Business Statistics Research Articles

Developments of Economic Growth and Employment in Bioeconomy Sectors across the EU

The development of the bioeconomy—or the substitution of fossil-based materials and energy by bio-based solutions—is considered a strategic economic orientation by the European Commission and its Green Deal. This paper presents a methodology to monitor the contribution of the bioeconomy to jobs and growth within the European Union (EU) and its Member States. Classified as an ‘‘output-based’’ approach, the methodology relies on expert estimations of the biomass content of the bio-based materials produced in the EU and the subsequent calculation of ‘‘sectoral’’ bio-based shares by using Eurostat statistics on the production of manufactured goods (prom). Sectoral shares are applied to indicators of employment, and value added is reported in Eurostat–Structural business statistics. This paper updates the methodology and time series presented in 2018. The bioeconomy of the EU (post-Brexit composition) employed around 17.5 million people and generated €614 billion of value added in 2017. The study evidences structural differences between EU national bioeconomies, which become more pronounced over time, especially in terms of the level of apparent labour productivity of national bioeconomies. Finally, this paper describes cases of transition over the 2008–2017 period.

Issues in Tourism Statistics: A Critical Review

The purpose of this paper is a discussion of some major concepts and operational definitions involved in tourism statistics within Regulation 692/2011, with a cross-country comparison and an in-depth look at the Italian case. Data and information are derived from main documents of major international and national institutions and Eurostat metadata. Both demand-side and supply-side data sources on tourism are discussed. The work highlights the main differences in the data production processes of different EU countries, although they follow the same regulation. The main critical points are: the definition of usual environment and survey design for the demand-side data, as well as the statistical unit for the supply-side data, which does not coincide with that used in structural business statistics. The analysis is limited to those EU countries with complete available Eurostat metadata. Moreover, only household surveys relating to trips and vacations are considered for demand-side data (border surveys are not treated). The main contribution is concerned with the description of the current situation in the production of tourism statistics, by looking and their comparability for cross-country analyses and at the possibility of their integration and reconciliation in the perspective of building a system of tourism statistics.

Enhancing Classroom Engagement Through Padlet as a Learning Tool: A Case Study

Activities conducted in classrooms are important to acquire students’ understanding and participation in a learning environment. Some of perceived barriers that prevent students to participate in classroom activities include difficulty to speak, shy, fear to interact or provide comments. This paper focuses on using Padlet for e-learning and presents the activities of engaging and stimulating students in active learning. This is one way of how instructors can obtain information from each student by encouraging participation. The research employs quantitative approach. A semi-structured questionnaire was distributed among 39 postgraduate students who enrolled in the Business Statistics for Data Science course. Factors such as motivation, active learning, collaboration, learning opportunity, usefulness, ease of use, and satisfaction were used to measure their engagement. The findings show that active learning through Padlet has a significant effect on improving students’ engagement in classroom activities.

Distributional Forests for Short-Term Density Predictions of U.S. Inflation

Recent work by Medeiros et al. (2019, Journal of Business & Economic Statistics) shows that point forecasts of the random forest machine learning algorithm systematically outperform well-established benchmarks at predicting U.S. inflation. This article extends their work from point to density forecasts derived from large-scale datasets by means of the novel distributional forest algorithm of Schlosser et al. (2019, The Annals of Applied Statistics), which allows us to simultaneously account for locally evolving means, time-varying volatilities, nonlinearities as well as heavy-tailed densities – all of which constitute stylized characteristics highlighted in the recent literature. We show that distributional forests typically achieve superior point and density predictions over random walk, auto-regressive and stochastic volatility benchmarks.

Role of Sports in Peace-Building: Insights from NCAA Community

Role of Sports in Peace-Building: Insights from NCAA Community

Teaching Business Statistics: Some Useful Relationships

The purpose of this paper is to suggest an instructional approach in the introductory business statistics course that utilizes relationships between separately introduced topics. The paper will explore three “useful relationships” that can assist classroom instruction: (1) the relationship between the simple arithmetic mean, the weighted arithmetic mean, and the expected value of a discrete probability distribution; (2) the relationship between the use of the multiplication rule to calculate the joint probability associated with two events, use of tree diagrams, and the use of the binomial and hypergeometric distributions; and (3) the relationship between the geometric mean and the compound interest rate. Each discussion includes detailed examples of calculations to demonstrate the relationships.

Exploring the Roles of Social Presence and Gender Difference in Online Learning

ABSTRACTOnline learning has become more popular in higher education with its advantages of flexibility and accessibility. However, there have been challenges to students’ learning experience in online learning. One critical challenge would be providing interactions between students and instructors as good or effective as in the face‐to‐face environment. However, providing face‐to‐face interactions in online learning is not feasible because students and instructors are not physically present together. In this study, we introduce and empirically investigate social presence as student learning experience in online learning in which physical presence does not exist. Drawing upon the social presence and online learning literature, we propose a research model to explore how the interactivity of communication tools can drive social presence and student satisfaction in online learning. Furthermore, this study examines gender difference as a moderator in the model. Data were collected from undergraduate students who were taking online business statistics courses where an interactive communication tool was required to use for class communication and collaboration. The results showed that social presence driven by tool interactivity had a significant impact on student satisfaction in online learning. We also found that gender difference moderated the relationship between tool interactivity and social presence in online learning.

Estimation of the average wage in Polish small companies using the robust approach

There is a growing demand for multivariate economic statistics for crossclassified domains. In business statistics, this demand poses a particular challenge given the specific character of the population of enterprises, which necessitates searching for methods of analysis that would represent the robust approach to estimation, where auxiliary variables could be utilised. The adoption of new solutions in this area is expected to increase the scope of statistical output and improve the precision of estimates. The study presented in the paper furthers this goal, as it is focused on testing the application of a robust version of the Fay-Herriot model, which makes it possible to meet the assumption of normality of random effects under the presence of outliers. These alternative models are supplied to estimate the parameters of small firms operating in 2012. Variables from administrative registers were used as auxiliary variables, which made the estimation process more comprehensive. The paper refers to small area estimation methods. The variables of interest are estimated at a low level of aggregation represented by the crosssection province and NACE sections.

Measuring Player Retention and Monetization Using the Mean Cumulative Function

Game analytics supports game development by providing direct quantitative feedback about player experience. Player retention and monetization have become central business statistics in free-to-play game development. Total playtime and lifetime value in particular are central benchmarks, but many metrics have been used for this purpose. However, game developers often want to perform analytics in a timely manner before all users have churned from the game. This causes data censoring, which makes many metrics biased. In this article, we introduce how the mean cumulative function (MCF) can be used to measure metrics from censored data. Statistical tools based on the MCF allow game developers to determine whether a given change improves a game or whether a game is good enough for public release. The MCF is a general tool that estimates the expected value of a metric for any data set and does not rely on a model for the data. We demonstrate the advantages of this approach on a real in-development free-to-play mobile game Hipster Sheep.

Global Supply Chains: European Union, Euro Area and New Member States

Supply chains are comprised of events that link the product or service from conception, different phases of production, to final delivery to the consumers. In this regard, global supply chains (GSC) economics is concerned with the effects on the host economy due to presence of GSC as well as the importance of GSC for exports, or more specifically, the value added from exports. Thus, in this study, the concept of value-added trade was used in relation to exports, employment and foreign direct investment (FDI) in terms of trade facilitation for the host economies. The analysis presented in this article is based on the main dataset for structural business statistics (SBS) presented by Eurostat, where, first, we calculate the extent of overall changes in exports, employment and FDI stock relative to manufacturing, and second, to capture the effect of export restructuring on manufacturing productivity growth, we use the standard growth accounting approach, a production function at the industry level to total factor productivity (TFP) growth. The results show that TFP is reliant on exports for the whole European Union economy and especially for the new member states.

A strategic and data production frameworks for the development of business statistics

This paper highlights the key characteristics and implications of the strategic and data production frameworks designed and progressively implemented by the United Nations Committee of Experts on Business and Trade Statistics (UNCEBTS) to enhance the relevance, accuracy and coverage of business statistics, according to an internationally comparable, result-oriented and sustainable approach. The strategic framework aims to expand the traditional scope of official business statistics by including all relevant environmental and social related issues. NSOs may achieve relevant improvements by focusing their efforts upon specific global goals consistent with their national ones, and sourcing from knowledge sharing with other countries and international coordination. It also highlights the relevance of an enterprise-centered approach for a better understanding of emerging phenomena by official statisticians, and for priority setting in improving the quality of business statistics. The data production framework is dominated by the crucial role of the Statistical Business Register (SBR) as the backbone of any current and future improvements in the relevance and accuracy of business statistics. Its implications, both in terms of sustainability of production lines, data integration and production of new indicators that exploit the variability dimension of business statistics are further investigated in the paper.

New measures on contribution of corporations towards sustainability

With the UN General Assembly’s adoption in September 2015 of the Sustainable Development Goals (SDGs) to be reached in 2030 a new, overarching and prominent policy framework was born. Following the adoption, the Danish government made Statistics Denmark (SD) the responsible authority for national SDG reporting. The strategy to fulfill this task has been to work closely with stakeholders in the business community, public authorities and NGO’s. SD has further worked to implement the SDG-framework on the business sector, in particular inspired by work done in UNCTAD about indicators for business entity reporting on economic, environmental, social and institutional issues. The work in SD has shown that it is possible to provide SDG-relevant information by type of industry using existing statistical data. Emission of CO2 and energy efficiency are examples from the environmental economic accounts. Social and business statistics can provide data on employment and wages broken down by gender, and also follow the development in occupational injuries, just to mention a few examples. However, existing data cannot provide information on how enterprises work with the SDGs. To cover this aspect, a survey among the largest private Danish enterprises was conducted in 2019. A third type of data source may be created by adding additional questions to existing surveys. The article is concluded by a discussion on the lessons learned so far and possible next steps are outlined.

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

The effect of cognitive and behavioral factors on student success in a bottleneck business statistics course via deeper analytics

In this article, we study a set of factors underlying student success in a bottleneck business course using statistical and data mining techniques. Factors included learning styles, motivational and other cognitive factors, personality traits, learning analytics, along with background demographic and academic ones. Our analysis yielded interesting insights that show some of these factors play significant roles in predicting both student performance and their propensity to utilize resources that help improve their performance, such as additional support services. The predictive accuracy of both of our models were over 95% (error rate <5%). Moreover, quantile regression models were used to determine factors that specifically affect the performance of low-performing students so that targeted intervention and support services can be developed specifically for them. In conclusion, deeper analytics via statistical models are crucial for forming an in-depth understanding of how to improve student performance in a bottleneck course and this has far-reaching implications for both educators and administrators in higher education.

Brand activism and millennials: an empirical investigation into the perception of millennials towards brand activism

The reckless pursuit of social, environmental, political and cultural issues and brands may alienate the very customer base, whom they try to impress, especially the millennials. Hence, this study intends to study the perceptions of millennials towards brand activism, so that the findings from the study can help the brand managers to steer their brands into the troubled waters of brand activism. The methodology followed is HTAB (Hypothesize, Test, Action, Business), a popular analysis framework given by Ken Black in his book titled “Business Statistics: Contemporary Decision Making (6th ed.)” A sample comprising of 286 respondents was collected. The final data had 286 observations and 45 features across seven categories. It was found that millennials prefer to buy a brand if it supports a cause or purpose and they stop buying if brand behaves unethically. It was also observed that there is no gender difference amongst the millennials towards their perceptions concerning brand activism. Moreover, millennials across different income categories have similar perceptions of brand activism. It was also substantiated that the emotional tie of the millennials with the brand existing for a cause goes beyond price shifts and brands taking a political stance, cherry-picking of issues and being disruptive prompts and creates profound backlash for the brands.

One Size Doesn’t Fit All: Administrative Data Quality Frameworks for Production of Official Statistics

Background with rationaleThe use of administrative data is key to achieving the UK Statistics Authority’s strategy of Better Statistics, Better Decisions. Integrating administrative data into official statistics can benefit policy decisions by allowing the possibility of greater granularity and improved timeliness in outputs, while delivering efficiency gains and reducing respondent burden. Quality assessment and communicating uncertainty of administrative data sources is critical to their effective integration into official statistical outputs.&#x0D; Main AimThis presentation will discuss the main challenges of quality assuring statistical outputs containing administrative data. The differences in existing quality frameworks and identified quality metrics will be discussed. In addition, the presentation will cover the need to tailor quality assessment to answer a specific research question that an identified source is being used for and the considerations required.&#x0D; Methods/ApproachA comprehensive literature review was carried out, bringing together existing quality frameworks and metrics from National Statistical Institutes (NSIs) and academia for production of statistics using administrative data sources.&#x0D; ResultsThe main challenges and considerations faced when quality assuring outputs produced using administrative sources have been identified. The quality requirements for different outputs across social, business and census statistics were summarised and a general quality framework for admin data developed. This framework draws on international best practices for use in the UK statistical system.&#x0D; ConclusionIntegrating administrative data presents challenges can’t be solved by a one-size fits all framework. Through unifying available guidance, an adaptable quality assurance methodology has been created, enabling the use of public data for the public good.

Research on Readers’ Behavior of College Libraries Based on Data Mining Technology

College libraries produce a large amount of book circulation data every day. In addition to recording readers’ personal information, these data are generally used for routine business statistics. Their potential use value is far from being fully tapped and utilized. A careful study of readers’ long-term borrowing history data reveals that there is a certain correlation between readers’ borrowing behavior and books, between different disciplines and between different types of readers and borrowing books. Digging out the correlation between these data is conducive to the rational allocation of resources and improving the utilization of resources. It can also improve the library’s service level. Based on the author’s learning and practical experience, this paper first analyzed the necessity of applying data mining technology to library and then discussed the basic techniques of data mining. The article proposed the basic steps of applying data mining to digital library systems and finally studied The application of data mining technology in the analysis of library readers’ borrowing behavior.

Modeling the Birth Rate of Single-Industry Towns on the Basis of Indicators of Business Demography

Without knowledge of business demography, it is impossible to obtain accurate quantitative characteristics of the market situation and conduct their research and forecasting. Without an understanding of the statistical structure of business statistics and statistical studies of the quantitative characteristics of entrepreneurship, any business can suffer serious damage. Only the use of methods of processing statistical indicators, the available data on the business environment can help managers, economists, managers and other consumers of information to form and improve their theories and better understand the processes of business development in the context of the creation of new enterprises, to assess its prospects.

EXPLORING THE EFFECT OF COLORING MANDALAS ON STUDENTS’ MATH ANXIETY IN BUSINESS STATISTICS COURSES

Purpose – the purpose of this article is to review a quasi-experiment study examining whether business students’ math anxiety is reduced after participating in mandala coloring activities. Research methodology – the research methodology integrated quantitative methods including independent t-tests and ANOVAs in a non-random convenient sample of 106 undergraduate students in 2018 in Texas, United States. Findings – results from the one-way ANOVA and t-test analyses revealed that anxiety levels differed across groups, such that after coloring a pre-drawn mandala, math anxiety was significantly reduced in comparison to the control (doodling) group. Paired sample t tests also demonstrated that when comparing the anxiety levels at the baseline and post-treatment, math anxiety was reduced after performing both the pre-drawn and free-coloring mandala activities. Additionally, an independent sample t-test and a two-by-two factorial ANOVA demonstrated that males experienced a significant reduction in their math anxiety than the females did after performing the mandala coloring activity. Research limitations – the study used a convenient sample, self-reported items, and a math anxiety measurement. Also, the findings found short-term evidence of math anxiety. Practical implications – the findings of this study suggest that business statistics instructors who integrate a mandala coloring activity in anxiety-provoking undertakings may help to reduce their students’ math anxiety. Originality/Value – This study is the first to investigate mandala coloring to reduce math anxiety in business students. Unlike previous studies that focus on anxiety in general, this study examines the benefit of mandala coloring on students’ math anxiety.

Supporting Student Learning through Instructional Videos in Business Statistics

ABSTRACTWhile statistics is an essential topic for business students, many students experience barriers to successful learning due to anxiety, motivation, or difficulty with quantitative understanding. This research examines the use of online videos with an effort to explore the relationship between student characteristics, video usage, and course performance measures. In addition, the study examines student perceptions of the supplemental resources in an effort to examine the efficacy related to student learning and performance. This study seeks to confirm previous research regarding the benefit of supplemental video resources and extend the knowledge base by understanding the impact for various types of students (e.g., level of course, level of previous academic performance, etc.). The study found that the use of the video resources varies based on students’ previous math performance and the difficulty of the material. Student ratings indicate that the videos were helpful in learning the content and that they provided an important resource when students needed additional tools to master the material. Analysis of the results provides implications for understanding how different students use online videos and offers recommendations for educators and researchers about how to enhance student success in difficult statistics coursework.