Logistic and multinomial-logit models: A brief review on their modifications and extensions

The work presents various techniques of the logistic and multinomial-logit modeling with their modifications. These methods are useful for regression modeling with a binary or categorical outcome, structuring in regression and clustering, singular value decomposition and principal component analysis with positive loadings, and numerous other applications. Particularly, these models are employed in the discrete choice modeling and the best-worst scaling known in applied psychology and socio-economics studies.

Multinomial Logit Model Building via TreeNet and Association Rules Analysis: An Application via a Thyroid Dataset

A model-building framework is proposed that combines two data mining techniques, TreeNet and association rules analysis (ASA) with multinomial logit model building. TreeNet provides plots that play a key role in transforming quantitative variables into better forms for the model fit, whereas ASA is important in finding interactions (low- and high-order) among variables. With the implementation of TreeNet and ASA, new variables and interactions are generated, which serve as candidate predictors in building an optimal multinomial logit model. A real-life example in the context of health care is used to illustrate the major role of these newly generated variables and interactions in advancing multinomial logit modeling to a new level of performance. This method has an explanatory and predictive ability that cannot be achieved using existing methods.

Innovation Activity and its Sources in Industry in the West Pomerania Province

Research background: Innovation activities, especially the implementation of new products and processes are desirable phenomena in economic development. For this reason, phenomena that contribute to the implementation of new solutions in enterprises should be identified. These include sources of innovation activity. Purpose: The main purpose of the article is to identify those sources of innovation activity that significantly affect product and process innovation. Research methodology: The research of the impact of sources of ideas and information for innovation on the implementation of product and process innovations was conducted in 2018 for the period 2015–2017 in the West Pomerania Province. The study was representative. It was attended by 270 entrepreneurs whose business profile corresponds to section C PKD (Polish Business Classification) – manufacturing. Logit modeling was used in the study. Results: As a result of the analyses it was noticed that in the region the implementation of process innovations was significantly influenced by foreign R&D centres, suppliers (but only when entrepreneurs began to cooperate with them), as well as by conferences, fairs and exhibitions. In the case of product innovations, internal resources were included in this group. Novelty: In the analyzed region, no advanced econometric analysis of the impact of sources of innovative activity on product and process innovations that would be representative was carried out.

Study of Green Logistics Managing Potential and the Preparedness of Auto Parts Industries in Thailand

This study aims to study green logistics managing potential and the preparedness of auto parts industries in Thailand. The statistical analysis is to identify factors with confirmatory factor analysis; oneway ANOVA is used to define relative factors affecting green logistics development of auto parts industries in Thailand. It can predict the results using multinomial logit modeling. The study suggests that factors affecting green logistics managing potential and the preparedness of auto parts industries in Thailand are environmental operations, internal green supply chain management, and external green supply chain management.

On Happiness in Teaching: An Ordered Logit Modeling Approach

This study was conducted to explain the degree of happiness in teaching and determine its influencing socio-economic factors. Using a probabilistic sampling method, the study employed 127 junior and senior high school teachers as respondents. Primary data were collected through developed questionnaires and analyzed using descriptive measures and ordered logit modeling. Results showed that this study documented a statistically significant determinant of the feeling of happiness in teaching, namely: other sources of income, creative and enjoyable teaching experience, school compound, social relationship, and health condition. Having other sources of income has an inverse effect on the happiness of teachers, this might be due to additional responsibilities while serving the students. The study showed that teachers are more likely happy if they found their job as creative and enjoyable which positively influences their well-being and professional growth. There is also a higher chance of being happy if the school environment is conducive for learning and provides comfort to teachers. Furthermore, being socially oriented and the healthy teacher are productive and efficient in work which is more likely to be happy.

Students’ social origins, educational process and post-college outcomes: The case of an elite Chinese university

Scholars debate whether and how higher education and elite education experiences break or reinforce the link between social origins and status attainment in meritocratic societies. We contribute to these debates focusing on post-college outcomes of elite university students in contemporary China. Using a longitudinal survey of the 2014 freshmen cohort from an elite Chinese university and a sequential logit modeling technique, we find that meritocracy is seemingly at play between the trajectories of graduate study and employment. However, within each trajectory, students’ hukou (urban/rural registration status) and regional backgrounds significantly constrain their post-college options, partly through differential participation in high-impact educational practices. Furthermore, social origins leave marks on students’ motives for graduate study.