Differential Game for Environmental-Regulation in Green Supply Chain

[[abstract]]This paper demonstrates that a proper design of environmental-regulation pricing strategies is able to promote Extended Product Responsibility for green supply chain firms in a competitive market. A differential game model comprising Vidale-Wolfe equation has been established in light of sales competition and recycling dynamics as well as regulation related profit function. Analytic solutions of Markovian Nash equilibriums are provided with the necessary condition derived from Hamilton-Jacobi-Bellman equations. We found that governments should opt to gradually raise regulation standards so that rational manufacturers will gradually improve its product recyclability, and, in turn, Extended Product Responsibility will get promoted

Intelligent synthesis of hyperspectral images from arbitrary web cameras in latent sparse space reconstruction

Synthesizing hyperspectral images (HSI) from an ordinary camera has been accomplished recently. However, such computation models require detailed properties of the target camera, which can only be measured in a professional lab. This prerequisite prevents the synthesizing model from being installed on arbitrary cameras for end-users. This study offers a calibration-free method for transforming any camera into an HSI camera. Our solution requires no controllable light sources and spectrometers. Any consumer installing the program should produce high-quality HSI without the assistance of optical laboratories. Our approach facilitates a cycle-generative adversarial network (cycle-GAN) and sparse assimilation method to render the illumination-dependent spectral response function (SRF) of the underlying camera at the first part of the setup stage. The current illuminating function (CIF) must be identified for each image and decoupled from the underlying model. The HSI model is then integrated with the static SRF and dynamic CIF in the second part of the stage. The estimated SRFs and CIFs have been double-checked with the results by the standard laboratory method. The reconstructed HSIs have errors under 3% in the root mean square

Pursuing extended producer responsibility in the context of EIPs by a Hotelling model

[[abstract]]This paper offers a prescriptive suggestion to preserve the extended producer responsibility goal in an eco-industrial park. A novel Hotelling model in reverse trading direction is developed to examine the technology-position decisions between specialized recycling processors. We find that the notion of eco-industrial parks may not always be compatible with extended producer responsibility, which motivates producers to improve their eco-design in clean production within the context of competition. Based on our analysis, competition helps certain types of parks become self-organized such that constituent firms spontaneously improve their eco-design. If eco-design is not improved in a park due to the existing competition and production conditions, an ordinary tax-subsidy should be sufficient to make the parks self-organized. Therefore, eco-industrial parks can be re-aligned to their environmental goals

Crowd Density Estimation from Few Radio-Frequency Tracking Devices: I. A Modelling Framework

[[abstract]]This study proposes a modeling framework based on few radio frequency (RF) tracking devices, such as smartphones or beacon. The proposed framework aims to estimate crowd density continuously where vision analysis is unreliable and the relation between pedestrian speed and density can be at least specified. The crowd density estimated through the modelling framework can not only be used for evacuation commanding at emergency times, but also can be used for commercial usage at a normal time and building/facility layout improvement during design time. In the proposed framework, the application level maps input data spaces into feature spaces. The model level applies multiple data models to increase the accuracy of the estimated states. Moreover, the abstract level fuses the heterogeneous parameters estimated from the model level. The models we included in the framework are cellular automata models, ferromagnetic models, social force models, and complexity models. The model parameters are estimated by Markov Chain Monte Carlo (MCMC) and particle swarm optimization (PSO) methods. The fusion algorithm factory instantiates a data assimilation approach and a continuous receiver operating characteristic (ROC) estimator

Regional diffusion for remanufactured tied products in ecologically conscious consumers

In this paper, we demonstrate that independent aftermarket replacement component remanufacturers are able to help the host product manufacturers establish their market share. We employ agent-based simulation and evolutionary game theory in the light of innovative diffusion process with network externality and sustainability consciousness, in microscopic and dynamic emergent perspectives. We suggest a strategic decision management insight for better marketing an environmental sustainable product in a new product diffusion process. We show that both market share and long-term profitability of a tied product firm, with inferior market share, indeed can be raised significantly by applying the suggested price-protection-distribution decision strategy at specific timing when the ecologically conscious consumer segment grows.sustainable economy; environmental sustainability; technology adoption; replicator dynamics; agent-based modelling; complex system simulation; regional diffusion; remanufactured tied products; ecologically conscious consumers; agent-based systems; multi-agent systems; component remanufacturing.

Stochastic Diffusion Analysis for Sustainable Green Innovation

[[abstract]]This study investigates the sustainability of green innovation under the influence of coopetitive diffusion. We focus on green innovations which repurpose discarded technology accessories for resale. Original manufacturers make every attempt to prevent the use of low-cost replacements. To encourage green innovation, incumbent market leaders need to be provided with business strategies which help them maximize profitability. Using a stochastic differential game from a Lotka–Volterra system, we predict a coopetitive diffusion path among participant stakeholders. We find that green innovation, combined with the positive effect of network externalities can indeed enhance total market growth. Factors such as product characteristics, product pricing, and compatibility protection strategies must interact properly for green innovation to be sustainable. Keywords: Stochastic Lotka–Volterra system; stochastic Hamilton–Jacobi–Bellman equations; green innovation; coopetitive diffusio

GIS, Grid Computing and RFID in Healthcare Information Supply Chain: A Case for Infectious Disaster Management

[[abstract]]Several healthcare disasters have occurred in the past decade, and their occurrence has become more frequent recently due to one natural catastrophe after another. The medical application requirement for such a disaster management system includes effective, reliable, and coordinated responses to disease and injury, accurate surveillance of area hospitals, and efficient management of clinical and research information. Based on the application requirements, this case study describes a grid-based system in a health information supply chain that monitors and detects national infectious events using geographical information system (GIS), radio-frequency identification (RFID), and grid computing technology. This system is fault-tolerant, highly secure, flexible, and extensible, thus making it capable of operation in case of a national catastrophe. It has a low cost of deployment and is designed for large-scale and quick responses. Owing to the grid-based nature of the network, no central server or data centre needs to be built. To reinforce the responsiveness of the national health information supply chain, this case study proposes a practical, tracking-based, spatially-aware, steady, and flexible architecture, based on GIS and RFID, for developing successful infectious disaster management plans to tackle technical issues. The architecture achieves a common understanding of spatial data and processes. Therefore, the system can efficiently and effectively share, compare, and federate—yet integrate—most local health information providers and results in more informed planning and better outcome

Moderating effect of environmental supply chain collaboration: evidence from Taiwan

[[abstract]]Purpose This study explores how corporate environmental strategies, namely, environmental management strategy (EMS) and green product strategy (GPS), affect the competitiveness of a firm. In addition, this study investigates whether the environmental collaboration in supply chains (ECSC), namely, environmental collaboration with suppliers (ECS), and environmental collaboration with customers (ECC) moderate the environment – performance relationship. Design/methodology/approach Survey methodology and regression modeling are adopted to assess the relationship between corporate environmental strategy and competitive performance of a company, including the moderating effects of ECSC. Findings Competitiveness is positively affected by EMS and GPS. ECSC moderately affects the links among EMS, GPS, and competitiveness. Regarding the differences between the impacts of ECS and ECC on performance, only ECS acts as a moderator in the enhancement of EMS and GPS. Thus, ECS positively contributes to enhance competitive advantage. In contrast to perceptions, ECC directly improves firm competitiveness. Research limitations/implications The findings support the understanding that the moderating role of ECSC may explain the conflicting results in environment–performance linkages. In particular, suppliers and customers could impact EMS and GPS in direct or interactive ways, or both, to enhance the performance of a firm. Practical implications Significant performance improvements are influenced not only by the real environmental commitment of companies to internal green management but also by the positive relations of firms with their external cooperative capabilities in environmental relationships with chain partners. Originality/value This research is the first to suggest and empirically test the moderating impacts of ECSC on the relationship between corporate environmental strategy and competitiveness

Human-Machine Interaction: Adapted Safety Assistance in Mentality Using Hidden Markov Chain and Petri Net

This study proposes a cognition-adaptive approach for the administrative control of human-machine safety interaction through Internet of Things (IoT) data. As part of Industry 4.0, a human operator possesses various characteristics, but cannot be consistently understood as well as a machine. Thus, human-machine interaction plays an important role. This study focuses on incumbent challenges on the basis of estimated mental states. Given the operation logs from data recording hardware, a Hidden Markov model on top of a human cognitive model was trained to capture a production line worker’s sequential faults. Our study found that retaining workers’ attention is insufficient and tracking the state of perception is key to accomplishing production tasks. A safe workflow policy requires attention and perception. Accordingly, our proposed Petri Net enhances operation safety and improves production efficiency

CIRCUIT RELIABILITY EVALUATION USING TWO-STAGE COMPLEX NETWORK ANALYSIS

[[abstract]]A novel two-stage network analysis method for a complex RF circuit was de-veloped to evaluate the reliability of circuit more efficient. An example of power amplifier circuit probability was calculated from 4 simplified type circuits and a value of probability of 0.89563 was obtained. This result was also verified by Monte Carlo method, and a convergent value of 0.55 wasobtained, which demonstrates the calculated reliability of complex RF circuit by two-stage etwork analysis method is valid