scholarly journals Broadcaster Choice and Audience Demand for Live Sport Games: Panel Analyses of the Korea Baseball Organization

2021 ◽  
pp. 1-12
Author(s):  
Kihan Kim ◽  
Hojun Sung ◽  
Yeayoung Noh ◽  
Kimoon Lee
Keyword(s):  
Panel Data ◽  
Team Performance ◽  
Field Performance ◽  
Data Set ◽  
Performance Quality ◽  
Korea Baseball Organization ◽  
Uncertain Outcomes ◽  
Practical Implications ◽  
Television Ratings

This study investigated the determinants of television viewership and its relation to broadcasters’ choices of matches for live telecasts. Also, factors driving the broadcasters’ choices were examined. A panel data set from the 2018 Korea Baseball Organization league pennant race was analyzed. Broadcasters’ choice order of matches and the actual television ratings of each match were regressed on a series of antecedent factors related to the game characteristics and audience preferences. It was found that the broadcasters’ choice order of matches positively affected the television ratings, suggesting that the broadcasters’ decisions were well reflected in the actual viewership. It also appeared that broadcasters’ choices were based on popularity and team performance/quality, whereas viewers showed preference for current games’ on-field performance. There was no evidence of audience preference for games with higher outcome uncertainty, whereas the broadcasters tended to choose games with more certain, rather than uncertain, outcomes. Theoretical and practical implications of the findings were discussed.

Exploring the dynamic influences and interaction effects of signals on backers’ investment in the crowdfunding market

2019 ◽  
Vol 33 (2) ◽  
pp. 792-812 ◽  
Author(s):  
Yang Song ◽  
Hong Wu ◽  
Jingdong Ma ◽  
Naiji Lu
Keyword(s):  
Panel Data ◽  
Negative Binomial ◽  
Early Stage ◽  
Substitution Effect ◽  
Interaction Effects ◽  
Data Set ◽  
Content Type ◽  
Funding Cycle ◽  
Practical Implications ◽  
Shed Light

Purpose As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle. Design/methodology/approach A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results. Findings The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic. Originality/value This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

Age and tenure diversity on the work floor

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kirsten Thommes ◽  
Janny Klabuhn
Keyword(s):  
Team Performance ◽  
Design Methodology ◽  
Past Research ◽  
Data Set ◽  
Content Type ◽  
Beneficial Effects ◽  
Age Diversity ◽  
Enhance Efficiency ◽  
Practical Implications ◽  
Age Disparity

Purpose Past research on how to compose a team is ambiguous, especially with respect to diversity dimensions. The authors argue that previous inconsistencies in results have arisen for two main reasons. First, there is a lack of clarity about the concept of age diversity, as age separation, age variety and age disparity are frequently used synonymously, but capture very different aspects of diversity. Second, in many research settings, age and tenure diversity have been intertwined. When staffing teams, many staff managers ask for staffing advise concerning staff diversity in order to enhance efficiency. This staffing problem is mainly a question how homogeneous and heterogeneous teams should be composed. In this paper, the authors capture both – age and tenure diversity – as well as their interaction and argue that age separation and tenure variety are most likely to affect team performance in a routine task. The paper aims to discuss these issues. Design/methodology/approach The authors are testing the hypothesis using rich quantitative field data from a steel company. Findings The results show that age separation decreases performance while tenure variety increases performance. Moreover, the beneficial effects of tenure variety cannot arise when age separation is too large. Research limitations/implications The authors show that diversity research is very sensitive to the operationalization of diversity. Practical implications Managers can benefit from the study by learning how to optimally staff teams: while age diversity should be low, tenure diversity can be high. Originality/value Due to the unique data set, the authors can separate the influence of tenure and age diversity.

A General Approach to Panel Data Set-Theoretic Research

2016 ◽  
Vol 1 (1) ◽  
pp. 11-41
Author(s):  
Roberto Garcia-Castro ◽  
◽  
Miguel A. Ariño ◽  
Keyword(s):  
Panel Data ◽  
Data Set

scholarly journals Determinants of prepaid systems of healthcare financing: a worldwide country-level perspective

2021 ◽  
Author(s):  
Andrea M. Leiter ◽  
Engelbert Theurl
Keyword(s):  
Health Care ◽  
Panel Data ◽  
Health Care Financing ◽  
Value Added ◽  
The Elderly ◽  
Dynamic Panel Data ◽  
Individual Characteristics ◽  
Minor Importance ◽  
Data Set ◽  
Country Level

AbstractIn this paper we examine determinants of prepaid modes of health care financing in a worldwide cross-country perspective. We use three different indicators to capture the role of prepaid modes in health care financing: (i) the share of total prepaid financing as percent of total current health expenditures, (ii) the share of voluntary prepaid financing as percent of total prepaid financing, and (iii) the share of compulsory health insurance as percent of total compulsory prepaid financing. In the econometric analysis, we refer to a panel data set comprising 154 countries and covering the time period 2000–2015. We apply a static as well as a dynamic panel data model. We find that the current structure of prepaid financing is significantly determined by its different forms in the past. The significant influence of GDP per capita, governmental revenues, the agricultural value added, development assistance for health, degree of urbanization and regulatory quality varies depending on the financing structure we look at. The share of the elderly and the education level are only of minor importance for explaining the variation in a country’s share of prepaid health care financing. The importance of the mentioned variables as determinants for prepaid health care financing also varies depending on the countries’ socio-economic development. From our analysis we conclude that more detailed information on indicators which reflect the distribution of individual characteristics (such as income, family size and structure and health risks) within a country’s population would be needed to gain deeper insight into the decisive determinants for prepaid health care financing.

Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters

2016 ◽  
Vol 16 (2) ◽  
pp. 185-202 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Ali Shamsoddini ◽  
S. Travis Waller
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Learning Method ◽  
Data Set ◽  
Content Type ◽  
Field Database ◽  
The Stability ◽  
Stable Learning ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose The purpose of this paper is to predict the concrete pouring production rate by considering both construction and supply parameters, and by using a more stable learning method. Design/methodology/approach Unlike similar approaches, this paper considers not only construction site parameters, but also supply chain parameters. Machine learner fusion-regression (MLF-R) is used to predict the production rate of concrete pouring tasks. Findings MLF-R is used on a field database including 2,600 deliveries to 507 different locations. The proposed data set and the results are compared with ANN-Gaussian, ANN-Sigmoid and Adaboost.R2 (ANN-Gaussian). The results show better performance of MLF-R obtaining the least root mean square error (RMSE) compared with other methods. Moreover, the RMSEs derived from the predictions by MLF-R in some trials had the least standard deviation, indicating the stability of this approach among similar used approaches. Practical implications The size of the database used in this study is much larger than the size of databases used in previous studies. It helps authors draw their conclusions more confidently and introduce more generalised models that can be used in the ready-mixed concrete industry. Originality/value Introducing a more stable learning method for predicting the concrete pouring production rate helps not only construction parameters, but also traffic and supply chain parameters.

scholarly journals A surrogate-based generic classifier for Chinese TV series reviews

2017 ◽  
Vol 45 (2) ◽  
pp. 66-74
Author(s):  
Yufeng Ma ◽  
Long Xia ◽  
Wenqi Shen ◽  
Mi Zhou ◽  
Weiguo Fan
Keyword(s):  
Design Methodology ◽  
Experimental Result ◽  
Digital Information ◽  
Data Set ◽  
Content Type ◽  
Category Labels ◽  
Information Supply Chain ◽  
Feature Selection Techniques ◽  
Practical Implications

Purpose The purpose of this paper is automatic classification of TV series reviews based on generic categories. Design/methodology/approach What the authors mainly applied is using surrogate instead of specific roles or actors’ name in reviews to make reviews more generic. Besides, feature selection techniques and different kinds of classifiers are incorporated. Findings With roles’ and actors’ names replaced by generic tags, the experimental result showed that it can generalize well to agnostic TV series as compared with reviews keeping the original names. Research limitations/implications The model presented in this paper must be built on top of an already existed knowledge base like Baidu Encyclopedia. Such database takes lots of work. Practical implications Like in digital information supply chain, if reviews are part of the information to be transported or exchanged, then the model presented in this paper can help automatically identify individual review according to different requirements and help the information sharing. Originality/value One originality is that the authors proposed the surrogate-based approach to make reviews more generic. Besides, they also built a review data set of hot Chinese TV series, which includes eight generic category labels for each review.

Abstiegserfahrungen in der Kommune und der Aufstieg Unabhängiger Wählergemeinschaften. Neue Befunde aus einem Mehrebenen-Kommunalwahlpanel

2021 ◽  
Vol 52 (1) ◽  
pp. 59-77
Author(s):  
Christina-Marie Juen ◽  
Markus Tepe ◽  
Michael Jankowski
Keyword(s):  
Panel Data ◽  
Voter Turnout ◽  
Party System ◽  
Local Politics ◽  
Tax Revenue ◽  
Data Set ◽  
Political Fragmentation ◽  
Electoral Success ◽  
Party Positions ◽  
Multi Level

In Germany, Independent Local Lists (UWG) have become an integral part of local politics in recent decades . Despite their growing political importance, the reasons for their electoral rise have hardly been researched . Recent studies argue that Independent Local Lists pursue anti-party positions, which makes them attractive to voters who are dissatisfied with the party system . Assuming that a decline of confidence in established parties corresponds with the experience of local deprivation, this contribution uses a multi-level panel data set to investigate how socio-economic (emigration, aging, declining tax revenue) and political­cultural (turnout, fragmentation) deprivation processes affect the electoral success of Inde­pendent Local Lists . The empirical findings suggest that Independent Local Lists are more successful in municipalities where voter turnout has fallen and political fragmentation has increased .

Detecting common breaks in the means of high dimensional cross-dependent panels

2021 ◽  
Author(s):  
Lajos Horváth ◽  
Zhenya Liu ◽  
Gregory Rice ◽  
Yuqian Zhao
Keyword(s):  
Panel Data ◽  
Common Factors ◽  
Real Data ◽  
Change Points ◽  
High Dimensional ◽  
Asymptotic Results ◽  
Cross Sectional ◽  
Data Set ◽  
Monte Carlo Simulation Study ◽  
Cross Sectional Dependence

Abstract The problem of detecting change points in the mean of high dimensional panel data with potentially strong cross–sectional dependence is considered. Under the assumption that the cross–sectional dependence is captured by an unknown number of common factors, a new CUSUM type statistic is proposed. We derive its asymptotic properties under three scenarios depending on to what extent the common factors are asymptotically dominant. With panel data consisting of N cross sectional time series of length T, the asymptotic results hold under the mild assumption that min {N, T} → ∞, with an otherwise arbitrary relationship between N and T, allowing the results to apply to most panel data examples. Bootstrap procedures are proposed to approximate the sampling distribution of the test statistics. A Monte Carlo simulation study showed that our test outperforms several other existing tests in finite samples in a number of cases, particularly when N is much larger than T. The practical application of the proposed results are demonstrated with real data applications to detecting and estimating change points in the high dimensional FRED-MD macroeconomic data set.

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