Marketer Behavior and Digital Ethics

The article conceptually substantiates the epistemological foundations of the digitalization of accounting-analytical support for enterprise management. It demonstrates that digital transformation reframes not only tools but also the very conditions of knowledge generation, validation, and legitimation in management. Within the digital paradigm, knowledge emerges from the interaction of people, data, algorithms, and technological infrastructures; an algorithmic rationality arises in which truth is anchored not solely in professional expertise but also in the properties of the information environment (performance, scalability, transparency, interoperability). The paper elucidates the ontological and gnoseological dimensions of digital knowledge: a shift from static, document-centric representations to dynamic dataflows that produce analytical insights via machine learning and artificial intelligence; a reorientation from retrospective to predictive reasoning; and a strengthened focus on data quality, metadata, and traceability. It argues for a role reconfiguration: accountants and analysts evolve into knowledge architects and curators of information streams who design cognitive models of business processes, tune algorithms, manage data risks, and ensure explainability. The study formulates methodological principles for a digital accounting-analytical system: synergy (holistic integration of accounting, analytics, IT, and management), reliability and transparency (verifiability of sources, quality assurance, immutability of records), cognitive adaptability (model self-learning, context sensitivity, scenario thinking), process intellectualization (from computation to interpretation and recommendation), and decision orientation (tight coupling of knowledge with managerial action and value creation). Implementing these principles yields a cognitive-technological enterprise milieu in which data become economic entities and knowledge a reusable asset supporting strategic planning, budgeting, compliance, and risk management. A conceptual framework is proposed for transitioning from a registration logic to a cognitive-algorithmic logic that integrates data governance, analytics, legal requirements, and ethical standards for AI use, ensuring reproducibility, explainability, and accountability of decisions. The scientific novelty lies in treating digitalization as an epistemic shift redefining the nature of truth in accountinganalytical systems and raising competency requirements to knowledge management. The practical significance is reflected in the design of adaptive, self-learning control loops that provide relevant, reliable, and predictive knowledge to enhance enterprise performance in the digital economy.

PurposeThis study aims to clarify the relationship between ethical orientation and earnings management perception phenomenon in the organization. It discusses to what extent earnings management is considered as a strategic adaptation or deliberate manipulation in an organization. The study also aims to expand the domain of ethical perspective of earnings management by considering mediating and moderating role of investor sentiment and corporate social responsibility (CSR) as inward pressure and outward commitment surrounding the organization, adopting a combined perspective of strategic management and also accounting discipline than is normally found in the ethics and earnings management literature.Design/methodology/approachThe study opted for literature synthesis to define key concepts surrounding ethics and earnings management perception in the organization. Besides, it attempted to identify influential mediators and moderators in explaining the earnings management phenomenon in the organization. Consequently, the study identified the gaps in current research to draw upon a more holistic conceptual framework. The rationale for the research was justified within the body of research.FindingsThe study suggested research propositions based on the literature synthesis in view of ethics and earnings management perception in the organization. More specifically, it has proposed a conceptual framework, explaining the relationship between ethical orientation and a multi-dimensional view of earnings management perception. It is envisaged that the mediating and moderating role of investor sentiment and CSR incorporated in this conceptual study will improve the predictive value of the proposed framework and offer additional insights about factors that inhibit or advance ethical orientation and earnings management practices in the organization.Research limitations/implicationsThis paper suffers from the obvious limitation of lacking empirical investigation. However, it does provide a theoretical rationale for the argument that alteration of earnings can be controlled if ethical orientation is emphasized in the organization apart from insulating internal and external pressures to manage such phenomenon from happening in the organization. Perhaps, the most important direction for future research is further extension and validation of this framework by performing an empirical investigation to produce newer insights into this phenomenon.Originality/valueThis conceptual study is different from previous studies on the grounds it has considered unexplored issues linking inward pressures and outward commitments in explaining this phenomenon further. To bridge the critical knowledge gap of earnings management phenomenon, a mediating effect of investor sentiment as an inward pressure and a moderating role of CSR as an outward commitment are also integrated within the model. The proposed model neither formulated nor tested empirically in previous studies locally or, perhaps, globally, therefore, stands out as an original contribution in the study of ethical orientation and earnings management perception.

Societal, Environmental and Stakeholder Drivers of Competitive Advantage in International Firms

Purpose of the study: The purpose of this paper is to examine the determinant factors that influence consumer switching intentions from conventional banks to Islamic banks in Central Java, Indonesia.
 Methodology: This study is quantitative research in which data is collected by using a survey with the questionnaire. Data was collected by distributing questionnaires to 480 Muslim respondents who were still registered as customers at three conventional government banks in Indonesia using purposive sampling techniques and analyzed with SEM-AMOS v24.
 Main Findings: The result showed that all out of the hypotheses tested, there is only one hypothesis that was rejected, is the fourth hypothesis. This research reveals that consumer trust in Islamic banks, consumer awareness and religiosity had a positive and significant effect on attitude toward Islamic banks. Furthermore, consumer awareness and religiosity are also able to predict consumer switching intentions at Islamic banks but consumer trust toward Islamic banks has insignificant consumer switching intentions at Islamic banks.
 Applications of this study: Based on the results of the study, conventional bank consumers' intentions to switch to Islamic banks are influenced by consumer awareness, level of religiosity, and consumer attitudes toward Islamic banks. Furthermore, this is becoming a very important concern for Islamic banks to pay more attention to the antecedents used in this study. Trust is an important predictor for companies in increasing intentions, in this study then it has not been proven to influence consumer intentions to move to Islamic banks. Trust will be able to increase intention if consumers have a good attitude towards Islamic banks.
 Novelty/Originality of this study: This study linked the variables of consumer awareness, religiosity, consumer trust, attitudes toward Islamic banks and consumer switching intentions on Islamic banks within a conceptual framework.

Luciano Floridi’s Information Ethics (IE) is a new theoretical foundation of Ethics. According to Floridi, ICT with all informational structures and processes generates our new informational habitat, the Infosphere. For IE, moral action is an information processing pattern. IE addresses the fundamentally informational character of our interaction with the world, including interactions with other agents. Information Ethics is macro-ethics as it focuses on systems/networks of agents and their behavior. The IE’s capacity to study ethical phenomena on the basic level of underlying information patterns and processes makes it unique among ethical theories in providing a conceptual framework for fundamental level analysis of present globalised ICT-based world. It allows computational modeling – a powerful tool for study which increases our understanding of informational mechanisms of ethics. Computational models help capturing behaviors invisible to unaided mind which relies exclusively on shared intuitions. The article presents an analysis of the application of IE as interpreted within the framework of Info-Computationalism. The focus is on responsibility/accountability distribution and similar phenomena of information communication in networks of agents. Agent-based modeling enables studying the increasing complexity of behavior in multi-agent systems when agents (actors) are ranging from cellular automata to softbots, robots and humans. Autonomous, learning artificial intelligent systems technologies are developing rapidly, resulting in a new division of tasks between humans and robots/softbots. The biggest present-day concern about autonomous intelligent systems is the fear of human loss of control and robots acting inappropriately and causing harm. Among inappropriate kinds of behavior is the ethically unacceptable one. In order to assure ethically adequate behavior of autonomous intelligent systems, artifactual ethical responsibility/accountability should be one of the built-in features of intelligent artifacts. Adding the requirement for artifactual ethical behavior to a robot/softbot does not by any means take responsibility from humans designing, producing and controlling autonomous intelligent systems. On the contrary, it will make explicit the necessity for all involved with such intelligent technology to assure its ethical conduct. Today’s robots are used mainly as complex electromechanical tools and do not have any capability of taking moral responsibility. But technology progress is remarkable; robots are quickly improving their sensory and motor competencies, and the development of artifactual (synthetic) emotions adds new dimensions to robotics. Artifactual reasoning and other information processing skills are advancing – all of which is causing significant progress in the field of Social Robotics. We have thus strong reasons to try to analyze future technological development where robots/softbots are so intelligent and responsive that they possess artifactual morality alongside with artifactual intelligence. Technological artifacts are always part of a broader socio-technological system with distributed responsibilities. The development of autonomous, learning, morally responsible intelligent agents relies consequently on several responsibility feedback loops; the awareness and preparedness for handling risks on the side of designers, producers, implementers, users and maintenance personnel as well as the support of the society at large which will provide a response on the consequences of the use of technology. This complex system of shared responsibilities should secure a safe functioning of hybrid systems of humans and intelligent machines. Information Ethics provides a conceptual framework for computational modeling of such socio-technological systems. Apart from examples of specific applications of IE, interpretation of several widely debated questions, such as the role of Levels of Abstraction, naturalism and complexity/diversity in Information Ethics, is offered through Info-Computationalist analysis.

The increasing integration of Artificial Intelligence (AI) in e-commerce has transformed digital marketing strategies, particularly through personalized recommendation systems. However, this advancement has raised ethical concerns regarding data privacy, algorithmic transparency, and consumer autonomy. In Southeast Asia, where digital platforms rapidly expand, these concerns become more complex due to diverse regulatory landscapes and user expectations. This study aims to analyze and compare the transparency of AI-based recommendation systems across three major e-commerce platforms in the region: Shopee, Lazada, and Tokopedia. A qualitative comparative approach was employed using content analysis of official policy documents, including privacy policies and AI guidelines, sourced from each platform between January and March 2024. The analysis utilized LLM-assisted text mining and thematic coding to identify ethical indicators such as algorithmic transparency, user control, and policy readability. The results reveal significant variation in ethical practices: Shopee scored the highest in all dimensions, including algorithmic transparency (score: 9/10), user control (8/10), and policy readability (9/10). Lazada ranked moderately with scores of 6/10, 4/10, and 6/10 respectively, while Tokopedia scored lowest with 3/10 for transparency, 0/10 for user control, and 4/10 for readability. These disparities indicate that ethical communication and user empowerment remain uneven across platforms. This study contributes to the discourse on digital ethics by highlighting the need for regional standards in AI transparency and promoting user-centric ethical design. The findings provide valuable insights for policymakers, platform designers, and digital consumers navigating trust in algorithm-driven environments.

This paper aims to propose an Industry 4.0 implementation model relevant to the composite manufacturing industry and offer it to academia and manufacturing practice in order to aid successful change and adoption. The research scope is defined at an intersection of challenges within the composites industry, as well as Industry 4.0. A critical review of relevant papers was used to establish key trends and gaps in professional practice. Exposed challenges and opportunities were then synthesized to propose a conceptual framework for implementing Industry 4.0. Findings suggest that the predicted growth of the composites sector depends on the paradigm shift in manufacturing. Industry 4.0, including automation, and horizontally and vertically integrated business models are seen as enablers. However, the value proposition or organizational resistance in establishing such integration is not sufficiently addressed or understood by the industry. Achieving a successful design for manufacturing (DFM), or, more generally, design for excellence (DFX), is identified as the target performance objectives and key business process enablers used to introduce Industry 4.0 technology. The identified key gap in professional practice indicate the lack of a model used for structuring and implementing Industry 4.0 technology into composite businesses. The existence of an identified gap, evidenced by the lack of literature and available knowledge, reinforces the need for further research. To enable further research, and to facilitate the introduction of Industry 4.0 in composite manufacturing firms, a conceptual implementation framework based on the systems engineering V model is proposed. The paper concludes with topics for further investigation.

The convergence of Artificial Intelligence (AI) and green marketing has become a pivotal topic in shaping sustainable consumer behavior amid global digital transformation and environmental challenges. However, previous studies remain fragmented, focusing separately on technological efficiency or environmental ethics without providing an integrated understanding of their intersection. This study aims to map and analyze global research trends on the integration of AI and green marketing strategies in influencing sustainable consumer behavior. Using a Systematic Literature Review (SLR) approach guided by the PRISMA protocol, this research systematically identified, screened, and synthesized peer-reviewed articles published between 2015 and 2025 across leading academic databases such as Scopus and Google Scholar. The analysis reveals an evolutionary trajectory of research from conceptual frameworks and ethical foundations toward data-driven personalization, transparency, and algorithmic accountability. Findings show that AI is increasingly recognized not only as a technological enabler but also as a strategic and ethical catalyst capable of enhancing consumer awareness, credibility, and engagement in sustainability-oriented marketing ecosystems. This synthesis highlights a paradigm shift where intelligent systems contribute to behavioral transformation by aligning digital innovation with ecological responsibility. The study concludes that integrating AI and green marketing provides a new framework for ethical, data-informed, and sustainability-driven marketing practices that support both environmental goals and consumer well-being.

Alongside the general and theoretical principles of information ethics and library ethics, this volume discusses ethical conflicts and dilemmas in professional library and information practice. Academically informed statements on information ethics and library ethics are fundamental to the value-based standardization of library work and are helpful for making ethically sound decisions in professional practice.

Abstract: The rapid expansion of Artificial Intelligence (AI) and big data analytics has changed the ways that brands use to contact their customers. They now can communicate directly with the consumer by using hyper, personalized marketing instead of traditional segmentation (Hemantha, Reddy, & Kamble, 2025). Hyper, personalisation is an AI, driven process where algorithms automatically generate marketing messages, content, and user experiences that best suit each consumer by analysing a large volume of data such as the route a user takes while browsing, purchase history, GPS coordinates, and preferences that are inferred (Al Prince et al., 2022). These programs, when used properly, draw in customers, increase the rate of transactions, and thus, long, term loyalty is solidified (Mulyono & Saputra, 2024). Nevertheless, they compromise consumers' privacy very deeply. The switch to behavioural and contextual data as a source of information has led to the emergence of challenges of ethical, regulatory, and trust kinds, as users, in most cases, have no power over the way their data are harvested, treated, and employed for automated decision, making (Gupta, Sharma, & Mathew, 2025). Literature findings imply that consumers demand relevance and ease of use, however, they voice uneasiness and reluctance when personalisation invades their privacy rights, thus marking the so, called "creepiness threshold" (Beniwal, Khanna, & Kaur, 2025). Furthermore, lawful regimes like the EU’s General Data Protection Regulation (GDPR) and India’s Digital Personal Data Protection Act (DPDPA) require that entities observing norms of data minimisation, acquiring clear consent, and algorithmic transparency be fulfilled (Mulyono & Saputra, 2024). Marketers are having a hard time strategically balancing these legal mandates with their endeavor for personalisation on a large scale. This paper discusses the increasing compromise between the scalability of hyper, personalisation and the safeguarding of consumer privacy in AI, powered marketing ecosystems. It thoroughly examines present literature, pinpoints the technological and organisational contributors to large, scale personalisation, and deliberates the ethical and regulatory restrictions accompanying data, driven marketing practices (Gupta et al., 2025). A conceptual framework is put forward to depict the interplay between scale, perceived benefits, privacy risks, and consumer trust. The research ends with the viewpoint that enduring hyper, personalisation is contingent on the implementation of privacy, by, design, transparency, and user empowerment principles (Tran et al., 2025), which give assurance to organisations that they are able to use AI in a responsible manner while at the same time, keep consumer trust and abide by regulations. Keywords: Hyper-personalisation, AI-powered marketing, consumer privacy, scale, ethical marketing, data protection.

Religious beliefs are widely recognised as shaping individuals' ethical orientations, behavioural tendencies, and interpersonal interactions. However, their specific influence on job performance within labour-intensive sectors such as construction remains insufficiently examined. This study explores the relationship between religiosity and job performance among construction site workers in selected states of Southwest Nigeria. A structured questionnaire was distributed to 396 construction site managers and supervisors, resulting in 289 completed surveys (73.0% response rate). Following data cleaning, 263 valid responses (66.4%) were subjected to both descriptive and inferential statistical analysis. Key performance indicators assessed included punctuality, quality of workmanship, safety compliance, and teamwork. The Kruskal–Wallis H test was employed to examine differences in performance outcomes across religious affiliations. Results indicated no statistically significant differences in any of the 27 performance variables across religious groups (p > 0.05), suggesting that religiosity does not serve as a determinant of job performance in this context. These findings imply that worker effectiveness in the construction sector is more closely associated with individual competencies and professional practices than with religious identity. The study underscores the value of merit-based workforce evaluation and advocates for inclusive policies that accommodate religious diversity without bias. Implications are offered for industry practitioners, policymakers, and human resource managers seeking to enhance workforce productivity and cohesion in multi-religious construction environments.

This chapter examines how Industry 4.0 technologies can be strategically repurposed beyond manufacturing to support human-centered, sustainable, and culturally embedded experiences in industrial-heritage tourism. While cyber-physical systems, artificial intelligence, and large-scale digitization have traditionally prioritized efficiency and automation, their potential to advance social, cultural, and environmental objectives remains underdeveloped. Building on recent scholarship in human-centered digitalization and the evolving paradigm of Industry 5.0, we propose the Human-Centered Heritage Experience Design Model – a conceptual framework that integrates augmented reality, virtual reality, mobile applications, and artificial intelligence-enhanced systems within heritage-driven industrial contexts. The model repositions technology as a facilitator of participatory engagement, digital storytelling, and stakeholder co-creation, emphasizing cultural authenticity, community agency, and socio-technical sustainability. Through illustrative application scenarios, we demonstrate how immersive technologies can enable inclusive learning, strengthen place-based identity, and reduce environmental impacts by minimizing reliance on physical infrastructure. At the same time, we address implementation challenges such as infrastructure disparities, digital ethics, institutional inertia, and cultural commodification. Ultimately, this work reframes Industry 4.0 tools as enablers of post-industrial regeneration, arguing that human-centered digitalization offers a viable pathway for aligning technological innovation with cultural preservation, community resilience, and the green transition in heritage tourism ecosystems.

The metaverse represents a rapidly evolving frontier in digital transformation, offering unprecedented opportunities for innovation in business and management. This paper explores current trends in the metaverse, analyzing its impact on various business sectors and management practices. Through a comprehensive review of existing literature and emerging case studies, this research identifies key trends, technological advancements, and strategic implications of the metaverse. The findings highlight the potential of the metaverse to revolutionize customer engagement, collaboration, and value creation, while also addressing challenges related to governance, security, and digital ethics.

The development and progress in information and communication technologies will transform traditional products into smart products and allow to offer novel smart services [1]. Herein, the digital twin (DT) concept is regarded as a key technology to create value with smart services [2]. Although the research and applications of DTs emerge continuously many concerns are to be scrutinized [3]. The lack of a shared conceptual framework for DTs with an unambiguous terminology [4] complicates cross-functional discussions. Therefore, a systematization of the main dimensions of DTs is proposed in the form of an ontology and a conceptual framework thereof derived. The research questions addressed in this paper are a) «Which dimensions are used to classify and structure DTs in academic literature?», b) «What are the fundamental differences or specifications within these dimensions?» and c) «How do these different specifications relate to each other?» The focus of the research is on the objective to find classification systematics that are a) representing the entire spectrum of DTs, b) universally valid in all DT related domains and c) applicable in research and practice. A systematic literature review on the relevant aspects of DTs was conducted and the findings iteratively advanced within workshop sessions with academic experts. DTs are considered as integrators of physical and digital worlds as well as internal and external value creation. Further, the creation of DTs requires per definition the use of digital data. Hence, the proposed ontology and conceptual framework for DTs include the following main dimensions to consider for every DT: Data resources, external value creation and internal value creation. The main subdimensions of the data resources are the data sources to obtain the data, the data categories and the data formats. The main subdimension of the external value creation are the attributes of the services as the basis of the value propositions, the level of smartness of the connected products and the actors on the different levels of the ecosystem. The main subdimensions of the internal value creation are the lifecycle phases of products, the product management levels and the different generations of both. The proposed ontology and conceptual framework support researchers and practitioners in positioning and structuring their intended DT activities and communicating them to internal and external stakeholders. The holistic view on the data resource dimension further allows to easily deduct the needed data for certain applications or deduct possible applications from already available data.

Object: The aim of the study is to determine the importance of consumer trust in value creation and to study how consumer trust influences their purchase decision and consumer loyalty.
 Methods: As it is shown in the scientific literature, several methods are used when writing a research paper, which are classified as field and desk, quantitative and qualitative. Typically, one or both of these may be used in a study. Depending on the purpose of our work in our study, at the first stage, we analyzed second-order information based on desk research. It was used to review scientific articles relevant to the topic of a previously published study. At the second stage of the study, we conducted an opinion poll using the method of quantitative research. The survey was conducted on the basis of a conceptual model and measuring scales of previous studies. To test the questionnaire developed for the survey, a pilot survey was organized for 40 respondents.
 To get answers to questions about who was conducted in research, how many of them should be, and how to se lect them, we conducted a selection using sources of scientific literature.
 Findings: The value of the study is specific, the significance of the work lies in the fact that our study considers the chain of consumer value creation in the production and sale of food products and involves the measurement of con sumer value in this chain based on factors that form consumer beliefs. In this regard, it complements the studies carried out so far on the problem of creating customer value.
 Conclusions: The results of the study can be considered when forming a chain of consumer value creation in the marketing activities of sausage manufacturers.