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This study aims to assess the effectiveness of online e-resource marketing tools used by university libraries to market e-resources. The specific objectives of this study were to uncover the e-resources that are showcased by university libraries, find out instructions posted by libraries to facilitate access and utilization of e-resources, examine marketing tools used, examine how current and relevant marketing messages and test the functionality of the marketing tools used.

An exploratory research design was used to assess the effectiveness of e-resources marketing tools. The study population included all public university libraries in Tanzania. The sample was purposively selected to include all publicly funded libraries as they work under similar management environments. Data collection involved the evaluation of online marketing tools using a matrix checklist.

It was revealed that most university libraries use websites for showcasing e-resources. The commonly used social media for marketing e-resources is Facebook followed by Instagram while Twitter and Ask a Librarian are the least used. The results further show that only a few universities provide instructions on how to access and use e-resources. The findings indicate that universities had active communication platforms for marketing e-resources. Furthermore, less than 50% of marketing messages are active and current. It is recommended that marketing e-resources should be integrated into the library’s plans and strategies and this should be informed by library policies.

Given that, this study involved Tanzanian public university libraries, it is possible that the findings do not represent the same situation in all academic university libraries in the nation.

This study assesses the effectiveness of online tools used to market e-resources in university libraries in Tanzania. It reveals the e-resources that are showcased online, the instructions provided on how to access the e-resources and the functionality of the marketing tools. Unlike the previous research, which primarily focused on evaluating the Web-based tools in university and college libraries, this study focused on public libraries in the country. The results will not only contribute to the theoretical and practical understanding of the functionality of the marketing tools but also provide actionable insights to decision-makers in libraries in marketing their e-resources.

This study aims to predict customers’ intention (INT) to visit green hotels through an extended norm activation model (NAM) framework. The extended NAM includes environmental concern (EC), price consciousness (PC) and aesthetic values (AEV).

A quantitative survey design was used to collect 340 valid responses from customers in Pakistan. Partial least square - structural equation modeling was used to assess the hypothesized relationships.

The results show that EC and awareness of consequences have a significant ascription of responsibility (AR) and personal norms (PN) towards INT. The results confirmed the moderating effect of PC on the relationship between PN and INT and the moderating effect of AEV on relationship between PN and INT and AR and INT. The findings indicate that PN does not mediate the relationship between AR and INT. These findings indicate that customers are aware of the consequences of resource depletion and environmental pollution that result from the unsustainable hotel practices. Therefore, customers tend to visit aesthetically green hotels at affordable prices.

The study proposes that green hotels should design marketing strategies in a way that increases customers’ awareness and concern towards environmental issues. Marketing campaigns focusing on environmental aspects of green hotels enhance its green reputation and motivate customers to visit green hotels. In addition, managers must consider enhancing the beauty of hotels at a competitive price.

This is the first study to use an extended NAM by integrating EC, average variance extracted and PC to predict customers’ INT towards green hotels. The extended NAM framework provides comprehensive understanding of the relationships between EC, AR and PN regarding visiting green hotels. In addition, the study emphasizes on AEV’s crucial role in influencing customers’ INT to visit green hotels.

Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study is to provide a framework to guide quality practitioners with the implementation of digitalisation in their existing practices.

A review of literature assessed how quality management and digitalisation have been integrated. Findings from the literature review highlighted the success of the integration of Lean manufacturing with digitalisation. A comprehensive list of Lean Six Sigma tools were then reviewed in terms of their effectiveness and relevance for the hybrid digitisation approach to process improvement (HyDAPI) framework.

The implementation of the proposed HyDAPI framework in an industrial case study led to increased efficiency, reduction of waste, standardised work, mistake proofing and the ability to root cause non-conformance products.

The activities and tools in the HyDAPI framework are not inclusive of all techniques from Lean Six Sigma.

The HyDAPI framework is a flexible guide for quality practitioners to digitalise key information from manufacturing processes. The framework allows organisations to select the appropriate tools as needed. This is required because of the varying and complex nature of organisation processes and the challenge of adapting to the continually evolving Industry 4.0.

This research proposes the HyDAPI framework as a flexible and adaptable approach for quality management practitioners to implement digitalisation. This was developed because of the gap in research regarding the lack of procedures guiding organisations in their digital transition to Industry 4.0.

This study aims to evaluate the relationship between the estimated levels of diet advanced glycation end products (dAGEs) intake and obesity in university students.

This cross-sectional study included 301 university students aged 18–30 years. dAGEs was estimated using a food frequency questionnaire, for 549 routinely consumed food items and were reported by dividing total energy intake. Dietary intake and sociodemographic data were collected using validated questionnaires, and the anthropometric characteristics were measured. The relationship between anthropometric measurements and dAGEs intake was examined by binary logistic regression.

A total of 43.2% of the participants had high levels of dAGEs. A significant decreasing trend was found in the percentage of carbohydrate intake compared to the increasing trend in dAGEs consumption (p = 0.005). The percentage of fat intake and meat consumption were significantly higher in participants with the highest consumption, compared with the lowest consumption of dAGEs (p = 0.006). According to the dAGEs classification of participants, body mass index, waist circumference and energy intake were found to be significantly related in all model groups. Accordingly, the increase in body mass index, waist circumference and energy intake were determined as a risk factor in those with high dAGEs intakes.

The findings of this study emphasized that higher intake of dAGEs was associated with an increased risk of obesity parameters in college students.

The factors involved in and obstacles to sharing economy adoption have been studied with several methods, and several models have occurred to clarify the underlying procedure of sharing economy (SE) adoption, which provide contradictory and scattered findings. This chapter seeks to offer a scientific outline of the academic structure of the SE adoption domain.

Designing effective business analytics (BA) platforms that visualise data, provide deep insights and support data-driven decision-making is a challenging task. Understanding the elements shaping BA platform design is crucial for success. The purpose of this study is to explore the impact of visualisation on usability (UI) and user experience (UX) while emphasising the importance of insights understanding in BA platform design.

This paper presents a case study following a startup’s journey as it undergoes two redesign phases for its BA platform. A combination of quantitative and qualitative methods is used to assess UX/UI and insights understanding of the platform. Indicatively this included semi-structured interviews, observations, think-aloud techniques and surveys to monitor runtime per task, number of errors, users’ emotions and users’ understanding.

Our findings suggest that modifications in aesthetics and information visualisation positively influence overall usability, UX, and understanding of platform insights – a critical aspect for the success of the startup.

Our goal is not to make a methodological contribution, but to illustrate how companies, constrained by time and pressure, navigate platform changes without meticulous design and provide learnings on important elements while designing BA platforms.

This paper concludes with suggested methods for assessing BA platforms and recommends practical practices to follow. These practices include recommendations on important elements for BA platform users, such as navigation and interactivity, user control and personalisation, visual consistency and effective visualisation.

This study contributes to practice as it presents a real-life case and offers valuable insights for practitioners.

The existing literature highlights challenges in measuring social impact within social and solidarity economy organisations, particularly regarding the social return on investment (SROI) methodology. This paper aims to address the barriers to SROI implementation while exploring the potential of artificial intelligence (AI) in enhancing the measurement of social impact.

This review-based paper synthesises research on SROI methodology limitations and recent AI developments while focusing on ethical considerations. Drawing from these domains, the study constructs a conceptual framework to guide future research.

The study identifies necessary enhancements to existing AI systems for social impact measurement and explores how advances in generative AI could refine current tools and address SROI constraints. It advocates for open AI models to address ethical concerns.

This study pioneers the integration of social impact assessment and AI, an innovative intersection in the academic literature. The growing disparity between academia and the rapidly evolving AI industry is highlighted and scholarly discourse is enriched through theoretical deliberations and innovative technological solutions.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.