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This study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.

The study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.

Findings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.

This study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

Inland shipping has been extensively recognised as a sustainable, efficient and good alternative to rail and road modes of transportation. In recent years, various authorities and academic researchers have advocated shifting from road to other sustainable modes like inland waterway transport (IWT) or rail transport. Academic work on modernisation and technological innovations to enhance the effectiveness and efficiency of waterborne transportation is becoming apparent as a growing body of literature caused by the need to achieve a sustainable transport system. Thus, it became apparent to explore the research trends on IWT.

A systematic and structured literature review study was employed in this paper to identify the challenges and concepts in modernising inland waterways for freight transportation. The review analysed 94 articles published in 54 journals from six well-known databases between 2010 and 2022.

The key findings of this review are that despite various challenges confronting the sector, there have been successful cases of technological advancement in the industry. The main interest among scholars is improving technical and economic performance, digitalisation, and safety and environmental issues. The review revealed that most of the literature is fragmented despite growing interest from practitioners and academic scholars. Academic research to address the strategic objectives, including strengthening competitiveness (shipbuilding, hydrodynamics, incorporating artificial intelligence into the decision-making process, adopting blockchain technology to ensure transparency and security in the transactions, new technologies for fleets adaptation to climate change, more effective handling, maintenance and rehabilitation technologies), matching growth and changing trade patterns (intermodal solutions and new logistics approaches) are major causes of concerns.

By employing the approach of reviewing previously available literature on IWT review papers, this review complements the existing body of literature in the field of IWT by providing in a single paper a consolidation of recent state-of-the-art research on technological developments and challenges for inland waterways freight transport in the intermodal supply chain that can act as a single resource to keep researchers up to date with the most recent advancements in research in the domain of inland waterway freight transport. Additionally, this review identified gaps in the literature that may inspire new research themes in the field of IWT.

Given that existing retail brand research tends to treat each level of a retail brand as a separate concept, this paper aims to unveil the holistic nature of a multi-level retail brand, considering the distinctiveness of each level and the interrelationships between the images of different levels.

This study uses a scoping review approach that includes 478 retail brand articles. Subsequently, a thematic analysis method is applied.

The brand attributes that shape the distinct image of each retail brand level encompass diverse intrinsic and extrinsic attributes. Moreover, the holistic nature of a multi-level retail brand is formed by the interrelationships between the images of different levels, which are reflected in the presence of common extrinsic attributes and their interplay at attribute, benefit and attitude levels.

Theoretically, this review provides conceptual clarity by unveiling the multi-level yet holistic nature of a retail brand, helping researchers refine and extend existing theories in retail branding, while also providing new research opportunities in this field. Practically, the findings could guide retailers in implementing differentiated branding strategies at each level while achieving synergy across all levels.

Workforce insufficiencies can impair firms' competitiveness in the hospitality industry. The problem of finding suitably trained employees has been aggravated by changes in consumer preferences, and the development of advanced technologies has led to the ‘smartization’ of upscale hotels. The consequent updating of business models means that decisive indicators of worker competence and employability are different from those applied previously. Thus, the aim of this study is to develop an indicator framework for assessing workforce employability with consideration of competence with artificial intelligence (AI) applications.

The initial indicators for the framework are obtained based on an intensive review of the relevant literature and roundtable meetings with academics and practitioners. The Delphi method is used to collect the data, and a hybrid fuzzy approach, which combines the modified Z-number and modified trapezoidal fuzzy number set techniques, is applied to quantify the information originating from the experts’ judgments. The interquartile range approach is applied to optimize the validity of the indicators.

The assessment framework is applied to evaluate workforce employability at an upscale hotel from the perspective of hotel executives. The capability of the workforce for the adoption of advanced technologies, including familiarity with AI, are considered.

The contributions of this research involve the identification of an updated list of determinants for the evaluation of workforce employability for hotels in today’s world, highlighting the value of AI applications to help ameliorate labor shortage problems. The results should benefit practitioners, allowing them to improve the efficiency of their operations, services and management practices, leading to sustainability and competitiveness in the upscale hotel industry.

This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

This paper aims to illuminate the nuanced dynamics of green supply chain management (GSCM), specifically focusing on the intersections of supplier relationships, supplier governance and organizational agility. Recognizing a gap in the understanding of how these elements confluence to promote green purchasing, the paper uses a quantitative study on data collected from the Australian food industry. Advanced analysis techniques provide empirical evidence underscoring the pivotal roles these elements play, expanding on current GSCM literature within a resource-based view.

This study, based on a questionnaire sent to Australian food professionals, used higher-order reflective constructs to assess supplier relationships and governance. Data was analyzed using partial least squares structural equation modeling and Hayes PROCESS, considering factors like firm revenue and manager experience. Both the reliability of measures and mediation hypotheses were stringently validated using established guidelines.

The comprehensive study validated supplier governance's key influence on green purchasing and supplier relationships. Notably, organizational agility emerged as a crucial mediator, underscoring the interplay of these constructs. Concurrently, the reflective measurement model exhibited robust validity and reliability. Interestingly, demographic factors such as company size, revenue and managerial experience showed no discernible impact on green purchasing practices.

In the Australian food sector, supplier governance and relationships are pivotal for advancing green purchasing. This study emphasizes the value of organizational agility in amplifying these practices. Managers, when aligning with supplier relationships enhanced by communication and mutual aid, can foster robust green initiatives. Embracing these insights and the critical importance of supplier governance, managers can drive more sustainable, informed supply chain decisions in the industry.

In pursuit of understanding the relationship between supplier governance, supplier relationships and green purchasing, this research uniquely situates itself within the resource-based view (RBV) to reveal critical theoretical and practical implications. By focusing on the Australian food industry, the study spotlights the often-overlooked mediating role of organizational agility in linking supplier relationships with green purchasing efforts. In doing so, this research not only strengthens the argument for fortified supplier relationships – as a catalyst for enhancing agility and thereby green practices – but also re-contextualizes the RBV in a fresh light. This new perspective provides managers with an enriched model, emphasizing the imperative of solid supplier governance for sustainable, agile and green supply chain operations in the food domain.

This paper aims to investigate the multifaced aspects and consequences of the EU Carbon Border Adjustment Mechanism (CBAM) from an Australia-China Relationship perspective.

This paper leverages the SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis to examine both the internal and external factors that affect Australia and China in the context of the CBAM. In addition, we employ the PEST (Political, Economic, Social and Technological) framework to identify effective strategies for Australia-China cooperation following the implementation of the CBAM.

Our analysis reveals numerous mutual interests and opportunities for bilateral collaboration, despite challenges and threats, positioning the CBAM as a potentially significant catalyst for joint initiatives.

This paper proposes 10 potential areas for Australia and China cooperation from the political economic social and technological PEST dimensions.

This paper makes a pioneering attempt to explore potential strategies, both individually, and together, that Australia and China can adopt to manage the impact and consequence of CBAM.

The rise of communication software has changed our work style. The objectives of this study are: (1) to explore the effect of supervisors making after-hours work requests using communication software (SWRUCS) on employees’ job stress, quality of life and (2) to examine the moderating effect of personality traits and the cross-level contextual effect of social support.

A questionnaire survey was conducted to obtain information from 357 employees.

The results suggested that SWRUCS exacerbated job stress, which negatively impacted on quality of life and well-being. Moreover, different personality traits can either increase or decrease the positive or negative effect of SWRUCS on job stress. This study also revealed that social support can reduce employees’ job stress in a cross-level fashion. Furthermore, social support, especially organizational and supervisory support, can decrease the negative effect of job stress on employees’ quality of life and well-being.

Theoretically, this study has broadened the research scope of the organizational application of communication software, and practically, this study has demonstrated the reason why organizations should provide social support and select employees with suitable personality traits.