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This study constructs an efficiency evaluation framework for assessing the human, structural and relational capital in the semiconductor industry of Taiwan. Furthermore, we analyze whether there are significant differences in efficiency across different levels concerning the industry supply chain (upstream, midstream and downstream), employee service tenure, capital scale and company establishment years.

This study focuses on Taiwanese semiconductor companies, utilizing data sourced from the Taiwan Economic Journal (TEJ) Database for the period spanning 2017 to 2021, encompassing a total of five years. Due to the nondisclosure of intangible asset values by all companies, an effort was made to ensure a comparable baseline by excluding companies with incomplete or missing data. Finally, empirical analysis was conducted on a sample of 64 companies using the dynamic network data envelopment analysis method.

(1) Overall efficiency demonstrates structural capital as the most prominent, followed by relational capital, while human capital shows relatively poorer efficiency. (2) To enhance the efficiency of intellectual capital, priority should be given to improving the efficiency of outputs related to intellectual property rights such as patents. (3) The midstream segment exhibits the best efficiency in both structural and relational capital. (4) Companies with longer employee service tenures exhibit superior efficiency in human capital in the long run. (5) Companies with extended establishment years and larger capital scales demonstrate superior efficiency in both human and structural capital.

Reflecting on past literature, scholars have primarily focused on the relationship between intellectual capital and firm efficiency, often emphasizing the overall efficiency of intellectual capital. However, within organizations, human capital, structural capital, and relational capital are interrelated. This study, for the first time, assesses the efficiency of these three components within an organization. The research addresses the challenges in analyzing the efficiency of intellectual capital and introduces a highly contemporary approach – dynamic network data envelopment analysis (DNDEA). Using the semiconductor industry in Taiwan as a case study, this paper conducts empirical analysis in a captivating and worthy industry. Therefore, the ideas presented in this paper are original.

Development has been a long-age phenomenon from the millennium to sustainability. This is because the new millennium ushered in the episode of development in the global economy from the role of inputs to the role of productivity and knowledge. Thus, understanding the forefront of initiatives to develop better policies for better lives and to find fact-based answers to social, economic, and environmental problems becomes unavoidable.

The study therefore assesses the impact of labor productivity and investment decisions on human development. A modified production theory was adopted for OECD economies. To address the problem of endogeneity and cross-sectional dependence, a two-step system generalized method of moments, Driscoll–Kraay estimator, and Panel Corrected Standard Error were used.

The findings reveal that the impact of labor productivity on human development differs significantly from the impact of investment decisions. The result shows that investment decisions will have a positive impact on human development when there is an insignificant capital fixed formation to boost the productivity of OECD economies. Further, the result shows that the organization governments through the provision of social security and essential services have a positive impact on the OECD human development.

This study has contributed significantly to assessing the drivers of human development within the purview of labor productivity, investment decisions and government expenditure in OECD countries.

This study aims to analyze the effects of cultural orientations (performance and sociality) on the trajectories of innovation inputs and their results in different countries worldwide between 2011 and 2021.

As a technique for data analysis, one of the spatial Bayesian models and Gray forecasting methods is used. This technique is adequate to achieve the objectives of the investigation because it allows analyzing how the variables move in time ranges and allow the generation of forecasts. This model also allows knowing if there are spills, which investing in a country can positively affect countries with geographical proximity. The databases used were the Global Innovation Index with data from 131 nations and the Globe Project with data from 157 countries between 2011 and 2021. The variables analyzed are institutions, human capital, research infrastructure, market sophistication and business sophistication. On the other hand, regarding moderations of cultural orientations, The Globe Project developed two factors: performance orientation (high degree of masculinity, avoidance of ambiguity, power distance and future orientation) and humane orientation (high-level of femininity, institutional and societal collectivism).

The results reveal that all inputs grow at different rates over time. In the case of institutions, it is the most difficult to generate changes over time. However, human capital, market sophistication and business sophistication are the ones that have grown the most over time, regardless of the country’s cultural orientation.

Among the main limitations is the set of data used because it only considers one approach to culture, especially the one considered by Hofstede. However, other approaches could help evaluate the results of this research. Considering the results obtained, the study attempts to provide a different view of the effects of cultural variables on companies’ innovation performance in different countries in the world. In the same way, evaluating these effects allows firms to consider variables associated with the country that will affect the strategies and performance of the firm.

The results achieved make it possible to strengthen the analysis of the countries’ strategies when it comes to innovation, especially in the permanent evaluation of the results that allow to encourage changes in the execution of innovative activities to maintain their performance over time.

The contributions allow us to understand the dynamics of innovation in the knowledge and creative outputs of countries over time.

The trajectory analysis used in the data analysis is perhaps one of the most robust techniques that makes a time series analysis. This allows identifying trajectories for the independent variables of the study and their influence on the innovation of the country.

Digital transformation is a confidence booster in intrapreneurship, but few have examined its impact on intrapreneurship. Further, quantitative analyses exploring the impact of Chinese enterprises' digital transformation on intrapreneurship at the micro-level are rare. Most enterprises do not have the dividend for digital transformation, and few enterprises have successfully achieved digital transformation through intrapreneurship, internal management re-engineering and technological innovation. This study investigates the effect of digital transformation on intrapreneurship in Chinese real economy enterprises.

The study develops and tests a theoretical model that digital transformation impacts intrapreneurship by promoting working capital turnover and furtherly influencing labor input. Panel data of 1,638 Chinese-listed companies between 2007 and 2020 were used to complete the empirical test.

Digital transformation impacted labor input, with an inverted-U shaped relationship between the two, and labor input significantly stimulated intrapreneurship. This effect promoted labor input's impact on working capital. Chinese real economy enterprises generally increase labor investment to promote intrapreneurship. Heterogeneity analysis revealed that enterprises' asset scale and ownership attributes uniformly affected labor input.

This study provided empirical evidence of the promotional effect of real economy enterprises' digital transformation on intrapreneurship. Further, it advanced the literature by examining this relationship at the micro-level. Moreover, the data sample was long-term and included most industries, thus providing representative results with practical implications.

To investigate the potential of raising the retirement age and reforming pension insurance in mitigating intra- and inter-generational income inequality, thereby offering empirical support for governmental policy formulation.

A dynamic general equilibrium model with intertemporal iteration is developed to comprehensively assess the impact of policies raising the retirement age on income inequality, taking into account delayed retirement, survival probability, and pension insurance. The theoretical hypotheses are validated through simulation using MATLAB.

Through theoretical analysis, it is determined that, given certain assumptions are satisfied, raising the retirement age can effectively mitigate intra-generational income inequality, inter-generational income inequality under both the pay-as-you-go and fund accumulation systems. Simulation results indicate that, under current parameter settings, raising the retirement age can reduce the Gini coefficient. Furthermore, this study reveals that regardless of the pay-as-you-go or fund accumulation system, pension insurance serves as a mechanism for income redistribution and alleviating income inequality.

It offers a theoretical foundation for the government's policy on delayed retirement and endowment insurance.

This study aims to investigate the impact of seaport efficiency on economic growth in Ghana over the period 2006–2020.

Comprehensive methodology, diverse data analysis techniques, including Augmented Dickey–Fuller tests, autoregressive distributed lag (ARDL) modeling and Granger Causality, were applied to explore the intricate relationship between Seaport Efficiency and Economic Growth.

The findings reveal a statistically significant and positive association between seaport efficiency and GDP, underscoring the crucial role of efficient seaport operations in actively stimulating economic growth. Beyond seaport efficiency, influential factors such as capital, human capital, knowledge spillover and productive capacities were identified, contributing to the dynamics of economic growth.

The Granger Causality Test solidifies seaport efficiency as a robust predictor of GDP fluctuations, emphasizing its significance in economic forecasting. Notably, this study contributes to the existing body of knowledge with its nuanced exploration of the intricate relationship between seaport efficiency and economic growth in the specific context of Ghana.

This study’s implications extend beyond academia, offering invaluable guidance for policymakers and planners. It serves as a comprehensive roadmap for informed decision-making, emphasizing the pivotal role of efficient seaports in charting a trajectory for enduring and resilient economic progress in the nation.

While the broader theme has been explored in existing literature, the uniqueness of this study lies in its specific application to the Ghanaian context. The choice of Ghana, a nation where maritime transport handles over 90% of trade, underscores the significance of understanding seaport efficiency in this regional and economic setting. The study’s originality is reinforced by incorporating diverse economic variables, aligning with recommendations for a comprehensive analysis of factors influencing port performance.

This paper explores the role of Internet of things (IoT) enabling factors in adopting digital supply chain.

Analytical hierarchy process (AHP) was used to rank performance measures and prioritise the enabling factors. Semi-structured interviews were conducted to validate and support key research findings from the AHP analysis.

The results show that level of customer demand is the most important indicator in adopting IoT while the level of product/process flexibility is the least important. System integration and IoT infrastructure are the top two enabling factors in increasing the level of process stability, supply chain connectivity, and product/process flexibility, respectively. Furthermore, the study suggests that the enabling factors for IoT adoption are directly connected with organisational resources/technological capabilities that support the resource-based view theory. This research identified interdependencies between IoT enabling factors and key performance measures for IoT adoption success in managing the digital supply chain.

Supply chain managers can use the empirical findings of this study to prioritise IoT adoption, based on the relative importance of enabling factors and performance measures. The research findings are focused on broader supply chain practices of large companies rather than a specific industry and SMEs. Hence, any industry-specific adoption factors and SMEs were not evident from this study.

This research study empirically established priorities of enabling factors for IoT adoption, along with inter-dependencies among enabling factors as a basis for developing guidelines for IoT adoption.

Women make a major contribution to the agricultural sector, especially in developing countries. Despite this, women still face many obstacles in carrying out their agricultural activities. These obstacles have a negative impact on their productivity and create a gender gap. This paper analyses the difference in agricultural productivity between male-headed and female-headed households in Burkina Faso.

Using data from the Permanent Agricultural Survey (EPA), we applied the Blinder-Oaxaca decomposition method to determine the size of the gender gap and identify the variables explaining this gap. In this study, we used the value of production per farm worker as a measure of productivity.

The results indicate a gender gap of 43.8 percentage points in favor of male-headed households. Around 131% of this difference is explained by differences in observable household characteristics. The factor that most explains this difference in productivity is the difference in the total area of land available to households.

This finding calls for women’s access to land to be considered in the design and implementation of agricultural development policies.

One of the main contributions of this article in relation to previous studies lies in the unit of analysis. Rather than focusing on individual producers, as in previous studies, we have instead considered the household as the unit of analysis, since in developing countries such as Burkina Faso, production decisions are taken at household level. It contributes to inform economic policy decisions by providing decision-makers with the factors on which they can act to bring about an increase in agricultural productivity by reducing the gap between male-headed households and female-headed households.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0923

This study employs firm-level data to evaluate how the knowledge economy impacts the financing constraints of businesses across 106 low- and middle-income nations, focusing on the influence of technological transformation on corporate financing choices.

The research centers on privately held, unlisted firms and examines the distinct effects of knowledge at both the within-country and between-country levels using a panel dataset. Rigorous sensitivity and endogeneity analyses are conducted to ensure the reliability of the findings.

The findings indicate that greater levels of the knowledge economy correlate with reduced financing constraints for firms. However, this effect varies depending on the location within a country and across different geographical regions. Firms situated in larger urban centers and more innovative regions reap the most significant benefits from the knowledge economy when seeking external funding. Conversely, firms in smaller cities, rural areas and regions characterized by structural and institutional inefficiencies in knowledge generation experience fewer advantages.

The impact of knowledge exhibits variability not only within and among countries but also between poor and affluent developing nations, as well as between larger and smaller countries. The knowledge effect on firms' access to external finance is influenced by factors such as financial openness and development, educational quality, technological absorption capabilities and agglomeration conditions within each country.

Microenterprises in emerging economies are known to operate in turbulent and resource-scarce environments. We test our hypothesis that a more comprehensive “Integrated Capital-Based Model” (ICBM) is needed when explaining the performance of microenterprises in such an environment. The model combines traditionally researched financial, human and social capital with more recently emphasized psychological and cognitive capital, providing greater explanatory power than models using only the traditional types of capital.

We use a pooled linear regression to analyze an existing survey of more than 900 independent business owners who were interviewed seven times between 2008 and 2012 in the Accra and Tema marketplaces in Ghana. We measure the performance of microenterprises using three dependent variables (revenue, profits, and productivity). We contrast the explanatory power of ICBM models against the more traditional models.

The ICBM has significantly higher levels of explanatory power over the traditional models in examining the performance of these microenterprises. These results highlight the importance of psychological and cognitive capital in emerging economies.

We advocate for a more comprehensive view of capital as shown in our ICBM. However, the data were gathered only in an urban setting, which limits the generalizability to rural parts of emerging economies.

These findings suggest the utility of government and appropriate agencies finding ways to enhance the level of psychological and cognitive capital of microenterprise owners.

This paper's originality stems from hypothesizing and empirically confirming the higher predictive efficacy of ICBM against more traditionally researched capital sources.