1 Introduction
Consumers may face challenges when evaluating product quality, particularly for those products with unobservable quality features. Retailers play a pivotal role in conveying transparent information that can bridge the divide between manufacturers and consumers (Guan & Chen,
2015). One may wonder if adopting digital technologies that enhance retailer transparency can reduce the information asymmetry regarding product quality, thereby improving consumer attitudes and behavioral intentions toward the retailer. The current paper revolves around this question.
In doing so, we focus on Blockchain Technology (BT). While BT is predominantly recognized for its role in finance, it has found increasing applications in various sectors. In retailing, one notable use of BT is to ensure supply chain traceability (Iansiti & Lakhani,
2017). Platforms like Provenance or IBM Blockchain enable firms to use BT for tracing products. Thus, by leveraging these platforms, retailers now have the opportunity to provide consumers with transparent information about products’ journeys (Gleim & Stevens,
2021).
Prior research has provided important insights into the role played by BT in supply chain management (Rejeb et al.,
2021; Zheng et al.,
2018). However, with few exceptions (e.g., Cozzio et al.,
2023; Treiblmaier & Garaus,
2023), less is known about the impact of retailer transparency provided by BT on consumer responses. Still, consumers play a central role within the supply chain since they represent its final node. Research has suggested that BT has the potential to alter consumer perceptions due to its transparent transaction mechanism, which allows consumers to access the full set of transactions of supply chains (Gleim & Stevens,
2021). With the goal of understanding more about the role of retailer transparency elicited by BT in affecting consumer responses, we conducted three online experiments.
Our findings offer different contributions. First, we respond to the call for research on the effects of transparency in the supply chain on consumers (Gleim & Stevens,
2021). Second, we make an original contribution to the literature on quality signals by showing that transparency provided by BT traceability works as an effective quality signal. Third, we identify a boundary condition for the effects of retailer transparency (i.e., information quantity). Finally, our findings encourage retailers to leverage BT to trace supply chains more transparently.
2 Theoretical background
Transparency stands out as a way for companies to enhance practices throughout the supply chain (Fraser & van der Ven,
2022). It refers to the practice of making information about the supply chain accessible and understandable to relevant stakeholders, including consumers (Sodhi & Tang,
2019). Companies are increasingly encouraged by the law to be transparent about their products (e.g., The California Transparency in Supply Chains Act). However, while many companies pursue transparency by disclosing more information about their products, their efforts may fall short if consumers cannot verify the accuracy of the claims (Reynolds & Yuthas,
2008). A technology that should enhance supply chain transparency and, thus, may help companies positively influence consumers, is BT (Gleim & Stevens,
2021).
BT is a large distributed ledger that stores a continuously growing set of transaction bundles, called blocks, which are linked and secured cryptographically in a peer-to-peer network (Alkhudary et al.,
2023). BT has unique features—e.g., transparency and security—compared to other tracking technologies (e.g., labels, barcodes, RFID; Moretto & Macchion,
2022). In the area of supply chain traceability, however, the transparency of BT plays the most critical role (Gleim & Stevens,
2021). Through this technology, companies can provide consumers with verifiable information about the product’s journey, from source to endpoint. BT decentralizes supply chain information, ensuring universal access instead of storing it in a single location. All transactions occurring along the chain are publicly accessible, and they cannot be altered without consensus.
While BT improves transparency at all stages of production and distribution (Saxena & Sarkar
2023), we are specifically interested in the transparency that BT elicits at the end of the supply chain, in the retailing stage, where the interaction with consumers takes place. In other words, we focus on retailer transparency.
1 We define it as the extent to which retailers are transparent, clear, and upfront in disclosing information about products (Bateman & Bonanni,
2019). Building on prior research on transparency and considering the unique features of BT, we advance that the higher transparency provided by BT is related to greater future intentions toward the retailer (i.e., patronage, WOM, and purchase intentions) compared to the lower transparency associated with other tracking technologies. Accordingly.
Why may this happen? We suggest that the transparency provided by BT acts as a quality signal compensating for the information asymmetry between retailers and consumers about product quality (Spence,
1973). Prior studies have addressed the issue of information asymmetry by proposing cues that retailers can use as quality signals, such as price (Kirmani & Rao,
2000). The underlying principle is that consumers cannot observe a product quality directly, and must infer it from other signals. Nonetheless, the issue of information asymmetry may endure even when quality signals are present, as information can be readily forged or manipulated (Treiblmaier & Garaus,
2023). One way to overcome this problem may be for retailers to leverage their own verifiable transparency (Bolton,
2019).
Research started exploring the role of BT as a quality signal (Xu et al.,
2022). For instance, in the context of supply chain finance, BT works better than conventional monitoring methods in signaling the firm’s quality (Chod et al.,
2020). Further, compared to company-owned labels, BT labels act as signals that increase consumers’ quality perceptions of food products (Treiblmaier & Garaus,
2023). Consistent with existing theorizing, we advance that retailer higher transparency provided by BT conveys a stronger signal of product quality compared to the lower transparency associated with non-BT traceability.
Indeed, for a signal to be more credible, it should be costlier (e.g., in terms of money, time, risk; Kirmani & Rao,
2000). Retailers adopting BT instead of other tracking technologies incur in higher implementation costs (Moretto & Macchion,
2022). More importantly from the consumer perspective, using BT means that product information is fully verifiable. The cost of verifiable information is that it entails the risk of immediate identification of any misstep (Chaudhry & Wald 2022). Therefore, transparency enabled by BT should be a stronger signal of product quality than the one provided by non-BT tracking methods.
One condition that is necessary for relational exchanges between retailers and consumers is trust, particularly when the exchange is characterized by information asymmetry (Singh & Sirdeshmukh,
2000). We consider trust as consumers’ confidence in the integrity and reliability of retailers (Inman and Nikolova 2017). A solid stream of literature shows that product quality is a significant antecedent of trust toward the retailer (e.g., Rubio et al.,
2017). Hence, consumers exposed to a more transparent retailer may not only infer higher product quality, but also, as a consequence, place more trust in the retailer. Further, trusting a company drives consumers to be more loyal, more willing to re-purchase, and more inclined to spread positive WOM (Kang and Hustvedt 2014). Building on these findings, we suggest that higher transparency should affect future intentions as mediated by increased product quality and trust. Therefore.
If consumers perceive higher transparency as a signal of product quality, then its beneficial impact may disappear in the presence of other quality signals. Thus, if consumers already perceive product quality as high, tracing the supply chain by means of BT could be less beneficial for retailers. We focus on information quantity as an alternative quality signal (Chang & Wildt,
1994).
Quantity is one of the cues that make information diagnostic (Andrews,
2013). Literature on crowdfunding shows that when creators provide extensive information about their projects, they signal higher quality to funders as they are perceived as more prepared (Wessel et al.,
2017). Indeed, offering a detailed description not only diminishes information asymmetry between parties, but also signals the costs invested by creators in terms of time and effort (Moradi & Badrinarayanan,
2021). Larger amounts of information offer a meaningful product quality cue even when the information provided is not highly informative, by serving a compensatory function (Keller & Staelin,
1987).
Accordingly, if retailers provide consumers with more information about the product’s journey (i.e., more details about each step of the supply chain), the latter should infer higher product quality. Hence, we propose that, when product information quantity is high, consumers should already perceive product quality as high, mitigating the positive effect of BT traceability. Formally.
4 Discussion
4.1 Theoretical and managerial implications
This research makes different theoretical contributions. First, we respond to the call for research on the effects of transparency in the supply chain on consumers (Gleim & Stevens,
2021). Our research provides evidence that BT can benefit retailers through greater transparency, adding also to the literature on in-store technologies. Such technologies have the potential to increase value perceptions (Pizzi and Scarpi 2020), but could also induce distrust (Darke et al.,
2016). We found that consumers trust retailers more and display increased future intentions thanks to higher transparency enabled by BT. Second, we uncovered an underlying mechanism for these effects. We found that transparency provided by BT traceability works as a product quality signal that increases trust toward the retailer. Third, we identified a boundary condition of these effects—i.e., information quantity. Our findings suggest that transparency and information quantity may work as substitute quality signals.
Our research also has managerial implications. Our results encourage businesses to leverage BT in order to more transparently trace the supply chain. Since retailers play a pivotal role between manufacturers and consumers, our results prompt them to weigh the cost of investing in the technological infrastructure needed to provide consumers with BT traceability against the higher levels of future intentions expressed by consumers in response to such traceability. Our results are relevant for manufacturers as well, as sharing transparency data with retailers could become an excellent trade marketing tool. Complete disclosure of product information is a necessary condition for successful implementations of transparency strategies and alignments between supply chain businesses. BT-induced transparency may not only boost retailers’ profits, but also generate backward advantages for all the suppliers involved with retailers.
4.2 Limitations and future research
Our research is not without limitations. First, drawing on existing literature and real-world evidence, we regarded BT as a fully secure technology, without questioning the assumption that the data recorded in the ledger could potentially be falsified or incorrect. However, wrong data may indeed be recorded by data providers, a misbehavior that could endanger consumer trust. This may represent a relevant avenue for future research.
Second, we assumed consumers view retailers as impartial verification agents (i.e., they adopt BT to solve an information asymmetry problem), but this may not always be the case. For example, what could happen if BT shows that the supply chain of the retailer’s private label is inferior to that of brands available in store? Would the retailer be an impartial verification agent in that scenario too? Future research could consider this alternative view and investigate the effect of BT traceability on channel relationships (e.g., channel conflict).
Finally, while we focused on the signaling power of BT-induced transparency, we recognized that other quality signals (e.g., WOM) may be stronger. We examined information quantity as an alternative quality signal. Future research could explore other quality signals that may act as boundary conditions for the positive effects of BT.
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