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Enabling Customer-Centricity and Relationship Management using Net Promoter Score

Abstract

We are in the fifth era of marketing development, that of relationship marketing, where the environment is influenced by globalization, informatization, market liberalization, and the overcapacity of production, and the focus will be not on increasing the volume of production, but on obtaining profit using relationship with profitable customers. Customer-centricity, customization, one-to-one relationship and measuring the value of each customer is an advantage in the fearless market. Organizations if they knew what customers wants would offering only those products or services they want, but to help them to know the customers’ needs better, they use models, new methods and calculation of performance indicators. One of the models which help organizations to determine the customer value and centricity is Net Promoter Score (NPS), its formula being developed by Reichheld F. in 2006. Our research is made on 10 organizations and on 150 respondents and is consisting in using NPS in order to observe customers’ perception of the analysed brands, to measure how well the brand is having satisfayed and loyal customers, and the desire for recommendation of the analysed brand. Our article is using simulation, modeling and IT programs to observe possible relationships and future trends.

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Investigating Weak Supervision in Deep Ranking

25 is the most common heuristic for generating weak relevance labels ( Dehghani et al., 2017 ; MacAvaney et al., 2017 ). Dehghani et al. (2017) used BM25 as the heuristic to generate weak labels and reported that their fine-tuned neural models outperformed BM25. By using documents’ titles as pseudo queries and BM25 scores as weak labels, MacAvaney et al. (2017) introduced a filtering method to effectively produce positive and negative query–document pairs. However, the implicit assumption that the exact matching signals can represent relevance usually brings

Open access
The Technical Efficiency of Tunisian Ports: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis Scores

Abstract

Maritime transportation for Tunisia plays an important role in trade exchange with other countries. Therefore, the objective of this paper is to measure the efficiency scores of 7 seaports in Tunisia by applying the Stochastic Frontier Analysis (SFA) with Cobb-Douglas production function and Data envelopment analysis (DEA) with CCR and BCC models. The annual data collected cover the 2007-2017 period for each port. Thus, the sample size for the analysis comprises a total of 77 observations. The empirical result shows that the total average scores of operating efficiency scores were DEA-BCC (0.746) >SFACD (0.536)>DEA-CCR (0.334) from 2007 to 2017. Given these results, the port of Gabes can be considered as the best efficient port in the 3 models (DEA-BCC, DEA-CCR and SFA-CD).

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Economic Evaluation of Health Programs – Health Expenditures in the European Union

economics, 23 : 589-613. Erik Biorn, Terge P. Hagen, Tor Iversen and Jon Magnussen, (2002), “ The effect of activity – based financing on hospital efficiency: A panel data analysis of DES efficiency scores 1992-2000” , university of Oslo. Gerdtham Ulf-G, SnrgaardJes, Andersson Fredrik, and Jenssona Bengt, (1992), “ An econometric analysis of health care expenditure: A cross-section study of the OECD countries” , Journal of health Economics, I : 63 – 84 North – Holland. Ifantopoulos, G., D. Polygenis, Ι. Takoumakis,(2004), “ Brtish health system ” Health

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Design of a generic, open platform for machine learning-assisted indexing and clustering of articles in PubMed, a biomedical bibliographic database

-dimensional space. The distance between any two PubMed articles can be calculated as a weighted sum of the pairwise similarity scores of the underlying features between each PubMed article. Then, the overall distance between a PubMed article and a training set will be some function of the weighted pairwise similarity scores (for each of the articles that make up the training set). Finally, articles can be classified as belonging to one or more categories (depending on the relative distance of an article to the positive vs. negative training sets) or similar articles can be

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Measurement of the Logistic Customer Service Level in Commercial Cargo Motor Transport Companies

assessment based on psychometric and diagnostic criteria,” in Journal of Marketing, No. 70 (3), 1994, pp. 201-230. 21. A. R. Meybodi, “Measuring service quality using Servqual model: A case study of brokerage ofices in Iran,“ in International Journal for Quality Research, No. 6(1), 2012, p.55-61. 22. F. Pakdil, and O. Aydin, “Expectations and perceptions in airline services: An analysis using weighted SERVQUAL scores,” in Journal of Air Transport Management, No. 13, 2007, p. 229-237. 23. C. Rafele, “Logistic service

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To Phrase or Not to Phrase – Impact of User versus System Term Dependence upon Retrieval

between quotes. Each of these 52 queries was assessed by 101 users. The scores in brackets in Table 1 show the average user agreement on the most popular user choice for each query, which we computed as the % of users (out of all 101 users) who agree on the most popular term dependence option for each query. For instance, the average agreement of 69% for “rain man” means that 70 out of 101 users (≈69%) selected the option “rain man”. The 52 train queries are sorted in Table 1 by decreasing user agreement. Table 1 Train queries used on the CrowdFlower

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Supporting Book Search: A Comprehensive Comparison of Tags vs. Controlled Vocabulary Metadata

bibliographical metadata change the search performance? Answer : There is no significant difference when combining Core bibliographical metadata with CVs. Including Core bibliographical metadata in general achieves a better performance. Any real-world book search engine would always include the core bibliographic data in its documents. The NDCG@10 scores seem to bene t from adding the Core elements to other metadata elements. These differences are significant according to a two-tailed paired t -test ( t (1307) = 4.799, p < .0005, ES = 0.13, 95% CI [0.0083, 0

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Usability Evaluation of E-Dunhuang Cultural Heritage Digital Library

control of the mouse: “I don’t know what’s happening, why it spins so fast, I just use my mouse to drag left and right because I want to check out the paintings around, why it is so hard to control!” (participant 4). Other participants also complained about the automatic spinning feature of the panoramic function: “I feel quite dizzy that it spins all the time!” (participant 1) “Why can’t I stop if from spinning?” (participant 8) 4.3.2 Organization of information Another criterion with lower scores was “organization of information” where

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Big Data in Health Care: Applications and Challenges

characteristics. Christy et al. (2015) proposed two cluster-based outlier detection algorithms including distance-based outlier detection and cluster-based outlier detection. The main purpose of the algorithms was to remove outliers that are irrelevant or only weakly relevant to the analysis of health care data. Experimental evaluation based on the metrics of F-score and likelihood ratio shows that the cluster-based outlier detection method outperforms distance-based outlier detection method. Huang and Yao (2016) proposed a novel clustering approach for multidimensional

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