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This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

This paper aims to examine the processes of sustainability reporting assurance (SRA) and the influence they have on shaping perception from disclosures. Given the evidence of inconsistencies and ambiguities in assurance processes, this paper examines how legitimacy is attained and maintained at different stages of SRA.

Evidence collected from 23 semi-structured interviews with assurance providers (APs), consultants, professionals and non-governmental organisations (NGOs) (non-APs) was used to conduct a thematic analysis from the perspectives of interviewees.

APs and non-APs are united in recognising the value of SRA, although, perspectives on transparency between the two groups differ. Experience and industry knowledge are essential to SRA delivery with non-APs preferring accounting APs. Nevertheless, non-APs are concerned about the role of companies in deciding assurance scope, as it can affect scrutiny. APs favour data accuracy (as opposed to data relevance) assurance due to team dynamics and internal review influences, with the latter also restricting assurance innovation. APs are interested in accessing better evidence and stakeholder engagement evaluations. Providing advisory services was not rejected by all APs. The perspectives of APs and non-APs demonstrate how progress in SRA has gained pragmatic legitimacy with noticeable gaps that serve to undermine attainment of moral legitimacy.

SRA is a developing practice that will adopt changes as it continues to mature; some of these changes could impact findings in this research. General perspectives on SRA were sought from interviewees, this affected the ability for an in-depth focus on any of the range of interesting SRA issues that arose over the course of the research. Interviews were conducted with relevant parties in the SRA space that operate in the UK. Perspectives from parties outside the UK were not solicited.

Companies make an important decision to commission SRA. Findings in this research have highlighted specific non-APs issues of concern that can be useful in structuring operations and reporting regimes to facilitate assurance procedures. The findings will also be helpful to APs as they can direct more emphasis on stakeholder concerns towards demonstrating greater stakeholder accountability. Regulatory and standard setters can enact appropriate policies that can potentially drive the practice forward for assessment of cognitive legitimacy.

The findings provide relevant account of stakeholder voices on the quality of corporate disclosures that has a direct effect on the wellbeing of communities and sustainability of societies. Collective stakeholder input on expectations can shape sustainability discourse.

This research demonstrates the applicability of financial audit quality indicators in SRA processes, extends the debate around the effectiveness of new audit fields and highlights the challenges of maintaining legitimacy with different audiences.

This study investigates CSR reporting’s role in debt access and cost of debt with the moderating role of external assurance and GRI adoption in emerging markets. Such an investigation will help facilitate external fund flow to firms in better terms.

We collected data from 16 emerging markets between 2008 and 2019 from the Thomson Reuters Eikon and ran fixed effects regression analysis and robustness tests by addressing endogeneity concerns, adopting alternative sample and integrating additional control variables.

The results show that CSR reporting has a positive association with access to debt and a negative association with the cost of debt. Furthermore, both external assurance and GRI adoption do not significantly moderate between CSR reporting and access to debt and cost of debt. Hence, creditors in emerging markets are not interested in CSR report assurance and GRI framework adoption and do not integrate them into their lending decisions.

Emerging markets are unique settings characterized by high growth rates, limited capital availability, high debt costs and weak institutional environments. Thus, reaching debt with convenient conditions is critical for emerging market firms to finance their growth. Hence, our study will help emerging market firms reach external funding more easily and in better terms via CSR transparency. Besides, our investigation is based on a broad sample of emerging markets, and hence updates prior emerging market studies conducted in single-country settings. Lastly, we test the complementarity of third-party assurance and GRI adoption to CSR reporting in loan contracting.

Replication is a primary self-correction device in science. In this paper, we have two aims: to examine how and when the results of replications are used in management and organization research and to use the results of this examination to offer guidelines for improving the self-correction process.

Study 1 analyzes co-citation patterns for 135 original-replication pairs to assess the direct impact of replications, specifically examining how often and when a replication study is co-cited with its original. In Study 2, a similar design is employed to measure the indirect impact of replications by assessing how often and when a meta-analysis that includes a replication of the original study is co-cited with the original study.

Study 1 reveals, among other things, that a huge majority (92%) of sources that cite the original study fail to co-cite a replication study, thus calling into question the impact of replications in our field. Study 2 shows that the indirect impact of replications through meta-analyses is likewise minimal. However, our analyses also show that replications published in the same journal that carried the original study and authored by teams including the authors of the original study are more likely to be co-cited, and that articles in higher-ranking journals are more likely to co-cite replications.

We use our results to formulate recommendations that would streamline the self-correction process in management research at the author-, reviewer- and journal-level. Our recommendations would create incentives to make replication attempts more common, while also increasing the likelihood that these attempts are targeted at the most relevant original studies.

Material extrusion-based additive manufacturing is a prominent manufacturing technique to fabricate complex geometrical three-dimensional (3D) parts. Despite the indisputable advantages of material extrusion-based technique, the poor surface and subsurface integrity hinder the industrial application of this technology. The purpose of this study is introducing the hot air jet treatment (HAJ) technique for surface treatment of additive manufactured parts.

In the presented research, novel theoretical formulation and finite element models are developed to study and model the polishing mechanism of printed parts surface through the HAJ technique. The model correlates reflow material volume, layer width and layer height. The reflow material volume is a function of treatment temperature, treatment velocity and HAJ velocity. The values of reflow material volume are obtained through the finite element modeling model due to the complexity of the interactions between thermal and mechanical phenomena. The theoretical model presumptions are validated through experiments, and the results show that the treatment parameters have a significant impact on the surface characteristics, hardness and dimensional variations of the treated surface.

The results demonstrate that the average value of error between the calculated theoretical results and experimental results is 14.3%. Meanwhile, the 3D plots of Ra and Rq revealed that the maximum values of Ra and Rq reduction percentages at 255°C, 270°C, 285°C and 300°C treatment temperatures are (35.9%, 33.9%), (77.6%,76.4%), (94%, 93.8%) and (85.1%, 84%), respectively. The scanning electron microscope results illustrate three different treatment zones and the treatment-induced and manufacturing-induced entrapped air relief phenomenon. The measured results of hardness variation percentages and dimensional deviation percentages at different regimes are (8.33%, 0.19%), (10.55%, 0.31%) and (−0.27%, 0.34%), respectively.

While some studies have investigated the effect of the HAJ process on the structural integrity of manufactured items, there is a dearth of research on the underlying treatment mechanism, the integrity of the treated surface and the subsurface characteristics of the treated surface.

Adequate means for easily viewing, browsing and searching knowledge graphs (KGs) are a crucial, still limiting factor. Therefore, this paper aims to present virtual properties as valuable user interface (UI) concept for ontologies and KGs able to improve these issues. Virtual properties provide shortcuts on a KG that can enrich the scope of a class with other information beyond its direct neighborhood.

Virtual properties can be defined as enhancements of shapes constraint language (SHACL) property shapes. Their values are computed on demand via protocol and RDF query language (SPARQL) queries. An approach is demonstrated that can help to identify suitable virtual property candidates. Virtual properties can be realized as integral functionality of generic, frame-based UIs, which can automatically provide views and masks for viewing and searching a KG.

The virtual property approach has been implemented at Bosch and is usable by more than 100,000 Bosch employees in a productive deployment, which proves the maturity and relevance of the approach for Bosch. It has successfully been demonstrated that virtual properties can significantly improve KG UIs by enriching the scope of a class with information beyond its direct neighborhood.

SHACL-defined virtual properties and their automatic identification are a novel concept. To the best of the author’s knowledge, no such approach has been established nor standardized so far.

The article investigates the institutional setup of e-lending in public libraries in Denmark, Norway and Sweden. Our point of departure is that e-lending has necessitated new library collaborations between local, regional and national levels, and therefore, institutional e-lending setups have emerged. The study seeks to provide better understanding of how the institutional setups are structured, how governance logics have shaped them and what tensions and dynamics become visible in the key actors’ problematisations of these setups.

The study is situated in the neo-institutional tradition and applies the institutional logics perspective. The research questions are answered by taking a qualitative approach, grounded in an extensive interview study with representatives of libraries, publishers and policy actors in three Scandinavian countries. To provide in-depth insight into e-lending setups, the scope of empirical material is then limited to accounts the central library and policy actors involved in establishing e-lending.

The analysis shows that the e-lending setups are both similar (especially when it comes to financing), and different across Scandinavia, especially when it comes to centralisation and involvement of librarians in this task. The differences are attributed to the influence of different governance logics (question of administrative autonomy, collaboration in the field and existing legal and political frames), and to what extent the digital and market logics are incorporated or rejected in the field.

The study provides new insights into the question of how Scandinavian public libraries face the consequences of the digitalisation of book distribution and consumption by investigating how they organise their e-lending services. This has not been explored before, notably in a comparative perspective.

Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

The effect of dynamic capabilities on operational excellence and the moderating effect of environmental dynamism on the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka were investigated while developing new psychometric scales to assess operational excellence and dynamic capacities constructs.

We followed the exploratory sequential research design with a mixed-method research approach, aligning with the pragmatic research philosophy. Thus, both qualitative and quantitative research methods were followed.

Dynamic capabilities positively affect operational excellence, and environmental dynamism moderates the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka such that when a higher environmental dynamism exists, a weaker positive relationship exists between dynamic capabilities and operational excellence. The two main dimensions of the operational excellence construct are continuous improvement of sustainable operational performance and sustainable competitive advantages. It empirically confirmed that sensing, seizing and reconfiguring capabilities are the three main dimensions of the dynamic capabilities construct.

This study was limited to the apparel industry in Sri Lanka. This research phenomenon should be explored in other industrial sectors worldwide to generalize the findings. The practitioners in the apparel sector may improve the organizational dynamic capabilities to achieve operational excellence and keep a strong positive relationship between dynamic capabilities and operational excellence in a highly dynamic environment if they address out-of-family situations with out-of-the-box thinking.

We generated two new empirical findings: (1) dynamic capabilities positively affect operational excellence, and (2) environmental dynamism moderates the relationship between dynamic capabilities and operational excellence. Also, we introduced validated new scales for assessing operational excellence and dynamic capabilities.

Prior research on meeting or beating earnings thresholds documents that firms with earnings momentum are awarded with valuation premiums. However, it is unclear from this strand of literature why this is the case. Therefore, this study aims to investigate the effects of time-varying earnings persistence on earnings momentum and their pricing effects.

This study exploits a firm that reports earnings momentum as research setting to examine whether earnings persistence is significantly higher for firms with consecutive earnings increases. In addition, it investigates a relation between earnings momentum and fundamentals-driven earnings persistence and estimates return associations of earnings momentum conditional on economic-based persistence of earnings.

The empirical evidence suggests that firms with earnings momentum reflect higher time-varying earnings persistence. It further reveals that longer duration of earnings momentum is associated with higher fundamentals-driven earnings persistence. More importantly, valuation premiums are exclusively assigned to earnings momentum determined by strong firm fundamentals, not momentum itself.

This study provides new empirical evidence that valuation premiums accrued to firms with earnings momentum are conditional on time-varying earnings persistence. The research implications are relevant to investors, regulators and auditors, as the results bring conclusions that earnings momentum reflects successful business models not poor accounting quality. This leads to a more complete view of earnings momentum and helps allocate resources when evaluating earnings-momentum firms.