SME’s export intensity: enhancers, inhibitors and firm characteristics

Abstract

This study aims to investigate the factors explaining the variation in SMEs’ degree of internationalization, measured by export intensity (i.e. the share of export revenue in total revenue). Primary data were collected through survey administered using questionnaire in seven provinces in Indonesia, yielding 497 usable responses. Principal component analysis was used to solve dimensionality issues of perceptual variables while Generalized Linear Model (fractional logit regression) and the Ordinary Least Square regression were used in the estimation. The findings show that SMEs’ export expansion is positively affected by firm characteristics namely firm age and total employees, as well as some exhibiting factors namely owners’ international work experience, central government assistance, network relationships with non-government actors, location, export market of choices and years of exporting. By contrast, SMEs’ export continuation is adversely affected by perceived difficulties in overcoming informational and human resources barriers, distribution, logistics and promotional barriers, financial barriers, foreign government barriers, procedural barriers and price barriers. The findings suggest that post-export assistance is as important as creating new exporters. Further, the findings provide insights on specific types of assistances required by exporting SMEs to exploit their export-exhibiting factors while also overcoming the export-inhibiting factors.

RÉSUMÉ

Cette étude vise à examiner les facteurs qui expliquent la variation du degré d’internationalisation des PME, mesuré par l’intensité des exportations (c’est-à-dire la part des recettes d’exportation dans les recettes totales). Les données primaires ont été collectées par le biais d’une enquête administrée à l’aide d’un questionnaire dans sept provinces indonésiennes, ce qui a permis d’obtenir 497 réponses utilisables. L’analyse en composantes principales a été employée pour résoudre les problèmes de dimensionnalité des variables perceptuelles, tandis que le modèle linéaire généralisé (régression logistique fractionnaire) et la régression par la méthode des moindres carrés ordinaires ont été utilisés pour l’estimation. Les résultats montrent que l’expansion des exportations des PME est positivement impactée par les caractéristiques de l’entreprise, à savoir l’âge de l’entreprise et le nombre total d’employés, ainsi que par certains facteurs d’exposition, à savoir l’expérience professionnelle internationale des propriétaires, l’aide du gouvernement central, les relations de réseau avec des acteurs non-gouvernementaux, la localisation, le marché d’exportation choisi et le nombre d’années d’exportation. En revanche, la poursuite des exportations des PME est négativement affectée par les difficultés perçues à surmonter les obstacles liés à l’information et aux ressources humaines, à la distribution, à la logistique et à la promotion, aux financements, aux gouvernements étrangers, aux procédures et aux prix. Les résultats suggèrent que l’aide après exportation est aussi importante que la création de nouveaux exportateurs. En outre, ils fournissent des indications sur les types spécifiques d’aide dont les PME exportatrices ont besoin pour exploiter leurs facteurs d’expansion à l’exportation, tout en surmontant les facteurs d’entrave à l’exportation.

Keywords:

• SMEs
• export performance
• export intensity
• export barriers
• Indonesia

Mots-clés:

• PME
• performance à l’exportation
• intensité des exportations
• obstacles à l’exportation
• indonésie

JEL CLASSIFICATION:

• F23
• L25
• M13
• M16
• O17

Ethical approval

This study was registered in the Human Ethics Committee of Lincoln University, New Zealand, under application No 2014-04, with approval granted by the Chair of the Committee.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The Association of Southeast Asian Nations (ASEAN) is a regional economic and political cooperation organisation that was founded in 1967 and currently comprises ten member states namely Indonesia, Malaysia, Philippines, Singapore, Thailand, Brunei Darussalam, Viet Nam, Lao PDR, Myanmar and Cambodia.

2 By September 2019, Indonesia had 11 FTAs in effect, including ASEAN (1993), ASEAN-China (2010), ASEAN-Australia and New Zealand (2010), ASEAN-India (2010), ASEAN-Japan (2008), ASEAN-Korea (2007), Indonesia-Japan (2008), Indonesia-Pakistan (2013), Indonesia-Chile (2017), Indonesia-EFTA CEPA (2018) and Indonesia-Australia (2019). Indonesia also has ongoing negotiations with several other regional and bilateral FTAs.

3 Prior to the implementation of the Law No. 20 (2008) on Micro, Small and Medium-Sized Enterprise, the “Small-sized Enterprise” term generally included small and micro-enterprises.

4 Online promotion at Ministry of Cooperatives and SMEs’ website, http://www.indonesian-products.biz.

5 The catalogue provides SMEs’ contacts and products description in four languages (English, Arabic, Japanese and Indonesian). The catalogue is published annually as part of the ministry’s promotion program.

6 The directory books listed all SMEs that participated in international trade shows organised by the Ministry of Cooperatives and SMEs’ during 2005-2009.

7 The BPS-Statistics Indonesia (National Agency for Statistics) performs economic censuses every ten years. When the survey for this study was conducted in 2014, the most recent census was the 2006 national census while the next census will be conducted in 2016 and published in 2018.

8 The population of small and medium-sized (excluding micro-sized) enterprises in the study area (N) is approximately 490,000 (around 70% of the 700,000 total population of Indonesian SMEs). Due to time and budget constraints, the sample size (n) is not expected to exceed 5% of the population (less than 24,500 SMEs). Hence, the following sample size formula for an infinite population is applied (Anderson, Sweeney, and Williams 2010; Crossley 2008; C. F. Lee, Lee, and Lee 1999): $n={\left(\frac{\left(Z_{\propto /2}\right)\sigma }{\mathrm{\text{MOE}}}\right)}^2,$ where n is the sample size; $Z_{\propto /2}$ is the value of the two-sided confidence interval in normal distribution, δ represents the variation of the variable of interest and MOE is the desired margin of error. Assuming that $Z_{\propto /2}$ = 1.96 (corresponds to a 95% confidence interval), response distribution σ = 0.5, MOE = 0.05 and N = 490,000, the calculated sample size is 384. However, the sample size was expanded by 25% (to at least 480) to increase the sample sufficiency.

9 We use a three-point Likert scale because in the pilot study the respondents had difficulties in indicating their answers when given a five-point and seven-point Likert scale. Jacoby and Matell (1971) argued that a three-point Likert scale is appropriate for capturing variations in non-binary responses and proved that the number of scale points is orthogonal to the accuracy of the measurement. The inherent upsides and downsides of an unbalanced Likert-scale – one which is absent of a neutral scale point – has been discussed thoroughly in extant literature. Unbalanced scale points are more prone to suffer from biasedness if the questions are considered by the subjects to be sensitive (to the local norms) in nature, thereby compelling them to pick the option that is socially more acceptable (Garland 1991; Johns 2010). We can assume that such bias is ultimately reduced in our study, as our topic involves neither politically nor socio-culturally sensitive questions, coupled with the fact that during the pilot study, our respondents displayed a strong tendency to opt for the neutral point when it is made available. Hence, in our case, the unbalanced three-point Likert scale was employed to ensure a choice is being made, without any trade-off of reliability, validity and unbiasedness principles. For the use of a three-point scale without a neutral scale in the survey for export barrier survey questions, see OECD (2012).

10 For further details on the PCA procedure, see for example PSU (2017) and Rencher (2012).

Additional information

Funding

This study is supported by the Research Grant Bank Indonesia [No. 22/29/PKS/BINS/2020] provided by The Bank Indonesia Institute in 2020.

Notes on contributors

Mohamad Dian Revindo

Mohamad Dian Revindo joined the Institute for Economic and Social Research, Universitas Indonesia (LPEM FEB UI) in 2009 and has been appointed as the head of Business Climate and Global Value Chain Research Group since 2017. His expertise and research interests include Small and Medium-sized Enterprises, Tourism, Local Economic Development, Microfinance, Industrial Organization, International Trade and International Business. In addition to research, he is a lecturer at the European Studies Program, Graduate School of Strategic and Global Studies, Universitas Indonesia, and a facilitator at LPEM FEB UI’s training of National Planner (FPP) and Regional Development Planning. He earned his Ph.D. in Economics from Lincoln University, New Zealand and a recipient of New Zealand-ASEAN Scholar Awards (2013–2017). He also holds a M.A. in European Studies from KU Leuven, Belgium (2008), a M.Sc. in Economics from KU Leuven, Belgium (2007) and a B.A. in Economics and Development Studies from University of Indonesia (2000).

Christopher Gan

Christopher Gan is a researcher and lecturer at the Faculty of Agribusiness and Commerce, Lincoln University, New Zealand. He has been intensively researching several areas of study, including commercial banking, micro-finance, rural finance, development economics, financial economics, and the Asian economy. He has also been actively involved in several editorial boards. Currently, he is serving as the Chief Editor in the Review of Applied Economics, and has been a board member of several journals including the International Journal of Bank Marketing, Commerce Journal International’s, among others. He earned his PhD in Economics from Louisiana State University. In addition, he also holds an M.S. degree in Finance from Indiana State University and a B.A. in Economics from the North Carolina University.

Sean Hambali

Sean Hambali joined the Institute for Economic and Social Research, Universitas Indonesia (LPEM FEB UI) at 2019 as a junior researcher. His expertise and research interests include Digital Economics, Rural Economic Development and Development Economics. Throughout his time in LPEM UI, he has engaged in various research projects with diverse clients – including government agencies, ministries and private players. In addition, he is also currently working at the World Bank as a Research Analyst. He holds a Bachelor in Economics from Universitas Indonesia (2018).