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This study primarily aims to analyse stakeholder management challenges and how these emerge in the stakeholder landscape in a large hospital project. From this analysis, the authors aim to identify the implications that stakeholder management has on value creation in a hospital project.

The research method is qualitative. Empirical data were collected in three cycles: project internal documentation, thematic interviews and survey. The literature related to hospital projects, stakeholder analysis and management, stakeholder salience and landscape is summarised, informing the qualitative design of the study.

The authors noted the importance of project-specific stakeholder identification, salience analysis and landscape description. The regulatory, formal and contractual stakeholders give an over-simplistic picture on stakeholder map. The operative stakeholder map and landscape describe the complexity, uncertainty, dynamism and institutional context inducing the challenges for the stakeholder management. There is an evident potential of utilising the stakeholder landscape and its elements in the resulting collaborative value creation in hospital projects. Multiple and changing stakeholders with differing expectations are an important opportunity to improve the value creation process.

Stakeholder management has recently attracted much attention in the industrial project setting. This research attempts to identify the operative stakeholder landscape in a large hospital project, not to mention its impact on value creation. This study offers a framework that can help academics and project management practitioners tackle the challenges amongst project stakeholders.

Using a discrete choice experiment (DCE), this study aims to better understand the job preference of postgraduate students studying at the Kwame Nkrumah University of Science and Technology-Institute of Distance Learning, Ghana and also rank the attributes of a job they deem important.

The research adopted a positivist epistemological design contextualised within a deductive approach and case study strategy. Primary survey data was collected from a stratified random sample of 128 postgraduate students with multi-sectorial career prospects. Sample students were subjected to a DCE in which their stated preferences were collected using closed-ended questionnaires with 28 pairs of hypothetical job profiles. Respondents’ preferences from the DCE data were then modelled using the conditional logit.

The research reveals that: salary in the range GHC 2,800.00 to GHC 3,400.00 ($1 = GHS 5.3); supportive management; very challenging jobs; and jobs located in the city were the top attributes that were significant and had the most impact in increasing the utility of selecting a particular job. Interestingly, jobs with no extra hours workload were not significant hence, had a negative impact upon student preferences.

This novel research is the first to use a DCE to better elicit preference and trade-offs of postgraduate students in a developing country towards varying job characteristics that have an impact on their future employment decisions. Knowledge advancements made provide invaluable insight to employers and policymakers on the key criteria that should be implemented to retain the best candidate.

Enormous amount of biomedical wastes (BMW) produced everyday across the world. Management of BMW depends on adherence to protocol. BMW management at generation point, definitely, depends upon the awareness, attitudes and practises of health-care staff, the purpose of this study will assess the awareness, attitude and practise regarding different aspects of BMW.

An observational with appropriate checklists, and a cross-sectional study, involving questionnaires, was conducted during 7-24 January 2016. The existing system of BMW management, funds, resources, etc., knowledge, attitude and practises about BMW were assessed amongst 273 health-care workers in selected public health-care institutes of Karnataka.

Of 273 study participants, majority (54%) of them have not received any training pertaining to BMW. The results showed a poor level of knowledge and awareness of BMW management amongst health-care personnel. Merely, 43% of the participants correctly knew the categorization of BMW and its disposal in proper colour-coded bins/bags. Awareness is very poor amongst the lower age group, male participants, lab-technicians/pharmacists and supporting staff. Doctors were good at theoretical knowledge such as rules, legislation and public-health importance of BMW management than the practical aspects such as categorization and colour-coding. Further, the attitude of health-care staff is favourable about BMW. Immunization for hepatitis-B was very poor amongst waste handlers (43%).

As the awareness and practise regarding BMW management were poor across different health-care staff there is a need to conduct periodic training and regular monitoring with special focus on the proper use of personal protective equipment. Further, precautionary immunization should be provided, especially waste handlers and sanitary workers.

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.