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Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

The Polish economy has undergone major challenges and changes over the past few decades. The country's trade flows, in particular, have become more firmly tied to the country’s Western neighbors as they have grown in volume. This study examines Poland's trade balances in ten Standard International Trade Classification (SITC) sectors versus the United States of America, first testing for and isolating structural breaks in each time series. These breaks are then included in a set of the cointegration models to examine their macroeconomic determinants.

Linear and nonlinear and nonlinear autoregressive distributed lag models, both with and without dummies corresponding to structural breaks, are estimated.

One key finding is that incorporating these breaks reduces the significance of the real exchange rate in the model, supporting the hypothesis that this variable already incorporates important information. It also results in weaker evidence for cointegration of all variables in certain sectors.

This study looks only at one pair of countries, without any third-country effects.

An important country pair's trade relations is examined; in addition, the real exchange rate is shown to incorporate economic information that results in structural changes in the economy. The paper extends the existing literature by conducting an analysis of Poland's trade balances with the USA, which have not been studied in such a context so far. A strong point is a broad methodology that lets compare the results the authors obtained with different kinds of models, both linear and nonlinear ones, with and without structural breaks.

This study aims to examine the rationales for and obstacles to developing a national qualifications framework (NQF) in Japan. From a research perspective, it attempts to propose a model of a qualifications framework in the national context to provoke further political discussion in developing the Japanese Qualifications Framework (JQF).

To propose a possible model of a qualifications framework in the Japanese context, this study employs a qualitative document analysis approach to known NQFs. Next, based on documents and the literature, including government data and the United Nations Educational, Scientific and Cultural Organization’s Tokyo Convention (2011a, b), this study analyzes the motives and challenges in developing the JQF.

Japanese motives to develop the JQF can be summarized in four conditions: (a) International expectations along with the Tokyo Convention and establishment of the National Information Center, (b) avoiding qualification holders’ disadvantages in mobility, (c) quality assurance of qualifications with a competence-based approach and (d) lifelong learning by promoting recognition of diverse learning. The challenges in developing the JQF are (a) fitness with the traditional employment system and (b) multiple stakeholders’ involvement. The current priority in developing an NQF in Japan is to make educational qualification information “visible” based on legal grounds, particularly entrance requirements, to facilitate mobility.

This study explores the possibility of the JQF by summarizing the background and roles of NQFs worldwide and clarifying the motives and challenges for developing the JQF. This study provides suggestions for the possible qualifications framework model in the Japanese context from academic and practical perspectives in Japan, where official discussions on establishing an NQF have not progressed. Ensuring the international compatibility of qualifications so that qualification holders can smoothly take the next step in their studies and employment is important.

This article aims to explore the concept of chain value of the public port system in Ecuador from the perspective of importing/exporting companies, analyzing how perceived value in the use of port services affects customer satisfaction and the intermediate links of the influence of trust and commitment on customer loyalty.

Relying on a survey of 634 Ecuadorian companies with experience in international trade as port users and a theoretical framework well-established in the literature on consumer behavior, the empirical study found evidence of a positive and significant relationship with the knowledge of chain effects.

The findings confirm the chain effect and reveal ways to maintain an ongoing satisfactory, trust and committed relationship with users, thereby ultimately gaining and maintaining their loyalty. The conclusions suggest how this postulate can help to close the gap referred to the effective management of port services, and point out that port managers should be concerned with a continuous in-depth understanding of the perceived value and its chain effects.

The authors add evidence of the use of the postulate of the chain of effects on these dimensions, whose applicability is very well established, tested and consensual for the doctrine in industrial marketing. In contrast, it is scarcely present in the port relationship with its users.