Hasil untuk "Business"

P. Gomber, Jascha-Alexander Koch, Michael Siering

C. Prahalad, A. Hammond

Randi L'hommedieu

In just the last seven years, from 2007 to 2014, mobile data traffic on our network increased 100,000 percent. People are consuming huge amounts of bandwidth with streaming video. Mobile devices are replacing wired connections in greater and greater numbers. And businesses are connecting everything to our network from cars and tractors to refrigerators and trash cans. This change in our business and our industry is revolutionizing our economy.

P. P. McDougall, B. Oviatt

R. Englund

P. Pavlou, O. E. Sawy

R. Freeman, A. Wicks, B. Parmar

F. Nah, J. Lau, Jinghua Kuang

Henry Mintzberg

P. Senge

Charles W. Hofer

T. Bartik

Stephan Sandfuchs, Diako Farooghi, Janis Mohr et al.

Artificial intelligence (AI) and Machine Learning (ML) have moved from research and pilot projects into everyday business operations, with generative AI accelerating adoption across processes, products, and services. This paper introduces the concept of Responsible AI for organizational practice, with a particular focus on small and medium-sized enterprises. It structures Responsible AI along four focal areas that are central for introducing and operating AI systems in a legally compliant, comprehensible, sustainable, and data-sovereign manner. First, it discusses the EU AI Act as a risk-based regulatory framework, including the distinction between provider and deployer roles and the resulting obligations such as risk assessment, documentation, transparency requirements, and AI literacy measures. Second, it addresses Explainable AI as a basis for transparency and trust, clarifying key notions such as transparency, interpretability, and explainability and summarizing practical approaches to make model behavior and decisions more understandable. Third, it covers Green AI, emphasizing that AI systems should be evaluated not only by performance but also by energy and resource consumption, and outlines levers such as model reuse, resource-efficient adaptation, continuous learning, model compression, and monitoring. Fourth, it examines local models (on-premise and edge) as an operating option that supports data protection, control, low latency, and strategic independence, including domain adaptation via fine-tuning and retrieval-augmented generation. The paper concludes with a consolidated set of next steps for establishing governance, documentation, secure operation, sustainability considerations, and an implementation roadmap.

Pranav Darshan, Rohan J S, Raghuveer Rajesh et al.

Non Fungible Tokens have changed digital ownership and how creators earn money. Between 2021 and 2024, the market value exceeded 40 billion. However, the fast growth of the NFT ecosystem has revealed serious issues in managing intellectual property rights. There is a lot of confusion about the difference between owning an NFT and owning the copyright for the underlying content. This research looks at the gap between traditional copyright laws and blockchain-based transactions. We use a mixed methods approach to analyze this disconnect. We create a new IP rights matrix that clearly shows how copyright law relates to NFT ownership structures. Additionally, we include a business model taxonomy that sorts new commercial applications by their IP risk and sustainability factors. By examining important legal cases, smart contracts, and interviews with stakeholders, we find key problems in enforcing laws across different regions, standardizing licenses, and assessing business opportunities.

Jeho Choi

Large Language Models (LLMs) have shown promise in enabling natural language interfaces for structured data querying through text-to-SQL generation. However, their application in real-world Business Intelligence (BI) contexts remains limited due to semantic hallucinations, structural errors, and a lack of domain-specific evaluation frameworks. In this study, we propose a Fact-Consistency Evaluation Framework for assessing the semantic accuracy of LLM-generated SQL outputs using Exaone 3.5--an instruction-tuned, bilingual LLM optimized for enterprise tasks. We construct a domain-specific benchmark comprising 219 natural language business questions across five SQL complexity levels, derived from actual sales data in LG Electronics' internal BigQuery environment. Each question is paired with a gold-standard SQL query and a validated ground-truth answer. We evaluate model performance using answer accuracy, execution success rate, semantic error rate, and non-response rate. Experimental results show that while Exaone 3.5 performs well on simple aggregation tasks (93% accuracy in L1), it exhibits substantial degradation in arithmetic reasoning (4% accuracy in H1) and grouped ranking tasks (31% in H4), with semantic errors and non-responses concentrated in complex cases. Qualitative error analysis further identifies common failure types such as misapplied arithmetic logic, incomplete filtering, and incorrect grouping operations. Our findings highlight the current limitations of LLMs in business-critical environments and underscore the need for fact-consistency validation layers and hybrid reasoning approaches. This work contributes a reproducible benchmark and evaluation methodology for advancing reliable natural language interfaces to structured enterprise data systems.

The bbchallenge Collaboration, Justin Blanchard, Daniel Briggs et al.

The Busy Beaver value $S(n)$ is the maximum number of steps that an $n$-state 2-symbol Turing machine can perform from the all-zero tape before halting. $S$ was historically introduced by Tibor Radó in 1962 as one of the simplest examples of an uncomputable function. We prove that $S(5) = 47,176,870$ using the Coq proof assistant. The proof enumerates $181,385,789$ Turing machines with 5 states and, for each machine, decides whether it halts or not. Our result marks the first determination of a new Busy Beaver value in over 40 years and the first Busy Beaver value ever to be formally verified, attesting to the effectiveness of massively collaborative online research (bbchallenge$.$org).

Selfira Salsabilla

Main Purpose - This study aims to analyze the influence of labor market considerations, subjective norms, self-efficacy-technical skills, and outcome expectations on the intention to become a tax consultant. Method - This study uses a quantitative method with the Structural Equation Modeling (SEM) approach. The research sample consisted of 170 students of the UII Tax Accounting study program. Main Findings - The results of the study indicate that students’ intention to become tax consultants is more influenced by subjective norms and outcome expectations. However, no influence of labor market considerations and self-efficacy of technical skills on the intention to become a tax consultant was found. Theory and Practical Implications - The results of the study show that the surrounding environment is a factor that influences becoming a tax consultant. Therefore, academics need to provide adequate information about the role of the current tax consultant profession. In addition, the results of this study can be a basis for companies that want to recruit tax consultants to provide compensation and rewards that are in accordance with their work. Novelty - This study elaborates on the Theory of Planned Behavior (TPB) and Social Cognitive Career Theory (SCCT) to explore students’ intentions to become tax consultants.

Konrad Schroeder

Artykuł ma charakter teoretyczny, a jego celem jest omówienie czynników pozwalających na wymiarowanie pracy działów HR i określenie, czy mają one zastosowanie w każdej organizacji, bez względu na charakter jej działalności i wielkość. Treść ta ma za zadanie przybliżyć zagadnienie mierzalności działań ukierunkowanych na efektywność realizowania zadań związanych z zarządzaniem kadrami, a także zweryfikować ich znaczenie dla funkcjonowania organizacji. Celem autora jest przedstawienie zagadnienia uniwersalnego wymiarowania pracy oraz konkretnych wskaźników, które to zadanie realizują. W niniejszym opracowaniu odbiorca znajdzie informacje na temat sześciu kategorii wskaźników: rekrutacyjnych, retencji i rotacji, zaangażowania i satysfakcji, szkoleniowych i rozwojowych, absencji, efektywności kosztowej. Artykuł odnosi się do aktualnych badań realizowanych przez ekspertów z branży zarządzania zasobami ludzkimi i rekrutacji.

Rosa Santero-Sánchez, Belén Castro Núñez

Despite the massive incorporation of women into the labor market, equal pay for equal work remains a challenge. This article analyzes the influence of gender diversity in management positions on the gender wage gap (GWG) throughout the entire pay scale in Spain. The results show the existence of a GWG, particularly for wages below the average; though it decreases when female participation in management is higher. This is in line with the reduction of information asymmetry problems considered in statistical discrimination theories, which explain the barriers to promotion associated with dynamics at entry-level and low-qualified positions. JEL CLASSIFICATION: C31, J31, J71, M14

Anisur Rehman, Aftab Ara, Harman Preet Singh

Abstract Saudi Arabia ranks amongst those nations with the highest amount of fossil carbon dioxide emissions. Due to the rising environmental and economic sustainability challenges in Saudi Arabia, investigating environmental sustainability in the nation has become imperative. Similar to business organisations, universities in Saudi Arabia are also intensifying their initiatives to enhance sustainability, contending with the nation’s established dependence on increasing greenhouse gas emissions, high energy and fossil fuels. There is a gap in research on the green human resource management (GHRM) practices of these universities aimed at promoting sustainability with the involvement of their faculty members. To address this gap, this study employs ability–motivation–opportunity (AMO) theory and change management theory to examine the effect of GHRM practices on the organisational citizenship behaviour towards environment (OCBE) and environmental performance (EP) of universities in Saudi Arabia. This study also investigates the moderating effect of technological competence and resistance to change on the association of GHRM practices with OCBE and EP. Results demonstrate that all three GHRM practices (green training and development, green employee involvement and green performance appraisal) have a positive and significant impact on OCBE, which subsequently influences EP. The mediating effect of OCBE and the moderating effects of technological competence and resistance to change were also confirmed. This study advances the existing research on the influence of GHRM practices on environmental outcomes through the lens of the AMO framework and change management theory in the university context of Saudi Arabia. This pioneering study also explores the role of technological competence and resistance to change as moderators in the above relationship. In addition to theoretical implications, this study offers novel insights for policymakers in higher educational institutions.