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Four professional public administrators returned to their alma mater to serve as role models, offer guidelines and cautions about working in highly political environments, and pose hypothetical case studies drawn from their own and others' experiences in such a setting. Counseling that the gravity and complexity of ethical dilemmas increase as one’s career advances, they suggest that the tensions between politics and policy figure among the more serious sources of ethical challenges facing professionals in the public sphere. While proposing that the professional’s duty in part is to empower elected officials to make the right decision with the best information and most useful tools, they note that some frustration is unavoidable in this complex environment; there are no easy answers because the issues themselves are not easy and perspectives about what is right and important vary. Centering on the duty of serving the public interest, their cases focus upon mixed allegiances, clashing loyalties, multiple perspectives, truthfulness and candor, privileged treatment, the appearance of impropriety, and accountability

The emergence of climate science denialism in the United States provides a challenge to STS theories of the relationship between scientific expertise and public policy because a situation of epistemic rift occurs: the capacity of scientific consensus to establish the grounds of political debate is broken, and the standard circulation of expertise from the scientists and funding from the state is interrupted. Three mechanisms for the containment of scientific expertise are studied: direct intellectual suppression of climate scientists, industry support of contrarian scientists and policymakers, and cutbacks on government research programs that support climate change. This situation politicizes climate scientists, who are drawn into the public sphere as a counterpublic to the effort to contain the circulation of their knowledge in the political field. Although the strategy of contained expertise has been effective in blocking climate legislation at the federal government level in the United States, it may be losing effectiveness, and an emergent alternative strategy based on adaptation may be coming to replace it. Factors that affect the reduction in the capacity to contain the circulation of scientific expertise are also analyzed.

This paper gives a bibliographical review of the finite element methods (FEMs) applied to the analysis of ceramics and glass materials. The bibliography at the end of the paper contains references to papers, conference proceedings and theses/dissertations on the subject that were published between 1977‐1998. The following topics are included: ceramics – material and mechanical properties in general, ceramic coatings and joining problems, ceramic composites, ferrites, piezoceramics, ceramic tools and machining, material processing simulations, fracture mechanics and damage, applications of ceramic/composites in engineering; glass – material and mechanical properties in general, glass fiber composites, material processing simulations, fracture mechanics and damage, and applications of glasses in engineering.

Organizations deal with digital technologies to achieve their strategic goals. The shift toward digitization is a major challenge because it requires companies to create a digital outlook that influences organizational design. As a result, investigation of institutional theory and entrepreneurial orientation theory in the European food industry has become the focus of research in recent times.

To this end, data were collected from 83 companies related to the food industry in the European context. By applying a hybrid phase of the partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) methods, this study captured the causal–non-linear relationships among the study constructs.

The findings revealed that the variables of institutional theory and entrepreneurial orientation theory affect the adoption of the digital strategy. There is also a dual interaction role for e-business capabilities and digital transformation. The results of non-linear relationships confirmed that digital strategy adoption is highly influenced by digital transformation, followed by risk-taking, digital leadership, e-business capabilities, organizational agility, proactiveness and innovativeness.

The authors provided significant implications for practitioners and academics about the most influential determinants of digital strategy – businesses must move swiftly toward digitization across its various units to achieve their objectives. An organization’s leadership must realize that equipping the employees with necessary skills is the first step toward digitalization.

The current study underscores the digital strategy, which is usually an overlooked area of investigation, in the food industry. The study identifies some important predictors of digital strategy adoption with the interaction’s role of digital transformation and e-business capabilities. Such relationships have been rarely discussed. In addition, the adoption of a hybrid SEM-AAN approach makes the study an original one.

Sellers view facial recognition mobile payment services (FRMPS) as a convenient and cost-saving way to receive immediate payments from customers. For consumers, however, these biometric identification technologies raise issues of usability as well as privacy, so FRMPS are not always preferable. This study uses the stressor–strain–outcome (S–S–O) framework to illuminate the underlying mechanism of FRMPS resistance, thereby addressing the paucity of research on users' negative attitudes toward FRMPS.

Drawing from the stressor–strain–outcome (S–S–O) framework, the purpose of this study is to illuminate the underlying mechanism of FRMPS resistance. To this end, they invited 566 password authentication users who had refused to use FRMPS to complete online survey questionnaires.

The findings enrich the understanding of FRMPS resistance and show that stressors (i.e. system feature overload, information overload, technological uncertainty, privacy concern and perceived risk) aggravate the strain (i.e. technostress), which then leads to users’ resistance behaviors and negative word of mouth.

Advances in payment methods have profoundly changed consumers’ consumption and payment habits. Understanding FRMPS resistance can provide marketers with strategies for dealing with this negative impact. This study theoretically confirms the S–S–O paradigm in the FRMPS setting and advances it by proposing thorough explanations of the major stressors that consumers face. Building on their findings, the authors suggest ways service providers can eliminate the stressors, thereby reducing consumers’ fear and preventing resistance or negative word-of-mouth behaviors. This study has valuable implications for both scholars and practitioners.

This paper aims to contribute to the literature on principal preparation by examining the experiences of novice principals and what their experiences mean for principal preparation in the USA.

The researchers employed qualitative methods to examine the experiences of four novice principals over a two‐year period.

The findings suggest that the current climate of efficiency and accountability is contributing to the socialization of principals who focus on the technical aspects of administration over the of relational aspects leadership.

This study focuses on the link between preparation programs and the practice of novice principals, an area that has not been fully explored in the literature.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

The purpose of this study is to solve the Reynolds equation for finite journal bearings by using the physics-informed neural networks (PINNs) method. As a meshless method, it is unnecessary to use big data to train the neural networks, but to satisfy the Reynolds equation and the corresponding boundary conditions by using the known physics information.

Here, the boundary conditions are enforced through the loss function firstly, i.e. the soft constrain method. After this, an equation was constructed to build a surrogate model for satisfying the corresponding boundary conditions naturally, i.e. the hard constrain method.

For the soft one, in brief, the pressure results agree well with existing results, apart from the ones on the boundaries. While for the hard one, it can be noted that the discrepancies on the boundaries are reduced significantly.

The PINNs method is used to solve the Reynolds equation for finite journal bearings, and the error values on the boundaries for the results of the soft constrain method are improved by using the hard constrain method. Therefore, the hard constraint maybe also a good option when the pressure results on the boundaries are emphasized.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0045/

This chapter traces an emerging place-based governance region and identity centered on the California Current large marine ecosystem, which takes in the states of Oregon, Washington, California, First Nations, and the federal government branches and agencies responsible for west coast ocean governance. These efforts have been fostered by Executive Orders aiming to coordinate the work of federal agencies responsible for governing the ocean and have been realized in the human and ocean data networks, and working forums of government representatives from the state, federal, and First Nations governments. My analysis brings science and technology studies, law and society studies, and anthropological ethnographic practice into conversation through an exploration of the bureaucratic socialities that are challenged with grappling with the social and ethical ramifications of unpredictable ocean conditions due to impending climate change and increased human uses.

This is the first officially‐released account following studies conducted at Columbian's recently‐opened laboratory