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Which venture capital is more beneficial in the product innovation of entrepreneurial ventures? The authors study the drawbacks and different effects of corporate venture capital (CVC) and independent venture capital (IVC) on the effectiveness and efficiency of product innovation in entrepreneurial ventures to answer this question.

This study uses a panel dataset of 502 high-tech ventures and runs the Heckman model to correct potential endogeneity issues.

The authors find that CVC increases the product innovation effectiveness of entrepreneurial ventures, but decreases their efficiency. IVC reduces innovation effectiveness and enhances efficiency. However, CVC performs less positively, while IVC performs more positively in terms of innovation effectiveness and efficiency in the B2B market than in the B2C market.

This study provides insights into how to leverage venture capital to develop new products effectively and efficiently.

This study moves beyond the current understanding of the finance-marketing interface. It delineates the two faces of venture capital and reveals the joint effects of equity stakes and market stakes between different types of venture capital and transaction markets in product innovation.

Research on makers and innovation has been equivocal regarding whether maker innovation is driven by internal motivation or external incentives. The motivation view favors the intrinsic motives of makers, whereas the incentive view supports external economic incentives. The authors combine both views to explore how innovation tournaments promote the product innovation outcomes of different creative and entrepreneurial makers, using economic incentives (money) or social incentives (love).

The authors interviewed 42 makers and collected a panel dataset of 29,823 makers from the largest digital maker community in China using a Python crawling program. The authors analyzed the data using multiple methods, including cluster analysis, discriminant analysis, factor analysis and negative binomial regression.

Compared with entrepreneurial makers, the product productivity of creative makers is inferior, but their product popularity is greater. The social incentive of innovation tournaments promotes the product productivity and popularity of creative makers compared with that of entrepreneurial makers, but the economic incentive is contradictory. In addition, social and economic incentives interact to generate inconsistent influences.

The study identifies creative and entrepreneurial makers and contributes to user innovation and innovation tournaments by integrating motivation and incentive views.

Entrepreneurial mentoring is widely regarded as an effective way to train novice entrepreneurs all over the world. However, the effectiveness of this approach and the determinants are not well understood under country-specific conditions. The purpose of this paper is to build a conceptual framework and use empirical analysis to explore the mentoring effect and its determinants, especially in the Chinese context.

The paper uses data from 172 young entrepreneurs which had been supported by Youth Business China, Mianyang Office since 2008. The factor analysis and structural equation model have been applied to analyze the data to investigate the quantitative relationship and path of the mentoring effect of entrepreneurship with mentor’s factors, young entrepreneurs (mentees’s factors) and their interrelationship.

The assessment scores of the entrepreneurship mentoring effect both in experience level and effectiveness level are relatively high, in the satisfactory range. The entrepreneurship mentoring effect, measured by the experience and the performance level, is determined by the coupling interaction of the mentor, the mentee and their interactive relationship. Among them, the mentor’s characteristic, the most important being his/her intention, has the biggest effect on the mentoring effect, significantly bigger than the mentor’s quality and skill. However, the mentor’s intention is not strong as expected. The interactive relationship between the mentor and the mentee also has a significant positive effect on entrepreneurial mentoring effect. The study also discovered the mentee factors have comparatively smaller effect on both the interactive relationship and the mentoring effect. Furthermore, it is found that the absorptive capability and learning intention of the young entrepreneur are relatively weak.

The construction of the index system of this research reflects the overall characteristics of the research objects and their static relationships. Therefore, the dynamic change of the mentoring relationship in different phases of the mentorship has not been taken into account. Also, self-serving bias may exist as this research measures the mentoring effect by the feedback on the mentor’s perception, using surveys completed by the mentees to measure both the mentee’s traits and the mentor’s qualities.

This study provides guidance on how entrepreneurship could be promoted and on how educational institutions in China can make the mentoring process a positive and effective system in order to enhance the mentoring effect.

The empirical conclusions of the present study can be applied to other business incubator, entrepreneurship education institutions and for the improvement and promotion of entrepreneurial mentoring system in China.

This paper probes into the mentoring system in the context of China from a new perspective and proposes an original conceptual model to study the entrepreneurship mentoring effect and its determinant.

The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated.

The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods).

Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns.

The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive.

An algorithm-based prediction tool would offer new perspectives to the management of tourism movements.

Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach.

This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.

Knowing the behavior of tourists visiting cultural destinations enables better management of tourist flows, a better understanding of areas with greater tourist density and an opportunity to decongest popular neighborhoods. The purpose of this study is to segment tourists according to their spatio-temporal behavior and identify the primary variables that characterize the resulting segments, which will help urban destinations prevent problems arising from the saturation of tourists in certain areas.

To do this, this paper analyzes the behavior of tourists visiting the southeastern Spanish city of Granada, one of the most highly visited cultural tourism destinations. The data analysis used the methodology of sequence alignment which is used to identify segments as a function of their contained elements and the order in which these appear.

The results demonstrate the existence of three segments with different behavioral patterns: the “explorer tourists” segment, the “non-traditional cultural tourists” segments and the “typical cultural tourists” segment. These segments show differences in the concentration of their visits. This study discovered that the segments that visit a greater number of destination areas are those with less cultural orientation, higher travel budgets and younger and more frequent visitors.

In the segmentation not only keep in mind the visited areas, but the order in which they were visited as well. In addition, one should consider the time that each tourist remains in each relevant zone of the destination, given that the visiting time is an important variable to assess the congestion of an area.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

The purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence.

A total of 14 factors influencing SNS fatigue are identified through an extensive literature review. Interpretive structural modeling (ISM) and Matrice d'Impacts Croisés Multiplication Appliqué à un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters.

The results revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work–life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue.

This study represents an initial step toward comprehensively understanding the interrelationships among the factors leading to SNS fatigue and reveals how determinants of SNS fatigue are hierarchically organized, thus extending existing research on SNS fatigue. It also provides logical consistency in the ISM-based model for SNS fatigue by grouping identified factors into dependent and independent categories. Moreover, it extends the applicability of the integration of the ISM and MICMAC approaches to the phenomenon of SNS fatigue.

The communication link in the engineering of Internet of Vehicle (IOV) is more frequent than the communication link in the Mobile ad hoc Network (MANET). Therefore, the highly dynamic network routing reliability problem is a research hotspot to be solved.

The graph theory is used to model the MANET communication diagram on the highway and propose a new reliable routing method for internet of vehicles based on graph theory.

The expanded graph theory can help capture the evolution characteristics of the network topology and predetermine the reliable route to promote quality of service (QoS) in the routing process. The program can find the most reliable route from source to the destination from the MANET graph theory.

The good performance of the proposed method is verified and compared with the related algorithms of the literature.

The purpose of this study is to estimate different data models on house prices using statistical models and the variables which are controlled by real estate policy.

This study used several statistical techniques, such as Vector auto-regression (VAR), Johansen co-integration and variance decomposition, which aim to assess the significant effect of macroeconomic factors on Chinese house prices.

The results show that land supply and other variables have negative effects on house prices. The results also indicate that financial mortgages for real estate have positive effects on house prices and the area of vacant houses as well as the area of housing sold.

This study only covers three cities in China because of limitations of data for other cities.

This study proposes policy suggestions according to the empirical results obtained.