Search results

This systematic literature review aims to identify the main areas of study related to co-creation and innovation in Higher Education Institutions (HEIs), as well as the main external and internal stakeholders with whom co-creation is made.

The empirical approach is based on 258 articles selected from the Web of Science (WoS), Clarivate Analytics and Scopus, Elsevier databases, with analysis of titles, abstracts and keywords following a research protocol. VOS viewer and CitNetExplorer software were used, with the twin aim of identifying publications with a higher number of citations and designing maps of reference word co-occurrence.

The analysis led to three clusters being identified: Cluster 1. Management and transfer of knowledge from HEIs to companies; Cluster 2. Co-creation and innovation in HEIs through cooperation between universities and companies; and Cluster 3. Universities’ third mission and their role in developing entrepreneurship education. The results of the literature clusters analysis led to proposing a conceptual model of analysis.

Despite only employing two databases and the content analysis criteria, the three found clusters are linked, recognising the interplay between co-creation and innovation in HEIs, knowledge transfer to enterprises and the influence on HEIs' third goal.

This systematic literature review highlights and gives a picture of the state-of-the-art in co-creation and innovation in HEIs, as well as presenting a model of co-creation and innovation in HEIs that can contribute to reinforcing the University-Industry-Community ties.

This study can lead to a better knowledge of the issue of co-creation and innovation at HEIs, as well as a deeper analysis of the sorts of relationships between HEIs and their stakeholders, as well as its impact on surrounding areas and influence.

The research highlights the interaction between HEIs and their stakeholders on a basis of value co-creation and innovation, providing mutual benefits for all involved, as well as greater development and recognition of HEIs and their surrounding regions’ image andreputation. A future research agenda is also presented on the topic of co-creation and innovation in HEIs.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

The work-from-home scheme (WFH) is increasingly being adopted in service firms. However, the blurred border between employees’ work and life can create work–life conflict (WLC) that negatively affects their well-being. Therefore, identifying factors that help employees overcome WLC and nurture their well-being is imperative. From a transformative service research (TSR) and personal psychology perspective, this study aims to explore the roles of service employee state of mindfulness and resilience in reducing WLC, alleviating its negative effects and ultimately nurturing their happiness.

A structural model was proposed. Data were collected from 339 WFH employees in various knowledge-based services such as professional services, information, education and training, financial consulting and marketing. Direct, indirect, mediating and moderating effects were estimated using the CB-SEM method.

Mindfulness is the overarching capability that helps reduce WLC and raise resilience. It nurtures WFH employee happiness not only directly but also via the mediation of resilience and WLC. Resilience, on the other hand, mediates the effect of mindfulness on happiness and moderates the negative impact of WLC on happiness.

Firms are recommended to organize mindfulness and resilience training programs, and encourage organizational- and job-related facilitators. WFH employees should actively participate in such programs and add them to their to-do-list practices.

To the best of the authors’ knowledge, this study is among the first empirical studies of employee mindfulness and resilience in the WFH context. It contributes to the TSR research stream and enriches the concepts of mindfulness and resilience by elucidating different mechanisms in which each of these personal qualities operates to help employees nurture happiness in this specific working condition.

The interest in sustainable human resource management has grown in the last decades. However, comprehensive, and systematic research concentrating on the evolution of this field, is still needed. The purpose of this study is to provide an overview and synthesis of the existing body of knowledge on human resource management (HRM) related to sustainability through a bibliometric study of articles published until 2022, identifying the most relevant research in this field. In the literature review, special attention is given to articles that link sustainable HRM to employees’ attitudes, identifying gaps and future research opportunities.

A bibliometric analysis and literature review was conducted over 105 documents obtained from the WoS database, using VOSviewer software program, from which 27 were selected for full-text reading. The applied database filters were: document type (article and early access); index (SSCI and SCI-expanded) and year (2019–2022).

The results show that: sustainable HRM literature is growing, especially after 2019; “Sustainability” is the journal with more publications; and England is the leading country. The network of co-occurrence of keywords analysis unveiled that performance, job satisfaction and behaviors are the most frequently studied topics in HRM.

For successful adoption of sustainable HRM practices, organizations should engage all staff comprehensively, focusing not only on consistent implementation but also on fostering a supportive organizational climate. This is vital for establishing a sustainable workplace where employees who strongly identify with the organization are less willing to leave it.

Through the Systematic Literature Review carried out on the articles published from 2019 to 2022, it was possible to identify opportunities for future research. These topics include employees' perceptions of the implementation of sustainable HRM practices in companies, as well as the impact of these practices on their attitudes and behaviors, taking into account the various HRM practices.

This paper argues that Bruno Latour’s work on translation provides an alternative to dominant anthropocentric, individualistic and managerial approaches in career studies by considering careers as precarious effects of networks instead of the implicit assumption of individual strategic career actors in extant career research paradigms.

The article first compares the three main current approaches to studying careers – structural functionalist, interpretivist and critical – illustrated by three exemplary empirical studies. Subsequently, three concepts from the sociology of translation that are relevant for the study of careers are introduced: career making as translating interests, careers as effects of networks and career action as dislocated and overtaken. Taken together, these three concepts allow us to conceive of careers as practices performed by human and nonhuman actors. Finally, an example from an ethnographic case study in the field of contemporary art illustrates how a Latourian approach can be used.

Latour’s work on translation provides conceptual and methodological tools to investigate career processes and practices in an era of unpredictability.

The paper introduces Bruno Latour’s work on translation to the study of careers.

Health-care marketing typically entails a coordinated set of outreach and communications designed to attract consumers (patients in the health-care context) who require services for a better health outcome and guide them throughout their health-care journey to achieve a higher quality of life. The purpose of this study is to understand the progress and trends in healthcare marketing strategy (HMS) literature between 2018 and 2022, with a special emphasis on the pre- and post-Covid-19 periods.

The authors examine 885 HMS-related documents from the WOS database between 2018 and 2022 that were extracted using a keyword-based search strategy. After that, the authors present the descriptive statistics related to the corpus. Finally, the authors use author co-citation analysis (ACA) and bibliographic coupling (BC) techniques to examine the corpus.

The authors present the descriptive statistics as research themes, emerging sub-research areas, leading journals, organisations, funding agencies and nations. Further, the bibliometric analysis reveals the existence of five thematic clusters: Cluster 1: macroeconomic and demographic determinants of healthcare service delivery; Cluster 2: strategies in healthcare marketing; Cluster 3: socioeconomics in healthcare service delivery; Cluster 4: data analytics and healthcare service delivery; Cluster 5: healthcare product and process innovations.

This study provides an in-depth analysis of the advancements made in HMS-related research between 2018 and 2022. In addition, this study describes the evolution of research in this field from before to after the Covid-19 pandemic. The findings of this study have both research and practical significance.

To the best of the authors’ knowledge, this is the first study of its kind to use bibliometric analysis to identify advancements and trends in HMS-related research and to examine the pattern before and after Covid-19 pandemic.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.

Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.