Despite being regarded as a significant step toward regulating Artificial Intelligence (AI) systems and its emphasis on fundamental rights, the European Union Artificial Intelligence (EU AI) Act is not immune to moral criticism. This research aims to investigate the impact of three major normative theories of ethics (virtue ethics, deontological ethics, and consequentialism) on the EU AI Act. We introduce the concept of influence, confirmed by philosophical and chronological analysis, to examine the underlying relationship between the theories and the Act. As a proxy measure of this influence, we propose using Semantic Textual Similarity (STS) to quantify the degree of alignment between the theories (influencers) and the Act (influencee). To capture intentional and operational ethical consistency, the Act was divided into two parts: the preamble and the statutory provisions. The textual descriptions of the theories were manually preprocessed to reduce semantic overlap and ensure a distinct representation of each theory. A heterogeneous embedding-level ensemble approach was employed, utilizing five modified Bidirectional Encoder Representations from Transformers (BERT) models, built on the Transformer architecture, to compute STS scores. These scores represent the semantic alignment between various theories of ethics and each of the two components of the EU AI Act. The theories were evaluated by using voting and averaging, with findings indicating that deontological ethics has the most significant overall influence.
Wilder Baldwin, Sepideh Ghanavati, Manuel Woersdoerfer
Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks posed by these technologies. In this paper, we present a mixed-methods survey study - combining statistical and qualitative analyses - to examine the ethical perceptions, practices, and knowledge of individuals involved in various AI development roles. Our survey comprises 414 participants from 43 countries, representing various roles such as AI managers, analysts, developers, quality assurance professionals, and information security and privacy experts. The results reveal varying degrees of familiarity and experience with AI ethics principles, government initiatives, and risk mitigation strategies across roles, regions, and other demographic factors. Our findings underscore the importance of a collaborative, role-sensitive approach that involves diverse stakeholders in ethical decision-making throughout the AI development lifecycle. We advocate for developing tailored, inclusive solutions to address ethical challenges in AI development, and we propose future research directions and educational strategies to promote ethics-aware AI practices.
Siddhartha Krothapalli, Kartikey Singh Bhandari, Tridib Kumar Das
et al.
As customer feedback becomes increasingly central to strategic growth, the ability to derive actionable insights from unstructured reviews is essential. While traditional AI-driven systems excel at predicting user preferences, far less work has focused on transforming customer reviews into prescriptive, business-facing recommendations. This paper introduces ReviewSense, a novel prescriptive decision support framework that leverages advanced large language models (LLMs) to transform customer reviews into targeted, actionable business recommendations. By identifying key trends, recurring issues, and specific concerns within customer sentiments, ReviewSense extends beyond preference-based systems to provide businesses with deeper insights for sustaining growth and enhancing customer loyalty. The novelty of this work lies in integrating clustering, LLM adaptation, and expert-driven evaluation into a unified, business-facing pipeline. Preliminary manual evaluations indicate strong alignment between the model's recommendations and business objectives, highlighting its potential for driving data-informed decision-making. This framework offers a new perspective on AI-driven sentiment analysis, demonstrating its value in refining business strategies and maximizing the impact of customer feedback.
The waste problem is still becoming a big concern in Indonesia. Waste, especially plastic waste comes from single-use packaging of daily necessities such as personal care and home care. PT. Siklus Refil Indonesia or Siklus, a retail company, comes to offer a sustainable solution of buying daily necessities by refill method. Since April 2020, Siklus has operated in the Greater Jakarta area and already impacted 20,000 customers. However, Siklus must change its new business model due to regulation from the Food and Drug Supervisory Agency (BPOM) that warned the company not to sell personal care who come in direct contact with skin. The warning impacted the decreasing customers, sales, and profit of Siklus. This research has the purpose of determining the new business model of Siklus using the design thinking concept. By this concept, this research empathizes with customers, defines customer needs, and ideates a business model. This research continues to decide the new business model by creating a matrix of stepwise selection. Then this research does a prototype business model and tests the new business model. After doing the process, Return from Home is selected as the new business model for Siklus.
The advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios.
Mehmet Seyhan, Gökmen Durmuş, Özlem Yaşar Uğurlu
et al.
İşletmelerin zaman içindeki gelişimlerinin ve dinamiklerinin kapsamlı bir şekilde anlaşılmasını sağlamak için işletme tarihi araştırmalarına ihtiyaç vardır. Bu araştırmanın amacı işletme tarihindeki değişmlerin bibliyometrik analiz yöntemiyle ortaya konulmasıdır. Böylelikle geçmiş ve mevcut durumlar hakkında bilgi sağlanırken gelecekle ilgili çeşitli öngörüler de sunulmuştur. Bu amaca yönelik olarak Web of Science'ta (WoS) indekslenen işletme tarihi alanındaki yayınların kamuya çık verilerinin, bibliyometrik analizi yoluyla ilgili literatüre ilişkin çıkarımlarda bulunulması amaçlanmıştır. Bibliyometrik çalışmalar doğalarının gereği olarak aynı alanda bile gerçekleştirilse her dönem farklı sonuçlar üretebilirler. Dolayısı ile mevcut döneme ilişkin olarak hazırlanan veri seti 1991-2023 yılları arasında yayınlanmış 1516 yayını içermektedir. WoS veritabanından elde edilen konuya ilişkin çalışmalar R kaynak kodlu Biblioshiny programı aracılığı ile analiz edilmiştir. Biblioshiny hem kamuya açık bir program olması hem de ilgili analiz çıktılarının görselleştirilmesinde sağladığı kolaylık sebepleriyle tercih edilmiştir. Ayrıca önceki dönemlerde bilimsel çalışmalar üzerinde gerçekleştirmesi göreli olarak güç sayılabilecek içerik analizleri de bu program aracılığı ile uygulanabilmektedir. Yapılan içerik analizleri bibliyometrik çalışmaları sadece bir sayım döküm işi olmaktan çıkarıp olguların özüne dair fikir edinilmesini mümkün kılmaktadır. Veriler çeşitli arama kriterlerine (dil, yayın türü, alan) uygun olarak elde edildikten sonra araştırmacılar tarafından manuel kontrol gerçekleştirilmiştir. Manuel kontrol ile ilk aramada konuyla bağlantılı görünmekle birlikte alan farklılığına sahip çalışmaların tespiti ve ayıklanması sağlanmıştır. Veri setinin derlenmesinin ve ayıklanmasının akabinde gerçekleştirilen analizlerin çıktıları iki kısımda ele alınmıştır. Bulguların başlangıç bölümünde veri setinde yer alan eserlerin yazarları, kurumları, yayımlandıkları dergiler, menşe ülkeleri, konuları ve birbirleriyle ilişkileri hakkında bilgiler paylaşılmıştır. Bibliyometrik analiz sonucunda çalışmaların ağırlıklı olarak ABD, İngiltere ve Avustralya'dan geldiği görülmüştür. Kurumlar arasında Harvard Üniversitesi'nin başı çektiği ancak Kopenhag ve Uppsala gibi İskandinav üniversitelerinin de verimlilik açısından ilk yirmi beşte yer aldığı görülmüştür. İngiliz ve Amerikan üniversitelerinin çoğunlukla birbirleriyle, daha sonra ise çoğunlukla Avrupa, Kanada ve Çin üniversiteleriyle işbirliği yaptığı tespit edilmiştir. Makaleler etkileri açısından incelendiğinde en yüksek etki düzeyine sahip akademik dergilerin Journal of Business Ethics, Business History ve Harvard Business Review dergileri olduğu görülmüştür. Yazarların konu seçiminde pragmatik davrandıkları, konularının tarihsel bağlama ek olarak ve hatta bazı dönemlerde daha baskın olarak büyüme, kapasite, etki ve strateji gibi performansla ilgili konular etrafında odaklandığı tespit edilmiştir. Alınan atıf ve yayın sayısı gibi kriterlere göre alanda en etkili yazarların Jones G., Maclean M. ve Augier M. olduğu gözlenmiştir. Daha sonraki kısımlarda ise veri seti ile gerçekleştirilen içerik analizlerine yer verilmiştir. Yapılan içerik analizleri kelime ağacı, kelime bulutu, tematik evrim analizi, birlikte oluşum ağı, trend konular ve tematik haritalandırmadan oluşmaktadır. Bu analizlerde arama terimlerinin kullanılıp kullanılmaması gerektiğine dair iki temel yaklaşım bulunmaktadır. İlk yaklaşıma göre bu kavramlar veri setinde ağırlıklı olarak yer alacağından sonuçları belli bir doğrultuya sürükleyeceğinden ötürü veri setinden çıkarılması yönündedir. İkinci yaklaşıma göre temel araştırma sorunsallarının diğer kavramlarla ilişkisinin net bir şekilde ortaya konulabilmesi için veri setinde kalması gerektiği yönündedir. Bu araştırmada yukarıdaki yaklaşımlardan ikincisi benimsenmiştir. Araştırmanın bulguları, temaların periyodik olarak değiştiğini ancak son yıllarda girişimcilik, yönetim ve büyümeye doğru bir eğilim olduğunu işaret etmektedir. Gelecek dönemlerde “sosyal sorumluluk”, “yönetişim”, “sosyo-duygusal zenginlik” kavramlarının yükselişe geçmesi beklenen bir durumdur. Son olarak yılda yaklaşık 80 yayının üretildiği gözlemlenmiştir. İşletme tarihinin hem Türkiye'de hem de yurt dışında gelişen bir bilim alanı olduğu göz önüne alındığında, daha fazla çalışılması beklenen bu alana ilişkin gerçekleştirilen haritalandırma faaliyetinin (alanın gelişim yönü, değişen konseptler, etkin aktörler, vb.) gelecek dönemlerde araştırmacılara katkı sağlaması olasıdır.
The article examines the connection between corporate culture and business ethics. Ethical
considerations have grown in importance in today's corporate environment, impacting not only
internal decision-making processes but also the culture of the entire corporation. This study delves
into the dynamics that underlie the interplay between business ethics and organizational culture,
examining how ethical principles are embedded in the values, norms, and behaviors that define an
organization's identity. By synthesizing existing literature and drawing on empirical examples, the
paper aims to elucidate the impact of ethical practices on the development and sustenance of a
positive organizational culture and investigates the reciprocal influence, exploring how the
prevailing culture within an organization can either foster or hinder the adoption and adherence to
ethical principles. The results of this study should deepen our understanding of the close connection
between organizational culture and business ethics, having important implications for scholars and
policymakers who work to foster ethical workplace environments.
Reskino Reskino, Rafrini Amyulianthy, Nadia Tri Silvi
This research aims to examine the impact of personal ethics and love of money on fraud tendencies, with religiosity as a moderating variable. This research uses primary data through questionnaires given to accounting and finance staff who work at Islamic commercial banks in the DKI Jakarta area. The research sample consisted of 149 respondents, and the analysis was carried out using the Partial Least Square method (PLS-SEM) using the SmartPLS. The results of this study reveal that love of money has a significant influence on fraud tendencies, while personal ethics does not have a significant influence on fraud tendencies. In addition, religiosity could only moderate the influence of the love of money on fraud tendencies, while no moderation occurred in the relationship between personal ethics and fraud tendencies. The novelty of this research lies in examining the complex relationship between factors such as personal ethics, love of money, religiosity, and fraud tendencies in the context of the Islamic banking environment. The results of this research can provide important insights regarding the factors that influence the tendency of fraud in the banking sector, especially Sharia banking, and the moderating role of religiosity in moderating the impact of the love of money. These findings can provide valuable guidance for Islamic banks and other researchers in their efforts to prevent fraud and develop sustainable business ethics.
Organizations that develop and deploy artificial intelligence (AI) systems need to take measures to reduce the associated risks. In this paper, we examine how AI companies could design an AI ethics board in a way that reduces risks from AI. We identify five high-level design choices: (1) What responsibilities should the board have? (2) What should its legal structure be? (3) Who should sit on the board? (4) How should it make decisions and should its decisions be binding? (5) What resources does it need? We break down each of these questions into more specific sub-questions, list options, and discuss how different design choices affect the board's ability to reduce risks from AI. Several failures have shown that designing an AI ethics board can be challenging. This paper provides a toolbox that can help AI companies to overcome these challenges.
Large language models of artificial intelligence (AI), such as ChatGPT, find remarkable but controversial applicability in science and research. This paper reviews epistemological challenges, ethical and integrity risks in science conduct in the advent of generative AI. This is with the aim to lay new timely foundations for a high-quality research ethics review. The role of AI language models as a research instrument and subject is scrutinized along with ethical implications for scientists, participants and reviewers. New emerging practices for research ethics review are discussed, concluding with ten recommendations that shape a response for a more responsible research conduct in the era of AI.
This study focuses on the ethical considerations that a consumer perceives with augmented reality (AR) in the context of smartphone applications. Through a systematic review, this research can provide an understanding and ability for developers, product managers, digital marketers and associated business professionals to effectively implement and deploy mobile AR related applications and campaigns, with consideration to the perceptions of the ethical considerations that consumers have of this growing technology. The rise in digital transformation and new technologies paved this research agenda. Trends in the data revealed two overarching factors of 'Benefits' and 'Ethical Considerations'. Within these two factors, several consumer perceived themes were identified with regards to AR applications and their association categorised either positive, negative or neutral. 'Benefits' revealed 3 consistent themes of personalisation, interactivity and information acquisition. 'Ethical Considerations' revealed consistent patterns of educational awareness, privacy, transparency and security. From identifying the consumer perceptions, business professionals can strategically address and or challenge the inherent limitations and their associations during AR application development, product adoption strategies or marketing purposes.
The aim of this paper is to present a systematic literature review of the existing research, published between 2006 and 2023, in the field of artificial intelligence for management information systems. Of the 3946 studies that were considered by the authors, 60 primary studies were selected for analysis. The analysis shows that most research is focused on the application of AI for intelligent process automation, with an increasing number of studies focusing on predictive analytics and natural language processing. With respect to the platforms used by AI researchers, the study finds that cloud-based solutions are preferred over on-premises ones. A new research trend of deploying AI applications at the edge of industrial networks and utilizing federated learning is also identified. The need to focus research efforts on developing guidelines and frameworks in terms of ethics, data privacy, and security for AI adoption in MIS is highlighted. Developing a unified digital business strategy and overcoming barriers to user–AI engagement are some of the identified challenges to obtaining business value from AI integration.
In their reconsiderations of hospitality through the thought and artistic practice of women of color, the contributions in this special issue rely heavily on historical memory, testimony, storytelling, affective politics, and decolonial phenomenology and epistemology. Given the mismatch between a humanistic, almost old-fashioned discourse of hospitality and the secular use of the word in the service business, the essays demonstrate a renewed interest in hospitality as a figuration of ethics and a critique of its practical and discursive contradictions: between a legally confirmed identity and the encounter with the unknown, between the unlimited responsibility toward a guest and gendered and racialized economic relations, between justice and fairness and essentialist views of the other (McNulty, 2007: viii).
Abstract Background Technological innovation is recognised as having the potential to enhance rehabilitation for people with disability. Yet, resistance to, and abandonment of, rehabilitation technology is prevalent and the successful translation of technology into rehabilitation settings remains limited. Therefore, the aim of this work was to develop an in-depth, multi-stakeholder perspective on what influences the adoption of rehabilitation technologies. Methods Semi-structured focus groups were conducted as part of a larger research project aiming to facilitate the co-design of a novel neurorestorative technology. Focus group data were analysed using a five-phase hybrid deductive-inductive approach to qualitative data analysis. Results Focus groups were attended by 43 stakeholders with expertise in one or more of the following fields: people with disability, allied health, human movement science, computer science, design, engineering, ethics, funding, marketing, business, product development, and research development. Six main themes influencing the adoption of technology in rehabilitation were identified: cost beyond the purchase price, benefits to all stakeholders, trust to be earned in technology, ease of technology operation, ability to access technology, and the ‘co’ in co-design. All six themes were found to be interrelated; in particular, the importance of direct stakeholder engagement in the development of rehabilitation technologies (the ‘co’ in co-design) was prevalent in all themes. Conclusions A range of complex and interrelated factors influence the adoption of rehabilitation technologies. Importantly, many of the issues that have the potential to negatively impact rehabilitation technology adoption may be addressed during development by utilising the experience and expertise of stakeholders who influence its supply and demand. Our findings state that a wider cohort of stakeholders needs to be actively engaged in the development of rehabilitation technologies to better address the factors that contribute to technology underutilisation and abandonment and facilitate better outcomes for people with disability.
What-if analysis (WIA) is essential for data-driven decision-making, allowing users to assess how changes in variables impact outcomes and explore alternative scenarios. Existing WIA research primarily supports the workflows of data scientists and analysts, and largely overlooks business professionals who engage in WIA through non-technical means. To bridge this gap, we conduct a two-part user study with 22 business professionals across marketing, sales, product, and operations roles. The first study examines their existing WIA practices, tools, and challenges. Findings reveal that business professionals perform many WIA techniques independently using rudimentary tools due to various constraints. We then implement representative WIA techniques in a visual analytics prototype and use it as a probe to conduct a follow-up study evaluating business professionals' practical use of the techniques. Results show that these techniques improve decision-making efficiency and confidence while underscoring the need for better data preparation, risk assessment, and domain knowledge integration support. Finally, we offer design recommendations to enhance future business analytics systems.
Background: Given that the impact of the South African business environment on small and medium-sized enterprises’ (SMEs) management of trade credit is largely unknown, this article argues that certain internal or external business environment variables could significantly impact SMEs’ management of trade credit effectiveness, making it necessary to ask the impact of business environment in South Africa on SMEs’ trade credit management effectiveness.
Aim: To determine the impact of internal (managerial competencies, collateral, financial and business information and networking) and external (legal system, ethics, macroeconomy and corruption) business environment variables on SMEs’ management of trade credit effectiveness.
Setting: This study was conducted by administering an online questionnaire.
Method: Quantitative research design with purposive sampling as the sampling method, administrated to 10 450 SMEs within South Africa.
Results: The results reveal several internal (5) and external (4) business environment factors significantly impacting SMEs’ effectiveness in managing trade credit.
Conclusion: The article reveals how internal and external business environment factors contribute to increased SME effectiveness in managing trade credit and, in so doing, helps mitigate financial problems associated with SMEs’ trade credit as a result of asymmetric information such as adverse selection, moral hazard and credit rationing, while also understanding the significance of corruption on SMEs’ effectiveness in managing trade credit.
This is a book review of: Bruno Frischherz, Liu Baocheng, Li Xiaosong, Anoosha Makka, Gordon Millar, Martin Brasser and Menno Brouwer. Teaching Intercultural Business Ethics. Globethics.net Education Praxis Series, Geneva: Globethics.net, forthcoming 2023.
There is a massive underserved market for small business lending in the US with the Federal Reserve estimating over \$650B in unmet annual financing needs. Assessing the credit risk of a small business is key to making good decisions whether to lend and at what terms. Large corporations have a well-established credit assessment ecosystem, but small businesses suffer from limited publicly available data and few (if any) credit analysts who cover them closely. We explore the applicability of (DL-based) large corporate credit risk models to small business credit rating.