Subscription Data Research Articles

Will they stay or will they go? application of machine learning classifiers of purchase and churn prediction to a digital journalistic platform

ABSTRACT Considering the ubiquity of data, purchase and churn prediction have become crucial for data-driven decision-making. While many sectors have benefited from the abundance of data in the wake of digital transformation, the applications of predictive analytics remain limited in small or medium-sized enterprises, and journalism. Thus, this study focuses on applying such techniques in the context of start-up journalism. For this purpose, article purchase and subscription data from a digital journalistic platform of over 2,700 individual customers were analysed in multiple models using the ensemble methods of random forest and gradient boosting, and logistic regression. The findings suggest, first, that variables typically associated with the recency, frequency and monetary value of customers are central to purchase prediction, and, second, that churn prediction depends on other behavioural variables, such as time/actions per visit. Furthermore, while naïve application of the logistic regression achieves comparable results to the ensemble methods for the purchase prediction, it strongly underperforms in churn prediction, while gradient boosting performs best throughout. Beyond, optimisation for recall leads to random forest to perform best. The results demonstrate high accuracy scores and hence imply the applicability of such models to journalism. Furthermore, this paper demonstrates how to reduce classification thresholds in models to improve sensitivity for small, imbalanced data sets.

Journalism as a Service: How Tablet News Service Influences Subscriber Retention and Long-Term Profitability

With the decline of advertising revenue, the newspaper industry faces the challenge of increasing audience-supported revenue. While news organizations must provide quality journalism to their readers, a complementary approach is to create better reading experiences using mobile news delivery. Focusing on the reading experience and building a long-term relationship are tenants of service-dominant logic theory. We study the Arkansas Democrat-Gazette, which provided its subscribers iPads with training and tech support while discontinuing its print edition. We analyze clickstream and subscription data to examine how participating in the iPad program influences subscriber retention, how the effect of the iPad program varies by region, and whether the customer lifetime value (CLV, discounted expected future profits) of subscribers who enrolled in the iPad program outweighs the cost of the program. The iPad program decreases subscriber churn across regions and subscriber segments. The CLV of subscribers in the iPad program is greater than the cost of iPads, training, and tech support, with newer subscribers showing higher CLV. The results demonstrate the importance of shifting to service-oriented approach in journalism and the potential of mobile devices to increase readership and long-term profitability.

Power consumption prediction for electric vehicle charging stations and forecasting income

Electric vehicles (EVs) are the future of the automobile industry, as they produce zero emissions and address environmental and health concerns caused by traditional fuel-poared vehicles. As more people shift towards EVs, the demand for power consumption forecasting is increasing to manage the charging stations effectively. Predicting power consumption can help optimize operations, prevent grid overloading, and power outages, and assist companies in estimating the number of charging stations required to meet demand. The paper uses three time series models to predict the electricity demand for charging stations, and the SARIMA (Seasonal Auto Regressive Integrated Moving Average) model outperforms the ARMA (Auto Regressive Moving Average) and ARIMA (Auto Regressive Integrated Moving Average) models, with the least RMSE (Root Mean Squared Error), MAE (Mean Absolute Error) and MAPE (Mean Absolute Percentage Error) scores in forecasting power demand and revenue. The data used for validation consists of charging activities over a four-year period from public charging outlets in Colorado, six months of charging data from ChargeMOD's public charging terminals in Kerala, India. Power usage is also forecasted based on wheels of vehicles, and finally, a plan subscription data from the same source is utilized to anticipate income, that helps companies develop pricing strategies to maximize profits while remaining competitive. Utility firms and charging networks may use accurate power consumption forecasts for a variety of purposes, such as power scheduling and determining the expected energy requirements for charging stations. Ultimately, precise power consumption forecasting can assist in the effective planning and design of EV charging infrastructure. The main aim of this study is to create a good time series model which can estimate the electric vehicle charging stations usage of power and verify if the firm has a good income along with some accuracy measures. The results show that SARIMA model plays a vital role in providing us with accurate information. According to the data and study here, four wheelers use more power than two and three wheelers. Also, DC charging facility uses more electricity than AC charging stations. These results can be used to determine the cost to operate the EVs and its subscriptions.

Newly subscribed! Effects of e-mail newsletters on news-reading habit and subscriber retention during onboarding: evidence from clickstream and subscription data

ABSTRACT Despite the increasing popularity of e-mail newsletters, there have been few studies that examine the effects of signing up for e-mail newsletters among news subscribers, especially its role in enhancing news reading behaviors and subscriber retention for new subscribers. This study investigates how e-mail newsletter sign-ups influence news-reading habits and subscriber retention during onboarding. Using single-source data that combine clickstream data from news sites, e-mail newsletter sign-up records, and payment histories of 16,284 new digital news subscribers across four major markets in the U.S. this study finds that signing up for e-mail newsletters improves news reading habits and digital news subscription duration, with an additive effect of the number of e-mail newsletters signed up for. Regarding the retention mechanism, signing up for e-mail newsletters contributes to retention by helping new subscribers read more frequently and intensely (measures of reading habit), which in turn positively affects subscriber retention.

Curbing the decline of local news by building relationships with the audience

Abstract In the struggle to find sustainable business models, many local news sites have turned to engaged journalism, which draws from social exchange theory and aims to build relationships with audiences. The causal impact of these initiatives is unclear, but important given that local news sites are critical information sources and face dire economic situations. In this study, 20 news sites were randomly assigned to launch a six-month engaged journalism initiative where journalists reported on audience questions or to continue their current practices. Although not a panacea, over time traffic and subscription data and a two-wave survey of audience members across the sites (n = 3,998) show that the initiative resulted in more subscriptions and more positive audience evaluations. The results highlight the applicability of social exchange theory to questions of local news viability and illustrate that engaged journalism can improve relationships between newsrooms and the communities they serve.

Studi Analisis Susut Energi Listrik Non Teknis dengan Cara Optimalisasi Peremajaan KWH Meter Pascabayar 1 Phasa di PT. PLN (Persero) ULP Painan

Loss is the amount of energy lost in the process of distributing electrical energy from the substation to consumers. PT PLN (Persero) ULP Painan losses in the second trimester of 2022 are cumulative with a total value of 3,627,350 kWh. Meanwhile, non-technical losses contributed a total kWh with a value of 841,032 kWh. Therefore, it is necessary to optimize the replacement of kWh meters to reduce non-technical losses by forming an independent replacement team and implementing a routine kWh meter replacement schedule, evaluating Subscription Data that Needs Attention (DLPD) to get Work Orders (WO) that are right on target, establishing communication. both with internal parties (Outsourced Personnel) to obtain accurate WO and implement the SOP for replacing kWh meters in the field. After efforts to optimize kWh replacement, the total loss for the third semester of 2022 was 273,096 kWh, a decrease of 567,936 kWh from the second trimester of 2022. If converted into Rp. 818,324,136 for the second trimester of 2022 while for the third trimester of 2022 Rp. 265,722,408 and savings of Rp. 552,601,728.00. The reduction in non-technical losses above was contributed by the achievement of kWh meter replacement of 49,140 kWh. Saving rupiah obtained from obtaining a kWh meter replacement of Rp. 47,813,220.00, therefore efforts to reduce non-technical losses by optimizing kWh meter replacement can be said to help reduce non-technical losses

Indispensable or unnecessary?: a data-driven appraisal of post-cancellation access rights

When breaking out of ‘big deals’, some libraries and consortia have found that they can save money by negotiating away post-cancellation access (PCA) to subscribed resources after the subscription concludes. Using subscription data regarding major publisher contracts at several US research libraries, this article reviews options around PCA for libraries and presents a model for assigning a value to PCA content when negotiating a renewal contract.

Extensive Reading as a Gateway to Create Research Gap: Valuable Lessons from Indonesian Expert Authors

Identifying research gaps from the extensive reading process is an inevitable choice for researchers in any field. This study aims to explore various approaches in identifying research gaps that have the potential to become elements of novelty. By using a grounded theory approach, the research reconstructs the cognitive experiences of a number of Indonesian expert authors in identifying research gaps. The results show that scientific journals as the primary source are accessed from the subscription data center; discuss and conduct knowledge sharing with expert groups; bibliography mapping by establishing a basic reference to avoid getting out of the focus of the research topic; state of the art and novelty elements will be seen from the extensive reading; using software to synthesize the literature review. It concludes that the research gap as the forerunner of the novelty element can only be done through an extensive reading process. Through extensive reading allows researchers or scientific writers to find many research gaps that can be explored.

An analysis of the utilisation of medical identification jewellery among children and young adults with type 1 diabetes mellitus in Australia

AimsPeople with type 1 diabetes mellitus (T1DM) are at risk of life-threatening illness. Medical jewellery is recommended for emergencies, but its uptake is unknown. This study assessed the use of medical jewellery among people with T1DM aged 0–24 years in Australia.MethodsA cross sectional analysis of subscription data to the largest medical identification jewellery service in Australia was analysed by age, sex and geographic location using Australian population data from 2018.ResultsThere were 1599 people with T1DM aged 0–24 in the database, but only 1061 had an active subscription, corresponding to an active subscription rate of 13.28/100,000 population or ~5% of the estimated patient population. Half of the active subscribers were male (543/1061, 51/3%). The average age of active subscribers was 17; very few (n = 12, 1.1%) were aged less than 5; and the highest number (n = 141, 39%) was in the 20–24 age group. Active subscription rates varied significantly by geographic location. 88.4% of active subscribers had a diagnosis of T1DM or equivalent inscribed on their emblem, while engraved instructions for management in an emergency were only included in 1.8% of records (n = 19).ConclusionsMedical jewellery subscription rates were lower than expected; increased with age; and varied significantly by state/territory. The use of medical identification jewellery may be limited by the lack of suitable engraved instructions for use in an emergency. Factors leading to low use should be addressed.Photo 1 Medical Jewellery with emblem

Short-term IPO Performance Amidst Fearof COVID-19 Pandemic: Evidence from India

The study of investor behaviour in and around tail events is important as these impact market returns. Since the onset of the COVID-19 pandemic, financial markets worldwide have seen enormous falls amid widespread uncertainty initially and then bounced back strongly with greater momentum. This article investigates the short-term performance of public issues which had their debut on the Indian Stock exchanges during the time of the COVID-19 pandemic. It also analyses the impact of fear of the pandemic on underpricing, if any and the factors impacting their performance. It compares the pre-COVID and post-COVID initial public offerings (IPOs) in Indian Capital Market with a sample of 158 listings across nine years from 2013 to 2021 on the main board segment of the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). With the help of the t-test and multivariate regression applied on subscription data, listing data, listing gains, issue size, return on net worth, age and other factors, a more active retail investor group emerges with a statistically significant increase in underpricing during the COVID-19 era. The study provides strong evidence that the pandemic contributed towards increase in number of firms getting listed and higher levels of underpricing. It also suggests that the impact was particularly on the investors’ sentiment with increase in retail subscription four folds. Desire to synthesize short term benefits and over optimism among the retail investors, has led to such increase. We summarize that in the post pandemic era, higher than usual listing gains and larger than usual issue sizes are affected by a radical shift in Indian retail investor behaviour. Tail events like COVID-19 have changed the way Indian investors behave and invest in IPO’s causing them to base their decisions on speculative metrics rather than the actual fundamentals of the issue. This article is a first-of-its-kind study to examine the impact of the pandemic on the equity market practices in India, namely, the anomaly of underpricing of IPOs or new listings on the main board segment.

A Blockchain Based User Subscription Data Management and Access Control Scheme in Mobile Communication Networks

A Blockchain Based User Subscription Data Management and Access Control Scheme in Mobile Communication Networks

Digital News Readership and Subscription in the United States during COVID-19: A Longitudinal Analysis of Clickstream and Subscription Data from a Local News Site

The COVID-19 pandemic created a unique opportunity where local news sites play an essential role in their readers’ lives. Whether this increased level of news readership will help save the business of local journalism is a question that journalism scholars and professionals seek to answer. We propose a framework that demonstrates the relationships between local news consumption experiences, reading behaviours, and audience retention. We analysed individual-level clickstream data and payment records of subscribers of a regional newspaper to track the changes in their news reading behaviours and renewal decisions before and after the virus outbreak. We found that reading behaviours spiked since the beginning of the pandemic and gradually decreased but remained at a relatively higher level compared to the same period in previous years. We also found that reading news on COVID-19 or local issues and signing up for email newsletters for local news or sports positively influenced establishing the regularity of online local news consumption. The regularity of consuming local news on the site, in turn, positively impacted audience retention, demonstrating the importance of building the habit of online news consumption by providing the value that current and potential subscribers seek from their digital news consumption experiences.

Penekanan Susut Non-Teknis dengan cara Optimalisasi Pelaksanaan P2TL di PT-PLN-(Persero)-ULP-Indarung

Loss is the amount of energy lost in the process of distributing electrical energy from the substation to the consumer. PT PLN (Persero) ULP Indarung's losses in semester 1 of 2020 were still quite high with a total of 10,314,804 kWh, while non-technical losses contributed 30.76% kWh of the total or equal to 3,173,508 kWh. Subscription Data Needs Attention (DLPD) to obtain Operational Targets (SO) and Operational Targets (TO), establish good communication with internal (Outsourcing) and External (community) parties to obtain accurate Operational Targets (TO), and implement P2TL SOPs in the field. After P2TL optimization efforts were made, the total losses in semester 1 of 2021 were 8,108,489 kWh, while non-technical losses in semester 1 of 2021 contributed 4.03% of the total or equal to 326,762 kWh. Therefore the P2TL optimization effort is said to be successful because it can reduce non-technical losses from 3,173,804 kWh to 326,762 kWh, with P2TL itself contributing 2,020,376 kWh.

Personal data confidentiality of consumers of the hospitality industry services in the digital age

The issues of information confidentiality and personal data processing are extremely relevant, especially in the age of digitalization. The current state of hospitality industry services consumers perception of the modern offers using Internet technologies is analyzed in the article and the influence of various factors on the decision to provide personal data to obtain a certain level of service is determined. Bypassing confidentiality destabilizes trust between social actors, reinforces feelings of insecurity and threatens social cohesion, which is a prerequisite for the sustainable development of our societies. Legislation as well as technology can protect personal information, but sometimes they are not user-friendly or are insufficient. In online interactions, users disclose information about themselves or others, while expressing concerns about breaches of confidentiality that may arise from self-disclosure practices rather than restricting or blocking their disclosure behavior. Hospitality industry companies typically collect two types of data: subscription data, which includes consumer personal information obtained during registration for a particular service use, and transactional information obtained when a consumer pays for a product or service. A question of consumers’ choice of hospitality institutions arises according to the volume of information confidentiality collected by the institution from the services consumer. A survey of university-age respondents was conducted in order to study the factors influencing decision-making when choosing a place of accommodation and the desire of young people to maintain privacy by confrontation or the desire to share personal data on the Internet. It is found that the majority of respondents either do not worry about the further confidentiality of personal data or consider it less important compared to the possible benefits of using access to the site or mobile applications. It has been proven that in order to improve mutual understanding with clients, companies in the hospitality industry should pay attention to the ethical aspects of the collection and use of personal data of services consumers.

Exploring a system architecture of content‐based publish/subscribe system for efficient on‐the‐fly data dissemination

SummaryIn a cloud‐scale publish/subscribe messaging system, it is difficult to partition subscription data among several servers. Without a sophisticated scheme and a system architecture, the messaging system would either waste resources or fail to deliver messages on time. In this study, we propose DRDA, a dynamic replication degree adjustment technology, for efficient message delivery. The technology calculates and maintains the number of subscription replications at a reasonable level by monitoring the statuses of servers, based on the number of subscription replications and the frequency of event dissemination. To verify the effectiveness of our proposed scheme and system architecture, we build a prototype of a content‐based publish/subscribe system that dynamically adjusts the number of replications among brokers. Furthermore, we compare the load balance, resource overhead, and performance of a publish/subscribe system with DRDA with a publish/subscribe system without DRDA. The experimental results show that DRDA outperforms other approaches under various parameter configurations. We have added the prototype code to a GitHub repository to make it publicly available.

Optimal Pricing of Internet of Things: A Machine Learning Approach

Internet of things (IoT) produces massive data from devices embedded with sensors. The IoT data allows creating profitable services using machine learning. However, previous research does not address the problem of optimal pricing and bundling of machine learning-based IoT services. In this paper, we define the data value and service quality from a machine learning perspective. We present an IoT market model which consists of data vendors selling data to service providers, and service providers offering IoT services to customers. Then, we introduce optimal pricing schemes for the standalone and bundled selling of IoT services. In standalone service sales, the service provider optimizes the size of bought data and service subscription fee to maximize its profit. For service bundles, the subscription fee and data sizes of the grouped IoT services are optimized to maximize the total profit of cooperative service providers. We show that bundling IoT services maximizes the profit of service providers compared to the standalone selling. For profit sharing of bundled services, we apply the concepts of core and Shapley solutions from cooperative game theory as efficient and fair allocations of payoffs among the cooperative service providers in the bundling coalition.

CellPred

Cellular data usage consumption prediction is an important topic in cellular networks related researches. Accurately predicting future data usage can benefit both the cellular operators and the users, which can further enable a wide range of applications. Different from previous work focusing on statistical approaches, in this paper, we propose a scheme called CellPred to predict cellular data usage from an individual user perspective considering user behavior patterns. Specifically, we utilize explicit user behavioral tags collected from subscription data to function as an external aid to enhance the user's mobility and usage prediction. Then we aggregate individual user data usage to cell tower level to obtain the final prediction results. To our knowledge, this is the first work studying cellular data usage prediction from an individual user behavior-aware perspective based on large-scale cellular signaling and behavior tags from the subscription data. The results show that our method improves the data usage prediction accuracy compared to the state-of-the-art methods; we also comprehensively demonstrate the impacts of contextual factors on CellPred performance. Our work can shed light on broad cellular networks researches related to human mobility and data usage. Finally, we discuss issues such as limitations, applications of our approach, and insights from our work.

OPEN ACCESS ROUTES DICHOTOMY AND OPPORTUNITIES: CONSOLIDATION, ANALYSIS AND TRENDS AT THE SPANISH NATIONAL RESEARCH COUNCIL

This article gives a comprehensive overview of recent Spanish National Research Council (CSIC) publications available in Open Access. With a focus on research articles from the last decade (2008–2018), this work aims to fill the gap in previous studies about publishing trends and impact monitoring of publications by researchers from the Spanish National Research Council. Evolution and main trends of Green and Gold Open Access routes at CSIC are addressed through a close insight into DIGITAL.CSIC repository and institutional Open Access Publishing Support Programme. The article draws on major conclusions at a time when an institutional Open Access mandate has just entered into force. The article also relates findings about performance of institutional Open Access Publishing Initiative and total volume of CSIC articles published in Open Access with an estimation of overall costs on article processing charges during these years. Furthermore, the data serve as a basis to make preliminary considerations as to opportunities to move from a subscription-based model to one fully aligned with Gold Open Access publishing. The data analyzed come from a variety of sources, including public information and internal records maintained by the CSIC E-resources Subscription programme, DIGITAL.CSIC and data retrieved from GesBIB, an internal, in-house development tool that integrates bibliographic information about CSIC publications as well as data from several external APIs, including Unpaywall, DOAJ and Sherpa Romeo.

Multi-Purpose Hybrid Recommendation System on Artificial Intelligence to Improve Telemarketing Performance

The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

Making sense of flipping data

Purpose The purpose of this paper is to detail the approach used in a project that worked with journal publication, subscription and article processing charges (APC) data. The project aim was to test if the resources allocated by the Matariki Network of Universities, a group of seven medium-sized universities, would pay for APC at the current level of publishing activity. Design/methodology/approach Data were collated and analysed from three years (2015–2017) for each of the seven partners. Findings A range of assumptions were made in dealing with the data. It was difficult to identify a subscription package that was common to all the partners. Data were not always consistent and in some instances it was incomplete. An iterative and flexible approach was required in this project. Even though testing had been carried out during planning, changes had to be made as the project was carried out. The timetable had to be flexible as those working on the project dealt with their day-to-day operational priorities and to enable each of the partners to contribute as resources allowed. Practical implications As alternative models of scholarly journal publication are evolving, it is important that the implications of these be tested to inform planning. Details of this testing need to be shared so that others can confirm the results, consider the approach and apply lessons learned. Originality/value This paper focuses on the details of the investigation so that others interested in repeating this project, or carrying out a similar project, can consider this in their planning.