Search results

The main purpose of this paper was to evaluate the validation process of food safety control measures.

The validation of control measures has been analyzed at 50 food companies in Serbia. The sample included companies that produce food of both plant and animal origin and have certified food safety management systems. A total of 156 control measures that combat physical hazards (41.6%), followed by microbial hazards (34.0%) and chemical hazards (24.4%), have been analyzed. To enable quantification of the validation protocols, each control measure was assigned a score.

The validation scores showed that the highest level of validation was observed in large companies, as opposed to small and medium-sized companies (p < 0.05). The type of food safety hazards and the food sector did not reveal any statistical differences in-between the scores. The main approach to validating control measures was referring to the technical documentation of equipment used (52.6%), followed by scientific and legal requirements (30.7%). Less than 20% of the analyzed control measures were validated with operational data collected on-site. No mathematical modeling was observed for the sampled food companies. Future steps should include the development of validation guides for different types of control measures and training modules.

This study can serve as an improvement guide for food safety consultants, food safety auditors, certification bodies, inspection services, food technologists and food managers.

This study is one of the first to provide an insight into how food companies validate their control measures to combat microbial, chemical and physical food safety hazards.

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper aims to build a decision model for obtaining optimal sampling plan under accelerated life test setting using Type-I hybrid censoring scheme for products covered under warranty.

The primary decision model proposed in this paper determines ALTSP by minimizing the relevant costs involved. To arrive at the decision model, the Fisher information matrix for Type-I hybrid censoring scheme under accelerated life test setting is derived. The optimal solution is attained by utilizing appropriate techniques following a nonlinear constrained optimization approach. As a special case, ALTSP for Type-I censoring is obtained using the same approach. ALTSP under Type-I hybrid censoring using the variance minimization approach is also derived.

On comparing the optimal results obtained using the above mentioned approaches, it is found that the cost minimization approach does better in reducing the total cost incurred. Results also show that the proposed ALTSP model under cost function setting has considerably lower expected testing time. Interesting findings from the sensitivity analysis conducted using a newly introduced failure dataset pertaining to locomotive controls are highlighted.

The research introduces a model to design optimum ALTSP for Type-I hybrid censoring scheme. The practical viability of the model makes it valuable for real-life situations. The practical application of the proposed model is exemplified using a real-life case.

The present paper proposes a framework for zero-defect manufacturing in Indian industries. Due to the current competitive market, there is a strong need to achieve zero defects from the customer's perspective. A survey questionnaire is analyzed based on the responses and a structured framework is drafted to implement zero defect manufacturing in the Indian industry.

To analyze zero-defect in Indian industries, a literature review and a survey questionnaire constituted a framework. This framework is independent of the type of process and product.

The findings of this study are based on a total of 925 responses received through survey questionnaires by different mediums. The framework has been tested in different manufacturing organizations to achieve zero-defect through the continuous improvement approach.

The study results aim to achieve zero-defect, help to improve customer satisfaction, reduce waste and rework in the manufacturing process. This framework is also used as a problem-solving approach to implement Six Sigma in the Indian industries.

Zero defect manufacturing is growing in India and globally. This framework helps to implement zero defect manufacturing in Indian industries. It is an essential tool to capture the voice of the customer.

The purpose of the paper is set to minimize the total cost of a manufacturing system when an acceptance sampling plan (ASP) is carried out in a fuzzy environment.

A fuzzy acceptance sampling plan (FASP) is employed for the inspection of the batch of products and a fuzzy cost optimization problem is formulated.

The extent of uncertainty determines an interval for the total cost function with upper and lower bounds. The effect of variation in the ambiguity of the proportion of defectives in the probability of acceptance is determined.

The proposed model is specifically designed for production and supply units with ASP for attributes. Still, the proportion of defectives in the inspection process is fuzzy.

Fuzzy probability distribution is used to model an optimal inspection plan for a general supply chain. Economic design of supply chain under fuzzy proportion of defectives is discussed for the first time.

Citizens can develop new products in the household sector (HHS), and although HHS innovations are generally valuable to others, they are seldom diffused by the innovator. In order to provide insight for the understanding of this diffusion failure, this article proposes to introduce the vocational and retirement perspective to consider how the innovator's chronological aging affects her diffusion channel selection. Commercial diffusion of HHS innovations allows older adults to continue a work-related identity. And, a satisfying work experience could enhance older adults' reliance on work for self-worth. Therefore, the relationship between the older HHS innovators and their commercial diffusion as well as the moderating effect of their person–organization (P–O) fit on this relationship was examined.

This study referred to the standard procedure and utilized a Japanese consumer panel to identify HHS innovators. The criterion of old age was set to 60+ years old. The hypotheses were tested with ordinary least squares regression analysis. The robustness of our findings was checked by analyzing two restricted samples.

In Japan, older adults are more likely to diffuse their HHS innovators commercially than to peers. This relationship is amplified when the older adults also perceived a P-O fit in their employer firm.

This paper adds to the evidence that older adults can be an important source of innovation. It – for the first time – points out that the vocational and retirement perspective can help researchers consider why a particular diffusion channel is selected and thereby provide insight for understanding when the diffusion failure of HHS innovation is alleviated. The moderating effect of the P–O fit originally suggests the “interdependent life spheres”, that is, older adults' work experience may affect their post-retirement life and their activity in the household sector.

The purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.

This study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.

Deploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.

This study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

Our prior work has identified a trade-off that new entrants face in obtaining favorable market reception, whereby initial entrants suffer from a deficit of legitimacy whereas later entrants suffer from a deficit of authenticity. This research has also proposed that a single mechanism is responsible for this trade-off: the tendency for customers and other stakeholders to assess the entrant's claim to originality based on the visible work that it has done to legitimate the new product or organizational form. This chapter extends and deepens our understanding of such “legitimation work” by showing how it can illuminate cases that seem in the first instance to defy this trade-off. In particular, we focus on two “off-diagonal” cases: (a) when, as in the case of “patent trolls” and fraudulent innovators, early entrants are viewed as inauthentic despite having a credible claim to originality; (b) when late entrants, as in the case of Dell Computers, mechanical watches and baseball ballparks, are viewed as authentic despite obviously not being the originators. We clarify how each off-diagonal case represents an ‘exception that proves the rule’ whereby audiences attribute authenticity on the basis of legitimation work rather than on the order of entry per se. The last case also leads to an opportunity to clarify why “cultural appropriation” can sometimes project authenticity and sometimes inauthenticity, why audiences bother to make inferences about a producer's authenticity on the basis of visible legitimation work, and why legitimacy is a universal goal of early movers whereas authenticity varies in its importance.

The purpose of this study is to evaluate whether a diversification by grape varieties may help wine producers reduce uncertainty in quantity and quality variations due to increasingly erratic climate conditions.

This study hand-collects granular quantity and quality data from wine harvest reports for vintages 2003 to 2017 for the Valais region in Switzerland. The data allows us to obtain detailed data on harvested kilograms/liters and Oechsle/Brix degrees. It is then merged with precise meteorological data over the same sample period. The authors use this data set to capture weather conditions and their impact on harvested quantities and quality. Finally, they build portfolios including different grape varieties to evaluate whether this reduces variations in quality and quantity over vintages.

The findings highlight that the weather varies relatively strongly over the sample period and that climate hazards such as hail, frost or ensuing vine diseases effectively occur. These strongly impact the harvested quantities but less the quality of the wine. The authors further show that planting different grape varieties allows for a significant reduction in the variation of harvested quantities over time and thus acts as a good solution against climate risk.

The effect of climate change on viticulture is becoming increasingly important and felt and bears real economic and social consequences. This study transposes portfolio diversification which is central to reducing risk in the finance industry, into the wine industry and shows that the same principle holds. The authors thus propose a novel idea on how to mitigate climate risk.