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The purpose of this study is to implement lean six sigma (LSS) methodology to improve the admission process in a higher education institute (HEI).

In this study, case study research methodology is adopted and implemented through an LSS define-measure-analyze-improve-control (DMAIC) framework.

The preliminary investigation showed that the completion of the whole admission process of a new student takes an average of 88 min, which is equivalent to a sigma level of about 0.71 based on the targeted admission cycle time of 60 min. The implementation of the proposed LSS approach increased the sigma level from 0.71 to 2.57, which indicates a reduction in the mean admission cycle time by around 55%. This substantial improvement is expected not only to provide an efficient admission process but also to enhance the satisfaction of students and employees and increase the reputation of the HEI to a significant level.

In this study, the sample size used in the analysis is considered small. In addition, the effectiveness of the proposed approach is investigated using a discrete event simulation with a single-case study, which may limit generalization of the results. However, this study can provide useful guidance for further research for the generalization of the results to wider scopes in terms of different sectors of HEIs and geographical locations.

This study uses several statistical process control tools and techniques through a LSS DMAIC framework to identify and element the root causes of the long admission cycle time at a HEI. The approach followed, and the lessons learned, as documented in the study, can be of a great benefit in improving different sectors of HEIs.

This study is one of the few attempts to implement LSS in HEIs to improve the administrative process so that better-quality services can be provided to customers, such as students and guardians. The project is implemented by a group of undergraduate students as a part of their senior design project, which paves the way for involving students in future LSS projects in HEIs. This study is expected to help to improve understanding of how LSS methodology can be implemented in solving quality-related problems in HEIs and to offer valuable insights for both academics and practitioners.

The purpose of this paper is to develop a framework that illustrates the role of Lean Six Sigma (LSS) in creating organisational innovation climate by investigating the relationship between LSS’s intangible impacts and organisational innovation climate factors.

A self-administrated survey questionnaire was distributed among 145 public sector officials to get their opinions on the relationship between various observable elements of LSS’s intangible impacts and organisational innovation climate factors, where a response rate of 73.8% was achieved. The collected data were demographically, descriptively and statistically analysed. Accordingly, a house-of-pillars-based framework that illustrates the role of LSS’s intangible impacts in creating innovation climate in an organisation was developed.

Results from this study indicated that LSS’s intangible impacts on organisational structure and hierarchy, culture, change adaptability, utilisation of staff and staff’s behavioural aspects are positively related to many of organisational innovation climate factors such as trust and openness, challenge and involvement, support for ideas and freedom and autonomy.

The findings of this study are based on the data collected from public sector organisations in the UAE and are supported by relevant literature. However, this study can provide useful guidance for further research for the generalisation of the results to wider scopes in terms of sectors and geographical domains.

The findings of this study will provide UAE public sector officials with a clear roadmap on how to use LSS for promoting innovation and fostering its implementation in practice. This study will also encourage professionals in public sectors to integrate LSS into their innovation strategies to enhance organisational innovativeness and improve service quality.

It is one of the first studies that explores LSS’s intangible impacts and assesses their relationship with organisational innovation climate factors. Hence, this study offers valuable insights for both academics and practitioners and is expected to lay a foundation for a better understanding of how LSS’s intangible impacts can be used in creating organisational innovation climate.

This paper aims to investigate the relationship between the intangible impacts of Lean Six Sigma (LSS) and organisational innovation climate factors and proposes a conceptual model to link them. This paper ultimately aims to extend the range of LSS application by proposing LSS as a tool for fostering organisational innovation.

The paper followed a qualitative research approach to identify, analyse and categorize the intangible impacts of LSS by reviewing previous literature on its application and conducting in-depth interviews with its experts. Then, a detailed description of organisational innovation climate was provided to highlight its main factors. Finally, a conceptual model was developed to illustrate the relationships among the collected information.

LSS was found to have many intangible impacts categorized as organisational or individual related. Organisational innovation climate is determined by a number of factors that were found to be positively influenced by many of LSS's intangible impacts. Thus, a number of propositions between LSS's intangible impacts and organisational innovation climate factors were proposed, as illustrated by a conceptual model.

Studying the relationship between LSS and innovation by considering LSS's intangible impacts and linking them to organisational innovation climate factors is a relatively new approach that makes the contribution of this research valuable and significant to academics and professionals.

Despite the increasing number of studies investigating environmentally sustainable practices in different sectors, no research exists on the issues related to the success factors for implementing environmentally sustainable practices in the utilities sector. To partially fill this research gap, the purpose of this study is to empirically examine these success factors in a public utilities organization in the United Arab Emirates.

An integrated interpretive structural modeling and fuzzy cross-impact matrix multiplication applied to classification approach was implemented to identify the critical success factors (CSFs) and to model and analyze the relationships among them.

Thirteen CSFs were identified and the relationships among them were represented by a seven-level hierarchical graphical model, and six CSFs were identified as drivers of success: government policies, regulations and environmental awareness programs; organization sustainability strategies; top management commitment; organizational capabilities; social and environmental responsibility; and eco-knowledge.

This is first kind of study to identify CSFs for implementing environmentally sustainable practices in the utilities sector. The results could guide government policymakers and decision-makers in utilities organizations that are interested in implementing environmentally sustainable practices.

This paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.

The critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.

For a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.

Only three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.

The proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.

This research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions.

The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations.

A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works.

The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity.

The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.

The purpose of this paper is to identify, present and categorise the main requirements, challenges and impacts of Lean Six Sigma (LSS) applications. Emphasis is given to the soft impacts of LSS applications, which are intangible in nature and difficult to quantify and measure, highlighting the most frequently cited ones.

A qualitative synthesis of the studies using the narrative synthesis approach is adopted to descriptively summarise and categorise the requirements, challenges and impacts of LSS applications. The studies were searched by using the following keywords: “LSS applications,” “LSS requirements,” “LSS challenges” and “LSS impacts” in almost all major electronic databases such as Emerald, Taylor and Francis, ScienceDirect and Wiley. A total of 116 articles published between 2007 and 2017 in 41 academic journals were collected and reviewed. Consideration was also given to a number of substantial publications in 2006, 2018 and 2019.

In addition to its process efficiency and financial impacts, LSS was found to have another impact category related to individual and organisational behaviours. Management commitment, training and organisational culture were concluded to be amongst the most important and required categories for successful LSS applications. It was also found that the lack of awareness of LSS tools and benefits and the lack of change management and resistance to change were amongst the most cited categories of implementation challenges.

The studies published between 2007 and 2017 are mainly considered in this paper. It is believed that 10-year publication period considered in this research is sufficient to study the evolution, benefits, limitations and future trends of a particular research topic. However, the exclusion criteria used in the search process with respect to the articles’ year of publication and search terms and keywords may limit the generalisation of the research findings. In addition, the qualitative nature of this research study and the lack of empirical data to support its findings is another limitation that future research should consider.

This research paper may serve as a valuable source of information for LSS researchers as it will provide them with useful and new insights and directions for further research in LSS. It will also increase the awareness of LSS practitioners about the kind of impact LSS has, and therefore, achieve a better utilisation of its tools by ensuring availability of application requirements and overcoming application challenges.

This study differs from previous research studies as it focusses attention on the soft impacts of LSS applications and highlights them. The study identifies and prioritises LSS application impacts, requirements and challenges. The study on these aspects was found to be limited and lacking in previous research studies.

This study explores the role of leadership in organisational innovation by reviewing several publications that discuss the relationship between various leadership styles and innovation.

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.

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.

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.

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.

The exponentially weighted moving average (EWMA) control charts are widely used in industries for monitoring small and moderate process shifts. The purpose of this paper is to develop an algorithm for the optimization design of the EWMA chart (known as MD‐EWMA chart).

The design algorithm adjusts the sample size n, sampling interval h, lower and upper control limits LCL and UCL, and the EWMA weight factor λ of the chart in an optimal manner in order to minimize the mean number of defective units (denoted as MD) produced per out‐of‐control case. The probability distribution of the random process shift (e.g. mean shift δ) is taken into account that may be modeled by a Rayleigh distribution based on the sample data acquired during the operation of the control chart.

The results of the comparison studies and an example show that the proposed MD‐EWMA chart is significantly superior to the Shewhart‐type MD‐X¯ chart and the other EWMA charts in terms of the overall mean defective MD.

As the economic charts, the proposed MD‐EWMA chart aims at reducing the quality cost. But the design of this chart only requires limited number of specifications that can be easily determined. Consequently, the MD chart provides the control chart designers with an alternative choice between the statistical design and the economic design. Specifically, the mean shift δ is handled as a random variable by using a parametric or nonparametric approach to manipulate the sample data of δ acquired during the operation of the control chart. The MD counts the number of defective units produced per out of control case; so the design of control chart based on MD is more realistic from a practical viewpoint. In addition, the design of MD‐EWMA chart combines forecasting with controlling methods of quality management.

This paper aims to assess the impact of the training program on fish traders in building awareness about formalin abuse in food items.

Primary data was collected from the fish traders in Bangladesh by using simple random sampling technique. Binary logistic regression was used to assess the opinions of the fish traders about training in building awareness of formalin abuse.

This study showed that the training of the fish traders played a positive role in improving their awareness level of formalin abuse.

Enhancement of both training and educational support could be an effective strategy in preventing formalin abuse in food.

This study helps in assessing the opinions of the fish traders about the effectiveness of the training programs in building awareness of formalin abuse.