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The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

The rapid growth of digitalization is being used for the betterment of the banking and financial services sector and many other industries. Digital banking (DB) is transforming traditional banking activities into a digital environment. The benefits and conveniences that DB bring to consumers and financial institutions (FIs) have led FIs to adopt various DB innovations. However, to determine whether the demand for DB is at a healthy level, it is necessary to evaluate how DB innovations are accepted among consumers. This chapter is a “viewpoint” of the author that reviews the background of DB in Sri Lanka (SL) and evaluates the success of its diffusion.

The status of the DB diffusion in SL is discussed under DB ecosystem, and DB customer adoption. The DB ecosystem is discussed through the topics of the country’s digital infrastructure (DI), technological know-how within the banks, technology adoption of the market vendors, and consumer’s digital literacy. Then, the consumer use of the DB services is evaluated using the transactions that happened through DB systems against paper-based payments. Statistics presented by Central Bank of Sri Lanka (CBSL) are used as secondary data for the study.

According to the findings of this report, consumer DB adaption is still in its infancy compared to the development of the country’s DB ecosystem. Considering the causes that drives consumer innovation decisions, this chapter highlights the need for industry practitioners to revisit their DB marketing strategies based on consumers’ culture and innovativeness. To that end, further studies are necessary on how individuals’ culture influences DB adoption.

The purpose of this study is to evaluate the effect of both positive and negative corporate cultures on employee performance in Saudi Arabia, in the presence of performance reviews and factors leading to positive work culture, in an environment that underwent serious modification with COVID-19. The changing work methods (online, remote, etc.) have left their mark necessitating revisiting the needs and capabilities of employees in the work environment.

This quantitative study uses primary data from small and medium-sized enterprises (SMEs), non-profit organizations, and transnational organizations, in their transient role and influence on organizational culture change. The data set includes 311 usable responses from 50 randomly selected organizations and is analysed using structural equation modelling to test the proposed model.

A healthy corporate culture serves as the basis for increased employee performance in the workplace. The three independent variables, availability of negative culture, availability of positive culture and employee perceived performance, have a positive impact on the dependent variable employee perceived effectiveness of performance reviews; however, factors leading to the development of a positive organizational has a negative influence.

This study faced a limitation with the potential similarity of responses due to the large number of same-background respondents (engineers). However, the results are indicative of a trend. Moreover, the responses did not allow for cross comparison between responding organizational types (SMEs, non-governmental organizations and multinational corporations) as was planned.

Managers should motivate their respective employees, through ensuring the diffusion and sustainability of the right culture work environment. This should allow their teams to complete tasks with little or no supervision. Moreover, as the Saudi economy is gearing up for global competitiveness, this performance culture becomes a key for the success of the strategic plans, thus the high importance of the positive culture at work today.

Understanding the importance of positive and negative culture at the managerial level would affect the relationship with employees and improve work environment and job satisfaction.

This study pinpoints the need to revisit a dimming topic, proving that with the end of the COVID-19 pandemic, managers need to go back to square one. The introduction of the many novel work systems, online, remote work, etc. have changed the work setting and environment. This is requiring a new look at the employees’ perceptions on factors influencing corporate culture and performance.

Referral marketing can be identified as the commercial form used to encourage word-of-mouth (WOM) communication. It has become popular in recent times, supporting organisations to attract new customers towards making strides in how customers are pursued to purchase certain types of products/industries. However, some factors impact the success of referral marketing programmes. This study focuses on analysing the impact of such factors as brand, rewards and celebrity endorsement on user engagement in social media referral marketing programmes.

Further, this study discusses the moderating impact of social ties on this relationship mainly focusing on the cosmetic industry. The data were collected from respondents with exposure to referral marketing programmes through the social media platforms: Facebook, LinkedIn, WhatsApp and Instagram. The structural equation modelling (PLS-SEM) was used to analyse the data collected.

The results of the study revealed that brand, reward and celebrity endorsement significantly impact the participation willingness of customers in social media referral marketing programmemes. Moreover, it showed that the social tie moderates only the brand impact on the participation willingness of customers, whereas it does not moderate the impact of rewards and celebrity endorsement on the participation willingness of customers. In doing so, the study looks extensively into the elements that drive or shape customer behaviour within this specific market niche by investigating the effect of brand, incentives and endorsements by celebrities on customer engagement.

Accordingly, this study sheds light on the complex relationship among brands, rewards and celebrity endorsements, while also considering social ties within the context of social media referral marketing initiatives. It also delivers useful information for academics as well as practitioners. Limited studies have been conducted in this field, and therefore, this study adds some knowledge, also highlighting the moderation effect of social ties.

Purpose: Tax fraudulence is not an aberration, but it is a deliberate attempt to get rid of the tax burden. The government took enormous measures to curtail tax fraud, which seems dispensable. Taxation is the largest area that needs to be explored as individuals make discrete stings while filing taxes. Since compliance-focussed systems for tax collection are missing, this department is facing difficulties in providing quality data. This chapter will cover blockchain operations in the tax system to streamline the entire process and highlight the challenges.

Need of the Study: As the growth of technology is in the boom stage, research should be carried out to create more awareness regarding its usage and its possible threats. This study will spark more light on taxation by taking blockchain as the torch to improvise the vision.

Design/methodology/approach: The researcher did a comprehensive analysis of the Indian Tax Department and determined whether simplifying taxation could be possible through blockchain. The study gathered concrete facts about the various challenges faced while implementing this system.

Finding: Blockchain technology is rapidly making a roadmap in the taxation system, and there is tremendous potential to create a future vision with blockchain.

Practical Implications: This study will accentuate the function of blockchain technology that is becoming more prominent in the global technology sphere. This study will aid scholars in elaborating on the role of blockchain technology.

The integration of ESD is a complex problem. It calls for an innovative, student-centred curriculum, as well as professional learning and agency, by which university teachers feel empowered to change their practice and direct their peers and institutions towards ESD. This study aims to explore what university teachers consider to be the most important attitudes in supporting their agency to deliver Education for Sustainable Development (ESD) via a Problem Based Learning (PBL) programme.

This study presents a theoretical framework for professional agency comprising three domains: intrapersonal, action and environmental. A Q methodology is adopted to explore university teachers’ perceptions of the most important environmental factors in supporting their ability to deliver ESD via a problem-based learning (PBL) programme. Twenty-eight participants from six Southeast Asian universities took part in a PBL-based professional development programme designed to improve teachers’ ESD- and PBL-based skills and competencies.

The results indicate that the participants were confident in their ability to implement PBL and saw PBL as an approach suitable for addressing current educational, professional and societal challenges. This study offers a series of recommendations to help university teachers develop their ESD and PBL practices.

Although the literature on human agency is extensive, research surrounding teachers’ professional agency in the context of ESD and PBL in higher education is lacking. The present study addresses this gap by capturing individual teachers’ beliefs, perceptions and views and by using Q methodology to examine the subjectivity of study participants.

The effects of failure mode and strain conditions of CFRP, concrete and stirrups on the shear capacity of reinforced beams bonded by geopolymer and epoxy are studied. In addition, a prediction model of the ultimate bearing capacity of CFRP-shear-strengthened beams is proposed, which considers adhesive performance parameters adhesive performance parameter ßE and FRP width parameter ßw.

This paper presents an experimental study on ultimate bearing capacity of CFRP-shear-strengthened pre-cracked beams with geopolymer and epoxy resin, which considers parameters such as impregnated adhesives types and CFRP-strengthened scheme.

The failure modes of CFRP-strengthened beams bonded by geopolymer are the combination of the CFRP-concrete interface substrate failure and fracture failure of CFRP, and that of epoxy is the local substrate failures with small area. The ultimate load of CFRP-strengthened beams is directly affected by the failure modes. The ultimate bearing capacity of CFRP-strengthened beams with geopolymer is 91.4% of that of epoxy resin. Compared with ultimate bearing capacity of CFRP-strengthened beams with U-shaped, that of complete-wrapping increases by 2.5%. Moreover, the stirrup peak strain is reduced by more than 30% in CFRP-strengthened beams bonded with geopolymer and epoxy resin in comparison with the unstrengthened beam. The existing prediction model cannot accurately predict the CFRP shear capacity contribution of strengthened beams with different CFRP-strengthened schemes and adhesive properties. The estimated results are much lower than the test data, and the deviation is much larger than 20%.

Geopolymer alternative to epoxy as an adhesive is feasible and effective for CFRP reinforcement. Furthermore, the accuracy is improved by introducing parameters about adhesive properties based on the existing prediction model. The estimated results are in excellent agreement with the test data, and the deviation is controlled within −12.80%, and the model is suitable for predicting the shear capacity of FRP-strengthened beams with ßf = 90° in shear capacity database.

Prioritizing the shift from a traditional economy towards complex integrated economies has been the top priority among policymakers to achieve sustainable development goals (SDGs). Countries involved in economic integration must safeguard their labor markets. The Developing-8 (D-8) is an alliance of economic cooperation including Bangladesh, Egypt, Indonesia, Iran, Malaysia, Nigeria, Pakistan and Turkey, all of which are among the world’s largest labor-abundant countries but have insufficient attention toward labor market policies, especially in gender roles. This issue motivated this study, which aims to investigate the impact of economic complexity on trade through with the interaction of gender equality.

The annual data for the panel of D-8 countries from 1990 to 2020 were collected. The Driscoll and Kraay (D-K) regression was employed for empirical investigation after observing the presence of autocorrelation, heteroscedasticity and cross-sectional dependency (CSD) across the sample.

Findings show that the economic complexity index (ECI) and gender equality (GE) have a significant impact on trade openness (TO). Moreover, the interaction of GE and ECI strengthens the relationship between ECI and TO. Therefore, both factors worked together to enhance the trading system by supplying the nation with highly sophisticated and complex products.

Policymakers in D-8 countries should enable equal access to resources, investment and decision-making for both men and women. This leads toward stubble, innovative and complex products that enhance trade and goodwill in the international market.

This study incorporated GE as an interaction term in economic complexity and TO in D-8 countries for the first time, to the best of the authors' knowledge.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0908

In the era of digitalization, digital technology has transformed businesses and created enormous opportunities for organizations worldwide. Unsurprisingly, research on digital transformation has garnered significant interest among academics in recent decades. However, this study aims to recognize the key and holistic antecedents influencing digital transformation in manufacturing firms. This study also investigates the indirect relationships of antecedents with firm performance.

The hypothesis was investigated using the partial least squares structural equation modeling (PLS-SEM) approach. The data was collected from 279 employees through a self-administered survey of manufacturing firms.

The results described a significant and positive impact of competitive pressure, leadership role, organization culture, organization mindfulness, government regulation, and IT readiness on digital transformation and firm performance. Furthermore, digital transformation partially mediates the relationship between antecedents and firm performance.

The study finds a holistic perspective of the critical antecedents of digital transformation using the mediation role of digital transformation and moderating effects of firm agility. Additionally, all antecedents have a significant association with Firm Performance.

This research aims to investigate the impact of artificial intelligence (AI) adoption on the innovation dynamics of Chinese manufacturing enterprises, with a specific focus on the intricate interplay with the labor structure.

Leveraging panel data of listed companies from 2010 to 2022, this study employs the two-way fixed effects (TWFE) model to examine the influence of AI adoption on Chinese manufacturing companies' innovativeness. Firm-level AI adoption is measured by constructing a three-dimensional attention, application and absorption index.

The results indicate that (1) AI adoption has a positive impact on both internal innovation capability and external innovation interaction, (2) AI adoption has dual effects on the education and skill structure of labor in manufacturing enterprises and (3) enterprises with a highly educated and skilled workforce exhibit a stronger influence of AI adoption on innovativeness.

This research contributes to the academic and practical discourse by unveiling the underlying mechanisms of AI affecting innovation and introducing a new measurement of the AI adoption index. The findings emphasize the need for a highly educated and skilled workforce to navigate the complexities of AI-driven innovation, offering valuable theoretical and practical implications for policymakers and enterprises.