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Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

We adopt an information risk view and argue that higher levels of pledge risk incurred by insiders incentivize opportunistic financial disclosure and impair the quality of information available to analysts to forecast firm performance.

We sample Chinese listed companies from 2010 to 2022. Following the literature, we apply established models to measure and test analysts’ forecasting accuracy/dispersion related to controlling shareholders pledging equity and the amount of margin call pressure. Analyst characteristics and nonfinancial disclosures proxied by CSR reports are also examined as factors likely to influence the relationship between pledge risk and analysts’ forecast quality.

We find that analysts’ earnings predictions are less accurate and more dispersed as the proportion of shares pledged (pledge ratio) increases and in combination with greater margin call pressure. Pledge ratios are significantly associated with several information risk proxies (i.e. earnings permanence, accruals quality, audit quality, financial restatements, related party transactions and internal control weaknesses), validating the channel through which equity pledges undermine analysts’ forecast quality. The results also demonstrate that forecast quality declines for a wide variety of analysts’ attributes, including high- and low-quality analysts and analysts from small and large brokerage firms. Importantly, nonfinancial disclosures, as proxied by CSR reporting, improve analysts’ forecasts.

We extend the literature by demonstrating that incremental pledge risk increases non-diversifiable information risk; all non-pledging shareholders pay a premium through more diverse and less accurate earnings forecasts. Our study provides important policy implications with economically significant costs to investors associated with insider equity pledges. Our results highlight the benefits of nonfinancial disclosures in China, which has implications for the current debate on the global convergence of CSR reporting.

This study aims to explore the synthesis and tribological performances of di-n-octyl sebacate (DOS) synthesized with spherical nano-MoS₂/sericite (SMS) and carboxylated SMS (CSMS) as catalysts.

SMS and CSMS were used as esterification catalysts to synthesize DOS from sebacic acid and n-octanol. The two catalysts were in situ dispersed in the synthesized DOS after the reaction to form suspensions. The tribological performances of the two suspensions after 20 days of storage were studied.

CSMS was more stably dispersed in DOS than SMS, and they reduced friction by 55.6% and 22.2% and wear by 51.3% and 56.5%, respectively. Such results were mainly caused by the COOH on CSMS, which was more conducive to improving the dispersion and friction reduction of CSMS than wear resistance. Another possible reason was the difference between the dispersion amounts of CSMS and SMS in DOS. The sericite of SMS was converted into SiO₂ to enhance wear resistance, while that of CSMS only partially generated SiO₂, and the rest still remained on the surface to reduce friction.

This work provides a more effective SMS catalytical way for DOS synthesis than the traditional inorganic acid catalytical method. SMS does not need to be separated after reaction and can be dispersed directly in DOS as a lubricant additive. Replacing SMS with CSMS can produce a more stable suspension and reduce friction significantly. This work combined the advantages of surface carboxylation modification and in situ catalytic dispersion and provided alternatives for the synthesis of DOS and the dispersion of MoS₂-based lubricant additives.

The main objective of this study is to analyze consumers’ willingness to pay (WTP) for country-of-origin (COO) labels of two processed food products, disentangling the value of information (VOI) that consumers place on COO information from the value they place on specific countries of origin.

A convenience sample of 96 university students completed a face-to-face experiment that included a multiple price list and a discrete choice experiment. Data are analyzed employing interval censored regressions, and random parameter logit models.

Our results indicate that, on average, consumers place a higher value on origin information when a country name is explicitly mentioned. Furthermore, COO information is, on average, more relevant to consumers for products with low involvement than for products with high involvement. Finally, the effect of ethnocentrism is heterogeneous across product categories.

Mandatory COO labeling may or may not reinforce domestic bias, depending on the rationale behind consumer support. If consumers are driven by blind ethnocentrism, it may lead to market inefficiencies. However, if they use COO as a cue to align their stated preferences with their choices, it will not. For this alignment to occur, consumers must be fully informed about product attributes, which requires new and smart methods of communicating product attributes.

The present study contributes to the literature on COO food labels, being the first in Italy to disentangle the VOI consumers place on origin information itself from the value they place on specific countries of origin. In addition, it is the first study that applies this methodology across different product categories, each of which has a different level of cultural sensitivity to consumers.

The purpose of this paper is to fill low content of silica to improve the wear resistance of graphite/polytetrafluoroethylene (PTFE) composites, and to discuss the effect of low content of silica on the morphology of terrace-like transfer film.

The tribological properties of silica/graphite/PTFE composites were tested by rotating pin-on-disk friction and wear tester, and the morphology of terrace-like transfer film was observed by 3D laser scanning microscope and quantitatively analyzed through the multi-Gaussian function linear combination model.

The results showed that adding 3 wt.% silica in graphite/PTFE composites can reduce the wear rate by 87%. More importantly, the morphology of terrace-like transfer film changed significantly after filling a small amount of silica, including the increase of the number of layers and the coverage rate of transfer film.

This work is of great significance for further understanding the transfer film and achieving its morphology control to optimize the wear of high performance PTFE composites.

This study aims to examine the effect of political conditions on the relationship between corporate governance and firm performance in two sub-Saharan African (SSA) countries, Ghana and Kenya.

This study used a panel data methodology, examining data from a sample of 72 companies (Ghana: 25 and Kenya: 47) from 2018 to 2022. This study used panel quantile regression and the Huber M-estimation robust least squares regression methods.

The research reported that larger boards, diversity and ownership concentration do not affect business performance while board independence improves corporate success in both countries. The findings about chief executive officer (CEO) duality were mixed. In Ghana, CEO duality has a positive effect on firm performance, but in Kenya, the study finds that CEO duality hurts firms’ performance. The results found that higher levels of institutional ownership decreased firm performance in both countries. The research found that Ghana’s political environment had a greater impact on corporate governance and business performance nexus than Kenya’s.

The research is limited to Ghana and Kenya. This study emphasises the necessity for governments in both countries to maintain a stable political environment, implement policies that encourage economic and policy continuity and reduce political uncertainty to improve business conditions.

This study emphasises the necessity for governments in both countries to maintain a stable political environment, implement policies that encourage economic and policy continuity, and reduce political uncertainty to improve business conditions.

To the best of the authors’ knowledge, this study is unique because it is the first in SSA to address a research gap by investigating a comparative analysis of the relationship between corporate governance, political environments and firm performance in two distinct countries with different political situations.

The purpose of this paper is to explore the different contextual and psychological determinants of organisational resilience (OR) in the context of global mobility in multinational enterprises (MNEs). Banking upon the conservation of resources theory, this paper studies how and when reattachment to work (RTW), work engagement (WE) and two types of presenteeism lead to OR. Further, in the backdrop of the post-pandemic world of work, this paper also conceptualises the conditional effects of trait resilience (TR), organisational support (OS) and expatriation type (ET) on the aforementioned linkages.

This paper develops a conceptual framework that depicts various antecedents of OR in MNEs. Several testable propositions are also offered alongside the model’s moderated mediation and moderated moderation relationships.

The conceptual framework depicts the causal relationships between RTW and OR, such that Flexible RTW increases OR through higher WE and functional presenteeism under the conditional influences of TR, OS and ET, whereas rigid RTW decreases OR through lower WE and dysfunctional presenteeism under the conditional effects of TR, OS and ET.

To the best of the authors’ knowledge, this paper is the first of its kind that explores the psychological and contextual antecedents of the OR of MNEs and offers numerous testable propositions. The nexus of unique relationships presented in the conceptual framework bridges a crucial gap in the literature that explores the complexities of the post-pandemic workplace in the context of global mobility.

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.

While prevalence and value of nonclinical hospital workers, like quality or education professionals, increase, their work engagement is understudied. Work engagement of nonclinical and clinical hospital workers is critical considering the pressure of major challenges in healthcare. The pandemic was a natural experiment for this.

We conducted an observational survey study among all nonclinical and clinical hospital workers of the Jeroen Bosch Hospital, the Netherlands. In an employee satisfaction survey, we measured work engagement under acute pressure (just after the first COVID-19 wave in July 2020) and chronic pressure (within the second COVID-19 wave in November 2020) and to what extent psychological demands and co-worker support were related to work engagement.

For all hospital staff, “average” levels of work engagement were found under acute (response rate 53.9%, mean 3.94(0.81)) and chronic pressure (response rate 34.0%, mean 3.88(0.95)). Under acute pressure, nonclinical hospital workers scored lower on the subcategory dedication than clinical workers (mean 4.28(1.05) vs mean 4.45(0.99), p < 0.001). Under chronic pressure, no differences were found. For both nonclinical and clinical hospital workers, co-worker support was positively related to overall work engagement (beta 0.309 and 0.372). Psychological demands were positively related to work engagement for nonclinical hospital workers (beta 0.130), whereas in clinical hospital workers, psychological demands were negatively related to vigor (beta −0.082).

Hospitals face times of pressure. Fostering co-worker support under pressure may be vital for hospital management.

Work engagement of nonclinical hospital workers is understudied.

Induction heating processes need to adapt to complex geometries or variable processes that require a high degree of flexibility in the induction heating setup. This is usually done using complex inductors or adaptable resonant tanks, which leads to costly and constrained implementations. This paper aims to propose a multi-level, versatile power supply able to adapt the output to the required induction heating process.

This paper proposes a versatile multilevel topology able to generate versatile output waveforms. The methodology followed includes simulation of the proposed architecture, design of the power electronics, control and magnetic elements and laboratory tests after building a 10-level prototype.

The proposed converter has been designed and tested using an experimental prototype. The designed generator is able to operate at 1 kVpp and 100 A at 250 kHz, proving the feasibility of the proposed approach.

The proposed converter enables versatile waveform generation, enabling advanced tests and processes on induction heating system. The proposed system allows for multifrequency generation using a single inductor and converter, or advanced tests for inductive and capacitive components used on induction heating systems. Unlike previous multifrequency proposals, the proposed generator enables a significantly improved versatility in terms of operational frequency and amplitude in a single converter.