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PurposeThe purpose of this study is to examine the perceptions of Malaysian and Bangladeshi retail small- and medium-sized enterprise (SME) business owners on the key elements of business growth.Design/methodology/approachThe construct measurements have all been taken from previous researches. The data were gathered from retail SMEs in Malaysia and Bangladesh in order to evaluate entrepreneurs' perception towards the essential elements of a business performance. Structural equation modeling (SEM) with PLS-technique, specifically Smart-PLS Version 3.2.4, was used to accomplish the study's objectives and analyze the measurements, as well as the structural model.FindingsAccording to the findings, Malaysian and Bangladeshi SMEs have different perspectives toward the dimensions of their business performance. For example, Malaysian retail SME owners consider business growth and financial results to be the most important aspects of their success. Retailers consider financial performance to be less critical than non-financial performance when it comes to their business's success. Owners of Bangladeshi retail SMEs, on the other hand, see efficiency relative to competition, and that non-financial performance is the key component to achieving business success. In the sense of Bangladeshi SMEs, market development and financial results are seen as less significant in attaining success.Research limitations/implicationsSince this research was only conducted in Malaysia and Bangladesh, it did not cover a large number of countries. The sample size was limited; therefore, the findings of this study cannot be applied to the entire population of Malaysian and Bangladeshi retail SMEs due to the non-probability sampling technique.Practical implicationsThe findings of this study show that entrepreneurs or business owners in the retail sector in Malaysian and Bangladeshi SMEs view the attributes of their business performance differently.Originality/valueThis study adds to the rising context of entrepreneurship by examining SME owners' perception of main business performance dimensions in the scope of Asian retail SMEs.

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Background Individual-patient data meta-analysis (IPD-MA) is an increasingly popular approach because of its analytical benefits. IPD-MA of observational studies must overcome the problem of confounding, otherwise biased estimates of treatment effect may be obtained. One approach to reducing confounding bias could be the use of propensity score matching (PSM). IPD-MA can be considered as two-stage clustered data (patients within studies) and propensity score matching can be implemented within studies, across studies, and combining both. Methods This article focuses on implementation of four PSM-based approaches for the analysis of data structure that exploit IPD-MA in two ways: (i) estimation of propensity score model using single-level or random-effects logistic regression; and (ii) matching of propensity scores (PS) across studies, within studies or preferential-within studies. We investigated the performance of these approaches through a simulation study, which considers an IPD-MA that examined the success of different treatments for multidrug-resistant tuberculosis (MDR-TB). The simulation parameters were varied according to three treatment prevalences (according to studies, 50% and 30%), three levels of heterogeneity between studies (low, moderate and high) and three levels of pooled odds ratio (1, 1.5, 3). Results All approaches showed greater biases at the higher levels of heterogeneity regardless of the choices of treatment prevalences. However, matching of propensity scores using within-study and preferential-within study reported better performance compared to matching across studies when treatment prevalence varied across-studies. For fixed prevalences, a random-effect propensity score model to estimate propensity scores followed by matching of propensity scores across-studies achieved lower biases compared to other PSM-based approaches. Conclusions Propensity score matching has wide application in health research while only limited literature is available on the implementation of PSM methods in IPD-MA, and until now methodological performance of PSM methods have not been examined. We believe, this work offers an intuition to the applied researcher for the choice of the PSM-based approaches.