Preliminary Results in a Multi-site Empirical Study on Cross-organizational ERP Size and Effort Estimation

This paper reports on initial findings in an empirical study carried out with representatives of two ERP vendors, six ERP adopting organizations, four ERP implementation consulting companies, and two ERP research and advisory services firms. Our study’s goal was to gain understanding of the state-of-the practice in size and effort estimation of cross-organizational ERP projects. Based on key size and effort estimation challenges identified in a previously published literature survey, we explored some difficulties, fallacies and pitfalls these organizations face. We focused on collecting empirical evidence from the participating ERP market players to assess specific facts about the state-of-the-art ERP size and effort estimation practices. Our study adopted a qualitative research method based on an asynchronous online focus group

Cost and Risk Considerations for Test and Evaluation of Unmanned and Autonomous Systems of Systems

The evolutionary nature of Unmanned and Autonomous systems of systems (UASoS) acquisition needs to be matched by evolutionary test capabilities yet to be developed. As part of this effort we attempt to understand the cost and risk considerations for UASoS Test and Evaluation (T&E) and propose the development of a parametric cost model to conduct trade-off analyses. This paper focuses on understanding the need for effort estimation for UASoS, the limitations of existing cost estimation models, and how our effort can be merged with the cost estimation processes. We present the prioritization of both technical and organizational cost drivers. We note that all drivers associated with time constraints, integration, complexity, understanding of architecture and requirements are rated highly, while those regarding stakeholders and team cohesion are rated as medium. We intend for our cost model approach to provide management guidance to the T&E community in estimating the effort required for UASoS T&E

Community Participation, Teacher Effort, and Educational Outcome: The Case of El Salvador's EDUCO Program

Based on a principal-agent model, this paper investigates the organizational structure that made the El Salvador's primary school decentralization program (EDUCO program) successful. First, we employ the "augmented" reduced form educational production function by incorporating parents and community involvement as a major organizational input. We observe consistently positive and statistically significant EDUCO participation effects on standardized test scores. Then we estimated teacher compensation function, teacher effort functions, and input demand functions by utilizing the theoretical implications of a principal (parental association)-agent (teacher) framework. While the EDUCO school teachers receive piece rate, depending on their performance, wage payment is relatively fixed in the traditional schools. Empirical results indicate that the slope of wage equation is positively affected by the degree of community participation. This finding can be interpreted as the optimal intensity of incentive. Hence, teacher's effort level in the traditional schools is consistently lower than that in the EDUCO schools, indicating a moral hazard problem. Community participation through parental group's classroom visits seems to enhance the teacher effort level and thus increases students' academic performance indirectly. Parental associations can affect not only teacher effort and their performance by imposing an appropriate incentive scheme but also school-level inputs by decentralized school management. Our empirical results support the view that decentralization of education system should involve delegation of school administration and teacher management to the community group.economic analysis of social sector reform, the optimal intensity of incentive condition, moral hazard, education production function, fixed effects instrumental variable estimation

Effort and Selection Effects of Incentive Contracts

We show that the improved effort of employees associated with incentive contracts depends on the properties of the performance measures used in the contract.We also find that the power of incentives in the contract is only indirectly related to any improved employee effort.High powered incentive increase the selection effect of the incentive contract and attract better employees to the firm.The selection effect of the incentive contract depends, in turn, on the (perceived) properties of the performance measures specified in the contract.These results hold after controlling for an array of incentive contract design characteristics and for differences in organizational context.Data is from a third party survey on compensation practices among Chief Executive Officers.Our estimation procedures address several known problems with using secondary datasets.incentives;contracts;performance measurement;employees

Costs, Benefits and Value Distribution – Ingredients for Successful Cross-Organizational ES Business Cases

This paper introduces my PhD research project on developing guidelines for creating successful business cases for Enterprise System implementations in network settings. Three important aspects that were found to be important in such business cases are: the costs, benefits and the value distribution within a network. Each of the three aspects is addressed in this paper and the relationships between them are pointed out. A research model is presented showing how all three aspects contribute to the main goal of defining successful business case guidelines

Implementation of Software Process Improvement Through TSPi in Very Small Enterprises

This article shows an experience in a very small enterprise related to improving software quality in terms of test and process productivity. A customized process from the current organizational process based on TSPi was defined and the team was trained on it. The pilot project had schedule and budget constraints. The process began by gathering historical data from previous projects in order to get a measurement repository. Then the project was launched and some metrics were collected. Finally, results were analyzed and the improvements verified

A Principled Methodology: A Dozen Principles of Software Effort Estimation

Software effort estimation (SEE) is the activity of estimating the total effort required to complete a software project. Correctly estimating the effort required for a software project is of vital importance for the competitiveness of the organizations. Both under- and over-estimation leads to undesirable consequences for the organizations. Under-estimation may result in overruns in budget and schedule, which in return may cause the cancellation of projects; thereby, wasting the entire effort spent until that point. Over-estimation may cause promising projects not to be funded; hence, harming the organizational competitiveness.;Due to the significant role of SEE for software organizations, there is a considerable research effort invested in SEE. Thanks to the accumulation of decades of prior research, today we are able to identify the core issues and search for the right principles to tackle pressing questions. For example, regardless of decades of work, we still lack concrete answers to important questions such as: What is the best SEE method? The introduced estimation methods make use of local data, however not all the companies have their own data, so: How can we handle the lack of local data? Common SEE methods take size attributes for granted, yet size attributes are costly and the practitioners place very little trust in them. Hence, we ask: How can we avoid the use of size attributes? Collection of data, particularly dependent variable information (i.e. effort values) is costly: How can find an essential subset of the SEE data sets? Finally, studies make use of sampling methods to justify a new method\u27s performance on SEE data sets. Yet, trade-off among different variants is ignored: How should we choose sampling methods for SEE experiments? ;This thesis is a rigorous investigation towards identification and tackling of the pressing issues in SEE. Our findings rely on extensive experimentation performed with a large corpus of estimation techniques on a large set of public and proprietary data sets. We summarize our findings and industrial experience in the form of 12 principles: 1) Know your domain 2) Let the Experts Talk 3) Suspect your data 4) Data Collection is Cyclic 5) Use a Ranking Stability Indicator 6) Assemble Superior Methods 7) Weighting Analogies is Over-elaboration 8) Use Easy-path Design 9) Use Relevancy Filtering 10) Use Outlier Pruning 11) Combine Outlier and Synonym Pruning 12) Be Aware of Sampling Method Trade-off

Individual-Level Determinants of the Propensity to Shirk

Employee shirking, where workers give less than full effort on the job, has typically been investigated as a construct subject to group and organization-level influences. Neglected are individual differences that might explain why individuals in the same organization or work-group might shirk. The present study sought to address these limitations by investigating subjective well-being (a dispositional construct), job satisfaction, as well as other individual-level determinants of shirking behavior. Results identified several individual-level determinants of shirking. Implications of the results are discussed