Performance Of Individual Users Research Articles

Met the expectations? A meta-analysis of the performance consequences of digital HRM

As the digitalization of Human Resource Management (HRM) has been going on for more than half a century the performance and, thus, the future continuance and intensification of digital HRM is regularly taken for granted. While there is a growing and increasingly unmanageable number of research contributions on the performance consequences of digital HRM, core reviews fail to offer consistent and convincing evidence on digital HRM performance. Current sentiments and implementations are based on implicit expectations rather than on explicit evidence. To provide the future digitalization of HRM with the necessary evidence, we conduct a meta-analysis on the performance consequences of digital HRM. Concretely, we analyze the performance of individual users, the operational, relational, and transformational performance of HRM, and the corporate performance of the entire organization. Based on evidence from 96 empirical studies with a total sample size of 37,924, our meta-analysis finds significant medium-sized associations between digital HRM and all performance categories. We also resolve the partially contradictory findings, quantify and compare performance effects, and uncover moderating effects. Our paper provides the so far lacking evidence that digital HRM constitutes a successful endeavor, which meets its performance expectations and thus should be continued and intensified in the future.

Examining the effect of user satisfaction and business intelligence system usage on individual job performance

Business intelligence systems are in widespread use today due to the many business benefits. Users are one of the key stakeholders in the business intelligence process. For optimal system adaptation, the user should be able to interact with the application in order to improve its capacity to contribute to decision-making. For the business intelligence process itself to be effective, it is necessary to define the user needs regardless of the type of work they do. If the user is satisfied and thinks that the system improves his/her performance or the quality of decisions made, they will want to use it even more. System usage has sometimes been viewed as a direct reflection of system performance; however, this is difficult to define in organizations where system usage is mandatory. Business intelligence systems are especially mandatory to use, as they are used in large organizations and require greater investment than other systems. This is why it is important to investigate the nature of system usage and its impact on individual performance. This research model deals with determinants that represent dimensions of the information system's success theory. Those determinants are: user satisfaction, intention to use, system usage, and individual performance. Obtained results show that increased user satisfaction and intention to use, lead to increased system usage and that both the increase in user satisfaction and system usage lead to a rise in individual user performance.

Towards a Deep Analysis of Millimeter Wave D2D Underlaid Cellular Networks

This paper provides a deep analysis for millimeter-wave device-to-device (mm-wave D2D) underlaid cellular networks to investigate how the performance of individual users or link percentiles under constraints are affected by the interaction between D2D and cellular communication modes integrated with the salient mm-wave features. Under a general Nakagami fading model, we derive the upper bounds for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$b$ </tex-math></inline-formula> -moments of the conditional signal-to-interference-noise ratio (SINR) distributions for the two modes given the network realization, and further calculate the upper bounds of SINR meta distributions (MDs). Moreover, we extend the MD-based analysis to evaluate the fine-grained performance for the transmission effectiveness, through deriving the bounding results for the user-perceived rate MD and spatial rate capacity (SRC), the latter of which is defined as the effective density of users satisfying a given transmission rate requirement with a certain probability. Numerical results validate the tightness of the proposed bounds and reveal the different effects of the network configuration parameter associated with mm-wave on the link and network performances from the view of individual users.

A Machine Learning Approach to Enhance the Performance of D2D-Enabled Clustered Networks

Clustering has been suggested as an effective technique to enhance the performance of multicasting networks. Typically, a cluster head is selected to broadcast the cached content to its cluster members utilizing Device-to-Device (D2D) communication. However, some users can attain better performance by being connected with the Evolved Node B (eNB) rather than being in the clusters. In this article, we apply machine learning algorithms, namely Support Vector Machine, Random Forest, and Deep Neural Network to identify the users that should be serviced by the eNB. We therefore propose a mixed-mode content distribution scheme where the cluster heads and eNB service the two segregated groups of users to improve the performance of existing clustering schemes. A D2D-enabled multicasting scenario has been set up to perform a comprehensive simulation study that demonstrates that by utilizing the mixed-mode scheme, the performance of individual users, as well as the whole network, improve significantly in terms of throughput, energy consumption, and fairness. This study also demonstrates the trade-off between eNB loading and performance improvement for various parameters.

A method for identifying faulty cells using a classification tree-based UE diagnosis in LTE

The latest advances in wireless technologies have led to a proliferation of data mobile devices and services. As a consequence, mobile networks have experienced a significant increase in data traffic, while voice traffic has shown nearly no growth. It is therefore essential for operators to understand the data traffic behavior at the user level in order to ensure a good customer experience. In the radio access networks (RANs), traditional solutions based on cell-level measurements are not adequate to analyze performance of individual users. Instead, novel alternatives such as the use of call traces and the definition of new user-centric indicators will provide detailed and valuable information for each connection. One of the key measurements related to data services is the user throughput. In this work, the user throughput is adopted as the main attribute to conduct diagnosis in the RAN, which has typically been the bottleneck for data services. To that end, a binary classification tree is proposed to determine the root cause of poor throughput in user-level data sessions. Then, this information is aggregated at the cell level in order to provide effective diagnosis of degraded cells. In particular, a correlation-based analysis of the cell status is proposed in order to identify abnormal cell behaviors in an automatic way. Evaluation has been carried out with datasets from live cellular networks. Results show that the proposed diagnosis approach is an effective means to identify the main factors that limit the user throughput in network cells.

Information system users’ creativity

PurposeInformation technology has been recognized as one of the keys to improved productivity in organizations. Yet, existing research has not paid sufficient attention to how information systems (ISs) influence the creative performance of individual users. The paper aims to discuss this issue.Design/methodology/approachThis study draws on the theories of flow and cognitive load to establish a model of the predicted influences. The authors hypothesize that the information technology supports creativity by engaging individuals in a creative process and by lowering their cognitive load related to the process. To test these hypotheses, the authors employ a meta-analytical structural equation modeling approach using 24 previous studies on creativity and ISs use.FindingsThe results suggest that factors that help the user to maintain an interest in the performed task, immerse the user in a state of flow, and lower a person’s cognitive load during IS use can affect the user’s creative performance.Research limitations/implicationsThe findings imply that a combination of the theories of flow and cognitive load complements the understanding of how ISs influence creativity.Originality/valueThis paper proposes an explanation on why ISs affect creativity, which can be used by scholars to position further research, and by practitioners to implement creativity support systems.

Statistical quality of service provisioning in multi‐user centralised networks

Statistical quality of service (QoS) provisioning is a performance metric that determine the user satisfaction as the main purpose of future wireless networks. Effective capacity (EC) is a valuable quantity which helps analysing delay QoS performance as the most popular QoS metric. In this study, the authors concentrate on characterising the delay QoS performance via the EC of uplink transmission mode of individual users in multiuser centralised networks in which the user's transmitted signals may interfere with each other. To reduce the computational complexity of finding EC, the authors first propose closed form expressions for the EC of each user, with or without considering the inter-symbol interference (ISI). Then, two general algorithms are presented to clarify the relation of EC and QoS guarantee performance of a system in which the way of analysing QoS guarantee performance is explained step-by-step. By the use of these algorithms and the obtained closed form EC functions, the authors investigate the statistical delay QoS performance of individual users and the effects of channel conditions and ISI on their performance. The numerical results validate our analytical outcomes in deriving closed form equations and evaluate the offered schemes in characterising delay QoS performance.

Research Note—A Multilevel Analysis of the Effect of Group Appropriation on Collaborative Technologies Use and Performance

This study develops a comprehensive model to predict and explain the use of collaborative technologies (CT) and the task performance of individual users as a result of using CT. The integrated model attempts to capture how the individual user's extent of use of CT is a function of both the technical features and the structures embedded within or created by the interactions among the technology, group, and organization. The model developed is tested using data collected from a national bank with 279 members working in 40 different workgroups. A hierarchical linear model (HLM) is used to test the hypotheses generated from the model. Results show that our integrated model provides a more complete explanation of the use of CT and task performance beyond those of the individual-level factors. The study is an early effort to develop an integrated theory to provide comprehensive insight into individual use of CT in a group or organizational context.

Localized access point selection in infrastructure wireless LANs with performance guarantee

AbstractEfficient network management can improve the network performance and reduce the cost of system maintenance and administration. One of the important duties assigned to the network management system in a infrastructure wireless LAN (or simply wireless LAN) is to assign users to appropriate accessible access points (APs). The current AP selection schemes in wireless LANs cause an unbalanced load, which in turn reduces the performance of individual users. This has motivated intensive studies attempting to determine efficient methods to balance loads among different APs. Existing works either provide heuristic solutions without performance guarantees or provide centralized solutions which are not desirable for the AP selection problem. In this paper, we study the localized solutions that can provide performance guarantees. We model the AP selection problem as a matching problem in bipartite graph. Our objective is to maximize total load among all APs. We propose a class of localized heuristics based on different user knowledge models. For some of these localized heuristics, we prove that there exists a constant approximation ratio in terms of expected total load through mathematical analysis. Simulations are conducted to verify our results. Copyright © 2009 John Wiley &amp; Sons, Ltd.

User Level Fairness of a Multirate 3G Technology (EVDO) With Application to Digital TV Return Channel Technology

In this work we investigate the end-to-end performance of individual users when a particular multi-rate 3G wireless air-interface is adopted. This technology, similarly to most modern wireless communications systems, adopt an adaptive modulation and coding procedure and a schedule algorithm that favors users that enjoy better channel/interference conditions aiming at optimizing the overall system throughput. The motivation for this effort was the choice of a radio technology to implement a return channel for a countrywide digital TV system. In this application it is essential that the quality of service offered to users does not differ substantially due to their geographical location that, in most instances, will be fixed. In order to evaluate user performance we implemented a simulation model for the EVDO technology, including detailed physical and link layer characteristics. Using this tool for a very general scenario that mixes a majority of fixed users with some mobile terminals it was observed that the average user performance is very adequate for the intended application. However, there are severe differences in performance depending on the positioning of the terminals. We discuss different ways of overcoming the user-level unfairness of this technology that do not depend on modifications to the scheduling algorithm because we feel that these would be ineffective to cope with the tradeoff between user fairness and system throughput. It is then shown that a simple solution can greatly improve the fairness characteristics without sacrificing the overall throughput.

Comparison of pilot symbol-assisted and differentially detected BPSK for DS-CDMA systems employing RAKE receivers in Rayleigh fading channels

The capacity of a code-division multiple-access (CDMA) system is a function of the bit error rate (BER) performance of individual users. Therefore, it is important to optimize the individual links before proceeding to system level analysis. This is particularly true for operating in a fading channel where the performance without diversity reception is rather poor. This paper compares the BER performance of differential detection and pilot symbol-assisted coherent detection of a direct-sequence (DS) spread-spectrum (SS) signal on a frequency-selective Rayleigh fading channel using RAKE reception. Both equal gain and maximal ratio combining are considered, and the effect of convolutional coding with interleaving is studied. It is shown that in the particular cases considered in this paper, rate 1/8 convolutionally encoded pilot symbol-assisted BPSK performs better than coded differential detection, thus providing a higher system capacity.

An Empirical Examination of the Value of Creativity Support Systems on Idea Generation

Because organizations seek more innovative ways to compete, the ability of their employees to generate new and valuable ideas becomes a fundamental survival skill. To the extent that computer software might enhance the creative performance of individual users, organizations might ultimately apply such tools to enhance the creative performance of their employees. A controlled laboratory experiment was performed to determine whether two popular creativity support applications significantly enhanced the creative performance of individual users. The results suggest that responses generated with software support are significantly more novel and valuable than responses generated by pen and paper. The results also question the previous creativity research practice of not directly controlling for idea fluency prior to experimental manipulation. It is hoped the findings from this investigation can be used to improve individual creative performance, further research concerning factors relevant to creativity, and guide future ICSS development efforts.

Optimal decentralized flow control of Markovian queueing networks with multiple controllers

A Markovian queueing network model is used to derive decentralized flow control mechanisms in computer communication networks with multiple controllers. Under the network optimization criterion, finding the optimal decentralized flow control that maximizes the average network throughput under an average network delay bound becomes a team decision problem. It is shown that the network optimization problem depends on the parameters of the network only through the conditional estimates of the total arrival and departure rates. Using linear programming, the network optimal control is demonstrated to be a set of window-type mechanisms. Under the user optimization criterion, each individual user maximizes its average throughput subject to a constraint on its average time delay. Finding the optimal decentralized flow control under the individual user's performance results in a multiple objective optimization problem and leads to a game theoretic formulation. Structural results which simplify the problem are presented. It is shown that the user optimization problem depends on the parameters of the network and the action of the other users only through the conditional estimate of the user service rate. The Nash equilibrium solution under the game theoretic formulation is demonstrated to be a set of window-type mechanisms. Finally, the class of decentralized flow control problems with Nash equilibrium solutions is characterized.

Time-sharing and self-tutoring: an exploratory case history.

This study is concerned with the effectiveness of individual user performance for an extended self-tutoring task in a time-shared computing facility. The investigation is an experimental case history of one individual (the author) following the TINT self-tutoring user manual from beginning to end in the SDC Q-32 Time-Sharing System at a Teletype console. (TINT is a user-oriented dialect of JOVIAL, an interpretive language adapted to time-sharing with many self-teaching features.) The methodology featured measurement of natural user behavior in which the user served as his own control in successive console sessions. The sample included 1,861 user input commands collected over 18 hours at the teletypewriter terminal. The quantitative results revealed some evidence for systematic learning and reinforcement effects; there were progressive tendencies toward higher productivity and lower error rates with increasing TINT experience. The qualitative findings revealed that the numerous and diversified exercises facilitated familiarity with the elements and the varied services of the TINT system. The chief drawback was exclusive reliance of the tutoring method on literal reproduction of the text by the user at his console. The paper concludes with recommendations for more genuine interactive involvement between the user, the central system, and self-tutoring aids.