The relationship between back-shoring and firms’ performance : the moderating effect of high-technology sector

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Master Thesis

The relationship between back-shoring and

firms’ performance: The moderating effect

of high-technology sector.

Georgios Gkanas - 11374063 Semester 2, 2016/2017 19 of June 2017, Final Version

MSc Business Administration: International Management Supervisor: Dr. N. Pisani

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Statement of originality

This document is written by the Student Georgios Gkanas who declares to take full responsibility for the content of this document.

I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in order to create it.

The Faculty of Economics and Business is responsible solely for the supervision concerning the completion of the work, and not for the content.

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Abstract

Back-shoring, is considered to be a topic of high interest nowadays. However, extant research does not address a relationship between back-shoring and firms’ performance. Many firms such as General Electric, Caterpillar and Ford Motor Company due to knowledge spillovers that experienced in the emerging markets or due to other unfavorable factors (e.g. labor costs, taxation, coordination costs) they have brought back to western countries part of their manufacturing and services. We aim to give more insights concerning the outcome of back-shoring strategies. In our study we investigate whether re-back-shoring of activities enhances firms’ performance. Additionally, we theorize a positive moderation effect on the above mentioned relationship when firms operate in the high-technology sector. Concerning the empirical analysis Orbis database was used; a database which publishes data for many companies around the world each year. We framed our dataset to the fortune global 500 (FG 500) firms. However, our results show that both of our hypotheses are not supported. Back-shoring has not a significant impact on firms’ performance as well as the moderation effect on the former relationship. Moreover, we make several suggestions concerning our research design, which we believe that will help future research to come to more conclusive results. Due to the economic instability, back-shoring is a phenomenon that will attract more attention the following years. Studies, which will shed light on this topic, will give useful insights to managers concerning back-shoring strategies.

Keywords: Back-shoring · Re-shoring · Spillovers · Firms’ performance · Offshoring · Offshore outsourcing

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1. Introduction

The globalization process has played an important role in the shaping of firms. Firms used to face trade, tariff and capital barriers. These types of barriers were responsible for the limited connectedness among countries. Consequently these barriers also affected the intensity of foreign direct investments (FDI), into offshore or nearshore destinations at that time. After the reduction of these types of barriers and after privatization and deregulation policies were introduced, it is more efficient for firms to be expanded internationally in terms of sales or even to be relocated in foreign markets due to available talent pool, lower taxes and wages in the offshore locations (Scherer & Palazzo, 2011; Manning et al. 2010). Firms which once were regional leaders have turned into large multinational enterprises (MNEs), due to the lowering of the barriers mentioned above and due to technological advancements, which allow them to create more complex corporation formats (Scherer & Palazzo, 2011). The location choice has been based on several frameworks (Barney 1991; Peteraf & Barney 1993; Dunning 2000) in order for the managers to select the ideal offshore location and establish their firms’ services according to the resources and the capabilities they seek from a market. Furthermore, MNEs seek to exploit their unique resources when entering a market, while they wish to access the local knowledge in order to create new capabilities, which they will use in order to be adjusted in the new market and then internalize them within the MNE network and create new capabilities for the whole corporation (Rugman & Verbeke 2004; Rugman 2011).

After the liberalization of markets, offshoring concerning manufacturing and services became a common strategy for big corporations in order to become more efficient and remain competitive in the global market. The business process offshoring, in other words the relocation of parts of a firm’s value chain into countries where it is more efficient compared

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to the home country (Pisani & Ricart 2016) is a strategy many firms followed the previous years and some of them are still following in order to enhance their competitiveness due to lower taxes and wages in the host country (Demirbag & Glaister 2010). Apart from cost reduction drivers, firms also offshore their operations due to natural resource seeking, market and knowledge seeking as well as a reaction to competitive pressures. The last driver refers to the fact that MNEs, in order to remain competitive, usually follow their rivals, to learn from them and develop new capabilities so as to retain their market share and power (Dossani & Kenney 2007; GAO et al. 2010; Javalgi et al. 2009; Manning et al. 2010). However, there is an opposition between authors concerning the operations a firm should offshore. While some (Murray & Kotabe 1999) believe that MNEs should relocate activities such as manufacturing, logistics, and customer service, others (Mudambi & Venzin 2010; Nieto & Rodriguez, 2011) state that firms should also relocate knowledge-intensive activities in order to enhance their limited in-house innovation, by entering into countries with skilled labor and competitive wages either through captive or non-captive modes and tap into new sources of knowledge.

However, many firms are now considering of bringing back home activities once performed in offshore locations. Corporations such as Apple, Caterpillar, Google and Ford Motor are thinking of re-shoring services or part of their manufacturing back home (Albertoni et al. 2017; Booth, 2013). More specifically in terms of services many companies have faced multiple problems by having, for example, their call centers in countries such as India. The accent of the Indian employees has caused serious problems to well-known companies and their customer service has been considered of low quality because many customers refuse to speak to non-native English speakers. On the other hand, when it comes to manufacturing firms have found that cheap manufacturing is being offset by the higher coordination costs, due to the fact that many firms have their research and development (R&D) centers in their home countries, whilst manufacturing is being performed in offshore

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locations (Booth, 2013). Additionally, many firms now perceive offshore locations as less efficient, due to the fact that they experience negative spillovers. According to Mariotti et al. (2010), when firms perceive knowledge leakages as more than the knowledge acquired in a specific location, they will disinvest from the specific country. Hence, back-shoring is a strategy many firms now consider, given the knowledge leakages that they experience in the offshore locations.

Our paper contributes to the literature by exploring the back-shoring phenomenon, which has been overlooked by academics, and its outcome on firms’ performance. The existing literature sheds light on the back-shoring phenomenon in general. In other words, findings show that MNEs are implementing such strategies in order to cope with several drawbacks. Such drawbacks accrue through negative spillovers and the difficulties in coordination of activities across the world. However, little is known about the impact of back-shoring strategies on firms’ performance. We try to give more insights concerning firms’ performance, after the implementation of back-shoring strategies.

MNEs are now considering re-shoring their activities back to their home countries due to costs that have not been identified (such as coordination costs and knowledge leakages) and due to the emergence of local firms in the offshore locations, which pose competitive pressures to MNEs. Furthermore, emerging countries such as China, which is a popular offshore location, seem not to be a favorable location anymore due to the rising of the benefits of the workforce, which in turn makes MNEs neutral between staying home and going abroad (Booth 2013). Secondly, the emergence of local firms affects Western firms’ performance in a sense that knowledge spillovers enhance the competitiveness of the former. Back-shoring is a strategy by which MNEs seek to restore their competitiveness by providing products of higher quality, in countries more proximate to the final consumer (Booth 2013).

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We seek to provide empirical evidence about firms’ performance after back-shoring their activities back to their home countries. Having in our mind that re-shoring is a phenomenon which is taking place over the last years, providing data about its results to firms’ performance will be very interesting and informative for firms which are considering back-shoring as a strategy to restore their competitiveness and improve their performance. Moreover, we are to investigate whether the performance of firms, which operate in the high-technology sector, will be positively moderated. In other words, we will test if knowledge-intensive firms work as a moderator concerning back-shoring and firms’ performance. In order to do so, we will gather data both for firms’ performance and affiliates in offshore locations and we will investigate if there is a trade-off between these two variables.

The paper is organized as follows. First, we elaborate on the existing literature about internationalization, offshoring, hidden costs-spillovers, and back-shoring, in order to give a clear view to the reader about these topics. Then we continue with our theoretical framework and state our hypotheses, and then the methodology chapter follows in which we explain how we conducted our data research and which methods we use in order to conclude to our results, which is the following chapter. The discussion & conclusion chapter follow the result chapter.

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2. Literature Review

2.1 Internationalization

Many scholars over the years have tried to tackle the field of firms’ internationalization. Over the years there were different approaches based on the level of analysis, from country level to MNE level and to subsidiary level of analysis (Rugman et al. 2011). In the pre-Hymer (1960) era, the focus was on countries’ specific advantages, while in 1970s the focus shifted to MNEs expansion and the transfer of their firm-specific advantages (FSAs) to the foreign locations. Such advantages are knowledge, brand name and financial power, which can create competitive advantages for firms when are being exploited in new markets. Later the focus shifted to the subsidiaries level and how the latter can generate knowledge, which can then be internalized in the MNE network and create new FSAs also for the whole corporation (Rugman et al. 2011).

Vernon (1966) with product lifecycle framework, argues that firms internationalize in order to exploit home country’s specific advantages (CSAs). Hence, MNEs expand into foreign regions and establish subsidiaries taking advantage of in-house knowledge. On the other hand, Hymer (1960), with his focus on MNEs and FSAs, explains that firms need to possess the latter in order to offset costs that will face due to the lack of knowledge when entering a new market. Moreover, the author states that except FSAs another condition should be met in order for FDI to take place. That condition is the imperfect final markets, which means that a firm can enjoy monopolistic advantages and create entry barriers for its competitors. While Hymer (1960) claimed that final markets should be imperfect, Coase (1937) based his theory on the imperfections in intermediate markets. Due to imperfections in the intermediate markets such as search and information costs, bargaining costs and incomplete contracts, firms often find it inefficient to have some of their activities being

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carried out by third parties. Internalization theory (Coase, 1937) explains that an MNE can expand vertically in order to coordinate activities which would not have taken place due to high transaction costs. However, according to Buckley & Casson (2009), firms internationalize and expand until the benefits of internalization are equal to the costs. Further, firms seek to find new locations, in order to minimize their costs and achieve higher levels of innovation in order to enhance their profitability and sustain their growth level.

Concerning innovation and location choice, Dunning (2000) with the eclectic paradigm also makes a substantial contribution to the business literature. The OLI paradigm, which breaks into ownership (O), location (L) and internalization (I) explains the motives of MNEs to expand in different regions (Dunning 2000). O stands for the advantages which derive from the ownership of specific resources or services. Such advantages are the trademark, production technique, and entrepreneurial skills. L is about advantages which stem from location and can be natural resources, low taxes, and wages. Finally, I, which concerns internalization, discusses advantages stemming from internalizing activities, such as own production within the MNE network (Dunning 2000). Drawing on the motives of firms to expand we can distinguish between the traditional investment motives where firms expand due to market seeking, as well as efficiency and resource seeking and the modern investment motives which concern all three mentioned plus strategic asset seeking motive (Dunning 1998). Strategic asset seeking refers to R&D, catch-up (either technologically or efficiency) and diversification. Dunning (1998) in addition to Buckley & Casson (2009), observes as reinforcing factor for firms’ expansion the renaissance of the market economy and technological changes. Furthermore, Dunning (1998) observes the emergence of intellectual capital as the key for wealth creation, the integration of economic activity and the increasing emphasis on “alliance” capitalism.

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Additionally to what have already been mentioned, there is also another approach which sheds light on the expansion of firms. The Resource Based View (RBV) (Barney 1991; Peteraf & Barney 2003) analyzes the reasons why firms decide to expand into new regions. Barney (1991), states that firms, in order to outperform their competitors, should have sustainable competitive advantages. A firm is said to have a competitive advantage when the value-creating strategy that the firm in question implements is not being implemented by other competitors at the same time, whereas a firm is said to have a sustainable competitive advantage when the value-creating strategy not only is not being implemented by competitors but also competitors are unable to duplicate the benefits of this strategy (Barney 1991). A sustainable competitive advantage derives from resources which are valuable, rare, inimitable and non-substitutable (VRIN) (Barney 1991). Later Barney & Peteraf (2003) introduced valuable, rare, inimitable, organization (VRIO) instead of VRIN. On this topic, Barney (1991) states that when resource homogeneity exists, then firms will implement the same strategies and will have the same levels of efficiency, hence no firm enjoys a sustainable competitive advantage in this case. A way for a firm to own unique resources is to be the first mover in a country or in an industry (Lieberman &Montgomery 1988). In other words, firms seek to create such an environment where they can enjoy unique resources which will lead them to a sustainable competitive advantage.

Rugman et al. (2011), give more insights in what firms seek when going abroad. Firms try both to exploit their FSAs in the host country and create new FSAs in the country in question, and then try to internalize them in the MNE network if possible. Moreover, they also desire to explore and finally exploit host countries’ CSAs (Rugman et al. 2011). As far as the FSAs are concerned they can be categorized into two distinct categories. The first category is the non-location bound FSAs (NLB FSAs), whereas the other is the location bound FSAs (LB FSAs). The former category describes FSAs such as R&D, managerial

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capabilities and access to capital, while the latter includes attributes such as local knowledge and brand name (Rugman et al. 2011). In other words, NLB FSAs are those FSAs which can be transferred either in the host or the home country at a very low cost; while LB FSAs either cannot be transferred at all (in the host or the home country) or they can, but the costs of doing so are very high (Rugman & Verbeke 2004). Concerning CSAs, MNEs seek to exploit them when entering a foreign market in order to create FSAs not only for the subsidiary in the specific location but also for the rest of the MNE network (Rugman & Verbeke 2004). Having all that in mind it can be inferred that firms have been searching for opportunities across the world and ways to expand. Offshoring is the mean for firms to do so.

2.2 Offshoring

Offshoring of services (OS) refers to the relocation of parts of the value chain from the home country to offshore locations, in order for the firms to achieve higher levels of efficiency (Pisani & Ricart 2016). OS has been a common strategy for many firms over the years and is considered by many published studies as a new type of internationalization (Javalgi et al. 2009; Lewin et al. 2009; Lewin & Peeters 2006; Nieto & Rodriguez 2011), which has substantial consequences in terms of individual, firm and country level (Bunyaratavej et al. 2008; Contractor et al. 2010; Kumar et al. 2009; Liesch et al. 2012; Manning et al. 2010). However, offshoring of services can take different forms. Hence, a firm can either establish an affiliate in a foreign country, captive offshoring or outsource the activity to a third-party provider abroad, offshore outsourcing. Additionally, if need be an MNE might prefer to enter a joint venture when going abroad. Depending on the nature and the peculiarities of the activities an MNE wants to offshore it will choose the optimal way to offshore its activities. According to Luo et al. (2013), a firm will choose a captive mode when information security is important, while a joint venture will be preferred when the knowledge specialization is

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higher. Finally if the activity can be easily codified then an independent vendor will be preferred.

Initially, firms entered into OS ventures through contractual agreements with host countries’ providers; while more recently complex OS relocations have been introduced (Lewin et al. 2009; Nieto & Rodriguez 2011). As mentioned in the previous section, the OLI paradigm (Dunning 2000) has largely been used to explain location choice. Similarly, it has also been used to address the choice of OS location (Bunyaratavej et al. 2008; Demirbag & Glaister 2010; Graf & Mudambi 2005; Kedia & Mukherjee 2009). Accordingly, the RBV (Barney 1991) has been used in the OS literature since 2007 as a suitable theoretical approach for identifying the resources and capabilities needed by firms in order to succeed in more complex OS implementations (Bunyaratavej et al. 2011; Javalgi et al. 2009). Findings from Nachum & Zaheer (2005) confirm that the drivers behind OS-related implementations are the same with the drivers of FDI. Efficiency-seeking represents the strongest driver, while market and resource seeking motivations are more relevant to industries that are not information-intensive (Pisani & Ricart 2016). Other drivers for firms to relocate abroad are R&D wage differences, as well as differences between home and host country and political risk level of the host country (Demirbag & Glaister 2010). Concerning these differences, firms expand into offshore locations in order to tap into natural resources, scarce in the home country, or to take advantage of the talent pools in the emerging countries, which can provide an MNE with highly-skilled labor force with substantially lower costs (Pisani & Ricart, 2016).

For knowledge-intensive services Lewin et al. (2009) identify the shortage of local talent as the driving force for firms to relocate their services abroad, while other studies suggest that this phenomenon is due to the emergence of global workforce and the changing dynamics affecting the supply and demand for high-skilled workforce around the globe (Demirbag & Glaister 2010; Levy 2005). This shift in the high-skilled workforce took place

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due to the fact that in Western Europe and the United States there was a steady decline in the annual number of graduates in science, technology, engineering, and mathematics, while in Asia, Latin America and Eastern Europe a larger pool of technical talent has been created. Consequently, highly-qualified personnel in offshore locations led to the growth of the OS phenomenon (Bunyaratavej et al. 2007; Doh 2005; Manning et al., 2008). Additionally to what has already been said, firms relocate to offshore locations for cost reduction purposes and because firms tend to follow their competitors in order to keep pace with them and seek to learn from their actions. All these drivers have contributed to the emergence of OS in specific offshore locations (Dossani & Kenney 2007; GAO et al. 2010; Javalgi et al. 2009; Manning et al. 2010).

However, there is a controversy when it comes to which services firms should relocate to offshore locations. While Murray & Kotabe (1999) state that firms will relocate only their supplementary services abroad and not the high-level professional activities, Mudambi & Venzin (2010) conclude that OS phenomenon involves also knowledge-intensive processes. The research of Manning et al. (2008, 2010 & 2011) also supports the offshoring of knowledge-intensive services to offshore locations. More specifically Manning et al. (2010), explain the offshoring of R&D services by introducing the clusters and how they develop. A cluster, in general, is a collection of similar firms which operate in really proximate locations, as for example the fashion firms in Italy or the car manufacturing in Germany. The author identifies both local and global drivers for MNEs to relocate their R&D services. Local drivers are the availability of skilled labor, government incentives, institutions, development of local service capabilities and growth of focal knowledge services. While global drivers are the competition for talent, wage inflation, the growth of competing clusters expansion of international service providers and location choice of global clients. This phenomenon, of offshoring knowledge-intensive activities, can be explained by

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the fact that MNEs do not only seek to use foreign R&D in order to be adapted to the local needs, but also to acquire knowledge through technological spillovers in the host country and then internalize it (Feinberg & Gupta 2004; Florida 1997; Von Zedtwitz & Gassmann 2002). In other words, FDI in R&D will increase a firm’s knowledge base by tapping into advantageous local resources (Le Bass & Sierra 2002). Another contribution to the topic of knowledge-intensive activities has been done by Nieto & Rodriguez (2011). The authors find that offshoring of R&D due to limited in-house innovation enhances firms’ performance. However, they also distinguish between captive offshoring and offshore outsourcing, stating that the former stands for product innovation, whereas the latter stands for process innovation. Moreover, they find that captive offshoring and product innovation have a greater impact on firms’ performance than offshore outsourcing and process innovation, due to the higher levels of complexity and difficulties in coordination for the latter.

Moving on to the literature about offshoring, Mihalache et al. (2012) state that offshoring has an inverted U-shaped influence on firm innovativeness. Moreover, the study in question considers top management teams (ΤΜΤ) as a moderating factor in a sense that the higher the information diversity between the TMT in the home and host country, the stepper the U-shaped relationship and vice versa. This area is attracting particular interest because knowledge-based activities are of increasing importance for firms (Ellram, Tate & Billington 2008; Kenney et al. 2009; Stringfellow et al. 2008; Westner & Strahringer 2010; Youngdahl & Ramaswamy 2008). Findings of R&D facilities relocation are supported by the fact that the share of USA, concerning R&D sites located in the country, declined from 59 percent to 52 percent while the share of China and India increased from 8 percent to 18 percent (Atkinson 2007). However, except positive outcomes for firms, OS also has negative effects that MNEs experience when going abroad.

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2.3 Hidden Costs & Spillovers

Jensen (2009) explains that relocation of services leads to a strategic transformation for an MNE, both in the home and host country. Moreover, other findings indicate that while OS implementation enhances several factors, such as trust building and partnership commitment, it decreases others, such as firms’ performance (Jensen 2012). OS is a process in which not all firms succeed (Peeters et al. 2014). Furthermore, besides the advantages of offshoring, there are also some possible disadvantages firms might encounter. Hidden costs, time compression diseconomies, the liability of regional foreignness (LORF) and spillovers are some of the most important reasons why firms face substantial problems when going abroad. Some examples of hidden costs are the coordination costs, the costs of transferring knowledge in the offshore locations and any other unanticipated costs when expanding abroad. A way firms can overcome such problems is through top management and employee commitment to the given projects and through trust, transparency, and understanding of the cultural differences (Soderberg et al. 2013). As for time compression diseconomies costs, are all these costs related to efforts of late-comers to shorten the time needed to catch-up with the established players in a market, in terms of knowledge and resources. Examples of LORF are the lack of knowledge MNEs have when entering an offshore location comparing to the local players and the changes that they should implement concerning their product mix, due to differences between the home and the host countries (e.g. cultural, taste). Finally, when employees of a given company move to other competitors’ companies or when MNEs engage in joint ventures with local players, then knowledge and firm’s capabilities might be transferred or revealed to rivals, causing what is called negative spillovers.

Furthermore, as far as the hidden costs are concerned, firms might fail to estimate them accurately when investing abroad, hence this might generate substantial costs for the firms (Larsen et al. 2013). Today firms offshore more and more complex projects abroad and

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many of them have begun to realize that coordinating such complex activities is more difficult and costly than initially expected (Dibbern et al. 2008; Stringfellow et al. 2008). The failure concerning the assessment of the hidden costs results in a disability for decision makers to estimate the impact of strategic decisions (Larsen et al. 2013). The higher the complexity of an offshore operation, the more difficult the estimation of total costs will be and the more the decision-making process will be affected (Larsen et al. 2013).

Another obstacle firms should have to overcome when expanding abroad is the LORF (Kim & Aguilera 2015). LORF stands for the extra costs, which firms face when doing business in a foreign region (Asmussen 2009; Asmussen & Goerzen 2013). In order to overcome the LORF, firms have to modify their capabilities according to the demands of the local market (Anand & Delios 1997; Zaheer 1995). In addition to the extra costs firms face when going abroad, they are also subjected to time compression diseconomies. MNEs face such costs when they have to take actions in the short run (Rugman & Verbeke 2004). So whereas on the one hand there are cost advantages, strategic flexibility, access to knowledge/skills and human resources, on the other hand there are also disadvantages for firms offshoring activities (e.g. erosion of a firm’s resources, relational problems between partnering firms, coordination costs related to organizational design and task interface) (Jensen 2012).

Furthermore, firms have to encounter possible spillovers in the offshore environment, which is considered as a negative effect of offshoring. According to Mariotti et al. (2010), managers tend to avoid being in locations where competitors have been established if they perceive that the environmental externalities will be negative for their firm and the knowledge spillovers will be greater from the firm to the location than from the location to the firm. In other words, knowledge spillovers are not unidirectional, as there might be either inflow or outflows of knowledge. An MNE considers knowledge inflows as positive, while

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any unintentional knowledge leakages of its intellectual capital are perceived as negative (Mariotti et al. 2010). Over the last decades, western firms expanded their activities mostly in emerging countries, such as China (Dossani & Kenney 2007). This made it possible for domestic firms to take advantage of the collaborations with MNEs and this was facilitated by the spillovers outflows of the latter (Luo & Tung, 2007). MNEs, in order to overcome such a problem, should change their strategic planning and come up with a solution so as to become again more competitive compared to firms from emerging countries.

2.4 Back-shoring

Back-shoring or re-shoring of services is a topic that has been overlooked in the OS literature. Firms which once chose to offshore specific activities abroad can decide to “reshore” them back in their home countries (Pisani & Ricart 2016). According to Mihalache et al. (2012), offshoring of primary functions has limitations and beyond a threshold benefits from offshoring may diminish. Thus, firms will consider re-shoring activities and services back to their home countries. However, back-shoring decisions have several explanations.

Such decisions may be triggered due to different reasons such as having a performance lower than the expected one in the offshore environment, political pressures (from the home or the host country) or overly complex coordination. Some of the biggest corporations around the globe (e.g. Google, General Electric, Caterpillar and Ford Motor Company) are now bringing back some of their production capacity or adding some production capacity at home (Booth 2013; Albertoni et al. 2017). More specifically, MNEs are now considering of re-shoring or near-shoring their activities. In other words, firms are thinking of relocating part of their value chain either in home or in proximate to their home base countries. MNEs consider this, in order to take advantage of benefits such as fast response, in terms of customer service and delivery; since efficiency advantages (e.g. low

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wages) in offshore locations are eroding over time, making offshoring in emerging countries inefficient (Ellram et al. 2013). Other findings also indicate that for a firm having R&D at home and other services in offshore locations may hinder its process of innovation and decrease the quality of its products, whereas if a firm moves the R&D department also in the offshore location, this may result in issues concerning theft of intellectual property (Booth 2013). These result in firms changing their strategic model of manufacturing in low-cost countries and then supply the rest of the world.

Further to these findings, Booth (2013) finds that the total costs of production in America are just ten percent higher than the costs of production in China. The same author also reveals that there was a rise in benefits for the average Chinese factory worker by ten percent a year from 2000 to 2005 and this rise speeded up the following years to nineteen percent a year. In other words, comparative advantages of low-cost countries, such as low wages, are now eroding and firms are now reconsidering the benefits and the costs of being in an offshore location (Fratocchi et al. 2014; Kinkel & Zanker, 2013; Albertoni et al. 2017). Hence, back-shoring of production and service activities may be due to the persistence of firms to continue operating having the same offshoring strategy. In other words, since there are no further opportunities for improvement in a specific location the company might decide to back-shore its activities (Albertoni et al. 2017). Other problems firms now face in countries such as China are the lack of high-quality workforce and the disloyalty of the personnel, since they may decide to leave the company for a salary five percent higher (Booth 2013). Additional reasons why firms decide to backshore their activities are the firms’ failure of international management due to lack of knowledge and planning of the foreign market (Anderson et al. 1998; Truijens 1992; Albertoni et al. 2017). Other authors (Hutzschenreuter et al. 2007; Manning et al. 2008) suggest that this particular phenomenon might take place due to external shocks of the economy (e.g. economic crisis), which affect FDI and relocation

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strategies. At the same time labor in Western countries is becoming more flexible, while workers in Asia are acquiring more rights as mentioned before (Booth 2013).

A different perspective on the back-shoring phenomenon is that Western firms expect that they will restore their industrial competitiveness they will also lower their total operational costs, based on the assumption that cost advantages in countries such as China will be gradually eroded by wage increases (Kinkel 2014). Transaction cost theory (Williamson 1985) also supports this view, since long physical and cultural distance between countries makes monitoring and supply chain coordination activities more costly.

Moreover, Western firms are not the only ones that they relocate their activities in European countries or in the United States. MNEs from emerging markets are moving production activities also in Western countries. Lenovo and the Tata Group, which is manufacturing Range Rover cars near Liverpool, are investing in production capacity also in countries of the developed world.

Although the importance of back-shoring, Kinkel (2011) states that reliable data to measure this phenomenon does not exist. Other studies (Booth, 2013; Fratocchi et al. 2014; Ellram et al. 2013) identify the drivers of back-shoring, such as increasing labor costs in the offshore locations, negative spillovers and increasing coordination costs, due to the complexity of these projects. They also find that the performance of firms which have offshored their activities have been affected in a negative way due to lower levels of efficiency. However, what these and other studies miss to address is the relationship between firms’ performance and back-shoring. In other words, MNEs back-shoring of activities has yet to be measured in terms of firms’ performance. Based on the existing literature we identify that there is a gap concerning the back-shoring phenomenon and its outcome for firms which have followed this strategy in the previous years. We believe that more research

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is needed on this topic in order to provide empirical evidence about the performance of firms which have “reshored” their activities back to their home countries. This is so because existing literature is more theoretical and does not provide concrete data about this phenomenon. This paper examines whether back-shoring affects firms’ performance in a positive way and tests if the performance of firms, which operate in the high-technology sector, will be positively moderated when re-shoring their services and activities back to their home countries. In other words, we seek to investigate whether knowledge-intensive activities work as a moderator to the prior relationship. Given that back-shoring is a trend many firms now follow; this paper will help us to advance our understanding on this topic by measuring the results of this strategy. We will measure the results of such a strategy by the difference in firms’ performance compared tothe number of their affiliates into foreign locations. In other words, we will investigate if MNEs with less foreign affiliates experience higher levels of performance.

3. Theoretical Framework

3.1 Back-shoring and firms’ performance

The hyper-competitive global markets dictate that firms have to relentlessly innovate and seek for higher levels of efficiency in order to survive (Nieto & Rodriguez, 2011). Favorable taxation, lower wages, and competitive pressures were and still are only some of the drivers, forcing firms to implement offshoring strategies (Scherer & Palazzo, 2011; Manning et al. 2010). Additionally, natural resources or skilled labor which both might be in shortage in the home country define MNEs decisions; in order for the latter to expand into other foreign locations (Pisani & Ricart, 2016).

For many years, Western firms were offshoring manufacturing and other types of activities to China, India and other emerging markets. They were doing so, in order to take

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advantage of the low operational costs and the governmental incentives in these countries (Dossani & Kenney, 2007; Manning et al. 2010). However, these benefits are now eroding, making these locations less favorable for firms to offshore their operations. Wages in China are rising and employees in emerging countries are acquiring more and more benefits. Moreover, transportation costs are also higher comparing to previous years, since petrol price is also on the rise. Consequently, these costs will affect firms’ performance when the latter operate in such markets. Furthermore, firms in offshore locations experience negative spillovers, since local firms acquire their knowledge either by engaging in joint ventures with them or by hiring employees which were previously working for the former (Booth, 2013).

Mariotti et al. (2010), state that when managers realize the negative spillovers in a location, they will try to disinvest as the offshore destination will not be considered as favorable anymore. Disinvestment relates to back-shoring, which means that firms which will decide to follow such a strategy will bring operations such as manufacturing, R&D, logistics and customer service back to their home country. By implementing such strategies they will try to increase their levels of performance. Moreover, by bringing back home activities such as manufacturing and R&D, Western firms will decrease their coordination costs and they will restore their competitiveness in terms of high-quality products; a factor which affects buying preferences (Booth, 2013). In other words, on the one hand, MNEs will decrease coordination costs and costs which accrue due to distance (e.g. cultural), by re-shoring their manufacturing, R&D and other type of activities and on the other hand they will boost their performance in terms of sales by producing products of higher quality than before. Additionally, being closer to the final consumers is more efficient since MNEs will be able to respond faster and to be more flexible in terms of customer service.

Having explained the drivers of firms’ internationalization and having highlighted that firms seek higher levels of efficiency is easy to understand that if costs are more than the

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benefits firms will rethink of their internationalization strategy, concerning their operations in foreign countries. Booth (2013) finds that production in China is not as favorable as in the previous years, since wages have increased and employees are acquiring more and more benefits and rights from their government. Due to these rising costs in the offshore locations, firms are experiencing lower levels of performance; thus moving out from countries such as China to countries where they can boost their performance seems a logical outcome. Additionally, production costs in America are estimated as just as ten percent higher than in China, while the labor force in the West is becoming more flexible (Booth, 2013). Considering also the transportation costs and costs related to coordination, monitoring and the lack of knowledge; re-shoring activities back to the United States for American firms seems an optimal solution. In other words, since comparative advantages of low labor costs countries are now eroding MNEs will come up with new internationalization strategies (Fratocchi et al. 2014). MNEs are implementing back-shoring strategies in order to enhance their performance by lowering costs due to distance and at the same time increase their potential in terms of sales due to higher quality products and faster response to their customers, therefore we expect that:

Hypotheses 1: Back-shoring (versus non back-shoring) of activities has a positive impact on

firms’ performance.

3.2 Back-shoring and high-technology sector

Firms expand their R&D activities into offshore locations in order to cope with limited in-house innovation (Nieto & Rodriguez, 2011). They do so in order to take advantage of the high-skilled employees in these locations, which are in shortage in the developed Western countries. Moreover, they do so in order to acquire new knowledge, create new capabilities and due to competitive pressures. By competitive pressures, we mean both the competition in

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emerging markets for high-skilled labor and the fact that wages are rising in countries which have been offshoring destinations for many years now; impelling firms to search for other destinations for their activities (Lewin et al. 2009; Manning et al. 2010). Similarly to other operations, R&D activities are being offshored mainly for efficiency seeking reasons. Further to efficiency seeking, firms offshore R&D in order to adapt to the new environment, generate new knowledge, create new capabilities and be able to provide suitable for these regions products (Nieto & Rodriguez, 2011).

However, MNEs which offshore R&D activities face the risk of conveying their knowledge to competitors, especially when joint ventures or other non-captive modes are being preferred (Mariotti et al. 2010). Firms, whose products are of low specificity, do not face the risk of conveying their knowledge to competitors. They do not face such a risk, due to the fact that they produce similar to competitors’ products. Hence, spillovers might not be a major issue for such firms. In other words, the power of firms, which products are of low specificity, does not lie on their level of R&D. Contrary to this, firms which operate in the high-technology sector are more sensitive to negative spillovers, due to the fact that their products are of high specificity and they rely more on their level of R&D (Murray & Kotabe, 1999). As already mentioned firms have offshored R&D activities in order to cope with the limited in-house innovation (Nieto & Rodriguez, 2011); however in these locations firms experience knowledge leakages which accrue due to the disloyalty of the employees, who are willing to work for another company just for a slightly higher wage (Booth, 2013). Furthermore, partnerships with local firms enabled the latter to acquire valuable knowledge and some of them to produce afterwards their own products. Nowadays, many Chinese firms are being considered as global leaders, such as Lenovo. Lenovo has acquired IBM’s laptop segment of business, which reveals the power of companies coming from emerging markets.

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All these reasons have led several MNEs to “reshore” their activities back to their home country and many more to consider doing so (Booth, 2013).

As mentioned above, firms, which operate in the high-technology sector, rely more on their R&D level and intellectual property is vital for them (Murray & Kotabe, 1999); hence their performance depends more on the technological innovations rather than in low labor cost manufacturing. When firms from high-technology sector back-shore their activities, they will gain more in terms of securing their knowledge-intellectual property than other firms. Hence, we believe that re-shoring strategies will have a greater impact on their performance, comparing to firms from other sectors. In other words, firms which operate in the high-technology sector will experience higher levels of performance than other firms, by implementing similar back-shoring strategies (Mariotti et al. 2010).

Having all that in mind, we expect that the greater dependence on the innovation process for firms, which operate in the high-technology sector, will positively moderate the relationship mentioned in hypothesis 1:

Hypotheses 2: High-technology sector, will positively moderate the relationship in H1.

Figure 1

Theoretical Framework

Back-Shoring of Activities (IV) Firm’s Performance (DV)

High-Tec firms

H1 (+)

H2 (+) Moderator

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4. Methodology

4.1 Sample

The source of our empirical study is a dataset derived from Orbis database; a database which publishes data for many companies around the world each year. We framed our dataset to the fortune global 500 (FG 500) firms. In order to create our dataset, we extracted from the above mentioned database data concerning the FG 500 firms for 2013 and 2015 fiscal year. However, as we expected, we could not utilize all 500 firms (1000 observations in total), due to missing values and differences in FG 500 list between 2013 and 2015 fiscal year. The final sample, which was used to test our hypotheses, consists of 265 observations. Concerning our hypotheses, the specific dataset (FG 500) is an appropriate empirical setting since big MNEs have the financial power and size to own foreign affiliates and to implement strategies, such as back-shoring.

4.2 Variables

Firms’ performance (dependent variable) and back-shoring (independent variable) are our main variables. In order to measure firms’ performance, we use returns on assets (ROA) based on 2015 fiscal year, which is widely used and it is preferred than returns on equity (ROE), due to the fact that among firms there is ambiguity concerning equity. Thus, ROA is a more accurate measurement, and widely used in the literature (Peng & Luo, 2000).

As for back-shoring, we investigate whether a firm has back-shored its activities from 2013 to 2015 (fiscal year) by using a dummy variable, which equals to 1 if a firm has back-shored its activities and 0 if not. In order to conclude this, we calculated the difference of firms’ foreign affiliates between the two years (Number of foreign affiliates 2015 – Number of foreign affiliates 2013). If the outcome of the calculation is negative it means that a firm

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has back-shored its activities and if not that it has not. Hence, in the former case, our dummy equals to 1 and in the latter equals to 0.

Our moderating variable is operationalized also by a dummy variable which takes the value of 1 when a firm operates in the high-technology sector and 0 if not. We took this information (whether a firm is in the high-technology sector or not) based on our data and more specifically on the specific sector each firm operates. We use this variable in order to test our second hypothesis and see if high-technology sector will positively moderate our first hypothesis (Almeida & Fernandes, 2008). Since our first hypothesis refers to the relationship between firms’ performance and back-shoring, we expect that our moderator will positively affect the specific relationship.

We also include a set of control variables, which we believe that will better explain our constant. Such variables are age of firms, size, ownership mode and whether they are listed in a stock exchange or not. Concerning the age of firms, we use the years of existence, which has been calculated by deducting from 2016 the year of a firm’s foundation (Fernandez & Nieto, 2006). As for the size, we use the number of employees, a variable widely used in previous studies (Nieto & Rodriguez, 2011). Then concerning ownership mode and listed companies, we use three dummies. The first one (State-ownership) takes the value of 1 when a firm is state-owned and 0 when it is not. The second dummy also concerns ownership and takes the value of 1 when a firm is family owned and 0 if it is not (Family-ownership). Our last dummy (Listed) takes the value of 1 when a firm is listed in a stock exchange and 0 when it is not. We expect that these dummies will provide a better explanation of the relationship between firms’ performance and back-shoring (Boardman & Vining, 1989; Dyer, 2006; Gang, 2000).

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5. Results

Table 1 summarizes the variables that we used in the empirical analysis and their operationalization. Table 2 contains the descriptive statistics and correlations between the variables. Concerning correlations, as we can see in Table 2 there are no reasons to believe that our variables raise multicollinearity concerns. In order to test our hypotheses, we use Ordinary Least Squares (OLS) regression analysis. Lastly, Tables 3 contains information concerning our regression analysis and Figure 2 illustrates our model.

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Concerning our model and the variables that we use, we can see in Table 3 that our variables do not explain adequately our dependent variable. According to R-squared, our variables explain only the 4% of firms’ performance in Model 3. This could be due to the fact that firms’ performance depends on many more factors which we do not include in our model. Back-shoring, size, and age of a firm are only some of the variables which might affect firms’ performance.

Further to our analysis, we observe in Table 3that our main variables, ROA and Back-shoring are not significant (in 95% confidence interval), with p-values of 0.089 and 0.263 respectively (Model 3). Tec-sector is also not significant in terms of direct effect on firms’ performance since p-value= 0.341. Similarly, the interaction term with p-value= 0.845 is not significant. Moving to our control variables none of them is significant in 95% confidence interval. However, State-ownership and size are significant in 90% confidence interval in all three models.

Concerning our hypotheses, we have the following results. In Hypothesis 1 we proposed that back-shoring will increase firms’ performance. The

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results concerning our first hypothesis show that the relationship between firms’ performance and back-shoring is not significant; hence Hypothesis 1 is not supported.

In our second hypothesis, we predicted that high-technology sector will positively moderate the relationship between firms’ performance and back-shoring. In other words, we proposed that firms, which operate in the high-technology sector, will experience higher levels of performance when back-shoring their activities compared to firms, which operate in different sectors. Our results show that the moderation effect is not significant; hence Hypothesis 2 is not supported. Additionally, in figure 2 we can see the minimal change of slopes between the two graphs, which shows that the moderation effect is not significant.

As far as the control variables are concerned, we have the following results about their coefficients. State-ownership’s and Family-ownership’s coefficients are negative in all three Models. On the other hand, the coefficient of the variable about listed companies is

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positive in Models 1 to 3. Age has a negative impact on firms’ performance in Models 1 and 3 and positive in Model 2. Lastly, firms’ size has a positive impact on performance in all three models.

Figure 2

6. Discussion & Conclusion

This study focuses on the back-shoring phenomenon. Although many firms are implementing offshoring strategies, some have started to consider relocating their activities, either back in their home countries or in proximate to their home countries destinations. So far, scholars have been mainly investigating the benefits and the costs of offshoring and re-shoring strategies, but little is known about how the latter strategy impacts firms’ performance. The main contribution of this paper is to enhance our understanding concerning back-shoring and firms’ performance. Our paper contributes to the literature by exploring the back-shoring phenomenon, which has been overlooked by academics, and its outcome on firms’ performance. Even if our results were not significant we tapped into a topic, which should be further investigated. The existing literature sheds light on the back-shoring phenomenon in general. In other words, findings show that MNEs are implementing such strategies in order

Low Back-shoring High Back-shoring

De p en d en t var iab le NonTec-sector Tec-sector

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to cope with several drawbacks. Such drawbacks accrue through negative spillovers and the difficulties in coordination of activities across the world. However, little is known about the impact of back-shoring strategies on firms’ performance.

We also tried to investigate the relationship between firms’ performance and back-shoring and how the latter is being affected when a firm operates in the high technology sector. We theorized a positive relationship between firms’ performance and back-shoring; and we predicted a positive moderation effect in our main relationship, when firms operate in high-technology sector. Our results show that both, the relationship between back-shoring and firms’ performance and the moderation effect are negative. However, they are not significant. Thus, we cannot speculate on our results, and give possible explanations. We also have to think the reasons why our results show no significance. We hypothesized a linear relationship between firms’ performance and back-shoring, which might not be the case. Maybe, the relationship between our DV and IV is not linear. Additionally, might be that our relationship is being mediated by another variable that we did not incorporated in our research design.

Concerning our control variables and more specifically their coefficients we can claim that our results are according to our expectations. State-ownership and Size are the only control variables, which are significant in 90% confidence interval. Concerning the former, we can attribute this to the fact that state-owned firms are rather inflexible. As for the latter, firm’s size positively affects firms’ performance, which can be explained due to the financial power of such firms and due to their aspiration to become more and more efficient. For the rest of our control variables we cannot make any speculations, due to the fact that they are not significant. Taking into account R-squared our variables do not adequately explain the DV. In combination with the insignificance of the most of our control variables, we can claim that our research design needs improvement on this aspect. In other words, we should have

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incorporated more control variables in order to try to explain our main relationship adequately.

However, our study has some limitations. We believe that it is not possible to see the results of back-shoring strategies within the same year. We should have incorporated this important fact in our research design and in a given year attribute firm’s performance with a lag of some years. In other words, for a given year (e.g. 2013) we should have firm’s performance for some years ahead (e.g. 2016, 2017). Having done so, our design model would be more accurate, since firms’ performance would reflect the outcome of back-shoring strategies. Another important limitation is the fact that concerning our dataset, we cannot measure offshore outsourcing. Many firms decide to hire external organizations in order the latter to perform some business functions for the former. Since we measure back-shoring by the number of foreign affiliates, we do not capture the entire level of back-shoring but only the part, which refers to captive offshoring. Lastly, we believe that a limitation of our research design lies in the fact that we did not use many control variables. Our model does not adequately explain the dependent variable. Having incorporated more control variables, we could make more accurate conclusions.

Concerning future research, we believe that future studies should focus on the phenomenon of back-shoring and try to explain its benefits and costs by capturing also offshore outsourcing. With the political instability around the world many changes will occur the following years; hence back-shoring will attract the attention of firms which operate in emerging countries. Studies to this direction, which will overcome our limitations, will be able to give some useful insights to managers concerning back-shoring strategies.

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The relationship between back-shoring and firms’ performance : the moderating effect of high-technology sector

Master Thesis