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Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

The purpose of this article is to examine the antecedents and consequences of organizational silence and employee silence to determine whether these two concepts should be distinguished rather than used interchangeably in research.

This study conducted a systematic literature review of 79 studies on organizational silence and 113 on employee silence, leading to three major findings.

First, this study shows that organizational silence is a collective phenomenon and employee silence occurs at the individual level; therefore, indicating they should be treated as two distinct concepts. Second, both types of silence are influenced by contextual factors (internal and external) and leadership. Third, organizational silence impacts both individual and organizational outcomes, whereas employee silence mainly affects an individual’s psychological health and performance.

This research clarifies the distinction between organizational silence and employee silence, offering guidance for researchers on how to approach these concepts. It also highlights the critical need to address workplace silence and the potential harm it may cause to both organizational and individual well-being if left unaddressed. Furthermore, this research supports organizational leaders and human resource developers in fostering a healthier work culture, improving performance and driving continuous improvement.

Digital technologies have transformed business management practices and adapted them to shorter product lifecycles. As a result, firms are shifting their approach to building new competitive advantage from cost-oriented to entrepreneurial orientation (EO). This study aims to analyze the innovation performance (IP) in the context of EO from a knowledge management perspective. It constructs the functional path of the relationships among EO, knowledge coupling (KC) and IP of Chinese manufacturing firms to achieve business success.

Using data from 157 listed Chinese manufacturing firms from 2012 to 2021, the authors construct a panel data model to test the effect of EO on IP. This study classifies KC into existing knowledge coupling (EKC) and new and existing knowledge coupling (NKC) and analyzes their mediating effects in the above relationships.

This study finds that EO has an insignificant, inverted U-shaped relationship with IP. Both EKC and NKC have a significant, inverted U-shaped relationship with IP; in other words, if EKC and NKC increase, the IP of Chinese manufacturing firms first increases and then decreases, and EKC and NKC have a complete mediating effect on the relationship between EO and IP.

This study provides an in-depth analysis of IP from an EO perspective. The study’s findings enrich and extend the theoretical relationship between EO and IP. The authors also propose a knowledge management perspective for entrepreneurship research. These findings improve the current understanding of the role and function of KC in EO.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

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.

Unhealthy diets are associated with an increased risk of non-communicable diseases and present a significant public health challenge. When developing effective interventions and policies, consideration must be given to the unique social culture in which food choice is embedded. Health vulnerabilities to poor nutrition exist throughout life but may be influenced by socio-cultural factors such as age. This study aimed to assess the attitudes of older or younger Chinese consumers towards healthy eating and explore the factors influencing their food choices.

Semi-structured interviews were conducted in Wuhan, China, with 20 consumers aged 18–25 (Group A) and 20 consumers aged 65 and over (Group B).

Thematic analysis revealed that the two groups had positive attitudes towards healthy eating, although Group A participants were more knowledgeable. Time pressure, food prices and social networks differentially influence healthy eating practices across age groups.

Given China’s economic and cultural context, healthy eating interventions should consider the individual characteristics and food preferences of the different age groups. This approach can optimize targeted healthy eating interventions, and media communications related to healthy eating.

Although the importance and variety of emotions have been emphasized in existing literature, studies on discrete emotions remain limited. This study aims to propose a method for more precise recognition and calculation of emotions in massive amounts of online data on attraction visitor experiences and behaviour, by using discrete emotion theory.

Using HowNet’s word similarity calculation technique, this study integrated multiple generic dictionaries, including the sentiment vocabulary ontology database of the Dalian University of Technology, the National Taiwan University Sentiment Dictionary and the Boson Dictionary. Word2vec algorithm filters emotion words unique to hospitality and tourism in 1,596,398 texts from Sogou News, Wikipedia and Ctrip reviews about attractions, and 1,765,691 reviews about attractions in China.

The discrete sentiment dictionary developed in this study outperformed the original dictionary in identifying and calculating emotions, with a total vocabulary extension of 12.07%, demonstrating its applicability to tourism.

The developed new dictionary can be used by researchers and managers alike to quickly and accurately evaluate products and services based on online visitor reviews.

To the best of the authors’ knowledge, this study is the first to construct a sentiment dictionary based on discrete emotion theory applicable to hospitality and tourism in the Chinese context. This study extended the applicability of affective psychology to hospitality and tourism using discrete emotion theory. Moreover, the study offers a methodological framework for developing a domain-specific sentiment dictionary, potentially applicable to other domains in hospitality.

The purpose of this study is to shed light on the impact of the COVID-19 pandemic on cross-border M&A advisory business in Japan.

Using the grounded theory approach and trust embedded in network theory, the authors conducted interviews with 12 Japanese senior M&A advisors from 8 different advisory firms, categorizing the results into three general themes.

The first theme comprises deep insights contributing to a “decrease in M&A deals” during the COVID-19 crisis as not many deals could be advised while several were canceled. The second theme is “time delays,” with ongoing deals taking more time to be completed. The third gen-eral theme concerns the “new normal” after the COVID-19 era, as M&A advisors have learned to cope with their challenges and are subsequently more efficient, especially time-wise, in dealing with clients.

The research was based on qualitative data gathered from only 12 interviewees from 8 different consultancies who were Japanese senior M&A advisors.

The practical implications of this research go beyond the findings of M&A studies conducted during and soon after the COVID-19 pandemic. Consulting firms commonly report on the COVID-19 impact on M&A markets or client firms but are silent about their own hardships in establishing trustful relationships with clients during the COVID-19 pandemic. In contrast, we turn the spotlight on the consulting firms themselves to understand their challenges.

The originality of this research goes beyond previous studies on the economic impact of firms; the authors lay out the foundation for the hardship of establishing trustful relationships between M&A advisors and their clients during the COVID-19 crisis. The three general themes elucidated the impact of the pandemic, highlighting the challenges confronting the Japanese M&A advisory business. These themes thus provide a more nuanced understanding of the COVID-19 impact.

This study aims to explore the roles of Zhongyong and political efficacy on citizens’ intention to use digital government platforms for e-participation (i.e. e-participation intention). Zhongyong is a dialectical way of thinking that influences Chinese behavioral intentions and approaches. Political efficacy is a predictor of traditional political participation. Both of them have not been adequately investigated in this digital era, particularly regarding e-participation in digital government platforms. Therefore, this study investigates their relationships.

A quantitative model is constructed to examine the relationship between Zhongyong and citizens’ e-participation intention (internal and external) political efficacy serves as a mediator. An online questionnaire gathered 345 responses from three representative provinces of China (i.e. Guangdong, Jiangxi and Shanxi). Partial least square structural equation modeling (PLS-SEM) was adopted and executed with Smart PLS 4.0 to analyze the data.

Zhongyong and (internal and external) political efficacy can positively influence citizens’ e-participation intention. Moreover, (internal and external) political efficacy mediates the relationship between Zhongyong and citizens’ e-participation intention.

This research focuses on Chinese culture Zhongyong and surveyed Chinese citizens, thus is limited to the Chinese context. Second, this study used cross-sectional data. Third, this study only investigated two factors’ effects on e-participation, i.e. Zhongyong and political efficacy.

The findings provide multifaceted strategies for improving citizens’ adoption of digital government platforms for e-participation. Incentive policies to boost citizens’ (internal and external) political efficacy can be launched. To achieve broader citizen participation, a participative culture can be cultivated based on Zhongyong.

This study constructs a novel model that innovatively links Zhongyong thinking, political efficacy and e-participation intention. The results underscore the importance of Zhongyong culture and political efficacy in increasing citizens’ e-participation intention.

Customer resource allocation efficiency (RAE) refers to the ability of customers to use, allocate and manage their available resource inputs to produce valuable outputs. This study draws on organizational entrainment theory (OET) to examine how the implementation of supplier digitalization affects customer RAE through supply chain entrainment.

Based on supplier and customer data disclosed by Chinese A-share listed firms from 2009 to 2022, this study uses fixed effects panel data models to empirically examine the impact of supplier digitalization on customer RAE and the mechanistic role of supply chain entrainment.

The results show that supplier digitalization significantly increases customer RAE. It improves RAE by influencing the three dimensions of supply chain entrainment (the bullwhip effect, inventory management coordination and risk management coordination).

This study provides important insights into how managers can adapt the external digital environments and maintain synchronous operations with their supply partners. Our findings demonstrate how managers can fully leverage the advantages of digitalization of their suppliers to improve their own RAE through supply chain entrainment strategies.

This study introduces the concept of supply chain entrainment to reveal how firms optimize their own resource allocation strategies and achieve efficient operations. Our research enriches the understanding of supply chain governance in the digital age and contributes to the literature on supply chain digitalization.