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This paper aims to depart from the premise that human capital investments and human capital outcomes are often tacit – an aspect, which is often neglected in the current literature on entrepreneurial human capital. The idea of this conceptual paper is to shed light on the social process of how human capital investments and human capital outcomes can be valued and made visible through the validation of prior learning. Thus, this study conceptualises the validation of prior learning as a post hoc, the reflective process through which an aspiring entrepreneur is guided.

This paper is conceptual and introduces a process model.

Findings indicate that the process of the validation of prior learning is well-suitable to inform aspiring entrepreneurs of their investments into human capital and their human capital outcomes. The process results in a (partial) certified qualification that provides entrepreneurial legitimacy.

Thus far, the model is conceptual and should be validated via interviews and further empirical studies in the field.

Literature in the field of entrepreneurial human capital suggests that human capital outcomes are more important for success than inputs. Furthermore, context-specific knowledge, skills and abilities are more important than generalised outcomes. These findings have implications for the design of validation procedures.

Human capital has only been recently conceptualised as consisting of human capital investments and outcomes of human capital investment. However, thus far the literature falls short in acknowledging the tacit nature of human capital investments and human capital outcomes. This paper contributes a structured process of how human capital investments and human capital outcomes are linked and assessed. In so doing, this study extends a recent model of human capital investments and outputs (Marvel et al., 2016, p. 616).

This historical example of the creation of the arms industry in the Connecticut River Valley in the 1800s provides new insights into the value of government venture capital (GVC) and government demand in creating a new industry. Since current theoretical explanations of the best uses of governmental venture capital are still under development, there is considerable need for further theory development to explain and predict the creation of an industry and especially those industries where failures in private capital supply necessitates governmental involvement in new firm creation. The purpose of this paper is to provide an in depth historical review of how the arms industry evolved spurred by GVC and government created demand.

This study uses abductive inference as the best way to build and test emerging theories and advancing theoretical explanations of the best uses of GVC and governmental demand to achieve socially required outcomes.

By observing this specific historical example in detail, the authors add to the understanding of value creation caused by governmental venture capital funding of existing theory. A major contribution of this paper is to advance theory based on detailed observation.

The relatively limited research literature and theory development on governmental venture capital funding and the critical success factors in startups are enriched by this abductive investigation of the creation of the historically important arms industry and its spillover into creating the specialized machine industry.

Intrapreneurial ability (IA) of employees strengthens an organization's internal as well as external growth. Employees' IA makes innovation a continuous practice and augments organization's intellectual capital (IC). This intellectual capital-based intrapreneurial ability (ICIA) helps professionals to effectively handle changes in the business ecosystem by creating innovative solutions. The onus of assessing and inculcating ICIA is a joint responsibility of both academia and industry. In academia, teacher as a servant leader (TASL) contributes towards building ICIA of working professionals (WP) by enhancing their self-efficacy (SE). The paper aims to strengthen the industry–academia interface by analyzing the role of TASL and SE in influencing the ICIA of WP.

Using a stratified sampling technique, data from 387 WP is analyzed on SmartPLS-4 to study the interrelationship between the stated constructs and the role of SE as a mediator between TASL and ICIA. PLSpredict is used to study the predictive relevance of the proposed model.

High R² = 0.654 shows that 65% of ICIA is determined by SE and TASL; reflecting model's robustness. SE partially mediates the relationship between TASL and ICIA. Results reported a higher ICIA of male WP than their female counterpart. The results indicate the low predictive accuracy of the model.

The proposed model of industry–academia partnership allows assessment of ICIA for enhancing corporate value in the present gig economy. The study also highlights the relevance of ICIA, particularly, for developing economies. In knowledge-driven economy, exploring the new ICIA will help organizations to draft a more robust performance measurement system.

This unique industry–academia partnership studies the role of TASL towards enhancing SE and ICIA of WP. The novelty of ICIA would enrich and provide a new perspective in IA literature. Additionally, the study also examines the role of gender in the ICIA of WP.

This paper investigates income convergence using different convergence concepts and methodologies for 72 countries over the period between 1960 and 2010.

This study applies beta (β), sigma (s), stochastic and club convergence approaches. For β-convergence analysis, it derives the cross-country growth regressions of the Solow growth model under the basic and augmented Cobb–Douglass (CD) production functions and estimates them using cross-section and panel data estimators. While it employs both the widely used coefficient of variation and recently developed weak s-convergence approaches for s-convergence, it applies three different unit root tests for stochastic convergence. To test club convergence, it estimates the log-t regression.

The results reveal that (1) there exists conditional β-convergence, meaning that poorer countries grow faster than richer countries; (2) income per worker is not (weakly) s-converging, and cross-sectional variation does not tend to fall over the years; (3) stochastic convergence is not found and (4) countries in the sample do not converge to the unique equilibrium, and there exist five distinctive convergence clubs.

The results clearly show that heavily relying on one of the convergence techniques might lead researchers to obtain misleading results regarding the existence of convergence. Therefore, to draw reliable inferences, the results should be checked using different convergence concepts and methodologies.

Contrary to the previous literature, which is generally restricted to testing the existence of absolute and conditional β-convergence between countries, to the best of the author’s knowledge, this is the first study to consider and compare all originally and recently developed fundamental concepts of convergence altogether. Besides, it uses the Penn World Table (PWT) 9.1 and extends the period to 2010. From this point of view, this study is believed to provide the most up-to-date empirical evidence.

This study investigates the effect of intellectual capital (IC) and its components on the technical efficiency of Indian commercial banks after controlling the influence of bank-specific and macroeconomic variables.

The study selects a sample of 37 listed Indian commercial banks from 2005 to 2019 and uses the two-step data envelopment analysis (DEA) approach. Banks' technical efficiency scores are first estimated, while the relationship between IC and technical efficiency is examined in the second stage using the panel data Tobit model.

This study's findings suggest a fluctuating trend in the technical efficiency of Indian banks. Notably, from 2015 onwards, a declining technical efficiency trend is observed for all banks. However, private-sector banks outperform public-sector banks in terms of technical efficiency. This study's regression analysis indicates a positive relationship between IC and banks' technical efficiency scores. Further, by decomposing IC into its components like human capital, structural capital and capital employed, the study's findings show that human capital and structural capital enhance banks' technical efficiency. Notably, capital employed reduces technical efficiency. Moreover, bank size, diversification, capitalization, net interest margin and the country's growth rate significantly drive Indian banks' efficiency. In contrast, their operating cost ratio and the country's inflation negatively influence the same.

This study makes a novel endeavor to examine the IC and bank's technical efficiency nexus in the Indian context, encompassing a period of landmark banking reforms.

The paper underpins an advanced domestic manufacturing that comes with some advanced employment specialization status of individual industries as the key determinant of foreign direct investment (FDI) and considers how FDI in the food processing industry in India relates to this focal point.

This paper investigates how inward FDI inflows relate to domestic investment and revival in the industry using Auto Regressive Distributed lags (ARDL) model over the period 2000–2017. The model allows for different specifications to study whether FDI is responsible for the revival or the prior revival induces the FDI.

The results show the lack of proper advanced specialized employment status of the food processing industry. FDI in food processing is mainly guided by exports and imports opportunities and FDI plays no role in the revival of advanced growth in the industry. This finding explains why FDI in the industry is predominantly service sector oriented.

The paper underlines (1) the proper conceptualization of human capital as an important determinant of FDI; (2) reinterpretation of Kaldor's technical progress function that uncovers how employment dynamics embedded in intermediate goods specializations play a key role in supporting a higher pace of investment (and FDI); (3) labor costs' importance should involve not only the wage rate but also the advantages that a specialized employment base and (4) FDI in manufacturing demands a greater policy focus on developing domestic bases of intermediate goods specializations.

Based on resource-based theory and intellectual capital theory, this paper aims to investigate the impact of digital investment on enterprise value and the mediating role of intellectual capital. Additionally, it explores the heterogeneous impacts of digital investment on enterprise value and intellectual capital.

The study utilizes a sample of listed companies in Chinese A-shares from 2013 to 2020. The entropy-weighted method is applied to measure digital investment from two dimensions: scale and increment. Finally, the research hypotheses are tested through multiple regression analysis.

The empirical results demonstrate that digital investment significantly and positively impacts enterprise value. From the channel mechanism test, digital investment can enhance enterprise value by influencing intellectual capital through human, structural and relational capital. Of these, the mediating effect of human capital is the most significant. Moreover, the impacts of digital investment on enterprise value and intellectual capital are related to the industry sectors. In the agricultural sector, digital investment has adverse effects. In the industrial and service sectors, digital investment promotes intellectual capital and enterprise value. However, in the service sector, the impact on relational capital is not significant, and the mediating effect of relational capital does not hold.

This research has a limited potential for generalization due to the lack of standard measurement models for the exploration of digital investment.

The research findings are valuable for assessing the economic effects of digital investment comprehensively and providing essential information for policy formulation and strategy implementation.

This study represents the first attempt to evaluate the relationship between digital investment and enterprise value using the entropy-weighted method. In addition, this study investigates the mediating role of intellectual capital.

This study investigates the impact of international remittances on the economic growth of remittance-receiving countries, using data from 113 developing countries between 1990 and 2015.

The authors used a novel approach to address the potential endogeneity of remittances. The authors estimated bilateral remittances and use them to create weighted indicators of remittance-sending countries, which the authors then use as instruments for remittance inflows to remittance-receiving countries.

The results indicate that while remittances have a positive impact on economic growth in developing countries with high human capital, they do not contribute to growth in developing countries with low human capital. The authors also examined the channels through which remittances affect growth. The findings suggested that remittances do not impact labor supply in developing countries with high human capital, but they reduce labor supply in countries with low human capital. Additionally, remittances increase investment in physical capital in developing countries with high human capital, but they do not have an effect on investment in developing countries with low human capital.

The authors investigated the impact of remittances on economic growth using a novel approach to address the endogeneity of remittances. Additionally, the authors examined the different indirect channels through which remittances can impact economic growth, such as their effect on labor supply and investment.

This study focuses on the relationship between foreign direct investment (FDI) and economic growth of the formal sector comprising all foreign and domestic registered enterprises engaged in production of goods and services.

This study uses a balanced longitudinal data set for the period from 2006 to 2014 from secondary sources in 63 provinces/cities of Vietnam. The generalized method of moments (GMM) estimation for a dynamic panel data model is applied.

The greater the share of FDI in capital resource, the more favorable the output growth in the whole formal sector. The FDI enterprises are more productive than domestic formal firms, and the output growth of FDI firms creates a positive spillover effect on the output growth of domestic firms.

The effect of FDI on economic growth is investigated at subnational level for the whole formal economic sector as well as the formal domestic firms. The domestic and foreign industrial agglomerations and the business environment are also examined.