Modified artificial diet for rearing of tobacco budworm, Helicoverpa armigera using the Taguchi method and Derringer’s desirability function

With the aim to improve the mass rearing feasibility of tobacco budworm, Helicoverpa armigera Hübner (Lepidoptera: Noctuidae), design of experimental methodology using Taguchi orthogonal array was applied. To do so, the effect of 16 ingredients of an artificial diet including bean, wheat germ powder, Nipagin, ascorbic acid, formaldehyde, oil, agar, distilled water, ascorbate, yeast, chloramphenicol, benomyl, penicillin, temperature, humidity, and container size on some biological characteristics of H. armigera was evaluated. The selected 16 factors were considered at two levels (32 experiments) in the experimental design. Among the selected factors, penicillin, container size, formaldehyde, chloramphenicol, wheat germ powder, and agar showed significant effect on the mass rearing performance. Derringer's desirability function was used for simultaneous optimization of mass rearing of tobacco budworm, H. armigera, on a modified artificial diet. Derived optimum operating conditions obtained by Derringer's desirability function and Taguchi methodology decreased larval period from 19 to 15.5 days (18.42 % improvement), decreased the pupal period from 12.29 to 11 days (10.49 % improvement), increased the longevity of adults from 14.51 to 21 days (44.72 % improvement), increased the number of eggs/female from 211.21 to 260, and increased egg hatchability from 54.2% to 72% (32.84 % improvement). The proposed method facilitated a systematic mathematical approach with a few well-defined experimental sets

Search Engine Advertising Adoption and Utilization: An Empirical Investigation of Inflectional Factors

© Taylor & Francis Group, LLC. Search engine advertising (SEA) is a prominent source of revenue for search engine companies, and also a solution for businesses to promote their visibility on the web. However, there is little academic research available about the factors and the extent to which they may influence businesses’ decision to adopt SEA. Building on Theory of Planned Behavior, Technology Acceptance Model, and Unified Theory of Acceptance and Use of Technology, this study develops a context-specific model for understanding the factors that influence the decision of businesses to use SEA. Using structural equation modeling and survey data collected from 142 businesses, this research finds that the intention of businesses to use SEA is directly influenced by four factors: (i) attitude toward SEA, (ii) subjective norms, (iii) perceived control over SEA, and (iv) perceived benefits of SEA in terms of increasing web traffic, increasing sales and creating awareness. Furthermore, the research we discover six additional factors that have an indirect influence: (i) trust in search engines, (ii) perceived risk of SEA, (iii) ability to manage keywords and bids, (iv) ability to analyze and monitor outcomes, (v) advertising expertise, and (vi) using external experts

Economic development, demographic characteristics, road network and traffic accidents in Zhongshan, China: gradient boosting decision tree model

This paper explores the joint effects of economic development, demographic characteristics and road network on road safety. Although extensive efforts have been undertaken to model safety effects of various influential factors, little evidence is provided on the relative importance of explanatory variables by accounting for their mutual interactions and non-linear effects. We present an innovative gradient boosting decision tree (GBDT) model to explore joint effects of comprehensive factors on four traffic accident indicators (the number of traffic accidents, injuries, deaths, and the economic loss). A total of 27 elaborated influential factors in Zhongshan, China during 2000–2016 are collected. Results show that GBDT not only presents high prediction accuracy, but can also handle the multicollinearity between explanatory variables; more importantly, it can rank the influential factors on traffic accidents. We also investigate the partial effects of key influential factors. Based on key findings, we highlight the practical insights for planning practice