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1 – 2 of 2Daniele Cerrato, Maurizio La Rocca and Todd Alessandri
The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy…
Abstract
Purpose
The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.
Design/methodology/approach
Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.
Findings
Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.
Practical implications
The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.
Originality/value
The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.
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Keywords
Abror Hoshimov, Anna Corinna Cagliano, Giulio Mangano, Maurizio Schenone and Sabrina Grimaldi
This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system…
Abstract
Purpose
This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.
Design/methodology/approach
A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.
Findings
The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.
Research limitations/implications
The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.
Originality/value
This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.
Details