scholarly journals Cherry Picking

2021 ◽  
Author(s):  
Megan Lang ◽  
Wenfeng Qiu
Keyword(s):  
Data Collection ◽  
Field Experiments ◽  
Simulated Data ◽  
Simple Algorithm ◽  
Original Data ◽  
Primary Data ◽  
Significant Treatment ◽  
Complex Sampling ◽  
Original Dataset ◽  
Peer Reviewers

Measures like pre-analysis plans ask researchers to describe planned data collection and justify data exclusions, but they provide little enforceable oversight of primary data collection. We show that a simple algorithm can select large subsets of data that yield economically meaningful and statistically significant treatment effects. The subsets cannot be distinguished from a random sample of the original data, rendering the selection undetectable if peer reviewers are unaware of the size of the original dataset. Our results hold using simulated data and replication data from a well-known study. We show that there are few natural deterrents to dataset manipulation: the results in our selected subset are robust to a range of alternative specifications, our algorithm performs well under complex sampling strategies, and our subset can yield artificially high effects on multiple outcomes. We conclude by proposing a measure to prevent such manipulation in field experiments.

PENGARUH KUALITAS PELAYANAN TERHADAP KEPUASAN PELANGGAN PLN RAYON KEDIRI KOTA (STUDI KASUS PEMBAYARAN REKENING LISTRIK DI PLN RAYON KEDIRI KOTA)

2019 ◽  
Vol 1 (2) ◽  
pp. 96
Author(s):  
Septiyan Budi Santoso ◽  
Heribertus Budi Santoso ◽  
Ana Komari
Keyword(s):  
Quality Of Service ◽  
Data Collection ◽  
Customer Satisfaction ◽  
Primary Data ◽  
Customer Complaints ◽  
Work Area

This study aims to determine how high the level of customer satisfaction with the service of PLN Rayon Kediri Kota, to determine the quality of service to customer satisfaction PLN Rayon Kediri Kota, to determine the response of the PLN Kediri Kota in dealing with customer complaints. This research was conducted in the work area of PLN Rayon Kediri Kota. The research time was on March 18, 2017 to March 24, 2017. In writing this thesis, the author uses primary data collection techniques, namely by distributing questionnaires to PLN Rayon Kediri Kota customers who come to the payment counter. and PLN District Kediri City services. Based on the results of the research, the quality of service conducted by PLN District Kediri Kota is sufficient to satisfy its customers, as evidenced by the results of a questionnaire that has been conducted on 100 respondents of PLN Rayon Kediri City.Penelitian ini bertujuan untuk mengetahui seberapa tinggi tingkat kepuasan pelanggan terhadap pelayanan PLN Rayon Kediri Kota, Untuk mengetahui kualitas pelayanan terhadap kepuasan pelanggan PLN Rayon Kediri Kota, Untuk mengetahui respons pihak PLN Kediri Kota dalam menghadapi keluhan pelanggannya. Penelitian ini dilakukan di wilayah kerja PLN Rayon Kediri Kota. Waktu penelitian pada tanggal 18 Maret 2017 sampai dengan 24 Maret 2017. Dalam penulisan skripsi ini, penulis menggunakan teknik pengumpulan data primer yaitu dengan membagikan kuesioner terhadap pelanggan PLN Rayon Kediri Kota yang datang ke loket pembayaran dan pelayanan PLN Rayon Kediri Kota. Berdasarkan hasil penelitian kualitas pelayanan yang dilakukan oleh PLN Rayon Kediri Kota sudah cukup memuaskan pelanggannya terbukti dengan hasil kuesioner yang telah dilakukan terhadap 100 responden PLN Rayon Kediri Kota.

PROFITABILITY ANALYSIS OF TERUBUK FARMING (SACCHARUM EDULE HASSKARL) IN SUBDISTRICT TOSA DISTRICT OF EAST TIDORE OF TIDORE ISLAND

2018 ◽  
Author(s):  
Suwandi S. Sangadji
Keyword(s):  
Data Collection ◽  
Research Method ◽  
Quantitative Method ◽  
Secondary Data ◽  
Primary Data ◽  
Profitability Analysis ◽  
Sample Method ◽  
Document Review ◽  
Revenue Production

The purpose of this researchment is to ascertain how wide the farming of species Saccharun Edule Hasskarl (terubuk) in sub district Tosa, district of East Tidore of Tidore Island through the indicator of the value revenue, production and selling prices so that the farmers will achieve The Break Event Point (BEP). The research method was used a quantitative method with the number of samples of 30 people. The determination of the sample method is using the census method or involving all members of the population into a sample of researchment. The secondary data collection was done by using library literature in the form of document review and relevant references to research object while primary data collection was done by using questionnaire. The data is using equation R /C Ratio, BEP Revenue, BEP Price, and BEP Production. Therefore from the results of the researchment it can be explained that the two of the thirty farmers come through the break event point, while the other twenty-eight farmers declared having a business that worth to be develop or experiencing profit, because the R/C ratio is above 1.0 with average profit reach Rp. 989.000, - per production / farmer.

Life Cycle Development of Successful Women-owned Enterprises

2020 ◽  
Vol 3 (4) ◽  
pp. 142-152
Author(s):  
Mohammad Waliul Hasanat ◽  
Kamna Anum ◽  
Ashikul Hoque ◽  
Mahmud Hamid ◽  
Sandy Francis Peris ◽  
...  
Keyword(s):  
Life Cycle ◽  
Data Collection ◽  
Research Work ◽  
Primary Data ◽  
Small Scale ◽  
Data Collection Process ◽  
Theoretical Finding ◽  
Successful Women ◽  
Two Phases ◽  
Life Cycle Development

In developing countries, the role of women in the business sector is continuously improving. As a result, female enterprises have also been encouraged in Pakistan. This study is based on life cycle development phases from which women-owned enterprises have to go through in order to become successful. As a primary data source, face-to-face interviews with owners of successful women-owned enterprises were preferred. The data collection process was divided into two phases i.e. Phase-I and Phase-II. After data collection, qualitative analysis has been performed using NVIVO. Findings provide both generic and specific factors involved in life cycle development of women-owned enterprises. This study provides a detailed view of life cycle development model followed by successful women enterprises. The outcome of this research work is a theoretical finding which can be utilized by entrepreneurs owning small scale enterprises to improve their level of performance. Findings can also be helpful for potentially talented women interested in setting up their own business.

PENGARUH HARGA DAN KUALITAS PRODUK TERHADAP LOYALITAS PELANGGAN ALUMUNIUM

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Widodo Widodo ◽  
Marshelly Chandra Kumala
Keyword(s):  
Data Collection ◽  
Product Quality ◽  
Customer Loyalty ◽  
Significant Influence ◽  
Secondary Data ◽  
Primary Data ◽  
Research Results ◽  
Is Research ◽  
Quality Of Products

<em>The objective of this is research was conducted to find out how the influence of the price and quality of products against customer loyalty at PT. Alakasa Extrusindo Jakarta. This research was conducted in Alakasa Extrusindo PT by doing data collection, through the primary data and secondary data.  The research results showed that the simultaneous price variables  and product quality  has a positive and significant effect against the variable customer loyalty. partially showed that price variables has a positive and significant influence towards customer loyalty. And partially showed that product quality variables  has a positive and significant influence towards customer loyalty</em>

Corporate Growth Strategies and Performance of Selected Savings and Credit Cooperative Societies in Nairobi City County, Kenya

2020 ◽  
Vol 2 (2) ◽  
pp. 19-30
Author(s):  
Hamida Mwilu ◽  
Reuben Njuguna
Keyword(s):  
Data Collection ◽  
Business Environment ◽  
Primary Data ◽  
Growth Strategies ◽  
Inferential Statistics ◽  
Market Expansion ◽  
Acquisition Strategies ◽  
Corporate Growth ◽  
Diversification Strategies ◽  
And Performance

The dynamic nature of business operating environment has called on business leaders to be strategic in their leadership roles if they are to sustain their competitiveness into the unforeseen future. Growth is important in Sacco’s because it is future oriented establishing ways in which the organizational operations can be aligned to future changes in the business environment to ensure that competitiveness is sustained. The SACCOs in Kenya have experienced problems in the past; some even shutting down therefore there is need for customer growth to be enhanced so as to increase their incomes so as to sustain the business. These SACCOs have to look for leaders and managers who can develop future targets, direct and lead other staffs towards meeting the firm’s objective and gaining a competitive edge. The aim of this study was an assessment of corporate growth strategies and performance in savings and cooperative societies in Kenya, Nairobi County. The study sought to determine the influence of market expansion, diversification strategies and acquisition strategies. The study target population was 41 licensed SACCOs in Nairobi County. The study used primary data to collect information, and the data collection instrument was a questionnaire which was given to the 41 operations managers in the 41 selected SACCOs. The data collection procedure was done by the researcher and drop-and-pick strategy will be applied. The data was coded and keyed in Statistical Package for Social Science (SPSS Version 23.0), and was analyzed using both descriptive and inferential statistics. For descriptive statistics was through mean scores, standard deviations, frequencies and percentages, while the inferential statistics was through regression analysis to establish the relationship between strategic leadership and customer growth. The findings were presented in tables and charts for easy understanding, interpreting, and describing the data. The study established that market expansion, diversification strategies and acquisition strategies as corporate growth strategies had a positive and significant effect on the performance of SACCOs in Nairobi City County. The study concluded that the SACCOs significantly employed market expansion strategies through improved branch network, customer base enhancement, new distribution channels and technological innovation. The study concluded that the SACCOs embraced a hybrid of the main diversification strategies, diverse products and services significantly. It was concluded that to a little extent the selected SACCOs in Nairobi City County have employed acquisition as a corporate growth strategy. The study recommends that the SACCOs should embrace integrate technology in the implementation of corporate growth strategies to enhance efficiency and effectiveness.  Further studies should be undertaken to establish the effect of corporate growth strategies on the performance of other SACCOs in other regions to establish the disparities or similarities among the financial sector players. 

On the Dimensionality of Measuring Tourist Satisfaction towards Homestay

2015 ◽  
Vol 8 (2) ◽  
Author(s):  
Gangaram Biswakarma
Keyword(s):  
Factor Analysis ◽  
Data Collection ◽  
Exploratory Factor Analysis ◽  
Life Style ◽  
Factor Loading ◽  
Primary Data ◽  
Cultural Performance ◽  
Latent Construct ◽  
Tourist Satisfaction ◽  
The Relationship

This study focuses on measuring tourist satisfaction towards home stay. This paper emphasized to identify the variables that are related to tourist satisfaction during tourist homestay. It is also focused on analyzing the relationship and impact of these latent construct of factors to overall tourist satisfaction towards home stay. In an attempt to visualize the purpose, tourists satisfaction in a homestay in Nepal has taken into as a case, with an aim to identify the underlying dimensions of tourist satisfaction during tourist homestay. Twenty six (26) manifest variables of homestay has been formulated to understand the dimensions. Likewise, for a conforming the latent construct (1) statement as dependent variable of overall satisfaction was developed for the purpose of the primary data collection. The manifest variables are basically focused on aspects of home stay attributes namely cultural attraction, hospitality, amenities and safety & security at the home stay destination. Post Exploratory Factor Analysis indicates factor loading for twenty two (22) items manifest variables as significant, loaded with five (5) factors of home stay attributes named as Amenities & Safety, Reception, Local Cuisine & Accommodation, Local Life style & Costumes, and Cultural Performance. This study contributes to the development of survey instrument for exploring tourist satisfaction for Home stay for future researchers.

scholarly journals A Siamese neural network model for the prioritization of metabolic disorders by integrating real and simulated data

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i787-i794
Author(s):  
Gian Marco Messa ◽  
Francesco Napolitano ◽  
Sarah H. Elsea ◽  
Diego di Bernardo ◽  
Xin Gao
Keyword(s):  
Predictive Accuracy ◽  
Hybrid Approach ◽  
Simulated Data ◽  
Original Data ◽  
Diagnostic Process ◽  
Great Promise ◽  
Metabolic Profiles ◽  
Inborn Errors ◽  
Metabolomic Data ◽  
Near Future

Abstract Motivation Untargeted metabolomic approaches hold a great promise as a diagnostic tool for inborn errors of metabolisms (IEMs) in the near future. However, the complexity of the involved data makes its application difficult and time consuming. Computational approaches, such as metabolic network simulations and machine learning, could significantly help to exploit metabolomic data to aid the diagnostic process. While the former suffers from limited predictive accuracy, the latter is normally able to generalize only to IEMs for which sufficient data are available. Here, we propose a hybrid approach that exploits the best of both worlds by building a mapping between simulated and real metabolic data through a novel method based on Siamese neural networks (SNN). Results The proposed SNN model is able to perform disease prioritization for the metabolic profiles of IEM patients even for diseases that it was not trained to identify. To the best of our knowledge, this has not been attempted before. The developed model is able to significantly outperform a baseline model that relies on metabolic simulations only. The prioritization performances demonstrate the feasibility of the method, suggesting that the integration of metabolic models and data could significantly aid the IEM diagnosis process in the near future. Availability and implementation Metabolic datasets used in this study are publicly available from the cited sources. The original data produced in this study, including the trained models and the simulated metabolic profiles, are also publicly available (Messa et al., 2020).

scholarly journals Mapping EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS)

2019 ◽  
Vol 29 (1) ◽  
pp. 265-274
Author(s):  
Ali Kiadaliri ◽  
Monica Hernández Alava ◽  
Ewa M. Roos ◽  
Martin Englund
Keyword(s):  
Disease Severity ◽  
Knee Injury ◽  
Cruciate Ligament ◽  
Simulated Data ◽  
Probit Model ◽  
Original Data ◽  
Cost Utility ◽  
Superior Performance ◽  
Outcome Score ◽  
Mapping Models

Abstract Purpose To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS). Methods The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models. Results Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS5, KOOS4). LR had the poorest performance overall and across the range of disease severity particularly at the extremes of the distribution of severity. Compared with the RM, the BM performed better across the entire range of disease severity except the most severe range (KOOS5 < 25). Moving from the most to the least disease severity was associated with 0.785 gain in the observed EQ-5D-3L. The corresponding value was 0.743, 0.772 and 0.782 for LR, BM and RM, respectively. LR generated simulated EQ-5D-3L values outside the feasible range. The distribution of simulated data generated from the BM model was almost identical to the original data. Conclusions We developed mapping models to estimate EQ-5D-3L from KOOS facilitating application of KOOS in cost-utility analyses. The BM showed superior performance for estimating EQ-5D-3L from KOOS. Further validation of the estimated models in different independent samples is warranted.

scholarly journals Spatially and temporally distributed data foraging decisions in disciplinary field science

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Cristina G. Wilson ◽  
Feifei Qian ◽  
Douglas J. Jerolmack ◽  
Sonia Roberts ◽  
Jonathan Ham ◽  
...  
Keyword(s):  
Data Collection ◽  
Simulated Data ◽  
Environmental Data ◽  
Distributed Data ◽  
Field Science ◽  
In Situ Data ◽  
Disciplinary Field ◽  
Variable Space ◽  
Query Selection ◽  
Fitting Error

AbstractHow do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore closely parallels classic search and foraging behavior. Here we conduct a novel simulated data foraging study—and a complementary real-world case study—to determine how spatiotemporal data collection decisions are made in field sciences, and how search is adapted in response to in-situ data. Expert geoscientists evaluated a hypothesis by collecting environmental data using a mobile robot. At any point, participants were able to stop the robot and change their search strategy or make a conclusion about the hypothesis. We identified spatiotemporal reasoning heuristics, to which scientists strongly anchored, displaying limited adaptation to new data. We analyzed two key decision factors: variable-space coverage, and fitting error to the hypothesis. We found that, despite varied search strategies, the majority of scientists made a conclusion as the fitting error converged. Scientists who made premature conclusions, due to insufficient variable-space coverage or before the fitting error stabilized, were more prone to incorrect conclusions. We found that novice undergraduates used the same heuristics as expert geoscientists in a simplified version of the scenario. We believe the findings from this study could be used to improve field science training in data foraging, and aid in the development of technologies to support data collection decisions.

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