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The purpose of this study was to investigate the impact of covid-19 on library services as perceived by international students and scholars at Kent State University, a medium-sized public research university in the mid-west, in the United States. A second general purpose was to increase awareness of library resources and services among the international student population. The study used a self-reported questionnaire (Qualtrics survey) to find out the use of library services and resources by international students' pre-pandemic and during the pandemic. Using google analytics, the study also compared visits of the library website from pre-pandemic and during the pandemic by the general student population. The author also obtained statistics from various library departments to compare pre-pandemic and pandemic usage. Additionally, informal interviews were conducted by the author to find out librarians' perceptions of how Covid-19 impacted their services and policies. The survey results showed a general lack of awareness of library resources and services among the international student population both pre-pandemic and during the pandemic. The usage statistics and reports from the librarians revealed a high impact of the pandemic on Interlibrary Loan (ILL), circulation, acquisitions and instruction services, but a modest/minimal impact on reference services and visits to the library website. Recommendations include increased marketing efforts and outreach to the international student population and by extension to all students especially long-distance students or online-only students. The study also highlights the importance of open access, consortia, and Institutional repositories and the role they play in enhancing equitable access to information. The study encourages libraries to leverage new technologies that would improve services while also advocating for policies that would help bridge the digital divide. [ABSTRACT FROM AUTHOR]

The modern e-commerce market is an economic environment with a high level of competition. That is why achieving commercial success in it largely depends on the ability of trade organizations to analyze and optimize their activities based on the data provided by web analytics services. The article highlights the importance of web analytics for evaluating and improving the performance of an online store. The opportunities provided by the two leading tools in this area, Google Analytics and Yandex Metrica, are reviewed. The focus is on conversion analysis, understanding the target audience and optimizing marketing efforts. The article offers a comprehensive approach to the use of web analytics in order to increase economic efficiency and ensure sustainable growth of economic performance indicators of an online store.

Marketing professionals and business owners strive to evaluate the effectiveness of their marketing investments. With multiple marketing channels at their disposal, understanding how these channels interact and influence each other is crucial. Digital analytics tools, such as Google Analytics, tend to measure the isolated success of each marketing channel. However, the intertwined effects and interdependencies between channels are often undervalued. This study, therefore, ventures into this territory. It focuses on the association between website traffic from various digital marketing channels and the purchases made by users visiting websites through direct traffic sources. We analyzed 89,394 purchases from an e-commerce business in Europe. We conclude that three marketing channels can explain 61% of the variance. By shedding light on this overlooked aspect, we aim to guide advertisers toward a more holistic understanding of digital marketing channels. [ABSTRACT FROM AUTHOR]

People are increasingly seeking complex health information online. However, how they access this information and how influential it is on their health choices remains poorly understood. Google Analytics (GA) is a widely used web analytics tool and it has been used in academic research to study health information-seeking behaviors. Nevertheless, it is rarely used to study the navigation flows of health websites. To demonstrate the usefulness of GA data, we adopted both top-down and bottom-up approaches to study how web visitors navigate within a website delivering complex health information about stem cell research using GA's device, traffic and path data. Custom Treemap and Sankey visualizations were used to illustrate the navigation flows extracted from these data in a more understandable manner. Our methodology reveals that different device and traffic types expose dissimilar search approaches. Through the visualizations, popular web pages and content categories frequently browsed together can be identified. Information on a website that is often overlooked but needed by many users can also be discovered. Our proposed method can identify content requiring improvements, enhance usability and guide a design for better addressing the needs of different audiences. This paper has implications for how web designers can use GA to help them determine users' priorities and behaviors when navigating complex information. It highlights that even where there is complex health information, users may still want more direct and easy-to-understand navigations to retrieve such information. [ABSTRACT FROM AUTHOR]

In March 2022, Google announced that their flagship Universal Analytics (UA) platform would stop processing new website sessions on July 1, 2023 (Ketchum 2022). Even though Google is offering users of UA the option to transition to their newer Google Analytics 4 (GA4) platform, which officially launched in October 2020, the sunsetting of the UA platform is causing great consternation in the web analytics and marketing analytics communities. Millions of businesses rely on UA to perform detailed analyses of their websites, providing insights into the make-up and engagement patterns of their website visitors and the performance of their digital marketing campaigns. Business analysts that are responsible for generating web analytics reports are now undergoing extensive training to learn how to operate in the GA4 environment. Marketing educators must also become well versed in the GA4 platform to teach undergraduate and graduate students how to use this new platform to perform a variety of critical marketing analytics tasks. This article provides a detailed overview of the new, free version of the GA4 platform, highlighting several of the platform's innovative features and capabilities. It also describes how educators and students can access comprehensive GA4 training resources and get certified on the platform. The goal of this article is to provide educators with practical information that can be used to help integrate the GA4 platform and corresponding web analytics concepts into the design of their marketing analytics and digital analytics courses. [ABSTRACT FROM AUTHOR]

This paper presents an empirical analysis of e-commerce data obtained through Google Analytics (GA) from two small businesses’ perspectives: an IT components company and a tourism agency website located within the same county in Romania. The objective of our study is to examine the enduring effects of the COVID-19 pandemic and seasonal variations over the last four years. The data collection spanned from January 2019, predating the onset of the COVID-19 pandemic, until mid-February 2023. To facilitate our analysis, we categorize the GA metrics into groups that encompassed website performance, site accessibility, and user behavior for the IT company. As for the tourism agency, we focus on website accessibility, user behavior, and marketing campaigns. Our goal is to empirically group or associate GA metrics according to their intrinsic meaning and check if each group reflects a certain latent concept (such as user behavior or site accessibility). Furthermore, our study aims to formulate and test five hypotheses regarding the immediate and long-lasting impact of the COVID-19 pandemic on the operations of small businesses. Our contribution consists of formulating and verifying the five hypotheses by providing descriptive data from the results of the Pearson correlation test, empirically grouping the GA metrics and verifying whether they reflect certain latent factors or topics, interpreting the results from the application of the ANOVA technique and Scarpello’s adaptation of the one factor test, respectively.

Patients considering gender-affirming surgery often utilize online health materials to obtain information about procedures. However, the distribution of patient concerns and content of online resources for gender-affirming surgery have not been examined. We aimed to quantify and comprehensively analyze the most searched questions of patients seeking gender-affirming surgery and to examine the quality and readability of associated websites providing the answers. Questions were extracted from Google using the search phrases "gender-affirming surgery," "transgender surgery," "top surgery," and "bottom surgery." Questions were categorized by topic and average search volume per month was determined. Websites linked to questions were categorized by type, and quality of the health information was evaluated utilizing the DISCERN instrument (16–80). Readability was assessed with the Flesch Reading Ease Score and Flesch-Kincaid Grade Level. Ninety questions and associated websites were analyzed. Common questions were most frequently answered by academic websites (30%). Topics included cost (27%), technical details of surgery (23%), and preoperative considerations (11%). Median (interquartile range) DISCERN score across all website categories was 42 (18). The mean readability was of a 12th-grade level, well above the grade six reading level recommended by the American Medical Association. Online gender-affirming surgery materials are difficult to comprehend and of poor quality. To enhance patient knowledge, informed consent, and shared decision-making, there is a substantial need to create understandable and high-quality online health information for those seeking gender-affirming surgery. [ABSTRACT FROM AUTHOR]

In the era of data analytics, the use of web analytics tools is widely spread among Small and Medium Enterprises (SMEs), especially in the e-commerce sector, to analyze web usage data and measure website performance due to the several features it provides. Most web analytics studies were conducted based on marketing rather than a managerial point of view. Therefore, there is a necessity to study the impact from a managerial perspective by exploring the impact on financial and non-financial performance and the decision-making process. This study assessed the impact of web analytics tools on the overall performance of SMEs, targeting Saudi SMEs and considering the lack of web analytics studies in this sector in Saudi Arabia. The sample involved eight Saudi SMEs who participated by answering interview questions, which were analyzed using thematic analysis. The findings demonstrated four main themes: the current web analytics tools used by Saudi SMEs, the motivations behind their use, and their impact on SMEs' performance and decision-making. The results showed that these tools positively affect the overall performance of SMEs. Google Analytics (GA) was the tool most used by the sample. Seven motives were discovered that encourage SMEs to use web analytics tools. This study also addressed the common Key Performance Indicators (KPIs) used by the participants. Concerning decision-making, it was found that web analytics tools affected and supported SMEs' decisions. Furthermore, this study evaluated the role of Zid, the Saudi e-commerce platform for data analytics and performance measurement. [ABSTRACT FROM AUTHOR]

This paper presents an empirical analysis of e-commerce data obtained through Google Analytics (GA) from two small businesses' perspectives: an IT components company and a tourism agency website located within the same county in Romania. The objective of our study is to examine the enduring effects of the COVID-19 pandemic and seasonal variations over the last four years. The data collection spanned from January 2019, predating the onset of the COVID-19 pandemic, until mid-February 2023. To facilitate our analysis, we categorize the GA metrics into groups that encompassed website performance, site accessibility, and user behavior for the IT company. As for the tourism agency, we focus on website accessibility, user behavior, and marketing campaigns. Our goal is to empirically group or associate GA metrics according to their intrinsic meaning and check if each group reflects a certain latent concept (such as user behavior or site accessibility). Furthermore, our study aims to formulate and test five hypotheses regarding the immediate and long-lasting impact of the COVID-19 pandemic on the operations of small businesses. Our contribution consists of formulating and verifying the five hypotheses by providing descriptive data from the results of the Pearson correlation test, empirically grouping the GA metrics and verifying whether they reflect certain latent factors or topics, interpreting the results from the application of the ANOVA technique and Scarpello's adaptation of the one factor test, respectively. [ABSTRACT FROM AUTHOR]

Within the modern era, corporates are compelled to own an appealing and effective website to survive and thrive within the competitive global digital marketplace. Whilst there are several web metrics to focus on, a key focus area of web analytics is the level of drop-offs. The drop-off rate represents the proportion of visitors that prematurely drop-off a website. Whilst the exact reason behind the drop-off may only be assumed (could be due to the loss of Internet connectivity or dis-interest), this study attempted to identify the triggers behind website drop-offs through a survival problem. Each person entering the website, at a given instance, can view any number of web pages (such as home, contact us, about us, etc.). However, on the studied website, roughly one in five visitors have prematurely dropped-off. The study was conducted on an engineering corporate website with the data collected via the Google Analytics tracking tool. The aim was to determine the key hazards that contributed to the observed drop-off rate through the use of a cox proportional hazard model and a survival random forest model. On the studied website, based on empirical evidence, the online visitors were censored so that those who viewed three or more webpages within the visit were labelled as 'survived'. Visitors who viewed two or less webpages before leaving the website were labelled as 'did not survive'. Thereby, the 'did not survive' observations represented the visits that prematurely dropped off the website. Using the visitor's physical and behavioral characteristics, as tracked by Google Analytics, the cox-proportional hazard and survival random forest models were employed to determine the hazards that influence survival. Visitor's physical characteristics include the device used to access the website, geolocation at the time of the visit, number of previous visits, etc., whilst the behavioral characteristics include the landing page on website, level of engagement, whether entry into the website originated through an organic search or not. Whilst both models have identified similar features as being key hazards, the survival random forest model has been shown to out-perform on the non-linear features relative to the cox proportional hazard model and obtained a higher classification accuracy. During the validation process, the survival random forest model (63%) outperformed the cox model (58%) on classification accuracy. The features that were identified as hazardous indicated that some webpages needed further attention, the visitor's level of engagement with the website (the degree of scrolling and clicks), the distance between a visitor's location and the studied corporate's location, the historic frequency of visiting the website, and if the website entry point was through an organic search. Whilst the study of drop-offs has been a commonly researched problem, this study details the investigation of key hazards through the use of survival models and compares the outcomes of a regression-based model to a machine learning survival model. [ABSTRACT FROM AUTHOR]

Health information websites can be useful for information seekers, and their design is crucial for the success of accessing the needed information. While web analytical tools (e.g. Google Analytics) used by such websites can provide descriptive measures of users, there is a disconnection between this data and the current understanding of health information-seeking behaviour. In this work, we leverage a theoretical model to interpret the Google Analytics data. Drawn on the visualisation of user behaviours based on this model, our research shows that better website design can be informed, and the evaluation of health websites can be performed on the basis of different user profiles. [ABSTRACT FROM AUTHOR]

The paper presents the impact of the COVID 19 pandemic on the demand for rental transport services (rent a car) in Romania. With the help of the graphic interface provided by Google Analytics, the data resulted from the traffic analysis of a reference website www.eurocars.ro is obtained, analyzed and compared. The information obtained reflects the global and national trend of losses generated by Covid 19 pandemic. [ABSTRACT FROM AUTHOR]

In recent years, legislatures worldwide have promoted projects for constructing digital humanities systems for parliamentary information. However, studies have yet to perform in-depth investigations on the overall effectiveness of such systems from a user perspective. Therefore, this study used a holistic approach and chose the “Taipei in the Making,” maintained by the Taipei City Council, to evaluate its performance. Specifically, Google Analytics (GA) was used to collect statistics on website use and user participation from 2016 to 2021. A usability assessment questionnaire was distributed randomly to different user groups, including councilors, to perform a usability and satisfaction survey. The results revealed that the website’s user base grew from 2016 and peaked in 2018 but decreased precipitously after 2018, and the returning users only comprised ≈ 25% of users, indicating that user engagement could be enhanced through a strategy such as interface improvements. In addition, the results of the usability assessment among respondents revealed that the satisfaction construct had the highest score, followed by memorability and learnability constructs, indicating that the system can satisfy the respondents’ search for parliamentary information needs. In conclusion, the Taipei City Council and government departments are recommended to combine various assessment methods to devise a holistic approach to develop the system further and facilitate public use of parliamentary information. [ABSTRACT FROM AUTHOR]

The formation of user paths on the way to conversion, customer touch points with the brand, funnel and their evaluation are current issues in the field of marketing. Despite the rapid spread of technology, there are still no general established user guidelines for analyzing the marketing activities of enterprises in combination with the use of analysis tools. The main purpose of this study is the use of analysis tools in working with big data, as well as the ability to evaluate the implementation of tracking the user path from the moment the ad is displayed to the completion of targeted conversions in the final product. The article discusses one of the most advanced analytics systems – Google Analytics, also known as end-to-end analytics, which provides companies with opportunities to conduct basic analysis. Based on this tool, the article carried out work on the implementation of Google Analytics in the «Avtobys» application operating in the field of e-commerce. As a result of the work, unified recommendations for the imple-mentation of an analytics system for applications were developed.Application performance criteria are defined. A model of user behavior in the application was modeled

Users are primarily interested in the comfort of use and the range of map service in terms of its functionalities. Publishers, in turn, monitor usage statistics in order to optimize the operation of their websites based on the analysis of these statistics. This also applies to municipal map apps. The present work’s objective is to analyse the reach and trends in the use of the Internet application presenting the local spatial development plan (eMPZP). The monitoring covered the map service of the Tomice municipality – in the Małopolska Region (Województwo Małopolskie), Wadowice district (Powiat Wadowicki), Poland – which is available on the municipality’s server at the Internet address https://www.tomice.pl/mpzp/. The data was collected in the period from January 1, 2013 to May 1, 2023. Selected website usage indicators were analysed. In a period of just over 10 years, the eMPZP application was displayed 31,713 times, of which 25,009 (78.86%) were unique views. The largest number of users was recorded in Poland, i.e. 13,044 (83.52%); followed by the United States, i.e. 565 (3.62%) and the United Kingdom, i.e. 434 (2.78%). Most users found the eMPZP application using search engines and direct links. In conclusion, it was demonstrated that map service usage statistics could be useful for municipal authorities, as they help to understand how the service is used, by whom it is used, and what the users’ preferences are. In addition, it was shown that eMPZP still fulfils a number of selected functions, despite the fact that in 2019 it was replaced by a geoportal (http://mpzp.tomice.pl). Accordingly, it is recommended that the so-called automatic redirection be set, sending the users to the current geoportal using specific HTML tags. [ABSTRACT FROM AUTHOR]

The presented notes focus partially on two of the basic elements (accessibility and image) of any managed tourism destination from the perspective of basic ETL processes over open and third-party data. The specific case aims to investigate the usability of open government data on occupancy in combination with third-party data on online audiences' engagement for DMOs' potential seasonal geotargeting via utilizing Openrouteservice's APIs. For the pilot case, a Slovak (Central Europe) destination's data on occupancy, and the DMO's website and social media engagement by origin were used to determine potential audiences' accessibility by car. Testing of the pilot results on a sample of foreign markets indicates that by a partial mix of the means of transportation, the vast majority of audiences are within a 4 h long incoming trip. Although the preliminary tests indicate a linear correlation between the destination's occupancy and online audiences' share accessibility by car, for further extrapolation, the list of missing input remains long. The main addition to the field of tourism and destination management may be the partial reusability of developed techniques for data extraction, and transformation for further data overlays, which may save some time. [ABSTRACT FROM AUTHOR]

Goal. To develop a system for monitoring WEB sites based on the research of methods and software tools that are used to raise the position of the site in search engines and increase the visitor rating with the help of SEO optimization. Methodology. The development of the system was based on theoretical and experimental research, which is used to analyze services and programs for promoting the site to the top positions of search engines, professional analysis of parameters, re-engagement of customers and monitoring of sites on the Internet. Results. As a result of the study of site monitoring systems, services and software AddWeb, Google Analytics, Web Position Gold were developed and analyzed. Based on the analysis, certain shortcomings were identified, which prevent a more accurate analysis of the resource. Taking this into account, a monitoring system called "WebMonit" was developed in the form of a website. This system uses a complex method of performance analysis and testing of site accessibility parameters on the Internet, and the developed software modules - scripts make it possible to output results for analysis and resolution of problem detection/This system checks resource elements that are important for search engine optimization. They include, in particular, tags, selection of keywords for which the resource is planned to be promoted, usability, ranking, semantic core of the site, content, user-friendly interface. If these elements are optimized, it is possible to display the resource in the TOP in search engines and the Internet. Scientific novelty. The proposed original solution in the form of a monitoring system that provides the opportunity to display not only the statistics of the site's working condition, but also to find problems and provide advice on their elimination to improve SEO optimization and expansion of functionality in the decisions made. Practical significance. There are many tools for promoting a site on the Internet, each of which is effective in a specific aspect. The work gives comparative characteristics of the use of tools for site promotion, identified advantages and disadvantages of existing systems and developed a monitoring system called "WebMonit" in the form of a website that will improve site monitoring, and developed software modules - scripts will improve site promotion. [ABSTRACT FROM AUTHOR]

Copyright of Zeszyty Studenckie Wydzialu Ekonomicznego Uniwersytetu Gdanskiego "Nasze Studia" is the property of Fundacja Rozwoju Uniwersytetu Gdanskiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

People are increasingly seeking complex health information online. However, how they access this information and how influential it is on their health choices remains poorly understood. Google Analytics (GA) is a widely used web analytics tool and it has been used in academic research to study health information-seeking behaviors. Nevertheless, it is rarely used to study the navigation flows of health websites. To demonstrate the usefulness of GA data, we adopted both top-down and bottom-up approaches to study how web visitors navigate within a website delivering complex health information about stem cell research using GA’s device, traffic and path data. Custom Treemap and Sankey visualizations were used to illustrate the navigation flows extracted from these data in a more understandable manner. Our methodology reveals that different device and traffic types expose dissimilar search approaches. Through the visualizations, popular web pages and content categories frequently browsed together can be identified. Information on a website that is often overlooked but needed by many users can also be discovered. Our proposed method can identify content requiring improvements, enhance usability and guide a design for better addressing the needs of different audiences. This paper has implications for how web designers can use GA to help them determine users’ priorities and behaviors when navigating complex information. It highlights that even where there is complex health information, users may still want more direct and easy-to-understand navigations to retrieve such information.

Objective: Limited knowledge exists regarding the information patients seek online about sinus procedures. The goals of our study were to identify the most searched online queries regarding functional endoscopic sinus surgery (FESS) and balloon sinuplasty and evaluate the sources to which patients are directed. Study Design: Observational. Setting: Online Google Database. Methods: Google data were analyzed using the search engine optimization tool Ahrefs. People Also Ask (PAA) questions (extracted from Google searches) helped identify questions for analysis of search query volume. Search results were categorized into specific topics, and the source (eg, academic vs medical practice) of the information was identified. The JAMA benchmark criteria were used to determine the quality of the online resource. Results: The most searched term (average monthly queries) on Google was "sinus surgery" (13,190), followed by "balloon sinuplasty" (9212). For FESS and balloon sinuplasty, most questions focused on treatment of sinusitis (71.64% vs 79.19%) and preoperative inquiries about sinus issues (11.50% vs 11.35%). Answers to PAA questions for FESS were obtained from academic sources at a higher frequency compared to balloon sinuplasty (26.7% vs 10.3%, P =.016) but a lower frequency from medical practice websites (15.2% vs 29.3%, P =.042). The mean (SD) JAMA scores for FESS and balloon sinuplasty sources were 1.59 (1.46) and 1.40 (1.46), respectively. Conclusion: There is a high volume of online search queries regarding FESS and balloon sinuplasty. The quality of the sources could be improved by addressing authorship, attribution, disclosure, and currency. This information may help otolaryngologists better address patient queries. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Research & Business Administration is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Within the modern era, corporates are compelled to own an appealing and effective website to survive and thrive within the competitive global digital marketplace. Whilst there are several web metrics to focus on, a key focus area of web analytics is the level of drop-offs. The drop-off rate represents the proportion of visitors that prematurely drop-off a website. Whilst the exact reason behind the drop-off may only be assumed (could be due to the loss of Internet connectivity or dis-interest), this study attempted to identify the triggers behind website drop-offs through a survival problem. Each person entering the website, at a given instance, can view any number of web pages (such as home, contact us, about us, etc.). However, on the studied website, roughly one in five visitors have prematurely dropped-off. The study was conducted on an engineering corporate website with the data collected via the Google Analytics tracking tool. The aim was to determine the key hazards that contributed to the observed drop-off rate through the use of a cox proportional hazard model and a survival random forest model. On the studied website, based on empirical evidence, the online visitors were censored so that those who viewed three or more webpages within the visit were labelled as ‘survived’. Visitors who viewed two or less webpages before leaving the website were labelled as ‘did not survive’. Thereby, the ‘did not survive’ observations represented the visits that prematurely dropped off the website. Using the visitor’s physical and behavioral characteristics, as tracked by Google Analytics, the cox-proportional hazard and survival random forest models were employed to determine the hazards that influence survival. Visitor’s physical characteristics include the device used to access the website, geolocation at the time of the visit, number of previous visits, etc., whilst the behavioral characteristics include the landing page on website, level of engagement, whether entry into the website originated through an organic search or not. Whilst both models have identified similar features as being key hazards, the survival random forest model has been shown to out-perform on the non-linear features relative to the cox proportional hazard model and obtained a higher classification accuracy. During the validation process, the survival random forest model (63%) outperformed the cox model (58%) on classification accuracy. The features that were identified as hazardous indicated that some webpages needed further attention, the visitor’s level of engagement with the website (the degree of scrolling and clicks), the distance between a visitor’s location and the studied corporate’s location, the historic frequency of visiting the website, and if the website entry point was through an organic search. Whilst the study of drop-offs has been a commonly researched problem, this study details the investigation of key hazards through the use of survival models and compares the outcomes of a regression-based model to a machine learning survival model.

An essential part of business operation for tourism industry is revenue management, i.e., how to sell the right tour package, to the right customers, at the right time, at the right price through the most appropriate and cost-effective channels. In today's world, the internet has revolutionized many business operations in the tourism industry which plays an important role in Thailand's GDP. Most tour operators utilize websites as the main channel to build relationships with customers. Thus, website performance measurement is an important strategic factor for online marketing. The objectives of this research were to identify factors contributing from Google Analytics metrics to online bookings and to forecast online bookings using those impactful factors. Several machine learning models namely artificial neural network (ANN), support vector regression, and random forest, were proposed to forecast online bookings using the mean absolute percentage error (MAPE) as the criterion for comparison. It was found that there were three Google Analytics metrics that contributed to online bookings, which were the sessions from referral, unique returning users, and the average session duration. In addition, the ANN model provided the highest accuracy result with a MAPE of 11.39%. The framework from this research can be applied to other online companies to forecast their online bookings, which is an important part of revenue management since accurate forecasts can help companies to achieve their goals. [ABSTRACT FROM AUTHOR]

Platform businesses, linking producers and consumers, have emerged as a very important industry. Meanwhile, value co-creation has become one of the critical issues concerning the operation of platform enterprises and the focus of researchers in this area. Platform businesses usually need to strengthen the interactions between all participants to maximize the commercial value. However, the majority of the literature has concentrated on the "platform business–consumer" interaction only, i.e., both "platform business–producer" and "platform producer–consumer" interactions have been almost completely neglected. Consequently, this study aims to fill the research gap by investigating "all-around interactions" and the relationships between the interaction with the value co-creation performance. A holistic framework of the value co-creation cycle is developed and validated. One of the largest platform businesses in Taiwan was examined, and Google Analytics (GA) code was embedded into its information system for data generation. The results confirmed the proposed framework and hypotheses. The study concludes that platform businesses need to gain insight into producers and consumers through data tracking and analysis as well as to provide innovative services that elevate satisfaction, user loyalty, and usage frequency, with a final goal of establishing a cycle of value co-creation. [ABSTRACT FROM AUTHOR]

Background: Parents frequently seek parental advice online and on social media; thus, these channels should be better utilized in child health interventions. The Parents in Child Nutrition Informing Community (PICNIC) program aims to facilitate peer-to-peer sharing of evidence-based child feeding information and support parents within their social networks. The present study aimed to explore web and social media analytics to evaluate reach and user engagement with the PICNIC online components.Methods: Online user activity data from the PICNIC Facebook closed group and public Page were collected through Facebook Insights, and program-specific website traffic data through Google Analytics. Analytics data from Nov-2019 to April-2021 was evaluated through visualisation and summary statistics to obtain insights into program growth and current reach in Australia, compare demographics of audience reached through the online channels, and explore parents' use and engagement in PICNIC content.Results: Results showed steady program growth in the 18 months of recruitment; participant numbers grew from 102 to 261 peer educators while the Facebook Page audience increased threefold, totalling 1615 followers. Intervention posts shared on Facebook (4-5 posts/week) typically reached only a portion of PICNIC Page followers each week, but also reached a wider audience through their friends. Throughout the evaluated period, Facebook users actively engaged in PICNIC posts, although the level of engagement varied considerably from post to post. Furthermore, results from this study suggest the strategy of directing potentially interested parents from social media to the website for program sign-up was successful. Finally, the explored data gave insights into users' availability, demographics and engagement, which will be used to inform refinement of the PICNIC website and social media strategies.Conclusions: Our findings confirm the benefits of using a peer education approach and existing social network channels to disseminate evidence-based child feeding information to parents. This study also demonstrates the usefulness of web and social media analytics to be used as part of a continuous evaluation for gaining insight to inform further development and improvement of program strategies.Trial Registration: The PICNIC project was retrospectively submitted for registration with the Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12622000230752 (09/02/2022). [ABSTRACT FROM AUTHOR]

Background: Information and communication technology (ICT) use may enhance social work practice and continuous professional development. Under the Hong Kong Jockey Club SMART Family-Link Project, we developed an innovative web-based training, learning, and sharing platform (i-TLS) to support not only ICT and other learning needs of Hong Kong social workers but also their practice. Objective: We developed i-TLS with 3 major components (i-Training, i-Learning, and i-Sharing) and assessed its acceptability and impact on facilitating ICT use in family services. Methods: We described the i-TLS development based on a 4-phase model and evaluated i-TLS using the platform database, Google Analytics, a self-administered survey, and individual phone interviews 1 year after launching. Results: i-TLS was launched in 12 nongovernmental organizations on July 1, 2019. The COVID-19 outbreak in December 2019 limited face-to-face services, which galvanized digital transformation in social work practice. By July 31, 2020, 313 social workers had registered with i-TLS. Approximately 79.6% (249/313) of users accessed i-TLS at least once in the past 28 days, averaging 3.2 (SD 1.35) platform visits per day and viewing 4.8 (SD 1.42) pages per visit. i-Training provided 41 mini-modules on applying ICT to family services, with 730 enrollments. Approximately 70% (511/730) of users completed the mini-modules and obtained digital mini-certificates. i-Learning provided 112 items of learning resources centered on ICT use in family services, with nearly 4000 page views. i-Sharing had 25 discussion threads with 59 posts. Approximately 53.7% (168/313) of users completed the 1-year evaluation survey, including 7.1% (12/168) who were phone interviewed. The mean i-TLS satisfaction score (out of 10) increased from light (4.99, SD 1.54) to occasional (6.15, SD 1.34) and frequent (6.31, SD 2.29) users. Frequent users showed higher scores (out of 10) than light users for an increase in knowledge (5.84, SD 1.34 vs 4.09, SD 1.74; P<.001), self-efficacy (5.23, SD 1.92 vs 3.96, SD 1.77; P=.02), and knowledge application (6.46, SD 1.33 vs 1.91, SD 1.40; P<.001). Interviewees reported increased ICT use in services and considered i-TLS an acceptable and supportive tool for learning and practice, especially during the pandemic. Conclusions: i-TLS is acceptable to social workers and enhances their learning and use of ICT in family services. This was achieved through access to self-directed and collaborative learning and sharing of experiences within their practice. Further research on enhancing web-based platforms is needed to expand participation and capacity building among social workers and other health and social care professionals. [ABSTRACT FROM AUTHOR]