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Project complexity has been comprehensively investigated over the last two decades, resulting in many descriptive frameworks and models. The common layout is a multidimensional construct. While the perception of the complexity of projects is essential for a managerial approach, only scant research has been conducted into how practitioners perceive project complexity. The purpose of the paper is to fill this gap.

This paper is a quantitative study based on a large survey among managers of projects with more than 1,000 participants. The questionnaire is designed based on a review of research literature on project complexity.

The findings indicate that practitioners' mental models are concentrated on only a few dimensions of the many found in descriptive models. Further, the findings indicate that the mental models are much influenced by the project role of the perceiver and less so by the type of project and sector.

This paper discusses the differentiation of concepts of perceived project complexity and provides a framework for a survey of the topic. The contribution of the paper is an increased understanding of practitioners' perceptions of project complexity as a concept very different from the descriptive frameworks that have been the focal point for research in project complexity thus far. The project complexity might be in the eye of the beholder; however, the findings indicate that the eyes are very much influenced by the project role of the beholder.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

The paper aims to provide methodological support for hybrid project management, in which the discipline of predictive methodologies combines with the flexibility of adaptive ones. Specifically, the paper explores the extent complexity and volatility dimensions of organisational problems inform choices of PM methodologies both theoretically and in current practice, as a first step towards better methodological support for hybridisation.

The paper takes a mixed method approach, including both secondary research and primary research with practitioners. Primary research consists of a small scale survey (n = 31) followed by semi-structured interviews, with findings triangulated against secondary evidence.

The paper provides empirical insights on how complexity and volatility of organisational problems can inform hybrid project management practices. Specifically, it suggests a mapping between volatility and complexity dimensions and predictive and adaptive risk controls as a first step towards the systematisation of hybrid combinations in projects.

Due to the small participant sample, the research results may lack generalisability.

The paper includes implications for the development of methodological support for setting up hybrid projects in practice.

The paper addresses a gap acknowledged both in the literature and by practitioners.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

The literature on software project management is extended into the broader domain of large‐scale IS management by studying enterprise‐wide system upgrade projects. In particular; examines the role that the intervention of project management practices (formal project methodologies and outsourcing) play in large and/or complex IS projects, which result in good project performance.

A survey instrument was completed by 449 information systems managers about a specific upgrade project. The primary analytical approach used was structural equation modeling (SEM).

It was found that neither project complexity nor project size are good indicators of meeting a project's target date. Large projects that adopted formal project management practices were more probable to meet the project target date. Projects with a high degree of complexity which involved outsourcing and adopted formal project management practices, were more likely to meet the project target date.

Clearly, the message to managers of IS projects is to establish a project methodology, especially in large, enterprise‐wide projects, and when some degree of outsourcing is required.

Future research should consider additional measures of performance such as cost, end‐user satisfaction and business value.

Much had been written in the literature about how large, complex IT projects have high failure rates. Our study provides conclusive evidence that, the greater the degree of methodology implementation, the greater the chance for meeting the project's target date. Prior to this research, this had not been explicitly shown in the research literature.

Project manager’s competency is crucial in the construction sector for the successful completion of projects, particularly in the case of developing countries like Nepal. Therefore, it is very essential to select competent project managers by finding the competency factors required by them. Hence, this study aims to identify the characteristics of competent project managers by expert opinion method and to evaluate their competency level by a questionnaire survey to develop a prediction model using a supervised machine learning approach via Waikato Environment for Knowledge Analysis (WEKA), a machine learning tool which predicts Project manager’s performance as “Higher than expected,” “Expected” or “Lower than expected” for the medium complexity construction projects of Nepal (from US$200,000 up to US$10M).

The data collection procedure for this research is based on an expert opinion method and survey. Expert opinion method is conducted to find the characteristics of a competent project manager by validating the top 15 competency factors based on literature review. The survey is conducted with the top management to assess their project manager’s competency level. Both qualitative and quantitative approaches are used to collect data for classification and prediction in WEKA, a machine learning tool.

The results illustrate that the project managers in Nepal have a high score in leadership skills, personal characteristics, team development and delegation, communication skills, technical skills, problem-solving/coping with situation skills and stakeholder/relationship management skills. Furthermore, among the seven classifiers (naïve Bayes, sequential minimal optimization [SMO], multilayer perceptron, logistic, KStar, J48 and random forest), the accuracy given by the SMO algorithm is highest of all in both the percentage split and k-folds cross validation method. The model developed using SMO classifier by k-folds cross-validation (k = 10) is acknowledged as a final model.

This research focuses to develop a prediction model to predict and analyze the competency of project managers by applying a supervised machine learning approach. Seven extensively used algorithms (Naïve Bayes, SMO, multilayer perceptron, logistic, KStar, J48, random forest) are used to check the accuracy of models and an algorithm that gives the highest accuracy is adopted. Data collection for this research is carried out by expert opinion method to validate the characteristics (factors) essential for competent project managers in the first round and the description of each factor as high, medium and low is inquired with the same experts in the second round. After an expert opinion, a structured questionnaire is prepared for the survey to assess the competency level of project managers (PMs). The competency level of PMs working under government funded, foreign aided or private projects from the contractor’s side is measured. This research is limited to the medium scale construction projects of Nepal.

This model can be a huge asset in the human resource department of construction companies as it helps to know the performance level of project managers in terms of “Higher than expected,” “Expected” or “Lower than expected” for the medium complexity construction projects of Nepal. Also, the model will assist human intelligence to make the decision while recruiting a new project manager/s for different types of projects at a time. Moreover, the model can be used for self-assessment of project manager/s to know their performance level. The model can be used to develop a user friendly interface system or an application such that it can be conveniently used anywhere any time.

This research shows that most of the project managers working in a medium complexity construction project of Nepal are male, maximum of them hold bachelor’s degree and study for road projects. Furthermore, most of the project managers scored high in leadership skills, personal characteristics, communication skills, technical skills, problem-solving/coping with situation skills, team development and delegation and stakeholder/relationship management skills. The model has given the “Personal characteristics” attribute the highest weightage. Likewise, other attributes having high weightage are communication skills, analytical abilities, project budget, stakeholder/relationship management, team development and delegation and time management skills.

This research was conducted to find the competency factors and to study the competency level of project managers in Nepal to develop a prediction model to predict the PM’s performance using a machine learning approach in medium scale construction projects. There is a lack of research to develop a model that predicts project manager’s competency using the machine learning approach. Therefore, the predictive model developed here helps in the identification of a competent project manager as it will be advantageous for project completion with a high success rate.

The purpose of this study is to investigate the influences of the characteristics of procurement strategies, in this instance labour-only, on project performance concerning health and safety (H&S), a project performance indicator.

Using non-probability purposeful and snowballing sampling methods, questionnaires were used to collect data from construction professionals in Nigeria. This was then analysed using descriptive (frequency and mean scores) and inferential statistics (Mann–Whitney-U and Kendall's Tau_b tests).

The findings indicate a statistically significant negative correlation between ‘the level of client involvement and ‘fatalities' and a positive one with ‘conducting of health and safety risk assessment' and ‘conducting employee surveys on health and safety attitude’. Poor hygiene is found to be the worst lagging indicator, while conducting of inspection is the most adopted leading indicator of project health and safety performance. It also emerged that there is no significant difference in the health and safety performance of projects procured through the procurement strategy in urban and rural areas.

The study provides valuable insight into the complexities in H&S management due to the high level of client involvement in labour-only procurement system (LoPS) projects and the level of diversity in their responsibilities therein. It creates a fundamental direction for developing a detailed framework or guidance notes for client involvement in the integration of H&S into LoPS projects.

This is the first study that examines the influence of the characteristics of procurement strategy on project health and safety performance. Evidence in the literature shows that project delivery outcomes significantly improve if procurement is strategically used, including when it is considered early in projects. However, integrating H&S into procurement strategies has received little attention.

Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.