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The purpose of this study is to propose and explore a conceptualization of decisional capital that is suitable for early career teachers.

This study uses exploratory factor analysis on a sample of early career teachers to examine a literature-derived conceptualization of decisional capital.

The factors that emerged support the literature-derived conceptualization. A subsequent confirmatory factor analysis on a second sample of early career teachers offers additional evidence for the proposed conceptualization. An exploration of the underlying factor structure comparing results across four competing models (i.e. unidimensional, correlated factors, second order, and bifactor) suggests that a second order factor explains the variance across the three proposed factors well. We conclude that this second order factor is decisional capital.

This is the first study that examines the discrete elements of decisional capital. Understanding these discrete elements is an avenue for investigation into the development of decisional capital beyond the acknowledgment that it takes time to develop.

The study explores manufacturers' supply chain social capital (SCSC) (structural social capital and relational social capital) and supply chain performance, respectively, as drivers and outcome of green supply chain management practices (GSCMPs). Additionally, the study explores the direct relationship between SCSC and supply chain performance of manufacturers.

The author develops and tests a research model grounded in the resource-based view and the natural resource-based view theory using survey data from 100 manufacturing firms operating in Ghana. The measurement model and hypothesized paths were examined using partial least squares structural equation modeling.

The findings revealed that relational social capital of manufacturers has a positive and significant relationship with supply chain performance, but structural social capital does not. Additionally, manufacturers' structural social capital and relational social capital were found to have a positive and significant relationship with GSCMPs. Lastly, GSCMPs were found to have a positive and significant relationship with supply chain performance.

The study contributes to the limited literature demonstrating the contribution of intangible relational assets, specifically SCSC, toward GSCMPs implementation.

The study aims to examine the impact of intellectual and social capital in funding businesses.

The study made use of fixed-effects panel data models with a sample of 142 countries from the five continents during the period 1998–2018.

It was found that human capital (HC), relational capital, structural capital and social capital play a role in investors’ decisions to fund a business. The study revealed that investors’ funding decisions in low human development index countries are based mainly on education, while those in high human development index countries are based mainly on the creativity component of HC and on relational, structural and social capital.

The study needs to be replicated using firm-level data within each country. Moreover, the search for new proxies for intellectual and social capital (although the list of variables is exhaustive) both at the country and firm level, constitutes an interesting avenue for future research.

Countries should pay attention to intellectual and social capital to encourage business activity. In particular, low human development countries should strengthen HC, such as the school enrollment rate, with early entrepreneurial training and increase research and development investments, while high human development countries should continue to foster strategic alliances, protect intellectual property and maintain or increase the level of trust in the country.

The study contributes to literature by being the first to explore such a variety of intellectual and social capital variables from a country-level perspective.

El estudio tiene como objetivo examinar el impacto del capital intelectual y social en la financiación de las empresas.

Utilizamos modelos de datos de panel de efectos fijos con una muestra de 142 países de los cinco continentes durante el periodo 1998-2018.

Encontramos que el capital humano (CH), el capital relacional, el capital estructural y el capital social juegan un papel en las decisiones de los inversionistas para financiar un negocio. Encontramos que las decisiones de financiamiento de los inversionistas en los países con bajo índice de desarrollo humano se basan principalmente en la educación, mientras que las de los países con alto índice de desarrollo humano se basan principalmente en el componente de creatividad del CH y en el capital relacional, estructural y social.

Sugerimos replicar el estudio utilizando datos a nivel de empresa dentro de cada país. Por otra parte, la búsqueda de nuevos indicadores de capital intelectual y social (aunque nuestra lista de variables es exhaustiva) tanto a nivel de país como de empresa, constituye una vía interesante para futuras investigaciones.

Los países deben prestar atención al capital intelectual y social para fomentar la actividad empresarial. En particular, los países con bajo desarrollo humano deberían fortalecer el CH, como la tasa de matriculación escolar, con una formación empresarial temprana y aumentar las inversiones en investigación y desarrollo, mientras que los países con un alto nivel de desarrollo humano deberían seguir fomentando las alianzas estratégicas, proteger la propiedad intelectual y mantener o aumentar el nivel de confianza en el país.

El estudio contribuye a la literatura al ser el primero en explorar tal variedad de variables de capital intelectual y social desde una perspectiva a nivel de país.

This study examines factors that influence organizations’ choices of an internal human capital development strategy and an external human capital acquisition strategy. The human resource architecture indicates that organizations will use different human capital acquisition strategies. Following the resource-based view, human capital theory and the human resource architecture, we examine factors that impact the choices of different human capital acquisition strategies.

We examine these important human capital decisions in the context of Major League Soccer. Data to test the hypotheses were collected from a variety of publicly available sources. We tested the hypotheses with regression analyses.

We find that while organizations employ both internal and external human capital strategies, organizations may have one dominant human capital strategy and the other strategy may be used to supplement the human capital needs of organizations. Additionally, our results indicate that organizations with an older workforce tend to use an internal human capital development strategy, while higher performing organizations are less likely to use an internal human capital development strategy.

This study makes contributions by examining the choices between internal and external human capital strategies and factors that influence the choice of an internal or external human capital strategy.

The purpose of paper one of the two‐article series exploration of human capital assessment is to examine the strategies by which library administrators can assess and benefit the human capital performance of their library and to lay the groundwork for the discussion of the strategic challenges of assessing and valuing human capital in article two.

This paper uses a literature review to identify potential strategies and metrics for library administrators to assess human capital productivity.

Human capital is an increasingly essential element of organizational performance assessment. Effectively assessing library staff expenditures (which generally receives the largest expenditure allocations within the library's budget) and the resulting performance generated by the staff, who are the primary knowledge tools and providers of the library's services, is an ever increasing possibility to account for greater amounts of tangible and intangible organizational performance. Library administrators have multiple options for developing effective strategies and metrics by which to assess their libraries human capital performance.

Developing an effective human capital assessment process as a standard component of the library's performance and budgetary assessment processes would benefit libraries and their administrators by increasing the organizational performance information available for resource allocation decisions regarding library staff development, recruitment, and retention in the larger overall management decision making and planning processes.

Data on shift‐working, annual hours and employment are used to derive alternative measures of capital utilisation in seven countries. There is a positive relationship between utilisation and capital intensity, and utilisation levels in developing countries are significantly higher than in industrialised countries. Inter‐country comparisons of capital productivity are made by comparing industries with similar levels of capital per production worker. It is shown that output per input of capital services in some developing countries is half that of comparable industries in industrialised countries. However, the higher levels of utilisation in developing countries partially offset these low values for the productivity of capital services. Data on labour productivity and earnings are combined to measure labour costs per unit of output and thus throw light on the overall competitive position of industry in the different countries.

Developing intellectual capital and knowledge management measuring systems are two fast growing research areas. Many companies are striving to be known as knowledge organizations and have started measuring and analyzing organizational intellectual capital indicators based on what has been reported in the literature. Very little effort has been made to standardize the measurement and reporting of these indicators with most organizations using very general components. This article discusses a research study that sets out to gain an understanding of management attitudes to the measurement of intellectual capital. The study was conducted with 36 top management participants with at least 20 years of experience in a service‐related industry in Australia. This research investigates the relationship between the perception of the importance of measuring intellectual capital indicators and the level of understanding of these indicators. The strategic implications of understanding the measurements are also discussed within the context of the attitude of top management.

The purpose of this paper is to highlight the relevance of intellectual capital for IT companies in general and, specifically, to analyze the importance of adequately managing intellectual capital in small IT companies.

Two small successful IT companies (one in Spain, another in Finland) are studied, in order to reach a better understanding of how intellectual capital is managed in small companies.

The companies analyzed show the dynamic relationships among the three sides of intellectual capital, and the challenges that managers have to face both to take the advantage of all these connections and mitigate its possible negative effects.

All three areas of intellectual capital (human, social and organizational) require special attention, especially in small knowledge‐intensive companies. Furthermore, the structural embeddedness of social capital seems to develop by following an emergent pattern, especially in small companies where organizational borders do not hinder it. The relational embeddedness of social capital – especially maximizing the spread of knowledge in a company and minimizing the risk of key competence walking out through the door – requires a conscious action from the management and use of work‐rotation techniques.

The paper demonstrates that small companies, even without the organizational resources of the large companies, can however be successful in managing the intellectual capital if their managers are aware of its potential, and understand the idea of the intellectual capital. The paper can help the managers of these kind of companies to know this potential as well as the way to manage it.

The literature shows several intellectual capital models. Nevertheless, there is little empirical evidence about the building blocks that form intellectual capital in practice. The purpose of this paper is to test the widespread categorization of human capital, structural capital, and relational capital with a survey applied to high‐technology firms from Spain.

Factor analysis was conducted with a sample of 49 firms (larger than 50 employees).

The results indeed demonstrate the existence of three main components of intellectual capital that, in general, fit the dominant structure proposed by other authors.

Before moving into an internationally accepted system for classification and measurement of intellectual capital, future research should seek a geographical and industrial agreement about the main components of this construct. In that direction, our empirical evidence provides only the experience of Spanish high‐tech firms; this experience could be different in other countries or industries.

In this paper, managers interested in the field can find a useful guidance for structuring an intellectual capital balance sheet, taking the three proposed components as main dimensions, and the items of the survey as a measurement tool for analyzing the intellectual strengths and weaknesses of their firms.

Academics can also benefit from this research, taking it as a basis for replication studies about intellectual capital in other countries and/or industries. This article presents one of the first empirical tests of the theoretically accepted components of intellectual capital.

Uses a model of technical change embodied in capital equipment to analyse average labour productivity growth. Determinants of productivity growth identified in this analysis are: (1) the rate of labour‐saving technical change; (2) the differential in the rates of change of wages and the rental price of capital; and (3) the rate of growth of industry productive capacity. Finds evidence that each of the identified factors has a positive and statistically significant relationship to average labour productivity growth in a cross‐section of Australian manufacturing industries.