Core Motivation Research Articles

A Fast Converter Synchronization Speed Method Based on the Frequency Difference on Both Sides of the Grid Connection Point

The challenge of achieving a reliable and safe synchronization process for microgrids under weak communication conditions is a significant issue in distributed grid-connected energy storage. This is also the core motivation of this study. First, the concept of weak communication is introduced, and weak communication conditions are simulated by limiting the number of communications. Additionally, a fast synchronization method based on the frequency difference at the grid connection point is proposed, which allows for the rapid synchronization of converters under weak communication conditions. This method also includes an analysis of the range for key parameters, providing practical and feasible guidance for its real-world application. Finally, the validity of the theory is verified through PSCAD/EMTDC simulations and physical experiments.

Toward high-quality pseudo masks from noisy or weak annotations for robust medical image segmentation

Deep learning networks excel in image segmentation with abundant accurately annotated training samples. However, in medical applications, acquiring large quantities of high-quality labeled images is prohibitively expensive. Thus, learning from imperfect annotations (e.g. noisy or weak annotations) has emerged as a prominent research area in medical image segmentation. This work aims to extract high-quality pseudo masks from imperfect annotations with the assistance of a small number of clean labels. Our core motivation is based on the understanding that different types of flawed imperfect annotations inherently exhibit unique noise patterns. Comparing clean annotations with corresponding imperfectly annotated labels can effectively identify potential noise patterns at minimal additional cost. To this end, we propose a two-phase framework including a noise identification network and a noise-robust segmentation network. The former network implicitly learns noise patterns and revises labels accordingly. It includes a three-branch network to identify different types of noises. The latter one further mitigates the negative influence of residual annotation noises based on parallel segmentation networks with different initializations and a label softening strategy. Extensive experimental results on two public datasets demonstrate that our method can effectively refine annotation flaws and achieve superior segmentation performance to the state-of-the-art methods.

Education system resilience in the face of inflationary pressures

This paper examines the detrimental impact of rapid inflation on the quality of private education in developing countries. By focusing on the financial challenges faced by private schools, the study highlights the tension between education policy and economic realities. While private schools often attract parents with smaller class sizes and specialized programs, the core motivation lies in investing in children’s future through quality education. However, this study demonstrates how inflation can cripple this sector. The case of Turkey exemplifies this challenge. Post-pandemic inflation created a financial stranglehold on private schools, as rising costs made it difficult to adjust teacher salaries. This, in turn, led to teacher demotivation and a mass exodus, ultimately compromising educational quality. Furthermore, government interventions aimed at protecting parents from high tuition fees, through limitations on fee increases, inadvertently sacrificed the very quality they sought to safeguard. The paper concludes by advocating for alternative policy approaches that prioritize direct support for education system during economic downturns. Such measures are crucial for ensuring a strong and resilient education system that benefits all stakeholders, including parents, students, and the nation as a whole.

Mitigating managerial short-sightedness in green technology innovation and corporate financial performance: The role of “National Team” shareholding

The potential for green technology innovation (GTI) to enhance corporate financial performance continues to be the core motivation for sustained investment by companies. However, the micro-mechanisms to enhancing financial performance have not yet received sufficient attention in the academic literature. Internal corporate governance and corporate management constitute crucial factors that affect the process in which GTI contributes to corporate technological progress, and to the enhancement of corporate financial performance. Specifically, this paper will examine the role of “National Team” shareholding in corporate governance in mitigating managerial short-sightedness in GTI. A two-way fixed effects panel OLS model will be applied for individual-time on 618 listed companies with consistent R&D activities from 2015 to 2022. The results show that corporate GTI promotes corporate financial performance via technological progress. Through the conditional process analysis, it shows that the interaction of CEO narcissism and the “National Team” shareholding proportion together moderate the relationship between corporate GTI and technological progress, with the “National Team” shareholding proportion contributing to the impact of technological progress on corporate financial performance. From a corporate governance point of view, the presence of institutional investors helps mitigate the negative impact of managerial short-sightedness in technological progress.

Collision of Environmental Expectations when Assessing the Supply Versus the Consumption of Electrical Energy

The use of energy supplies for economic activities is a major global concern due to its environmental impact. Mitigating this problem involves the adoption of clean energies, so it is not trivial to assess those that can fit into this category, particularly the part corresponding to electrical energy. While the consumption of the latter is often perceived as more environmentally friendly than other sources, its production process raises significant questions, hence the core motivation to evaluate the behavior of the main inputs for electrical energy production over 50 years and its correlation with the world Gross Domestic Product (GDP), confirming a prominent dependence on fossil fuels, a situation that seems to differ from the expectations set forth through the Paris Agreement and the United Nations Conference of the Parties. On the other hand, even though the production of electrical energy is consistent with the behavior of the world GDP, it shows heterogeneous annual percentage changes.

Changes in harm avoidance and incompleteness across group CBT for OCD and their relationship with symptom change.

Obsessive-compulsive disorder (OCD) symptoms are hypothesized to be driven by two core motivations: harm avoidance and incompleteness. While cognitive-behavioural therapy (CBT) is an effective treatment for OCD, many posit that OCD presentations characterized by high incompleteness may be harder to treat. The relationship between the core motivations and treatment outcomes remains to be further explored. To investigate if harm avoidance and incompleteness decrease across group CBT and to examine the relationship between treatment outcomes and both baseline and changes in harm avoidance and incompleteness throughout treatment. A naturalistic sample of 65 adult out-patients with OCD completed self-report questionnaires measuring OCD symptom severity and the core motivations before, during, and after 12 weeks of group CBT for OCD. Harm avoidance and incompleteness scores significantly decreased from pre- to post-treatment. Pre-treatment harm avoidance and incompleteness levels did not predict post-treatment symptom severity, but changes in the core motivations throughout treatment were significant predictors of treatment outcome. Specifically, reductions in harm avoidance across treatment and reductions in incompleteness early in treatment, were associated with better treatment outcomes. Participants who completed group CBT for OCD experienced modest reductions in the core motivations thought to maintain OCD symptoms and these changes predicted better outcomes. However, pre-treatment levels of harm avoidance and incompleteness do not appear to moderate treatment outcome.

Acquisition parameters influence AI recognition of race in chest x-rays and mitigating these factors reduces underdiagnosis bias

A core motivation for the use of artificial intelligence (AI) in medicine is to reduce existing healthcare disparities. Yet, recent studies have demonstrated two distinct findings: (1) AI models can show performance biases in underserved populations, and (2) these same models can be directly trained to recognize patient demographics, such as predicting self-reported race from medical images alone. Here, we investigate how these findings may be related, with an end goal of reducing a previously identified underdiagnosis bias. Using two popular chest x-ray datasets, we first demonstrate that technical parameters related to image acquisition and processing influence AI models trained to predict patient race, where these results partly reflect underlying biases in the original clinical datasets. We then find that mitigating the observed differences through a demographics-independent calibration strategy reduces the previously identified bias. While many factors likely contribute to AI bias and demographics prediction, these results highlight the importance of carefully considering data acquisition and processing parameters in AI development and healthcare equity more broadly.

Beyond Information Overload: Leveraging How the Brain Learns for Meaningful Impact

Abstract: This article discusses the importance of understanding neuroscience principles of how the brain learns and integrates new information with prior knowledge through its natural associative processes, as when new concepts are linked to past experiences through meaningful connections and context. Emotion is also key to effective memory and learning, as emotional experiences are more vividly remembered due to evolutionary priorities, yet interactions often lack meaning and human connection to optimize learning. Practical applications for organizations are suggested, such as frontloading context in new initiatives by relating them to past strategies and challenges faced, explicitly connecting new hire onboarding information to personal experiences, enhancing trainings with impactful real-world examples, and leveraging empathy during product development by mapping user needs and tying features back to core motivations. By consciously activating neural networks through association, emotion, context and meaning, organizations can optimize the brain's innate learning abilities compared to passive data consumption, forming deeper, more accessible insights through simple yet intentional techniques. This allows companies to cut through information overload and strategically leverage knowledge in today's changing business environment by operationalizing cognitive principles of learning.

Explicit Knowledge Graph Reasoning for Conversational Recommendation

Traditional recommender systems estimate user preference on items purely based on historical interaction records, thus failing to capture fine-grained yet dynamic user interests and letting users receive recommendation only passively. Recent conversational recommender systems (CRSs) tackle those limitations by enabling recommender systems to interact with the user to obtain her/his current preference through a sequence of clarifying questions. Recently, there has been a rise of using knowledge graphs (KGs) for CRSs, where the core motivation is to incorporate the abundant side information carried by a KG into both the recommendation and conversation processes. However, existing KG-based CRSs are subject to two defects: (1) there is a semantic gap between the learned representations of utterances and KG entities, hindering the retrieval of relevant KG information; (2) the reasoning over KG is mostly performed with the implicitly learned user interests, overlooking the explicit signals from the entities actually mentioned in the conversation. To address these drawbacks, we propose a new CRS framework, namely, the Knowledge Enhanced Conversational Reasoning (KECR) model. As a user can reflect her/his preferences via both attribute- and item-level expressions, KECR jointly embeds the structured knowledge from two levels in the KG. A mutual information maximization constraint is further proposed for semantic alignment between the embedding spaces of utterances and KG entities. Meanwhile, KECR utilizes the connectivity within the KG to conduct explicit reasoning of the user demand, making the model less dependent on the user’s feedback to clarifying questions. As such, the semantic alignment and explicit KG reasoning can jointly facilitate accurate recommendation and quality dialogue generation. By comparing with strong baselines on two real-world datasets, we demonstrate that KECR obtains state-of-the-art recommendation effectiveness, as well as competitive dialogue generation performance.

Is wine perception influenced by sustainability information? Insights from a consumer experiment with fungus resistant grape and organic wines

Literature has highlighted that the organic attribute has heuristic value for many consumers, representing an overarching signifier of positive characteristics. Nowadays a plethora of alternative systemic approaches side organic production in the aim to improve the overall sustainability of the agrifood sector. Current study, based on blind and informed tasting, measured sustainability information influence on respondents’ (n = 162) perceptions of organic and fungus-resistant grape (FRG) white wines. Findings of the within-subject non hypothetical experiment revealed that information has a stronger, positive impact on participants’ perception of organic wine (increasing 13 % monetary preferences) compared to FRG wine (+9%). Additionally, attitudinal characteristics driving consumers’ preferences towards FRG wine diverge from organic core motivations.

Exploring Political Participation of First-Time Malay Voters in Tik Tok

The emergence of Internet has permeated in almost every part of our lives, and the younger generations especially are the one been permeated at most. Especially in political aspect, the emergence of social media has brought the opportunity to change the way of people to experience the politics, information seeking and involved in some political activities. Furthermore, previous studies also found out the positive relationship between social media and political participation of the youth in Malaysia. However, previous studies only focus on the social media such as Facebook, Instagram, Twitter. The new and rapidly grow social media – TikTok have not been studied before in Malaysia regarding the political participation of youth in Malaysia. Moreover, previous GE15 has been reported that TikTok is the effective and efficient tool to reach the young voters, especially the first-time Malay voters that utilized by PN and PAS. This study is aimed to investigate about the role of TikTok on the political participation of the first-time Malay voters. Survey results indicates that three independent variables – TikTok Usage, Political Interest and Political Knowledge have positive significant relationship with the dependent variable – Political Participations. The analysis shown political interest is the core motivation driven the Malay voters for political participation during GE15. TikTok played a significant role in here, because most of the respondents agreed that they rely on TikTok for political information consumption during GE15, and the younger first-time voters will use TikTok more frequent than the other age categories.

Enablers and disablers for contactless payment acceptance among Malaysian adults

While a body of knowledge on contactless payment acceptance exists, a comprehensive understanding of the core motivations underpinning such acceptance, particularly in developing countries, is lacking in the literature. This study identified the predictors for contactless payment acceptance in Malaysia by constructing a Contactless Payment Acceptance model using the Technology Readiness Index 2.0 and the Unified Theory of Acceptance and Use of Technology 2 models. Employing a cross-sectional research design, this study utilized survey research as its primary method, administered self-reporting questionnaires through online channels, and garnered 434 valid responses. Structured Equation Modeling identified perceived usefulness, perceived ease of use, lack of awareness, and discomfort as the most influential factors affecting customers’ acceptance of contactless payment systems, with an R-squared value of 71.2%. These results have implications for service providers and can guide future research endeavors, thus facilitating the development and implementation of effective strategies to encourage wider adoption of contactless payment systems among individuals in developing countries.

Motivations for volunteers to participate in ecological restoration: a systematic map

Volunteering is a central means by which communities become engaged in ecological restoration projects and understanding what motivates volunteers is a core preoccupation of researchers because it may help recruit more people. This study addresses the question: what are the motivations and barriers to participation in ecological restoration projects? The systematic literature map method was used to answer this question. The results revealed a typology of motivations that consists of 15 categories. A co‐occurrence network analysis of those categories revealed five core motivations that co‐occur most in the literature: having a positive environmental impact, acquiring and sharing knowledge, caring for the environment, social interactions and community, and human health and well‐being. Barriers to volunteering and the demographics of volunteers were also mapped in the literature, as they appeared frequently alongside motivations. The five core motivations represent a set of widely studied and well‐understood motivations which can inform the design of volunteer programs. The literature indexed by the systematic map can form the basis of further systematic reviews and meta‐analyses. This study highlights three major areas for future research: extrinsic motivations, demographics of volunteers who participate in ecological restoration, and project organization as a motivation.

A FRAMEWORK FOR TRANSFORMING CORPORATE PURPOSE INTO ORGANISATIONAL CULTURE

Purpose: One of the most powerful and talked about approaches in the management and leadership of modern business today is Organisational Purpose. When placed at the heart of strategy, it is said to increase employee engagement exponentially, resulting in the unlocking of human potential, lighting up passion and enthusiasm within people, and beating the line in financial performance through overservicing and delighting customers, by as much as 42% compared to the stock market. However, as much as Organisational Purpose is heralded as the core motivation behind the sustainable success of any organisation, 90% of these purpose-led strategies fail in implementation. The article investigates this phenomenon. Theoretical Framework: This study falls within the framework where leadership and strategy implementation meet. One of the most profound gaps identified during the literature reviewed for this article is that the purpose (‘deep self’) of an organisation cannot be defined or even implemented without defining the individual purposes (‘deep self’) of its leadership, in that an organisation can only ever be as conscious as its leader. Design/ methodology/ Approach: This study, therefore, sets out to create a framework that can guide leaders towards implementing corporate purpose into organisational culture through raising leadership and organisational consciousness and, in doing so, overcoming this persisting barrier to implementation. By choosing Action Design Research as the methodology for this research, the researchers co-create a potential solution with 14 Chief Executive Officers, each a market leader within their diverse industries. Findings: A solution that suggests that the successful transformation of corporate purpose into organisational culture lies at the intersection of the individual purpose of each executive leader, the purpose of the organisation, and the individual purpose of each of its employees. Against the plethora of existing frameworks, which are by and large said to be unsuccessful in the face of implementation failure, the framework presented as a product of this study offers an alternative solution. Research, Practical & Social Implications: A practical solution that puts the potential of people at its heart is offered as a framework for implementation. Originality/Value: The framework is called: ‘The Growing Greatness Implementation Framework’. This presents a new and unique contribution to the current literature about Strategic Business Management.

A cluster-based disambiguation method using pose consistency verification for structure from motion

Structure from motion (SfM) recovers scene structures and camera poses based on feature matching, and faces challenges from ambiguous scenes. There are a large number of ambiguous scenes in real environment, which contain many duplicate structures and textures. The ambiguity leads to incorrect feature matches between images with similar appearance, and makes geometric misalignment in SfM. To address this problem, recent methods have focused on investigating the inconsistencies in feature topology among multi-view images. However, the feature topology is directly derived from 2D images. Thus, it is susceptible to feature occlusion caused by changes in perspective. Therefore, we propose a new method that disambiguates scenes using pose consistency rather than feature consistency. The pose consistency is conducted in 3D geometric space which is less sensitive to feature occlusion. Thus, the pose consistency is more robust than feature consistency. Our core motivation lies that the incorrect matches between ambiguous images will cause pose deviation from the global poses generated by correct matches. To detect this pose deviation, we first combine local and global information of the scene to generate the global reliable camera poses. The local information of each image is obtained by image clustering, and it strengthens the global information that is represented as the verified maximum spanning tree of clusters. Then, the global poses serve as the reference for further pose consistency verification. The global poses also enable us to perform both rotation and translation consistency verification for uncertain matches. During the pose consistency verification, the pose deviation calculated on image-level may be too small to be noticed. Thus, we propose to perform pose consistency verification at cluster-level instead of image-level to amplify the pose deviation. In the experiments, we compared our approach with several state-of-the-art methods, including COLMAP, Geodesic-SfM and TC-SfM, on both ambiguous and regular datasets. The results demonstrate that our approach achieves the best robustness, only our approach succeeds on all ambiguous image sequences (14/14). The quantitative evaluation results on image sequences with ground truth also show that our approach achieves the best accuracy (average RMSE of translation = 0.109, average RMSE of rotation = 0.827) among all methods. The source code of our approach is publicly available at https://github.com/gongyeted/MA-SfM.

“MOTIVATION” AND “GOD-IMAGE” OF INDONESIAN MIGRANT WORKERS IN HONG KONG

This paper explores the motivations and perceptions of God among Indonesian migrant workers in Hong Kong, focusing on their unique experiences and faith struggles. The study, guided by Interpretative Phenomenological Analysis (IPA), is based on the narratives of five female migrant workers with 6-12 years of experience in Hong Kong. From our study, compassion is identified as a fundamental motivator for Indonesian migrant workers. The study finds that all respondents maintain a positive God-Image, perceiving God as their Helper, Caregiver, and source of strength. Their faith is identified as a core motivation for survival. The Good Samaritan (Luke 10:25-37) is employed to illustrate this approach. Finally, this paper tries to contribute to offering a unique perspective on the lives of Indonesian migrant workers in Hong Kong, emphasizing the critical roles of compassion, faith, and a positive God-image in their experiences, and promoting a fresh approach to addressing their struggles.

Nash Bargaining Game Enhanced Global Malmquist Productivity Index for Cross-Productivity Index

The Global Malmquist Productivity Index (GMPI) stands as an evolution of the Malmquist Productivity Index (MPI), emphasizing global technology to incorporate all-time versions of Decision-Making Units (DMUs). This paper introduces a novel approach, integrating the Nash Bargaining Game model with GMPI to establish a Cross-Productivity Index. Our primary objective is to develop a comprehensive framework utilizing the Nash Bargaining Game model to derive equitable common weights for different time versions of DMUs. These weights serve as a fundamental component for cross-evaluation based on GMPI, facilitating a holistic assessment of DMU performance over varying time periods. The proposed index is designed with essential properties: feasibility, non-arbitrariness concerning the base time period, technological consistency across periods, and weight uniformity for GMPI calculations between two-time versions of a unit. This research amalgamates cross-evaluation and global technology while employing geometric averages to derive a conclusive cross-productivity index. The core motivation behind this methodology is to establish a reliable and fair means of evaluating DMU performance, integrating insights from Nash Bargaining Game principles and GMPI. This paper elucidates the rationale behind merging the Nash Bargaining Game model with GMPI and outlines the objectives to provide a comprehensive Cross-Productivity Index, aiming to enhance the robustness and reliability of productivity assessments across varied time frames.

LGBTQ+ collecting institutions: the culture of strategic management, motivation and professionalization

ABSTRACT This paper presents findings from an Australian Research Council Linkage Project investigating LGBTQ+ memory, migration and collecting institution practices. It analyses the ways in which minority LGBTQ+ collecting institutions (galleries, libraries, archives and museums) have professionalized in recent decades and adopted the use of strategic management documents such as strategic plans, mission statements and annual reports. Analysing documents from the 48 most prominent LGBTQ+ collecting institutions around the world, this article explores the ways in which such documents present narratives about the motivation and justification for minority collecting institutions, and how they represent themselves as professional rather than grassroots or activist organizations. Three core motivations emerged from the study: the preservation and celebration of the past, sustaining an ‘ethnic minority’ model of LGBTQ+ community through engagement in the present and aspiration for social change and justice for the future. The paper unpacks the underlying discourses to provide a perspective on the role of these cultural institutions in minority communities.

Safeguarding Filipiniana Materials: Recognizing and Prioritizing Risks in Transporting, Moving or Relocating Library, Archives, and Museum Collections

Objectives. Libraries, archives, and museums are vital for learning and culture. Disasters threaten both their buildings and collections. Safety is paramount during crises, but safeguarding collections is also essential. The study investigated why five Filipiniana institutions – Filipinas Heritage Library, Lopez Museum and Library, National Archives of the Philippines, National Library of the Philippines, and University of the Philippines Diliman – Main Library – moved their collections and managed risks. Methods. The researcher used qualitative and quantitative methods, assessing risks based on probability and impact. Results. The findings revealed motivations for moving collections, either extrinsic (like renovations) or intrinsic (pride). It highlighted the importance of recognizing and prioritizing risks, even low-level ones, to protect collections and the institutions' core motivations. Conclusion. Failure to mitigate risks may lead to losses and damage, impacting these institutions' core motivations.

School-based research centres: one school’s exploration

School-based research centres are growing in number and have potential to amplify school students’ voices in research through activities within the school. This paper explores how one research centre in an independent school in Australia, in a financially and socially privileged context, is using tertiary-type structures (namely, an ethics committee, research journal and conference) to engage students in research activities and give them voice about research in their school. Writing as centre director and practitioner researcher in the school, I explore these activities which position research as a skill with potential to further students’ academic capital, as well as their ability to challenge their understanding of privilege in the world. A core motivation for this paper is consideration of the transposition of structures designed for adults into the school context and exploring how students engage with these structures in order to have a voice as researchers and in research.