Modelling the underpinning factors of word of mouth (WOM) intentions of students in an ODL institution

The purpose of this research is to examine the impact of the predictors – quality of service, students perceived satisfaction, and university image on word of mouth (WOM) intention in an open distance learning (ODL) institution. Understanding the expectation of customers is an important component in the marketing kit. Competitive market among educational institution lead educational institutions to think of ways to improve the marketing strategy. The paper also investigates the mediating effect of university image and student perceived satisfaction on WOM intentions of students on the institution. Online survey questionnaires were distributed to 1012 students who are studying at an ODL institution. The sample is selected from the various learning centres and selection is based on the number of semesters these students have been studying at the institution. For the purpose of the research the sample are those who have completed six semesters of study at the institution. The items in the questionnaire were developed using existing constructs. The findings showed that student perceived satisfaction; quality services and university image have a positive and significant impact on word of mouth intention at p 0.05. This study establishes the fact that the quality of services provided, the image of the university and how students feel about the services are predictors of word of mouth intention of students about the university. (Abstract by authors

The study on the application of business intelligence in manufacturing: a review

A manufacturing based organization operates in an environment where a fast and effective decision is needed. This is to ensure that the output is met with customer compliance. There exists manufacturing systems that collect the operational data and the data turns out to be in a high volume due to the state of the art of the abundant manufacturing operational data. Having a lot of data without the tool to analyze and extracting valuable information from it, increases the amount of time spent by employees focusing on the data itself. This eventually leads to a delay in a decision making process, resulting in a delay of products delivery to customer. To fill in this gap, a Business Intelligence (BI) implementation will be reviewed, with the aim to execute the right action at the right time or in other words, to improve the decision making process of an organization

International Nosocomial Infection Control Consortium report, data summary of 50 countries for 2010-2015: Device-associated module

•We report INICC device-associated module data of 50 countries from 2010-2015.•We collected prospective data from 861,284 patients in 703 ICUs for 3,506,562 days.•DA-HAI rates and bacterial resistance were higher in the INICC ICUs than in CDC-NHSN's.•Device utilization ratio in the INICC ICUs was similar to CDC-NHSN's. Background: We report the results of International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2010-December 2015 in 703 intensive care units (ICUs) in Latin America, Europe, Eastern Mediterranean, Southeast Asia, and Western Pacific. Methods: During the 6-year study period, using Centers for Disease Control and Prevention National Healthcare Safety Network (CDC-NHSN) definitions for device-associated health care-associated infection (DA-HAI), we collected prospective data from 861,284 patients hospitalized in INICC hospital ICUs for an aggregate of 3,506,562 days. Results: Although device use in INICC ICUs was similar to that reported from CDC-NHSN ICUs, DA-HAI rates were higher in the INICC ICUs: in the INICC medical-surgical ICUs, the pooled rate of central line-associated bloodstream infection, 4.1 per 1,000 central line-days, was nearly 5-fold higher than the 0.8 per 1,000 central line-days reported from comparable US ICUs, the overall rate of ventilator-associated pneumonia was also higher, 13.1 versus 0.9 per 1,000 ventilator-days, as was the rate of catheter-associated urinary tract infection, 5.07 versus 1.7 per 1,000 catheter-days. From blood cultures samples, frequencies of resistance of Pseudomonas isolates to amikacin (29.87% vs 10%) and to imipenem (44.3% vs 26.1%), and of Klebsiella pneumoniae isolates to ceftazidime (73.2% vs 28.8%) and to imipenem (43.27% vs 12.8%) were also higher in the INICC ICUs compared with CDC-NHSN ICUs. Conclusions: Although DA-HAIs in INICC ICU patients continue to be higher than the rates reported in CDC-NSHN ICUs representing the developed world, we have observed a significant trend toward the reduction of DA-HAI rates in INICC ICUs as shown in each international report. It is INICC's main goal to continue facilitating education, training, and basic and cost-effective tools and resources, such as standardized forms and an online platform, to tackle this problem effectively and systematically