Deconstructing Online Hospitality Review Systems

Online hospitality reviews have an important impact on consumers’ travel and hospitality booking decisions in the Internet age. A well-designed online hospitality review system is crucial to reduce the uncertainty of consumers’ decision making, to grasp the actual needs of consumers, and to improve the quality experience of platforms. In this context, this research conducts an empirical study on the design features of online hospitality review systems based on the Kano model. First, the paper analyzes the design features of online hospitality review systems. Then, the paper proposes an improved method to classify design features on the basis of the Kano questionnaire design and survey data. Finally, the paper quantitatively measures their importance in online hospitality review systems. Results can provide scientific basis for online travel platforms or hospitality operators to optimize the design of online hospitality review systems and to obtain reference value to increase the satisfaction of consumers’ decision making.

The Transparency of Quantitative Empirical Legal Research (2018–2020)

Scientists are increasingly concerned with making their work easy to verify and build upon. Associated practices include sharing data, materials, and analytic scripts, and preregistering protocols. This has been referred to as a “credibility revolution”. The credibility of empirical legal research has been questioned in the past due to its distinctive peer review system and because the legal background of its researchers means that many often are not trained in study design or statistics. Still, there has been no systematic study of transparency and credibility-related characteristics of published empirical legal research. To fill this gap and provide an estimate of current practices that can be tracked as the field evolves, we assessed 300 empirical articles from highly ranked law journals including both faculty-edited journals and student-edited journals. We found high levels of article accessibility (86% could be accessed without a subscription, 95% CI = [82%, 90%]), especially among student-edited journals (100% accessibility). Few articles stated that a study’s data are available, (19%, 95% CI = [15%, 23%]), and only about half of those datasets are reportedly available without contacting the author. Preregistration (3%, 95% CI = [1%, 5%]) and availability of analytic scripts (6%, 95% = [4%, 9%]) were very uncommon. We suggest that empirical legal researchers and the journals that publish their work cultivate norms and practices to encourage research credibility.

Optimization of Raw Material Inventory Control CV. Dirga Eggtray Pinrang Using Probabilistic Model with Backorder and Lostsales Condition

This research discusses about the comparison of raw material inventory control CV. Dirga Eggtray Pinrang. It starts with forecasting inventory for the next 12 periods using variations of the time series forecasting method, where the linear regression method provides accurate forecasting results with a Mean Absolute Percentage Error (MAPE) value of 1,9371%. The probabilistic models of inventory control used are the simple probabilistic model, Continuous Review System (CRS) model, and Periodic Review System (PRS) model. The CRS model with backorder condition is a model that provides the minimum cost of Rp. 969.273.706,20 per year compared to another probabilistic model with the largest difference of Rp. 1.291.814,95 per year, with the optimum number of order kg, reorder level kg, and safety stock kg.

Chennai Floods 2021: Sentiment Analysis of Twitter Data using Tweepy and TextBlob

The rise in the usage of Twitter for the exclamation of the problems worldwide and also as a ‘review system,’ where the customers can directly hold an entity responsible in front of the public by tweeting and tagging them, gives them immense power and counts towards being an advantage for researchers to analyze such data that can be scraped and used through APIs for a variety of purposes. Through this research, our motive is to analyze the 2021 Chennai floods with data sourced from twitter to understand the public sentiment during the 14-day span. The same is achieved with the help of Tweepy to authenticate data extraction from Twitter and TextBlob, for the classification of sentiment tags - positive, negative, and neutral. The result of this study focuses on the visualization of our findings, with various charts and metrics indicating the sentiment of the tweets we have scraped and analyzed. Keywords: Sentiment Analysis, WordCloud, Subjectivity, Polarity, Chennai Floods

Perencanaan Persediaan Darah di Unit Transfusi Darah (UTD) Palang Merah Indonesia Kota Madiun

UTD PMI Kota Madiun merupakan pemasok darah untuk beberapa Bank Darah Rumah Sakit (BDRS) di wilayah Kota Madiun dan sekitarnya. Tingginya permintaan yang masuk, terkadang permintaan darah tidak dapat dipenuhi dan di sisi lain banyak juga darah yang sudah expired. Permasalahan ini dapat diselesaikan dengan menentukan stok yang aman serta kapan harus dilakukan pemesanan darah kembali. Data yang digunakan dalam penelitian ini adalah jumlah permintaan produk darah Packed Red Cells selama periode 2020 yang dikumpulkan dari database PMI. Pada penelitian ini dilakukan evaluasi sekaligus penentuan stok yang optimal untuk menghindari banyaknya darah yang rusak sekaligus mengurangi biaya persediaan dengan menggunakan metode Continuous Review System. Hasil dari penelitian ini diperoleh persediaan optimal yang harus disediakan PMI Kota Madiun sekaligus rekomendasi untuk menggunakan Two-Bin System dalam penyimpanan persediaan darah, selain itu biaya persediaan dapat berkurang sebesar 40%.

The role and significance of peer-review in Russian and foreign library and information science journals: a comparative analysis

The paper summarizes experience of the authors as peer-reviewers of more than 100 manuscripts in twelve Russian and foreign academic journals on Library and Information Science in the last seven years. Prepared peer-reviews were used for making a list of the most usual critical and special comments for each manuscript that were subsequently structured for the conducted analyzes. Typical issues accompanying the peer-review process are shown. Significant differences between the results of peer-review in Russian and foreign journals are detected: although the initial quality of newly submitted manuscripts is approximately equal, the final published versions in foreign journals addressed all critical and the majority of minor reviewers’ comments, while in Russian journals more than one third of final versions were published with critical gaps. We conclude about low interest in high quality peer reviews among both authors and editors-in-chief in Russian journals. Despite the limitations of the samples, the obtained findings can be useful when evaluating the current peer-review system in Russian academic journals on Library and Information Science.

If You Like Me, Please Don’t “Like” Me: Inferring Vendor Bitcoin Addresses From Positive Reviews

Bitcoin and similar cryptocurrencies are becoming increasingly popular as a payment method in both legitimate and illegitimate online markets. Such markets usually deploy a review system that allows users to rate their purchases and help others to determine reliable vendors. Consequently, vendors are interested into accumulating as many positive reviews (likes) as possible and to make these public. However, we present an attack that exploits these publicly available information to identify cryptocurrency addresses potentially belonging to vendors. In its basic variant, it focuses on vendors that reuse their addresses. We also show an extended variant that copes with the case that addresses are used only once. We demonstrate the applicability of the attack by modeling Bitcoin transactions based on vendor reviews of two separate darknet markets and retrieve matching transactions from the blockchain. By doing so, we can identify Bitcoin addresses likely belonging to darknet market vendors.