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The paper aims to provide a benchmark study of the European Union (EU) e‐government policy within the e‐Europe programme. The main objective of the European strategy for the development of e‐government was that the member states should ensure “online public services”. To monitor this policy the European Commission defined two indicators.

The European Commission developed a list of 20 basic public services. The Commission and Capgemini defined a framework to evaluate the online availability of each of the services in each of the EU member states, plus Norway, Iceland and Switzerland.

The study finds that since 2001 a considerable improvement in online public service provision was measured, even so the 2004 result of 65 per cent online sophistication of public service delivery in the EU still shows an important gap with the 100 per cent objective, the result was considered a positive. When considering the different types of public services, income generating services including income tax, VAT and corporate tax are by far the most developed online. The new member countries seem to be only two years behind in the development of online public service. The most advanced countries exceed 80 per cent but seem to evolve to a “plateau”. They have developed their most feasible services, demanding less effort, now only the “hard” ones are undeveloped, mostly services delivered at a decentralised level.

The study provides information on the online development of public services, i.e. the provision and interactivity of public services through the internet. It does not analyse the provision of services through other channels, neither the quality of the service delivery, nor the use or impact of these new ways of public service supply. Therefore a new EU e‐government measurement system must change the focus from “availability” of e‐government services, to “use” and desired positive “impact” of e‐government programmes.

This study provides the only available data measured scientifically over a longer period concerning the development of e‐government in the EU.

The purpose of this paper is to introduce the theme of this special issue, “Advances in e‐democracy: engaging citizens and electorates”.

An overview is provided of developments in e‐government before providing a summary discussion of the papers that are presented in this issue.

While governments around the world, not least in the UK, have been enthusiastic about the use of information and communication technologies to provide better citizen access to government and public services, there is still much to be learned about how these online services can be effectively implemented and will be taken up.

This paper provides a primer for the remainder of this issue which combines research reports from academics working in the e‐democracy field and from practitioners in government and commercial service suppliers.

Building on the risk balancing theory and on recent discussions the appropriateness of using farm income maximization as behavioural assumption, this paper extends the risk balancing framework by accounting for business-household interactions. The purpose of this paper is to theoretically introduce the concept of farm household risk balancing, a theoretical framework in which the farm household sets a constraint on the total household-level risk and balances farm-level and off-farm-level risk.

The paper argues that the risk behaviour of farmers is better understood by considering risk at the household level. Using an analytical framework, equations are derived linking the farm activities, off-farm activities, consumption and business and private liquidity.

The framework shows that a farm household that wants to minimize the risk that total household cash flow falls below consumption needs, may exhibit a wide variety of behavioural responses to changes in the policy and economic environment.

The framework suggests multiple ways for policy makers and individual farmers to support risk management.

Risk management is at the core of the agricultural policy and it is of paramount importance to be able to understand behavioural responses to market and policy instruments. This paper contributes to that by suggesting that the focus of current risk analysis and management studies may be too narrowly focused at the farm level.

The purpose of this paper is to investigate a farm manager’s personal characteristics (personality, age, education, objectives, experience, etc.) as drivers of debt payback success and rates. Traditionally bankers have used historic business statistics, and equity levels, to assess loans and credit worthiness. It is hypothesised that a managers’ personal characteristics are likely to be a better predictor of future debt payback performance.

The literature was searched to isolate the managers’ personal variables likely to determine debt payback. The information led to defining a quantitative model based on the theory of planned behaviour (TPB) which was hypothesised as determining payback rates where a choice was available. A postal random stratified survey of NZ owner operator farm managers provided the data to test the model and define its parameters using regressions, structural equation modelling and statistical comparisons.

The modelling results make it clear a manager’s personal characteristics are highly correlated with debt payback and, logically, are very likely to be the drivers. Four random effects equations and a comparison of high- and low-debt payback managers led to this conclusion.

Bankers should use the managers’ personal characteristics, as defined in the regressions, alongside traditional measures when assessing farm business loan requests. This approach is opposite to the traditional methods using mainly historic data.

The use of the TPB in assessing debt payback is a new and novel approach showing how enduring personal characteristics can be used in assessing proposals, and particularly, entrepreneurs’ adventurist investments in situations where historic data are not available.

This study aims to investigate the effect of color temperature on consumption. Color is one of the most powerful elements of sensory marketing. However, how warm and cool colors drive consumer indulgence and interact with other visual cues is minimally understood.

This research conducts six experiments to investigate the effect of eight warm and cool colors and the effect of warm/cool color’s interaction with reflectance on indulgent consumption/use in various retail environments.

Studies 1a and 1b support the contrasting effects of warm vs cool colors on consumers’ indulgent consumption. Studies 2a and 2b establish the serial mediating role of arousal and self-reward focus in the color-indulgence relationship. Study 3a demonstrates the interactive effect of warm (vs cool) colors and glossy (vs matte) reflectance on consumer indulgence, and Study 3b confirms how glossy (vs matte) reflectance moderates the serial mediating effect of arousal and self-reward focus in the color-indulgence relationship.

This research contributes to the growing stream of research on the visual aspect of sensory marketing, especially color, and advances the theoretical knowledge of how color could be used effectively to influence consumer indulgence.

This research provides actionable managerial implications on the effective use of warm and cool colors and glossy and matte reflectance to influence consumer indulgence.

This research advances the theoretical and empirical knowledge of color’s interaction with other visual sensory cues and the underlying psychological processes shaping consumer indulgence.

The purpose of this paper is to investigate the endogeneity of asset values and how it relates to farm financial stress in US agriculture. The authors conceptualize an implied measure of farm financial stress as a function of debt position. The authors posit that there are variations in the asset values that are beyond the farmer’s control and therefore have implications on farm debt.

The framework recognizes the endogeneity of return on assets (ROA). It uses a non-parametric technique to approximate the variance of expected ROA (VEROA). The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Further, the authors use a dynamic balanced panel data set from 1960 to 2011 for 15 US agricultural states from the Agricultural Resource Management Survey, and information from traditional state-level financial statements.

Estimation of linear dynamic debt panel data models accounting for the endogeneity of ROA and VEROA is a challenging task. Estimated variances are unstable. Hence, the authors focus on variance specification that uses the residuals squared from the ARIMA specification and non-parametric estimators. Arellano-Bover/Blundell-Bond generalized method of moments estimation procedures, although may be biased, show that VEROA has a negative and significant effect on the total amount of debt in the agricultural sector.

The instruments used in this analysis are lagged regressors which may be weakly correlated with the relevant first-order condition, hence not properly identifying the parameters of interest. Future research could include the identification of better instruments, potentially use of sequential moment conditions.

Unlike previous study, the authors use non-parametric approximation of VEROA. The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Second, the authors make use of a large dynamic balanced panel data set from 1960 to 2011 for 15 agricultural states in the USA. To the best of the authors’ knowledge, this study is one of the few that provides evidence on risk-balancing behavior at the agricultural sector level, of the USA.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

The purpose of this paper is to consider how the federal crop insurance (FCI) program influences farm debt use, one of the key financial decisions made by farm operators.

Using data from the nationally representative Agricultural Resource Management Survey, the paper implements a propensity score matching model of the impact of FCI participation on various measures of farm business debt use. To account for the simultaneity of financial decisions, the paper further tests this relationship using a seemingly unrelated regression model.

FCI participation is associated with an increase in use of short-term farm debt, but not long-term debt, consistent with risk balancing behavior and current trends in the farm sector.

In addition to risk balancing, the results are also consistent with credit constraints or lender preferences. The paper cannot fully establish causality between crop insurance participation and short-term debt levels. Future research should address these limitations.

Agricultural lending standards are generally conservative and the farm sector as a whole currently has historically low leverage, which implies that an increase in debt use may not be a threat to the financial health of the farm sector.

The results indicate that the reduction in total risk facing the farm sector is significantly less than the decline in risk provided by FCI, which is an important consideration for policymakers.

This is the first paper to use an econometric model to analyze the relationship between FCI and farm debt use decisions. This paper can inform future research on the FCI program and farm financial decisions.