Multiple regression is a widely used technique for data analysis in social and behavioral research. The complexity of interpreting such results increases when correlated predictor variables are involved. Commonality analysis provides a method of determining the variance accounted for by respective predictor variables and is especially useful in the presence of correlated predictors. However, co...

The Commonality-Based Crossover Framework defines crossover as a two-step process: 1) preserve the maximal common schema of two parents, and 2) complete the solution with a construction heuristic. In these “heuristic” operators, the first step is a form of selection. This commonality-based form of selection has been isolated in GENIE. Using random parent selection and a non-elitist generational...

Software engineers today are often asked to do both rapid production and careful engineering at the same time. One way to help resolve the tension between these often conflicting goals is to develop families of software and to invest in facilities for rapidly producing family members. Success in such an endeavor requires that the software engineers be able to identify the desired family members...

This paper presents a template for the commonality analysis of a family of models of physical phenomena. The commonality analysis template includes documentation of the potential system context, the variabilities between models and the common aspects shared by all family members, including sections for terminology, goals, assumptions and theoretical models. The commonality analysis document als...

Firms often determine whether or not to make components common across products by focusing on the manufacturing and sales of new products only. However, component commonality decisions that ignore remanufacturing can adversely affect the profitability of the firm. In this paper, we analyze how remanufacturing could reverse the OEM’s commonality decision that is based on the manufacturing and sa...

Component commonality and postponement have been the focus of research for the last twenty years. Since then numerous models and theories have been developed, but industrial evidence is still rare. This work will make a contribution and show the positive benefits of postponement and component commonality in the automotive industry. The insights from literature and a case study are combined to e...

This article proposes a set of math-based approaches for making commonality and modularity decisions when designing product families. The performance of products that share some components is usually compromised relative to the individual optimum. This deviation occurs because of the commonality constraints that are included in the optimal design problem, especially when the objectives in the m...

The concepts of cross-theoretical and empirical integrations are taken into consideration at the methodological, theoretical, empirical, practical levels. Some conditions for integration theories highlighted analyzed. Among them differentiation, potential generalization, dynamic structures divergent functions, levels multidimensionality, mediation, relativity complementarity, integrative qualit...

In investigating the effects of algorithmic trading on stock market liquidity and commonality in liquidity in different market conditions in an electronic limit order market, we find algorithmic trading increases stock liquidity by narrowing quoted and effective bid–ask spreads. Furthermore, algorithmic trading decreases commonality in liquidity; this finding is robust across a variety of liqui...