The influence of cultural and institutional distance on China's OFDI efficiency: fresh evidence from stochastic frontier gravity model

Abstract

PurposeCulture and institutions are among the essential sources of comparative advantage in international trade and may influence a country's FDI influx. This paper aims to analyze the impact of cultural distance (CD) and institutional distance (ID) on the efficiency of China's outward foreign direct investment (OFDI) for the panel of 43 countries during 2003–2016.Design/methodology/approachThe stochastic frontier approach (SFA) has been incorporated into the standard gravity model of gravity Kalirajan, 1999; Ravishankar and Stack, 2014). SFA has traditionally been implemented to evaluate the production frontier as the highest yield that could possibly be generated from specified input levels. The production process is viewed to be fully efficient if the real output is performed at frontier level. Otherwise, the production process is assumed technically inefficient, which implies potential scope for enhanced output. This error term is split into two parts, a non-negative term and more standard asymmetrical term. The former identifies inefficiencies in production, while the latter retrieves random disordersFindingsThe outcomes assert a U-shaped relationship between CD and the efficiency of China's OFDI. Put differently, when the CD is minimal, the “liability of foreignness” (LOF) effect plays a dominant role; and CD tends to reduce the efficiency of China's OFDI. On the flip side, when the culture distance is greater than a certain threshold level, the “advantages of foreignness” (AOF) effect plays a predominant role, and CD improves the efficiency of China's OFDI. Institutional distance results in the “LOF” effect significantly reduce the efficiency of China's OFDI.Research limitations/implicationsNotwithstanding these contributions, our study has some limitations which offer directions for future research. The major limitation of this research work is the availability of comprehensive data for a well extended time, in particular for the variable of CD. Further, a firm-level study can shed light on the motivations and performance of China OFDI. Finally, given that our analysis focuses on emerging market multinational enterprises (EMNEs) from China, the findings might not be explicitly generalizable to MNEs from other developing countries. Future studies should concentrate on the comparative study of China's OFDI with other developing countries, to deepen our understanding of the effects of ID and CD on the efficiency of OFDI.Originality/value(1) The work is novel in nature as the authors attempt to explore the effect of ID and CD on efficiency of Chinese FDI. To the best of the authors’ knowledge, no research is conducted in this direction in terms of Chinese FDI. (2) Further, the prior studies employed standard gravity model, which may not correctly evaluate the trade potential viewed as the highest potential value. To overcome the shortcomings of the standard gravity model in estimation of the trade performance and efficiency, the SFA has been incorporated into the standard gravity model of gravity.

Corruption, foreign aid, and international trade

“…Furthermore, we also collected country‐level corruption data for the 150 trading partners from two sources: (i) World Governance Indicators (Okada & Samreth, 2012) and (ii) Transparency International (Javorcik & Wei, 2009). We controlled for multiple individuals and bilateral factors with data from several sources such as World Development Indicators, the Heritage Foundation, CePII, World Integrated Solutions, the Global Preferential Trade Agreements, and Hofstede (1983) (Cuervo‐Cazurra, 2006; Musila & Sigué, 2010; Pettersson & Johansson, 2013; Zheng, Wang, Kamal, & Ullah, 2020). We used the gravity model of bilateral trade flows between 29 OECD countries and their 150 trading partners (excluding OECD members) from 1995 to 2018 to test our proposed framework.…”

Performance of Chinese foreign subsidiaries: the role of national distance, organizational learning and overseas Chinese networks

“…, 2017; Rosenbusch et al. , 2019; Zheng et al , 2020), or they have focused on aspects such as network embedding and organizational learning (Ferraris et al , 2020; Isaac et al. , 2019; Pu and Soh, 2017; Thakur-Wernz and Samant, 2019).…”

“…In the past few decades, IB scholars have studied the antecedents at the national and corporate levels to understand why some subsidiaries can achieve better performance than others. Some scholars focus on the macro level of home country and host country, and they believe that the institutional distance, cultural distance and knowledge distance between countries are important antecedents affecting subsidiary performance (Kostova et al, 2020;Zheng et al, 2020), but the research conclusions are not consistent. Some scholars argue that the distance between countries means obstacles that need to be overcome, and it will increase the cost and risk of subsidiary, thus has a negative impact on performance (Belderbos et al, 2020;Rickley, 2019), while other scholars argue that distance is an important source of Performance of Chinese foreign subsidiaries heterogeneous knowledge and learning ability (Jeong, 2021), helping subsidiaries overcome rigidity and inertia, promote learning and innovation, and achieve better performance (Elia et al, 2019(Elia et al, , 2020Magnusson et al, 2014;Morosini et al, 1998).…”

Analyzing the Characteristics and Evolution of Chinese Enterprises’ Outward Forward Direct Investment Host Country Network

“…However, they also have a joint investment motive, that is, to acquire technologies that are beneficial to the development of enterprises [8]. There are many factors affect the OFDI of Chinese enterprises which include market size, infrastructure development, human resources, geographical proximity, natural resource endowment of the host country [9,10], the institutional distance between host country and home country [11,12], the cultural distance [11,13], One Belt, One Road strategy [14]. One Belt, One Road strategy directs firms to invest in countries along the Belt and Road where good infrastructure and rich human resources are more likely to attract business investment [15].…”

“…From a micro perspective, research is mostly conducted by using the data of listed companies, Oriana Asia-Pacific Enterprise Analysis Database or customs database [21]. For example, Wu et al [12,22] collected data from companies and found that OFDI improves the total factor productivity of its home country through reverse technology spillover.…”