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The purpose of this paper is to explore the key factors influencing the service innovation of mobile social networks (MSNs), figure out the mechanism of all factors in different stages of service innovation and help mobile social application developers promote better service innovation.

From previous research, this paper adopted nine initial factors that influence the service innovation of MSNs, and divide the service innovation process into three stages (i.e. demand analysis, service design and innovation implementation). On that basis, the authors constructed a model, and then collected data from 184 managers from 20 leading MSN corporates in China through questionnaires to examine the model. Furthermore, factor analysis was used to extract key factors influencing the service innovation of MSNs, correlation analysis was employed to discuss the relationship among factors and regression analysis was applied to explore their specific roles in different stages in the service innovation process.

The empirical results show that the service innovation of MSNs is mainly influenced by five key factors: user, developer, market environment, social environment and technology. The authors found that different factors played remarkably different roles in the three stages. In specific, all factors but technology are important in the demand analysis stage; all factors but social environment are critical to service design; and all factors but user contribute to the implementation of service innovation.

The results of this study can help mobile social application developers and mobile social service providers in China to better understand the driving force of service innovation and what should be emphasized in different stages, and then find the optimal path to implement service innovation, improve their service quality and user experience and facilitate the development of Chinese MSNs.

This is the first research that comprehensively explores factors influencing the service innovation of Chinese MSNs from multi-dimensional perspectives, which provides profound theoretical guidance to the practice of service innovation in China. Also, it contributes to the development of innovation theory of traditional web services.

The purpose of this paper is to solve the comprehensive evaluation of the equipment maintainability level based on grey system theory, and make an analysis of the corresponding influencing factors and their prioritization process.

Considering the diversity, uncertainty and small sample size of the influencing factors of the equipment maintainability level, a multilayer evaluation attribute system is set up, and the grey relational method is utilized to assess the equipment's comprehensive maintainability. First, the bottom layer relational coefficient and weighted relational degree are analyzed, and, by means of the focus of relational degree through the bottom layer to top layer, the general evaluation of the equipment maintainability is carried out. Second, the equipment maintainability level and its influencing factors model, i.e. GM(1,N) model are set up, and the prioritization of the influencing factors is achieved through the comparison of the size of the model drive coefficients. Finally, the practical example calculation results show that this method has not only realized a sensible and effective evaluation of the equipment maintainability level, but also provided a prioritization of the influencing factors, which helps to focus attention on the major influencing factors and make this method of significant engineering application value in the improvement of the equipment maintainability level.

The modeling of electronic equipment maintainability level and analysis of its corresponding practical example prove that grey system theory could not only perform a comprehensive evaluation of the equipment maintainability level, but also provide a quantitative analysis of its various influencing factors, whereas, other methods such as fuzzy mathematics, etc. can only make a general evaluation of the equipment maintainability level.

This paper has realized an integral evaluation of the equipment maintainability level and has made an analysis of the prioritization of its various influencing factors. These investigation results could be introduced as a promising innovative idea in the evaluation of the equipments' other performances and the prioritization of its various corresponding influencing factors.

Considering the diversity and uncertainty of influencing factors of the equipment maintainability level, this paper has realized a multilayer evaluation attribute system to perform a comprehensive evaluation of equipment maintainability level by means of weighted grey relational degree model. Furthermore, the prioritization of its various influencing factors is achieved based on the GM(1,N) model.

With the increasing abundance of network resources and big data, multi-modal information search (MMIS) has been paid more and more attention, but the research results of MMIS are relatively few. This paper attempts to put forward constructive suggestions for the design of multi-modal information system, so that the system can have a better user experience, help users improve the efficiency of obtaining information and optimize the information service mode.

A research model of influencing factors is established by using the TAM (technology acceptance model) theory. The influencing factors of users' multi-modal information search behavior (MMISB) are analyzed by using questionnaire, experiment and the structural equation model. On the basis of this, some suggestions are put forward to build the multi-modal search (MMS) system and improve the efficiency of MMIS.

The research shows that users' MMISB is directly related to their search intention, and the search intention can influence users' cognition of the usefulness and ease of MMIS through their own information search ability and system characteristics. The user's MMIS ability is affected by the demand expression ability and retrieval ability cognition; the user's cognition of system characteristics is affected by the system function and information quality. This shows that the user's MMISB is closely related to the user's cognitive situation, but due to the author's limited time and research ability, only the questionnaire survey method cannot be used to in-depth research and explore the influencing factors of MMIS. Therefore, in the future research, we should combine the interview method to further track the user's emotional factors and scene factors.

For the first time, TAM theory is combined with cross-modal retrieval behavior and the paper explores the influencing factors and evaluation indexes of users' MMISB. The second, the questionnaire was compiled to investigate the influencing factors of the MMISB of the university group, and the reliability analysis, validity analysis, correlation analysis and structural equation model analysis of the survey data are carried out . The survey data and analysis results are original, which can provide a theoretical basis for improving the service level of MMIS.

The purpose of this paper is to seek to drive the modernization of the entire national economy and maintain in the long-term stability of the whole society; this paper proposes an improved model based on the first-order multivariable grey model [GM (1, N) model] for predicting the housing demand and solving the housing demand problem.

This paper proposes an improved model based on the first-order multivariable grey model [GM (1, N) model] for predicting the housing demand and solving the housing demand problem. First, a novel variable SW evaluation algorithm is proposed based on the sensitivity analysis, and then the grey relational analysis (GRA) algorithm is utilized to select influencing factors of the commodity housing market. Finally, the AWGM (1, N) model is established to predict the housing demand.

This paper selects seven factors to predict the housing demand and find out the order of grey relational ranked from large to small: the completed area of the commodity housing> the per capita housing area> the one-year lending rate> the nonagricultural population > GDP > average price of the commodity housing > per capita disposable income.

The model constructed in the paper can be effectively applied to the analysis and prediction of Chinese real estate market scientifically and reasonably.

The factors of the commodity housing market in Wuhan are considered as an example to analyze the sales area of the commodity housing from 2015 to 2017 and predict its trend from 2018 to 2019. The comparison between demand for the commodity housing actual value and one for model predicted value is capability to verify the effectiveness of the authors’ proposed algorithm.

Subway systems are highly susceptible to external disturbances from emergencies, triggering a series of consequences such as the paralysis of the internal network transportation functions, causing significant economic and safety losses to cities. Therefore, it is necessary to analyze the factors affecting the resilience of the subway system to reduce the impact of disaster incidents.

Using the interval type-2 fuzzy linguistic term set and the K-medoids clustering algorithm, this paper improves the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to construct a subway resilience factor analysis model for emergencies. Through comparative analysis, this study confirms the superior performance of the proposed approach in enhancing the precision of the DEMATEL method.

The results indicate that the operation and management level of emergency command organizations is the key resilience factors of subway operations in China. Furthermore, based on real case analyses, the corresponding suggestions and measures are put forward to improve the overall operation resilience level of the subway.

This paper identifies four emergency scenarios and 15 resilience factors affecting subway operations through literature review and expert consultation. The improved fuzzy DEMATEL method is applied to explore the levels of influence and causal mechanisms among the resilience factors of the subway system under the four emergency scenarios.

The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Starting from choosing influence factors on grain production and dividing the 30 years (from 1979 to 2009 year) of grain production in Henan province into three periods, the authors calculate grey incidence degree between grain yield and every influencing factor by grey incidence analysis method, respectively, then obtain the grey incidence order of influencing factors in every period. Also based on the three grey incidence orders from different periods, the authors find a changeable tendency of influencing factors on grain production and key influencing factors on grain production in different periods. Finally, to keep Henan province grain production stable and sustainable, several policy suggestions are given.

The results are convincing: it is effective and powerful to analyze dynamically influencing factors of grain production using grey systems theory, and it is urgent to strengthen agricultural science and technology input, and pay close attention to the influence of dosage of pesticide and fertilizers on grain production.

Grey incidence analysis and findings exposed in the paper can be used by agricultural firms to optimize grain production plans, and by government to formulate reasonable agricultural production policies.

The paper succeeds in getting dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

This study aims to explore the critical influencing factors that lead to the site selection failure of waste-to-energy (WtE) projects in China under the influence of the “Not In My Back Yard” (NIMBY) effect, which can provide references to improve the decision-making process of similar projects in the future.

The fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was used to propose an analytical framework for exploring the critical influencing factors affecting the site selection failure of WtE projects. The causal relationship between different influencing factors is finally determined on the basis of the opinions of 12 experts from universities, government departments, consulting units, planning and design units, construction units and WtE enterprises.

Results showed that six crucial factors resulted in the site selection failure of WtE projects from the NIMBY effect perspective: “Insufficient public participation,” “Near the place of residence,” “Nonstandard government decision-making processes,” “Low information disclosure,” “Destroys the surrounding environment,” and “Imperfect compensation scheme.”

Results can determine the priorities and causal relationships among the various influencing factors. The decision-making optimization suggestions can provide reference for decision- makers, thereby possibly promoting the scientific and standardization of site selection decision process.

The purpose of this paper is to explore the influencing factors of cost performance of design-bid-build (DBB) and design-build (DB) projects and comparing the differences of influencing factors between these two delivery methods.

This research identified and refined 14 influencing factors through literature review and academic expert discussions. Questionnaire survey was conducted to collect data about the influencing factors and project cost performance. Then those factors were reduced to four components by factor analysis. Logistic regression analysis is used to investigate the relationship between four principal components and project cost performance.

The results indicate that the significant influencing factors of project cost performance of DBB projects and DB projects are different. For DBB projects, owner abilities, such as owner team ability, owner experience, and owner finance, are important influencing factors causing cost overruns, while for DB projects cost performance is more sensitive to the contractor abilities, namely, contractor team ability, contractor finance, contractor experience, etc.

The results of the paper are mainly derived by quantitative research method based on the survey of 144 samples, so the results may need validation by qualitative studies. Further research could apply case study or interview to validate the findings in this research. In addition, project type and location are not considered as control variables due to the limited number of samples, future research could be conducted to investigate their relationship with project performance.

The findings of this research not only help practitioners have a better understanding of the factors influencing project cost performance, but also provide some guidelines for practitioners to pay attention to different factors to better control the cost performance within different delivery systems.

Owner ability and contractor ability are found to be of different importance in influencing cost performance of DBB and DB projects. This research extends previous research on cost management by considering different significant factors in influencing project cost performance within DBB and DB projects.

This paper provides a comprehensive assessment of the influencing factors on knowledge transfer through meta-analysis with an emphasis on the influence of cultural contexts.

The approach involved the evaluation and analysis of 69 published empirical studies and the categorization of these studies into two groups based on different cultural contexts as described by Hofstede. A meta-analytic approach was then employed to provide a comparative analysis of the categorized studies.

The results of the meta-analysis of the influencing factors of knowledge transfer are consistent with the results obtained in most previous studies, indicating a maturation of research in this area. Influencing factors such as knowledge ambiguity, tie strength, trust, and common cognition are shown to impact knowledge transfer in different cultural contexts, particularly with regard to the individualism-low power distance and collectivism-high power distance dimensions defined by Hofstede.

This analysis was limited to the correlation between the influencing factors and the general performance in knowledge transfer and did not specifically address more detailed dimensions such as efficiency and effectiveness. In addition, this analysis was restricted to the cultural contexts of only two cultural dimensions. However, the review of this broad range of studies provided sufficient data to allow an in-depth analysis of related influencing factors and helped to illustrate and exemplify the influencing mechanisms of culture on knowledge transfer.

The results presented in this paper can help managers working in cross-cultural environments to understand the key influencing factors that affect knowledge transfer in the workplace. By understanding these factors, managers can more effectively implement methods and procedures that improve cross-cultural knowledge transfer in the work environment.

This paper provides a detailed insight into the influencing factors found between two distinctive cultural contexts and offers a fresh analysis of influencing factors with regard to knowledge transfer in a cross-cultural environment.

Realizing project portfolio benefits (PPBs) is considered a key challenge faced by enterprises. This challenge can largely be attributed to an unclear understanding of the factors influencing PPBs. However, synergistic relationships create complexity for the management of influencing factors. In response to this dilemma, the objective of this study is to quantitatively investigate the factors influencing PPBs while considering the synergistic effect among factors to provide guidelines for benefits management.

Through an integration of the synergy degree of the composite system model and social network analysis (SNA), a refined model is proposed to explore the factors influencing PPBs. First, a list that includes financial and nonfinancial influencing factors is clarified. Then, the corresponding network links, which represent the synergistic relationships among the factors, are innovatively assessed based on the synergy degree of the composite system. Finally, the influencing factor network is analyzed using both individual and overall indicators of SNA.

The resulting evidence demonstrates that four critical influencing factors exist, namely, “project managers,” “purchasers,” “development capacity” and “tangible resources.” These factors are relatively important and should be prioritized. Furthermore, the factors are divided into three subgroups: participant, resource and governmental factors. A general observation from the results is that factors that share the same subgroup are more likely to have a synergistic effect advantage, which leads to an increase in PPBs.

The value of this paper lies in its proposition of a quantitative model that can be used to measure and analyze the factors influencing PPBs with synergy considerations. This research contributes to the body of knowledge on benefits management by linking synergy with PPBs. It presents new insights for managers on how PPBs may be effectively managed and promoted from the perspective of influencing factors.