variability of returns in our sample, with the exception of emerging markets.

The dispersion of returns can predict the swings of long-term volatilities of Nordic and Europe markets, while the risk aversion factor can predict the long-run volatilities of sustainable markets except Nordic.

The current study presents, for the first time in the sustainable finance literature, an empirical analysis of herding and risk aversion in sustainable investment returns over time. Our findings offer valuable insights to fund managers, finance professionals and investors, providing them with an opportunity to proactively manage their portfolios and reduce financial risk by understanding the volatility behavior of sustainable investing. Furthermore, it is crucial to explore and understand how the dispersion of returns and risk aversion interact with sustainable markets for the construction of optimal portfolios.

The question of whether intellectual capital (IC) is beneficial to firm performance is debatable because of the diverse effects of IC and its components on firm performance. Building on the concept of pay–performance relation, this study aims to provide new insights into how changes in IC affect changes in firm performance.

Data envelopment analysis is employed to measure firm performance, and value-added intellectual coefficient (VAIC™) is selected to evaluate the IC and its components, namely human capital efficiency (HCE), structural capital efficiency (SCE), and capital employed efficiency (CEE). Ordinary least squares regression is applied to study the relationship between changes in IC and changes in firm performance using 6,408 firm-year observations of electronics companies listed in Taiwan from 2006 to 2017.

Empirical results suggest that IC efficiency and CEE significantly and negatively affect firm performance, thereby suggesting a contradictory common sense with the resource-based view on the beneficial effects of IC. However, changes in IC efficiency and HCE are significantly and positively related to changes in firm performance, including changes in firm efficiency and sales growth.

This study suggests that managers should continuously pay attention to adjusting their IC, especially human capital (HC) for better decisions that help grow firm performance. Moreover, investors can grasp how sensitive firm performance is to IC.

This study argues the relationship between IC and firm performance in the same vein as a pay-for-performance link, suggesting that future studies should account for increases or decreases in IC.

The purpose of this study is to examine the question of whether the repatriation adjustment process varies with different combinations of duration and purpose of international assignments.

A multiple-case study within one company was conducted based on in-depth interview data.

The authors find that learning-driven international assignments are more beneficial for career growth and receive better organizational support, as assignees are able to maintain regular communication (visibility) with the home unit. On the other hand, those on demand-driven, long-duration international assignments need to have a closer connection (integration) with employees in the host unit and find it challenging to maintain high visibility in the home unit simultaneously.

The authors contribute to existing research by highlighting that demand-driven assignees on longer assignments face greater challenges upon returning home. In addition, expatriates on short-term assignments face drastically fewer challenges than expatriates on longer assignments.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

The purpose of this paper is to investigate the effect of nickel-plated graphene (Ni-GNS) on the microstructure and mechanical properties of 96.5Sn3Ag0.5Cu (SAC305) lead-free solder joints before and after an electro-migration (EM) experiment.

In this paper, SAC305 solder alloy doped with 0.1 Wt.% Ni-GNS was prepared via the powder metallurgy method. A U-shaped sample structure was also designed and prepared to conduct an EM experiment. The EM experiment was carried out with a current density of 1.5 × 104 A/cm2. The microstructural and mechanical evolutions of both solder joints under EM stressing were comparatively studied using SEM and nanoindentation.

The experimental results showed that for the SAC305 solder, the interfacial intermetallic compounds (IMC) formulated a protrusion with an average height of 0.42 µm at the anode after 360 h of EM stressing; however, despite this, the surface of the composite solder joint was relatively smooth. During the stressing period, the interfacial IMC on the anode side of the plain SAC305 solder showed a continuous increasing trend, while the IMC at the cathode presented a decreasing trend for its thickness as the stressing time increased; after 360 h of stressing, some cracks and voids had formed on the cathode side. For the SAC305/ Ni-GNS composite solder, a continuous increase in the thickness of the interfacial IMC was found on both the anode and cathode side; the growth rate of the interfacial IMC at the anode was higher than that at the cathode. The nanoindentation results showed that the hardness of the SAC305 solder joint presented a gradient distribution after EM stressing, while the hardness data showed a relatively homogeneous distribution in the SAC305/ Ni-GNS solder joint.

The experimental results showed that the Ni-GNS reinforcement could effectively mitigate the EM behavior in solder joints under high current stressing. Specifically, the Ni particles that plated the graphene sheets can work as a fixing agent to suppress the diffusion and migration of Sn and Cu atoms by forming Sn-Cu-Ni IMC. In addition, the nanoidentation results also indicated that the addition of the Ni-GNS reinforcement was very helpful in maintaining the mechanical stability of the solder joint. These findings have provided a theoretical and experimental basis for the practical application of this novel composite solder with high current densities.

The purpose of this paper is to examine how communication practices influence individuals’ team assembly and performance in open innovation contests.

This study analyzed behavioral trace data of 4,651 teams and 19,317 participants from a leading open innovation platform, Kaggle. The analyses applied weighted least squares regression and weighted mediation analysis.

Sharing online profiles positively relates to a person’s performance and likelihood of becoming a leader in open innovation teams. Team assembly effectiveness (one’s ability to team up with high-performing teammates) mediates the relationship between online profile sharing and performance. Moreover, sharing personal websites has a stronger positive effect on performance and likelihood of becoming a team leader, compared to sharing links to professional social networking sites (e.g. LinkedIn).

As team collaboration becomes increasingly common in open innovation, participants’ sharing of their online profiles becomes an important variable predicting their success. This study extends prior research on virtual team collaboration by highlighting the role of communication practices that occur in the team pre-assembly stage, as an antecedent of team assembly. It also addresses a long-standing debate about the credibility of information online by showing that a narrative-based online profile format (e.g. a personal website) can be more powerful than a standardized format (e.g. LinkedIn).

Open innovation organizers should encourage online profile sharing among participants to facilitate effective team assembly in order to improve innovation outcomes.

The current study highlights the importance of team assembly in open innovation, especially the role of sharing online profiles in this process. It connects two areas of research that are previously distant, one on team assembly and one on online profile sharing. It also adds new empirical evidence to the discussion about online information credibility.