Project Team Size Research Articles

Factors influencing the relationship between product modularity and supply chain integration

PurposeThe purpose of this paper is to explore the relationship between product modularity (PM) and supply chain integration (SCI), and to identify factors influencing this relationship.Design/methodology/approachA case study approach involving in‐depth interviews on three modular and two non‐modular design projects in the Hong Kong and Pearl River Delta region was conducted. Within and cross‐case analyses were adopted.FindingsResults support the current view that modular design is related to a loosely coordinated supply chain, whereas integrated design is associated with a tightly coordinated supply chain. However, this relationship is affected and explained by four contingency factors: new module/component development, technological knowledge leakage and creation, project team size and supply chain efficiency.Research limitations/implicationsThe paper used a case study approach so the generalizability of the study is limited. This approach, however, enabled us to examine explicitly the relationship between PM and SCI, where empirical research was lacking. The rich content of each case suggested how and why modular design affects supply chain management.Originality/valueThe findings of this paper increase the understanding of the dynamics of modular product design and supply chain management. The paper also explores four contingency factors affecting the relationship.

Antecedents of open source software defects: A data mining approach to model formulation, validation and testing

This paper develops tests and validates a model for the antecedents of open source software (OSS) defects, using Data and Text Mining. The public archives of OSS projects are used to access historical data on over 5,000 active and mature OSS projects. Using domain knowledge and exploratory analysis, a wide range of variables is identified from the process, product, resource, and end-user characteristics of a project to ensure that the model is robust and considers all aspects of the system. Multiple Data Mining techniques are used to refine the model and data is enriched by the use of Text Mining for knowledge discovery from qualitative information. The study demonstrates the suitability of Data Mining and Text Mining for model building. Results indicate that project type, end-user activity, process quality, team size and project popularity have a significant impact on the defect density of operational OSS projects. Since many organizations, both for profit and not for profit, are beginning to use Open Source Software as an economic alternative to commercial software, these results can be used in the process of deciding what software can be reasonably maintained by an organization.

Special issue devoted to papers presented at the second INFORMS workshop on artificial intelligence and data mining, Seattle, November 3, 2007

The Second INFORMS Workshop on artificial intelligence and data mining (WAID-07) was held in Seattle on November 3, 2007. The workshop was a pre-conference workshop to the National INFORMS meeting. Twenty papers were presented at the workshop, divided in two tracks—AI and Data Mining. A special issue of Information Technology and Management was devoted to papers from WAID-07. Twelve papers were submitted for possible publication in the special issue, of which six have been accepted for publication. Three papers were published in Volume 10 issue 1, 2009 of Information Technology and Management. Three more papers are being published in this issue. The first paper, titled ‘‘A Finite-Sample Simulation Study of Cross Validation in Tree-Based Models’’ by Seoung Bum Kim, Xiaoming Huo and Kwok-Leung Tsui, explores the behavior of cross validation in tree-based classifiers. The performance of cross-validated tree-based classifier and Bayes classifier are empirically tested. The authors find that the differences between the testing and training errors from a cross-validated tree classifier and the Bayes classifier follow a simple linear regression model. Based on their experience, the authors recommend using cross-validated tree-based classifiers when sample size is relatively small. The second paper, titled ‘‘Antecedents of Open Source Software Defects: A Data Mining Approach to Model Formulation, Validation and Testing’’ by Uzma Raja and Marietta J. Tretter, uses data mining and text mining techniques to develop, test and validate a model for the antecedents of Open-Source Software (OSS) defects. The authors look at over 5,000 active and mature OSS projects to validate their model. Results indicate that variables such as project type, end-user activity, process quality, team size and project popularity have a significant impact on the defect density of operational OSS projects. The third paper, titled ‘‘Identifying Fall-Related Injuries: Text Mining the Electronic Medical Record’’ by Monica Chiarini Tremblay et al. uses data mining and text mining techniques to investigate if unstructured text-based information included in the electronic medical records can validate and enhance those records in the administrative data that should have been coded as fall related injuries. The authors identify many challenges involved in any study involving text mining.

A STATISTICAL METHODOLOGY TO SIMPLIFY SOFTWARE METRIC MODELS CONSTRUCTED USING INCOMPLETE DATA SAMPLES

Software metric models predict the target software metric(s), e.g., the development work effort or defect rates, for any future software project based on the project's predictor software metric(s), e.g., the project team size. Obviously, the construction of such a software metric model makes use of a data sample of such metrics from analogous past projects. However, incomplete data often appear in such data samples. Moreover, the decision on whether a particular predictor metric should be included is most likely based on an intuitive or experience-based assumption that the predictor metric has an impact on the target metric with a statistical significance. However, this assumption is usually not verifiable "retrospectively" after the model is constructed, leading to redundant predictor metric(s) and/or unnecessary predictor metric complexity. To solve all these problems, we derived a methodology consisting of the k-nearest neighbors (k-NN) imputation method, statistical hypothesis testing, and a "goodness-of-fit" criterion. This methodology was tested on software effort metric models and software quality metric models, the latter usually suffers from far more serious incomplete data. This paper documents this methodology and the tests on these two types of software metric models.

Dynamics of change management in a technology project context

In this paper, we capture and analyse the change management dynamics of a technology project using a system dynamics simulation model. This model incorporates several features yet to be actively addressed in the literature and focuses on Earned Value Management (EVM). The effects of time-varying project team size, of training and communication overload and of project orientation are incorporated into this model. The results indicate that changes occurring later in the project make completion of the project within the scheduled time more difficult despite availability of abundant resources. These phenomena are propagated through the Earned Value (EV) measures to see the actual effects upon schedule and cost performance indices. 'Resorting to overtime', 'staying on top from the beginning' and 'controlled staffing' are used in policy experimentations; the results provide useful and interesting insights for formulating effective change management strategies to assess the cost, humanpower and schedule implications for changes during the project execution.

Determinants of budget overruns on IT projects

Using data collected from a sample of 76 project managers from 64 firms, we explore the relative impact of project characteristics, frequency of problems encountered on the projects, perceived impact of these problems on the budget performance, project managers’ personal characteristics, and project managers’ conflict management styles on budget overruns on information technology (IT) projects. The study reveals that schedule overrun is the strongest predictor of budget overrun. Usage level of accommodation as a conflict management style, project team size, and project management experience were also found to be important, but to a lesser extent. We then utilize the findings to construct a model that predicts budget overrun as a percentage of the initial budget estimate. We conclude with recommendations for future research.

Contracts in Offshore Software Development: An Empirical Analysis

We study the determinants of contract choice in offshore software development projects and examine how the choice of contract and other factors in the project affect project profits accruing to the software vendor. Using data collected on 93 offshore projects from a leading Indian software vendor, we provide evidence that specific vendor-, client-, and project-related characteristics such as requirement uncertainty, project team size, and resource shortage significantly explain contract choice in these projects. Our analysis suggests that contract choice significantly determines project profit. Additionally, some ex ante vendor-, client-, and project-related characteristics known at the time of choosing the contract continue to significantly influence project profits after controlling for contract choice. We also provide evidence to show that project duration and team size affect project profits.

Some Correlates of IS Project Teams' Internal Interaction and Outcome in a Developing Country

This investigation explores some of the factors that affect internal interaction and performance in IS project teams in the context of a developing country. The study hypothesizes that project team size, leader capability, and training affect participation and coordination, which in turn affect IS project team performance. Our statistical analyses reveal many interesting findings. Some of these findings are inconsistent with the conclusions of previous research, which have been carried out in developed countries. We found that coordination could negatively affect the performance of IS project teams. We also found that training could hinder the coordination within the IS project team. In addition, we found that leader capability positively affected participation and that project team size negatively affected coordination. We discuss the implications of our findings for managerial practice and for future research.

A model of the software development process

This paper presents a model of the programming process. The model has four parts. A resources model specifies how many useful man-months of design effort are available from project team members after subtracting the time required for learning and team communications. A system design model specifies how many man-months of effort are required to derive program module specifications, as a function of the number of team members, program size, and number of modules. A coding model specifies how many man-months of effort are required for coding, as a function of team, module, and program size. Finally, a checkout model specifies how many man-months are required for checkout as a function of program size, error detection and correction rates, and a design-complete factor. The model as a whole predicts that programmer productivity will decrease as project team size is increased and that project duration will first decrease and then increase as team size is increased. It also shows that productivity and project duration vary enormously as a function of project management factors, even when project complexity and programming staff competence are held constant.

Histoplasmin Sensitivity Investigation in Japan (Nagoya District)

This study aims to identify how traditional organizational roles are transformed towards Agile roles. A grounded theory study with 5 software teams in a large software development company in Spain was conducted. We interviewed 21 people, participated in Agile Coaching sessions and observed daily activities in the company during a six-month period. The transition of organizational roles during the Agile transformation process is influenced by many circumstances such as: higher management commitment and support, knowledge about Agile, project team size and culture. The theory demonstrates how enterprise factors influence the transition of organizational roles and how practitioners cope with the challenges during the Agile transformation process. Based on our results, we proposed recommendations and guidelines for organizational roles transition during the Agile method adoption.