This study examines the impact of agile practices on supply chain performance measurements in manufacturing firms. Following COVID-19, there have been operational and logistics disruptions in manufacturing firms and supply chains worldwide. We study the link between supply chain performance and...

We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense...

Background: Team viability, understood as the ability to adapt and collaborate effectively over time, is a key concept in organizational literature. In Peru, where changes are constant, culturally adapted tools are needed for its measurement. Objective: To translate and validate a team viability...

In this paper, we propose a component-based dynamic factor model for nowcasting GDP growth. We combine ideas from "bottom-up" approaches, which utilize the national income accounting identity through modelling and predicting sub-components of GDP, with a dynamic factor (DF) model, which is...

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel data. The model exploits both serial and cross-sectional information in the data and can easily cope with time-variation in conditional means and variances, as well as with either...

We propose a new rank-based test for the number of common primitive shocks, q, in large panel data. After estimating a VAR(1) model on r static factors extracted by principal component analysis, we estimate the number of common primitive shocks by testing the rank of the VAR residuals'...

Purpose - This paper aims to develop and validate a comprehensive scale for measuring consumer perceptions towards social commerce (S-Commerce). With the growing prominence of social media platforms in electronic commerce (e-commerce), understanding consumer perceptions and attitudes is...

The literature on financial openness is rich, yet the selection of a suitable financial index remains a challenge. In this paper, Principal Component Analysis (PCA) and Factor Analysis (FA) are utilized to reduce the dimensionality of five publicly available financial openness indices. The...

The United Nations established Sustainable Development Goals (SDGs) to address resource depletion, global warming, and other environmental issues caused by profit-driven economic activities. In line with the sustainability mission, this study examines the financial factors influencing the...

This study develops and validates an innovation management framework based on the integration of dynamic capabilities and multidimensional innovation process factors. A mixed-methods approach was employed, combining a quantitative survey of 267 respondents from the Porto Digital ecosystem with...

It is common to transform data to stationarity, such as by differencing and demeaning, before estimating factor models in macroeconomics. Imposing these transformations, however, limit opportunities to learn about trending behaviour. Trends and deterministic processes can play a central role in...

Factor modelling extracts common information from a high-dimensional data set into few common components, where the latent factors usually explain a large share of data variation. Exploratory factor estimation induces sparsity into the loading matrix to associate units or series with those...

Globally, countries are engaged in developing strategies and undertaking initiatives for green transitioning of the financial system and achieving net-zero targets by 2050. Green transitioning of the financial system includes boosting green finance (GF) and green investment (GI) in the country....

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...

This paper describes the Bundesbank's weekly financial stress indicator for Germany. The indicator condenses several financial market variables into a summary measure of financial stress. It represents a contemporaneous, market-based indicator that captures the materialisation of systemic risk...

This paper makes a twofold contribution. First, it develops the dynamic factor model of by allowing for fractional integration instead of imposing the classical dichotomy between I(0) stationary and I(1) non-stationary series. This more general setup provides valuable information on the degree...

This paper shows that the Expectation-Maximization (EM) algorithm for regime-switching dynamic factor models provides satisfactory performance relative to other estimation methods and delivers a good trade-off between accuracy and speed, which makes it especially useful for large dimensional...

The importance of energy-saving behaviour has become crucial due to recent negative events. The current empirical study investigates the factors that influence such behaviour. Hypotheses based on the revised theory of planned behaviour (Ajzen, 2020: 314f.) were formulated to examine the...

This paper introduces a novel dynamic factor model designed to capture common locally explosive episodes, also known as common bubbles, within large-dimensional, potentially non-stationary time series. The model leverages a lower-dimensional set of factors exhibiting locally explosive behavior...

Determining a plausible number of components in a factor model is a nontrivial issue in case of weak data, sparse model restrictions and diffuse prior information. We discuss the issue of structural parametric identification in a static factor model and introduce orthogonal restrictions which...

Traditional approaches based on intuitive decisions of executivies, teams, or individuals often prove inadequate in managing complex technology development processes. Theoretical models proposed for successful technology development processes emphasize the necessity of standardized processes....

We propose a high-frequency digital economy index by combining official white papers and big data. It aims to resolve the discrepancy between the new economic reality and old economic indicators used by decision-makers and policymakers. We have demonstrated a significant effect due to keyword...

The biopharmaceutical sector is of considerable interest during the COVID-19 pandemic. This study aims to investigate the biopharmaceutical sector using the Shenwan Industry Classification and provides insights into investment strategies. We combine factor and cluster analyses to reduce data...