Showing papers in "Quality & Quantity in 2018"
TL;DR: It is concluded that saturation should be operationalized in a way that is consistent with the research question(s), and the theoretical position and analytic framework adopted, but also that there should be some limit to its scope, so as to risk saturation losing its coherence and potency if its conceptualization and uses are stretched too widely.
Abstract: Saturation has attained widespread acceptance as a methodological principle in qualitative research. It is commonly taken to indicate that, on the basis of the data that have been collected or analysed hitherto, further data collection and/or analysis are unnecessary. However, there appears to be uncertainty as to how saturation should be conceptualized, and inconsistencies in its use. In this paper, we look to clarify the nature, purposes and uses of saturation, and in doing so add to theoretical debate on the role of saturation across different methodologies. We identify four distinct approaches to saturation, which differ in terms of the extent to which an inductive or a deductive logic is adopted, and the relative emphasis on data collection, data analysis, and theorizing. We explore the purposes saturation might serve in relation to these different approaches, and the implications for how and when saturation will be sought. In examining these issues, we highlight the uncertain logic underlying saturation—as essentially a predictive statement about the unobserved based on the observed, a judgement that, we argue, results in equivocation, and may in part explain the confusion surrounding its use. We conclude that saturation should be operationalized in a way that is consistent with the research question(s), and the theoretical position and analytic framework adopted, but also that there should be some limit to its scope, so as not to risk saturation losing its coherence and potency if its conceptualization and uses are stretched too widely.
4,750 citations
TL;DR: Three empirical examples are deployed to address the potential impact of inter-relationships among independent variables in regression model results and how they are interpreted in the light of prior expectations, with results which suggest considerable problems.
Abstract: Many ecological- and individual-level analyses of voting behaviour use multiple regressions with a considerable number of independent variables but few discussions of their results pay any attention to the potential impact of inter-relationships among those independent variables-do they confound the regression parameters and hence their interpretation? Three empirical examples are deployed to address that question, with results which suggest considerable problems. Inter-relationships between variables, even if not approaching high collinearity, can have a substantial impact on regression model results and how they are interpreted in the light of prior expectations. Confounded relationships could be the norm and interpretations open to doubt, unless considerable care is applied in the analyses and an extended principal components method for doing that is introduced and exemplified.
420 citations
TL;DR: The author discusses the years of the development of structural modeling as the consequence of many researchers’ systematically growing needs (in particular in the social sciences) who strove to effectively understand the structure and interactions of latent phenomena.
Abstract: This paper is a tribute to researchers who have significantly contributed to improving and advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and presents its beginnings, historical development, its usefulness in the social sciences and the statistical and philosophical (theoretical) controversies which have often appeared in the literature pertaining to SEM. Having described the essence of SEM in the context of causal analysis, the author discusses the years of the development of structural modeling as the consequence of many researchers’ systematically growing needs (in particular in the social sciences) who strove to effectively understand the structure and interactions of latent phenomena. The early beginnings of SEM models were related to the work of Spearman and Wright, and to that of other prominent researchers who contributed to SEM development. The importance and predominance of theoretical assumptions over technical issues for the successful construction of SEM models are also described. Then, controversies regarding the use of SEM in the social sciences are presented. Finally, the opportunities and threats of this type of analytical strategy as well as selected areas of SEM applications in the social sciences are discussed.
305 citations
TL;DR: Structural equation modeling (SEM) is a family of statistical techniques that has become very popular in marketing as mentioned in this paper, and it does not come as a surprise that some of the most cited scholarly articles in the marketing domain are about SEM (e.g., Bagozzi and Yi 1988; Fornell and Larcker 1981).
Abstract: Structural equation modeling (SEM) is a family of statistical techniques that has become very popular in marketing. Its ability to model latent variables, to take various forms of measurement error into account, and to test entire theories makes it useful for a plethora of research questions. It does not come as a surprise that some of the most cited scholarly articles in the marketing domain are about SEM (e.g., Bagozzi and Yi 1988; Fornell and Larcker 1981), and that SEM is covered by two contributions within this volume. The need for two contributions arises from the SEM family tree having two major branches (Reinartz et al. 2009): covariance-based SEM (which is presented in Chap. 11) and variance-based SEM, which is presented in this chapter.
271 citations
TL;DR: The literature on mixed methods and multimethods has burgeoned over the last 20 years, and researchers from a growing number and diversity of fields have progressively embraced these approaches However, rapid growth in any movement inevitably gives rise to gaps or shortcomings.
Abstract: The literature on mixed methods and multimethods has burgeoned over the last 20 years, and researchers from a growing number and diversity of fields have progressively embraced these approaches However, rapid growth in any movement inevitably gives rise to gaps or shortcomings, such as “identity crises” or divergent conceptual views Although some authors draw a clear and sometimes opinionated distinction between mixed methods and multimethods, for others, they are synonymous The concepts underlying both terms therefore have become blurred and generated much confusion The aim of this article is to explore the origins of the confusion, describe our view of mixed methods and multimethod studies, and by doing so, help to clearly delineate the two concepts The authors have presented their opinion of how these terms and concepts should be distinguished and call for a constructive debate of the issues involved in the mixed methods and multimethod literature This is a way truly to propel the field forward
135 citations
TL;DR: In this article, the authors investigated the dynamic relationship between economic growth, renewable energy consumption, energy consumption and CO2 emissions in Tunisia over the period 1990-2015 and found that economic growth affects CO2 emission in the short and long run, while there is a unidirectional link running from energy use to economic growth at short run.
Abstract: The aim of this document is to investigate the dynamic relationship between economic growth, renewable energy consumption, energy consumption and CO2 emissions in Tunisia over the period 1990–2015. Unit root tests and co-integration test was used in order to detect the order of stationary and to test the existence long run links between the used variables. We apply the Granger causality test and VECM model to discover the short and long run links between the variables. Results have shown a bidirectional causal relationship between energy use and CO2 emissions. Economic growth affects CO2 emission in the short and long run. While there is a unidirectional links running from energy use to economic growth at short run. The paper shares best practices from Tunisia in terms of efficient use of renewable energy policy enablers, which may be contextualized in other emerging economies in order to keep sustainability and to achieve the green economy.
114 citations
TL;DR: This paper provides an updated and detailed classification of the design decisions that matter in questionnaire development, and a summary of what is said in the literature about their impact on data quality.
Abstract: Quite a lot of research is available on the relationships between survey response scales’ characteristics and the quality of responses. However, it is often difficult to extract practical rules for questionnaire design from the wide and often mixed amount of empirical evidence. The aim of this study is to provide first a classification of the characteristics of response scales, mentioned in the literature, that should be considered when developing a scale, and second a summary of the main conclusions extracted from the literature regarding the impact these characteristics have on data quality. Thus, this paper provides an updated and detailed classification of the design decisions that matter in questionnaire development, and a summary of what is said in the literature about their impact on data quality. It distinguishes between characteristics that have been demonstrated to have an impact, characteristics for which the impact has not been found, and characteristics for which research is still needed to make a conclusion.
108 citations
TL;DR: The MIR framework was developed to help cross disciplinary borders, especially those between the natural sciences and the social sciences, and it allows for a range of methods’ combinations (case study, mixed methods, etc.).
Abstract: Many of today’s global scientific challenges require the joint involvement of researchers from different disciplinary backgrounds (social sciences, environmental sciences, climatology, medicine, etc.). Such interdisciplinary research teams face many challenges resulting from differences in training and scientific culture. Interdisciplinary education programs are required to train truly interdisciplinary scientists with respect to the critical factor skills and competences. For that purpose this paper presents the Methodology for Interdisciplinary Research (MIR) framework. The MIR framework was developed to help cross disciplinary borders, especially those between the natural sciences and the social sciences. The framework has been specifically constructed to facilitate the design of interdisciplinary scientific research, and can be applied in an educational program, as a reference for monitoring the phases of interdisciplinary research, and as a tool to design such research in a process approach. It is suitable for research projects of different sizes and levels of complexity, and it allows for a range of methods’ combinations (case study, mixed methods, etc.). The different phases of designing interdisciplinary research in the MIR framework are described and illustrated by real-life applications in teaching and research. We further discuss the framework’s utility in research design in landscape architecture, mixed methods research, and provide an outlook to the framework’s potential in inclusive interdisciplinary research, and last but not least, research integrity.
92 citations
TL;DR: A Monte Carlo simulation with different population models shows that OrdPLSc provides almost unbiased estimates, and if all constructs are modeled as common factors, it yields estimates close to those of its covariance-based counterpart, WLSMV, but is less efficient.
Abstract: This article introduces a new consistent variance-based estimator called ordinal consistent partial least squares (OrdPLSc). OrdPLSc completes the family of variance-based estimators consisting of PLS, PLSc, and OrdPLS and permits to estimate structural equation models of composites and common factors if some or all indicators are measured on an ordinal categorical scale. A Monte Carlo simulation (N =500 ) with different population models shows that OrdPLSc provides almost unbiased estimates. If all constructs are modeled as common factors, OrdPLSc yields estimates close to those of its covariance-based counterpart, WLSMV, but is less efficient. If some constructs are modeled as composites, OrdPLSc is virtually without competition.
87 citations
TL;DR: The authors investigated class diversification at both spatial scales in a Mediterranean city (Athens, Greece) using the European Socioeconomic Classification based on population census data referring to 1991-2001, a phase of economic expansion and intense urban sprawl preceding the 2004 Olympic games.
Abstract: Economic expansion indirectly promotes class diversification at the neighbourhood scale with a consequent reduction of social divides at the regional scale. To verify this working hypothesis, the present study investigates class diversification at both spatial scales in a Mediterranean city (Athens, Greece) using the European Socioeconomic Classification based on population census data referring to 1991–2001, a phase of economic expansion and intense urban sprawl preceding the 2004 Olympic games. Results of multivariate analysis and diversity indexes outline a local-scale social mix associated to suburban expansion, and regional-scale class segregation, reflecting an increasing polarization in affluent and economically deprived urban districts. The contrasting pattern at the two spatial scales results in a complex social geography with class diversification and moderate changes over time in the economic spatial divide between urban and neighbouring rural areas. These findings contribute to design scale-dependent policies reducing social inequalities and improving quality of life in urban areas. Future paths for socio-spatial processes were delineated for sprawling metropolitan regions under economic expansion and discussed in the light of future demographic trends in both developed and emerging countries.
87 citations
TL;DR: Group-mean-centering is, in short, no more dangerous than any other statistical procedure, and should remain a normal part of multilevel data analyses where it can be judiciously employed to good effect.
Abstract: Kelley et al. argue that group-mean-centering covariates in multilevel models is dangerous, since—they claim—it generates results that are biased and misleading. We argue instead that what is dangerous is Kelley et al.’s unjustified assault on a simple statistical procedure that is enormously helpful, if not vital, in analyses of multilevel data. Kelley et al.’s arguments appear to be based on a faulty algebraic operation, and on a simplistic argument that parameter estimates from models with mean-centered covariates must be wrong merely because they are different than those from models with uncentered covariates. They also fail to explain why researchers should dispense with mean-centering when it is central to the estimation of fixed effects models—a common alternative approach to the analysis of clustered data, albeit one increasingly incorporated within a random effects framework. Group-mean-centering is, in short, no more dangerous than any other statistical procedure, and should remain a normal part of multilevel data analyses where it can be judiciously employed to good effect.
TL;DR: It is argued HAPC estimates are the result not of the distinctive substantive APC processes occurring in the dataset, but are primarily an artefact of the data structure—that is, the way the data has been collected.
Abstract: It is claimed the hierarchical-age–period–cohort (HAPC) model solves the age–period–cohort (APC) identification problem. However, this is debateable; simulations show situations where the model produces incorrect results, countered by proponents of the model arguing those simulations are not relevant to real-life scenarios. This paper moves beyond questioning whether the HAPC model works, to why it produces the results it does. We argue HAPC estimates are the result not of the distinctive substantive APC processes occurring in the dataset, but are primarily an artefact of the data structure—that is, the way the data has been collected. Were the data collected differently, the results produced would be different. This is illustrated both with simulations and real data, the latter by taking a variety of samples from the National Health Interview Survey (NHIS) data used by Reither et al. (Soc Sci Med 69(10):1439–1448, 2009) in their HAPC study of obesity. When a sample based on a small range of cohorts is taken, such that the period range is much greater than the cohort range, the results produced are very different to those produced when cohort groups span a much wider range than periods, as is structurally the case with repeated cross-sectional data. The paper also addresses the latest defence of the HAPC model by its proponents (Reither et al. in Soc Sci Med 145:125–128, 2015a). The results lend further support to the view that the HAPC model is not able to accurately discern APC effects, and should be used with caution when there appear to be period or cohort near-linear trends.
TL;DR: This article analyzed existing schools of thought on the nature of populism and argued that conceptualizing populism as a specific type of anti-elite discourse in the name of the people is both conceptually and methodologically the most coherent and useful way to understand the phenomenon.
Abstract: Populism is a concept employed to qualify the political behavior of a large number of actors at a worldwide scale, with scientists classifying the latter into populists and non-populists according to dimensions such as ideology, strategy, discourse, economic policy, and even style. This article analyzes existing schools of thought on the nature of populism and argues that conceptualizing populism as a specific type of anti-elite discourse in the name of the People is both conceptually and methodologically the most coherent and useful way to understand the phenomenon. Additionally, it suggests discarding crude, dichotomous classification in favor of a gradated view of populist mobilization by means of quantifying populist discourse and observing its spatial and temporal variation. It adds value to current methods of measurement by demonstrating why and how clause-based semantic text analysis can provide optimal quantitative results while retaining qualitative elements for mixed-methods analysis. Aiming, moreover, at expanding the scope of populism studies by overcoming a narrow view that focuses exclusively at party system developments, it applies semantic text analysis to the study of grassroots mobilization during the Great Recession. Results point to the wide use of populist discourse on the part of movement activists seeking an inclusive language when framing disparate social grievances in a given constituency, a finding with important implications with regards to how populism can facilitate straddling the divide that purportedly distinguishes institutionalized party system behavior from the social movement milieu.
TL;DR: The study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different, and refers to a reduced version of the well-established technology acceptance model.
Abstract: Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.
TL;DR: A statistical evaluation of progress being made by EU member states in meeting Europe 2020 indicates that most of EU countries show average progress in realisation of Europe’s development programme, which may suggest that the goals may not be achieved in the prescribed time.
Abstract: The European Union (EU), striving to create economic dominance on the global market, has prepared a comprehensive development programme, which initially was the Lisbon Strategy and then the Strategy Europe 2020. The attainment of the strategic goals included in the prospective development programmes shall transform the EU into the most competitive economy in the world based on knowledge. This paper presents a statistical evaluation of progress being made by EU member states in meeting Europe 2020. For the basis of the assessment, the authors proposed a general synthetic measure in dynamic terms, which allows to objectively compare EU member states by 10 major statistical indicators. The results indicate that most of EU countries show average progress in realisation of Europe's development programme which may suggest that the goals may not be achieved in the prescribed time. It is particularly important to monitor the implementation of Europe 2020 to arrive at the right decisions which will guarantee the accomplishment of the EU's development strategy.
TL;DR: This article explored the relationship between unemployment and well-being in Turkey using data from Life Satisfaction Surveys for the period between 2004 and 2013 and found that the unemployed experience significantly lower levels of life satisfaction than the employed.
Abstract: This paper has three purposes. First, it explores the relationship between unemployment and well-being in Turkey using data from Life Satisfaction Surveys for the period between 2004 and 2013. Second, it examines to what extent joblessness at the household level interacts with own unemployment. Third, it tests whether the negative effect of unemployment on well-being varies with individuals’ own perceptions of their labor market prospects. Consistent with the other studies in the literature, findings indicate that the unemployed experience significantly lower levels of life satisfaction than the employed. While the results do not provide support for the social norm effect at the household level, they do indicate that that the impact of labor market status on well-being varies with the job prospects. There is also suggestive evidence that women and men are similarly affected by unemployment and job prospects.
TL;DR: It is concluded that AR application increased student achievement and also ensured that the self-control level of students is increased.
Abstract: A digital layer is being added on real world images through augmented reality (AR), one of the developed new technologies, which has been popular in recent years due to its contributions to the field of education. Permanence and efficiency of science classes where beings and happenings are examined depends on the methods, techniques and materials used. The more senses are addressed, the more positive results are obtained. In this paper, taking into consideration the requirements of science teaching, an AR application was designed for science classes and it was aimed to determine the impact of this application on the achievement and problem-solving skills of students. This study employs quantitative research method and consists of 147 seventh grade students. Among others, it is concluded that AR application increased student achievement and also ensured that the self-control level of students is increased.
TL;DR: In this paper, the authors investigated the environmental impact of urbanization for 49 African countries from 1990 to 2010 within the Stochastic Impacts by Regression on Population, Affluence and Technology framework.
Abstract: Africa’s rapid urbanization pose challenges for her environment and sustainable development. This paper investigates the environmental impact of urbanization for 49 African countries from 1990 to 2010 within the Stochastic Impacts by Regression on Population, Affluence and Technology framework. Using a recently developed semi-parametric panel fixed-effects regression technique, and two atmospheric air pollutants, namely carbon dioxide (CO
$$_2$$
) and ambient particulate matter (PM
$$_{10}$$
) emissions, the evidence show that urbanization reduces environmental pollution. The semi-parametric analysis suggest that the result is more pronounced with PM
$$_{10}$$
but weaker for CO
$$_2$$
emissions. Moreover, there is no evidence to confirm the Kuznets’ hypothesis of an inverted U-shaped curve between urbanization and environmental pollution. Hence, to reap the benefits of urbanization, there is need for a strategic urban planning with basic infrastructure investment that promotes a green environment.
TL;DR: Whether the measures of attitudes toward gender roles included in many representative international and national omnibus surveys need to be adjusted to specific social changes is discussed.
Abstract: The measures of attitudes toward gender roles included in many representative international and national omnibus surveys were developed mostly in the 1970s and 1980s with a focus on the male breadwinner model. This article deals with the issue of whether the measures provided in these omnibus surveys need to be adjusted to specific social changes. A review of these measures has found that adjustments have occurred in a limited way that focused on the role of women and disregarded the role of men. Furthermore, most of these measures only examined the traditional roles of men and women. More egalitarian role models have not been considered sufficiently. In addition, most items that have been measured are phrased in a general form and, for example, do not specify parents’ employment or the ages of children. A specification of these aspects of measurement would help to clarify the conceptual meaning of the results and increase the possibility of more accurately analyzing gender role attitudes over time.
TL;DR: In this paper, a gamified flipped classroom environment is proposed to enhance students' motivations, learning achievements and their perceptions of the designed environment, and the experimental results indicate that the students from the experimental group had a significantly increased motivation for the classroom and learning achievements in comparison to the students in the control group.
Abstract: Increasing students’ motivation for classes and learning has been a critical research topic in the flipped classroom approach. A gamified flipped classroom environment is proposed in this study. The objective of the study is to enhance students’ motivations, learning achievements and their perceptions of the designed environment. In the study, a true experimental design was used. The study was conducted with 61 undergraduate students taking a Physics-2 course. The experimental group students learned in the gamified flipped classroom environment, while the control group students learned with the flipped classroom approach without a gamification strategy. Data were collected from a physics motivation questionnaire, electromagnetism achievement test and semi structured interviews. The experimental results indicate that the students from the experimental group had a significantly increased motivation for the classroom and learning achievements in comparison to the students in the control group. Moreover, it has been determined that the students’ opinions on the gamified classroom environment were positive. Additionally, the students interviewed stated that the approach had positive effects on their motivation for physics class. The results of this study can assist lecturers and instructors in integrating the gamification strategy to the flipped classroom approach.
TL;DR: In this article, the authors apply asymmetric causality tests, proposed by Hatemi-J, with an application to the impact of fiscal policy on economic performance in Scandinavia, to revisit military expenditures-growth nexus for the world top six defense spenders during the period of 1988-2013.
Abstract: This study applies asymmetric causality tests, proposed by Hatemi-J (Asymmetric panel causality tests with an application to the impact of fiscal policy on economic performance in Scandinavia, 2011; Empir Econ 43(1):447–456, 2012), to revisit military expenditures-growth nexus for the world top six defense spenders during the period of 1988–2013. Empirical results indicate that the military expenditure-led hypothesis is supported in China and Japan. However, the growth-led hypothesis is supported in four countries, i.e. France, Russia, Saudi Arabia and US. Except for Saudi Arabia, strong economic growth by no means implies automatic expansion of military expenditures. Defense planning in these countries is a matter of matching their limited resources to attain the suitable priorities. The more threats they perceive, the more spend for defense. This evidence provides useful insight into the behavior of other potential defense suppliers.
TL;DR: In this paper, the authors examined the relationship between housing and subjective well-being among the Vietnamese elderly, using data from the 2011 Vietnam Ageing Survey, and found that permanent housing and better amenities are major factors contributing to housing satisfaction and life satisfaction.
Abstract: This study examines the relationship between housing and subjective well-being among the Vietnamese elderly, using data from the 2011 Vietnam Ageing Survey. Our regression analysis reveals that permanent housing and better amenities are major factors contributing to housing satisfaction and life satisfaction. Notably, we find that housing satisfaction has a strongly positive impact on life satisfaction and the impact is stronger after controlling for endogeneity problems. Thus, the finding confirms that housing is an important life domain and as a result, housing satisfaction is a strong predictor of life-satisfaction judgments. The findings might suggest that people made a rational choice when they invested a large amount of resources in their houses with notable well-being gains. Also, another implication here is that policies and programs to assist poor families in moving out of temporary accommodation or improving housing amenities are likely to be beneficial in improving well-being for the poor elderly.
TL;DR: In this paper, the Lpmin method, based on Lp-norm estimation, an adaptive robust procedure that is used when the residual distribution has deviated from normality, is introduced.
Abstract: Multicollinearity is one of the most important issues in regression analysis, as it produces unstable coefficients’ estimates and makes the standard errors severely inflated. The regression theory is based on specific assumptions concerning the set of error random variables. In particular, when errors are uncorrelated and have a constant variance, the ordinary least squares estimator produces the best estimates among all linear estimators. If, as often happens in reality, these assumptions are not met, other methods might give more efficient estimates and their use is therefore recommendable. In this paper, after reviewing and briefly describing the salient features of the methods, proposed in the literature, to determine and address the multicollinearity problem, we introduce the Lpmin method, based on Lp-norm estimation, an adaptive robust procedure that is used when the residual distribution has deviated from normality. The major advantage of this approach is that it produces more efficient estimates of the model parameters, for different degrees of multicollinearity, than those generated by the ordinary least squares method. A simulation study and a real-data application are also presented, in order to show the better results provided by the Lpmin method in the presence of multicollinearity.
TL;DR: In this paper, the authors explored the interrelationship among CO2 emissions, economic growth, disaggregated energy (fossil fuel and renewable) consumption and population and examined the potential role of renewable energy consumption to ensure environmental quality in favour of growth.
Abstract: An economy in transition that is growing fast coupled with rising population requires more energy Economic growth and greenhouse gas emissions in China have been increasing together over the past several years Exploring the dynamic relationship among these variables has a lot of policy implications related to environment–growth–energy linkage This paper explores the interrelationship among CO2 emissions, economic growth, disaggregated energy (fossil fuel and renewable) consumption and population The broad objective of the paper is to examine the potential role of renewable energy consumption to ensure environmental quality in favour of growth Data spanned from 1971 to 2013 sourced from World Bank data base The results from auto regression distributed lag suggests that fossil fuel energy consumption increases CO2 emissions, both in the short and the long run, but renewable energy consumption reduces CO2 emissions in the long run Although economic growth and population increase CO2 emissions in the short run, their impacts on CO2 emissions in the long run diminish, validating the environmental carbon Kuznets curve hypothesis in China Short run vector error correction mechanism Granger causality results reveal unidirectional causality from both fossil fuel and renewable energy consumption to CO2 emissions revealing growth hypothesis Bidirectional causality exists between both energies and economic growth confirming the role of energy on economic expansion vis-a-vis the role of income on energy consumption The findings have important policy implications for harmonizing economic growth vis-a-vis environmental quality and thus climate change mitigation with a higher proportion of energy from renewables
TL;DR: In this article, the authors synthesized the technology acceptance model, the information system success model, and perceived enjoyment into a hypothesized model to discuss and predict nurses' intentions of using the blended e-learning system continuously.
Abstract: The blended e-learning system (BELS), combining face-to-face classes with e-learning modules, is now widely used in education. The primary purpose of this research was to investigate the factors affecting nurses’ behavioral intentions of using the BELS. We synthesized the technology acceptance model, the information system (IS) success model, and perceived enjoyment (PE) into a hypothesized model to discuss and predict nurses’ intentions of using the BELS continuously. Self-reporting questionnaires were distributed to district hospitals and regional hospitals in central Taiwan. From the 800 distributed questionnaires, we received 557 completed questionnaires, yielding a response rate of 69.6%. Structural equation modeling was used to show that information quality, system quality, and service quality significantly affect perceived usefulness (PU) and the perceived ease of use (PEOU). The effect of service quality on PU, however, was not significant. PU, PEOU, and PE were significantly related to the attitude, and indirectly, to the behavioral intention of using the BELS. This research contributed to the literature by (1) identifying the IS success model (information quality, system quality, and service quality) and PE as antecedents of BELS usage; (2) advancing the theoretical development of behavioral intention regarding nurses’ use of the BELS; (3) providing empirical support for the effects of external factors on the PU and PEOU, which lead to attitude and behavioral intention of usage; and (4) providing hospital managers with a reference for assessing future developments and approaches to promote the BELS.
TL;DR: The study found that the project developed was effective to help students to achieve the learning objectives of the unit, and also to begin building, coding and programming 3D models.
Abstract: This paper presents the findings of a study conducted in the state-funded Infant, Primary and Secondary School Santisima Trinidad in Salamanca. The main objectives of the research were, to evaluate the use of the visual programming environment, Lego Education WeDo, in natural science and to know the benefits of the use of this tool to teach abstract concepts, solve problems and motivate students. In order to achieve these objectives, we used the case study method since we focused on individuals who represented the phenomenon of our interest, and explored and investigated in depth the phenomenon in its natural context bounded by time and space. In the research were involved a teacher and fifty-two students of 4th grade of primary education. The study found that the project developed was effective to help students to achieve the learning objectives of the unit, and also to begin building, coding and programming 3D models. The research showed the teacher’ fundamental role as a guide and students’ active role as builders, programmers, or presenters. There were evidences of the possibilities offered to acquire the skills of critical thinking, creative thinking, problem solving, reflection, collaboration, communication, and time management. Due to the positive results obtained in this study, it is recommended to incorporate computational thinking in primary education and in core content areas since it is fundamental in the current society.
TL;DR: In this article, the authors examined the link between corporate social responsivity and corporate stability and how product market competition affects this relationship and found that firms with stronger CSR performance tend to be more stable.
Abstract: The study examines the link between corporate social responsivity (CSR) and corporate stability, and how product market competition affects this relationship. Using the unique CSR scores to the Chinese firms over the period 2009–2015, we find firms with stronger CSR performance tend to be more stable. This result consistent with the argument that ethically forward-looking managers employ CSR as a powerful tool to manage risk. However, this above positive association between CSR and stability is significant only in highly competitive industries, suggesting that product market competition provides modest incentives for managers to invest in CSR activities for general stakeholders’ interests.
TL;DR: This paper examined and discussed survey strategies among political elites at different government levels in three countries; Belgium, Canada and Israel, and found that the right mix of closed (survey) and open (interview-like) questions decreases item non-response.
Abstract: This study examines and discusses survey strategies among political elites at different government levels in three countries; Belgium, Canada and Israel. More specifically, we discuss recruitment strategies that produce high response levels among hard to reach target populations in different political and cultural environments. Next, we also examine which political elites are most likely to engage in survey research and which ones are hardest to target. We find that (former) top elites (e.g. members of the executive, different types of leadership) are less likely to participate while regional politicians tend to be more likely to participate in this type of research. Finally, we analyze item non-response and find that the right mix of closed (survey) and open (interview-like) questions decreases item non-response. Moreover, after having established trust and rapport, respondents—even high profile elites—will provide answers to relatively personal and intrusive questions. While item non-response remains low in all three countries throughout the survey, there is a noticeable difference between Belgium and Canada on one hand, and Israel on the other, with markedly higher item non-response in the latter.
TL;DR: In this article, the item difficulty and distractive indices of the university wide courses were ascertained, and a range of 112-1956 undergraduate students participated in this study, with the use of secondary data, the expost facto design was adopted for this project.
Abstract: Teachers and Students worldwide often dance to the tune of tests and examinations. Assessments are powerful tools for catalyzing the achievement of educational goals, especially if done rightly. One of the tools for 'doing it rightly' is item analysis. The core objectives for this study, therefore, were: ascertaining the item difficulty and distractive indices of the university wide courses. A range of 112-1956 undergraduate students participated in this study. With the use of secondary data, the ex-post facto design was adopted for this project. In virtually all cases, majority of the items (ranging between 65% and 97% of the 70 items fielded in each course) did not meet psychometric standard in terms of difficulty and distractive indices and consequently needed to be moderated or deleted. Considering the importance of these courses, the need to apply item analyses when developing these tests was emphasized.
TL;DR: In this article, the authors illustrate the most recent stage in the scholarly development of the field of Business Analytics using around 23,000 research publications collected from the Web of Science, and network-analyzed four types of dataset that include keywords, titles, institutions, and countries.
Abstract: In this study, we illustrate the most recent stage in the scholarly development of the field of Business Analytics. Using around 23,000 research publications collected from the Web of Science, we network-analyzed four types of dataset that include keywords, titles, institutions, and countries. It is noteworthy that we found a thematic cluster focusing on analytical techniques and tools, particular with the rapid dissemination of “big data”-related studies. It is not surprising that universities and institutions in advanced countries in the West still occupy the central position of the collaboration network. However, we can discern a global shift toward certain developing and transitional economies in the world science base.