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The purpose of this paper is to investigate significant impact of partner similarity on the success of horizontal alliances in logistics service providers (LSPs) from China.

Primary data were collected via questionnaire distribution to 380 Chief Executive Officers and Managing Directors in 262 small and medium logistics enterprises in China. There are 316 valid questionnaires for further analysis with 83 percent accuracy in response rate. Structural equation modeling was used to test the impact of partner similarity on alliance management capability, stability and performance.

Partner similarity and logistics alliance management capability (LAMC) are positively correlated to alliance stability and performance in horizontal alliances among Chinese LSPs, especially competence similarity and cultural similarity. Moreover, alliance stability mediates the impact of partner similarity and LAMC on alliance performance.

The basic limitation of this research is to collect data just from small and medium logistics enterprises that operate in China with sample size (n=316). This research could further be extended to other regions in China or other countries.

This research verifies the positive relationship between partner fit and management capability. Besides, based on research findings, the research proposes guidelines for LSPs pursuing horizontal alliances

This research proposes an experimental model for Chinese LSPs to cooperate successfully and build horizontal alliances in order to increase their effective customer response capability.

The purpose of this paper is to investigate the relationship between e-marketing (eM) and consumers’ buying behavior particularly exploratory buying behavior tendencies (EBBT) with moderating effect of a gender in the context of China.

Structural equation modeling using SPSS/AMOS was majorly applied to ascertain the relationship and hypotheses testing. First, the correlation of eM toward EBBT is examined using five factors: internet marketing (IM), e-mail marketing (EMa), intranet marketing (IMa), extranet marketing (EM), and mobile marketing (MM). Second, the relationship of each dimension of the eM model is determined autonomously to ensure the importance of such emerging technologies in marketing communications. Third, the effect of gender as a moderator is measured. To this end, primary data were collected through random distribution of the questionnaires among 1,600 consumers particularly students of the universities between February 2016 and August 2016 within North China.

The findings revealed that eM has a significant correlation on consumers’ EBBT. The comprehensive analysis of each factor of eM, i.e., IM, EMa, IMa, EM, and MM is positively correlated to EBBT. The present study revealed that gender did not moderate among the relationships of eM and EBBT. Additionally, study furnishes practical directions on how managers can utilize such emerging and revolutionary technologies in marketing activities to probe, understand, and reinforce consumers’ buying behavior.

The research has limitations related to geographical location and sample size which thus limits the widespread generalization.

This study affirmed that organizations must engage the consumers using such technologies that are more likely acceptable by consumers in the present customer-oriented and digital era. The marketers must engage consumers the way they wish to be engaged by developing appropriate promotional strategies. The study provides possible implications both theoretical and managerial along with a contribution to the literature of eM and consumers’ buying behavior.

Understanding the emerging technologies may furnish valuable insights for individuals to work well within Chinese SMEs.

The topic of eM has acknowledged as an evolving concept which is gaining an intense concern of both academician and practitioners. Therefore, more research mainly empirical work is still needed to probe the insights of eM across the globe. This study attempts to fulfill such need with empirical evidence together with an in-depth examination of eM determinants, collectively and autonomously.

This study embarks on a comprehensive investigation into the intricate relationship between consumer trust in e-commerce platforms and the adoption of Green Supply Chain Management (GSCM). It delves into a multifaceted analysis of how these dynamics influence the landscape of online shopping, with a specific focus on four critical dimensions: the efficiency of online purchasing processes, the fulfillment of product delivery commitments, the convenience associated with e-platform utilization, and the safeguarding of consumers' personal information.

This research employs sophisticated Structural Equation Modeling (SEM) techniques, facilitated by SPSS and SmartPLS software, to meticulously analyze the amassed data and subject the formulated hypotheses to rigorous testing. The empirical foundation of this study draws from a sample of 377 randomly selected online shoppers, providing a robust basis for its insights.

At its core, this research is squarely focused on unraveling the dynamics of consumer trust within e-commerce platforms and highlighting the pivotal role played by GSCM in making online shopping more ecologically responsible and sustainable. Of paramount importance is the novel dimension introduced by this study the integration of trust in e-commerce platforms, GSCM practices, and the multifarious dimensions of online shopping all within a unified conceptual framework. Trust on e-commerce platforms leads to GSCM. GSCM determines online shopping satisfaction, i.e. efficiency, fulfillment, convenience, and privacy. Finally, GSCM mediates between trust on e-commerce platforms and online shopping satisfaction.

This holistic approach represents a ground-breaking contribution to the existing body of literature. It presents a fresh perspective on the intricate interactions that define the contemporary e-commerce landscape.

This initial research integrates trust in e-commerce platforms, GSCM, and online shopping in a single framework through UTAUT2.

The purpose of this paper is to examine the impact of two typical relationship management approaches (trust relationship with suppliers and reciprocity) on manufacturer resilience in the context of the COVID-19 crisis. Moreover, this paper aims to deepen the understanding of environmental uncertainty's moderating effect on the association between the trust relationship with suppliers (TRS) and reciprocity.

Structural equation modeling has been used to test the hypotheses on 361 Chinese manufacturing firms' managers and independent directors during the COVID-19 crisis.

The results reveal that reciprocity positively enhances three dimensions of manufacturer resilience, namely, preparedness, responsiveness and recovery capability. Reciprocity positively mediates the relationships between TRS and preparedness, responsiveness and recovery capability. Moreover, environmental uncertainty moderates the association between TRS and reciprocity.

This study highlights the critical role of reciprocity, the relational governance approach, in enhancing manufacturer resilience in practice. This paper suggests that during emergencies such as the COVID-19 pandemic, managers should adopt trust and reciprocity in supplier relationship governance to strengthen the resilience of manufacturing companies and adapt effective strategies according to the environment.

This study is unique in developing new scales of manufacturer resilience through interviews and surveys with Chinese manufacturers and theoretical research. Based on the social capital theory and social exchange theory, this study shed light on the role of trust and reciprocity. It also bridges relational governance theory with the literature on manufacturing firm resilience literature to help manufacturers better understand the transdisciplinary links between relationship management and resilient operations in emergencies.

The purpose of this paper is to understand the influence of knowledge-sharing behavior (KSB) on the innovative work behavior (IWB) and job satisfaction (JS) among employees considering the moderating role of motivating language (ML) of supervisors.

The hypothesized relationships were examined applying modeling of structural equation and hierarchical multiple regression analysis. The data was collected from Chinese multinational companies in Kazakhstan with final sample of 322 respondents.

The findings suggest that the link between KSB and JS is significantly positive with the moderating impact of ML, while KSB itself has significantly negative effect on JS. Moreover, ML buffers the insignificant effect of KSB on IWB.

Research is atypical, as it has focus on the moderating roles of ML in the direct relationship of employee KSB and JS, and in the direct linkage of employee KSB and IWB in Chinese multinational organization in the network field.

This paper aims at studying the concept of innovation ecosystems and investigating the factors affecting them based on their interrelationships with respect to different innovation archetypes.

The methodology is based on using multivariate statistical analysis of the inter-correlations among a number of variables which led to extracting a reduced set of new significant factors that affect China’s innovation ecosystem.

The results showed that innovation archetypes differ significantly with respect to the majority of the new factors.

Through identifying these challenges, decision-makers can develop a better understanding of the variables affecting each archetype of innovation and act accordingly.

The study is the first to fill the gap of addressing a large number of variables affecting innovation and analyzing their interrelationships.

This study aims to develop a better understanding of radical innovation performance and proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China. Both quantitative and qualitative techniques were used to test the hypotheses regarding barriers to radical innovation and the model proposed in this research.

The data was collected through questionnaires and semi-structured interviews with researchers from different research institutions across several cities in China. Next, the data was analyzed by deploying the structural equation modeling technique and calculating the statistical significance of correlations, regression and path coefficients among the latent variables.

The results indicated the major barriers impeding radical innovation in Chinese research institutes. Based on these findings, suggested policies, regulations and business models are put forward that can promote radical innovation in these institutes through increasing research freedom, enhancing organizational flexibility, attracting talented researchers and expanding research collaboration.

The research proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China.

The purpose of this paper is to examine empirically China’s determined thrust to attain a high level of technological innovation and the factors affecting moving towards a smart and sophisticated manufacturing ecosystem in conjunction with the Belt and Road Initiative (OBOR).

This research provides empirical determination of the factors affecting moving towards smart manufacturing ecosystems in China. The method is based on combining two approaches: semi-structured interview and questionnaire-based with academics, experts and managers in various Chinese industrial sectors. The results are based on the multivariate analysis of the collected data. A case study of the current manufacturing ecosystem was also analyzed, in order to understand the present state as well as the potential for China’s competitive edge in the developed OBOR countries.

The results illustrate the importance of the infrastructure dimension comprising variables related to ecosystems, industrial clusters and Internet of Things IoT and other advanced technologies. A case study of the city of Shenzhen’s transformation into a smart cluster for innovative manufacturing points out how China’s OBOR initiative for regional collaboration will further transform the regional smart clusters into an ultra-large innovation based smart ecosystem.

This research is the first to study China’ policies towards playing a prominent role in the Fourth Industrial Revolution 4IR in the context of the OBOR initiative, through empirically defining the factors affecting moving towards a knowledge-intensive smart manufacturing ecosystem where the added value is mostly innovation based.

The purpose of this paper is to analyse the efficiency and benefits of supply chain (SC) scientifically and validate the usability of methods on performance evaluation index system.

At the performance evaluation index, the enhanced balanced scorecards (BSC) are developed based on the BSC. Regarding society environment and future development, the construction of performance evaluation index system includes five aspects such as finance, customer service, intra‐flow process, learning and development, and society development within SC. The indexes of performance evaluation system are all quantified to achieve their practical application. Another new point is that the logarithm triangular fuzzy number‐analytic hierarchy process (AHP) method expanding from fuzzy environment and developing from traditional AHP method is creatively used to evaluate the integrative performance evaluation index system.

The enhanced BSC and the special AHP method can overcome some disadvantages that experts directly give definite numbers when the traditional method is used to value certainty and evaluate the qualitative index. It is a scientific qualitative and quantitative evaluation tool.

Accessibility and availability of data are the main limitations affecting which model will be applied.

This paper is a very useful method for SC managers.

The new approach of performance evaluation index system is attempted due to structure and fuzzy sets. The paper is aimed at operational researchers, engineers and special managers.