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The objective of this study is to construct a theoretical framework concerning wage determination, grounded in principles and supplemented by conventional theories. It discusses the Islamic perspectives on minimum wage and examines contemporary challenges and intricacies in its application.

This study uses thematic analysis to create the conceptual framework, drawing upon a review of pertinent literature such as academic papers, books and articles published up to 2023.

The framework encompasses various categories, namely, employee characteristics, job characteristics, market factors, compensation practices and Islamic principles. Each category consists of multiple variables. The resulting framework offers a holistic and ethically grounded methodology for wage determination, aligning with both Islamic and conventional perspectives. This study notes the absence of a universally agreed-upon minimum wage. Islamic economics faces challenges due to the unclear application of principles, limited awareness, legal constraints and a lack of empirical evidence on wage systems, along with complexities in their implementation.

The paper’s limited scope focuses solely on the Islamic perspective on wage determination, without comparing it to the conventional viewpoint. This may have implications for future research.

The insights on Islamic principles and wage determination guide scholars and policymakers interested in promoting just and equitable wages.

This study is distinct in its integration of various factors to propose an all-encompassing framework for wage determination, rooted in the Quran and principles, while also reinforcing the framework with conventional theories. Additionally, it adds to the growing body of literature by investigating the Quran’s stance and principles on minimum wage, as well as discusses the challenges involved in implementing an Islamic approach to wage determination, which has received limited attention in Islamic literature.

Successful knowledge transfer (KT) between younger and older workers (YW and OW, respectively) is critical for organizational success, especially in light of the recent surge in employment volatility among the youngest and oldest segments of the workforce. Yet, practitioners and scholars alike continue to struggle with knowing how best to facilitate these exchanges. The qualitative study offers insight into this phenomenon by exploring how KT unfolds in YW/OW dyads.

The authors performed a reflexive thematic analysis of semistructured interviews with two samples of blue- and white-collar younger/older workers from the USA (N = 40), whereby the authors interpreted the “lived experiences” of these workers when engaged in interdependent tasks.

The analysis, informed by social exchange theory and exchange theories of aging, led to the development of the knowledge transfer process model in younger/older worker dyads (KT-YOD). The model illustrates that, through different combinations of competence and humility, KT success is experienced either directly (by workers weighing the perceived benefits versus costs of KT) and/or indirectly (through different bases of trust/distrust perceived within their dyads). Further, humility in dyads appears to be necessary for KT success, while competence was insufficient for realizing KT success, independently.

In exposing new inner workings of the KT process in YW/OW dyads, the study introduces the importance of humility and brings scholars and organizations a step closer toward realizing the benefits of age diversity in their workplaces.

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.