<p>In the last three decades, complexity theory has gained a lot of importance in several scientific disciplines like astronomy, geology, chemistry etc. It has slowly extended its usage in the field of project management. While trying to understand the managerial demands of modern day projects and the different situations faced in projects, the term ‘complexity’ is progressively becoming a benchmark term. In the recent past some of the challenging projects that have been completed are the Heathrow Terminal 5 and the construction of venues for the Beijing Olympics. But can we call these projects complex?It is probably too simplistic to classify projects as complex or non-complex. What is particularly important is to identify the source of the complexity, the level and also the implications of the complexity. Several academicians have studied the different dimensions and established different classifications of complexity. These are put together into models of complexity.But is this classification well-grounded in reality? This is what we aim to explore through this research. The specific questions that we wish to explore by conducting this research are:</p><ul><li>How does the understanding of project complexity in actuality conform to the theoretical complexity models?</li></ul><p>In an effort to answer the primary question, our study will also throw some light on factors of complexity across different sectors. We hope that this distinction will pave way for further research within these sectors. This now brings us to our sub-question:- How do the factors that contribute to complexity compare across different sectors?At the outset of this research, the literature on complexity was reviewed. An attempt was made to understand what complexity means with a focus on the field of project management.It was observed that there is a new wave of thinking in this field and a camp which believes that regular project management tools and techniques cannot be used for complex projects.</p><p>This has drawn several academicians to generate models of complexity based on various factors. In this research we have focused on some important models like that of Turner and Cochrane, Ralph Stacey, Terry Williams, Kahane and Remington and Pollack. We have tried to see if any of these models fit in with how practitioners understand complexity.To find out how practitioners comprehend complexity, we followed a grounded theory approach and also used quantitative methods to supplement the results in accordance in a mixed methodology. Semi-structured interviews were carried out with nine project managers from different sectors and different  geographical locations. The interviews were analyzed and the data was broken down to different categories referred to as open coding where labelling was done. This was followed by Axial coding where we describe the properties and build relations between these categories. The final stage is selective coding where the emerged theory is integrated and refined.Quantitative data was collected through a short questionnaire which listed out some factors which could cause or lead to complexity in projects. A total of 29 responses were obtained for the questionnaires. By analyzing this data we were able to determine the factors that project managers thought caused complexity in projects. A new dimension was also added by analyzing it sector-wise. Since we collected data from two different sources, via interviews and through questionnaires, it gave us the opportunity to triangulate the findings. Wesincerely hope that this piece of work will pave way for future research on similar areas like models of complexity and perception of complexity in project management</p>

In the last three decades, complexity theory has gained a lot of importance in several scientific disciplines like astronomy, geology, chemistry etc. It has slowly extended its usage in the field of project management. While trying to understand the managerial demands of modern day projects and the different situations faced in projects, the term ‘complexity’ is progressively becoming a benchmark term. In the recent past some of the challenging projects that have been completed are the Heathrow Terminal 5 and the construction of venues for the Beijing Olympics. But can we call these projects complex?It is probably too simplistic to classify projects as complex or non-complex. What is particularly important is to identify the source of the complexity, the level and also the implications of the complexity. Several academicians have studied the different dimensions and established different classifications of complexity. These are put together into models of complexity.But is this classification well-grounded in reality? This is what we aim to explore through this research. The specific questions that we wish to explore by conducting this research are: How does the understanding of project complexity in actuality conform to the theoretical complexity models? In an effort to answer the primary question, our study will also throw some light on factors of complexity across different sectors. We hope that this distinction will pave way for further research within these sectors. This now brings us to our sub-question:- How do the factors that contribute to complexity compare across different sectors?At the outset of this research, the literature on complexity was reviewed. An attempt was made to understand what complexity means with a focus on the field of project management.It was observed that there is a new wave of thinking in this field and a camp which believes that regular project management tools and techniques cannot be used for complex projects. This has drawn several academicians to generate models of complexity based on various factors. In this research we have focused on some important models like that of Turner and Cochrane, Ralph Stacey, Terry Williams, Kahane and Remington and Pollack. We have tried to see if any of these models fit in with how practitioners understand complexity.To find out how practitioners comprehend complexity, we followed a grounded theory approach and also used quantitative methods to supplement the results in accordance in a mixed methodology. Semi-structured interviews were carried out with nine project managers from different sectors and different  geographical locations. The interviews were analyzed and the data was broken down to different categories referred to as open coding where labelling was done. This was followed by Axial coding where we describe the properties and build relations between these categories. The final stage is selective coding where the emerged theory is integrated and refined.Quantitative data was collected through a short questionnaire which listed out some factors which could cause or lead to complexity in projects. A total of 29 responses were obtained for the questionnaires. By analyzing this data we were able to determine the factors that project managers thought caused complexity in projects. A new dimension was also added by analyzing it sector-wise. Since we collected data from two different sources, via interviews and through questionnaires, it gave us the opportunity to triangulate the findings. Wesincerely hope that this piece of work will pave way for future research on similar areas like models of complexity and perception of complexity in project management

The purpose of this study was to examine whether there was a correlation between employees’ perception of completed organizational change projects and their perceived job satisfaction. In order to examine the purpose of the study and hence the research question, a quantitative research with cross- sectional design, in the form of a web- based survey was executed.  To examine prevalent correlations collected data was analyzed using a multiple regression analysis was conducted. The result indicates a significant correlation between employees’ perception of completed organizational change projects and perceived job satisfaction, where employee’s perception predicts job satisfaction to 41%. The variable with the strongest unique association with job satisfaction is valence, which generated a Beta coefficient of 0,37.