Hasil untuk "Business"

Danny Miller, Isabelle Le Breton-Miller

Majed A. Al-Mashari, Abdullah S. Al-Mudimigh, M. Zairi

Philip Scranton, A. Chandler

R. Gordon, J. E. Howell

N. Holmes

Edo Roos Lindgreen

Het is niet nodig om in dit voorwoord te vermelden dat de wereld sterk in beweging is. Als MAB-lezer heeft u genoeg informatiebronnen tot uw beschikking, en uiteraard uw eigen observaties, die de enorme veranderlijkheid en soms schokkende absurditeit van onze wereld in het huidige tijdperk elke dag weer bevestigen. Wel is het goed om stil te staan bij de impact van deze veranderlijkheid op onze bedrijven en instellingen, onze verdienmodellen, onze medewerkers, op alle stakeholders – en dus ook op internal audit. Voor u ligt het derde special issue van het MAB met internal audit als thema. Bij de vorige editie – een speciale uitgebreide uitgave in 2022 ter gelegenheid van het 25-jarig bestaan van het Institute of Internal Auditors (IIA) in Nederland – was het thema ‘nieuwe blikken’. Dat waarderen we in deze editie graag op naar: nieuwe perspectieven. Evenals bij de vorige editie heeft de redactie zich ook nu ten doel gesteld om internal auditors en andere belangstellenden te inspireren met vernieuwende bijdragen van binnen en buiten het vakgebied. Frans Eusman, John Bendermacher en ondergetekende bijten het spits af met een opiniërend artikel, getiteld “Internal audit als witte zwaan”, over de positie van internal audit in de turbulente jaren die voor ons liggen. Wat kunnen organisaties doen om deze turbulentie niet alleen te doorstaan, maar ook om te zetten in strategisch voordeel? En wat is een mogelijke rol van internal audit daarbij? In hun bijdrage “Technology and internal auditing: An overview of performance effects” adresseren Marc Eulerich, Anna Eulerich en Annika Bonrath de inzet van technologieën als data-analyse, AI en RPA in het auditproces. De auteurs gaan daarbij in op de relatie met de New Global Internal Audit Standards van het IIA; zij beschrijven hoe de inbedding van nieuwe technologieën in het auditproces de ‘performance’ kan verhogen en belichten de uitdagingen die dat met zich meebrengt. Svetlana Vrubleuskaya en Evelyn Bell beschrijven in hun boeiende bijdrage “Criminologische inzichten voor internal auditors: een multidisciplinaire benadering van afwijkend gedrag” een onderzoek naar de wijze waarop criminologische theorieën internal auditors kunnen helpen bij het begrijpen en aanpakken van mogelijke oorzaken van afwijkend gedrag binnen organisaties. Hierbij staat niet de inbreukmaker centraal, maar de omgevingsfactoren in de organisatie die invloed hebben op zijn of haar gedrag. Complexe systemen trekken de laatste jaren sterk de aandacht in uiteenlopende disciplines zoals biologie, planologie en organisatieleer. Complexe systemen zijn systemen en processen waarbij de samenstellende entiteiten op ingewikkelde manieren met elkaar interacteren en die onder meer gekenmerkt worden door niet-lineair gedrag, onvoorspelbaarheid en schaalinvariantie. Ook internal auditors zijn geïnteresseerd in complexe systemen, en in deze editie vindt u hierover twee bijdragen. In het artikel “Responsief Auditen: over de wenselijkheid en toegevoegde waarde bij complexe vraagstukken”, een pakkende bewerking van zijn referaat bij de Post-master opleiding Internal Audit & Advisory aan de Erasmus Universiteit Rotterdam, gaat Frank Schuiten in op responsief auditen; een nieuwe auditaanpak die is gestoeld op constructionistische uitgangspunten, waarin verhalen en onderlinge dialoog kernconcepten zijn. Peter Hartog, Paul Hamaker en ondergetekende betogen in de bijdrage “Internal audit and complex systems: emerging approaches” dat nagenoeg elk auditobject moet worden beschouwd als een complex systeem, of een onderdeel daarvan, en dat de Internal Audit Function (IAF) haar auditaanpak daarop zou moeten aanpassen; een traditionele reductionistische auditaanpak kan leiden tot een verlies aan informatie, en daarmee tot minder goede beslissingen door stakeholders. De auteurs presenteren de contouren van een nieuwe aanpak, mede gebaseerd op het Cynefinraamwerk. De stormachtige opkomst van AI, ingezet met de introductie van ChatGPT, nu bijna drie jaar geleden, biedt organisaties enorme kansen, maar brengt zoals altijd ook risico’s met zich mee. Ook hierover twee bijdragen. Kunter Orpak beschrijft in zijn artikel “Generative AI and cybersecurity: Exploring opportunities and threats at their intersection” hoe AI wordt ingezet door aanvallers én verdedigers in de wereld van cybersecurity. Hackers, steeds vaker aangestuurd door statelijke actoren, weten goed gebruik te maken van AI-technologie; cybersecurityteams zetten AI in bij het analyseren van dreigingen, het detecteren van aanvallen en het formuleren en executeren van een passende respons. Vincent Damen, Menno Wiersma, Gokce Aydin en Rens van Haasteren gaan in op de impact van de nieuwe Europese AI Act. Wat betekent deze regelgeving voor onze organisaties, hoe kan compliance worden gewaarborgd, wat is de rol van internal audit daarbij, en hoe kan Explainable AI een bijdrage leveren aan compliance? Het antwoord vindt u in de bijdrage “Explainable AI for EU AI Act Compliance Audits”. Ten slotte een belangwekkend paper over een thema dat het afgelopen jaar wellicht door de Omnibus directive wat op de achtergrond lijkt geraakt, maar niets aan relevantie heeft ingeboet: duurzaamheid. In hun bijdrage “Internal Audit’s Strategic Role in Sustainability and ESG Transformation” pleiten Rob de Leeuw en Arjan de Draaijer voor een intensieve en meer strategische rol van internal audit. Wij hopen met deze artikelen een bijdrage te leveren aan de verdere ontwikkeling van het prachtige vakgebied internal auditing en wensen u veel leesplezier. Mede namens Peter Hartog, Barbara Majoor en Annemarie Oord, Edo Roos Lindgreen, Redacteur van dit special issue

Yang Sun, Feng Zhao, Liya Gao

The accelerating emissions of greenhouse gases—particularly carbon dioxide (CO2)—pose serious challenges to global environmental sustainability, with China being a major contributor due to its rapid economic and financial expansion. This study investigates the nexus between financial development (FD), renewable energy consumption, and CO2 emissions in China over the period 1996–2022. Using advanced time-series econometric methods, including dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), canonical cointegration regression (CCR), and Granger causality analysis, this study aims to uncover the long-run relationships and causal directions among economic growth, financial development, renewable energy use, human capital, agricultural productivity, and carbon emissions (CEs). The findings reveal five key results: (1) economic growth is positively associated with CO2 emissions, confirming an environmental trade-off; (2) financial development also significantly increases emissions, indicating potential ecological risks from financial sector expansion; (3) renewable energy consumption significantly reduces CO2 emissions, confirming its role in promoting environmental quality; (4) human capital and agricultural productivity both contribute to emission reduction; and (5) causality tests show unidirectional and bidirectional relationships among variables, highlighting the interdependence of energy, finance, and environmental dynamics. The study concludes that China can reduce carbon emissions without compromising economic growth by accelerating renewable energy adoption, investing in green technologies, and promoting sustainable agricultural practices through targeted environmental and economic policies.

Michelle Cherfane, Michelle Cherfane, Michelle Cherfane et al.

ObjectivesThis study evaluates the effectiveness of a brief, culturally tailored educational video in improving stroke-related knowledge among residents of the United Arab Emirates (UAE).MethodsA pre-post intervention study was conducted with 407 UAE residents aged 25 years and older. Participants viewed a 3-min educational video addressing stroke symptoms, risk factors, and preventive strategies. Stroke knowledge was measured using a structured questionnaire immediately before and after the video. Statistical analyses included paired t-tests, repeated measures ANOVA, and linear regression models.ResultsStroke knowledge significantly increased following the intervention (mean score: 20.80 pre-test to 23.53 post-test; p < 0.001), with notable improvements in identifying symptoms and risk factors. Regression analyses indicated that female gender, higher education, and healthy lifestyle practices positively influenced knowledge gains, whereas older age was associated with smaller improvements.ConclusionA brief, culturally relevant audiovisual intervention effectively enhances stroke-related knowledge. Such scalable educational tools should be integrated into global public health strategies to promote earlier stroke recognition and intervention.

O. V. Shcherbakova

The subject. Economic, technological and geopolitical changes are leading to the digitalization of virtually all structures of the labor market: from the process of production and human resources management to the organization of the workplace. The use of new digital technologies makes it possible to give up routine human labor, contribute to improving the quality of working life of employees and employers, and increase industrial production, which means economic growth of the state. Thus, in accordance with the National Security Strategy, approved by the Decree of the President of the Russian Federation dated July 2, 2021 No. 400, the situation in the production industry is one of the key criteria of Russia's competitiveness and contributes to the strengthening of the state's defense capability. Ensuring Russia's independence  and competitiveness was also announced to be the main goal of the Strategy for Scientific and Technological Development of the Russian Federation, approved by Presidential Decree No. 642 dated December 1, 2016. On the other hand, the use of new technologies may have time-delayed risks. The most important risk today is the increasing release of labor force and mass cuts of jobs requiring average qualifications, as well as dismissal of employees due to failure to pass tests because of the lack of skills in digital tools.The purpose of the study was to substantiate the urgent character of the implementation of digital profile programs as a part of the employer's personnel policy to achieve the objectives set in the National Security Strategy of the Russian Federation dated 2021.The methodology of comprehensive research, including methods of document analysis, comparative analysis, secondary use of sociological and economic data were used.Main results. The study shows that the use of the employee digital profile programs will allow the employer to identify weaknesses in any of the employee’s skills well in advance, and to pave individual learning pathway, based on his/her preferences, hobbies  and intentions, in order to upgrade the skills. It is deemed that the competence of employees is a factor for transfer of any business to digitalization. This policy of the employer will allow to cover for low-quality job cut and give personnel the minimum knowledge that makes it possible to acquire information on modern information technologies, be able to use it to solve the set problems and have necessary skills and technology, which will facilitate solution of the problems. Ultimately, these are tools to achieve the tasks set by the state in the framework of the state's defensive capability and competitiveness. At the same time, the lack of normative methodologies for the creation and operation of employee digital profiles and comprehensive scientific research predetermine increasing risks of violation of personal data of employees, privacy of employees, as well as discrimination in making legally significant decisions. Today there are no normative standards of data processing and system interaction, which leads to the diminution of guarantees of employees' rights in terms of respect for personal data and other data in terms of classified information.

M. Velasquez

Nofi Tri Wijayanti, Rifda Nabila

This research adopts a quantitative research type in analyzing the influence of integrated marketing communication, Islamic service quality and complaint handling on customer loyalty with customer satisfaction as an intervening variable. The population in this study were all customers of the State Savings Bank (BTN) Syariah KCP Ungaran. In determining the sample, the researcher used purposive sampling techniques and the Lemeshow formula to determine the sample size so that 100 respondents were obtained.  In testing the hypothesis, this research applies multiple linear regression analysis and path analysis using SPSS 23 software. Based on the results of the hypothesis test, integrated marketing communication has a negative effect on customer loyalty. Islamic service quality has no effect on customer loyalty. Complaint handling has a positive effect on customer loyalty. Integrated marketing communication has no effect on customer satisfaction. Islamic service quality has a positive effect on customer satisfaction. Complaint handling has a positive and significant effect on customer satisfaction. Customer satisfaction has a positive effect on customer loyalty. Customer satisfaction is unable to mediate the influence of integrated marketing communication on customer loyalty. Customer satisfaction is able to mediate the influence of Islamic service quality on customer loyalty. Customer satisfaction is unable to mediate the influence of integrated marketing communication on customer loyalty.

Jasman Pardede, Desita Nurrohmah

Background: Hepatitis is a contagious inflammatory disease of the liver and is a public health problem because it is easily transmitted. The main factors causing hepatitis are viral infections, disease complications, alcohol, autoimmune diseases, and drug effects. Some hepatitis variants such as B, C, and D can also cause liver cancer if left untreated. Objective: This research aims to determine the effect of Backward Elimination feature selection on the performance of hepatitis disease identification compared to cases where Backward Elimination is not applied. Methods: XGBoost classification, capable of handling machine learning problems, was utilized. Additionally, Backward Elimination was used as a featured selection to increase accuracy by reducing the number of less important features in the data classification process. Results: The results for training XGBoost model with Backward Elimination, and applying Random Search for hyperparameter optimization, achieved an accuracy of 98.958% at 0.64 seconds. This performance was better than using Bayesian search, which produced the same accuracy of 98.958% but required a longer training time of 0.70 seconds. Conclusion: The use of features obtained from Backward Elimination process as well as the use of feature average values for missing value treatment, produced an accuracy of 98.958%.the precision in training XGBoost model with hyperparameter Bayesian search achieved accuracy, recall, and F1 score of 98.934%, 98.934%, and 98.934%, respectively. Consequently, the use of Backward Elimination in XGBoost model led to faster training, improved accuracy, and decreased overfitting.   Keywords: Hepatitis, Backward Elimination, XGBoost, Bayesian Search, Random Search

Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh et al.

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily life monitoring, assisting workers during industry manufacturing, caring for the elderly. Computer vision-based activity recognition is challenging due to problems such as partial occlusion, background clutter, appearance, lighting, viewpoint, and changes in scale. Our research aims to detect human kinematic motions such as walking or running using smartphones’ sensor data within a high-performance framework. An existing dataset based on smartphones’ gyroscope and accelerometer sensor values is utilized for the experiments in our study. Sensor exploratory data analysis was conducted in order to identify valuable patterns and insights from sensor values. The six hyperparameters, tunned artificial indigence-based machine learning, and deep learning techniques were applied for comparison. Extensive experimentation showed that the ensemble learning-based novel ERD (ensemble random forest decision tree) method outperformed other state-of-the-art studies with high-performance accuracy scores. The proposed ERD method combines the random forest and decision tree models, which achieved a 99% classification accuracy score. The proposed method was successfully validated with the k-fold cross-validation approach.

B. Mintz, M. Schwartz

Yong Liu, Hongxiao Su, Jianping Gu et al.

Industrial activity is widely regarded as one of the important sources of air pollution. However, existing studies still debate the complex effects of industrial patterns on air pollution. This study proposes a multidimensional framework to explore the multiple effects of industrial enterprises on the air quality index in China. We examine the industrial core-edge, structure, and technology effects on air pollution by using spatial Durbin models based on geospatial databases. Results show that industrial core agglomeration exerts a spatial spillover effect on air pollution, especially continuous pollution. The increasing industrial scale and diversity intensify air pollution, reflecting the structure effect. Enterprises with long business lifespans are conducive to mitigating air pollution through the technical alleviation effect. The high ratio of state-owned enterprises exacerbates air pollution in northern China. The industrial spatial spillover effect contributed remarkably to air pollution, calling for cross-regional and intergovernmental collaboration on air quality improvement.

L. Gaskill, Howard E. Van Auken, R. Manning

R. Whitley

C. Burnside, M. Eichenbaum, Sergio Rebelo

R. Solomon

J. Boatright