相关论文: Total Factor Productivity and its determinants: an…
Industries learn productivity improvements from their suppliers. The observed empirical importance of these interactions, often omitted by input-output models, mandates larger attention. This article embeds interdependent total factor…
Measured aggregate productivity and the income share of top earners are strongly and positively correlated in the Canadian data. Productivity slowdown since the early 2000s was accompanied with a flattening income share of top earners.…
Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and…
Predicting high-growth firms has attracted increasing interest from the technological forecasting and machine learning communities. Most existing studies primarily utilize financial data for these predictions. However, research suggests…
In this paper, we focus on exploiting the group structure for large-dimensional factor models, which captures the homogeneous effects of common factors on individuals within the same group. In view of the fact that datasets in…
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This paper extends Gandhi et al.'s (2020) proxy variable framework for structurally identifying production functions to a more general case when…
Managing software development productivity and effort are key issues in software organizations. Identifying the most relevant factors influencing project performance is essential for implementing business strategies by selecting and…
As the digital economy grows increasingly intangible, traditional productivity measures struggle to capture the true economic impact of artificial intelligence (AI). AI systems capable of cognitive work significantly enhance productivity,…
Most of the manufacturing firm aims to optimize their Supply Chain in terms of improved profitability of its products through value Addition. This study takes a critical look into the factors that affect the Performance of internal supply…
Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of…
This paper studies inter-firm heterogeneity in production. Unlike much of the existing research, which primarily addresses heterogeneous production through unobserved fixed effects, our approach also focuses on differences in factors'…
Drawing upon Resource-Based Theory (RBT) and the Knowledge-Based View (KBV), this study investigates the impact of Knowledge-Based Organizational Support (KOS), AI-Driven Knowledge Sharing (KS), Organizational Learning (OL), and Knowledge…
The relatedness between a country or a firm and a product is a measure of the feasibility of that economic activity. As such, it is a driver for investments at a private and institutional level. Traditionally, relatedness is measured using…
This study examines the influence of employee education and health on firm-level Total Factor Productivity (TFP) in China, using panel data from A-share listed companies spanning from 2007 to 2022. The analysis shows that life expectancy…
Tis paper is a literature review focusing on human capital, skills of employees, demographic change, management, training and their impact on productivity growth. Intrafirm behaviour has been recognized as a potentially important driver for…
This work provides an in-depth analysis of the relation between the different types of collaboration and research productivity, showing how both are influenced by some personal and organizational variables. By applying different…
Firms' positions in innovation networks determine their access to external knowledge, yet how these positions shape technological search behavior and influence productivity remains underexplored. We propose that central network positions…
Recent crises like the COVID-19 pandemic and geopolitical tensions have exposed vulnerabilities and caused disruptions of supply chains, leading to product shortages, increased costs, and economic instability. This has prompted increasing…
The design of data-driven formulations for machine learning and decision-making with good out-of-sample performance is a key challenge. The observation that good in-sample performance does not guarantee good out-of-sample performance is…
We introduce heterogeneous R&D productivities into an endogenous R&D network formation model, generalizing the framework of Goyal and Moraga-Gonz\'alez (2001). Heterogeneous productivities endogenously create asymmetric gains from…