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This study aims to investigate two issues inherent in accounting judgements: the directional influence of uncertainty expressions and how they might positively or negatively affect accounting judgements and the foreign-language effect (FLE), which refers to the reduction of judgement bias that occurs when an accounting judgement is made in one’s foreign language. This study examines both issues in the context of accounting judgements made in Chinese and English languages.

This study conducted two experiments. The first experiment applied a 2 × 2 between-subject research design, and the second experiment adopted a 2 × 2 within-subject approach.

The overall results revealed that directionality biases existed in the exercise of accounting judgement in subjects’ native and foreign languages. However, when the language was switched from the subjects’ native tongue to a foreign language, overall directionality biases are reduced.

This study suggests that the use of native and non-native languages can have unintended consequences on accounting judgements. However, because of the limitations of using students as proxies for professionals and applying self-assessed language scales, the literature would benefit from future research that extends the subject profile to professional accountants and that assesses language skills more objectively.

This study contributes to the literature on cross-lingual accounting, both theoretically and methodologically. It also extends the FLE theory to an accounting context, providing insights on how language is involved in judgements concerning uncertainty expressions.

The purpose of this paper is to propose a new inspecting algorithm for defect detection on PCB circuits.

PCB circuit images were processed by a radon transformation. A Radon histogram was formed and utilized to establish a texture directional characteristic similarity function. Then, a region of the image which contained the same texture directionality feature was segmented. Furthermore, a directionality estimation method is presented. As the circuit was damaged, the directionality was weakened correspondingly. According to principle, the concept of directional intensity was proposed and then used to measure directionality through analysis of the Radon histogram fluctuation. Finally, the defect was detected based on directional intensity.

The method has been applied to an inspecting system used in practice and it achieved a higher accuracy and efficiency in comparison with similar methods.

Although work on highly intensive PCB circuitry inspection and flaw detection is presented, defect classification was not involved although this is also a very important requirement of inspection.

The paper provides a new way to detect PCB circuitry defects based on texture directionality and proposes evaluating the similarity between image texture directionalities using a radon transformation to search the inspected area. As the inspected region was located, the concept of directional intensity was defined to measure texture directionality to identify defects. The new algorithm performs stably and efficiently and is fit for practical application.

The purpose of this paper is to study the application of advanced computer image processing techniques for flaw detection on flexible printed circuit (FPC) solder.

Texture directionality feature is obtained based on texture gradient, contour's position is extracted and directionality information obtained through analyzing the distribution of directionality. Contour similarity function is established to filter out false contour and keep proper contour, and the solder's location work is accomplished based on reversed contour. After that, a combination of grey and texture gradient's value deviation from reference value is utilized to reflect and describe texture on the solder's surface. Flaw can be distinguished from homogeneous texture background.

The method has been applied to the inspecting system and achieved a higher accuracy and a lower false defect rate. It demonstrates that the method can detect flaws efficiently and effectively.

Although the work on FPC solder's location and flaw detection is presented, defective classification is not involved that is also very important content for inspection.

The paper provides a new way to locate solder based on directionality. The method not only extracts contour feature but also gains directional parameters to help realize accurate location, especially for some solders that are deformed to some extent. Entropy statistic based on distribution of grey and texture gradient is proposed to describe and measure solder's surface texture. The new algorithm performs stably and efficiently and is fit for practical application.

Business models are increasingly recognized as a concept to support innovation in organizations. The implementation and operation of a new or altered business model involves the (re-)design of an organization's business processes and their successful execution. This study reviews and synthesizes the existing body of literature to guide organizations in systematically moving from a business model design to the implementation and operation of the business model through their underlying business processes.

A systematic literature review of the methods that bridge business models and business processes is performed. The selected 34 studies are classified according to the method's characteristics and the support in the design, implementation and operation of business models.

The results of the systematic review provide an overview of existing methods that organizations can adopt when moving from business model design into the implementation and operation of their business model using processes.

This work provides a comprehensive overview and detailed insight into the existing methods that align business models and business processes. It increases the understanding on how these two concepts can be synthesized to support more effective digital innovation in organizations. Based on the review results, knowledge gaps are identified and an agenda for future research bridging the fields of business models and business processes is proposed.

This paper aims to assess the effect of narrative transportation, portrayed action and photographic style on viewers’ likelihood to comment on posted consumer photos.

Integrating visual semiotics and experiments, this research examines the influence of consumer photos on viewers’ likelihood to comment on the visualised narrative. One pilot, three experimental and a content analysis involve photos varying in their narrative perspective (selfie vs elsie) and portrayed content (no product, no action or directed action). The authors also test for the boundary condition of the role of the photographic style (snapshot, professional and “parody” selfie) on the likelihood to comment on consumer photos.

Viewers are more likely to comment on photos displaying action. When these photos are selfies, the effect is exacerbated. The experience of narrative transportation – a feeling of entering a world evoked by the narrative – underlies this effect. However, if a snapshot style is used (primed or manipulated) – namely, the photographic style appears genuine, unconstructed and natural – the superior effect of selfies disappears because of greater perceived silliness of the visualised narrative.

Managers should try to motivate consumers to take selfies portraying action if their aim is to encourage electronic word-of-mouth.

Organisations can effectively use consumer photos portraying consumption for educational purpose (e.g. eating healthfully and reducing alcohol use).

This research links consumer photos and electronic word-of-mouth and extends the marketing literature on visual narratives, which is mainly focused on company rather than user-generated content.

Young children write to learn the alphabetic code, take notes to help them remember, and provide meaningful text to others. These are cognitively and linguistically complex processes. Reciprocal relationships among the development of writing, the purposes of writing, and the learners of interest impact instructional approaches and student outcomes. Teachers can increase success when they provide explicit and systematic self-regulation and writing instruction, view children as collaborators in the process, provide scaffolding that gradually shifts the responsibility to the children, and adapt instruction to meet the abilities and interests of the children. Effective instructional practices for young children with disabilities or who are at risk, are presented, for example, scaffolded writing, the use of graphic organizers, and self-regulated strategy development.

This paper aims to advance a theoretical framework that integrates knowledge management, change management and “soft” issues, focussing on uncovering the nature of “soft” issues embedded in knowledge management and change management processes.

Both empirical work (case study at an electronics contract manufacturing plant) and literature review were used in order to build the proposed theoretical framework.

It argues that the “soft” dimension assists in better understanding the process of organizational knowledge transfer. In this context, “soft” issues refers to the mutual understanding – of both sender and receiver units – of underlying assumptions, the role of macro‐institutional factors affecting firm level actions (the macro‐micro link) and interpretative aspects that permeate the process of organizational knowledge transfer, including knowledge management and change management issues.

Guidelines for managerial action were formulated in order to make explicit, be aware of and understand embedded “soft” issues. Presented guidelines represent an attempt to uncover the crucial “soft” issues that are usually overlooked by the conventional literature.

This paper offers an alternative framework for guiding both practical intervention and further research on knowledge management‐related issues. It contributes to a better understanding of the process of organizational knowledge transfer.

The application of dry-type transformers is growing in the market because the technology is non-flammable, safer and environmentally friendly. However, the unit dimensions are normally larger and material costs become higher, as no oil is present for dielectric insulation or cooling. At designing stage, a transformer thermal model used for predicting temperature rise is fundamental and the modelling of cooling system is particularly important. This paper aims to describe a thermal model used to compute dry transformers with different cooling system configurations.

The paper introduces a fast-calculating thermal and pressure network model for dry-transformer cooling systems, preliminarily verified by analytical methods and advanced CFD simulations, and finally validated with experimental results.

This paper provides an overview of the network model of dry-transformer cooling system, describing its topology and its main variants including natural or forced ventilation, with or without cooling duct in the core, enclosure with roof and floor ventilation openings and air barriers. Finally, it presents a formulation for the new heat exchanger element.

The network approach presented in this paper allows to model efficiently the cooling system of dry-type transformers. This model is based on physical principles rather than empirical assessments that are valid only for specific transformer technologies. In comparison with CFD simulation approach, the network model runs much faster and the accuracies still fall in acceptable range; therefore, one is able to utilize this method in optimization procedures included in transformer design systems.

This study aims to identify context-specific antecedents to schools’ absorptive capacity (AC) and to show how those can enact “a virtuous learning circle.”

The study uses a mixed method: an exploration based on semi-structured interviews with educational experts; the development of a measurement scale and a partial least squares structural equation modelling to test the impact of the antecedents.

The results yielded four empirically-grounded antecedents and their measurement scales, namely, prior knowledge, employees’ skills, educational projects and interactions with the environment (Studies one and two). All antecedents are significantly and positively related to AC processes (study three). Using the organizational learning theory perspective, the results have been interpreted as an AC “virtuous learning circle.”

With increasing pressures to adapt, a case of which was the COVID-19 pandemic, schools can greatly benefit from absorbing knowledge flows. This suggests the construction a favourable environment for AC. To this end, the individual (employees’ prior knowledge and skills), organizational (educational projects) and institutional level of managerial action (interactions with the environment) can be effective when create a recursive organizational learning circle. In addition, this study offers an expert-validated measurement scale for self-assessment of a school’s specific contingencies, and thus, for planning of punctual interventions to develop AC.

This study advances the existing body of knowledge management in the educational context by rigorously identifying and validating a scale for measuring the antecedents of AC and developing an interpretive approach to the AC “virtuous circle.”

Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective to be accurate enough. It is necessary to explore a method that can quantify professional experience into objective indicators to evaluate the sensory comfort of the optical illusion skirt quickly and accurately. The purpose of this paper is to propose a method to objectively evaluate the sensory comfort of optical illusion skirt patterns by combining texture feature extraction and prediction model construction.

Firstly, 10 optical illusion sample skirts are produced, and 10 experimental images are collected for each sample skirt. Then a Likert five-level evaluation scale is designed to obtain the sensory comfort level of each skirt through the questionnaire survey. Synchronously, the coarseness, contrast, directionality, line-likeness, regularity and roughness of the sample image are calculated based on Tamura texture feature algorithm, and the mean, contrast and entropy are extracted of the image transformed by Gabor wavelet. Both are set as objective parameters. Two final indicators T1 and T2 are refined from the objective parameters previously obtained to construct the predictive model of the subjective comfort of the visual illusion skirt. The linear regression model and the MLP neural network model are constructed.

Results show that the accuracy of the linear regression model is 92%, and prediction accuracy of the MLP neural network model is 97.9%. It is feasible to use Tamura texture features, Gabor wavelet transform and MLP neural network methods to objectively predict the sensory comfort of visual illusion skirt images.

Compared with the existing uncertain and non-reproducible subjective evaluation of optical illusion clothing based on experienced experts. The main advantage of the authors' method is that this method can objectively obtain evaluation parameters, quickly and accurately obtain evaluation grades without repeated evaluation by experienced experts. It is a method of objectively quantifying the experience of experts.