Strategic Orientations, Access to Finance, and SMEs Performance in Thailand: Data Screening and Preliminary Analysis

Main Article Content

Nifaosan Raden Ahmad
Mohd Noor Mohd Shariff
Mohammad Haroon Hafeez
Napitchya Cherdchom

Abstract

This study aimed to conduct a data screening and preliminary analysis about the effect of strategic orientations towards SMEs performance and the moderating effect of access to finance in Thailand’s gem and jewelry industry. Samples of 310 were selected from the population of 1,601 SMEs operating in Thailand’s gem and jewelry business using a systematic sampling technique to collect the data. In addition, data diagnostics were performed to meet the preliminary assumptions for further multivariate analysis, particularly an advanced Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis. Thus, the study carried out response rate, missing data analysis, non-response bias test, normality test, assessment of outliers, common method bias test, and multicollinearity test. Likewise, all the assessments were conducted through the IBM SPSS 20, G*Power 3.1, and SmartPLS 3.2.8 software. Conclusively, the data met the requirements for further multivariate analysis, but the normality test still needed to be met. Although, the normality assumption was not met, the non-normally distributed samples can be analyzed further since PLS-SEM works well with non-normal data distributions. This study contributes to the current literature as it will steer other researchers in conducting data screening and preliminary analysis.

Article Details

How to Cite
Raden Ahmad, N. ., Mohd Shariff, M. N. ., Hafeez, M. H., & Cherdchom, N. . (2024). Strategic Orientations, Access to Finance, and SMEs Performance in Thailand: Data Screening and Preliminary Analysis. Asia Social Issues, 17(6), e267964. https://doi.org/10.48048/asi.2024.267964
Section
Research Article

References

Acuna, E., & Rodriguez, C. (2004). The treatment of missing values and its effect on classifier accuracy (pp. 639-647). In Banks, D., McNorris, F. R., Arabie, P., & Gual, W. (Eds.). Classification, clustering, and data mining application: Studies in classification, data analysis, and knowledge organization. New York, USA: Springer- Verlag Berlin Heidelberg.

Adeboye, N. O., Fagoyinbo, I. S., & Olatayo, T. O. (2014). Estimation of the effect of multicollinearity on the standard error for regression coefficients. IOSR Journal of Mathematics, 10(4), 16-20.

Adomako, S., Danso, A., & Damoah, J. O. (2016). The moderating influence of financial literacy on the relationship between access to finance and firm growth in Ghana. Venture Capital, 18(1), 43-61.

Aminu, I. M., & Mohd Shariff, M. N. (2015). Influence of strategic orientation on SMEs access to finance in Nigeria. Asian Social Science, 11(4), 298-309.

Arora, R. U. (2014). Access to finance: An empirical analysis. European Journal of Development Research, 26(5). 798-814.

Baruch, Y. (1999). Response rate in academic studies: A comparative analysis. Human Relations, 52(4), 421-437.

Brennan, M. (1992). Techniques for improving mail survey response rates. Marketing Bulletin, 3(4), 24-37.

Charles, L., Joel, C., & Samwel, C. (2012). Market orientation and firm performance in the manufacturing sector in Kenya. European Journal of Business and Management, 4(10), 20-27.

Clottey, T. A., & Grawe, S. J. (2014). Non-response bias assessment in logistics survey research: Use fewer tests? International Journal of Physical Distribution & Logistics Management, 44(5), 412-426.

Clottey, T., & Benton, W. C. (2013). Guidelines for improving the power values of statistical tests for nonresponse bias assessment in OM research. Decision Sciences, 44(4), 797-812.

Cokluk, O., & Kayri, M. (2011). The effects of methods of imputation for missing values on the validity and reliability of scales. Educational Sciences: Theory & Practice, 11(1), 303-309.

Conway, J. M., & Lance, C. E. (2010). When reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25, 325-334.

Cousineau, D., & Chartier, S. (2010). Outliers detection and treatment: A review. International Journal of Psychological Research, 3(1), 58-67.

Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign environments. Strategic Management Journal, 10, 75-87.

Daoud, J. I. (2017). Multicollinearity and regression analysis. Journal of Physics: Conference Series, 949(1).

Das, K. R., & Imon, A. H. M. R. (2016). A brief review of tests for normality. American Journal of Theoretical and Applied Statistics, 5(1), 5-12.

Department of International Trade Promotion, (2018). Thailand’s gem and jewelry export performance (January – May, 2018). Bangkok, Thailand: DITP.

Dillman, D. A. (2007). Mail and internet survey: The tailored design method (2nd eds.). New Jersey: John Wiley & Sons.

Eggers, F., Kraus, S., Hughes, M., Laraway, S., & Snyeerski, S. (2013). Implications of customer and entrepreneurial orientations for SME growth. Management Decision, 51(3), 524-546.

Ernst, A. F., & Albers, C. J. (2017). Regression assumptions in clinical psychology research practice: A systematic review of common misconceptions. PeerJ, 16(5), e3323.

Farooq, R. (2016). Role of structural equation modeling in scale development. Journal of Advances in Management Research, 13(1), 75-91.

Favero, N., & Bullock, J. B. (2014). How (not) to solve the problem: An evolution of scholarly responses to common source bias. Journal of Public Administration Research and Theory, 25, 285-308.

Filzmoser, P. (2004). A multivariate outlier detection method (pp. 18-22). In Aivazian, S., Filzmoser, P., & Kharin, Y. (Eds.). In Proceedings of the 7th International Conference on Computer Data Analysis and Modeling. Minsk, Belarus: Belarusian State University.

Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2015). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192-3198.

Gem and Jewelry Institute of Thailand, (2018). Thailand aims to become the world’s gem and jewelry trading hub within 5 years. Bangkok, Thailand: GIT.

Hair, J. F. Jr., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). USA: SAGE Publications.

Hakala, H. (2010). Strategic orientations in management literature: Three approaches to understanding the interaction between market, technology, entrepreneurial and learning orientations. International Journal of Management Reviews, 13, 199-217.

Hakala, H. (2013). Entrepreneurial and learning orientations: Effects on growth and profitability in the software sector. Baltic Journal of Management, 8(1), 102-118.

Hinton, P. R., McMurray, L., & Brownlow, C. (2014). SPSS Explained (2nd eds.). United Kingdom: Routledge.

Jannoo, Z., Yap, B. W., Auchoybur, N., & Lazim, M. A. (2014). The effect of nonnormality on CB-SEM and PLS-SEM path estimates. International Journal of Mathematical, Physical and Quantum Engineering, 8(2), 285-291.

Johnson, D. M., & Shoulders, C. W. (2017). Power of statistical tests used to address nonresponse error in the Journal of Agricultural Education. Journal of Agricultural Education, 58(1), 300-312.

Kock, N. (2014). Single missing data imputation in PLS-SEM. Laredo, TX: Script Warp Systems.

Kock, N. (2016). Non-normality propagation among latent variables and indicators in PLS-SEM simulations. Journal of Modern Applied Statistical Methods, 15(1), 299-315.

Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580.

Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: The construct, research propositions, and managerial implications. Journal of Marketing, 54, 1-18.

Lidner, J. R., Murphy, T. H., & Briers, G. E. (2001). Handling nonresponse in social science research. Journal of Agricultural Education, 42(4), 43-53.

Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral and causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123-146.

Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. The Academy of Management Review, 21(1), 135-172.

MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542-555.

Marco, A. D., Mangano, G., & Zou, X-Y. (2012). Factors influencing the equity share of build-operate-transfer projects. Built Environment Project and Asset Management, 2(1), 70-85.

Martin, W. E., & Bridgmon, K. D. (2012). Quantitative and statistical research methods: From hypothesis to results. USA: Jossey-Bass.

Meade, A. W., Watson, A. M., & Kroustalis, C. M. (2007). Assessing common methods bias in organizational research. In Proceedings of the 22nd Annual Meeting of the Society for Industrial and Organizational Psychology. New York, USA.

Miller, D. (1983). The correlates of entrepreneurship in three types of firms. Management Science, 29(7), 770-791.

Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(4), 20-35.

Nithisathian, K., & Walsh, J. (2011). Comparative study between the Thai and Hong Kong fine gold jewelry export industries. Information Management and Business Review, 3(3), 139-147.

Office of Small and Medium Enterprises Promotion. (2018). SMEs white paper report on June, 2018. Bangkok, Thailand: OSMEP.

Osborne, J. W., & Overbay, A. (2004). The power of outliers (and why researchers should ALWAYS check for them). Practical Assessment, Research & Evaluation, 9(6).

Pongyeela, A. (2012). The decision making process of jewelry buyers in Thailand. Procedia Economics and Finance, 3, 188-192.

Raykov, T., & Marcoulides, G. A. (2008). An introduction to applied multivariate analysis. USA: Routledge.

Razali, M. N., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolgomorov-Smirnov, Liliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analysics, 2(1), 21-33.

Reio, T. G. (2007). Survey nonresponse bias in social science research. New Horizons in Adult Education and Human Resource Development, 21(1/2), 48-51.

Schwarz, A., Rizzuto, T., Carraher-Wolverton, C., Roldan, J. L., & Barrera-Barrera, R. (2017). Examining the impact and detection of the “Urban Legend” of common method bias. The Data Base for Advances in Information Systems, 48(1), 93-119.

Shamsudeen, K., Keat, O. Y., & Hassan, H. (2017). The moderating role of access to finance on the impact of entrepreneurial awareness on Nigerian SMEs’ performance. Journal of Business Management and Accounting, 7(1), 89-102.

Sinkula, J. M., Baker, W. E., & Noordewier, T. (1997). A framework for market-based organizational learning: Linking values, knowledge, and behavior. Academy of Marketing Science, 25(4), 305-318.

Tabachnik, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th eds.). USA: Pearson Education.

Tehseen, S., Ramayah, T., & Sajilan, S. (2017). Testing and controlling for common method variance: A review of available methods. Journal of Management Sciences, 4(2), 144-173.

Wu, S. I., & Lu, C. L. (2012). The relationship between CRM, RM, and business performance: A study of the hotel industry in Taiwan. International Journal of Hospitality Management, 31(1), 276-285.

Zainuri, N. A., Jemain, A. A., & Muda, N. (2015). A comparison of various imputation methods for missing values in Air Quality Data. Sains Malaysiana, 44(3), 449-456.

Zhang, Z. (2016). Missing data imputation: Focusing on single imputation. Annals of Translational Medicine, 4(1).