Strategic corporate social responsibility with spillover effect in innovation

Purpose This paper aims to investigate the motivation for firms to innovate their products to be socially responsible in the presence of the spillover effect. The follower of the innovation in corporate social responsibility (CSR) can benefit from the leader’s innovation by technological spillover. For instance, evidence can be found in the cosmetics industry (e.g. Lush Retail Ltd. and The Body Shop) and the market of hybrid electric vehicles (e.g. Toyota and Honda). Moreover, consumers may have different perceptions on the sequence of CSR innovation by firms, they may prefer more on the CSR product launched by the leader because they usually relate the desired stage to their interests when making a purchase decision. Therefore, the firms’ decision to be a leader of the CSR innovation depends on the trade-off between the loss in the spillover effect and the benefit of the first-mover advantage, which has not been considered by the existing literature. This paper explains the firms’ motivation on CSR innovation in a realistic situation where competing firms’ CSR programs are launched sequentially and sheds light on the private sector’s decision on strategy from the perspective on the social contribution, and provides some managerial implications about the competing firms’ strategies of launching the CSR innovation. Design/methodology/approach The authors construct a two-period Hotelling model in which consumers are divided into two groups: the altruistic and normal consumers. The altruistic consumers have more willingness to pay for the CSR product while the normal consumers only care about the product performance improved by the firms’ CSR activities. Firms have the option to innovate their basic products to be socially responsible and make their decision on such CSR innovation sequentially. Moreover, the follower of the innovation can receive a spillover effect from the leader, meaning that there may exist a second-mover advantage in terms of innovation (the authors define this as a spillover effect), but in the meanwhile, the altruistic consumers value more on the CSR product sold by the leader than that by the follower (the authors define this as a preference-reduction effect). This implies that the firm can benefit in the production process from being a second-mover of the CSR innovation but may lose its first-mover advantage in terms of the preference-reduction effect. By finding and analyzing the sub-game perfect Nash equilibrium, the authors try to figure out the firms’ decisions on CSR innovation in various situations. Findings The authors find that the firms’ motivation of CSR innovation crucially depends on the fraction of the altruistic consumers, as well as the spillover effect and the preference-reduction effect. A large (small) fraction of the altruistic consumers attracts (restricts) both the leader and the follower to engage in CSR innovation. More importantly, when such fraction is not too large but stays at a relatively high level, a potential leader of the CSR innovation may not wish to innovate. Hence, the potential follower may be the monopolist in the market of the socially responsible product. In addition, the authors reexamine this result in a variation model where a leader can make its decision on the CSR innovation to be more flexible by allowing it can innovate in either periods 1 or 2. The authors demonstrate that when the fraction of the altruistic consumers falls in an intermediate range, the leader may wish to delay the CSR innovation to period 2. In such a case, the leader of the CSR innovation may tend to trade its first-mover advantage for head-to-head competition with the follower and prevents the follower from benefiting from the spillover effect. Moreover, a flexible choice on the CSR innovation brings greater initiative to a firm to be the leader of the innovation. Originality/value Nearly all the studies about firms’ decisions on CSR innovation are conducted in an environment of simultaneous move, which is not appropriate to describe the real business world; many pieces of evidence show that many CSR programs are launched sequentially rather than simultaneously. The theory identifies a couple of important factors of the CSR innovation in a more realistic situation, i.e. sequential more on CSR innovation. Both spillover effect and preference-reduction effect crucially affect the firms’ decision on innovating their products to be socially responsible, which contributes to the existing literature in CSR and strategic decision. This paper also sheds some light on managerial implications with CSR innovation under various situations of competition.

3D Printing Improve the Effectiveness of Fracture Teaching and Medical Learning: A Comprehensive Scientometric Assessment and Future Perspectives

Fractures of complex body parts are often serious and difficult to handle, and they have high technical and training requirements. However, the realistic situation is that there are few opportunities for the junior residents, trainee doctors, and especially medical students to contact enough clinical practice and see such fracture patients. Fortunately, with the rapid development and continuous progress of 3D printing and related technologies, this situation has gradually gotten better and better. In this research, we confirmed that 3D printing technology could improve the effectiveness of fracture teaching and medical learning from multiple dimensions. We comprehensively screened and assessed 223 papers from the Web of Science (WoS) Core Collection on October 3, 2021, with “((3D) AND ((printing) OR (printed)) AND (fracture)) AND ((education) OR (training) OR (teaching))” as the retrieval strategy. Additionally, we used the VOSviewer software to analyze the keywords and countries and the organizations of the publications, then a series of scientometric and visualized analyses were made based on the retrieval results. Afterward, multiple databases were retrieved according to our selection criteria, we selected eight studies for the extensive literature analysis. The extracted data contained information of authors, problems solved, participants, methods, assessments, results, and benefits/limitations. These intuitive and in-depth analyses further confirmed and appraised the advantages of 3D printing in complex fracture models more objectively. In conclusion, 3D printing could improve the effectiveness and extension of fracture teaching, as well as medical learning, by providing the powerful interaction with 3D effect, wakening students learning interest, and allowing the junior residents, trainee doctors to have as realistic a virtual practice experience as possible. Through this research, it is expected that more researchers could be attracted to conduct more comprehensive and thorough studies on the application of 3D printing for training and educational propose, to promote the development of 3D technology-based medical education practice and further deepen the reform of medical education and improve the quality of fracture education and learning.

Anthocyanins: Dietary Sources, Bioavailability, Human Metabolic Pathways, and Potential Anti-Neuroinflammatory Activity

The objectives of this chapter are to summarize and discuss (i) the anthocyanins structure and content in foodstuffs and their dietary intake (ii) the anthocyanins bioavailability and human metabolic pathways and (iii) the in vitro and in vivo potent anti-neuroinflammatory effects of anthocyanins and their metabolites. Indeed, anthocyanins are polyphenolic compounds belonging to the group of flavonoids, and are one of the most commonly consumed polyphenols in a normal diet. They are responsible of red, blue and purple color of several fruits and vegetables and their intake has been related with several human health benefits. The anthocyanins structures diversities as well as their content in various fruits, vegetables and cereals is addressed. Moreover, despite the growing evidence for the protective effects of anthocyanins, it is important to highlight that the in vivo bioavailability of these compounds is relatively low in comparison to their more stable metabolites. Indeed, after consumption, these bioactives are subjected to substantial transformations in human body. Phase I and II metabolites generated by intestinal and hepatic enzymatic reactions, and phenolic acids produced by gut microbiota and their metabolized forms, are the most important metabolic anthocyanins forms. For this reason, the study of the biological properties of these circulating metabolites represents a more in vivo realistic situation. Although the anthocyanin bioavailability researches in humans are limited, they will be discussed together with a global metabolic pathway for the main anthocyanins. Moreover, several works have demonstrated that anthocyanins can cross the blood brain barrier, and accumulate in brain endothelial cells, brain parenchymal tissue, striatum, hippocampus, cerebellum and cortex. Consequently, the study of anthocyanins as potent therapeutic agents in neurodegenerative diseases has gained relevance and the principal and the most recent studies are also discussed in the book chapter.

A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures

Hybrid simulation is an experimental method used to investigate the dynamic response of a reference prototype structure by decomposing it to physically-tested and numerically-simulated substructures. The latter substructures interact with each other in a real-time feedback loop and their coupling forms the hybrid model. In this study, we extend our previous work on metamodel-based sensitivity analysis of deterministic hybrid models to the practically more relevant case of stochastic hybrid models. The aim is to cover a more realistic situation where the physical substructure response is not deterministic, as nominally identical specimens are, in practice, never actually identical. A generalized lambda surrogate model recently developed by some of the authors is proposed to surrogate the hybrid model response, and Sobol’ sensitivity indices are computed for substructure quantity of interest response quantiles. Normally, several repetitions of every single sample of the inputs parameters would be required to replicate the response of a stochastic hybrid model. In this regard, a great advantage of the proposed framework is that the generalized lambda surrogate model does not require repeated evaluations of the same sample. The effectiveness of the proposed hybrid simulation global sensitivity analysis framework is demonstrated using an experiment.

‘Fearful-place’ coding in the amygdala-hippocampal network

Animals seeking survival needs must be able to assess different locations of threats in their habitat. However, the neural integration of spatial and risk information essential for guiding goal-directed behavior remains poorly understood. Thus, we investigated simultaneous activities of fear-responsive basal amygdala (BA) and place-responsive dorsal hippocampus (dHPC) neurons as rats left the safe nest to search for food in an exposed space and encountered a simulated ‘predator.’ In this realistic situation, BA cells increased their firing rates and dHPC place cells decreased their spatial stability near the threat. Importantly, only those dHPC cells synchronized with the predator-responsive BA cells remapped significantly as a function of escalating risk location. Moreover, optogenetic stimulation of BA neurons was sufficient to cause spatial avoidance behavior and disrupt place fields. These results suggest a dynamic interaction of BA’s fear signalling cells and dHPC’s spatial coding cells as animals traverse safe-danger areas of their environment.

Efficient computation of target-oriented link criticalness centrality in uncertain graphs

We challenge the problem of efficiently identifying critical links that substantially degrade network performance if they do not function under a realistic situation where each link is probabilistically disconnected, e.g., unexpected traffic accident in a road network and unexpected server down in a communication network. To solve this problem, we utilize the bridge detection technique in graph theory and efficiently identify critical links in case the node reachability is taken as the performance measure.To be more precise, we define a set of target nodes and a new measure associated with it, Target-oriented latent link Criticalness Centrality (TCC), which is defined as the marginal loss of the expected number of nodes in the network that can reach, or equivalently can be reached from, one of the target nodes, and compute TCC for each link by use of detected bridges. We apply the proposed method to two real-world networks, one from social network and the other from spatial network, and empirically show that the proposed method has a good scalability with respect to the network size and the links our method identified possess unique properties. They are substantially more critical than those obtained by the others, and no known measures can replace the TCC measure.

The Projected Implementation of Human Geography on the basis of Practical Design: A Case Study of Taking a Map to the Journey

This paper begins with the quality analysis of the current project-based learning task of Humanities Geography, and further analyzes the “inauthenticity” and “"insubstantiality" phenomenon in the process of project-based learning design, mainly in analyzing the problems of the entire process of determination of objectives, creation of situations, design of driving tasks, implementation, presentation and evaluation of tasks. This paper chooses Taking a Map to the Journey as an example, which is the project task “the Application of Maps in Daily Life” in Humanities Geography, from the development of resources and determination of the theme to the creation of a realistic situation, from the design of higher-order thinking-driven "real" tasks to the organization and implementation of group “real” cooperation, and finally presents personalized achievement and designs the gauge to deepen the "real evaluation". By these means, the classroom project-based learning can be more effective and efficient and fully indicate the subject's core literacy, and thus realizing the "real design" of project-based learning.

A Coordinated Optimization Model of the Complex System of the Green Supply Chain Distribution Network

A well-established distribution network is fundamental to the sound management of the green supply chain. To adapt to the market demand and policies for green products, it is urgent to build an efficient and rational logistic distribution network for the green supply chain. Many researchers have tried to design distribution networks through the coordinated optimization of the green supply chain, in the light of realistic situation. However, there are very few optimization models that consider all kinds of influencing factors. To solve the problem, this paper attempts to establish a coordinated optimization model of the complex system of the green supply chain distribution network (GSCDN). Firstly, the authors plotted the structure and game logic of the GSCDN and defined the upper limit of sales induced by the limited production capacity of producers. Secondly, the coordinated optimization conditions were configured for the distributor layer, producer layer, and market demand layer, and a coordinated optimization model was set up for the complex system. Finally, the contractual coordinated optimization mechanism was detailed for the complex system under the profit-sharing contract. The proposed model and solving algorithm were proved valid through experiments.

Designing a warehouse internal layout using a parabolic aisles based method

Refined layout is a basis of warehousing efficiency. Straight aisle is a typical feature of current warehouse internal layouts. The purpose of this paper is to explore the possibility of using curve aisles for warehouse layout. By Choosing typical non-traditional layouts and transforming their inclined cross-aisle trajectory into parabola, two parabolic aisle layouts, parabolic Flying-V and parabolic Fishbone, are constructed. For unit-load warehouses, based on the morphological characteristic analysis and the parabolic types selection, the picking distance model and the cross-aisle length formula are presented. Interval Numerical Simulation Method (INSM) and Genetic Algorithms (GA) are adopted to solve the model respectively in order to verify the results. This research breaks through the realistic situation of straight aisle leading warehouse layout, and enriches the relevant layout theory. The calculation results of 100 warehouses with different sizes show that the picking distance of parabolic Flying-V could be reduced by 0.22-0.62 % compared with the straight layout, and the theoretical possible improvement space has been compressed by 2.42-12.26 %. Its length of cross-aisle is shortened by -0.03-3.10 %. The picking distance of parabolic Fishbone could be only reduced by 0.02-0.04 %. The theoretical possible improvement space has been compressed by 1.27-1.83 %. But its length of cross-aisle will increase by 4.63-19.50 % significantly. We believe that the layout of non-rectangular complex special-shaped warehouses based on curve trajectory aisles would become an important research topic. In addition, after some necessary modifications to the objectives and constraints, the proposed method in this paper may also be used for the arrangement of machines and devices in a workshop in principle.

Emergence of spatial transitions in urban congestion dynamics

The quantitative study of traffic dynamics is crucial to ensure the efficiency of urban transportation networks. The current work investigates the spatial properties of congestion, that is, we aim to characterize the city areas where traffic bottlenecks occur. The analysis of a large amount of real road networks in previous works showed that congestion points experience spatial abrupt transitions, namely they shift away from the city center as larger urban areas are incorporated. The fundamental ingredient behind this effect is the entanglement of central and arterial roads, embedded in separated geographical regions. In this paper we extend the analysis of the conditions yielding abrupt transitions of congestion location. First, we look into the more realistic situation in which arterial and central roads, rather than lying on sharply separated regions, present spatial overlap. It results that this affects the position of bottlenecks and introduces new possible congestion areas. Secondly, we pay particular attention to the role played by the edge distribution, proving that it allows to smooth the transitions profile, and so to control the congestion displacement. Finally, we show that the aforementioned phenomenology may be recovered also as a consequence of a discontinuity in the node’s density, in a domain with uniform connectivity. Our results provide useful insights for the design and optimization of urban road networks, and the management of the daily traffic.