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Understanding intra-urban human mobility patterns and their potential driving forces are vital to city planning and commercial site selection. In this paper, we first investigate the functions of urban regions and how different region types dynamically influence people's trip decisions. Furthermore, we characterize urban circadian rhythms by time-vary inter-regional transition probabilities between these regions with different functions, and integrate them into intervening opportunity model to predict human mobility. Public transportation card data in Shanghai are used to demonstrate the effectiveness of the model in terms of station passenger flows, travel time and trip flux. By taking regional function into consideration, the proposed model significantly improved the prediction accuracy. Quantitative analysis ulteriorly indicates that trip intentions and regional features are critical elements in trip flux prediction, especially in the afternoon and evening when people have an abundance of opportunities to travel by their own volition. When the function of a certain region changes, our model is able to make reasonable predictions accordingly. The results indicate the importance of considering individual travel motivation and regional function in modeling human mobility. The proposed model could serve as a guide for popularity and trip flux prediction in urban planning and reconstruction.

We carry out a quantitative analysis of the financing measures proposed for the European Deposit Insurance Scheme (EDIS) regarding the target level of the fund and the contribution scheme of member entities. We estimate the loss distribution of the EDIS considering different sources of systemic risk associated with the correlations between bank assets inside and outside the eurozone countries, and we analyse the sensitivity of the results to bank portfolio risk. We determine the variations in the cost of insurance due to the relative risk profile of banks in the Banking Union and the loss-absorbing capacity of the contribution made by countries with the methodologies proposed by the European Banking Authority (2015). Our findings show how the interconnection between banks of different countries has an important influence on accumulated losses in the tail of the distribution, although the correlation within a country exerts a stronger effect. Both aspects must be considered in the calibration of the target level of the fund to avoid underestimating financing needs. Likewise, deterioration in the quality of bank portfolios produces a significant reduction in the fund's loss-absorbing capacity, which calls into question its soundness in times of economic recession. Finally, we assess the impact of the new contribution scheme on moral hazard and the possibility of cross-border subsidies between the countries of the Banking Union. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Quantitative analysis is a solid, well established mathematical technique that can be used to analyze the result of survey(s) in a specific field. Survey analysis is usually based on the study of the effect of independent variables on a dependent variable. Although quantitative analysis can use an R-Squared value as a method to measure the strength of the relationship between the independent and dependent variables, it does not capture the effect of participants' ambiguity when answering questionnaires. The source of such ambiguity stems from the process of completing the survey, whereby the respondent may have answered most of the independent questions with ease, but has difficulty in responding to the overall dependent question (or vice versa). The objective of this paper is to demonstrate the use of fuzzy logic as a mechanism to measure the uncertainty faced by participants when filling a questionnaire. Based on the participants' responses to the independent variables, the proposed technique uses fuzzy logic inference to measure the subjectivity (qualitative aspect) of the participants' response to the dependent variable. Beyond quantitative analysis, augmentation with such a fuzzy module can provide clearer picture to analysts when analyzing the survey results.

This paper revisits multiple-airport systems from a noise pollution perspective. It aims to investigate the contradictions between the ( re )development of an older airport located close to the core city, despite the existence of newer airports on the one hand and noise pollution issues on the other hand. Case studies include Tokyo, Shanghai, Paris, Milan, Houston and Rome. Quantitative analysis shows that traffic patterns are more diverse than previous classifications. The qualitative analysis highlights the factors inherent in these patterns, which include passengers' preference for shorter access/egress journeys; inconsistent public policies (older airport not closed, a lack of effective rules for distributing air traffic among airports, permissive land planning and relaxing operational restrictions); low-cost airlines’ network strategies; and high-speed rail/air service integration.

PurposeThis study aims to explore and understand consumers' perceptions and behaviour towards pyjamas in the People's Republic of China (China).Design/methodology/approachA quantitative analysis and comparative methods were used for this study. From a large body of literature, seven product attributes were identified and used to measure and evaluate what constitutes consumers' purchasing decision for pyjamas. A total of 203 usable surveys were compiled, analyzed and collated.FindingsThis study shows evidence that consumers are more conscious of the functional values of a low‐involvement product than the symbolic values. The results of this survey indicate that comfort, fabric and quality are significant attributes, whereas country‐of‐origin and brand are relatively insignificant determinants for purchasing a pair of pyjamas.Research limitations/implicationsLimitations of this study include the use of a convenience sample of female college students and confinement to a specific product – pyjamas. The results of this study are useful for fashion designers and marketers to understand Chinese consumers' perceptions of pyjamas.Originality/valueThis study is one of the few consumer research studies on a low‐involvement and privately consumed apparel product – pyjamas. The findings of this study provide insight and implications for fashion practitioners to develop their product and business in China.

The study’s aim is analyzing the influence of management of customer relationship and brand image on loyalty by way of decision to stay. Population of this study was guests who stayed more than twice at Santika Taman Mini Hotel. The sampling technique uses purposive sampling to obtain 243 respondents. The method of data analysis is quantitative descriptive. The quantitative analysis is done by the use of SEM (Structural Equation Modeling). The results of this research indicate that customer relationship management has a significant which gives influence on stay decision , brand image has got influence which is significant on decision to stay, customer relationship management has a significant influence on loyalty, brand image has a significant influence on loyalty, decision to stayhas a significant on loyalty, customer relationship management has an influence that is indirect on loyalty through decision to stay, and brand image has an indirect influence on loyalty through decision to stay.

In the social sciences, a theoretical analysis has predominated in its research. The scarcity of data and its difficulty in collecting and storing it, has been the main limitation for the social sciences to adopt quantitative approaches. However, the large amount of information generated in recent years, mainly through the use of the Internet, has allowed the social sciences to include more and more quantitative analysis. This study proposes the use of technologies such as Machine Learning (ML) are the answers to solving this data scarcity. The objective is to estimate the multidimensional poverty index at the personal level in a particular territory of Ecuador by using Machine Learning (ML) regression models based on a limited amount of data for training. Ten ML models are compared, such as linear, regularized, and assembled models and Random Forest performs outstandingly against the other models. An error of 7.5% was obtained in the cross-validation and 7.48% with the test data set. The estimates are compared with statistical approximations of the MPI in a geographical area and it is obtained that the average MPI estimated by the model compared to the average reported by the statistical studies differs by 1%.

Purpose This study aims to investigate the relevance of knowledge-oriented leadership (KOL) to technology standard innovation (TSI) from a temporary-team perspective. The mediating and moderating effect on knowledge integration (KI) and leader–member exchange (LMX) is emphasized. Design/methodology/approach The conceptual model is built based on an exhaustive literature review and is empirically tested in terms of a sample of 341 Chinese individuals with TSI experience. Quantitative analysis was performed using a questionnaire with the bootstrapping method used to demonstrate the mediating effect of KI. Findings The empirical results of this study prove that KI mediates the relationship between KOL and TSI. The authors deduce that LMX moderates the positive relation between KOL and KI. Originality/value Few studies have investigated the innovation activities of technology standards from a temporary-team perspective. To the best of the authors’ knowledge, this is the first study to look into the underlying mechanism of KOL in TSI. This research deepens the analysis by introducing LMX’s moderating role in the innovation process of technology standards, thereby providing valuable insights for leaders of innovation activities of technology standards and illuminating new aspects of knowledge-intensive temporary-team management.

Existing studies on the information technology (IT) usage of firms are constrained within the perspective of “IT tool” or “IT investment.” Few studies have analyzed the IT usage of firms from a new perspective. This study aims to fill this gap by examining the impact of IT usage on the innovation performance of small- and medium-sized enterprises (SMEs) from the perspective of the product value chain (PVC). A research model integrating IT usage width, IT usage frequency, manufacturing flexibility, human capital quality, and firm innovation performance was proposed for this analysis. Furthermore, a quantitative analysis was performed on a sample of more than 1300 Chinese manufacturing firms using the newest data provided by the World Bank. Results validate that IT usage width and IT usage frequency have a significantly positive impact on the innovation performance of SMEs. Manufacturing flexibility plays a partially mediating role between IT usage frequency and the innovation performance of SMEs. Moreover, human capital quality has a significantly positive moderating effect on IT usage width and the innovation performance of SMEs. IT usage width and IT usage frequency appear to be important predictors of the innovation performance of SMEs, whereas there are substantial differences in the influencing mechanism of IT usage width and IT usage frequency on the innovation performance of SMEs.

Purpose. Quantitative analysis and identification of determinants of Russian universities’ financial sustainability.Methods. Non-parametric methods for data analysis and machine learning.Results. We proposed two groups of working hypothesis. The levels of financial sustainability of Russian state universities are linked to internal environmental factors including the levels of financial management quality, income-generating activities scale, debt financing, fiscal discipline, academic and research-based activities scales. The levels of financial sustainability of Russian state universities are linked to external environmental factors and depend on the funding patterns and regional dimensions.Conclusions. Special conditions for increased state funding are not sufficient to strengthen universities’ financial sustainability. Moreover, we have established the insignificance of the university geographical location influence on financial sustainability. We have come to a conclusion that both financial management efficiency and prior year financial sustainability have key roles to play in current sustainability formation. Universities with a large scale of income-generating activities are more financially stable due to the diversification of sources of financial support for their overall activities.

We evaluate the welfare cost of housing transaction taxes with a new assignment model-based framework, where welfare effects are driven by distortions in the matching of houses and households. We calibrate the model with data from the Helsinki metropolitan region to assess the impact of a reform where an ad valorem transaction tax is replaced with a revenue-equivalent property tax. The aggregate welfare gain from this reform increases rapidly with the initial transaction tax rate, with the Laffer curve peaking at about 10%. The proportion of households that lose out from the reform is nevertheless increasing in the tax rate. We compare our model-based counterfactual aggregate welfare results with welfare calculations based on reduced-form estimates from previous policy evaluation studies; they are broadly in line, despite the latter using data from different housing markets at various levels and changes of the tax rate.

The purpose of this study is to show how the Japanese government has created laws with harsher punishment since the 1990s. While a tendency toward harsher punishment is common in advanced Western countries, a similar tendency in Japan has prompted scholarly discussion on whether it can be understood through the “penal-populism” framework. However, it lacks in systematic evidence. This study presents three findings that differ from previous studies through a quantitative analysis of legislation with harsher punishment. First, while previous literature argues that the legislation increased in the latter half of the 1990s, this study shows that it peaked in the middle of the 2000s. Second, while previous literature argues that the bureaucrats of the Ministry of Justice promote the legislation, this study shows that it is caused by every ministry’s drafting Bills. Third, this study shows that it does not quantitatively avoid partisan conflicts, contrary to the prediction of the “penal-populism” theory.

Attitude repurchase decision influenced by other three components, which are stay experience. This article aims to discover the psychological effect of customers’ service on the re-purchase decision of AirBNB accommodation facilities in Jakarta. The research uses quantitative analysis. The data collection technique used is questionnaire circulation and literature reviews. The result shows that there are three components influencing respondents to reuse AirBNB services, which are Motivation, Perception, and, Users Review, and Price Sensitivity. Every component provides each influence in determining the repurchase decision of Air bnb. Service psychology holds a great impact on the AirBNB repurchase decision. Other components such as motivation, perception, and attitude play significant roles in the decision and greatly impacted the customers, as well as other factors such as stay experience, guest review and price sensitivity.

Rewriting books was a widespread phenomenon during the Baroque period of the Czech literature. The manuscripts were not always „honest copies”, on the contrary, scribes often compiled several sources or added their own texts to the original. The famous book Golden Key of Heaven by Martin of Cochem is compared with a manuscript Key of Heaven from a Regional museum in the town of Náchod. We use two statistical methods, both of them strongly indicate that the manuscript is a copy of some chapters from the Golden Key of Heaven rather than a compilation.

Purpose This study aims to serve as an important resource for customer engagement (CE) researchers by presenting a comprehensive, up-to-date and objective assessment of the status and evolution of the CE literature. This purpose is achieved through simultaneous consideration and separate analyses of both the marketing/service and hospitality/tourism literature where CE research dominates. Design/methodology/approach This study integrated three review techniques, including a systematic review technique, evaluative technique and relational technique, to present a state-of-the-art analysis of 236 articles. It provides an updated picture of scientific research on CE, as well as the thematic evolution and structure of the CE literature across the two disciplines. Findings Through a comprehensive review of the CE literature in marketing/service and hospitality/tourism domains, the present study findings build a robust foundation to evaluate how this strand of literature has developed and evolved over time. More importantly, a comparative and quantitative analysis of marketing/service and hospitality/tourism journals delivers actionable insight for hospitality and tourism scholars. Research limitations/implications This study reframes the scientific knowledge regarding the evolution of CE literature, along with interrelation patterns, to advance relevant studies in hospitality and tourism. Findings offer a broadened perspective on the concept’s scholarly development and current research trends, thereby charting a new path for future research. Originality/value By adopting three review techniques, to the best of the authors’ knowledge, this state-of-the-art analysis is the first to compare and synthesize a large volume of marketing/service and hospitality/tourism research, assembling a springboard from which to evaluate how CE studies have developed.

Interteaching is a behavioral teaching method that departs from the traditional lecture format (Boyce & Hineline in BA 25:215–226, 2002). We updated and expanded previous interteaching reviews and conducted a meta-analysis on its effectiveness. Systematic searches identified 38 relevant studies spanning the years 2005–2018. The majority of these studies were conducted in undergraduate face-to-face courses. The most common independent variables were manipulations of the configuration of interteaching or comparisons to traditional-lecture format. The most common dependent variables were quiz or examination scores. Only 24% of all studies implemented at least five of the seven components of interteaching. Prep guides, discussions, record sheets, and frequent assessments were the most commonly implemented. Meta-analyses indicated that interteaching is more effective than traditional lecture or other control conditions, with an overall large effect size. Furthermore, variations in the configuration of the interteaching components do not seem to substantially limit its effectiveness, as long as the discussion component is included. Future research informed by the present review includes: (a) investigating the efficacy of interteaching in additional academic areas, online environments, workplace training, and continuing education, (b) testing alternative outcome measures, generalization, and procedural integrity, (c) conducting systematic component analyses, and (d) measuring social validity from the instructor’s perspective. Supplementary Information The online version contains supplementary material available at 10.1007/s10864-021-09452-3.

The construction industry in Saudi Arabia represented around 5.5% of the gross domestic product (GDP) in 2019 and employed around 26.4% of the total workforce in the Saudi private sector; however, only 12.5% of the construction workers are locals. In 2020, unemployment has reached 15.4% among Saudi nationals. Concurrently, approximately 6.7 million workers in the Saudi private sector are non-locals. This paper investigates the challenges and opportunities of employing locals in the construction industry. A quantitative analysis of the public statistics is conducted to determine the genuine challenges and potential opportunities in replacing non-locals with locals in the construction industry. The analysis reveals that although most of the Saudi construction industry workforce (87.5%) are non-local, the construction industry practically can accommodate around 9.5% of unemployed Saudis annually based on the current distribution of unemployed Saudis and the construction labor market. The analysis, also reveals that most unemployed Saudis are college graduates with majors that do not fit to find, suitable jobs in the construction industry. Among the findings that the Saudi construction industry will continue to need a non-Saudi workforce. Furthermore, though most unemployed Saudis are college graduates, there is a shortage of Saudis with appropriate training and academic majors.

Purpose This paper aims to propose an Islamic compliant approach that deals with the prepayment rebate on debts resulting from cost-plus sales and their accompanied sale-based financing contracts. The proposed approach uses the time value of money concept without charging excessive fees from the debtor in the early settlement of debts. Design/methodology/approach The paper uses a qualitative analysis via analyzing and reviewing relevant literature. A quantitative analysis is subsequently used with a proposed computation that addresses prepayment rebate accompanied by debts resulting from cost-plus sales. Findings The proposed approach results in a rebate amount for the debtor greater than those rebate amounts resulting from either conventional finance techniques or current Islamic finance practices. Research limitations/implications The application of the descending rebate proposed computation in this paper is restricted to cost-plus sale and their accompanied sale-based financing contracts only. The computation does not address any agreement or deal that may involve a rebate without a selling transaction. Originality/value The paper criticizes the prevailing practices for computing rebates in the case of debt prepayment, whether those nominated by conventional finance or others currently employed by most Islamic financial institutions. The paper also introduces a new rebate computation aimed to comply with Islamic finance's real context.

Purpose This study aims to examine the impact of the three dimensions of materialism, namely, possessiveness, envy and non-generosity along with attitude on the purchase intention of sustainable luxury products. Design/methodology/approach The research study contains a descriptive approach to research with a quantitative analysis done with exploratory and confirmatory factor analysis with 229 respondents. Findings The findings of the results contribute to research by extending the model of the theory of planned behavior with the material dimensions as an add-on. Research limitations/implications The same could have been extended to all major metro cities of Indian where luxury brands are present in malls. Practical implications This shows that the consumer with a high level of materialism trait would be a very prospective segment for sustainable luxury brands. Originality/value The study shows that the three dimensions of materialism do impact the purchase intention of sustainable luxury producers and these findings will be crucial for devising consumer behavior-based strategies for sustainable luxury brands.

This paper uses the exogenous shock generated by the COVID-19 pandemic and the relative government response as an informative case in investigating the factors able to affect policy efficacy. Lockdown measures have been widely adopted to limit the diffusion of COVID-19, indirectly supporting the capacity of the hospital system to face the pandemic. Lockdown obliges people to change their social behaviour significantly, and consequently is a matter of serious concern amongst the population. For this reason, how people react to lockdown is of the utmost importance, since failure to observe it properly will be of little benefit in reducing contagion. In this rationale, factors correlated with individuals’ behaviour could affect the efficacy of such measures. The aim of this paper is to investigate whether differences in institutional quality and social capital are correlated with the efficacy of lockdown measures, taking the Italian provinces as a case study. Using a quantitative analysis employing F-GLS estimators, our results suggest that both local social capital and institutional quality have affected the efficiency of lockdown measures in Italian provinces. In general terms these factors contribute to forming the set of incentives able to promote individual behaviour that is in closer compliance with government choices. In this perspective, institutional quality and social capital can be considered factors able to influence the efficacy of policies.

With European Union agencies becoming increasingly significant actors in European governance, further research is needed to understand how they interact with their environment. Applying the ‘reputation’ literature to Europol, this article examines in greater detail how agencies behave with their ‘informal’ audiences in comparison with the formal ones. It demonstrates that agencies are deeply invested in the shaping of their reputation, including towards their informal audiences especially if the latter represent ‘reputational threats.’ Based on a quantitative analysis of activity reports and on a qualitative study of the face-to-face engagements of Europol with the European Parliament over time, this research sheds light on the complementary communicative strategies agencies can use to (re)present themselves depending on the dimension of their reputation at stake.

Many researchers are confused about which software to use because there is no research on software comparisons for quantitative research data analysis. The purpose of this study is to compare the results of quantitative research data processing in the field of education management using Lisrel, Tetrad, GSCA, Amos, SmartPLS, WarpPLS, and SPSS software for small samples or respondents. This research method is quantitative and research data analysis uses the four types of software to obtain a comparison of the results of the analysis. The analysis in this study focuses on the analysis of hypothesis testing and regression analysis. Regression analysis is used to measure how much influence the independent variable has on the dependent variable. The field of this research is education management and the research data uses quantitative data derived from questionnaire data for a small sample of 40 respondents with three research variables, namely the independent variable of transformational leadership and job satisfaction, while the dependent variable is teacher performance. Based on the results of the analysis using Lisrel, Tetrad, GSCA, Amos, SmartPLS, WarpPLS, and SPSS software, the results showed that for a small sample there was no significant difference in the significance value of p-value and t-value. There is also no significant difference in the determination value, and the correlation value in the resulting structural equation also has no significant difference in results, while for CB-SEM represented by Lisrel, Tetrad cannot process data with a Little respondents size. The novelty of this research is the result of comparative analysis of Lisrel, Tetrad, GSCA, Amos, SmartPLS, WarpPLS, and SPSS

PurposeThis paper aims to compare the rebate computation in Islamic sale-based financing contracts as proposed by Bank Negara Malaysia (BNM) in its guidelines on ibrāʾ (rebate) – with the rebate computation in conventional finance that is applicable to conventional loans, thus examining if there is a significant difference between the two approaches.Design/methodology/approachThe paper employs the qualitative analysis method, involving review and discussion of relevant literature. Subsequently, a quantitative analysis is utilized to compare both rebate computations: the one proposed by BNM for Islamic sale-based financing contracts and the conventional finance computation that is utilized in conventional loans.FindingsBNM's rebate computation for debts resulting from sale-based financing contracts does not differ from the conventional finance rebate computation applied to conventional loans; such similarity may raise the usury concerns that the conventional finance rebate computation raises.Research limitations/implicationsThe paper focuses only on the fixed profit rate rebate computation proposed by BNM guidelines.Practical implicationsThe results highlight the need for seeking another rebate computation to be applied in Islamic financial institutions in the case of mandatory bilateral rebate for sale-based financing contracts – a computation that differs from the practice utilized in conventional loans in order to avoid any usury implications associated with conventional finance computation.Originality/valueThe paper examines the rebate practice proposed by BNM for sale-based financing contracts. Forcing a predetermined rebate computation in sale-based financing contracts could be plausible as BNM requires; however, the suggested computation might be questionable because it resembles conventional finance computation.

With the big data bibliometric analysis function of CNKI, 925 documents were retrieved with "research travel" as the keyword. Visual analysis and index analysis were performed on these documents. In terms of development trend, authors, keywords, fund support and research level, the characteristics of research progress of domestic research travel are summarized.According to the quantitative analysis results of big data, it can be seen that the research on research travel is in the exploratory stage and the research level is single.In the future, researchers need to continuously deepen their research, increase the research of industry guidance, vocational guidance, basic and applied basic research and other types, and constantly enrich the research levels; grasp the hot spots such as geographical practice, core literacy, geographic core literacy, curriculum development, quality education, small research topics, etc, and deepen the research contents of research travel.

The development of industry is inseparable from the improvement of technical personnel's English level. Nowadays, College English classroom is inefficient. Various experts and scholars start from changing the teaching content, teaching methods and teachers' position in the classroom to solve the practical problems. No matter what aspect of the reform has promoted the further development of College English teaching, but it has not completely solved the practical problems in College English classroom. This paper proposes a quantitative teaching model of College English classroom performance to stimulate students' enthusiasm. Through the combination of qualitative analysis and quantitative analysis, this paper analyzes the teaching practice results of College English curriculum integration. The research shows that the integration of College English curriculum and multi teaching education can effectively improve students' English literacy. In the current environment, it is an effective way for colleges and universities to carry out media literacy education. The study also reflects the low level of students' English literacy, which needs to be paid attention to.

When it comes to COVID-19, access to reliable data is vital. It is crucial for the scientific community to use data reported by independent territories worldwide. This study evaluates the reliability of the pandemic data disclosed by 182 countries worldwide. We collected and assessed conformity of COVID-19 daily infections, deaths, tests, and vaccinations with Benford’s law since the beginning of the coronavirus pandemic. It is commonly accepted that the frequency of leading digits of the pandemic data shall conform to Benford’s law. Our analysis of Benfordness elicits that most countries partially distributed reliable data over the past eighteen months. Notably, the UK, Australia, Spain, Israel, and Germany, followed by 22 different nations, provided the most reliable COVID-19 data within the same period. In contrast, twenty-six nations, including Tajikistan, Belarus, Bangladesh, and Myanmar, published less reliable data on the coronavirus spread. In this context, over 31% of countries worldwide seem to have improved reliability. Our measurement of Benfordness moderately correlates with Johns Hopkin’s Global Health Security Index, suggesting that the quality of data may depend on national healthcare policies and systems. We conclude that economically or politically distressed societies have declined in conformity to the law over time. Our results are particularly relevant for policymakers worldwide.

Platform-based banking provides opportunities for financial systems to increasing competition, stimulating a FinTech economy, and improving the availability and quality of service to the customers. Platform-based banking is a system that provides a user with a network of financial institution’s data through the use of application programming interfaces. With the help of platform banking, it is easy to show how data be created, accessed, and shared. The purpose of this paper is to provide a model of platform banking in commercial banks of Iran by benefiting banking experts. A mixed method was used in the present research including qualitative and quantitative analysis. The qualitative strategy of the present study is based on the grounded theory method, and the quantitative strategy is conducted using the structural equation model based on the Strauss and Corbin model. The main tool for collecting qualitative information was semi-structured interviews, in which the data were coded in three stages: open, axial, and selective coding. In the quantitative phase, the descriptive survey method was used to analyze and explain the proposed model through structural equations and using SmartPLS software. According to the codes which were obtained from the interviews, the 373 final codes were extracted in the form of 51 concepts, 25 sub-categories, and 6 main categories. In the quantitative part of the research, causal relationships between variables and testing the research hypotheses were performed. The findings show that the platform banking model has six components such as economic management and banking process reform, customers experience management, infrastructure engineering, and implementation mechanisms, digital strategic management of customer, and facilitate the achievement of structural productivity and digital governance in the shadow of knowledge partnerships with competing partners. Developing a model of platform banking model depends on the superior management of these components. Also, the research results indicate the confirmation of the conceptual model presented using the structural equation model. All structural model fit indices had acceptable values.

Bénabou [(2002) Econometrica 70, 481–517.] demonstrated how progressive redistribution mitigates unequal opportunity for education to promote growth. We ask how effective that policy is when it affects the average quality of education. So, we add a learning externality in his model of human capital accumulation. It captures how knowledge diffusion through global channels—such as a national educational curriculum—influences children’s learning outcomes and, hence, growth. Whether inequality is a curse or a blessing for economic growth depends on how efficiently an economy designs these channels and to what extent they influence children’s education. The greater this efficiency, the lower is the optimal progressiveness of income redistribution for maximizing the long-run output growth rate. Interestingly, if poorly designed global channels exert greater influence in education, the optimal progressivity may increase. Our quantitative analysis reveals new implications for redistributive policies, including a surprisingly low optimal progressivity (approximately 6–7%) for the calibrated US economy.

Peer review is one of the most important processes of scientific evaluation. This paper proposes a consistency index to measure the performances of scholar journal reviewers on recognizing papers with higher scientific influences with respect to citations. The index is initially designed based on three consistencies, i.e., expert consistency, editor consistency and academic community consistency, to capture both the knowledge implied in the review data and the bibliometric data. An iterative computation process is then proposed to make the consistency flow among experts based on their historical performances. Further, a quantitative indicator is designed to characterize the ability of an expert of recognizing papers with higher quality during review process. Experiments are conducted to verify the convergence of the iterative computation, and to evaluate the effectiveness of the consistency index. The experimental results show that the performance of the top experts (with regard to consistency index) is always better than the tail experts, and the performance can be maintained over time. We believe that the proposed index can help journal editors get deeper understanding to their reviewers, and provide evidence in the process of reviewer selection.

Philanthropic endeavors are a form of institutionalized collective action that enhances a community’s capacity to address community needs and interests. Despite studies investigating the complex relationships between local economies, social capital, and local philanthropy, much remains unknown concerning the interaction between diverse local economic structures, social capital, and local philanthropy. Therefore, we explore whether local economies and social capital affect a community’s capacity to mobilize collective resources for two distinct forms of local philanthropy: elite and social welfare-oriented. Using a quantitative analysis, we empirically examine these relationships using a dataset covering three specified years spanning 3,036 US counties. Findings suggest that the diversity of local economic structures play a moderating role in facilitating the effect of social capital on local philanthropic activities aimed at satisfying local community demands and interests. The results illustrate important policy implications concerning the diversification of economic resources for local policymakers and community leaders.

Purpose This paper aims to explore the possibilities in using such national, statutory data sets for evaluating change and the challenges of understanding service patterns and outcomes in complex cases when only a limited view can be gained using existing data. The discussion also explores how methodologies can adapt to an evaluation in these circumstances. Design/methodology/approach This paper examines the use of data routinely collected by local authorities (LAs) as part of the evaluation of innovation. Issues entailed are discussed and illustrated through two case studies of evaluations conducted by the research team within the context of children’s social care in England. Findings The quantitative analysis of LA data can play an important role in evaluating innovation but researchers will need to address challenges related to: selection of a suitable methodology; identifying appropriate comparator data; accessing data and assessing its quality; and sustaining and increasing the value of analytic work beyond the end of the research. Examples are provided of how the two case studies experienced and addressed these challenges. Research limitations/implications • Quasi-experimental methods can be beneficial tools for understanding the impact of innovation in children’s services, but researchers should also consider the complexity of children’s social care and the use of mixed and appropriate methods. • Those funding innovative practice should consider the additional burden on those working with data and the related data infrastructure if wishing to document and analyse innovation in a robust way. • Data, which may be assumed to be uniform may in fact not be when considered at a multi-area or national level, and further study of the data recording practice of social care professionals is required. Originality/value The paper discusses some common issues experienced in quasi-experimental approaches to the quantitative evaluation of children’s services, which have, until recently, been rarely used in the sector. There are important considerations, which are of relevance to researchers, service leads in children’s social care, data and performance leads and funders of innovation.

Many popular social network sites (SNSs) provide the post-syncing functionality, which allows users to synchronize posts automatically among different SNSs. Nowadays there exists divergence on this functionality from the view of sink SNS. The key to solving this problem is to understand the characteristics of users’ post-syncing practice and goals and evaluate whether they are consistent with an SNS’s norms, cultures, and goals. However, studying and understanding the characteristics of post-syncing practice and goal are challenging tasks as a result of the difficulty of data sampling and the complexity of post-syncing behavior. In this article, we focus on investigating this question by quantitative analysis in combination with qualitative analysis. In the quantitative study, by utilizing 211,233 synced-posts sampled from Weibo, we aim to investigate characteristics of post-syncing from three perspectives: user, content, and goal. The results suggest that post-syncing plays an important role in exhibiting one’s current activities, creations, and skills as well as advertisements but involves a risk of exhibiting personal sensitive profiles. To understand the results, we present an interview-based qualitative study based on thematic analysis. It indicates that the publicity, urgency, and remarkableness of contents and differences of social affordances and social circles between sink SNS and source SNS as well as the one-time consent of post-syncing authentication jointly account for the major role of post-syncing. Based on these results, we propose insights for post-syncing functionality’s adoption, design, and promotion.

Purpose In southeast Asia, international companies are growing to serve customers with multiple faiths. This study aims to focus on Thailand and it is one of Southeast Asia’s nations and it has Muslim minority customers. To represent Thai Muslim companies, Thai Muslims are marketing their goods by bearing the tagline “we are Islamic”. Scholars described it as “Islamic brands”. This research describes the significant feature of Islamic brands between Thai Muslim people. It examines, which of the Islamic brand dimensions motivates Thai customers towards buying Islamic brands. Design/methodology/approach The current study’s conceptual model was the theory of planned behaviour (TPB) and 281 Thai Muslims responded via a standardised survey. The data was collected from four southern Thailand provinces (Narathiwat, Pattani, Satun and Yala) and the statistical application Smart-partial least-squares 3 was used for data analysis. Findings The most significant factor motivating Thai Muslims towards purchasing Islamic brands is the customer’s Islamic brand. The second factor was the Islamic brands by compliance and Islamic brands by country of origin. Research limitations/implications Three regions in Thailand have been researched, as well as the results concentrate only on three Islamic brand attitudes as independent variables and the development of behavioural expectations of TPB. This research also presents a model that could help understand the consumer perceptions about Islamic brands and established brands amongst various consumers. Practical implications The present research applies to small companies and multi-national businesses, as it illuminates and recognises the image of Islamic brands and suggests the preferences of customers in selecting the brand of Islamic brand. Originality/value The current study aims to explain Thai Muslim customers’ buying behavioural intentions while purchasing Islamic brands in Thailand.

This study aims to find out more about the management of the basic food stall business so that it can compete with other basic food stalls. The method used in this research is a qualitative and quantitative analysis method. Qualitative analysis is used to determine the management process using management functions (Planning, Organizing, Actuating, Controlling), and quantitative analysis using the calculation of Cash Flow, Break Even Point (BEP), Payback Period, and B/C Ratio (Benefit Cost Ratio). ). From the results of the calculation of the financial aspect, it can be seen that the profit of Mr. Rahmad's food stall business using cash flow calculations is Rp. 7,670,000 per month, while the payback period is 4 months, the return on investment is acceptable. The calculation of the unit BEP is 143.36 kg. Meanwhile, the rupiah unit BEP is Rp. 3,442,959. According to the calculation of the Benefit Cash Ratio of 18.4 > 1, Pak Rahmad's basic food stall is feasible.

The purpose of this study is to make a quantitative analysis and to compare scientific productivity between the countries of India and South Korea: both countries offer scholarships and fellowships for various programs and disciplines. The data are collected from SCOPUS through the open access portal www.scimagojr.com and mainly focus on rank and number of publications, global publication share and growth of publications, international collaboration pattern, quality of publications, and open access pattern. Various bibliometric indicators have been used along with simple percentage. Further, a new relative indicator Relative Open Access Index (ROAI) is proposed to compare the number of documents in an open access platform with its overall scientific production. Among the most productive countries, India is ranked at fifth and South Korea at thirteenth in the year 2018. India improved by eight positions while South Korea did by three from 1998 to 2018 at the global level. South Korea has a higher proportion of publications with international collaboration as compared to India. Both countries maintain better positions in a few disciplines such as chemical engineering and materials science.

After the Brexit referendum, the behavior of the UK economy defied widespread expectations, as it did not exhibit a V-shaped recession but a slow decline in production. We show that this pattern of propagation arises when uncertainty is about future, rather than current, fundamentals and if the expected duration of uncertainty is sufficiently long. We reach this conclusion within the confines of a heterogeneous firms model featuring news uncertainty rather than conventional uncertainty shocks. In the quantitative analysis, uncertainty is informed by firm-level probability distributions on the expected effect of Brexit on sales. (JEL E22, E23, E24, E32, F15)

The aim of this study is to determine the impact on tax management of the fixed asset intensity, debt level, and compensation of the board of commissioners and directors in manufacturing companies listed on the Indonesian Stock Exchange. This is a quantitative analysis that employed the purposive sampling approach to obtain a sample of 29 businesses. The data used is secondary data from financial reports on manufacturing firms that were listed on the Indonesian Stock Exchange between 2015 and 2019. Multiple linear regressions used to evaluate the data. The findings indicate that the intensity of fixed assets has an effect on tax management, the amount of debt has no effect on tax management, and compensation for commissioners and directors has no effect on tax management. Simultaneously, the intensity of fixed assets, the amount of debt, and board of commissioners and director salaries all have a huge impact on tax management.

We presentCogNet, a large-scale, automatically-built database of sense-taggedcognates—words of common origin and meaning across languages. CogNet is continuously evolving: its current version contains over 8 million cognate pairs over 338 languages and 35 writing systems, with new releases already in preparation. The paper presents the algorithm and input resources used for its computation, an evaluation of the result, as well as a quantitative analysis of cognate data leading to novel insights on language diversity. Furthermore, as an example on the use of large-scale cross-lingual knowledge bases for improving the quality of multilingual applications, we present a case study on the use of CogNet for bilingual lexicon induction in the framework of cross-lingual transfer learning.

The purpose of this paper is to report on a quantitative analysis of the LCGFT vocabulary within a large set of MARC bibliographic data retrieved from the OCLC WorldCat database. The study aimed to provide a detailed analysis of the outcomes of the LCGFT project, which was launched by the Library of Congress (LC) in 2007. Findings point to a moderate increase in LCGFT use over time; however, the vocabulary has not been applied to the fullest extent possible in WorldCat. Further, adoption has been inconsistent between the various LCGFT disciplines. These and other findings discussed here suggest that retrospective application of the vocabulary using automated means should be investigated by catalogers and other technical services librarians. Indeed, as the data used for the analysis show somewhat uneven application of LCGFT, and with nearly half a billion records in WorldCat, it remains a certainty that much of LCGFT’s full potentials for genre/form access and retrieval will remain untapped until innovative solutions are introduced to further increase overall vocabulary usage in bibliographic databases.

PurposeSimulation has attracted increasing attention in lean production research as a response to address the complexities of the production environment and difficulties of dealing with changes within a system. Considerable growth of using simulation to facilitate lean acceptance and implementation has been observed across different projects and sectors. However, a thorough review of the development and use of simulation in lean production research is limited.Design/methodology/approachThis study aims to address this gap by reviewing 311 journal papers published in the past two decades on this specific research area and identify the state-of-the-art development and propose future research directions.FindingsThe review shows that current studies related to simulation in lean production research can be categorised into two major research streams, namely, simulation assisted lean facilitation and evaluation, and simulation-based lean education and training. Under the first research stream, a total of 19 application areas have been identified which applied both lean and simulation in their studies. The evolution of the simulation techniques used in these studies has been analysed as well. Meanwhile, four types of simulation games have been identified in the stream of simulation-based lean education and training and the impact and applicability of the different simulation and games have been discussed. A framework for engaging lean and simulation is suggested based on the review of the existing studies. The analysis in both streams also highlights the importance of stakeholder engagement and the utilisation of information technologies for future studies.Practical implicationsThe findings of this study are expected to provide useful references for the future development and application of simulation in lean production research.Originality/valueThis paper conducted a broad and extensive review of simulation integrated lean production research. An in-depth examination of the retrieved papers was conducted through a structured and quantitative analysis to understand the current body of knowledge.

Purpose: The purpose of the study was to assess practices, opportunity and challenges of SIP in selected primary schools of Elu Gelan Woreda. Methodology/Approach/Design: A descriptive survey method was employed. The population of the study was 90 teachers, 14 principals, 7 primary school supervisors, 1Woreda Education Office heads, 3 Woreda Education Office process owners and 31 SIP committee. The data obtained from the questionnaires were analyzed using simple statistical tools such as frequent count and percentages, while the data obtained through interviews, Focus Group discussions, Observation checklist and Document review were analyzed qualitatively to substantiate the result of quantitative analysis. Findings: The findings of the study showed that there is a shortage of financial support and a lack of awareness among stakeholders. The results also indicate that there is a lack of learning facilities and poor community participation. The study revealed poor management, poor community mobilization, and poor collaboration in SIP implementation. Practical Implications: Based on the results of the study, it is proposed that an adequate awareness creation program should be implemented to ensure the practical involvement of all stakeholders; organizing and allocating the necessary resources, providing proper technical support and practical training to support the implementation of SIP. The findings of the study may help schools and other educational authorities at different administrative levels in providing valuable information for planners and policymakers to set strategies for better school improvement. Originality/Value: SIP in the study area was not implemented as indicated in the framework of SIP.

In recent years, international and national university ranking exercises have become commonplace, serving a host of stakeholders and beneficiaries including students, institutions, and governments. As such, they have drawn increasing scrutiny from academics and other observers, many of whom have called into question the integrity of the methodologies employed, and thus the outcomes of the process. By contrast, relatively little attention has been paid to largely external factors that can affect a given institution’s ability to compete within a given ranking exercise, such as their corporate status, geographic location, and/or access to resources. Building on previous work examining the impact of such “extraneous” factors, this study undertakes a quantitative analysis of the best-known university ranking exercise in Brazil to better understand the impact of such variables, both within other national contexts and well beyond.

Simulation-based dynamic traffic assignment (DTA) models play a vital role in transportation planning and operations. While the widely studied equilibrium-seeking DTA including dynamic user equilibrium (DUE) often provides robust and consistent outcomes, their expensive computational cost for large-scale network applications has been a burden in practice. The noniterative stochastic route choice (SRC) model, as a nonequilibrium seeking DTA model, provides an alternative for specific transportation operations applications that may not require equilibrium results after all (e.g., evacuation and major network disruptions) and thus tend to be computationally less expensive, yet may suffer from inconsistent outcomes. While DUE is a widely accepted approach for many strategic planning applications, SRC has been increasingly used in practice for traffic operations purposes. This paper aims to provide a comparative and quantitative analysis of the two modeling approaches. Specifically, a comparison has been made at two levels: link-level flows and network-level congestion patterns. Results suggest that adaptive driving improves the quality of the SRC solution, but its difference from DUE still remains significant at the link level. Results have practical implications for the application of large-scale simulation-based DTA models for planning and operations purposes.

Purpose of the paper: The aim of this paper is to explore the effects generated by a suite of cultural micro-medium events in an urban destination on both hotels’ performance and the seasonality structure in order to promote sustainable tourism development. Methodology: The empirical analysis uses a mixed method that combines a quantitative analysis of the daily performance of a destination with a desk analysis of press interviews to local stakeholders. Findings: The results highlight a positive contribution of cultural micro-medium events to tourism at the destination. This evidence contributes to the academic debate on strategic event management by shedding light on the potential role of minor cultural events as a driver for sustainable tourism development. Practical implications: This study suggests guidelines to destination managers on how to benefit from micro-medium cultural events: a strong connection with the destination’s vocations, the importance of public-private collaboration and the establishment of a portfolio of recurrent events. Limitations of the research: This explorative study presents two main limitations: the authors cannot exclude that other small events were taking place in the city at the same time as the micro-medium cultural events analysed. Secondly, several of the events studied are recent and therefore their impact on the destination could be underestimated. Originality of the paper: During the last decades, the managerial literature has been devoting considerable attention to the role and the benefits generated by events. However, the main focus of these studies has been on large and mega events while little consideration has been dedicated to smaller events which are widespread, recurrent and relatively easier to manage.

Intellectual capital means asset as valuable power source for firms to increase firm performance. One of performance measured is economic value added (EVA). The study aims to find empirical evidence the role intellectual capital and EVA for Firms listed in Indonesia Stock Exchange. Research Method uses quantitative analysis with SPSS 15. Examining data uses linier Regression Analysis that means examining independent variable to dependent variable. The study provided some findings that intellectual capital influence to EVA. Parsial test showed that VACA and VAHU significant influence to EVA, however STVA can not influence significantly to EVA. The beneficial of research such as developing literature between intellectual capital and EVA, for managing intellectual capital and EVA in public firms.Keywords : Intellectual capital, economic value added, Indonesia Stock Exchange

Purpose: Multiple-measure principal evaluation systems have become commonplace in the past decade, but we do not know how principals perceive their evaluations under these regimes. This study analyzes how principals perceive evaluation in a state that was an early adopter of such a system. It describes how attitudes are explained by individual and contextual factors, performance ratings, and elements of the evaluation process. Research Methods: Using data from a statewide survey of Tennessee principals in three consecutive school years, we create an index of principal evaluation perceptions of evaluation, then employ regression analysis to predict principals’ attitudes with measures gleaned from survey and administrative data sources. Findings: High school and veteran principals have more negative views of their evaluations. Practice ratings from the principal’s supervisor, though not the overall evaluation score, are positively correlated with attitudes. Principals assigned ratings more often view evaluation more positively, even accounting for their rating, as do principals who have worked longer with their evaluator. We find no evidence that racial or gender matching between principals and raters leads to more positive perceptions, and in fact Black principals may perceive evaluation more negatively when their evaluator is Black. Implications: Our results suggest some directions for states and districts seeking to make evaluation more meaningful for principals. Principals appear to value both frequency of feedback and consistency in raters over time. These factors may be especially important for low-rated principals, veteran principals, and those in secondary schools, who may perceive less value from principal evaluation.

In the context China-US commerce war and Covid 19 and Industry 4.0, wht happens to banking sustainability in emerging markets such as Vietnam? By using both quantitative analysis with statistics, charts and comparison, combined with qualitative analysis with synthesis, inductive and explanatory methods, research results show us that June is the month banks experience highest or lowest values of market risks, and during pre low inflation time, more beta values (max, mean, median) are equal to 1 or lower than 1. Whereas during post low inflation stage, several more beta values (max, mean, median) higher than 1. Then, Main findings could be used for socio-economic policy implications in Vietnam. And research model can be applied for other countries, esp. Emerging markets. © 2021 Karadeniz Technical University. All rights reserved.