The Acquisition of Quality Information in a Supply Chain with Voluntary vs. Mandatory Disclosure

Cao, Heng; Guan, Xu; Fan, Tijun; Zhou, Li

doi:10.1111/poms.13130

Cited by 62 publications

(37 citation statements)

References 46 publications

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“…These connections are aided by IoT technologies such as RFID, where connecting devices through the internet offers a strengthened supplier integration [ 1 , 53 ]. These connections enhance capabilities to recognise, anticipate network, and process information to connect with other devices and services over the internet [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

Towards Supply Chain Visibility Using Internet of Things: A Dyadic Analysis Review

Ahmed

Kalsoom

Ramzan

et al. 2021

Sensors

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The Internet of Things (IoT) and its benefits and challenges are the most emergent research topics among academics and practitioners. With supply chains (SCs) gaining rapid complexity, having high supply chain visibility (SCV) would help companies ease the processes and reduce complexity by improving inaccuracies. Extant literature has given attention to the organisation’s capability to collect and evaluate information to balance between strategy and goals. The majority of studies focus on investigating IoT’s impact on different areas such as sustainability, organisational structure, lean manufacturing, product development, and strategic management. However, research investigating the relationships and impact of IoT on SCV is minimal. This study closes this gap using a structured literature review to critically analyse existing literature to synthesise the use of IoT applications in SCs to gain visibility, and the SC. We found key IoT technologies that help SCs gain visibility, and seven benefits and three key challenges of these technologies. We also found the concept of Supply 4.0 that grasps the element of Industry 4.0 within the SC context. This paper contributes by combining IoT application synthesis, enablers, and challenges in SCV by highlighting key IoT technologies used in the SCs to gain visibility. Finally, the authors propose an empirical research agenda to address the identified gaps.

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Section: Discussionmentioning

confidence: 99%

Towards Supply Chain Visibility Using Internet of Things: A Dyadic Analysis Review

Ahmed

Kalsoom

Ramzan

et al. 2021

Sensors

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“…How to elicit accurate information about the performance of private entities has long been of interest to scholars (Akerlof, 1970; Stigler, 1961) and continues to be relevant today (e.g., Cao et al, 2019; Kalkanci & Plambeck, 2020; Swift et al, 2019). Due to the vast literature on the acquisition and use of information, we focus our review primarily on sources of biases, be it from third‐parties or self‐reports.…”

Section: Related Literaturementioning

confidence: 99%

“…Relying on firms to voluntarily self-report information is a widely adopted information-gathering mechanism used in contexts as varied as product quality (Cao et al, 2019;Ghosh & Galbreth, 2013), demand planning (Cachon & Lariviere, 2001;Kaipia et al, 2017), environmental and social responsibility measurement (Kalkanci & Plambeck, 2020;Montabon et al, 2007;Villena & Dhanorkar, 2020), and regulatory monitoring and enforcement (Short & Toffel, 2015;Toffel & Short, 2011).…”

Section: Introductionmentioning

confidence: 99%

The consequences of self‐reporting biases: Evidence from the crash preventability program

Scott

Balthrop

2021

J of Ops Management

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Relying on firms to self-report information is an information-gathering mechanism that often results in biased measures due to the incentives of the reporting firms. What is less commonly understood is that using self-reported information for decision-making results in endogenous selection bias, which creates spurious associations between the measure being reported and factors that influence reporting. Thus, conditioning on self-reported information can lead to inaccurate evaluations of firms and bias predictions of future performance, even when the self-reported measure is not intentionally misrepresented. We examine endogenous selection bias in self-reporting regimes using directed acyclic graphs (DAGs). We illustrate the problem using data from a policy change by the U.S. Department of Transportation that allowed firms to report not-at-fault for accidents. We find that large for-hire firms are much more likely to report not-at-fault for accidents-over 40 times more likely than independent drivers-even after controlling for time, location, and weather. When comparing independent drivers with large firms, the reporting disparities make large firms appear 25% safer when using at-fault accidents versus all accidents while providing no improvement in predicting future accidents. This study highlights the consequences of poorly designed informationgathering mechanisms and the usefulness of DAGs for understanding causality in supply chain research.

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“…The authors also show that disclosure strategy impacts the optimal pricing decision in a nonmonotonic way. Other works have explored optimal information disclosure strategies among different players in a distribution channel (e.g., Cao et al 2020, Guan and Chen 2017, Sun and Tyagi 2020.…”

Section: Product Information Disclosurementioning

confidence: 99%

Dynamic Pricing and Information Disclosure for Fresh Produce: An Artificial Intelligence Approach

Yang

Feng

Whinston

2022

Production and Operations Management

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Failing to sell fresh produce before expiration not only hurts the bottom line of grocery retailers, but also leads to food waste. This work combines dynamic pricing and information disclosure to help retailers to effectively sell fresh produce and promote sustainability. We focus on a quality‐based pricing strategy and whether retailers should disclose information on food quality to customers. We consider a model where a monopolistic retailer sells fresh produce to customers who have different perceptions about food quality within a given time period. We employ a deep reinforcement learning algorithm to derive the optimal pricing and information strategies. Our simulation results show that a quality‐based pricing strategy yields lower prices than a pricing strategy that does not consider quality. Lower prices drive demand, thus improving profits and reducing food waste. Additionally, we show that, when an information strategy is allowed, the prices in a quality‐based pricing strategy stay the same or even increase during the selling season. This is because information disclosure helps align customers’ biased perceptions on food quality with the actual levels. We show that a combination of quality‐based pricing and information disclosure further improves profits and reduces food waste when a large portion of customers consider quality to be lower than actual levels. To implement our ideas, we propose a cloud‐based automated system that integrates sensor data, artificial intelligence, and customer communications. Our results have profound implications for the food industry on managing fresh produce.

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The Acquisition of Quality Information in a Supply Chain with Voluntary vs. Mandatory Disclosure

Cited by 62 publications

References 46 publications

Towards Supply Chain Visibility Using Internet of Things: A Dyadic Analysis Review

Towards Supply Chain Visibility Using Internet of Things: A Dyadic Analysis Review

The consequences of self‐reporting biases: Evidence from the crash preventability program

Dynamic Pricing and Information Disclosure for Fresh Produce: An Artificial Intelligence Approach

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