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This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

Digital learning systems are crucial for education and data collected can analyse students learning performances to improve support. The purpose of this study is to design and build an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet.

A Learning Box has been build based on minicomputer and a web learning management system (LMS). This study presents different options to create such a system and discusses various approaches for data syncing. The structure of the final setup is a Moodle (Modular Object Oriented Developmental Learning Environment) LMS on a Raspberry Pi which provides a Wi-Fi hotspot. The authors worked with lecturers from X University who work in remote Northern Territory regions to test this and provide feedback. This study also considered suitable data collection and techniques that can be used to analyse the available data to support learning analysis by the staff. This research focuses on building an asynchronous hardware and software system that can store data on a local device until able to share. It was developed for staff and students at university who are using the limited internet access in areas such as remote Northern Territory. This system can asynchronously link the users’ devices and the central server at the university using unstable internet. Digital learning systems are crucial for education, and data collected can analyse students learning performances to improve support.

The resultant system has been tested in various scenarios to ensure it is robust when students’ submissions are collected. Furthermore, issues around student familiarity and ability to use online systems have been considered due to early feedback.

Monitoring asynchronous collaborative learning systems through analytics can assist students learning in their own time. Learning Hubs can be easily set up and maintained using micro-computers now easily available. A phone interface is sufficient for learning when video and audio submissions are supported in the LMS.

This study shows digital learning can be implemented in an offline environment by using a Raspberry Pi as LMS server. Offline collaborative learning in remote communities can be achieved by applying asynchronized data syncing techniques. Also asynchronized data syncing can be reliably achieved by using change logs and incremental syncing technique.

Focus on audio and video submission allows engagement in higher education by students with lower literacy but higher practice skills. Curriculum that clearly supports the level of learning required for a job needs to be developed, and the assumption that literacy is part of the skilled job in the workplace needs to be removed.

To the best of the authors’ knowledge, this is the first remote asynchronous collaborative LMS environment that has been implemented. This provides the hardware and software for opportunities to share learning remotely. Material to support low literacy students is also included.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

Compulsive social media use has the potential to reduce well-being. In this study, the authors propose that there are two main paths to compulsive social media consumption. One is behavioral and based on habit; the other is motivational and rooted in the fear of missing out. This study aims to test the antecedents of these two drivers as well as their consequences for the tendency to engage in compulsive social media consumption.

The authors applied a quantitative research design and collected data through a survey of 600 respondents from a representative sample. The authors used structural equation modeling to test their conceptual model and hypotheses. Gender and age were included as moderators to investigate the model’s boundary conditions.

The authors found support for all the suggested relationships in the conceptual model. The findings indicate two main manifestations of compulsive social media use – always being logged in (i.e. the frequency of social media consumption) and excessive use (the intensity of consumption) – that in turn spurred a reinforcer of compulsivity: disconnection anxiety. The findings also indicate two main paths to compulsive social media consumption. One path is behavioral, based on habit, and the other is motivational, based on fear of missing out. Moreover, the authors identified the key antecedents of both paths. Habit formation was observed to be a function of situational cues (technological nudges in the online sphere) and consumer engagement. Fear of missing out was shaped by both injunctive norms (a consumer norm to be online) and descriptive norms (social proof).

Although the antecedents of compulsive social media consumption suggested in this study have a strong and significant effect, the explained variance in the dependent variables being always logged in and excessive social media use indicates that there might be other drivers as well. These should be explored along with moderators other than gender and age to identify the potential boundary conditions of the model.

The main implications of the present work point to the “ease” with which typical or normal social media use may spiral out of control and become compulsive, with adverse implications for consumer health and well-being.

The behavioral and motivational paths to compulsive social media consumption have been less explored and have not yet been studied in conjunction, nor have their antecedents and consequences. Thus, this is a novel approach to understanding how social media use can potentially lead to reduced control and well-being.

This paper aims to develop a decision support system for predicting the knitting production’s efficiency based on the input parameters of an order. This tool supports the operations managers to make reliable decisions of estimated delivery time, which will result in reducing waste arising from late delivery, overtime and increased labor.

The decision tree method with a set of logical IF-THEN rules is used to determine the knitting production’s efficiency. Each path of the decision tree represents a rule of the following form: “IF <Condition> THEN <Efficiency label>.” Starting with identifying and categorizing input specifications, the model is then applied to the observed data to regenerate the results of efficiency into classification instances.

The production’s efficiency is the result of the interaction between input specifications such as yarn’s component, knitting fabric specifications and machine speed. The rule base is generated through a decision tree built to classify the efficiency into five levels, including very low, low, medium, high and very high. Based on this, production managers can determine the delivery time and schedule the manufacturing planning more accurately. In this research, the correct classification instances, which is simply a ratio of the correctly predicted observations to the total ones, reach 80.17%.

This research proposes a new methodology for estimating the efficiency of weft knitting production based on a decision tree method with an application of real data. This model supports the decision-making process of the estimated delivery time.

This study aims to examine the impact of signaling through social media (SM) on funding achieved by start-ups.

This study follows a causal research design and is based on unique data set compiled from Crunchbase-Pro and Twitter. The sample size is 1,672 Indian start-ups. Heckman’s model and ordinary least squares regression is used to test the hypothesis.

Devising a thoughtful SM strategy, should be an integral part of the overall strategy of the start-ups looking out for funds. LinkedIn presence is in itself a positive signal. Active usage of Twitter and feedback from other Twitter users has a positive impact on funds raised by the start-up. Posting retweets and repetitive usage of URLs and media is not a predictor of funds raised by the start-up.

An early-stage strategy on SM adoption, especially Twitter can play an important role in attracting interest and attention of stakeholders. To capitalize SM, entrepreneurs should maintain an active SM account of the start-up.

India has emerged as one of the start-up hubs of the world. However, there is a dearth of literature on SM usage by start-ups in India. To the best of the authors’ knowledge, this study is first of its kind and establishes the results empirically based on more than 100k tweets for a large pool of Indian start-ups.

The purpose of this research is to explore and explain education management information system (EMIS) post-adoption in the context of mandatory settings, focusing on perceived benefits and individual and institutional post-adoption usage.

To fulfill the research objectives, the study proposes a conceptual model grounded in the technology acceptance model (TAM) and the technology-organization-environment (TOE) framework. Data for model validation were obtained via a questionnaire and were collected from 144 teachers in public primary schools in the Republic of North Macedonia. For statistical analysis, PLS-SEM was used.

Based on the conducted statistical analysis, it is found that in mandatory environments, perceived ease of use, perceived usefulness, compatibility, complexity and governmental support are the factors that have indirect effects on the post-adoption usage, and only the factors, technological knowledge and external information and communication technology (ICT) support, have direct effects on the post-adoption usage. The individual post-adoption usage in mandatory settings depends on whether benefits are perceived in the course of EMIS usage; they become a central factor due to the accumulated knowledge and experience.

The main contribution of this study is to theoretically and empirically discover the most important factors that influence EMIS post-adoption usage. Perceived benefits are considered as external factors to the TOE framework and mediate the effect of TAM-TOE factors on individual post-adoption usage.

Online news websites provide huge amounts of timely news, bringing the challenge of recommending personalized news articles. Generative adversarial networks (GAN) based on collaborative filtering (CFGAN) can achieve effective recommendation quality. However, CFGAN ignores item contents, which contain more latent preference features than just user ratings. It is important to consider both ratings and item contents in making preference predictions. This study aims to improve news recommendation by proposing a GAN-based news recommendation model considering both ratings (implicit feedback) and the latent features of news content.

The collaborative topic modeling (CTM) can improve user preference prediction by combining matrix factorization (MF) with latent topics of item content derived from latent topic modeling. This study proposes a novel hybrid news recommendation model, Hybrid-CFGAN, which modifies the architecture of the CFGAN model with enhanced preference learning from the CTM. The proposed Hybrid-CFGAN model contains parallel neural networks – original rating-based preference learning and CTM-based preference learning, which consider both ratings and news content with user preferences derived from the CTM model. A tunable parameter is used to adjust the weights of the two preference learnings, while concatenating the preference outputs of the two parallel neural networks.

This study uses the dataset collected from an online news website, NiusNews, to conduct an experimental evaluation. The results show that the proposed Hybrid-CFGAN model can achieve better performance than the state-of-the-art GAN-based recommendation methods. The proposed novel Hybrid-CFGAN model can enhance existing GAN-based recommendation and increase the performance of preference predictions on textual content such as news articles.

As the existing CFGAN model does not consider content information and solely relies on history logs, it may not be effective in recommending news articles. Our proposed Hybrid-CFGAN model modified the architecture of the CFGAN generator by adding a parallel neural network to gain the relevant information from news content and user preferences derived from the CTM model. The novel idea of adjusting the preference learning from two parallel neural networks – original rating-based preference learning and CTM-based preference learning – contributes to improve the recommendation quality of the proposed model by considering both ratings and latent preferences derived from item contents. The proposed novel recommendation model can improve news recommendation, thereby increasing the commercial value of news media platforms.

Usage of learning management systems (LMSs) has become widespread with the disruption of face-to-face educations after the COVID-19 pandemic. There are several software products, usually named as LMS to enable and support distance education. However, selection of a suitable LMS is a complex multiple criteria decision making (MCDM) problem that requires consideration of many criteria and inputs from different parties like students, academicians, education managers, etc. Usability evaluation of LMS is one of the critical steps in deciding which LMS system to be adapted. There are several studies related to usability evaluation of LMS in the literature, but utilization of MCDM methods and real life case studies are very rare. Based on this motivation, perceived usability evaluation of SAKAI-LMS that is in use at an academic department is performed by employing axiomatic design procedure (ADP). This paper aims to discuss the aforementioned issues.

ADP is considered as a suitable MCDM method for perceived usability evaluation as it allows an easy approach to data fusion and setting performance targets for decision makers. A questionnaire is developed to collect data from three types of system users about predetermined usability criteria and their importance. After detailed statistical analyses and weighting criteria via analytical hierarch process (AHP), ADP is carried out to evaluate usability of the LMS.

It is found that the proposed ADP based approach is easy to apply in practical circumstances and able to quantify perceived usability of the LMSs.

The proposed approach provides an easy and practical evaluation of perceived usability of the LMSs for decision makers who are responsible for the implementation of LMSs. The developed novel and practical MCDM-based perceived usability approach for LMS in this study has been verified through a real life case study at an academic department. Perceived usability results, therefore, reflects only the views of this focus group and are not generalizable.

First time in the literature, a comprehensive ADP based MCDM approach is proposed based on the analyses of the related literature and information gathered from the system users.

This paper aims to study the dimensions and subdimensions of humanitarian supply chain resilience through the case of an non-governmental organization (NGO) logistics organization facing the international COVID-19 pandemic.

The methodology of this empirical research paper is based on a qualitative study using semistructured interviews with key actors of the Médecins Sans Frontières Logistique (MSF Log), NGO during the COVID-19 crisis in 2020 and 2021.

The data analysis highlighted four main dimensions of humanitarian supply chain resilience: organizational capacity, collaboration, flexibility and humanitarian culture. The transversal importance of the information system and that of the humanitarian culture were also pointed out. Furthermore, the authors have identified the subdimensions of each dimension; these subdimensions further elaborate the main dimension and provide a more detailed understanding of the concept. These dimensions require both proactive and reactive actions to be effective. Finally, based on these empirical results, a conceptual model of humanitarian supply chain resilience is proposed.

Additionally, further research can be done to explore the impact of digital technologies on the humanitarian supply chain resilience and how these technologies can be used to improve the resilience of humanitarian supply chains. Additionally, future research can also be conducted to explore how to measure the resilience of humanitarian supply chains and how to develop methods to improve the resilience of these supply chains.

The dimensions and subdimensions of resilience that have been highlighted may provide a guide for managers to target their actions, both responsively and proactively, to act on resilience over time when facing a crisis such as an international pandemic.

The value of this research is linked to the findings that result not only from literature about resilience but are also founded on an empirical and qualitative study of an NGO logistics organization facing an international crisis. The research provides an in-depth understanding of the practical application of supply chain resilience in a humanitarian context and the specific challenges and opportunities that arose during the COVID-19 pandemic for MSF Log. It also highlights the importance of information systems and humanitarian culture in maintaining the supply chain resilience. The findings of this research can be used as a guide for other humanitarian organizations to improve their supply chain resilience in times of crisis.