Consumers' willingness to pay for traceable pork, milk, and cooking oil in Nanjing, China

Zhang, Caiping; Bai, Junfei; Wahl, Thomas

doi:10.1016/j.foodcont.2012.03.001

Cited by 134 publications

(99 citation statements)

References 24 publications

(28 reference statements)

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“…Estimating this loss in demand and how a firm can attempt to influence customers to return can be daunting, but several studies (e.g., Richards and Patterson, 1999, Verbeke and Ward, 2001, Zhang et al, 2012 have modeled demand changes resulting from past food contaminations and quantified the substitution effect and the impact of both negative and positive media stories on demand. The analysis from these historic cases can be used to estimate demand fluctuations for a future contamination.…”

Section: Figurementioning

confidence: 99%

Modeling disruption in a fresh produce supply chain

MacKenzie

Apte

2017

IJLM

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Purpose-The purpose of this paper is to quantify elements that make fresh produce supply chains vulnerable to disruptions and to quantify the benefits of different disruption management strategies.Design/methodology/approach-This paper develops a mathematical model of a disruption in a fresh produce supply chain and analyzes the relationships among variables. Findings-The model determines the optimal safety stock as a function of the perishability of the produce, the length of time it takes to find the contamination, the level of demand during the disruption, and the amount of produce that can be rerouted. Applying the model to the 2006 E. coli spinach contamination reveals that the drop in customer demand for fresh spinach plays the largest role in Dole losing sales.Research limitations-The model includes several parameters that may be difficult to estimate.Future models can incorporate uncertainty that is inherent in supply chain disruptions. 2Practical implications-The model in this paper can help a supply chain manager explore the trade-offs of different disruption management strategies. For example, a supply chain manager can determine the value of holding additional safety stock versus trying to improve traceability in the supply chain.Originality/value-This paper quantifies and models insights delivered in the qualitative analyses of fresh produce supply chain disruptions. The theoretical contributions include an analysis of the interaction among safety stock, levels of demand, communication, and traceability parameters in order to help supply chain managers evaluate different strategies to mitigate the effects of contaminated produce.3

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Section: Figurementioning

confidence: 99%

Modeling disruption in a fresh produce supply chain

MacKenzie

Apte

2017

IJLM

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“…Ortega, Wang, Olynk, Wu, and Bai (2012) found that pork consumers were willing to pay an additional 3.5 RMB for 250 mL of milk if it were certified "safe" by the government. Similarly, Zhang, Bai, and Wahl (2012) found positive willingness to pay for government certification in China for pork, milk and cooking oil. Wang, Mao, and Gale (2008) found that Chinese consumers were also willing to pay a 5% premium for dairy products certified under the voluntary Hazard Analysis Critical Control Point (HACCP) management system.…”

Section: Introductionmentioning

confidence: 95%

Regional patterns of food safety in China: What can we learn from media data?

Holtkamp¹,

Liu²,

McGuire³

2014

China Economic Review

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“…Consumers' purchase intentions toward traceable food are affected by a numbers of factors like concern about traceability system, trust for traceable food, and issuer for traceability certificate [7] [8]. Moreover, Consumers' purchase intentions were influenced by consumers' socio-demographic variables [9].…”

Section: Introductionmentioning

confidence: 99%

Consumers’ Purchase Intentions toward Traceable Beef—Evidence from Beijing, China

Song¹,

Wang²,

Hu³

2017

AJIBM

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The utility of food traceability standards aims to reduce the of food security and to provide consumers with targeted information. A survey has been conducted on sample of consumers in Beijing (n = 234), aiming to explain the intention toward purchasing traceable beef using the theory of planned behavior (TPB). Based on the TPB, the present study has added new variable: past experience. Structural Equation Modeling is applied to test the TPB model. Results show that attitude, subjective norm and past experience are positively associated with intention to traceable beef.

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Consumers' willingness to pay for traceable pork, milk, and cooking oil in Nanjing, China

Cited by 134 publications

References 24 publications

Modeling disruption in a fresh produce supply chain

Modeling disruption in a fresh produce supply chain

Regional patterns of food safety in China: What can we learn from media data?

Consumers’ Purchase Intentions toward Traceable Beef—Evidence from Beijing, China

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