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The advent of digital technologies has ushered in a new era of quality management (QM) known as Quality 4.0 (Q4.0). The successful implementation of Q4.0 requires the involvement of both leaders and employees. Leadership plays a critical role in motivating employees involved in quality practices. However, the mechanisms by which leadership inspires quality professionals to engage in continuous learning and remain vigorous in their roles are not well understood. This study aims to determine the impact of Q4.0 leadership on thriving at work (TAW) among quality professionals and to identify the underlying mechanisms.

Utilising the identity theory and social identity theory, a multilevel TAW model was developed. This study surveyed 63 team leaders and 243 subordinates, who are quality professionals working for companies implementing Q4.0. Multilevel structural equation modelling (MSEM) was applied to assess the hypotheses.

The study finds that Q4.0 leadership enhances TAW among quality professionals. The linkage between Q4.0 leadership and TAW is mediated by work group identification (WGI) at the group level and job identification (JI) at the individual level.

Insights from this study will enable organisations to make informed decisions regarding the leadership styles that best support TAW among quality professionals. By understanding the mechanisms linking Q4.0 leadership to TAW, organisations can foster both WGI and JI, ultimately enhancing engagement and performance in quality initiatives.

This study offers a novel contribution to the QM field by examining the role of Q4.0 leadership in motivating and sustaining the engagement of quality professionals. Exploring the relationships between Q4.0 leadership, WGI, JI and TAW helps to deepen our understanding of how Q4.0 leadership can enhance TAW among quality professionals.

This chapter examines Taylor Swift’s exceptional team-building and sustaining efforts that enhance her brand. Using social capital and Hackman’s team effectiveness model (Hackman, 1987, 2002, 2009), the chapter delves into how Swift surrounds herself with talented professionals and forms strategic relationships with emerging musicians. These connections foster trust, reciprocity, and collaborative success. By aligning her team with shared goals and maintaining strong interpersonal relationships, Swift exemplifies effective leadership in the music industry. This chapter provides insights into building and managing high-performing teams through unity and shared purpose.

The need to optimize the triangle formed by “quality, cost and time” culminated in increasing the focus from product to process quality. By analyzing the evolution of quality and the impact of Industry 4.0 on it, this research seeks, through a technical point of view, to comprehend the state of the art of quality 4.0 and intelligent quality management (IQM) by defining concepts, technologies, challenges and applications.

The review was conducted only in English, on IEEE Xplore, Scopus, Engineering Village and Web of Science databases with a backward citation analysis, having technology and quality as main concepts. In total, 109 papers were reduced to 24, and 11 characteristics were extracted.

Although many authors point to the same 4.0 technologies and the importance of quality for Industry 4.0, they differ in the concept of quality 4.0 and the implementation frameworks to achieve it.

This paper is one of the few studies that have searched for the roots of quality 4.0 and IQM. The work also seeks to identify their differences and their relationship with Industry 4.0.

This case is written on the basis of available secondary data sources including news articles, book chapters, video (YouTube) interviews, research papers and industry reports.

The case study examines Taylor Swift’s professional journey from her debut in the mid-2000s to the present, highlighting her notable accomplishments as a singer-songwriter and entrepreneur. Swift’s success in music, evident through chart-topping albums, sold-out tours and strategic partnerships, positions her as a significant figure in the industry. However, her primary challenge involves maintaining relevance and staying ahead in a continually evolving environment. To sustain her leadership role, Swift must consistently innovate across music, public image and promotional approaches. This entails adapting to changing trends, using digital platforms for increased audience engagement and exploring themes such as audience connection, brand evolution, effective marketing and the ongoing pursuit of competitiveness and influence amid dynamic market conditions. This case delves into Taylor Swift’s evolution as a multifaceted entrepreneur, exploring her strategies to merge personal values with commercial success while navigating public scrutiny and market demands. It highlights her strategic use of social media, engagement with controversies and carefully crafted personal brand to maintain her global influence.

This case may be taught in advanced undergraduate level courses or graduate level courses such as MBA. This case is appropriate for students studying entrepreneurship, marketing and business strategy.

Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the implementation of GenAI for SCM remains challenging, mainly due to the lack of knowledge regarding its key drivers. To address this gap, this study examines the factors driving GenAI implementation in an SCM environment and how these factors optimize SCM performance.

A thorough literature review was followed to identify the drivers. The resultant model from the drivers was validated using a quantitative study based on partial least squares structural equation modeling (PLS-SEM) that used responses from 315 expert respondents from the field of SCM.

The results confirmed the positive effect of performance expectancy, output quality and reliability, organizational innovativeness and management commitment to GenAI usage. Further, they showed that successful GenAI usage improved SCM performance through improved transparency, better decision-making, innovative design, robust development and responsiveness.

This study reports the potential drivers for the contemporary development of GenAI in SCM and highlights an action plan for GenAI’s optimal performance. The findings suggest that by increasing the rate of GenAI implementation, organizations can continuously improve their strategies and practices for better SCM performance.

This study establishes the first step toward empirically testing and validating a theoretical model for GenAI implementation and its effect on SCM performance.

This research focuses on people’s activities in the Liuhua Clothing Wholesale District in Guangzhou, China. The increasing use of social media in business, especially during the COVID-19 pandemic, has created inevitable changes to the way space is utilised. Lockdowns and transport restrictions pushed the clothing wholesale traders to engage in livestreaming to maintain their business. This research aims to understand how spaces have been mediatised with the use of social media.

To investigate changes in the use of spaces, this research draws on actor-network theory and regards spaces as actors, adopting qualitative research methods, including observation, semi-structured interviews and mapping.

The research finds that spaces are mediatised for presentation on social media. During the COVID-19 pandemic, when in-person activities were suspended, the virtual space, constituted by elements that exist in physical and virtual spaces, became more valued. Physical space is no longer perceived as a whole but as elements, such as background, sound and light, all of which are involved in the construction of virtual space on social media. The perception of physical space has become less important than the images presented on social media.

Social media now exists in many people’s everyday lives, but its influence on architecture and space has received insufficient attention. This research interrogates this phenomenon in a clothing wholesale district in China to reflect on the influence. Its significance lies in documenting the spatial implications of dependence on social media and the changes to spatial use in the age of social media.

Money laundering has affected the economy in different ways, where the fraudulent activities are either domestic or abroad, resulting in financial instability globally. Anti-money laundering (AML) system is applied to detect and report any suspicious transactions. There are numerous approaches, techniques and algorithms in AML that are applied to fight against money laundering. This study aims to understand, identify and document the AML techniques applied to detect and prevent money laundering activities.

A systematic literature review is applied for searching articles based on methods used for AML from the electronic database platform. For review, data is considered from journal articles, books and conference proceedings with a time framework from 2014 to 2024.

In total, 53 papers were selected in the domain of money laundering concepts, issues and techniques of AML. The review articles are on the techniques of AML, such as machine learning, data mining, graph networks and artificial intelligence, which are applied to detect and prevent money laundering issues.

Money laundering, being a global issue, is a threat to the economy and society. Detecting money laundering activities is utmost required; this study contributes in selecting the articles that are involved in the application of techniques of AML in detecting and preventing money laundering activities. The results of this study can provide support instruments to identify the better AML techniques that are useful for practitioners and industry experts working in the AML domain. Further research can be explored with other AML techniques.

While big data analytics can spur innovation among firms, it is unclear whether it can effectively drive value creation, value proposition, value delivery and value capture to deal with disruptions and the ever-changing demands of customers. This study therefore aims to examine how value creation, value proposition, value delivery and value capture can be improved through big data analytics capability (BDAC). This study advances the discourse by investigating how the market environment and strategic orientations play significant but little-studied roles in enhancing or lessening BDAC’s impact on business model innovation (BMI).

Drawing on dynamic capability and contingency perspectives, a model of five hypotheses was developed and validated using survey data from 208 managers of manufacturing firms in Ghana. Covariance-based structural equation modeling was used for the analysis.

The findings revealed that BDAC and strategic orientation (market and learning) directly influence the dimensions of BMI (value creation, value proposition, value delivery and value capture). The findings further showed that strategic orientations partially mediate the BDAC–BMI link. The authors also noted that the BDAC–BMI link is amplified at high levels of market dynamism.

The findings suggest that investing in BDA alone may not be sufficient to drive superior business model innovation. However, market orientation and continuous learning are crucial to fully realizing BDAC’s full potential in enabling value creation, value proposition, value delivery and value capture, especially in a dynamic market environment.

This study contributes to existing BMI literature by being the first to examine how BDAC facilitates value creation, value proposition, value delivery and value capture in developing countries. This paper also advances BM literature by theorizing and validating important but rarely studied roles of strategic orientations and market dynamism. Thus, this paper extends the understanding of the conditions and mechanisms through which the effect of BDAC on value creation, value proposition, value delivery and value capture can be optimized.

The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).

The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.

The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.

The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.

The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.

Using the resource-based view (RBV), our study aims to provide theoretical and empirical insights into blockchain capabilities’ (BCs) compounded and sequential effects on supply chain competitive advantages (CA).

We combined a systematic literature review and an expert interview. Interpretive Structural Modelling and a Matrix of Cross-Impact Multiplications Applied to Classification were used to determine the relationship between the capabilities. Simple Additive Weighting assessed each capability’s relative importance and impact.

We reveal a sequential development path for BCs. Foundational capabilities, such as cybersecurity, provide immediate performance benefits, establishing a unique, valuable and inimitable resource. As firms progress to advanced capabilities, the compounded value of these capabilities generates a stronger, dynamic resource for sustained CA. Moreover, the study underscores the strategic importance of timing in adopting and developing BCs, as early adoption can secure a competitive edge difficult for later entrants to replicate.

Our proposed framework guides managers in incorporating blockchain technology into supply chain management (SCM) processes once it demonstrates that firms can enhance their CA by prioritizing the technical basics BC, leveraging the informational capabilities in level two and enabling effective problem-solving through level three. Our framework also shows that a learning process occurs as BCs are used and their results are explored.

Our study extends the RBV by demonstrating BCs’ cumulative and interdependent nature in SCM. It emphasizes the synergistic interactions between these capabilities, which collectively enhance CA.