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This paper illustrates how Guba and Lincoln's parallel criteria for establishing trustworthiness, can be adapted and applied to qualitative research on indigenous social protection systems. It provides insights for social protection researchers, exploring plausible qualitative research rigor evaluation criteria, on plausible alternatives.

The paper draws on qualitative evidence from a larger ethnographic study on the dynamics of indigenous social protection systems in Nigeria. It illustrates the systematic application of Guba and Lincoln's parallel criteria.

Available evidence from the study shows that Guba and Lincoln's parallel criteria is viable for establishing trustworthiness of qualitative research on indigenous social protection systems. The criteria can facilitate credible and reliable research outcomes in research on improving social protection policy and practice.

Qualitative inquiries that draw on Guba and Lincoln's parallel criteria as evaluation criteria for trustworthiness can complement quantitative research on social protection. This makes it imperative to incorporate both, in social protection research for a holistic system. How this can be done is beyond the scope of this paper but needs to be explored by future research.

Contrary to the use of Guba and Lincoln's parallel criteria in qualitative research in other contexts, the use of the criteria has not been carefully examined in qualitative research on indigenous social protection systems. This paper is an attempt to fill this gap.

The different dimensions and contexts within which value is co-created has generated varied views of how value is understood or formed. This study aims to examine employee-guest perceived value as important factors for the successful implementation of value co-creation (VCC).

The study employs an interpretive paradigm, using in-depth interviews, focus group discussions and participant observation in a qualitative design to increase understanding of employee-guest perceived value to aid the implementation of VCC at the dyadic level.

Findings highlight eight value perceptions including value for money, hotel location, physical evidence, mutual respect, appreciation, safety & security, quality & varieties of food and technological characteristics of service as important factors for the successful implementation of VCC at the dyadic level.

Generalisability of the findings is a limitation not only due to the smaller sample size but also due to industry-specific context. The study follows rigorous procedures to minimise biases, yet research limitation is acknowledged from the researcher’s participation in the research process.

The notion that actor’s assess value differently from the same service suggests that diverse service elements might be experienced differently. This study provides insights for hotel managers to recognise not only individuals’ value preferences but also service types that reflect employee-guest collective service preferences for sustainability.

This study integrates and extends extant literature by examining employees’ and guests’ individual and collective views at distinct hotel contexts to gain useful insights into value and VCC. The study proposes a framework that hospitality firms can use to address service failure and competition-related issues.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.