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A separate study of the different behavioral biases does not allow for a full understanding of the complexity and stability of the heterogeneity of beliefs. Therefore, through a more global view of these anomalies, the authors wish to show that they can converge on a single concept, which is the heterogeneity of beliefs.

It is therefore essential to stress that the importance of this study is mainly reflected in the methodological approach used in the construction and analysis of the map and not only in the results achieved. This contribution states that structural analysis, as a means of building the cognitive map, can facilitate the task of investors and other decision-makers, in the identification and analysis of the heterogeneity of beliefs that can therefore guide investors' strategy in decision-making.

The authors have studied the behavior of the investor and its way of interpreting the information and the authors have emphasized the value of studying the concept of heterogeneity of beliefs in its complexity. So that part of the work seems to be relevant and crucial to filling, if you will, that void. In this sense, the authors have shown that behavioral abnormalities are multidimensional concepts: “self-deception”, “cognitive bias”, “emotional bias” and “social bias”.

In particular, this article will aim to achieve the objective of proposing a model for measuring the heterogeneity of beliefs. Thus, the authors want to show that the heterogeneity of beliefs can be measured directly through the different behavioral anomalies.

This paper aims to study the impact of human resource heterogeneity on firms’ cash-holding policies.

The authors construct a proxy for human resource heterogeneity using the dissimilarity in employees’ skill structure between the firm and its peers in the same industry.

The authors report evidence that firms with heterogeneous human resources hold more cash than other firms. This effect is more pronounced in labor-intensive firms and firms more susceptible to hold-up by employees, i.e. firms located in regions with more labor disputes and firms surrounded by more external employment opportunities. In addition, the authors demonstrate that high cash holdings triggered by human resource heterogeneity reduce the scale and efficiency of firms’ capital investment.

This study highlights the role of human resource heterogeneity in determining firms’ cash policies. This paper adds to the understanding of labor adjustment costs within the firm and provides insights into firms’ cash-holding decisions.

The purpose of this paper is to provide insights into the implications of board human capital heterogeneity for company innovation by focusing on the educational and the functional background of directors. Moreover, it examines the moderating effect of the CEO expertise-overlap within the innovation domain on the relationship between board human capital heterogeneity and firm innovation.

The hypotheses are tested through a set of ordinary least squares regressions on a unique dataset of 149 Italian high-tech companies observed between 2012 and 2015.

Findings show that the educational and the functional background heterogeneity of directors increase both the innovation input and output. However, results highlight that these relationships are negatively moderated by the CEO expertise-overlap within the innovation domain.

The paper emphasizes the importance of appointing directors with different and specific educational and functional backgrounds to foster the company innovation.

The paper fills a gap in the literature as it has devoted limited attention to the performance implications of board human capital heterogeneity in the high-tech industry where knowledge and skills are the primary sources of value. Moreover, the paper integrates the research on the CEO-board interface by shedding light on how the CEO expertise within the innovation domain affects the contribution of heterogeneous boards to company innovation.

The purpose of this paper is to investigate the impact of shipyard and shipowner heterogeneity on the price formation for individual newbuilding contracts.

The model controls for the shipbuilding market cycle, input costs, firm size, yard experience and contract-specific variables and captures the impact of yard and owner heterogeneity in fixed-effects regressions. The data sample contains contract information on 3,759 tankers, bulkers and container vessels constructed at 77 shipyards between 1990 and 2014.

Although the newbuilding price benchmarks (market conditions) and gross domestic product per capita (salary costs) are influential covariates, the main conclusion is that shipyards and, particularly, shipowners play an influential role on the US$ per Compensated Gross Tonnage price level in individual contracts.

The paper represents the first study of the impact of buyer and seller heterogeneity at the micro level in the shipbuilding market.

Prior studies have shown that heterogeneity plays a crucial role in addressing soft issues linked to a firm’s corporate social responsibility stance. The purpose of this paper is to extend the prior literature on the effect of gender heterogeneity on environmental, social and economic performance dimensions, specifically, whether the female boardroom presence weakens or strengthens the performance along the three dimensions, commonly referred to as the corporate sustainability.

The study from a positivist philosophy adopts a quantitative approach, and the final sample consisted of forty-six companies listed on the Nigerian Stock Exchange for the year 2011–2018. The final sample was a balanced panel of 344 firm years. The dependent variables were return on assets (ROA), environmental performance (ENV) and donations made for social causes (SOP). The ENV was measured using a content scoring system, with range of 1 to 5. The data were analysed using the fixed effects and GLM regression models. To further address the issue of endogeneity, a two-stage least squares regression was conducted.

The findings show a positive relationship between gender heterogeneity and ROA, which was also confirmed for the environmental performance index. However, the sign reversed in the SOP model and showed a negative relationship between gender heterogeneity and donations, the proxy for SOP. The results are in tandem with the stakeholder axioms that argue that commitment to other stakeholder groups strengthens firm performance in the long run.

An implication of this study is the fact that information availability has been rapidly escalating in the country, leading to rising social movements and civic unrest; therefore, corporations that face negative castigations may pay the huge price of product boycott and loss of market value.

The findings of this study provide additional insight into the influence of female boardroom presence on the environmental, social and economic performance of firms. The findings suggest the relevance of the resource dependence theory, especially from a developing country context, to ensure an improved corporate governance structure in Nigerian manufacturing firms.

The purpose of this paper is to review the empirical literature on the relationship between the characteristics of the top management teams (TMTs) and the performance of entrepreneurial firms.

A literature review was carried out on 33 empirical studies related to TMTs and performance through analyzing and summarizing the quantitative studies conducted in this area.

The results of the literature review show that the relationship between TMTs (demographics and heterogeneity) and the performance of entrepreneurial firms is not straightforward and further investigation is still needed in this area.

The author maps the theoretical and empirical research of TMT demographics and heterogeneity in relation to firms’ performance and possible moderators and mediators, which govern the relationship between TMT composition and firms’ performance.

The author presents a detailed future research agenda for the purpose of advancing the theoretical and empirical knowledge on TMT-performance links. The review provides a comprehensive picture of TMT-firms’ performance literature and what should be done to enrich the literature.

The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.

Relying on the support vector machine (SVM)-based classification model, the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face, and the identification calculation was carried out for the five test tunnels. Then, the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.

The results show that compared with the two classification models based on neural networks, the SVM-based classification model has a higher classification accuracy when the sample size is small, and the average accuracy can reach 87.9%. After the samples are replaced, the SVM-based classification model can still reach the same accuracy, whose generalization ability is stronger.

By applying the identification method described in this paper, the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified, and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting, and can provide a basis for local optimization of support parameters.

People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

This paper aims to model the efficiency of labour offices belonging to the public employment services (PESs) in Spain using a stochastic matching frontier approach.

With this aim in mind, the authors apply a random parameter model approach to control for observed and unobserved heterogeneity.

Results indicate that when the information criteria of the estimates are analysed, it improves by controlling both, observed and unobserved heterogeneity in the inefficiency term. Also, results suggest that counsellors improve the productivity of labour offices and that the share of unemployed skilled persons, unemployed persons aged 44 or younger, as well as the share of unemployed persons in the construction sector, all affect the technical efficiency of PESs offices.

The model extends the previous specifications in the matching literature that capture only observed heterogeneity. Moreover, as far as the authors know, it is the first paper that estimates a matching frontier for the Spanish case. Finally, the database they use is at the office level and includes the work carried out by counsellors, which is a novelty in the analysis of this type of studies at the Spanish level.

Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.