An experimental investigation of the impact of NSS and proximity on negotiation outcomes

Negotiations are often not as rational as desired due to the cognitive difficulty of finding optimal agreements. With higher information-processing capacity and capability, negotiation support systems (NSS) are viewed as a viable solution to overcome this difficulty and help negotiators achieve integrative agreements. In addition, advances in network communication technology have enabled distributed meetings to be carried out easily. This in turn leads to the notion of conducting distributed negotiations by combining NSS and distributed communication technology. This study examined the impact of NSS in face-to-face and distributed settings. The results suggested that NSS led to higher and fairer outcomes for both face-to-face and distributed dyads. Another interesting finding from this study is that there were gains with respect to initial expectations of outcomes when NSS support was provided. As corporations expand globally, NSS will play a significant role in coordinating distributed negotiations, saving time and cost.     

An experimental investigation of personality types impact on pair effectiveness in pair programming

In this paper, pair programming is empirically investigated from the perspective of developer personalities and temperaments and how they affect pair effectiveness. A controlled experiment was conducted to investigate the impact of developer personalities and temperaments on communication, pair performance and pair viability-collaboration. The experiment involved 70 undergraduate students and the objective was to compare pairs of heterogeneous developer personalities and temperaments with pairs of homogeneous personalities and temperaments, in terms of pair effectiveness. Pair effectiveness is expressed in terms of pair performance, measured by communication, velocity, design correctness and passed acceptance tests, and pair collaboration-viability measured by developers’ satisfaction, knowledge acquisition and participation. The results have shown that there is important difference between the two groups, indicating better communication, pair performance and pair collaboration-viability for the pairs with heterogeneous personalities and temperaments. In order to provide an objective assessment of the differences between the two groups of pairs, a number of statistical tests and stepwise Discriminant Analysis were used.

An experimental investigation of the impact of domain complexity on knowledge acquisition (KA) methods

This paper experimentally examines the effects of domain complexity on the quality of knowledge acquired and the efficiency with which knowledge acquisition (KA) is accomplished. The experiment is performed using two of the most prominent KA methods: unstructured interviews and protocol analysis. One contribution of the research is that it employs an experimental strategy that pays particular attention to addressing problematic issues of measurement and control. The experimental results indicate that domain complexity strongly influences the quality of knowledge acquired when protocol analysis is used for KA. While finding the other hypotheses to be inconclusive, some interesting trends were also identified regarding the quality and efficiency of knowledge acquisition methods.     

An experimental investigation of the impact of aggregation on the performance of data mining with logistic regression

We studied the impact of data aggregation on the performance of logistic regression on predicting the direction of the Dow Jones industrial average (DJIA) stock market index. Data aggregation is a common operation in business, science, engineering, medicine, etc.; it is performed for purposes such as statistical, financial, and sales and marketing analysis — particularly within the context of a data warehouse. We showed experimentally that, for this example, as long as aggregation does not shrink the sample size unduly, it does not significantly impair the performance of the logistic regression model for predicting the direction of the DJIA stock market index. We also observed that aggregation-based models are simpler (less over-parameterized) than detail-based models. We used the receiver operating characteristic (ROC) analysis to evaluate the robustness of such predictive models. Specifically, we used the area under the ROC curve as a summary measure of the overall performance of a given model.     

The impact of available information on negotiation results

Negotiation is the most famous tool for reaching an agreement between parties. Usually, the different parties can be modeled as a buyer and a seller, who negotiate about the price of a given item. In most cases, the parties have incomplete information about one another, but they can invest money and efforts in order to acquire information about each other. This leads to the question of how much each party will be willing to invest on information about its opponent, prior to the negotiation process. In this paper, we consider the profitability of automated negotiators acquiring information on their opponents. In our model, a buyer and a seller negotiate on the price of a given item. Time is costly, and incomplete information exists about the reservation price of both parties. The reservation price of the buyer is the maximum price it is willing to pay for an item or service, and the reservation price of the seller is the minimum price it is willing to receive in order to sell the item or service. Our research is based on Cramton’s symmetrical protocol of negotiation that provides the agents with stable and symmetric strategies, and involves a delay in proposing an offer for signaling. The parties in Cramton’s model delay their offers in order to signal their strength, and then an agreement is reached after one or two offers. We determine the Nash equilibrium for agents that prefer to purchase information. Then, in addition to the theoretical background, we used simulations to check which type of equilibrium will actually be obtained. We found that in most of the cases, each agent will prefer to purchase information only if its opponent does. The reason for these results lies in the fact that an agent that prefers to purchase information according to a one-side method, signals its weakness and thereby reduces its position in the negotiation. Our results demonstrate the efficiency of joint information acquisition by both agents, but they also show that one-sided information purchasing may be inefficient, if the acquisition activity is revealed by the opponent, which causes it to infer that the informed agent is relatively weak.     

Online teaching and technological affordances: An experimental investigation into the impact of modality and clarity on perceived and actual learning

Online courses have become commonplace at many institutions of higher education. While the popularity on online courses is growing, there are still many questions regarding the effectiveness of such courses in facilitating learning outcomes. Using theories from mass communication and education, we designed an online lecture which employed a 2 (modality) × 2 (clarity) between-subjects factorial design to better understand how variations in the mode (text only; audio and text) and structure/clarity (high clarity; low clarity) of information impacted feelings of instructor closeness, credibility, and perceived and actual learning. Results indicated that online lectures presented in a multimodal format were better at facilitating positive student experiences with instructors, as well as perceived and actual learning than lectures that contained only one mode of information. Implications of these findings are discussed with a specific focus on instructional design and technology.     

An investigation of the impact of abusive supervision on technology end-users

Although they are likely to occur in many organizations, few research efforts have examined the impact of negative supervisor behaviors on technology end-users. In this study we investigate abusive supervision, and the effects it has on perceptions about the work and psychological, attitudinal, and behavioral intention outcomes. Our sample consisted of 225 technology end-users from a large variety of organizations. Results revealed that abusive supervision has a positive impact on perceived pressure to produce, time pressure, and work overload, and a negative impact on liking computer work, and ultimately these variables impact job strain, frustration, turnover intentions, and job satisfaction.     

An investigation on the impact of auditory and haptic feedback on rhythmic walking interactions

This paper presents a system capable of rhythmic walking interaction by auditory and haptic display. Likewise, it summarizes the results of the research on the influence of the audio and haptic stimulation on rhythmic walking interaction. The system detects user’s footsteps and either provides interactive real-time feedback or suggests a pace using a synthetic walking sound or vibration. This pace is either a constant tempo or adapts to the walker. Auditory and haptic feedback signals are either ecological physically-based synthetic walking signals or simple sinusoidal beeps. In the experiment, the different auditory and haptic feedback and interaction modes are studied with respect to their effect on the walking tempo. The results show that participants synchronise equally well with the tempo with either audio or haptic cues, but indicate the audio–haptic conditions as the easiest to synchronise with. Moreover, results indicate that multimodal audio–haptic feedback provide the most natural feeling. These results have implications on the design of interactive entertainment or therapeutical applications.     

An experimental investigation of the predictive accuracy of induction and regression

As both research efforts and commercial adoption of Expert Systems (ESs) increase, knowledge acquisition continues to engage the attention of many ES developers. Many view the development of automated knowledge acquisition methods as one of the last remaining barriers to more widespread ES adoption and use. Rule induction has been advanced as a promising method of knowledge acquisition for expert systems, both to understand the weighting and importance of decision criteria and to provide a predictive capability for new examples. One important strand of research has naturally begun to compare the performance of rule induction to those of traditional statistical methods, such as multiple regression. In pursuing this subject, we document a comparison of the predictive capabilities of both induction and multiple regression. The study uses a sample of over 400 MBA students, employing their current GPA as the dependent variable or goal and prior (undergraduate) GPA and GMAT scores as independent or causal variables. An extensive comparison of both methods yields conclusions at variance with many previous studies which assert the superiority of the inductive method. Furthermore, the study identifies conditions under which the inductive method may be more effective as a predictor and develops recommendations for a contingency-based approach to knowledge acquisition for ES.     

An investigation of the impact of MVA normalization on the advanced front-end features

Feature normalization is a key objective in speech related applications. In this paper, we study the effects of the Mean subtraction, Variance normalization, and Autoregressive Moving Average (ARMA) filtering (MVA) normalization method on the ETSI Advanced Front-End (AFE) features. A series of experiments, on the Aurora-2 task, was conducted to show the impact of MVA normalization for different subsets of AFE feature components. Compared to the AFE baseline system, recognition results show performance improvement when only the logarithmic energy coefficient is normalized. However, the performance is degraded through the normalization of the rest of AFE coefficients. To investigate this degradation, other experiments were performed by eliminating the AFE implemented blind equalization post-processing block. It has shown that one part of this degradation can plausibly be interpreted as the effect of over-normalization caused by the MVA post-processing to the AFE original features. Furthermore, by analyzing the statistical distributions of AFE features we found that the effectiveness of MVA could also be affected by the high intra-frame variability of AFE features.     

Correlation and relaxation labelling: An experimental investigation on fast algorithms

This paper compares experimental results between three popular matching functions: the cross-correlation coefficient (CCC); the sum of squared difference (SSD); and sum of the absolute value of difference (SAVD), within our newly developed correlation-relaxation (C-R) framework (Wu 1995). The C-R framework is a general method for determining optical flow and has been applied to determining cloud motion from satellite images. SSD and SAVD are simpler and faster functions to calculate, when compared with CCC, and their uses can lead to significant savings in computer time in the initial selection of displacement candidates. Given that the image distortion is Gaussian noise, and the motion is translational, the study shows that while computationally more expensive, the performance of the CCC function is better, or at least no worse, than using SSD and SAVD in the selection of initial displacement candidates. Similarly, the performance of SSD is better, or no worse, than using SAVD. Computationally, SSD is the fastest among the three functions. In the presence of high level distortion, however, the poor quality of initial candidates selected using SSD and SAVD usually means a large number of iterations of the subsequent relaxation labelling process. In contrast, the CCC function gives high quality initial candidates, and only a small number of iterations are needed. The CCC function also usually leads to better final quality in motion estimations than that produced using the SSD or the SAVD function in the C-R algorithm. In the presence of moderate and low level distortion, however, the performance of SSD can be adequate, and its use can lead to faster processing without much sacrifice to the overall motion estimation quality.     

An experimental investigation into the process of knowledge-based systems development

This paper presents an experimental study into the processes that may contribute to building a better knowledge-based system. A model that defines quality to be composed of two related aspects, internal and external quality, is introduced. To test the model, 24 subjects developed a knowledge-based system for MBA course planning in an experimental setting over a 7 week period. Subjects were factored by development methodology (structured vs rapid prototyping), knowledge representation scheme used (rule-based vs hybrid) and programmer quality (naive vs experienced). The major finding is that an appropriate mix of development methodology, knowledge representation and personnel is necessary. No single development methodology or knowledge representation scheme is best, and a considerable number of interactions was observed in the experiment. Rapid prototyping combined with rule-based representation produced the best external quality in terms of functionality, but when combined with hybrid representation produced the worst. Similarly, rapid prototyping combined with hybrid representation produced the worst usability. Programmer quality had a positive effect on coding productivity, which in turn resulted in an increase in system usability. As with conventional software, increasing programmer quality can be very beneficial to both process and content. The study presented provides some evidence of the anomalies that are generated in the course of system development, and how they relate to internal quality. As might be expected, experienced programmers produced significantly fewer anomalies. A relationship was found between internal quality and usability, but not functionality.     

An experimental investigation of distributed matrix multiplication techniques

This paper discusses the development and refinement of several distributed matrix multiplication algorithms. Our goal in this research has been to determine if successful distribution of this problem is possible within a loosely-coupled environment. Our criteria for success are fast execution speed and, to a lesser extent, memory efficiency. Our results indicate that, perhaps counter-intuitively, it is possible to use distribution to improve the performance of dense matrix multiplication. The speed increase obtained ranges up to a factor of four, depending upon the algorithm and the process configuration used. Among the factors affecting performance are computational complexity, number and size of interprocess messages, and bookkeeping overhead. We conclude that this approach to matrix multiplication has potential. Furthermore, some of the principles discussed here may be usefully employed in the distribution of other algorithms of the same O(n³) computational complexity, such as LU decomposition (linear system solvers) and Cholesky factorization.     

An experimental investigation of formality in UML-based development

The object constraint language (OCL) was introduced as part of the Unified Modeling Language (UML). Its main purpose is to make UML models more precise and unambiguous by providing a constraint language describing constraints that the UML diagrams alone do not convey, including class invariants, operation contracts, and statechart guard conditions. There is an ongoing debate regarding the usefulness of using OCL in UML-based development, questioning whether the additional effort and formality is worth the benefit. It is argued that natural language may be sufficient, and using OCL may not bring any tangible benefits. This debate is in fact similar to the discussion about the effectiveness of formal methods in software engineering, but in a much more specific context. This paper presents the results of two controlled experiments that investigate the impact of using OCL on three software engineering activities using UML analysis models: detection of model defects through inspections, comprehension of the system logic and functionality, and impact analysis of changes. The results show that, once past an initial learning curve, significant benefits can be obtained by using OCL in combination with UML analysis diagrams to form a precise UML analysis model. But, this result is however conditioned on providing substantial, thorough training to the experiment participants.     

An investigation into the impact of safety features on the ergonomics of surgical scalpels

In the case of surgical scalpels, blade retraction and disposability have been incorporated into a number of commercial designs to address sharps injury and infection transmission issues. Despite these new designs, the traditional metal reusable scalpel is still extensively used and this paper attempts to determine whether the introduction of safety features has compromised the ergonomics and so potentially the take-up of the newer designs. Examples of scalpels have been analysed to determine the ergonomic impact of these design changes. Trials and questionnaires were carried out using both clinical and non-clinical user groups, with the trials making use of assessment of incision quality, cutting force, electromyography and video monitoring. The results showed that ergonomic performance was altered by the design changes and that while these could be for the worse, the introduction of safety features could act as a catalyst to encourage re-evaluation of the ergonomic demands of a highly traditional product.     

An experimental study of the impact of visual semantic feedback on novice programming

Prior empirical studies of programming have shown that novice programmers tend to program by exploration, relying on frequent compilation and execution of their code in order to make progress. One way visual and end-user programming environments have attempted to facilitate this exploratory programming process is through their support of “live” editing models, in which immediate visual feedback on a program's execution is provided automatically at edit time. Notice that the notion of “liveness” actually encompasses two distinct dimensions: (a) the amount of time a programmer must wait between editing a program and receiving visual feedback (feedback delay); and (b) whether such feedback is provided automatically, or whether the programmer must explicitly request it (feedback self-selection). While a few prior empirical studies of “live” editing do exist, none has specifically evaluated the impact of these dimensions of “live” editing within the context of the imperative programming paradigm commonly taught in first-semester computer science courses. As a preliminary step toward that end, we conducted an experimental study that investigated the impact of feedback self-selection on novice imperative programming. Our within-subjects design compared the impact of three different levels of feedback self-selection on syntactic and semantic correctness: (a) no visual feedback at all (the No Feedback treatment); (b) visual feedback, in the form of a visualization of the program's execution state, provided on request when a “run” button is hit (the Self-Select treatment); and (c) visual feedback, in the form of a visualization of the program's execution state, updated on every keystroke (the Automatic treatment). Participants in the Automatic and Self-Select treatments produced programs that had significantly fewer syntactic and semantic errors than those of the No Feedback treatment; however, no significant differences were found between the Automatic and Self-Select treatments. These results suggest that, at least in the case of novice imperative programming environments, the benefits of delivering a continuously updated visual representation of a program's execution may fail to justify the substantial costs of implementing such feedback. We recommend that programming environment designers instead direct their efforts toward carefully considering when programmers will be ready to take advantage of the feedback that is coming toward them, along with what content will be of most benefit to them.     

An experimental investigation of the influence of agentic and communal Facebook use on grandiose narcissism

Does activity on a social networking site (e.g., Facebook) increase grandiose narcissism? It was hypothesized that the type of activity (agentic vs. communal) might make a difference. In the first experiment, 88 males were randomly assigned to one of three computer activity conditions (agentic Facebook activity, communal Facebook activity, control computer activity). In the second experiment a larger and more diverse sample (N = 218) engaged in agentic, communal, or control activities either on a computer or not, in order to assess the impact of medium as well as thinking type. In both experiments, self-reported daily Facebook activity was correlated with narcissism. However, the experimental manipulation of agentic vs. communal Facebook use did not significantly increase state narcissism, as indicated by synthesizing the findings of the two experiments. The findings cast doubt on the notion that social networking site use promotes narcissism, though additional research on the topic is warranted.     

An experimental investigation of additional actuators on a submarine diesel generator

Additional actuators and active generator load control have been suggested to improve performance on submarine diesel generators. Until recently, a lack of systematic control design has limited the ability to thoroughly investigate their potential. In this paper, model predictive control is used to produce near-optimal actuator commands for an experimental diesel generator on a test bed capable of producing representative submarine operating conditions. The performance with different actuator subsets is compared against an existing speed governor control architecture over a range of operating conditions. It is demonstrated that a minimum of two actuators may substantially improve generator performance. The study also investigates how model predictive control, when combined with additional actuators, can be used to enforce appropriate operational constraints that may lead to better longevity of the generator.     

An investigation of the impact of media capabilities and extraversion on social presence and user satisfaction

A significant body of research examines media use and user satisfaction, and these studies are mostly focused on the choice of a specific media. The purpose of the present study is to investigate the effects of media capabilities and individual characteristics on social presence, and the subsequent impact on user satisfaction. Drawing on Media Synchronicity Theory, we propose a research model that identifies five physical media capabilities as the determinants of social presence (i.e. the degree to which individuals feel connected to others in online communities), and we then assess the effect of social presence on user satisfaction. Our results suggest that (1) certain media capabilities and (2) extraversion have a positive impact on whether individuals feel connected to others in online communities (i.e. computer-mediated communications). In addition, our moderation analysis shows that extraversion affects social presence differently across communication tasks, suggesting that social presence is a result of the dynamic interaction between media capabilities, the individual, and the task. These results should be of interest to organisations that rely upon virtual meetings to accomplish tasks, as well as to media developers who seek media capabilities that promote a feeling of connected communication between individuals in virtual space.