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The purpose of this paper is to discuss characteristics of organic food value chain governance and policy tools that can increase the supply of good quality of agri-products.

This paper discusses a national organic food supply system in China, identifying the link between an organization form with a social confidence crisis and information asymmetry as the main challenges. It develops an analytical model of the market structure of organic certification based on the contract theory, which considers the certification incentive driven by both farmers and processors. Two cases of raw milk producers and processors provide empirical data.

The argument which is brought forward is that product information asymmetry together with strict requirement for ensuring organic food integrity brings the organic milk value chain into a highly integrated organization pattern. A tight value chain is effective in the governance of organic food supply chain under third party certification (TPC), while a loose value chain discourages producing organic products because of transaction costs. TPC is found to be a positively correlation with a tight value chain, but it brings high organizational cost and it raises cost for consumers.

This is the first paper discussing the governance of organic food value chain in Chinese milk industry.

This study aims to propose an optimal procurement model of the collaborative supply chain in the furniture industry. The final output is the total cost minimisation to produce a furniture product that covers material cost, processing cost, transportation cost and holding cost. Therefore, if companies can give the best value to customers at a low cost, then competitive advantages can be achieved.

A genetic algorithm (GA) as a metaheuristic approach was used to solve problems in this research. The optimisation was initiated by developing a mathematical model to formulate the objective function.

Based on the case study, the proposed GA model was able to reduce the total cost of production. The cost was reduced by 73.09% compared to the existing system. Besides, the production time of the proposed model is within the capacity of both companies; hence, no penalty cost is imposed.

The proposed GA model has been implemented and tested to minimise production costs in the Indonesian furniture industry.

To the best of author knowledge, there is no research has proposed an optimisation model that incorporates production cost, transportation cost and production time capacity together in the collaborative supply chain. This research is the first to collaborate these factors using GA in the furniture industry.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

The operational component of a company’s short‐term plan (amounts of products to be delivered and sold to various markets at prices that vary according to markets, sales channels, types of customers and quantities sold, levels of utilization of production capacity, assignment of resources to the manufacturing of different products, amounts of raw materials purchased from different sources, stocks of raw materials and finished products) gives rise to a series of cash inflows and outflows which are not synchronized. The financial component of a company’s short‐term plan has to indicate how to compensate the imbalances, in time, generated by the operational plan, between availabilities and requirements of cash, and indicate the sources of financing to be used and how to temporarily invest cash surpluses. The approach, too often followed in companies, that defines the financial component of a company’s short‐term plan as a consequence of the operational component of the plan, ignores the potential interactions between them and the possibility of defining simultaneously a more economic interfunctionally integrated plan. A model is presented for the decisions in the operational component and a model for the decisions in the financial component. If these models are used separately, they can be integrated resorting to an iterative approach that mutually adapts their separate solutions in order to define the company plan. However, the best approach is to build a model that integrates the two separate models into one structured in a way that can define the optimal integrated short‐term operational and financial plan. The lack of integration between the operational and the financial components of the short‐term company plan is a common weak point in the existing literature and practice.

Complaints about lower agricultural farm-gate price and higher consumer price have emerged in China in recent years. The large gap between dairy farm-gate price and consumer price gives rise to worries that China's dairy industry is characterized by strong degree of oligopoly. The purpose of this paper is to take the dairy processing industry as an epitome of China's food industry, and use a new approach to investigate whether it is oligopolistic and/or oligopsonistic.

Based on a new proposed Primal-Dual Solow Residual model, the authors first test the hypothesis that there are significant oligopoly and oligopsony powers in China's dairy sector, and the latter is stronger. The authors then turn to measure these two kinds of market power using regressions of the model.

The estimation results show that firms in the sector have both strong oligopoly and oligopsony power, but the latter is stronger than the former. Meanwhile, with the continuous reinforcement of competition in China's dairy sector, market power in both the upstream and downstream has decreased slightly.

This paper is the first to simultaneously test oligopoly and oligopsony power in China's dairy sector. The empirical results explicitly imply that more attention should be paid to the raw milk purchase market.

The paper aims to precise and fast categorization on to transaction evolves into indispensible. The effective capacity difficulty of all the IDS simulates today at below discovery amount of fewer regular barrage associations and therefore the next warning rate.

The reticulum perception is that the methods which examine and determine the scheme of contact on unearths toward number of dangerous and perchance fateful interchanges occurring toward the system. Within character of guaran-teeing the slumberous, opening and uprightness count of to socialize for professional. The precise and fast categorization on to transaction evolves into indispensible. The effective capacity difficulty of all the intrusion detection simulation (IDS) simulates today at below discovery amount of fewer regular barrage associations and therefore the next warning rate. The container with systems of connections are reproduction everything beacon subject to the series of actions to achieve results accepts exists a contemporary well-known method. At the indicated motivation a hybrid methodology supported pairing distinct ripple transformation and human intelligence artificial neural network (ANN) for IDS is projected. The lack of balance of the situation traversing the space beyond information range was eliminated through synthetic minority oversampling technique-based oversampling have low regular object and irregular below examine of the dominant object. We are binding with three layer ANN is being used for classification, and thus the experimental results on knowledge discovery databases are being used for the facts in occurrence of accuracy rate and disclosure estimation toward identical period. True and false made up accepted.

At the indicated motivation a hybrid methodology supported pairing distinct ripple transformation and human intelligence ANN for IDS is projected. The lack of balance of the situation traversing the space beyond information range was eliminated through synthetic minority oversampling technique-based oversampling have low regular object and irregular below examine of the dominant object.

Chain interruption discovery is the series of actions for the results knowing the familiarity opening and honor number associate order, the scientific categorization undertaking become necessary. The capacity issues of invasion discovery is the order to determine and examine. The arrangement of simulations at the occasion under discovery estimation for low regular aggression associations and above made up feeling sudden panic amount.

The purpose of this paper is to attempt to realize a distribution network optimization in supply chain using grey systems theory for uncertain information.

There is much uncertain information in the distribution network optimization of supply chain, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in supply chain, however grey information of the supply chain has not been covered. In the distribution problem of supply chain, grey demands are taken into account. Then, a mathematics model with grey demands has been constructed, and it can be transformed into a grey chance‐constrained programming model, grey simulation and a proposed hybrid particle swarm optimization are combined to resolve it. An example is also computed in the last part of the paper.

The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about distribution of supply chain, but grey chance‐constrained programming, grey simulation and particle swarm optimization can be combined to resolve the grey model.

The method exposed in the paper can be used to deal with distribution problems with grey information in the supply chain, and network optimization results with a grey uncertain factor could be helpful for supply chain efficiency and practicability.

The paper succeeds in realising both a constructed model of the distribution of supply chain with grey demands and a solution algorithm of the grey mathematics model by using one of the newest developed theories: grey systems theory.

The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

The purpose of this paper is to analyse the effect of the proportion of temporary workers on the profit‐to‐sales ratio (or price‐cost margin) of Spanish manufacturing firms in the 1990s.

The relation between the proportion of temporary workers and the profit‐to‐sales ratio is estimated using the information provided by the “Encuesta Sobre Estrategias Empresariales” (Entrepreneurship Strategy Survey), a panel data set for the Spanish manufacturing sector carried out over the period 1990‐1999. The model is estimated in logarithmic first differences in order to remove fixed effects. To correct endogeneity problems, the instrumental variables method has been used.

The outcomes show that the rise in the proportion of temporary workers reduces the price‐cost margin of Spanish firms. It also leads to a fall in labour productivity and in the hourly average wage, and to an increase in the total cost of production.

The dataset refers only to manufacturing industry. It would be interesting to extend the analysis, if possible, to the service sector of Spanish economy.

The outcomes show that those policies oriented to reduce the high proportion of temporary workers (which has been over 30 per cent since 1990) by means of stimulating permanent labour contracts are expected to be positive for Spanish firms.

This article is the first empirical work aimed at assessing the impact of the proportion of temporary workers on the profit‐to‐sales ratio.