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Purpose: The prominence of quality education for building sustainable development is undeniable and is distinctly pointed out in 1 of the 14 sustainable development goals (SDGs). In the same context, this study intends to investigate the role of university commitment, perceived organisational prestige, student satisfaction, and perceived employability in enhancing sustainability in higher education.

Need of the Study: To evaluate how student satisfaction mediates the relationship between university commitment, perceived organisational prestige, and perceived employability with sustainable university institutes.

Methodology: An adapted questionnaire was used in this study to capture the perception of 458 management graduates selected through the purposive sampling method. Partial least squares structural equation modelling (PLS-SEM) technique was used to analyse the data with the help of Smart PLS software.

Findings: The results of this study show that student satisfaction is the strongest predictor of sustainable university institutes. University commitment was found to lead to student satisfaction significantly. Furthermore, student satisfaction wasn’t found to play the role of mediator in the proposed model.

Practical Implications: This study aims to fulfil theoretical, research, and management implications for students, higher education institutes (HEIs), and policymakers. HEIs are recommended to instil university commitment, perceived organisational prestige and student satisfaction via various practices and amendments in their curriculum. Students are recommended to enhance their perceived employability to achieve career sustainability.

An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.

This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.

This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.

This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.

This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.

This study examines how health-conscious consumers utilize nutrition facts panel labels when purchasing food products, focusing specifically on the dimension of ethical evaluation. It aims to understand how ethical considerations influence the decision-making process of consumers who prioritize health. By analyzing the impact of ethical evaluation on label usage, the study sheds light on the significance of ethics in consumer behavior in the context of purchasing packaged edible oil.

Empirical data were collected using an online survey and a non-ordered questionnaire. In total, 469 valid responses were obtained. The study used SPSS version 27.0 and SmartPLS version 3 for demographic analysis and structural equation modeling.

The findings suggest that three factors – perceived benefits, perceived threats, and nutrition self-efficacy, positively impact the use of NFP labels. However, perceived barriers negatively influence the use of NFP labels. In additionally, ethical evaluation mediates the usage of NFP labels.

In the health belief model, ethical evaluation functions as a mediator and has a greater influence on NFP label use. This study provides a framework for marketers to promote consumer health consciousness by encouraging them to incorporate NFP labels.

This study is one of the first attempts to demonstrate that ethical evaluation mediate health beliefs and the use of nutrition labels.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.

Manufacturing companies continue to encounter a diverse set of obstacles while embracing sustainable development goals. Accordingly, the purpose of this study is to explore critical sustainable development-related barriers to flexible packaging manufacturing companies in the New Zealand context.

Drawing on a qualitative multiple case studies approach, the authors collected data from the New Zealand flexible packaging industry. Semistructured interviews were conducted with the senior corporate managers in two large flexible packaging companies. Following the thematic analysis approach, the authors analyzed the information collected from the participants and synthesized our findings under the key dimensions of internal and external barriers to sustainable development.

The findings revealed that internal barriers to sustainable flexible packaging are linked to economic, operational and technical issues. Conversely, external barriers include global crises and disruption, customer behavior and preferences and institutional and infrastructural-related aspects. Based on the analysis of empirical findings, the authors further identified the underlying reasons for sustainable flexible packaging barriers and recommended guidelines that could assist corporate managers and policymakers in addressing obstacles inhibiting the flexible packaging industry from adopting sustainable business practices.

The authors argue that this study is one of the early studies to consider inhibiting factors to incorporate sustainable development into the New Zealand flexible packaging industry context. Building on a range of theoretical perspectives, the authors extend the current body of knowledge seeking to advance the sustainable development agenda in the New Zealand flexible packaging industry and offer recommended pathways fostering sustainable development in a distinctive manufacturing context.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

As a new type of spinning machine, the jet spinning machine absorbs the carding system of the rotating cup spinning series and the nozzle part of the jet spinning. This paper aims to intends to introduce the double carding structure currently studied by the rotating cup spinning into the jet spinning machine, and analyze the influence of the nozzle characteristic number on the flow field in the double carding structure to verify the advantages of the double carding structure.

The simulation is used to evaluate the performance of single/double split jet spinning and nozzle feature number, verify the technical advantages of double split jet spinning and evaluate the influence of nozzle feature number on flow field. The influence of the nozzle characteristic number on the flow pattern in the four models is compared. The advantages and disadvantages of a conventional single comb and a double comb with a bypass channel on the longer side of the transport channel as an additional air supply channel are also evaluated.

At present, the double comb technology of rotary cup spinning is being studied at home and abroad to improve the spinning quality and improve the difficult problem of mixed yarn with large difference in processing fiber properties. At present, the jet spinning machine combines the advantages of rotary cup spinning and jet spinning, absorbing the comb system of rotary cup spinning series and the nozzle part of jet spinning. Therefore, it is found that the introduction of the double-split structure into the wool jet spinning has research value to improve the spinning quality.

The purpose of this paper is to refer to the previous research on the double comb structure in rotary spinning, and to apply the double comb structure in the new jet spinning machine to improve the spinning quality. The simulation is used to evaluate the performance of single/double split jet spinning and nozzle feature number, verify the technical advantages of double split jet spinning and evaluate the influence of nozzle feature number on flow field.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.