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Achieving project performance goals in extremely resource-constrained environments, such as those of social enterprises, is challenging. These organizations often employ bricolage – making the most of available resources – to navigate challenging landscapes. This study aims to understand how bricolage capabilities enhance or attenuate organizational project outcomes in resource-constrained social enterprises.

An exploratory survey was conducted to understand project management practices in Canadian social enterprises. Established scales were used to measure constructs with confirmatory factor analysis, and linear regression was employed to analyze relationships.

The study provides empirical evidence of the positive influence of bricolage on organizational project performance, with a crossover interaction observed for moderators – entrepreneurial leadership and project management capabilities. While project capabilities strengthen the positive impact of bricolage capabilities on project performance, entrepreneurial leadership has the opposite effect.

The insights from this study offer an initial roadmap for project managers for effective resource acquisition and utilization through bricolage, ultimately enhancing project management effectiveness in resource-constrained environments.

Despite the crucial role of bricolage capabilities in resource-constrained environments, the project management literature has largely neglected this concept. It is unclear how organizations use bricolage to manage projects. This lack of understanding challenges organizations, hindering their ability to apply bricolage consistently and thoughtfully in managing projects. Our study provides a deeper understanding of how bricolage facilitates project performance and enriches our understanding of it as an effective resource mobilization strategy within social enterprises.

The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.

This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.

The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.

While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.

Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.

Artificial intelligence (AI) radically transforms organizations, yet ethical AI’s effect on employee innovation remains understudied. Therefore, this study aims to explore whether responsible artificial intelligence (RAI) enhances high-tech employees’ innovative work behavior (IWB) through creative self-efficacy (CSE) and employee mental health and well-being (EMHWB). The study further examines how leaders’ RAI symbolization (LRAIS) moderates RAI’s effect.

Through structural equation modeling, 441 responses of high-tech firms’ employees from Pakistan were utilized for hypotheses testing via SmartPLS-4.

The results revealed that second-order RAI enhances employees’ IWB. The effect was supported directly and indirectly through CSE and EMHWB. Findings also showed that LRAIS significantly moderates RAI’s influence on CSE, on the one hand, and EMHWB, on the other.

High-tech firms’ managers can fix AI-outlook issues that impair their employees’ IWB by prioritizing an ethical AI design involving actions like AI control mechanisms, bias checks and algorithmic audits. Similarly, these managers should facilitate RAI discussions and targeted trainings focusing on employees’ cognitive development and well-being. Likewise, RAI embracement programs and evaluations for leadership positions could be incorporated into high-tech firms.

This study advances the mainstream AI literature and addresses a notable gap concerning RAI’s influence on employees’ IWB while grounding in social cognitive theory. Moreover, this study unveils how CSE and EMHWB affect IWB within RAI milieus. Additionally, through signaling theory, it underscores the significance of LRAIS in amplifying the direct association between RAI, CSE, and EMHWB within high-tech firms in emerging markets.

Drawing upon the authors’ experiences as minoritised academic scholars within leadership roles of a Black, Asian, Minority Ethnic (BAME) Network in the United Kingdom (UK) academe, the authors explored the research question “In what ways do racially minoritised academics use coping techniques and strategies to counter racism and inequality in the higher education environment”.

The authors used a collective autoethnography approach accompanied by storytelling, underpinned by a qualitative interpretative process, supported by inductive, data-driven theorising. The authors’ approach is supplemented by the usage of content analysis (Schrieier, 2012) to analyse the data and generate findings.

The research findings specifically highlight (1) collectivism, solidarity and belonging, (2) knowledge expansion and critical consciousness, (3) disarming approaches and emotional labour, (4) resistance through setting boundaries and (5) intersectionality and BAME men allyship, as specific approaches for taking forward anti-racism.

Autoethnographic research has encountered challenges around verification, transparency and veracity of data, and issues have been debated due to its subjective nature (see Jones, 2010; Keeler, 2019; Méndez, 2013). Additional complications arise regarding neutrality and objectivity associated with the researchers' identities and experiences being represented in autoethnographic accounts. The authors acknowledge that the accounts provided are subjective, and have influenced the research process and product.

Research on the experiences of minoritised academics leading staff equality networks constitutes a research gap. This article offers an original analysis through outlining the authors’ lived experiences in leadership positions of a BAME Network and hope to other minoritised employees undertaking anti-racist work.

This paper aims to present the results of a project deployment on voluntary data exchange between a municipality and commercial entities built on the Commitment-Trust theory. The research also discovers whether data sharing can be a vital instrument to foster city socio-economic development.

Inspired by the engaged scholarship approach, this research explores the economic and operational results of data integration from two different information sources, the legislation impact and the effects on citizens as final beneficiaries. Over a period of 27 months, the authors observed changes the voluntary data sharing brings in traditional interaction between multiple ecosystems. The impact of positive and negative factors was validated via 12 exit interviews with key stakeholders.

Voluntary data sharing is driven by parties’ goodwill to improve public services for residents, the organisations gain tremendously much more benefits than they can do separately on their own. When the parties commit to voluntarily share data, this increases trust in each other and the responsibility of each data contributor. This research proposes that the Commitment-Trust theory is well-replicable for the government-to-business relationship.

This research contributes to the current body of knowledge of voluntary data exchange between different ecosystems, especially between a government and its environment. This paper presents a relevant project deployment from an emerging economy and its consequences for a city municipality, businesses and residents.

In keeping with recent body image social trends, consumer demand for the adoption of plus-size models is increasing, although the use of thin models remains prevalent. The current study explores how consumers process information about fashion products displayed on different sizes of models in advertisements, focusing on model and consumer body sizes and both genders. As an underlying mechanism explaining how the relationship between model and consumer body sizes shapes consumer purchase intention, this study explores the role of guilt, shame and mental imagery.

The current study uses a text analytics technique to identify female consumers' general opinions of thin models in advertising. Employing a 3 (consumer body size: normal, overweight, obese) × 2 (model body size: thin, plus-size) × 2 (gender: male, female) between-subjects online experiment (n = 718), the main study comparatively analyzes the influences of plus-size and thin models on consumer responses.

The results reveal that, despite body positivity movements, thin models still generate negative emotions among female consumers. For obese female consumers, advertisements featuring plus-size models produce fewer negative emotions but not more mental imagery than advertisements featuring thin models. Conversely, for obese male consumers, advertisements featuring plus-size models generate more mental imagery but not more negative emotions than advertisements featuring thin models. The results also reveal that the relationship between consumer body size and guilt is moderated by perceived model size, which is also moderated by gender in generating mental imagery. While guilt plays a mediating role in enhancing mental imagery, resulting in purchase intention, shame does not take on this role.

This study is the first to present an integrated model that elucidates how consumers with varying body sizes respond to different sizes of models in advertising and how these responses impact purchase intentions.

Our findings only apply to contexts where consumers purchase fashion clothing in response to advertisements featuring thin versus plus-size models.

Exposing normal-size consumers to plus-size models generates less mental imagery, and thus, practitioners should seek to match the body sizes of the models featured in advertising to the body sizes of their target audience or ad campaigns that include both plus-size and thin models may help improve message persuasiveness in fashion advertising. Moreover, guilt-appeal advertising campaigns using thin models would appeal more to thin consumers of both genders than shame-appeal advertising.

Inspired by the concept of the moment of truth, this study aims to examine how service interactions between hotel front-desk staff and a first-time check-in guest affect the guest’s brand satisfaction and brand attitudes, considering the moderating effect of welcome hospitality.

This study employs a between-subjects 2 (check-in service with high-service interaction vs low-service interaction) × 2 (with welcome hospitality vs without welcome hospitality) experimental method to investigate the mechanism of building brand attitudes towards a hotel during the check-in process.

The results of Study 1 showed that participants in the high-service interaction group reported higher brand satisfaction and brand attitudes than the low-service interaction group. It also confirmed that brand satisfaction fully mediates the relationship between service interactions and brand attributes. The results of Study 2 demonstrated the moderating effect of welcome hospitality. When service interaction is low, welcome hospitality can effectively improve brand satisfaction, but when service interaction is high, the improvement in brand satisfaction is smaller.

This research contributes to the literature on service interactions by potentially first experimentally examining the impact of first-time employee-customer interactions within a hotel setting. Recommendations were provided to hotel operators on how hotel staff can improve their service interactions.

Design of architecture, engineering and construction (AEC) project organizations expose project management practitioners (PMPs) to poor mental health due to the influence of project organization designs on project management activities assigned to the PMPs. The AEC project organization design comprises the integration of permanent organization, project organization and external environment layers. In spite of the link between project organization design and mental health, limited studies have examined the impact of permanent organization factors, project organization factors and external environmental factors on mental health management practices. Therefore, this study aims to examine the interactive relationships between permanent organization factors, project organization factors, external environment factors and mental health management indicators.

Four organizational theories: institutional theory, agency theory and resource-based theory were integrated to develop a theoretical model guiding the aim of the study. Eighty-two survey data were collected from PMPs in AEC firms in Australia. Structural equation modelling was used to test the relationships between the constructs.

The study found that mental health management indicators are predicted by the interactive and direct effects of permanent organizational factors, project organizational factors and external environmental factors. The results of the interactive effects of the factors and mental health management indicators revealed that 20 of 26 proposed hypotheses were supported. Based on the established hypotheses, economic factors, technological factors, environmental factors, legal factors and organizational culture positively correlated with mental health management indicators. Likewise, human resources management (HRM), corporate governance, project governance and integrated project delivery (IPD) positively impact mental health management indicators. However, political factors, social factors, knowledge management and project management skills negatively impact mental health management indicators. Moreover, political factors, economic factors, technological factors, environmental factors, legal factors and organizational culture are positively related to corporate governance. Additionally, organizational culture positively impacts corporate governance, project governance and HRM, whereas project governance positively correlated with IPD and knowledge management.

The findings provide guidelines to AEC firms on achieving positive mental health management indicators through concentration on project organization design.

There are calls for irradiated food labelling due to a significant need for food safety and extensive procedures to safeguard consumer health. Additionally, there is a strong push from producers for mandatory Country of Origin (COO) labelling. The study examines how the COO and Radura labels influence consumer behaviour and shows the interplay between these influences. Using Attitude-Behavior-Context theory, a conceptual model is proposed and tested to evaluate these factors. The use of multiple labels allows for more choices. How the information presented on labels corresponds to consumers' pre-purchase information search is tested on regular label users.

Structural Equation Modelling (SEM), Generalised Linear Modelling and Cluster Analysis were used to analyse the data on a sample of 322 Australian respondents.

The study revealed that COO labelling had a significant positive relationship with attitudes but a negative relationship with WTP, acting as a suppressed mediator between attitudes and WTP. Interestingly, while knowledge was not found significant, label confidence emerged as a significant factor. Furthermore, the research suggests that regular users may prioritize COO labels over Radura labels.

This research contributes novelty by being the first to address the interplay between COO and irradiated labels, complementing the growing body of literature on irradiation labelling. It also offers valuable insights for retail practitioners, providing an understanding that can facilitate the delivery of high-value multiple labels at the point of purchase.

The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.

Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.

The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology’s role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.

To the best of the authors’ knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers’s DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.