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This paper critically evaluates potential barriers to employment opportunities for ethnic minority (EM) individuals in Scottish Local Authorities – both in terms of access to job and development opportunities. It provides a fundamental discussion of concepts around race and ethnicity, and the levels of social injustice, with an explicit focus on institutional racialisation, discrimination and segregation. The paper explores organisational approaches towards recruitment, including positive action and workforce development.

This paper adopts a subjectivist (ontology) and interpretivist (epistemology) stance, based on a small-scale, in-depth investigation. The data have been gathered through semi-structured interviews with equality diversity and inclusion (EDI) officers in four Scottish Local Authorities, utilising thematic analysis.

The finding suggests that participating local authorities have a long way to go to ensure the elimination of barriers to employment for EM people. This is largely based on concerns around limitations in the application of positive action and elimination of disadvantages in recruitment and access to career and development opportunities?

The paper aims to contribute by exploring the availability of employment opportunities for EMs through the eyes of EDI Officers in four local authorities. Their thorough understanding, over- and insight into potential equality issues from an employment perspective are invaluable, focussing on more tangible organisational issues and approaches.

There is evidence that spirituality at the workplace has positive effects on work outcomes, and there are different models conceptualizing the construct. To date, there is no discussion highlighting how digitalization is affecting workplace spirituality and vice versa. The present review tries to close this gap by discussing the psychological dynamics in light of digitalization and spirituality in the context of work.

This is a conceptual discussion based on an extensive narrative review. The conceptual design is further tested with a real-life case study.

The result is a model that may guide future research, which consists of the four highly interdependent domains, namely psychology (with the dimensions of emotion, cognition and behavior), digitalization (with the dimensions of platforms, data and algorithms), spirituality (with the dimensions of meaning, self-transcendation and belonging), as well as the workplace (with the dimensions of work tasks, location, community and culture and values). The discussion includes implications for the future of work, suggestions for management decisions and potential future research directions.

To date, there are many discussions about digital transformation and a limited amount of them have invested in analyzing psychological dimensions. The application to spirituality and the workplace – especially when the two are combined – is almost wholly absent, which makes the present discussion both innovative and original.

In today’s world, empowering individuals, promoting social cohesion and advancing economic development all hinge on access to high-quality education, prioritizing diversity, inclusion and equality. Rethinking current educational strategies using cyber-physical learning assets is necessary to accommodate the learning inclusivity and equity and escalating demands of a globalized world. There is a pressing demand for evidence to support the efficacy of collaborative learning in transforming curriculum and fostering learner inclusion. However, it is recognized as a pedagogical technique within the quality education domain. This study aims to address this knowledge gap by investigating how hybridized cybergogy paradigms facilitate collaborative learning, focusing on diversity, equity and inclusion, to improve educational quality in higher education.

This study used a qualitative approach with an exploratory design guided by an interpretive philosophical perspective. The data was gathered from 60 prospective teachers from the public sector university of Sindh, Pakistan. Semi-structured interviews were conducted with participants. They were then analyzed using theme analysis to understand their views on the potential of hybridized cybergogy paradigms for collaborative learning to improve the quality of education provided at institutions.

The study results confirm that learners benefit from increased access to learning resources, improved critical thinking and problem-solving skills and a more diverse and inclusive classroom working together in a collaborative hybridized cybergogy setting. By fostering SDG 4 (Quality Education) and the 21st-century skills necessary for global marketplace engagement and competing in progressive environments, this creative method equips learners with the capabilities to face modern global challenges.

The study offers valuable practical suggestions to stakeholders in higher education, including faculty, policymakers and teacher education programs, for integrating hybridized cybergogy and collaborative learning to align curricula with sustainable development goals. Additionally, it bridges a significant gap in the existing literature, which will aid future researchers interested in exploring this area.

This study stands out as it explores an underexamined area while providing novel educational insights.

This study examines the relationship between streamers' product descriptions, customer comments and online sales and focuses on the moderating effect of streamer–viewer relationship strength.

Between June 2021 and April 2022, the structured data of 965 livestreaming and unstructured text data of 42,956,147 characters from two major live-streaming platforms were collected for the study. Text analysis and regression analysis methods were employed for data analysis.

First, the authors' analysis reveals an inverted U-shaped relationship between comment length and product sales. Notably, comment volume and comment emotion positively influence product sales. Furthermore, the semantic richness, emotion and readability of streamers' product descriptions also positively influence product sales. Secondly, the authors find that the strength of streamer–viewer relationship weakens the positive effects of comment volume and comment emotion without moderating the inverted U-shaped effect of comment length. Lastly, the strength of streamer–viewer relationship also diminishes the positive effects of emotion, semantics and readability of streamers' product descriptions on product sales.

This study is the first to concurrently examine the direct and interactive effects of user-generated content (UGC) and marketer-generated content (MGC) on consumer purchase behaviors in livestreaming e-commerce, offering a novel perspective on individual decision-making and cue utilization in the social retail context.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

This study aims to investigate the impact of stakeholders’ nonfinancial resources (NFRs) on companies’ profitability, filling a significant gap in the literature regarding the role of NFRs in value creation.

Data from 76 organizations from 2017 to 2019 were collected and analyzed. Four primary NFRs and their key value drivers were identified, representing core elements that support different dimensions of a company’s performance. Statistical tests examined the relationship between stakeholders’ NFRs and financial performance measures.

When analyzed collectively and individually, the results reveal a significant positive influence of stakeholders’ NFRs on a firm’s profitability. Higher importance assigned to NFRs correlates with a higher return on sales.

This study contributes to the literature by empirically bridging the gap between stakeholder theory and the resource-based view, addressing the intersection of these perspectives. It also provides novel insights into how stakeholders’ NFRs impact profitability, offering valuable implications for research and managerial practice. It suggests that managers should integrate nonfinancial measures of NFRs within their performance measurement system to manage better and sustain companies’ value-creation process.

This paper aims to make sense of the social enterprise in a frame of social procurement and conceptualise it as a provider of public welfare based on bibliometric material. Comprehensively, it contributes to developments in social procurement, which has received limited attention.

Scoping literature from Web of Science and using bibliometric methods, the paper identifies and qualitatively explores the literary intersections between social enterprise and social procurement.

Of the 183 articles, four literary clusters are revealed illustrating scholarly intersections and a detailed exploration of social enterprise as a public provider. The alignment and themes of the clusters further indicate the application of, and role played by, social enterprise in social procurement. Collectively, they reveal the dominance of social enterprise in this dyadic relationship and a minor undertaking of research in social procurement.

This “sense-making” groundwork forms a foundational step in developing our understanding of procurements through social enterprises. Furthermore, a positioning and conceptualisation of social enterprise accredits their utility and applicability in delivering public benefits. In this way, the paper informs and supports scholarly and practice-based interest into social enterprises for the delivery of public services.

The paper presents the first bibliometric conceptualisation of social enterprise in relation to social procurement and offers detailed insights through the bibliometric clusters. Furthermore, the paper contributes to the underdeveloped social dimension of procurement and bridges the gap between two distinct fields of scholarship: public management and administration and social entrepreneurship.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

This study aims to reveal the knowledge structure of social media influencer marketing literature by performing science mapping analysis through a state-of-the-art bibliometric approach to determine the current and future trends. Social media influencer marketing is one of the most effective approaches to presenting a brand and offering value to consumers via social media.

This study evaluates the knowledge structure to uncover the emerging trends and future predictions in social media influencer marketing through bibliographic coupling and co-word analysis. In total, 917 journal publications were retrieved from the Web of Science database and analyzed using VOSviewer software.

The central theme in social media influencer marketing reflects digital engagement between influencers and followers and communication between influencers and followers. The theoretical and managerial implications are discussed.

This study unleashes the knowledge structure according to the fundamental literature of social media influencer marketing and the underlying themes related to the phenomenon.

The world is increasingly threatened by climate change. As the dimensions of this danger grow, it becomes essential to develop the most effective policies to mitigate its impacts and adapt to these new conditions. Technology is one of the most crucial components of this process, and this study focuses on examining climate change adaptation technologies. The aim of the study is to investigate the entire spectrum of technology actors and to concentrate on the technology citation network established from the past to the present, aiming to identify the core actors within this structure and provide a more comprehensive outlook.

The study explores patent citation relationships using social network analysis. It utilizes patent data published between 2000 and 2023 and registered by the US Patent and Trademark Office.

Study findings reveal that technologies related to greenhouse technologies in agriculture, technologies for combatting vector-borne diseases in the health sector, rainwater harvesting technologies for water management, and urban green infrastructure technologies for infrastructure systems emerge as the most suitable technologies for adaptation. For instance, greenhouse technologies hold significant potential for sustainable agricultural production and coping with the adverse effects of climate change. Additionally, ICTs establish intensive connections with nearly all other technologies, thus supporting our efforts in climate change adaptation. These technologies facilitate data collection, analysis, and management, contributing to a better understanding of the impacts of climate change.

Existing patent analysis methods often fall short in detailing the unique contributions of each technology within a technological network. This study addresses this deficiency by comprehensively examining and evaluating each technology within the network, thereby enabling us to better understand how these technologies interact with each other and contribute to the overall technological landscape.