Technological innovation in electronic inventory solutions:an analysis of patent data

The purpose of this paper is to investigate the technological development of electronic inventory solutions from perspective of patent analysis. We first applied the international patent classification to classify the top categories of data processing technologies and their corresponding top patenting countries. Then we identified the core technologies by the calculation of patent citation strength and standard deviation criterion for each patent. To eliminate those core innovations having no reference relationships with the other core patents, relevance strengths between core technologies were evaluated also. Our findings provide market intelligence not only for the research and development community, but for the decision making of advanced inventory solutions.

A fuzzy expected value approach under generalized data envelopment analysis

Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.

Decision-making in product quality based on failure knowledge

Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

A Method for Solving a Class of Multiple-Criteria Analysis Problems

AMS subject classification: 90C29.

Electronic information sharing in local government authorities:factors influencing the decision-making process

Local Government Authorities (LGAs) are mainly characterised as information-intensive organisations. To satisfy their information requirements, effective information sharing within and among LGAs is necessary. Nevertheless, the dilemma of Inter-Organisational Information Sharing (IOIS) has been regarded as an inevitable issue for the public sector. Despite a decade of active research and practice, the field lacks a comprehensive framework to examine the factors influencing Electronic Information Sharing (EIS) among LGAs. The research presented in this paper contributes towards resolving this problem by developing a conceptual framework of factors influencing EIS in Government-to-Government (G2G) collaboration. By presenting this model, we attempt to clarify that EIS in LGAs is affected by a combination of environmental, organisational, business process, and technological factors and that it should not be scrutinised merely from a technical perspective. To validate the conceptual rationale, multiple case study based research strategy was selected. From an analysis of the empirical data from two case organisations, this paper exemplifies the importance (i.e. prioritisation) of these factors in influencing EIS by utilising the Analytical Hierarchy Process (AHP) technique. The intent herein is to offer LGA decision-makers with a systematic decision-making process in realising the importance (i.e. from most important to least important) of EIS influential factors. This systematic process will also assist LGA decision-makers in better interpreting EIS and its underlying problems. The research reported herein should be of interest to both academics and practitioners who are involved in IOIS, in general, and collaborative e-Government, in particular. © 2013 Elsevier Ltd. All rights reserved.

Numerical analysis of artificial neural network and volterra-based nonlinear equalizers for coherent optical OFDM

One major drawback of coherent optical orthogonal frequency-division multiplexing (CO-OFDM) that hitherto remains unsolved is its vulnerability to nonlinear fiber effects due to its high peak-to-average power ratio. Several digital signal processing techniques have been investigated for the compensation of fiber nonlinearities, e.g., digital back-propagation, nonlinear pre- and post-compensation and nonlinear equalizers (NLEs) based on the inverse Volterra-series transfer function (IVSTF). Alternatively, nonlinearities can be mitigated using nonlinear decision classifiers such as artificial neural networks (ANNs) based on a multilayer perceptron. In this paper, ANN-NLE is presented for a 16QAM CO-OFDM system. The capability of the proposed approach to compensate the fiber nonlinearities is numerically demonstrated for up to 100-Gb/s and over 1000km and compared to the benchmark IVSTF-NLE. Results show that in terms of Q-factor, for 100-Gb/s at 1000km of transmission, ANN-NLE outperforms linear equalization and IVSTF-NLE by 3.2dB and 1dB, respectively.

Bagging model with cost sensitive analysis on diabetes data

Diabetes patients might suffer from an unhealthy life, long-term treatment and chronic complicated diseases. The decreasing hospitalization rate is a crucial problem for health care centers. This study combines the bagging method with base classifier decision tree and costs-sensitive analysis for diabetes patients' classification purpose. Real patients' data collected from a regional hospital in Thailand were analyzed. The relevance factors were selected and used to construct base classifier decision tree models to classify diabetes and non-diabetes patients. The bagging method was then applied to improve accuracy. Finally, asymmetric classification cost matrices were used to give more alternative models for diabetes data analysis.

Specification and quantitative analysis of probabilistic cloud deployment patterns

Cloud computing is a new technological paradigm offering computing infrastructure, software and platforms as a pay-as-you-go, subscription-based service. Many potential customers of cloud services require essential cost assessments to be undertaken before transitioning to the cloud. Current assessment techniques are imprecise as they rely on simplified specifications of resource requirements that fail to account for probabilistic variations in usage. In this paper, we address these problems and propose a new probabilistic pattern modelling (PPM) approach to cloud costing and resource usage verification. Our approach is based on a concise expression of probabilistic resource usage patterns translated to Markov decision processes (MDPs). Key costing and usage queries are identified and expressed in a probabilistic variant of temporal logic and calculated to a high degree of precision using quantitative verification techniques. The PPM cost assessment approach has been implemented as a Java library and validated with a case study and scalability experiments. © 2012 Springer-Verlag Berlin Heidelberg.

Is pregnancy a teachable moment for diet and physical activity behaviour change? An interpretative phenomenological analysis of the experiences of women during their first pregnancy

OBJECTIVES: Pregnancy may provide a 'teachable moment' for positive health behaviour change, as a time when women are both motivated towards health and in regular contact with health care professionals. This study aimed to investigate whether women's experiences of pregnancy indicate that they would be receptive to behaviour change during this period. DESIGN: Qualitative interview study. METHODS: Using interpretative phenomenological analysis, this study details how seven women made decisions about their physical activity and dietary behaviour during their first pregnancy. RESULTS: Two women had required fertility treatment to conceive. Their behaviour was driven by anxiety and a drive to minimize potential risks to the pregnancy. This included detailed information seeking and strict adherence to diet and physical activity recommendations. However, the majority of women described behaviour change as 'automatic', adopting a new lifestyle immediately upon discovering their pregnancy. Diet and physical activity were influenced by what these women perceived to be normal or acceptable during pregnancy (largely based on observations of others) and internal drivers, including bodily signals and a desire to retain some of their pre-pregnancy self-identity. More reasoned assessments regarding benefits for them and their baby were less prevalent and influential. CONCLUSIONS: Findings suggest that for women who conceived relatively easily, diet and physical activity behaviour during pregnancy is primarily based upon a combination of automatic judgements, physical sensations, and perceptions of what pregnant women are supposed to do. Health professionals and other credible sources appear to exert less influence. As such, pregnancy alone may not create a 'teachable moment'. Statement of contribution What is already known on this subject? Significant life events can be cues to action with relation to health behaviour change. However, much of the empirical research in this area has focused on negative health experiences such as receiving a false-positive screening result and hospitalization, and in relation to unequivocally negative behaviours such as smoking. It is often suggested that pregnancy, as a major life event, is a 'teachable moment' (TM) for lifestyle behaviour change due to an increase in motivation towards health and regular contact with health professionals. However, there is limited evidence for the utility of the TM model in predicting or promoting behaviour change. What does this study add? Two groups of women emerged from our study: the women who had experienced difficulties in conceiving and had received fertility treatment, and those who had conceived without intervention. The former group's experience of pregnancy was characterized by a sense of vulnerability and anxiety over sustaining the pregnancy which influenced every choice they made about their diet and physical activity. For the latter group, decisions about diet and physical activity were made immediately upon discovering their pregnancy, based upon a combination of automatic judgements, physical sensations, and perceptions of what is normal or 'good' for pregnancy. Among women with relatively trouble-free conception and pregnancy experiences, the necessary conditions may not be present to create a 'teachable moment'. This is due to a combination of a reliance on non-reflective decision-making, perception of low risk, and little change in affective response or self-concept.

Putting children forward for epilepsy surgery:a qualitative study of UK parents' and health professionals' decision-making experiences

Background Against a backdrop of recommendations for increasing access to and uptake of early surgical intervention for children with medically intractable epilepsy, it is important to understand how parents and professionals decide to put children forward for epilepsy surgery and what their decisional support needs are. Aim The aim of this study was to explore how parents and health professionals make decisions regarding putting children forward for pediatric epilepsy surgery. Methods Individual interviews were conducted with nine parents of children who had undergone pediatric epilepsy surgery at a specialist children's hospital and ten healthcare professionals who made up the children's epilepsy surgery service multidisciplinary healthcare team (MDT). Three MDT meetings were also observed. Data were analyzed thematically. Findings Four themes were generated from analysis of interviews with parents: presentation of surgery as a treatment option, decision-making, looking back, and interventions. Three themes were generated from analysis of interviews/observations with health professionals: triangulating information, team working, and patient and family perspectives. Discussion Parents wanted more information and support in deciding to put their child forward for epilepsy surgery. They attempted to balance the potential benefits of surgery against any risks of harm. For health professionals, a multidisciplinary approach was seen as crucial to the decision-making process. Advocating for the family was perceived to be the responsibility of nonmedical professionals. Conclusion Decision-making can be supported by incorporating families into discussions regarding epilepsy surgery as a potential treatment option earlier in the process and by providing families with additional information and access to other parents with similar experiences.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

Mental health pharmacists views on shared decision-making for antipsychotics in serious mental illness

Background People diagnosed with serious mental illnesses (SMIs) such as schizophrenia and bipolar affective disorder are frequently treated with antipsychotics. National guidance advises the use of shared decision-making (SDM) in antipsychotic prescribing. There is currently little data on the opinions of health professionals on the role of SDM. Objective To explore the views and experiences of UK mental health pharmacists regarding the use of SDM in antipsychotic prescribing in people diagnosed with SMI. Setting The study was conducted by interviewing secondary care mental health pharmacists in the UK to obtain qualitative data. Methods Semi-structured interviews were recorded. An inductive thematic analysis was conducted using the method of constant comparison. Main outcome measure Themes evolving from mental health pharmacists on SDM in relation to antipsychotic prescribing in people with SMI. Results Thirteen mental health pharmacists were interviewed. SDM was perceived to be linked to positive clinical outcomes including adherence, service user satisfaction and improved therapeutic relations. Despite more prescribers and service users supporting SDM, it was not seen as being practised as widely as it could be; this was attributed to a number of barriers, most predominantly issues surrounding service user’s lacking capacity to engage in SDM and time pressures on clinical staff. The need for greater effort to work around the issues, engage service users and adopt a more inter-professional approach was conveyed. Conclusion The mental health pharmacists support SDM for antipsychotic prescribing, believing that it improves outcomes. However, barriers are seen to limit implementation. More research is needed into overcoming the barriers and measuring the benefits of SDM, along with exploring a more inter-professional approach to SDM.

Cooperation in supply chains: A cooperative game theoretic analysis = Együttműködés ellátási láncokban: Egy kooperatív játékelméleti elemzés

A cikkben a kooperatív játékelmélet fogalmait alkalmazzuk egy ellátási lánc esetében. Az ostorcsapás-hatás elemeit egy beszállító-termelő ellátási láncban ragadjuk meg egy Arrow-Karlin típusú modellben lineáris készletezési és konvex termelési költség mellett. Feltételezzük, hogy mindkét vállalat minimalizálja a fontosabb költségeit. Két működési rendszert hasonlítunk össze: egy hierarchikus döntéshozatali rendszert, amikor először a termelő, majd a beszállító optimalizálja helyzetét, majd egy centralizált (kooperatív) modellt, amikor a vállalatok az együttes költségüket minimalizálják. A kérdés úgy merül fel, hogy a csökkentett ostorcsapás-hatás esetén hogyan osszák meg a részvevők ebben a transzferálható hasznosságú kooperatív játékban. = In this paper we apply cooperative game theory concepts to analyze supply chains. The bullwhip effect in a two-stage supply chain (supplier-manufacturer) in the framework of the Arrow-Karlin model with linear-convex cost functions is considered. It is assumed that both firms minimize their relevant costs, and two cases are examined: the supplier and the manufacturer minimize their relevant costs in a decentralized and in a centralized (cooperative) way. The question of how to share the savings of the decreased bullwhip effect in the centralized (cooperative) model is answered by transferable utility cooperative game theory tools.

Analysis of purchasing activity with discounted cash flow inventory models = Beszerzési tevékenység elemzése diszkontált pénzáramlású készletmodellel

A klasszikus tételnagyság probléma két fontosabb készletezési költséget ragad meg: rendelési és készlettartási költségek. Ebben a dolgozatban a vállalatok készpénz áramlásának a beszerzési tevékenységre gyakorolt hatását vizsgáljuk. Ebben az elemzésben a készpénzáramlási egyenlőséget használjuk, amely nagyban emlékeztet a készletegyenletekre. Eljárásunkban a beszerzési és rendelési folyamatot diszkontálva vizsgáljuk. A költségfüggvény lineáris készpénztartási, a pénzkiadás haszonlehetőség és lineáris kamatköltségből áll. Bemutatjuk a vizsgált modell optimális megoldását. Az optimális megoldást egy számpéldával illusztráljuk. = The classical economic order quantity model has two types of costs: ordering and inventory holding costs. In this paper we try to investigate the effect of purchasing activity on cash flow of a firm. In the examinations we use a cash flow identity similar to that of in inventory modeling. In our approach we analyze the purchasing and ordering process with discounted costs. The cost function of the model consists of linear cash holding, linear opportunity cost of spending cash, and linear interest costs. We show the optimal solution of the proposed model. The optimal solutions will be presented by numerical examples.

The analysis of bullwhip effect in a HMMS-type supply chain

The aim of the paper is to investigate the well-known bullwhip effect of supply chains. Control theoretic analysis of bullwhip effect is extensively analyzed in the literature with the Laplace transform. This paper tries to examine the effect for an extended Holt–Modigliani–Muth–Simon model. A two-stage supply chain (supplier–manufacturer) is studied with quadratic costs functional. It is assumed that both firms minimize the relevant costs. The order of the manufacturer is delayed with a known constant. Two cases are examined: supplier and manufacturer minimize the relevant costs decentralized, and a centralized decision rule. The question is answered, how to decrease the bullwhip effect.