Girish H. Subramanian

Software quality and IS project performance improvements from software development process maturity and IS implementation strategies

The capability maturity model (CMM) is part of several software process improvement (SPI), six sigma, and total quality management (TQM) initiatives in organizations. SPI and continuous quality improvements are associated with better return on investment (ROI) for organizations. The purpose of this empirical research is to study the impact of the CMM on certain critical factors in information systems implementation strategy, software quality and software project performance. Our findings are that CMM levels do associate with IS implementation strategies and higher CMM levels relate to higher software quality and project performance. We also conclude that information systems (IS) implementation strategies have a significant impact on software quality and project performance. While certain IS implementation strategies - executive commitment and prototyping - have a significant impact on both software quality and project performance, training had a significant effect only on software quality and simplicity has a significant effect only on project performance.

A comparison of the decision table and tree

T he decision table and decision tree are essential tools for systems analysts ([6], [12]). These decision aids are used by systems analysts in depict ing conditional logic for p rogrammers and in validating this logic with the user. In addition, many authors recommend the decision table and tree as useful aids in decision making ([4, 11, 14, 21, 22]). The effectiveness of the decision aids is de te rmined by their ability to help in the unders tanding of conditional logic. The i r relative effectiveness in facilitating such understanding however, has previously not been subject to p rope r empirical testing. Our research concerns the effectiveness of the decision table and tree in the user interface (i.e., we are interested in their relative effectiveness as communicat ion tools in user validation of conditional logic and as decision aids in problem solving). Since these aids are normally applied in a specific context involving the users, we use a computer investment game that requires their use for decision making. A key feature of our research is the use of this computer game to promote highly motivated and engaged subjects. The comparison of graphs and tables in their effect on interpretation accuracy [ 17] and their performance in the user interface ([20, 23, 24]), and the studies on graphs and their effects on decision-making ([1, 18]) are topics related to our research. However, the comparison of the table and tree at the user interface has not been examined. Thus, our research becomes significant.

An empirical study of the Cobb-Douglas production function properties of software development effort

In this paper we study whether software development effort exhibits Cobb-Douglas functional form with respect to team size and software size. We empirically test this relationship using real-world software engineering data set containing over 500 software projects. The results of our experiments indicate that the hypothesized Cobb-Douglas function form for software development effort with respect to team size and software size is true. We also find increasing returns to scale relationship between software size and team size with software development effort.

An Exploratory Case Study of Enterprise Resource Planning Implementation

Enterprise Resource Planning (ERP) systems are a growing area of research in business information systems. The primary purpose of this research was to test the effect of ERP implementation on users. We used the implementation and performance stage model and studied issues related to adaptation, acceptance, and routinization stages. An exploratory case study was conducted to study these research issues. The case study consisted of a survey and interview of 25 employees at one organization. The results provide data analysis findings from the survey and qualitative findings from the interview. The findings of the case study point to a positive user climate during transition to SAP, increased user productivity, and improved job understanding through the use of SAP software.

An empirical study of the effect of complexity, platform, and program type on software development effort of business applications

Several popular cost estimation models like COCOMO and function points use adjustment variables, such as software complexity and platform, to modify original estimates and arrive at final estimates. Using data on 666 programs from 15 software projects, this study empirically tests a research model that studies the influence of three adjustment variables—software complexity, computer platform, and program type (batch or online programs) on software effort. The results confirm that all the three adjustment variables have a significant effect on effort. Further, multiple comparison of means also points to two other results for the data examined. Batch programs involve significantly higher software effort than online programs. Programs rated as complex have significantly higher effort than programs rated as average.

The Phases of ERP Software Implementation and Maintenance: A Model for Predicting Preferred ERP Use

Nearly all information technology educators and practitioners are familiar with the concept of a systems development life cycle (SDLC). The SDLC model is mainly based on new software development. The stages vary based on methodology, but mostly include planning and requirements definition, analysis, design of the new system, implementation, and post-implementation support such as maintenance and security. Less explored and known are the stages involved in commercial off the shelf installation. The actual implementation of commercial off the shelf software ERP (enterprise resource planning) systems is an area that is suggested to have a life cycle of its own. The importance of specific phases of this ERP implementation life cycle is the subject of this study. By surveying SAP enterprise resource planning implementations at two divisions of a major manufacturing company, a confirmatory factor analysis confirms the existence of four distinct phases of ERP implementation — preparation and training, transition, performance and usefulness, and maintenance. In addition, the overall preferred ERP use is studied and compared with these factors. It was found that the two significant phases which directly influenced preferred ERP use were preparation and training phase, and performance and usefulness phase. Neither transition nor maintenance was found to significantly affect preferred ERP use. This suggests to practitioners that more focus needs to be placed on the key determinants of preferred ERP use — preparation and training phase, and performance and usefulness phase.

An empirical study of ICASE learning curves and probability bounds for software development effort

Abstract In this paper, we investigate the existence of learning curves in software development. Under the assumption of independent and identical distribution (iid) of programmer’s experience and identical effort-experience learning curve relationship for different programmers, we illustrate the existence of an exponentially decreasing learning curve relationship between a programmer’s effort and his/her ICASE tool experience, and show that the effort-experience relationship is inelastic when a programmer’s ICASE tool experience is low. We analyze the impact of our assumptions on actual software development effort, and propose a tight probability upper bound and a central-limit theorem based probability estimator for estimating the approximate probability that the software development effort will be less than or equal to a certain number. Examples to illustrate the use of the probability estimator are also provided.

Information systems in supply chain management: a comparative case study of three organisations

Supply Chain Management (SCM) is recognised as a core competitive strategy for businesses in almost every industry. A strong supply chain provides products and services to consumers faster, cheaper, and better. The paper discusses SCM and information systems in the supply chain. Case studies of Wal-Mart, Amazon.Com and United Parcel Services (UPS) and their use of information systems in the supply chain are presented. Wal-Mart and Amazon have established critical and timely strategies in their supply chains through huge investments in Information Technology (IT). While Wal-Mart and Amazon are offering their products to consumers, UPS offers logistics solutions to clients. These companies use a variety of information technologies which include satellite systems, barcodes, web-based Electronic Data Interchange (EDI), Radio Frequency Identification (RFID), data warehousing, and e-commerce in their supply chain. The supply chain and use of these technologies in SCM are reviewed and compared for these three organisations.

An empirical study of certain object-oriented software metrics

Abstract This research focuses on analyzing certain software metrics in an object-oriented (OO) environment. The metrics collected and analyzed includes size, number of message (NOM) sends, reuse, inherited methods, and hierarchical nesting level. The site used is the factory systems department of a large manufacturing company. This department uses SmallTalk as the OO programming language to implement the OO design paradigm. Using automated tools developed in SmallTalk, these metrics were collected from three domain applications comprising 600 classes. Four propositions are empirically tested and the results provided in this study.

An empirical evaluation of factors influencing expert systems effectiveness

This study explores expert system effectiveness by testing an expert system development model and analyzing the life cycle development process. The objective is to determine the nature of the interactions within the expert system development process and how the process affects expert system effectiveness. The results suggest that life cycle development stages critically impact the overall perception of system effectiveness.