Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
This paper investigates the effectiveness of time-dependent data in improving the quality of AI-based products and services. Time-dependency means that data loses its relevance to problems over time. This loss causes deterioration in the algorithm's performance and, thereby, a decline in created business value. We model time-dependency as a shift in the probability distribution and derive several counter-intuitive results.
We, theoretically, prove that even an infinite amount of data collected over time may have limited substance for predicting the future, and an algorithm that is trained on a current dataset of bounded size can attain a similar performance. Moreover, we prove that increasing data volume by including older datasets may put a company in a disadvantageous position.
Having these results, we answer questions on how data volume creates a competitive advantage. We argue that time-dependency weakens the barrier to entry that data volume creates for a business. So much that competing firms equipped with a limited, but sufficient, amount of current data can attain better performance. This result, together with the fact that older datasets may deteriorate algorithms' performance, casts doubt on the significance of first-mover advantage in AI-based markets.
We complement our theoretical results with an experiment. In the experiment, we empirically measure the value loss in text data for the next word prediction task. The empirical measurements confirm the significance of time-dependency and value depreciation in AI-based businesses. For example, after seven years, 100MB of text data becomes as useful as 50MB of current data for the next word prediction task.
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020.
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Feng Zhu, Xinxin Li, Ehsan Valavi and Marco Iansiti
Digital technologies have led to the emergence of many platforms in our economy today. In certain platform networks, buyers in one market purchase services from providers in many other markets, whereas other platform networks may comprise local clusters in which buyers primarily purchase services from providers within the same cluster. Consequently, network interconnectivity varies across different industries. We examine how network interconnectivity affects interactions between an incumbent platform serving multiple markets and an entrant platform seeking to enter one of these markets. Our model yields several interesting results. First, even if the entrant can advertise at no cost, it still may not want to make every user in a local market aware of its service, as doing so may trigger a competitive response from the incumbent. Second, having more mobile buyers, which increases interconnectivity between markets, can reduce the incumbent’s incentive to fight and, thus, increase the entrant’s incentive to expand. Third, stronger interconnectivity between markets may or may not make the incumbent more defensible: when advertising is not costly and mobile buyers consume in both their local markets and the markets they visit, a large number of mobile buyers will increase the entrant’s profitability, thereby making it difficult for the incumbent to deter entry. However, when advertising is costly or mobile buyers only consume in the markets they travel to, a large number of mobile buyers will help the incumbent deter entry. When advertising cost is at an intermediate level, the entrant prefers a market with moderate interconnectivity between markets. Fourth, we find that even if advanced targeting technologies can enable the entrant to also advertise to mobile buyers, the entrant may choose not to do so in order to avoid triggering the incumbent’s competitive response. Finally, we find that the presence of network effects is likely to decrease the entrant’s profit. Our results offer managerial implications for platform firms and help understand their performance heterogeneity.
Problem Definition: Farmers face several challenges in agricultural supply chains in emerging economies that contribute to extreme levels of poverty. One common challenge is that farmers only have access to one channel, often an auction, for which to sell their crops. Recently, e-intermediaries have emerged as alternate, technology-driven posted-price channels. We aim to develop insights into the structural drivers of farmer and supply chain profitability in emerging markets and understand the impact of e-intermediaries.
Academic / Practical Relevance: In practice, much attention has been given to e-intermediaries and they have often been touted as for-profit social enterprises that improve farmers' welfare. Yet, studies in the operations literature that systematically analyze the impact of e-intermediaries are lacking. Our work fills this gap and answers practical questions regarding the responsible operations of e-intermediaries.
Methodology: We develop an analytical model of a supply chain that allows us to study several key features of intermediated supply chains. We complement the model's insights with observations from a numerical study.
Results: In the absence of an e-intermediary, auctions cause farmers to either overproduce or underproduce compared to their ideal production levels in a vertically integrated chain. The presence of an e-intermediary with limited market share improves farmers' profits; however, if the e-intermediary grows too large, it negatively impacts both farmers' and supply chain profits. Finally, as the number of farmers increases, farmers' profits approach zero, irrespective of the e-intermediary's presence.
Managerial Implications: Our results provide a balanced perspective on the value of e-intermediation, compared to the generally positive views advanced by case studies. For-profit e-intermediaries that also aim to improve farmers' livelihoods cannot blindly operate as pure profit-maximizers, assuming that market forces alone will ensure that farmers benefit. Even when e-intermediation benefits farmers, it is insufficient to mitigate the negative effects of supply fragmentation, suggesting that for farmers, market power is more important than market access.
