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The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

Most educational institutions worldwide have shifted to online teaching and learning approaches to mitigate risks imposed by the COVID-19 pandemic. This causes several issues, particularly in delivering the construction management (CM) courses which require site visits, interpreting technical drawings and developing 3D building models. This paper aims to identify the key strategies for online learning and teaching adopted during the COVID-19 pandemic and to investigate the implications for construction management education.

The research approach is twofold. First, the study presents a systematic literature review (SLR) through a synthesis of the existing literature to identify the key strategies and lessons learned about online education during the COVID-19 pandemic in tertiary programs. It also discusses their implications in the context of the construction management (CM) sector in particular. Secondly, the authors shared their hands-on experience as construction management course facilitators – using the autoethnography approach – during the COVID-19 crisis.

In addition to identifying the key strategies such as online course delivery and assessments, the paper critically discusses the barriers to online learning and teaching, including (1) the technological and infrastructure barriers; (2) required online teaching skills and competencies; (3) issues surrounding mental health and wellbeing; (4) lack of consistency in the online delivery of various courses in a given program (5) difficulties around students' engagement and (6) the course characteristics and requirements.

The study offers some implications and recommendations not only for educational institutions and staff but also for vendors of online course delivery software. To prepare educational institutions for future online course delivery, the paper proposes several strategies. These include developing a set of guidelines for online course delivery, incorporating online teaching training modules into the recruitment process for academic staff, applying agile and resilience teaching and learning methods, wellbeing and mental health support and continuously improving course features to adapt to the online environment.

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.

Corrosion is a major concern for many industries that use metals as structural or functional materials, and the use of corrosion inhibitors is a widely accepted strategy to protect metals from deterioration in corrosive environments. Moreover, the toxic nature, non-biodegradability and price of most conventional corrosion inhibitors have encouraged the application of greener and more sustainable options, with natural and synthetic drugs being major actors. Hence, this paper aims to stress the capability of natural and synthetic drugs as manageable and sustainable, environmentally friendly solutions to the problem of metal corrosion.

In this review, the recent developments in the use of natural and synthetic drugs as corrosion inhibitors are explored in detail to highlight the key advancements and drawbacks towards the advantageous utilization of drugs as corrosion inhibitors.

Corrosion is a critical issue in numerous modern applications, and conventional strategies of corrosion inhibition include the use of toxic and environmentally harmful chemicals. As greener alternatives, natural compounds like plant extracts, essential oils and biopolymers, as well as synthetic drugs, are highlighted in this review. In addition, the advantages and disadvantages of these compounds, as well as their effectiveness in preventing corrosion, are discussed in the review.

This survey stresses on the most recent abilities of natural and synthetic drugs as viable and sustainable, environmentally friendly solutions to the problem of metal corrosion, thus expanding the general knowledge of green corrosion inhibitors.