Principal component analysis is a versatile statistical method for reducing a cases-by-
variables data table to its essential features, called principal components. Principal …

The new business challenges in the B2B sector are determined by connected ecosystems,
where data-driven decision making is crucial for successful strategies. At the same time, the …

Nature contributes substantially to human well-being through its diverse material and
nonmaterial contributions. However, despite the growing literature on the nonmaterial …

This study examines the effect of financial inclusion on poverty and vulnerability to poverty of
Ghanaian households. Using data extracted from the seventh round of the Ghana Living …

Data clustering is a commonly used data processing technique in many fields, which divides
objects into different clusters in terms of some similarity measure between data points …

This article traces a methodological path for constructing a statistically and normatively
validated assets indicator, that in turn can be used within an internationally comparable …

Technology alone will not achieve building energy conservation goals, and humans and
their energy-related behavior in buildings must be included in energy performance efforts …

Dimensionality reduction (DR) is frequently applied during the analysis of high-dimensional
data. Both a means of denoising and simplification, it can be beneficial for the majority of …

As world is affected by demand volatility; process uncertainty; supply chain complexity and
information ambiguity forming a VUCA world. To manage this scenario, industries are …

The development of the Internet and the implementation of traditional marketing strategies
have given rise to the emergence of digital marketing strategies exploited both by SMEs and …