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The paper explores the implementation and process of a Participatory Action Research (PAR) project in Jacksonville, Florida. Using PAR principles, we sought to disrupt traditional dynamics in research, co-generating knowledge with the community. We aimed to elevate disenfranchised voices and foster effective solutions for neighborhood revitalization and resilience, which are designed and led by the community. In this paper we explore researcher positionality, examining how engagement with the community context profoundly influences researchers' perspectives and roles, thereby shaping the study trajectory.

We use reflexive and thematic approaches to analyze researcher positionalities and dynamics with the community. Researchers' reflections were scrutinized with a focus on their backgrounds, adaptability to community pace of work, lessons learned and evolving perspectives on community-centered research. We present a comprehensive discussion of emerging themes and emphasize the transformative nature of PAR and the significance of the researcher pursuing a relationship of belonging within the community.

The study uncovered key themes clarifying the transformations experienced by researchers engaged in PAR. We underwent a significant shift from a predetermined, structured PAR model to a more organic, community-driven model. This shift is illustrated under key themes in the paper: being vulnerable, valuing relationships, transforming the sense of self and solidarity, focusing on the process and recognizing and valuing community-derived knowledge. We write about the metamorphosis of researchers' roles from passive observers to active and empathic participants and about the implications for our methodological approach. As a result of this adaptation, the research process was enhanced and a symbiotic learning environment was created between the researchers and the community.

This paper distinguishes itself through its community-centric approach, diverging from traditional research paradigms. It explores how PAR-based community engagement can have a positive impact on those who are involved in PAR themselves, contributing to a better understanding of reciprocal dynamics in community-based research. We hope that our process of reflection can help other disaster researchers to ask better questions of themselves when engaging with communities and be open to following the lead and the pace of the community.

Universities in the United Kingdom, like their counterparts globally, are confronting difficulties associated with the well-being of students. The origins of these challenges are complex, exacerbated by various global events. In response, universities are trying to address these growing concerns and the escalating need for student support. Faculty members are often recruited to assist students in navigating academic and personal challenges. The aim of this study was to investigate how the process of student mentoring, by faculty members, could be made more operationally robust to better support student demand, thus yielding greater value for both students and staff.

A qualitative approach was adopted with 19 academic faculty working as mentors within a UK business school who participated in 90-minute semi-structured interviews. Interviews were analysed using an operational (transformation) management framework, with findings categorised under three key headings – inputs, transformations and outputs – to discover how the operational process of mentoring students could be enhanced.

Participants discussed the inputs required to deliver mentoring, the process of transformation and their desired outputs. Findings suggest coordinated and relevant inputs that is, information, environments and technology, coupled with good mentor selection and recruitment improves operational robustness, adding greater value to the student experience by creating more purposeful outputs, thereby benefiting themselves and their students.

The application of an operational (transformation) process framework to analyse faculty mentoring of students is unique, thereby offering new insights into the construction and management of these types of academic support initiatives.

Current solutions for monitoring the progress of pavement construction (such as collecting, processing and analysing data) are inefficient, labour-intensive, time-consuming, tedious and error-prone. In this study, an automated solution proposes sensors prototype mounted unmanned ground vehicle (UGV) for data collection, an LSTM classifier for road layer detection, the integrated algorithm for as-built progress calculation and web-based as-built reporting.

The crux of the proposed solution, the road layer detection model, is proposed to develop from the layer change detection model and rule-based reasoning. In the beginning, data were gathered using a UGV with a laser ToF (time-of-flight) distance sensor, accelerometer, gyroscope and GPS sensor in a controlled environment. The long short-term memory (LSTM) algorithm was utilised on acquired data to develop a classifier model for layer change detection, such as layer not changed, layer up and layer down.

In controlled environment experiments, the classification of road layer changes achieved 94.35% test accuracy with 14.05% loss. Subsequently, the proposed approach, including the layer detection model, as-built measurement algorithm and reporting, was successfully implemented with a real case study to test the robustness of the model and measure the as-built progress.

The implementation of the proposed framework can allow continuous, real-time monitoring of road construction projects, eliminating the need for manual, time-consuming methods. This study will potentially help the construction industry in the real time decision-making process of construction progress monitoring and controlling action.

This first novel approach marks the first utilization of sensors mounted UGV for monitoring road construction progress, filling a crucial research gap in incremental and segment-wise construction monitoring and offering a solution that addresses challenges faced by Unmanned Aerial Vehicles (UAVs) and 3D reconstruction. Utilizing UGVs offers advantages like cost-effectiveness, safety and operational flexibility in no-fly zones.

The purpose of this paper is to explore how variations in management’s tone within management’s discussion and analysis (MD&A) sections of 10-K reports can serve as an indicator of tax avoidance and highlight the complex relationship between such linguistic shifts and the tax avoidance decisions within firms.

The paper uses a textual analysis approach to identify linguistic cues in MD&A sections of 10-K filings related to tax avoidance, going beyond traditional quantitative measures. The study uses differences in negative word occurrences in MD&A to measure management’s tone change and examines various measures of tax avoidance. The sample covers the period from 1993 to 2017 and comprises all firms with 10-K filings available on EDGAR, totaling over 30,000 firm-year observations.

The findings indicate a complementary relationship between tax avoidance and other drivers of firm performance. When firms have more negative management’s tone, they are less willing to engage in tax avoidance and vice versa. The study’s approach with management’s tone change provides a different and statistically significant improvement in model fit for detecting tax avoidance.

This paper provides actionable insights for detecting tax avoidance through the analysis of management’s tone in corporate disclosures, offering a new tool for researchers, investors and tax authorities. It highlights the importance of linguistic cues as indicators of tax avoidance behavior, complementing traditional financial metrics.

The paper contributes to the literature by using management’s tone change as a time-varying factor to explain tax avoidance behavior. It uncovers a larger set of linguistic cues in MD&A that can be used to detect tax avoidance. This research provides a complementary approach to traditional quantitative tax avoidance measures and offers insights into the overall relationship between tax avoidance and firm performance, going beyond one-dimensional measures typically used in prior literature.

Construction organizations' investment in effective talent-development programs is a key strategy in attracting, developing and retaining staff. Such programs are especially important given the current challenges in the construction workforce, including labor shortages, an aging workforce, generational differences in the workforce, supply chain disruptions and the need to effectively train staff in the skills that are essential in a constrained labor environment. To address these challenges, this study proposes a performance measurement strategy that construction companies can use as input to design their talent development programs.

The strategy intends to assess the performance of project managers and develop criteria that define categories of their performance, including the top performers' category. This enables construction organizations to provide each project manager with individualized training that addresses areas of weakness and in turn, develops the skills that correspond with being top performers. The proposed strategy was developed and tested by surveying the immediate supervisors of 187 project managers working for general and specialty contractors in the United States. Principal component analysis was used to develop a single performance construct from seven performance criteria.

This construct was used to organize the project managers into the categories of top, above-average and below-average performers. According to the findings, top-performing project managers have well-rounded skills in the areas of leadership, communication, technical proficiency and overall job knowledge.

The outcomes of this study can help construction organizations focus their talent-development programs on the skills most associated with PMs being top performers.

This study provides construction organizations with a comprehensive performance-measuring construct to focus their talent-development programs on the skills most associated with top-performing project managers. Researchers can use this study as a foundation for further understanding how performance is related to various construction professions.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

A global crisis like that caused by the COVID-19 pandemic threatens the survival of any business, but especially of nascent entrepreneurs, due to their vulnerable situation. At this stage of entrepreneurship, information and communication technology capabilities (ICTCs) are critical skills that help entrepreneurs develop their new businesses, fostering economic adaptability to counteract adverse effects. This study advances knowledge of how nascent entrepreneurs react in an environment of global crisis.

The study analyzes a sample of 331 Spanish nascent entrepreneurs to determine the mediating effect of ICTCs on the relationship between the impact of a global crisis (e.g. COVID-19) and the firm’s strategic response.

The results suggest that crises influence adaptation and compensation strategies significantly and that ICTCs exert a total mediating effect on this relationship. The results do not, however, establish a clear relationship between the impact of the COVID-19 crisis and disengagement response, but rather a negative relationship, possibly influenced by government attempts to mitigate the pandemic’s economic consequences (economic aid to maintain the workforce, financial support for business model survival).

The COVID-19 crisis revealed ICT as a key technology for continuing business operations. This study analyzes how ICTCs affect nascent entrepreneurs’ strategies in crisis environments. Our analysis is important because these entrepreneurs have invested resources in their new project. We must determine their strategic response to crisis environments: adaptation, compensation or disengagement. The sample itself, collected during the pandemic, provides unique insights into the impact of the crisis on nascent business decisions.

像2019冠狀病毒病大流行等的全球危機一旦發生，各工商企業能否繼續生存必會受到威脅和影響。這影響以剛開始發展的創業者為甚，因為他們處於脆弱的處境。在這個創業階段，創業者必須擁有資訊與通訊科技能力，才能發展他們的新業務，他們亦需培養經濟上的適應能力，以能抵銷各種不利的影響。本研究擬就剛開始發展的創業者在全球危機發生時應如何應對進行探討，以增進我們對這課題的知識。

本研究分析一個涵蓋331名西班牙新生創業者的樣本，來鑒定資訊與通訊科技能力對全球危機 (如2019冠狀病毒病) 帶來的影響與企業戰略應對之間的關聯所起的中介效應。

研究結果似顯示，危機會顯著地影響企業的適應和賠償策略; 研究結果似乎也顯示，資訊與通訊科技能力會對這關聯 (全球危機所帶來的影響與企業戰略應對之間的關聯) 發揮極大的中介效應。但研究結果並沒有就2019冠狀病毒病危機的影響與脫離反應、建立明確的關聯。反之，研究結果似顯示兩者有一個負相關的關係，這可能是因為政府施行應對方法，以減輕大流行所帶來的經濟後果所致 (這些應對方法包括用以維持勞動力隊伍的經濟援助、和使商業模式能繼續生存的財政支援) 。

2019冠狀病毒病危機揭示了資訊與通訊科技是讓商業運作能繼續進行的關鍵技術。本研究分析資訊與通訊科技能力如何於危機發生時影響新生創業者的策略。我們的分析有其重要性，這是因為這些創業者把資源投入他們的新項目; 我們必須鑒定他們對危機所採取的戰略對策: 適應、賠償和脫離。取自大流行期間有關的樣本本身已能就危機如何影響新生創業者的商務決策、提供獨特的啟示。

The purpose of this study is to investigate how expressing gratitude and forgiveness on social media platforms relates to the overall sentiment of users, aiming to understand the impact of these expressions on social media interactions and individual well-being.

The hypothesis posits that users who frequently express gratitude or forgiveness will exhibit more positive sentiment in all posts during the observed period, compared to those who express these emotions less often. To test the hypothesis, sentiment analysis and statistical inference will be used. Additionally, topic modelling algorithms will be used to identify and assess the correlation between expressing gratitude and forgiveness and various topics.

This research paper explores the relationship between expressing gratitude and forgiveness in X (formerly known as Twitter) posts and the overall sentiment of user posts. The findings suggest correlations between expressing these emotions and the overall tone of social media content. The findings of this study can inform future research on how expressing gratitude and forgiveness can affect online sentiment and communication.

The authors have demonstrated that social media users who frequently express gratitude or forgiveness over an extended period of time exhibit a more positive sentiment compared to those who express these emotions less. Additionally, the authors observed that BERTopic modelling analysis performs better than latent dirichlet allocation and Top2Vec modelling analyses when analysing short messages from social media. This research, through the application of innovative techniques and the confirmation of previous theoretical findings, paves the way for further studies in the fields of positive psychology and machine learning.

This study aims to identify key research clusters (or sub-fields) in the field of performance measurement research, analyse its historical development and propose future research avenues.

Several bibliometric analysis methods, including co-citation analysis and text mining techniques, were used to review papers published on performance measurement research.

This study reveals eight main clusters of research in this field, ranging from theoretical-focused clusters (e.g. strategic performance measurement) to practical-focused clusters (e.g. design of performance measurement). These clusters are further categorised into four groups based on the size and degree of connectedness. Regarding the analysis of historical development, the established clusters, such as supply chain management, remain important, while newer clusters, such as hospitality and humanitarianism, have recently gained increasing interest.

This study applies citation-based clustering, a type of bibliometric literature review method that has been underused in the field of performance measurement. Moreover, the results obtained from this study are also distinct from those of previous studies, offering valuable insights especially for researchers. With a comprehensive understanding of the field, researchers can use it to understand the key literature, observe ongoing developments within their specialisation and inform their future research directions.

The purpose of this study is to examine the effect of the coopetition strategy (CS) (the simultaneous pursuit of collaboration and competition) on sustainable performance (SP) through the serial mediation of knowledge sharing (KS) and open innovation (OI).

A structured questionnaire was used to gather data from corporate business enterprises, and partial least squares structural equation modeling was used for analysis.

Empirical evidence supports the coopetition strategy's role in enhancing KS, which in turn fosters OI, leading to improved SP. It has also been concluded that KS and OI have a significant serial mediation effect on the relationship between CS and SP.

Through the integration of KS and inward-outward open innovation, the coopetition model enables coopetitors leverage each other’s resources and capacities for mutual sustainability. To fully benefit from it, small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) must change their perception of free competition and actively engage in coopetition activities, particularly in the realms of knowledge and OI.

The most novel contribution of this study to the growing body of knowledge on SP is the establishment of empirical evidence regarding the crucial role of a serial mediation of KS and OI in the relationship between CS and SP. Unlike earlier research, this study provides a structured perspective and understanding of how and why CS, KS and OI were leveraged to enhance the SP of SMEs.