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The purpose of this paper is to examine a recent comprehensive corporate real estate (CRE) alignment model which was derived from previous CRE alignment models. This study proposes several modifications and additions based on business and decision-making literature to increase the framework’s multidisciplinary strength and extend its implementation phase.

Literature from various fields is reviewed and “lessons” incorporated into the framework. The business literature review began with corporate strategy theories cited in CRE alignment theory and extended to critiques of those and more recent theories. Likewise, decision-making and implementation both began with material cited in CRE literature and “rippled” out to encompass pertinent material.

The model used provides a robust framework, and this study has identified several areas that would appear to improve that model from a theoretical and practical perspective. Areas of further research are identified that appear to offer opportunities to further develop the framework.

Historically, there has been a tendency for new CRE alignment models to be created rather than existing ones being developed further. Here, a framework derived from a meta-study of CRE alignment models is reviewed, and improvements are proposed to further develop CRE alignment theory and its application in practice through the addition of viewpoints from the business field and more focus on the implementation phase of the model.

This study aims to examine the impact of lending liquidity on house prices especially during black swan events such as the Global Financial Crisis of 2007–08 and COVID-19. Homeownership is an important goal for many, and house prices are a significant driver of household wealth and the wider economy. This study argues that excessive liquidity from central banks may be driving house price increases, despite negative changes to fundamental drivers. This study contributes to the literature by examining lending liquidity as a driver of house prices and evaluating the efficacy of fiscal policies aimed at boosting liquidity during black swan events.

This study aims to examine the impact of quantitative easing on Australian house prices during back swan events using data from 2004 to 2021. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation's Central Bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration among some of the I(1) variables, the auto-regressive distributed lag model was selected given its flexibility and relative lack of assumptions.

The Australian housing market continued to perform well during the COVID-19 pandemic, with the house price index reaching an unprecedented high towards the end of 2021. Research using data from 2004 to 2021 found a consistent positive relationship between house prices and housing finance, as well as population growth and the value of work commenced on residential properties. Other traditional drivers such as the unemployment rate, economic activity, stock prices and income levels were found to be less significant. This study suggests that quantitative easing implemented during the pandemic played a significant role in the housing market's performance.

Given the severity of COVID-19, policymakers have responded with fiscal and monetary measures that are unprecedented in scale and scope. The full implications of these responses are yet to be completely understood. In Australia, the policy interest rate was reduced to a historic low of 0.1%. In the following periods house prices appreciated by over 20%. The efficacy of quantitative easing and associated fiscal policies aimed at boosting liquidity to mitigate the impact of black swan events such as the pandemic has yet to be tested empirically. This study aims to address that paucity in literature by providing such evidence.

This study aims to enrich our understanding of the characteristics of non-urban coworking spaces (CSs) that focus on corporate users, as well as the benefits that companies expect to gain from incorporating those CSs into their corporate real estate (CRE) portfolios.

This study leverages a series of in-depth interviews with owners and managers of CSs in non-urban locales that focus on serving corporate clients.

The research reveals various CS characteristics and forms within non-urban areas, focusing on corporate clients. It suggests that implementing a CS in corporate premises is perceived to enhance CRE use-value strategies with a focus on the employee's well-being, innovation and the attraction of talents. Moreover, exchange-value strategies with a focus on portfolio flexibility may benefit from the implementation of a CS. However, strategies related to life-cycle cost optimization or gains are not perceived to be supported. Social events for the surrounding neighborhood and the choice of location emerge as critical success factors for non-urban CSs. Besides infrastructure and connectivity, non-urban corporate-centric CSs built their location decisions rather on a personal connection to the location and place of residence of potential users than on lower rental prices.

This research pioneers in providing a comprehensive understanding of non-urban CSs, particularly in the context of their perceived implications for corporate real estate management. The nuanced perspectives it offers are invaluable for stakeholders looking to leverage CSs as part of their corporate strategies.

Organisational strategy becomes reality by connecting organisation’s resources and capabilities in daily operations, and physical workspace is one of the environments in which this takes place. This study aims to explore to what extent factors required for successful strategy implementation are considered when designing, using and managing workspaces of knowledge-intensive organisations.

For the study, managers in 25 large and medium-sized knowledge-intensive organisations were interviewed. The semi-structured interviews focused on organisation’s strategy, strategy implementation practices and workspace design and management. To form a comprehensive framework of strategy implementation success factors for the study, the factors of 11 frameworks were analysed, grouped and renamed.

Current workspace design, usage and management mainly support human-related strategy implementation factors. However, both organisation- and human-related factors are needed for the strategy implementation to be successful. Therefore, the organisations studied may have unused potential in their workspaces to ensure strategy-aligned operations and behaviour.

Due to the potential imbalance between organisation- and human-related strategy implementation factors, a more holistic, organisational-level approach to workspace design, usage and management is recommended to ensure the success of strategy implementation.

Workspaces have extensively been studied from individual strategy implementation factors’ as well as employees’ perspectives. Prior to this work, there are only few studies exploring workspace in the holistic, strategy implementation context.

This chapter tells the story of how the concept of Pareto efficiency was shipped from Lausanne to the modern US theory of competitive general equilibrium, focusing on the specific role of Maurice Allais. It identifies similarities in both epistemological approach and theoretical achievements realized first by Pareto, then by Allais, and finally by Debreu and Arrow and Hahn. It also shows that these similarities are not casual, since historical circumstances account for the influence of Pareto on Allais and later of Allais on Arrow and Debreu.

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

In the new development stage of comprehensively building a socialist modern state, it is imperative to adhere to the guidance of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, comprehensively summarize China's practical experiences in economic development, strengthen research on capital issues, construct theories of socialist political economy with Chinese characteristics regarding capital and provide scientific theoretical guidance for further promoting the positive role of various types of capital while preventing and overcoming their negative effects, which is a major theoretical issue and a glorious task for the theoretical and economic circles in China.

From the perspective of Marx's theory on capital and historical development, modern capital represents the organizational mode of socialized mass production and market economy. It serves as both the economic foundation of bourgeois society and a tool for socialist economic development.

The market economy represents an inevitable historical stage and form of socialist economic development, necessitating the adoption of capital as an organizational form within socialist economies.

The utilization of capital to advance a socialist economy is a remarkable achievement by the CPC and Chinese people, representing a significant innovation in both theory and practice. The role of capital is inherently dual under any social condition. In the context of a socialist system, capital can play a positive role effectively, and its behavior can be guided and regulated correctly to curb its negative or even destructive impact.

The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”. Big data platforms are shaping the processes of production, labour, the price of products and market conditions. “Digital platforms” and “big data” have become an integral part of the processes of production, distribution and exchange relations. These twin pillars are central to the capitalist accumulation processes. The article argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”.

As a conceptual paper, this paper follows critical methodological lineages and traditions based on non-linear historical narratives around the conceptualisation, construction and transition of the “Marxist theory of capital accumulation” in the age of platform economy. This paper follows a discourse analysis (Fairclough, 2003) to locate the way in which an artificial intelligence (AI)-led platform economy helps identify and conceptualise new forms of capitalist accumulation. It engages with Jørgensen and Phillips' (2002) contextual and empirical discursive traditions to undertake a qualitative comparative analysis by exploring a broad range of complex factors with case studies and examples from leading firms within the platform economy. Finally, it adopts two steps of “Theory Synthesis and Theory Adaptation” as outlined by Jaakkola (2020) to synthesise, adopt and expand the Marxist theory of capital accumulation under platform capitalism.

This article identifies new trends and forms of data driven capitalist accumulation processes within the platform capitalism. The findings suggest that an AI led platform economy creates new forms of capitalist accumulation. The article helps to develop theoretical understanding and conceptual frameworks to understand and explain these new forms of capital accumulation.

This study builds upon the limited theorisation on the AI and new capitalist accumulation processes. This article identifies new trends and forms of data driven capitalist accumulation processes within platform capitalism. The article helps to understand digital and platform capitalisms in the lens of digital labour and expands the theory of capitalist accumulation and its new forms in the age of datafication. While critiquing the Marxist theory of capitalist accumulation, the article offers alternative approaches for the future.

The purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.

This study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.

Deploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.

This study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.