Interfirm relationships and business performance in China

In identifying barriers to firm growth, much attention has been paid to barriers that act at the level of the individual firm. But firms do not operate in a vacuum; business relationships are potentially central. And because of frictions such as lack of information or lack of trust, such relationships may not form efficiently, limiting firm growth. Although their potential role for development was highlighted in an early study by McMillan and Woodruff (1999), there is limited evidence on the causal impact of networks on firm performance. Existing approaches to induce variation in firm networks exploit either the introduction of a new transportation technology using observational data (Bernard et al. 2015), or experimentally induced occasional meetings in committees (Fafchamps and Quinn 2014). But we have no experimental evidence about the impact of intensive business networking on firm performance, about the underlying mechanisms, and about policies that can induce such a change.

The study: Participation in regular business meetings

To make progress on these issues, in 2013, we invited tens of thousands of young firms in Nanchang, Jiangxi province, China to participate in regular business meetings (Cai and Szeidl 2016). From the pool of applicants, 2,820 were randomly selected as the study sample. These firms were small, but not tiny – on average, they employed 36 workers and had an annual profit of €105,000.

In the main intervention, 2,820 managers were randomly divided into a treatment group and a control group. Within the treatment group, the managers were randomly split into subgroups of ten people. Each subgroup was then tasked to hold monthly business meetings for one year. Managers in the control group were not tasked to hold meetings. All the firms were surveyed before (baseline), immediately after (mid-line), and one year after (end-line) the intervention.

Effects on firm performance

Figure 1 shows the effect of business meetings on firm revenue. The blue bars act as a benchmark by showing revenue growth for control firms that did not participate in the meetings. The red bars measure the additional growth of treatment firms that did participate in the meetings. Growth rates are measured relative to revenue at base-line, that is, the fiscal year before the intervention.

Figure 1 Effect of meetings on firm revenue

Figure 1 shows large, significant, and persistent revenue effects of the treatment. By the mid-line, revenue increased by only 0.4% in the control group, but it increased by an additional eight percentage points in the treatment group. The bar for the end-line shows that this increase persisted in the year after the intervention.

We found similarly large and persistent effects for a wide range of firm performance measures: profit, factors of production (employment and fixed assets), as well as inputs of production (materials and utilities). All these effects are statistically significant. Taken together, the results show substantial improvements in firm performance across a range of domains.

Intermediate outcomes

We also found significant effects for several intermediate outcomes: a survey-based management score; the number of suppliers and clients; and the probability of borrowing. These outcomes are suggestive of two possible channels by which the meetings may have improved performance:

• learning from peers leading to improved business management; and
• better firm-to-firm matching leading to establishing more business partners.

But these results are only suggestive; it is also possible that another channel created firm growth, which then improved these outcomes. Below we discuss more direct evidence on the channels.

Whom you know matters

How did group composition, that is, the type of peers, affect performance? Due to the random grouping of firms, some firms ended up with better peers than others. Proxying peer quality with size (employment) before the intervention, we found evidence of significant and persistent peer effects. For example, being randomised into a group in which the average peer firm was 10% larger significantly increased revenue by more than one percent. Similar effects were found for several other outcomes. This result further confirms that the meetings mattered. What’s more, it highlights that the identity of peers mattered.

Channels of peer learning

What made the meetings successful? To complement the suggestive evidence on possible peer learning channels discussed earlier, we implemented additional interventions that more directly isolate concrete channels. In one such intervention we distributed information about financial opportunities to a subset of managers. We were interested in the extent to which managers shared this information with their peers, that is, the rate of diffusion.

Figure 2 Information diffusion rate

The first set of bars in Figure 2 plot the diffusion rate concerning a firm funding opportunity (a cash grant from the government). The first bar shows that managers were 29% more likely to apply for this funding if some of their peers were informed, confirming that learning from peers was indeed an active force in the meetings.

The second and third bar separately measure diffusion for ‘non-competitive’ and ‘competitive’ groups, defined by the share of firms in the group who were competitors of each other. Diffusion was lower in competitive groups, suggesting that product market rivalry can hinder learning.

The second set of bars plot the analogous diffusion rates of a second financial opportunity, which was a personal savings account. Because this opportunity did not affect rival firm performance, competition was not expected to affect the rate of information diffusion. The evidence shown in Figure 2 confirms this, with equally strong diffusion effects in competitive and non-competitive groups. These findings not only establish that learning was an active channel, but also uncover a new mechanism: that competition can limit the transmission of rival information.

We used another additional intervention to document the mechanism of improved firm-to-firm matching. In this intervention, we organised one-time meetings between managers from different groups. We found that more new partnerships were created in the regular meetings than in these cross-group meetings. This result confirms that regular meetings reduced the cost of firm-to-firm matches, and hence led to improved partnering.

Performance gains and policy impact

We also used our estimates to conduct a cost-benefit calculation, and found that the average profit gains from the meetings exceeded the associated time cost of the managers by a factor of two. While this calculation relies on some assumptions, the extent to which the benefits outweigh the costs strongly suggests that the meetings were overall beneficial. We conclude that in our context, business meetings were a low-cost intervention that generated substantial and persistent performance gains.

Conclusion

While more work is needed to fully evaluate the contexts to which these findings generalise, our results suggest that working with a sample of young firms interested in networking contributed to the success of the intervention. We therefore encourage policymakers interested in similar interventions to focus especially on such participants. We are also looking forward to further research that helps us more fully understand the contexts in which, and the mechanisms through which, business networks affect firm performance.

Editor's note: This article is based on this PEDL Project.

Photo credit: Chris @ flickr.

References

Bernard, A B, A Moxnes, and Y U Saito (2015) "Production Networks, Geography and Firm Performance," NBER Working Paper No. 21082.

Cai, J and A Szeidl (2016), "Interfirm Relationships and Business Performance", CEPR Discussion Paper No. 11717.

Fafchamps, M and S Quinn (2016), "Networks and Manufacturing Firms in Africa: Results from a Randomized Field Experiment", World Bank Economic Review.

McMillan, J and C Woodruff (1999), "Interfirm Relationships and Informal Credit in Vietnam", Quarterly Journal of Economics 11: 1285-1320.