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Literature shows that the antecedents of eWoM have received limited attention and the present scales used for measuring eWoM in the hospitality and tourism industry are outdated. Therefore, this study aims to construct a new scale for the generation of positive eWoM in the hospitality and tourism industry.

This study developed a novel scale on eWoM based on the four dimensions of the unified theory of acceptance and use of technology.

The exploratory and confirmatory factor analysis confirms the factorial structure of the new scale. The exploratory factor analysis shows that “performance expectancy” has the highest impact on the constitution of positive eWoM with 8 items, followed by “social influence” and “facilitation condition” with 5 items each. The factor “effort expectancy” is found to have the lowest impact on the constitution of positive eWoM in the hospitality and tourism industry with 3 items. The confirmatory factor analysis in terms of the construct reliability, average variance extracted and maximum shared variance tests confirmed the model validity of the new scale.

This study ensures measuring eWoM with the latest norms that will assist in prudent policy formulation. These results insights into policymakers from the hospitality and tourism industry for the generation of positive eWoM towards their business which will help them achieve better customer loyalty.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

This paper aims to investigate the relationship between uncertainty and corporate cash holdings with the moderating role of political connections.

We employ fixed effects estimation on a panel dataset of 669 Vietnamese listed firms over the 2010–2020 period, with one- and two-way standard error clustering. We conduct various robustness tests, including two-stage least squares/instrumental variable and generalized method of moments regressions, alternative cash holding measure, and additional controls for macroeconomic conditions and ownership types.

The effect of uncertainty on cash holdings is weakened for firms with political connections relative to those without the connections. Although general firms depend on cash flows to adjust their cash holding behavior when uncertainty increases, our findings suggest that politically connected firms do not rely on internal cash flows to accumulate cash when confronted high uncertainty.

Our findings on the role of political connections in moderating the relationship between cash holding and economic policy uncertainty have practical implications for policymaking. Since political connections serve as a buffer for a firm’s liquidity, firms may want to seek those connections, which can, in turn, lead to increasing informal costs and unfair business environment.

This is the first study investigating the role of political connections to the nexus of cash, cash flow and uncertainty, providing novel evidence regarding the less dependence on internal cash flows to save cash by politically connected firms. Second, the paper enriches the literature on the motives of cash holdings by proposing a modified agency view in the context of weak investor protection. Therefore, our findings strengthen the explanation for the positive effect of uncertainty on firms’ cash holdings in emerging markets.

Research on the organizational ramifications of chief executive officer (CEO) greed remains scarce. This study intends to fill this gap by examining the impact of CEO greed on an important yet risky corporate strategy, corporate tax avoidance (CTA). Drawing on upper echelons theory, the authors argue that greedier CEOs tend to engage in more CTA. The relationship is weaker when CEOs experienced economic recessions in their early career and stronger when CEOs are endowed with equity ownership of their respective firms.

The authors test the hypotheses with data from US public firms from 1997 to 2008 and employ the ordinary least square regression analysis to analyze the hypothesized relationships. The authors also test the robustness of the results by performing the two-stage least square regression and propensity score matching analyses.

The findings lend broad support to all the hypotheses. The authors find that greedier CEOs tend to engage in more CTA by paying lower corporate taxes. The impact of greed on CTA is attenuated when CEOs are recession CEOs and is exacerbated when CEOs own large numbers of firm shares.

This paper contributes to the upper echelons research by investigating a novel executive personal characteristic, greed, and its negative impact on an important organizational outcome. This paper also contributes to the growing tax research that recognizes the important role executives play in shaping corporate tax strategies.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

This study examines the impact of university science parks’ (USPs) capabilities on revenue generation and introduces regional innovation as a moderating variable. This study aims to provide insights into enhancing revenue generation and fully leveraging the role of USPs in promoting revenue generation.

This study employs system generalized method of moments (GMM) estimation for 116 universities in China from 2008 to 2020, using hierarchical regression analysis to examine the relationships between variables.

The findings suggest that USPs play a beneficial role in fostering revenue generation. Specifically, the provision of incubation funding demonstrates a positive correlation, while USPs size exhibits an inverted U-shaped pattern, with a threshold at 3.037 and a mean value of 3.712, highlighting the prevalent issue of suboptimal personnel allocation in the majority of USPs. Moreover, the analysis underscores the critical moderating influence of regional innovation, affecting the intricate interplay between USPs size, incubation funding and revenue generation.

The single country (China) analysis relied solely on the use of secondary data. Future studies could expand the scope to include other countries and employ primary data collection. For instance, future research can further examine how regional development and USPs strategic plan impact revenue generation.

The study recommends that USPs managers and policymakers recognize the importance of incubation funding and determine the optimal quantity of USPs size to effectively foster revenue generation in USPs. Policymakers can use regional innovation as a moderating variable to reinforce the relationship between USPs size and incubation funding on revenue generation.

The study’s findings can contribute to the strategic industry growth and economic development of nations by promoting revenue generation. Leveraging the role of USPs and implementing the study’s recommendations can strengthen innovation and technology capabilities, driving strategic industry growth and economic development. This can enhance global competitiveness and promote sustainable economic growth.

This study introduces regional innovation as a moderating variable and provides empirical evidence of its influence on the relationship between USPs size and incubation funding on revenue generation. This adds value to research to the existing literature on USPs and revenue generation by showcasing the importance of examining the regional impact in research and innovation.

A reconfigurable manufacturing system (RMS) can provide manufacturing flexibility, meet changing market demands and deliver high performance, among other benefits. However, adoption and performance improvement are critical activities in it. The current study aims to identify the important factors influencing RMS adoption and validate a conceptual model as well as develop a structural model for the identified factors.

An extensive review of RMS articles was conducted to identify the eight factors and 47 sub-factors that are relevant to RMS adoption and performance improvement. For these factors, a conceptual framework was developed as well as research hypotheses were framed. A questionnaire was developed, and 117 responses from national and international domain experts were collected. To validate the developed framework and test the research hypothesis, structural equation modeling was used, with software tools SPSS and AMOS.

The findings support six hypotheses: “advanced technologies,” “quality and safety practice,” “strategy and policy practice,” “organizational practices,” “process management practices,” and “soft computing practices.” All of the supported hypotheses have a positive impact on RMS adoption. However, the two more positive hypotheses, namely, “sustainability practices” and “human resource policies,” were not supported in the analysis, highlighting the need for greater awareness of them in the manufacturing community.

The current study is limited to the 47 identified factors; however, these factors can be further explored and more sub-factors identified, which are not taken into account in this study.

Managers and practitioners can use the current work’s findings to develop effective RMS implementation strategies. The results can also be used to improve the manufacturing system’s performance and identify the source of poor performance.

This paper identifies critical RMS adoption factors and demonstrates an effective structural-based modeling method. This can be used in a variety of fields to assist policymakers and practitioners in selecting and implementing the best manufacturing system.

This paper aims to facilitate researchers, practitioners and policymakers in understanding and managing the impact of the black swan event – COVID-19 on work from home in the social science subject area through bibliometric analysis. For this purpose, the authors analyzed publications from the Scopus database.

In this paper, the authors conducted bibliometric analysis based on two major techniques: performance analysis and science mapping. The authors applied VOSviewer and Biblioshiny to address the research questions of present study. The study explored the hot trend topics and summarized them with discussions and implications.

Based on the analysis of 500 publications, the authors present an overview of performance and science mapping from the perspective of different aspects such as publication output and authors. Also, authors visualized the text mining by co-word analysis forming nine clusters as well as mapping trend topics. The existing publications were divided into ten clusters according to different keyword analyses: Leadership, Mental health, Technology, Crisis Management, Gender, Challenges, well-being and Work-life balance.

Sample from the Scopus database is not exhaustive, and the dataset may be skewed due to the adoption of the selection criteria. The authors’ concentration was on academic publications in English that excludes potentially intriguing and pioneering studies done in other languages. The study area was limited to social science only.

The paramount lesson is that the COVID-19 quandary is multifaceted, necessitating not simply adaptations to current strategies but also an understanding and analysis of advancements in the economy, commerce and society. According to the analysis presented above, to overcome the COVID-19 “black swan event”, managers must think ahead. The analysis gives leaders and decision-makers a range of useful information on work from home (WFH) difficulties in COVID-19, as well as initiatives and revisions that must be implemented at the economic, social and scientific aspects when dealing with such uncertainties. The findings also aid managers in forecasting the need for sophisticated technology, organizational agility and resilience to attain the desired direction of progress.

With a focus on addressing WFH during COVID-19 from social science perspective and to synthesize its future research directions systematically, the authors performed Bibliometric analysis both with VOSviewer and Biblioshiny, in order to enhance the overall analysis for higher accuracy and more reliable results that is unique value addition and contribution to the existing literature.