Harold Siow Song Teng, Gurpreet Singh Bhatia and Sajid Anwar
The purpose of this paper is to examine the potential success and failure of small‐ and medium‐sized enterprises (SMEs).
Abstract
Purpose
The purpose of this paper is to examine the potential success and failure of small‐ and medium‐sized enterprises (SMEs).
Design/methodology/approach
An exploratory business success versus failure (S/F) prediction model is introduced, modeled after the Lussier prediction model, using data from Singapore. Using logistic regression analysis, it is found that the Lussier model (p=0.057) and the exploratory model (p=0.047) are significant predictors of business success and failure.
Findings
The Lussier model accurately predicted 85.6 percent of the surveyed firms and explained 25 percent of the variance of contributing factors to S/F, and the exploratory model explained 86.3 and 38 percent of the same, respectively. SMEs regard the top four most important factors contributing to their business S/F as: employment, training, and the retainment of high‐quality staff members; prevalence of good products, services, and optimum timing in introducing these in the marketplace; excellent relationships with customers and availability of top managers with good leadership qualities.
Research limitations/implications
It is surprising that while pursuing their respective business activities, the SMEs surveyed in this study regarded government policy and the availability of business finance, amongst other factors, of lesser importance compared to the above‐mentioned four broad variables.
Originality/value
This paper establishes benchmarks that could be helpful to decision makers for improving future business‐related policy formulation and research. Business leaders could pursue their goal of ensuring business successes with better personnel management and leadership training by, for example, taking more business management and leadership courses and personal development. Government public policy makers and others could utilize such a model to assess a firm's potential for success so that society could benefit via the allocation of limited resources toward higher potential firms.
Details
Keywords
The purpose of this paper is to highlight the fact that a common universal qualitative model of measurement is lacking in global productivity analysis. International quantitative…
Abstract
Purpose
The purpose of this paper is to highlight the fact that a common universal qualitative model of measurement is lacking in global productivity analysis. International quantitative comparisons of country macro-level measurements of productivity have been available in the world for decades. However, there has been no consensus on what exactly constitute the indicators and measures of productivity with a focus on quality.
Design/methodology/approach
Through literature review and analysis, a new conceptual qualitative productivity measurement model is being suggested. This model could become the basis for future research undertakings in productivity studies.
Findings
This paper finds that there are differences in the definitions of what constitute productivity at the global level and what measurements could be considered to make productivity studies more quantitative as well as qualitative at the same time.
Originality/value
This paper aims to bring about further discussions for a general agreement on what factors constitute a more well-balanced qualitative as well as quantitative productivity measurement model.