Project‐Level Reuse Factors: Drivers for Variation within Software Development Environments*

Systematic reuse can dramatically improve software development productivity and quality even though a software reuse methodology may require substantial investments. Some projects may fail to achieve the targeted amounts of reuse within organizations that are overall successful in employing reuse. To explain such variation, this research explores the effects of project‐level factors in the success of software reuse. A model that relates project factors to project reuse success is developed using an information‐rich case study approach. The results are based on the insights obtained in a nominal group technique session, triangulated with structured interviews and comparative case studies. Success factors identified by the study relate to client influence, project culture, project attributes, and developer reuse experience. An organization that can successfully identify the factors affecting potential software reuse will be able to better target investments for the improvement of its reuse methodology and thus positively affect its software development productivity and quality.     

Evaluating USAF Vehicle Maintenance Productivity Over Time: An Application of Data Envelopment Analysis

In response to increasing costs and reductions in manpower, the Tactical Air Command (TAC) of the USAF experimented with a specialized productivity measurement model known as data envelopment analysis (DEA). A medium-sized application of DEA was employed by TAC to evaluate the productivity of its seventeen subordinate vehicle maintenance sections over a four-year period. The application reports gains in productivity and the reactions of the field managers to the use of DEA.     

A Performance Measure for Software Reuse Projects

The efficient development of software has become a critical factor to the success of many organizations. Significant competitive advantage can be realized by reducing the time to complete software development, while maintaining or improving quality levels. Project management activities, including the measurement of performance at the level of the project, can help the organization to both control projects and learn from experience. Traditionally, the productivity of a software development project has been measured as the complexity of code produced per unit of labor involved. An increasing number of organizations, however, are adopting the practice of software reuse, and under such conditions, such a traditional measure of productivity does not fully capture all the relevant elements of the reuse-driven development environment. This research develops a new performance measure that considers four major components of performance: productivity associated with development of new code, productivity associated with the reuse of previously written code, quality of the reuse decision, and relative value of reuse to the company. To illustrate the feasibility of the measure, a real-world productivity assessment is presented for an example company, and related implementation issues are discussed.     

How Software Project Risk Affects Project Performance: An Investigation of the Dimensions of Risk and an Exploratory Model*

To reduce the high failure rate of software projects, managers need better tools to assess and manage software project risk. In order to create such tools, however, information systems researchers must first develop a better understanding of the dimensions of software project risk and how they can affect project performance. Progress in this area has been hindered by: (1) a lack of validated instruments for measuring software project risk that tap into the dimensions of risk that are seen as important by software project managers, and (2) a lack of theory to explain the linkages between various dimensions of software project risk and project performance. In this study, six dimensions of software project risk were identified and reliable and valid measures were developed for each. Guided by sociotechnical systems theory, an exploratory model was developed and tested. The results show that social subsystem risk influences technical subsystem risk, which, in turn, influences the level of project management risk, and ultimately, project performance. The implications of these findings for research and practice are discussed.     

Group Support Systems,Power, and Influence in an Organization: A Field Study

Emerging group technologies are attracting attention from researchers and practitioners for the benefits they potentially offer in terms of communications, productivity, and decision-making capabilities within an organization. To date, research in this area has focused on process or outcome variables, substantively ignoring organizational context issues. This paper reports on a field study that investigated users' perceptions of the impact of group support systems on power and influence within the organization. The study was conducted within a division of a major U.S. software company specializing in the development of business software tools for desktop PCs. Fifteen purposively selected managers and nonmanagers, spanning diverse functional areas, were extensively interviewed for this study. Evidence gathered suggested that group support systems are perceived to exert an equalizing force on power and influence by (1) increasing participation in the decision-making process, (2) improving access to information, (3) improving access to persons, (4) reducing the “power distance” to key individuals, and (5) providing increased opportunities to influence the opinions of others. These results provide a basis for future studies that will attempt to clarify the relationships between organizational context and group technology usage.     

Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization

The performance of a decision making unit (DMU) can be evaluated in either a cross-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. In order to eliminate the inconsistency caused by using different frontier facets to calculate efficiency, common-weights DEA models have been developed, under which a group of DMUs can be ranked for a specific period. This study proposes a common-weights DEA model for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity changes of all DMUs have a common basis for comparison. The common-weights global MPI not only has sound properties, but also produces reliable results. The case of Taiwan forests after reorganization shows that the MPIs calculated from the conventional DEA model produce misleading results. The common-weights global MPI approach, on the other hand, correctly identifies districts with unsatisfactory performance before the reorganization and those with unsatisfactory productivity improvement after the reorganization.     

风险条件下研发项目改进DEA选择模型

研发项目是企业提高竞争力的关键,研发项目选择关系到企业的战略和未来发展趋势。研发项目在生命周期内面临技术风险、突发风险和市场风险,本文考虑到研发项目的风险特征,结合企业战略,构建了基于效率排序的研发项目选择模型。首先,本文对研发项目的有效性和相对于其它备选项目的相对优势进行分析;然后针对数据包络分析模型排序的不足,结合平衡计分卡理念,规范研发项目投入的比例,引入实物期权理论,改进数据包络分析模型,实现了对研发项目的效率排序;最后通过实际算例对模型进行验证、横向对比和敏感性分析,结果表明：相对于标准数据包络分析模型,本文提出的模型具有更高的效率区分度,并且能够敏感地捕捉到研发项目投入和产出的变化对效率影响的演变过程。     

System Development Project Effectiveness: Problem-Solving Competence as a Moderator Variable*

In spite of end-user programming, for the foreseeable future users and information systems (IS) specialists will build systems together. A better understanding of this partnership (which has a troubled history) will help IS managers and users improve their management skills. This study investigates the relative contributions to project effectiveness of problem-solving competence, the quality of the working relationship, and the quality of the development process. Seventy-five medium-sized projects in 16 organizations were investigated using individual, one hour, structured interviews with the IS project leader and with the primary user. Results suggest that more complex models should be used to study system development. Moreover, problem-solving competence demonstrated a complex effect on project effectiveness.     

Efficiency improvement from multiple perspectives: An application to Japanese banking industry

The current study focuses on efficiency improvement for banking systems from multiple perspectives, which have different definitions of input/output about various attributes of a banking system. In this research we utilize data envelopment analysis (DEA) and Nash bargaining game (NBG) theory to improve inefficient banks in order to: (1) Make the inefficient bank be the state of Pareto Optimality for multiple perspectives, which can avoid discontentment of some perspectives. (2) Improve a bank by changing its attributes and provide various improving schemes for decision makers. A numerical case study of Japanese banks is also given to show the results of equilibrium solution from multiple perspectives.     

Efficiency measurement for hierarchical network systems

The conventional data envelopment analysis (DEA) models for measuring the relative efficiency of a set of decision making units (DMUs), without considering the operations of the component processes, often produce misleading results, and network models have thus been recommended. This paper discusses the development of a network DEA model for systems with a hierarchical structure. It is shown that the hierarchical structure is equivalent to a parallel structure, with the components being the units at the bottom of the hierarchy. Due to the characteristics of a parallel system, the efficiency of a hierarchical system is thus a weighted average of those of the units at the bottom of the hierarchy. A hypothetic example shows that the proposed model is able to distinguish the order of the efficient DMUs evaluated by the conventional DEA model. Moreover, it provides the efficiencies of the functions of the DMU, which enables managers to identify areas of weakness, and thus better focus efforts to improve overall performance.     

Mapping IS failure factors on PRINCE2® stages: an application of Interpretive Ranking Process (IRP)

The social, political and cultural issues faced by organisations and their senior management team in the delivery and adoption of strategic projects, is highly complex and problematic. Despite a mature body of literature, increasing levels of practitioner certification, application of standards and numerous government initiatives, improvements in success have been minimal. In this study, we analyse the key underlying factors surrounding the failure of Information Systems (IS) projects and explore the merits of articulating a narrative that focuses on senior management embracing practical pessimism. Specifically, we develop a hypothesis supported by empirical study that leverages expert’s views on the dominance and interrelationships between failure factors within PRINCE2® project stages using an Interpretive Ranking Process. Our findings establish how the concept of dominance between individual failure factors can necessitate senior management to make key informed and timely decisions that could potentially influence project outcomes based on an empirical derived, interpretive predictive framework.     

Corporate philanthropic selection using data envelopment analysis

This paper presents a case study involving quantitative models for the selection of corporate philanthropic projects. The four analytic techniques used by this company for ranking and selecting philanthropic projects are all based on Data Envelopment Analysis (DEA). Instead of relaying only on one traditional DEA model, the four approaches employed in this study enable the decision maker to identify the most deserving school.     

Safety Does Not Happen by Accident: Antecedents To A Safer Warehouse

On a daily basis, thousands of employees suffer from severe occupational accidents worldwide. These accidents not only lead to negative consequences for the physical and mental health of employees, but also to high costs for companies and the society as a whole. A large share of these accidents take place in warehouses. Prior research has demonstrated the critical role of leadership, and especially safety‐specific transformational leadership (SSTL), in reducing warehouse accidents. Yet several important questions concerning SSTL remain: What effects does SSTL have on outcomes other than safety, and what determines whether leaders display SSTL behaviors? To answer these questions, this research studies the relationship between SSTL of warehouse managers and not only occupational accidents, but also quality and productivity. Moreover, it investigates the managers who are most likely to display SSTL. Data from 87 warehouse managers and 1233 employees were used to test the conceptual model. The results suggest that the dispositional prevention focus of the manager (one of two possible motivational strategies that people deploy) positively relates to SSTL, and that SSTL negatively relates to occupational accidents. Furthermore, SSTL and its identified negative relationship with occupational accidents does not appear to have detrimental impact on productivity or quality. These results extend existing models of SSTL and safety, and can help companies to reduce the number of accidents and the associated costs by selecting and developing safety‐specific transformational leaders.     

Systems innovation manager

Each year organizations spend a significant amount of money developing new products and processes in an effort to satisfy customer demands and manufacture high-quality products efficiently. Both development processes - product and process, are complex, resource intensive and thrive on innovation. They demand a variety of skills and resources, but in particular, participation among all staff in generating ideas, managing projects and implementing change. There are currently a number of software tools and methods that facilitate change in a systems environment. These range from complex modelling tools to information management tools. The tools have been developed around paradigms, e.g. world class manufacturing, total quality management and business process reengineering. They are often complex, requiring the efforts of skilled designers and managers. Current thinking within a systems environment reflects a more participative and less specialist approach to managing innovation and change. There is a need to create compromise between detailed project engineering and good management practice. This paper introduces a new paradigm centred on good management practice, and identifies the critical issues in systems innovation and change. The paradigm is articulated through a series of change levers and a methodology that guides managers and designers. It is supported by a series of software tools that together bring innovation management to life within the industrial organization.     

基于最近距离投影的DEA两阶段效率评价方法研究

数据包络分析是进行效率评价最重要的方法之一。传统的数据包络分析理论主要寻找有效前沿面上的最远距离投影，在极大化无效性指数的同时也面临着效率改进的巨大难度和高额成本。对于具有两阶段内部生产结构的决策单元，本文从考虑最小改进难度的视角出发，提出了最近距离投影的两阶段效率评价方法。该方法首先得到所有强有效决策单元的线性组合，且这些组合均占优于被评价的两阶段决策单元。然后建立了两阶段范围调整效率评价模型，在确定具有最近投影距离的占优组合的同时，得到了两阶段评价效率。最后，本文运用我国32家上市银行的年度数据对所提出方法进行了应用验证。     

资源约束型两阶段生产系统的DEA效率评价模型

经典的数据包络分析(DEA)模型将决策单元看作"黑箱",忽视决策单元的内部过程,必然会高估决策单元的效率。本文研究了一种资源约束型两阶段生产系统的DEA效率评价方法,针对此类生产过程的内部过程,研究其内部运行机制对整体效率的影响。本文提出的模型实质上是一类特殊的网络DEA模型,其评价原理有别于已有的研究成果,但更有助于管理者确定生产过程的非有效来源及其效率改进方向。实例证实本文方法的合理性。     

Directional distance based diversification super-efficiency DEA models for mutual funds

Current data envelopment analysis (DEA) models with diversification cannot discriminate the performance of efficient mutual funds. Based on the directional distance function and diversification DEA models, this paper proposes two diversification super-efficiency models for discriminating the performance of efficient mutual funds on financial market. The proposed diversification super-efficiency models as well as the corresponding diversification DEA models are feasible and can deal with negative values in risk measures, transaction costs and return measures. The proposed methods generate bounded super-efficiency scores for all the funds. Under the assumption of discrete return distributions, all the models in the proposed diversification super-efficiency methods can be transformed into linear programming (LP) problems by choosing proper risk and return measures. To demonstrate the validity and practicality of the proposed diversification super-efficiency methods, we apply them to evaluate the performance of mutual funds in the American market. The empirical results show that the proposed diversification super-efficiency models can distinguish efficient funds well and the linear combination of efficient funds might be inefficient. Moreover, the backtesting results show that the proposed diversification super-efficiency models generally have a good practice value for the actual portfolio selection.     

An intelligent dynamic simulation model for designing software development processes

This paper describes a computer-aided software development process design. This is a computerized intelligent tool designed to aid managers of software development projects in planning, managing and controlling the development process of medium to large scale software projects. The application of this computerized tool should help reduce the uncertainties involved in the budget, personnel and schedule planning of software development projects.     

CONTINUITY IN MIS/DSS LABORATORY RESEARCH: THE CASE FOR A COMMON GAMING SIMULATOR*

To date, case analyses and field studies have predominated in MIS/DSS research. Laboratory studies seem not to have been given the attention they deserve. This trend is partially due to: (1) the high costs associated with developing decision simulators and related software to support laboratory research and (2) difficult problems with external validity because of unrealistically simple simulated decision environments and DSS software. Since MIS/DSS laboratory research has been most successful when studies have occurred in an interrelated stream, the development of common, portable, and flexible simulators seems desirable. Common simulators would reduce the time and cost of developing experiments, provide for research continuity, comparability, and replication, and facilitate researcher-to-researcher communication. Sufficiently complex simulators and DSS software would reduce problems with external validity by providing more realistic laboratory models. This paper presents a software package that offers considerable potential as a common tool for DSS research.