Investment In Assets Research Articles

The role of cluster ecosystems and intellectual capital in achieving high-growth entrepreneurship: evidence from Germany

PurposeThis paper examines the role played by business cluster ecosystems and intellectual capital (IC) in achieving high-growth firm (HGF) status.Design/methodology/approachWe draw our insights from the knowledge-based perspective and economic geography as a theoretical lens, which combined offer a more unifying understanding of how business cluster ecosystems and IC foster high growth entrepreneurship.FindingsDrawing on a sample of 11,360 German incorporated firms across 80 clusters, we find that cluster ecosystems play a significant role in supporting firms to become HGFs. More specifically, being located in business clusters increases the likelihood of becoming HGFs by 2.2% to 4.49%. We also find that clusters with more productive firms in the ecosystems provide favorable conditions for member firms to achieve HGF status, while the impact of other cluster-specific conditions (high-tech cluster membership and multinational enterprise share in clusters) is less clear. Additional insights suggest that firm IC (investments in intangible assets) enables firms to achieve high growth status.Research limitations/implicationsThe findings of this paper hold theoretical and managerial relevance and shed more light on the impact of cluster-specific factors in the ecosystems and firm IC in achieving high growth entrepreneurship.Originality/valueThis paper is among the first of its kind to bring together three distinct literatures (HGFs, business clusters and IC) and utilize insights from each to derive a conceptual framework that links them in explaining high-growth entrepreneurship.

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

Migration experience and risky financial assets investments of county households: evidence from China

Enhancing the support for inclusive finance in county economies is crucial in achieving the strategic goal of building financial power. Drawing upon the theoretical lens of county-level inclusive financial accessibility, this study examines the effect of the migration experience (ME) of county socialites on their risky financial assets investment (FAI) and the underlying mechanisms. We utilize data sourced from the County Consumption Survey, a nationwide effort by the Department of Sociology of Tsinghua University and the 58 Tongzhen Research Group. Our findings reveal that the ME of county socialites significantly boosts their likelihood of engaging in financial markets. Furthermore, housing inequality factors, such as housing property rights and housing loans, play a moderating role in the impact of individual ME on their FAI. Additionally, the financial concept has a masking effect rather than a mediating effect on the path of the ME affecting FAI. Notably, the promotion effect of ME displays heterogeneity. Specifically, ME has a stronger positive effect on FAI among college-educated groups, members of the Communist Party of China (CPC), and urban hukou residents than on those who have not completed college education, non-CPC members and rural hukou households. In light of these findings, we propose policy recommendations to optimize the distribution of financial services, adjust the housing equality policy, and enhance inclusive financial literacy.

County-Level Spatiotemporal Dynamics and Driving Mechanisms of Carbon Emissions in the Pearl River Delta Urban Agglomeration, China

Encouraging cities to take the lead in achieving carbon peak and carbon neutrality holds significant global implications for addressing climate change. However, existing studies primarily focus on the urban scale, lacking more comprehensive county-level analyses, which hampers the effective implementation of differentiated carbon mitigation policies. Therefore, this study focused on the Pearl River Delta urban agglomeration in China, adopting nighttime light data and socio-economic spatial data to estimate carbon emissions at the county level. Furthermore, trend analysis, spatial autocorrelation analysis, and Geodetector were adopted to elucidate the spatiotemporal patterns and influencing factors of county-level carbon emissions. Carbon emissions were predominantly concentrated in the counties on the eastern bank of the Pearl River Estuary. Since 2010, there has been a deceleration in the growth rate of carbon emissions in the region around the Pearl River Estuary, with some counties exhibiting declining trends. Throughout the study period, construction land expansion consistently emerged as a predominant factor driving carbon emission growth. Additionally, foreign direct investment, urbanization, and fixed asset investment each significantly contributed to the increased carbon emissions during different development periods.

The Perception of Policy Uncertainty and the Labor Income Share of Firms: Empirical Research Based on Double Machine Learning

ABSTRACTBased on the double machine learning model, this study examines the impact of perception of policy uncertainty (PPU) on labor income share (LIS). We find that PPU negatively influences LIS. Mechanism test indicates that PPU not only results in a reduction in fixed asset investment, distorting human capital structure, but leads to a financing dilemma for firms, ultimately exerting a detrimental effect on LIS. Additionally, PPU primarily diminishes LIS of ordinary employees rather than executives. Furthermore, the inhibitory effect of PPU on LIS is significantly more pronounced in firms characterized by smaller union scales and those operating within monopolistic industries.

How bankruptcy system innovation affects firm investment behavior: A quasi-natural experiment based on the establishment of bankruptcy courts in China

This study investigates the effects of bankruptcy system innovation on firm investment behavior. Taking the establishment of bankruptcy courts in China as a quasi-natural experiment and using the difference-in-differences method, we show a significant positive relationship between the bankruptcy system and firm investment in financial assets. Improving creditor protection, increasing firms' financing constraints and costs, and increasing the bankruptcy reorganization rate are the main mechanisms through which the establishment of bankruptcy courts promotes firm investment in financial assets. Moreover, the effects of bankruptcy court establishment on firm investment in financial assets are more significant for non-state-owned firms, firms with CEOs who do not have a financial background, and firms in regions with better institutional environments. Finally, we find that the increased investment in financial assets by firms after the establishment of the bankruptcy court balances the efficiency of investment in financial assets at the same time. The findings of this study can provide a reference for optimizing the allocation of market resources and improving the financial rules of the legal system.

Measuring Rurality and Analyzing the Drivers of Rurality in Megacities—A Case Study of Shanghai, China

The Rurality Index is an important reference for the formulation of rural development strategies and policies, but the evaluation of the rurality of megacities based on the township scale is relatively limited. Based on the perspective of spatial governance, this study constructed the evaluation index system of Shanghai’s rurality and carried out the evaluation of Shanghai’s rurality at the township scale from 2005 to 2020. The article adopts the MGWR model to analyze the driving effects of five key driving factors (the proportion of foreign population, per capita industrial output value, public finance revenue, social fixed asset investment, and rail transit coverage), and adopts the Geo-Detector model to analyze the interactive driving effects of two factors. The results indicate that the rurality index of megacities and townships as a whole shows a weakening trend, and the above factors have a predominantly negative impact on rurality, with differences in the intensity of the impact in different periods. There is an obvious interactive additive effect between the factors. When formulating policies for township development, government departments need to take into account the functional positioning of the region and comprehensively adopt targeted policies on population, industry, transportation, finance and investment to regulate and guide the transformation or sustainable development of the countryside.

Identifying NFT consumer segments: a consumption value theory and luxury perspective

PurposeThe present research takes a qualitative approach to examine young adult consumers’ perceptions and intentions toward non-fungible tokens (NFTs). The goal of the study is to identify consumer sub-segments of young adults based on their perceptions of/intentions toward NFTs.Design/methodology/approachThis research utilized qualitative/thematic analysis.FindingsThe results revealed three sub-segments of young adults with different perceptions of NFTs. The largest group, Authenticators, perceive NFTs as luxurious digital possessions that are prestigious, have premium prices and are high quality. They are most likely to be early/late majority, but some are innovators/early adopters. The second-largest group, Pessimists, hold negative views about NFTs, seeing them as fads, silly and/or a waste of time and believing that investing in them is risky. These individuals are most likely to be laggards in terms of adoption. The smallest group, Futurists, hold forward-thinking views about NFTs. They are most likely to see themselves as innovators/early adopters, think of NFTs as the future of asset ownership, investment and digital life, and do not perceive them as overly risky.Originality/valueThe findings add to the scant literature on NFTs in marketing by documenting three potential sub-segments of young adult consumers for NFTs. NFT marketers should take care in effectively marketing NFTs’ value and addressing their risks to consumers as they relate to the identified consumer segments.

Current State of the Capital Investment Account in Enterprises and Directions for Its Improvement

The article examines the situation of capital investments in businesses today, pointing out problems with capital investment accounting and offering solutions by implementing global standards in the face of the expanding digital economy. The inefficiency of describing capital investment records for various asset kinds, which restricts openness and decision-making usefulness, is one of the major information gaps that has been found. The study's methodology includes a comparative analysis, economic analysis, and data from "Saturn Metalworking LLC" to examine capital investment methods. Results indicate that consistent accounting practices obfuscate precise information about investments in certain assets. One suggestion is to improve accounting procedures to make it easier to track spending in modernization, construction, and various equipment categories. By optimizing capital investment records, these changes hope to enhance stakeholder knowledge and strategic resource allocation in a digital economy.

Investment Allowance and Financial Performance of Dt-Saccos in Nairobi County, Kenya

Purpose: The main objective of the study was to determine the effect of investment allowance on financial performance of DT-SACCOS in Nairobi County, Kenya. Methodology: This study utilized explanatory research design to investigate the influence of tax policies, including investment allowances, accelerated depreciation, and capital gains tax exemption, on the financial health of Deposit Taking SACCOs in Nairobi County, Kenya. The study used advanced estimation techniques, such as correlation and panel data regression models to estimate the relationship. Results: The study established that investment allowance has a significant negative impact on the financial performance of deposit-taking savings and credit cooperative societies (DT-SACCOs) in Nairobi County. Conclusion: Investment allowances, despite their negative association with financial performance, offer a valuable opportunity for DT-SACCOS to reduce taxable income and optimize investment in growth-enhancing assets. However, this should be balanced with careful planning to avoid potential adverse effects on financial performance.

METODE MEAN-SEMIVARIANCE DALAM PEMBENTUKAN PORTOFOLIO REKSA DANA SAHAM TERBAIK BAROMETER BAREKSA

The most popular investment product today is mutual funds. One of the factors in selecting mutual funds is the low investment risk. This risk can be minimized again by combining several assets and then compiling them into a portfolio. The portfolio formation method used in this study is the Mean-Semivariance method and the Sharpe Index to calculate portfolio performance. The data used is the daily net asset value per unit of Mandiri Investa Atraktif Syariah, Rencana Cerdas, Manulife Saham SMC Plus and BNP Paribas Solaris for the period January 3 2022 to March 9 2023, Jakarta Composite Index (IHSG) data as a benchmark and BI-7 Day Reverse Repo Rate as a riskfree interest rate. The minimum risk of the portfolio will be achieved by compiling a portfolio of two mutual funds, namely Mandiri Investa Atraktif Syariah with a weight of 92,50% and the Smart Plan with a weight of 7,50% with an expected return rate of 0,00019 and a risk of 0,000000663. The Sharpe Index is 0.08971 indicating that the portfolio formed has good performance and can be used as a choice of investment assets by investors.

Managerial ability and firm growth: intellectual capital components

PurposeThis study analyses the way various components of intellectual capital (IC), namely, human capital (HC), structural capital (SC), relational capital (RC) and innovation capital (INNC), act as mediators in the relationship between managerial ability (MA) and a firm’s ability to achieve growth.Design/methodology/approachThis study employs data envelopment analysis to quantify the MA of 825 Taiwanese listed electronics companies from 2017 to 2022. The proxies of firm growth are return on asset growth, operating income growth and total asset growth. This study then utilises a three-step mediation analysis methodology to examine the relationships between MA, IC and firm growth.FindingsFindings indicate that HC, SC, RC and INNC mediate the link between MA and firm growth. This suggests that competent managers can capitalise on the potential benefits of these investments to achieve firm growth.Practical implicationsCompetent managers can utilise different IC investments to grow the financial performance and strength of their businesses. Managers should continually scan, secure opportunities and adjust their investments in knowledge assets in accordance with the dynamic capabilities view. That is, managers, in general, and operations managers, in particular, can implement guidelines that prioritise IC investments in the future to expedite firms’ development.Originality/valueThis study extends the existing frameworks that study investment variables as mediators between MA and firm outcomes. Most particularly, this study adopts four components of IC for measurement. Moreover, firm performance is measured using dynamic growth indicators rather than static measures.

Effects of economic growth target on the urban–rural income gap in China: An empirical study based on the urban bias theory

Urban–rural imbalance is a common phenomenon, and its prominent manifestation is the sustained expansion of the urban–rural income gap. For emerging countries, this gap encountered during the development process should be addressed by promoting development, which also puts forward high requirements for economic management. Inspired by political economy theory and the widening urban–rural income gap in China, this study constructs a theoretical framework of “purpose-behavior-performance-structure” based on the urban bias theory, and then quantitatively examines the effect of economic growth target on the urban–rural income gap based on panel data at the provincial level. In addition, we explore the mechanism by which economic growth targets affect the urban–rural income gap with the mediating effect model, and investigate the impact of marketization and spatial structure on the relationship between economic growth targets and urban–rural income gap with the moderating effect model. The results show that the economic growth target significantly contributes to the widening urban–rural income gap in the face of the political promotion incentives and economic growth target accountability system, and this effect exhibits substantial spatiotemporal heterogeneity. In addition, fiscal expenditure, fixed asset investment, and labor mismatch under urban bias are important mechanisms that lead to the widening urban–rural income gap, and the marketization level and spatial structure significantly affect this relationship. We put economic growth management, urban bias, and urban–rural income gap into the “purpose-behavior-performance-structure” theoretical framework, which provides a new explanatory perspective for understanding the urban–rural income gap in emerging economies, and new policy insights for rational economic growth management.

Determinants of Crypto Investment Decisions: Ra-tional Behavior or Irrational Behavior?

The current phenomenon is that crypto asset investment is considered high risk, yet the number of crypto asset investors is increasing. This research investigates the determinants of crypto investment decisions: driven by rational or irrational behavior, specifically testing the moderating role of social influence on the determinants of investment decisions. The research combines technological factors (crypto platforms) and psychological factors (herding behavior FOMO (Fear of Missing Out)) with external factors of social influence a moderating variable. This study uses quantitative research methods and primary data from respondents who are crypto asset investors domiciled in Indonesia. The sample consisted of 124 respondents consisting of 95 male respondents and 29 female respondents. Statistical analysis including analysis of the Outer Model, Inner Model and direct effect and Moderated Regression Analysis was carried out using SmartPLS 0.3 software. The results showed that crypto platforms, financial literacy, herding behavior, FoMO had an effect on investment decisions, and social influence was able to moderate the influence of crypto platforms, financial literacy, herding behavior, FoMO on investment decisions. Suggestions given for further research are: develop further research models that can represent the determinants of investment decisions in crypto by using other research variables in predicting their influence on investment decisions such as regret experience, attitude, risk tolerance, etc.

A comprehensive review of behavioral biases in financial decision-making: from classical finance to behavioral finance perspectives

This paper offers a detailed analysis of the evolution of financial decision-making theories, focusing on the shift from classical finance to behavioral finance. Classical finance theories, including the Efficient Market Hypothesis and Modern Portfolio Theory, assume that investors behave rationally and that the market is efficient. However, these theories have faced criticisms highlighting the importance of considering irrational behaviors in financial markets. Behavioral finance addresses this gap by integrating psychological insights into financial decision-making. This study systematically reviews the literature on behavioral biases that affect individual investors, identifying fundamental biases and their impact on investment decisions. The analysis emphasizes the role of cognitive limitations and psychological tendencies in shaping market dynamics, influencing asset pricing, investment strategies, and market returns. The research also notes a shift in focus from market-level outcomes to the behavior of individual investors, with an increase in publications. The paper concludes that understanding investors’ biases is crucial for developing effective risk management strategies and investment recommendations, ultimately leading to improved market performance. The findings underscore the growing importance of behavioral finance in explaining investor behavior and market anomalies, highlighting areas for future research in this evolving field.

Dynamic Risk Spillover in International Real Estate Investment Trusts: Implications for Asset Investors

Dynamic Risk Spillover in International Real Estate Investment Trusts: Implications for Asset Investors

Law, Commodification, and the Distribution of Resources

Abstract By exploring the historical and theoretical underpinnings of law as a source of distributional inequities and resource depletion, in tandem with its influence on investment in tangible and intangible assets in contemporary capitalism, this special issue paves the way for new understandings that might better promote shared community interests in sustainability and social equality.

Multi-criteria mathematical application using MatLab and C++ for inventories and marketing of acrylic fiber products

Today, companies at a global level compete in the field of technology and available resources to meet the needs and preferences of the market. That is why, at national and local levels, strategies are implemented that allow companies to grow optimally, incorporating new elements in their policies to improve their performance in the marketing of products. The daily challenges that companies face lead to the search for solutions, especially with regard to inventories, which represent a significant capital investment in assets that entail expenses for materials, personnel and storage. This is why practical solutions are required that achieve a balance between customer needs and product rotation. The main objective of this study is to solve this problem by implementing a mathematical model and a computer application that allows finding efficient solutions for order management of the most demanded products in the local and national market. This optimizes resources and achieves a balanced inventory that increases the level of marketing and sales. The computer application is a versatile and practical tool that allows analyzing various elements and speeding up the process of selecting the most suitable products for the market. In the case of the company "Lanas Elsy", the Vilfredo Pareto ABC classification technique is used, combined with a multi-criteria mathematical model and a computer application designed in C# and Matlab. These tools are essential for the development of the company and its inventory strategy at a global level

To What Extent Has the Real Estate Industry Affected China's Economic Growth?

This paper focuses on the impact of the real estate industry on China's economic growth. We discovered, through an examination of certain specialist literature and statistical data analysis, that the real estate sector has been a major factor in China's economic expansion. Particularly, real estate investment is a considerable portion of fixed asset investments and makes a noteworthy contribution to economic growth. However, every coin has two sides. The rapid development of real estate also comes with some problems, such as the risk of real estate bubble and high leverage. Therefore, in order to make the real estate better promote the development of the national economy, the government has decided to guide the orderly and stable development of the real estate industry through policy regulation. In this article, by reviewing the previous literature and analyzing some relevant data about real estate, I will explore the impact of real estate industry on China's economic growth. The research finds that the development of the real estate industry is good for economic growth, but at the same time, policymakers should also pay attention to controlling the development speed of the real estate, such as: real-time monitoring of the market and formulating relevant policies to avoid problems.

Reinforcement learning-based portfolio optimization with deterministic state transition

Portfolio optimization has attracted substantial interest within the artificial intelligence community due to its significant impact on financial decision-making, risk management, and market analysis. Reinforcement learning fits well with portfolio optimization because their goal is to maximize cumulative returns. In reinforcement learning, state transition probabilities are often unknown and must be estimated. However, in portfolio backtesting experiments, these probabilities are deterministic, making the conventional reinforcement learning approach to estimating state transitions suboptimal for portfolio optimization. Addressing this issue, this study decomposes the portfolio optimization into two core tasks: prediction and profit policy optimization and proposes a novel reinforcement learning framework that assumes deterministic state transition probabilities, comprised of three main modules: feature extraction, prediction, and profit strategy optimization. To model assets more effectively and comprehensively, we capture their temporal features, relational features, and market state. We introduce a patch-wise correlation method and attribute based gate to enhance feature extraction. In the profit policy module, we utilize a deterministic strategy, employing a recursive reinforcement learning method based on Monte Carlo sampling to train the policy network. This enables dynamic adjustments of asset investment weights, ensuring the maximization of cumulative returns. Extensive experiments conducted on cryptocurrency datasets demonstrate the superior performance of our approach, and achieving 36.6%-75.6% improvements in main measurements on cryptocurrency datasets.