Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem

In the global economy, the modern commercial and industrial organization needs to develop better methods of assessing the performance of the human resource than simply using performance measures such as efficiency or effectiveness. As organizations seek more aggressive ways to cut costs and to increase global competitiveness, the importance of establishing and sustaining high levels of employee performance increases. The main purpose of this paper is to solve the human performance improvement problem by employing Analytic Hierarchy Process (AHP) method. Decision makers (DMs) often deal with problems that involve multiple criteria. At given moments in time, companies will display characteristics that make certain factors; key factors in their competences. In this paper, we present a model, which illustrates the relations and importance between human performance improvement and the style of management. In using the AHP to model this problem, we developed a hierarchic structure to represent the problem of human performance management and made pairwise comparisons. In this paper, the AHP is suggested as a tool for implementing a multiple criteria performance improvement scheme. The AHP was used for the purpose of structuring and clarifying the relations and importance between human performance improvement and the style of management. The study found that in terms of company culture, participation, human capability, and attitudes the best management style in improving human performance is management by values.     

Development of fuzzy process accuracy index for decision making problems

Several statistical decision making tools and methods are available to organize evidence, evaluate risks, and aid in decision making. Process capability indices are the summary statistics to point out the process performance. In this paper, these indices are analyzed to obtain a new decision making tool. Process accuracy index (C_a) measures the degree of process centering and gives alerts when the process mean departures from the target value. It focuses on the location of process mean and the distance between mean and target value. We modify the traditional process accuracy index to obtain a new tool under fuzziness. With the proposed tool, specification limits and process mean can be defined as triangular or trapezoidal fuzzy numbers. The proposed tool is illustrated to solve a supplier selection problem.     

Data analytics competency for improving firm decision making performance

This study develops and validates the concept of Data Analytics Competency as a five multidimensional formative index (i.e., data quality, bigness of data, analytical skills, domain knowledge, and tools sophistication) and empirically examines its impact on firm decision making performance (i.e., decision quality and decision efficiency). The findings based on an empirical analysis of survey data from 151 Information Technology managers and data analysts demonstrate a large, significant, positive relationship between data analytics competency and firm decision making performance. The results reveal that all dimensions of data analytics competency significantly improve decision quality. Furthermore, interestingly, all dimensions, except bigness of data, significantly increase decision efficiency. This is the first known empirical study to conceptualize, operationalize and validate the concept of data analytics competency and to study its impact on decision making performance. The validity of the data analytics competency construct as conceived and operationalized, suggests the potential for future research evaluating its relationships with possible antecedents and consequences. For practitioners, the results provide important guidelines for increasing firm decision making performance through the use of data analytics.     

Online information search and decision making: Effects of web search stance

A naturalistic online information search exposes individuals to multiple sites and conflicting perspectives. In this study, we evaluated how the holistic stance of a web search toward a product influences purchasing decisions. We recruited 109 participants who completed an initial product choice task regarding bottled water, a brief Internet search, and then a second post-search product choice task. Internet searches were analyzed to identify query terms, site visits, and stance. Results show that query terms influenced the types of sites obtained in a search, which in turn shaped the overall search stance. Participants were more likely to buy bottled water when they visited websites that emphasized environmental, economic, or health benefits for bottled water (i.e., positive stance). Participants who were asked to focus on environmental issues were less likely to buy bottled water unless packaged in recycled plastic.     

Towards agent-based decision making in the electronic marketplace: interactive recommendation and automated negotiation

The bloom of electronic commerce has changed the whole outlook of traditional trading behavior. Through the Internet, different business entities can now easily interact with each other and then have their transactions within a minimum time. However, the advanced hardware facilities for Internet infrastructure and the entrancing Web sites are not the only decisive factors to guarantee a successful business in the electronic market. To enable the transactions, the problems that ensue during the complicated activities in electronic commerce have to be resolved. This paper presents an agent-based system to support two types of activities most related to the decision-making process in the Internet commerce. The first part of our system is for interactive recommendation; and the second part, for automated negotiation. Experiments have been conducted to evaluate their corresponding performance and the results show the efficiency of the proposed system and its potential toward the future electronic market.     

A De Novo multi-approaches multi-criteria decision making technique with an application in performance evaluation of material handling device

Application of multiple conventional approaches to a particular multi-criteria decision making (MCDM) problem often suffers rank reversal giving rise to confusion and ambiguity in appropriate decision making. To eradicate the confusion, this paper proposes a De Novo multi-approaches multi-criteria decision making method namely Technique of Precise Order Preference (TPOP). The TPOP first examines the inconsistency in the ranking order of the alternatives of a MCDM problem by using multiple conventional approaches. If inconsistency/rank reversal in ranking order of the alternatives exists then TPOP, using advanced version of entropy weighting method introduced in this research work, measures weights of the final selection values of conventional approaches. Subsequently, TPOP based on these weights and final selection values computes precise selection indices (PSI) that determines accurate ranking order for the alternatives. The proposed technique is illustrated by two real life examples on material handling device (MHD) ranking and selection problems. The first example is initially solved using five conventional integrated fuzzy multi-criteria decision making techniques (FMCDMs) whereas the second example is taken from previous researchers’ works. The results obtained using TPOP justify the validity, applicability and requirements of the proposed technique. The study shows that the proposed multi-approaches, multi-criteria decision making technique can be a useful and effective model in MCDM.     

The methodology of multiple-criteria decision making in the optimization of an urban transportation system: case study of Poznań City in Poland

The methodology of multiple-criteria decision making applied to the optimization of an urban transportation system is presented in the paper. Three mathematical models of different complexity are constructed to optimize the allocation of vehicles to certain routes in a mass transit system. All models take into account both passengers' and operator's objectives. The optimization problems are formulated in terms of multiple-objective fuzzy linear programming and multiple-objective non-linear programming. The sensitivity and precision analysis of the models is carried out. Two interactive multi-objective mathematical programming procedures are utilized to solve the problems. They generate samples of Pareto-optimal compromise solutions and provide the decision maker (DM)with an effective tool that supports him/her in the decision making process. Finally, the DM selects the solution that best fits his or her expectations.     

A two-layer fuzzy synthetic strategy for operational performance assessment of an industrial hydrocracking process

The operating performance may deteriorate from the optimal condition in industrial hydrocracking process due to changes in product requirements, equipment performance degradation, environmental noises, and random disturbances, etc. Therefore, it is necessary to carry out effective online operating performance assessment for it. In this paper, a two-layer fuzzy synthetic strategy is proposed for operating performance assessment of the hydrocracking process. First, an operating performance assessment index is constructed based on the concept of positive deviation of the quality variables. As there are many products in the process, an assessment system is further built based on the performance index. To calculate the indicators in the assessment index system in real-time, partial least squares is used for prediction. To solve the problem of limited labeled samples in the prediction, the process variables are classified into several subspace blocks according to their correlations with different key indicators. Then, a two-layer fuzzy synthetic evaluation strategy is designed to evaluate the actual operating performance of the hydrocracking process. The proposed strategy is finally illustrated with a series of cases on an industrial hydrocracking process in China.     

Developing an research and development (R&D) process improvement system to simulate the performance of R&D activities

Because of a shorter R&D cycle time and the increasing complexity of technology development, efficient decision support systems for R&D activities are necessary to facilitate R&D processes. In particular, small and medium enterprises (SMEs) require efficiency of R&D projects due to a lack of R&D budgets and resources. Therefore, this paper aims to develop a system which can assess current levels of R&D processes of companies and improve problematic processes. To this end, the proposed system applies a standard R&D process to evaluate the R&D level of companies, including four types of database and three modules: performance level analysis, comparison analysis, and performance simulation analysis. First, the module of performance level analysis aims to draw strong and weak R&D processes of companies, using three factors: importance, performance goal and current performance on each process. The second module provides the function of comparison analysis that compares the performance level of a company with that of others. Finally, the performance simulation analysis investigates influences of critical processes on R&D outcomes and predicts how much the processes can enhance technical, economic and process outcomes. In particular, a case study is presented to illustrate the application of the proposed system to an IT company. This system can help managers enhance their R&D performance by presenting necessary improvements on critical processes.     

EMUSIM: an integrated emulation and simulation environment for modeling,evaluation, and validation of performance of Cloud computing applications

Cloud computing allows the deployment and delivery of application services for users worldwide. Software as a Service providers with limited upfront budget can take advantage of Cloud computing and lease the required capacity in a pay‐as‐you‐go basis, which also enables flexible and dynamic resource allocation according to service demand. One key challenge potential Cloud customers have before renting resources is to know how their services will behave in a set of resources and the costs involved when growing and shrinking their resource pool. Most of the studies in this area rely on simulation‐based experiments, which consider simplified modeling of applications and computing environment. In order to better predict service's behavior on Cloud platforms, we developed an integrated architecture that is based on both simulation and emulation. The proposed architecture, named EMUSIM, automatically extracts information from application behavior via emulation and then uses this information to generate the corresponding simulation model. We performed experiments using an image processing application as a case study and found that EMUSIM was able to accurately model such application via emulation and use the model to supply information about its potential performance in a Cloud provider. We also discuss our experience using EMUSIM for deploying applications in a real public Cloud provider. EMUSIM is based on an open source software stack and therefore it can be extended for analysis behavior of several other applications. Copyright © 2012 John Wiley & Sons, Ltd.     

The role of creation mode and social networking mode in knowledge creation performance: Mediation effect of creation process

This study proposes and empirically examines a research model that incorporates the knowledge creation mode and social networking mode to describe knowledge creation performance. The mediation effect of the knowledge creation process is explored in terms of socialization, externalization, combination, and internalization (SECI). The data collected from the manufacturing and service industries in Taiwan were analyzed. The goal-driven mode and web topology are found to be significantly associated with product or service creation primarily because of the creation efficacy aspect. The SECI with web topology has a mediation function when the goal-driven mode is adopted. Implications and suggestions are also provided.     

An e-commerce performance assessment model: Its development and an initial test on e-commerce applications in the retail sector of China

We developed a performance assessment model for e-commerce; it included indicators, indicator weights, and evaluation methods. The model has seven methods of assessing e-commerce performance and uses four criteria to compare and select the appropriate one for a particular situation. This model was tested in the retail sector of China. According to the data collected from 70 Chinese retailers, 16 indicators of e-commerce performance consisted of four constructs: marketing and sales, customer service, supply chain efficiency, and financial performance. The indicators for those constructs provide a comprehensive measurement of performance. Then weights were assigned for each indicator using a majority aggregation method. Comparison of the results from seven evaluation methods showed that discordance analysis and simple additive weighting were the best evaluation methods for the enterprises we had sampled.     

Presence and task performance: an approach in the light of cognitive style

The paper highlights the relationship between each of four bi-polar dimensions of personality cognitive style, such as extraversion–introversion, sensing–intuition, thinking–feeling and judging–perceiving, and the level of sense of presence experienced. Findings indicate that individuals who are more sensitive, more feeling or more introverted experience a higher level of presence. While not reaching statistical significance, differing cognitive styles appear to impact on task performance. The apparent negative relationship discovered between sense of presence and task performance should be considered in the light of task characteristics. We discuss the implications of these findings and how they contribute to an understanding of the complex relationship that exists between presence and task performance and how this subsequently ought to influence the design of virtual environments.     

The effect of process tailoring on software project performance: The role of team absorptive capacity and its knowledge‐based enablers

Software process tailoring (SPT) is a team‐based and learning‐intensive activity that addresses the particular dynamic characteristics of a development project. Because SPT critically influences how projects are conducted, its performance should be investigated. However, the extant literature lacks empirical evidence on how the underlying effects of SPT performance and its team‐supportive factors operate and influence software project performance. From the knowledge perspective, this study adopts dynamic capabilities theory and considers the learning ability and absorptive capacity of software project teams to develop a theoretical model to address this gap. The results of an empirical examination of the model with 135 software project teams advance our understanding of how team‐level learning antecedents—experience, communication quality and trust—dynamically facilitate teams' absorptive capacity (AC) when they conduct SPT, which in turn reinforces project performance. The mediating effects of the proposed model are unveiled and discussed, and theoretical implications as well as practical guidance for how AC and these factors promote SPT and project performance are suggested.     

Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study

In this study, secondary school teachers’ acceptance of a digital learning environment (DLE) was investigated. Questionnaires were taken on three times (T1/T2/T3) during the same school year, with the Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical framework. Next to questionnaires, user-logs were collected during the entire school year. A total of 72 teachers completed a questionnaire on at least one occasion: 64 teachers responded at T1, 41 at T2, and 55 at T3. We first investigated which factors influence teachers’ acceptance of a DLE. The main predictors of DLE acceptance were performance expectancy and social influence by superiors to use the DLE. Effort expectancy and facilitating conditions were of minor importance. We then investigated how well the amount of final observed use could be predicted, and found that at T1 about one third, at T2 about one fourth and at T3 about half of the variance in observed use was predicted by attitude, behavioral intention and self-reported frequency of use. Our study showed that to maximize use of a DLE, its usefulness should be demonstrated, while school boards or principals should strongly encourage teachers to (start to) use the DLE.