Can fuzzy Multi-Criteria Decision Making improve Strategic planning by balanced scorecard?

Strategic management is momentous for organizational success and competitive advantage in an increasingly turbulent business environment. Balanced scorecard (BSC) is a framework for evaluating strategic management performance which translates strategy into action via various sets of performance measurement indicators. The main objective of this research is to develop a new fuzzy group Multi-Criteria Decision Making (MCDM) model for strategic plans selection process in the BSC. For this to happen, the current study has implemented linguistic extension of MCDM model for robust selection of strategic plans. The new linguistic reasoning for group decision making is able to aggregate subjective evaluation of the decision makers and hence create an opportunity to perform more robust strategic plans, despite of the vagueness and uncertainty of strategic plans selection process. A numerical example demonstrates possibilities for the improvement of BSC through applying the proposed model

Using crowdsourcing tools for implementing open strategy: A case study in education

Following critiques on the conventional methods of strategic planning, and the stream of research on the effect of more participation on the success of strategy process, the new concept of open strategy has been introduced to the literature. Based on the notion of open innovation, this new concept covers two principles of inclusiveness and transparency. The current study introduces an in-progress case study of using the crowdsourcing model to implement the open strategy concept in an Australian university. We use the principles of Design Science Research Methodology (DSRM) for open strategic planning by using the crowdsourcing model and evaluate the method by comparing the quality of resultant plan in delivering its objective. This study explains our approach and a conceptual design for the proposed method as well as our plan for conducting future phases of the research. The introduced process can be used in similar practices of open strategic planning

A Review of Critical Factors for Communicating With Customers on Social Networking Sites

This paper undertakes a systematic review to gain insight into existing studies on the application of Social Network Sites (SNS). Our systematic review of studies from 1995 to 2012 examines the background and trend of research in the area and provides critical factors that organizations should consider for effectively use social networking sites to communicate with their customers. We note a huge growth in the number of academic papers on the topic since 1998. Seventeen factors were identified as a result of review, which shaped two main themes: (i) A customercentric organizational culture, and (ii) SNS Know-How. The findings show that for a successful and effective use of SNSs, and in particular Facebook, a combination of good understanding of SNSs tools and capabilities as well as a constant and transparent relationship with customers are essential. The findings show that for a successful and effective use of SNSs, and in particular Facebook, a combination of good understanding of SNSs tools and capabilities as well as a constant and transparent relationship with customers are essential

A generalized finite element method for modeling arbitrary interfaces in large deformation problems

In this paper, a generalized–FEM technique is presented in modeling of arbitrary interfaces in large deformations. The method is used to model the internal interfaces and arbitrary geometries using a uniform non-conformal mesh. The technique is applied to capture independent deformations at both sides of separated element cut by the interface in a uniform regular mesh. In this approach, a uniform non-conformal mesh is decomposed into subelements that conform to the internal interfaces. The geometry of interface is used to produce various triangular, quadrilateral and pentagonal elements at the intersection of interface with regular FE mesh, in which the extra degrees-of-freedom are defined along the interface. The level set method is employed to describe the material geometry on the background mesh. The technique is used to extrude any arbitrary geometry from an initial background mesh and model under different external effects. The most feature of the technique is to introduce the conformal decomposition finite element method, in which the new conforming elements are produced in the uniform structured mesh by decomposing the uniform mesh into elements that is conformed to the material interfaces. Finally, several numerical examples are analyzed to demonstrate the efficiency of proposed technique in modeling arbitrary interfaces in large deformations

Quantitative evaluation of polymer gel dosimeters by broadband ultrasound attenuation

Ultrasound has been examined previously as an alternative readout method for irradiated polymer gel dosimeters, with authors reporting varying dose response to ultrasound transmission measurements. In this current work we extend previous work to measure the broadband ultrasound attenuation (BUA) response of irradiated PAGAT gel dosimeters, using a novel ultrasound computed tomography system

Strategic information system planning in healthcare organizations

Copyright © 2015, IGI Global. The healthcare industry is a critical and growing part of economies worldwide. To provide better quality of care, and value for money, billions of dollars are being spent on bettering information systems in healthcare organizations. Strategic Information System Planning (SISP) is instrumental in making informed decisions to achieve the health organizations' goals and objectives. This paper undertakes a systematic review to gain insight into existing studies on SISP in healthcare organizations. Our systematic review of papers on SISP from 1985 to 2011 examines the background and trend of research into SISP in the healthcare industry, classification of topics in SISP, as well as sets of tools and guidelines to aid practitioners and the research community alike

Asynchronous spiking neurons, the natural key to exploit temporal sparsity

Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is optimized for real-time dynamic signal processing. We believe one important feature of the brain (asynchronous state-full processing) is the key to its excellence in this domain. In this work, we show how asynchronous processing with state-full neurons allows exploitation of the existing sparsity in natural signals. This paper explains three different types of sparsity and proposes an inference algorithm which exploits all types of sparsities in the execution of already trained networks. Our experiments in three different applications (Handwritten digit recognition, Autonomous Steering and Hand-Gesture recognition) show that this model of inference reduces the number of required operations for sparse input data by a factor of one to two orders of magnitudes. Additionally, due to fully asynchronous processing this type of inference can be run on fully distributed and scalable neuromorphic hardware platforms

Empirical Evaluation of the Influence of EMR Alignment to Care Processes on Data Completeness

Data completeness is an important dimension of data quality in electronic medical records (EMR). There are many constructs that influence data completeness in EMR. In this paper, we investigate three of these constructs: Clinical staff participation, EMR integration, and EMR alignment to care processes. We use these constructs from related studies as theoretical support to propose a conceptual model of factors influencing data completeness in EMR. The conceptual model is empirically validated using a survey with clinical staff participants. The results reveal that a high level of clinical staff’s participation influences the data completeness in EMR. Furthermore, the alignment of EMR to the care processes has an impact on the data completeness in EMR

Evaluation of combination effects of 2-methoxyestradiol and methoxyamine on IUdR-induced radiosensitization in glioma spheroids

Background: Glioblastoma is the most common and most malignant cancer of central nervous system. Targeted radiotherapy is an effective method toward its treatment. Iododeoxyuridine (IUdR) is a halogenated thymidine analogue known to be effective as a radiosensitizer in human cancer therapy. In this study we have evaluated the combination effects of 2-Methoxyestradiol, an inhibitor of h y poxia inducible factor 1 α (HIF-1α) a n d Methoxyaminem, an inhibitor of base excision repair (BER) pathway on radiosensitization of IUdR in glioblastoma spheroid culture. Materials and Methods: The cytotoxic damages of DNA in U87MG cell line were compared using colony formation assay. Experiments were performed in large spheroids with a diameter of approximately 350 μm. Results: Evaluation of the effects of IUdR with 2ME2 and MX pretreatment on spheroid cultured cell followed by ionizing irradiation showed more enhancemented (p � 0.001) IUdR induced-radiosensitization. These results introduced a key role for 2ME2 in IUdR related studies. Conclusion: Pretreatment of tumor cells with IUdR, MX and 2ME2 before irradiation enhances tumor radiosensitization and may improve therapeu- tic index for IUdR and 2ME2. Iran. J. Radiat. Res., 2010; 7 (4): 211-216