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The purpose of this paper is to investigate the role that weather shocks can play in the livestock mortality microinsurance take-up when the insured risk has a prevalent covariant component.

The sample consists of 360 rural Ethiopian households. Data were collected in a panel-structure at the end of three agricultural seasons (2011-2013). In the questionnaire, a specific section on insurance was meant to collect information on the farmer’s willingness-to-pay (WTP) for a set of insurance products, including livestock mortality insurance. Two OLS regression models and a quantile regression model were employed to estimate the impact of weather anomalies on the WTP for the insurance product.

The authors find that weather anomalies contribute to changes in the WTP to a large extent. Negative (positive) changes in precipitation (temperature) anomalies can lead to more than a 30 percent reduction in the WTP. This general finding is complemented with the analysis of the conditional distribution of the WTP, which shows that other elements can prevail for low values of the conditional distribution. In this case, the WTP seems to be represented more by the interviewee’s age and basic knowledge of insurance, and village fixed-effects. Basic knowledge of insurance, in particular, can increase WTP by about 60 percent.

This paper has straightforward implications from a policy perspective. It suggests that farmers would prefer an insurance premium that follows the changes in the systemic component. On the contrary, insurance as well as reinsurance companies are usually reluctant to frequently revise their premiums. Financial education programs, farmer-driven design, trust building, and bundling insurance with other financial and non-financial products can increase the value proposition perceived by the farmers. From a marketing perspective, the overall findings suggest that continuous fine-tuning of the contract, transparency, and targeted information campaigns can contribute to increase and stabilize potential customers’ WTP.

To the best of the authors’ knowledge, this is the first paper that considers the impact of weather shocks on the WTP for a livestock mortality insurance product. Livestock is one of the most strategic assets of poor rural households in Africa. This study contributes to the theoretical and empirical literature on the determinants of weather insurance take-up in developing countries and, in particular, the role of spatiotemporal adverse selection and basis risk (e.g. Jensen et al., 2016).

The purpose of this paper is to examine how shocks suffered by rural households in Ethiopia influence their decision to borrow and the source of credit.

First, suppose a household faces a set of four borrowing alternatives: only formal borrowing, only informal borrowing, both formal and informal borrowing, and non-borrowing. Second, the paper assumes that the random component is independently and identically distributed in accordance with the extreme value distribution. These assumptions lead to the multinomial logit model. The paper estimates the model using data from a survey of 350 rural households in Southern Ethiopia.

The paper finds that shocks are important factors in explaining both the decision to borrow and the source of credit. In particular, negative shocks that affect household's assets, such as the seizing of farmland and theft, or human capital, such as the death of the family head, reduce the probability of borrowing from formal lenders or from both formal and informal lenders at the same time. The study supports only to some extent the assumption that informal credit contributes to smooth consumption. Last, networking effect is very significant and demonstrates how the two markets interact.

A model that would consider dynamic consumption patterns would have been more appropriate. In fact, one of the limitations of the study is the reliance on a cross-section analysis and the data is limited to just one village. Further research would extend the data set geographically and across time.

The formal lenders are not willing to provide contingent loans, maybe because of a limited ability to assess and diversify risk. Besides, the available formal credit products are not proper to finance long term risk management strategies but pesticides, fertilizers and improved seeds that are entirely used in every agricultural cycle. In this regard, proper risk transfer strategies and instruments, as well as better tailored loan products, are needed in order to increase outreach into the rural areas.

To the authors’ knowledge, this is the first paper that investigates how shocks influence the decision to borrow and the source of credit in Ethiopia.

Although the literature on corporate governance and firm innovation finds that board independence is important, this paper proposes that the presence of independent directors alone is not enough to explain their impact on firm innovation. This study analyses if diversity among independent directors may affect the relationship between board independence and firm innovation.

A panel data on a sample of 124 Spanish listed companies for the period 2008–2019 used to test the hypotheses.

Results suggest that independent directors have a negative effect on firm innovation, measured as number of patents, but when there are high levels of gender and nationality diversity among such directors, this negative effect may be mitigated.

Considering that firm innovation is a complex process associated with decision-making and that board independence itself may be not enough, this study goes a step further and delves deeper into the characteristics of independent directors. As far as is known, this paper is the first theoretical and empirical study that considers that independent director diversity as a moderating variable between board independence and firm innovation. Besides, this research contributes to the debate on the role of independent directors in firm innovation and the results may also serve as a guideline for policy makers and firms for structuring boards that are pro-innovation.

The purpose of this study is to underscore the impact of the family variable on performance. The authors were interested in understanding whether the differences between Family Firms (FFs) and Non-Family Firms (NFFs), on the one hand, and between large FFs and medium-sized FFs, on the other, were reflected in the performance achieved.

In this paper a sample of 80 industrial companies listed on the Italian Stock Market (FTSE MIB and STAR indexes) were considered, and mixed criteria to distinguish FFs and NFFs (Smyrnios-Romano et al., 1998) were used. The empirical method allowed the development of some research hypotheses by exploiting the Pearson correlation.

There are two main categories of FFs, which correspond to two different strategic and organizational categories, namely, the FFs listed on the large capitalized companies index (FTSE MIB) and the FFs listed on the medium-capitalized companies index (STAR). Each kind of FFs (large FFs and medium-sized FFs) has a specific effect on profitability and financial performance. Specifically, if a company is medium sized, family presence is a relevant variable in achieving better profitability and financial performance than NFFs of the same size; on the other hand, if the company expands to become a large one, the family presence is an irrelevant variable in terms of both profitability and financial leverage (debt ratio).

Limitations of the study concern the definition of the sample, as this paper focused on the industrial sector and the method adopted, as it could be integrated with some econometrical models. The implications of this paper are relevant for families and regulatory bodies because it helps them better understand the effects of governance and company size both on short- and long-term performance. Moreover, the findings of the study can influence the decision-making process of investors to identify the long-term outperformers listed on the Italian Stock Exchange.

This study contributes to the literature on FFs by defining two different categories of FFs, namely, large and medium-sized. It seems that larger companies record a weaker family influence on short-term profitability.

The aim of this research is twofold: first, to get more insights on digital maturity to face the emerging 4.0 augmented scenario by identifying artificial intelligence (AI) competencies for becoming hybrid employees and leaders; and second, to investigate digital maturity, training and development support and HR satisfaction with the organization as valuable predictors of AI competency enhancement.

A survey was conducted on 123 participants coming from different industries and involved in functions dealing with the ramifications of Industry 4.0 technologies. The sample has included predominately small-to-medium organizations. A quantitative analysis based on both exploratory factor analysis and multiple linear regression was used to test the research hypotheses.

Three main competency clusters emerge as facilitators of AI–human interaction, i.e. leadership, technical and cognitive. The interplay among these clusters gives rise to plastic knowledge, a kind of moldable knowledge possessed by a particular human agent, here called hybrid. Moreover, organizational digital maturity, training and development support and satisfaction with the organization were significant predictors of AI competency enhancement.

The size of the sample, the convenience sampling method and the geographical context of analysis (i.e. California) required prudence in generalizing results.

Hybrids’ plastic knowledge conceptualized and operationalized in the overall quantitative analysis allows them to fill in the knowledge gaps that an AI agent-human interplay may imply, generating alternative solutions and foreseeing possible outcomes.