1. Introduction
In the context of globalization, the quality of a country’s cross-cultural communication has become a crucial reflection of its soft power and international influence. While China has achieved remarkable success in cultural dissemination abroad, it also faces multifaceted challenges.
Outward foreign direct investment (OFDI) by Chinese enterprises has been a focal topic under the BRI. Zhang Runze et al. examined the shared cultural imprints among BRI countries and their impact on China’s OFDI, noting that common cultural imprints serve as a key factor in mitigating risks and uncertainties, narrowing cultural distance, and fostering deeper cooperation [1]. Thus, research on advancing Chinese OFDI holds significant and far-reaching implications for enhancing national comprehensive strength and promoting global peace and development.
To date, few studies have explored the relationship between China’s cross-cultural communication and Chinese OFDI. Existing research on China’s cultural dissemination primarily focuses on linguistic translation, linguistics, and communication studies. For instance, Xiang Zhiqiang et al. proposed stratified communication strategies from a linguistic perspective [2]. Studies linking cultural dissemination to economic and trade impacts are even scarcer. These gaps provide the research space for this paper. This study aims to investigate the impact mechanism of cross-cultural communication on corporate OFDI, utilizing panel data from Chinese enterprises between 2013 and 2023 to uncover the role of cultural soft power in transnational economic behavior, thereby offering insights for corporate internationalization strategies.
The potential marginal contributions of this paper are as follows. Theoretically, first, it expands the interdisciplinary research on cultural communication and economic behavior, providing new theoretical perspectives. Second, by analyzing how the quality of China’s cross-cultural communication influences OFDI, this study further elucidates the economic effects of cultural outreach. Finally, incorporating cross-cultural communication into the analysis of OFDI determinants enables a more comprehensive understanding of the cultural environment and communication backdrop faced by Chinese enterprises overseas. Practically, understanding the impact mechanism of cultural dissemination on OFDI can help enterprises factor in the potential influence of cultural communication when formulating overseas investment strategies, thereby improving investment success rates and economic outcomes. The findings provide robust economic support for a scientific understanding of Chinese culture’s global dissemination, enhancing international recognition and reducing cultural misunderstandings and biases, ultimately fostering a more favorable global public opinion environment.
2. Literature review
2.1. Determinants of OFDI
Outward Foreign Direct Investment (OFDI) refers to an international investment approach in which a country directly invests in overseas enterprises for operational purposes. Existing research on Chinese OFDI primarily focuses on empirical analyses of internal efficiency improvements and external economic growth, particularly in the context of the Belt and Road Initiative, with an emphasis on the impact of “digital transformation” and external environmental factors. Accordingly, this section examines the determinants of Chinese OFDI from both host-country and home-country perspectives.
Many scholars have explored the locational choices of Chinese OFDI based on the operational environment of host countries. Wang Jianxin et al. find that it has a dampening effect on Chinese firms’ OFDI location choice to locate in both the US and other regions [3]. Chen Sheng et al found that developing countries are more attractive to China’s OFDI than developed countries [4]. Zhou Wei et al. combine the development trend of “digital economy” with cultural, geographical and institutional factors to study the impact of multi-dimensional distance on China’s OFDI [5].
Some scholars also study the impact of industrial empowerment of home countries on OFDI. Liu Xiaodi et al theoretically analysed and empirically tested that digital transformation can significantly improve the efficiency of corporate OFDI [6]. Wang Bijun et al. examined the impact of home country government support on the performance of OFDI and found that the return on assets of China’s overseas subsidiaries decreased after the introduction of dividend policies such as the Belt and Road Initiative, and then proposed improvement measures [7].
2.2. The impact of cross-cultural communication
In this study, cross-cultural communication is defined as the diffusion or transmission of one culture to other cultures through certain communication channels adapted to the times, and a series of collisions and mingling between the two, so that the latter can better respect and understand the former. In recent years, most of the academic research has focused on the exploration of measures.
China’s cross-cultural communication has a crucial impact on international cultural trade. Starting from the perspective of international cultural trade, Hua Jian et al. explored the new actions that should be taken by outbound cultural communication under the new trend of cultural trade [8].
2.3. Research gaps
Regarding Chinese OFDI, existing studies predominantly focus on empirical analyses of internal efficiency improvements and external economic growth, particularly in BRI-related contexts, with an emphasis on “digital transformation” and external environmental influences. While research perspectives from host-country operational environments and home-country industrial empowerment have provided in-depth discussions on OFDI determinants, other potential influencing factors remain underexplored.
Despite extensive research on OFDI determinants and the effects of cross-cultural communication, few studies systematically integrate the two. Furthermore, the potential impact of cross-cultural communication on Chinese OFDI decision-making and performance has not been sufficiently explored. In summary, this paper employs a fixed-effects model and moderation analysis using panel data from Chinese enterprises (2013-2023) to empirically investigate the impact mechanism of cross-cultural communication on Chinese OFDI.
3. Mechanism analysis and hypothesis development
3.1. Mediating mechanisms
Yu Guoming et al. found that international sister-city relationships significantly promote Chinese OFDI, further evidencing the role of cultural communication in facilitating OFDI [9]. When the public in a host country possesses a deeper understanding and higher acceptance of Chinese culture, the operational environment for Chinese enterprises becomes more favorable, thereby reducing operational costs and market entry barriers. Thus, cultural dissemination fosters a conducive external environment for Chinese OFDI by enhancing cultural awareness and acceptance, ultimately encouraging outward investment.
International cultural trade, defined as the exchange of cultural products and services between nations, serves as a critical vehicle for expanding cross-cultural communication and securing international discourse power, pricing power, and market control. Increased cultural trade not only reflects the intensity of cultural exchange between two countries but also provides Chinese enterprises with greater market opportunities and resource support. Moreover, thriving cultural trade may facilitate the flow of technology, management expertise, and other resources, further incentivizing Chinese OFDI. Consequently, cultural dissemination promotes OFDI by stimulating cultural trade, which offers expanded market opportunities and resource support for overseas investments.
Furthermore, cross-cultural communication drives domestic industrial upgrading by exporting cultural symbols and value systems. For example, the resulting increase in technological sophistication not only elevates the value chain of cultural products but also fosters new forms of technology-intensive trade. This technology-enabled trade expansion optimizes global resource allocation - once firms establish sufficient technological barriers and brand recognition in foreign markets, they are incentivized to expand direct investment through cross-border M&As and overseas R&D centers to mitigate trade frictions and better access consumer markets. Thus, a transmission mechanism emerges: enhanced export technological sophistication promotes cultural product trade, which in turn drives OFDI.
Based on this analysis, we propose the following core hypothesis:
Effective cross-cultural communication positively facilitates Chinese OFDI, i.e., China's cross-cultural communication exhibits a significantly positive correlation with Chinese OFDI.
3.2. Moderating mechanism
Zhang Zengtian et al. found that executives’ overseas experience can enhance managers’ risk appetite and self-confidence [10]. However, the overseas background of corporate executives may potentially weaken the relationship between China's cross-cultural communication and Chinese OFDI. Although executives with international experience can reduce cultural friction in investments through cross-cultural management skills, their globalized background may lead firms to rely more on “localization strategies” rather than proactive cultural dissemination to gain host-country acceptance.
Specifically, overseas executives tend to advance investments by adapting to the host country’s institutional environment and avoiding culturally sensitive issues. In this context, the executives’ personal cultural experience replaces cultural communication as the primary means of mitigating investment risks. This weakening effect may be more pronounced in investment destinations with greater cultural differences, as overseas executives must prioritize resolving immediate cultural conflicts over strategic cultural dissemination initiatives.
Cheng Zhengzhong’s empirical study demonstrated that both the absolute and relative levels of foreign direct investment (FDI) promote revenue growth in high-tech zone enterprises, exhibiting significant technology spillover effects [11]. By fostering an international business ecosystem, FDI can significantly amplify the positive impact of China's cross-cultural communication on Chinese OFDI.
4. Model specification and variable selection
4.1. Data and variables
The dependent variable in this study is the scale of Chinese enterprises’ outward foreign direct investment (OFDI) in host countries, measured by either investment amount or the number of investment projects. The relevant data is sourced from the CSMAR database.
The core independent variable is international cultural communication (ICC), operationalized using the level of opening-up (LOU) as a proxy measure.
This empirical study incorporates the following firm-level control variables. Return on Equity (ROE): Reflects corporate profitability. Firms with higher ROE may possess greater resources for overseas expansion. Asset Turnover Ratio (ATO): Measures operational efficiency in asset utilization. Firms with higher efficiency typically find it easier to achieve cross-border resource integration. Cash Flow Ratio: Evaluates liquidity and risk resilience. Higher ratios indicate sufficient cash reserves for expansion, mergers/acquisitions, or investment projects, and generally reflect better creditworthiness. Inventory Ratio (INV): Calculated as net inventory divided by total assets. Lower inventory levels suggest higher asset liquidity. Revenue Growth Rate: Firms with higher growth rates typically demonstrate stronger investment intentions and internationalization ambitions.
4.2. Model specification
To examine the relationship between China's cross-cultural communication and Chinese enterprises’ OFDI, this study employs panel data models for empirical analysis. For parameter estimation, we adopt the following fixed-effects model:
where
5. Empirical analysis
5.1. Descriptive statistical analysis
The descriptive statistical analysis of the research sample is presented in Table 1. The sample comprises 37,626 observations spanning the period from 2013 to 2023. The dependent variable OFDI exhibits a mean value of 2.075 with a standard deviation of 5.548, indicating substantial variation in overseas investment scales across enterprises. The core explanatory variable LOU shows a mean of 0.0221 and standard deviation of 0.0185, reflecting an uneven distribution of cultural communication intensity among different firms. Regarding control variables, the sample enterprises demonstrate an average return on equity (ROE) of 5.66%, asset turnover ratio (ATO) of 0.622, cash ratio of 4.77%, inventory ratio of 13.4%, and revenue growth rate of 14.4%, which collectively characterize the fundamental financial profile of the sampled firms.
(1) |
(2) |
(3) |
(4) |
(5) |
|
VARIABLES |
N |
mean |
sd |
min |
max |
LOU |
29,326 |
0.0221 |
0.0185 |
0 |
0.229 |
OFDI |
31,473 |
2.075 |
5.548 |
0 |
20.18 |
ROE |
37,583 |
0.0566 |
0.141 |
-0.962 |
0.414 |
ATO |
37,621 |
0.622 |
0.416 |
0.0546 |
2.891 |
Cashflow |
37,626 |
0.0477 |
0.0681 |
-0.199 |
0.266 |
INV |
37,267 |
0.134 |
0.123 |
0 |
0.778 |
Growth |
37,608 |
0.144 |
0.384 |
-0.653 |
3.808 |
5.2. Baseline regression analysis
Table 2 reports the specific results of the baseline regression. Column (1) presents the direct regression results of OFDI on the level of opening-up (LOU) without including control variables or controlling for year effects. The results show that the level of opening-up has a significantly positive impact on OFDI scale. Column (2) introduces firm-level control variables, and the positive effect of opening-up on OFDI scale remains significant. Column (3) further incorporates time fixed effects based on Column (2), and the results remain positive and statistically significant at the 1% level. These findings support Hypothesis 1, indicating that effective cross-cultural communication can significantly promote Chinese firms’ OFDI.
(1) |
(2) |
(3) |
|
VARIABLES |
OFDI |
OFDI |
OFDI |
lnLOU |
0.158*** |
0.162*** |
0.146*** |
(0.0347) |
(0.0349) |
(0.0353) |
|
ROE |
-0.346 |
-0.368 |
|
(0.303) |
(0.303) |
||
ATO |
0.637*** |
0.599*** |
|
(0.0864) |
(0.0863) |
||
Cashflow |
1.293** |
1.408** |
|
(0.587) |
(0.590) |
||
INV |
-0.214 |
-0.342 |
|
(0.286) |
(0.286) |
||
Growth |
0.0831 |
0.125 |
|
(0.0946) |
(0.0955) |
||
Constant |
2.710*** |
2.306*** |
3.344*** |
(0.142) |
(0.161) |
(0.200) |
|
Observations |
24,105 |
23,859 |
23,859 |
R² |
0.001 |
0.004 |
0.008 |
Year FE |
NO |
NO |
YES |
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
5.3. Heterogeneity analysis
(1)Non-duality status |
(2)Duality status |
(3)non-SOEs |
(4)SOEs |
|
VARIABLES |
OFDI |
OFDI |
OFDI |
OFDI |
LOU1 |
0.157*** |
0.172** |
0.146*** |
0.209*** |
(3.94) |
(2.37) |
(3.11) |
(4.08) |
|
Control variables |
Controlled |
Controlled |
Controlled |
Controlled |
Constant |
2.225*** |
2.489*** |
2.522*** |
2.016*** |
(11.96) |
(7.70) |
(11.60) |
(8.63) |
|
N |
16,958 |
6,901 |
14,989 |
8,870 |
R² |
0.004 |
0.003 |
0.002 |
0.009 |
Year FE |
NO |
NO |
NO |
NO |
t-statistics in parentheses
*** p<0.01, ** p<0.05, * p<0.1
5.4. Robustness tests
This paper applies four methods to systematically test the reliability of the benchmark regression results (see Table 4). All robustness tests show consistent and statistically significant coefficients (p<0.05) for the cultural communication variable, confirming the methodological robustness of baseline findings.
(1)two-way fixed effects |
(2) explanatory variable replaced |
(3)dependent variable replaced |
(4)additional control variable |
|
VARIABLES |
OFDI |
lnOFDI |
OFDI frequency |
OFDI |
lnLOU |
0.172** |
0.016*** |
0.154*** |
|
(2.40) |
(3.78) |
(4.37) |
||
Control variables |
Controlled |
Controlled |
Controlled |
Controlled |
TobinQ |
-0.166*** |
|||
(-6.35) |
||||
lnCE |
0.015** |
|||
(2.05) |
||||
Constant |
2.554*** |
2.758*** |
0.341*** |
3.696*** |
(5.79) |
(37.68) |
(14.15) |
(17.86) |
|
N |
2,826 |
200 |
23,859 |
23,859 |
R² |
0.014 |
0.109 |
0.005 |
0.009 |
Number of stkcd |
426 |
|||
Year FE |
YES |
YES |
YES |
YES |
id FE |
YES |
NO |
NO |
NO |
t-statistics in parentheses
*** p<0.01, ** p<0.05, * p<0.1
5.5. Mechanism testing
Cross-cultural communication drives domestic industrial technological upgrading through the export of cultural symbols and value systems. By establishing multi-layered international cultural networks, it significantly enhances urban export resilience. This resilience enhancement essentially represents the transformation of cultural capital into organizational capacity. When enterprises accumulate sufficient technological barriers and brand recognition in overseas markets, they naturally expand direct investment.
Based on prefecture-level city panel data, this study systematically examines the relationships between cross-cultural communication (LOU) and mediating variables-export technological sophistication (Prody) and “urban export resilience” (CER) - with results presented in Table 5. The regression results demonstrate that cross-cultural communication exerts significantly positive effects on OFDI, export technological sophistication, and urban export resilience, verifying its role as a fundamental driving force. Further analysis reveals that improvements in export technological sophistication and urban export resilience serve as crucial mediating mechanisms.
Table 5 Mechanism Testing
(1) |
(2) |
(3) |
|
VARIABLES |
OFDI |
CER |
Prody |
lnLOU |
0.146*** |
0.0331*** |
0.119*** |
(0.035) |
(0.000503) |
(0.002) |
|
Control variables |
Controlled |
Controlled |
Controlled |
Constant |
3.344*** |
0.300*** |
10.548*** |
(0.200) |
(0.00284) |
(0.011) |
|
Observations |
23,859 |
24,541 |
24,522 |
R² |
0.008 |
0.194 |
0.425 |
Year FE |
YES |
YES |
YES |
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
5.6. Moderating effect test
This study introduces executives’ overseas experience (Oversea_QTY) and foreign direct investment (FDI) as moderating variables to examine the impact of corporate investment decisions and foreign capital agglomeration on the relationship between cultural communication and OFDI. Executives’ overseas experience is measured by the number of overseas executives in the company, while FDI is measured by the number of contracted foreign direct investment projects. The moderating effect test results are shown in Table 6. Column (2) shows that executives’ overseas experience weakens the positive effect of China’s cross-cultural communication on Chinese enterprises’ OFDI. Possible reasons include: overseas executives may have a better understanding of host country cultures, thereby reducing reliance on cultural communication; in addition, overseas executives are more aware of overseas investment risks and are more cautious in such decisions, thereby inhibiting the effect of promoting investment expansion. Column (3) shows that foreign capital agglomeration can significantly and positively moderate the impact of cultural communication on OFDI. And when the number of foreign investment projects exceeds a certain threshold, the success rate of cultural enterprises going global is significantly improved.
(1) |
(2) |
(3) |
(4) |
|
VARIABLES |
OFDI |
OFDI |
OFDI |
OFDI |
lnLOU |
0.121*** |
0.176*** |
0.151*** |
0.106*** |
(3.52) |
(4.67) |
(3.83) |
(0.0407) |
|
Oversea_QTY |
1.224*** |
0.548** |
||
(27.18) |
(2.84) |
|||
interaction1 |
-0.174*** |
|||
(-3.60) |
||||
Control variables |
Controlled |
Controlled |
Controlled |
Controlled |
FDI |
0.0674*** |
0.916*** |
||
(3.88) |
(4.64) |
|||
interaction2 |
0.233*** |
|||
(4.32) |
||||
Constant |
1.777*** |
2.367*** |
2.284*** |
2.090*** |
(0.187) |
(0.264) |
(12.47) |
(11.09) |
|
Observations |
23,859 |
23,859 |
20,057 |
20,057 |
R² |
0.005 |
0.005 |
0.004 |
0.005 |
Year FE |
NO |
NO |
NO |
NO |
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
6. Conclusions
This study systematically reveals the impact mechanism of China’s cross-cultural communication on firms’ outward foreign direct investment based on the panel data of Chinese enterprises from 2013 to 2023. It is found that foreign cultural communication significantly promotes OFDI by Chinese enterprises through enhancing host country’s cultural awareness, strengthening policy support and stimulating technological upgrading of local industries. Moderating effects show that corporate executives with overseas backgrounds and foreign capital agglomeration can significantly strengthen this positive effect. Heterogeneity analyses show that state-owned enterprises (SOEs), due to their policy and financing advantages, and Non-duality status, due to their optimised governance structure, are more likely to contribute to OFDI through cultural diffusion.The robustness test further verifies the reliability of the findings.
Based on the above findings, the following suggestions are made: The government should support the integration and development of cultural industry with science and technology and foreign investment through policies, for example, establishing incubation platforms for cultural enterprises to go overseas in high-tech cities and foreign-investment gathering areas, so as to reduce the risk of firms’ overseas investment. Enterprises need to pay attention to digital communication capabilities and enhance the efficiency of cultural communication through social media, cross-border e-commerce platforms and other channels, as well as improve their governance structure, such as optimising foreign policies to unleash the potential of cultural “going out”.
In summary, this study not only provides empirical evidence for understanding the economic effects of cultural dissemination but also offers valuable references for the coordinated development of culture and economy under the BRI framework.
References
[1]. Zhang Runze, Qiu Peiyao, Lu Duan, et al. Shared Cultural Imprints and Enterprise Outward Investment [J]. South China Journal of Economics, 2023, (03): 76-93.
[2]. Xiang Zhiqiang, Ma Tingzi. Stratified Strategies for China's Cross-Cultural Communication Under Linguistic Distance [J]. Journal of Hunan University (Social Sciences), 2020, 34(05): 141-145.
[3]. Wang Jianxin, Li Ping, Yang Chen. U.S. Economic Policy Uncertainty and Location Choice of Chinese Enterprises' OFDI [J]. International Business Research, 2021, 42(05): 44-56.
[4]. Chen Sheng, Guo Yong. Host Country Business Environment and Home Country Outward Foreign Direct Investment: An Empirical Study Based on China's OFDI in BRI Countries [J]. Forum of World Economics & Politics, 2021, (03): 78-105.
[5]. Zhou Wei, Xu Zixuan, Zhao Xiaoyi, et al. Impact of Host Country Digitalization Level and Multidimensional Distance on China's OFDI [J]. Statistics & Decision, 2023, 39(21): 149-153.
[6]. Liu Xiaodi, Zhang Hong, Li Qingyang. Digital Transformation Empowering Chinese Enterprises' Outward Foreign Direct Investment: A Framework Analysis Based on Eclectic Paradigm Theory [J]. International Economics and Trade Research, 2024, 40(04): 86-101.
[7]. Wang Bijun, Song Ziwei. Home Country Government Support and Performance of Enterprise Outward Foreign Direct Investment [J]. International Economics and Trade Research, 2023, 39(03): 53-70.
[8]. Hua Jian, Tian Ye. New Trends in International Cultural Trade and China's New Approaches to Cross-Cultural Communication [J]. Journal of Shanghai Jiaotong University (Philosophy and Social Sciences), 2023, 31(04): 78-92.
[9]. Yu Guoming, Pan Jiabao. Paths and Strategies for Enhancing China's International Cultural Influence [J]. Media Observer, 2021, (04): 11-18.
[10]. Zhang Zengtian, Yao Zhenjiu, Lu Qi, et al. Can Executives' Overseas Experience Promote Corporate Green Innovation? [J]. Foreign Economics & Management, 2023, 45(08): 68-82.
[11]. Cheng Zhengzhong, Xia Enjun. Does Foreign Direct Investment Generate Spillover Effects on Development of High-Tech Zones? Evidence from Panel Data of 31 National High-Tech Zones [J]. Journal of Technology Economics, 2020, 39(03): 87-93.
Cite this article
Li,S. (2025). The Impact of Cross-Cultural Communication on Firm’s OFDI: Evidence from China. Advances in Economics, Management and Political Sciences,206,76-85.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Zhang Runze, Qiu Peiyao, Lu Duan, et al. Shared Cultural Imprints and Enterprise Outward Investment [J]. South China Journal of Economics, 2023, (03): 76-93.
[2]. Xiang Zhiqiang, Ma Tingzi. Stratified Strategies for China's Cross-Cultural Communication Under Linguistic Distance [J]. Journal of Hunan University (Social Sciences), 2020, 34(05): 141-145.
[3]. Wang Jianxin, Li Ping, Yang Chen. U.S. Economic Policy Uncertainty and Location Choice of Chinese Enterprises' OFDI [J]. International Business Research, 2021, 42(05): 44-56.
[4]. Chen Sheng, Guo Yong. Host Country Business Environment and Home Country Outward Foreign Direct Investment: An Empirical Study Based on China's OFDI in BRI Countries [J]. Forum of World Economics & Politics, 2021, (03): 78-105.
[5]. Zhou Wei, Xu Zixuan, Zhao Xiaoyi, et al. Impact of Host Country Digitalization Level and Multidimensional Distance on China's OFDI [J]. Statistics & Decision, 2023, 39(21): 149-153.
[6]. Liu Xiaodi, Zhang Hong, Li Qingyang. Digital Transformation Empowering Chinese Enterprises' Outward Foreign Direct Investment: A Framework Analysis Based on Eclectic Paradigm Theory [J]. International Economics and Trade Research, 2024, 40(04): 86-101.
[7]. Wang Bijun, Song Ziwei. Home Country Government Support and Performance of Enterprise Outward Foreign Direct Investment [J]. International Economics and Trade Research, 2023, 39(03): 53-70.
[8]. Hua Jian, Tian Ye. New Trends in International Cultural Trade and China's New Approaches to Cross-Cultural Communication [J]. Journal of Shanghai Jiaotong University (Philosophy and Social Sciences), 2023, 31(04): 78-92.
[9]. Yu Guoming, Pan Jiabao. Paths and Strategies for Enhancing China's International Cultural Influence [J]. Media Observer, 2021, (04): 11-18.
[10]. Zhang Zengtian, Yao Zhenjiu, Lu Qi, et al. Can Executives' Overseas Experience Promote Corporate Green Innovation? [J]. Foreign Economics & Management, 2023, 45(08): 68-82.
[11]. Cheng Zhengzhong, Xia Enjun. Does Foreign Direct Investment Generate Spillover Effects on Development of High-Tech Zones? Evidence from Panel Data of 31 National High-Tech Zones [J]. Journal of Technology Economics, 2020, 39(03): 87-93.