Showing papers on "Quality (business) published in 2015"

Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

Abstract: Background: The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings. Objective: The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps. Methods: A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability. Results: There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79). Conclusions: The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

Developing a Scale to Measure the Perceived Quality of an Internet Shopping Site (PQISS)

Abstract: Internet shopping sites must be of high quality to attract consumers and influence their shopping decisions. We have developed a scale to measure the perceived quality of an Internet shopping site (PQISS). This scale can be used to evaluate Internet shopping sites and to examine the relationships between the site quality and relevant variables.

The Common Core State Standards for Mathematics

Abstract: The Common Core State Standards for Mathematics (CCSSM) was published in 2010 and includes a complete collection of standards that are published and reviewed as a ‘common core’ in which math skills have been extensively adopted. The recommendations provided have been entirely or partially adapted by more than 47 states of the US. Authorities have commited and incredible amount of time, money and resources in creating these new standards and additional effort will be required to implement these standards The new math standards address two established issues in US education, the ordinary quality of mathematics learning and equal opportunity in U.S. schools. It is a fact that deprived students are most likely to have inexperienced or under qualified teachers, and children from impoverished families are much less likely to have the same kind of supports or enrichment opportunities than their more fortunate peers. It is important for the authorities to produce and adapt material for the development of children in such a way that it can clearly address the content and practice of math for the CCSSM and this material should be able to give learning and teaching methods which are in line with CCSSM. It is concluded from this research that there are challenges that have emerged for implementation of CCSSM in which basic challenges include issues of quality, equality, challenges for math teachers, and teaching CCSSM to disabled students.

The Challenges of Data Quality and Data Quality Assessment in the Big Data Era

Abstract: High-quality data are the precondition for analyzing and using big data and for guaranteeing the value of the data. Currently, comprehensive analysis and research of quality standards and quality assessment methods for big data are lacking. First, this paper summarizes reviews of data quality research. Second, this paper analyzes the data characteristics of the big data environment, presents quality challenges faced by big data, and formulates a hierarchical data quality framework from the perspective of data users. This framework consists of big data quality dimensions, quality characteristics, and quality indexes. Finally, on the basis of this framework, this paper constructs a dynamic assessment process for data quality. This process has good expansibility and adaptability and can meet the needs of big data quality assessment. The research results enrich the theoretical scope of big data and lay a solid foundation for the future by establishing an assessment model and studying evaluation algorithms.

Household Surveys in Crisis

Abstract: Large and nationally representative surveys are arguably among the most important innovations in social science research of the last century. As the leadership of the Committee on National Statistics of the National Academy of Sciences wrote: “It is not an exaggeration to say that large-scale probability surveys were the 20th-century answer to the need for wider, deeper, quicker, better, cheaper, more relevant, and less burdensome official statistics” (Brown, Citro, House, Marton, and Mackie 2014). Household surveys are the source of official rates of unemployment, poverty, health insurance coverage, inflation, and other statistics that guide policy. They are also a primary source of data for economic research and are used to allocate government funds. However, the quality of data from household surveys is in decline. Households have become increasingly less likely to answer surveys at all, which is the problem of unit nonresponse. Those that respond are less likely to answer certain questions, which is the problem of item nonresponse. When households do provide answers, they are less likely to be accurate, which is the problem of measurement error. We will

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group.

Abstract: Background—Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. Methods—The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced afte...

Bioactive peptides and protein hydrolysates: research trends and challenges for application as nutraceuticals and functional food ingredients

Abstract: The past decade has seen a burgeoning of literature on food-derived peptides and protein hydrolysates with diverse biological activities, but to date, empirical and bioinformatics studies have provided primarily in vitro data and limited clinical evidence to justify the development of these bioactive peptides and hydrolysates as nutraceuticals and functional foods for promoting health. Several obstacles must be overcome on the road to commercialization of these products. In conjunction with the need to implement efficient and cost-effective strategies for industrial scale production, the successful transfer of the technology to market requires standardization of analytical methods for assurance of product quality, assessment of sensory properties for consumer acceptance, and most importantly, well-designed clinical trials to provide robust evidence for supporting health claims.

The Effect of Experience Quality on Perceived Value, Satisfaction, Image and Behavioral Intention of Water Park Patrons: New versus Repeat Visitors

Abstract: This study proposed a conceptual model to examine how customers' perceptions of the quality of experiences influence perceived value, water park image, customer satisfaction and behavioral intentions for first-time and repeat customers of the water park of the tourism industry This study finds that the quality of participants' experiences significantly affects perceived value, water park image and customer satisfaction Moreover, perceived value and water park image exert a direct influence on customer satisfaction, and they also positively affect behavioral intentions Finally, the impacts on customer satisfaction of experience quality and water park image significantly differ between first-time and repeat customers Copyright © 2013 John Wiley & Sons, Ltd

IFRS Adoption and Accounting Quality: A Review

Abstract: Literature on IFRS adoption by countries concerning high quality, understandable and applicable IFRS in order to be worldwide accepted has generated a pertinent discussion, since the results presented in the literature are not unanimous on the adoption of IFRS and accounting quality. Soderstrom and Sun (2007) analyzed a research published in leading accounting journals selected from 1990’s on the consequences of IFRS adoption and found that the determinants of accounting quality after the adoption of these standards are articulated in: quality of the standards; political and judicial system in the country; financial reporting incentives. Based on Soderstrom and Sun (2007) study, this work aims to analyze literature on IFRS adoption and the accounting quality from 2006. In order to achieve this goal, a systematic search of the literature focused on a "Web of Science" database associated with a bibliometric analysis was done, aiming to understand the discussion on IFRS adoption and accounting quality in literature. As a result, it was found that the adoption of IFRS related to the accounting standard factors, political and judicial systems of the countries and the financial reporting incentives discussed by Soderstrom and Sun (2007) to determine the quality of accounting remains persistent. Overall, this analysis concludes that the quality of accounting cannot be evaluated only in terms of IFRS adoption, either on a voluntary or mandatory basis. The results of this study present at least two limitations: The studies on IFRS adoption researched, despite tackling institutional issues, do not show the real complexity of the reality, due to reduce the quality of the social context to the quality of economic rationality; and the alleged quality of standards based on principles is not enough to determine the quality of accounting.

“Well, I’m tired of tryin’!” Organizational citizenship behavior and citizenship fatigue.

Abstract: This study seeks to identify workplace conditions that influence the degree to which employees feel worn out, tired, or on edge attributed to engaging in organizational citizenship behavior (OCB) and also how this phenomenon, which we refer to as citizenship fatigue, is associated with future occurrences of OCB. Using data collected from 273 employees and their peers at multiple points in time, we found that the relationship between OCB and citizenship fatigue depends on levels of perceived organizational support, quality of team-member exchange relationships, and pressure to engage in OCB. Specifically, the relationship between OCB and citizenship fatigue is significantly stronger and positive when perceived organizational support is low, and it is significantly stronger and negative when the quality of teammember exchange is high and pressure to engage in OCB is low. Our results also indicate that citizenship fatigue is negatively related to subsequent acts of OCB. Finally, supplemental analyses reveal that the relationship between OCB and citizenship fatigue may vary as a function of the specific facet of OCB. We conclude with a discussion of the key theoretical and practical implications of our findings.

The use of Triangulation in Social Sciences Research : Can qualitative and quantitative methods be combined?

Abstract: This article refers to a study in Tanzania on fringe benefits or welfare via the work contract1 where we will work both quantitatively and qualitatively. My focus is on the vital issue of combining methods or methodologies. There has been mixed views on the uses of triangulation in researches. Some authors argue that triangulation is just for increasing the wider and deep understanding of the study phenomenon, while others have argued that triangulation is actually used to increase the study accuracy, in this case triangulation is one of the validity measures. Triangulation is defined as the use of multiple methods mainly qualitative and quantitative methods in studying the same phenomenon for the purpose of increasing study credibility. This implies that triangulation is the combination of two or more methodological approaches, theoretical perspectives, data sources, investigators and analysis methods to study the same phenomenon.However, using both qualitative and quantitative paradigms in the same study has resulted into debate from some researchers arguing that the two paradigms differ epistemologically and ontologically. Nevertheless, both paradigms are designed towards understanding about a particular subject area of interest and both of them have strengths and weaknesses. Thus, when combined there is a great possibility of neutralizing the flaws of one method and strengthening the benefits of the other for the better research results. Thus, to reap the benefits of two paradigms and minimizing the drawbacks of each, the combination of the two approaches have been advocated in this article. The quality of our studies on welfare to combat poverty is crucial, and especially when we want our conclusions to matter in practice.

Remanufactured products in closed-loop supply chains for consumer goods

Abstract: This study empirically investigates consumer perceptions of remanufactured consumer products in closed-loop supply chains. A multi-study approach led to increasing levels of measure refinement and facilitated examination of various assumptions researchers have made about the consumer market for remanufactured products. Based in part on the measure building studies, an experimental study examined remanufactured product perceptions from a national panel of consumers. The consumers responded to remanufactured product descriptions that manipulated price discount and brand equity. The results indicate that discounting had a consistently positive, linear effect on remanufactured product attractiveness. Curiously, the brand equity manipulation proved less important to consumers than specific remanufactured product quality perceptions. The results also show that green consumers and consumers who consider remanufactured products green typically found remanufactured products significantly more attractive. Finally, the findings introduce the concept of negative attribute perceptions, such as disgust, that had a significantly detrimental effect on remanufactured product attractiveness.

Does Twitter matter? The impact of microblogging word of mouth on consumers’ adoption of new movies

Abstract: This research provides an empirical test of the “Twitter effect,” which postulates that microblogging word of mouth (MWOM) shared through Twitter and similar services affects early product adoption behaviors by immediately disseminating consumers’ post-purchase quality evaluations. This is a potentially crucial factor for the success of experiential media products and other products whose distribution strategy relies on a hyped release. Studying the four million MWOM messages sent via Twitter concerning 105 movies on their respective opening weekends, the authors find support for the Twitter effect and report evidence of a negativity bias. In a follow-up incident study of 600 Twitter users who decided not to see a movie based on negative MWOM, the authors shed additional light on the Twitter effect by investigating how consumers use MWOM information in their decision-making processes and describing MWOM’s defining characteristics. They use these insights to position MWOM in the word-of-mouth landscape, to identify future word-of-mouth research opportunities based on this conceptual positioning, and to develop managerial implications.

Collaboration Between Firms and Universities in Italy: The Role of a Firm’s Proximity to Top-Rated Departments

Abstract: This work aims at examining the determinants of research collaboration between firms and universities using the results of the 15th wave of the Bank of Italy Business Outlook Survey on Firms, together with data on the quality and the importance of university research. The distance from top research centres is the most important factor in determining the probability of collaboration. The presence of different innovation sources increases the probability of collaboration; proximity is more important for small- and medium-sized firms, while larger ones collaborate with universities better able to sell the results of their research, regardless of their location.

Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones

Abstract: What can wearable sensors and usage of smart phones tell us about academic performance, self-reported sleep quality, stress and mental health condition? To answer this question, we collected extensive subjective and objective data using mobile phones, surveys, and wearable sensors worn day and night from 66 participants, for 30 days each, totaling 1,980 days of data. We analyzed daily and monthly behavioral and physiological patterns and identified factors that affect academic performance (GPA), Pittsburg Sleep Quality Index (PSQI) score, perceived stress scale (PSS), and mental health composite score (MCS) from SF-12, using these month-long data. We also examined how accurately the collected data classified the participants into groups of high/low GPA, good/poor sleep quality, high/low self-reported stress, high/low MCS using feature selection and machine learning techniques. We found associations among PSQI, PSS, MCS, and GPA and personality types. Classification accuracies using the objective data from wearable sensors and mobile phones ranged from 67–92%.

Dying in the hospital setting: A systematic review of quantitative studies identifying the elements of end-of-life care that patients and their families rank as being most important

Abstract: Background: The majority of expected deaths occur in hospitals where optimal end-of-life care is not yet fully realised, as evidenced by recent reviews outlining experience of care. Better understanding what patients and their families consider to be the most important elements of inpatient end-of-life care is crucial to addressing this gap. Aim and design: This systematic review aimed to ascertain the five most important elements of inpatient end-of-life care as identified by patients with palliative care needs and their families. Data sources: Nine electronic databases from 1990 to 2014 were searched along with key internet search engines and handsearching of included article reference lists. Quality of included studies was appraised by two researchers. Results: Of 1859 articles, 8 met the inclusion criteria generating data from 1141 patients and 3117 families. Synthesis of the top five elements identified four common end-of-life care domains considered important to both patients and their families, namely, (1) effective communication and shared decision making, (2) expert care, (3) respectful and compassionate care and (4) trust and confidence in clinicians. The final domains differed with financial affairs being important to families, while an adequate environment for care and minimising burden both being important to patients. Conclusion: This review adds to what has been known for over two decades in relation to patient and family priorities for end-of-life care within the hospital setting. The challenge for health care services is to act on this evidence, reconfigure care systems accordingly and ensure universal access to optimal end-of-life care within hospitals.

Vocal minority and silent majority: how do online ratings reflect population perceptions of quality

Abstract: Consumer-generated ratings typically share an objective of illuminating the quality of a product or service for other buyers. While ratings have become ubiquitous and influential on the Internet, surprisingly little empirical research has investigated how these online assessments reflect the opinion of the population at large, especially in the domain of professional services where quality is often opaque to consumers. Building on the word-of-mouth literature, we examine the relationship between online ratings and population perceptions of physician quality. We leverage a unique dataset which includes direct measures of both the offline population's perception of physician quality and consumer-generated online reviews. As a result, we are able to examine how online ratings reflect patients' opinions about physician quality. In sharp contrast to the widely voiced concerns by medical practitioners, we find that physicians who are rated lower in quality by the patient population are less likely to be rated online. Although ratings provided online are positively correlated with patient population opinions, the online ratings tend to be exaggerated at the upper end of the quality spectrum. This study is the first to provide empirical evidence of the relationship between online ratings and the underlying consumer-perceived quality, and extends prior research on online word-of-mouth to the domain of professional services.

The relationship between motivation, monetary compensation, and data quality among US- and India-based workers on Mechanical Turk

Abstract: In this study, we examined data quality among Amazon Mechanical Turk (MTurk) workers based in India, and the effect of monetary compensation on their data quality. Recent studies have shown that work quality is independent of compensation rates, and that compensation primarily affects the quantity but not the quality of work. However, the results of these studies were generally based on compensation rates below the minimum wage, and far below a level that was likely to play a practical role in the lives of workers. In this study, compensation rates were set around the minimum wage in India. To examine data quality, we developed the squared discrepancy procedure, which is a task-based quality assurance approach for survey tasks whose goal is to identify inattentive participants. We showed that data quality is directly affected by compensation rates for India-based participants. We also found that data were of a lesser quality among India-based than among US participants, even when optimal payment strategies were utilized. We additionally showed that the motivation of MTurk users has shifted, and that monetary compensation is now reported to be the primary reason for working on MTurk, among both US- and India-based workers. Overall, MTurk is a constantly evolving marketplace where multiple factors can contribute to data quality. High-quality survey data can be acquired on MTurk among India-based participants when an appropriate pay rate is provided and task-specific quality assurance procedures are utilized.