Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature*

A considerable amount of research has been conducted over a long period of time into the effects of graphical and tabular representations on decision-making performance. To date, however, the literature appears to have arrived at few conclusions with regard to the performance of the two representations. This paper addresses these issues by presenting a theory, based on information processing theory, to explain under what circumstances one representation outperforms the other. The fundamental aspects of the theory are: (1) although graphical and tabular representations may contain the same information, they present that information in fundamentally different ways; graphical representations emphasize spatial information, while tables emphasize symbolic information; (2) tasks can be divided into two types, spatial and symbolic, based on the type of information that facilitates their solution; (3) performance on a task will be enhanced when there is a cognitive fit (match) between the information emphasized in the representation type and that required by the task type; that is, when graphs support spatial tasks and when tables support symbolic tasks; (4) the processes or strategies problem solvers use are the crucial elements of cognitive fit since they provide the link between representation and task; the processes identified here are perceptual and analytical; (5) so long as there is a complete fit of representation, processes, and task type, each representation will lead to both quicker and more accurate problem solving. The theory is validated by its success in explaining the results of published studies that examine the performance of graphical and tabular representations in decision making.     

An Investigation of Localization as an Element of Cognitive Fit in Accounting Model Representations

Cognitive fit, a correspondence between task and data representation format, has been demonstrated to lead to superior task performance by individual users and has been posited as an explanation for performance differences among users of various problem representations such as tables, graphs, maps, and schematic faces. The current study extends cognitive fit to accounting models and integrates cognitive fit theory with the concept of localization to provide additional evidence for how cognitive fit works. Two accounting model representations are compared in this study, the traditional DCA (Debit‐Credit‐Account) accounting model and the REA (Resources‐Events‐Agents) accounting model. Results indicate that the localization of relevant objects or linkages is important in establishing cognitive fit.     

Assessment of leader problem-solving capabilities

We describe the development of and initial psychometric evidence for a set of five constructed response measures designed to assess complex problem-solving skills and knowledge expected to influence leadership. Structured (cued) and unstructured (uncued) problem solving scenarios intended to assess process skills associated with creative problem solving are presented first. Solution construction tasks developed to assess attention to constraints and characteristics in the broader problem context are presented next. Finally, social judgment tasks intended to assess understanding of people and social systems and a task sort to assess knowledge of leadership roles are presented. Preliminary evidence for the reliability and construct validity of these constructed response measures supports their efficacy in assessing skills that underlie effective organizational leadership.     

Presenting Geographic Information: Effects of Data Aggregation,Dispersion, and Users' Spatial Orientation

Geographic information systems (GIS) have taken on an increasingly important role supporting decision making in many organizations. GIS have been used to support a breadth of tasks including oil and mineral exploration, facility location, logistics support, and facilities management decisions. The effectiveness of GIS as a decision support tool comes primarily from the visual display of data in the form of maps. When presenting information as a geographic map, the level of data aggregation potentially affects aspects of task complexity such as information load and the potential for pattern recognition by the user. Other task attributes expected to be related to data aggregation effects include problem size, the degree of data dispersion, and users' spatial orientation skills. We conducted an experiment to study these effects and their interactions. Subjects used a GIS including map-based information characterized by different levels of problem size, data dispersion, and data aggregation. Spatial orientation skill was examined as a covariate in the experimental treatments. The results indicate that all of these geographic information characteristics have significant impacts on decision performance. Moreover, many interactions are present among the factors. We evaluate these interactions in order to derive implications for practice and for future research.     

The Emergence of Hypertext and Problem Solving: An Experimental Investigation of Accessing and Using Information from Linear versus Nonlinear Systems*

Past research suggests that problem solving and/or decision behavior can be altered and improved by the changes in the way information is accessed and displayed. Also, researchers have found that the usefulness of different information display formats are contingent on the characteristics of the problem task. This research investigated the impact on problem solving when accessing and using information from linear and nonlinear systems. Also, the research investigated problem-solving performance of linear and nonlinear systems when applied to different combinations of problem tasks. In a laboratory setting, linear and nonlinear systems were developed to conduct this experiment. This experiment used 64 graduate business students in a two-factor repeated-measures design employing a multivariate analysis of variance to analyze the data. Repeated measures were conducted to analyze the experimental group under both linear and nonlinear treatments. The findings from the study support the notion that the nonlinear system resulted in superior problem solving and higher levels of user satisfaction than the linear system. Specifically, the nonlinear system enabled users to make faster and more accurate decisions on perceptual problem tasks than did the linear system. For analytical problem tasks, users performed faster with the nonlinear system; however, there was no significant difference in accuracy. User satisfaction was higher with the nonlinear system under both perceptual and analytical tasks.     

Assembly Line Balancing with Resource Dependent Task Times*

Paced assembly lines are widely used in repetitive manufacturing applications. Most previous research on the design of paced lines has assumed that each task along the line can be performed by only one worker (or a fixed number of workers). In many cases, however, task duration times may be reduced by increasing the number of workers or changing the equipment assigned to work stations. Thus, the problem becomes one of assigning resource alternatives (e.g., workers and/or equipment) and tasks to work stations to minimize total cost for a desired production rate. For this problem, we present three procedures. The first formulates the problem as a shortest path problem and guarantees optimality. The second and third are heuristic adaptations of the shortest path procedure that are capable of solving large problems. The procedures are compared in terms of solution quality and computation time on a set of 128 randomly generated problems for which optimal solutions could be found. Our simulation results indicate that the choice of procedure depends on problem complexity and resource costs.     

Scheduling and packing malleable and parallel tasks with precedence constraints of bounded width

We study the problems of non-preemptively scheduling and packing malleable and parallel tasks with precedence constraints to minimize the makespan. In the scheduling variant, we allow the free choice of processors; in packing, each task must be assigned to a contiguous subset. Malleable tasks can be processed on different numbers of processors with varying processing times, while parallel tasks require a fixed number of processors. For precedence constraints of bounded width, we resolve the complexity status of the problem with any number of processors and any width bound. We present an FPTAS based on Dilworth’s decomposition theorem for the NP-hard problem variants, and exact efficient algorithms for all remaining special cases. For our positive results, we do not require the otherwise common monotonous penalty assumption on the processing times of malleable tasks, whereas our hardness results hold even when assuming this restriction. We complement our results by showing that these problems are all strongly NP-hard under precedence constraints which form a tree.     

Determinants and Consequences of Perceived Complexity in Human-Computer Interaction*

A number of recently published studies on human-computer interface variables report contradictory results. A lack of underlying theory may be the cause. This study investigates the usefulness of employing an intermediate variable–perceived complexity–in examining the impact of two information system (IS) variables on performance: the mode of presentation, which has been extensively studied; and the number of windows, which has scarcely been studied. The study demonstrates the usefulness of understanding the role of perceived complexity in human-computer interaction. The specific results support past findings with regard to graphs vs. tables and reveal new findings on the role of windows. Most interesting is the interaction between the two IS variables. The use of more windows is significantly more beneficial for tabular, rather than graphical, presentation. The realization that perceived complexity is affected by task complexity and by IS variables has important implications for the design of flexible information systems. These implications are discussed.     

Tour Scheduling and Task Assignment of a Heterogeneous Work Force: A Heuristic Approach

The dual problem of work tour scheduling and task assignment involving workers who differ in their times of availability and task qualifications is examined in this paper. The problem is presented in the context of a fast food restaurant, but applies equally well to a diverse set of service operations. Developing a week-long labor schedule is a nontrivial problem, in terms of complexity and importance, which a manager spends as much as a full workday solving. The primary scheduling objective (the manager's concern) is the minimization of overstaffing in the face of significant hourly and daily fluctuations in minimum staffing requirements. The secondary objective (the workers’ concern) is the minimization of the sum of the squared differences between the number of work hours scheduled and the number targeted for each employee. Contributing to scheduling complexity are constraints on the structure of work tours, including minimum and maximum shift lengths and a maximum number of workdays. A goal programming formulation of a representative problem is shown to be too large, for all practical purposes, to be solved optimally. Existing heuristic procedures related to this research possess inherent limitations which render them inadequate for our purposes. Subsequently, we propose and demonstrate a computerized heuristic procedure capable of producing a labor schedule requiring at most minor refinement by a manager.     

A fast greedy sequential heuristic for the vertex colouring problem based on bitwise operations

In this paper a fast greedy sequential heuristic for the vertex colouring problem is presented. The suggested algorithm builds the same colouring of the graph as the well-known greedy sequential heuristic in which on every step the current vertex is coloured in the minimum possible colour. Our main contributions include introduction of a special matrix of forbidden colours and application of efficient bitwise operations on bit representations of the adjacency and forbidden colours matrices. Computational experiments show that in comparison with the classical greedy heuristic the average speedup of the developed approach is 2.6 times on DIMACS instances.     

Group leadership and shared task representations in decision making groups

The development of adequate shared understanding of the task is of critical importance to group functioning. Group leaders play an important role in this respect, as a key function of leadership is to shape group members' understanding of their job. In the present study we focus on decision making groups with distributed information and examine how group leaders shape members' mental representations of the group decision task through leadership behavior rooted in their own representations of the task. We propose that the extent to which the group leader has task representations that emphasize information exchange and integration affects group members' task representations, group information elaboration, and decision quality. We tested these hypotheses in an experiment (N = 94 three-person groups) in which we manipulated whether a group leader was present and whether this leader held representations emphasizing information elaboration. Results supported the hypotheses, and suggest that team leaders may play an important role in creating a socially shared understanding of team tasks.     

Combinatorial Optimization in Real-Time Scheduling: Theory and Algorithms

Real-time computer systems are essential for many applications, such as robot control, avionics, medical instrumentation, manufacturing, etc. The correctness of the system depends on the temporal correctness as well as the functional correctness of the task executions. In order to assure temporal correctness it is necessary that the resources be scheduled to meet the temporal requirements of applications. When we consider the problem of nonpreemptive scheduling of a set of tasks in a processor for which no feasible solution exists, some tasks may have to be rejected so that a schedule can be generated for the rest. In this paper, we consider the problem of generating an optimal schedule such that the number of rejected tasks is minimized, and then the finish time is minimized for the accepted tasks. We propose to use an analytic approach to solve this problem. We first discuss the super sequence based technique which was originally proposed for reducing the search space in testing the feasibility of a task set. Then we show by the Conformation theorem that the super sequence constructed from the task set also provides a valid and reduced search space for the optimization problem. While the complexity of our scheduling algorithm in the worst case remains exponential, our simulation results show that the cost is reasonable for the average case.     

An Empirical Investigation of the Effects of Decision Aids on Problem-Solving Processes*

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem-solving processes in a semi-structured problem. Results indicate that decision aids influence the problem-solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem-solving processes into future examinations are proposed.     

Scheduling in a Management Context: Uncertain Processing Times and Non-Regular Performance Measures*

Decision makers often face scheduling problems in which processing times are not known with certainty. Non-regular performance measures, in which both earliness and tardiness are penalized, are also becoming more common in both manufacturing and service operations. We model a managerial environment with task processing times (which include sequenceindependent set-up times) prescribed by three-parameter lognormal distributions. Upon completion, each task derives a reward given by a particular piecewise-linear reward function. The objective is to select a sequence of tasks maximizing the expected total reward. The relative generality of the problem renders many enumerative methods inapplicable or computationally intractable. To overcome such difficulties we develop efficient priorityinduced construction (PIC) heuristics which build up a complete schedule by inserting tasks (singly from a list) into a partial sequence of tasks. In each partial and complete sequence a period of idle time is permitted prior to the first task. Performance on realistic-sized problems is very encouraging, with cost penalties averaging less than one percent.     

Education CREATIVE THINKING AND INNOVATIVE EDUCATION IN THE DECISION SCIENCES

Creative problem solving is seldom addressed directly in the decision sciences literature. The first half of this paper reviews current thinking about creativity and its educational importance. The remainder addresses creative problem-solving processes and, in particular, the process developed by Parnes, Noller and Biondi [24] and Osborn [23]. This process has been integrated into an OR/MS problem-solving course which is described. Conclusions and implications for decision sciences education and practice in general are discussed.     

Flexible home care scheduling

Home care services are in high demand given how they are steadily becoming the primary source of care for the elderly. Powerful decision support tools are indispensable for effectively managing available staff in the context of ever-increasing demand for care and limited caregiver availability. This paper advances home care literature by introducing flexible task durations, thereby enabling tasks to be completed faster and ultimately more care to be scheduled. This new concept, which originates from practice, introduces an additional decision to be made when creating a schedule, thereby greatly increasing the scheduling complexity. Consequently, this paper introduces a new optimization-based decision support model which allows for scheduling with flexible task duration, as well as other types of flexibility. A computational study quantifies the impact of: (i) scheduling with a finer task granularity thereby enabling accurate prioritization of high and low priority care, (ii) flexibility in task duration enabling tasks to be completed faster and more care to be scheduled, and (iii) increasing the number of different locations visited by a caregiver thereby enabling a trade-off between the number of serviced clients and caregiver workload. A new publicly available real-world data set is used, obtained directly from home care organizations operating in Flanders. Analysis of the computational results demonstrates that significant improvements in operational efficiency may be realized with minimal effort required by organizations. Furthermore, the proposed algorithm’s performance is confirmed by comparison against the bounds obtained by solving an integer programming formulation of the problem. Finally, a management policy scheme is proposed which, when gradually implemented in a home care organization, results in a more efficient and therefore cost-effective deployment of its workforce.     

Decision Making in an Automated Environment: The Effects of Anonymity and Proximity with a Group Decision Support System*

Recent advances in information systems technology have made it possible to support the work of interacting groups using networked personal computers. A laboratory experiment was conducted using a group decision support system to evaluate effects of anonymity and proximity on group process in automated group problem solving. Twenty groups of four persons each performed an idea-generating task using an interactive electronic brainstorming program. This experiment's main findings were: (1) Group members working anonymously and apart generated more comments. (2) Working in the same room increased satisfaction. (3) Highest levels of perceived system effectiveness were reported under anonymity.     

An Arborescent Network Formulation and Dual Ascent Based Procedure for the Two-Stage Multi-Item Dynamic Demand Lotsize Problem

Traditional approaches for modeling and solving dynamic demand lotsize problems are based on Zangwill's single-source network and dynamic programming algorithms. In this paper, we propose an arborescent fixed-charge network (ARBNET) programming model and dual ascent based branch-and-bound procedure for the two-stage multi-item dynamic demand lotsize problem. Computational results show that the new approach is significantly more efficient than earlier solution strategies. The largest set of problems that could be solved using dynamic programming contained 4 end items and 12 time periods, and required 475.38 CPU seconds per problem. The dual ascent algorithms averaged .06 CPU seconds for this problem set, and problems with 30 end items and 24 time periods were solved in 85.65 CPU seconds. Similar results verify the superiority of the new approach for handling backlogged demand. An additional advantage of the algorithm is the availability of a feasible solution, with a known worst-case optimality gap, throughout the problem-solving process.     

How transformational leadership works during team interactions: A behavioral process analysis

Transformational leadership is generally considered helpful for team functioning. However, the social dynamics underlying the benefits of transformational leadership remain elusive to date. To understand how and why transformational leadership can foster team functioning, this study focuses on leader–follower communication dynamics during team interactions. From the perspective of leadership as social problem solving, we argue that transformational leadership is linked to functional team problem-solving processes because transformational leaders use solution-focused communication (mediator model). In a sample of 30 videotaped problem-solving team meetings from two organizations, we coded transformational leadership style and the verbal behavioral interactions of leaders and team members over the course of their entire meetings (30,128 behavioral units in total). Multilevel results showed that transformational leadership was positively linked to functional problem-solving communication by team members. This positive relationship was mediated by leaders' solution-focused communication. Moreover, at the micro-level of conversational dynamics within the meeting process, lag sequential analysis revealed that leaders' ideas and solutions triggered subsequent solution statements by team members and inhibited counterproductive communication by team members, such as running off topic, criticizing, or complaining. We discuss theoretical and methodological implications for conceptualizing dynamic leader–follower processes as well as managerial implications for leading effective meetings in organizations.     

The Impact of Geographic Proximity on What to Buy,How to Buy,and Where to Buy: Evidence from High‐Tech Durable Goods Market*

Social contagion effects due to geographical proximity refer to the social effects wherein the behavior of an individual varies with the behavior of other individuals who are geographically close. Although the influence of such effects on consumer choices has been established in several contexts, much of the extant studies have focused on its effect on consumers’ decision of whether to buy a new product or adopt a new innovation. There has been no systematic examination of the influence of geographic proximity on other aspects of consumers’ product buying process such as what to buy (i.e., brand choice), how to buy (i.e., the channel), and where to buy (i.e., retailers). Such effects can matter significantly in high‐technology and durable goods markets and therefore, it is critical to understand the scope of these on consumers’ choice of retailers and channel as well. Drawing on literatures from word of mouth effects, ecommerce, and consumers’ perception of risk in their purchase process, we develop a set of hypotheses on the effect of geographic proximity on consumers’ choices of what to buy, how to buy, and where to buy. Leveraging a microlevel dataset of purchases of personal computers, we develop brand‐, retailer‐, and channel‐related measures of proximity effects at the individual consumer level and estimate a joint disaggregate model of the three choices that make up a product purchase process to test these hypotheses. Our results indicate a significant contagion effect on each of the three choices. Furthermore, we find evidence of a greater effect of geographic proximity on inexperienced consumers—those who are new to the product category. Our results thus help develop a holistic understanding of the influence of social contagion effects on consumers’ decision making.