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This paper aims to take the four resin as adsorbent and coal ash alkaline solution as the material and use the single factor experimental method to study absorption influence factors for each resin to absorb lithium. At the same time, the authors got the special properties of some kinds of resin and compared the test results of each resin at the optimum factors.

Because many factors affect the test, this study uses the method of comparison and control variables. This method study on the influencing factors of ion exchange resin adsorption Li⁺.

In these adsorption experiments, the basic resin adsorption effect is more obvious. The optimum adsorption conditions are as follows: resin quality is 0.1 g, the volume of fly ash solution is 100 ml, magnetic stirrer speed is 140 r/min and the adsorption time is 60 min. Under these conditions, the adsorption rate of Li⁺ could reach 25.17 per cent aluminum.

Li extracted from coal ash can not only relieve the lithium resources in short supply but can also provide a new mode to the field of coal resources in recycling economy and transition economy. At the same time, the extraction of Li resources will provide an important reserve of raw materials for the future of nuclear power plant.

The purpose of this paper is to empirically investigate the effects of institutional support on product and process innovation and firm performance and describe how dysfunctional competition influences relevant outcomes.

This study develops a research model based on institution-based view and tests it using structural equation modeling and empirical data collected from 300 manufacturers in China.

The results show that institutional support positively affects product and process innovation and firm performance. Both product and process innovation improve firm performance. The findings reveal that dysfunctional competition significantly reduces the positive effects of institutional support on product and process innovation but leaves the effects of institutional support and product and process innovation on firm performance unaffected.

This study contributes to innovation literature by providing insights into the impact of China’s institutional environment on manufacturing firms’ product and process innovation decisions. The findings also contribute to institution-based view literature by providing empirical evidence on the joint effects of institutional support and dysfunctional competition on product and process innovation and firm performance. This study can help manufacturers in China take advantage of institutional environment and adjust product and process innovation decisions accordingly.

Malicious attacks extremely traumatize knowledge networks due to increasing interdependence among knowledge elements. Therefore, exposing the damage of malicious attacks to knowledge networks has important theoretical and practical significance. Despite the insights being offered by the growing research stream, few studies discuss the diverse responses of knowledge networks’ robustness to different target-attacks, and the authors lack sufficient knowledge of which forms of malicious attacks constitute greater disaster when knowledge networks evolve to different stages. Given the irreversible consequences of malicious attacks on knowledge networks, this paper aims to examine the impacts of different malicious attacks on the robustness of knowledge networks.

On the basic of dividing malicious attacks into six forms, the authors incorporate two important aspects of robustness of knowledge networks – structure and function – in a research framework, and use maximal connected sub-graphs and network efficiency, respectively, to measure structural and functional robustness. Furthermore, the authors conceptualize knowledge as a multi-dimensional structure to reflect the heterogeneous nature of knowledge elements, and design the fundamental rules of simulation. NetLogo is used to simulate the features of knowledge networks and their changes of robustness as they face different malicious attacks.

First, knowledge networks gradually form more associative integrated structures with evolutionary progress. Second, various properties of knowledge elements play diverse roles in mitigating damage from malicious attacks. Recalculated-degree-based attacks cause greater damage than degree-based attacks, and structure of knowledge networks has higher resilience against ability than function. Third, structural robustness is mainly affected by the potential combinatorial value of high-degree knowledge elements, and the combinatorial potential of high-out-degree knowledge elements. Forth, the number of high in-degree knowledge elements with heterogeneous contents, and the inverted U-sharp effect contributed by high out-degree knowledge elements are the main influencers of functional robustness.

The authors use the frontier method to expose the detriments of malicious attacks both to structural and functional robustness in each evolutionary stage, and the authors reveal the relationship and effects of knowledge-based connections and knowledge combinatorial opportunities that contribute to maintaining them. Furthermore, the authors identify latent critical factors that may improve the structural and functional robustness of knowledge networks.

First, from the dynamic evolutionary perspective, the authors systematically examine structural and functional robustness to reveal the roles of the properties of knowledge element, and knowledge associations to maintain the robustness of knowledge networks. Second, the authors compare the damage of six forms of malicious attacks to identify the reasons for increased robustness vulnerability. Third, the authors construct the stock, power, expertise knowledge structure to overcome the difficulty of knowledge conceptualization. The results respond to multiple calls from different studies and extend the literature in multiple research domains.

Drawing upon relative absorptive capacity (AC) perspective, this study proposes a research model connecting R&D investment, three types of supply chain AC—AC from suppliers, customers and university and research institutes (U&RIs)—and firm innovativeness and investigates the contingent effects of dysfunctional competition on the link between R&D investment and supply chain AC.

The authors used data collected from 262 manufacturers in three areas of China to empirically examine the conceptual model. The corresponding hypotheses were tested with structural equation modeling and regression analysis.

The empirical results demonstrate that AC from customers and AC from U&RIs play significant mediating roles in the relationship between R&D investment and firm innovativeness. Moreover, R&D investment has a significantly greater effect on AC from U&RIs under high levels of dysfunctional competition.

First, by conceptualizing AC from a relative view, this study discloses the unique roles of knowledge from different supply chain partners in realizing the benefits of R&D investment in innovation. Second, the exploration of the contingent roles of dysfunctional competition in the emerging economy of China enriches insights on the roles of institutional environment on knowledge absorption and the knowledge on relative AC in emerging economies.

The privatization of infrastructure promotes efficiency and service standards. While cross-border private participation infrastructure (PPI) projects hosted in emerging markets have become more prevalent in recent years, there have also been more failures. The purpose of this paper is to investigate how governance distance affects the survival of cross-border PPI projects.

The authors provide theoretical justification and empirical evidence to verify our views. The authors test the hypotheses on a sample of 4,678 cross-border PPI project investments made in emerging market countries between 1990 and 2016. Estimation techniques consist of a binary logistic regression model and a rare events logistic model.

The findings suggest that increased governance distance can lead to project failure. The study results show that governance distance is negatively correlated with the probability of project survival. Greenfield investment intensifies the negative effect of governance distance while competitive contracts mitigate the negative effect of governance distance.

The results reveal that transnational investment in infrastructure projects is susceptible to institutional differences between home and host countries. Therefore, both private enterprises and host government should pay attention to the impact of inter-country differences on negotiations and project operation. Competitive contracts mitigate this negative effect, but entering in the form of greenfield investment amplifies the negative effect of distance.

Transnational industrial engineering projects are easily affected by the differences in governance levels between the two countries. This study introduces governance distance into the field of infrastructure projects, focusing on the impact of differences between home and host countries on transnational projects. The findings on infrastructure projects that are closely related to host government contribute to the literature by broadening the research of institution and distance.

The purpose of this paper is to investigate how supplier concentration influences a buyer firm's R&D intensity. This study proposes a mediation and moderation model to test this relationship in the Chinese household appliance industry. Specifically, this study tests the mediation effect of operational slack on the relationship between supplier concentration and R&D intensity and the moderation effect of financial constraints on this relationship.

Drawing upon real options theory and resource dependence theory, the proposed relationships are tested with the Chinese household appliance market using financial data from listed companies over a ten-year span from 2012 to 2021. Fixed effects (within-group) panel regression models are used to test the hypotheses. In addition, the authors use the bias-corrected bootstrap method to test the mediation effect.

The authors find that supplier concentration negatively affects a buyer firm's R&D intensity and that internal operational slack mediates this relationship. Interestingly, financial constraints from the external financing organization weaken the negative relationship between the buyer firm's supplier concentration and R&D intensity.

Based on the argument of real options theory and resource dependence theory, this study provides novel insights into the issue of how concentration on several major suppliers may reduce buyer firms' R&D intensity. First, this study introduces operational slack as a form of internal uncertainty that mediates the supplier concentration–R&D intensity relationship. Second, this study suggests that the effect of supplier concentration on R&D intensity is contingent upon firms' financial constraints from external financial organizations, disclosing a synergetic interactive effect of supplier concentration and financial constraints on firms' R&D activities. Third, this study is conducted in the unique institutional context of China, providing meaningful insights into the relationship between supplier concentration and R&D intensity.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

Opinion mining (OM), also known as “sentiment classification”, which aims to discover common patterns of user opinions from their textual statements automatically or semi-automatically, is not only useful for customers, but also for manufacturers. However, because of the complexity of natural language, there are still some problems, such as domain dependence of sentiment words, extraction of implicit features and others. The purpose of this paper is to propose an OM method based on topic maps to solve these problems.

Domain-specific knowledge is key to solve problems in feature-based OM. On the one hand, topic maps, as an ontology framework, are composed of topics, associations, occurrences and scopes, and can represent a class of knowledge representation schemes. On the other hand, compared with ontology, topic maps have many advantages. Thus, it is better to integrate domain-specific knowledge into OM based on topic maps. This method can make full use of the semantic relationships among feature words and sentiment words.

In feature-level OM, most of the existing research associate product features and opinions by their explicit co-occurrence, or use syntax parsing to judge the modification relationship between opinion words and product features within a review unit. They are mostly based on the structure of language units without considering domain knowledge. Only few methods based on ontology incorporate domain knowledge into feature-based OM, but they only use the “is-a” relation between concepts. Therefore, this paper proposes feature-based OM using topic maps. The experimental results revealed that this method can improve the accuracy of the OM. The findings of this study not only advance the state of OM research but also shed light on future research directions.

To demonstrate the “feature-based OM using topic maps” applications, this work implements a prototype that helps users to find their new washing machines.

This paper presents a new method of feature-based OM using topic maps, which can integrate domain-specific knowledge into feature-based OM effectively. This method can improve the accuracy of the OM greatly. The proposed method can be applied across various application domains, such as e-commerce and e-government.

Most of the studies in entrepreneurship depend on single-source rating methods to collect data on both predictors and criteria. The threat to effect sizes as a result of using single-source ratings is particularly relevant to psychology-based entrepreneurship research. Therefore, the purpose of this paper is to explore the prospects of applying 360-degree feedback to the field of entrepreneurship and to discuss a set of cases regarding how 360-degree feedback may boost effect sizes in entrepreneurship research.

A qualitative review of current literature was performed.

The review indicated that the effect sizes in psychology-based entrepreneurship research are mostly small and the use of single-source ratings is prevalent; some preliminary findings supported the utility of 360-degree feedback in entrepreneurship research; entrepreneurial orientation (EO) research may benefit from 360-degree feedback; and members of top management teams, employees from research and product development, sales agents, retail buying agents, store sales clerks, and consumers are all valid informants to provide ratings of EO.

The present study provided theoretical explanations and used empirical evidence to elucidate how 360-degree feedback may benefit the field of entrepreneurship. In addition, recommendations for future research using 360-degree feedback in entrepreneurship research were offered and discussed. A sample research study on EO using 360-degree feedback was delineated.

The topic of entrepreneurial intention, which refers to a person’s degree of interest in creating a new business venture, has received close scrutiny in the entrepreneurship literature. The empirical results regarding the relation between emotional intelligence (EI) and entrepreneurial intention were nevertheless mixed across studies. Based on fit theory and trait activation theory, the purpose of this paper is to explain the fundamental reason for the mixed findings in the extant literature thus far.

Random-effects meta-analyses, based on 12 studies (along with 12 effect sizes), were performed to not only investigate the overall relation between EI and entrepreneurial intention but also to examine the moderators (i.e. individualism (vs collectivism), masculinity (vs femininity), power distance, long-term orientation (vs short-term orientation), uncertainty avoidance, and indulgence (vs restraint)) that influence this relation.

The results of this meta-analysis demonstrated that EI is positively related to entrepreneurial intention; the positive relationship between EI and entrepreneurial intention is stronger in long-term-oriented cultures; and the positive relationship between EI and entrepreneurial intention does not significantly differ based on a culture’s level of collectivism, masculinity, power distance, uncertainty avoidance, and indulgence.

This meta-analysis advances the current understanding of the relation between EI and entrepreneurial intention from cross-cultural perspectives.