Relevant Dimensions Research Articles

Postal Digital Transformation Dynamics—A System Dynamics Approach

The key motivation of the study was to explore and enlarge our understanding of the factors that inhibit and drive the performance of the postal sector in a dynamic setting in the context of Southern Africa. This study was prompted by the unsatisfactory performance of the postal sector in Southern Africa as measured by the Integrated Index on Postal Development (2IPD), an index used by the Universal Postal Union to measure the performance of posts across the globe on dimensions of reliability, resilience, reach, and relevance. Postal operators across the world are faced with inescapable business model disruptions steered by the digital era, and Southern Africa is not an exception. System dynamics was adopted as a modelling approach to simulate the interaction of the stocks (digital culture, operations capability, adoption, and financial performance). The system dynamics approach revealed that the postal sector can be described as a complex phenomenon due to intricate interdependent variables that interact in a dynamic setting. The complex nature of the postal sector is further amplified by multiple feedback systems of non-linear relations. The results of the study point to the complex interaction of these variables that inhibit and drive the digital transformation and competitiveness of the postal sector. It is by grasping these complexities that decision-makers and policymakers can exploit the insights revealed by this research to direct the postal sector toward a sustainable future.

Service Quality in Rail Systems: Listen to the Voice of Social Media

Service quality is essential to increase and maintain user loyalty to the railway system. In the literature, surveys have been used to measure user satisfaction, and mathematical methods have been applied to quantify the survey results. In recent years, user-generated content, including comments and complaints shared via social media, has been used to measure the quality of rail services. This content may provide important insights into the quality of the service provided with its dynamic structure. In this study, a SERVQUAL-based social-media analytics approach is used to measure railway service quality, placing special emphasis on the temporal variations in a national rail system. Topic modeling was used to assign each content item to the relevant service dimension and sentiment analysis was applied to measure the level of satisfaction. Importance–performance analysis was employed at the final stage to generate policy suggestions. Gathering more than 2.3 million social-media messages posted from 2011 to 2021, we examined the temporal evolution of service quality of the Turkish rail system. The results reveal the most and least important services and the satisfaction level of each dimension. The differences between the priorities of conventional and high-speed rail passengers are defined, and policy recommendations are presented.

Family in societal redistribution: a theoretical inquiry

PurposeThe family is one of the foundations of society; its significance for societal redistribution in modern societies, though, remains particularly unclear. A major reason for this is that theoretical approaches to societal redistribution have not adequately included family either in social philosophy or in welfare state theory. As a consequence, also empirical analyses of differences and developments in societal redistribution have not included family or only in as far as family is affected by other redistributive principles. This paper contributes to filling this theoretical gap.Design/methodology/approachThis paper theorises family as a redistributive principle. With reference to the major theoretical concepts of redistribution, it identifies the relevant dimensions of family in societal redistribution and develops a typology of its inclusion in societal redistribution.FindingsApproaches to redistribution are shaped by distinct concepts of equal or unequal exchange, the relevant actors they identify and by different understandings of the economy. These distinctions are central to understanding the position of family in societal redistribution. With reference to the major theoretical concepts of redistribution, this paper identifies the relevant dimensions of family in societal redistribution and develops a typology of its inclusion in societal redistribution. Further investigations might draw on this typology and detect the theoretical foundations of its conceptualisations and its similarities to and deviations from the developed types.Originality/valueThis paper provides a theoretical groundwork for theoretical and empirical investigations of societal redistribution and for better comprehending its international variation. It aims to initiate a fundamental rethinking of the usual understanding of societal redistribution that widely ignores family as a redistributive principle of its own.

How standardized must a code be to be useful?

If, as it appears, failure of standardization blocks the rise of general-purpose ideography, then a more precise characterization of "standardization" should help illuminate aspects of the process. Comparison is made with several histories of standardization to outline relevant dimensions and thresholds. This line of inquiry is particularly important for the forward-looking question of whether such ideography can ever arise.

How to increase and maintain high immunization coverage: Vaccination Demand Resilience (VDR) framework

BackgroundResilience in vaccination demand is ever more critical as the COVID-19 pandemic has increased our understanding of the importance of vaccines on health and well-being. Yet timid demand for COVID-19 vaccines where available and reduced uptake of routine immunizations globally further raise the urgent need to build vaccination resilience. We demonstrate the complexity of vaccination demand and resilience in a framework where relevant dimensions are intertwined, fluid, and contextual. MethodsWe developed the Vaccination Demand Resilience (VDR) framework based on a literature review on vaccination demand and expert consultation. The matrix framework builds on three main axes: 1) vaccination attitudes and beliefs; 2) vaccination seeking behavior; and 3) vaccination status. The matrix generated eight quadrants, which can help explain people’s levels of vaccination demand and resilience. We selected four scenarios as examples to demonstrate different interventions that could move people across quadrants and build vaccination resilience. ResultsIncongruence between individuals’ attitudes and beliefs, vaccination behavior, and vaccination status can arise. For example, an individual can be vaccinated due to mandates but reject vaccination benefits and otherwise avoid seeking vaccination. Such incongruence could be altered by interventions to build resilience in vaccination demand. These interventions include information, education and communication to change individuals' vaccination attitudes and beliefs, incentive programs and reminder-recalls to facilitate vaccination seeking, or by strengthening healthcare provider communications to reduce missed opportunities. ConclusionsVaccination decision-making is complex. Individuals can be vaccinated without necessarily accepting the benefits of vaccination or seeking vaccination, threatening resilience in vaccination demand. The VDR framework can provide a useful lens for program managers and policy makers considering interventions and policies to improve vaccination resilience. This would help build and sustain confidence and demand for vaccinations, and help to continue to prevent disease, disability, and death from vaccine-preventable diseases.

Prioritizing the Components of the Disaster Resilient System Using DEMATEL and ANP for Urban Areas

Although many research studies have been performed on vulnerability assessment and hazard mitigation, it is extremely hard for communities to cope with disasters appropriately. There are many uncertainties and unanticipated issues in disasters; therefore, coping with disasters and emergencies is not as simple and easy as mitigation and preparedness activities. The concept of disaster resilience has been described as a method to overcome unforeseen problems. This paper aims to discover and prioritize dimensions and components of Disaster Resilient System (DRS) in urban areas using Delphi, Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). Numerous frameworks and models have been used to define relevant dimensions and components of DRS based on the Delphi method. The relationship between the components has been determined using DEMATEL. Finally, obtained data has been applied to ANP to define a conceptual model and to obtain a weighted supermatrix for prioritizing the main components of DRS. The results of the study have shown that a Comprehensive Emergency Plan (CEP) is the most important component for earthquake resilience in urban areas.

FE MODELLING FOR CAPACITIES OF HEADED STUD SHEAR CONNECTORS IN COMPOSITE STEEL BEAMS WITH SLABS CONCRETE

This study discusses the overall performance of the behavior the shear stud in the composite steel beam. The work has been modeled by using ANSYS APDL program. Under of the influence of lateral horizontal pressure. The analyzed structure is a composite of beam-slab. The beam section is (254 X 254 X 73 kg/m) with slab of (1600 mm length, 1200 mm width and 150 mm height) and 6 headed studs 19mm diameter with 100 mm high featuring a single row of pointed studs spaced at 150 mm intervals. First, the study was placed on 200 mm from the end of the slabs on both sides. Headed studs and the value of the limited load are the most relevant dimensions for the aims of this study. One parameter was changed which was the load value. The resulted composite steel was analyzed for each change in the parameters. The results were compared to those from the experimental which revealed a possible alternate analysis that included the selected changes. Besides, the Von-mises stresses and stress intensity have been studied. It was found through structural analysis that there were stresses in the area of the studs which they are resistance to horizontal slips caused by lateral pressure loading. Four composite steel were evaluated at each parameter and were checked with the other factors. For this aim a utilizing parametric analysis software using ANSYS. Language of Design (APDL) was constructed to examine the behavior of the structure.

How flexible is cognitive control? (Mouse) tracking conflict adaptation across context similarities.

Exerting cognitive control to remain on-task and reach our goals is a crucial skill, as is the ability to flexibly adapt our responding in rapidly changing environments. The dynamics of cognitive control are typically studied by examining how participants process stimuli that contain competing relevant and irrelevant information in so-called conflict tasks. Adjustments in performance following the experience of conflict, also termed conflict adaptation, suggests a certain degree of flexibility in the deployment of cognitive control. The present study investigated to what extent conflict adaptation effects transfer across trials of the same and different tasks in three online mouse-tracking experiments. Adaptations of the Simon and Stroop tasks were combined to create different levels of context similarity between the paired tasks. Based on a previous review (Braem et al., Frontiers in Psychology 5:1-13, 2014), across-task conflict adaptation was expected only in the most and least similar contexts. In contrast to our hypothesis, conflict adaptation effects were observed in at least one measure in all three experiments. To our surprise, task order also seemed to impact the size of across-task conflict adaptation effects. The heterogeneity in the current results highlight the importance of using sensitive measurement tools to evaluate conflict adaptation and suggest that the occurrence of across-task conflict adaptation may be conditional on more than just shared relevant and irrelevant dimensions.

Relation between fluid intelligence and mathematics and reading comprehension achievements: The moderating role of student teacher relationships and school bonding.

Several studies have shown the relevance among students of the quality of their interpersonal relationships for their academic achievement. Nevertheless, most studies available have explored the relation between the cognitive functioning and academic achievement without taking into account the quality of the relationships experienced in the school environment. Furthermore, the studies that have begun to consider the joint role of these factors in the prediction of academic achievement are scant. Therefore, it appears of relevance to deepen the relation between cognitive functioning and quality of school relationships in order to support students' academic achievement and the potential of youth. In this paper, we examined the moderating role of the quality of student-teacher relationships and school bonding (STR-SB) in the associations of fluid intelligence (Gf) with academic achievement among adolescents (N = 219). A multiple-group structural equation modelling analysis revealed that STR-SB quality moderated unexpectedly only the link between Gf and mathematics. The findings support the idea that the quality of student-teacher relationships may be a relevant dimension to be considered to clarify the association between cognitive functioning and academic achievement.

The nexus between social media advertising and customers’ purchase intention with the mediating role of customers’ brand consciousness: evidence from three South Asian countries

PurposeThis empirical paper is an endeavor to explore the relationship between social media advertising (SMA) and customers' purchase intention (CPI) in three South Asian countries. SMA was further divided into three relevant dimensions: perceived relevance (PR), perceived informativeness (PI) and perceived credibility (PC). Furthermore, the authors incorporated a single mediator: customers' brand consciousness (CBC) to test the mediating effects on the direct relationships.Design/methodology/approachThe authors purposively selected 1937 fashion-conscious individuals based on a cross-sectional survey design. The authors applied SPSS 25 for explanatory statistics and structural equation modeling (SEM) (through AMOS 25) for testing the hypothesized relationships.FindingsBased on the responses and the application of statistical measures, the authors revealed that all of the three dimensions of SMA have significant positive relationships with CPI. CBC is also significantly and positively related to CPI. Regarding the mediating effects, CBC was identified to have full mediation effects on the relationships between PR and CPI and PI and CPI. On the contrary, the same variable was found to have partial mediation on the relationship between PC and CPI.Originality/valueSouth Asia is a growing business hub and the largest consumer market in terms of population. This empirical study was undertaken to reveal the role of SMA on CPI in the three highly populated South Asian countries, which is rare in academia. The outcomes of this empirical study are expected to be useful for further research attempts regarding SMA and consumer behavior. Businesses and policymakers are also expected to benefit from formulating SMA-related strategies to retain present buyers as well as attract the prospective ones.

NNFSRR: Nearest Neighbor Feature Selection and Redundancy Removal Method for Nearest Neighbor Search in Microarray Gene Expression Data

INTRODUCTION: Gene expression data analysis is a critical aspect of disease prediction and classification, playing a pivotal role in the field of bioinformatics and biomedical research. High-dimensional gene expression datasets hold a wealth of information, but their effective utilization is hindered by the presence of irrelevant dimensions and noise. The challenge lies in extracting meaningful features from these datasets to enhance the accuracy of disease prediction and classification while maintaining computational efficiency.
 Feature selection is a crucial step in addressing these challenges, as it aims to identify and retain only the most informative characteristics from large high-dimensional microarray datasets. In the context of microarray gene expression data, characterized by its substantial dimensionality, selecting relevant features is essential for efficient nearest neighbor search, a fundamental component of various analytical tasks in bioinformatics and data mining.
 Existing feature selection methods in high-dimensional data often face issues related to the trade-off between search accuracy and computational efficiency. This paper introduces a novel approach, the Nearest Neighbor Feature Selection with Symmetrical Uncertainty-based Redundancy Removal (NNFSRR) method, designed to enhance the classification of microarray gene expression data through feature selection. The NNFSRR method focuses on reducing the dimensionality of the dataset by identifying and removing redundant features, allowing subsequent searches to operate solely on relevant dimensions.
 OBJECTIVES: The primary goal is to evaluate the NNFSRR method's effectiveness in improving nearest neighbor search in microarray gene expression datasets by reducing dimensionality. This method utilizes Symmetrical Uncertainty-based correlation between dimensions for feature selection and aims to enhance accuracy and efficiency compared to existing methods.
 METHODS: The NNFSRR method uses Symmetrical Uncertainty to identify and remove redundant features from microarray gene expression datasets. Reduced datasets are used for nearest neighbor search, improving accuracy and efficiency. Experiments are conducted using real-world datasets, and comparisons with existing methods are made based on search time and accuracy.
 RESULTS: The NNFSRR method demonstrates improved nearest neighbor search performance, outperforming basic brute force methods and existing feature selection techniques. Selected feature sets exhibit strong class associations while minimizing feature correlations, enhancing classification precision.
 CONCLUSION: In conclusion, the NNFSRR method presents a promising approach to address the challenges posed by high-dimensional gene expression data. It effectively reduces dimensionality, improves search accuracy, and enhances the efficiency of nearest neighbor search. Our experimental results demonstrate that this method outperforms existing techniques in terms of search time and accuracy, making it a valuable tool for applications in bioinformatics, data mining, pattern recognition, and biological information retrieval. The NNFSRR method holds the potential to advance our understanding of complex biological processes and support more accurate disease prediction and classification.

Enhanced but Indeterminate? How Attention Colors our World

AbstractAttention makes things look brighter and more colorful. In light of these effects, representationalist philosophers propose that attentive experiences represent more determinate color properties than inattentive experiences. Although this claim is appealing, we argue that it does not hold for one of our best conceptualizations of content determinacy, according to which an experience has more determinate contents if it represents a narrower range of values within the relevant dimension. We argue that our current empirical evidence fails to show that attention has this kind of effect on color perception. We then offer an alternative, representationalist-friendly account of the attentional effects, as changes in vividness.

Into the wild or into the library? Perceived restorativeness of natural and built environments

Exposure to natural environments can promote recovery from mental fatigue and restore cognitive resources. However, previous research has tended to compare the restorative potential of hospitable natural environments, such as lakes, with the restorative potential of harsh built environments, such as streets with traffic. Thus, it has overlooked the potential restorativeness of hospitable built environments such as libraries, or the potentially limited restorativeness of harsh natural environments, such as deserts. Moreover, studies on perceived restorativeness have traditionally focused on four basic dimensions identified by Attention Restoration Theory (ART); being away, fascination, compatibility, and extent. However, they have scarcely considered two other relevant dimensions: opportunity for reflection (also identified by ART) and feeling of safety. Additionally, there is limited empirical evidence on the relationship between basic ART dimensions, reflection, and overall perceived restorativeness. In our study, we hypothesized that (1) cluster analysis would support categorizing 12 natural and 12 built environments into four clusters (hospitable natural, harsh natural, hospitable built, harsh built), based on ratings of the six abovementioned dimensions of perceived restorativeness, (2) ratings of ART dimensions, as summarized by a Perceived Restorativeness Scale (PRS) score, reflection, and safety would predict overall perceived restorativeness, and (3) opportunity for reflection would partially mediate the relationship of the PRS score and safety with overall perceived restorativeness. We identified the four expected clusters of environments, plus a fifth cluster of functional built environments. While hospitable natural environments showed the greatest overall perceived restorativeness, hospitable built places were rated as more restorative than harsh natural ones, indicating that the distinction between natural and built environments may be too simplistic. Path analysis indicated that PRS score, reflection, and safety predict overall perceived restorativeness. Moreover, reflection partially mediated the relationship of PRS score, and safety in some environments, with overall perceived restorativeness.

Validation of a framework for evaluating knowledge mobilization strategies: A Delphi method approach.

Background: A growing number of knowledge-oriented organizations, such as granting agencies, governments, public organizations, universities, and health authorities, are investing considerable resources to increase the use of research knowledge to improve professional practice, decision making, and public policy. The proliferation of research on knowledge mobilization (KMb) over the past two decades has deepened our understanding of the dynamics of this process and of the factors that can impede its deployment, such as knowledge users’ capabilities (their beliefs, capacity to absorb knowledge, etc.), contextual conditions (resources, leadership, facilitating factors, etc.), and the availability of effective mobilization strategies (frequency, implementation, fit with context). However, yet, few good-quality studies have evaluated the impacts of KMb, such that we still know too little about the effectiveness of the different strategies and the contextual conditions in which they may be effective. This is problematic, in that their development cannot be fully grounded in empirical evidence. In fact, their evaluation is complicated by the virtual absence of evaluation tools and validated indicators that would allow organizations to assess the impacts of their KMb strategies. Moreover, the difficulty that these organizations experience in relation to evaluation (due to lack of expertise and resources) is a concern that has been raised many times. Aims: This study will address this expressed need to improve organizations’ capacity to conduct KMb evaluation studies. Using a collaborative co-construction approach with key actors in KMb, our aim is to design and validate an integrative and operational framework for the evaluation of KMb strategies in the social domain. Design/approach: a first step in this project, we conducted a scoping review of frameworks and theories commonly used to evaluate KMb strategies. 71 articles were selected from this scoping review. Our analyses of these articles, we identified four potentially relevant dimensions for planning and evaluation: the context, implementation process, effects, and impacts of these strategies. Using the Delphi approach, a consultation has been undertaken to enrich and validate the dimensions of this framework developed after a scoping review. Results: This paper presents the results of the Delphi consultation with an international panel of experts working in the field of knowledge mobilization. This evaluation exercise should lead to a validation of the framework components and potential indicators to be considered when evaluating knowledge mobilization strategies.

Distinguishing the Dimensions of Learning Spaces: A Systematic Literature Review

Nowadays, public and private organisations appear increasingly committed to fostering the skills necessary to deal with the challenges of the current scenario. From this perspective, public and private organisations are developing new spaces for learning. The notion of learning space draws its origin and main application in educational institutions. However, it constitutes a distinctive concept for all the organisational contexts in which the creation and management of knowledge and learning dynamics are enabling factors that support innovation and growth dynamics. Although several studies have already discussed the features characterising a learning space or a learning environment, the literature is fragmented and does not provide a comprehensive, fresh view of the learning space, its components, or its impact on learning processes and knowledge dynamics. This is particularly true in management literature. The research results synthesise data and knowledge gathered from the systematic literature review, providing researchers and practitioners with an integrative picture of the definitions of "learning space" and "learning environment" in the management literature and producing a descriptive framework that highlights the relevant dimensions that influence learning processes and knowledge dynamics.

ROUGE-SEM: Better evaluation of summarization using ROUGE combined with semantics

With the development of pre-trained language models and large-scale datasets, automatic text summarization has attracted much attention from the community of natural language processing, but the progress of automatic summarization evaluation has stagnated. Although there have been efforts to improve automatic summarization evaluation, ROUGE has remained one of the most popular metrics for nearly 20 years due to its competitive evaluation performance. However, ROUGE is not perfect, there are studies have shown that it is suffering from inaccurate evaluation of abstractive summarization and limited diversity of generated summaries, both caused by lexical bias. To avoid the bias of lexical similarity, more and more meaningful embedding-based metrics have been proposed to evaluate summaries by measuring semantic similarity. Due to the challenge of accurately measuring semantic similarity, none of them can fully replace ROUGE as the default automatic evaluation toolkit for text summarization. To address the aforementioned problems, we propose a compromise evaluation framework (ROUGE-SEM) for improving ROUGE with semantic information, which compensates for the lack of semantic awareness through a semantic similarity module. According to the differences in semantic similarity and lexical similarity, summaries are classified into four categories for the first time, including good-summary, pearl-summary, glass-summary, and bad-summary. In particular, the back-translation technique is adopted to rewrite pearl-summary and glass-summary that are inaccurately evaluated by ROUGE to alleviate lexical bias. Through this pipeline framework, summaries are first classified by candidate summary classifier, then rewritten by categorized summary rewriter, and finally scored by rewritten summary scorer, which are efficiently evaluated in a manner consistent with human behavior. When measured using Pearson, Spearman, and Kendall rank coefficients, our proposal achieves comparable or higher correlations with human judgments than several state-of-the-art automatic summarization evaluation metrics in dimensions of coherence, consistency, fluency, and relevance. This also suggests that improving ROUGE with semantics is a promising direction for automatic summarization evaluation.

The Dynamism of the Environment — The Impact on Service Company Competitive Advantage from a CRM Dynamic Capabilities Perspective

Abstract Objective To explore the dynamism of the environment and the impact on service company competitive advantage from a customer relationship management (CRM) dynamic capabilities (DCs) perspective. This work also aims to develop a multidimensional conceptualisation of the dynamic environment and propose a theoretical model for analysing the impact of the environment's dynamism on the relationship between dynamic CRM capabilities and competitive advantage. Research Design and Methods Based on the resource-based view (RBV) and dynamic capabilities view (DCV), the method of critical literature analysis was used. Literature sources written in the last two decades were analysed. Findings The result of the literature research became the development of a new conceptualisation of the dynamic environment and its three relevant dimensions, as well as the proposal of constructs in the theoretical model, where the dynamism of the environment plays a moderating role in the relationship between dynamic CRM capabilities and competitive advantage. Implications/Recommendations As implications for further research, empirical verification of the created model and checking the relationship between the constructs should be indicated. Contribution The findings extend the application of RBV and DCV in marketing knowledge. In addition, the model and this study's conclusions direct service firms to develop CRM capabilities that can enhance the company, thereby enabling the building of competitive advantage in a dynamic environment.

Electrochemical Production of Formate Directly from Amine-Based CO2 Capture Media

Introduction There is an urgency for the development and establishment of technologies to deal with the effects of climate change and increasing temperature of the planet.1 The decrease in the CO2 emissions is a possible path, and the capture of CO2 from the atmosphere is another alternative to try and tackle the effects of climate change.2 The combination of capture and conversion of CO2 is a potential approach to achieve the net-zero emission goals and a circular economy for the future.3 Amine scrubbing is an industrially established capture technology that utilizes mainly monoethanolamine (MEA) as the capture solution to capture CO2 from post-combustion flue gases. The process has the disadvantage of a high energy demand, which prevents its wider application.2 This study proposes a novel capture and utilization (CCU) combination: the use of the MEA capture solution as electrolyte for the electrochemical CO2 reduction (eCO2R). In that way, the CO2 capture and conversion will be combined in the same medium, avoiding the energy-intensive regeneration step, thus saving energy, as well as generating products of industrial interest. Sn-based catalysts were primarily chosen due to their selectivity towards formate, one of the most straightforward reduction products from CO2. Results The eCO2R from the capture media (30 wt% MEA solutions, saturated with CO2) was promoted in a zero-gap type reactor, composed of an Sn-based cathode, a Ni foam anode and a bipolar membrane (BPM) separating the cathode and anode compartments. The BPM is responsible for providing protons to the cathode side of the electrolyzer, which promote the hydrolysis of the carbamate on the surface of the catalyst and thus enhances the CO2 availability and consequently the eCO2R. Figure 1 presents a scheme of the zero-gap electrolyzer, highlighting the hydrolysis of the carbamate in contact with the catalyst, and compares the faradaic efficiencies (FE) towards formate obtained by different setups of the zero-gap electrolyzer, at -50 mA cm-2.The Sn nanoparticle (SnNP)-based catalysts show a low efficiency for the eCO2R from the capture media (up to 5%). As published in the literature, surfactants are capable to inhibit the hydrogen evolution reaction (HER) in electrochemical systems and thus promote the eCO2R.4 The surfactant cetyltrimethylammonium bromide (CTAB) was therefore added to the system and the FE towards formate increased, although merely up to 6.43%. To further increase the surface area available for the eCO2R, a metal gauze was introduced as support for the working electrode (WE). Here, a Cu gauze with electrodeposited Sn (SnED) was used as WE and the obtained FE was 70% higher than for the carbon supported SnNP catalysts, up to 8.49%, without the addition of the surfactant. The hydrophilic nature of the metal surface (in comparison to the carbon paper substrate of the NPs) and a bigger surface area could be the reasons behind this enhancement in the FE using metal WE. Future studies will focus on the further enhancement of the FE towards formate. Conclusion This study shows the feasibility of a novel CCU technology: the electrochemical reduction of CO2 to formate from an amine-based capture medium. Sn-based catalysts lead to an FE of up to 8.49%. The use of a metallic electrode lead to a larger enhancement of the FE, in comparison to the addition of a surfactant to the electrolyte for the SnNP-based catalyst. There is yet room for further improvement of the faradaic efficiency by the combination of the metal electrode and the use of surfactants to inhibit the HER, as well as the use of catalysts with higher selectivity towards the product, such as Bi. The use of a zero-gap electrolyzer shows the feasibility of scaling up the system to industrially relevant dimensions and the easiness of incorporating the electrochemical system to the end of pre-existing capture plants. References Ghiat, I., & Al-Ansari, T. (2021). Journal of CO2 Utilization, 45.Gutiérrez-Sánchez, O., Bohlen, B., et al. (2022). ChemElectroChem, 9(5), e202101540.Li, M., Irtem, E., et al. (2022). Nature Communications 2022 13:1, 13(1), 1–11.Chen, L., Li, F., et al. (2017). ChemSusChem, 10(20), 4109–4118. Figure 1

Demystifying the use of corporate social responsibility terminology in the investment context

Orientation: Interest in corporate social responsibility (CSR) is escalating in the 21st century. Globally, companies are increasingly attempting to enhance their reporting on sustainability concerns, given that terminology can noticeably affect the attitudes and behaviours of investors and other key stakeholders.Research purpose: A growing number of responsible investors incorporate sustainability considerations when making investment decisions. Therefore, it is important to determine the relevant CSR definitions and dimensions based on the breadth of existing research on CSR in the investment context.Motivation for the study: As investors incorporate companies’ reporting on a range of financial and sustainability performance metrics when making investment decisions, it is necessary to clarify sustainability-related terminology from an investor perspective.Research approach/design and method: A systematic literature review was performed to explore sustainability terminology in the investment context with a particular focus on CSR. Content and thematic analyses were conducted on 94 articles.Main findings: The findings confirm that although concepts such as sustainability and corporate citizenship have been used interchangeably with CSR by previous scholars, referral to CSR has remained relevant in the investment context. Eight key dimensions were identified to describe CSR in an investment context, namely, social concerns, stakeholders, economic factors, environment, action, voluntarism, ethics, and sustainability.Practical/managerial implications: The identification of context-specific CSR dimensions provides a foundation for developing CSR measurement tools for investors and corporate decision makers.Contribution/value-add: Eight core dimensions of CSR were identified and combined in a comprehensive, context-specific definition applicable to the investment context.

THE RELEVANCE OF LEARNING OUTCOMES INCLUDED IN ESTONIAN GRADE 7-9 SCIENCE SUBJECT CURRICULA ASSOCIATED WITH THE CONCEPT OF ENERGY

This study on the Estonian lower secondary (7-9th grade) science curricula, is seen as an important framework for educators preparing students as tomorrow’s citizens able to reflect on sustainable energy development. As the curriculum is taken to be the major document allowing insights into Estonian educational standards, this study identifies components within the intended lower secondary science curricula for subjects of biology, chemistry, earth science, physics, and interdisciplinary science. Using document analysis, verbs associated with career-related learning outcomes are detected, allowing the relatedness of the energy conceptualizations and determination of their cognitive level utilizing SOLO (Structure of Observed Learning Outcomes) taxonomy. A team of coders identify a total of 782 learning outcomes across three learning domains: psychomotor (176), affective (32), cognitive (574) at unistructural (33), multistructural (225), relational (276), and extended abstract (40) levels. The majority of energy concept learning outcomes (274) are identified in the source (form) and transfer (transform) categories. Very few career-related learning outcomes are detected with the science education relevance dimensions (individual, societal, career). The suitability of the findings is discussed. The current analyzing method can be applied to other educational disciplines for raising awareness of disciplinary crosscutting concepts. Keywords: energy concept, learning outcomes, relevance in science education, lower secondary science curriculum, SOLO taxonomy