Purpose: This study explores the role of leadership in organisational innovation by reviewing several publications that discuss the relationship between various leadership styles and innovation.Design/methodology/approach: The study followed a descriptive research methodology by reviewing 64 journal articles on the relationship between various leadership styles and innovation. The articles were analysed descriptively and then reviewed based on the leadership style it discusses to derive meaningful findings on the relationship between leadership and innovation.Findings: Various leadership styles had a positive impact on organisational innovation either directly or indirectly, by influencing the organisational climate, employees' and leaders' behaviours or other organisational variables such as learning and knowledge sharing. Some leadership styles had both direct and indirect impacts on organisational innovation.Research limitations/implications: This study collected journal articles published in almost all major electronic databases such as Emerald, ScienceDirect, Taylor & Francis and Scopus. However, the review is limited to journal articles in which the title, abstract or author-specified keywords contain the search terms “leadership” and “innovation,” and published between 2000 and 2019. Therefore, this review may miss some relevant research insights mentioned in the literature that discussed innovation or leadership separately not combined.Originality/value: This study contributes to the existing body of research on leadership and innovation by extensively discussing the role of various leadership styles in determining organisational innovation. The analysis reveals that prior studies had many limitations and focused on specific leadership styles only. The study goes a step further by explaining how the leadership and innovation aspects are related, and classifying various leadership styles according to their impact on organisational innovation being direct, indirect or both.

(2004). Optimization design of control charts based on Taguchi's loss function and random process shifts. International Journal of Production Research: Vol. 42, No. 2, pp. 379-390. doi: 10.1081/00207540310001614169

The purpose of this study is to investigate the impact of implementing the International Organisation for Standardisation asset management standard (ISO 55000) on organisational performance. In particular, does following the ISO 55000 requirements and recommendations affect organisational performance? This study investigates this issue by identifying relevant asset management key performance indicators (KPIs) through a comprehensive literature review and classifying these KPIs using the balanced-scorecard-framework. Then, the KPIs were validated by expert opinions through a questionnaire and non-parametric hypothesis testing. Finally, using the relevant KPIs, this study assesses the impact of ISO 55000 with a set of ISO 55000-certified companies in the United Arab Emirates. Hypothesis testing on the difference between the status of each KPI before and after ISO 55000 implementation used linguistic assessment and a sign test for two non-parametric dependent samples. According to industry experts, increasing market share is not a relevant KPI in asset management. However, ISO 55000 has a positive effect on all the identified perspectives (financial, customer, business processes, and learning and growth), indicating that organisations adopting ISO 55000 International Standard certification will be able to achieve better performance from the effective and efficient management of their assets. Consequently, investing in such systems is valuable.

This study proposes and follows a specific and systematic framework for implementing Lean Six Sigma (LSS) methodology in a telecom company in order to improve customer satisfaction by minimizing the company’s response time to customer requirements. The goal of this study was achieved by utilizing several LSS tools under five phases of the DMAIC methodology. Unlike previous studies in the telecom sector that used only qualitative method, in this study, both qualitative and quantitative methods were utilized to draw meaningful conclusions. As a result of the implementation of the LSS methodology, the average order fulfilment lead time for sales orders (SO) and value-added service (VAS) orders was reduced from 10.3 to 5.9 days and from 1.5 to 0.5 days, respectively. The reduction in lead time resulted in an increase in the sigma level for SO and VAS orders from 0.44 to 1.26 and from 0.73 to 2.66, respectively. These improvements were expected to lead to a financial benefit in savings of over $600,000 per year in operational costs, enhancements to customer experience and an increase in revenue generating opportunities. Moreover, this article enriches the existing literature on the application of LSS concept in the service industry, and helps the company to speed up the response to customer requirements.

Fuzzy Monte Carlo Simulation (FMCS) uses both the probability density function (pdf) and possibility distributions (e.g., fuzzy numbers) to model the uncertainty/imprecision associated with the input parameters and, then, to simulate the uncertainty/imprecision associated with the output parameters. A probability–possibility transformation is needed to transfer the information of a fuzzy number into its equivalent pdf, while performing the simulation. This study deals with an approach of FMCS that uses a point-cloud-based probability–possibility transformation. Let x(t), t = 0,1,…, n, be a set of points that represents some random states of an uncertain/imprecise quantity. The collection of points (x(t), x(t+i)), t = 0,…, n–i, i∈ {1,2,…} is called point-cloud, providing a visual/computational representation of variability, modality, and ranges associated with the quantity. This study identifies the pdf and possibility distribution (fuzzy number) underlying a given point-cloud. Using these distributions, the relationships between the triangular fuzzy number and unimodal pdf (normal/uniform distributions) are identified. Two numerical examples are described elucidating the effectiveness of the proposed transformation. The first example deals with the issue of monitoring a FMCS process. The other example deals with the issue of making a decision by using FMCS.