Research on the innovation process from ideas to product
Tian is an associate professor @ Emory's Goizueta Business School researching and teaching on how teams develop new products and services. His research work focuses on two related areas: (a) collaborations in different work settings (collaborative design, complex problem-solving, customer-supplier co-production, and collective action projects), and (b) the emergence of novelty through design or creative product modifications. He has worked on various technological development and operational improvement projects in complex logistical settings.
He holds a PhD in Technology and Operations Management from INSEAD, MS in Management Science & Engineering from Stanford University, and BS in Mechanical Engineering from UC Berkeley.
Complex and important decisions are often made with advice from a committee of experts. But how do a committee's "rules of engagement" affect the way individuals discuss, how they vote, and ultimately the quality of their collective recommendation? Compiling verbatim transcripts from U.S. Food and Drug Administration Advisory Committee meetings, we study how a 2007 switch from sequential to simultaneous voting procedures changed discussions, information exchange, and decision-making. Consistent with past findings, we show that, compared to a sequential voting protocol, simultaneous voting led to a reduction in the likelihood of unanimous votes. Importantly, we show novel evidence that the majority of this reduction in unanimity was mediated by changes in discussion patterns---specifically, by the increased diversity of information surfaced during discussions. We also find evidence of behavioral and linguistic changes that support our theory that voting protocols changed the incentives for members to elicit more diverse information from each other: under simultaneous voting, members exhibited greater equality in talking time, directed a greater proportion of questions to each other, and adopted language that was more positive, authentic, and equal in projecting status and confidence. Finally, we show that recommendations under simultaneous voting were more likely to be accurate, as drugs recommended and approved were less likely to encounter safety-related post-market events. In sum, voting protocols affect the incentives for individuals to engage in robust discussions, leading to marked improvements in how information is exchanged between individuals, and in the process by which groups of experts arrive at joint recommendations.
Collective action projects (e.g., online petitions, digital protests, fan activism, or collective stock trades) depend on mobilizing many participants in online communities (OCs), often in direct competition with other OCs on the same platform. Our paper theorizes how the influence structure of an OC, conceptualized as a continuum ranging from hierarchical to flat, affects the success of an OC in collective action projects. Specifically, we argue that the latent (or less active) users in hierarchical OCs are more motivated to contribute when they observe the effects of peer contributions, but their contribution declines when competition reduces the visibility of peer contributions. Compiling data from Reddit's r/place 2022 event, we show evidence that hierarchical OCs (relative to flat OCs) progress faster toward their goal when competition among OCs is low. However, their performance declines as competition intensity increases. Two sets of results corroborate our theory: first, the above pattern of results is stronger when the OC has a large pool of latent users, suggesting that the effect we observe is driven by differences in OCs' ability to mobilize latent users (as opposed to active contributors); second, OCs make faster progress when they observe more contributions in the previous period, but this relationship weakens when competition intensity increases, suggesting that the ability to link peer contributions to project progress is essential in motivating contributions. The paper advances our understanding of online community dynamics by theorizing how the influence structure of an OC shapes its ability to mobilize latent users and succeed in collective action projects, particularly under varying intensities of inter-community competition. With the increasing democratization of internet platforms, a key implication of our study is that the visibility of peer contributions can enhance community performance by mitigating the adverse effects of competition on user motivation, especially in hierarchical OCs. - With Shizhen Chen and Anandhi Bhardwaj
Research has demonstrated that certain team composition factors—high expertise similarity, high network cohesion, and mixed-gender teams—have predominantly negative effects on the teams’ invention outcomes. We highlight how these effects depend on an invention’s integrality, which increases task interdependencies among team members and thereby strengthens the positive relationship between team coordination and invention value. We show that (i) the main effects of these team composition factors reduce a team’s invention value but, more importantly, that (ii) invention integrality positively moderates those effects.
We challenge the notion that collaboration is always better than working alone. In our study using technological and design patents we find that the decomposability of the invention significantly moderates the effectiveness of the lone inventor. Particularly, tasks that are less decomposable relatively advantages the lone inventor. We also show that lone inventors working on non-decomposable inventions and who have collaborated widely in the past outperforms even teams.
Using text analysis of business method (BM) patents, we show that BM innovation in the US manufacturing and trade sectors improves how a firm targets customers, manages product delivery, or enhances the product through service offerings. We then show that BM innovation creates value on average, but the value is larger when (1) it is engaged by trade (vs. manufacturing) firms; and (2) the firm’s BM innovation covers the range of customer targeting, product delivery, and product service support.
Using data from a major medical body scanner manufacturer, we show that free-rider problems impose a heavy cost in the maintenance of medical body scanners, and that pay per service maintenance plans can improve performance and reduce costs.
We show how user requirements (categorized into function, form, and other project or product quality requirements) affect their ability to discover new product functionalities in the process of hacking or creatively modifying existing products. - With Shiying Lim
Exaptation refers to the emergence of novel functionalities in existing products. We compare how product-first (compared to problem-first) search affects the occurrence of exaptations in a dataset consisting of creative modifications (i.e., hacks) of IKEA products. We show how problem-specific knowledge that customer users have improve their ability to search for exaptations starting from a problem.
(Dis)similarity between designs is an important measure to detect the novelty of a design. Can Computer Vision techniques be used to measure similarity between two designs? In this paper we develop a technique that shows that, with careful calibration to suit the design context, CV techniques can deliver a measure of similarity between designs. - With Egbert Amoncio and Cornelia Storz
Comparative processes are crucial to how consumers evaluate design. What we show, however, is that consumers can be sophisticated in such comparisons. Given a novel design, they would lean on its similarities to past designs to understand its functionalities, but also lean on dis-similarities to other contemporary designs to seek distinctiveness and express their individuality.
We show how one can identify styles (categories of product design that are perceived to be similar) using design patents. Using this data set we show that (i) style turbulence (unpredictable changes in style) is increasing over time, and (ii) technological turbulence (unpredictable changes in technology) have a U-shaped relationship to style turbulence. I use this data platform to study other questions (see e.g., “Anchored Differentiation”).