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Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.

Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.

An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.

To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

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.