A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item GOVERNANCE STRATEGIES FOR ENTERPRISE APPLICATION SYSTEM IMPLEMENTATIONS(2013) Ghosh, Saumyendu N.; Skibniewski, Miroslaw J; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Enterprise application system implementations are highly complex implementations that automate several business functions, such as financials, accounting, supply chain, customer services management, human resources management and reporting among others. This study aims at providing an alternative view of organization's enterprise application system (EAS) acceptance. Despite the large body of literature, there are still empirical inquiries to investigate the EAS system implementation from adopters' perspectives and how to identify risks in a multi-stakeholder and dynamic environment. The thesis consists of three essays on various aspects of relationship between enterprise application implementation in a multi-stakeholder environment and project governance. Valid measurement scales for predicting organization's acceptance of enterprise systems are in short supply. The first essay develops and validates new scales for two specific variables, integration and inter-dependency risks. These variables are hypothesized as key determinant for organizational success of enterprise application implementations by mitigating risks involved in a multi-stakeholder environment. A model of organization acceptance of enterprise systems was developed using these two scales and then tested for reliability from a total of 365 users and nine application groups. The measures were validated using ten different direct measures with reliabilities between 0.72 and 0.96. Integration risk was significantly related with perceived ease of use, consultant's product knowledge and training provided to the end users. Inter-dependency risk was significantly correlated with perceived usefulness, consultant's industry and product knowledge. Both integration and inter-dependency risks are significantly related with success of the new enterprise application. This study would benefit project executives by offering valuable managerial insights that enable them to appreciate and improve integration and inter-dependency of stakeholders. Implications for theory and practice are discussed for two sub-groups: that less experienced resources treat risks differently than more experienced resources, and business applications compared to technical enterprise applications. Academic community has not addressed governance of enterprise application projects that involve dynamic environments and how to mitigate integration and inter-dependency risks. In the second essay it is argued that acceptance of the system from end users is not enough? Adopters of new enterprise wide information technology solutions get most benefit when the solution continues to be adaptable when business, environment or other organizational priorities change - therefore making an implementation sustainable. The second essay discussed characteristics of sustainability of enterprise application implementation from organizational perspective. A case study was used to validate the characteristics of sustainability. The thesis sought to demonstrate the causal relationship between the organization's preparedness for sustainability and the emergence of implementation problems. The study extracted insight into the criticality of certain factors and the type of problems making decisions under weak governance situation. The third essay develops determinants for project governance success of enterprise application implementations by mitigating risks in a multi-stakeholder environment. This essay develops and validates new scales for five specific variables. Definitions of five variables were used to develop a model that was presented for content validity and then tested for reliability from a total of 117 project executives globally. The measures were validated with reliabilities between 0.73 and 0.94. Relationships between five measures were broken down to meaningful components and a three tier project governance structure was proposed to mitigate integration and inter-dependency risks in a multi-stakeholder environment.Item APPROXIMATION ASSISTED MULTIOBJECTIVE AND COLLABORATIVE ROBUST OPTIMIZATION UNDER INTERVAL UNCERTAINTY(2012) Hu, Weiwei; Azarm, Shapour; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Optimization of engineering systems under uncertainty often involves problems that have multiple objectives, constraints and subsystems. The main goal in these problems is to obtain solutions that are optimum and relatively insensitive to uncertainty. Such solutions are called robust optimum solutions. Two classes of such problems are considered in this dissertation. The first class involves Multi-Objective Robust Optimization (MORO) problems under interval uncertainty. In this class, an entire system optimization problem, which has multiple nonlinear objectives and constraints, is solved by a multiobjective optimizer at one level while robustness of trial alternatives generated by the optimizer is evaluated at the other level. This bi-level (or nested) MORO approach can become computationally prohibitive as the size of the problem grows. To address this difficulty, a new and improved MORO approach under interval uncertainty is developed. Unlike the previously reported bi-level MORO methods, the improved MORO performs robustness evaluation only for optimum solutions and uses this information to iteratively shrink the feasible domain and find the location of robust optimum solutions. Compared to the previous bi-level approach, the improved MORO significantly reduces the number of function calls needed to arrive at the solutions. To further improve the computational cost, the improved MORO is combined with an online approximation approach. This new approach is called Approximation-Assisted MORO or AA-MORO. The second class involves Multiobjective collaborative Robust Optimization (McRO) problems. In this class, an entire system optimization problem is decomposed hierarchically along user-defined domain specific boundaries into system optimization problem and several subsystem optimization subproblems. The dissertation presents a new Approximation-Assisted McRO (AA-McRO) approach under interval uncertainty. AA-McRO uses a single-objective optimization problem to coordinate all system and subsystem optimization problems in a Collaborative Optimization (CO) framework. The approach converts the consistency constraints of CO into penalty terms which are integrated into the subsystem objective functions. In this way, AA-McRO is able to explore the design space and obtain optimum design solutions more efficiently compared to a previously reported McRO. Both AA-MORO and AA-McRO approaches are demonstrated with a variety of numerical and engineering optimization examples. It is found that the solutions from both approaches compare well with the previously reported approaches but require a significantly less computational cost. Finally, the AA-MORO has been used in the development of a decision support system for a refinery case study in order to facilitate the integration of engineering and business decisions using an agent-based approach.Item A Decision Support System for Dynamic Integrated Project Scheduling and Equipment Operation Planning(2012) AHRARI, AMIR; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Common practice in scheduling under limited resource availability is to first schedule activities with the assumption of unlimited resources, and then assign required resources to activities until available resources are exhausted. The process of matching a feasible resource plan with a feasible schedule is called resource allocation. Then, to avoid sharp fluctuations in the resource profile, further adjustments are applied to both schedule and resource allocation plan within the limits of feasibility constraints. This process is referred to as resource leveling in the literature. Combination of these three stages constitutes the standard approach of top-down scheduling. In contrast, when scarce and/or expensive resource is to be scheduled, first a feasible and economical resource usage plan is established and then activities are scheduled accordingly. This practice is referred to as bottom-up scheduling in the literature. Several algorithms are developed and implemented in various commercial scheduling software packages to schedule based on either of these approaches. However, in reality resource loaded scheduling problems are somewhere in between these two ends of the spectrum. Additionally, application of either of these conventional approaches results in just a feasible resource loaded schedule which is not necessarily the cost optimal solution. In order to find the cost optimal solution, activity scheduling and resource allocation problems should be considered jointly. In other words, these two individual problems should be formulated and solved as an integrated optimization problem. In this research, a novel integrated optimization model is proposed for solving the resource loaded scheduling problems with concentration on construction heavy equipment being the targeted resource type. Assumptions regarding this particular type of resource along with other practical assumptions are provided for the model through inputs and constraints. The objective function is to minimize the fraction of the execution cost of resource loaded schedule which varies based on the selected solution and thus, considered to be the model's decision making criterion. This fraction of cost which hereafter is referred to as operation cost, encompasses four components namely schedule delay cost, shipping, rental and ownership costs for equipment.