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The purpose of this paper is to translate consumer requirements regarding olive-oil quality attributes into specific olive-growing practices that most contribute to satisfy these attributes.

After identifying consumer requirements or needs regarding different attributes of olive-oil quality, through a survey of 439 olive-oil consumers, the authors determine the olive-growing practices that optimally satisfy consumer needs through expert opinions. Finally, the use of expert knowledge to construct the House of Quality or the first matrix of quality function deployment allow the authors to define the relative contribution of the various olive-farming practices to the satisfaction of consumer requirements.

The findings have shown that the olive-oil quality attributes most requested by consumers incorporate organoleptic (e.g. acidity, flavour, colour), sociocultural (e.g. creating employment in rural areas, maintenance of the rural population) and environmental ones (environmental externalities). The “separation of olives collected from ground and trees” (separation), “timing of harvesting” (according to a fruit-ripeness index), the “method of the ground harvest” (no picking from the ground), and the “method of tree harvest” (handpicking) were some of the most commonly identified olive-farming practices that contribute the most to meeting consumers’ needs with regard to olive-oil quality.

The study suggests detailed analyses of the relationships between customer requirements and other agents practices involved in the olive sector (processing industries: mills, distribution, and marketing management, etc.) to more fully investigate the impact of all these practices on consumers’ perceived olive-oil quality attributes. This is the most reliable way to guarantee that the most sought-after quality characteristics are taken into account, not only in the farming stage but also in the various different stages of the olive agri-food chain.

Findings represent an opportunity in the market value chain to develop a quality olive oil which is more oriented towards the consumer and able to face future segmentations in the market. This is one of the main innovative features of this study, as it offers “good practice” guidelines to agents of the olive-oil sector from the consumer perspective.

This study provides positive implications to consumers, providing them important tools to make an informed choice, and producers and marketers helping the design of production strategies to optimally satisfy the consumer preference with regard to olive-oil quality, and attain a competitive advantage by adding value to the product.

This paper is regarded as the pioneer in the literature translating the “consumer voice” regarding olive-oil quality into specific olive-growing practices “good-practices guidelines”. Thus, the relevant required quality olive-oil attributes should be clearly described on the label, to enable consumers to identify the quality features and make an informed choice. Furthermore, to meet consumers’ needs, the olive-oil sector should focus on the olive-growing practices that optimally satisfy consumer requirements concerning olive-oil quality attributes. This would help to improve legitimacy and boost public support for the Common Agricultural Policy subsidies for the agricultural sector in general, and the olive sector in particular. The findings are particularly valuable in helping policy makers to design marketing strategies to improve the sustainability and competitiveness of Spanish olive oil.

This paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.

This paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.

The findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.

The outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.

Specifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions. The period is divided into sanctioned and non-sanctioned periods by Markov switching model.

The results show that the pass-through of oil price shocks into Iran’s inflation are time-varying, and there are significant differences at sanction period from other time horizons. An increase in oil price has a positive effect on inflation and its effects are stronger during the sanctions period. It is also observed that the producer price index is more sensitive to changes in the oil price than the consumer price index. The necessity of the government’s earnest efforts to improve international relations to lift the sanctions, along with diversification of exports, and making the economy of Iran independent of oil revenues is obvious.

In addition to the exogenous oil price shocks, Iran’s economy faces numerous restrictions for its oil exports due to the sanctions. The main purpose of this paper is to investigate the dynamics effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions.