Institutional Repository of Academic Research University of Macedonia
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2215 research outputs found
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The role of organisational culture in total quality management adoption and cost of quality
No full textOrganisational Culture (OC) is related to the implementation of TQM, while both are associated with the economic aspect of TQM meaning the Cost of Quality (CoQ). The present study aims to investigate the impact of different types of OC, namely group, developmental, rational and hierarchical culture on TQM and CoQ. Moreover, the study aims at determining the impact of TQM on CoC and CoNC. Greek manufacturing and service companies were approached through a structured questionnaire and 292 participated in the study. Confirmatory Factor Analysis was applied to examine the reliability and validity of latent constructs, the relationships of which were determined through Multiple Linear Regression analyses. According to the findings, all the cultural types have a positive impact on TQM. TQM has a significant and positive impact on CoC and a negative influence on CoNC. Finally, CoC is significantly influenced by two types of OC (developmental culture and hierarchical culture), while CoNC is directly affected only by rational culture. This study offers clear implications for managers who want to fully adopt TQM and improve CoQ by reinforcing specific OC types. To the best of the authors’ knowledge, no previous research has discussed these relationships in the Greek business environment.3315-161718173
Time Series Forecasting of Software Vulnerabilities Using Statistical and Deep Learning Models
No full textSoftware security is a critical aspect of modern software products. The vulnerabilities that reside in their source code could become a major weakness for enterprises that build or utilize these products, as their exploitation could lead to devastating financial consequences. Therefore, the development of mechanisms capable of identifying and discovering software vulnerabilities has recently attracted the interest of the research community. Besides the studies that examine software attributes in order to predict the existence of vulnerabilities in software components, there are also studies that attempt to predict the future number of vulnerabilities based on the already reported vulnerabilities of a project. In this paper, the evolution of vulnerabilities in a horizon of up to 24 months ahead is predicted using a univariate time series forecasting approach. Both statistical and deep learning models are developed and compared based on security data coming from five popular software projects. In contrast to related literature, the results indicate that the capacity of Deep Learning and statistical models in forecasting the evolution of software vulnerabilities, as well as the selection of the best-performing model, depends on the respective software project. In some cases, statistical models provided better accuracy, whereas in other cases, Deep Learning models demonstrated better predictive power. However, the difference in their performance was not found to be statistically significant. In general, the two model categories produced similar forecasts for the number of vulnerabilities expected in the future, without significant diversities.1118282
University Lifelong Learning Programs and Perceived Employability: The Case of Aristotle University of Thessaloniki
No full textThis qualitative research explores the impact of university lifelong learning programs on the participants’ perceived employability by examining six training programs implemented by the Lifelong Learning Center of Aristotle University of Thessaloniki. The grounded theory approach was used throughout the research. After a set of data were gathered through face-to-face interviews with the programs’ directors, 21 semistructured interviews were conducted with people who attended the programs. Through a process of data coding and analysis, a theoretical model was developed. The findings indicated that the programs examined enhanced the three dimensions of the participants’ perceived employability (career identity, personal adaptability, and human and social capital). Moreover, the interviewees emphasized that universities should strengthen their links with the labor market and the local society, to meet the needs of a larger number of citizens.721658
User-Generated Content behavior and digital tourism services: A SEM-neural network model for information trust in social networking sites
No full textSocial media and User-Generated Content contribute to the hospitality sector. Consumers usually post reviews, suggestions, or judgements on hotel booking websites regarding their accommodation during their travel and afterward. This article investigates the determinants that affect users’ trust in shared information related to travel acquired from social media or tourism sites. Data was obtained from 266 SNS users. Data was analyzed using both the Structural Equation Model (SEM) and the neural network model. Results show that perceived enjoyment and perceived value were the most critical factors that affected SNS users’ trust in the shared information about travel from social media or tourism sites. This paper provides valuable insight into travelers’ behavior and managerial implications of sharing information from SNS. From SNS, tourism managers should increase the delightful and fulfilling features of their websites to gain more shared information about travel.2110005
Α path to our heart: Visual metaphors and "white" space in advertising aesthetic pleasure
No full textContemporary advertising is increasingly based upon the successful implementation of two creative design tools, visual metaphors, and "white" space. Yet, despite their established coexistence, there is not enough evidence on the mechanism that takes place to affect consumers’ attitude toward the ad (Aad). The present study builds on the scarce evidence on the combination of visual metaphors with "white" space to decipher the role of "white" space on the effectiveness of metaphoric advertising. A content analysis of 405 international print ads establishes the widespread use of visual metaphors (fusions) with extended "white" space (monochrome, in shades of grey). Based on Berlyne’s theory of aesthetic preference this study proposes a serial mediation model with novelty, arousal, aesthetic response, and pleasure as successive mediating factors on the impact of visual metaphors (and especially visual metaphors with "white" space) on Aad. Three between-subjects (two with a Greek sample and one with U.S. and U.K. sample) experiments provide solid evidence in support of the proposed model. The attested sequence of effects fire starts a discussion on the significant creative opportunities and the associated communication implications for both academics and practitioners.41473177
Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score
No full text(1) Background: Length of stay (LOS) has been suggested as a marker of the effectiveness of short-term care. Artificial Intelligence (AI) technologies could help monitor hospital stays. We developed an AI-based novel predictive LOS score for advanced-stage high-grade serous ovarian cancer (HGSOC) patients following cytoreductive surgery and refined factors significantly affecting LOS. (2) Methods: Machine learning and deep learning methods using artificial neural networks (ANN) were used together with conventional logistic regression to predict continuous and binary LOS outcomes for HGSOC patients. The models were evaluated in a post-hoc internal validation set and a Graphical User Interface (GUI) was developed to demonstrate the clinical feasibility of sophisticated LOS predictions. (3) Results: For binary LOS predictions at differential time points, the accuracy ranged between 70–98%. Feature selection identified surgical complexity, pre-surgery albumin, blood loss, operative time, bowel resection with stoma formation, and severe postoperative complications (CD3–5) as independent LOS predictors. For the GUI numerical LOS score, the ANN model was a good estimator for the standard deviation of the LOS distribution by ± two days. (4) Conclusions: We demonstrated the development and application of both quantitative and qualitative AI models to predict LOS in advanced-stage EOC patients following their cytoreduction. Accurate identification of potentially modifiable factors delaying hospital discharge can further inform services performing root cause analysis of LOS.29129088910
The impact of bank ownership on lending behavior: Evidence from the 2008–2009 financial crisis
No full textThis paper investigates the lending behavior of banks with different ownership types (domestic-private, foreign, and government-owned) during normal and financial crisis periods. Using panel data for the period 2004–2013, our results indicate that the 2008–2009 crisis caused a negative shock to banking sector loan growth rates which was considerably higher during 2008 compared to 2009. Although loan supply decreased during the crisis, there were differences under different ownership types and between high and upper-middle income countries. Our findings suggest that consumer and retail loans declined significantly more in high income economies compared to upper-middle income countries. Further, in upper-middle income economies, the reduction in consumer and retail loans in 2009 was higher under foreign bank ownership in comparison to domestic-private bank ownership. Overall, the results indicate that the lending behavior of banks with different types of ownership is significantly different in upper middle income countries compared to high-income countries.2722006202
The north-south divide, the euro and the world
No full textThe European north–south divide has been an issue of a long-standing debate. We employ a Global VAR model for 28 developed and developing countries to examine the interaction between the global trade imbalances and their impact within the euro-area framework. The aim is to assess the propagation mechanisms of real shocks, focusing on the interconnections among the north euro area and the south euro area. We incorporate theory-based long-run over-identifying restrictions and examine the effects of (i) non-export real output shocks, (ii) expansionary shocks and (iii) real exchange rate shocks. An expansionary policy of the north euro area and increased competitiveness in the south euro area could alleviate trade imbalances of the debtor euro area economies. From the south euro area perspective, internal devaluation decreases output but at the same time, it also reduces current account deficits. North euro area origin shocks to domestic output exert a dominant influence in the rest of the Europe and Asia.12110251
Theory Generation from Literature Reviews: A Methodological Guidance
No full textThis article aims to assist researchers in navigating the path to theory creation by investigating how they might build theory through literature reviews. In particular, we propose and elaborate upon the Theory Generation from Literature Review (TGLR) process, capturing different methods and techniques to be applied depending on the level of development and saturation characterizing the focal area of inquiry. In the second part of the article, we briefly present the 21 articles conducting systematic literature reviews on consumer research topics selected for this special issue in IJCS.4651505151
Unemployment claims during COVID-19 and economic support measures in the U.S
No full textGovernments want to know how effective COVID-19 anti-contagion policies and implemented economic stimulus measures have been to plan their short-run interventions. We condition on the state of the pandemic to assess the impact of non-pharmaceutical interventions and economic stimulus policies on the excess unemployment insurance claims in the United States. We focus on weekly data between February 2020 and January 2021 and motivate our analysis by the theoretical framework of the second-wave SIR-macro type models to build a panel Vector AutoRegressive (VAR) specification. Non-pharmaceutical interventions become effective immediately and impact the labor market negatively. Economic stimulus takes about a month to turn effective and only partially eases the economic welfare losses. Health-related restrictive measures are primarily driven by the state of the pandemic. Economic support policies depend predominantly on the reaction of the labor market rather than the severity of the pandemic itself.11310589