Mesbah U. Ahmed

Effects of interface style on user perceptions and behavioral intention to use computer systems

This study examines the influence of two interface styles (menu- and command-based) on the perceived ease of use, perceived usefulness, and behavioral intention of the user to use the system. We have treated the system interface style as an external factor in the technology acceptance model (TAM) to examine its direct and indirect effects on behavioral intention to accept and use a system. The results showed that the interface style had direct effects on perceived ease of use and perceived usefulness which, in turn, demonstrated significant effects on behavioral intention to use the system. Further, the results showed that perceptions of the menu-based interface were more favorable than perceptions of the command-based interface. These results provide several theoretical and practical implications for designing an effective system.

Documenting information systems for management: a key to maintaining user satisfaction

Abstract Executives responsible for the information system function need to be concerned about developing a base of satisfied users and maintaining continuing user satisfaction after implementation. This article focuses on user satisfaction among on-going user manager, explores the role of good user documentation, and examines the results of a survey of 144 user managers from 55 firms. The results indicate that good user documentation appears to be an important factor in insuring user understanding and continuing user satisfaction. Thus firms considering alternative ways of keeping users satisfied (i.e., personal computer applications, end user computing, or information centers) might well examine their user documentation practices before exploring other alternatives.

Minimizing the weighted sum of late and early completion penalties in a single machine

We consider the problem of scheduling n jobs on a single machine so as to minimize weighted absolute deviation of completion times from their due dates. The general problem is NP-complete, but we show how to solve a special case.

Expert systems adoption: an analytical study of managerial issues and concerns

Abstract The experience of introducing expert systems technology into six automotive component manufacturing organizations in the mid-western United States is described. The domain of expert system application as well as the procedural and organizational hurdles that were encountered are also documented. An overview of relevant literature shows the shortage of studies of this kind. A synthesis is provided of the study observations and implications for better management of expert systems adoption in manufacturing.

A Path Analysis of the Impact of Application-Specific Perceptions of Computer Self-Efficacy and Anxiety on Technology Acceptance

Perceptions of computer self-efficacy CSE and computer anxiety are valuable predictors of various computer-related behaviors, including acceptance and utilization of information systems IS. Although both factors are purported to have general and application-specific components, little research has focused on the application or system-specific component, especially in IS acceptance contexts. Thus, little is known about the effects of application-specific beliefs on IS acceptance or how such effects compare with the effects of more general CSE and computer anxiety beliefs. Accordingly, a research model comprising application CSE, application anxiety, perceived ease of use, perceived usefulness, attitude, and intention was proposed and tested via path analysis. The results demonstrated that the direct impacts of application CSE and application anxiety on perceived ease of use and perceived usefulness were almost equal, but in opposite directions. However, the indirect effect of application CSE on attitude and intention was stronger than that of application anxiety.

A volume and material handling cost based heuristic for designing cellular manufacturing cells

Abstract One of the major problems in a group technology or cellular manufacturing environment is the formation of part groups and machine cells. Because of the combinatorial nature of the cell formation problem, it is difficult to solve the problem optimally. Most of the procedures related to cell design in cellular manufacturing operate on the part-machine incidence matrix in an attempt to identify block diagonality. If complete block diagonality does not exist, the decision about cell configuration is left to the subjective judgement of the designer. These procedures are also generally based on part routing only, and do not consider part volume and material handling costs. In this paper we develop an integer programming model, as well as a heuristic to effectively assign machines to cells. In these procedures we consider component volumes, costs related to movement of components between and within cells, and penalty for not using all machines in a cell visited by a component. Since the integer programming formulation becomes large even for small problems, an efficient heuristic is developed to solve larger problems. The heuristic solutions to 180 randomly generated small problems were compared against the optimal solutions obtained by the integer programming model. The heuristic has been found to identify optimal solutions in all 180 cases. This heuristic is also compared to several well known algorithms on 900 larger test problems. These problems were generated to cover a wide range of environmental situations such as varying levels of block diagonality in the part-machine incidence matrix, and diversity in the component volumes and material handling costs. In 99% of the problems our heuristic generated solutions which are better or as good as the best solution obtained by other algorithms. Further, in situations where complete block diagonality in the part-machine incidence matrix did not exist, our heuristic produced even better results. Since the maximum number of iterations required in our heuristic is the number of machines in the problem, the heuristic is computationally efficient.

Dynamic single-machine-weighted absolute deviation problem: predictive heuristics and evaluation

We address a dynamic single-machine scheduling problem where the objective is to minimize the weighted absolute deviation of completion times from the due dates. This objective approximates a decisionmakers goal in a just-in-time environment which is the primary motivation for the problem. Several heuristics are developed and tested. We use a novel approach to heuristic development by designing it in modules. At each decision epoch, the front end provides a look-ahead feature, the main theme develops a sequence, and the balancing routine determines the schedule. The performance of the heuristics as well as modules of the heuristics are tested by simulation experiments across several classes of problems. By analysing the results we develop some guidelines for operational decisions.

Statistical Sampling to Instantiate Materialized View Selection Problems in Data Warehouses

In any online decision support system, the backbone is a data warehouse. In order to facilitate rapid response to complex business decision support queries, it is a common practice to materialize an appropriate set of the views at the data warehouse. However, it typically requires the solution of the Materialized View Selection (MVS) problem to select the right set of views to materialize in order to achieve a certain level of service given a limited amount of resource such as materialization time, storage space, or view maintenance time. Dynamic changes in the source data and the end users requirement necessitate rapid and repetitive instantiation and solution of the MVS problem. In an online decision support context, time is of the essence in finding acceptable solutions to this problem. In this chapter, we have used a novel approach to instantiate and solve four versions of the MVS problem using three sampling techniques and two databases. We compared these solutions with the optimal solutions corresponding to the actual problems. In our experimentation, we found that the sampling approach resulted in substantial savings in time while producing good solutions.

View Materialization in a Data Cube: Optimization Models and Heuristics

Data warehouse has become an integral part in developing a DSS in any organization. One of the key architectural issues concerning the efficient design of a data warehouse is to determine the “right†number of views to be materialized in order to minimize the query response time experienced by the decision makers in the organization. We consider a bottleneck objective in designing such a materialization scheme which has the effect of guaranteeing a certain level of performance. We examine linear integer programming formulations, and develop heuristics and report on the performance of these heuristics. We also evaluate heuristics reported in the literature for the view materialization problem with a simpler objective.