A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature

The Electricidal Effect Is Active in an Experimental Model of Staphylococcus epidermidis Chronic Foreign Body Osteomyelitis ▿

Treatment with low-amperage (200 μA) electrical current was compared to intravenous doxycycline treatment or no treatment in a rabbit model of Staphylococcus epidermidis chronic foreign body osteomyelitis to determine if the electricidal effect is active in vivo. A stainless steel implant and 104 CFU of planktonic S. epidermidis were placed into the medullary cavity of the tibia. Four weeks later, rabbits were assigned to one of three groups with treatment administered for 21 days. The groups included those receiving no treatment (n = 10), intravenous doxycycline (n = 14; 8 mg/kg of body weight three times per day), and electrical current (n = 15; 200 μA continuous delivery). Following treatment, rabbits were sacrificed and the tibias quantitatively cultured. Bacterial load was significantly reduced in the doxycycline (median, 2.55 [range, 0.50 to 6.13] log10 CFU/g of bone) and electrical-current (median, 1.09 [range, 0.50 to 2.99] log10 CFU/g of bone) groups, compared to the level for the control group (median, 4.16 [range, 3.70 to 5.66] log10 CFU/g of bone) (P < 0.0001). Moreover, treatment with electrical current was statistically significantly more efficacious (P = 0.035) than doxycycline treatment. The electricidal effect (the bactericidal activity of low-amperage electrical current against bacterial biofilms) is active in vivo in the treatment of experimental S. epidermidis chronic foreign body osteomyelitis

Analytical structural model for implementing innovation practices in sustainable food value chain

In the current scenario, sustainability is asserting a profound effect on the global Food Supply Chain (FSC). It is driven primarily by growing consciousness of consumers who want healthy food and at the same time, they demand that food production should not harm the environment. However, sustainability cannot be improved in isolation. It has to be a collaborative effort of all the players involved in the supply chain. This study is aimed at exploring the possibilities for agri-food sector of India to sustainably remunerate as good as its potential. From the perspective of a company engaged in production of an agri-food product, it is a challenging area of research to investigate into the decision-making methodologies which suit the requirements of the stakeholders as well as generate a positive sustainable impact on the FSC. In this study, a detailed analysis is done considering the present sustainable practices followed and scope for future strategies which can be adopted by its Production Plant (PP). This is achieved with the aid of Interpretive Structural Modeling (ISM) technique, a multi-criteria decision methodology and fuzzy-MICMAC analysis. A structured framework is obtained which shows the strength of the impact of each practice on the other. Using the result findings, it has been concluded that the PP must prioritize their efforts in taking measures for water reservation, pollution reduction, creating awareness among farmers and traders, and adopting sustainable employment practices. This research work can, hence, steer the focus of the company in the direction of appropriately prioritizing their sustainability practices for achieving a sustainable supply chain.http://www.springer.comseries/111562020-11-28hj2020Industrial and Systems Engineerin