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Agenda for knowledge creation within inter-project alliances and inter-firm supply chain networks has been extensively debated. However, the existing knowledge networks within consultant-supplier interfaces in the architecture, engineering and construction (AEC) industry seem to be vague, loose, incidental and insignificant. This study examines factors affecting knowledge networking intention (KNI) within construction service supply chain (CSSC) networks.

Data analysis was conducted on a quantitative survey of 161 consulting professional service firms in Tanzania, employing stepwise regression modelling as the statistical technique.

The results indicate that three types of knowledge inertia (KI) exert varying effects on KNI. While both procedural (PI) and learning inertia (LI) negatively impact KNI, experience inertia (EI) has no impact on KNI. In addition, knowledge governance (KG) mechanisms are found to strongly strengthen and leverage the negative effects of PI and LI on KNI and the positive link between EI and KNI within outbound and heterogeneous CSSC actors, with formal KG having greater leverage than informal KG.

The study offers guidance on how managers of PBOs should strategically orchestrate knowledge governance mechanisms within CSSC networks to leverage KI behaviours.

Current literature on KNI, KI and KG within CSSC networks offers a limited understanding of how KI behaviours influence KNI of project-based organizations (PBOs) in tapping vibrant outbound peripheral knowledge. The research presents two major original contributions. First, the empirical evidence contributes to deepening the current understanding of how heterogeneous external knowledge within consultant-supplier interactions is negatively influenced by KI. Lastly, the study suggests formal and informal knowledge governance strategies for managers on how to counteract KI forces, thus extending the theoretical debate on KNI, KI and KG literature.

The main purpose of this study is to investigate the effects of flexibility-oriented human resource management (FHRM) systems on intellectual capital and organizational resilience. This study also examines the moderating effect of digital capability on the relationship between intellectual capital and organizational resilience.

Data were collected from 219 Chinese businesses in the Yangtze River Delta region of China during the COVID-19 pandemic. Confirmatory factor analysis was used to verify the validity and reliability of the measurements, and hypotheses were tested using hierarchical regression.

The empirical results show that FHRM systems are positively correlated with intellectual capital and organizational resilience. Intellectual capital mediates the link between FHRM systems and organizational resilience. Moreover, digital capability serves as a positive moderator between intellectual capital and organizational resilience.

From the perspectives of resilience theory, the resource-based view and the theory of dynamic capabilities, this study is among the first to identify the process mechanism by which FHRM systems affect organizational resilience through intellectual capital. Digital capability is introduced as a situational factor for understanding the effect of intellectual capital on organizational resilience, which provides new insights for further research.

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the mediating role of relationship quality in the association of CSR with organizational resilience, and the moderating role of data-driven culture in the association between CSR and relationship quality.

Data were collected from Chinese agricultural firms with a sample of 241 senior or middle executives and structural equation modeling was used to test the research model and hypotheses.

The results indicate that CSR positively affects the relationship quality between agribusinesses and farmers, which in turn positively affects both proactive resilience and reactive resilience. Relationship quality has a partial mediating role in the association of CSR with proactive resilience and reactive resilience. Data-driven culture has a positive moderating effect on the relationship between CSR and relationship quality.

By arguing for CSR toward organizational resilience and analyzing its underlying mechanism, this study enriches the literature on CSR and organizational resilience and expands the existing knowledge on the roles of relationship quality and data-driven culture. This study also provides practical insights into how to improve organizational resilience.

The absence of government intervention and market supervision cannot effectively promote green process innovation in manufacturing industries. As a new government regulation approach, environmental taxes provide a platform to internalize the externality of environmental pollution. This paper empirically investigates the impact of environmental taxes on green process innovation and the moderating effects of industry pollution heterogeneity and green credit.

This research collects manufacturing industry data ranging from 2008 to 2020, resulting in a total of 351 observations. Time-individual, two-way fixed effect models are constructed to examine the hypotheses.

The results indicate environmental taxes have an inverted-U effect on green process innovation in manufacturing industries. Implementation intensity of the current environmental taxes on China's manufacturing industries does not reach an inflection point. Further analysis suggests that environmental taxes exert influence on the inverted-U relationship with low-pollution industries displaying a steeper curvilinear pattern than high-pollution industries. Moreover, the analysis shows that green credit plays a moderating role in the inverted-U relationship, as low green credit provides more limited stimulus than high green credit in terms of the effect of environmental taxes on green process innovation.

This study offers empirical evidence to accommodate negative externalities of corporate production and provides new perspectives in nudging corporate green-process innovation.

This paper verifies the effect of environmental taxes on green process innovation amid industry pollution heterogeneity by introducing an industrial-level analysis unit. This study improves the means by which environmental taxes are measured. Existing literature has narrowly used pollution discharge fees as a proxy for environmental taxes. The authors have summed up the taxes on vehicle and vessels, urban land use, urban maintenance and construction, vehicle purchases, waste gas, wastewater and solid waste to measure the effect of environmental taxes in this study.

Technological progress is a determining factor in the factors leading to economic and social well-being. Simultaneously, the development of a sustainable economy is based on the conservation of resources. In the energy sector, this fact can be corroborated with the reduction of energy consumption, thus increasing economic efficiency. On the one hand, improving energy efficiency contributes to increasing the quality of life, productivity, and, implicitly, the economy, but on the other hand, it leads to excess energy use – this behavioral change is known as rebound. The research estimates the rebound effect at the macroeconomic level for European countries in the period 2000–2019, referring the analysis to each country's gross domestic product (GDP) and energy consumption, as well as comparing the preaccession and postaccession periods of Romania in the EU space. The rebound effect is determined using multidimensional analysis methods, depending on the GDP of each country as well as the behavior of each in the use of energy resources in industry, agriculture, and services. Although the study results confirm the strong link between energy consumption and GDP at the level of each state, they did not show considerable changes between countries at the level of the two periods.

This paper aims to explain the causal complexity between ecosystems of doing business and living standards based on the theoretical model of the ecosystem of doing business proposed by Li (2019) and Du et al. (2020). By integrating ecological theory, transaction cost theory and institutional logics theory, this study explored effective ecosystems of doing business that achieve high living standards and explained the interpretive mechanisms behind different ecosystems of doing business. Moreover, this study also analyzed whether there were any necessary elements that lead to high living standards and discussed how the interactions between these elements influence carrying capacity and transaction costs from government logic and market logic, thus affecting living standards.

In this study, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) were combined to analyze the data from the 2020 China City Statistical Yearbook, covering the main socioeconomic statistical data of cities at all levels in 2019.

This study found that no individual factor of the ecosystems of doing business was necessary to achieve high living standards, but the high level of human capital, innovation capacity, financial access and market demand play a significant role in achieving high living standards. Furthermore, two effective types of ecosystems of doing business lead to high living standards, namely, market dominance (government’s “invisible hand” or “nudging hand”) and government–market logic mutualism/symbiosis (government’s “helping hand”).

First, this work found that individual elements were not a necessary condition for high living standards, not only in kind but also in degree, complementing fsQCA with NCA, which indicates that environmental elements can be substituted by others. Second, this study considered the complex effects and explained the mechanisms behind different ecosystems of doing business, drawing on ecological theory, transaction cost theory and institutional logics theory from a configurational perspective. This study deepened the theories’ applications in the field of living standards and further discussed the elements interactions. Third, this study introduced configurational perspective and QCA into living standards research and adopted a mixed method that combines fsQCA and NCA to analyze the causal complexity between ecosystems of doing business and people’s living standards.

Doctor–medical institution collaboration (DMIC) services are an emerging service mode in focal online health communities (OHCs). This new service mode is anticipated to affect user satisfaction and doctors' engagement behaviors. However, whether and how DMIC occurs is still ambiguous because the topic is rarely examined. To bridge this gap, this study explores doctors' participation in DMIC services and its effects on their online performance, as well as its effect on patients' evaluation of them on OHC platforms.

The authors propose hypotheses based on structural holes theory. A unique dataset obtained from one of the most popular OHCs in China is used to test the hypotheses, and difference-in-differences estimation is adopted to test the causality of the relationship.

The results demonstrate that providing DMIC services improves doctors' online consultation performance and patients' evaluations of them but has no significant effect on doctors' knowledge-sharing performance on OHC platforms. Doctors' knowledge-sharing performance and consultation performance mediate the relationship between participation in DMIC services and patients' evaluation of doctors. Regarding doctors' participation in DMIC services, its impact on doctors' consultation performance and patients' evaluation of them is weaker for doctors with higher professional titles than for doctors with lower professional titles.

The findings clarify the value creation mechanisms of online collaboration between doctors and medical institutions and thereafter facilitate doctors' participation in DMIC services and enhance the sustainable development of OHCs.

This paper aims to test the causal relationship between urban-biased policy and urban-rural income gap and further examine the moderating role of government intervention.

Based on the provincial Government Work Reports and the long-term policy practice of implementing the target responsibility system, the authors construct a unique indicator of urban-biased policy in China. Further, applying the panel data of 30 Chinese provinces in 2003–2018, the authors explore the causal relationship between urban-biased policy and urban-rural income gap.

The results show that urban-biased policy has contributed to the widen urban-rural income gap in China, which supports Lipton's urban-biased hypothesis. Further research shows that the stronger the government intervention, the bigger the role of urban-biased policy in widening urban-rural income gap.

On the one hand, this study not only investigates the direct effect of urban-biased policy on urban-rural income gap, but also examines the moderating effect from the perspective of government intervention, which helps to enrich the relevant studies of urban-biased theory. On the other hand, the authors' findings provide the latest empirical evidence for urban-biased policy to widen urban-rural income gap and presents a reference and warning for China and other developing countries about balancing the relationship between equity and efficiency during economic development.