The present study aims to determine the impact of green innovation (GI) on the overall performance of an organization while keeping the variable of environmental management (EM) as a moderator. We used a dataset consisting of four data years, from 2014 to 2017, of A-share companies listed on the Shanghai Stock Exchange (SSE). The concept of green innovation refers to the use of advancements in technology that enable savings in energy, along with the recycling of waste material. When advanced technology is utilized in the production process, the products are referred to as green products and the whole process of adopting such technologies and product design is referred to as “Corporate Environmental Management”. Such innovations improve the overall financial performance of companies as it enables them to improve their social image by reducing their carbon footprint and ensures their long-term sustainability. The main issue is the limited focus and attention given to the topic, from the perspective of companies. This research focuses on the impact of green innovation and the importance of environmental management for the sustainability of companies. Our findings suggest that the relationship between green innovation and the performance of the company is positive and verifies the existence of moderating effects of environmental management on the relationship between green innovation and firm performance. Implications are given to academia and practitioners.

Melatonin functions as a plant growth regulator, has diverse functions and plays an important role in ripening and fruit senescence. In the current study, we investigated the effect of exogenous melatonin (0.1 mM and 0.5 mM) on reactive oxygen species (ROS) metabolism, membrane lipid peroxidation and antioxidant enzyme activity of avocado (Persea americana Mill. cv. 034) during fruit ripening at 22oC ± 1 and 75-80% relative humidity (RH). The results showed that postharvest fruits treated with 0.5 mM melatonin effectively reduced the accumulation of superoxide anion (O2.), hydrogen peroxide (H2O2) and malondialdehyde (MDA) in the mesocarp of the fruit. In addition, melatonin treatment also significantly promoted the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) in avocado. It is suggested that enhanced antioxidant enzyme activity induced by melatonin treatment may contribute to scavenge ROS and alleviating membrane lipid peroxidation in avocado fruit. The results indicate that the MT application might collectively contribute to the delay senescence and maintain postharvest quality of avocado.

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Data preparation is a compulsory process in any data science project. Many research have shown that it constitutes 80% of the time, effort and resources of a data science project. Depending on the particular project and data type, Data preparation step may required different methods/steps. Detecting and processing outlier data is one of the important preprocessing steps in data preparation , especially for time series data. This paper reviews two methods for detecting outliers for low dimensional data, namely Z - Score and Box - plot charts. We also present results of experiments which applied these methods for temperature data collected from 43 monitoring stations in 3 - hour in Vietnam over the last 6 years from 01/01/2014 to 31/12/2019.