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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.

COVID-19 has immensely disrupted business dynamism, providing catalyst innovation opportunities and transposing society's perception of disruptive technology (DT). This research increases the understanding of the impact of the pandemic in influencing the way organizations perceive DT and whether any mitigating factors were considered when deciding to adopt new technology during the pandemic.

A qualitative approach was adopted in this research, consisting of 14 semi-structured interviews with eight senior managers and six employees, representing both the private and public sectors in New Zealand. All participants had in-depth knowledge of organizational DT adoption during the pandemic. Two separate sets of semi-structured interviews were used to enable comparison between senior managers' and employees' experiences of organizational adoption of DT post-emergence of COVID-19. Due to the nature of this research being conducted on organizational adoption of DT during the pandemic, time constraints and sample size were two of the key limitations of this research. Specifically, potential participants widely cited unavailability due to additional pressure from COVID-19. Given the limited research in this area, this study is explorative by nature and adds significant insights to the literature.

The findings suggest that COVID-19 has contributed towards an increased acceptance of, reliance on and adoption of DT across both organizational and social landscapes. The authors found that one of the reasons COVID-19 expedites the adoption of DT correlates with the notion of technology dependency, with organizations citing DT as a viable part of a business continuity plan (BCP) to counter the unpredictability of ongoing disruptive events associated with COVID-19 or any similar disruption which may be on the horizon. These findings are highly relevant as they suggest that the labor market in New Zealand is flexible so organizations and employees can adapt to DT and COVID-19.

This research adds much-needed insight into the emerging field of research that examines COVID-19's impact on the adoption of DT from both management and employee perspectives.

This chapter examines the connections between race and class divisions and examines how they shape racial inequities in the distribution of resources, power and privilege. Throughout history, racial identity has been a key factor in determining a person's position in modern capitalist societies. As such, issues of race and class have preoccupied sociologists and other scholars with diverse ideological orientations. This is highlighted in debates around the nexus of race and class in the production of racial structures, laws and institutions that legitimate and perpetuate the normalisation and centrality of whiteness. This chapter summarises some of the historical and ongoing debates, providing a synthesis of how race and class divisions continue to shape contemporary intergroup relations and social policy. It delves into racial capitalism and how race intersects with other social identities to determine socio-economic hierarchy in many western countries.

The aim of this Real Estate Insight is to comment upon commercial real estate research. Much of the current research on commercial real estate sits in academic silos, constrained by disciplinary boundaries and rejecting insights from other areas. This can lead to an impoverished understanding of the processes and practices that drive market behaviour.

This Real Estate Insight, through the lens of history, draws on insights from a century earlier and, in particular, from the work of Frank Ramsey; the paper argues that market behaviour is shaped by the role of key actors and persistent beliefs which need to be accounted for in our models of market practice.

The paper argues that current research paradigms need to accommodate agency explicitly into existing models and that real estate research will benefit immensely if researcher were more open in seeking ideas from outside the real estate field and to be more open to external ideas and concepts.

The paper suggests that property research needs to be more embracing of other academic disciplines to develop a full understanding of the numerous and various drivers within commercial real estate markets.

This is a review of how beliefs impact upon commercial real estate markets. As with many things, history can help researchers today get a broader and more appropriate perspective on market drivers and how they affect decision-making.

The purpose of this study is examined whether coproduction appears spontaneously in the literature on public sector innovation and governance, the citizens’ role in coproduction and the implication of citizens’ participation in the governance of innovation networks.

The review complied with preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. The search was performed in the Ebsco, Scopus and WOS databases. The authors analyzed 47 papers published from 2017 to 2022. Thematic and content analysis were adopted, supported by MAXQDA.

The papers recognize the importance of the citizens in public innovation. However, only 20% discuss coproduction, evidencing the predominance of governance concepts related to interorganizational collaborations – but not necessarily to citizen engagement. The authors also verified the existence of polysemy regarding the concept of governance associated with public innovation, predominating the term “collaborative governance.”

The small emphasis on “co-production” may result from the search strategy, which deliberately did not include it as a descriptor, considering the research purpose. One can consider this choice a limitation.

Considering collaborative governance as a governing arrangement where public agencies directly engage nonstate stakeholders in a collective decision-making process that is formal, consensus-oriented and deliberative (Ansell and Gash, 2007), the forum where the citizen is supposed to be engaged should be initiated by public agencies or institutions and formally organized, as suggested by Österberg and Qvist (2020) and Campomori and Casula (2022). These notions can be useful for public managers concerning their role and how the forums structure should be to promote collaboration and the presence of innovation assets needed to make the process fruitful (Crosby et al., 2017).

Despite the collaborative nature of public innovation, the need for adequate governance characteristics, and the importance of citizens in the innovative process, most studies generically address collaborative relationships, focusing on interorganizational collaboration, with little focus on specific actors such as citizens in the governance of public innovation. Thus, it is assumed that the literature that discusses public innovation and governance includes the discussion of coproduction. The originality and contribution of this study is to verify this assumption.

States have intervened with legislation to improve cashflow within construction project supply chains. The operation of the UK’s Housing Grants, Construction and Regeneration Act 1996 leads to payment obligations stated either as a contract administrator’s certificate (or equivalent) or an adjudicator’s decision. The purpose of the intervention would be defeated unless there are speedy ways of transforming these pieces of paper into real money. The combination of the legislation, contractual provisions and insolvency law has produced a minefield of complexity concerning enforcement of payment obligations stated in these documents. Unfortunately, the knowledge and understanding required to navigate these complexities have been sorely lacking. The purpose of this paper is to plug this gap.

Legal research methods and case study approaches, using relevant court decisions as data, were adopted.

The enforcement method advised by the court is the summary judgment procedure provided under the Civil Procedure Rules. An overdue payment obligation, either under the terms of a construction contract or an adjudicator’s decision, amounts to a debt that can be the subject of insolvency proceedings. Although the insolvency enforcement method has been successfully used on some occasions, using it purely as a debt collection weapon would be inappropriate and likely to be punished by the court.

The paper contributes to knowledge in two ways: (i) it maps out the factual situations in which these payment challenges arise in language accessible to the construction industry’s professions; and (ii) comparative analysis of payment enforcement methods to aid decision-making by parties to construction industry contracts. It is relevant to the other common-law jurisdictions in which similar statutory interventions have been made.

This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

Although it is assumed that migration and tourism directly affect each other, neither has received enough attention in the literature. Moreover, the relationship between them remains unclear. The UNWTO interprets said relationship in two ways: tourism-led migration (TLM) and migration-led tourism (MLT). The latter is crucial for the marketing of tourism. This study aims to clarify the migration-tourism relationship in ways the relevant literature has inadequately addressed and to evaluate the significance of MLT for Turkey's tourism marketing.

The study was carried out with a qualitative research design. Document scanning was used to collect data. A time series analysis was performed based on secondary data. Vector autoregressive models (VARs), which test the relationship between two or more variables, were preferred in the analysis selection. The empirical evidence depends on annual data of German tourists visiting Turkey and persons admitted to Germany from 2006 to 2019.

The findings of the study revealed a significant short-term relationship between those immigrating to Germany and tourists visiting Turkey.

The research shows that migration is a factor in the purchasing behavior of touristic products. In this respect, the practical conclusion of the study reveals that it may be beneficial for national tourism marketers in these countries to promote touristic products through citizens who have migrated abroad.

In the relevant literature, the relationship between tourism and migration (RTM) has been limitedly examined from an MLT perspective. In this respect, the subject has not been examined in detail in many respects (distribution by years, various sampling and data collection technique, etc.). The present research helps fill this literature gap by addressing the subject directly.

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.