Implementing the “hierarchical diagnosis and treatment” system highlights the important role of general practitioners as “residents’ health gatekeepers.” Still, the low level of career growth always limits the realization of their service value. Inertial thinking uses a single factor to explain the complexity of career growth in previous studies; in fact, it isn’t easy to assess whether the factor is a sufficient and necessary condition for a high level of career growth. Herein, we have used a set theory perspective to (...) analyze the mechanism of influencing high-level career growth by combining psychological and organizational factors. This research aims to analyze causal complexity relationship between these conditions and results is analyzed in detail. We choose fuzzy-set qualitative comparative analysis with a sample of 407 GPs to test 5 antecedent conditional variables that can affect their career growth. The variables include professional identity, self-efficacy, achievement motivation, training mechanism, and incentive mechanism. To ensure the universality and diversity of data, the samples were selected from community medical institutions in different regions of China. The results show that three pathways can affect the high career growth of GPs, and the optimal pathway A2 is the linkage matching of high incentive mechanism, high professional identity, high achievement motivation, and high self-efficacy. At the same time, we find that professional identity plays an alternative role in the three pathways. When professional identity is at a high level, as long as achievement motivation and self-efficacy are superior, or achievement motivation, self-efficacy, and achievement motivation are superior, a high level of career growth can be achieved. We broke the shackles of previous studies that only focused on the impact of single factors on the career growth of GPs. From the perspective of set theory, we use configurational thinking to construct Influential pathways of high career growth of GPs by integrating antecedents. The results can provide effective support for improving GPs’ service ability and realizing their service value to protect residents’ health. (shrink)

Green innovation investments have rapidly grown since 2000. Green innovation indexes play important roles and are typically constructed by screening and indexing. However, Nobel Laureate Markowitz emphasizes portfolio selection instead of security selection and accentuates that “A good portfolio is more than a long list of good stocks.” Moreover, the screening-indexing strategies ignore that investors can take green innovation as an additional objective and thus gain additional utility. We consequently construct 3-objective portfolio selection for green innovation in addition to variance (...) and expected return. An efficient frontier of portfolio selection then extends to an efficient surface which is a panorama of the optimal variance, expected return, and expected green innovation. Investors thus fully envisage the trade-offs and enjoy the freedom of choosing preferred portfolios on the surface. In contrast, the screening-indexing strategies inflexibly leave investors with only one point. As the originality, we prove in a theorem that there typically exists a curve on the efficient surface so all portfolios on the curve dominate the green innovation index. We test the dominance by component stocks of China Securities Index 300 and obtain affirmative results out of sample. The results still hold in robustness tests. At last, we classify green innovation into categories, further model the categories by general k -objective portfolio selection, and still illustrate the dominance. Consequently, investors can consider and control each category. (shrink)

With the development of mobile Internet technology, firms need to complete the entire process of consumer targeting, ad content generation, and ad display in a very short time window. Therefore, computational advertising, such as native ads on social media platforms, has become the mainstream of online advertising with its automation and personalization features. However, computational advertising faces some problems when using artificial intelligence technology to generate content. First, the images should have a significant enough impact on consumers and be easy (...) to adjust to save computational power at the same time; second, the iteration of the computational advertising system relies on consumer behaviors or advertising effectiveness, and firms need to learn the relationship between ad design and consumer behaviors. Under the above two problems, this paper selects visual distance as the main variable, and images can be adjusted by cropping to save computational power. This paper incorporates image design and ad effectiveness metrics into the construal level theory framework, under which the effectiveness metrics can be quickly determined. Following previous studies, we use click-through rate to represent the early stage of the sales funnel and a higher construal level and CVR to represent the later stage of the sales funnel and a lower construal level. Therefore, visually distant images bring distant psychological distance or higher construal level, which can get higher CTR; visually proximate images bring near psychological distance or lower construal level, which can bring higher CVR. These findings suggest that firms can improve the efficiency of their advertising systems and gain more revenue by understanding consumer psychological states. (shrink)

本书从伦理学视角系统论述了守法问题,内容包括:守法的道德证明、守法的道德构成、守法的道德机制、守法的道德价值等。.