Investigating Nearshoring Drivers and Impact on Shareholder Value: A Cross-Industry Study of Oslo Stock Exchange

Abstract

This thesis investigates what drives a company to nearshore, and whether such announcements are valued by shareholders. We examine producing firms on Oslo Stock Exchange from 2020 through 2023. We employed a logit regression and linear probability models to identify factors driving nearshoring decisions, examining freight rates, commodity prices from China and production cost while considering company size and industry. Additionally, we investigated the impact of nearshoring announcements on stock returns through an event study and assessed how company size and industry influence these returns. We further enriched our analysis by investigating two companies through case studies.

Our first research question examines which factors drives nearshoring decisions. Through our analyses, we found conflicting results. While only production cost appeared to influence nearshoring decision from the logit regression, the linear probability model provided results significantly different from zero for freight rates and commodity prices from China. The deviating results can be caused by the linear probability model controlling for fixed effects. Though experiencing conflicting results from our models, the relevance of these three factors were highlighted in our case studies, as they all appeared critical for nearshoring decisions for these companies. The second research question investigates whether shareholders value nearshoring announcements. Our results provided evidence that shareholders value the announcements, through a cumulative abnormal return of 7,48 percent with an event window including the announcement date, the day prior and the day after the announcement. Research question three examines whether size matters for nearshoring decision and the following returns. We found that smaller firms are more likely to nearshore and experience greater abnormal returns. The fourth research question aims to study whether industry matters for nearshoring decision and the following returns, which provided conflicting results. The linear probability model exhibited results significantly different from zero for industrials, technology and consumer discretionary. This is in contrast to the insignificant results provided from the logit model. Furthermore, there appeared to be little difference in abnormal returns between the industries.

This thesis investigates what drives a company to nearshore, and whether such announcements are valued by shareholders. We examine producing firms on Oslo Stock Exchange from 2020 through 2023. We employed a logit regression and linear probability models to identify factors driving nearshoring decisions, examining freight rates, commodity prices from China and production cost while considering company size and industry. Additionally, we investigated the impact of nearshoring announcements on stock returns through an event study and assessed how company size and industry influence these returns. We further enriched our analysis by investigating two companies through case studies.

Our first research question examines which factors drives nearshoring decisions. Through our analyses, we found conflicting results. While only production cost appeared to influence nearshoring decision from the logit regression, the linear probability model provided results significantly different from zero for freight rates and commodity prices from China. The deviating results can be caused by the linear probability model controlling for fixed effects. Though experiencing conflicting results from our models, the relevance of these three factors were highlighted in our case studies, as they all appeared critical for nearshoring decisions for these companies. The second research question investigates whether shareholders value nearshoring announcements. Our results provided evidence that shareholders value the announcements, through a cumulative abnormal return of 7,48 percent with an event window including the announcement date, the day prior and the day after the announcement. Research question three examines whether size matters for nearshoring decision and the following returns. We found that smaller firms are more likely to nearshore and experience greater abnormal returns. The fourth research question aims to study whether industry matters for nearshoring decision and the following returns, which provided conflicting results. The linear probability model exhibited results significantly different from zero for industrials, technology and consumer discretionary. This is in contrast to the insignificant results provided from the logit model. Furthermore, there appeared to be little difference in abnormal returns between the industries.