Agile manufacturing practices: the role of big data and business analytics with multiple case studies

The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four U.K. organizations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes

Determinants of Capital Structure in Non-Financial Companies

In this paper, we evaluate firm-, industry- and country-specific factors determining a firm’s capital structure. The empirical validity of several capital structure theories has been ambiguous so far. We shed light on the main drivers of leverage and depict differences in industry and country characteristics. Using a short panel data set with a large cross-section, we are able to show that firm size, industry leverage, industry growth and tax shield positively affect leverage ratios, while profitability and liquidity have negative impacts. Moreover, our model is an improvement over Rajan and Zingales’ (1995) four-factor core model in terms of explaining data variation. The results are robust against different panel estimators, decompositions and over time

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

Impact of internet of things (IoT) in disaster management: a task-technology fit perspective

YesDisaster management aims to mitigate the potential damage from the disasters, ensure immediate and suitable assistance to the victims, and attain effective and rapid recovery. These objectives require a planned and effective rescue operation post such disasters. Different types of information about the impact of the disaster are, hence, required for planning an effective and immediate relief operation. The IoT technology available today is quite mature and has the potential to be very useful in disaster situations. This paper analyzes the requirements for planning rescue operation for such natural disasters and proposes an IoT based solution to cater the identified requirements. The proposed solution is further validated using the task-technology fit (TTF) approach for analyzing the significance of the adoption of IoT technology for disaster management. Results from the exploratory study established the core dimensions of the task requirements and the TTF constructs. Results from the confirmatory factor analysis using PLS path modelling, further, suggest that both task requirements and IoT technology have significant impact on the IoT TTF in the disaster management scenario. This paper makes significant contributions in the development of appropriate constructs for modeling TTF for IoT Technology in the context of disaster management

The morphometric changes of endometrium and serum leptin levels during the implantation period of the embryo in the rat in response to exogenous ovarian hyperstimulation by human menopausal gonadotropin and recombinant follicle stimulating hormone.

59th Annual Meeting of the American-Society-for-Reproductive-Medicine -- OCT 11-15, 2003 -- SAN ANTONIO, TEXASWOS: 000185672400733Amer Soc Reprod Me

Retrospective analysis of hysteroscopic findings in breast cancer patients having adjuvant tamoxifen treatment

PubMed ID: 20882884Purpose of Investigation: To evaluate the effects of tamoxifen on the endometrium of breast cancer patients by hysteroscopy and endometrial sampling. Methods: Thirty-seven breast cancer patients using tamoxifen underwent hysteroscopy because of post-menopausal endometrial thickening or abnormal uterine bleeding. Hysteroscopic findings were compared with histopathology and ultrasonographic measurement of the endometrium. Results: Nineteen women showed endometrial abnormalities (51%) out of 37 patients. Negative and positive predictive values for hysteroscopy in detecting endometrial abnormalities were 100% and 94%, respectively. Conclusion: Endometrial surveillance is an important part of gynecological follow-up in breast cancer patients using tamoxifen and the liberal use of hysteroscopy aids in the diagnosis of abnormal endometrium