As the consumer market changes rapidly, retail networks require a system to optimize the quantity and assortment of goods. The authors develop and test theoretical and practical assortment optimization and distribution principles. The study aims to improve retail assortment management by...

Background: The significant increase in home healthcare (HHC) driven by technological advancements, an ageing population, and heightened disease outbreaks-especially evident during the COVID-19 pandemic-has created an urgent need for improved medical waste management. Methods: This paper...

The Internet of Things (IoT) has attracted the attention of researchers and practitioners in supply chains and logistics (LSCs). IoT improves the monitoring, controlling, optimizing, and planning of LSCs. Several researchers have reviewed the IoT-based LSCs publications indexed by academic...

Multi-criteria decision analysis (MCDA) is well suited to address complex public policy problems but could benefit from new tools to involve many laypeople. Online information on specialized topics could be more engaging by including game elements. This paper reports an experiment that assessed...

The paper describes the marketing mix modeling results for companies in nonfood retailing. The main objectives of the research are to demonstrate the viable way of making effective recommendations for optimizing the media strategy by modeling offline and online traffic to the stores based on...

Business analytics is a balanced mix of art and science, where methods form the structure, and visualization breathes meaning and creativity into it. The key to success in problem-solving lies in the art of asking the right questions. Successful problem-solving combines curiosity and courage to...

This study aims to expand the application of the multi-criteria decision-making (MCDM) technique based on expanded information on the alternatives from sub-alternatives. For this purpose, some initial information is collected at the sub-alternative level. Then, based on the scores obtained for...

The increasing use of intelligent data processing and its capacity to handle vast data sets enhance efficiency and effectiveness in production management. Consequently, machine learning models have become essential for decision-making in this domain. Previous literature reviews have not...

The growing adoption of renewable energy, particularly photovoltaic (PV) solar systems, has led to the development of numerous simulation software tools to simplify system design, analysis, and optimization. This study evaluates five widely used PV simulation software packages-SAM, PVsyst,...

Background: The global climate crisis has intensified the demand for sustainable solutions, positioning Reverse Logistics (RL) as a critical strategy for minimizing environmental impacts. Simultaneously, Industry 4.0 technologies are transforming RL operations by enhancing their collection,...

The digitisation of seaports has brought about a significant improvement in efficiency, productivity, and communication within the maritime industry. However, the increasing reliance on technology exposes seaports to cyber threats, constituting significant risk to the economy and national...

This study integrates the House of Risk (HOR) approach with the Fuzzy Inference System (FIS) to manage supply chain risks in steel fabrication by addressing market uncertainties and operational challenges to enhance stability and productivity. The study begins with risk identification using HOR...

This large-scale study assesses the impact of human oversight on countering discrimination in AI aided decision-making for sensitive tasks. We use a mixed research method approach, in a sequential explanatory design whereby a quantitative experiment with HR and banking professionals in Italy and...

This study addresses the vast amount of information held by the banking sector, especially regarding opportunities in tourism development, production, and large residential projects. With advancements in information technology and databases, data mining has become essential for banks to...

Vor dem Hintergrund zunehmender regulatorischer Anforderungen im Bereich der Energie- und Klimapolitik, aber auch vor dem Hintergrund steigender Energiepreise gewinnen Energiemanagementsysteme und Emissionsbilanzierungssysteme auch für kleine und mittelgroße Handwerksbetriebe an Bedeutung. Der...

The Event Driven Technology Intelligence (EDTI) model offers a structured approach to navigating the complexities of technological innovation. This research aims to summarize the core concepts and phases of the EDTI model while also exploring its significance in various industries. By expanding...

Financial sentiment analysis is crucial for making informed decisions in the financial markets, as it helps predict trends, guide investments, and assess economic conditions. Traditional methods for financial sentiment classification, such as Support Vector Machines (SVM), Random Forests, and...