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The purpose of this paper is to address the formulation, implementation, and adaptation of closely coupled multi‐physics problems with h‐ and p‐adaptive finite element methods. A general formulation is chosen allowing for coupled problems of various types. Adaptation algorithms for h‐ and p‐refinement are given.

A generic system of second‐order differential equations is used, where the field of each individual problem is represented as an entry in the list of field variables. Specific problems are implemented by mapping material coefficients to the coefficients of the generic form. An example with four natures is investigated with close coupling between electric, mechanical and thermal fields. h‐ and p‐refinement using a single mesh is considered, where the element order may differ for individual fields.

In coupled problems, the error in each single field is affected by approximation properties of all other field quantities. In order to allow for optimal convergence order in the number of degrees of freedom, the error contributions of all fields have to be considered. Separate error estimation in each field is needed especially in h‐adaptation on a single mesh. Energy coupling coefficients were introduced to derive an adaptation criterion. Convergence analysis of h‐ and p‐adaptation proves the feasibility of the approach.

Piezopyroelectricity considers thermal effects in high‐frequency piezoelectric materials, which is a coupled problem of four natures. The paper introduces an adaptation criterion for such complicated coupled problems and proves feasibility.

This paper aims to show that simple geometry‐based hp‐algorithms using an explicit a posteriori error estimator are efficient in wave propagation computation of complex structures containing geometric singularities.

Four different hp‐algorithms are compared with common h‐ and p‐adaptation in electrostatic and time‐harmonic problems regarding efficiency in number of degrees of freedom and runtime. An explicit a posteriori error estimator in energy norm is used for adaptive algorithms.

Residual‐based error estimation is sufficient to control the adaptation process. A geometry‐based hp‐algorithm produces the smallest number of degrees of freedom and results in shortest runtime. Predicted error algorithms may choose inappropriate kind of refinement method depending on p‐enrichment threshold value. Achieving exponential error convergence is sensitive to the element‐wise decision on h‐refinement or p‐enrichment.

Initial mesh size must be sufficiently small to confine influence of phase lag error.

Information on implementation of hp‐algorithm and use of explicit error estimator in electromagnetic wave propagation is provided.

The paper is a resource for developing efficient finite element software for high‐frequency electromagnetic field computation providing guaranteed error bound.

The purpose of this paper is to investigate how the service constellation perspective affects innovation strategies and potentially contributes to the innovation literature, proposing a research agenda.

By analyzing the notion of a service constellation, the authors provide an overview of major implications for service innovation research and practice.

Firms and service innovation researchers need to focus on the perceived consumer value of the constellation rather than on individual services. The authors illustrate how service innovation from the constellation perspective requires coordination and synchronization between projects and different approaches to portfolio management and screening.

Adoption of the service constellation perspective creates new opportunities.

This paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest's four-component model of antecedents for ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners.

This research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning the years 2015–2020. This review's narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods.

In the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest's component model of antecedents for ethical decision-making as a stable framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI.

This paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest's model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.

When CEOs are publicly weighing in on sociopolitical debates, this is known as CEO activism. The steadily growing number of such statements made in recent years has been subject to a flourishing academic debate. This field offers first profound findings from observational studies. However, the discussion of CEO activism lacks a thorough theoretical grounding, such as a shared concept accounting for the heterogeneity of sociopolitical incidents. Thus, the aim of this paper is to provide an archetypal framework for CEO activism.

The authors used a multiple case study approach on 145 activism cases stated by CEOs and found seven distinct statement archetypes.

The study identifies four main structural design elements accounting for the heterogeneity of activism, i.e. the addressed meta-category of the statement, the targeted outcome, the used tonality and the orientation of the CEOs’ positions. Further, the authors found seven distinguishable archetypes of CEO activism statements: “Climate Alerts”, “Economy Visions”, “Political Comments”, “Self-reflections and Social Concerns”, “Tech Designs”, “Unclouded Evaluations” and “Descriptive Explanations”.

This typology classifies the heterogeneity of CEO activism. It will enable the analysis of interrelationships, mechanisms and motivations on a differentiated level and raise the comprehensibility of research-results.

The framework supports executives in understanding the heterogeneity of CEO activism and to analyse personality-fits.

To the authors’ knowledge, this marks the first conceptualisation of activism developed cross-thematically. The work supports further theory-building on CEO activism.

A recent stream of research has focused on typicality associations – those that bring origins and products together. Most of the research has focused on typical products but atypical products have received very little attention, even though they are more and more present on the market. As it has yet to be reviewed, the relationship between intrinsic and extrinsic product cues and product evaluations is examined in this paper for typical and atypical origin products.

Wine was used as the stimulus, and consumer evaluations of typical and atypical wines were reviewed. Consumers were segmented based on their knowledge of the product category. French respondents (n = 370) participated in an online questionnaire regarding the product cues they found most important, depending on if the wine was from the New World or the Old World.

The results show that extrinsic cues are just as important as intrinsic cues in the evaluation of origin products, contrary to what prior research suggests. Furthermore, consumer knowledge moderates the evaluations of origin products; the results empirically confirms the theoretical country of origin – elaboration likelihood model (CoO-ELM) proposed by Bloemer et al. (2009) for atypical origin products, but show typical products are evaluated differently.

This is the first study that empirically tests the CoO-ELM and includes the added dimension of typicality. The results allow for a better understanding of consumer perceptions of origin products and their cues.