• Title/Summary/Keyword: Distribution data

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Factors of Successful Online Marketing Strategy to Food Distribution SMEs

  • PANAWAN, Chusripat;PEERAWAT, Chailom
    • Journal of Distribution Science
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    • v.20 no.12
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    • pp.71-79
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    • 2022
  • Purpose: This study aimed to apply factors of successful online marketing strategy for food distribution SMEs and the effects of these successful strategies to achieve higher performances. Research design, data, and methodology: Questionnaires were used to collect data from 400 samples of SMEs in Thailand. We employed structural Equation Modeling techniques for data analysis. Results: The results revealed that distribution strategies directly affected the success of business operations, as follows: 1) Customer communication channels, product variety, preserved privacy, and personal service had direct positive effects on the distribution success in terms of financial perspective, customer perspective, internal process perspective, and earning and growth perspectives; 2) Ability to learn a competitor had a positive direct relationship with the distribution success in terms of financial perspective and learning and growth perspectives, excluding customer perspective and internal process perspective; and 3) Responses to market on time had a positive and direct influence on distribution success in terms of customer, internal process perspective and learning and growth perspectives excluding financial perspective. Conclusions: This research has made an essential contribution to SMEs that they should focus on and adopt these 6ODS+4BSC concepts as development guidelines for food distribution SMEs to be more efficient and effective.

EVALUATION OF AN ENHANCED WEATHER GENERATION TOOL FOR SAN ANTONIO CLIMATE STATION IN TEXAS

  • Lee, Ju-Young
    • Water Engineering Research
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    • v.5 no.1
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    • pp.47-54
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    • 2004
  • Several computer programs have been developed to make stochastically generated weather data from observed daily data. But they require fully dataset to run WGEN. Mostly, meterological data frequently have sporadic missing data as well as totally missing data. The modified WGEN has data filling algorithm for incomplete meterological datasets. Any other WGEN models have not the function of data filling. Modified WGEN with data filling algorithm is processing from the equation of Matalas for first order autoregressive process on a multi dimensional state with known cross and auto correlations among state variables. The parameters of the equation of Matalas are derived from existing dataset and derived parameters are adopted to fill data. In case of WGEN (Richardson and Wright, 1984), it is one of most widely used weather generators. But it has to be modified and added. It uses an exponential distribution to generate precipitation amounts. An exponential distribution is easier to describe the distribution of precipitation amounts. But precipitation data with using exponential distribution has not been expressed well. In this paper, generated precipitation data from WGEN and Modified WGEN were compared with corresponding measured data as statistic parameters. The modified WGEN adopted a formula of CLIGEN for WEPP (Water Erosion Prediction Project) in USDA in 1985. In this paper, the result of other parameters except precipitation is not introduced. It will be introduced through study of verification and review soon

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Investigations into Coarsening Continuous Variables

  • Jeong, Dong-Myeong;Kim, Jay-J.
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.325-333
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    • 2010
  • Protection against disclosure of survey respondents' identifiable and/or sensitive information is a prerequisite for statistical agencies that release microdata files from their sample surveys. Coarsening is one of popular methods for protecting the confidentiality of the data. Grouped data can be released in the form of microdata or tabular data. Instead of releasing the data in a tabular form only, having microdata available to the public with interval codes with their representative values greatly enhances the utility of the data. It allows the researchers to compute covariance between the variables and build statistical models or to run a variety of statistical tests on the data. It may be conjectured that the variance of the interval data is lower that of the ungrouped data in the sense that the coarsened data do not have the within interval variance. This conjecture will be investigated using the uniform and triangular distributions. Traditionally, midpoint is used to represent all the values in an interval. This approach implicitly assumes that the data is uniformly distributed within each interval. However, this assumption may not hold, especially in the last interval of the economic data. In this paper, we will use three distributional assumptions - uniform, Pareto and lognormal distribution - in the last interval and use either midpoint or median for other intervals for wage and food costs of the Statistics Korea's 2006 Household Income and Expenditure Survey(HIES) data and compare these approaches in terms of the first two moments.

Operational Risk Measurement of Financial Institutions via AHP (AHP 분석을 이용한 금융기관 운영리스크 측정)

  • Choi, Seung-Il
    • Korean Management Science Review
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    • v.28 no.3
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    • pp.73-82
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    • 2011
  • Basel II advanced measurement approaches for operational risk need to estimate the frequency and severity distribution of operational losses. Due to lack of internal loss data, the estimation is impossible in many cases and so external loss data might be used by scaling on asset or gross income. To get around lack of loss data, scenario analysis combined with loss distribution approach can be useful in calculating the capital charge of operational risk. However, scenario based loss distribution approach requires much time and effort. Instead we may apply the analytic hierarchy process to measure operational risk of financial institutions. The analytic hierarchy process combined with loss distribution approach is to estimate the capital charge of operational risk in other areas based on the operational VaR in an area with sufficient loss data. AHP provides a tool for timely measurement of operational risk in this rapidly changing global environment.

Development of Wireless Monitoring System for Distribution Transformer (배전용 변압기의 무선 부하감시 시스템 개발)

  • Jung, Joon-Hong;Kang, Tae-Goo;Kim, Il-Kyung
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.414-415
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    • 2008
  • In this paper, we consider the development methodology of wireless monitoring system for a distribution transformer. The master/ slave devices are installed in the power distribution feeder and measure the current state of pole or ground transformers. After measuring, the devices send the measurement data to operating room through the wireless network such as RF and CDMA so that the power distribution supervisor can prevent a distribution transformer damaging caused by overloads and imbalance of loads.

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Study of Chinese Distribution Market Trends

  • Su, Shuai
    • Journal of Distribution Science
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    • v.11 no.9
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    • pp.31-34
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    • 2013
  • Purpose - This paper aims to explain that the Chinese distribution market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand. Research design, data, methodology - A survey was conducted on China's retail market data during 2012. By empirically analyzing the data for retail sales of online markets and franchises, we conclude that the online retail market in China will continue to grow. Results - Based on data from 2012, 2013 is expected to be a challenging year for the retail sector, as both external and internal pressure is likely to persist. This paper outlines some major challenges facing retailers in China. Conclusions - The study shows that retailers in the Chinese market will face some major challenges: 1) the Chinese retail market is considerably affected by an uncertain economic outlook 2) an unfair environment of competition exists and 3) product safety is a serious issue. However, in the future, China's retail market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand.

Families of Distributions Arising from Distributions of Ordered Data

  • Ahmadi, Mosayeb;Razmkhah, M.;Mohtashami Borzadaran, G.R.
    • Communications for Statistical Applications and Methods
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    • v.22 no.2
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    • pp.105-120
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    • 2015
  • A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.

New approach for analysis of progressive Type-II censored data from the Pareto distribution

  • Seo, Jung-In;Kang, Suk-Bok;Kim, Ho-Yong
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.569-575
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    • 2018
  • Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

CIM based Distribution Automation Simulator (CIM 기반의 배전자동화 시뮬레이터)

  • Park, Ji-Seung;Lim, Seong-Il
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.3
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    • pp.87-94
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    • 2013
  • The main purpose of the distribution automation system (DAS) is to achieve efficient operation of primary distribution systems by monitoring and control of the feeder remote terminal unit(FRTU) deployed on the distribution feeders. DAS simulators are introduced to verify the functions of the application software installed in the central control unit(CCU) of the DAS. Because each DAS is developed on the basis of its own specific data model, the power system data cannot be easily transferred from the DAS to the simulator or vice versa. This paper presents a common information model(CIM)-based DAS simulator to achieve interoperability between the simulator and the DASs developed by different vendors. The CIM-based data model conversion between Smart DMS (SDMS) and Total DAS (TDAS) has been performed to establish feasibility of the proposed scheme.

GENERALIZED LINDLEY DISTRIBUTION USING PROPORTIONAL HAZARD FAMILY AND INFERENCE OF FAILURE TIME DATA

  • Ahmed AL-Adilee;Hawraa A. AL-Challabi;Hassanein Falah;Dalael Saad Abdul-Zahra
    • Nonlinear Functional Analysis and Applications
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    • v.28 no.3
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    • pp.793-800
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    • 2023
  • In this paper, we propose a generalization of Lindley distribution (GLD) via a special structure that is concern with progressively Type-II right censoring and time failure data. We study the modern properties that we have built by such combination, for example, survival function, hazard function, moments, and estimation by non-Bayesian methods. Application on some selected data related to Lindley distribution (LD) and (ED) have been employed to find out the best distribution that can fit data comparing with the GLD.