Hasil untuk "Business ethics"

R. Solomon

Ruiming Min

This study examines whether the tariff policies delivered on promises to revitalize American manufacturing and create jobs. Using county-level business application data from 2018-2025, we analyze the relationship between tariff implementation and new business formation through linear regression analysis. Our findings reveal a statistically significant positive association between US tariffs on China and American business applications. However, when Chinese retaliatory tariffs are included in the analysis, their negative coefficient substantially exceeds the positive US tariff effect, suggesting that retaliatory measures largely offset the benefits of protectionist policies. Control variables including inflation rate, federal funds rate, and government spending show significant positive effects on business formation. These results indicate that while protectionist trade policies may stimulate domestic business formation, their effectiveness is significantly diminished by retaliatory responses from trading partners. The study provides evidence that unilateral tariff measures without diplomatic coordination produce limited net benefits, confirming that trade wars create scenarios where potential gains are neutralized by counteractions.

C. G. Liu, P. Bodorik, D. Jutla

This paper addresses the challenge of creating smart contracts for applications represented using Business Process Management and Notation (BPMN) models. In our prior work we presented a methodology that automates the generation of smart contracts from BPMN models. This approach abstracts the BPMN flow control, making it independent of the underlying blockchain infrastructure, with only the BPMN task elements requiring coding. In subsequent research, we enhanced our approach by adding support for nested transactions and enabling a smart contract repair and/or upgrade. To empower Business Analysts (BAs) to generate smart contracts without relying on software developers, we tackled the challenge of generating smart contracts from BPMN models without assistance of a software developer. We exploit the Decision Model and Notation (DMN) standard to represent the decisions and the business logic of the BPMN task elements and amended our methodology for transformation of BPMN models into smart contracts to support also the generation script to represent the business logic represented by the DMN models. To support such transformation, we describe how the BA documents, using the BPMN elements, the flow of information along with the flow of execution. Thus, if the BA is successful in representing the blockchain application requirements using BPMN and DMN models, our methodology and the tool, called TABS, that we developed as a proof of concept, is used to generate the smart contracts directly from those models without developer assistance.

Dănuț TRIFU

Social sciences have always been subject to ethical considerations, from research to explicit use and implicit meaning of their findings; Consumer Neuroscience has vigorously developed over the last twenty years and associated ethical concerns have promptly come into the picture. As the effectiveness of the existing neuroscience tools and techniques is just being discovered by researchers in most social sciences, I hypothesize that associated ethical issues will become more prominent in the future. The current article does not attempt to provide an exhaustive view of these issues and possible solutions; it just tackles some of the most important ones differentiating between those specific to Consumer Neuroscience and those rather common for most other social sciences. From this standpoint, large differences were found when analyzing research objectives, instruments, data disclosure, and findings dissemination and use as well as participants’ protection and data privacy rights. The framework of the Neuromarketing Science and Business Association (NMSBA) proposed Code of Ethics was used as a starting point for this material, which provides a brief assessment of the current state of each principle put forward by the Code based on an extensive literature review. Although this Code’s provisions are quite similar to the ones put forward by the European Charter for Researchers of 2000, European Commission’s Ethics in Social Sciences and Humanities of 2001, and several national-level regulations, it was the first choice for this study as it comes specifically from researchers and practitioners in Consumer Neuroscience. Finally, the current paper shall argue for a balanced and realistic approach when attempting to regulate the domain, ensuring the rules effectively protect the participants and users while not unnecessarily increasing research difficulty. As Neuroscience approaches are increasingly accepted by Marketing and other social sciences, a sound and functional ethical foundation would help safe, fair, and fast advances rather than allow for abuses or constitute unnecessary impediments.

Ilham Fitriyansyah, Muhhamad Aris Syafi'I, Hendri Hermawan Adinugraha

This research aims to discuss the integration between strategic management and Islamic business ethics in encouraging the development of a just and sustainable Islamic economy. The research approach used is quantitative method with literature study research type. This study found that managerial strategies that are aligned with Islamic ethics are able to increase trust, consumer loyalty, and contribution to the welfare of the people (maslahah). Islamic business ethics is not only a moral guideline, but also an effective strategic tool in decision making and business management. In conclusion, the integration of strategic management and Islamic ethics can be a strong foundation in building an inclusive, competitive and sustainable Islamic economic system. This research recommends the need for internalization of Islamic values in managerial practices to support a more meaningful economic transformation.

Abdene Weya Kaso, Berhanu Gidisa Debela, Habtamu Endashaw Hareru et al.

Abstract Background In Ethiopia, out-of-pocket medical expenses make up one-third of all medical expenses, which makes it difficult for households to obtain and utilize healthcare. One of the prepayment mechanisms that shield low-income households from unaffordable medical bills is the community-based health insurance (CBHI) program. This systematic review and meta-analysis aimed to estimate the pooled willingness to join Community-based Health Insurance schemes and its associated factors among households in Ethiopia. Methods Articles were searched from PubMed, Google Scholar, Web of Science, Scopus, Science Direct, and Ethiopian Universities’ repositories for grey literature. The study used the modified PRISMA guidelines for rewriting and reviewing the literature. The quality of studies was assessed using Joanna Briggs Institute Critical Appraisal tools. Data was extracted using Microsoft Excel and exported to STATA version 16 software for analysis. Cochran’s Q statistic and I2 tests were utilized to determine the heterogeneity between studies. Studies publication bias was determined using a funnel plot and Egger’s test. Subgroup analysis was conducted to demonstrate variations of the effect sizes across study regions. Finally, we utilized a random-effect model to compute the overall willingness to join the CBHI scheme and its determinants among households in Ethiopia. Result We included thirty studies to determine the pooled prevalence of willingness to join the CBHI scheme and its determinants. The pooled magnitude of households’ willingness to join the CBHI scheme was 60.42% (95% CI: 51.45%, 69.38%). Old aged (AOR = 2.17, [95% CI: 1.37, 3.44], I2 = 82.33%), formal educational status(AOR = 2.74, [95% CI: 2.10, 3.56], I2 = 59.85%), Rich wealth index (AOR = 2.51, [95% CI: 1.99, 3.18], I2 = 48.25%), good knowledge/awareness of CBHI scheme(AOR = 4.21, [95% CI: 3.01, 5.88], I2 = 66.0%), experienced illness in the last three months (AOR = 3.42, [95% CI: 2.19, 5.35], I2 = 71.15%), and large family size (AOR = 2.36, [95% CI: 1.95, 2.87], I2 = 50.81%) were determinants of willingness to join the CBHI scheme. In addition, affordability of CBHI premium (AOR = 3.12, [95% CI: 2.34, 4.14], I2 = 10.35%), poor health status (AOR = 3.23, [95% CI: 2.57, 4.06], I2 = 35.97%), trust in scheme (AOR = 4.38, [95% CI: 1.91, 10.06], I2 = 88.35%), chronic diseases (AOR = 3.24, [95% CI: 2.40, 4.37], I2 = 67.15%) and good quality of healthcare services (AOR = 2.91, [95%CI:2.08, 4.09], I2 = 65.40%) were also predictors of willingness to join the CBHI program. Conclusion The pooled prevalence of willingness to join the CBHI scheme was low and below the national target of 80%. Age, family size, educational status, wealth status, illnesses in last three months, presence of chronic illnesses, affordability of the premium for the CBHI scheme, self-reported health status, Knowledge/awareness of the scheme, trust in the scheme and perceived quality of healthcare service were significantly determine the willingness to join the CBHI scheme. Health providers should provide detailed awareness creation through health education on the concepts and principles of the CBHI scheme.

Edward Y. Chang

This paper explores the integration of human-like emotions and ethical considerations into Large Language Models (LLMs). We first model eight fundamental human emotions, presented as opposing pairs, and employ collaborative LLMs to reinterpret and express these emotions across a spectrum of intensity. Our focus extends to embedding a latent ethical dimension within LLMs, guided by a novel self-supervised learning algorithm with human feedback (SSHF). This approach enables LLMs to perform self-evaluations and adjustments concerning ethical guidelines, enhancing their capability to generate content that is not only emotionally resonant but also ethically aligned. The methodologies and case studies presented herein illustrate the potential of LLMs to transcend mere text and image generation, venturing into the realms of empathetic interaction and principled decision-making, thereby setting a new precedent in the development of emotionally aware and ethically conscious AI systems.

Мarian Аmbrozy, Zuzana Kuběnová

The topic of unfair competition for job positions is a significant yet underexplored issue within the domains of managerial and business ethics. This study aims to shed light on this problem by examining three core themes related to unethical struggles for job positions. The first theme addresses the barriers that inhibit effective prevention of unethical behavior in the workplace. The study aims to identify these barriers reliably and explore specific reasons that obstruct efforts to curb such behavior. The second theme investigates the intricate relationship between ethical codes and unethical competition for positions. Not all ethical codes are effective; some may inadvertently support behaviors that allow managers to abuse their power to eliminate potential rivals. This phenomenon, known as “hidden bossing”, involves managers using mandatory but ethically dubious behavior models, combined with sanctions, as tools for maintaining control and stifling competition. The study underscores the need for ethical codes that explicitly address the selection mechanisms for managerial positions, including the imposition of sanctions for violations of these codes. The third theme focuses on identifying the personality traits of individuals prone to using unfair means to climb the corporate ladder. Traits such as egotism, primary and secondary narcissism, and a tendency toward manipulative behavior are examined. The research delves into the psychological underpinnings of these traits, highlighting how self-centered personalities and individuals with narcissistic personality disorder are more likely to engage in unethical competition. The results of this research have significant implications for organizational culture and management practices. By identifying the barriers to ethical behavior and the personality traits associated with unethical competition, the study offers practical recommendations for fostering a more ethical workplace. These include the development of ethical codes that are integrated with organizational policies and the promotion of a culture of accountability and ethical responsibility.

Aleksandra Paravina

Qualitative transdisciplinary research has contributed to the development of a dynamic scientific area that is best suited to analyze real-life data from real people. To determine how ethnicity and gender intersect to shape the social worlds of the participants in a Serb business discussion forum, I apply two theoretical orientations based on ethnomethodology: Conversation Analysis (CA) and membership categorization analysis (MCA). I analyze 15 videos with predominantly female Serb discussants. My findings from this project reveal a significant presence of stigma in the perceptions of Serb ethnicity in Croatia. I argue that due to patriarchal values as a type of cultural cache, Serb women experience demeaning gender categories in various areas of their lives. To improve this situation, it is suggested that there is a need for feminist ethics of care and a coalition with men.

Anthony Magoma, Enid Ernest, Ernest Kasheshi

This study investigates the impact of board characteristics on the financial performance of 14 listed banks in Kenya, Tanzania, and Uganda. We use 84 firm-year observations of 14 listed banks from three stock markets in East Africa, namely Dar es Salaam Stock Exchange (DSE), Nairobi Security Exchange (NSE), and Uganda Security Exchange (USE) for a six-year period that is 2017–2022. The accounting measure of financial performance was the net interest margin (NIM). This study used a fixed-effects panel analysis model to test the hypotheses. The empirical results reveal that board financial expertise positively and significantly influences financial performance. This implies that an increase in the proportion of board members with financial and accounting backgrounds increases bank performance. On the other hand, the proportion of foreign directors decreased bank performance as the variable exerted a negative and significant effect on bank performance. The results suggest that board structure has an important role to play in the governance of listed banks in East African frontier stock markets.

Kerianne L. Hobbs, Bernard Li

Designing a safe, trusted, and ethical AI may be practically impossible; however, designing AI with safe, trusted, and ethical use in mind is possible and necessary in safety and mission-critical domains like aerospace. Safe, trusted, and ethical use of AI are often used interchangeably; however, a system can be safely used but not trusted or ethical, have a trusted use that is not safe or ethical, and have an ethical use that is not safe or trusted. This manuscript serves as a primer to illuminate the nuanced differences between these concepts, with a specific focus on applications of Human-AI teaming in aerospace system control, where humans may be in, on, or out-of-the-loop of decision-making.

Tsvetelina Hristova, Liam Magee, Emma Kearney

Data sharing partnerships are increasingly an imperative for research institutions and, at the same time, a challenge for established models of data governance and ethical research oversight. We analyse four cases of data partnership involving academic institutions and examine the role afforded to the research partner in negotiating the relationship between risk, value, trust and ethics. Within this terrain, far from being a restraint on financialisation, the instrumentation of ethics forms part of the wider mobilisation of infrastructure for the realisation of profit in the big data economy. Under what we term `combinatorial data governance' academic structures for the management of research ethics are instrumentalised as organisational functions that serve to mitigate reputational damage and societal distrust. In the alternative model of `experimental data governance' researchers propose frameworks and instruments for the rethinking of data ethics and the risks associated with it - a model that is promising but limited in its practical application.

Forhan Bin Emdad, Shuyuan Mary Ho, Benhur Ravuri et al.

Artificial Intelligence (AI) aims to elevate healthcare to a pinnacle by aiding clinical decision support. Overcoming the challenges related to the design of ethical AI will enable clinicians, physicians, healthcare professionals, and other stakeholders to use and trust AI in healthcare settings. This study attempts to identify the major ethical principles influencing the utility performance of AI at different technological levels such as data access, algorithms, and systems through a thematic analysis. We observed that justice, privacy, bias, lack of regulations, risks, and interpretability are the most important principles to consider for ethical AI. This data-driven study has analyzed secondary survey data from the Pew Research Center (2020) of 36 AI experts to categorize the top ethical principles of AI design. To resolve the ethical issues identified by the meta-analysis and domain experts, we propose a new utilitarian ethics-based theoretical framework for designing ethical AI for the healthcare domain.

Iryna Pozovna, Stanislav Arhipov, Aleksandra Kuzior

Rapid technological development, globalization, digitalization, the COVID-19 pandemic, and many other factors cause significant transformations in education, which requires regular updating of forecasts of short-term and long-term trends in the development of the educational services market, determination of labour market needs, updating of strategies for training qualified specialists, etc. The research aims to identify the main determinants that determine the leadership of 31 European countries in higher education for 2017-2021. The following research methods were used to achieve the goal of the research: analysis and synthesis, comparison and grouping, induction and deduction, abstraction and logical generalization, tabular and graphic method, factor analysis (principal component method), cluster analysis (hierarchical, Ward's method). The input data array includes fifteen different indicators (official statistical data of Eurostat and the European Commission) characterizing the development of higher education. The factor analysis was carried out using the principal component method proved that the most significant determinants determining the leadership of European countries in higher education are the number of students enrolled in higher education institutions, the number of new entrants, the number of teachers and scientific and pedagogical workers in higher education, state and private expenses for higher education, financial assistance to students of higher education, number of graduates by level of higher education. These variables are the basis of a hierarchical cluster analysis using Ward's method. It made it possible to identify five clusters among European countries that differ in the determinants that determine the country's leadership in higher education. All calculations were made in the STATA/SE 18.0 software package. Modelling found that funding is a determinant of leadership in higher education for the United Kingdom, France and Germany. Turkey is the leader in the number of students enrolled in higher education in 2017 and 2021. At the same time, for most of the studied countries, indicators of financing higher education and indicators characterizing the number of participants in the educational process tended to decrease in 2021 compared to 2017. The obtained results can be used by state and local authorities, as well as other interested parties, to harmonize the reforming of the higher education market, and higher education institutions to improve the quality of educational services and their compliance with the needs of the labour market.

Juan Francisco Rivera Feijoo

En Perú, la COVID-19 produjo la mayor tasa de mortalidad en el mundo, causando grandes estragos. El consecuente estado alterado de la salud mental lo hemos observado tal como ha sido reportado a nivel mundial. Según estimaciones epidemiológicas en varios lugares del mundo hubo un incremento en trastornos de ansiedad y en trastornos depresivos muy cercanos al 30%. El país inicialmente se hallaba en una situación muy frágil para atender las necesidades de salud y ahora tiene más casos que atender. La ansiedad y la depresión no tratadas cursan con discapacidad. Describimos los cuadros clínicos de mayor causa biológica para explicar por qué no se incrementaron. Una viñeta clínica ilustra esta relación al mismo tiempo que muestra el frecuente fenómeno de comorbilidad en atención de salud mental. Hemos contextuado con lo que ha sucedido en todo el mundo y con otros cuadros de salud mental menos agravados por la pandemia.

L. Christensen, E. Peirce, L. Hartman et al.

Jia Xu, Humza Naseer, Sean Maynard et al.

Digital business transformation has become increasingly important for organizations. Since transforming business digitally is an ongoing process, it requires an integrated and disciplined approach. Data Operations (DataOps), emerging in practice, can provide organizations with such an approach to leverage data and analytics for digital business transformation. This paper proposes a framework that integrates digital business transformation, data analytics, and DataOps through the lens of information processing theory (IPT). The details of this framework explain how organizations can employ DataOps as an integrated and disciplined approach to understand their analytical information needs and develop the analytical information processing capability required for digital business transformation. DataOps-enabled digital business transformation, in turn, improves organizational performance by improving operational efficiency and creating new business models. This research extends current knowledge on digital transformation by bringing in DataOps and analytics through IPT and thereby provide organizations with a novel approach for their digital business transformations.

Mona Sloane, Janina Zakrzewski

Within the current AI ethics discourse, there is a gap in empirical research on understanding how AI practitioners understand ethics and socially organize to operationalize ethical concerns, particularly in the context of AI start-ups. This gap intensifies the risk of a disconnect between scholarly research, innovation, and application. This risk materializes acutely as mounting pressures to identify and mitigate the potential harms of AI systems have created an urgent need to assess and implement socio-technical innovation for fairness, accountability, and transparency. Building on social practice theory, we address this need via a framework that allows AI researchers, practitioners, and regulators to systematically analyze existing cultural understandings, histories, and social practices of ethical AI to define appropriate strategies for effectively implementing socio-technical innovations. Our contributions are threefold: 1) we introduce a practice-based approach for understanding ethical AI; 2) we present empirical findings from our study on the operationalization of ethics in German AI start-ups to underline that AI ethics and social practices must be understood in their specific cultural and historical contexts; and 3) based on our empirical findings, we suggest that ethical AI practices can be broken down into principles, needs, narratives, materializations, and cultural genealogies to form a useful backdrop for considering socio-technical innovations.

Michael Desmond, Evelyn Duesterwald, Vatche Isahagian et al.

Most business process automation is still developed using traditional automation technologies such as workflow engines. These systems provide domain specific languages that require both business knowledge and programming skills to effectively use. As such, business users often lack adequate programming skills to fully leverage these code oriented environments. We propose a paradigm for the construction of business automations using natural language. The approach applies a large language model to translate business rules and automations described in natural language, into a domain specific language interpretable by a business rule engine. We compare the performance of various language model configurations, across various target domains, and explore the use of constrained decoding to ensure syntactically correct generation of output.

Mirna Rafki, Idris Parakkasi, Sirajuddin Sirajuddin

The rapid development of business and technology has had a positive impact on the business world so that attention to consumer trust and repeat orders is an important thing that must be considered. The purpose of this study is to analyze the role of Islamic business ethics in increasing consumer confidence and the implications for increasing consumer repeat orders. This study uses a qualitative method with a type of phenomenological research. The data sources used are primary and secondary data. Primary data was obtained through observation and direct interviews with 14 informants while secondary data was obtained from relevant literature. The research results show that CV. Sibuh Soppeng Regency focuses its operations on two things, namely service and marketing by implementing Islamic business ethics. Several indicators are used in building consumer trust such as good service, honesty, keeping promises, being responsible for consumers, and working on time which has implications for repeat orders from these consumers.   Perkembangan bisnis dan teknologi yang semakin pesat membawa dampak positif dalam dunia bisnis sehingga perhatian terhadap kepercayaan dan repeat order konsumen menjadi hal penting yang harus diperhatikan. Tujuan dari penelitian ini adalah untuk menganalisis peran etika bisnis Islam dalam meningkatkan kepercayaan konsumen serta implikasinya terhadap peningkatan repeat order konsumen. Penelitian ini menggunakan metode kualitatif dengan jenis penelitian fenomenologi. Sumber data yang digunakan yaitu data primer dan sekunder. Data primer diperoleh melalui observasi dan wawancara langsung dengan 14 informan sedangkan data sekunder didapat dari literatur yang relevan. Hasil Penelitian menunjukkan bahwa CV. Sibuh Kabupaten Soppeng memfokuskan operasionalnya pada dua hal yaitu pelayanan dan pemasaran dengan mengimplementasikan etika bisnis Islam. Beberapa indikator digunakan dalam membangun kepercayaan konsumen seperti pelayanan yang baik, kejujuran, menepati janji, bertanggung jawab terhadap konsumen, serta bekerja tepat waktu yang berimplikasi terhadap repeat order dari konsumen tersebut.