Hasil untuk "Business ethics"

Natacha Rocha Guterres, Marcelo Wüst, Maria Luisa Martins Meinhart et al.

Esse estudo avalia como a espiritualidade se manifesta entre familiares que acompanham pacientes em uso de substâncias no retorno da hospitalização compulsória. É um estudo observacional, do tipo estudo de casos múltiplos, com abordagem qualitativa, que acompanhou 31 atendimentos, por meio de entrevistas de seguimento de 30, 90 e 180 dias. As falas foram agrupadas em três categorias de análise: condições para prosseguir, a responsabilização de terceiros e expectativas das famílias na religiosidade. As manifestações de espiritualidade mostraram-se como um recurso útil no enfrentamento e suporte nestas situações adversas. Após a hospitalização psiquiátrica, as abordagens têm ênfase na consulta médica, ajustes medicamentosos e controle dos sintomas, esquecendo-se de ferramentas alternativas, como fatores espirituais ou religiosos. Quando utilizada como ferramenta de apoio, a espiritualidade fortalece o vínculo com a equipe e contribui para a melhora da autoestima dos familiares, indicando que esse recurso deveria ser mais explorado pelas equipes de saúde.

Héctor Guzmán García, Héctor Guzmán Sanchéz

Este texto analiza la relación entre filosofía y la ecología acústica en la Reserva Ecológica del Pedregal de San Ángel (REPSA), resaltando el papel del sonido en la comprensión del entorno. Se abordan tres enfoques filosóficos: la fenomenología, que estudia la percepción del paisaje sonoro; la ética ambiental, que defiende el valor de la biodiversidad sonora; y la estética filosófica, que aprecia la belleza del sonido natural. A través de estos enfoques, se reflexiona sobre el impacto del ruido urbano y la importancia de preservar el equilibrio acústico en los ecosistemas urbanos.

S. Schneider, Jean-Louis Barsoux

Majid Ghasemi, Mark Crowley

This paper critiques common patterns in machine ethics for Reinforcement Learning (RL) and argues for a virtue focused alternative. We highlight two recurring limitations in much of the current literature: (i) rule based (deontological) methods that encode duties as constraints or shields often struggle under ambiguity and nonstationarity and do not cultivate lasting habits, and (ii) many reward based approaches, especially single objective RL, implicitly compress diverse moral considerations into a single scalar signal, which can obscure trade offs and invite proxy gaming in practice. We instead treat ethics as policy level dispositions, that is, relatively stable habits that hold up when incentives, partners, or contexts change. This shifts evaluation beyond rule checks or scalar returns toward trait summaries, durability under interventions, and explicit reporting of moral trade offs. Our roadmap combines four components: (1) social learning in multi agent RL to acquire virtue like patterns from imperfect but normatively informed exemplars; (2) multi objective and constrained formulations that preserve value conflicts and incorporate risk aware criteria to guard against harm; (3) affinity based regularization toward updateable virtue priors that support trait like stability under distribution shift while allowing norms to evolve; and (4) operationalizing diverse ethical traditions as practical control signals, making explicit the value and cultural assumptions that shape ethical RL benchmarks.

Lawrence W. Abrams

It is time to move on from attempts to make the pharmacy benefit manager (PBM) reseller business model more transparent. Time and time again the Big 3 PBMs have developed opaque alternatives to piece-meal 100% pass-through mandates. Time and time again PBMs have demonstrated expertise in finding loopholes in state government disclosure laws. The purpose of this paper is to provide quantitative estimates of two transparent insurance business models as a solution to the PBM agency issue. The key parameter used is an 8% gross profit margin figure disclosed by the Big 3 PBMs themselves. Based on reported drug trend delivered to plans, we use a $1,200 to $1,500 per member per year (PMPY) as the range for this key performance indicator (KPI). We propose that discussions of PBM insurance business models start with the following figures: (1) a fixed premium model with medical loss ratio ranging from 92% to 85%; (2) a fee-for-service model ranging from $96 to $180 PMPY with risk sharing of deviations from a contracted PMPY delivered drug spend.

Maryam Sayad Shirazi, Iman Zaghian

The aim of this research is to investigate and analyze the level of religious commitment among female students, considering the influence of attachment styles, identity styles, and family functioning. The research employed the structural equation modeling method. The statistical population consisted of students from Al-Zahra University, with 387 participants selected using non-random available sampling, including 287 single and 31 married individuals.According to the findings of this research, there is a positive and significant relationship between informational, normative, and commitment identity styles with religious commitment, with correlation coefficients of r = 0.283, r = 0.552, and r = 0.396 respectively (p ≤ 0.05). The dimensions of family functioning also show a positive and significant relationship with religious commitment, with a correlation coefficient of r = 0.453. Furthermore, a positive and significant relationship was found between secure attachment style and religious commitment, with a correlation coefficient of r = 0.410. Conversely, avoidant and ambivalent attachment styles exhibit significant negative relationships with religious commitment, with correlation coefficients of r = -0.283, r = -0.254, and r = -0.252 respectively (p ≤ 0.05).Based on these findings, it can be concluded that identity styles and attachment styles have an impact on the level of religious commitment among female students, with family functioning mediating this relationship. ‌Keywords Identity, Attachment, Female Students, Religious Commitment, Family ‌‌IntroductionReligion is a profoundly significant phenomenon with profound effects on human life. Commitment and belonging to religion lead to positive changes in a person's life, including increased life satisfaction, happiness, and overall health.One component closely related to religious commitment is identity styles. Various classifications exist in this regard, with two prominent examples being those of Berzonsky and Marcia. Marcia categorizes identity into four types: achieved, foreclosed, confused, and diffused. Berzonsky, on the other hand, categorizes identity as informational, normative, and diffuse/avoidant.Attachment styles, another aspect investigated in this research concerning religious commitment, originate from attachment theory developed by John Bowlby and Mary Ainsworth in 1992. This theory categorizes attachment into two main styles: secure and insecure. Insecure attachment is further divided into three categories: avoidant, ambivalent, and disorganized (Mamarian et al., 1991).Furthermore, religiosity is believed to enhance family functioning. According to Islamic teachings, an efficient family is one where members are committed to religious beliefs, Islamic laws, and ethics, fostering the nurturing and discovery of individuals' talents. This research aims to investigate the relationships between various attachment and identity styles and their impact on religious commitment, with family functioning serving as a potential mediator. MethodologyThe method used in this research is descriptive correlational structural equation modeling (path analysis). The target statistical population in this research includes students of Al-Zahra University (approximately 9,400 people). A sample of 318 individuals was selected using non-random sampling (availability sampling). The software used for analysis in this research included SPSS 26 and Amos 26. The tools used in this research included the religious commitment questionnaire by Jan-Borzuri, Berzonsky's identity style questionnaire, and Collins and Reed's adult attachment style questionnaire. FindingsBased on the results obtained, the relationship between informational identity style, normative identity style, and commitment identity style with religious commitment is positive, with values of r = 0.283, r = 0.552, and r = 0.396, respectively. These relationships are significant (p < 0.05). However, the relationship between avoidant identity style and religious commitment is not statistically significant (p ≥ 0.05).Furthermore, the relationship between dimensions of family functioning and religious commitment, with a value of r = 0.453, is positive and meaningful. Additionally, the relationship between secure attachment style and religious commitment, with r = 0.410, is positive and significant. On the other hand, the relationships between avoidant and ambivalent attachment styles with religious commitment, with values of r = 0.283 and r = 0.254, respectively, are significant. The negative relationship with r = -0.252 is also significant (p ≥ 0.05). It should be noted that the correlation matrix between the variables is significant at the p < 0.01 level.Based on the results obtained, the direct effect of secure attachment style on family functioning (0.36), avoidant attachment style on family functioning (-0.15), and ambivalent attachment style on family functioning (-0.20) is statistically significant. Similarly, the direct effect of secure attachment style on religious commitment (0.27) and family functioning on religious commitment (0.35) is also significant.Regarding the direct effects of identity styles and commitment on family functioning, it was found that the direct effect of informational identity style and commitment on family functioning was not significant. However, the direct effects of normative identity style and avoidant identity style on family functioning are statistically significant, with coefficients of 0.31 and -0.24, respectively.Moreover, the direct effect of normative identity style on religious commitment (0.47) was found to be significant. Conversely, the direct effects of avoidant and ambivalent attachment styles and commitment on religious commitment were not significant. Non-significant paths were consequently removed from the equation to improve the model fit. In all significant paths, the absolute values of t exceed ±1.96, indicating the significance of these paths. Sobel's test was employed to ascertain the significance of the relationship between the pattern of religious commitment based on attachment style and the mediation of family functioning. ResultIn this research, these two questions were addressed, revealing that avoidant and normative identity styles exert a reverse effect, while others have a direct impact on an individual's religious adherence. Additionally, the secure attachment style plays a direct and indirect role, mediated by family functioning, whereas avoidant and ambivalent attachment styles exhibit a negative and significant relationship solely through mediation by family functioning.Thus, it should be emphasized that the family serves as the most crucial foundation for fostering self-awareness and psychological well-being in individuals. 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Elvys Linhares Pontes, Mohamed Benjannet, Raymond Yung

Understanding the business cycle is crucial for building economic stability, guiding business planning, and informing investment decisions. The business cycle refers to the recurring pattern of expansion and contraction in economic activity over time. Economic analysis is inherently complex, incorporating a myriad of factors (such as macroeconomic indicators, political decisions). This complexity makes it challenging to fully account for all variables when determining the current state of the economy and predicting its future trajectory in the upcoming months. The objective of this study is to investigate the capacity of machine learning models in automatically analyzing the state of the economic, with the goal of forecasting business phases (expansion, slowdown, recession and recovery) in the United States and the EuroZone. We compared three different machine learning approaches to classify the phases of the business cycle, and among them, the Multinomial Logistic Regression (MLR) achieved the best results. Specifically, MLR got the best results by achieving the accuracy of 65.25% (Top1) and 84.74% (Top2) for the EuroZone and 75% (Top1) and 92.14% (Top2) for the United States. These results demonstrate the potential of machine learning techniques to predict business cycles accurately, which can aid in making informed decisions in the fields of economics and finance.

Atahan Karagoz

Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering industries tools to generate diverse and sophisticated text and images with remarkable creativity and efficiency. This paper examines both the capabilities and challenges of these models within creative workflows. While they deliver high performance in generating content with creativity, diversity, and technical precision, they also raise significant ethical concerns. Our study addresses two key research questions: (a) how these models perform in terms of creativity, diversity, accuracy, and computational efficiency, and (b) the ethical risks they present, particularly concerning bias, authenticity, and potential misuse. Through a structured series of experiments, we analyze their technical performance and assess the ethical implications of their outputs, revealing that although generative models enhance creative processes, they often reflect biases from their training data and carry ethical vulnerabilities that require careful oversight. This research proposes ethical guidelines to support responsible AI integration into industry practices, fostering a balance between innovation and ethical integrity.

Urszula Jessen, Dirk Fahland

Anomalies in complex industrial processes are often obscured by high variability and complexity of event data, which hinders their identification and interpretation using process mining. To address this problem, we introduce WISE (Weighted Insights for Evaluating Efficiency), a novel method for analyzing business process metrics through the integration of domain knowledge, process mining, and machine learning. The methodology involves defining business goals and establishing Process Norms with weighted constraints at the activity level, incorporating input from domain experts and process analysts. Individual process instances are scored based on these constraints, and the scores are normalized to identify features impacting process goals. Evaluation using the BPIC 2019 dataset and real industrial contexts demonstrates that WISE enhances automation in business process analysis and effectively detects deviations from desired process flows. While LLMs support the analysis, the inclusion of domain experts ensures the accuracy and relevance of the findings.

Stanisław Ciupka

The article argues that the goal of business is to increase profit, but it also recognizes that proper relationships must exist between the entrepreneur and employees, customers, the state, and society at large. These relationships are deemed necessary for business to occur, and additional relationships, such as those with contractors, the media, and the natural environment, may also be relevant. The ethical aspects of business are inseparable from the ethical problems present in society. Undesirable behaviors within business activities are discussed as morally reprehensible, affecting both business conduct and generating moral dilemmas within society. Economic issues are noted as playing a significant role in contemporary society, often becoming modern idols. Consequently, there is a growing call for proper ethical conduct in the business world to address these concerns and ensure the common good. The article highlights that answers within the realm of business ethics are influenced by researchers' ethical and economic perspectives. The distinction between entrepreneurs and managers is emphasized, with the latter often assuming entrepreneurial roles. This separation raises concerns regarding the alignment of owners' moral obligations with the goals and commitments of managerial staff. Shareholder interests, primarily focused on profit maximization, sometimes

Dennis O'Higgins

Despite the critical importance of Digital Transformation, up to 95% of initiatives fail to deliver expected business benefits. This paper explores the role of Business Architecture practices in enhancing digital transformation success. Using an adapted Balanced Scorecard approach and a Structural Equation Model (SEM), we analysed survey responses from 129 industry practitioners using a Partial Least Squares (PLS) approach. Our findings indicate that effective business architecture practices significantly improve business alignment, efficiency, service delivery, and strategic outcomes, leading to successful digital transformation. The study also validates factors proposed by AL-Malaise AL-Ghamdi (2017) in the context of digital transformation. The paper presents an adapted conceptual model addressing discriminant validity issues in previous models and benefiting from the robustness of the Balanced Scorecard approach. The study concludes by highlighting the essential role of business architecture in driving digital transformation success.

Javane Rostampoor, Roghayeh Joda, Mohammad Dindoost

In order to address the need for more capacity and coverage in the 5th generation (5G) of wireless networks, ultra-dense wireless networks are introduced which mainly consist of indoor small cells. This new architecture has paved the way for the advent of a new concept called Micro Operator. A micro operator is an entity that provides connections and local 5G services to the customers and relies on local frequency resources. We discuss business models of micro operators in a 5G coopetitive environment and develop a framework to indicate the business model canvas (BMC) of this new concept. Providing BMC for new businesses is a strategic approach to offer value to customers. In this research study, BMC and its elements are introduced and explained for 5G micro operators.

Giada Pistilli, Carlos Munoz Ferrandis, Yacine Jernite et al.

The growing need for accountability of the people behind AI systems can be addressed by leveraging processes in three fields of study: ethics, law, and computer science. While these fields are often considered in isolation, they rely on complementary notions in their interpretation and implementation. In this work, we detail this interdependence and motivate the necessary role of collaborative governance tools in shaping a positive evolution of AI. We first contrast notions of compliance in the ethical, legal, and technical fields; we outline both their differences and where they complement each other, with a particular focus on the roles of ethical charters, licenses, and technical documentation in these interactions. We then focus on the role of values in articulating the synergies between the fields and outline specific mechanisms of interaction between them in practice. We identify how these mechanisms have played out in several open governance fora: an open collaborative workshop, a responsible licensing initiative, and a proposed regulatory framework. By leveraging complementary notions of compliance in these three domains, we can create a more comprehensive framework for governing AI systems that jointly takes into account their technical capabilities, their impact on society, and how technical specifications can inform relevant regulations. Our analysis thus underlines the necessity of joint consideration of the ethical, legal, and technical in AI ethics frameworks to be used on a larger scale to govern AI systems and how the thinking in each of these areas can inform the others.

Kenneth E. Goodpaster

Much has been written about stakeholder analysis as a process by which to introduce ethical values into management decision-making. This paper takes a critical look at the assumptions behind this idea, in an effort to understand better the meaning of ethical management decisions. A distinction is made between stakeholder analysis and stakeholder synthesis. The two most natural kinds of stakeholder synthesis are then defined and discussed: strategic and multi-fiduciary. Paradoxically, the former appears to yield business without ethics and the latter appears to yield ethics without business. The paper concludes by suggesting that a third approach to stakeholder thinking needs to be developed, one that avoids the paradox just mentioned and that clarifies for managers (and directors) the legitimate role of ethical considerations in decision-making. So we must think through what management should be accountable for; and how and through whom its accountability can be discharged. The stockholders’ interest, both short- and long-term, is one of the areas. But it is only one. Peter Drucker, 1988 Harvard Business Review

Abderrahmane Benlahcene, Oussama Saoula, Mathivannan Jaganathan et al.

IntroductionThe challenge of restricting unethical behavior requires public companies to reinforce ethical practices among leaders through various instruments. Previous research suggests that the (un)ethical behavior of leaders can be influenced by many situational factors. This study aimed to investigate the influence of ethics training and education on unethical leadership behavior in the Algerian public companies.MethodsData were collected through semi-structured interviews with 15 leaders from public companies in Algeria. Data analysis was facilitated using ATLAS. ti 8 qualitative analysis software.ResultsThe findings show that public companies in Algeria suffer from several issues related to leaders’ ethics training and education. The findings also indicate that some of these unethical leadership behaviors are the result of ineffective training programs and poor ethics education within public companies.DiscussionThe absence or ineffectiveness of ethics training and education within and outside organizational settings has a detrimental impact on leaders’ ethical character. This study is the first to explore how public companies in Algeria engage in ethical training and leadership education. The different sectors of the Algerian business can use the findings as a point of reference to embed the appropriate ethical climate in their respective organizations.

Zdeněk Caha, Jan Urban, Tomáš Mrhálek

Over the long-term, companies, their managements and even employees have been facing increasing external demands from customers, business partners, as well as wider society, to behave ethically. At the same time, similar demands and requirements have been coming from within companies themselves in relation to performance management and employee motivation. These demands are placing greater emphasis on the need for ethical management and a code of ethics as the primary tool for promoting and enforcing the ethical conduct of an organisation, its management and employees. This paper focuses on the prevalence and role of codes of ethics in Czech companies, their goals and contents, the principles behind their creation and enforcement, as well as the main prerequisites for their efficacy. It is based on an extensive longitudinal analysis of a broad sample of 1,242 Czech companies of various sizes, the main aim of which was to determine the aforementioned and, in addition, whether those companies that have created codes of ethics, strengthen the consistency of their use by regularly evaluating and updating their contents.

Ayman Al Armoti, Hamad Abdullah Al Meqbali , Abdullah Saleh Noor

Business ethics not only upgrades the corporations’ working standards but also innovates employees’ aptitude for effective project management. Due to business ethics implementation, Emaar Properties is a multinational real estate developmental corporation. In Emaar Properties, business ethics casts a beneficial impact on stakeholders’ involvement, employee loyalty, and consumers’ satisfaction with the latest product portfolio. This paper yields the business ethics practices within Emaar and the reasons for being engaged in such practices. Moreover, the paper inspects Emaar’s ethical behavior in several activities, scrutinizes if the company has ever been penalized for any unethical behavior, and provides some essential recommendations for management concerning ethical behaviors.

Gyunam Park, Wil. M. P. van der Aalst

Constraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 hours after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e.g., a patient in a healthcare process, and each event is associated with the case notion. However, in reality, business processes are object-centric, i.e., multiple case notions (objects) exist, and an event may be associated with multiple objects. For instance, an Order-To-Cash (O2C) process involves order, item, delivery, etc., and they interact when executing an event, e.g., packing multiple items together for a delivery. The existing techniques produce misleading insights when applied to such object-centric business processes. In this work, we propose an approach to monitoring constraints in object-centric business processes. To this end, we introduce Object-Centric Constraint Graphs (OCCGs) to represent constraints that consider the interaction of objects. Next, we evaluate the constraints represented by OCCGs by analyzing Object-Centric Event Logs (OCELs) that store the interaction of different objects in events. We have implemented a web application to support the proposed approach and conducted two case studies using a real-life SAP ERP system.

Josephine Meyer, Noah Finkelstein, Bethany Wilcox

Quantum information science (QIS) is an emerging interdisciplinary field at the intersection of physics, computer science, electrical engineering, and mathematics leveraging the laws of quantum mechanics to circumvent classical limitations on information processing. With QIS coursework proliferating across US institutions, including at the undergraduate level, we argue that it is imperative that ethics and social responsibility be incorporated into QIS education from the beginning. We discuss ethical issues of particular relevance to QIS education that educators may wish to incorporate into their curricula. We then report on findings from focus interviews with six faculty who have taught introductory QIS courses, focusing on barriers to and opportunities for incorporation of ethics and social responsibility (ESR) into the QIS classroom. Few faculty had explicitly considered discussion of ethical issues in the classroom prior to the interview, yet instructor attitudes shifted markedly in support of incorporating ESR in the classroom as a result of the interview process itself. Taking into account faculty's perception of obstacles to discussing issues of ESR in coursework, we propose next steps toward making ESR education in the QIS classroom a reality.

Shubham Thakar, Dhananjay Kalbande

Business intelligence (BI) is any knowledge derived from existing data that may be strategically applied within a business. Data mining is a technique or method for extracting BI from data using statistical data modeling. Finding relationships or correlations between the various data items that have been collected can be used to boost business performance or at the very least better comprehend what is going on. Root cause analysis (RCA) is discovering the root causes of problems or events to identify appropriate solutions. RCA can show why an event occurred and this can help in avoiding occurrences of an issue in the future. This paper proposes a new clustering + association rule mining pipeline for getting business insights from data. The results of this pipeline are in the form of association rules having consequents, antecedents, and various metrics to evaluate these rules. The results of this pipeline can help in anchoring important business decisions and can also be used by data scientists for updating existing models or while developing new ones. The occurrence of any event is explained by its antecedents in the generated rules. Hence this output can also help in data-driven root cause analysis.