• Title/Summary/Keyword: TOBIT Model

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The Impact of Chinese SMEs' Financial Structure on Innovation Efficiency (중국 중소기업 재무구조가 혁신 효율성에 미치는 영향)

  • Wang, Yiqi;Sim, Jae-Yeon
    • Industry Promotion Research
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    • v.7 no.4
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    • pp.97-108
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    • 2022
  • This paper examined the impact of financing structure on the innovation efficiency of SMEs by constructing an econometric model using panel data of SMEs listed on the SME board from 2010 to 2020 as the research sample. The innovation efficiency of SMEs was measured by the Stochastic Frontier Analysis (SFA), the relationship between financing structure and innovation efficiency of SMEs was examined with the help of the Tobit model, and the corresponding heterogeneity analysis was conducted. Finally, the robustness of the model was tested. It was concluded that the effects of debt and equity financing on the quantitative efficiency of innovation were non-linear and mainly showed an inverted "U" shaped relationship. For innovation quality efficiency, bond financing could positively contribute, while equity financing negatively inhibits. Finally, the corresponding advice was given.

Study of Virtual Goods Purchase Model Applying Dynamic Social Network Structure Variables (동적 소셜네트워크 구조 변수를 적용한 가상 재화 구매 모형 연구)

  • Lee, Hee-Tae;Bae, Jungho
    • Journal of Distribution Science
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    • v.17 no.3
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    • pp.85-95
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    • 2019
  • Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

A Model Specification for the Household Demand for Credit (가계의 신용 수요 모형 설정에 관한 연구)

  • 최현자
    • Korean Journal of Rural Living Science
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    • v.6 no.2
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    • pp.173-183
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    • 1995
  • On the basis of intertemporal utility maximization theory and stock-adjustment hypothesis, a multivariate stock-adjustment credit demand model, which included on- and cross-adjustment effects of credit and cross-adjustment effects of assets was developed. With weighted four-year panel data from 1983 and 1986 Surveys of Consumer Finances, the theoretical model was tested using two-stage estimation method for tobit model. The results supported the hypothesis that, in general, the household demand for a certain type of credit was related to the demand for other types of credit and asset components in the portfolio. The household demand for mortgage credit, installment credit and revolving credit card debt depended not only on the disequilibrium of itself but on the disequilibrium of the other types of credit and asset components in the portfolio. The household demand for non-installment credit was related not to the disequilibrium of itself and other types of credit but to the disequilibria of asset components in the portfolio.

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An Analysis of the Efficiency and Determinants of Coffee Franchises that Use DEA (DEA를 이용한 커피 프랜차이즈의 효율성 및 결정요인 분석)

  • Kim, Bo-Ram
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.159-168
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    • 2020
  • This study aims to utilize DEA, analyze the efficiency of Korean coffee franchises, look into the factors that affect efficiency, and improve the efficiency of Korean coffee franchises. The main results of this study are as follows. First, according to CCR model standards, there are a total of 9 efficient coffee franchises and according to BCC model standards, there are a total of 12 efficient coffee franchises. A total of three of the inefficient DMUs were found to have a value of 1 for BCC, while the other 25 were found to be inefficient for both technology and scale. Second, of 28 franchises, 11 were analyzed to be decreasing return to scale and through future increased investments of optimum levels, business performance can be improved and efficiency can be enhanced. Analysis showed that 9 franchises appeared as CRS and it is most ideal to maintain the yield of future output elements at current levels and the work efficiency of 8 franchises in increasing returns to scale states expands as production scales increase according to specialization and role division and yield can relatively improve a lot. Third, the analysis of factors affecting the efficiency of franchises through the Tobit regression analysis showed that the number of franchises and operating periods had a positive (+) effect on efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency.

Determinants of Export Manufacturing Firm Efficiency: Focusing on R&D Intensity in a KOSDAQ-listed Firm (수출제조기업의 효율성 결정요인에 관한 분석: 코스닥 기업의 연구개발집약도를 중심으로)

  • Hwang, Kyung-Yun;Koo, Jong-Soon
    • International Area Studies Review
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    • v.20 no.2
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    • pp.63-83
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    • 2016
  • This paper examines the determinants of efficiency in a KOSDAQ-listed manufacturing firm. We use Data Envelopment Analysis (DEA) to estimate the efficiency of the export manufacturing firm. We employ two inputs (number of employees, equity) and one output (sales) in the DEA. The determinants of export manufacturing firm efficiency are estimated using the panel Tobit model. An analysis of 369 export manufacturing firms from 2013 to 2015 indicates the following results: First, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores. However, export intensity had a negative impact on CCR efficiency scores in a KOSDAQ-listed total export manufacturing firm. Second, the R&D intensity had a positive impact on both the CCR and BCC efficiency scores, but export intensity, the wage and salary intensity, and equity ratio each had a negative impact on the CCR and BCC efficiency scores in a KOSDAQ-listed large export manufacturing firm. Third, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores; respectively, in a KOSDAQ-listed small and medium export manufacturing firm.

Analysing Weekend Travel Characteristics in Seoul (서울시 주말 통행특성 분석 연구)

  • Choo, Sang-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.3
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    • pp.92-101
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    • 2012
  • Trip demands and patterns on weekends have been changed significantly over the past decade due to the income growth and the spread of the 5-day workweek in Korea. The increased weekend trips for shopping, leisure activities, entertainment and friendship have exacerbated traffic congestion in major highways or principal arterial roads from Friday afternoon through Sunday. Therefore, it is necessary to focus on travel demand forecasts and transport policies for weekend trips by investigating specific characteristics of the trips. Previous research efforts focus on simple analysis of characteristics of weekend trips and comparison of travel characteristics between weekdays and weekends. The paper analyzes the differences between weekday and weekend trips via statistical analyses to derive multiple types of characteristics of weekend trips, and develops Tobit models to identify key factors that may affect the number of trips, using Seoul city's weekend trip survey data in 2006. The model results show that weekend trips appear differently from weekdays by household or individual characteristics. Age, residence area and type of residence affected the number of trips, regardless of the type of the day, whereas gender, occupation, income, presence of household vehicle showed different impacts on trips between weekdays and weekends.

Productivity Evaluation and Factor Analysis in Commercial Road Freight Transport Industry (영업용 도로화물운송업의 생산 효율성 평가 및 영향요인 분석)

  • Han, Sang-Yong
    • Journal of Korean Society of Transportation
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    • v.28 no.5
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    • pp.31-41
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    • 2010
  • The objective of this paper is to evaluate production efficiency of the commercial road freight transportation industry using quarterly actual data by individual truck drivers from January 2005 to September 2009. In addition, this study analyzes various impact factors that influence production efficiency, including regulatory factors (e.g., entrust management system and multi-level transactions). For this purpose, this study uses data envelopment analysis and a truncated Tobit model. As a result, production efficiency of the general freight sector is higher than those of the other two sectors. Also, production efficiency in the steel goods sector ranks the highest; meanwhile, production efficiency in the oil goods sector ranks the lowest. In particular, production efficiency indicators of the commercial road freight transportation industry fluctuate with time by a small margin, and have an upward tendency on the whole. Finally, some policy implications are given to promote production efficiency of the commercial road freight transportation industry.

Evaluation of Efficiency in the Seoul's Arterial Bus Routes Considering Undesirable Outputs (유해산출물을 고려한 서울시 간선버스노선의 효율성 평가)

  • Han, Jin-Seok;Kim, Hye-Ran;Go, Seung-Yeong
    • Journal of Korean Society of Transportation
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    • v.28 no.5
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    • pp.43-54
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    • 2010
  • In order to improve the existing evaluation system of bus services and gain more reasonable analysis outputs, the authors evaluate the efficiency of 113 arterial bus routes in Seoul in 2009 using a modified BCC model considering not only desirable outputs but also undesirable outputs. Each Decision Making Unit (DMU) is assumed to use inputs such as possession costs, operating costs, the ratios of median bus stops overlapped route lengths to produce estimates of desirable outputs (the number of passengers and service satisfaction score) and undesirable outputs (CO2 emissions). According to the analysis, the modified BCC model considering both desirable outputs and undesirable outputs shows more appropriate results. DMUs would be more efficient on average to reduce nearly 10% of the 3 inputs (possession costs, operating costs, and overlapped route lengths) and increase by about 160% the ratios of median bus stops. Also, a Tobit regression analysis is conducted to identify the most effective variables for maximum efficiency and discover that the variable of possession costs and the ratios of median bus stops are statistically significant.

A Study on Relationship between Media Environment and Adolescent Cyber-Delinquency : Focused on X-rated Media Commitment (매체환경과 청소년 사이버비행과의 관계에 대한 연구 : 성인매체몰입을 중심으로)

  • Lee, Chang-Moon;Moon, Jin-Young;Park, Ju-Won
    • Journal of Digital Convergence
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    • v.17 no.4
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    • pp.365-379
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    • 2019
  • The purpose of this study is to investigate what factors affect cyber-delinquency after examining the previous research focusing on the general strain theory and the delinquency opportunity theory in the existing studies. And as adolescents move from middle school to high school, this study is intended to analyze what factors affect cyber-delinquency from a longitudinal perspective using KCYPS(Korea Child and Youth Panel Survey) elementary 4th grade fourth and seventh data. The adolescence cyber-delinquency probability of occurrence were analyzed through the panel logit fixed-effect model using STATA. And then the cyber-delinquency frequency of adolescents were analyzed through the panel tobit random-effect model. As a result of analyzing the factors affecting cyber-delinquency frequency, Adult media commitment, computer use time, and cell phone dependency increased cyber-delinquency frequency. On the other hand, among the parenting attitudes, the attitude of supervising attentively and adolescents' age-increasing decreased cyber-delinquency frequency.

Analysis of U.S. Port Efficiency Using Double-Bootstrapped DEA (이중 부트스트랩 DEA 활용한 미국항만 효율성 분석)

  • Lee, Yong Joo;Park, Hong-Gyun;Lee, Kwang-Bae
    • Journal of Korea Port Economic Association
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    • v.37 no.3
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    • pp.75-91
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    • 2021
  • Due to increased competition in supply side to reduce operational costs, port professionals have experienced extreme pressure, which demanded academicians to develop the model for efficient port operations from the industry perspective. Among many ports in the world, U.S. ports are our primary interest to analyze in our study for its high volume of cargoes transacted in the U.S. ports. We primarily employed DEA (Data Envelopment Analysis) technique to research the productivity of U.S. ports and applied the algorithm of double bootstrapped DEA proposed by Simar & Wilson (2007) to further investigate the driving forces of the performance of U.S. port operations. The external variables employed in our study comprise onDock Rail, Channel Depth, Location, Area, Acres, ForeignCargoRatio, and TEUChange, out of which onDock Rail, Acres, ForeignCargoRatio, and TEUChange were significant. In order to evaluate the effects of methodology selection, we conducted the same analysis applying the Censored model (Tobit) and contrasted the outcomes drawn from the two different techniques. Based on the findings from this work we proposed managerial implications and concluded.