Search results

In developing countries, numerous small- and medium-sized enterprises (SMEs) must innovate because of their scarce resources. This study aims to address the ambidextrous innovation (radical and incremental) associated with firm performance on the SMEs and investigate the moderating effect of environmental factors on the relationship between technological innovation and firm performance.

The authors formulate a path model with the variables to investigate the impacts of the two different innovation strategies and their joint effects on firm performance. Meanwhile, they hypothesized that external environmental factors – market dynamism, labour availability, business cost and competitive hostility – moderate the association of radical and incremental innovations with firm performance. The validity of the proposed model was evaluated using a structural equation modelling approach. Confirmatory factor analysis was used to evaluate the convergent validity of the constructs.

The authors find that positive association between radical innovation and firm performance; it shows that the radical innovation strategies are positively related to firm performance in SMEs. They also find that the relationship between radical innovation and firm performance has moderated by environmental factors. Second, they find that the incremental innovation strategies have a negative impact to firm performance, and the relationship between incremental innovation and firm performance has no moderated by environmental factors.

This paper suggests that the managers of SMEs must involve in technological innovation, and offer fourth main implications above. In particular, the authors forewarn SMEs’ managers of the necessity of generating that the relationship between radical innovation and firm performance has moderated by environmental factors, there are approaches fourth items around.

This study highlights the crucial importance of the mediating role of environmental dynamism when examining the relationship between ambidexterity (radical and incremental innovations) with firm performance; firms can perceive environmental factors and develop technological innovation strategies to enhance business performance.

The present paper aims to present the results of a simulation study on the behavior of the four 95 percent bootstrap confidence intervals for estimating C_pk when collected data are from a multiple streams process.

A computer simulation study is developed to present the behavior of four 95 percent bootstrap confidence intervals, i.e. standard bootstrap (SB), percentile bootstrap (PB), biased‐corrected percentile bootstrap (BCPB), and biased‐corrected and accelerated (BCa) bootstrap for estimating the capability index C_pk of a multiple streams process. An analysis of variance using two factorial and three‐stage nested designs is applied for experimental planning and data analysis.

For multiple process streams, the relationship between the true value of C_pk and the required sample size for effective experiment is presented. Based on the simulation study, the two‐stream process always gives a higher coverage percentage of bootstrap confidence interval than the four‐stream process. Meanwhile, BCPB and BCa intervals lead to better coverage percentage than SB and PB intervals.

Since a large number of process streams decreases the coverage percentage of the bootstrap confidence interval, it may be inappropriate to use the bootstrap method for constructing the confidence interval of a process capability index as the number of process streams is large.

The present paper is the first work to explore the behavior of bootstrap confidence intervals for estimating the capability index C_pk of a multiple streams process. It is concluded that the number of process streams definitively affects the performance of bootstrap methods.

The purpose of this paper is to examine the inter-relations among the US stock indices.

Data of nine US stock indices spanning a period of sixteen years (2000-2015) are employed for this purpose. Asymmetries are examined via an error correction model. Non-linear inter-relations are researched via Breitung’s nonlinear cointegration, a M-G nonlinear causality model, shocks to the forecast error variance, a shock spillover index and an asymmetric VAR-GARCH (VAR-ABEKK) approach.

The inter-relations are significant. The results are robust across all types of inter-relations. They are highest in the Lehman Brothers sub-period. Higher stability after the EU debt crisis, enhances independence and growth for the US stock indices.

To the best of the knowledge, this is the first study to examine the inter-relations of US stock indices. Most studies on inter-relations concentrate on the portfolio analysis to reveal diversification benefits among various asset markets internationally. Hence this study contributes to this literature on the inter-relations of a specific asset market (stock), and in a specific nation (USA). The evident inter-relations support the notion of diversification benefits in the US stock markets.